This article highlights the scientific and practical aspects of qualification of laboratory equipment within the pharmaceutical quality control system. It substantiates that the proper selection, installation, and operation of laboratory instruments are crucial for ensuring the reliability, accuracy, and reproducibility of pharmaceutical analysis results.

The article provides a detailed analysis of the internationally accepted stages of laboratory equipment qualification—DQ (Design Qualification), IQ (Installation Qualification), OQ (Operational Qualification), and PQ (Performance Qualification)—their content, and their role within the pharmaceutical quality system. It also examines the classification of equipment into Groups A, B, and C in accordance with ISPE and WHO guidelines, as well as the determination of the appropriate level of qualification required for each group.

Furthermore, the importance of qualifying laboratory equipment in compliance with GMP, ISO 17025, USP <1058>, and WHO requirements is substantiated. The scientific and practical foundations for implementing this process in the pharmaceutical industry of Uzbekistan are also presented.

The research findings have practical significance for improving the quality system in pharmaceutical laboratories and ensuring reliable analytical results.

This systematic review synthesizes evidence on non-pharmacological interventions for managing acute, non-traumatic musculoskeletal pain (<6 weeks) and summarizes findings across efficacy, safety, acceptability, and cost-related considerations. A structured literature search was conducted on 15 June 2025 across four databases (PubMed/MEDLINE, the Cochrane Library, Embase, and Scopus) for publications from 1 January 2021 to 15 June 2025, supplemented by targeted website screening, outreach to relevant organisations, and backward citation searching. Study selection followed PRISMA 2020 with deduplication, title/abstract screening, and full-text assessment; 18 studies meeting the acute <6 weeks criterion was included in the final evidence base and narratively synthesized. Across the included evidence, advice to remain active and graded mobilization were consistently represented as core components of care, while selected modalities (e.g., superficial heat and transcutaneous electrical nerve stimulation) demonstrated short-term symptom relief in some settings. Evidence for cryotherapy was inconsistent and generally of low certainty in acute sprain populations, and findings for manual therapy and complementary approaches were heterogeneous and often condition-specific. Psychoeducational approaches were associated with improvements in pain-related cognitions (e.g., catastrophizing) in limited pilot evidence. Overall, the literature supports a pragmatic multimodal approach that prioritizes early activity and function, complemented by short-acting physical/neuromodulatory modalities and brief psychoeducation when appropriate; however, heterogeneity of populations, intervention parameters, and outcomes limits definitive comparative conclusions, and longer-term trials of predefined combinations are needed. The article will be helpful to clinicians, physiotherapists, pain specialists, and researchers developing integrated models of non-pharmacological rehabilitation.

Hypertension remains a leading contributor to cardiovascular morbidity and premature mortality worldwide, with increasing prevalence observed among younger populations. Although avoidable lifestyle factors account for a substantial proportion of hypertension risk, prevention efforts depend heavily on adequate awareness and understanding of these factors. This study examines the level of knowledge of avoidable risk factors of hypertension among university students in England and evaluates the relationship between these factors and hypertension status. A cross-sectional quantitative design was employed using a structured questionnaire administered to students at a large English university. Descriptive statistics, chi-square analysis, and multinomial logistic regression were used to analyse the data. Findings indicate a high level of knowledge of avoidable risk factors, including alcohol consumption, obesity, high salt intake, and junk food consumption. Despite this, significant associations were observed between several avoidable risk factors and hypertension status, particularly alcohol use, body mass index, salt intake, and frequent consumption of junk food. The results highlight a clear disjunction between knowledge and health behaviour, suggesting that awareness alone is insufficient to reduce hypertension risk among university students. The study underscores the need for prevention strategies that extend beyond information provision to address behavioural, social, and environmental drivers of risk.

In recent years, wearable health technologies have become a cornerstone of digital healthcare innovation. These devices—ranging from smartwatches and fitness bands to biosensors and implantable monitors—enable continuous, non-invasive monitoring of vital physiological parameters such as heart rate, blood oxygen saturation, blood pressure, temperature, and sleep quality. The growing adoption of wearable technologies has significantly enhanced preventive medicine by allowing individuals and healthcare professionals to detect potential health risks before they develop into serious conditions. Wearable devices play a vital role in chronic disease management, providing real-time feedback for patients with diabetes, cardiovascular diseases, and respiratory disorders. By integrating data analytics and artificial intelligence, wearable systems can identify abnormal trends, issue alerts, and recommend timely interventions. Furthermore, their integration into telemedicine platforms has enabled remote patient monitoring, reducing hospital visits, healthcare costs, and the burden on medical staff—especially during public health crises such as the COVID-19 pandemic.

The article studied the morphological and morphometric characteristics of the thymus organ of 3- and 21-day old offspring born from mother rats exposed to chronic stress and compared them with offspring in the control group, and developed an appropriate assessment criterion. The expected results showed that the thymus of the offspring in the experimental group showed profound and significant morphological changes compared to those in the control group.

Background

Substance use among adolescents and young adults is a growing public health concern in Nigeria and other low- and middle-income countries. Despite increasing prevalence, there remains limited systematic evidence on the psychosocial and environmental predictors of substance use disorders in this population. Existing studies often focus on isolated substances or risk factors, overlooking the complex interplay of determinants across developmental stages.

Methods

This systematic review synthesized findings from 22 peer-reviewed studies published between 2015 and 2025 that examined substance use among adolescents and young adults in Nigeria. Databases searched included Web of Science, PubMed and African Journals Online. Studies were selected based on relevance to psychosocial, environmental, and developmental predictors of substance use. Data were extracted and analyzed thematically to identify recurring patterns and gaps.

Results

Findings revealed that adolescent substance use in Nigeria is shaped by emotional neglect, peer pressure, family dysfunction, socioeconomic hardship, and weak institutional support. Most studies (86.4%) used cross-sectional designs and focused on mixed substances (59.1%). Alcohol use ranged from 30.6% to 82.5%; tobacco from 5.5% to 35.3%. Early initiation, often before age 15, was common. Mental health outcomes appeared in 68.2% of studies, and several supported the self-medication hypothesis. Longitudinal and multi-level approaches were notably lacking.

Conclusion

The review highlights the urgent need for comprehensive, multi-factorial research on adolescent substance use in Nigeria. Future studies should adopt integrative models that account for developmental trajectories, psychosocial stressors, and environmental contexts. Strengthening regulatory frameworks and early intervention programs is essential to mitigate long-term health consequences and reduce the burden of substance use disorders in this vulnerable population.

Background:
Gastric and gastro-oesophageal junction cancers encompass a heterogeneous group of malignancies with distinct histological and biological characteristics. Histological classification remains central to diagnosis, prognostication, and therapeutic decision-making, particularly in settings where molecular profiling is not routinely available.

Objective:
This study examined the histological spectrum and classification patterns of gastric and gastro-oesophageal junction cancers diagnosed over a ten-year period in Anambra State, South-East Nigeria.

Methods:
A retrospective review was conducted of gastric and gastro-oesophageal junction cancer cases diagnosed between January 2011 and December 2020 across four major histopathology laboratories in Anambra State. Archived haematoxylin and eosin–stained slides and paraffin blocks were reviewed. Tumours were classified according to the 2019 World Health Organization classification of gastric tumours, with carcinomas further categorised using the Lauren classification system. Descriptive statistics and chi-square testing were applied, with statistical significance set at p < 0.05.

Results:
Ninety-three cases met inclusion criteria. Carcinomas constituted the majority of tumours, followed by mesenchymal tumours, lymphomas, and neuroendocrine tumours. Tubular adenocarcinoma was the most frequent carcinoma subtype, while intestinal-type carcinoma predominated under the Lauren classification. Most graded carcinomas were well differentiated. No statistically significant associations were identified between histological subtype and patient age or sex.

Conclusion:
Gastric and gastro-oesophageal junction cancers in this setting are dominated by epithelial malignancies, particularly tubular and intestinal-type adenocarcinomas. The observed histological profile aligns with patterns reported across Nigeria and other low- and middle-income settings, underscoring the continuing relevance of morphology-based classification in regional cancer practice.

This scientific article examines rational topical therapy for atopic dermatitis in children, focusing on a basic barrier-restoring strategy and the role of the emollient "Aquatopic" (AQUATOPIC Stay Hydrated) in the daily care of xerotic and atopic skin.

The existing systems of health care in the world today are finding it difficult to cope with the historical strain in their operations whereby administrative and clinical inefficiencies are liable about 25% of the annual health care expenditure. Customary packets of analysis are not generally as dexterous as the multi-modal and quick data that is generated by the current Electronic Health Records (EHR). Purpose: The application of state-of-the-art Data Science techniques based on optimizing the predictive model precision and maximizing the systemic performance of healthcare analytics will be the research problem. Methodology: The present research relies on the evaluation of ensemble learning systems and deep neural networks depending on principles of AI-based engineering and infrastructural solidity. The performance metrics to be used during the study are Area Under the Curve (AUC), and throughput rate to determine the effectiveness of this type of models used in the actual clinical environment. Results: According to the analysis, the AI predictive models are better at identifying sepsis at infancy and chronic heart diseases; its AUC value is 0.85-0.92, which is more advanced compared to 0.70, the typical clinical scoring. In addition, performance optimization algorithms were also capable of reducing patient waiting time by 15-20 percent and reducing the efficiency in bed utilization by 12 percent, which all eased the hospital bottlenecks. Data science systems entail the inclusion of strong data science systems to ensure the creation of robust healthcare infrastructure. Even after the set of questions about the privacy of the data and the transparency of the algorithms would still remain critical issues, the transition to predictive and AI-based systems offers a measurable roadmap of the course toward sustainable clinical performance and reduced wastes in the operation. Ultimately, the integration of these AI-driven frameworks serves as a catalyst for a proactive rather than reactive medical paradigm. By harmonizing high-speed computational power with clinical intuition, healthcare providers can mitigate human error and standardize care across diverse demographics. This shift not only addresses immediate fiscal leaks but also establishes a scalable blueprint for global health equity. Consequently, the maturation of these technologies signifies a pivotal evolution toward an automated, precision-oriented future in public health management.

Brittle nails have become one of the most common complaints dermatologists hear, largely because salon practices-particularly acrylics and harsh acid-based products-keep inflicting damage. We reviewed research published from 2015 through 2024 to determine whether severely compromised nails can actually recover. Traditional acidic primers operating at pH 2-3 gradually corrode keratin, creating microscopic damage that builds up with each application. Formulations maintaining pH 5-7 achieve bonding without chemically degrading keratin. Gentler salon approaches-careful cuticle work, minimal filing, replacing acrylics with water-based gel systems-substantially reduce mechanical damage. Home care involves daily moisturizer application, 2.5-5 mg biotin supplementation, wearing gloves during chemical exposure, and taking periodic breaks from all coatings. Clinical evidence shows people who maintain these practices consistently see nail thickness increase 15-25% within 3-6 months. Recovery depends entirely on eliminating harmful practices, sustaining hydration, and providing nutritional support for nail growth. Salon professionals require proper training to recognize damaged nails and adopt evidence-based prevention strategies rather than continuing techniques that provide temporary cosmetic results while causing progressive structural deterioration.

Predictive analytics and health information systems (HIS) have become the focus of the current healthcare revolution that provides unprecedented potential to enhance patient outcomes, streamline clinical processes, and lower the increasing cost of care. Although electronic health records (EHRs) and claims-based databases are widely adopted, a number of healthcare organizations still experience difficulties in extracting practical insights off their data resources, especially when it comes to anticipating high-risk events like hospital readmissions. The present research uses a data-intensive method to investigate the role of combined HIS infrastructures in conjunction with cutting-edge predictive modeling methods in positively influencing clinical decision-making and minimizing preventable readmissions. Based on the real-world EHRs and claims datasets, the study creates a multi-layered analytics pipeline covering data extraction, data standardization via HL7 FHIR and ICD-10 coding systems, and feature engineering, and model development with logistic regression, random forest, and gradient boosting algorithms. To assess the clinical reliability of the model, AUC, precision, recall, and F1-score were used to compare model performance. The results indicate that predictive models based on harmonized HIS data are capable of identifying high-risk patients with a high level of discriminatory power, which allows hospitals to apply timely interventions, allocate resources more effectively, and save the cost-per -patient on preventive care measures. In addition, the operational framework that is suggested in this study offers a blueprint of integration of predictive analytics to the clinical routine working process that can be scaled. The paper provides a contribution to the existing literature by connecting health information systems engineering to applied data science and providing an evidence-based roadmap of health organizations wishing to operationalize patient outcome improvement using analytics. The study presents important implications to clinical practice, hospital management as well as health policy especially in the value-based and population health care models.