**6. References**

66 Contact Dermatitis

or low molecular weight as acyclovir may give doubtful results in sensitized patients, possibly due to poor penetration of this substances through the epidermis. Scratch–patch testing, by compromising epidermal barrier function, enables enhanced penetration of substances into the skin [**35-37**]. The method is performed by causing mechanical injury to the epidermis with a sterile skin prick lancet in order to compromise the stratum corneum, which represents the most important barrier limiting hapten penetration. The test reactions are usually read after D2 and D3, when possible, also after D4 and D7. The method of grading a positive scratch–patch test is identical to that used for conventional patch testing with no differences. It can be used for many drugs: low molecular wheight molecules (e.g. *β*-blockers, antiviral drugs etc.) and also high molecular wheight

Contact allergy to topical *β*-blockers is a well-recognized side-effect of glaucoma treatment [**38-41**]. Sensitization may be singly to agents such as timolol, befunolol, levobunolol, or,

A closed patch test, usually used in clinical practice for the diagnosis of allergic contact dermatitis, is often sufficient to show *β*-blockers contact allergy. However, there may be difficulties in obtaining positive patch tests to *β*-blockers, as showed in earlier reports [**42- 43**]. Poor penetration through intact skin on the back, where patch testing is normally

Topical antiviral drugs are frequently used, but although repeated applications can lead to contact reactions **[44-45]**, adverse cutaneous reactions are not commonly observed. Allergic contact dermatitis caused by acyclovir is rare, with only 20 studies reported **[46-48].** Because of the doubtful reactions with antiviral, especially acyclovir, and in view of the suggestive clinical history, we recommend the scratch–patch test followed by repeated open

Heparin is a sulfated glycosaminoglycan with anticoagulant properties. It is usually injected intravenously or subcutaneously but is also available for topical application. Cutaneous

We report a case of patch-test-negative allergic contact dermatitis, diagnosed by scratch patch testing, from a gel containing heparin. Allergic reaction to subcutaneously injected heparins is not a rare occurrence **[51-52]** but there are only a few reports of contact

In cases of suspected contact allergy, when conventional closed patch test shows negative or doubtful results, scratch–patch testing should be considered. We recommend, after performing scratch-patch test, to execute a ROAT to be sure the drug can be applied

allergic reactions due to subcutaneously injected heparin have been reported **[49-50].**

molecules (e.g. heparin etc.):

applied, may be a factor.

**5.3.2 Antiviral drugs**

application test (ROAT).

dermatitis from topical heparin **[53].**

**5.3.3 Heparin**

safely.

more rarely, to multiple *β*-blockers in a single patient.

**5.3.1** *β***-blockers**

Topical Delivery of Haptens: Methods of Modulation of the

Contact Dermatitis 1997:10:1113–6.

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2001:12:217–9.

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[34] Holdiness MR. Contact dermatitis to topical drugs for glaucoma. Am J Contact Dermat

[35] Nino M, Suppa F, Ayala F, Balato N. Allergic contact dermatitis due to the beta-blocker

[36] Katoh N, Kanzaki T. Contact dermatitis due to befunolol hydrochloride eyedrops.

[37] Van der Meeren H L, Meurs P. Sensitization to levobunolol eyedrops. Contact

[38] Quiralte J, Florido F, Saenz de San Pedro B. Allergic contact dermatitis from carteolol

[39] Corazza M, Virgili A, Mantovani L, Taddei Masieri L. Allergic contact dermatitis from

[40] O'Donnell B F, Foulds I S. Contact allergy to beta-blocking agents in ophthalmic

[41] Sánchez-Pérez J, Jesús Del Río M, Fernández-Villalta M J, García-Díez A. Positive use

[42] Nino M, Balato N, Di Costanzo L, Gaudiello F. Scratch-patch test for the diagnosis of allergic contact dermatitis to aciclovir. Contact Dermatitis 2009:60:56–7. [43] Serpentier-Daude A, Colet E, Didier A F et al. Contact dermatitis to topical antiviral

[44] Holdiness M R. Contact dermatitis from topical antiviral drugs. Contact Dermatitis

[45] Goh C. Compound allergy to Spectraban 15 lotion and Zovirax cream. Contact

[46] Vernassiere C, Barbaud A, Trechot P H et al. Systemic acyclovir reaction subsequent to

[47] Lammintausta K, Makela L, Kalimo K. Rapid systemic valaciclovir reaction subsequent

[48] Maroto-Iitani M, Higaki Y, Kawashima M. Cutaneous allergic reaction to heparins:

[49] Hohenstein E, Tsakiris D, Bircher AJ. Delayed-type hypersensitivity to the ultra-

[50] Jappe U, Juschka U, Kuner N, Hausen BM, Krohn K.. Fondaparinux: a suitable

[51] Schindewolf M, Ludwig RJ, Wolter M, Himsel A, Zgouras D, Kaufmann R, et al.

heparinoids? A study of 7 cases. Contact Dermatitis 2004;51:67–72.

heparin. J Eur Acad Dermatol Venereol 2008;22:378–80.

to aciclovir contact allergy. Contact Dermatitis 2001:45:181.

acyclovir contact allergy: which systemic antiviral drug should then be used?

subcutaneous but not intravenous provocation Contact Dermatitis 2005;52:228–30.

low-molecular-weight heparin fondaparinux. Contact Dermatitis 2004;51:149–

alternative in cases of delayed-type allergy to heparins and semisynthetic

Tolerance of fondaparinux in patients with generalized contact dermatitis to

test in contact dermatitis from betaxolol hydrochloride. Contact Dermatitis

cross-reacting β-blocking agents. Contact Dermatitis 1993:28:188–9.

and timolol in eyedrops. Contact Dermatitis 2000:42:245.

preparations. Contact Dermatitis 1993:28:121–2.

drugs. Ann Dermatol Venereol 2000:127:191–4.

befunolol in eyedrops, with cross-sensitivity to carteolol. Contact Dermatitis

[18] Mauro T, Hollerann WM, Grayson S, Gao WN, Man MQ, Kriehuber E, et al. Barrier

[19] Rougier A, Lotte C, Corcuff TP. Relationship between skin permeability and cornecyte

[20] Berardesca E, Maibach HI. Racial differences in skin pathophysiology. J Am Acad

[21] Menon GK, Elias PM, Feingold KR. Integrity of the permeability barrier is crucial for manteinance of the epidermal calcium gradient. Br J Dermatol 1994;130:139-47. [22] Surber C, Davis AF. Bioavailability and Bioequivalence of Dermatological

[23] Hauck WW. Bioequivalence studies of topical preparations: statistical considerations.

[24] Skelly JP, Shah VP, Maibach HI. FDA and AAPS report of workshop on principles and

[25] Shah VP, Elkins J, Hanus J, Noorizadeh C, Skelly JP. In vitro release fo hydrocortisone from topical preparations and automated procedure. Pharm Res 1991;8:55-9. [26] Davis AF, Gyurik RJ, Hadgraft J. Formulation strategies for modulating skin

[27] Patil S, Singh P, Szolar-Platzer C, Maibach HI. Epidermal enzymes as penetration enhancers in transdermal drug delivery? J Pharm Sci 1996;85:249-52. [28] Mitragotri S. Synergistic effects of enhancers for transdermal drug delivery. Pharm Res

[29] Tsai JC, Guy RH, Thornfeldt CR, Gao WN, Feingold KR, Elias PM. Metabolic

[30] Johnson ME, Mitragotri S, Patel A, Blankschtein D, Langer R. Synergistic effects of

[31] Choi EH, Lee SH, Ahn SK, Hwang SM. The pretreatment effect of chemical skin

[32] Singh J, Maibach HI. Transdermal delivery and cutaneous reactions. In: Kenneth AW,

[33] Jappe U, Uter W, Menezes de Pádua C A, Herbst R A, Schnuch A. Allergic contact

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dermatitis due to beta-blockers in eye drops: a retrospective analysis of multicentre

**5**

**Progress on the Development of Human**

*In Vitro* **Assays for Assessment of the**

**Sensitizing Potential of a Compound:**

*Department of Dermatology, VU University Medical Centre, Amsterdam,*

Contact dermatitis is a common health problem, which affects both men and women and accounts for 85-90% of all skin diseases. Two main types of contact dermatitis can be distinguished, according to the patho-physiological mechanisms involved, i.e. allergic and irritant contact dermatitis. Allergic contact dermatitis requires the activation of antigen specific (i.e. acquired) immunity leading to the development of effector T cells, which mediate skin inflammation (Nosbaum et al., 2009; Saint-Mezard et al., 2004). Irritant contact dermatitis is due to inflammatory and toxic effects caused by exposure to xenobiotics activating an innate local inflammatory reaction (Mathias and Maibach, 1978; Nosbaum et al., 2009). Identification of a potential sensitizer and its distinction from an irritant substance (non-sensitizer) currently completely relies on animal testing. The mouse Local Lymph Node Assay (LLNA) is the most frequently used and accurate test with regards to relevance (predictive capacity) and reliability (reproducibility within and between laboratories) in distinguishing a sensitizer from a non-sensitizer (Basketter et al., 2007; Gerberick et al., 2005; Kimber, 2002). This is closely followed by the Guinea pig maximization test (Basketter and Scholes, 1992). In Europe as from 2013 animal testing of cosmetic products will be prohibited (Directive 76/768/EEC), while the implementation of the REACH (Registration, Evaluation and Authorization of Chemicals) legislation (European Regulation 2006) will result in an increased demand for risk assessment of nearly 30,000 chemicals already marketed in the EU. Moreover, the replacement, reduction, and refinement of the use of test animals in general is now strongly advocated. Therefore, there is an urgent need for reliable *in vitro* assays, which are able to distinguish sensitizers from non-sensitizers. This chapter describes the progress being made to develop a battery of assays, which mimics human sensitization *in vitro* and therefore

which may in the future be able to replace the use of test animals.

In order to develop such a battery of assays it is important to first understand the different *in vivo* events which occur during sensitization. The skin functions as a barrier protecting an individual from dehydration, mechanical trauma, irradiation, microbial insults, and

**1. Introduction**

**Breaking Down the** *In Vivo* **Events**

Susan Gibbs and Krista Ouwehand

*The Netherlands*

[52] Nino M, Patruno C, Zagaria O, Balato N. Allergic contact dermatitis from heparincontaining gel: use of scratch patch test for diagnosis. Dermatitis 2009: 20: 171– 172.


*3.1. Proximate Composition and Degree of Hydrolysis*

Table 1 shows the proximate composition of cricket and mealworm meals, as well as their protein hydrolysates generated at atmospheric pressure (control—0.1 MPa) or using high hydrostatic pressures (HHP) treatment prior to enzymatic hydrolysis by Alcalase®. Pretreatment of insect meals with HHP did not change the proximate composition of either insect hydrolysate (*p* > 0.05). The dry matter values for all insect species and ingredients (meals and hydrolysates) were close to 100% (96.5 to 98.6%) and slightly higher for mealworms compared to crickets. This difference directly correlates with the differences observed for crude protein, lipid, chitin and ash contents. The chitin content was similar in both insect meals (4.2 to 4.8%) but was significantly lower in hydrolysates (0.02 to 0.07%) because this water-insoluble polysaccharide [40] was removed by the centrifugation step performed to recover the soluble protein fraction. Similarly, lipid content was decreased by about 50% in cricket hydrolysates and 21% in mealworm hydrolysates, compared to their respective initial meals, due to the centrifugation step [41]. The higher lipid concentrations recovered in mealworm (20.6 and 23.3%) vs. cricket hydrolysates (7.5 and 8.3%) were related to differences in fatty acid composition since the unsaturated fatty acid fraction of the mealworm matrix is higher than that in the cricket [45]. The filtration method after the centrifugation step did not successfully remove the entire unsaturated lipid fraction, which was in a liquid form at room temperature. As expected, ash content was higher in control and pressure-treated hydrolysates compared to initial meals for both insect species. This is explained by the addition of Na+ from the NaOH required to control pH during enzymatic hydrolysis [38]. Contrary to previous studies [4,55], the crude protein content was higher for cricket meal (55.5%) than for mealworm meals (39.6%). Insect diet and rearing techniques could account for this difference [56]. After enzymatic hydrolysis, the protein content was increased in both hydrolysates. This result is consistent with the findings of Hall et al. after enzymatic hydrolysis of cricket protein by Alcalase®, due to the increase in protein solubility [20,22,23,57]. Table 1 also presents the degree of hydrolysis (DH) after in vitro digestion of cricket and mealworm proteins by Alcalase®. The DH was similar for both insect species with values ranging from 28.1 to 33.8%. These values were consistent with values obtained by Boukil et al. [42]: lower than those obtained by Hall et al. [3] after enzymatic hydrolysis of cricket (G. sigillatus) proteins by Alcalase® (ranged from 42.1 to 52.4%; E/S = 3.0%; hydrolysis time ranged from 30 to 90 min) and higher than the published study of Purschke et al. [20], calculated after

in vitro digestion of migratory locust proteins with Alcalase® (ranging from 11.6 to 15.2%; E/S = 1.0%; hydrolysis time ranging from 30 to 120 min). Different parameters known to influence the degree of hydrolysis (E/S ratio, temperature, pH and reaction duration) can explain these differences [57,58]. The protein quality is also important since production of edible insect meals at laboratory or commercial scale might impact protein denaturation and aggregation, and consequently, their solubility which could affect the efficiency of enzymatic hydrolysis [19]. As shown in Table 1, HHP pretreatment of mealworm meal decreased the degree of hydrolysis (25.6%) compared to control (33.8%). This result is probably due to protein denaturation and aggregation phenomena caused by HHP which may decrease the efficiency of enzymatic hydrolysis [59].


**4.** *F***1 score**

The value of accuracy in testing the data is known by the *F*1 score, which is the average of Precision and Recall, where both metrics are calculated simultaneously [10]. Precision describes the degree of precision between the required data and the model's predicted outputs [10]. The percentage of success of a model in recovering information is represented through Recall. The formula for the *F*1 score is as follows:

$$F\_1 \\ \text{Score} = 2 \* \frac{precision \* recall}{precision + recall} \tag{5}$$

The *F*1 score calculation can be used as an evaluation standard from the predictive classification result if there is a class imbalance in the data.

The following are the steps taken to conduct this research:

#### **4.1 Result and discussion**

This research begins by analyzing the dataset that has been prepared to determine whether the data has missing values, data imbalances, and other problems in the data. Proceed to the preprocessing stage to remove symbols, emoji, number punctuations, and white/multiple spaces in the text.  Then, To identify the frequency of occurrence of a word in the document, the data is transformed into vector form, and the value of Term Frequency (TF) and Inverse Document Frequency (IDF) for each token (word) is calculated. The clean and weighted data is then divided into train and testing groups with varying ratios. The support vector machine method and the radial basis function (RBF) kernel are used to classify Instagram caption data. The whole process ends with evaluating the algorithm performance using the *F*1 score to overcome the imbalanced data. The difference in the distribution of train data and testing data proportion aims to see whether there is an effect of the training data and testing data proportion on the results of the *F*1 score.

The outcome of the analysis is as follows:

From **Table 3**, we can see the *F*1 score is obtained from the experiment. The *F*1 score is generated using a distinct proportion of training and testing data and the results of Recall value and Precision. The results show that a bigger proportion of data training, compared to the data testing, will produce a more significant *F*1 score compared to the other proportions.

**Tables 4**–**7** show particular findings for Precision value, Recall, and *F*1 Score in each category with a varied proportion of data training and testing (70:30, 60:40, 50:50, and 40:60, respectively).The following is the result of the calculation for Precision value, Recall, and *F*1 Score in each data proportion:

In **Table 3** the classification results are presented using the Support Vector Machine algorithm. The average *F*1 score is above 88% and the largest *F*1 score is the proportion of training and testing data with a proportion of 70:30. These results are obtained through the Kernel Radial Basis Function (RBF). This proves that a larger amount of training data in a model can produce better results. The *F*1 scores from each category with different training data share and testing data proportions are shown in **Tables 4**–**7**. The proportion of data share from training data and testing data generated is 70:30. These results are better, especially in the Technology category.

It might be interesting to split training data set and testing data set with the ratio of 80 per cent training set and 20 per cent test set and perform another experiment using that ratio. The result could give higher or lower accuracy compared with previous experiment. However, based on the references, it will be depends on the method and algorithm used.

**Table 3.**

*Comparison of precision, recall, and F*1 *score for each training and testing proportion.*