A Cross-Sectional Study Evaluating the Basic Course in Biomedical Research Among Medical Postgraduates and Teachers.

Introduction and methodology This study aims to give feedback on the Basic Course in Biomedical Research (BCBR) program, an initiative of the National Medical Council (NMC) in collaboration with the National Institute of Epidemiology (ICMR-NIE) using the SWAYAM ("Study Webs of Active-Learning for Young Aspiring Minds") portal. The objectives of the study areto evaluate the usefulness of BCBR and the content and conduct of the BCBR program using a questionnaire among medical postgraduates and teachers. The study design used was a cross-sectional study and collected data from 392 participants who completed the BCBR program. A validated questionnaire was utilized to gather information on participant demographics, reasons for enrolment, satisfaction with course material, assignments, technical issues during exams, and perceived usefulness of the course. Results The study found a predominance of postgraduate students among participants (65.31%), reflecting their inclination towards research. Primary reasons for enrolment included institutional requirements and eligibility criteria to appear for the final postgraduate examination. Most participants utilized both videos and lecture hand-outs. This course facilitated its participants to improve their ability to conduct research by 89.03%. Feedback suggested a need for improvement in course content, particularly in simplifying statistical concepts and incorporating more interactive sessions and practical demonstrations. Conclusion The findings highlight the effectiveness of the BCBR program to up-skill the ability of participants to perform research. Overall, the study offers valuable feedback about the BCBR course.

Adjuvant therapy may improve overall survival in high-risk periampullary adenocarcinomas patients - A match-pair analysis from a multi-institutional cohort study (The MIPPAP study).

BACKGROUND: The role of adjuvant therapy in resected periampullary adenocarcinomas is equivocal due to contrasting data and limited prospective trials. METHODS: The Multicentre Indian Pancreatic & Periampullary Adenocarcinoma Project (MIPPAP), included data from 8 institutions across India. Of the 1679 pancreatic resections, 736 patients with T3/T4 and/or Node positive adenocarcinomas (considered as high risk for recurrence) were included for analysis. Three (adjuvant): one (observation) matching, using T3/T4 T staging, nodal positivity and ampullary subtype was performed by using the nearest neighbour matching method. RESULTS: Of 736 patients eligible for inclusion, 621 patients were matched of which 458 patients received adjuvant therapy (AT) (predominantly gemcitabine-based) and 163 patients were observed (O). With a median follow-up of 42 months, there was a statistical difference in overall survival in favour of patients receiving AT as compared to those on observation [68.7 months vs. 61.1 months, Hazard ratio: 0.73 (95% CI: 0.54-0.97); p = 0.03]. Besides AT, presence of nodal involvement (median OS: 65.4 months vs not reached; p = 0.04) predicted for inferior OS. CONCLUSIONS: The results of the match-pair analysis suggest that adjuvant therapy improves overall survival in periampullary adenocarcinomas at high risk of recurrence with a greater benefit in T3/T4, node-positive and ampullary subtypes.

Correction: Hybrid optimal-FOPID based UPQC for reducing harmonics and compensate load power in renewable energy sources grid connected system.

[This corrects the article DOI: 10.1371/journal.pone.0300145.].

Modulation of nuclear receptor 4A1 expression improves insulin secretion in a mouse model of chronic pancreatitis.

OBJECTIVES: Diabetes secondary to chronic pancreatitis (CP) presents clinical challenges due to insulin secretory defects and associated metabolic alterations. Owing to lack of molecular understanding, no pharmacotherapies to treat insulin secretory defects have been approved to date. We aimed to delineate the molecular mechanism of ß-cell dysfunction in CP. METHODS: Transcriptomic analysis was conducted to identify endocrine specific receptor expression in mice and human CP on microarray. The identified receptor (NR4A1) was overexpressed in MIN6 cells using PEI linear transfection. RNA-Seq analysis on NovaSeq 6000 of NR4A1 overexpressed (OE) MIN6 cells was performed to identify aberrant metabolic pathways. Upstream trigger for NR4A1OE was studied by InBio Discover and cytokine exposure. Downstream effect of NR4A1OE was examined by Fura2 AM based fluorometric and imaging studies of intracellular calcium. Mice with CP were treated with IFN-γ neutralizing monoclonal antibodies to assess NR4A1 expression and insulin secretion. RESULTS: Increased expression of NR4A1 associated with decreased insulin secretion in islets (humans: controls 9 ± 0.2, CP 3.7 ± 0.2, mice: controls 8.5 ± 0.2, CP 2.1 ± 0.1 µg/L). NR4A1OE in MIN6 cells (13.2 ± 0.1) showed reduction in insulin secretion (13 ± 5 to 0.2 ± 0.1 µg/mg protein/minute, p = 0.001) and downregulation of calcium and cAMP signaling pathways. IFN-γ was identified as upstream signal for NR4A1OE in MIN6. Mice treated with IFN-γ neutralizing antibodies showed decreased NR4A1 expression 3.4 ± 0.11-fold (p = 0.03), improved insulin secretion (4.4 ± 0.2-fold, p = 0.01), associated with increased Ca2+ levels (2.39 ± 0.06-fold, p = 0.009). CONCLUSIONS: Modulating NR4A1 expression can be a promising therapeutic strategy to improve insulin secretion in CP.

Hybrid optimal-FOPID based UPQC for reducing harmonics and compensate load power in renewable energy sources grid connected system.

Integration of renewable energy sources (RES) to the grid in today's electrical system is being encouraged to meet the increase in demand of electrical power and also overcome the environmental related problems by reducing the usage of fossil fuels. Power Quality (PQ) is a critical problem that could have an effect on utilities and consumers. PQ issues in the modern electric power system were turned on by a linkage of RES, smart grid technologies and widespread usage of power electronics equipment. Unified Power Quality Conditioner (UPQC) is widely employed for solving issues with the distribution grid caused by anomalous voltage, current, or frequency. To enhance UPQC performance, Fractional Order Proportional Integral Derivative (FOPID) is developed; nevertheless, a number of tuning parameters restricts its performance. The best solution for the FOPID controller problem is found by using a Coati Optimization Algorithm (COA) and Osprey Optimization Algorithm (OOA) are combined to make a hybrid optimization CO-OA algorithm approach to mitigate these problems. This paper proposes an improved FOPID controller to reduce PQ problems while taking load power into account. In the suggested model, a RES is connected to the grid system to supply the necessary load demand during the PQ problems period. Through the use of an enhanced FOPID controller, both current and voltage PQ concerns are separately modified. The pulse signal of UPQC was done using the optimal controller, which analyzes the error value of reference value and actual value to generate pulses. The integrated design mitigates PQ issues in a system at non-linear load and linear load conditions. The proposed model provides THD of 12.15% and 0.82% at the sag period, 10.18% and 0.48% at the swell period, and 10.07% and 1.01% at the interruption period of non-linear load condition. A comparison between the FOPID controller and the traditional PI controller was additionally taken. The results showed that the recommended improved FOPID controller for UPQC has been successful in reducing the PQ challenges in the grid-connected RESs system.

Application of machine-learning model to optimize colonic adenoma detection in India.

AIMS: There is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at developing a machine-learning model to optimize colonic adenoma detection in a prospective cohort. METHODS: All consecutive adult patients undergoing diagnostic colonoscopy were enrolled between October 2020 and November 2022. Patients with a high risk of colonic adenoma were excluded. The predictive model was developed using the gradient-boosting machine (GBM)-learning method. The GBM model was optimized further by adjusting the learning rate and the number of trees and 10-fold cross-validation. RESULTS: Total 10,320 patients (mean age 45.18 ± 14.82 years; 69% men) were included in the study. In the overall population, 1152 (11.2%) patients had at least one adenoma. In patients with age > 50 years, hospital-based adenoma prevalence was 19.5% (808/4144). The area under the receiver operating curve (AUC) (SD) of the logistic regression model was 72.55% (4.91), while the AUCs for deep learning, decision tree, random forest and gradient-boosted tree model were 76.25% (4.22%), 65.95% (4.01%), 79.38% (4.91%) and 84.76% (2.86%), respectively. After model optimization and cross-validation, the AUC of the gradient-boosted tree model has increased to 92.2% (1.1%). CONCLUSIONS: Machine-learning models may predict colorectal adenoma more accurately than logistic regression. A machine-learning model may help optimize the use of colonoscopy to prevent colorectal cancers. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT04512729).

Crosslinked hydrogel-derived carbons activated by trace amounts of aqueous potassium carbonate for carbon dioxide adsorption.

A new method for green synthesis of activated carbon using chitosan-based hydrogel precursors is reported. Chitosan-based hydrogel materials are designed to absorb trace amounts of non-toxic and non-corrosive activating agent K2CO3 from dilute aqueous solution. The K2CO3 impregnated hydrogels are further freeze-dried and converted to activated carbons with tuneable pore structure by a single-step pyrolysis. Activated carbon with highest pore volume of 0.76 cm3/g and surface area of 2026 m2/g is obtained by using K2CO3 as low as 0.23 g per gram of chitosan hydrogel. It can adsorb maximum CO2 of 4.2 mmol/g at 25 °C and 1 bar. This study demonstrates that biopolymer hydrogels impregnated with trace amounts of K2CO3 are excellent precursor materials to design high surface area carbons for CO2 capture.

Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma / El valor de ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico del glioma

Background: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. Methods: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan–Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. Results: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis.Conclusions: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients.(AU)

Introducción: Los gliomas presentan una alta incidencia y un mal pronóstico, por lo que es necesario un tratamiento más efectivo. Algunos estudios han confirmado que los ARN no codificantes de cadena larga (ARNncl) regulan diferentes enfermedades, entre las que se incluyen los gliomas. Se ha postulado que HAS2-AS1 actúa como un ARNncl, con un efecto oncogénico en diferentes tipos de cáncer. Este estudio tiene como objetivo analizar el valor del ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico de glioma. Métodos: Descargamos los datos clínicos y de expresión de micro-ARN de la base de datos del Atlas del Genoma del Cáncer (TCGA) para realizar el análisis diferencial y de supervivencia. También analizamos la expresión de HAS2-AS1 en muestras patológicas y muestras de tejido adyacente normal de 80 pacientes con glioma. Para analizar la capacidad diagnóstica y el valor pronóstico de HAS2-AS1 en el glioma, recurrimos a la curva ROC. También utilizamos curvas de Kaplan-Meier para evaluar la supervivencia de los pacientes con glioma con diferentes niveles de expresión de HAS2-AS1. Resultados: La expresión de HAS2-AS1 era significativamente mayor en las muestras patológicas que en el tejido normal. Las curvas de supervivencia demostraron que la sobreexpresión de HAS2-AS1 estaba relacionada con una menor supervivencia general y supervivencia libre de progresión. Algunos factores clínico-patológicos de los pacientes con glioma, como el tamaño del tumor y su grado, según la clasificación de la OMS, mostraron una correlación significativa con la expresión de HAS2-AS1 en los tejidos afectados. La curva ROC mostró un área bajo la curva de 0,863, lo que indica que la expresión de HAS2-AS1 posee un importante valor diagnóstico. El área bajo la curva de la supervivencia general estimada fue de 0,906; para la supervivencia libre de progresión estimada, de 0,88. Ambos valores muestran que la sobreexpresión de HAS2-AS1 se asocia con un mal pronóstico...(AU)

Biflanged metal stents versus plastic stents for endoscopic ultrasound-guided drainage of walled-off necrosis: a randomized controlled trial.

BACKGROUND: Endoscopic ultrasound (EUS)-guided drainage of walled-off necrosis (WON) using either plastic or metal stents is the mainstay of WON management. Our single-center randomized controlled trial aimed to evaluate the efficacy of biflanged metal stents (BFMSs) and plastic stents for WON drainage. METHODS: Patients with symptomatic WON amenable to EUS-guided drainage were randomized to receive either BFMSs or plastic stents. The primary outcome was reintervention-free clinical success at 4 weeks. Secondary outcomes were: overall clinical success (complete resolution of symptoms and significant reduction in size of WON [<50% of original size and <5 cm in largest diameter at 4-week follow-up]); number of reinterventions; adverse events (AEs); hospital stay for first admission; and medium-term outcomes at 6 months (recurrence, disconnected pancreatic duct, chronic pancreatitis, and new-onset diabetes mellitus). RESULTS: 92 patients were randomized: 46 in each arm. The reintervention-free clinical success rate was significantly higher in the BFMS group on intention-to-treat analysis (67.4% vs. 43.5%; P = 0.02). Overall clinical success at 1 month was similar in both groups. There were significantly fewer reinterventions (median 0 [IQR 0-1] vs. 1 [0-2]; P = 0.03) and shorter hospital stays in the BFMS group (7.0 [SD 3.4] vs. 9.1 [5.5] days; P = 0.04). There were no differences in procedure-related AEs, mortality, or medium-term outcomes. CONCLUSIONS: BFMSs provide better reintervention-free clinical success at 4 weeks, with shorter hospital stay and without increased risks of AEs, compared with plastic stents for EUS-guided drainage of WON. Medium-term outcomes are however similar for both stent types.

AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach.

Heart disease is a major global cause of mortality and a major public health problem for a large number of individuals. A major issue raised by regular clinical data analysis is the recognition of cardiovascular illnesses, including heart attacks and coronary artery disease, even though early identification of heart disease can save many lives. Accurate forecasting and decision assistance may be achieved in an effective manner with machine learning (ML). Big Data, or the vast amounts of data generated by the health sector, may assist models used to make diagnostic choices by revealing hidden information or intricate patterns. This paper uses a hybrid deep learning algorithm to describe a large data analysis and visualization approach for heart disease detection. The proposed approach is intended for use with big data systems, such as Apache Hadoop. An extensive medical data collection is first subjected to an improved k-means clustering (IKC) method to remove outliers, and the remaining class distribution is then balanced using the synthetic minority over-sampling technique (SMOTE). The next step is to forecast the disease using a bio-inspired hybrid mutation-based swarm intelligence (HMSI) with an attention-based gated recurrent unit network (AttGRU) model after recursive feature elimination (RFE) has determined which features are most important. In our implementation, we compare four machine learning algorithms: SAE + ANN (sparse autoencoder + artificial neural network), LR (logistic regression), KNN (K-nearest neighbour), and naïve Bayes. The experiment results indicate that a 95.42% accuracy rate for the hybrid model's suggested heart disease prediction is attained, which effectively outperforms and overcomes the prescribed research gap in mentioned related work.

Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma.

BACKGROUND: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. METHODS: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. RESULTS: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. CONCLUSIONS: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.

Pediatric suicide: Review of a preventable tragedy.

Concepts of suicide are explored in this issue with a focus on suicide in children and adolescents. The epidemiology of pediatric suicide in the United States is reviewed; also, risk and protective factors, as well as prevention strategies, are discussed. Suicide in the pediatric athlete and the potential protective effect of exercise are examined. In addition, this analysis addresses the beneficial role of psychological management as well as current research on pharmacologic treatment and brain stimulation procedures as part of comprehensive pediatric suicide prevention. Though death by suicide in pediatric persons has been and remains a tragic phenomenon, there is much that clinicians, other healthcare professionals, and society itself can accomplish in the prevention of pediatric suicide as well as the management of suicidality in our children and adolescents.

Assessing the Efficacy of a Novel Massive Open Online Soft Skills Course for South Asian Healthcare Professionals.

In healthcare professions, soft skills contribute to critical thinking, decision-making, and patient-centered care. While important to the delivery of high-quality medical care, soft skills are often underemphasized during healthcare training in low-and-middle-income countries. Despite South Asia's large population, the efficacy and viability of a digital soft skills curriculum for South Asian healthcare practitioners has not been studied to date. We hypothesized that a web-based, multilingual, soft skills course could aid the understanding and application of soft skills to improve healthcare practitioner knowledge, confidence, attitudes, and intent-to-change clinical practice.In September 2019 a needs assessment observing soft skills practices was conducted in several Indian states. We developed a communication-focused soft skills curriculum that comprised seven 10-minute video lectures, recorded in spoken English and Hindi. Participants consisted of any practicing healthcare professionals and trainees in select South Asian countries age 18 and over. Participant knowledge, confidence, attitudes, and intent-to-change clinical practice were evaluated using pre- and post-course tests and surveys. Statistical analyses were performed using STATA and SPSS.From July 26, 2021 to September 26, 2021, 5750 registered and attempted the course, 2628 unique participants completed the pre-test, and 1566 unique participants completed the post-test. Participants demonstrated small but statistically significant gains in confidence (𝑝<0.001), attitudes toward course topics relevance (𝑝<0.001), and intent-to-change clinical practice (𝑝<0.001). There was no statistically significant gain in knowledge. A digital soft-skills massive open online course for healthcare practitioners in South Asia could serve as a viable approach to improve the quality of soft skills training in low-to-middle income countries.

Precision in stereochemistry: the integral role of catalytic asymmetric Biginelli reaction in crafting enantiomerically pure dihydropyrimidinones.

One well-known multicomponent reaction that is helpful in the synthesis of dihydropyrimidinones (DHPMs), important molecules in organic synthesis and medicinal chemistry, is the Biginelli reaction. Because of their wide range of biological activities, DHPMs are regarded as essential chemicals. A great deal of research has been done in the last few decades to find ways to produce enantiomerically pure DHPMs because of their notable and focused target-oriented biological activities. In this reaction, numerous structural variants and catalysts have been employed in a range of solvents to yield an enormous number of Biginelli-type compounds. In the present review, the available catalysts in the literature including ionic liquids, Lewis acids, and organocatalysts for the Biginelli reaction and synthesis of a large number of asymmetric compounds since 2003 are summarized.

Tofacitinib use in ulcerative colitis: An expert consensus for day-to-day clinical practice.

Rising number of inflammatory bowel disease (IBD) cases in developing countries necessitate clear guidance for clinicians for the appropriate use of advanced therapies. An expert consensus document was generated to guide the usage of tofacitinib, a Janus kinase inhibitor, in ulcerative colitis. Tofacitinib is a useful agent for the induction and maintenance of remission in ulcerative colitis. It can be used in the setting of biological failure or even steroid-dependent and thiopurine refractory disease. Typically, the induction dose is 10 mg BD orally. Usually, clinical response is evident within eight weeks of therapy. In those with clinical response, the dose can be reduced from 10 mg BD to 5 mg BD. Tofacitinib should be avoided or used cautiously in the elderly, patients with cardiovascular co-morbidity, uncontrolled cardiac risk factors, previous thrombotic episodes and those at high risk for venous thrombosis or previous malignancy. Baseline evaluation should include testing for and management of hepatitis B infection and latent tuberculosis. Where feasible, it is prudent to ensure complete adult vaccination, including Herpes zoster, before starting tofacitinib. The use of tofacitinib may be associated with an increased risk of infections such as herpes zoster and tuberculosis reactivation. Maternal exposure to tofacitinib should be avoided during pre-conception, pregnancy, and lactation. There is emerging evidence of tofacitinib in acute severe colitis, although the exact positioning (first-line with steroids or second-line) is uncertain.

WHOOPH: whale optimization-based optimal placement of hub node within a WBAN.

Biosensor nodes of a wireless body area network (WBAN) transmit physiological parameter data to a central hub node, spending a substantial portion of their energy. Therefore, it is crucial to determine an optimal location for hub placement to minimize node energy consumption in data transmission. Existing methods determine the optimal hub location by sequentially placing the hub at multiple random locations within the WBAN. Performance measures like link reliability or overall node energy consumption in data transmission are estimated for each hub location. The best-performing location is finally selected for hub placement. Such methods are time-consuming. Moreover, the involvement of other nodes in the process of hub placement results in an undesirable loss of network energy. This paper shows the whale optimization algorithm (WOA)-based hub placement scheme. This scheme directly gives the best location for the hub in the least amount of time and with the least amount of help from other nodes. The presented scheme incorporates a population of candidate solutions called "whale search agents". These agents carry out the iterative steps of encircling the prey (identifying the best candidate solution), bubble-net feeding (exploitation phase), and random prey search (exploration phase). The WOA-based model eventually converges into an optimized solution that determines the optimal location for hub placement. The resultant hub location minimizes the overall amount of energy consumed by the WBAN nodes for data transmission, which ultimately results in an elongated lifespan of WBAN operation. The results show that the proposed WOA-based hub placement scheme outperforms various state-of-the-art related WBAN protocols by achieving a network lifetime of 8937 data transmission rounds with 93.8% network throughput and 9.74 ms network latency.

Comparing the efficacy of coefficient of variation control charts using generalized multiple dependent state sampling with various run-rule control charts.

This paper aimed to develop a coefficient of variation (CV) control chart utilizing the generalized multiple dependent state (GMDS) sampling approach for CV monitoring. We conducted a comprehensive examination of this designed control chart in comparison to existing control charts based on multiple dependent state sampling (MDS) and the Shewhart-type CV control chart, with a focus on average run lengths. The results were then compared to run-rule control charts available in the existing literature. Additionally, we elucidated the implementation of the proposed control chart through concrete examples and a simulation study. The findings clearly demonstrated that the GMDS sampling control chart shows significantly superior accuracy in detecting process shifts when compared to the MDS sampling control chart. As a result, the control chart approach presented in this paper holds significant potential for applications in textile and medical industries, particularly when researchers seek to identify minor to moderate shifts in the CV, contributing to enhanced quality control and process monitoring in these domains.

Exploring the potential of neem and tamarind gum as release retardants: Design and statistical optimisation of vildagliptin extended release matrix systems using D-optimal quadratic mixture design.

Exploring the significant role of natural polymers in developing drug delivery systems has been a promising area of research interest. The current investigation uses a D-optimal quadratic mixture design to design and evaluate neem and tamarind gum-based vildagliptin extended-release matrix tablets. Studying the combination effect of gums is one of the major objectives. Initial screening studies were performed to select the factors and their levels. The variables selected at different levels in mg/tablet are neem gum, tamarind gum, polyvinylpyrrolidone, and lactose monohydrate. Based on the screening experiments with both gums, the polymer content of 165 mg was chosen as the highest level in the DOE. Nineteen runs were generated to screen the desired parameters as responses. The total weight of the formulation was kept constant at 275 mg. Time (hours) required for 50 %, 90 % and 100 % of drug release and tablet hardness were selected as the responses for each run. The wet granulation method was adopted, and the critical variables were optimised using the design of experiments following Design Expert software. Statistical analysis was conducted, and the optimised formulations were prepared and evaluated to compare with the predicted responses. Stability studies were performed for the optimised batches. Results indicated that the prepared batches met the compendial limits and confirmed the application of neem and tamarind gum in the development of extended-release tablets of vildagliptin for 24 h. An optimised formulation comprising of 16.52 mg of neem gum and 148.48 mg of tamarind gum with a hardness of 7.5-8.5 kp produced 50 %, 90 % and 100 % drug release in 12, 22 and 25 h.

Cracking the Code of Lumpy Skin Disease: Identifying Causes, Symptoms and Treatment Options for Livestock Farmers.

The novel bovine viral infection known as lumpy skin disease is common in most African and Middle Eastern countries, with a significant likelihood of disease transfer to Asia and Europe. Recent rapid disease spread in formerly disease-free zones highlights the need of understanding disease limits and distribution mechanisms. Capripox virus, the causal agent, may also cause sheeppox and Goatpox. Even though the virus is expelled through several bodily fluids and excretions, the most common causes of infection include sperm and skin sores. Thus, vulnerable hosts are mostly infected mechanically by hematophagous arthropods such as biting flies, mosquitoes, and ticks. As a result, milk production lowers, abortions, permanent or temporary sterility, hide damage, and mortality occur, contributing to a massive financial loss for countries that raise cattle. These illnesses are economically significant because they affect international trade. The spread of Capripox viruses appears to be spreading because to a lack of effectual vaccinations and poverty in rural areas. Lumpy skin disease has reached historic levels; as a consequence, vaccination remains the only viable option to keep the illness from spreading in endemic as well as newly impacted areas. This study is intended to offer a full update on existing knowledge of the disease's pathological characteristics, mechanisms of spread, transmission, control measures, and available vaccinations.