Novel benzenesulfonamide derivatives as potential selective carbonic anhydrase IX, XII inhibitors with anti-proliferative activity: Design, synthesis and in silico studies.

As inhibitors of carbonic anhydrases (CAs) IX and XII, a novel series of 1,2,3-triazole benzenesulfonamide derivatives 17a-l containing pyrazolyl-thiazole moiety was designed, synthesized, and tested for anti-proliferative activity. Compounds 17e-h demonstrated more effective inhibitory activity than acetazolamide (IC50 63 nM CA IX and IC50 92 nM CA XII), with IC50 range of 25-52 nM against CA IX and IC50 range of 31-80 nM against CA XII. To verify selectivity against CA IX and CA XII, carbonic anhydrase inhibitory activity of compounds 17e-h against the physiological CA I and CA II isoforms was carried out. The results showed that compounds 17e-h induced lower inhibitory activity against CA I and CA II with IC50 range of 0.428-0.638 µM (CA I) and 0.095-0.164 µM (CA II), in addition to higher selectivity indices (CA I/CA IX S.I. 8.9-19.92, CA I/CA XII S.I. 5.78-16.06) and (CA II/CA IX S.I. 2.83-4.35, CA II/CA XII S.I. 2.05-3.15) when compared to that of acetazolamide, IC50 of 0.199 µM (CA I), 0.133 µM (CA II) (CA I/CA IX S.I. 3.15, CA I/CA XII S.I. 2.16) and (CA II/CA IX S.I. 2.11, CA II/CA XII S.I. 1.44). Concerning anti-proliferative activity of compounds 17e-h, investigations were done on HEPG-2 cell line with IC50 ranges of 3.44-15.03 µM in comparison, 5-FU and doxorubicin showed IC50 values of 11.80 and 9.53 µM, respectively. Furthermore IC50 of MCF-7 and MDA-MB-231 were determined under both normoxic and hypoxic conditions with IC50 values ranging from 3.18-8.26 µM MCF-7 (normoxic), 1.39-6.05 µM MCF-7 (hypoxic), 7.13-26.3 µM MDA-MB-231 (normoxic), 0.76-16.3 µM MDA-MB-231 (hypoxic) using acetazolamide and SLC-0111 as selective CA inhibition references. Moreover, compounds 17e-h demonstrated greater safety against the normal cell line, MCF-10A, with IC50 of 23.06-99.50 µM in comparison to 5-FU and doxorubicin IC50 of 59.8 and 71.8 µM respectively. They also demonstrated (MCF-7 S.I. range of 3.77-31.28) in contrast to doxorubicin (S.I. 13.72) and (HepG-2 S.I. range of 3.60-6.95) in comparison to doxorubicin (S.I. 7.53). In relation to CA IX, XII inhibition, molecular docking of and ADME studies of sulfonamide derivatives 17a-l with CA IX (PDB: 5FL6) and CA XII (PDB: 1JD0) was carried out. Additionally, molecular dynamic simulation was carried out for compounds 17e and 17g which maintained good stability inside the active sites of both enzymes, with average RMSDs of 2.3 Å and 2.1 Å, respectively.

Rate of glucose-6-phosphate dehydrogenase deficiency in neonatal indirect hyperbilirubinemia at a private tertiary centre.

OBJECTIVES: To investigate the rate of hospitalized neonates with glucose-6-phosphate dehydrogenase (G6PD) deficiency presented with indirect hyperbilirubinemia at a private tertiary center in Al-Ahsa, Saudi Arabia, over 4 years and to compare the characteristics of G6PD-deficient and normal neonates admitted for indirect hyperbilirubinemia. METHODS: The retrospective case control study was carried out at Almoosa Specialist Hospital, Al-Ahsa, Saudi Arabia. Data were collected from Yassasi Medical System from 2018-2021 and finalized in 2024. The study included 2 groups: G6PD-normal and G6PD-deficient neonates with indirect hyperbilirubinemia not having recognizable triggers of hemolysis. The analysis focused on serum bilirubin levels, direct bilirubin levels, hematocrit levels, hemoglobin levels, reticulocyte percentage, G6PD levels, duration of phototherapy, and the need for exchange transfusion. RESULTS: The study enrolled 3200 neonates with hyperbilirubinemia, of whom 274 met inclusion criteria. A total of 103 (37.6%) neonates were G6PD-deficient, with 77 (74.8%) being male and 26 (25.2%) female. Glucose-6-phosphate dehydrogenase-deficient neonates exhibited significantly higher initial total bilirubin levels and earlier sampling times. There was no significant correlation between G6PD deficiency and hematocrit or hemoglobin levels in hyperbilirubinemic neonates, but 4 neonates required exchange transfusion, demonstrating statistical significance (p=0.009). CONCLUSION: High rate of G6PD deficiency in neonates with indirect hyperbilirubinemia, requiring close monitoring to prevent exchange transfusions, with no significant differences in hematocrit or hemoglobin levels.

Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease - A retrospective cohort study.

BACKGROUND: Risk stratification for patients undergoing coronary artery bypass surgery (CABG) for left main coronary artery (LMCA) disease is essential for informed decision-making. This study explored the potential of machine learning (ML) methods to identify key risk factors associated with mortality in this patient group. METHODS: This retrospective cohort study was conducted on 866 patients from the Gulf Left Main Registry who presented between 2015 and 2019. The study outcome was hospital all-cause mortality. Various machine learning models [logistic regression, random forest (RF), k-nearest neighbor, support vector machine, naïve Bayes, multilayer perception, boosting] were used to predict mortality, and their performance was measured using accuracy, precision, recall, F1 score, and area under the receiver operator characteristic curve (AUC). RESULTS: Nonsurvivors had significantly greater EuroSCORE II values (1.84 (10.08-3.67) vs. 4.75 (2.54-9.53) %, P<0.001 for survivors and nonsurvivors, respectively). The EuroSCORE II score significantly predicted hospital mortality (OR: 1.13 (95% confidence interval: 1.09-1.18), P<0.001), with an AUC of 0.736. RF achieved the best ML performance (accuracy=98, precision=100, recall=97 and F1 score=98). Explainable artificial intelligence using SHAP demonstrated the most important features as follows: preoperative lactate level, emergency surgery, chronic kidney disease (CKD), NSTEMI, nonsmoking status, and sex. QLattice identified lactate and CKD as the most important factors for predicting hospital mortality this patient group. CONCLUSION: This study demonstrates the potential of ML, particularly the Random Forest, to accurately predict hospital mortality in patients undergoing CABG for LMCA disease and its superiority over traditional methods. The key risk factors identified, including preoperative lactate levels, emergency surgery, chronic kidney disease, NSTEMI, nonsmoking status, and sex, provide valuable insights for risk stratification and informed decision-making in this high-risk patient population. Additionally, incorporating newly identified risk factors into future risk scoring systems can further improve mortality prediction accuracy.

New 1,2,3-triazole/1,2,4-triazole hybrids linked to oxime moiety as nitric oxide donor selective COX-2, aromatase, B-RAFV600E and EGFR inhibitors celecoxib analogs: design, synthesis, anti-inflammatory/anti-proliferative activities, apoptosis and molecular modeling study.

A new series of bis-triazole 19a-l was synthesised for the purpose of being hybrid molecules with both anti-inflammatory and anti-cancer activities and assessed for cell cycle arrest, NO release. Compounds 19c, 19f, 19h, 19 l exhibited COX-2 selectivity indexes in the range of 18.48 to 49.38 compared to celecoxib S.I. = 21.10), inhibit MCF-7 with IC50 = 9-16 µM compared to tamoxifen (IC50 = 27.9 µM). and showed good inhibitory activity against HEP-3B with IC50 = 4.5-14 µM compared to sorafenib (IC50 = 3.5 µM) (HEP-3B). Moreover, derivatives 19e, 19j, 19k, 19 l inhibit HCT-116 with IC50 = 5.3-13.7 µM compared to 5-FU with IC50 = 4.8 µM (HCT-116). Compounds 19c, 19f, 19h, 19 l showed excellent inhibitory activity against A549 with IC50 = 3-4.5 µM compared to 5-FU with IC50 = 6 µM (A549). Compounds 19c, 19f, 19h, 19 l inhibit aromatase (IC50 of 22.40, 23.20, 22.70, 30.30 µM), EGFR (IC50 of 0.112, 0.205, 0.169 and 0.066 µM) and B-RAFV600E (IC50 of 0.09, 0.06, 0.07 and 0.05 µM).

Green synthesized silver nanoparticles using the plant-based reducing agent Matricaria chamomilla induce cell death in colorectal cancer cells.

OBJECTIVE: There is a need to treat cancer cells with safe and natural nanoparticles to avoid the side effects of chemotherapeutic agents. Chamomile is considered a safe, natural plant with anticancer activity. We synthesize simple, inexpensive, and eco-friendly silver nanoparticles (SNs) using Chamomile (CHM) to tune their anticancer properties. MATERIALS AND METHODS: SN-CHM was synthesized by reducing 1 mM silver nitrate aqueous solution in 100 mL with the aqueous ethanolic flower extract of CHM (18 mg/mL, w/v). The reaction proceeded overnight at 600 rpm and 28°C. SN-CHM was characterized for their % yield, average diameter, charge, morphology, and silver release. Moreover, SN-CHM was investigated for its antioxidant and anticancer activities at 200 µg/mL and 5 mg/ mL, respectively. RESULTS: A 59.12% yield and a uniform SN-CHM size of 115 ± 3.1 nm with a ζ-potential of -27.67 ± (-3.92) mv were observed. The UV-visible absorption showed shifts from 379.5 to 383.5 nm for CHM and SN-CHM, respectively. Moreover, Ag+ was ultimately released from SN-CHM after 5 h. Fourier Transform Infrared Spectroscopy (FT-IR) showed characteristic absorption peaks of CHM and produced SN-CHM. Furthermore, SN-CHM showed moderate antioxidant activity. SN-CHM inhibited the % viability of SW620 and HT-29 cell lines at 20 µM. SN-CHM may also greatly upregulate the apoptotic gene BAX while considerably downregulating the anti-apoptotic genes BCL2 and BCL-Xl. CONCLUSIONS: CHM can be a safe soft drink, especially when conjugated with Ag ions as anticancer NPs. SN-CHM is considered potent anticancer activity against SW620, and HT-29 cell lines.

New pyrazolyl-thiazolidinone/thiazole derivatives as celecoxib/dasatinib analogues with selective COX-2, HER-2 and EGFR inhibitory effects: design, synthesis, anti-inflammatory/anti-proliferative activities, apoptosis, molecular modelling and ADME studies.

Two new series of pyrazolyl-thiazolidinone/thiazole derivatives 16a-b and 18a-j were synthesised, merging the scaffolds of celecoxib and dasatinib. Compounds 16a, 16b and 18f inhibit COX-2 with S.I. 134.6, 26.08 and 42.13 respectively (celecoxib S.I. = 24.09). Compounds 16a, 16b, 18c, 18d and 18f inhibit MCF-7 with IC50 = 0.73-6.25 µM (dasatinib IC50 = 7.99 µM) and (doxorubicin IC50 = 3.1 µM) and inhibit A549 with IC50 = 1.64-14.3 µM (dasatinib IC50 = 11.8 µM and doxorubicin IC50 = 2.42 µM) with S.I. (F180/MCF7) of 33.15, 7.13, 18.72, 13.25 and 8.28 respectively higher than dasatinib (4.03) and doxorubicin (3.02) and S.I. (F180/A549) of 14.75, 12.96, 4.16, 7.07 and 18.88 respectively higher than that of dasatinib (S.I. = 2.72) and doxorubicin (S.I = 3.88). Derivatives 16a, 18c, 18d, 18f inhibit EGFR and HER-2 IC50 for EGFR of 0.043, 0.226, 0.388, 0.19 µM respectively and for HER-2 of 0.032, 0.144, 0.195, 0.201 µM respectively.

A Honeybee-Inspired Framework for a Smart City Free of Internet Scams.

Internet scams are fraudulent attempts aim to lure computer users to reveal their credentials or redirect their connections to spoofed webpages rather than the actual ones. Users' confidential information, such as usernames, passwords, and financial account numbers, is the main target of these fraudulent attempts. Internet scammers often use phishing attacks, which have no boundaries, since they could exceed hijacking conventional cyber ecosystems to hack intelligent systems, which emerged recently for the use within smart cities. This paper therefore develops a real-time framework inspired by the honeybee defense mechanism in nature for filtering phishing website attacks in smart cities. In particular, the proposed framework filters phishing websites through three main phases of investigation: PhishTank-Match (PM), Undesirable-Absent (UA), and Desirable-Present (DP) investigation phases. The PM phase is used at first in order to check whether the requested URL is listed in the blacklist of the PhishTank database. On the other hand, the UA phase is used for investigation and checking for the absence of undesirable symbols in uniform resource locators (URLs) of the requested website. Finally, the DP phase is used as another level of investigation in order to check for the presence of the requested URL in the desirable whitelist. The obtained results show that the proposed framework is deployable and capable of filtering various types of phishing website by maintaining a low rate of false alarms.

Efficient Authentication Scheme for 5G-Enabled Vehicular Networks Using Fog Computing.

Several researchers have proposed secure authentication techniques for addressing privacy and security concerns in the fifth-generation (5G)-enabled vehicle networks. To verify vehicles, however, these conditional privacy-preserving authentication (CPPA) systems required a roadside unit, an expensive component of vehicular networks. Moreover, these CPPA systems incur exceptionally high communication and processing costs. This study proposes a CPPA method based on fog computing (FC), as a solution for these issues in 5G-enabled vehicle networks. In our proposed FC-CPPA method, a fog server is used to establish a set of public anonymity identities and their corresponding signature keys, which are then preloaded into each authentic vehicle. We guarantee the security of the proposed FC-CPPA method in the context of a random oracle. Our solutions are not only compliant with confidentiality and security standards, but also resistant to a variety of threats. The communication costs of the proposal are only 84 bytes, while the computation costs are 0.0031, 2.0185 to sign and verify messages. Comparing our strategy to similar ones reveals that it saves time and money on communication and computing during the performance evaluation phase.

Global trends and research frontiers on heat stress in poultry from 2000 to 2021: A bibliometric analysis.

Background: Heat stress remains a major environmental factor affecting poultry production. With growing concerns surrounding climate change and its antecedent of global warming, research on heat stress in poultry has gradually gained increased attention. Therefore, this study aimed to examine the current status, identify the research frontiers, and highlight the research trends on heat stress in poultry research using bibliometric analysis. Methods: The literature search was performed on the Web of Science Core Collection database for documents published from 2000 to 2021. The documents retrieved were analyzed for their publication counts, countries, institutions, keywords, sources, funding, and citation records using the bibliometric app on R software. Network analysis for co-authorship, co-occurrence, citation, co-citation, and bibliographic coupling was visualized using the VOSviewer software. Results: A total of 468 publications were retrieved, and over the past two decades, there was a gradual increase in the annual number of publications (average growth rate: 4.56%). China had the highest contribution with respect to the number of publications, top contributing authors, collaborations, funding agencies, and institutions. Nanjing Agricultural University, China was the most prolific institution. Kazim Sahin from Firat University, Turkey contributed the highest number of publications and citations to heat stress in poultry research, and Poultry Science was the most productive and the most cited journal. The top 10 globally cited documents mainly focused on the effects of heat stress, alleviation of heat stress, and the association between heat stress and oxidative stress in poultry. All keywords were grouped into six clusters which included studies on "growth performance", "intestinal morphology", "heat stress", "immune response", "meat quality", and "oxidative stress" as current research hotspots. In addition, topics such as; "antioxidants", "microflora", "intestinal barrier", "rna-seq", "animal welfare", "gene expression", "probiotics", "feed restriction", and "inflammatory pathways" were identified for future research attention. Conclusion: This bibliometric study provides a detailed and comprehensive analysis of the global research trends on heat stress in poultry over the last two decades, and it is expected to serve as a useful reference for potential research that will help address the impacts of heat stress on poultry production globally.

A systematic and thematic analysis of the top 100 cited articles on mRNA vaccine indexed in Scopus database.

The success of mRNA vaccines against SARS-CoV-2 implies that this technology can be applied to target any pathogen. However, the scientific production and research trends using the bibliometric method are still unknown. The top 100 most cited articles on mRNA vaccine research were obtained from the Scopus database from 1995 to 2021. Bibliometrix, an R-Package, and VOSviewer 1.6.11 were used for data analysis. There is a rapid growth in scientific outputs with a gradual increase in 2021. The United States produced 45 (45%) of the articles, followed by Germany with 15 (15%) and Israel with 10 (10%). The New England Journal of Medicine published the most papers in this field 13 (13%), followed by Nature 6(6%). Barney S. Graham was the most productive author among the top 100 most cited mRNA vaccine articles. University of Pennsylvania Perelman School of Medicine, US, was the top ranking institution, having 37 (37%). The visualization map clearly and spontaneously displayed the current state and research hot spots of mRNA research from a specific perspective. The most frequent keywords were COVID-19, vaccine, mRNA vaccine, mRNA, SARS-CoV-2, and immunogenicity, among others. A systematic review of the articles provided evidence that out of 100 articles, approximately 25 (25%) were focused on vaccine production and evaluation, followed by 26 (26%) in mRNA vaccine safety and efficacy, 23 (23%) were into mRNA vaccination, 23 (23%) considered risk factors associated with mRNA vaccination, while 8 (8%) of the articles covered the issue of mRNA vaccine delivery. In addition, 42% of the articles focused on COVID-19, 17% on cancer, 8% on influenza virus, 4% on COVID-19 and kidney disease, 3% COVID-19 and myocarditis, and 3% on rabies virus, among others. The findings of this systematic and thematic analysis provided the knowledge basis for further research on mRNA vaccines globally.

Genome-wide analysis identified candidate variants and genes associated with heat stress adaptation in Egyptian sheep breeds.

Heat stress caused by climatic changes is one of the most significant stresses on livestock in hot and dry areas. It has particularly adverse effects on the ability of the breed to maintain homeothermy. Developing countries are advised to protect and prepare their animal resources in the face of potential threats such as climate change. The current study was conducted in Egypt's three hot and dry agro-ecological zones. Three local sheep breeds (Saidi, Wahati, and Barki) were studied with a total of 206 ewes. The animals were exercised under natural heat stress. The heat tolerance index of the animals was calculated to identify animals with high and low heat tolerance based on their response to meteorological and physiological parameters. Genomic variation in these breeds was assessed using 64,756 single nucleotide polymorphic markers (SNPs). From the perspective of comparative adaptability to harsh conditions, our objective was to investigate the genomic structure that might control the adaptability of local sheep breeds to environmental stress under hot and dry conditions. In addition, indices of population structure and diversity of local breeds were examined. Measures of genetic diversity showed a significant influence of breed and location on populations. The standardized index of association (rbarD) ranged from 0.0012 (Dakhla) to 0.026 (Assuit), while for the breed, they ranged from 0.004 (Wahati) to 0.0103 (Saidi). The index of association analysis (Ia) ranged from 1.42 (Dakhla) to 35.88 (Assuit) by location and from 6.58 (Wahati) to 15.36 (Saidi) by breed. The most significant SNPs associated with heat tolerance were found in the MYO5A, PRKG1, GSTCD, and RTN1 genes (p ≤ 0.0001). MYO5A produces a protein widely distributed in the melanin-producing neural crest of the skin. Genetic association between genetic and phenotypic variations showed that OAR1_18300122.1, located in ST3GAL3, had the greatest positive effect on heat tolerance. Genome-wide association analysis identified SNPs associated with heat tolerance in the PLCB1, STEAP3, KSR2, UNC13C, PEBP4, and GPAT2 genes.

A Comparison Between Working and Nonworking Donkeys Welfare Issues in Nyala City, South Darfur, Sudan.

In impoverished nations, donkeys help people make a living. The welfare of donkeys in Sudan is neglected compared with developed countries. However, there is no information available about donkey welfare in Nyala. This study aimed to assess the welfare of donkeys in Nyala. Donkeys were divided into two groups (n = 50), working and nonworking. The donkeys' physical, emotional, and clinical parameters and an owner's interview were assessed. There were significant differences in body condition scores: 37% and 47% of working and nonworking donkeys, respectively, had ideal body condition scores, while 13% of working donkeys were emaciated. Of the working and nonworking 33% and 19% had hoof problems, respectively. Fifteen percent of working donkeys had ocular discharge, and 25% had wounds. In working donkeys, 7% and 5% depressive and aggressive behavioral responses, respectively, were observed. Furthermore, there were significant differences in tools used for hitting donkeys, with 33% and 17% of owners using a stick and whip, respectively, for hitting working donkeys. Eighty-two percent of owners feed their donkeys one to three times daily (50% working and 32% nonworking donkeys), and free access feeding was only observed in 18% of nonworking donkeys. There were no significant differences (P > .06) in emotional parameters. We conclude that working donkeys suffer from multiple welfare problems more than nonworking donkeys in Nyala. More awareness, veterinary services, and research are needed to improve donkey care in Nyala.

Smart films fabricated from natural pigments for measurement of total volatile basic nitrogen (TVB-N) content of meat for freshness evaluation: A systematic review.

Major databases were searched from January 2012 to August 2021 and 54 eligible studies were included in the meta-analysis to estimate the overall mean of total volatile basic nitrogen (TVB-N) in meat. The mean of TVB-N was 24.96 mg/100 g (95 % CI:23.10-26.82). The pooled estimate of naphthoquinone, curcumin, anthocyanins, alizarin and betalains were 25.98 mg/100 g (95 %CI:19.63-32.33), 30.03 mg/100 g (95 %CI: 24.15-35.91), 24.92 mg/100 g (95 %CI: 22.55-27.30), 23.37 mg/100 g (95 %CI:19.42-27.33) and 19.50 mg/100 g (95 %CI:17.87-21.12), respectively. Meanwhile, subgroups based on meat types showed that smart film was most used in aquatic products at 27.19 mg/100 g (95 %CI:24.97-29.42), followed by red meat at 19.69 mg/100 g (95 %CI:17.44-21.94). Furthermore, 4 °C was the most storage temperature used for testing the performance of smart films at 25.48 mg/100 g (95 %CI:23.05-27.90), followed by storage at 25 °C of 25.65 mg/100 g (95 %CI:22.17-29.13). Substantial heterogeneity was found across the eligible studies (I2 = 99 %, p = 0.00). The results of the trim-and-fill method demonstrated publication bias was well controlled.

Genomic signatures for drylands adaptation at gene-rich regions in African zebu cattle.

BACKGROUND: Indigenous Sudanese cattle are mainly indicine/zebu (humped) type. They thrive in the harshest dryland environments characterised by high temperatures, long seasonal dry periods, nutritional shortages, and vector disease challenges. Here, we sequenced 60 indigenous Sudanese cattle from six indigenous breeds and analysed the data using three genomic scan approaches to unravel cattle adaptation to the African dryland region. RESULTS: We identified a set of gene-rich selective sweep regions, detected mostly on chromosomes 5, 7 and 19, shared across African and Gir zebu. These include genes involved in immune response, body size and conformation, and heat stress response. We also identified selective sweep regions unique to Sudanese zebu. Of these, a 250 kb selective sweep on chromosome 16 spans seven genes, including PLCH2, PEX10, PRKCZ, and SKI, which are involved in alternative adaptive metabolic strategies of insulin signalling, glucose homeostasis, and fat metabolism. CONCLUSIONS: Our results suggest that environmental adaptation may involve recent and ancient selection at gene-rich regions, which might be under a common regulatory genetic control, in zebu cattle.

Artificial Intelligence and Machine Learning in Cancer Research: A Systematic and Thematic Analysis of the Top 100 Cited Articles Indexed in Scopus Database.

INTRODUCTION: Cancer is a major public health problem and a global leading cause of death where the screening, diagnosis, prediction, survival estimation, and treatment of cancer and control measures are still a major challenge. The rise of Artificial Intelligence (AI) and Machine Learning (ML) techniques and their applications in various fields have brought immense value in providing insights into advancement in support of cancer control. METHODS: A systematic and thematic analysis was performed on the Scopus database to identify the top 100 cited articles in cancer research. Data were analyzed using RStudio and VOSviewer.Var1.6.6. RESULTS: The top 100 articles in AI and ML in cancer received a 33 920 citation score with a range of 108 to 5758 times. Doi Kunio from the USA was the most cited author with total number of citations (TNC = 663). Out of 43 contributed countries, 30% of the top 100 cited articles originated from the USA, and 10% originated from China. Among the 57 peer-reviewed journals, the "Expert Systems with Application" published 8% of the total articles. The results were presented in highlight technological advancement through AI and ML via the widespread use of Artificial Neural Network (ANNs), Deep Learning or machine learning techniques, Mammography-based Model, Convolutional Neural Networks (SC-CNN), and text mining techniques in the prediction, diagnosis, and prevention of various types of cancers towards cancer control. CONCLUSIONS: This bibliometric study provides detailed overview of the most cited empirical evidence in AI and ML adoption in cancer research that could efficiently help in designing future research. The innovations guarantee greater speed by using AI and ML in the detection and control of cancer to improve patient experience.

Single anastomosis sleeve jejunal (SAS-J) bypass as a treatment for morbid obesity, technique and review of 1986 cases and 6 Years follow-up. Retrospective cohort.

BACKGROUND: Santoro's operation is a sleeve gastrectomy with transit bipartition. The operation aims to maintain passage to the duodenum to minimize nutritional deficiency. This procedure is rapidly changed to single anastomosis sleeve ileal (SASI) bypass. SAS-J bypass is a modification of SASI with a short biliary limb. MATERIAL AND METHODS: This study is a retrospective study of prospectively collected data. The study includes a comprehensive review of 1986 patients who underwent SAS-J bypass over 6 years. The total number is used to evaluate the perioperative data. One- and two-year follow-up was used to evaluate weight loss and comorbidities; follow-up of more than 5 years was used to obtain long-term results. RESULTS: In this study, 70.4% of patients were female and 29.6% were male. The mean body mass index (BMI) was 44.7. The mean age was 42 years. Regarding comorbidities, 25.8% of the patients had type 2 diabetes, 31% were hypertensive, 14.2% had sleep apnea syndrome, 6.6% had gastroesophageal reflux disease (GERD), and 39.6% had hyperlipidemia. Of the 1294 patients who complete one-year follow up, %EWL reached 87%. Blood glucose levels were normalized in 98.5% of patients, hypertension remitted in 93%, hyperlipidemia improved in 97%, SAS is improved in all cases, and GERD improved in 89% of patients. After 5 years, 94 patients' BMI decreased from 44.3 to 28.3 without significant nutritional deficiency. CONCLUSIONS: Laparoscopic SAS-J bypass is an effective and simple alternative bariatric procedure at short- and long-term follow-up.

Early Diagnosis of Brain Tumour MRI Images Using Hybrid Techniques between Deep and Machine Learning.

Cancer is considered one of the most aggressive and destructive diseases that shortens the average lives of patients. Misdiagnosed brain tumours lead to false medical intervention, which reduces patients' chance of survival. Accurate early medical diagnoses of brain tumour are an essential point for starting treatment plans that improve the survival of patients with brain tumours. Computer-aided diagnostic systems have provided consecutive successes for helping medical doctors make accurate diagnoses and have conducted positive strides in the field of deep and machine learning. Deep convolutional layers extract strong distinguishing features from the regions of interest compared with those extracted using traditional methods. In this study, different experiments are performed for brain tumour diagnosis by combining deep learning and traditional machine learning techniques. AlexNet and ResNet-18 are used with the support vector machine (SVM) algorithm for brain tumour classification and diagnosis. Brain tumour magnetic resonance imaging (MRI) images are enhanced using the average filter technique. Then, deep learning techniques are applied to extract robust and important deep features via deep convolutional layers. The process of combining deep and machine learning techniques starts, where features are extracted using deep learning techniques, namely, AlexNet and ResNet-18. These features are then classified using SoftMax and SVM. The MRI dataset contains 3,060 images divided into four classes, which are three tumours and one normal. All systems have achieved superior results. Specifically, the AlexNet+SVM hybrid technique exhibits the best performance, with 95.10% accuracy, 95.25% sensitivity, and 98.50% specificity.

Easing or tightening control strategies: determination of COVID-19 parameters for an agent-based model.

Some agent-based models have been developed to estimate the spread progression of coronavirus disease 2019 (COVID-19) and to evaluate strategies aimed to control the outbreak of the infectious disease. Nonetheless, COVID-19 parameter estimation methods are limited to observational epidemiologic studies which are essentially aggregated models. We propose a mathematical structure to determine parameters of agent-based models accounting for the mutual effects of parameters. We then use the agent-based model to assess the extent to which different control strategies can intervene the transmission of COVID-19. Easing social distancing restrictions, opening businesses, speed of enforcing control strategies, quarantining family members of isolated cases on the disease progression and encouraging the use of facemask are the strategies assessed in this study. We estimate the social distancing compliance level in Sydney greater metropolitan area and then elaborate the consequences of moderating the compliance level in the disease suppression. We also show that social distancing and facemask usage are complementary and discuss their interactive effects in detail.

The use of analytical techniques coupled with chemometrics for tracing the geographical origin of oils: A systematic review (2013-2020).

The global market for imported, high-quality priced foods has grown dramatically in the last decade, as consumers become more conscious of food originating from around the world. Many countries require the origin label of food to protect consumers need about true characteristics and origin. Regulatory authorities are looking for an extended and updated list of the analytical techniques for verification of authentic oils and to support law implementation. This review aims to introduce the efforts made using various analytical tools in combination with the multivariate analysis for the verification of the geographical origin of oils. The popular analytical tools have been discussed, and scientometric assessment that underlines research trends in geographical authentication and preferred journals used for dissemination has been indicated. Overall, we believe this article will be a good guideline for food industries and food quality control authority to assist in the selection of appropriate methods to authenticate oils.