**Spinasterol, 22,23-Dihydrospinasterol and Fernenol from** *Citrullus Colocynthis* **L. with Aphicidal Activity against Cabbage Aphid** *Brevicoryne Brassicae* **L.**

### **Maqsood Ahmed 1,2, Peiwen Qin 1,\*, Mingshan Ji 1,\*, Ran An 1, Hongxia Guo 1 and Jamil Shafi 3**

Academic Editor: Giovanni Benelli

Received: 7 April 2020; Accepted: 29 April 2020; Published: 7 May 2020

**Abstract:** *Brevicoryne brassicae* is a problematic pest in cabbage and other field crops. Synthetic pesticides are used to control this pest, but they are injurious for human health and the environment. The present study aimed to purify and identify the active compounds from *Citrullus colocynthis* leaves with an appraisal of their efficacy against *B. brassicae*. Separation and purification were performed via different chromatographic techniques. Molecular analysis and chemical structures were recognized by mass spectrum (MS) and nuclear magnetic resonance (NMR), respectively. Moreover, in vitro and in vivo aphicidal activity was assessed using various concentrations, i.e., 6.25, 12.5, 25 and 50 μg/mL at 12, 24, 48 and 72 h exposure. The outcome shows that mass spectrum analyses of the purified compounds suggested the molecular formulae are C30H50O and C29H50O, C29H48O. The compounds were characterized as fernenol and a mixture of spinasterol, 22,23-dihydrospinasterol by 1H-NMR and 13C-NMR spectrum analysis. The toxicity results showed that the mixture of spinasterol and 22,23-dihydrospinasterol showed LC50 values of 32.36, 44.49 and 37.50 μg/mL by contact, residual and greenhouse assay at 72 h exposure, respectively. In contrast, fernenol recorded LC50 values as 47.99, 57.46 and 58.67 μg/mL, respectively. On the other hand, spinasterol, 22,23-dihydrospinasterol showed the highest mortality, i.e., 66.67%, 53.33% and 60% while, 30%, 23.33% and 25% mortality was recorded by fernenol after 72 h at 50 μg/mL by contact, residual and greenhouse assay, respectively. This study suggests that spinasterol, 22,23-dihydrospinasterol are more effective against *B. brassicae* which may be introduced as an effective and suitable substitute of synthetic chemical pesticides.

**Keywords:** *Citrullus colocynthis*; spinasterol, 22,23-dihydrospinasterol; fernenol; insecticidal activity; LC50

### **1. Introduction**

The cabbage aphid, *Brevicoryne brassicae* L. belongs to (Hemiptera: Aphididae) is one of the key pest of vegetables and crops, commonly distributed in warm and moderate areas of the world [1,2]. Due to the heavy infestation of *B. brassicae* on cabbage, yield losses can be increased up to 70% and under-promising circumstances, it can cause complete loss of leafy vegetables of brassica [3,4]. Being an injurious pest, it negatively affects cabbage production by developing sooty mold on plants surface [2,5]. Continued feeding of this pest caused yellowing, wilting and stunting of plant growth, ultimately cause plant death and lead to economic losses [6]. Moreover, most of the species of aphid have gained resistance against many synthetic aphicidal agents [7].

Although synthetic chemicals are widely used to manage this pest but, intensive and continuous use of these chemicals has resulted in the development of pest resistance, resurgence to these chemicals and may also leave hazardous effects on humans and the environment [8]. In contrast, botanical insecticides are relatively safe to some extent and are effective substitutes of these chemicals which play a fundamental role in the field of biopesticides. However, plant derivatives play a vital role in their biologic tasks [9]. Numerous findings have specified that phenols, terpenoids and nitrogen-based constituents are imperative phytoalexins which afford a protective system to plants being attacked by other injurious insect-pests [9,10].

*Citrullus colocynthis* is an important plant from the pharmacological and pesticidal viewpoint. It belongs to the Cucurbitaceae family, mostly grows in desert areas and has attracted the consideration of researchers as a natural botanic pesticide. The insecticidal potential of this desert plant has been assessed against various insect species [11]. *Citrullus colocynthis* exerts carcinogenic, antidiabetic, antibacterial, antioxidant properties, and possesses toxic properties against several harmful insects [12–15]. Numerous active chemical compounds have been reported from *C. colocynthis*, including bitter materials (colocynthetin and colocynthin), various cucurbitacins such as A, B, C, D and E [16], other cucurbitacins like E, I, J, K and L [17], cucurbitacins glycosides [18,19], the cucurbitacins glucosides I and L [19], flavone glycosides and flavonoids [19,20]. However, the cucurbitacins tetracyclic triterpens possess extensive biologic activities. Numerous biologic compounds belong to this group being examined because of their cytotoxic, hepatoprotective, cardiovascular, antioxidant action of B and I cucurbitacins [21].

Song et al. [22] isolated two cucurbitacins from the ethyl acetate extract of *C. colocynthis* fruit, but these were not evaluated against insects. Similarly, Ding et al. [23] identified a mixture of spinasterol, 22,23-dihydrospinasterol from the roots of *Bermeuxia thibetica,* but its bioactivity was also not evaluated. However, Sinha et al. [24] reported that spinasterol, 22,23-dihydrospinasterol exhibited by *Melothria maderaspatana* showed biologic activities. It has been reported that Artemisia extracts contain valuable phytochemicals, possess insecticidal activity which were mainly attributed to the presence of fernenol and other phytoconstituents [25]. Furthermore, constituents of *Artemisia vulgaris* like psilostachy C, Maackiain, psilostachyin A and fernenol possess medicinal as well as antibacterial activities and also used by farmers for the preservation of crops and stored grains products [26].

Although some studies have been conducted on isolation and identification of various compounds including spinasterol, 22,23-dihydrospinasterol and fernenol from natural plant resources, their use as insecticidal purposes especially against *B. brassicae* has not been evaluated so far. Therefore, the present novel study was conducted in a comprehensive way for the isolation, characterization and evaluation of biochemical compounds from *C. colocynthis* leaves against *B. brassicae.*

### **2. Results**

### *2.1. Preliminary Toxicity Evaluations*

Interestingly, all solvents extract caused significant mortality of *B. brassicae*. However, maximum mortality (85%) was recorded at 96 h post exposure by methanol extract, followed by ethanol and chloroform extract (80%) and (76.67%), respectively. In contrast, at 72 h exposure, maximum mortality afforded by methanol extract was 66.67%, followed by chloroform and ethanol extract (58.33%) and (53.33%), respectively. However, minimum mortality was recorded via distilled water extract which was 35% and 18.33% at 96 and 72 h exposure, respectively. The results also revealed that mortality is dependent upon concentration and prolonged time exposure (Figure 1).

**Figure 1.** Mortality of *Brevicoryne brassicae* by *Citrullus colocynthis* leaves extracts. Values are represented as mean ± standard deviation followed by different superscripts (a, b, c, d, e, f, ab, bc, cd) were not significantly different according to Duncan multiple range test (DMRT) at *p* > 0.05. E. Acetate (ethyl acetate); D. Water (distilled water); CK (check in distilled water); Time (h).

### *2.2. Extraction, Separation and Purification of Extract*

Powdered leaves of *C. colocynthis* were extracted with different polarity based solvents. Fractionation of the extract was performed by chromatographic techniques. Collected fractions followed by separation by silica gel column were concentrated and weighed following their Thin Layer Chromatography (TLC) analysis (Table 1). Out of 8 of the obtained fractions, D2 fraction was further purified by repeated column chromatography on silica gel column, Sephadex gel column and preparative TLC and finally two compounds referred to as D2 (N) and D3A bearing weight 35 mg and 21 mg, respectively were purified.

**Table 1.** Obtained fractions by silica gel column.

### *2.3. Mass Spectrum and Elemental Analysis*

The C, H and N elemental analysis is helpful for the calculation of empirical formula. The mass spectrometer examination recorded the molecular ion peak (M) at *m*/*z* 426, 414 and 412. These data suggested the expected molecular formula as C30H50O (Figure 2) and a mixture of C29H50O, C29H48O (Figure 3) for D3A and D2 (N), respectively. However, D2 (N) was a mixture of two compounds referred to as D2 (N1) and D2 (N2) and the ratio of these two compounds was recorded as 5:4 from the mass spectrum and nuclear magnetic resonance analysis.

**Figure 2.** (**a**–**e**) The full mass spectrum for the purified compound, D3A from *Citrullus colocynthis* leaves.

**Figure 3.** (**a**–**c**) The full mass spectrum for the purified compound, D2 (N) from *Citrullus colocynthis* leaves.

### *2.4. NMR Analysis (1H-NMR and 13C-NMR)*

The chemical structures of the purified compounds D2 (N) and D3A were characterized by nuclear magnetic resonance (NMR), Bruker BioSpin, Billerica MA for 1D (1H-NMR, 13C-NMR), mass spectrum and elemental analysis. All NMR experiments were carried out at room temperature.

In the 1H-NMR and 13C-NMR spectrum of the compound D2 (N 1) 1H-NMR (600 MHz, CDCl3) δ 5.16 (m, 1H, H-7), 3.60 (m, 1H, H-3) allylic protons, 0.93 (d, *J* = 7.0 Hz, 3H, -CH3), 0.85 (t, *J* = 6.8 Hz, 3H, -CH3), 0.82 (d, *J* = 6.9 Hz, 3H, -CH3), 0.81 (d, *J* = 6.9 Hz, 3H, -CH3), 0.80 (s, 3H, -CH3), 0.55 (s, 3H, -CH3) (Figure 4a). 13C-NMR (151 MHz, CDCl3) δ 11.8, 12.0, 13.0, 18.8, 19.0, 19.7, 21.5, 22.9, 23.0, 26.1, 27.9, 29.1, 29.6, 31.4, 33.8, 34.1, 36.5, 37.1,37.9, 39.5, 40.2, 43.3, 45.8, 49.4, 55.0, 56.0, 71.0, 117.3, 139.5, (Spinasterol, C29H50O; 414.0 g/mol) (Figure 4b). However, 1H-NMR and 13C-NMR spectra of the compound D2 (N 2) 1H-NMR (600 MHz, CDCl3) δ 5.16 (overlap, 1H H-7), 5.16 (overlap, 1H, H-22), 5.03 (dd, *J* = 15.1, 8.8 Hz, 1H, H-23), 3.60 (m, 1H, H-3), ) the allylic protons, 1.03 (d, *J* = 7.0 Hz, 3H, -CH3), 0.85 (t, *J* = 6.8 Hz, 3H, -CH3), 0.82 (d, *J* = 6.9 Hz, 3H, -CH3), 0.81 (d, *J* = 6.9 Hz, 3H, -CH3), 0.80 (s, 3H, -CH3), 0.54 (s, 3H, -CH3) (Figure 4). 13C-NMR (151 MHz, CDCl3) δ 11.9, 12.2, 13.0, 18.9, 21.0, 21.3, 21.5, 22.9, 25.3, 28.4, 29.6, 31.4, 31.8, 34.1, 37.1, 37.9, 39.4, 40.2, 40.8, 43.2, 49.4, 51.2, 55.0, 55.8, 71.0, 117.4, 129.4, 138.1, 139.5, (22,23-dihydrospinasterol, C29H48O; 412.0 g/mol) (Figure 4b).

In the 1H-NMR and 13C-NMR spectra of the compound D3A, 1H-NMR (600MHz, CDCL3) δ 5.30 (s, 1H, C=CH), 3.26–3.17 (m, 1H, -OH), the allylic protons, 1.07 (s, 3H, -CH3), 0.96 (s, 3H, -CH3), 0.89 (d, *J* = 6.4 Hz, 3H, -CH3), 0.87 (s, 3H, -CH3), 0.84–0.80 (m, 6H, two -CH3), 0.76 (s, 3H, -CH3), 0.73 (s, 3H, -CH3), 0.73–2.03 (m, 48H, including 8 CH3) (Figure 4c). 13C-NMR (151 MHz, CDCL3) δ: 13.90, 15.77, 17.87, 19.07, 20.05, 22.04, 22.98, 25.13, 27.37, 28.13, 28.06, 29.20, 29.63, 30.69, 36.07, 36.65, 37.57, 37.70, 39.19, 39.27, 39.90, 40.96, 42.85, 44.20, 50.29, 51.88, 59.58, 79.07, 116.11, 150.98, (Fernenol; C30H50O; 426.7 g/mol) (Figure 4d).

**Figure 4.** *Cont*.

**Figure 4.** (**a**). 1H-NMR spectrum of the compound D2 (N); (**b**). 13C-NMR spectrum of compound D2 (N); (**c**). 1H-NMR spectrum of the compound D3A; (**d**). 13C-NMR spectrum of the compound D3A.

### *2.5. Structures Elucidation of the Compounds*

Chemical structures of the identified fractions of D3A and D2 (N) were characterized by 1H-NMR and 13C-NMR spectroscopy and their molecular formulae were predicted by the mass spectrum. D3A compound was identified as fernenol (Figure 5). Another purified compound was a little bit impure and due to this impurity, the 1H-NMR spectrum was overlapped and hence, mixture of two compounds was identified as Spinasterol and 22, 23-dihydrospinasterol from the fraction D2 (N) with ratio 5:4 in the mixture (Figure 6a,b).

**Figure 5.** Chemical structure of compound; Fernenol from D3A.

**Figure 6.** Chemical structures of compound; (**a**). Spinasterol; (**b**) 22, 23-dihydrospinasterol from D2 (N).

### *2.6. Bioassay Study*

Toxicity of the identified compounds was evaluated extensively against *B. brassicae* by contact, residual and greenhouse assay and data were collected after a specific period of time exposure.

### 2.6.1. In Vitro Contact Toxicity

The mortality data described in Table 2 exposed the contact efficacy of the spinasterol, 22,23-dihydrospinasterol and fernenol against *B. brassicae*. It was observed that the percent mortality rate of aphids was directly associated with the concentration and period of exposure. Results indicated that extreme mortality recorded was 66.67% and 56.66% at 72 and 48 h exposure, respectively by spinasterol, 22,23-dihydrospinasterol at 50 μg/mL. In contrast, moderate mortality was recorded by fernenol which was 30.00% and 21.67% at 72 and 48 h exposure, respectively, at the same concentration.

### 2.6.2. In Vitro Residual Toxicity

The mortality data described in Table 3 exposed the residual efficacy of spinasterol, 22,23-dihydrospinasterol and fernenol against *B. brassicae*. Results demonstrated that highest mortality (53.33%) was observed at exposure of 72 h followed by (43.33%) at 48 h by spinasterol, 22,23-dihydrospinasterol at the concentration of 50 μg/mL. On the other hand, fernenol afforded lower mortality, i.e., (23.33%) and (16.67%) at the same exposure time and concentration, respectively.

### 2.6.3. In Vivo Assay

The mortality data presented in Table 4 revealed the insecticidal activity of the purified compounds against *B. brassicae* under greenhouse conditions. Results showed that mortality rate of aphids under greenhouse conditions was 60.00% at 72 h exposure via spinasterol, 22,23-dihydrospinasterol at 50 μg/mL. In contrast, mortality recorded by fernenol was 25.00% at 50 μg/mL concentration and 72 h exposure.

 **2.**Mortality of*Brevicoryne brassicae*by spinasterol, 22,23-dihydrospinasterol and fernenol via contact assay. Values are described as mean ± standard error followed by different superscripts were significantly different according to (Duncan multiple range test DMRT *p* > 0.05).square);df(Degreeoffreedom);M.S(Meansquare);F(Significance);CK(Check);\*\*\* (Highlysignificant);\*\*(Highlysignificant);\*(Significant).

Statics summary

S.S

df

M.S

F

 426.6

 4

 106.67

 8.00\*\*

 10.00

 4

 2.50

 0.750\*

 1240

 4

 310.0

 15.00\*\*\*

 290.0

 4

 72.50

 8.70\*\*\*

 4093

 4

 1023

 38.37\*\*\*

 493.3

 4

 123.3

 18.50\*\*\*

 5560.0

 4

 1390

 41.70\*\*\*

 923.3

 4

 230.8

 23.08\*\*\*

 S.S (Sum of

square); df (Degree of freedom); M.S (Mean square); F

(Significance);

 CK (Check); \*\*\* (Highly significant); \*\* (Highly significant); \* (Significant).

#### *Molecules* **2020** , *25*, 2184

Probit analysis exposed the LC50, slope value, Chi-square and fiducial limits at 95% confidence interval. Lowest LC50 values recorded by spinasterol, 22,23-dihydrospinasterol were 32.36 and 44.79 μg/mL after 72 h and 48 h of exposure period, respectively via contact assay. In contrast, at the same exposure period, LC50 values by residual assay were 44.57 and 58.38 μg/mL, respectively. On the other hand, LC50 values recorded by greenhouse assay were 37.50 and 48.90 μg/mL at 72 and 48 h exposure, respectively (Table 5). Similarly, LC50 values recorded via fernenol were 47.99 and 63.08 μg/mL; 57.46 and 104.46 μg/mL; 58.67 and 76.52 μg/mL at 72 and 48 h by contact, residual and greenhouse assay, respectively (Table 6).

**Table 5.** Probit analysis of the effects of spinasterol, 22,23-dihydrospinasterol on *Brevicoryne brassicae.*

F.L; Fiducial limits. χ(2); Chi-square.

F.L; Fiducial limits. χ(2); Chi-square.

### **3. Discussion**

Because of the problems associated with the use of chemical pesticides for pest administration, the introduction of natural products particularly from plants source is pressing. Essential oils or extracts of plant origin are commonly used for plant protection measures because of their effectiveness against different life stages of insect pests. However, screening of suitable candidate plants for isolation, purification and identification of active ingredients is very crucial [27]. This technique was adopted to

obtain active compounds from *C. colocynthis* leaves. Additionally, different techniques are used in the extraction, separation and purification of bioactive compounds from natural plant resources.

In our results for the preliminary toxicity evaluations of the solvents extract showed significant mortality of *B. brassicae.* Among the solvents extracts, methanol extract afforded high mortality which is in accordance with [28–30] who reported maximum mortality of *Aphis craccivora* by methanolic extract of *C. colocynthis* followed by ethyl acetate and petroleum ether extract. However, the activity of the crude extract can be attributed to the existence of specific chemical compounds of the plants like fatty acids (linoleic and oleic acid) glycosides (flavonoids, phenols, saponins), terpenoids and alkaloids, etc. [31]. Recently, Ahmed et al. [32] reported that solvents (methanol, ethanol, ethyl acetate, chloroform, acetone and hexane) extract of *C. colocynthis* leaves exhibited important phytochemicals such as alkaloids, glycosides, steroids, saponins, phenol, tannins and flavonoids along with potential antioxidant activities however, acetone and ethanol extract displayed as potent antioxidants. Further, these solvents extract also exhibited pronounced insecticidal activities [33]. Butanol fraction of the methanol extract from the *C. colocynthis* plant possessed insecticidal properties because of the presence of flavone glucosides and two cucurbitacins glucosides [19] Moreover, Yoshikawa et al. [34] described that alcoholic extract obtained from *C. colocynthis* fruits contains various compounds comprising cucurbitacins E 2-*O*-a-d-glucopyranoside, colocynthosides A and B, aglycon and cucurbitacins E. Among the isolated two triterpens glycosides and four cucurbitacins from *C. colocynthis* leaves, one was found effective against colon cancer cells HT29 and Caco-2 [35]. Plants possess a wide range of biologic compounds involved in their mechanism of chemical defense. These natural products contain significant prospective against variety of insects [36,37]. Activity of some of the natural compounds was evaluated against *Blattellea germanica* which showed LC50 values as 0.07 mg cm−1, 0.06 mg cm−1 and 0.07 mg cm−1 via camphor, pulegone and verbenone, respectively [38]. Similarly, eugenol, isoeugenol, carvecol, thymol and p-cymene had shown anti-adulticidal activity at 1 mg adult−1 against *B. germanica* [39].

As different techniques are employed in the extraction, separation, purification and identification of bioactive compounds thus, following these techniques, two compounds were identified as; a mixture of spinasterol and 22,23-dihydrospinasterol and other pure compound fernenol (d:c-friedo-b':a'-neogammacer-9(11)-en-3alpha-olfern-9(11)-en-3alpha-o). Spinasterol is contained by Cucurbitaceae, Stegnospermaceae, Phytolaccaceae and Polygalaceae. In a study Meneses-Sagrero et al. [40] identified spinasterol form the methanol extract of *Stegnosperma halimifolium* (B.) and evaluated against cancer cell line. It was reported that spinasterol exhibited potential activity as antiproliferative against two cell lines of cervical cancer such as HeLa and RAW 264.7. Studies have also demonstrated that spinasterol exhibited different biologic activities including antidepressant [41], anti-ulcerogenic [42], anti-inflammatory [43], and antiproliferative activities [44]. Spinasterol, 22,23-dihydrospinasterol possess pharmacological and cytotoxic exertions likewise, it was isolated from *Bougainvillea spectabillis* and exhibited strong inhibition of xanthine oxidase being IC50 of 39.21 μM [45].

Fernenol belongs to the class of organic compounds known as triterpenoids containing six isoprene units. Xian-xue W et al. [46] isolated this compound from the whole plant extract of *Arenaria polytrichoides*, however, its activity was not evaluated against pests. Similarly, Li et al. [47] isolated three terpenoids including fernenol from *Ainsliaea yunnanensis* showed cytotoxic effects on human acute monocytic Leukemia cell line with IC50 being 1.73 μM. Some studies revealed that fernenol play an important role in the inhibition of mycelial development of *Colletotrichum gloeosporioides* being 47.5 mg mL−1 EC50, and also significantly effective against anthracnose of mango when used at 100 mg L−1 and 200 mg L−1 concentration [48].

Our results demonstrated that spinasterol, 22,23-dihydrospinasterol exhibited aphicidal activity which caused significant mortality of this pest via different bioassays whereas, fernenol exhibited moderate aphicidal activity. Similar findings on extraction, purification and activity of purified compound 2-*O*-β-d-glucapyranosylcucurbitacin E was evaluated by Torkey et al. [49] against *Aphis*

*craccivora* showed significant mortality with LC50 being 11,003 ppm. Moreover, aphicidal activity of *Eupatorium adenophorum* isolated compound 9-oxo-10, 11-dehydroageraphorone was evaluated against *Pseudoregma bambucicola* displayed 73.33% mortality at 2 mg mL−1 with 6 h exposure. Similarly, Nong et al. [50] recorded complete control of this pest at the same concentration after 30 days in a field experiment.

Thus, this unique and innovative research was performed first time for isolation, purification and characterization of bioactive compounds from *C. colocynthis* leaves and to investigate their insecticidal potential against cabbage aphid *B. brassicae*, which is an injurious pest of cabbage and other crops. It is worth mention that these compounds were isolated and evaluated from *C. colocynthis* for the first time against this pest.

### **4. Material and Methods**

### *4.1. Collection of Plants and Aphids*

*C. colocynthis* (Colocynth), locally recognized as Tumba, was the study plant. Leaves were collected from natural habitat of desert one climate of District Bahawalnagar, Pakistan with latitudinal and longitudinal gradients (29◦59- 34- 'N, 73◦15- 13- 'E) from March to April 2018. This area contains dry climate with an average precipitation of 204 mm annually and temperature ranges from 12.7–45 ◦C. The samples were authenticated at Entomological Research Institute Faisalabad, Pakistan.

Cabbage aphids were collected from wild cabbage plants from the surrounding field area of Shenyang Agricultural University, Shenyang China. During the collection of aphids it was insured that no pesticides was applied on the plants. The population of the aphids was maintained on cabbage plants grown in the greenhouse at 20 ± 5 ◦C and 45% ± 5% relative humidity (RH), along with a photoperiod of 16:8 (light: dark).

### *4.2. Extraction of Plant Material*

Extraction was performed thrice at room temperature for three days by using the cold extraction/solvent extraction method. Different organic solvents were used for extraction purposes bearing varying polarity. Then, filter the contents and volume was reduced by concentrating the filtered material through the rotary evaporator (Model R-210, Buchi Switzerland, Flawil, Switzerland). Next, the filtrate was allowed to dry for 12 h in a fume hood at 28 ◦C and then, the dry extract was preserved in glass bottles at 4 ◦C for further experimentation.

### *4.3. Sample Preparations and Preliminary Toxicity Evaluations*

Each of the extract obtained by using different solvents was evaluated against *B. brassicae* at 50 μg/mL concentration at an exposure of 6, 12, 24, 48, 72 and 96 h. For toxicity tests, dried extracts were dissolved in acetone (1 mL for each solvent extract) and mixed with 1% Tween-20 (prepared in distilled water) for preparing concentration. For control treatment, check (CK) was also prepared in 1% Tween-20 including acetone but excluding extract to prepare a 50 μg/mL concentration. Thus, to obtain homogenous mixture for separation and purification purposes, a 2-g sample from each solvent extract was taken in porcelain dish (14 g in total), dissolved in appropriate amount of dichloromethane and then added equal quantity of silica gel into it. The resulting mixture was left for overnight in a fume hood at 28 ◦C to evaporate the solvent and on drying; the residue was ground to fine powder by mortar and pestle and stored in glass stopper vials at 4 ◦C for further use.

### *4.4. Separation and Purification of Extract*

The prepared sample was separated and purified by column chromatographic techniques. The dried sample was chromatographed on silica gel column (200–300 mesh). Gradient eluent of 300 mL each of the eluted fraction was collected using a gradient ratio of petroleum ether and ethyl acetate. The mobile phases used for silica gel column were PE:EA of 100:0, 100:2, 100:4, 100:8, 100:16, 100:32,

100:64, 100:100 and at the end methanol was used and finally, total 49 fractions were collected. Lastly, eight sub-fractions (A-H) were obtained followed by the mixing of the same polarity fractions. The mobile phases used for gel column Sephadex, LH-20 (40–120 μm) were methanol and dichloromethane with 1:1 ratio. For further purification preparative TLC plates were used and target compounds were scrapped, dissolved in ethyl acetate and concentrated on a rotary evaporator (Buchi Switzerland R-210, Flawil, Switzerland) for obtaining pure compounds with weight calculation.

### *4.5. Mass Spectrum and Elemental Analysis*

Mass spectrum data were calculated on the Triple Quad GC-MS 7000C and Triple Quad LC/MS 6440 mass Spectrometer (Agilent Technologies, Santa Clara, CA, USA). Vario EL III element analyzer was used for elemental analysis (Elementar Analyssensysteme GmbH, Frankfurt, Germany).

### *4.6. Nuclear Magnetic Resonance (NMR) 1H-NMR and 13C-NMR Spectrum*

To determine 1H-NMR spectra, Deuterated chloroform (CDCL3) was used as a solvent while for an internal standard, tetramethylsilane (TMS) was used. 1H-NMR spectra were evaluated on 300 MHz and 600 MHz spectrometer whereas, 13C-NMR spectra were assessed on a 151-MHz spectrometer (Bruker, Karlsruhe, Germany). Chemical shift values were recorded in parts per million (δ, ppm). The coupling constants value (J) was described in Hz. The splitting patterns of proton signals were also designated as follows: singlet (s), doublet (d), a doublet of doublets (dd), a doublet of the doublet of doublets (ddd), triplet (t), the quartet (q) and the multiplet (m)

### *4.7. Bioassay Study*

Activity of the compound against *B. brassicae* was evaluated In vitro and In vivo. For In vitro assay, contact and residual toxicity methods were adopted while; In vivo experiment was conducted under greenhouse condition of Shenyang Agricultural University. Serial concentrations such as 6.25, 12.50, 25 and 50 μg/mL were prepared in Tween-20 (1%) solutions and replicated thrice.

### 4.7.1. In Vitro Contact Toxicity

For contact assay, 10 adult wingless aphids were dipped in respective concentrations for 5 s and released on freshly cut cabbage leaves placed in glass petri dishes. Check (CK) was prepared in 1% Tween-20 solution, but without adding a purified compound. All of the prepared petri dishes including control were placed in an incubator at 20 ± 5 ◦C, 65% RH for three days along with 16:8 (light: dark) photoperiod.

### 4.7.2. In Vitro Residual Toxicity

Fresh cabbage leaves were cut off and dipped for 10 s in respective concentration and dried in air for half an hour. Next, 10 adult wingless aphids were released on these leaves contained in glass petri dishes. Check (CK) was prepared in 1% Tween-20 solution, but without adding purified compound. All of the prepared petri dishes including check were placed in an incubator at 20 ± 5 ◦C, 65% RH for three days along with 16:8 (light: dark) photoperiod.

### 4.7.3. In Vivo Toxicity

Cabbage plants were grown and maintained in the greenhouse for the rearing of aphids and bioassay study. Prior to experiment, plants were sprayed with water to remove impurities and left for half an hour to dry in the open environment. Then, 10 wingless adult aphids were released on cabbage plants at 6–8 true leaf stage. After one hour of releasing aphids, plants were sprayed with respective concentrations (1–2 showers) with hand pump/sprayer. A control treatment was sprayed with distilled water solution in 1% Tween-20. Treated plants along with control were left for three days in greenhouse conditions.

### *4.8. Data Collection and Statistical Analysis*

Data on mortality at a specific time period of 12, 24, 48 and 72 h were recorded regularly by examination under the microscope. Those individuals who presented no response on probing by needle were recorded as dead.

Analysis of the mortality data were performed by using analysis of variance (ANOVA). The mean mortality difference among treatments was intended at *p* = 0.05 by Duncan multiple range test DMRT with IBM-SPSS statistics 25.0 version software. Probit analysis was performed using EPA Probit analysis program version 1.5.

### **5. Conclusions**

The present investigations indicated that *C. colocynthis* possess potential botanical agents. Results also demonstrated that *B. brassicae* showed reasonable sensitivity to isolated spinasterol, 22,23-dihydrospinasterol via all bioassay. In contrast, fernenol displayed moderate toxicity against this pest. Additionally, the contact bioassay produced higher mortality than the residual bioassay. Therefore, these chemical compounds may be introduced as alternatives to synthetic chemical insecticides. However, additional research is necessary for the purification and characterization of more bioactive constituents and their appraisals against *B. brassicae* and other field crops insect pests.

**Author Contributions:** Formal analysis, M.A., R.A. and H.G.; methodology, M.A; project administration, M.J.; software, J.S.; supervision, M.J.; Visualization, P.Q.; Writing—original draft, M.A.; Writing—review & editing, M.J., P.Q. and J.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** The financial support provided by the National Key Research & Development Program of China (2016YFD0200500) is greatly acknowledged.

**Conflicts of Interest:** The authors have declared no conflict of interest.

### **References**

**Sample Availability:** Samples of the compounds are available from the authors.

© 2020 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 (http://creativecommons.org/licenses/by/4.0/).


*2.4. Bruise Analysis*

To allow for the full development of bruising sustained during the mechanical shock testing, the apples were kept at ambient laboratory conditions after drop testing for a period of 24 h, prior to inspection and analysis. The total number of bruises per apple was recorded for each tray to determine the frequency of occurrence and distribution of bruising inside the container. The bruise area (BA) and bruise volume (BV) were measured for each apple after testing. The bruise dimensions were measured using digital calipers (±0.01 mm). The BA was measured using the major and minor bruise width, and the BV was calculated by measuring the depth of the bruise by cutting the fruit perpendicularly along the major bruise width (Figure 3). BA and BV were quantified using an assumed elliptical bruise shape [24–26] using Equations (1) and (2).

$$BA = \frac{\pi}{4} w\_1 w\_2\tag{1}$$

$$BV = \pi \frac{d\_b}{24} (3w\_1 w\_2 + 4d\_b^2) \tag{2}$$

where *w*1 is the bruise width along the major axis (mm), *w*2 is the bruise width along the minor axis (mm), and *db* is the depth of the bruise (mm)

**Figure 3.** Elliptical bruise thickness method used for BA and BV.

The bruise susceptibility (BS) was computed as the ratio of the *BV* to the impact energy (*IE*), as shown in Equation (3) [2,26]. Table 1 and Equation (4) display how *IE* was calculated for each tray type.

$$BS = \frac{BV}{IE} \tag{3}$$

where *BV* is the bruise volume (mm3) and *IE* is the impact energy (J).

$$IE = m\_i \mathfrak{g} h\_d \tag{4}$$

where *mi* is the mass of the falling object (kg), *g* is the acceleration due to gravity (m/s2), and *hd* is the drop height (m).

**Table 1.** Equivalent impact energy (J) of the package types.


**Physical Processes in Lakes**

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**Author details**

Navaneetham Janardhana1 \* and Basavaraj Manjula2

1 Department of Psychiatric Social Work, NIMHANS, Bangalore, India

2 Narayana Hrudayalaya, Bangalore, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**123**

*Adolescents Romantic Relationship: Dynamics of Parent-Child Relationship from India*

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**3. Reference values in an adult and pediatric population**

Generally, normal values of laboratory parameters in a neonatal population are difficult to define, because removal of blood is usually not performed in healthy neonates and reference ranges are composed by assessing patients with minor illness (Christensen et al., 2009). To our knowledge, the first published reference values for neutrophil cells in neonates including the total neutrophil count, the absolute number of immature neutrophils, and the IT-ratio during the first 28 days of life refers to a study by Manroe in 1979 (Manroe et al., 1979). About 15 years later the same study group found that in VLBW these reference values are of limited applicability because a wider range of distribution was found in this subgroup of patients compared to larger or older counterparts (Mouzinho et al., 1994). These new data comprised a wider range of the absolute total neutrophil count and a considerable decreased lower limit in the first 60 hours after birth, whereas reference ranges for the immature neutrophil count and IT values remain unchanged. It has been assumed that low neutrophil counts soon after birth might be caused by a placental factor inhibiting neutrophil production. Clearance of this factor within the first week could lead to the observed increase in immature neutrophil cells. Anyhow, the capability of the bone marrow to rapidly produce immature as well as mature neutrophil forms by the second week is well documented. Neutropenia occurred rarely in infants at an age of more than 7 days, but neutrophilia occurred frequently in association with stress conditions inducing an adrenergic increase in cyclic adenosine monophosphate (cAMP) leading to a release of neutrophil cells (Mouzinho et al., 1994). Hence, neutropenia has been described as a better predictor for neonatal sepsis than an elevated neutrophil count because besides accelerated utilization in case of infection there a fewer factors (i.e. hemolytic disease, asphyxia, maternal hypertension) causing a decrease of neutrophil granulocytes. Lower levels of normal for neutrophil values have been set at 1800/mm3 at birth and < 7800/mm3 12-14 hours after birth in term and late preterm infants (Manroe et al., 1979).

A large trial evaluating more than 30000 samples from infants born at 23 to 42 weeks of gestational age reinvestigated the previously published reference ranges using an automated blood cell counter (Schmutz et al., 2008). In this study lower limits of normal for the neutrophil count were determined as follows (Table 1):

#### The Role of Immature Granulocyte Count and Immature Myeloid Information in the Diagnosis of Neonatal Sepsis 67

**Table 1.** Neutrophil count at birth and 6-8 hours postnatally (pn) comparing groups of different gestational age (Polin, 2012; Schmutz et al., 2008).

66 Neonatal Bacterial Infection

nucleus size (Sysmex Corporation, 2005).

al., 2003; Fernandes & Hamaguchi, 2007).

composition of the cell (nucleus, granules). Differences in RF resistance detected as electrical pulses are plotted in a two dimensional scattergram reflecting the distribution of cell and

The IMI-channel determines the total number of myeloid precursor cells by distinguishing selectively immature myeloid cells from mature leukocytes. The reaction principle of the IMI-channel is based on differences in membrane composition between mature and immature cells. It has been shown that the flow cytometric IGC performed by the Sysmex XE-2100 is superior to the manual morphology count as a reference method for IG counting and that the percentage of IGs is a better predictor of infection than the WBC (Ansari-Lari et

Generally, normal values of laboratory parameters in a neonatal population are difficult to define, because removal of blood is usually not performed in healthy neonates and reference ranges are composed by assessing patients with minor illness (Christensen et al., 2009). To our knowledge, the first published reference values for neutrophil cells in neonates including the total neutrophil count, the absolute number of immature neutrophils, and the IT-ratio during the first 28 days of life refers to a study by Manroe in 1979 (Manroe et al., 1979). About 15 years later the same study group found that in VLBW these reference values are of limited applicability because a wider range of distribution was found in this subgroup of patients compared to larger or older counterparts (Mouzinho et al., 1994). These new data comprised a wider range of the absolute total neutrophil count and a considerable decreased lower limit in the first 60 hours after birth, whereas reference ranges for the immature neutrophil count and IT values remain unchanged. It has been assumed that low neutrophil counts soon after birth might be caused by a placental factor inhibiting neutrophil production. Clearance of this factor within the first week could lead to the observed increase in immature neutrophil cells. Anyhow, the capability of the bone marrow to rapidly produce immature as well as mature neutrophil forms by the second week is well documented. Neutropenia occurred rarely in infants at an age of more than 7 days, but neutrophilia occurred frequently in association with stress conditions inducing an adrenergic increase in cyclic adenosine monophosphate (cAMP) leading to a release of neutrophil cells (Mouzinho et al., 1994). Hence, neutropenia has been described as a better predictor for neonatal sepsis than an elevated neutrophil count because besides accelerated utilization in case of infection there a fewer factors (i.e. hemolytic disease, asphyxia, maternal hypertension) causing a decrease of neutrophil granulocytes. Lower levels of normal for neutrophil values have been set at 1800/mm3 at birth and < 7800/mm3 12-14 hours

**3. Reference values in an adult and pediatric population**

after birth in term and late preterm infants (Manroe et al., 1979).

the neutrophil count were determined as follows (Table 1):

A large trial evaluating more than 30000 samples from infants born at 23 to 42 weeks of gestational age reinvestigated the previously published reference ranges using an automated blood cell counter (Schmutz et al., 2008). In this study lower limits of normal for The notable difference in altitude between the two studies might have influenced the results. The dynamic process of granulopoesis after birth is reflected by a rapid increase of neutrophil cells reaching peak levels at 6 to 8 hours postnatally (Polin, 2012; Schmutz et al., 2008). Allowing sufficient reaction time to inflammatory stimuli alterations in mature and immature granulocytes are more likely to occur between 6 to 12 hours after birth. This should be taken into account when planning blood sampling (Polin, 2012).

A quite similar time course has been shown for the absolute immature neutrophil count: Maximal values increase from 1100/µL soon after birth to a peak of 1500/µL at 12 hours postnatally. In contrast to that, maximum normal values for the IT-ratio have been observed directly after birth followed by a decline with increasing age (Polin, 2012; Schmutz et al., 2008). In the most immature infants between 24 and 26 weeks of gestational age, an elevation of ANC has been shown during the first month of life. In the first three weeks of life a weekly decrease of ANC to values between 2000/µL and 4000/µL has been observed. As the prevalence of both neutropenia as well as neutrophilia decreased with maturity, it can be concluded that granulopoetic function stabilizes with higher gestational age enabling adequate reactions to infectious or stress stimuli. Deviations from the normal range of neutrophil granulocytes without additional signs of clinical symptoms or conditions occurred frequently even in a hospitalized population (Juul et al., 2004). In the face of these data more interest should be attracted on considering the gestational age as well as the time point of blood sampling when interpreting CBC results (Polin, 2012). The influence of birth weight on CBC in healthy term infants was examined in a study performed by Ozyürek and co-workers. Their data revealed a clear difference in several CBC parameters comparing healthy, term infants with intrauterine growth retardation to appropriate for gestational age (AGA) counterparts showing neutropenia in 21% as well as higher IT-ratios in small for gestational age (SGA) newborns. Beyond these findings, a higher rate in immature neutrophil cells, namely in the absolute number of metamyeolcytes, was observed in the SGA babies. The authors suggested that this elevation might be interpreted as a reaction of the bone marrow to compensate for the initially frequent low neutrophil count (Ozyurek et al., 2006).

Some authors have considered the method of automated measurement of IGC as not sensitive enough to be used as a sole screening assay for the prediction of infection. However, it has been demonstrated that a high percentage of IG (> 3%) is a very specific predictor (> 90%) of sepsis (Ansari-Lari et al., 2003) and that IG values less than 0.5% are associated with a high negative predictive value. These findings might be of use in a clinical context (Nigro et al., 2005). Recently published reference values have defined a median of 0.63x103/µL (0.1–2.4; 2.5%–97.5% confidence interval) for IG number (IG#) and a cut-off value of 3.2% for IG% as optimal for a normal adult population. Using a cut-off in a range between 4% and 5% of total WBC would result in a too high rate of missed cases (Bernstein & Rucinski, 2011). In a large outpatient pediatric population comprising more than 2400 samples, age dependent upper limits for reference ranges for the automated enumeration of IG were defined as 0.30% and 40/µL for IG% and IG#, respectively for children aged below 10 years (Roehrl et al., 2011). Above the age of 10 years, an upper limit of 0.90% and 70.0/µL for relative and absolute IG count was recommended (Roehrl et al., 2011). In this study blood samples were analyzed using the Sysmex XT-1800i instrument (Sysmex, Kobe, Japan). The defined upper limits showed no differences dependent on the patient sex. As expected the cause of elevated IGC differed between both groups. While respiratory or gastrointestinal infections were common associations with elevated IGC in the group < 10 years, the older children showed hematologic malignancies, drug therapy (glucocorticoids, chemotherapy), severe infections, and pregnancy (young females). In a subgroup analysis of patients < 1 year this study revealed age-stratified nonparametric estimates of upper limits of normal (95th percentiles) and associated 90% confidence intervals (CI) for IG# and IG% of 40/µL (30.0–50.0) and 0.30% (0.20–0.40). In addition, this study described an important observation: Even the most abnormal IGCs in the younger age group were quite low compared with abnormal IGCs in the older individuals. This fact highlights the importance of particular reference values appropriate for different age groups. Otherwise especially younger children with associated disease and with only small elevations of IGCs could be overlooked (Roehrl et al., 2011). As neonates represent a highly particular and often vulnerable patient population we aimed at investigate a possible correlation between IGC and sepsis.

The Role of Immature Granulocyte Count

and Immature Myeloid Information in the Diagnosis of Neonatal Sepsis 69

infection, blood samples were always taken before the initiation of antibiotic therapy. ROC curves were used for comparison of infectious indices by plotting the test sensitivity (equivalent to the true positive rate) on the y-axis and 1-specifity (equivalent to the false positive rate) on the x-axis for all possible cut off values of the diagnostic test (see Figure 1).

**Figure 1.** a and b: Diff- and IMI scattergram showing graphic output of WBC differential results performed with the Sysmex XE 2100. By courtesy of © Sysmex Europe GmbH, Norderstedt, Germany.


**7. Conclusion**

This chapter summarizes the crystal structures of aromatic amide derivatives that bear one halogen or sulfur atom at the ortho position of the amide unit to observe the possibility of forming the weak intramolecular N–H⋅⋅⋅X (X = F, Cl, Br, I, S) H-bonds. Generally, the five-membered H-bonds are easier to form than the six-membered ones for the identical aromatic backbone. Considering the difference of the chemical, steric and electronic environments of the heteroatom at the two different positions, this observation does not lead to conclusion that the former H-bonds are stronger than the latter ones. One straightforward reason for this difference is that the formation of the six-membered Hbonding requires to confine the rotation of three single bonds, while the five-membered one just needs to confine two. Since many complicated factors may affect the formation and stability of these intramolecular H-bonds, it is still difficult to predict whether or not a compound forms such H-bonding in the crystal. However, in most cases, if the competition of the intermolecular C=O⋅⋅⋅H−N H-bonding is suppressed, there will be a good chance of observing them, and for the halogen derivatives of the same backbone, it is obvious that their capacity of accepting the amide proton is in the order of F>Cl>Br>I, which is in the same order as electronegativity but reverse of atomic size and polarizability.

The fact that a compound does not form the above intramolecular H-bonding in crystal does not mean that it does not form the intramolecular H-bonding in solution. In crystal, the compound usually has one or two conformations, while in solution it generally exists as a dynamic mixture of several conformers of low energy and their distribution ratios will be affected by strong and weak interactions. In crystal, the structure and conformation of a compound is affected remarkably by intermolecular interactions, while in solution, the intermolecular interactions are highly concentration- and solventdependent. In a solvent of high polarity, the intermolecular interactions are broken by the solvent molecules, and the intramolecular H-bonding may also be weakened by the solvent to the extent that it is difficult to be detected. However, in a solvent of low polarity, a compound of low concentration should have a good chance to form the above intramolecular H-bonding.

In the past decades, the conventional, strong N−H⋅⋅⋅O and N−H⋅⋅⋅N H-bonds of amide derivatives have been the "protagonists" in studies in molecular recognition, crystal engineering, materials and biological sciences. In recent years, the above relatively weak Hbonding patterns have been used in discrete research areas. For example, the N−H⋅⋅⋅F and N−H⋅⋅⋅Cl H-bonds have been utilized to construct artificial secondary structures (Li et al., 2005; Gan et al., 2010, 2011a, 2011b), and the N−H⋅⋅⋅S H-bond has been used to create antimicrobial agents by restraining their conformations (Tew et al., 2010; Choi et al., 2009). We may expect that they will find more applications in the future, in particular in crystal engineering and supramolecular chemistry.

### **8. Acknowledgement**

Works in the authors' laboratory are financially supported by the National Natural Science Foundation (20732007, 20921091, 20872167, 20974118), and the Ministry of Science and Technology of China (2007CB808001), the Science and Technology Committee of Shanghai Municipality, and the Chinese Academy of Sciences.

### **9. References**

108 Current Trends in X-Ray Crystallography

This chapter summarizes the crystal structures of aromatic amide derivatives that bear one halogen or sulfur atom at the ortho position of the amide unit to observe the possibility of forming the weak intramolecular N–H⋅⋅⋅X (X = F, Cl, Br, I, S) H-bonds. Generally, the five-membered H-bonds are easier to form than the six-membered ones for the identical aromatic backbone. Considering the difference of the chemical, steric and electronic environments of the heteroatom at the two different positions, this observation does not lead to conclusion that the former H-bonds are stronger than the latter ones. One straightforward reason for this difference is that the formation of the six-membered Hbonding requires to confine the rotation of three single bonds, while the five-membered one just needs to confine two. Since many complicated factors may affect the formation and stability of these intramolecular H-bonds, it is still difficult to predict whether or not a compound forms such H-bonding in the crystal. However, in most cases, if the competition of the intermolecular C=O⋅⋅⋅H−N H-bonding is suppressed, there will be a good chance of observing them, and for the halogen derivatives of the same backbone, it is obvious that their capacity of accepting the amide proton is in the order of F>Cl>Br>I, which is in the same order as electronegativity but reverse of atomic size and

The fact that a compound does not form the above intramolecular H-bonding in crystal does not mean that it does not form the intramolecular H-bonding in solution. In crystal, the compound usually has one or two conformations, while in solution it generally exists as a dynamic mixture of several conformers of low energy and their distribution ratios will be affected by strong and weak interactions. In crystal, the structure and conformation of a compound is affected remarkably by intermolecular interactions, while in solution, the intermolecular interactions are highly concentration- and solventdependent. In a solvent of high polarity, the intermolecular interactions are broken by the solvent molecules, and the intramolecular H-bonding may also be weakened by the solvent to the extent that it is difficult to be detected. However, in a solvent of low polarity, a compound of low concentration should have a good chance to form the above

In the past decades, the conventional, strong N−H⋅⋅⋅O and N−H⋅⋅⋅N H-bonds of amide derivatives have been the "protagonists" in studies in molecular recognition, crystal engineering, materials and biological sciences. In recent years, the above relatively weak Hbonding patterns have been used in discrete research areas. For example, the N−H⋅⋅⋅F and N−H⋅⋅⋅Cl H-bonds have been utilized to construct artificial secondary structures (Li et al., 2005; Gan et al., 2010, 2011a, 2011b), and the N−H⋅⋅⋅S H-bond has been used to create antimicrobial agents by restraining their conformations (Tew et al., 2010; Choi et al., 2009). We may expect that they will find more applications in the future, in particular in crystal

Works in the authors' laboratory are financially supported by the National Natural Science Foundation (20732007, 20921091, 20872167, 20974118), and the Ministry of Science and

**7. Conclusion**

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intramolecular H-bonding.

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**5**

*Spain*

**Supramolecular Arrangements in Organotellurium Compounds** *via*

Angel Alvarez-Larena, Joan Farran and Joan F. Piniella

*In memory of Professor Gabriel Germain, for his guidance and his friendship*

The understanding of the atomic interactions involved in crystal structures is fundamental in the crystal engineering field. In a first instance, this knowledge can be correlated with the crystal properties and, in a second instance, it can be applied to the design of crystalline

In molecular crystals, the crystal cohesion is attributed to weak attractive forces, unlike strong covalent interactions that hold the atoms bonded in a molecule. Some of these weak interactions, for example the hydrogen bonds between electronegative atoms, have been recognized and studied for a long time (Pimentel & McClellan, 1960; Jeffrey & Saenger, 1991; Steiner, 2002). Nonconventional and weaker hydrogen bonds between AH (AH = OH, NH, etc.) and soft bases (π systems) or between CH and B (B = O, N, etc.), π··· π interactions, halogen bonds, cation··· π interactions, have become the focus of interest in the last decades due to their potential role in supramolecular chemistry and in biochemical processes (Desiraju & Steiner, 2001; Metrangolo et al., 2008; Nishio et al., 2009; Schneider, 2009;

Soft interactions between heavy p-block elements and electronegative atoms are frequent and have been shown to play a significant role in supramolecular chemistry. Tellurium is a chemical element showing this kind of soft interactions, also known as secondary bonding (Alcock, 1972). Organotellurium compounds have been investigated mainly in organic synthesis (Singh & Sharma, 2000; Petragnani & Stefani, 2005), but also in medicine (Ba et al., 2010), in materials science (Steigerwald & Sprinkle, 1987; Hails et al., 2001) and recently in polymerization processes (organotellurium-mediated living radical polymerization (TERP)) (Kitayama et al., 2010) and to protect materials (lubricants, polymers) from oxidation

The type of the Te···X interaction (and the secondary bonding interaction) and its relevance in the tellurium coordination polyhedra have been discussed (Alcock, 1972; Zukerman-Schpector & Haiduc, 2001). This chapter deals with the weak Te···halogen (Te···X) interactions found in organotellurium crystal structures and with the supramolecular

**1. Introduction**

Salonen et al., 2011).

(Shanks et al., 2006).

materials for specific applications.

**Te**···**Halogen Contacts**

*Universitat Autònoma de Barcelona*

Zhu, Y.-Y., Wu, J., Li, C., Zhu, J., Hou, J.-L., Li, C.-Z., Jiang, X.-K., & Li, Z.-T. (2007) *Cryst. Growth Des.*, 7, 1490.

Zhu, Y.-Y., Yi, H.-P., Li, C., Jiang, X.-K., & Li, Z.-T. (2008) *Cryst. Growth Des.*, 8, 1294.