Vitamin D Receptor (VDR) Gene Polymorphisms and High-Turnover Renal Osteodystrophy or Secondary Hyperparathyroidism in End-Stage Renal Disease: A Systematic Review.

Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are often complicated by high-turnover renal osteodystrophy (HTRO) and secondary hyperparathyroidism (SHPT), characterized by disturbances in mineral metabolism and skeletal abnormalities. Genetic variations within the vitamin D receptor (VDR) gene, known as VDR gene polymorphisms, have been implicated in modulating the susceptibility to HTRO and SHPT. This systematic review aims to evaluate the existing literature on the association between VDR gene polymorphisms and the development of these complications in ESRD and hemodialysis patients. A comprehensive literature search across multiple databases was conducted, and studies investigating VDR gene polymorphisms and HTRO or SHPT in ESRD or hemodialysis patients were included. The included studies examined various VDR gene polymorphisms, such as BsmI, ApaI, TaqI, and FokI, and their associations with clinical outcomes like parathyroid hormone (PTH) levels, bone mineral density, and the development of SHPT or HTRO. The findings suggest that certain VDR gene polymorphisms, notably the ApaI "aa" genotype, BsmI "bb" genotype, TaqI "tt" genotype, and FokI variant, may contribute to the pathogenesis of SHPT and HTRO by affecting PTH levels, bone turnover markers, and vitamin D sensitivity. However, the studies had relatively small sample sizes and were conducted in different populations, limiting generalizability. Further larger-scale studies, functional investigations, and exploration of gene-environment interactions are warranted to elucidate the underlying mechanisms and facilitate personalized treatment approaches for CKD and ESRD patients with mineral and bone disorders.

Metformin and Atrial Fibrillation: A Systematic Review of Their Association.

Atrial fibrillation (AF) is a common cardiac arrhythmia with a significant impact on patient outcomes and healthcare systems. Given the rising incidence of AF with age and its association with conditions, such as diabetes, there is growing interest in exploring pharmacological interventions that might mitigate AF risk. Metformin, a widely prescribed antihyperglycemic agent for type 2 diabetes mellitus (T2DM), has demonstrated various cardiovascular benefits, including anti-inflammatory and antioxidative properties, leading to speculations about its potential role in AF prevention. This systematic review synthesizes findings from five studies examining the association between metformin use and AF risk in patients with T2DM. The review included a dynamic cohort study, three retrospective cohort studies, and a case report, all sourced from databases, such as PubMed, Embase, and the Cochrane Library. The results are mixed; while some studies suggest that metformin use is linked to a reduced incidence of AF, others report no significant association, particularly in postoperative settings. The largest cohort study highlighted a dose-response relationship, suggesting prolonged metformin use correlates with lower AF risk. Conversely, a case report raised concerns about metformin-induced lactic acidosis potentially triggering AF episodes. The review underscores the heterogeneity in study designs and outcomes, pointing to the need for more robust research to establish causality and clarify underlying mechanisms. Future studies should prioritize prospective designs and explore the pleiotropic effects of metformin on atrial remodeling and electrophysiology to better understand its potential role in AF prevention.

Assessing the Renal Outcomes of Semaglutide in Diabetic Kidney Disease: A Systematic Review.

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes, posing a significant health burden. Semaglutide, a glucagon-like peptide-1 receptor agonist, has shown promise in mitigating renal outcomes in DKD. This systematic review aimed to evaluate the renal effects of semaglutide in individuals with DKD. A comprehensive literature search identified six eligible studies, including two case reports and four cohorts, from diverse geographic locations. The primary outcomes assessed were changes in estimated glomerular filtration rate (eGFR) and albuminuria. Secondary outcomes included acute kidney injury (AKI) incidence and other renal biomarkers. The impact of semaglutide on eGFR was variable, with some studies reporting decreases and others showing improvements or no significant changes. Albuminuria, however, was more consistently reduced, particularly in patients with macroalbuminuria. Notably, the case reports described semaglutide-associated AKI, including acute interstitial nephritis, highlighting the need for careful monitoring during therapy. Beyond renal outcomes, semaglutide consistently improved glycemic control and promoted weight loss, with generally manageable gastrointestinal side effects. The findings suggest that semaglutide may effectively reduce albuminuria in DKD, potentially slowing disease progression. However, the risk of AKI and the variable impact on eGFR underscore the need for a personalized approach and vigilant monitoring, particularly in patients with advanced CKD. Future large-scale, long-term randomized controlled trials are warranted to definitively assess the renal benefits and risks of semaglutide in DKD.

Hepatopulmonary Syndrome: A Comprehensive Review.

Hepatopulmonary syndrome (HPS) is defined by abnormally dilated blood vessels and shunts within the lungs, leading to impaired oxygen exchange. This condition results from intricate interactions between the liver, the gastrointestinal system, and the lungs. This complex system primarily affects pulmonary endothelial, immunomodulatory, and respiratory epithelial cells. Consequently, this contributes to pathological pulmonary changes characteristic of HPS. A classification system based on the severity of oxygen deficiency has been proposed for grading the physiological dysfunction of HPS. Contrast-enhanced echocardiography is considered the primary radiological evaluation for identifying abnormal blood vessel dilations within the lungs, which, combined with an elevated alveolar-arterial gradient, is essential for making the diagnosis. Liver transplantation is the sole effective definitive treatment that can reverse the course of the condition. Despite often being symptomless, HPS carries a significant risk of mortality before transplantation, regardless of the severity of liver disease. Meanwhile, there is varying data regarding survival rates following liver transplantation. The adoption of the model for end-stage liver disease (MELD) standard exception policy has notably improved the results for individuals with HPS compared to the period before MELD was introduced. This review offers a summary of the present understanding, highlighting recent advancements in the diagnosis and treatment of HPS. Furthermore, it aims to augment comprehension of the condition's fundamental mechanisms through insights derived from experimental models and translational research.

Artificial intelligence and machine learning in peritoneal dialysis: a systematic review of clinical outcomes and predictive modeling.

BACKGROUND: The integration of artificial intelligence (AI) and machine learning (ML) in peritoneal dialysis (PD) presents transformative opportunities for optimizing treatment outcomes and informing clinical decision-making. This study aims to provide a comprehensive overview of the applications of AI/ML techniques in PD, focusing on their potential to predict clinical outcomes and enhance patient care. MATERIALS AND METHODS: This systematic review was conducted according to PRISMA guidelines (2020), searching key databases for articles on AI and ML applications in PD. The inclusion criteria were stringent, ensuring the selection of high-quality studies. The search strategy comprised MeSH terms and keywords related to PD, AI, and ML. 793 articles were identified, with nine ultimately meeting the inclusion criteria. The review utilized a narrative synthesis approach to summarize findings due to anticipated study heterogeneity. RESULTS: Nine studies met the inclusion criteria. The studies varied in sample size and employed diverse AI and ML techniques, reflecting the breadth of data considered. Mortality prediction emerged as a recurrent theme, demonstrating the significance of AI and ML in prognostic accuracy. Predictive modeling extended to technique failure, hospital stay prediction, and pathogen-specific immune responses, showcasing the versatility of AI and ML applications in PD. CONCLUSIONS: This systematic review highlights the diverse applications of AI/ML in peritoneal dialysis, demonstrating their potential to enhance predictive accuracy, risk stratification, and decision support. However, limitations such as small sample sizes, single-center studies, and potential biases warrant further research and external validation. Future perspectives include integrating these AI/ML models into routine clinical practice and exploring additional use cases to improve patient outcomes and healthcare decision-making in PD.

Mobile Health Interventions: A Frontier for Mitigating the Global Burden of Cardiovascular Disease.

Mobile health (mHealth) interventions have emerged as a promising approach for cardiovascular disease (CVD) prevention and management. The proliferation of smartphones and wearable devices enables convenient access to health monitoring tools, educational resources, and communication with healthcare providers. mHealth interventions encompass mobile apps, wearables, and telehealth services that empower users to monitor vital signs, adhere to medication, and adopt healthier lifestyles. Their effectiveness hinges on user engagement, leveraging behavioral science principles and gamification strategies. While mHealth offers advantages such as personalized support and increased reach, it faces challenges pertaining to data privacy, security concerns, and resistance from healthcare providers. Robust encryption and adherence to regulations like the Health Insurance Portability and Accountability Act (HIPAA) are crucial for safeguarding sensitive health data. Integrating mHealth into clinical workflows can enhance healthcare delivery, but organizational adjustments are necessary. The future of mHealth is closely intertwined with artificial intelligence (AI), enabling remote monitoring, predictive algorithms, and data-driven insights. Tech giants are incorporating advanced health-tracking capabilities into their devices, paving the way for personalized wellness approaches. However, mHealth grapples with ethical dilemmas surrounding data ownership, privacy breaches, and inadvertent data capture. Despite its potential, mHealth necessitates a concerted effort to overcome obstacles and ensure ethical, secure, and practical implementation. Addressing technical challenges, fostering standardization, and promoting equitable access are pivotal for unlocking the transformative impact of mHealth on cardiovascular health and reducing the global burden of CVD.

Predicting the Progression of Chronic Kidney Disease: A Systematic Review of Artificial Intelligence and Machine Learning Approaches.

Chronic kidney disease (CKD) is a progressive condition characterized by gradual loss of kidney function, necessitating timely monitoring and interventions. This systematic review comprehensively evaluates the application of artificial intelligence (AI) and machine learning (ML) techniques for predicting CKD progression. A rigorous literature search identified 13 relevant studies employing diverse AI/ML algorithms, including logistic regression, support vector machines, random forests, neural networks, and deep learning approaches. These studies primarily aimed to predict CKD progression to end-stage renal disease (ESRD) or the need for renal replacement therapy, with some focusing on diabetic kidney disease progression, proteinuria, or estimated glomerular filtration rate (GFR) decline. The findings highlight the promising predictive performance of AI/ML models, with several achieving high accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve scores. Key factors contributing to enhanced prediction included incorporating longitudinal data, baseline characteristics, and specific biomarkers such as estimated GFR, proteinuria, serum albumin, and hemoglobin levels. Integration of these predictive models with electronic health records and clinical decision support systems offers opportunities for timely risk identification, early interventions, and personalized management strategies. While challenges related to data quality, bias, and ethical considerations exist, the reviewed studies underscore the potential of AI/ML techniques to facilitate early detection, risk stratification, and targeted interventions for CKD patients. Ongoing research, external validation, and careful implementation are crucial to leveraging these advanced analytical approaches in clinical practice, ultimately improving outcomes and reducing the burden of CKD.

Preparation and application of hydroxypropyl methylcellulose blended with beeswax and essential oil edible coating to enhance the shelf life of sweet cherries.

The study involved preparing and applying edible nano-emulsion coatings containing hydroxypropyl methylcellulose (HPMC), beeswax (BW), and essential oils (thyme, cinnamon, clove, and peppermint) onto sweet cherries. The application was conducted at 4 °C, and the coated cherries were stored for 36 days. This research examines synthesized nano-emulsions physicochemical properties and antibacterial and antifungal activities (C1, C2, and C3). Additionally, it evaluates the quality parameters of control and coated sweet cherry samples. The features of the three edible coatings were assessed, and the findings from the zeta sizer, zeta potential, FTIR, and SEM analyses were deemed satisfactory. It was observed that the application of nano-emulsion coating C1 yielded positive results in maintaining quality attributes such as total suspended solids (TSS), total solids (TS), color, weight loss, respiration rate, firmness, total phenolic contents, and sensory evaluations. Nano-emulsion coating C1 demonstrated efficacy as an antibacterial and antifungal agent against foodborne pathogens E. coli and A. niger, respectively. The current research results are promising and applicable in food industries. The implications suggest that composite nano-emulsion, specifically nano-emulsion edible coatings, can be extensively and effectively used to preserve the quality and shelf life of fruits and vegetables. Furthermore, the environmental waste from conventional food packaging will be minimized using edible packaging applications.

Durability and Accelerated Ageing of Natural Fibers in Concrete as a Sustainable Construction Material.

This paper presents an experimental study on the influence of alkaline environments on natural fibers of plant and mineral origin in concretes. The durability of concrete-based composite materials is influenced by the properties of the reinforcing fiber, and the serviceability of concrete is dependent on its durability. The aim of the present study is to investigate the strength, weight loss %, and surface degradation of jute, sugarcane, coconut, sisal, as well as basalt fibers through an accelerated aging method when used as reinforcements in concrete. The samples were immersed in an alkaline environment of sodium and calcium hydroxide at two different levels of pH for one week. Further, the fibers were immersed in NaOH and Ca(OH)2 solutions of 1 M, 2 M, 4 M, and 6 M concentrations for 48 h in order to investigate the gradual effect of an alkaline environment on the mechanical properties of the fiber. It was concluded that the weight loss % was greatest for jute fibers when used in concrete composite, while there was no significant effect on the basalt fiber samples. The strength of jute fiber in the concrete sample was also most severely affected by the aging process, compared to other fibers. The strength of basalt fibers in a concrete composite was least affected by the aging process. In some cases, the sisal fiber sample showed an increase in fiber tenacity after the aging process due to fibrillation, which might have increased the interfacial area. The fiber microstructure before and after the aging was evaluated through the use of scanning electron microscopy (SEM). SEM analyses of different fibers were carried out to investigate surface degradation. The fiber pull-out strength was found to be the greatest for basalt fiber, followed by jute and sisal. This is indicative of the excellent adhesion of such fibers with cement in a concrete composite. In these cases, the use of sisal fiber results in defibrillation and increased specific surface area. Sugarcane and coconut fibers ruptured due to their inherent weakness and provided only a small increment in the mechanical performance of the concrete. Basalt fiber-reinforced concrete offered the greatest compressive strength, followed by jute and sisal. These observations provide crucial information regarding the durability and aging of natural fiber-reinforced concrete.

IgG4 Autoimmune Disease Masquerading As Oroantral Fistula.

IgG4-related disease (IgG4-RD) is an immune-mediated disorder that involves multiple organs and is characterized by the infiltration of lymphoplasmacytic cells, including IgG4-positive plasma cells, along with storiform fibrosis and obliterative phlebitis in the inflamed organs. The primary sites affected by this condition include the pancreas, bile ducts, salivary glands, aorta, lungs, kidneys, meninges, lacrimal glands, mediastinal lymph nodes, and retroperitoneum. The pathogenesis is linked to a type 2 T-helper-cell cytokine profile and the involvement of regulatory T cells. However, the exact mechanism is still unknown. Patients with IgG4-related disease are frequently misdiagnosed as having malignancies due to the resemblance of the lesions to infections or other immune-mediated diseases and certain tumors, such as pancreatic cancer and pseudo-renal pelvis tumor. Prompt identification of IgG4-related disease is essential as a delayed diagnosis until advanced stages can result in severe organ damage and potentially fatal outcomes, despite the disease being highly responsive to treatment. This report presents a highly unusual case of IgG4-related disease (IgG4-RD) with an atypical presentation in a 38-year-old female patient. The patient sought medical attention in the emergency department due to nasal septal erosions and an oral-antral fistula. Nasal cultures were conducted and indicated the presence of Klebsiella ozaena. Subsequent investigations, including a nasal biopsy, confirmed the diagnosis of IgG4-related autoimmune disease.

Optimization of seismic performance in waste fibre reinforced concrete by TOPSIS method.

For a sustainable environment and to tackle the pollution problem, industrial wastes can be used in concrete composite materials. This is especially beneficial in places prone to earth quack and lower temperature. In this study, five different types of waste fibres such as polyester waste, rubber waste, rock wool waste, glass fibre waste and coconut fibre waste were used as an additive in 0.5% 1%, and 1.5% by mass in concrete mix. Seismic performance related properties of the samples were examined through evaluation of compressive strength, flexural strength, impact strength, split tensile strength, and thermal conductivity. Results showed that, impact strength of the concrete significantly improved by the addition of fibre reinforcement in concrete. Split tensile strength and flexural strength were significantly reduced. Thermal conductivity was also influenced by addition of polymeric fibrous waste. Microscopic analysis was performed to examine the fractured surfaces. In order to get the optimum mix ratio, multi response optimization technique was used to determine the desired level of impact strength at an acceptable level of other properties. Rubber waste was found to be the most attractive option followed by coconut fibre waste for the seismic application of concrete. The significance and percentage contribution of each factor was obtained by Analysis of variance ANOVA (α = 0.05) and pie chart which showed that Factor A (waste fibre type) is the main contributor. Confirmatory test was done on optimized waste material and their percentage. The order preference similarity to ideal solution (TOPSIS) technique was used for developed samples to obtain solution (sample) which is closest to ideal as per given weightage and preference for the decision making. The confirmatory test gives satisfactory results with error of 6.68%. Cost of reference sample and waste rubber reinforced concrete sample was estimated, which showed that 8% higher volume was achieved with waste fibre reinforced concrete at approximately same cost as pure concrete. Concrete reinforced with recycled fibre content is potentially beneficial in terms of minimizing resource depletion and waste. The addition of polymeric fibre waste in concrete composite not only improves seismic performance related properties but also reduces the environmental pollution from waste material which has no other end use.

Multiscale Principal Component Analysis-Signed Directed Graph Based Process Monitoring and Fault Diagnosis.

The chemical process industry has become the backbone of the global economy. The complexities of chemical process systems have been increased in the last two decades due to online sensor technology, plant-wide automation, and computerized measurement devices. Principal component analysis (PCA) and signed directed graph (SDG) are some of the quantitative and qualitative monitoring techniques that have been widely applied for chemical fault detection and diagnosis (FDD). The conventional PCA-SDG algorithm is a single-scale FDD representation origin, which cannot effectively solve multiple FDD representation origins. The multiscale PCA-SDG wavelet-based monitoring technique has potential because it easily distinguishes between deterministic and stochastic characteristics. This study uses multiscale PCA-SDG to detect, diagnose the root cause and identify the fault propagation path. The proposed method is applied to a continuous stirred tank reactor system to validate its effectiveness. The propagation route of most process failures is detected, identified, and diagnosed, which is well-aligned with the fault description, demonstrating a satisfactory performance of the suggested technique for monitoring the process failures.

Importance Of Clinical Risk Index For Babies Score For Predicting Mortality Among Neonates.

BACKGROUND: High mortality among premature and very low birth weight (VLBW) babies necessitates the need to formulate and use scoring systems like CRIB score to predict the mortality in this vulnerable group. Objective of the study was to determine the strength of Clinical Risk Index For Babies (CRIB) score in detecting neonatal mortality in babies presenting with very low birth weight so that timely intervention can be done. It was a cross-sectional study, conducted at NICU, Children Hospital, Pakistan Institute of Medical Sciences Islamabad (PIMS) in nine months starting from First July 2017. METHODS: A total of two hundred and fifty-four (n=254) new-borns with birth weight of between 500-1500 grams and gestational age lesser than 35 weeks were included in the study. CRIB score was calculated in all neonates and its association was assessed with mortality during NICU stay. Recorded data was analysed for demographic variables. Means and standard deviation was calculated for numeric variables. Chi-square test was applied to find p-value for the correlation between the main variables. RESULTS: 54.3% (n=138) patients were males and 45.7% (n=116) were females. Mean gestational age was 33.3 weeks±1.04 SD and mean birth weight of study population was 1129.9 grams±210.6 SD. Mean CRIB score among the study population was 6.3±3.1SD and overall mortality was found to be 54.7% (n=139). Mean CRIB score was found to be 8.27±2.1 SD among mortality group and it was 3.87±3.4 SD among newborns who were discharged (p<0.05). Mortality was present in 4.3% (n=4) of neonates with CRIB score between 1 to 5, 87.1% (n=121) who had CRIB score between 6 to 10 and 100% (n=14) of neonates who had CRIB score level 11-15 (p<0.05), so a significantly higher percentage mortality was noted among neonates with higher CRIB scores. CONCLUSIONS: According to our study mean CRIB score is a significant predictor of neonatal mortality.

Sensitivity Profiles of Human Prostate Cancer Cell Lines to an 80 Kinase Inhibitor Panel.

BACKGROUND: Taxanes and anti-androgen therapies are routinely used for the treatment of metastatic prostate cancer, however the majority of patients eventually develop resistance. MATERIALS AND METHODS: Eighty kinase inhibitors were screened regarding their ability to inhibit cell viability in CWR22, 22Rv1, PC-3 and DU145 prostate cancer cells using automated toxicity assays. Four kinase inhibitors were selected for further investigation. RESULTS: No significant difference in sensitivity patterns was found between the androgen receptor wild-type CWR22 and its androgen receptor mutant variant 22Rv1, indicating that androgen receptor mutation did not impact on kinase inhibitor sensitivity in this model. Metastatic PC-3 and DU145 prostate cancer cell lines were less sensitive to kinase inhibitors than the non-metastatic CWR22 and 22Rv1. All four cell lines responded to GSK-3 inhibitor BIO, and MEK inhibitor PD198306. DU145 cells were resistant to p75NTR/TrkA and CHK4 inhibitors, RO-082750 and Ryuvidine. CONCLUSION: Kinase inhibition may be an appropriate strategy for the treatment of prostate cancer.

Cranial meningioma co-localised with Langerhans cell histiocytosis.

We present a case in which a patient was initially diagnosed and treated for a para-cavernous meningioma with radiotherapy. An accompanying lesion overlying the left frontal convexity was surgically removed several months later to provide a histological diagnosis. Surprisingly, meningioma and Langherhans cell histiocytosis were found in the same lesion.

Beliefs and perceptions of acne among a sample of students from Sindh Medical College, Karachi.

OBJECTIVE: To determine the beliefs of undergraduate medical students regarding acne. METHOD: A cross-sectional study in 630 medical students (aged 16-29 years) was conducted. A voluntary self administered questionnaire was used to collect data regarding their beliefs and perceptions about acne. Both acne and non-acne sufferers were included in the study. RESULT: Of the 630 respondents, 55.9% were sufferers while 44.1% were non-sufferers. Of all, 67.0% of the affected believed it to be relieved by frequent face washing and that they should seek treatment, whereas 79.84% students believed in seeking dermatologist's advice regarding treatment. Mass media was the most common source of information. As to the cause, 21.7% students believed that hereditary factors and 20.1% thought environmental factors are the major cause of acne. In diet, soft drinks (29.2%) were considered the major exacerbating factor. The most significant emotional impact of acne on medical students was embarrassment (26.2%). CONCLUSION: The results of this study pointed out that misconceptions and false beliefs on acne are widespread and enduring among Medical students' too. Health education programme on acne is needed to improve their understanding of the condition.