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Ishwar Singh Malhi, Mohammed Bilal Khan Manchester Medical School, Faculty of Biology, Medicine and Health University of Manchester, Manchester, UKCorrespondence: Ishwar Singh Malhi; Mohammed Bilal KhanManchester Medical School, Faculty of Biology, Medicine and Health University of Manchester, Manchester, UKEmail ishwar.malhi@student.manchester.ac.uk; mohammed.khan-19@student.manchester.ac.ukWe would like to extend our gratitude to the contributing writers of this article in providing an insight into the attitudes of recently admitted undergraduate medical students on learning communications skills from Chitwan Medical College, Bharatpur, and would like to present some of our comments on the study.1The article demonstrates that there is a need to integrate communication skills into the current college curriculum, finding that a large proportion of students were not aware of the importance of communication skills for a physician (n=24), with almost half unsure about the ability to learn the skill itself (n=40).1 Nevertheless, as highlighted in the paper, the small sample size based on a single university’s applicants (n=99) impedes the ability to compare and contrast the study, in turn limiting its generalizability. Moreover, the characteristics of participants within the questionnaire included their prior educational institutions, yet the relevance of this has not been identified. Further investigations into whether there is a connection to the aforementioned would highlight any significance.View the original paper by Timilsina and colleagues

Diabetic myonecrosis is a rare complication of poorly controlled diabetes mellitus which commonly affects the thigh and is managed conservatively. Spontaneous ischemic necrosis of muscle is noted without a reduction in vascular supply. Pyomyositis caused by Staphylococcus aureus infection is another rare complication. Atypical presentation of myonecrosis and pyomyositis can occur in the form of simultaneous or sequential involvement of multiple muscle groups. We present a rare case of myonecrosis with pyomyositis in a 39-year-old male patient with a background of type 2 diabetes mellitus who presented with a 5-day history of worsening pain of the right thigh radiating to the right ankle, associated with groin swelling and fever. It is important for clinicians to have a low threshold of suspicion of this rare condition due to the other diverse and similar diagnoses, as well as to prevent further complications and morbidity.

Background: The management of thromboembolic risk and the necessity for timely hemorrhage control make anticoagulant-related gastrointestinal (GI) bleeding clinically challenging., Objective: This study aimed to evaluate clinical outcomes (such as bleeding control and mortality) and the effectiveness of anticoagulation reversal techniques in patients with anticoagulant-related GI bleeding in emergency settings., Methodology: This prospective, observational study conducted at Lady Reading Hospital, Peshawar, from January to December 2023, included patients aged 18 or older with GI bleeding on warfarin or direct oral anticoagulants (DOACs). Key clinical data, including demographics and comorbidities, were collected. The study followed a multidisciplinary approach with emergency physicians, gastroenterologists, and surgeons. Pharmacologic management (Vitamin K for warfarin and idarucizumab for DOACs) was initiated based on clinical judgment, with endoscopic interventions performed within 24 hours if needed, and surgical intervention considered if other methods failed or complications arose. Outcomes such as bleeding control, transfusion needs, and mortality were tracked. Data were collected prospectively via case report forms, and patients were followed for up to six months post-discharge. Statistical analysis was performed using SPSS version 27 (IBM Corp., Armonk, NY), with descriptive statistics for all variables. Continuous variables were compared using independent t-tests, and categorical data were assessed using chi-square tests. Adjusted odds ratios were calculated for mortality and bleeding control outcomes, accounting for confounders.  Results: A total of 384 patients were included, with 180 (46.88%) on warfarin and 204 (53.12%) on DOACs. Bleeding control was significantly better in the DOAC group (170/204, 83.33% vs. 130/180, 72.22%, P = 0.03), while mortality was higher in patients on warfarin (20, 11.11% vs. 10, 4.90%, P = 0.02). Patients on warfarin also had longer hospital stays (6.89 vs. 5.52 days, P = 0.01) and times to intervention (5.28 vs. 4.64 hours, P = 0.03). Although demographic characteristics (e.g., age and gender) and comorbidities (e.g., hypertension and diabetes) were comparable between groups, DOACs showed safer profiles during hospitalization. Long-term follow-up outcomes, including readmission rates, recurrent bleeding, and post-discharge mortality, were similar across both groups., Conclusions: The study demonstrates that DOACs offer better outcomes in bleeding control and mortality compared to warfarin in anticoagulant-related GI bleeding, emphasizing the importance of tailored treatment strategies. These findings highlight the potential benefits of DOACs in emergency settings, supporting the need for customized management plans to optimize patient outcomes., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. The Institutional Review Board and Ethical Committee of Lady Reading Hospital, Medical Teaching Institution (MTI) issued approval 1816/LRH/MTI; dated 06/07/2022. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Ullah et al.)

Background Gallbladder carcinoma (GBC) is a rare but highly aggressive malignancy, often discovered incidentally during cholecystectomy for symptomatic cholelithiasis. Despite significant geographic variation, the association between gallstones and GBC is well-documented, with chronic inflammation from gallstones potentially contributing to carcinogenesis. Objective This study aims to determine the prevalence of incidental GBC in patients undergoing cholecystectomy for symptomatic cholelithiasis at a tertiary care hospital in Peshawar, Pakistan. Materials and methods This retrospective cohort study was conducted at the General Surgery Department, Hayatabad Medical Complex, Peshawar, from February 2, 2021, to July 1, 2024. A total of 230 patients, aged 18-55 years and diagnosed with symptomatic cholelithiasis, were included. Cholecystectomy was performed, and all excised gallbladders were histopathologically examined for carcinoma. Statistical analysis was conducted using IBM SPSS (version 26), with a significance threshold of p ≤ 0.05. Results Out of 230 patients, 7 (3.04%) were found to have incidental GBC upon histopathological examination. Among these, five had adenocarcinoma, and two had papillary carcinoma. The carcinoma was confined to the mucosa (T1a) in four cases, while three cases had deeper invasion (T1b). Patients with incidental carcinoma had a significantly longer symptom duration (mean: 14.2 ± 3.1 months) and were older on average (mean age: 49.2 ± 4.3 years) compared to non-carcinoma patients (p = 0.001 and p = 0.002, respectively). No malignancy was suspected intraoperatively in any case. Conclusion Incidental GBC was present in 3.04% of patients undergoing cholecystectomy for symptomatic cholelithiasis, with longer symptom duration and older age as significant risk factors. The findings underscore the importance of histopathological examination of cholecystectomy specimens in regions with high gallstone prevalence, as early detection of incidental carcinoma can facilitate timely oncological intervention., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Institutional Review Board (IRB) Hayatabad Medical Complex Peshawar issued approval 1679. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Alam et al.)

It is widely recognized that fuzzy number theory relies on the characteristic function. However, within the fuzzy realm, the characteristic function transforms into a membership function contingent upon the interval [0,1]. This implies that real numbers and intervals represent exceptional cases of fuzzy numbers. By considering this approach, this paper introduces a new L P space and novel refinements for integral variations of Hölder's inequality which is known as Hölder's-like inequality over fuzzy domain. Numerous prevailing inequalities associated with Hölder's-like inequality can be enhanced through the newly acquired inequalities, as demonstrated through an application. By using newly defined special means, some new versions of integral inequalities have obtained where differentiable mappings are real-valued convex-like (or convex fuzzy) mappings Lastly, nontrivial numerical examples are also included to validate the accuracy of the presented inequalities as they vary with the parameter ꙍ ., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Loredana Ciurdariu reports article publishing charges was provided by Politehnica University Timisoara Department of Mathematics. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

As a springboard to explore novel potent inhibitors of cholinesterase enzymes (AChE and BChE) responsible for causing Alzheimer disorder, the current study was conducted to synthesize pyrrole derived triazole based Schiff base scaffolds by facile synthetic route. These compounds were validated by 1 HNMR, 13 CNMR and HREI-MS. All these scaffolds (1-16) were examined for their inhibitory activity against AChE and BChE in contrast to Donepezil (10.20 ± 0.10 and 10.80 ± 0.20 µM) and Allanzanthone (12.40 ± 0.10 and 13.10 ± 0.10 µM). All pyrrole derived triazole based Schiff base scaffolds (1-16) showed varied range of inhibitory potentials against acetylcholinesterase and butyrylcholinesterase enzymes with lowest inhibition concentration values ranging from 5.10 ± 0.40-27.10 ± 0.10 µM (for AChE) and 5.60 ± 0.30-28.40 ± 0.30 µM (for BChE). SAR analysis of these derivatives revealed analog 7 as lead molecule against targeted enzyme, while analog 6 and 11 were ranked as second and third most potent scaffolds. Binding affinity and selectivity of potent molecules against targeted enzymes were examined by molecular docking and obtained results showed that potent molecule have versatile significant binding interactions with stated enzymes. Furthermore, safety profiles of potent analogues were predicted via ADMET protocols., (© 2024. The Author(s).)

This study examines the impacts of various pollutants on foliar biochemical parameters, including relative water content (RWC), total chlorophyll, leaf extract pH, and ascorbic acid content, and their relationship with the Air Pollution Tolerance Index (APTI). RWC, a crucial indicator of plant resilience, showed a significant positive correlation with APTI values (r = 0.4503, p < 0.05). Species with higher RWC, such as Carica papaya and Cassia fistula, demonstrated enhanced tolerance to pollutants, with RWC values reaching up to 85%. Chlorophyll content, which is vital for photosynthesis, exhibited a significant reduction in polluted areas, with levels ranging from 0.28 to 3.23 mg/g (p < 0.05). Notably, Cassia fistula had high APTI values but lower chlorophyll content, reflecting the complex relationship between tolerance and chlorophyll levels. Leaf extract pH was significantly lower in polluted areas, with pH values consistently below 7, correlating with higher APTI values (p < 0.05). Ascorbic acid content, an important antioxidant, was significantly higher in plants exposed to pollution, with positive correlations to APTI (r = 0.9214) and pH levels (r = 0.62). Principal Component Analysis (PCA) identified that pH, ascorbic acid, and APTI were positively correlated, while total chlorophyll and RWC showed opposing trends. Sensitivity analysis indicated that RWC (95.84% impact on Carica papaya and 85.92% on Cassia fistula) and pH were the primary factors influencing APTI and Metal Accumulation Index (MAI) values. The findings underscore the role of RWC, chlorophyll, pH, and ascorbic acid as biomarkers for plant responses to pollution and highlight the effectiveness of species with high MAI values in heavy metal accumulation and environmental monitoring., Competing Interests: Declaration of competing interest There is no competing interest related to the publication of this work., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: Sepsis is a serious condition that often results in high fatality rates, particularly in intensive care units (ICUs). Its nonspecific clinical characteristics makes early diagnosis and therapy difficult, despite how critical they are. The use of biomarkers like procalcitonin (PCT) and C-reactive protein (CRP) in the diagnosis and prognosis of sepsis has demonstrated encouraging results. In contrast to PCT, which is highly selective for bacterial infections, CRP is an acute-phase protein that reflects systemic inflammation., Objective: This study aimed to assess the diagnostic accuracy and prognostic significance of CRP and PCT in early sepsis detection and outcome prediction., Methodology: This study was a retrospective cohort study that involved 90 patients in the ICU who met the criteria for sepsis-3. CRP and PCT levels, clinical data, and outcomes were obtained from electronic medical records. The diagnostic accuracy was tested using receiver operating characteristic (ROC) curves, while the prognostic relevance was analyzed by Kaplan-Meier survival analysis and Cox proportional hazards regression., Results: The mean CRP level was 102.3 mg/L and PCT level was 5.4 ng/mL. ROC analysis revealed an area under the curve (AUC) of 0.78 for CRP and 0.82 for PCT, indicating better diagnostic performance for PCT. High levels of CRP and PCT were associated with poorer survival, with median survival times of 18 and 15 days, respectively, for high-level groups. Cox regression identified CRP and PCT as significant predictors of mortality, with hazard ratios of 1.50 and 1.68, respectively., Conclusion: Both CRP and PCT are valuable biomarkers for diagnosing and prognosticating sepsis. PCT, with its higher specificity for bacterial infections, demonstrates superior diagnostic accuracy compared to CRP. Elevated levels of both biomarkers are associated with increased mortality risk, highlighting their potential role in early sepsis management and outcome prediction., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Review Board (IRB) of Lady Reading Hospital-MTI issued approval 948/LRH/MTI. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Daud et al.)

We studied the distribution and population status of the Cheer pheasant (Catreus wallichii) in Azad Jammu and Kashmir (AJ&K). Study was mainly conducted in four localities Jhelum Valley (JV), Machiara National Park (MNP), Haveli and Nar Sher Ali Khan (NSAK) from 2016-2020, for five breeding seasons. Population status of Cheer pheasant was determined by the call counts method. In total 105 breeding pairs (210 birds) were estimated highest (134) being recorded from Jhelum valley followed by MNP, Haveli and Nar Sher Ali Khan While applying correction factor 158 birds were recorded. Extensive surveys were carried out in an area of 19.23 km2. Our results indicate an expansion in distribution ranges of Cheer pheasant and population has established in several new sites. Highest Mean population density of 6.11pair/km2 was recorded in Qazi Nag area of Jhelum Valley. The mean population density of Cheer pheasant was slightly higher in the month of May. Furthermore, 58% of the calling birds were detected at elevations ranging from 2300-2600m, while 17% were found at elevations between 1900-2200m. Expansion in distribution ranges of Cheer might be due to reason that bird might have been underestimated in the past or conservation measures and community awareness programs taken by the Department of Wildlife and Fisheries, AJ&K.

The present study addresses advanced monitoring techniques for particles and airborne molecular contaminants (AMCs) in cleanroom environments, which are crucial for ensuring the integrity of semiconductor manufacturing processes. We focus on quantifying particle levels and a representative AMC, hydrogen chloride (HCl), having known detrimental effects on equipment longevity, product yield, and human health. We have developed a compact laser sensor based on open-path cavity ring-down spectroscopy (CRDS) using a 1742 nm near-infrared diode laser source. The sensor enables the high-sensitivity detection of HCl through absorption by the 2-0 vibrational band with an Allan deviation of 0.15 parts per billion (ppb) over 15 min. For quantifying particle number concentrations, we examine various detection methods based on statistical analyses of Mie scattering-induced ring-down time fluctuations. We find that the ring-down distributions' 3rd and 4th standard moments allow particle detection at densities as low as ~10 5 m -3 (diameter > 1 μm). These findings provide a basis for the future development of compact cleanroom monitoring instrumentation for wafer-level monitoring for both AMC and particles, including mobile platforms.

Bangladesh is currently experiencing significant infrastructural development in road networking system through the construction or reconstruction of multiple roads and highways. Consequently, there is a rise in traffic intensity on roads and highways, along with a significant contamination of adjacent agricultural soils with heavy metals. The purpose of this study was to evaluate the ecological risk, health risk and the abundance of seven heavy metals (Cu, Mn, Pb, Cd, Cr, As, and Ni) in three distance gradients (0, 300, and 500 m) of agricultural soil along the Dhaka-Chattogram highway. The concentration of heavy metals was measured with an Atomic Absorption Spectrophotometer (AAS) on a total of 36 soil samples that were taken from 12 different sampling sites. Based on the findings, Cd had a high contamination factor for all distance gradients, whereas Cr had a moderate contamination factor in 67% of the study areas. According to the Pollution Load Index (PLI), Cd, Cr, and Pb were the predominant pollutants. Principal component analysis (PCA) result shows these metals mainly came from anthropogenic sources. The considerable positive correlations between Cu-Pb, Cu-Cd, Pb-Cd, and Cr-Ni all pointed to shared anthropogenic origins. As per Potential Ecological Risk Assessment (PERI) analysis, Pb, Cd, Cr, and Ni each contribute significantly and pose a moderate threat. The Target Hazard Quotient (THQ) values for all pathways of exposure to Pb and Cr in soils were more than 1, which would pose a significant risk to human health in the following order: THQ adult female  > THQ adult male  > THQ children . This study will help to evaluate the human health risk and develop a better understanding of the heavy metal abundance scenario in the agricultural fields adjacent to this highway., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: The ancient science of life known as Ayurveda uses a variety of formulations or herbal compounds to treat a wide range of illnesses. Male infertility accounts for half of all infertility worldwide, and numerous etiological variables play a role. A pharmacologically active tobacco component called nicotine has a negative impact on male fertility and the reproductive system. Musalyadi Churna (MSC) is one of the polyherbal compound formulations mentioned in Ayurveda Classics for aphrodisiac therapy and recommended for the treatment of male infertility., Objective: The current study aims to evaluate the spermatogenic potential of MSC along with its protective effect against testicular degeneration induced by nicotine in rat models., Materials and Methods: Sixty adult Sprague-Dawley male rats were used in the experiment, which were divided into ten groups of six rats each. Nicotine was administered orally as disease control. The standard and vehicle control were also included along with study drug groups in which MSC was administered orally to the rats. The study was conducted for 70 days for each group with assessment of body weight and food consumption. After treatment, rats were weighed and sacrificed for evaluation of parameters like organ weight, epididymal sperm count, and sperm morphology along with histological assessment. The data were statistically evaluated using analysis of variance test and Bonferroni multiple-comparison range test to compare different treatment groups., Results and Conclusion: In the present study, MSC possesses substantial spermatogenic efficacy, and the result indicates that the study drug possesses a protective effect against nicotine-induced impaired testicular functions in rats, but further research to elucidate its exact mechanism of action is essential., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Journal of Pharmacy and Bioallied Sciences.)

Generative adversarial networks (GANs) have gained significant attention in the field of image synthesis, particularly in computer vision. GANs consist of a generative model and a discriminative model trained in an adversarial setting to generate realistic and novel data. In the context of image synthesis, the generator produces synthetic images, whereas the discriminator determines their authenticity by comparing them with real examples. Through iterative training, the generator allows the creation of images that are indistinguishable from real ones, leading to high-quality image generation. Considering their success in computer vision, GANs hold great potential for medical diagnostic applications. In the medical field, GANs can generate images of rare diseases, aid in learning, and be used as visualization tools. GANs can leverage unlabeled medical images, which are large in size, numerous in quantity, and challenging to annotate manually. GANs have demonstrated remarkable capabilities in image synthesis and have the potential to significantly impact digital histopathology. This review article focuses on the emerging use of GANs in digital histopathology, examining their applications and potential challenges. Histopathology plays a crucial role in disease diagnosis, and GANs can contribute by generating realistic microscopic images. However, ethical considerations arise because of the reliance on synthetic or pseudogenerated images. Therefore, the manuscript also explores the current limitations and highlights the ethical considerations associated with the use of this technology. In conclusion, digital histopathology has seen an emerging use of GANs for image enhancement, such as color (stain) normalization, virtual staining, and ink/marker removal. GANs offer significant potential in transforming digital pathology when applied to specific and narrow tasks (preprocessing enhancements). Evaluating data quality, addressing biases, protecting privacy, ensuring accountability and transparency, and developing regulation are imperative to ensure the ethical application of GANs., (Copyright © 2023 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights reserved.)

This study explores the relationship between structural alterations of nirmatrelvir, such as homologation and deuteration, and metabolic stability of newly synthesized derivatives. We developed a reliable synthetic protocol toward dideutero-nirmatrelvir and its homologated analogues with high isotopic incorporation. Deuteration of the primary metabolic site of nirmatrelvir provides a 3-fold improvement of its human microsomal stability but is accompanied by an increased metabolism rate at secondary sites. Homologation of the lactam ring allows the capping group modification to decrease and delocalize the molecule's lipophilicity, reducing the metabolic rate at secondary sites. The effect of deuteration was less pronounced for the 6-membered lactam than for its 5-membered analogue in human microsomes, but the trend is reversed in the case of mouse microsomes. X-ray data revealed that the homologation of the lactam ring favors the orientation of the drug's nitrile warhead for interaction with the catalytic sulfur of the SARS-CoV-2 M pro , improving its binding. Comparable potency against SARS-CoV-2 M pro from several variants of concern and selectivity over human cysteine proteases cathepsin B, L, and S was observed for the novel deuterated/homologated derivative and nirmatrelvir. Synthesized compounds displayed a large interspecies variability in hamster, rat, and human hepatocyte stability assays. Overall, we aimed to apply a rational approach in changing the physicochemical properties of the drug to refine its biochemical and biological parameters., Competing Interests: The authors declare the following competing financial interest(s): The Governors of the University of Alberta has filed a patent application that also contains a few of the molecules in this manuscript and currently some authors are listed as inventors., (© 2023 The Authors. Published by American Chemical Society.)

Biological bioprostheses such as grafts, patches, and heart valves are often derived from biological tissue like the pericardium. These bioprostheses can be of xenogenic, allogeneic, or autologous origin. Irrespective of their origin, all types are pre-treated via crosslinking to render the tissue non-antigenic and mechanically strong or to minimize degradation. The most widely used crosslinking agent is glutaraldehyde. However, glutaraldehyde-treated tissue is prone to calcification, inflammatory degradation, and mechanical injury, and it is incapable of matrix regeneration, leading to structural degeneration over time. In this work, we are investigating an alternative crosslinking method for an intraoperative application. The treated tissue's crosslinking degree was evaluated by differential scanning calorimetry. To confirm the findings, a collagenase assay was conducted. Uniaxial tensile testing was used to assess the tissue's mechanical properties. To support the findings, the treated tissue was visualized using two-photon microscopy. Additionally, fourier transform infrared spectroscopy was performed to study the overall protein secondary structure. Finally, a crosslinking procedure was identified for intraoperative processing. The samples showed a significant increase in thermal and enzymatic stability after treatment compared to the control, with a difference of up to 22.2 °C and 100%, respectively. Also, the tissue showed similar biomechanics to glutaraldehyde-treated tissue, showing greater extensibility, a higher failure strain, and a lower ultimate tensile strength than the control. The significant difference in the structure band ratio after treatment is proof of the introduction of additional crosslinks compared to the untreated control with regard to differences in the amide-I region. The microscopic images support these findings, showing an alteration of the fiber orientation after treatment. For collagen-based biomaterials, such as pericardial tissue, the novel phenolic crosslinking agent proved to be an equivalent alternative to glutaraldehyde regarding tissue characteristics. Although long-term studies must be performed to investigate superiority in terms of longevity and calcification, our novel crosslinking agent can be applied in concentrations of 1.5% or 2.0% for the treatment of biomaterials.

Dengue is caused by the dengue virus (DENVs) infection and clinical manifestations include dengue fever (DF), dengue hemorrhagic fever (DHF), or dengue shock syndrome (DSS). Due to a lack of antiviral drugs and effective vaccines, several therapeutic and control strategies have been proposed. A systemic literature review was conducted according to PRISMA guidelines to select proper references to give an overview of DENV infection. Results indicate that understanding the virus characteristics and epidemiology are essential to gain the basic and clinical knowledge as well as dengue disseminated pattern and status. Different factors and mechanisms are thought to be involved in the presentation of DHF and DSS, including antibody-dependent enhancement, immune dysregulation, viral virulence, host genetic susceptibility, and preexisting dengue antibodies. This study suggests that dissecting pathogenesis and risk factors as well as developing different types of therapeutic and control strategies against DENV infection are urgently needed., Competing Interests: Declaration of Competing Interest We have no conflict of interest to declare., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

This work provides numerical simulations of the nonlinear breathing transmission epidemic system using the proposed stochastic scale conjugate gradient neural networks (SCGGNNs) procedure. The mathematical model categorizes the breathing transmission epidemic model into four dynamics based on a nonlinear stiff ordinary differential system: susceptible, exposed, infected, and recovered. Three different cases of the model are taken and numerically presented by applying the stochastic SCGGNNs. An activation function 'log-sigmoid' uses twenty neurons in the hidden layers. The precision of SCGGNNs is obtained by comparing the proposed and database solutions. While the negligible absolute error is performed around 10 -06 to 10 -07 , it enhances the accuracy of the scheme. The obtained results of the breathing transmission epidemic system have been provided using the training, verification, and testing procedures to reduce the mean square error. Moreover, the exactness and capability of the stochastic SCGGNNs are approved through error histograms, regression values, correlation tests, and state transitions., (© 2023. Springer Nature Limited.)

The evaporation of liquid hydrocarbon n-heptane is discussed in detail with experimentation and numerical techniques. A maximum wall temperature of 1050 K was reported during an experimental process with a two-phase flow that was stable and had a prominent meniscus at a small fuel flow rate (FFR) ≤ 10 µL/min. At medium to high FFR (30-70 µL/min), the flow field was unstable, with nucleating bubbles and liquid droplets inside the microtube and the maximum temperature recorded was 850 K for 70 µL/min. For the numerical model, the temperature of the wall was used as a boundary condition. Using the numerical model, the evaporative flux at the meniscus, pressure drop, pressure oscillation, and heat transfer coefficient (HTC) were investigated. A single peak in HTC was obtained at a low fuel flow rate, while multiple peaks were obtained for high FFR. At low FFR, the pressure peak was observed to be 102.4 KPa, whereas at high FFR, the pressure peak increased to 105.5 KPa. This shows a 2% increase in pressure peak with an increase in FFR. Similarly, when the FFR increased from 5 µL/min to 70 µL/min, the pressure drop increased from 500 Pa to 2800 Pa. The high amplitude of pressure drops and a high peak of HTC were found, which depend on the mass flow rate. The coefficient of variation for pressure drop depends mainly on the fuel flow rate.

Ferromanganese oxide biochar composite (FMBC) is an efficient remediation material for cadmium -contaminated soils. However, the effect of FMBC under varied water managements on the remediation of Cd-polluted soil is unclear. In this study, we conducted both incubation and field experiments to investigate the combined effects of corn-stover-derived biochar modified with ferromanganese on the immobilization and uptake of Cd by rice under continuous aerobic (A), aerobic-flooded (AF), and flooded-aerobic (FA) water management regimes. The results showed that loading iron-manganese significantly increased the maximum sorption capacity (Qm) of Cd on FMBC (50.46 mg g -1 ) due to increased surface area, as compared to the pristine biochar (BC, 31.36 mg g -1 ). The results revealed that soil Eh and pH were significantly affected by FMBC and it's synergistic application with different water regimes, thus causing significant differences in the concentrations of DTPA-extractable Cd under different treatments. The lowest DTPA-extractable Cd content (0.28-0.46 mg -1 ) was observed in the treatment with FMBC (2.5 %) combined FA water amendment, which reduced the content of available Cd in soil by 2.63-28.4 %. Moreover, the treatments with FMBC-FA resulted the proportion of residual Cd increased by 22.2 % compared to the control. Variations in the content and fraction of Cd had a significant influence on its accumulation in the rice grains. The FMBC-FA treatments reduced the Cd concentration in roots, shoots and grains by 37.97 %, 33.98 %, and 53.66 %, respectively, when compared with the control. Predominantly because of the reduction in Cd biological toxicity and the improved soil nutrient content, the combined application increased the biomass and yield of rice to some extent. Taken together, the combination of the Fe-Mn modified biochar and flooded-aerobic water management may potentially be applied in Cd-polluted soil to mitigate the impacts of Cd on rice production., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Urine biomarkers of kidney tubule injury associate with incident hypertension in older adults with comorbidities, but less is known about these associations in younger adults., Methods: In 1170 participants of the CARDIA study (Coronary Artery Risk Development in Young Adults; mean age, 45 years; 40% Black people; 56% women) without hypertension, cardiovascular disease, or kidney disease at baseline, we examined associations of urine MCP-1 (monocyte chemoattractant protein-1), α1m (alpha-1-microglobulin), KIM-1 (kidney injury molecule-1), EGF (epidermal growth factor), IL (interleukin)-18, YKL-40 (chitinase-3-like protein 1), and UMOD (uromodulin) with incident hypertension (onset of systolic blood pressure [BP] ≥130 mm Hg or diastolic BP ≥80 mm Hg or initiation of hypertension medications) and longitudinal BP change in models adjusted for hypertension risk factors, estimated glomerular filtration rate, and albuminuria., Results: After a median 9.9 (interquartile range, 5.9-10.2) years, 376 participants developed incident hypertension. In demographic-adjusted analyses, higher tertiles of EGF associated with lower risk of incident hypertension in both Black and White participants. After multivariable adjustment, the risk of incident hypertension remained lower in tertile 2 (hazard ratio, 0.70 [95% CI, 0.50-0.97]) and tertile 3 (hazard ratio, 0.58 [0.39-0.85]) of EGF versus tertile 1. In fully adjusted models, participants in EGF tertile 3 had smaller 10-year increases in systolic (-3.4 [95% CI, -6.1 to -0.7] mm Hg) and diastolic BP (-2.6 [95% CI, -4.6 to -0.6] mm Hg) than tertile 1. Other biomarkers showed inconsistent associations with incident hypertension and BP change., Conclusions: In middle-aged adults without hypertension, cardiovascular disease, or kidney disease, higher urine EGF associated with lower risk of incident hypertension and lower 10-year BP elevations., Competing Interests: Disclosures O.M. Gutiérrez reports receiving grant funding and honoraria from Akebia and Amgen; grant funding from GlaxoSmithKline; honoraria from AstraZeneca, Reata, and Ardelyx; and serving on a Data Monitoring Committee for QED. The other authors report no conflicts.

CRISPR-Cas9-based therapeutic genome editing approaches hold promise to cure a variety of human diseases. Recent findings demonstrate pre-existing immunity for the commonly used Cas orthologs from Streptococcus pyogenes (SpCas9) and Staphylococcus aureus (SaCas9) in humans, which threatens the success of this powerful tool in clinical use. Thus, a comprehensive investigation and potential risk assessment are required to exploit the full potential of the system. Here, we investigated existence of immunity to SpCas9 and SaCas9 in control rhesus macaques ( Macaca mulatta) alongside monkeys transplanted with either lentiviral transduced or CRISPR-SpCas9 ribonucleoprotein (RNP)-edited cells. We observed significant levels of Cas9 antibodies in the peripheral blood of all transplanted and non-transplanted control animals. Transplantation of ex vivo transduced or SpCas9-mediated BCL11A enhancer-edited cells did not alter the levels of Cas9 antibodies in rhesus monkeys. Following stimulation of peripheral blood cells with SpCas9 or SaCas9, neither Cas9-specific T cells nor cytokine induction were detected. Robust and durable editing frequencies and expression of high levels of fetal hemoglobin in BCL11A enhancer-edited rhesus monkeys with no evidence of an immune response (>3 years) provide an optimistic outlook for the use of ex vivo CRISPR-SpCas9 (RNP)-edited cells., Competing Interests: S.G. has patent applications in the fields of cell and/or gene therapy for cancer. S.G. is a consultant of TESSA Therapeutics, a DSMB member of Immatics, and has received honoraria from Tidal, Catamaran Bio, Sanofi, and Novartis within the last 2 years.

The COVID-19 pandemic has presented a unique challenge for physicians worldwide, as they grapple with limited data and uncertainty in diagnosing and predicting disease outcomes. In such dire circumstances, the need for innovative methods that can aid in making informed decisions with limited data is more critical than ever before. To allow prediction with limited COVID-19 data as a case study, we present a complete framework for progression and prognosis prediction in chest X-rays (CXR) through reasoning in a COVID-specific deep feature space. The proposed approach relies on a pre-trained deep learning model that has been fine-tuned specifically for COVID-19 CXRs to identify infection-sensitive features from chest radiographs. Using a neuronal attention-based mechanism, the proposed method determines dominant neural activations that lead to a feature subspace where neurons are more sensitive to COVID-related abnormalities. This process allows the input CXRs to be projected into a high-dimensional feature space where age and clinical attributes like comorbidities are associated with each CXR. The proposed method can accurately retrieve relevant cases from electronic health records (EHRs) using visual similarity, age group, and comorbidity similarities. These cases are then analyzed to gather evidence for reasoning, including diagnosis and treatment. By using a two-stage reasoning process based on the Dempster-Shafer theory of evidence, the proposed method can accurately predict the severity, progression, and prognosis of a COVID-19 patient when sufficient evidence is available. Experimental results on two large datasets show that the proposed method achieves 88% precision, 79% recall, and 83.7% F-score on the test sets.

Diabetic retinopathy is one of the most significant retinal diseases that can lead to blindness. As a result, it is critical to receive a prompt diagnosis of the disease. Manual screening can result in misdiagnosis due to human error and limited human capability. In such cases, using a deep learning-based automated diagnosis of the disease could aid in early detection and treatment. In deep learning-based analysis, the original and segmented blood vessels are typically used for diagnosis. However, it is still unclear which approach is superior. In this study, a comparison of two deep learning approaches (Inception v3 and DenseNet-121) was performed on two different datasets of colored images and segmented images. The study's findings revealed that the accuracy for original images on both Inception v3 and DenseNet-121 equaled 0.8 or higher, whereas the segmented retinal blood vessels under both approaches provided an accuracy of just greater than 0.6, demonstrating that the segmented vessels do not add much utility to the deep learning-based analysis. The study's findings show that the original-colored images are more significant in diagnosing retinopathy than the extracted retinal blood vessels.

The main protease of SARS-CoV-2 (M pro ) is the most promising drug target against coronaviruses due to its essential role in virus replication. With newly emerging variants there is a concern that mutations in M pro may alter the structural and functional properties of protease and subsequently the potency of existing and potential antivirals. We explored the effect of 31 mutations belonging to 5 variants of concern (VOCs) on catalytic parameters and substrate specificity, which revealed changes in substrate binding and the rate of cleavage of a viral peptide. Crystal structures of 11 M pro mutants provided structural insight into their altered functionality. Additionally, we show M pro mutations influence proteolysis of an immunomodulatory host protein Galectin-8 (Gal-8) and a subsequent significant decrease in cytokine secretion, providing evidence for alterations in the escape of host-antiviral mechanisms. Accordingly, mutations associated with the Gamma VOC and highly virulent Delta VOC resulted in a significant increase in Gal-8 cleavage. Importantly, IC50s of nirmatrelvir (Pfizer) and our irreversible inhibitor AVI-8053 demonstrated no changes in potency for both drugs for all mutants, suggesting M pro will remain a high-priority antiviral drug candidate as SARS-CoV-2 evolves., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Toxoplasma gondii is an intracellular zoonotic protozoan parasite usually infects human and animal worldwide. This study aimed to analyze the sero-prevalence of T. gondii in blood of lactating animals and human living in close proximity and also to detect Toxoplasma DNA in unpasteurized milk of the studied animals. A total of 233 blood and milk samples were collected from lactating animals, and 735 blood samples were taken from humans in District Upper Dir, Khyber Pakhtunkhwa, Pakistan. The blood samples were analyzed through ELISA while the milk samples were analyzed by PCR for the presence of T. gondii DNA. A standard questionnaire was introduced to collect the data from the participants. In animals, the reported sero-prevalence was 32.18% for IgM, 17.16% for IgG, and 6.4% for both IgM and IgG. The reported positivity for T. gondii DNA in milk was 14.44%, 34.8%, 20%, and 26% in sheep, goats, cows, and buffaloes, respectively. In the human blood samples, 9.8% were found positive for IgM and 11.2% for IgG while none of the samples was found positive for both IgM and IgG. Overall sero-prevalence reported in females was significantly higher than the male (p<0.05) poor hygiene condition (p < 0.0001) were the significant risk factors associated with T. gondii infections in animals. In conclusion, T. gondii infection is prevalent in lactating animals and humans using their raw milk in the study area. It is suggested that raw milk should be considered as a vehicle for the transmission of T. gondii to humans. Proper pasteurization of milk is very useful in limiting the transmission of infection. Awareness and control programs should be implemented to prevent the infection.

Ischemia-reperfusion (I/R) injury is a complication impacting multiple organs and tissues in clinical conditions ranging from peripheral arterial disease to musculoskeletal trauma and myocardial infarction. Stem cell-derived extracellular vesicles (EVs) may represent one therapeutic resource for preventing the tissue damage associated with I/R injury. Here we tested the hypothesis that lyophilized extracellular vesicles derived from adipose stem cells could serve as an "off-the-shelf" treatment modality for I/R injury in a mouse hindlimb ischemia model. Ischemia was induced for 90 min using a rubber band tourniquet and extracellular vesicles (0, 50, or 100 µg) administered via tail vein injection immediately prior to reperfusion. Perfusion was measured prior to, during, and after ischemia using laser Doppler imaging. Serum and tissue were collected 24 h after reperfusion. Mass spectrometry (MS)-based proteomics was used to characterize the EV cargo and proteins from the ischemic and non-ischemic hindlimb. Inflammatory cytokines were measured in muscle and serum using a multiplex array. Results indicate that EVs significantly increase reperfusion and significantly increase expression of the anti-inflammatory factor annexin a1 in skeletal muscle; however, the increased reperfusion was also associated with a marked decrease in muscle structural proteins such as dystrophin, plectin, and obscurin. Circulating inflammatory cytokines TNF-alpha and IL-6 were increased with EV treatment, and serum TNF-alpha showed a significant, positive correlation with reperfusion level. These findings suggest that, while EVs may enhance reperfusion, the increased reperfusion can negatively impact muscle tissue and possibly remote organs. Alternative approaches, such as targeting mitochondrial permeability, may be more effective at mitigating I/R injury.

Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. Various contact and non-contact-based methods are discussed in the literature for breathing monitoring. Radio frequency (RF)-based breathing monitoring has recently gained enormous popularity among non-contact methods. This method eliminates privacy concerns and the need for users to carry a device. In addition, such methods can reduce stress on healthcare facilities by providing intelligent digital health technologies. These intelligent digital technologies utilize a machine learning (ML)-based system for classifying breathing abnormalities. Despite advances in ML-based systems, the increasing dimensionality of data poses a significant challenge, as unrelated features can significantly impact the developed system's performance. Optimal feature scoring may appear to be a viable solution to this problem, as it has the potential to improve system performance significantly. Initially, in this study, software-defined radio (SDR) and RF sensing techniques were used to develop a breathing monitoring system. Minute variations in wireless channel state information (CSI) due to breathing movement were used to detect breathing abnormalities in breathing patterns. Furthermore, ML algorithms intelligently classified breathing abnormalities in single and multiple-person scenarios. The results were validated by referencing a wearable sensor. Finally, optimal feature scoring was used to improve the developed system's performance in terms of accuracy, training time, and prediction speed. The results showed that optimal feature scoring can help achieve maximum accuracy of up to 93.8% and 91.7% for single-person and multi-person scenarios, respectively.

The outbreak of the novel coronavirus disease COVID-19 (SARS-CoV-2) has developed into a global epidemic. Due to the pathogenic virus's high transmission rate, accurate identification and early prediction are required for subsequent therapy. Moreover, the virus's polymorphic nature allows it to evolve and adapt to various environments, making prediction difficult. However, other diseases, such as dengue, MERS-CoV, Ebola, SARS-CoV-1, and influenza, necessitate the employment of a predictor based on their genomic information. To alleviate the situation, we propose a deep learning-based mechanism for the classification of various SARS-CoV-2 virus variants, including the most recent, Omicron. Our model uses a neural network with a temporal convolution neural network to accurately identify different variants of COVID-19. The proposed model first encodes the sequences in the numerical descriptor, and then the convolution operation is applied for discriminative feature extraction from the encoded sequences. The sequential relations between the features are collected using a temporal convolution network to classify COVID-19 variants accurately. We collected recent data from the NCBI, on which the proposed method outperforms various baselines with a high margin.

In the last 2 years, we have witnessed multiple waves of coronavirus that affected millions of people around the globe. The proper cure for COVID-19 has not been diagnosed as vaccinated people also got infected with this disease. Precise and timely detection of COVID-19 can save human lives and protect them from complicated treatment procedures. Researchers have employed several medical imaging modalities like CT-Scan and X-ray for COVID-19 detection, however, little concentration is invested in the ECG imaging analysis. ECGs are quickly available image modality in comparison to CT-Scan and X-ray, therefore, we use them for diagnosing COVID-19. Efficient and effective detection of COVID-19 from the ECG signal is a complex and time-taking task, as researchers usually convert them into numeric values before applying any method which ultimately increases the computational burden. In this work, we tried to overcome these challenges by directly employing the ECG images in a deep-learning (DL)-based approach. More specifically, we introduce an Efficient-ECGNet method that presents an improved version of the EfficientNetV2-B4 model with additional dense layers and is capable of accurately classifying the ECG images into healthy, COVID-19, myocardial infarction (MI), abnormal heartbeats (AHB), and patients with Previous History of Myocardial Infarction (PMI) classes. Moreover, we introduce a module to measure the similarity of COVID-19-affected ECG images with the rest of the diseases. To the best of our knowledge, this is the first effort to approximate the correlation of COVID-19 patients with those having any previous or current history of cardio or respiratory disease. Further, we generate the heatmaps to demonstrate the accurate key-points computation ability of our method. We have performed extensive experimentation on a publicly available dataset to show the robustness of the proposed approach and confirmed that the Efficient-ECGNet framework is reliable to classify the ECG-based COVID-19 samples., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Nawaz, Nazir, Javed, Malik, Saudagar, Khan, Abul Hasanat, AlTameem and AlKhathami.)

Online product recommendation (OPR) systems have gained prominence in the context of e-commerce over the past years. Despite the increased research on OPR use, less attention has been paid to examining how decision and affective assessment of the OPR are contingent upon the product type. This study proposes and examines a recommendation-product congruity proposition based on cognitive fit and schema congruity theories. The proposition states that when the content (i.e., a stimulus-based schema) of the OPR [either system-generated recommendation (SGR) or a consumer-generated recommendation (CGR)] matches the brain-stored schema initiated by a particular product (either a search product or an experienced product), then a consumer would use a schema-based information assessment strategy and experience favorable decision and affective assessment of the OPR. This then affects consumers' intentions to purchase and reuse OPR. The proposition is tested via a 2 × 2 between-respondents factorial design of a cross-sectional survey with 482 Amazon customers. The results support the following two matching conditions of the proposition: (1) SGR describing a search product and (2) CGR explaining an experienced product, which might lead customers to perceive lower decision effort, greater decision quality, and higher enjoyment with the OPR that subsequently have a significant impact on their intentions to purchase and reuse OPR. This study expands our understanding of how recommendation-product congruence influences the consumer's decision and affective assessment behavior and provides practical implications for the identification and presentation of the recommendation type and product type for a better customer decision., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Khan, Ashraf, Orangzab, Sharif and Ahmad.)

In this paper, we investigate the nonlinear dynamics associated with controlled Lagrangians involving higher-order derivatives. More precisely, we establish the controlled higher-order Hamilton ordinary differential equations (ODEs) and Hamilton-Jacobi partial differential equation (PDE) for the considered class of Lagrangians governed by higher-order derivatives of the state variables. Moreover, we formulate and prove an invariance result with respect to the state variable. In addition, in order to validate the theoretical results and to highlight their effectiveness, some illustrative applications are presented., (© 2022. The Author(s).)

Coronavirus (COVID-19) is a highly severe infection caused by the severe acute respiratory coronavirus 2 (SARS-CoV-2). The polymerase chain reaction (PCR) test is essential to confirm the COVID-19 infection, but it has certain limitations, including paucity of reagents, is computationally time-consuming, and requires expert clinicians. Clinicians suggest that the PCR test is not a reliable automated COVID-19 patient detection system. This study proposed a machine learning-based approach to evaluate the PCR role in COVID-19 detection. We collect real data containing 603 COVID-19 samples from the Pakistan Institute of Medical Sciences (PIMS) Hospital in Islamabad, Pakistan, during the third COVID-19 wave. The experiments are separated into two sets. The first set comprises 24 features, including PCR test results, whereas the second comprises 24 features without PCR test. The findings demonstrate that the decision tree achieves the best detection rate for positive and negative COVID-19 patients in both scenarios. The findings reveal that PCR does not contribute to detecting COVID-19 patients. The findings also aid in the early detection of COVID-19, mainly when PCR test results are insufficient for diagnosing COVID-19 and help developing countries with a paucity of PCR tests and specialist facilities., Competing Interests: The authors share no conflicts of interests., (Copyright © 2022 Zunera Jalil et al.)

Asiatic black bear has long been in conflict with human beings crop raiding is a major cause of this conflict frequently noted in South Asia. Crops raided by black bears affected by temporal, spatial and anthropogenic attributes. Insight in this conflict and its mitigation is vital for the conservation of this threatened species. Present study aimed to evaluate crop raiding by black bears in the mountainous region of Azad Jammu and Kashmir. Field surveys were carried out to observe spatial and temporal crop raiding features between 2015-2020 and data gathered using designed questionnaires randomly tailored in villages nearby the forests. Results revealed that maize was the sole crop raided by black bears. A total of 28-acre area was raided by black bear in the fall season (Aug-November) resulting in a damage of 51 metric tons, whole raiding was carried out at night. Each respondent received crop damage on 0.09 acre with a loss of 0.17 metric ton yield. Crop quantity and area were significantly correlated to each other. District Neelum shared 49% of the total crop loss, while 47% of the maize was raided at the altitudinal range of 2100-2500 m. crop raiding was highly significantly ( χ 2 = 1174.64 ; d f = 308 ;   p < 0.01 ) dependent upon distance to the forest. Linear regression revealed that maize quantity was determined by area, time and the total field area. Farmers faced 3.8 million PKRs loss due to crop damage by black bears. Despite the huge loss, the majority (23%) of the respondents did not respond to the query on mitigation measures indicating a poor adaptation of preventive measures. Preferred strategy to avoid crop damage was making noise (27.8%) when bears attacked their crops. A start of compensation scheme to the farmers is recommended that will have turned their negative attitude into a positive one toward the wildlife and black bear particularly. Study provides a new insight in human-bear conflict, particularly in spatial and temporal context of crop raiding in AJ&K.

The outbreak of COVID-19, since its appearance, has affected about 200 countries and endangered millions of lives. COVID-19 is extremely contagious disease, and it can quickly incapacitate the healthcare systems if infected cases are not handled timely. Several Conventional Neural Networks (CNN) based techniques have been developed to diagnose the COVID-19. These techniques require a large, labelled dataset to train the algorithm fully, but there are not too many labelled datasets. To mitigate this problem and facilitate the diagnosis of COVID-19, we developed a self-attention transformer-based approach having self-attention mechanism using CT slices. The architecture of transformer can exploit the ample unlabelled datasets using pre-training. The paper aims to compare the performances of self-attention transformer-based approach with CNN and Ensemble classifiers for diagnosis of COVID-19 using binary Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and multi-class Hybrid-learning for UnbiaSed predicTion of COVID-19 (HUST-19) CT scan dataset. To perform this comparison, we have tested Deep learning-based classifiers and ensemble classifiers with proposed approach using CT scan images. Proposed approach is more effective in detection of COVID-19 with an accuracy of 99.7% on multi-class HUST-19, whereas 98% on binary class SARS-CoV-2 dataset. Cross corpus evaluation achieves accuracy of 93% by training the model with Hust19 dataset and testing using Brazilian COVID dataset., (© 2022. The Author(s).)

Cerebral ischemia and reperfusion initiate cellular events in brain that lead to neurological disability. Investigating these cellular events provides ample targets for developing new treatments. Despite considerable work, no such therapy has translated into successful stroke treatment. Among other issues-such as incomplete mechanistic knowledge and faulty clinical trial design-a key contributor to prior translational failures may be insufficient scientific rigor during preclinical assessment: nonblinded outcome assessment; missing randomization; inappropriate sample sizes; and preclinical assessments in young male animals that ignore relevant biological variables, such as age, sex, and relevant comorbid diseases. Promising results are rarely replicated in multiple laboratories. We sought to address some of these issues with rigorous assessment of candidate treatments across 6 independent research laboratories. The Stroke Preclinical Assessment Network (SPAN) implements state-of-the-art experimental design to test the hypothesis that rigorous preclinical assessment can successfully reduce or eliminate common sources of bias in choosing treatments for evaluation in clinical studies. SPAN is a randomized, placebo-controlled, blinded, multilaboratory trial using a multi-arm multi-stage protocol to select one or more putative stroke treatments with an implied high likelihood of success in human clinical stroke trials. The first stage of SPAN implemented procedural standardization and experimental rigor. All participating research laboratories performed middle cerebral artery occlusion surgery adhering to a common protocol and rapidly enrolled 913 mice in the first of 4 planned stages with excellent protocol adherence, remarkable data completion and low rates of subject loss. SPAN stage 1 successfully implemented treatment masking, randomization, prerandomization inclusion/exclusion criteria, and blinded assessment to exclude bias. Our data suggest that a large, multilaboratory, preclinical assessment effort to reduce known sources of bias is feasible and practical. Subsequent SPAN stages will evaluate candidate treatments for potential success in future stroke clinical trials using aged animals and animals with comorbid conditions.

Currently, the spread of COVID-19 is running at a constant pace. The current situation is not so alarming, but every pandemic has a history of three waves. Two waves have been seen, and now expecting the third wave. Compartmental models are one of the methods that predict the severity of a pandemic. An enhanced SEIR model is expected to predict the new cases of COVID-19. The proposed model has an additional compartment of vaccination. This proposed model is the SEIRV model that predicts the severity of COVID-19 when the population is vaccinated. The proposed model is simulated with three conditions. The first condition is when social distancing is not incorporated, while the second condition is when social distancing is included. The third one condition is when social distancing is combined when the population is vaccinated. The result shows an epidemic growth rate of about 0.06 per day, and the number of infected people doubles every 10.7 days. Still, with imparting social distancing, the proposed model obtained the value of R 0 is 1.3. Vaccination of infants and kids will be considered as future work.