First-principles study of a SiC nanosheet as an effective material for nitrosourea and carmustine anti-cancer drug delivery.

The development of novel nanosheet-based drug delivery systems requires a systematic understanding of the interactions between the drug and the nanosheet carrier under various physiological environments. In this work, we investigated electronic and quantum molecular descriptors of a SiC monolayer adsorbed with the anticancer drugs nitrosourea (NU) and carmustine (BCNU) using density functional theory (DFT). Our calculations revealed negative adsorption energies for both drugs, indicating a spontaneous and energetically favorable adsorption process. Density of states and orbital population analysis studies revealed that both drugs are capable of significantly (>30%) narrowing the gap between HOMO and LUMO, depending on the configuration of the adsorption complex. Furthermore, the electronic and quantum molecular descriptors were investigated in gas and water mediums to explore the effect of the solvent on the adsorption process. Our calculations predict a higher narrowing of the HOMO-LUMO gap in the water phase compared to the gas phase. Besides, a modest reduction in global hardness and a marked increase in the global electrophilicity index were observed after the adsorption of the drug molecules by the SiC nanosheet, indicating its high reactivity towards both NU and BCNU. Changing the medium to water showed a maximum 2× increase in the global electrophilicity index of the nanosheet for NU and a maximum 7× increase for BCNU. Additionally, the thermodynamic study of the adsorption process indicates that the formation energies at high temperatures are smaller than those at low temperatures, unfolding the potential of SiC nanosheet for application in the phototherapy of these drugs.

Correction to: Osmotic and convective hot air drying of sweet gourd.

[This corrects the article DOI: 10.1007/s10068-022-01193-x.].

Osmotic and convective hot air drying of sweet gourd.

Kinetics of osmotic dehydration (OD) and insights into the effect of salt concentration (5%, 10%, 15%, 20%), drying temperature (50 ∘C, 60 ∘C, 70 ∘C), and sample thickness (4 mm, 6 mm, 8 mm) on the drying kinetics of sweet gourd of two varieties (SGV-1 and SGV-2) were investigated based on the Fick's second law of diffusion model. Quality attributes (chemical and organoleptic) of biscuit formulated with osmotic dehydrated sweet gourd powder were assessed. Results showed that, significant changes occurred during the first 2 h of process where mass transfer kinetics were increased with increasing salt concentration. With increasing time, drying rate was proportional to the temperature, inversely proportional to the sample thickness as well as salt concentration. Moreover, sweet gourd variety has shown impact on formulated products quality and consumer acceptability which could serve as a ground to diversify the use of sweet gourd towards industrial application. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-022-01193-x.

Recent advances in probiotication of fruit and vegetable juices.

Probiotics are live bacteria beneficial to health when consumed adequately. Health professionals now recommend probiotics on regular diets due to their positive effects on human health. The probiotics that are usually consumed from the market through food products are mostly dairy-based. Fruit and vegetables are gaining popularity as preferred matrices for probiotic carriers to the human body, owing to their high cholesterol content and the lactose intolerance of dairy products. On the other hand, fruits and vegetable juices are rich in nutrient content such as vitamins, minerals, and antioxidants and do not contain a starter culture that can compete with the nutrients. The probiotication of fruit and vegetable juices (apple, carrot, citrus fruit, pome-granate, watermelon, tomato, and pineapple) are performing as efficient probiotic bacteria carriers. This review covers the previous works that highlighted the variety of probiotic fruit and vegetable juices as well as the viability of each probiotic in various products after proper fermentation and storage. In addition, physicochemical and sensory changes that occurred during the processing and storage period have been discussed. Furthermore, strategies (microencapsulation, adding prebiotics, antioxidant addition, maintaining optimum pH, temperature, adaptation with resistance, and good packaging) to improve the stability of probiotic bacteria are outlined, as it is difficult to maintain the stability of probiotic bacteria during storage. Finally, the manuscript discusses the effect of probiotic fruit and vegetable juices on human health.

SVR achievement in triple therapy treated hepatitis C induced cirrhosis: A dual center retrospective cohort study.

Background and objective: Multiple prospective and retrospective cohort studies from the West have demonstrated the conflicting results about the efficacy of direct-acting antivirals (DAAs) by sustained virologic response (SVR) achievement rate in hepatitis C virus (HCV) infected patients. But there is limited to no data about the effectiveness of triple therapy ribavirin-sofosbuvir-daclatasvir in cirrhotic hepatitis C infected patients from Pakistan. Methods: We conducted a retrospective cohort study by retrieving records of 359 hepatitis C infected patients treated with triple therapy from two tertiary care hospitals in Pakistan [Cirrhotic = 187 (53%); non-cirrhotic = 172 (47%)] from February 18, 2018, to June 29, 2019. We lost the follow-up of 158 (44.1%) patients due to death (n = 24, 6.68%), non-responding/wrong contact number (n = 43, 9.63%), and whom consented to study but didn't complete follow-up/refused to participate in the study (n = 91, 25.34%). Only 201 (45.9%) completed follow up, and of these 87 (43.2%) were cirrhotic patients based on Liver Stiffness Index. Analysis was run by dividing groups into subgroups; who achieved SVR/who didn't achieve SVR. Results: We analyzed the data of 201 (45.9%) who completed follow-up including cirrhotic patients (n = 87, 43.2%). Mean age was 50.6 + 10.65 years. 81 (94.18%) did achieve SVR while 5 (5.81%) did not achieve SVR. Achievement of SVR was statistically associated with low platelet count, higher total bilirubin, and lower albumin (p < 0.05) while other demographic and disease-related characteristics of patients were not statistically significant (p > 0.05). Conclusion: Triple therapy (ribavirin-sofosbuvir-daclatasvir) achieves over 94% SVR in the Pakistani population, so proved to be highly effective against hepatitis C infection.

Quality Assessment of Beef Using Computer Vision Technology.

Imaging technique or computer vision (CV) technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of CV technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 h post-mortem. Traits evaluated were color value (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, thiobarbituric acid reactive substance (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total viable count (TVC) and total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination were done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XVI. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r=0.65) and moisture (r=0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in lightness (r2 c=0.73, r2 p=0.69) in beef. Results of this work show that CV technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

Quality assessment of different commercial and local milk available in the local markets of selected area of Bangladesh.

OBJECTIVE: This study aimed to assess the organoleptic, physico-chemical, and microbial quality as well as the presence of any adulterants in different commercial and local milk samples. MATERIALS AND METHODS: Three brands of ultra-high temperature (UHT) milk, three brands of pasteurized milk, and three raw milk samples were procured and analyzed for different quality tests. Consumer preference about the milk samples were studied by evaluating the organoleptic properties by a testing panel of 15 panelists. Physico-chemical, adulteration, and microbial analysis of the milk samples were performed by following different standard methods. RESULTS: Most of the organoleptic properties were varied significantly at p ≤ 0.05 for UHT and pasteurized milk samples, while raw milk samples were equally acceptable to the panelists in most cases. From physico-chemical analysis, it was found that raw milk contained the highest amount of moisture (90.68%), whereas UHT had the lowest (87.60%), and other components were ranged as 0.68%-0.78% ash, 3.20%-3.58% protein, 3.15%-3.56% fat, 4.35%-4.62% lactose, 0.14%-0.22% acidity, 6.17%-8.95% solid not fat, 9.32%-12.40% total solid, and 1.026%-1.034% specific gravity. All adulteration tests responded negatively for raw samples, whereas commercial milk samples showed positive response only on added sugar test. Total standard plate count and coliform count tests showed that there was no microorganism in a detectable range in commercial milk samples, though raw samples had a significant amount. CONCLUSION: Though there were some fluctuations in some parameters of the three milk categories, but this study concluded that the quality of UHT and pasteurized milk were excellent with respect to parameters studied.

Outcome Of Use Of 1% Silver Nitrate In Patients With Low Lying Perianal Fistula.

BACKGROUND: Anorectal fistula is a common illness which is seen among the middle-aged male patients. Various surgical procedures have been proposed and are associated with the recurrence of the fistula, repeated surgery and in some cases incontinence which may reach up to 43% in complicated fistulas. The purpose of this study was to assess and formulate a non-surgical procedure for fistula in ano through irrigation of the fistula tract with 1% of silver nitrate solution in healing the low perianal fistula. METHODS: Seventy-nine patients presenting to the outpatient department of Ward 3, Surgical unit 1 in Jinnah Postgraduate Medical Centre during a period of 8 months from April to November 2017 with complain of perianal pain and pussy discharge were included in the study. Three patients of the total 79 patients lost to follow up. Outcome measure were cessation of the symptoms for consecutive 10 weeks. RESULTS: Seventy-six patients were assessed and underwent irrigation using this 1% of silver nitrate solution. Out of 76 patients, 58 (76.3%) patients showed complete clinical healing while 18 (23.68%) of patients showed failure to clinical healing. Patients with continuous discharge had a significantly higher rate of complete clinical healing than those with intermittent discharge. CONCLUSIONS: From this study it can be concluded that cauterizing and corrosive properties of silver nitrate are effective in treating the patients with low lying perianal fistula. We suggest that this method should be used as a first line treatment option for all the patients presenting with low lying anal fistula since it is simple, can be easily performed on an OPD basis is minimally invasive and avoids any complication.

Parsimonious classification of binary lacunarity data computed from food surface images using kernel principal component analysis and artificial neural networks.

Lacunarity is about quantifying the degree of spatial heterogeneity in the visual texture of imagery through the identification of the relationships between patterns and their spatial configurations in a two-dimensional setting. The computed lacunarity data can designate a mathematical index of spatial heterogeneity, therefore the corresponding feature vectors should possess the necessary inter-class statistical properties that would enable them to be used for pattern recognition purposes. The objectives of this study is to construct a supervised parsimonious classification model of binary lacunarity data-computed by Valous et al. (2009)-from pork ham slice surface images, with the aid of kernel principal component analysis (KPCA) and artificial neural networks (ANNs), using a portion of informative salient features. At first, the dimension of the initial space (510 features) was reduced by 90% in order to avoid any noise effects in the subsequent classification. Then, using KPCA, the first nineteen kernel principal components (99.04% of total variance) were extracted from the reduced feature space, and were used as input in the ANN. An adaptive feedforward multilayer perceptron (MLP) classifier was employed to obtain a suitable mapping from the input dataset. The correct classification percentages for the training, test and validation sets were 86.7%, 86.7%, and 85.0%, respectively. The results confirm that the classification performance was satisfactory. The binary lacunarity spatial metric captured relevant information that provided a good level of differentiation among pork ham slice images.

Classification of pre-sliced pork and Turkey ham qualities based on image colour and textural features and their relationships with consumer responses.

Images of three qualities of pre-sliced pork and Turkey hams were evaluated for colour and textural features to characterize and classify them, and to model the ham appearance grading and preference responses of a group of consumers. A total of 26 colour features and 40 textural features were extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, two best colour [mean of S (saturation in HSV colour space), std. deviation of b*, which indicates blue to yellow in L*a*b* colour space] and three textural features [entropy of b*, contrast of H (hue of HSV colour space), entropy of R (red of RGB colour space)] for pork, and three colour (mean of R, mean of H, std. deviation of a*, which indicates green to red in L*a*b* colour space) and two textural features [contrast of B, contrast of L* (luminance or lightness in L*a*b* colour space)] for Turkey hams were selected as features with the highest discriminant power. High classification performances were reached for both types of hams (>99.5% for pork and >90.5% for Turkey) using the best selected features or combinations of them. In spite of the poor/fair agreement among ham consumers as determined by Kappa analysis (Kappa-value<0.4) for sensory grading (surface colour, colour uniformity, bitonality, texture appearance and acceptability), a dichotomous logistic regression model using the best image features was able to explain the variability of consumers' responses for all sensorial attributes with accuracies higher than 74.1% for pork hams and 83.3% for Turkey hams.