Low molecular weight serine protease from the viscera of sardinelle (Sardinella aurita) with collagenolytic activity: Purification and characterisation

A new low molecular weight (LMW) serine-protease from sardinelle (Sardinella aurita) viscera was purified using ammonium sulphate precipitation and Sephadex G-100 gel filtration, with a 3.82-fold increase in specific activity. The molecular weight of the enzyme was estimated to be 14.2 kDa by SDS-PAGE. The optimum pH and temperature for the enzyme activity were around pH 8.0 and 60 °C, respectively. The purified protease was strongly inhibited by phenylmethylsulphonyl fluoride, a serine-protease inhibitor, and soybean trypsin inhibitor. The N-terminal amino acid sequence of the first 10 amino acids of the purified protease was APVQPCVVVI. This sequence showed low homology with several peptidases, suggesting that the enzyme is a new protease. Interestingly, the protease was found to cleave collagen type I and hydrolyze succinyl-L-Ala-L-Ala-L-Pro-L-Phe-p-nitroanilide (sAAPFpna), an amide substrate of chymotrypsin. Our findings indicate that the S. aurita protease is a new LMW enzyme with collagenolytic activity.     

Pomegranate (Punica granatum) juices: chemical composition, micronutrient cations, and antioxidant capacity

Abstract: Phenolics, flavonoids, anthocyanins, and tannins of pomegranate juices, obtained from 9 Tunisian ecotypes were quantified. Phenolics and flavonoids in the variety Tounsi (TN) (3299 mg gallic acid equivalents [GAE]/L and 636 mg quercetin equivalents [QE]/L of juice, respectively) were higher than in the variety Gabsi (GB) (1570 mg GAE/L and 135 mg QE/L of juice, respectively). The highest anthocyanins quantity was found in GB 2 with 156 mg cyanidin‐3‐glucoside equivalents (CGE)/L. TN 3 ecotype showed the highest tannins quantity with 2550 mg catechin equivalents (CE)/L of juice. TN 1 presented the highest radical‐scavenging activity (2, 2′‐azinobis‐3‐ethylbenzothiazoline‐6‐sulphonate [ABTS], IC₅₀ [50% inhibition concentration] = 525 mg/L), as well as the highest concentration of micronutrient cations (potassium and sodium). A high correlation (R²= 0.80) between antioxidant capacity and proanthocyanin contents was found, this suggests that proanthocyanins are the principal contributor in the antioxidant capacity of pomegranate. Our data suggest also that the high concentrations of K⁺ and Na⁺ may play a role in the adaptation of pomegranate to arid environments.     

Analysis of cooling curve to determine the end point of freezing

The cooling curve method used for the measurement of freezing point of food is further analyzed to explore whether it can be used to identify the end point of freezing or glass transition. In this method, slope of the cooling curve is determined and plotted as a function of time to identify the end point of freezing (T′_m). Initially, the slope is decreased and then reached a minimum value, which is identified as the nucleation of ice. Then the slope is increased until the end point of freezing. The end point of freezing is identified when the slope starts to decrease from its highest value or plateau. Sucrose solutions and starch gels were used to measure its T′_m in identifying validity of the proposed method. The measured values of T′_m by the proposed method is very close to the literature values.     

Detection of microscopic glaucoma through fundus images using deep transfer learning approach

Glaucoma disease in humans can lead to blindness if it progresses to the point where it affects the oculus' optic nerve head. It is not easily detected since there are no symptoms, but it can be detected using tonometry, ophthalmoscopy, and perimeter. However, advances in artificial intelligence approaches have permitted machine learning techniques to diagnose at an early stage. Numerous methods have been proposed using Machine Learning to diagnose glaucoma with different data sets and techniques but these are complex methods. Although, medical imaging instruments are used as glaucoma screening methods, fundus imaging specifically is the most used screening technique for glaucoma detection. This study presents a novel DenseNet and DarkNet combination to classify normal and glaucoma affected fundus image. These frameworks have been trained and tested on three data sets of high-resolution fundus (HRF), RIM 1, and ACRIMA. A total of 658 images have been used for healthy eyes and 612 images for glaucoma-affected eyes classification. It has also been observed that the fusion of DenseNet and DarkNet outperforms the two CNN networks and achieved 99.7% accuracy, 98.9% sensitivity, 100% specificity for the HRF database. In contrast, for the RIM1 database, 89.3% accuracy, 93.3% sensitivity, 88.46% specificity has been attained. Moreover, for the ACRIMA database, 99% accuracy, 100% sensitivity, 99% specificity has been achieved. Therefore, the proposed method is robust and efficient with less computational time and complexity compared to the literature available.     

The effect of fiber insertion on fracture strength and fracture modes in endocrown and overlay restorations

Aim of this study was to determine the fracture strength and modes of endocrown and overlay restorations with/without fiber reinforcement on endodontically treated teeth. Sixty-five molar teeth were used: Group IN (intact teeth), Group E (endocrown), Group ER (endocrown + ribbond), Group O (overlay), Group OR (overlay + ribbond; n = 13). Ribbond (Seattle, WA) was inserted at the base of pulp chamber in Group ER and OR. All restorations were designed and produced by using computer-aided design and computer-aided manufacturing (Sirona Dental Systems, Bensheim, Germany) and Cerasmart (GC Corp. Kasugai, Aichi, Japan). All teeth were subjected to thermomechanical aging and fractured in a universal test device. Fractured surfaces were analyzed with a stereomicroscope (SMZ1000, Nikon, Japan). Data were analyzed with Welch's analysis of variance and Games–Howell test (p < .001). Group E showed significantly lower fracture strength values than other groups(p < .05). No statistically significant differences were found among the other groups(p > .05). Most of the unfavorable fractures were seen in Groups E and O. Overlay restorations showed higher fracture strength values than endocrown restorations. Although fiber insertion did not improve the fracture strength of the indirect restorations, it reduced the frequency of irreparable fracture mode. Overlay restorations and fiber application are more advantageous in preserving the durability of the endodontically treated teeth.     

Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging

Early detection of post-traumatic stress disorder (PTSD) is essential for proper treatment of the patients to recover from this disorder. The aligned purpose of this study was to investigate the performance deviations in regions of interest (ROI) of PTSD than the healthy brain regions, to assess interregional functional connectivity and applications of machine learning techniques to identify PTSD and healthy control using resting-state functional magnetic resonance imaging (rs-fMRI). The rs-fMRI data of 10 ROI was extracted from 14 approved PTSD subjects and 14 healthy controls. The rs-fMRI data of the selected ROI were used in ANOVA to measure performance level and Pearson's correlation to investigate the interregional functional connectivity in PTSD brains. In machine learning approaches, the logistic regression, K-nearest neighbor (KNN), support vector machine (SVM) with linear, radial basis function, and polynomial kernels were used to classify the PTSD and control subjects. The performance level in brain regions of PTSD deviated as compared to the regions in the healthy brain. In addition, significant positive or negative functional connectivity was observed among ROI in PTSD brains. The rs-fMRI data have been distributed in training, validation, and testing group for maturity, implementation of machine learning techniques. The KNN and SVM with radial basis function kernel were outperformed for classification among other methods with high accuracies (96.6%, 94.8%, 98.5%) and (93.7%, 95.2%, 99.2%) to train, validate, and test datasets, respectively. The study's findings may provide a guideline to observe performance and functional connectivity of the brain regions in PTSD and to discriminate PTSD subject using only the suggested algorithms.     

A new mathematical approach to improve residual stress measurement in ring-core method

Journal of Mechanical Science and Technology - III-conditioning at the inverse equation of integral method in ring-core residual stress measurement leads to high stress sensitivity to strain...     

Concurrent impact of chipping and pitting damages in a locomotive power transmission system

Journal of Mechanical Science and Technology - The reliability of power transmission systems in locomotives directly impacts trains’ availability and running safety. The failure of gears,...     

热暴露对激光沉积Ti60A高温钛合金组织性能影响

对比研究了激光沉积Ti60A高温钛合金经600℃,100 h的恒温热暴露和循环热暴露后显微组织、拉伸性能及断口形貌。结果表明,恒温热暴露后α相体积分数略有增大。循环热暴露后β相体积分数显著减小,α相体积分数增加约12%。这2种热暴露后合金中Ti3Al共格有序相和100~150 nm的六方S2型椭球状硅化物(TiZr0.3)6Si3的析出基本一致,拉伸性能均明显下降,尤其是循环热暴露后的塑性几乎丧失,这与合金组织在循环热应力作用下的显著变化密切相关。     

镍-铝复合涂层的电沉积机理

在改进的Watts溶液中电沉积镍-铝复合涂层。采用Z电位分析、伏安法和电化学阻抗谱（EIS）,研究涂层的电化学行为。结果发现,铝颗粒的Z电位是-4 mV,与氧化铝的非常接近。添加导电铝颗粒到电解液中,导致极化曲线向负电位方向移动,且EIS曲线的环路尺寸增大。结果表明,镍-铝复合层的共沉积行为服从Guglielmi模型。加入的导电铝颗粒起惰性粒子的作用,证实在铝颗粒表面存在薄的氧化铝层。