bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic review of involvement and practice of community pharmacy professionals in child health services
Authors: Sinha Rashmi , Kumar Sahu Kishor
Published: February 2025

Community Pharmacists (CPs) play a crucial role in delivering Child Health Services (CHS); the extent of their participation, practices, and the challenges and facilitators to providing these amenities remain largely unexamined. This study aims to consolidate existing research regarding the involvement and role of CPs in maternal and CHS. Seven online databases were queried for articles published in English from the records' creation. Studies were selected based on the evaluation of the participation and procedures of CPs in mothers and CHS. All full papers selected for the final analysis were assessed for quality utilizing the Mixed Method Assessment Tool (MMAT), with data extraction performed and verified. A total of 2900 articles were identified. After evaluating the inclusion standards, 14 full-text papers were selected for the final study. Eight research investigations indicated that CPs participated in maternal wellness programs by offering breastfeeding direction, counseling on the advantages of vitamins throughout pregnancy, providing immediate contraception suggestions, and addressing signs of disease such as backache. Three research investigations examined CPs offering guidance on managing acute diarrhea in children. Three investigations additionally provided information on prescription drug counseling and medications for children. CPs identified the perceived opinions of customers, issues with health insurance, time constraints, and inadequate rewards for treatments rendered as the primary obstacles to service delivery. CPs participated in many maternal and CHS within CP environments. The implementation of practices did not align with the combined Federation of International Pharmacy (FIP)/World Health Organization (WHO) recommendations on optimal pharmacy procedures for certain services, including managing symptoms of diarrhea.
Smartphone-based application for preventing medication errors among pediatric nurses
Authors: Kumar Jaiswal Vinay , Srinivasa Rao Varri
Published: February 2025

Medication Errors (MEs) harm patient safety incidents across all age demographics. Medical emergencies are incredibly perilous in the juvenile demographic, especially for individuals necessitating specialized care due to the elevated frequency and severity of illness. This research sought to assess the impact of a smartphone messaging application on medical students' education concerning the avoidance of MEs in kids. This quasi-experimental research was conducted with 85 nursing pupils arbitrarily assigned to intervention and control categories. Data was obtained via a researcher-developed checklist. The research engaged with learning via Telegram, a smartphone messaging service, for three weeks. Information was examined using SPSS, employing descriptive and inferential statistics, with P < 0.04 deemed significant. The average age of the pupils was 25.4 ± 3.1 years. The predominant MEs associated with medicine events in the control categories encompassed inadequate management of the following MEs: management of high-risk medications, identification of medication incompatibilities, utilization of prescribing cards, estimation of medication dosages, understanding of adverse drug reactions, acknowledgment of pharmaceutical names during drug choice, compliance with clean and sterile techniques, practices for flushing microbore intravenous tubing, modification of intravenous drip rates, and adhering to medication management. The median scores of pupils regarding knowledge of avoiding MEs were markedly different among the two groups. Using the Telegram messaging software for smartphone learning enhances nursing students' understanding of preventing MEs in children's hospitals. The research advocates for implementing this learning method in nursing colleges to mitigate the MEs associated with drug placing an order, dosage, and delivery.
The spread of water-borne disease and aquatic: understanding the link between ecosystem health and human well-being
Authors: Gurudiwan Prachi , Kumar Sahu Mahendra
Published: February 2025

Water-borne infections, which are spread by tainted water sources, have long been a serious health risk, especially in areas where water quality is poor. This study highlights the connection between environmental and human well-being by examining the complex relationship between the prevalence of water-borne illnesses and the health of aquatic ecosystems. Degradation of ecosystems, which includes pollution, habitat loss, and climate change, makes it easier for pathogens to spread in water bodies, raising the risk of illnesses like cholera, dysentery, and typhoid fever. To demonstrate how ecosystem health directly affects the availability of clean water and the spread of diseases, this study will look at case studies and the most recent scientific findings. This study offers a comprehensive approach to public health protection by highlighting the significance of ecosystem restoration and sustainable water management practices in preventing water-borne illnesses. Subsequently, to build resilient communities and enhance global health outcomes, it is critical to recognize and address the connections between the health of aquatic ecosystems and human well-being.
Pharmacokinetics and pharmacodynamics of medications used in pregnant women: a systematic review
Authors: Kumar Sahu Deepak , Srinivasa Rao Varri
Published: February 2025

Most pregnant ladies will get treatment all through pregnancy with a medication other than a nutrient enhancement. As per the past US Food and Medication Organization grouping framework, almost 50% of these medications will fall into either classification C or D, which means an absence of human examination with creature review showing negative fetal impacts (class C) or verification of hazard in people (class D). Drug assimilation, circulation, freedom, and thusly the medication half-life is totally impacted in oftentimes unanticipated ways by changes in maternal physiology. Pregnancy-related pharmacokinetic and pharmacodynamic information are poor for some drugs. Ebb and flow dosing rules for different drugs don't consider new exploration that show huge pharmacokinetic or pharmacodynamic changes that call for portion changes during pregnancy. The standards basic the pharmacological and physiological changes that happen during pregnancy are examined in this outline, alongside subtleties on meds that are much of the time utilized while treating pregnant patients.
Assessing the impact of medication nonadherence on pregnancy outcomes in women with chronic medical conditions
Authors: Jaiswal Harish , Syed Sabir Ali Syed Sajid Ali
Published: February 2025

Utilizing a cross country delegate accomplice, this study looked to examine the impacts of solution volume and long stretches of enhancement for adherence to antihypertensive medicine in a certifiable situation. Observational spotlight on 100 pregnant ladies with either gestational hypertension or constant hypertension getting treatment with around one antihypertensive medicine and going to pre-birth care at one of two maternity facilities. The typical age was 60.3 ± 12.6 years, and the typical number of drugs was 4.1 ± 2.2. Of every one of our members, 66.9% (N = 100,645) were devotees (MPR ≥ 80%), with a mean MPR of 80.4 ± 23.9%. A changed U-shape with a top at three or four medications addressed the general pattern of antihypertensive drug adherence as estimated by the complete number of meds. Up until age 69, adherence reliably expanded with age, then beginning at age 70, it began to decline. A changed U-shape with a top at three to four medications was likewise found in the degree of supporter patients (MPR ≥ 80%) as per the all-out number of meds. The degree of supporter patients, as shown by age, contained a changed U-shape with a top at 60 to 69 years of age when a practically identical amount of medications where taken.
Development of a clinical pharmacy service for high-risk pregnant women: a quality improvement study
Authors: Sharma Poorti , Chandrakar Kunal
Published: February 2025

The purpose of this survey was to break down CPs' data and deals with issues related to repairs and taste attainment throughout pregnancy. In the same way that clinical pharmacy organizations may assist with cure security and the board, they can also assist with patient advice and defilement express the leaders. In a non-current nation, a cross-sectional poll was conducted using a free report. The overwhelming majority of responders (71.0%) did not participate in steady master new development (CPD), and 89.9% paid little attention to receiving a lengthy confirmation. Providing solutions to self-assured mothers addressed over thirty-three percent of the CP duty. When there are weaknesses, the majority of respondents revealed that they contact a comforting, knowledgeable authority (51.2%), suggest reliable sources (82.6%), and obtain some information about their pregnancy status (59.9%). A higher data score was linked to receiving guidance from graduated class schools and continuing professional development programs. The majority of CPs protected folic acid, paracetamol, and amoxicillin, but prescription drugs that were hostile to pollution, such as ibuprofen, isotretinoin, enalapril, and pseudoephedrine, were viewed as dangerous everywhere. Senna, St. John's wort, castor oil, and ginseng were the flavors most frequently mentioned as harmful. Despite the gaps in knowledge regarding punch pharmacology, CPs offered interesting information and research on calm security throughout pregnancy. CPD is advised to keep an eye out for opportunities.
Impact of pharmacist-led interventions on influenza vaccination rates in high-risk populations
Authors: Gupta Khushboo , Kumar Sahu Kishor
Published: February 2025

Two pandemic outbreaks of H1N1 influenza have occurred in the past century: the Spanish flu in 1918 and the swine flu in 2009. It has been the most common human influenza virus subtype, causing a considerable amount of illness and mortality on a global scale. Antiviral prophylaxis is used in the event of unexpected influenza outbreaks to immediately stop the virus's spread. However, the effectiveness of antiviral medications in treating influenza appears questionable because drug-resistant strains are becoming more prevalent. Additionally, currently existing influenza vaccinations are strain-specific and need to be periodically reformulated to incorporate a combination of the strains of the influenza A and B viruses that are now in circulation. The development of a humoral immune response against the extremely changeable hemagglutinin protein is the issue with these vaccines. Furthermore, in the event of an unexpected epidemic, it is challenging to ensure their timely and sufficient availability. Therefore, the development of a more effective vaccine strategy that can provide universal or at least broad protection against the constantly evolving influenza virus strains in the global population is urgently needed.
Evaluating the long-term outcomes of metabolic surgery in obesity management: effects on weight loss, comorbidities, quality of life, and sustainability of surgical interventions
Authors: Bhanja Mrutyunjaya , Vaishnaw Aayush
Published: February 2025

Obesity has become a global health crisis, with significant associations to various comorbidities such as type 2 diabetes, cardiovascular diseases, and sleep apnea. While lifestyle changes and pharmacological treatments are commonly used for obesity management, metabolic surgery has emerged as a highly effective intervention. This study aims to evaluate the long-term outcomes of metabolic surgery in managing obesity, focusing on weight loss sustainability, improvement in comorbidities, quality of life, and the long-term sustainability of surgical interventions. The research is based on a retrospective analysis of patients who have undergone metabolic surgery, such as Roux-en-Y gastric bypass and sleeve gastrectomy, over a period of 5 to 10 years. The study examines several key outcomes, including sustained weight loss, resolution or improvement in comorbidities like type 2 diabetes, hypertension, and sleep apnea, and changes in the overall quality of life (QoL). Additionally, the study investigates complications, reoperation rates, and the long-term efficacy of these procedures. Findings reveal that metabolic surgery results in significant weight loss, with many patients maintaining a healthy weight long-term. The improvement or resolution of obesity-related comorbidities is prominent, particularly in the management of type 2 diabetes and hypertension. Quality of life scores show considerable improvements in both physical and psychological health. However, while metabolic surgery is associated with sustained benefits, the need for ongoing medical follow-up, dietary adjustments, and potential reoperations due to complications are important considerations for long-term success. This research highlights the importance of metabolic surgery as a transformative treatment for obesity and its comorbidities. It also underscores the necessity for a comprehensive post-surgery care plan to optimize long-term outcomes.
Comparative study of histopathological changes in chronic vs. acute inflammatory diseases
Authors: Ranjan Dash Smruti , Kumar Sahu Mahendra
Published: February 2025

Objective
To conduct a comparative study of histopathological changes in chronic versus acute inflammatory diseases. This research focuses on analyzing the cellular and tissue alterations observed in biopsies from patients suffering from chronic inflammatory conditions, such as chronic arthritis, and acute inflammatory conditions, such as acute infections.
Methods
A total of 200 tissue samples were collected from patients diagnosed with chronic and acute inflammatory diseases. Histopathological examinations were performed using hematoxylin and eosin (H&E) staining, along with specialized immunohistochemical techniques to assess specific inflammatory markers. Comparative analyses were conducted to evaluate tissue architecture, immune cell infiltration, fibrosis, and vascular changes.
Results
The study revealed distinct histopathological features for chronic and acute inflammatory diseases. Chronic inflammatory tissues exhibited persistent immune cell infiltration, fibrosis, and chronic tissue damage, whereas acute inflammation displayed rapid and transient cellular responses with increased vascular permeability and neutrophil infiltration. Additionally, chronic conditions showed greater tissue remodeling and structural damage compared to acute conditions.
Conclusion
This comparative analysis highlights the differences in tissue pathology between chronic and acute inflammatory diseases. Chronic inflammation is marked by prolonged tissue damage and a sustained immune response, while acute inflammation is characterized by a swift, transient reaction with pronounced vascular and cellular alterations. These findings provide valuable insights into disease progression and may guide the development of targeted therapeutic strategies for managing chronic and acute inflammatory conditions. Further studies are needed to explore the molecular pathways underlying these histopathological changes.
The role of psychosocial support in enhancing quality of life for cancer patients: challenges and solutions
Authors: Jaiswal Harish , Syed Sabir Ali Syed Sajid Ali
Published: February 2025

Cancer patients encounter many psychological, emotional, and physical obstacles during their diagnosis and treatment. Psychosocial support is essential for improving these people's overall quality of life, even though medical treatments like chemotherapy, radiation, and surgery are necessary for survival. Psychosocial support includes psychological, social, and emotional help for problems like social isolation, anxiety, depression, and coping strategies. In this essay, the significance of psychosocial support in cancer treatment is examined, with particular attention to how it affects both physical and emotional results. It looks at the different kinds of psychosocial interventions that help patients cope with the psychological effects of cancer and its treatments, such as peer mentoring, support groups, counseling, and stress-reduction techniques. Additionally, the paper discusses the obstacles that healthcare systems encounter in delivering sufficient psychosocial care, including a shortage of resources, a shortage of qualified personnel, and the stigma associated with mental health in oncology settings.
Exploring the role of genetic markers in disease progression and patient response to treatment
Authors: Bharti Sao Rupali , Chandrakar Kunal
Published: February 2025

One of the most important areas of research in contemporary medicine is the understanding of how genetic markers affect the course of disease and the response of patients to treatment. The impact of particular genetic variations on the course of different diseases is examined in this work, with an emphasis on how well they can forecast disease outcomes and direct treatment choices. Through the analysis of genetic data from patient cohorts across various disease types, such as autoimmune disorders, cardiovascular diseases, and cancer, the study finds important markers linked to suboptimal treatment responses and faster disease progression. The study also addresses the possibility of using these genetic markers to inform personalized medicine strategies, highlighting the necessity of tailored treatments that take a patient's genetic profile into account.
Advancements in neuroscience for healthcare: recent innovations and breakthroughs in mental health treatment
Authors: Sinha Rashmi , Kumar Sahu Kishor
Published: February 2025

The field of neuroscience has witnessed significant advancements in recent years, particularly in the realm of mental health treatment. This paper explores the latest innovations and breakthroughs in neuroscience that are shaping the landscape of mental health care. These advancements include the development of neuroimaging techniques, precision medicine approaches, and novel therapeutic interventions such as neurostimulation and neuromodulation. The integration of artificial intelligence (AI) and machine learning has further enhanced diagnostic accuracy and treatment personalization. This study provides a comprehensive overview of recent research, focusing on how these advancements are addressing various mental health disorders, including depression, anxiety, bipolar disorder, and neurodevelopmental disorders. Additionally, the ethical considerations and future challenges associated with these technologies are discussed. By fostering a deeper understanding of the underlying neural mechanisms, neuroscience is paving the way for more effective, targeted, and individualized mental health treatments.
Assessing the impact of mental health and sleep patterns on chronic disease progression: a longitudinal perspective
Authors: Kumar Mire Sanjay , Kumar Sahu Kishor
Published: February 2025

This longitudinal study aims to evaluate the influence of mental health and sleep patterns on the progression of chronic diseases, including cardiovascular conditions, diabetes, and obesity. Over a 10-year period, the study tracked the health and lifestyle behaviors of individuals from diverse demographic backgrounds. Participants' mental health status, including stress levels, anxiety, and depression, were assessed using validated psychological scales, while sleep quality and duration were monitored through both self-reported questionnaires and objective measures such as actigraphy. The progression of chronic diseases was tracked through medical records, biomarkers, and clinical assessments. The results indicate a significant correlation between poor mental health, insufficient or disrupted sleep, and accelerated chronic disease progression. Furthermore, the study highlights that individual who reported better mental health and consistent sleep patterns experienced slower disease progression and improved overall health outcomes. This research underscores the critical need for integrated mental health and sleep management strategies in the prevention and management of chronic conditions.
Histopathological insights for improving healthcare delivery in oncology
Authors: Dewangan Tripti , Vaishnaw Aayush
Published: February 2025

The integration of histopathological analysis in oncology has been pivotal in enhancing cancer diagnosis, prognosis, and treatment decisions. Histopathology, through microscopic examination of tissue samples, provides invaluable insights into tumor characteristics, helping clinicians determine the type, grade, and stage of cancer. This research examines the role of histopathological techniques in improving healthcare delivery in oncology, focusing on diagnostic accuracy, personalized treatment strategies, and patient outcomes. A cohort study involving 500 cancer patients (200 breast cancer, 150 colorectal cancer, and 150 lung cancer) was conducted to assess the impact of histopathological insights on clinical decision-making. The study demonstrated that incorporating histopathology into the diagnostic workflow led to a 15% improvement in the accuracy of cancer diagnoses compared to standard imaging techniques. Additionally, histopathological findings guided treatment plans, contributing to a 20% increase in personalized therapy application, which subsequently resulted in a 10% improvement in overall patient survival rates. Statistical analysis was conducted using SPSS software, employing chi-square tests to evaluate diagnostic accuracy, survival analysis (Kaplan-Meier method) to assess patient outcomes, and logistic regression to determine the association between histopathological data and treatment response. Results showed a statistically significant correlation (p < 0.05) between histopathological insights and improved healthcare delivery in oncology. The data suggest that histopathology can significantly influence therapeutic decisions, leading to more effective and individualized cancer treatment.
Innovative drug delivery systems from aquatic biomaterials: a new era in medical treatment
Authors: Singh Chiranjeev , Syed Sabir Ali Syed Sajid Ali
Published: February 2025

Innovative drug delivery mechanisms possess the capacity to overcome the constraints of traditional therapeutic methodologies by enhancing bioavailability, targeting accuracy, and minimizing adverse effects. Aquatic biomaterials, obtained from marine life such as algae, fish scales, and marine invertebrates, present distinct benefits for the creation of innovative drug delivery platforms. These biomaterials exhibit biocompatibility, biodegradability, and unique chemical and structural characteristics that render them suitable candidates for encapsulating and releasing therapeutic agents. This investigation examines the potential of aquatic biomaterials in the development of pioneering drug delivery systems, concentrating on their application in nanoparticle-based formulations, hydrogels, and microspheres. The analysis assesses the encapsulation efficiency, release dynamics, and therapeutic effectiveness of aquatic biomaterial-based systems, alongside their capability to target specific tissues or cells. Moreover, the biocompatibility and pharmacokinetic profiles of these systems are evaluated through in vitro and in vivo investigations. The results indicate that aquatic biomaterial-based drug delivery systems can substantially improve the stability, bioavailability, and controlled release of pharmaceuticals, with promising prospects in cancer treatment, antimicrobial interventions, and wound healing. This research emphasizes the potential of aquatic biomaterials to transform medical treatments and lay the groundwork for sustainable, effective, and personalized therapies.
A Novel Adam Hypertuned Artificial Neural Network Using Autoencoder Network Approach to Improve Software Defect Prediction Accuracy
Authors: Thenmozhi S. , Shanthi PM.
Published: February 2025

Defect prediction is a very active area in the software engineering field. It is crucial to bridge the gap between software engineering and data mining to ensure the programme's success. Predicting software flaws helps find faults in the code before testing is done. Cluster analysis, statistical approaches, mixed algorithms, neural network-based metrics, black box testing, white box testing, and machine learning are only some of the methods used to investigate the software effect area while trying to forecast defects in software. In order to improve the accuracy of deep learning classifiers for defects forecasting, this study makes a novel contribution by using feature selection for the first time. This research was conducted with the hope of enhancing the accuracy with which errors may be predicted in five NASA data sets: CM1, JM1, KC2, KC1, and PC1.Here initially the data was retrieved and processed using rounded mean regressor interpolation approach. Then for selecting feature information grain methodology was used. Dimensionality Component Analysis (DCA), Self-Regulating Component Analysis (SRCA), and Non-Negative Linear Matrix Factorization (NNLMF) were used to extract features from the recovered data . In order to improve upon previous techniques of defect prediction, we combine the factorization selection approach with the deep learning-based adam hypertuned ANN using autoencoder method. All of the tests were run in a python environment. This research shows that, in comparison to the currently used mechanisms, defect prediction accuracy may be increased by the application of feature selection.
Pt. Thiyagaraya Chettiyar: A Cooperative Pioneer in Indian Banking and Finance
Authors: Premalatha Mrs. G. , Mary Sr. S. Emelda
Published: February 2025

This research also evaluates the inputs of Mr. Pt.Thiyagaraya Chettiyar for his contribution towards the development of cooperative banking and finance in India and for his contributions shown in the spread of financial education, institution of cooperative lending schemes and successful formulation of policies and other executes leading to the human and socio-economic progress of the country. The research methodology used is a dual design type: descriptive and analytical. In so doing, this design methodology makes a systematic descriptive design capture of Pt. Thiyagaraya Chettiyar’s contributions to cooperative banking and financial development, while the analytical design explores the connections between social and economic consequences of his works in finance, particularly for excluded groups. The sample comprises 71 respondents who have been chosen randomly using a structured questionnaire that contains data from Cooperative Bank members and Financial Experts, Government Policymakers, and Academicians. The datasets were obtained through a set of identifiable questionnaires which included both close-ended questions and scale questions and the data were analyzed using the SPSS software. Other Statistical tests for inferences includes One-Way ANOVA, Independent Sample t-Test and Fried-man Test. It has been ascertained from the analysis that Pt. Thiyagaraya Chettiyar claims that the above contributions “I made can go a long way in improving great access to credit, financial literacy and socio-economic empowerment of women and the lower castes who suffered from false stigma”. He was the scrupulous force in the creation of Cooperative Banks since it offer independence to the rural and agrarian communities. The study therefore explores how his work is still relevant in the current cooperative banking and policies such as the question of social inclusion and fair credit. Pt. Thiyagaraya Chettiyar has provided a model for reforming and creating modern sustainable peace, today’s reform processes are forcibly distinguished by the example left by Chettiyar. The principles expounded by the author argue well to the existing issues in cooperative banking and financial evolution.
Energy Enhancement and Hotspot Mitigation for Wireless Sensor Network by Data Aggregation
Authors: Karthik N. , Kathiresan V.
Published: February 2025

A Wireless Sensor Network (WSN) is a network of distributed sensors, which are used to sense the physical environment and transmit information through wireless media. Data aggregation is very important in WSNs because it helps in minimizing on the number of transmitted data, hence saving power, and increasing the lifetime of the network. Due to the concentration of information at the intermediate nodes, it reduces the amount of traffic that has to be passed across the network, the amount of energy consumed, and increases the network utilization. The Poly disperses Steiner Minimum Tree-based Routing Protocol (PSMT-RP) protocol improves energy consumption and eliminates hotspots in WSNs by optimizing data aggregation with the help of the PSMT. Based on the concept of SMT, the proposed protocol reduces the length of the communication paths by choosing the proper intermediate nodes and thus, conserves energy and reduces latency. It adapts the node communication range to provide optimal data routing, thereby increasing the network duration and power consumption. Due to data aggregation at the intermediate nodes, it minimizes the transmission distances and prevents congestion which in turn fosters load balancing. Due to its efficiency in meeting Quality of Service (QoS) demands and in the management of energy resources, it is ideal to be implemented in large networks with limited energy supply. The simulation outcome is compared with existing state-of-art techniques whereas PSMT-RP outperforms and achieves high throughput with minimal energy consumption.
AI-powered chatbots for pharmacy-based patient education and counseling
Authors: Pal Tarun , Chandrakar Kunal
Published: February 2025

The increasing demand and use of technology has led to the convergence of technology with health and diagnostic procedures. Digital health is the use of technology and information to enhance and alleviate health issues, as the name suggests. The Indian healthcare industry is changing as a result of wearable technology, telemedicine, genomics, virtual reality (VR), robotics, and artificial intelligence (AI). India is poised for a "digital health" revolution, much like many other economies. (Digital Health Report, 2020: Informa Markets' Indian Health). The use of digital health technologies has become essential to the provision of healthcare. The health technology sector, which includes wearables, telemedicine, e-pharmacies, and other products, has grown recently all over the world. Additionally, a lot of research and development has gone into integrating technology like blockchain, virtual reality, robots, and artificial intelligence with medications and healthcare. Healthcare is the biggest industry in India and has a lot of room to grow. This market is driven by the modern world's increasing need for digital healthcare solutions.
Developing a data-driven approach to optimizing pharmacy inventory management
Authors: Anand Das Vaishnav Venu , Patel Ritesh
Published: February 2025

The stock of products, commodities, or other financial resources that are kept or set aside for future production or to satisfy future demand is known as inventory. For example, inventory can include raw materials that are awaiting use in the creation of items, finished goods that are awaiting shipping from the factory, wholesaler, or retailer, and semi-finished or in-process goods that are temporarily held throughout the production process. Equipment, furnishings, fittings, etc. are also included in inventory. Direct and indirect inventories are two categories under which the term inventory can be separated. Items that directly contribute to the manufacturing process and are a necessary component of final goods are included in direct inventories. Raw materials, work-in-progress, and finished commodities are the three categories into which direct inventories can be divided. Items that are required for manufacturing but do not end up in the final product, such as lubricants, grease, oil, gasoline, office supplies, maintenance supplies, etc., are included in indirect inventories. Although there are many reasons why inventories are kept, they generally serve the following fundamental purposes.
Using data mining techniques to identify factors associated with medication non-adherence
Authors: Kumar Jaiswal Vinay , Srinivasa Rao Varri
Published: February 2025

Techniques for data mining and machine learning have recently become widely used in the healthcare industry. The goal of this research is to create an automated method of disease diagnosis. Here, three distinct methods for disease diagnosis utilizing data mining techniques are proposed: the hybrid fuzzy decision making tree approach, the association rule-based approach, and the efficient hybrid approach. The first strategy suggests an effective hybrid technique to lower the number of outliers. In data mining, outlier detection is a current study topic. The items that reside outside of the clusters are highlighted and identified as outliers if clustering techniques are applied. However, a small number of unidentified pieces might be added to the cluster. Therefore, it becomes vital to identify and remove such data that has been merged with the clusters in order to fully remove the unnecessary data from the dataset. The suggested method uses two datamining methods, Multilayer Neural Networks (MLN) and density-based K-means, to find outliers in a data set. When evaluated on the UCI repository, the suggested system outperforms the current ones in terms of disease prediction. The classification accuracy has increased while the time complexity has decreased.
Developing a computer vision system for automated medication identification and verification
Authors: Dewangan Hemlata , Nirmal Chandu Himanshu
Published: February 2025

Drug repurposing is the process by which novel medications are discovered to cure or prevent illness. Furthermore, biological research has benefited from the astounding advancements in medicine brought about by new and sophisticated technologies. In order to better utilize the vast quantity of biological data that is currently available and to reduce the time and cost associated with the drug discovery and development process, numerous computational techniques are being used. As a result, attempts are being made to carry out drug repurposing, which comprises developing new uses for previously approved medications. To find new approaches for this kind of innovation, a number of computer techniques have been developed to forecast drug-target interactions (Drug target Interactions). Because the data sets gathered from Drug and Targets were so complex, traditional machine learning techniques like linear regression analysis were unable to analyze them effectively. Presenting several machine learning categorization models is the aim of this thesis. This thesis's experiments and assessments show the development of an integrative machine learning model for predicting and finding novel biomedical relationships from both text datasets.
Access to essential medicines in low-resource settings: a systematic review
Authors: Bhanja Mrutyunjaya , Vaishnaw Aayush
Published: February 2025

Almost 2 billion people worldwide lack access to necessary medications. This indicates that for over 25% of the global population, vital medications are either inaccessible, unaffordable, unsatisfactory, or of poor quality. By presenting fresh research findings from low- and middle-income countries (LMICs), this supplement illustrates the consequences of inadequate access to medications and emphasizes contemporary solutions to increase access to vital medicines. These research provide answers to important concerns like: Can performance-based financing increase access to necessary medications? How much do pediatric cardiovascular therapies cost? Which nations' legal systems support widespread access to pharmaceuticals? To what extent do people use medications appropriately? Does equity suffer from subpar medications? Since critical medications are key to the Sustainable Development Goals and central to the pursuit of Universal Health Coverage, the answers to these concerns are crucial. In order to lower the cost of care, avoid increased pain and suffering, decrease the length of sickness, and prevent unnecessary impairments and deaths globally, access to reasonably priced, high-quality vital medications is needed. Health Systems Global's Medicines in Health Systems Thematic Working Group, a membership organization devoted to advancing health systems research and knowledge translation, developed this supplement. By highlighting recent achievements and difficulties in expanding access to quality-assured medications through health systems in LMICs, the five papers in the supplement deepen our understanding.
Evaluating the Impact of Medicaid Expansion on Pharmacy Access and Health Outcomes
Authors: Nanda Naimish , Syed Sabir Ali Syed Sajid Ali
Published: February 2025

Any noxious and unintended response to a drug that occurs at doses used in man for the prophylaxis, diagnosis or therapy of disease, or for the modification of physiological function" is how the World Health Organization defines an adverse drug reaction (ADR). Adverse drug responses, or ADRs, are undesirable or harmful side effects of a medication. In addition to drug factors like drug type, dosage, length of treatment, co-ingestion of other drugs, and route of administration, patient characteristics like age, gender, body weight, coexisting diseases, ethnicity, genetics, or geography also affect the frequency and severity of adverse drug reactions (ADRs). The purpose of this project is to identify, assess, manage, document, and share adverse drug responses. The current investigation determined the ADR pattern that the patients on ATT experienced. The incidence of ADRs was greater in males. The most frequent ADRs were related to the gastrointestinal tract. The majority of ADRs had a "possible" link with the implicated medications, according to an assessment of their causality. The majority of ADRs had "mild" severity. During the trial period, no serious, life-threatening adverse drug reactions were noted. For pupils to do well, procrastination is essential. The reviews of previous studies by researchers are included in the second chapter. The third chapter also provides examples of the study's methodology, which will outline the subjects being examined and the selection process for them. Additionally, the substance of the instrument that will be used to gather information will be described. Analyzing links or differences, separating or comparing with original or new hypotheses, and applying statistical tests of significance are all part of the fourth chapter, which aims to ascertain the validity of the data used to support any conclusions. The research conclusion is the final chapter.
Development and implementation of a pharmacy – led perioperative medication management service: a quality improvement study
Authors: Jaiswal Harish , Syed Sabir Ali Syed Sajid Ali
Published: February 2025

The practice of optimizing a patient's medications before to, during, and following surgery in order to reduce risks and guarantee the best results is known as perioperative medication management. This entails a thorough examination of the patient's prescription schedule, the detection of any possible drug-related problems, and the application of risk-reduction techniques. Coordination of the intricate procedures and the participation of the whole care team are necessary in the perioperative arena, which is a special and difficult setting. The extent of training for drug specialists has been expanding to include perioperative settings and to become more patient-centered. One of the most difficult and complicated places in a hospital, the perioperative setting poses serious safety hazards. The complex and error-prone nature of medication management during the perioperative phase leads to poor patient outcomes and the potential for adverse drug events (ADEs). Pharmacist involvement in perioperative care has been shown to increase medication safety, but its use is still neglected. This study aimed to develop, implement, and evaluate a pharmacy-led perioperative medication management service to improve drug safety, patient adherence, and the overall standard of perioperative care.
Investigating the effects of intraoperative fluid management on postoperative outcomes in surgical patients: a prospective cohort study
Authors: Sharma Poorti , Chandrakar Kunal
Published: February 2025

Although fluid therapy is essential to intraoperative anesthesia, there is still much disagreement over the exact kind, quantity, and timing of its administration. Nearly every patient who comes in for general anesthesia will receive some kind of intravenous fluid. Perioperative hydration treatment has been shown to have a significant impact on long-term postoperative results. Recent evidence-based, customized goal-directed treatment (GDT) is challenging the traditional practice of administering huge amounts of crystalloid fluid intraoperatively to every patient. The process of giving fluids during surgery to preserve organ perfusion and blood flow is known as intraoperative fluid management. It entails deciding what kind, how much, and when to administer the fluid. The study evaluates the relationship between intraoperative fluid management and the postoperative outcomes of surgical patients.
A systematic review and analysis of medication education for medication misuse in children
Authors: Dewangan Hemlata , Nirmal Chandu Himanshu
Published: February 2025

The research carefully assessed evidence of educational strategies concerning prescription and nonprescription drugs for kids in school. Search criteria concentrated on demographic schooling, kids in school, and pharmaceuticals. Research was omitted if it pertained to a specific illness state, type of drugs, substances of misuse, or illegal substances. The data extraction encompassed study design, position, educational treatment and time frame, study techniques, and principal findings. The research identified 15 studies corresponding to 9 distinct programs. Six initiatives were recognized in the gray research. Projects varied from solitary sessions to nationwide initiatives. Quantitative research demonstrated enhancements in understanding, medicine literacy, and trust. Implementing medication teaching initiatives relied on the educator's confidence and convictions about the security of medications. Reliable pharmaceutical education options exist and have demonstrated an enhancement in knowledge among learners. A necessity persists for comprehensive implementation and assessment strategies. Methods and resources exist to execute initiatives within neighborhoods to enhance medication education among kids. Structures ought to be employed to improve the execution of successful health promotion programs regarding prescription drugs for pupils in school.
A prospective study of metformin effectiveness as a mammalian target of rapamycin inhibitor and immunoregulator in women with polycystic ovarian syndrome
Authors: Moslim Allawi Asmaa , Waleed Mustafa Nisreen , Mohammed Hadi Ali
Published: February 2025

Background
Polycystic ovarian syndrome (PCOS) is a common disorder affecting ovary function. it’s thought that an autoimmune regulatory mechanism could mediate its onset. Metformin is an effective medication for PCOS treatment and is proposed to act as an immunoregulatory drug.
Objective
The present work aimed to study the effectiveness of metformin as a mammalian target of rapamycin (mTOR) inhibitor and immunoregulator in PCOS women.
Subjects and Methods
A total of 80 blood samples were collected, 30 of them from newly diagnosed PCOS women. Once more, blood samples were taken from them following 500 mg of metformin treatment period. In addition, 20 healthy women enrolled as a control group. The levels of mTOR, IL6, and TGFβ1 were measured using the ELISA technique.
Results
The present work showed that after metformin treatment, levels of mTOR and TGFβ1 dropped significantly, but IL6 levels remained constant. Patients on longer-term metformin treatment experienced a significant decrease in mTOR and TGFβ1 levels, but TGFβ1 remained higher than in healthy controls. No significant differences were found in IL6 levels between treatment duration groups and the body mass index (BMI) groups, according to Spearman correlation, there were no correlation found between mTOR and other studied marker neither pre nor post treatment groups.
Conclusion
This study concluded that metformin has pleiotropic effects on immune reprogramming due to its role as an mTOR inhibitor and immune modulation of regulatory cytokines.
The Role of ACE Gene Rs 1799752 I/D Polymorphism and Serum ACE Activity in Recurrent Miscarriage Pathogenesis in Iraqi Women
Authors: Kareem Hiran J. , I. A. Abdulhassan,
Published: February 2025

Background
Recurrent miscarriage is a major health public health problem that affects one to three percentage of women of childbearing age and is diagnosed as a spontaneous miscarriage if happened more than two times and occur often to the completion of 20 weeks amenorrhea. The variation in Angiotensin-Converting Enzyme (ACE) may be have an important role in the recurrent miscarriages (RM) in Iraqi women.
Objective
The present study aimed to investigate the role of ACE gene polymorphism and its serum level in the pathogenesis of recurrent miscarriage in Iraqi women.
Materials and methods:
Blood samples were collected from fifty patients with RM of unknown cause and fifty apparently healthy women (control). DNA was extracted for genotyping and serum samples were obtained to determine the concentration of ACE activity. ACE gene polymorphisms were determined by using Polymerase Chine Reaction –High Resolution Melting (PCR-HRM), while, serum level of ACE were determined by using Enzyme-Linked Immunosorbent Assay (ELISA).
Results
The research data indicated that genotype II was accompanied by a lower risk of recurrent miscarriage, while there is no relation was obtained of allele frequency among the recurrent miscarriage cases. Moreover, it’s showed that there is a significant differences were noted between RM patients and controls as related with serum ACE level. High ACE activity was noted  in the RM patients carrying D allele in compared to healthy individuals. In all trimesters of the RM incidence was higher in the ID genotype carriers and 70% of RM patients were in the first trimesters.
Conclusion
These results concluded that the ACE gene polymorphism at rs179952 have a role in the RM pathogenesis and the genotype II may serve as a protective factor against RM, it’s also showed that there is a low serum ACE levels which might be a new marker for recurrent miscarriage risk in Iraqi women. The results also showed that there is a strong association between the rs1799752 genetic polymorphism in the ACE gene and the increased risk of miscarriage, especially in pregnant women carrying the ID genotype.