Journal of Clinical & Biomedical Research
Journal of Clinical & Biomedical Research is an open access peer-reviewed journal from the publishers of Scientific Research and Community (SRC) which publishes articles in the form of written, video and power-point presentations from the arena of Clinical & Biomedical Research. The journal focuses to build up accessing the complete content of articles freely from online for reader’s perusal. Article acceptance will be in the form of Research, Review, Case Reports, Analysis, Magazines, Editorials, Opinion, Communications, Mini-Review, Short Communications, Picturized, Book Review, Video type and Power Point Presentations (PPTS). Articles can be submitted through online from https://srcpublishers.com/Clinical-Biomedical-research/user/register or can send through an e-mail with attachment for biomedresearch@onlinescientificresearch.info 1.5 Impact Factor 84.5% Citations 90% Acceptance
Thyroid Tissue Gone Rogue: Malignant Struma Ovarii
Background: Malignant struma ovarii is an exceptionally rare ovarian tumor arising from thyroid tissue within a monodermal teratoma. Papillary thyroid carcinoma is the most common malignant transformation, and management remains controversial due to the absence of standardized guidelines. Case Presentation: A 34-year-old woman with polycystic ovarian syndrome presented with intermittent lower abdominal pain and was found to have bilateral ovarian cysts. She underwent robotic bilateral ovarian cystectomy at an outside facility. Histopathology revealed an immature teratoma of the left ovary (stage IC, post-cystectomy) and a mature teratoma of the right ovary containing a microscopic 3 mm focus of papillary thyroid carcinoma (infiltrative follicular subtype). Imaging showed no evidence of peritoneal disease or lymphadenopathy. Neck ultrasonography did not reveal any thyroid lesion. Serum tumour markers and thyroid function tests were within normal limits. Management and Outcome: Following slide review and multidisciplinary evaluation, the patient underwent laparoscopic bilateral salpingo-oophorectomy with omental biopsy, along with total thyroidectomy. Histopathology confirmed malignant Struma ovarii with papillary thyroid carcinoma-type malignant transformation and vascular invasion. In view of the microscopic tumour burden and absence of extra-ovarian spread, radioactive iodine therapy was deferred. The patient was initiated on thyroid hormone replacement therapy and planned for long-term surveillance with serial serum thyroglobulin monitoring. Conclusion: This case highlights the diagnostic and therapeutic challenges of malignant Struma ovarii. Treatment should be individualized based on disease extent and histopathological risk factors. Long-term follow-up is essential due to the possibility of delayed recurrence.
Copyright (c) 2026 Journal of Clinical & Biomedical Research
What is wounded in an anorectic young person? The best description is by an anorectic girl when she says: You don’t know what it is like to be near this black hole!’ The black hole is a wound from loss of attunement in early infancy. It is opened up again during a crisis in the physically and emotionally developing adolescent girl whose whole brain is changing and her body becoming sexually mature.
Disrupted Growth Plate Hypertrophy in X-Linked Hypophosphatemia: Insights from 3D Morphological Analysis
X-linked Hypophosphatemia (XLH) is a rare disorder ranking among the most common inherited forms of rickets. XLH arises from mutations in the PHEX gene which leads to increased levels of the phosphaturic hormone FGF23, disrupting vitamin D metabolism and causing an imbalance in phosphate homeostasis. This cascade of events manifests in characteristic features including short stature, leg bowing, dental anomalies, and bone deformities. While growth impairment is a prominent feature, limited research focuses on the mechanism underlying this growth arrest. The Growth Plate (GP) cells undergo differentiation and hypertrophy, ultimately transforming into bone-forming cells or providing space for new bone formation. Although final length is directly related with final chondrocyte size, in XLH and other growth disorders, little is known about the hypertrophy process, likely due to the GP heterogeneity and complexity. This study utilized advanced three-dimensional morphological analyses of the growth plate of young XLH mice, providing a comprehensive view growth plate mineralization. The integrated approach revealed that growth plate can be divided in more than the 3 classical zones and determines molecular signatures mainly affecting hypertrophy zone in XLH. Indicating that these cells are not able to final differentiate and hypertrophy and therefore synthesize matrix proteins properly, forming eventually an aberrant extrapolation of cells identified as cluster 8 in confocal microscopy. Therefore, these findings highlight an alteration of ECM, in turn, changes the biomechanical environment of articulations independently of grade of bone bowing. This further will drive the progression of degenerative disease as Osteoarthritis even in presence of bone surgery correction. This study enhances our comprehension of XLH’s impact on skeletal development and illuminate the underlying molecular mechanisms governing longitudinal bone growth.
The Impact of Diet and Traumatic Brain Injury on Long-Term Neurological Health
Traumatic Brain Injury (TBI) is a significant risk factor for the development of various neurological disorders. Even mild TBIs, such as concussions, can lead to long-term cognitive, emotional, and behavioral challenges, while moderate to severe injuries increase the risk of conditions such as dementia, Parkinson’s disease, epilepsy, and Chronic Traumatic Encephalopathy (CTE). Repeated brain trauma, commonly observed in contact sports or certain occupations, further exacerbates the likelihood of developing neurodegenerative diseases. The impact of TBI on brain function can result in persistent cognitive impairments, mood disorders, and a significant decline in quality of life, highlighting the importance of monitoring and managing the effects of brain injuries. Diet plays a crucial role in both the recovery and prognosis of TBI as well as in the management of neurological disorders. Proper nutrition can significantly influence brain health by reducing inflammation, promoting neurogenesis (the growth of new neurons), and protecting the brain from oxidative stress. Diets rich in antioxidants, found in fruits, vegetables, and whole grains, have been shown to help mitigate brain damage associated with conditions such as Alzheimer’s and Parkinson’s disease. In contrast, High Fat Diets (HFD) have been shown to impair the brain’s ability to compensate for injury by decreasing Brain-Derived Neurotrophic Factor (BDNF) levels in the hippocampus, thereby impairing cognitive function and memory, as demonstrated in a Controlled Cortical Impact (CCI) rat model. HFD consumption has also been linked to worsened outcomes in several neurodegenerative and neurological disorders. Maintaining hydration and stable blood glucose levels is also essential for supporting brain function, as fluctuations in hydration or glucose levels can negatively affect cognitive performance. Overall, a well-balanced diet can enhance recovery from TBI and potentially reduce the risk of long-term neurological complications. Both diet and TBI are recognized as independent risk factors for neurological disorders. Understanding their individual and combined roles in brain health may improve our understanding of their contributions to the development and progression of neurological diseases.
Automated Facial Symmetry Analysis Judith Ijeoma Nwaiwu- The Impact of Diet and Traumatic Brain Injury on Long-Term Neurological Health
Facial nerve disorders are common and can have various causes, from medical conditions to injuries. Assessing the function of the facial nerve is crucial for tracking recovery, and while several grading scales exist, they often rely on subjective evaluation. This subjectivity can lead to inconsistencies, making it harder to accurately monitor a patient’s progress. To address this, researchers have been working on automating facial symmetry assessments using facial landmark coordinates. However, there is still limited data on the expected range of symmetry indices. This study explores how facial symmetry changes during different facial expressions, focusing on the forehead and mouth regions. We recorded videos of 20 participants (15 men, 5 women, aged 22-37) performing eight facial movement tests. Using an automated system, we identified key facial landmarks and calculated symmetry indices. The goal was to determine which expressions provide the most reliable symmetry measurements. Our findings suggest that the most consistent symmetry indices come from the “eyebrow raising” and “eye squeezing” tests for the forehead, and the “smile,” “forced smile,” and “lip stretching” tests for the mouth. These expressions showed the least variation in symmetry, making them the best candidates for objective assessments of facial nerve function. By improving the accuracy and reliability of facial nerve assessments, this approach could help doctors track recovery more effectively and provide patients with clearer insights into their progress. Automating this process also reduces human error, making evaluations more consistent and accessible.
AI-Driven Insights into End-of-Life Decision-Making: Ethical, Legal, and Clinical Perspectives on Leveraging Machine Learning to Improve Patient Autonomy and Palliative Care Outcomes
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into end-of-life decision-making is reshaping ethical, legal, and clinical frameworks in palliative care. Traditional approaches to end-of-life care often face challenges in balancing patient autonomy, medical ethics, and clinical decision-making. AI-driven insights offer the potential to enhance predictive analytics for disease progression, optimize pain management strategies, and support personalized care planning. By analyzing patient data, ML models can assist healthcare providers in identifying optimal palliative interventions, forecasting life expectancy, and facilitating shared decision-making between patients, families, and medical teams. However, the deployment of AI in this sensitive domain raises critical ethical and legal concerns, including data privacy, informed consent, and potential biases in algorithmic recommendations. This study examines the opportunities and challenges of leveraging AI to improve end-of-life care, emphasizing the need for a patient-centred approach that upholds dignity, autonomy, and compassionate decision-making. The findings suggest that responsible AI integration can enhance palliative care outcomes, streamline clinical workflows, and empower patients in making informed end of-life choices.
Ethical, Legal, and Clinical Perspectives on Leveraging Machine Learning to Improve Patient Autonomy and Palliative Care Outcomes
AI and ML in Healthcare: Redefining Diagnostics, Treatment and Personalized Medicine
Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare by enhancing diagnostics, treatment planning, and personalized medicine. Traditional medical practices often rely on generalized treatment approaches and manual diagnostic processes, which can be time-consuming and prone to human error. AI-driven models, powered by deep learning and predictive analytics, enable faster and more accurate disease detection, improving early diagnosis and patient outcomes. Machine learning algorithms analyze vast amounts of medical data, including imaging, genetic information, and electronic health records, to tailor treatment plans based on individual patient profiles. Additionally, AI enhances drug discovery, robotic-assisted surgeries, and real time health monitoring through wearable technologies. This study explores the transformative impact of AI and ML in healthcare, highlighting key advancements, challenges such as data privacy and algorithmic bias, and the potential for more efficient, accessible, and precise medical care. The integration of AI in healthcare is not only redefining medical practices but also paving the way for a future of truly personalized and data-driven medicine.
Challenges and Innovations in Multi-Patterning Lithography for Advanced Node Technologies: Addressing Line Edge Roughness and Critical Dimension Variability
As semiconductor manufacturing advances to smaller technology nodes, Multi-Patterning Lithography (MPL) has become essential for extending the capabilities of optical lithography. However, MPL introduces significant challenges, including Line Edge Roughness (LER) and Critical Dimension (CD) variability, which can impact device performance and yield. This study explores the technical hurdles associated with MPL and examines emerging innovations to mitigate these effects. Advanced process control strategies, including computational lithography, machine learning-driven metrology, and novel resist materials, are evaluated for their effectiveness in improving pattern fidelity. Additionally, the role of self-aligned patterning techniques, etch process optimizations, and next-generation lithographic solutions, such as Extreme Ultraviolet (EUV) and high-NA lithography, is analyzed. This research provides insights into the evolving landscape of semiconductor fabrication, emphasizing the balance between cost, complexity, and precision in achieving high-resolution, high-yield manufacturing for advanced node technologies.
AI-Powered Predictive Health Risk Management in Insurance Plans: A Multi-Agent System Approach for Personalized Policy Customization
AI-powered predictive health risk management is transforming insurance by enabling personalized policy customization through advanced analytics and automation. This study explores the integration of a Multi-Agent System (MAS) approach, where AI-driven agents analyze vast health datasets, assess individual risk factors, and tailor insurance plans based on predictive modeling. Machine learning algorithms enhance risk stratification, enabling insurers to offer dynamic pricing, preventive healthcare incentives, and real time policy adjustments. The MAS framework facilitates efficient data exchange, ensuring transparency, compliance, and ethical AI governance in insurance decision-making. Cloud computing and secure data pipelines further enhance scalability and privacy while optimizing underwriting processes. This research highlights the benefits, challenges, and future prospects of AI-driven predictive analytics in insurance, emphasizing its potential to improve risk assessment accuracy, enhance customer experience, and promote proactive healthcare management in a rapidly evolving insurance landscape.
Revolutionizing Healthcare Management with AI driven Genomic Analysis: A Machine Learning and Cloud Computing Approach to Precision Medicine and Population Health Monitoring
Artificial Intelligence (AI)-driven genomic analysis is transforming healthcare management by enabling precision medicine and large-scale population health monitoring. This study explores the integration of Machine Learning (ML) and cloud computing to analyze genomic data, predict disease risks, and personalize treatment strategies. ML algorithms enhance genomic sequencing by identifying genetic markers, uncovering complex patterns, and improving diagnostic accuracy. Cloud computing facilitates secure, scalable, and real-time data sharing, allowing healthcare providers and researchers to collaborate on global genomic datasets while ensuring data privacy and compliance. Additionally, AI-powered genomic insights contribute to early disease detection, targeted therapies, and public health interventions. This research highlights the benefits, challenges, and ethical considerations of AI-driven genomic analysis, emphasizing its role in revolutionizing precision medicine, optimizing healthcare workflows, and improving patient outcomes in an increasingly data-driven medical ecosystem.
Transforming Sports Medicine with Deep Learning and Generative AI: Personalized Rehabilitation Protocols and Injury Prevention Strategies for Professional Athletes
Deep learning and generative AI are revolutionizing sports medicine by enabling personalized rehabilitation protocols and advanced injury prevention strategies for professional athletes. This study explores how AI-driven models analyze biomechanical data, medical histories, and performance metrics to tailor rehabilitation programs, optimize recovery timelines, and minimize reinjury risks. Generative AI enhances injury prediction by simulating stress factors on the body, providing real-time feedback, and recommending data-driven interventions. Additionally, AI-powered motion analysis and wearable sensor integration improve athlete monitoring, allowing for early detection of musculoskeletal imbalances and fatigue patterns. The research examines key challenges such as data privacy, ethical considerations, and the integration of AI with existing sports medicine practices. By leveraging deep learning and generative AI, sports medicine can move towards a more proactive, precise, and athlete-centric approach, ultimately enhancing performance longevity and overall well-being in professional sports.
Artificial Intelligence and Cloud-Enabled Big Data Analytics for Genomic Research: Transforming Healthcare Management Through RealTime Decision Support Systems and Predictive Modeling
The integration of Artificial Intelligence (AI) and cloud-enabled big data analytics is revolutionizing genomic research, enabling real time decision support systems and predictive modeling for advanced healthcare management. This study explores how AI-driven algorithms analyze vast genomic datasets to identify disease markers, predict patient outcomes, and personalize treatment strategies. Cloud computing provides scalable and secure infrastructure for processing large-scale genomic data, facilitating collaboration among researchers, clinicians, and healthcare institutions. Machine learning models enhance precision medicine by uncovering complex genetic patterns, improving diagnostic accuracy, and optimizing therapeutic interventions. Additionally, AI-powered predictive analytics supports early disease detection and population health monitoring, enabling proactive healthcare strategies. Key challenges, including data privacy, ethical considerations, and regulatory compliance, are examined alongside emerging solutions. This research highlights the transformative potential of AI and big data in genomic medicine, driving innovation in personalized healthcare and accelerating advancements in medical research.
Integrating Cloud Computing and Big Data Analytics in AI Driven Genetic Research: Enhancing Healthcare Management Through Predictive Modelling and Personalized Treatment Strategies
The integration of cloud computing and big data analytics in AI-driven genetic research is revolutionizing healthcare management by enabling predictive modelling and personalized treatment strategies. This study explores how machine learning algorithms analyze vast genomic datasets to identify disease-associated genetic markers, enhance diagnostic accuracy, and optimize therapeutic interventions. Cloud computing provides a scalable and secure infrastructure for processing large-scale genetic data, facilitating real-time collaboration among researchers and clinicians while ensuring data privacy and regulatory compliance. AI-powered predictive analytics supports early disease detection, risk assessment, and targeted drug development, advancing precision medicine and improving patient outcomes. Additionally, this research highlights the challenges of data interoperability, ethical considerations, and algorithmic transparency in AI-driven genomic research. By leveraging cloud-enabled AI and big data analytics, the healthcare industry can enhance decision-making, accelerate medical discoveries, and deliver more effective, patient-centric treatment solutions.
The Future of AI enabled Medical Device Engineering: Integrating Predictive Analytics, Regulatory Automation, and Intelligent Manufacturing
The integration of Artificial Intelligence (AI) in medical device engineering is revolutionizing the healthcare industry by enhancing predictive analytics, regulatory automation, and intelligent manufacturing. AI-driven predictive analytics enables early fault detection, real-time performance monitoring, and proactive maintenance, ensuring the reliability and efficiency of medical devices. Additionally, regulatory automation powered by AI streamlines compliance processes by continuously monitoring evolving standards and automating documentation, reducing time-to-market for new medical technologies. In manufacturing, intelligent AI-driven automation optimizes production workflows, enhances quality control, and minimizes defects, leading to more precise and cost effective medical device production. This paper explores the transformative potential of AI-enabled medical device engineering, highlighting its impact on device safety, efficiency, and scalability, while also addressing challenges such as data privacy, regulatory hurdles, and ethical considerations. The future of AI in medical device engineering promises smarter, safer, and more adaptive technologies that improve patient outcomes and revolutionize the healthcare landscape.
Omni-channel Retail: Leveraging Machine Learning for Personalized Customer Experiences and Transaction Optimization
Omni-channel retail is revolutionizing the shopping experience by integrating physical and digital touchpoints to deliver seamless, personalized customer interactions. This study explores the role of Machine Learning (ML) in enhancing omni-channel strategies through data-driven personalization and transaction optimization. Traditional retail models often struggle with fragmented customer journeys, inefficient inventory management, and inconsistent engagement across channels. ML-driven solutions analyze customer behavior, predict preferences, and enable dynamic pricing, real-time recommendations, and targeted marketing campaigns. Additionally, AI-powered analytics optimize supply chain operations, fraud detection, and demand forecasting, improving overall efficiency and profitability. However, challenges such as data privacy, algorithmic bias, and system integration require careful consideration. This paper examines the transformative potential of ML in omni-channel retail, emphasizing its impact on customer experience, operational efficiency, and business growth. By leveraging AI-driven insights, retailers can create a more responsive, efficient, and engaging shopping environment in the digital era.
Healthcare systems worldwide are facing a critical challenge with a shrinking pool of doctors and a rapidly growing and aging patient population. LLMs and other self-supervised models can change the situation but require access to a large volume of data to be generalizable and less biased. Without large amount of data, the models are not generalizable and biased. ChatGPT is trained on publicly available internet data, and even they report that it is no longer enough. Imagine how dire the situation is in AI in Healthcare that requires access to Personal Medical records. These records are not just bits and bytes, but somebody’s very personal very private data. E.g., on the dark web price for a person’s healthcare record is 500x the price for a credit report. To give AI in Healthcare access to the personal medical data, the data must be deidentified. Local large volume deidentified multimodal medical data lakes offer a feasible solution that empowers hospitals and individual patients to make a significant impact, while monetizing their data.
Prevalence of Mixed Infections in HCV Chronically Infected Patients
Introduction: Mixed infections by different HCV genotypes constitute an important concern worldwide. Τhe aim of this study is to determine the prevalence of mixed infections by two or more HCV genotypes in HCV chronically infected patients. Materials and Methods: 100 HCV-RNA positive patients were included in this study. This retrospective study was conducted according to the Helsinki Declaration. Informed consent of patients was not compulsory due to its retrospectivity. HCV-RNA was detected by means of Cobas Taqman 48 with High Pure System, Roche. Sequencing was performed by Trugene® HCV 5’NC Genotyping Kit (Siemens). Statistics were performed with SPSS version 25.0. Results: mixed infections were detected in 15 patients (15.0 %, 8 male and 7 female). Mixed infections were as follows: 3 patients were infected by types 1a+1b, 3 by types 2a+2c, 2 by types 3a+3c, 1 by types 3a+3d, 1 by types 3a+3d+3e, 2 by types 3a+3e, 2 by 4a+4d and 1 by types 4a+4c+4d. Mixed infections were equally distributed among male and female patients (p-value = 0.402). The mean age of individuals infected only with one HCV type was 41.9 years old; while of those mix-infected were 51.9. Statistically significant differences of mix infections distribution according to age were detected (p-value = 0.032). There were no cases with mixed infections across types. Conclusions: Mixed HCV infections have been reported in many studies. Their prevalence varies worldwide and regional differences exist in their distribution. Mixed infection prevalence depends on the risk factors in the population under study. In this study, the prevalence of mixed HCV infections was 15.0 % and all patients belonged to high-risk groups. Moreover, all mix-infected patients had long-lasting disease course and liver cirrhosis.
Hepatitis C Virus, Genotype, Phylogenetic Tree, Sequences, Mixed Infections, Subtype
Quality of Life, Support before and after Surgery which Cholelithiasisby Laparoscopic and Traditional Methods
Introduction: Laparoscopic cholelithiasis is a common surgical procedure worldwide and remains the golden standard for the treatment of mild diseases of the gallbladder and bile ducts. The aim of this study was to assess the quality of life, social support of patients before and after surgery with gallstones treated laparoscopically and traditionally Methods: The study was conducted in 96 patients with gallbladder stones treated surgically with laparoscopic and traditional methods at the Department of General, Oncological and Minimally Invasive Surgery of the Stefan Zoromski Specialist Hospital in Kraków from March to December 2024. Approval was obtained from the bioethics committee to conduct the study. The study was conducted using a diagnostic survey method with standardized research tools: The World Health Organization Quality of Life and Multidimensional Scale of Perceived So-cial Support. Statistical analysis was done using IBM SPSS software. Differences between the two groups were compared using the Mann-Whitney test. Differences between pre- and post-treatment post-measures on the same scales were tested using Wilcoxon tests for dependent samples. A p<0.05 was used as the limit of the significance level. Results: Statistically significant differences were found between laparoscopic and traditional surgery types for the somatic domain before surgery and all domains after surgery assessing quality of life. All domains had higher values in the laparoscopically operated group. Statisti-cally significant differences were found between pre- and post-operative measurements for social support, where higher values were found after surgery. No significant differences in quality of life were shown when analyzing all domains between pre- and post-operative meas-urements. Conclusions: Laparoscopically operated patients showed higher values for the somatic do-main before surgery, as well as for all domains after surgery, compared to traditionally operat-ed patients. Patients after surgery for gallbladder stones were shown more support from rela-tives, family and friends, compared to patients before surgery
Immunofluorometrical Exploring of FSH Levels in the Serum of Patients with Histologically Verified Large-cell Lung Carcinoma(LCLC)
It is already known in the science that the cells of some types of LCLC can produce gonadotropins. By following the levels of FSH, in the serum of LCLC patients, we could make some statistical conclusions how significant these levels would be in eventual future early diagnostic procedures, besides already existing tumormarkers etc. This work would connect the Oncology, Endocrinology and Immunology fields containing very interesting immunofluorometrical procedures, hormonal theories and statistical estimates.
Challenges and Limitations of Personalized Cancer Vaccines
Personalized cancer vaccines represent a promising frontier in oncology, offering the potential for highly targeted and effective treatments. However, this innovative approach faces significant challenges and limitations, including tumor heterogeneity rapid cellular mutation manufacturing complexity, immune system evasion, identifying suitable antigens, and cost [1,2]. Furthermore, limited long-term efficacy data, scalability, and regulatory hurdles create serious obstacles to applying personalized cancer vaccines
Treatment Option of Inherited Hemophilia A and B: In Case ofGene Therapy
Hemophilia is the X-linked inherited bleeding illness caused by genetic abnormalities in the F8 (hemophilia A) or F9 (hemophilia B) genes. Hemophiliacs experience bleeding episodes into the joints and soft tissues, which can be managed with self-infusion of concentrations of factor VIII or IX. Because hemophilia is a monogenic illness with easily measured outcomes (factor levels and bleed rates), it makes it a desirable target for gene therapy. One of the most promising vectors for hemophilia gene therapy is lentiviral or adeno-associated virus (AAV)-based. Recombinant adeno-associated viral (AAV) vectors have been used successfully in all preclinical and clinical trials to far for factor VIII or IX hepatocyte transduction. These vectors were used to repair the bleeding phenotype in preclinical animal models of hemophilia A and B. Clinical translation to individuals with severe hemophilic phenotype was spurred by some of these encouraging preclinical results. This represents a significant advancement in the field because these patients undergoing gene therapy with AAV vectors demonstrated long-term expression of therapeutic FIX levels. With gene therapy, hemophilia patients can have a single treatment and maintain their factor levels for years or decades rather than relying on a steady supply of medication and frequent delivery at short intervals. Over the past ten years, significant progress has been achieved in the development of gene therapy for hemophilia. The phase III trial stage of adeno-associated virus (AAV) vector-mediated gene transfer in hemophilia A and B has begun. Clinical trials are currently evaluating factor VIII (FVIII) or factor IX (FIX) gene editing technologies or lentiviral vector gene transfer. It is anticipated that major markets will authorize and distribute the first gene therapy drugs, FVIII and FIX, in the near future
Prevention of Falls in Patients Cared for in the Out-Of-Hospital Emergencies of the Sierra de Cadiz Summary
Falls are the most common safety incident among patientes treated, with out-of-hospital patients being the most vulnerable too harm. The prevention of these generates great benefits and important economic savings. Objetive: To know the incidence of fall in patients treated in out-of-hospital emergencies by professionals from the UGC Urgencias Sierra de Cádiz. Methods: Descriptive, observational and cross-sectional study carried out in the month of May 2024. A random simple of 150 participants was selected who responded to an anonymous telephone questionnaire with voluntary participation of 9 semi-structures questions as a data collection tool Results: The average age of those surveyed is 62 years, with 41% men and 59% women. 97% acknowledged that there werw no physical barriers and 94% answered that the transfer was comfortable, 98% stated that there was good lighting. 100% did not suffer any injuries and 96% did not consider that werw at risk of falling. In 98% of cases, retraint measures and other measures werw used in 98% to prevent falls.. Discussion: The patients treated by the profesionals belonging to the Urgencias Sierra de Cádiz did not suffer injuries during their out-of-hospital healthcare,and measures werw taken to prevent them. It is important to identify risks in the out-of-hospital environment and prevent falls.
Copyright (c) 2025 Journal of Clinical & Biomedical Research
Effect of Respiratory Muscle Training on Cough Efficacy, FunctionalRecovery and Length of Stay Post-Open-Abdominal Surgery: ASingle Blinded Randomised Controlled Trial
Introduction: Abdominal surgery is associated with post-operative depressed cough efficacy which results in the pooling of secretions, altered pulmonary function and an increased risk of postoperative pulmonary complications (PPCs) leading to a prolonged length of hospital stay (LOS). Physiotherapy interventions, such as respiratory muscle training (RMT), have been implemented post-abdominal surgery with the aim to enhancing inspiratory muscle strength. However, it is unclear whether the increased strength translates to an improved cough. Aim: To assess the effect of RMT in comparison with conventional chest physiotherapy (DBEx) on cough efficacy, functional recovery and length of stay (LOS) post-abdominal surgery. Method: This is a single blinded randomized controlled trial with thirty-six (36) patients scheduled for elective abdominal surgery. Participants were randomly assigned into experimental (Exp) and control (Ctl) groups. Exp Group received RMT & Early Mobilization (EM), Ctl Group received DBEx and EM. The outcome variables include; peak cough flow (PCF), functional recovery, LOS and pulmonary function. Inferential statistics of Analysis of Variance (ANOVA) was used to evaluate the significant difference in the 3 stages of data collection (pre-op, immediate post-op and post-op day 7 (POD7) or discharge(if discharged before POD7). Independent t-test was used to compare the outcome variables between the groups. Result: 32 participants completed this study. In both groups, ANOVA showed a significant decrease in PCF, BIS and pulmonary function at immediate post-op followed by an increase at discharge or POD7. There was no statistically significant difference between the 2 groups following the t-test analysis in all variables. Conclusion: RMT or DBEx in addition to EM will improve cough efficacy, functional recovery, LOS and pulmonary function post-abdominal surgery. None is more effective than the other in the management of patients’ post-abdominal surgery.
Quality of Life, Self-Efficacy, Disease Acceptance and Support in Stroke Patients
Introduction: Stroke is a cerebrovascular disease that is the second cause of death and the leading cause of disability worldwide The aim of this study was to evaluate quality of life, independence, disease acceptance and social support in stroke patients, taking into account the analysis of chronic diseases - hyper-tension and diabetes and obesity. Material and Methods: The study was carried out in 83 stroke patients from May 2024 to January 2025 at the Neurology Department with Stroke Treatment Subdivision of the Stefan Żeromski Specialist Hospital in Krakow. Approval from the bioethics committee was ob-tained. The study was conducted using standardized survey instruments: The World Health Organi-zation Quality of Life (WHOQOL)-BREF, Lawton scale, AIS and the Multidimensional Per-ceived Social Support Scale. Statistical analysis was developed in IBM SPSS software. Differences were assessed using the Mann-Whitney test. Spearman’s correlation coefficients were used to assess relationships between quantitative variables. A p<0.05 was used as the limit of significance level Discussion: Quality of life after stroke depends on a comprehensive view of subjective health, including measures of perceived physical, mental and social well-being and functioning. De-mographic factors, comorbidities, patient self-efficacy and psychosocial factors and social support are important predictors of quality of life in stroke survivors and have a significant impact on the rehabilitation process and recovery. Conclusions: The less support patients received from a significant other after a stroke, the lower the quality of life in terms of the psychological domain. The more support post-stroke patients received from a significant person - a friend, the more independent the patients are. Patients with hypertension definitely had a problem with stroke acceptance. There is no relationship between quality of life in post-stroke patients and acceptance of the disease and independence.
Ageing, Cellular Senescence and Diabetes, Exploring the Connections between these Processes and their Implications for Treatment and Management
The defined disparity between ageing and senescence is that ageing constitutes an intricately complex and definite biological mechanism characterized by a progressive depreciation in physiological functionalities and elevated mortality risk. Senescence features a cellular mechanism of a conditioned state of the arrest of cell cycle and secretion of inflammatory molecules. Cellular senescence correlates to the ageing process as the ageing immune system declines in efficiency culminating in senescent cells accumulation with superimposition on healthy cells. This impacts ability to cope with stress or impaired health, injury recovery, and configure or inculcate new ideas as brain senescent cells are capable of the impairment of cognitive activities. The aetiologies of cellular senescence are triggered by multifarious factors which include reiterated cell culture, telomere attrition, irradiation, oncogene activation, and oxidative derangement, as well as impairment of mitochondrial homeostasis, with propensity to accelerate age-associated phenotypes. The pathophysiologic mechanisms related with diabetes impacting the ageing elderly population due to advanced age culminate in the exacerbation of systemic chronic inflammation, oxidative stress, DNA damage, decline of mitochondrial function, cellular senescence, and tissue dysfunction, all conditions which contribute to generate metabolic disorders. With increasing age, the pancreas produces diminished insulin and resultant prolonged increased blood sugar. The process of cellular ageing is associated with increasing cell size and diminished capabilities to divide and/or multiply. In addition to other alterations, there is augmentation of pigments and fatty structures or lipids within the cells. Ageing impacts cellular actions which contribute to age-related disorders as ageing cells accumulate misfolded and perturbed proteins due to functional deterioration in the homeostasis or proteostasis process of the proteins. The cellular senescence mechanism results since cellular senescence is a highly formidable cell cycle arrest that is generated in reaction to disparate stresses. With the imposition of any growth arrest, senescence restricts aged or deranged cell replication. Age constitutes a major risk factor for type 2 diabetes However, it is not clearly explicated how senescence contributes to the pathogenesis of diabetes. Thus, available treatment regimen has not targeted the defined portion of the disease. Suppression of the deranged presentations of cellular ageing is important as a novel type 2 diabetes treatment where pancreatic beta cells is impaired regarding insulin secretion. Adequate therapeutic trajectories necessitate characterization of senescent β-cell populations and the spatiotemporal variations of senescence gene expression.
Investigating Intestinal Parasites Infection among University Studentsat Jiblah University for Medical and Health Sciences, Yemen, 2024
This study aimed to assess the prevalence of intestinal parasitic infections and their associated risk factors among 200 students at Jiblah University, Ibb, Yemen. Methods and Result: Sociodemographic data showed that 55.5% of participants were female, 41.5% were over 23 years old, and 77.5% lived in urban areas. The prevalence of intestinal parasites infected was 42.5%. The most common of intestinal parasites were Entamoeba histolytica (76.5%), followed by Giardia lamblia (9.5%). The intestinal parasites were higher among groups aged fewer than 21 years (49.2%) and those aged 21-22 years (48%), male (43.8%) and female group (41.4%), while it was (42.8%) in students from urban areas, and (41.5%) from rural areas. Moreover, it was observed that intestinal parasitic infections were higher among students who sometimes or never washed fruits and vegetables before eating (58.1%) with a p= (0.019. Finally, the intestinal parasites infected were higher (50%) among students who ate in restaurants. Conclusion: The findings from the current study revealed that intestinal parasites infection was higher among the group under 21 years old, male, married, urban, students who sometimes or never washed fruits and vegetables before eating and students who ate in restaurants.
Water Clarification and Impact Transfer on Tissues in Wet Contact
Water is a pure substance that picks up a huge load during its cycles on the earth, in bio systems, in washing and cleaning, as well as in industrial and agricultural processes. Water can be clarified and loaded again with desirable gases like clean air within seconds by the new integrated clarification technology in tube condition. The clarified and reloaded water is able to transfer impact of the load on tissues in wet contact, and pick in slag from the tissue due to reduced surface tension. The water clarification technology is presented with illustrations briefly, and selective case studies of air impact transfer on bio tissues in wet contact are reported briefly here. OxTube, a new water treatment innovation, clarifies water matrices in tube condition within seconds by four seamless phases; (1) separation of dissolved substances, (2) activation of molecules, (3) clarification and (4) post dissolving and refreshing. It separates and removes dissolved gases like radon, carbon dioxide, hydrogen sulfide and hydrocarbon, and dissolved solids like iron, manganese compounds, calcium, fluorine and phosphorus within seconds. Combined removal of pharmaceutical residues, disinfection and clarification in one within seconds is verified by ozone feed. Efficiency is based on kinetic energy of the flow converted to high dynamic pressure, even mixing and high collision probability of molecules in tube condition. Health and wellness impact of clean air can be dissolved in to the water such a way that exchange of slag and air gas between bio systems and the water initiates immediately in wet contact. Comparable iron gets rusted right away in this treated water but it could take years in dry air.
Examining the Effects of Domestic Violence and Anemia on Maternal and Child Health in Peru
The study aims to examine the association between domestic violence against women and anemia in women and their children under 5 years in Peru. A cross-sectional study was conducted using data from the 2023 Demographic and Family Health Survey (ENDES) in Peru, focusing on women aged 15-49 years who reported having children aged 5 years or younger. Domestic violence was defined as physical, psychological, or sexual abuse perpetrated by a partner or husband. Anemia was assessed through blood tests measuring hemoglobin levels. Two outcomes were evaluated: Model 1 (both the woman and her child are anemia-free; 1 = both anemia-free, 0 = at least one is anemic) and Model 2 (at least the child is anemia-free; 1 = child is anemia-free, 0 = child has anemia). Multivariate logistic regression analysis was used to estimate both unadjusted and adjusted odds ratios for the association between domestic violence and anemia in women and children. The most usual form of partner violence against women was psychological violence, with 44.5% of women reporting exposure. The maternal-child anemia index showed that 64.3% of woman-child pairs had at least one anemic member, and 32.6% of children under 5 were anemic among women reporting all forms of violence. In adjusted Model 1, anemia was significantly associated with physical violence (aOR = 0.72, 95% CI: 0.61, 0.85; p-trend = <0.000); and in adjusted Model 2, anemia in children was significantly associated with sexual violence (aOR = 0.60, 95% CI: 0.38, 0.95; p-trend = 0.028). These findings indicate that domestic violence is a critical determinant of health outcomes. The association between violence and anemia highlights the instrumental health benefits of addressing partner violence, with the potential to improve both maternal and child health outcomes.
A Cross-Sectional Study on the Clinical Presentation of Vitamin D Deficiency at a Family Medicine Specialist Center in Kenya
Background and Aims: The pandemic of vitamin D deficiency bears many an enigma. Clinically, many a primary care clinician prescribes vitamin D to anyone suspect of the deficiency, whilst the exact range of symptoms associated with the deficiency is yet to be fully defined. Newly associated symptoms have been proposed, and the most clinically relevant normal reference range for the deficiency and insufficiency of the vitamin is a question that is yet to be satisfactorily answered in the Kenyan population. The local populations with higher risk despite sunlight exposure is an additional question that warrants further looking into. Method: Considering the above we conducted a cross-sectional study at a family medicine specialty center in Nairobi over a period of 3 months from 15th April 2023 to 15th July 2021, and the clinical findings of newly proposed symptoms by family physicians to be associated with vitamin D deficiency were correlated to the respective serum vitamin D levels in 168 patients with informed consent. They were then called in 3 months after supplementation to confirm resolution of symptoms through Vitamin D supplementation. Results: Overall deficiency prevalence was 37%. It was a female-dominated study representing mainly the African and Indian-Asian ethnicity. Symptoms strongly associated were undue fatigue, bowel irregularities, hormone imbalance, myalgia, and arthralgia. Urolithiasis had a weaker association and mood disorders were not associated significantly. Most associations persisted till around the serum level of 75 ng/ml, thereby implying higher optimal levels of vitamin D rather than the current globally accepted reference range. Definitions: For Vitamin D, 30ng/ml is equivalent to 75 nmol/L
Biochemical and Molecular Characterization of Biofilm ProducingEscherichia Coli Isolated from Environmental Specimens withinEkpoma and its Environs
A community of bacteria that are permanently adhered to a surface and covered with extracellular polymeric substances (EPS) and have heightened resistance to host cellular and chemical reactions is referred to as a biofilm in microbiology. One or consortium of microorganisms affixed to various surfaces make up biofilms. This study analyzed the biochemical and molecular characterization of biofilm producing Escherichia coli isolated from environmental specimens within Ekpoma and its environs to separate the ambient E. coli specimens, identify the biofilm-forming capacity or capacities, and show the antibiotic resistance and biofilm-forming genes. In ambient samples, Escherichia coli was recovered with a prevalence of 112. Biofilm generation was demonstrated using two techniques: the microtitre plate method and the Congo red agar (CRA) method. This resulted in a 90% re-producibility. There were a lot of weak formers (41.1%) among the environmental isolates (20.5%). The results of the statistical analysis indicated that there was no significant difference between the two approaches, with the p-value being 0.167369 and p≥0.05. Prior to biofilm formation, antibiotic resistance was modest (65.2%), but it increased after biofilm formation. Plasmid-encoded fimbriae H (fim h) and aggregation genes [(agg)3IV] for biofilm formation for strong, moderate, and weak formers alone from both isolate sources were constituted by molecular characterization test. Multidrug resistance of routinely used antibiotics in their typical routine dosages was made possible by the inclusion of plasmids for biofilm development. The existence of antibiotic resistance genes for aminoglycosides and quinolones served as additional evidence of this. These can be investigated further with the goal of preventing the formation of biofilm by infection-associated cells. Acrydine orange (AO) dye at a concentration of 75 ul/g was used to evaluate biofilm-forming isolates for plasmid curing. The findings revealed a decrease in antibiotic resistance from 87.5% to 6.3% and biofilm development from roughly 90% to 9.9%. Plasmid-mediated antibiotic resistance is a major public health concern and a serious threat to chemotherapy and medicine worldwide.