**A Brief Survey on Intelligent Swarm-Based Algorithms for Solving Optimization Problems**

Siew Mooi Lim and Kuan Yew Leong

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.76979

#### Abstract

This chapter presents an overview of optimization techniques followed by a brief survey on several swarm-based natural inspired algorithms which were introduced in the last decade. These techniques were inspired by the natural processes of plants, foraging behaviors of insects and social behaviors of animals. These swam intelligent methods have been tested on various standard benchmark problems and are capable in solving a wide range of optimization issues including stochastic, robust and dynamic problems.

Keywords: optimization, artificial intelligence, swarm intelligence, nature-inspired and bio-inspired computation

#### 1. Introduction

Optimization is a form of mathematical procedure for determining optimal allocation of scare resources. In recent years, the optimization area has received enormous attention primarily due to the rapid emerging science and technology in computing, communication, engineering, environment and society. Several types of optimization problems exist. Two important classes of objects for most optimization problems are limited resources and activities. Resources include land size, plant capacity and sales force. Whereas production activities are like produce stainless steel, low carbon steel or high carbon steel; how we solve them will depend on the circumstances to determine the best condition of activity levels using the resources available. All optimization problems have an objective function, constraints, and choice variables which will lead to the improvement in application or audience. For instance, tradeoffs between faster algorithm with more consumption of memory and vice-versa are used to bring the greatest interest to the audience [1].

© 2018 The Author(s). Licensee IntechOpen. Distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited.

Three categories of optimizations techniques namely stochastic optimization (SO), robust optimization (RO) and dynamic optimization (DO) are presented in the following subsections with the conclusions given on the advantages and application in practice for each technique. The main motivation behind this study on the nature inspired computation is to identify among the connection, social conduct and rise. This work is needed in the current scientific community to utilize the use of computing to demonstrate the living marvels, to investigate and to enhance our life by using computers. This study will substantially contribute in bringing the inspiration of computerized solutions through a wide range of nature processes.

#### 1.1. Stochastic optimization

Stochastic optimization (SO) process involves randomness in the minimization or maximization of a function and lends itself to real-life phenomena which involve uncertainty and imprecision. The randomness may be present as either noise in measurements or Monte Carlo randomness in the search procedure, or both. Some common techniques of SO are: direct search methods, stochastic approximation, stochastic programming, simulated annealing, genetic algorithms, etc. These techniques can cope with the inherent system noise, and systems with high nonlinearity and high dimensional models.

In other words, these models are derived, solved analytically or numerically and analyzed to extract information to be presented to decision makers [2]. SO is important in analyzing, designing and operating modern systems. Specific applications of SO in business include short and long-term investment decisions, aerospace engineering in designing missile or aircraft, new drug design and the network in traffic control. The challenge in real-life applications is hard to estimate the accurate probabilistic description of the randomness, if such information is available, stochastic programming can be applied as a powerful modeling tool. SO has the advantage of solving problems in polynomial time. Theoretically, it guarantees the quality of the solutions generated. Practically, SO is limited by its heavy dependency on the availability of historical data and complex modeling [3, 4].

#### 1.2. Robust optimization

Robust optimization (RO) is a rather new approach that deals with data uncertainty. The two motivational factors of RO are firstly the uncertainty model is rather deterministic and setbased. This motivational concept is the most appropriate notion of parameter uncertainty in many applications. The second motivational factor is the computational tractability. For instance, for a given optimization problem, multiple robust versions exist depend on the structure of the uncertainty set, therefore maintaining tractability is important. The classification models for RO includes local vs. global and probabilistic vs. non-probabilistic. Based on the nature of the problem, this technique is also known as min-max or worst-case approach. It provides a good guaranteed solution for most possible realizations of the uncertainty in the data. It is also useful if some of the parameters belong to the estimation process and contains estimation errors.

One important concept in defining and interpreting robustness and the resulting models is constraint robustness (model robustness) [5]. The application of RO in engineering is known as robust design optimization or reliability-based design optimization where the solutions remain feasible for all possible values of the uncertain inputs. RO methodology is applicable to every generic optimization problem in which numerical data can be separated from the structure of the problems. The challenge of RO is that it gives the same weight and values to all of the uncertain parameters. The advantages of RO formulation are cost saving and increment of stability, qualitative and quantitative robustness. The practical usage of RO is that it does not significantly increase the complexity of the considered optimization problems in most cases [6, 7].

#### 1.3. Dynamic optimization

Dynamic optimization (DO), also known as dynamic programming is a process of finding the optimal control profile of one or more control parameters of a system. It is used to find the possible number of solutions for a given problem. There are several approaches of DO such as based on the calculus variations, deal with optimization discrete time and extend the static optimization. Basically, the process of DO implementation involves a system controller, a performance criterion and an algorithm to execute the control. Two key attributes of DO are optimal substructure and overlapping sub-problems [8]. Four major steps on development of DO algorithm are:

The advantage of this paradigm: it performs the optimization recursively by dividing the problems into a collection of simpler sub-problems. Each sub-problem is solved only once using either top-down or bottom-up approach. To facilitate its lookup, a technique called memorization is applied where the solutions of subproblems are indexed based on its input parameter values, thereby solving computation time at the expense of modest expenditure in storage space. Practically, the concept of DO is universal and flexible which can be applied to the execution of any effort [9].

#### 2. Algorithms

Artificial intelligence (AI) has been viewed as a regulation in computer science. It has been developing and examining frameworks which work logically. Bio-inspired computation, metaheuristics and computational intelligence are the common examples of algorithms from numerous parts of AI. Bio-inspired computation utilizes the computing power to demonstrate

the living marvels. Computational intelligence which emphasizes on strategy and outcome can be broadly divided into five dominant fields: swarm intelligence, evolutionary computation, artificial neural networks, artificial immune system and fuzzy systems. This chapter will be focusing on a few swarm intelligence-based algorithms which are inspired by their natural processes.

### 3. Swarm intelligence

Swarm intelligence (SI) is evaluated as an adaptive strategy which takes collective intelligence as a behavior without centralized control structure on how an individual should behave. The rules of SI are simple, self-organizing, co-evolution and being widely applied in the domains of optimizing, searching methods, research in DNA computing improvement, heating system planning etc. SI paradigm includes bird flocking, cuckoo search, animal herding and fish schooling etc. However, the two dominant subfields of SI are ant colony optimization, inspired by pheromone-trail of the ant behavior and particle swarm optimization, inspired by flocking and swarming behavior [10].

However, providing a complete review to all the swarm-based algorithms is rather impossible. The next sub-sections present the inspiration, working, metaphor and heuristic of eight popularly known swarm-based methods. These methods have been introduced and implemented in the last decade. The main challenges of the field and their future trends have also been discussed.

#### 3.1. Bat algorithm

Bat algorithm (BA) [11] helps in simplicity and flexibility. It is found to be very efficient in handling nonlinear and multi objective issues. Bats have a special high-level capability of biosonar (echolocation) which is used to find their prey, obstacles, roosting crevices detection and discriminate different types of insects.

The efficiency of BA depends on the features below:

Microbats are the famous examples among all the bat species. The echolocation attribute of microbat is used to model BA. Literature has reported a diverse range of BA applications such as loading pattern of nuclear core in engineering optimization, nonlinear economic dispatch problem, design of a power system stabilizer, size optimization for the skeletal structures which consist of truss and frame, multilevel image thresholding which is an image processing technique. In the context of inverse problem and parameter estimation, bat calculations have been utilized in solving numerical improvement, advancing the brushless DC wheel engines, and enhancing topological shape in microelectronic applications [12–15].

There are some successful implementations of BA in SO. In their work of stochastic resonance for MR images enhancement [16], proposed a neuron model that tapped on the BA multi-objective optimization property to tune the parameters. In their work, the BA is utilized to maximize both the image performance indices contrast enhancement factor and the mean opinion score. Their results show that the method has improved the gray-white matter differentiation, which has been found useful to diagnose MR images. In another work by [17], BA is adapted with inclusion of two operations—(1) iterative local search, and (2) stochastic inertial weight to improve its performance in terms of accuracy, speed and convergence stability. It is claimed that BA is easy to fall into local optima and has unstable optimization results due to low global exploration ability. The authors overcome the weaknesses of BA when their iterative local search algorithm disturbs the local optimum and do some local re-search, such that the BA has better ability to get out of the local optima. Adding with their stochastic inertial weight to disrupt the velocity updating equation, it enhances the diversity and flexibility of bat population. They proved their results based on 10 classic benchmark functions, CEC 2005 benchmark suite, and two (2) real-world problems, in which they concluded with improved performance.

A robust tuning of power system stabilizer is demonstrated to be possible by using BA [18]. In such scenario of RO application, the stability of the power system is highly critical. This paper proposed BA to optimize the gain and the pole-zero parameters of the stabilizer. They compared that the BA approach is superior than PSO optimization method. The optimization was performed with objective function based on eigenvalue shifting to guarantee the stability of nonlinear plant for a wide range of operating conditions.

A dynamic perceptive BA [19] is used to optimize particle filter for multiple targets tracking. This is an example of DO in which the authors proposed a multiple-maneuvering-target tracking algorithm and combined it with the BA to optimize particle filter typically used in a modern radar tracking system. Their combined algorithm regards the particles as bats and it simulates the behavior of bats preying by dynamically adjusting the radar tracking system's components of frequency, volume and pulse rate. This dynamic control of adjusting the particle filter, adding with a joint probabilistic data association has enabled an improved accuracy in target tracking even under a complex environment.

In other relevant applications, BA has been reported in data mining techniques of classifications and clustering. BA has been applied in grouping microarray information, minimization of make span and mean flow time to study half breed flow shop booking issues [20]. In the application of image processing, BA has been utilized for full body human stance estimation. In this study, BA has outperformed particle swarm optimization, particle filter and annealed particle filter. Bat based model has also shown its effectiveness in envision coordinating as compared in evolution and genetic algorithms [15]. In fuzzy logic and other applications, BA has been applied in investigating the ideal capacitor position for misfortune decrease in dispersion frameworks. BA and fluffy frameworks have also been utilized for energy displaying and energy changes in a gas turbine [15].

#### 3.2. Firefly algorithm

The current population of firefly species is over 2000. The short and rhythmic blazing light of fireflies is an astounding sight in the sky of the tropical and calm areas. This nature capability of fireflies inspired the firefly algorithm (FA) [21]. Bioluminescence is the process of generating the flash light. The light is used to model the warning signals. Each objective function of optimization problem is represented by different light intensity. They are some similarities between FA and bacterial foraging algorithm. Their attractions are based on objective function, fitness and distance respectively. FA can solve discrete and continuous optimization problems. Kwiecien and Filipowicz [22] have applied FA in cost optimization of queueing systems. A study carried out by Gandomi et al. [23] has proven that FA is better than other nonlinear optimization techniques in designing the stepped cantilever beam. FA has been reported in the recent literature as an efficient computational procedure for simultaneously generating multiple different alternatives to an optimal solution [24].

FA has a wide spread of applications since its introduction, attributed mainly to its simplicity of implementation as compared to some traditional approaches. In content-based image retrieval, feature extraction has been done with the Euclidean distance estimation between the pixels. However, such approach needs more precision, and this has motivated [25] to employ FA to optimize the image features. Their work is closely related to SO as the potential image features are stochastically found by FA. They benchmarked their FA image optimization results with PSO and GA and discovered the differences of each model in terms of precision and image recall. [26] also applied FA to solve a SO problem in linear phase finite impulse response filter (FIR) design. Differential evolution (DE) is known as one of the best performer in used for such problem. However, they proved through their simulation of designing FIR filters that FA is better than other relevant algorithms (inclusive of PSO and GA). The improvement was recorded not only in the convergence speed but also in the performance of the designed filter.

Other variants of FA have also found their applications in several various disciplines. [27] proposed a hybrid PSO-FA to solve a combinatorial optimization issue in floor planning. [28] introduced a hybrid FA and DE method to estimate the parameters of the nonlinear biological model. In the optimization design of sewer pipes, [29] has proposed a novel method by combining a support vector regression and the FA to predict the minimum velocity required to avoid sediment settling in the pipe channels.

#### 3.3. Lion optimization algorithm

Lion optimization (LO) [30] is a population-based algorithm which was inspired by lion's social system and collaboration characteristics which can be described with the term 'pride'. The uniqueness of lion's social behavior makes them the strongest mammal in the world. LO is modeled based on two unique behaviors of lion: territorial defense and territorial takeover. Based on these two behaviors, the solutions of LO are generated through three steps: (1) to differentiate whether each cub solution is an original or a derived solution; (2) territorial defense will proceed to evaluate and compare the existing and new solutions; (3) if the existing solution is better than the new solution, then territorial takeover will keep the existing solution to further improve it. LO can perform huge search space to solve continuous, single variable and multi-variable optimization problems. LO algorithm has been validated using De-Jong's Type 1 function and the performance has been compared against evolutionary programming. The results shown that LO performed better than evolutionary programming.

LO is still in its early stage of application, both [31, 32] have experimented on its optimization capability and benchmarked it on some function optimization problems. Both authors concluded on the high performance of LO in functions optimization. While [33] has taken LO further to perform clustering of data by utilizing the optimization capability of LO. Such data clustering approach is very much a SO problem. In their work, the LO is modified with the fractional theory to search the cluster centroids of data instead of typical distance measurement.

#### 3.4. Chicken swarm optimization algorithm

Chickens are sociable birds that they live in groups. Chicken swarm optimization (CSO) algorithm [34] was inspired by the social behavior of chickens. Every chicken has their own motion laws. The fitness values of the chickens will identify themselves as the roosters, hens and chicks. These identities will put them into groups. The fittest, the weakest and the intermediate chickens are simulated as a rooster, as a chick and as hens accordingly. The hierarchal order plays a vital part in the group of chickens and this characteristic is used to model CSO algorithm. CSO has been applied in solving the design of speed reducer efficiently. In that research, a gearbox has been created with the design of most efficient speed. The research on CSO has been promising. It has been used to improve the performance of the greedy algorithm [35].

A deadlock-free migration of virtual machine consolidation is optimized using CSO [36]. In such consolidation of services, two separate but related issues of virtual machine placement and migration is a challenging optimization task. The authors proposed a consolidation scheme utilizing CSO that turns the virtual machine consolidation problem into a vector packing optimization based on deadlock-free migration. The optimization also helps to minimize the energy consumptions. The proposed method achieved higher convergence rate as compared to several other deadlock-free migration algorithms.

CSO is also applied to a classical job-shop scheduling problem in the work of [37]. An improved version of CSO is also being applied to identifying the maximum power point tracking control of a photovoltaic system [38]. CSO has also seek its application in disaggregation of non-invasive domestic appliances [39].

#### 3.5. Social spider algorithm

Social spiders are organism living in groups. They are solitary and having aggressive characters among their own species. Their foraging behaviors and their corporation in performing daily tasks are used to model social spider algorithm (SSA) [40]. In SSA, two different evolutionary operators are created based on the gender of male and female spiders to divide their tasks for predation, web design and mating. This algorithm can solve a wide range of continuous optimization problems including minimization of molecular potential energy function [41, 42]. SSA has been validated using standard benchmark problems to study its performance. An analysis has been carried out on the performance SSA against particle swarm optimization and artificial bee colony. The results shown that SSA has outperformed the other techniques.

SSA has some wide application in recent researches. An SSA is proposed to solve a non-convex economic load dispatch problem [43]. Economic load dispatch (ELD) is one of the essential components in power system control and operation. Most modern power system introduces new models of the power units which are non-convex, non-differentiable, and sometimes noncontinuous; such RO problem is hence difficult to be solved by conventional mathematical techniques. In this paper, the authors modified the SSA to suit the characteristics of ELD, and their simulation results show that such ELD problem can be solved by SSA effectively and efficiently.

Another example of employing SSA to a DO problem is proposed by [42] to solve the transmission expansion planning in electrical power system. The authors tested SSA in solving the transmission expansion planning problem of three benchmark systems having 6-busses, 46 busses, and 87-busses. They achieved great performance as well as reduction in the total investment cost.

In a multi-objective optimization problem of QoS-aware web services, [44] applied SSA to perform optimized selection of numerous functionality in the web services involving complex tasks delivery. They studied current approaches of GA and PSO to realize that the time performance of such approaches is still a great concern. The proposed SSA has outperformed PSO in terms of both execution time and fitness.

#### 3.6. Spider monkey optimization algorithm

Spider monkey (SM) [45] is a population-based optimization algorithm which was inspired by the intelligent ways of spider monkeys to search for the most suitable food sources. The excellency of food source corresponds to the fitness of a solution. Major characteristics and the strategies of SM algorithm are similar to artificial bee colony algorithm. The exploration and exploitation functions allowed SM algorithm to perform huge search space and generate greatest feasible solutions. SM algorithm is simple and speedy. It is used to solve numerical optimization problems.

An example of SM application in continuous numerical optimization can be found in the work of [46]. They modified SM to enable it for solving some constrained optimization problems. Their proposed SM was tested on the well-defined constrained optimization problems of CEC2006 and CEC2010 benchmark sets. The algorithm acquired some promising results when compared to PSO, artificial bee colony and DE methods.

Although SM could be best to implement for a numerical problem, several other researchers have applied it to some wider scope of optimization problems. Both [47, 48] in their separate studies, have proposed SM to solve antenna optimization. [47] focuses their work in the thinning of concentric circular antenna arrays. While such thinning problem is a binary optimization, the original SM might not be suitable. Hence, they suggested their version of binary SM in which it must handle the logical operators of the thinning problem. Their results proved the competence and superiority of a binary SM as compared to existing metaheuristic algorithms. On the other hand, [48] applies SM to synthesize the factor of a linear antenna's array and to optimally design an E-shaped patch antenna. They discovered that their SM, when compared to traditional method for such optimization problem, can reach optimum solutions with less number of iterations.

#### 3.7. African buffalo optimization algorithm

African buffalo optimization (ABO) algorithm [49] was inspired by the practice of African buffalos in the vast African forests and savannahs in finding pastures. Three specific characteristics of these animals are used to model ABO algorithm. Firstly, these animals have high memory capacity. This skill enables them to monitor their routes up to thousands of kilometers in Africa continent. Secondly, they communicate among themselves using two specific vocalizations: 'maa' and 'waa' to support each other in surviving. Lastly, African buffalos practice 'democracy' system in making decisions.

The information of every buffalo's past and current location is used in tackling the issue of premature convergence. Leading buffalo's search space and the experience of all other buffalos complement to the exploration and exploitation strategies in ABO. This algorithm utilizes only learning parameters, therefore it is a simple and yet easy to implement algorithm which guarantees quick convergence. The efficiency and powerful features of this algorithm are capable in solving knapsack problems. ABO has been validated using traveling salesman benchmark problems to study its cost effectiveness. A study has been carried out on the comparative CPU time for ABO against Genetic Algorithm, Honey Bee Mating Optimization, Ant Colony Optimization, Simulated Annealing and Adaptive Simulated Annealing with Greedy Search. ABO has outperformed all other techniques to obtain the solutions at an incredibly fast rate.

[50] has used ABO to solve the well-studied Traveling Salesman's Problem (TSP). They performed ABO on 33 benchmark symmetric TSP and observed excellent exploration and exploitation of the search space through regular communication, cooperation, good memory of its previous individual and collective exploits. They concluded that ABO is as competitive as other algorithms superior in TSP.

In another DO example, ABO is used to optimize parameters tuning of proportional-integralderivative (PID) controller [51]. The PID controller in their study is used to automatically regulate voltage. It was noted that existing metaheuristic tuning methods have been proven to be quite successful, but the authors wanted to improve the gain overshoot and steady state errors of the system. They gained some encouraging results with ABO when it was compared to several other optimization algorithms.

#### 3.8. Flower pollination algorithm

The goal of plants, like any other living organism is producing offspring for the next generation. Pollination is the process of transferring pollen grains from the male anther of a flower to the female stigma. Two types of pollinations process are self-pollination and cross pollination. When pollen grains are produced, pollinators will spread it among the flowers to either local or global flow of pollination. The process of passing the pollen grains from the stamens

to the ovule-bearing organs during pollination is used to model flower pollination algorithm (FPA) [52].

The assumption on the current version of FPA: each flower only produces one pollen gamete. The time complexity of FPA is shorter; therefore, it is flexible and easy to implement. A study has been carried in structural engineering to evaluate the cost optimization of tubular column under compressive load using FPA against Cuckoo search algorithm, fuzzy rules and engineering optimization techniques. The results showed that FPA is the most efficient method and the convergence of the algorithm is very effective. This algorithm has been applied for solving continuous, single objective and multi-objective optimization problems. It can be improved further to apply in the areas of image compression and graph coloring. FPA has successfully converged in shape matching problem based on a relatively new branch called atomic potential matching model [53].

FPA is applied to a visual tracking problem in the work of [54]. In their model, visual tracking is considered to be a process of optimal reproduction of flowering plants. This is a typical example of DO. FPA is then presented with a switch probability that changes dynamically with generation numbers. To compare the tracking ability of the FPA tracker, the tracking accuracy of particle filter, mean shift and PSO are studied as well. Comparative results show that their method outperforms the other three trackers. Other applications of FPA can be found in the works of [55–57]. [55] proposed a FPA to optimize a SO problem of static economic dispatch incorporating wind farm. [56] worked on the sizing optimization of truss structures. Again, this is another example of SO. While [57] applied FPA on a DO problem of photovoltaic parameters optimization. Through their simulation, FPA is recommended as the fastest and the most accurate optimization technique for the optimal parameters extraction process, after benchmarking it on several other methods.

#### 4. Conclusion

All different creatures survive with their own unique behaviors and features. Their characteristics are concealing in the natural world. This chapter has reviewed eight natural inspired algorithms mainly from the field of swarm intelligence. These techniques are becoming powerful in numerical optimization and have shown remarkable robustness, high accuracy and have immense capacity in solving different types of optimization problems.

In dealing with real world problems of optimization, we are now presented with even more choices of algorithm thanks to inspirations form the nature, as well as persistence research contributions by many researchers. However, with more choices means it could be even harder to decide which one of the algorithms is a better candidate for a problem at hand. Based on No-Free-Lunch theorem, there is surely no single best algorithm for every problem. The complexity, characteristics and diversity of optimization problems mean that it is very unlikely to have a single method that can handle all types of optimization problems. This is very much the current state of research in optimization, despite the abundance of nature inspired algorithms being added to the solution pool.

Moving ahead, the research community is definitely not looking for a single most powerful algorithm to solve all types of problem. Indeed, we might witness even more successful variants of algorithm being developed from their current counterparts. This is a trend we have observed since any introduction of a new algorithm being inspired. It is also possible that more and more new optimization algorithms are to be inspired, given that the vast unknown and untested phenomena in the nature are still beyond our exploration.

### Author details

Siew Mooi Lim<sup>1</sup> \* and Kuan Yew Leong<sup>2</sup>

\*Address all correspondence to<EMAIL_ADDRESS>
1 Faculty of Computing, University Malaysia of Computer Science and Engineering, Putrajaya, Malaysia

2 School of Information Technology (Caulfield), Monash University, Melbourne, Victoria, Australia

#### References

Algorithms and Applied Optimization. Studies in Computational Intelligence, Vol. 744. Springer; 2018

## *Edited by Javier Del Ser and Eneko Osaba*

Nature-inspired algorithms have a great popularity in the current scientifc community, being the focused scope of many research contributions in the literature year by year. Te rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research felds and problem instances. Tis book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative fndings when used in diferent subfelds of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.

Published in London, UK © 2018 IntechOpen © BirdHunter591 / iStock


**Author details**

Bilal Rah† , Shazia Ali† , Mohd Ishaq Dar† and Dil Afroze\*

\*Address all correspondence to<EMAIL_ADDRESS>
Department of Immunology and Molecular Medicine, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, J&K, India

† These authors contributed equally.


**2. Ventricular assist devices**

#### **2.1 First generation**

The earliest VADs incorporated a diaphragm and unidirectional artificial valves to replicate the pulsatile cardiac cycle with a diastolic filling time and a systolic emptying of the devices, mimicking that of the native heart [19]. These devices are pumps designed to mechanically assist a failing Left Ventricle (LV) by removing blood from the LV and returning it into the circulatory system *via* the aorta. While LV dysfunction is more common, VADs can also be used to treat right ventricular failure or both. These first-generation VADs were either pneumatically or electrically driven, included the Thoratec HeartMate IP ("Implantable Pneumatic"), VE ("Vented Electric"), XVE ("Extended Vented Electric") (Abbott Laboratories, formerly Thoratec, Pleasanton, CA), and the Berlin Heart EXCOR (Berlin Heart, Berlin, Germany) [1]. These early devices were used to support patients as a BTT and could be used as left-, right-, and biventricular devices (LVAD, RVAD, and BiVAD). The first-generation devices introduced electromechanical actuation, which allowed some to be powered by a battery worn on the waist, affording better mobility, and allowing patients to be discharged from the hospital waiting for a new heart [20]. Anecdotally, these first devices had several disadvantages including large size, noise emission, infectious diseases, malfunctioning, mechanical tears, or valve degradation.

First-generation LVADs were known as volume displacement pumps and generated flow *via* a pulse generator [15, 21]. The goal of the first-generation LVADs was to provide long-term circulatory support, such that these devices could be used as a bridge to transplant [20, 22].

The HeartMate systems were housed within a titanium shell and situated beneath the patient's diaphragm on the left side. Within the housing, a polyurethane diaphragm divided the blood-contacting chamber and the chamber housing the motor. A sintered titanium microsphere layer was applied to the titanium blood-contacting surfaces of the pump and a fibrillar texture was on the polyurethane diaphragm. These surface modifications allowed circulating cells to adhere and form an intimalike tissue layer [20, 22]. The HeartMate IP (Abbott Laboratories, formerly Thoratec, Pleasanton, CA, USA) was the first LVAD to receive FDA approval for use in patients as a BTT in 1994. Clinical trials of the HeartMate VE began in 1992. Following the positive outcomes from the REMATCH trial, the HeartMate VE was approved by the FDA as destination therapy in 2003. This VAD was later updated to the HeartMate XVE device and served as the device to which the next generation of LVAD was compared. The Heartmate VE and XVE systems were driven by an electric motor. The REMATCH results propelled widespread use of LVADs in the clinical setting and led

to FDA approval of the HeartMate VE (HeartMate I) and the inclusion of other firstgeneration LVADs such as the Thoratec Implantable VAD (IVAD), an intracorporeal device, as well as the Thoratec PVAD, a paracorporeal device. Both devices provide the option of being used as left, right, or biventricular support and are both approved for use as BTTs. They were pulsatile flow devices comprising a 65-mL blood chamber with unidirectional flow achieved by tilting disk mechanical valves [23].

The Novacor LVAS (formerly WorldHeart, Oakland, CA, and acquired by HeartWare International, Inc., Framingham, MA) features an implanted pump/ drive unit and an external control console. The pump consisted of a polyurethane sac bonded to dual pusher plates contained in a housing that included valve fittings. This device became available in 1984, initially as a console-based unit, but a wearable configuration became available in 1993. This unit was initially intended for destination therapy (DT) in the treatment of individuals with end-stage heart failure, but it was eventually used as a BTT [24]. The first clinical implant for a bridge to transplantation reportedly occurred in 1984 by Portner et al. [25]. Complications associated with the device included cerebral vascular accidents, bleeding, and infection. This device was discontinued by the manufacturer in 2008 with a greater focus on newergeneration VADs.

The Arrow LionHeart LVAD 2000 (Arrow International Inc., Reading, PA) was an implantable pulsatile VAD, designed for use for DT in patients with end-stage heart failure. The system had no percutaneous lines or connections and consisted of a titanium blood pump with inflow and outflow assemblies, a motor, a compliance chamber, and a transcutaneous energy transmission system [26]. The Clinical Utility Baseline Study was performed to establish whether the transcutaneous energy transmission system resulted in fewer infections than the observed during the REMATCH trial and concluded that Lionheart recipients exhibited less sepsis and device-related infection than the REMATCH trial group. The device, however, was discontinued in 2005.

The Berlin Heart EXCOR VAD was developed in Berlin, Germany, by Berlin Heart and is a pneumatically driven paracorporeal support device that can be used to provide left, right, or biventricular support. Its size ranges from pediatric to adult sizes. The device was first used as a BTT in 1988 [27, 28]. In 1992, the Berlin Heart became the first commercially available pulsatile assist device for children. This device received the CE mark in Europe in 2000 but was granted FDA approval for pediatric use only in the USA in 2011. This device is specifically designed for infants and children with stroke volumes of 10, 25, and 30 mL [29]. It is a pneumatic, compressor-operated diaphragm pump with polyurethane valves. Larger pumps (50, 60, and 80 mL) are equipped with mechanical valves.

BiVADs may be useful in patients with total heart failure and support both sides of the heart by balancing left and right pump flows. First-generation BiVADs included Abiomed BVS5000 and AB5000 (AbioMed Inc., Danvers, MA, USA), Thoratec PVAD and IVAD (Thoratec), Berlin Heart EXCOR (Berlin Heart, Berlin, Germany), and Medos HIA-VAD (MEDOS Medizintechnic GmbH, Stolberg, Germany) [2].

The Abiomed BVS5000 (AbioMed) was clinically introduced in 1987 and approved for use by the FDA in 1992. The device is an extracorporeal, dual-chambered BiVAD. The advantages of this device include simplicity and low cost, making it one of the most frequently used BiVADs worldwide [30]. The BVS5000 has two separate pumping and filling bladders driven by a pulsatile drive console. The device has demonstrated reasonable success in bridging patients to recovery from cardiogenic shock; however, issues with portability and thrombus incidence present limitations

#### *A Historical Review of Mechanical Circulatory Support DOI: http://dx.doi.org/10.5772/intechopen.110525*

should long-term VAD support be required [31]. The Abiomed AB5000 (AbioMed) gained FDA approval in 2003 and is very similar to the BVS5000, as it is a pneumatically driven volume displacement pump. Unlike the BVS5000, its paracorporeal location means that this device can be used as a VAD treatment or as a replacement, allowing the patient greater mobility [32].

The Thoratec PVAD (Thoratec) was approved by the FDA in 1995 for BTT and in 1998 for postcardiotomy support. It is a pneumatically driven paracorporeal VAD suited for left, right, or biventricular assistance, as well as use as a total artificial heart. The Thoratec IVAD (Thoratec) was approved by the FDA in 2004 to support systemic and/or pulmonary circulations in left, right, or biventricular assist configuration. This device is intracorporeal, pneumatically actuated, and pulsatile, operating in a full-to-empty mode utilizing optical infrared sensors to detect the end-systolic and diastolic position of the membrane providing an adequate balance of blood flow [33].

The Medos HIA-VAD is a paracorporeal device with transparent pump chamber sizes to be used in adult, infant, and pediatric cases. Development was initiated in 1982 at Helmholtz Institute for Biomedical Engineering in Aachen, Germany, and was acquired by Medos Medizintechnik GmbH in 1990. It has been used since 1994 and received the CE trademark in Europe in 1997. The system can work either at a fixed rate or with an electrocardiogram trigger and is pneumatically actuated, providing left, right, or biventricular support [15, 19].

The NIPRO-VAD (National Cardiovascular Center/Toyobo ventricular assist system) is an extracorporeal pneumatically driven diaphragm pump. It was reportedly first implanted in 1982 at the Saitama University Medical School and the Osaka University Hospital. While the device has been used long term, up to 1264 days, patients supported by this system have limited mobility and therefore the device has been exchanged for second- and third-generation devices [22].

The Zeon VAD is a pneumatically driven extracorporeal pump, first implanted in 1980. The pump was used for left, right, and biventricular support as BTT in Japan. The pump was discontinued in 2005 [22].

## **2.2 Second generation**

Since first-generation pumps were limited by their large size, high noise emissions, decreased patient mobility, and durability issues, research to develop smaller, more reliable devices was initiated [15]. Some of the features that characterize the second-generation LVADs from the first are that they are continuous, rather than pulsatile pumps, and that they produce axial blood motion using a rotor [34]. The second- and third-generation VADs replace or support only the ventricular function. There is no direct attempt made to imitate the modality of the native, ventricular function [20, 34].

The first reported device that falls in the second-generation category is the Biomedicus Bio-Pump (Medtronic Inc., Eden Praire, MN, USA). It has been used since the mid-1980s. Is a centrifugal pump that provides extracorporeal left and/or right ventricular assistance for short-term bridge-to-bridge, bridge-to-recovery, and bridge-to-transplant support [34, 35].

The HemoPump was the first implantable rotary blood pump with an extracorporeal drive. It required continuous infusion of a purge fluid. It was only used within clinical trials in the USA and the first in man use was in 1988, marking the beginning of the era of implantable, less invasive, rotary ventricular assist devices [36].

A few years later in Europe, in 1999, the ROTAFLOW (Maquet, Hirrlingen, Germany) was approved for pulmonary and/or ventricular support, including cardiopulmonary bypass, or used in the framework of extracorporeal membrane oxygenation (ECMO) procedures [34].

The first clinical use in a human of the DeBakey VAD, which later evolved to the HeartAssist 5, was in November 1998, and this marks the beginning of a new era of long-term second-generation LVADs. The VAD itself consists of a miniaturized axial flow pump system, an external controller system, and a clinical data acquisition system [37, 38]. This is the only rotary LVAD where the flow is measured directly at the outflow prosthesis with an ultrasonic transducer, thereby producing reliable system monitoring [38].

After a decade of pioneering work achieved with the HemoPump, the Impella product family evolved into a platform technology. In 1999, the Impella device was approved for use in Europe. The Impella RP (AbioMed Inc., Danvers, MA, USA) is a minimally invasive temporary microaxial pump for the percutaneous treatment of RV failure in pediatric or adult patients for up to 14 days. The device is exclusively inserted percutaneously through the femoral vein and advanced in an antegrade fashion across the pulmonary valve into the pulmonary artery under fluoroscopy. The pump aspirates blood from the inferior vena cava and ejects it into the pulmonary artery. This action provides forward flow in the pulmonary circulation and unloading of the RV [39]. The Impella 2.5, CP, 5.0, 5.5, and LD have also been designed and approved for use in High-Risk Percutaneous Coronary Interventions (HRPCI) and cardiogenic shock [34].

The Impella 2.5 and CP are percutaneous microaxial circulatory support pumps. The Impella 2.5 can deliver up to 2.5 l/min of systemic flow augmentation by pumping directly from the left ventricle into the ascending aorta [40]. The Impella CP can deliver flows up to 3.7 l/min. The Impella 2.5 and CP are used for HRPCI. The Impella 2.5 showed better results in patients undergoing HRPCI than the intra-aortic balloon pump [41]. In addition, the Impella CP due to easy placement access through the femoral artery, can be used in cases of acute decompensated heart failure or worsening cardiogenic shock driven by the left ventricle.

The Impella 5.0 and 5.5 are larger microaxial pumps implanted through a conduit sutured to the axillary artery [42] or directly sutured to the aorta through a graft either through a full sternotomy or through partial upper one in cases of small axillary artery [43] and can provide flows, 5.0 and 5.5 l/min, respectively, like that of durable LVADs [44]. They also promote patient mobilization and therefore give patients the ability to participate in physical therapy. They can also be used when other smaller microaxial pumps result in refractory hemolysis, resulting in better outcomes [45]. The Impella 5.5 can be used in cardiogenic shock as a bridge to recovery, a bridge to transplant, a bridge to a decision, or a durable LVAD [46].

The Jarvik 2000 FlowMaker (Jarvik Heart, Inc., New York, NY) is an axial flow LVAD that has been used in patients since the year 2000 as a bridge to recovery (BTR), BTT, and DT. This device uses alternative outflow connections and can also be used to support right ventricular function in humans. The pump is equipped with five speeds that can be manually set [47]. It is one of the smallest clinically available LVADs as well as having the longest period of left ventricular support with 9.5 years of uninterrupted support [16].

In 2001, Thoratec introduced the most successful LVAD, with respect to implantation numbers and studies, the HeartMate II VAD which was smaller and lighter than the original HeartMate XVE [3] (**Figure 2**). The development was initiated in

#### *A Historical Review of Mechanical Circulatory Support DOI: http://dx.doi.org/10.5772/intechopen.110525*

1991 with research collaboration between the McGowan Center of the University of Pittsburgh and Nimbus Company [20, 34]. It was approved for use in 2005 in Europe and the USA, the FDA approved it as a BTT device in 2008 and as a DT device in 2010. It is an axial-flow device composed of a blood pump, percutaneous lead, an external power source, and a system driver. The pump rotor and blood tube are made of smooth titanium, while the stators, inlet and outlet elbows, and intraventricular cannula are textured with titanium microsphere coatings. This design reduced prothrombotic sites and minimized wear and tear associated with multiple moving parts. Surfaces contacted by blood were designed with a textured titanium lining as an antithrombotic measure. Initially, the pump was placed in the intra-abdominal position but was then switched to a preperitoneal position where the body of the pump can then be easily accessed for pump exchange through a left subcostal approach [48]. From 2009 to 2017, the HeartMate 2 was the main LVAD being implanted worldwide. Although the improvement of survival over time has led to widespread adoption of this therapy, adverse events persist including, infection, bleeding, and pump thrombosis [49]. The rate of pump thrombosis has been reported as high as 10% after the first-year post-implantation, with a rate of 13% of pump exchange secondary to pump thrombosis [50]. One cause of driveline failure in the HeartMate II is damage to the wiring insulation of the percutaneous lead resulting in an electrical short to ground, referred to as a short-to-shield (STS). The percutaneous lead has six electrical wires attached to six motor stators to power a three-phase pump. There are three stranded primary wires and three backup wires for each of the phases. An STS occurs when there is an inappropriate electrical connection between one of the stranded wires and the shield, disrupting the normal flow of power [51]. A phase-to-phase short occurs when there is a loss of insulation between the three redundant motor coils (i.e., phases) of the driveline. When present, phase-to-phase short is particularly troublesome in that pump stoppages are likely and unpredictable. The manufacturer, therefore, recommended against controller exchange due to concern over the possibility that the pump would not restart, and instead recommended driveline repair, followed by surgical pump exchange should the problem persist [52]. Currently, there are still thousands of patients supported with the HeartMate 2 pump, **Figure 2**.

The CircuLite Synergy Micro-Pump, unlike the HemoPump and the Impella, was approved as a long-term LVAD and was implanted for the first time in a human in 2007. This pump was mainly used as a partial support device and sits in a pacemakerlike pocket [34].

The EVAHEART is the only implantable, centrifugal second-generation LVAD. The first-in-human use was in 2005 and was approved in Japan in 2010. It requires continuous insertion of cool seal fluid (purified water) [34].

The Heartmate X was announced in 2012 as an axial LVAD and leverages HeartMate 2 core bearing technology and is still under development in the animal stage [34]. It is a smaller pump and potentially allows for a less invasive implantation technique and could be used for smaller patients [53].

The Thoratec PHP was approved in Europe in 2015, which was the last approval of the second-generation LVADs, consisting of a shaft-driven axial pump with a foldable impeller. The device is inserted through the femoral artery and advanced to the aortic valve.

The MERA HCF-MP23 (Senki Medical Instrument Manufacturing Co. Ltd., Tokyo, Japan) is a centrifugal pump used for short-term extracorporeal circulatory support. The use is aimed at open heart surgery circulatory support and for bridge-to-decision

#### **Figure 2.**

*Schematic representation of the HeartMate II (Abbott Laboratories, Abbott Park, IL). A successful continuousflow pump with axial design.*

use for up to 4 weeks. However, it was successfully used as an RVAD in a patient with right heart failure post-LVAD implantation for up to 17 weeks [54].

#### **2.3 Third generation**

Third-generation LVADs are continuous-flow centrifugal pumps designed with magnetic and/or hydrodynamic levitation of the impeller with non-contact bearings and outflow directed perpendicular to the axis of rotation [15, 19, 20, 55]. Fully magnetically levitated implantable blood pumps were proposed in patients by Olsen and Bramm in 1986 and Moise in 1987 [55]. Currently, continuous flow LVADs (CF-LVADs) are used in 99% of patients requiring an LVAD [30]. The development of third-generation devices aimed to improve durability and hemocompatibility. The two main LVADs discussed in this chapter are HeartMate III and HeartWare. Other examples include the TandemHeart (CardiacAssist Inc., Pittsburgh, PA, USA), Levacor (World Heart Inc., Salt Lake City, UT), and the DuraHeart (Teruma Heart, Inc., Ann Arbor, MI).

The HeartWare HVAD (Medtronic Inc., FL, USA) was approved by the FDA for BTT in 2012 and its implantation is completely intrapericardial; a smaller pump size eliminates the need for an abdominal pocket [30, 55]. From 2012 to 2017 was the pump of choice as BTT and for an additional year was the pump most commonly implanted as destination therapy. This device has magnetic and hydrodynamic levitation of the internal rotor and is connected directly to the heart at the base of the

#### *A Historical Review of Mechanical Circulatory Support DOI: http://dx.doi.org/10.5772/intechopen.110525*

left ventricle. This device had the advantage that could be implanted without cardiopulmonary bypass easily due to the design of the coring knife [56]. The FDA recalled this device and Medtronic halted distribution and sale in June 2021 due to increased risk of neurological events and mortality associated with the internal pump, and the ability to restart if the internal pump stops [57].

The HeartMate III (Abbott Laboratories, formerly Thoratec Corporation, Pleasanton, CA, USA) was initially approved by the FDA for adults awaiting a heart transplant in 2017 and approved for long-term use in 2018. Its initial development started in 1998, using the same technology as the CentriMag, but modified to be fully implantable [55]. The first in human use was in June 2014. This device is implanted directly into the left ventricle and is fully magnetically levitated. It is designed to pass an inflow cannula through the apex of the heart and is directed toward the mitral valve to optimally drain blood from the left ventricle through the outflow graft and into the systemic circulation. The implications of this technology are substantial. Data from the MOMENTUM three randomized trial and subsequent publications (including the 5-year follow-up) have demonstrated the superiority of the centrifugal-flow LVAD to the HeartMate II with respect to survival to transplant, recovery, or LVAD support free of debilitating stroke or reoperation [58]. The superior performance of the HM3 at 6 months was due to 0% of the HM3 patients experiencing pump thrombosis, whereas 10.1% of patients with HM2 experienced pump thrombosis. Significant differences were not appreciated when comparing HM3 and HM2 with respect to bleeding, sepsis, driveline infection, right heart failure, arrhythmia, respiratory failure, renal dysfunction, hepatic dysfunction, or hemolysis not associated with pump thrombosis.

The HeartMate 6, an off-label use of two HeartMate 3 devices for biventricular support as a total artificial heart, has been reported in a patient as a successful bridge to transplant [59].

The Abbott CentriMag was the first available third-generation blood pump that was fully magnetically levitated. Originally developed and commercialized by Levitronix in 1995, the medical arm of Levitronix was then acquired by Thoratec in 2011 and Thoratec was later acquired by Abbott in January 2017 [55]. It is an extracorporeal centrifugal pump and is approved for use as an RVAD for up to 30 days in patients with cardiogenic shock. The magnetic levitation and motor principles are identical to those of the HeartMate 3, described above. Cannulation configuration differs depending on the support needed, i.e., LVAD, RVAD, or BiVAD. The CentriMag can also be used as a pump in the ECMO circuit [55].

In the US, it is approved for 6-hour acute extracorporeal circulatory support during cardiac surgery or humanitarian use device for RVAD support in cardiogenic shock as a result of right-sided heart failure. It is the surgical temporary ventricular assist device of choice. In Europe, it is approved for 30 days of extracorporeal VAD support [55].

The Levacor LVAD (WorldHeart has ceased trading) development was originally started by Medquest in 1996 and then was later acquired by WorldHeart. The first in human use was in March 2006. It is a radial flow pump employing a hybrid active and passive bearing to suspend a centrifugal impeller. In 2011, World Heart discontinued efforts to commercialize this device as a result of large device size and technical issues [60].

The Terumo DuraHeart LVAD (Terumo Corporation, Tokyo, Japan) was developed in 1991 with its first human use in January 2014. It is an implantable radial flow pump incorporating an axial magnetic bearing providing long-term left ventricular

assistance with a contact-free impeller suspension system. The US SUSTAIN trial (A Study Evaluating Safety and Effectiveness of the DuraHeart Left Ventricular Assist System in Bridge to Transplant Patients) began in 2008 but was prematurely terminated in December 2011, due to slow recruitment based on the size of the device and the difficult configuration of the inflow cannula [61].

The HeartWare MVAD (Medtronic Inc., FL, USA) is a miniaturized implantable VAD that uses a passive maglev and hydrodynamic bearing system to levitate the rotor once it is rotating. It was developed in 2004 with the first in human use in July 2015. Its clinical trial was suspended 2 months later and has not been restarted [55].

The TandemHeart (CardiacAssist Inc., Pittsburgh, PA, USA) uses a paracorporeal, continuous flow, centrifugal pump originally developed for left atrial-to-femoral artery bypass to provide hemodynamic support during high-risk coronary interventions and post-cardiotomy cardiac failure. It was first used in a human in the year 2000 The use of this device has been reported in several conditions and with a change in cannulae configuration it can be used in acute myocardial infarction, post-LVAD implantation, pulmonary hypertension, severe acute mitral regurgitation, and cardiac rejections after heart transplantation [34, 62]. This device has also been successfully used for post-myocardial infarction interventricular septum defect, allowing time for left ventricular recovery and definitive surgical repair [63].

The Berlin Heart INCOR (Berlin Heart GmbH., Berlin, Germany) is an implantable VAD that has an active magnetically levitated rotor. It is implanted below the diaphragm in an abdominal pump pocket and due to the size, it is not viewed as being suitable for less invasive implantation methods. Despite its designs, the initial results were undermined due to issues with the design of the inflow cannula causing high rates of embolic complications. The first in human use was in 2002. However, recent results with new designs have shown improved results with respect to GI bleeding and *de novo* pump thrombosis [64].

The Ventracor (is no longer trading) was developed in 1997 with the first in human use in 2003. Approximately 450 devices were implanted before the company ceased trading in 2009 [55].

The Arrow CorAide left ventricular assist system (LVAS) (Arrow International, Reading, PA, USA) is a continuous flow left ventricular assist device, as a bridge to transplantation or recovery as well as destination therapy in patients with New York Heart Association (NYHA) class IV heart failure. Its use has been limited to clinical trials and was originally developed at the Cleveland Clinic. The first patient was implanted in May 2003. It was the first third-generation magnetically levitated pump to be included in a clinical trial [65].


*3.1. CNN Architecture*

We first tested different pre-trained base CNNs (VGG, ResNet, Inception, Xception, MobileNet and DenseNet) to which we added trainable layers. The combined CNN model was trained with a batch size of 32 for 100 epochs. In the case of no learning, the training stopped earlier. Out of the 50% of balanced data used for training, we used 10% for validation. These data were not seen by the network, but were used only to calculate loss and accuracy per epoch. These metrics and their curves looked most promising for VGG19 [25]. Then we applied the trained network to the remaining 50% of testing data. VGG19 is a 19 layer deep CNN developed by the Visual Geometry Group (VGG) from the University of Oxford (Oxford, Oxfordshire, UK). It is trained to classify images into 1000 object categories, such as keyboard, mouse pencil and many animals. It has learned high-level features for a wide range of images from ImageNet [34]. ImageNet is a dataset of over 15 million labeled high-resolution images with around 22,000 categories. Compared to other CNNs, VGG has shown to generalize well, compared to more complex and less deep CNN architectures [25].

We used VGG19 layers pre-trained for 20,024,384 parameters as a base model. Next, we modified hyper-parameters for VGG19 on the learning optimizer, the depth of the fully connected layer, and the dropout rate to optimize accuracy and loss. We used softmax as an activation function to retrieve predictions for tiles being 'not boundary' in the range [0, 1]. These values represent the weights for the later least-cost-path calculation. Sigmoid activation, which is a type of softmax for a binary classification problem, provided similar results in terms of accuracy and loss. However, it required more post-processing, as the resulting value in the range [0, 1] cannot be understood as described for softmax activation.

The aim was to maximize the accuracy for training and validation data, while minimizing loss. To avoid over-fitting, the curves for training and validation accuracy should not diverge, which was achieved by increasing the dropout rate from 0.5 to 0.8. To avoid under-fitting, the curve for training accuracy should not be below that of the validation accuracy, which was avoided by increasing the depth of the fully connected layer from 16 to 1,024. To avoid oscillations in loss, the learning rate was lowered from 0.01 to 0.001. Learning was stopped once the validation accuracy did not further improve. Results and observations derived from different hyper-parameter settings and different pre-trained base CNNs are provided in the Appendix A (Table A1).

We achieved the best results after training 8,242 parameters on four trainable layers added to 22 pre-trained VGG19 layers (Table 3). This led to a validation accuracy of 71% and a validation loss of 0.598 after 200 epochs (Figure 7). The accuracy could be increased by 1% after 300 epochs, with validation loss restarting to increase to 0.623. We conclude that optimal results are achieved after 200 epochs. 100 epochs halve the training time to 11 hours, whilst obtaining 1% less accuracy and a loss of 0.588. The implementation relies on the open source library Keras [35], and this is publically available [23]. All experiments are conducted on a machine having a NVIDIA GM200 (GeForce GTX TITAN X) GPU with 128 GB RAM (Nvidia Corporation, Santa Clara, CA, US).

**Figure 7.** Accuracy and loss for our fine-tuned VGG19.

#### *3.2. RF vs. CNN Classification*

Of those lines that should get a boundary likelihood > 0, i.e., those that fall within the cadastral reference buffer, 100% for RF and 98% for CNN are assigned a boundary likelihood > 0 (Table 4). This means that both classifiers predict a boundary likelihood in the range [0, 1] when there is some overlap with the cadastral reference buffer.

**Table 4.** Is the boundary likelihood predicted for the correct lines?

Next, we looked at how valid the boundary likelihood is, i.e., whether its value is equal to the line's overlap with the cadastral reference buffer. For this we excluded lines having no overlap with the cadastral reference buffer, i.e., those having an overlap = 0. We grouped the remaining lines to compare boundary likelihood and overlap values (Table 5). For RF-derived boundary likelihoods, we obtained an accuracy of 41% and a precision of 49%. For CNN-derived boundary likelihoods, we obtained an accuracy of 52% and a precision of 76%. The percentage of lines per value interval of 0.25 for the same boundary likelihood and overlap value deviated on average by 15% for RF and by 7% for CNN (Table 5).

Overall, CNN-derived boundary likelihoods obtained a similar recall, a higher accuracy, and a higher precision (Table 4). The percentage of lines for different ranges of boundary likelihoods represented the distribution of overlap values more accurately (Table 5). Even though the values of overlap and boundary likelihood do not express the same, they provide a valid comparison between RF- and CNN-derived boundary likelihoods. We consider CNN-derived boundary likelihoods a better input for the interactive delineation, and continue the accuracy assessment for a boundary classification based on CNN.

**Table 5.** How correct is the predicted boundary likelihood?

#### *3.3. Manual vs. Automated Delineation*

Indirect surveying, comprising of manual or automated delineation, both rely on visible boundaries. Before comparing manual to automated delineation, we filtered the cadastral reference data for Ethiopia (Figure 2b) to contain visible parcels only. We kept only those parcels for which all boundary parts were visually demarcated. As in Kohli et al. [4], we consider only fully closed polygons that are entirely visible in the image. From the original cadastral reference data, we kept 38% of all parcels for which all boundaries were visible. In Kohli et al. [4], the portion of fully visible parcels has been reported to average around 71% of all cadastral parcels in rural Ethiopian areas. We can confirm 71% for parts of our study area that cover smallholder farms. Cadastral data for Rwanda and Kenya were delineated based on local knowledge in alignment with visible boundaries. As for Ethiopia, only fully closed and visible parcels were considered. The mean size of our visible parcels amounts to 2,725 m2 for Ethiopia, 656 m2 for Rwanda, and 730 m2 for Kenya.

When manually delineating visible boundaries, we observed how tiring a task this manual delineation is: The delineator has to continuously scan the image for visible boundaries to then click precisely and repeatedly along the boundary to be delineated. Apart from the visual observation of the ortho-image, the delineator has no further guidance on where to click. Each parcel is delineated the same way, which makes it a highly repetitive task that exhausts the eyes and fingers in no time.

When comparing manual to automated delineation, this impression changes: The delineator now has lines and vertices to choose from, which can be connected automatically using multiple functionalities (Table 2, Figure 6). Complex, as well as simple, parcels require fewer clicking when delineating with the automated approach: To follow a curved outline, manual delineation requires frequent and accurate clicking while zooming in and out. Automated delineation requires clicking on vertices covering the start and endpoint once, before they are automatically connected precisely following object outlines (Figure 6d). Similarly, the automated delineation is superior for simple rectangular parcels: While manual delineation requires accurate clicking on each of the at least four corners of a rectangle, automated delineation allows clicking once somewhere inside the rectangle to retrieve its outline (Figure 8a).

However, choosing the optimal functionality can be time-consuming, especially in cases of fragmented MCG lines obtained from high-resolution UAV data. We assume that the time for automated delineation can be reduced through increased familiarity with all functionalities and by further developing their usability, e.g., by keyboard shortcuts.

**Figure 8.** (**a**) Automated delineation requires clicking once somewhere in the parcel, while manual delineation requires precise clicking at least four times on each corner. (**b**) Boundaries partly covered or delineated by vegetation impede indirect surveying and limit the effectiveness of our automated delineation compared to manual delineation.

Automated delineation required fewer clicks for our rural and peri-urban study areas (Table 6). Only those parcels for which one of our functionalities was more effective than manual delineation are considered for the automated delineation, amounting to 40–58% of all visible parcels. The effectiveness of manual delineation is considered for all 100% of the visible parcels. By maximizing the number of delineated parcels, we aimed to minimize the effect of unusual parcels that required much effort to delineate manually. We expect the measures that we obtained for the manual delineation to be similar for the 40–58% of parcels considered for the automated delineation. For the remaining parcels, MCG lines were either not available, or not aligning enough with the reference data. Manually delineating these parcels with the plugin requires the same number of clicks and time as conventional manual delineation, but is partly less tiring, as the delineation can be snapped to the MCG lines and vertices.

**Table 6.** Does automated delineation cost less effort?

Nevertheless, the lines and vertices can also impede the visibility: For our data from Rwanda and Kenya, the boundaries are not continuously visible. The partly vegetation-covered boundaries result in zigzagged and fragmented MCG lines (Figure 8b). Additionally, visible boundaries with low contrast were partly missed by MCG image segmentation. In both cases, the advantages of automated delineation are limited.

We claimed that the least-cost-path based on the boundary likelihood is beneficial to delineate long and curved outlines [21,22]. For the Ethiopian data, we now barely made use of the boundary likelihood: For the often small and rectangular parcels, connecting all lines surrounding a click or a selection of lines was more efficient. For areas with few fragmented, long or curved outlines, the workflow is assumed to be of similar effectiveness when leaving out the boundary classification. To include the boundary classification is beneficial when boundaries are demarcated, e.g., by long and curved boundaries, such as roads, waterbodies, or vegetation.

For our data from Kenya and Rwanda, we omitted the boundary classification, since we hardly used it for the Ethiopian data. The least-cost-path, for which a weight attribute can be selected in the plugin interface, used line length instead of boundary likelihood. Since the boundaries differ from

the boundaries in the Ethiopian scene, the CNN would need to be retrained or fine-tuned for the new boundary types. Retrieving CNN-derived boundary likelihoods for these UAV data would require further experiments on whether and how to rescale tiles to 224 × 224 pixels, while providing context comparable to our aerial tiles (Figure 5).

Overall, the automated delineation provided diverse functionalities for different boundary types (Table 7), which made delineation less tiring and more effective (Table 6). Improvements to manual delineation were the strongest for parcels fully surrounded by MCG lines. Such parcels were mostly found in the Ethiopian rural scene, where boundaries aligned with agricultural fields. In the Rwandan scene, automated delineation was time-consuming, since the boundaries were not demarcated consistently. Selecting and joining fragmented MCG lines required more careful visual inspection compared to the rural Ethiopian scene. In the Kenyan scene, the boundaries were less often covered by vegetation, and thus were in general better visible. Compared to the rural Ethiopian scene, the automated delineation still required more zooming, as boundaries were demarcated by more diverse objects.

**Table 7.** Which plugin functionality to use for which boundary type?


*1.3.1 Inorganic filling particles*

Fillers are often fine-grained nanometer- or micrometer-sized particles and fibers, which can be made of organic or inorganic materials. Generally, such particles and fibers are named as conventional sized fillers according to their size range. Composites formed by using these fillers are labeled as conventional sized filled composites, for example, nanocomposites and microcomposites. Recently, filler materials have been used to improve electrical, mechanical strength, and thermal properties [5]. Polymers are chosen in electrical engineering according to the required application, and their properties can be modified by adding inorganic fillers in it. The quantity of fillers in the base polymer matrix is still under question from the literature that which amount by weight is most suitable to improve the desired properties. Therefore, we only use very low filler quantity of nanoparticles into the base polyimide. The common used organic polymers and their derived inorganic fillers are shown in **Table 2** [6].

### **Table 2.**

*Organic and inorganic fillers and their chemical family.*


*Article* **Exosomes Derived from Fisetin-Treated Keratinocytes Mediate Hair Growth Promotion**

**Mizuki Ogawa 1, Miyako Udono 2, Kiichiro Teruya 1,2, Norihisa Uehara 3 and Yoshinori Katakura 1,2,\***

**Abstract:** Enhanced telomerase reverse transcriptase (TERT) levels in dermal keratinocytes can serve as a novel target for hair growth promotion. Previously, we identified fisetin using a system for screening food components that can activate the TERT promoter in HaCaT cells (keratinocytes). In the present study, we aimed to clarify the molecular basis of fisetin-induced hair growth promotion in mice. To this end, the dorsal skin of mice was treated with fisetin, and hair growth was evaluated 12 days after treatment. Histochemical analyses of fisetin-treated skin samples and HaCaT cells were performed to observe the effects of fisetin. The results showed that fisetin activated HaCaT cells by regulating the expression of various genes related to epidermogenesis, cell proliferation, hair follicle regulation, and hair cycle regulation. In addition, fisetin induced the secretion of exosomes from HaCaT cells, which activated β-catenin and mitochondria in hair follicle stem cells (HFSCs) and induced their proliferation. Moreover, these results revealed the existence of exosomes as the molecular basis of keratinocyte-HFSC interaction and showed that fisetin, along with its effects on keratinocytes, caused exosome secretion, thereby activating HFSCs. This is the first study to show that keratinocyte-derived exosomes can activate HFSCs and consequently induce hair growth.

**Keywords:** telomerase reverse transcriptase; keratinocyte–hair follicle stem cell interaction; exosomes; telogen–anagen transition; hair cycle regulation

#### **1. Introduction**

Telomerase reverse transcriptase (TERT) maintains telomere length and is known to be active in stem cells as well as cancer cells. Sarin et al. (2005) reported that when TERT is transgenically introduced into mouse skin, the hair follicle cycle shifts from the telogen phase, the quiescent phase, to the anagen phase, the active phase, resulting in hair growth [1]. The overexpression of TERT induces the proliferation of hair follicle stem cells (HFSCs) in the bulge region, leading to hair growth. In addition, Choi et al. (2008) showed that the presence of TERT in skin keratinocytes activates dormant HFSCs, which in turn activates hair follicles and promotes hair growth [2]. These studies suggest that TERT overexpression in dermal keratinocytes could be a target to promote hair growth. In a previous study, we constructed a system for screening food components that can activate the TERT promoter in keratinocytes and identified fisetin, a type of polyphenol. Fisetin activated keratinocytes, promoted hair growth, increased skin thickness, activated β-catenin, and increased the proliferation of HFSCs [3].

Recent studies have reported that exosomes derived from hair follicle tissues are involved in hair growth promotion and function as the molecular basis of cell–cell interactions [4–9]. In the present study, we aimed to determine whether fisetin activates keratinocytes, resulting in the activation of keratinocyte–HFSC interaction, which leads to

**Citation:** Ogawa, M.; Udono, M.; Teruya, K.; Uehara, N.; Katakura, Y. Exosomes Derived from Fisetin-Treated Keratinocytes Mediate Hair Growth Promotion. *Nutrients* **2021**, *13*, 2087. https://doi.org/ 10.3390/nu13062087

Academic Editor: Jean Christopher Chamcheu

Received: 18 May 2021 Accepted: 16 June 2021 Published: 18 June 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

hair growth. In addition, we sought to confirm the presence of exosomes as the molecular basis of this interaction.

#### **2. Materials and Methods**

#### *2.1. Cell Line and Reagent*

HaCaT cell line (human keratinocyte), obtained from Riken Bioresource Center (Tsukuba, Japan), was cultured in Dulbecco's modified Eagle's medium (Nissui, Tokyo, Japan) supplemented with 10% fetal bovine serum (Life Technologies, Gaithersburg, MD, USA) at 37 ◦C in a 5% CO2 atmosphere. Human HFSCs were obtained from Celprogen (Torrance, CA, USA) and cultured in human hair follicle stem cell complete growth medium with serum (Celprogen) at 37 ◦C in a 5% CO2 atmosphere. Fisetin (>96.0% purity; Tokyo Chemical Industry Co., Ltd., Tokyo, Japan) was purchased from

#### *2.2. Quantitative Reverse Transcriptase-Polymerase Chain Reaction*

RNA was extracted from cells and skin samples using the High Pure RNA Isolation Kit (Roche Diagnostics GmbH, Mannheim, Germany) and RNeasy Fibrous Tissue Mini Kit (Qiagen, Hilden, Germany), respectively, according to the manufacturers' instructions. cDNA synthesis and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) were performed, as described previously [3,10]. Samples were analyzed in triplicate, and gene expression levels were normalized to the corresponding β-actin gene level. The PCR primer sequences were described previously [3].

#### *2.3. Investigation of Hair Growth in Experimental Animals*

Six-week-old female C57BL/6 mice were obtained from Clea Japan (Tokyo, Japan) and acclimated with food and water ad libitum for one week. Nine mice were used for control and fisetin treatment, respectively. At 7 weeks of age, the dorsal hair of the mice was trimmed using electric hair clippers (Thrive Model 2100, Daito Electric Machine Industry, Osaka, Japan), shaved using an electric shaver (Panasonic, Osaka, Japan), and removed using a hair removal cream (CBS, Reckitt Benckiser, Tokyo, Japan), and all the hair follicles were synchronized in the telogen stage, as described previously [11,12]. This was followed by the daily topical application of 0.05 mL of 50% ethanol containing fisetin (1% *w/v*) using a spatula for 12 days, and hair growth was evaluated. Animal experiments were conducted in accordance with the "Guide for the Care and Use of Laboratory Animals" and approved by the Ethics Committee on Animal Experimentation of Kyushu University (approval number: A28-187-0).

#### *2.4. Immunohistochemistry*

Skin tissue sample preparations and treatments were described previously [3]. Paraffinembedded hair follicles were cut out to a thickness of 5 micrometers. Immunohistochemical analysis was performed as previously described [3]. The tissues were first stained with primary antibodies (anti-Ki67, #12202, Cell Signaling Technology, Danvers, MA, USA; anti-β-catenin, #8480, Cell Signaling Technology; and anti-CD34, sc-74499, Santa Cruz Biotechnology, Santa Cruz, CA, USA) and then with secondary antibodies (Alexa Fluor 555 anti-rabbit IgG or Alexa Fluor 488 anti-mouse IgG, Thermo Fisher Scientific KK, Tokyo, Japan). After staining with Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA), the tissue samples were observed with the EVOS M5000 Imaging System (Thermo Fisher Scientific).

#### *2.5. Evaluation of Mitochondrial Characteristics*

Cells were stained with 250 nM of MitoTracker Red CMXRos (Thermo Fisher Scientific) and incubated at 37 ◦C for 30 min. Next, these cells were stained with 200 nM MitoTracker Green FM (Thermo Fisher Scientific) and incubated at 37 ◦C for 30 min. Finally, the cells were stained with Hoechst 33342 (Dojindo, Kumamoto, Japan), followed by incubation at 37 ◦C for 30 min. Then, the stained cells were analyzed using the IN Cell Analyzer 2200

(GE Healthcare, Amersham Place, UK), and the number, area, and activity of mitochondria were quantitatively determined using the IN Cell Investigator high-content image analysis software (GE Healthcare).

#### *2.6. mRNA Microarray Assay*

Total RNA was extracted from HaCaT cells treated with fisetin using Isogen II (Nippon Gene, Tokyo, Japan). Microarray analysis was performed, as described previously [10].

We identified genes with altered expression, as previously described [13]. Then, we established the following criteria for significantly upregulated or downregulated genes: upregulated genes, Z-score ≥ 2.0 and ratio ≥ 1.5-fold; downregulated genes, Z-score ≤ −2.0 and ratio ≤ 0.66-fold. To determine significantly over-represented gene ontology (GO) categories and significantly enriched pathways, we used the tools and data provided by the Database for Annotation, Visualization, and Integrated Discovery (http://david.abcc. ncifcrf.gov, 2 February 2021) [14,15].

#### *2.7. Exosome Isolation*

The MagCapure Exosome Isolation Kit PS (Fujifilm Wako Pure Chemical Corp., Osaka, Japan) was used to isolate exosomes from the medium of HaCaT cells treated with 10 μM fisetin, according to the manufacturer's instructions [10,16].

#### *2.8. Immunocytochemistry*

The cells were fixed in 4% paraformaldehyde at 25 ◦C for 15 min. After washing with phosphate-buffered saline (PBS), the cells were blocked with blocking buffer (5% goat serum and 0.3% Triton X-100 in PBS) at room temperature for 1 h. After removing the buffer, the cells were incubated with primary antibodies (anti-Ki67, #12202; anti-activeβ-catenin, #05-665, Merck Millipore, Billerica, MA, USA; and anti-TOMM20, ab186735, Abcam, Cambridge, UK) at 4 ◦C overnight. After washing with PBS, the cells were incubated with secondary antibodies (Alexa Fluor 555 anti-rabbit IgG, Alexa Fluor 488 antirabbit IgG, or Alexa Fluor 555 anti-mouse IgG) at 25 ◦C for 2 h. Then, the cells were washed and stained with Hoechst 33342 at room temperature for 20 min and observed under a fluorescence microscope (BZ-X800, Keyence, Osaka, Japan) [3].

#### *2.9. Statistical Analysis*

All experiments were performed at least three times, and the representative data are presented. The results are shown as the mean ± standard deviation. Statistical significance was determined using a two-sided Student's *t*-test. Statistical significance was defined as *p* < 0.05 (\* *p* < 0.05; \*\* *p* < 0.01; \*\*\* *p* < 0.001).

#### **3. Results**

#### *3.1. Fisetin Augments the Expression of TERT in Keratinocytes*

In our previous study, we observed that fisetin augmented the expression of TERT in a human keratinocyte cell line and the dorsal skin cells of mice [3]. In the present study, we evaluated the expression of TERT in dorsal skin cells of mice treated with fisetin. The results clearly showed that fisetin augmented TERT expression in the dorsal skin cells of mice (Figure 1A).

**Figure 1.** Hair growth-promoting effect of fisetin. (**A**) The expression of *mTert* in the dorsal skin cells of fisetin-treated mice and investigated using qRT-PCR. (**B**) Evaluation of the effect of fisetin treatment on the dorsal skin of C57BL/6 mice and hair growth after 12 days.  Statistical significance was determined using a two-sided Student's t-test. Statistical significance was defined as *p* < 0.05 (\*\* *p* < 0.01; \*\*\* *p* < 0.001).

#### *3.2. Fisetin Promotes Hair Growth in Mice*

Since the functions and properties of the skin change significantly with the hair cycle, it is generally considered important to control the hair cycle in animal experiments on hair growth. To obtain a uniform hair cycle, it is widely known that hair removal creams and electric shavers can be used to simultaneously remove hair within a certain range of the telogen phase and stimulate them to induce a uniform anagen phase [12]. Hair growth was strongly promoted in mice in the fisetin group compared to those in the control group (Figure 1B). The degree of hair growth was scored using skin color and hair growth as indicators, and the results showed that hair growth was significantly enhanced in the fisetin group compared to the control group (Figure 1C).

#### *3.3. Fisetin Activates HFSCs In Vivo*

After the hair growth test was completed, the condition of the HFSCs was observed using paraffin-embedded sections of the skin using antibodies against β-catenin, CD34 (a stem cell marker), and Ki67 (a cell proliferation marker). The results showed that βcatenin and Ki67 were strongly expressed in CD34+ cells in the vicinity of hair follicles on the dorsal side of the skin of fisetin-treated mice (Figure 2). This suggested that the proliferation of HFSCs in the vicinity of the dorsal skin of fisetin-treated mice was activated and that fisetin activated the interaction between keratinocytes and HFSCs, resulting in the promotion of hair growth.

**Figure 2.** Effects of fisetin treatment on the expression of marker proteins in dorsal skin sections. Immunohistochemistry analysis of skin sections was performed using anti-β-catenin, anti-Ki67, and anti-CD34 antibodies ((**A**), Control; (**B**), Fisetin) (DP, dermal papilla; HB, hair bulge).

#### *3.4. Fisetin Activates HaCaT Cells*

First, we examined the effects of fisetin on keratinocytes. The results showed that fisetin augmented the expression of SIRT1 and further increased and activated the mitochondria in HaCaT cells (Figure 3A,B). In addition, fisetin regulated the expression of various genes, such as those encoding secretory factors and those involved in epidermogenesis, cell proliferation, hair follicle regulation, and hair cycle regulation (Tables 1 and 2). These results suggest that fisetin activates HaCaT cells.

**Figure 3.** Effects of fisetin on keratinocytes. (**A**) The expression of *SIRT1* in HaCaT cells was evaluated using qRT-PCR. (**B**) Effects of fisetin on mitochondria evaluated using mitochondrion-specific probes (MitoTracker Red CMXRos and MitoTracker Green FM) and IN Cell Analyzer 2200. Statistical significance was determined using a two-sided Student's t-test. Statistical significance was defined as *p* < 0.05 (\*\* *p* < 0.01; \*\*\* *p* < 0.001).

**Table 2.** GO analysis.

#### *3.5. Effects of Exosomes Derived from Fisetin-Treated HaCaT Cells on HFSCs*

In this study, we focused on exosomes as the mediators of the interaction between keratinocytes and HFSCs and hypothesized that the exosomes secreted by keratinocytes activated by fisetin would activate the HFSCs. Therefore, we first prepared exosomes from the supernatant of fisetin-treated HaCaT cells and tested their effect on the proliferation of HFSCs. The results showed that fisetin-treated HaCaT cell-derived exosomes triggered the nuclear translocation of β-catenin (Figure 4A), augmented the expression of AXIN2 (Figure 4B), and increased the number of Ki67+ cells in HFSCs (Figure 4C). These results suggest that fisetin-treated HaCaT cell-derived exosomes activate the proliferation of HFSCs.

**Figure 4.** Effects of exosomes derived from fisetin-treated keratinocytes on hair follicle stem cells (HFSCs). (**A**) Localization of β-catenin in HFSCs was evaluated by immunocytochemistry using anti-β-catenin antibody. Nuclear localization of β-catenin (red in pie chart) in HFSCs treated with exosomes was quantitatively determined using IN Cell Analyzer 2200. (**B**) Expression of axin in HFSCs treated with exosomes was quantitatively determined using qRT-PCR. (**C**) Ki67+ cells in HFSCs were detected by immunocytochemistry using anti-Ki67 antibody. The number of Ki67+ cells (red in pie chart) was determined using IN Cell Analyzer 2200. Statistical significance was determined using a two-sided Student's t-test. Statistical significance was defined as *p* < 0.05 (\* *p* < 0.05).

We next tested whether fisetin-treated HaCaT cell-derived exosomes could activate the mitochondria in HFSCs. The HFSCs were treated with fisetin-treated HaCaT cell-derived exosomes, and the expression of TOMM20, a mitochondrial marker, was verified by immunostaining. The results showed that the number of TOMM20+ cells was significantly increased in the HFSCs (Figure 5A). Moreover, the number and activity of mitochondria were evaluated using the fluorescence probes MitoTracker Green FM and MitoTracker Red CMXRos, respectively. The results showed that fisetin-treated HaCaT cell-derived exosomes significantly increased the number of cells harboring activated mitochondria relative to the total number of mitochondria (Figure 5B).

**Figure 5.** Effects of exosomes derived from fisetin-treated keratinocytes on the mitochondria in HFSCs. (**A**) TOMM20+ cells in HFSCs were detected by immunocytochemistry using anti-TOMM antibody. The number of TOMM20+ cells (red in pie chart) was determined using IN Cell Analyzer 2200. (**B**) Mitochondria in HFSCs were detected by immunocytochemistry using specific probes (MitoTracker Red CMXRos and MitoTracker Green FM). The relative number of cells harboring active mitochondria (yellow cells in photo; red in pie chart) was determined using IN Cell Analyzer 2200.

#### **4. Discussion**

In a previous study, we reported that fisetin, which augments the expression of TERT in keratinocytes, induces a shift from telogen to anagen in the hair follicles by inducing the proliferation of HFSCs, thus promoting hair growth [3]. These results suggest that fisetin activates keratinocytes and further strengthens the interaction between keratinocytes and HFSCs. In the present study, we aimed to clarify the molecular basis of fisetin-induced hair growth.

First, after confirming that fisetin is not toxic to keratinocyte at concentrations up to 10 μM, we examined whether keratinocytes are activated by fisetin. We found that fisetin activated the SIRT1-mitochondrial axis as well as keratinocytes by regulating the expression of various genes, such as those encoding secretory factors and those involved in epidermogenesis, cell proliferation, hair follicle regulation, and hair cycle regulation. Since mitochondrial dysfunction in skin cells is believed to cause an increase in reactive

oxygen species levels and may be a cause of skin aging [17], activation of the SIRT1– mitochondrial axis by fisetin may lead to keratinocyte improvement and activation [18]. These results suggest that fisetin activates keratinocytes, which could lead to the promotion of hair growth.

Next, we examined the molecular basis for the activation of the keratinocyte–HFSC interaction induced by fisetin. We assumed that exosomes are involved in the activation of cell–cell interactions. Exosomes are an important component of paracrine signaling and can mediate communication between distant cells by directly transferring various biomolecules, including miRNAs, from donor cells to recipient cells [10,19,20]. However, the potential of exosomes as modulators of hair follicle dynamics has not received widespread attention. Previous studies have shown that exosomes derived from dermal papillae [4,5], dermal fibroblasts [6], and mesenchymal stem cells [7–9] can activate the proliferation of HFSCs and consequently induce hair growth. Key findings regarding the relevance of exosomes in skin and hair follicle regeneration have been reported [21], with an emphasis on the signaling pathways that mediate these effects. It is widely known that Wnt is a master regulator of hair follicle morphogenesis and hair growth [22]. Furthermore, mitochondrial aerobic respiration is activated during HFSC differentiation [23]. Thus, activation of the Wnt pathway and mitochondria is essential for hair follicle activation and differentiation.

In the present study, we found that fisetin-treated HaCaT cell-derived exosomes activated β-catenin and promoted HFSC growth, in addition to activating the mitochondria. These results revealed exosomes as the molecular basis of keratinocyte–HFSC interaction and that fisetin, along with its effects on keratinocytes, could cause exosome secretion and the consequent activation of HFSCs. Furthermore, since hair growth is triggered by exosome secretion, the hair growth-promoting effect is expected to continue for some time after fisetin application is discontinued. To the best of our knowledge, this is the first study to show that keratinocyte-derived exosomes can activate HFSCs, which in turn induces hair growth.

In conclusion, based on the obtained results, exosomes can be considered as natural mediators that could be involved in hair cycle regulation as well as serve as promising delivery vehicles for improving skin and hair regeneration because of their potential to target various molecular processes and cells. Further studies are required to clarify the mode of involvement of exosomes in the hair cycle in vivo and the therapeutic effects that can be expected when using exosomes to regulate hair growth in clinical settings.

**Author Contributions:** Conceptualization, Y.K.; methodology, Y.K.; validation, K.T. and N.U.; investigation, M.O.; data curation, M.U.; writing—original draft preparation, Y.K.; writing—review and editing, Y.K.; project administration, Y.K.; funding acquisition, Y.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee on Animal Experimentation of Kyushu University (approval number: A28-187-0).

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are openly available in QIR at [ https://catalog.lib.kyushu-u.ac.jp/opac\_browse/papers/?lang=0, accessed on 18 June 2021].

**Acknowledgments:** We would like to thank G. Takada and T. Nakazawa (Cytiva, Tokyo, Japan) for providing expert assistance with IN Cell Analyzer 2200 and K. Yasuda (Cell Innovator, Fukuoka, Japan) for her assistance with the microarray analysis.

**Conflicts of Interest:** The authors declare no conflict of interest.

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**Abstract**

The authors have carried out a literature review of targeted relevant research with a focus on two countries of the African Great Lakes Region, i.e. Rwanda and the Democratic Republic of the Congo (DRC). The aim was to find a common thread between nulliparity and timely caesarean section through external clinical pelvimetry. Higher rates of nulliparity and caesarean section were found with poor outcome in terms of foeto-maternal prognosis. External clinical pelvimetry presented in Rwandan and Congolese nulliparae the same characteristics during pregnancy and at delivery: lower average values in comparison with multiparae who never experienced caesarean section; average values significantly lower in women who underwent caesarean than in those who delivered naturally; and a gradual and significant decrease in caesarean section rate as pelvic sizes increased. Cephalopelvic disproportion, the main cause of mechanical dystocia, was associated with significantly lower pelvic average values. On the basis of an appropriate tool to predict cephalopelvic disproportion and taking as an illustration of complication the case of obstetrical fistulas, the authors finally advocate the use of the pelvimeter to screen in time pelvises at higher risk for cephalopelvic disproportion in resource-constrained environment.

**Keywords:** childbirth, nulliparae, external pelvimetry, caesarean, African Great Lakes Region