Search Results (694)

Background: Traumatic brain injury manifests itself in various forms, ranging from mild impairment of consciousness to severe coma and death. Traumatic brain injury remains one of the leading causes of morbidity and mortality. Currently, there is no therapy to reverse the effects associated with traumatic brain injury. New neuroprotective treatments for severe traumatic brain injury have not achieved significant clinical success. Methods: A literature review was performed to summarize the recent interdisciplinary findings on management of traumatic brain injury from both clinical and experimental perspective. Results: In the present review, we discuss the concepts of traditional and new approaches to treatment of traumatic brain injury. The recent development of different drug delivery approaches to the central nervous system is also discussed. Conclusions: The management of traumatic brain injury could be aimed either at the pathological mechanisms initiating the secondary brain injury or alleviating the symptoms accompanying the injury. In many cases, however, the treatment should be complex and include a variety of medical interventions and combination therapy. Full article

The human leucocyte antigen (HLA) allele variability was studied in cohorts of patients with idiosyncratic drug-induced liver injury (iDILI). Some reports showed an association between HLA genetics and iDILI, proposing HLA alleles as a potential risk factor for the liver injury. However, the strength of such assumptions heavily depends on the quality of the iDILI diagnosis, calling for a thorough analysis. Using the PubMed database and Google Science, a total of 25 reports of case series or single cases were retrieved using the terms HLA genes and iDILI. It turned out that in 10/25 reports (40%), HLA genetics were determined in iDILI cases, for which no causality assessment method (CAM) was used or a non-validated tool was applied, meaning the findings were based on subjective opinion, providing disputable results and hence not scoring individual key elements. By contrast, in most iDILI reports (60%), the Roussel Uclaf Causality Assessment Method (RUCAM) was applied, which is the diagnostic algorithm preferred worldwide to assess causality in iDILI cases and represents a quantitative, objective tool that has been well validated by both internal and external DILI experts. The RUCAM provided evidence-based results concerning liver injury by 1 drug class (antituberculotics + antiretrovirals) and 19 different drugs, comprising 900 iDILI cases. Among the top-ranking drugs were amoxicillin–clavulanate (290 cases, HLA A*02:01 or HLA A*30:02), followed by flucloxacillin (255 cases, HLA B*57:01), trimethoprim–sulfamethoxazole (86 cases, HLA B*14:01 or HLA B*14:02), methimazole (40 cases, HLA C*03:02), carbamazepine (29 cases, HLA A*31:01), and nitrofurantoin (26 cases, HLA A*33:01). In conclusion, the HLA genetics in 900 idiosyncratic drug-induced liver injury cases with evidence based on the RUCAM are available for studying the mechanistic steps leading to the injury, including metabolic factors through cytochrome P450 isoforms and processes that activate the innate immune system to the adaptive immune system. Full article

Eosinophilic esophagitis (EoE) disease activity can be caused by treatment non-adherence. Medication possession ratio (MPR) is an established metric of medication adherence. A higher MPR correlates with better outcomes in several chronic diseases, but MPR has not been investigated with respect to EoE. A retrospective cohort study was performed using an established EoE registry for the years 2005 to 2020. Treatment periods were identified, MPRs were calculated, and medical records were assessed for histologic remission (<15 eos/hpf), dysphagia, food impaction, stricture occurrence, and esophageal dilation that corresponded to each treatment period. In total, 275 treatment periods were included for analysis. The MPR in the histologic remission treatment period group was 0.91 (IQR 0.63–1) vs. 0.63 (IQR 0.31–0.95) for the non-remission treatment period group (p < 0.001). The optimal MPR cut-point for histologic remission was 0.7 (Sen 0.66, Spec 0.62, AUC 0.63). With MPRs ≥ 0.7, there were significantly increased odds of histologic remission (odds ratio 3.05, 95% confidence interval 1.79–5.30) and significantly decreased odds of dysphagia (OR 0.27, 95% CI 0.15–0.45), food impaction (OR 0.26, 95% CI 0.11–0.55), stricture occurrence (OR 0.52 95% CI 0.29–0.92), and esophageal dilation (OR 0.29, 95% CI 0.15–0.54). Assessing MPR before repeating an esophagogastroduodenoscopy may decrease unnecessary procedures in the clinical management of eosinophilic esophagitis. Full article

Background: This study investigated how the expression of heat shock protein 27 (HSP27), cellular FLICE-like inhibitory protein (cFLIP), and clusterin (CLU) affects the progression of cancer cells and their susceptibility to doxazosin-induced apoptosis. By silencing each of these genes individually, their effect on prostate cancer cell viability after doxazosin treatment was investigated. Methods: PC-3 prostate cancer cells were cultured and then subjected to gene silencing using siRNA targeting HSP27, cFLIP, and CLU, either individually, in pairs, or all together. Cells were then treated with doxazosin at various concentrations and their viability was assessed by MTT assay. Results: The study found that silencing the CLU gene in PC-3 cells significantly reduced cell viability after treatment with 25 µM doxazosin. In addition, the dual silencing of cFLIP and CLU decreased cell viability at 10 µM doxazosin. Notably, silencing all three genes of HSP27, cFLIP, CLU was most effective and reduced cell viability even at a lower doxazosin concentration of 1 µM. Conclusions: Taken together, these findings suggest that the simultaneous silencing of HSP27, cFLIP, and CLU genes may be a potential strategy to promote apoptosis in prostate cancer cells, which could inform future research on treatments for malignant prostate cancer. Full article

Pharmacogenomics (PGx) can facilitate the transition to patient-specific drug regimens and thus improve their efficacy and reduce toxicity. The aim of this study was to evaluate the overlap of PGx classification for drug absorption, distribution, metabolism, and elimination (ADME)-related genes in the U.S. Food and Drug Administration (FDA) PGx labeling and in the Clinical Pharmacogenetics Implementation Consortium (CPIC) database. FDA-approved drugs and PGx labeling for ADME genes were identified in the CPIC database. Drugs were filtered by their association with ADME (pharmacokinetics)-related genes, PGx FDA labeling class, and CPIC evidence level. FDA PGx labeling was classified as either actionable, informative, testing recommended, or testing required, and varying CPIC evidence levels as either A, B, C, or D. From a total of 442 ADME and non-ADME gene–drug pairs in the CPIC database, 273, 55, and 48 pairs were excluded for lack of FDA labeling, mixed CPIC evidence level provisional classification, and non-ADME gene–drug pairs, respectively. The 66 ADME gene–drug pairs were classified into the following categories: 10 (15%) informative, 49 (74%) actionable, 6 (9%) testing recommended, and 1 (2%) testing required. CYP2D6 was the most prevalent gene among the FDA PGx labeling. From the ADME gene–drug pairs with both FDA and CPIC PGx classification, the majority of the drugs were for depression, cancer, and pain medications. The ADME gene–drug pairs with FDA PGx labeling considerably overlap with CPIC classification; however, a large number of ADME gene–drug pairs have only CPIC evidence levels but not FDA classification. PGx actionable labeling was the most common classification, with CYP2D6 as the most prevalent ADME gene in the FDA PGx labeling. Health professionals can impact therapeutic outcomes via pharmacogenetic interventions by analyzing and reconciling the FDA labels and CPIC database. Full article

Background: Cancer therapeutics have a low success rate in clinical trials. An interdisciplinary approach is needed to translate basic, clinical, and remote fields of research knowledge into novel cancer treatments. Recent research has identified high dietary phosphate intake as a risk factor associated with cancer incidence. A model of tumor dynamics predicted that reducing phosphate levels sequestered in the tumor microenvironment could substantially reduce tumor size. Coincidently, a low-phosphate diet is already in use to help patients with chronic kidney disease manage high serum phosphate levels. Methods: A grounded-theory literature-review method was used to synthesize interdisciplinary findings from the basic and clinical sciences, including oncology, nephrology, nutritional epidemiology, and dietetic research on cancer. Results: Findings of tumor remission associated with fasting and a ketogenic diet, which lower intake of dietary phosphate, support the hypothesis that a low-phosphate diet will reduce levels of phosphate sequestered in the tumor microenvironment and reduce tumor size. Additionally, long-term effects of a low-phosphate diet may reverse dysregulated phosphate metabolism associated with tumorigenesis and prevent cancer recurrence. Conclusions: Evidence in this article provides the rationale to test a low-phosphate diet as a dietary intervention to reduce tumor size and lower risk of cancer recurrence. Full article

Background: Obesity is linked to chronic diseases in adults and children. Its prevalence continues to grow in the United States, necessitating the need for healthcare provider training and presenting an opportunity for the education of future medical providers. Despite this need, effectively implementing obesity education into medical school curricula has been challenging. Anti-obesity bias amongst healthcare providers and trainees represents a significant obstacle to the care of patients with obesity. Obesity bias may affect up to 1/3 of medical students. Methods: This study describes the development and preliminary testing of a brief, 2.5 h multi-modality teaching intervention consisting of online, interactive, and independent learning modules for first-year medical students and a patient panel focused on obesity, obesity bias, and motivational interviewing. The participants took Crandall’s anti-fat attitude (AFA) questionnaire before and after an online independent learning module on motivational interviewing and obesity bias. The AFA consists of three subscales (“dislike”, “fear of fat”, and “willpower”). Individual responses were measured using a nine-point Likert-type response format (0 = very strongly disagree; 9 = very strongly agree). An average composite score was calculated for each subscale. Results: Data were analyzed from 103 first-year medical students enrolled at a college of medicine in the southwestern United States in 2022. The AFA mean composite scores decreased significantly, indicating a decrease in explicit anti-obesity attitude bias after completing the online module. This decrease was present in all three domains of fear (4.63 vs. 3.72, p < 0.001), dislike (1.25 vs. 0.88, p < 0.001) and willpower (3.23 vs. 2.31, p < 0.001). Conclusions: Relatively brief educational interventions can positively impact students’ anti-obesity attitudes. Full article

Background: The objective of this study is to find novel antineoplastic agents that display greater toxicity to malignant cells than to neoplasms. In addition, the mechanisms of action of representative compounds are sought. This report describes the cytotoxicity of a number of dimers of 3,5-bis(benzylidene)-4-piperidones against human malignant cells (promyelocytic leukemia HL-60 and squamous cell carcinoma HSC-2, HSC-3, and HSC-4). Methods: Tumor specificity was evaluated by the selectivity index (SI), that is the ratio of the mean CC₅₀ for human non-malignant oral cells (gingival fibroblasts, pulp cells, periodontal ligament fibroblasts) to that for malignant cells. Results: The compounds were highly toxic to human malignant cells. On the other hand, these molecules were less toxic to human non-malignant cells. In particular, a potent lead molecule, 3b, was identified. A QSAR study revealed that the placement of electron-releasing and hydrophilic substituents into the aryl rings led to increases in cytotoxic potencies. The modes of action of a lead compound discovered in this study designated 3b were the activation of caspases-3 and -7, as well as causing PARP1 cleavage and G2 arrest, followed by sub-G1 accumulation in the cell cycle. This compound also depolarized the mitochondrial membrane and generated reactive oxygen species in human colon carcinoma HCT116 cells. In conclusion, this study has revealed that, in general, the compounds described in this report are tumor-selective cytotoxins. Full article

Background: Hypoxia is a well-recognized characteristic of the tumor microenvironment of solid cancers. This study aimed to analyze hypoxia-related genes shared by groups based on tumor location. Methods: A total of 9 hypoxia-related pathways from the Kyoto Encyclopedia of Genes and Genomes database or the Reactome database were selected, and 850 hypoxia-related genes were analyzed. Based on their anatomical locations, 14 tumor types were categorized into 6 groups. The group-specific genetic risk score was classified as high- or low-risk based on mRNA expression, and survival outcomes were evaluated. Results: The risk scores in the Female Reproductive group and the Lung group were internally and externally validated. In the Female Reproductive group, CDKN2A, FN1, and ITGA5 were identified as hub genes associated with poor prognosis, while IL2RB and LEF1 were associated with favorable prognosis. In the Lung group, ITGB1 and LDHA were associated with poor prognosis, and GLS2 was associated with favorable prognosis. Functional enrichment analysis showed that the Female Reproductive group was enriched in relation to cilia and skin, while the Lung group was enriched in relation to cytokines and defense. Conclusions: This analysis may lead to better understanding of the mechanisms of cancer progression and facilitate establishing new biomarkers for prognosis prediction. Full article

Heart failure (HF) presents an increasingly significant problem as the population ages. The cause of HF plays a significant role in determining treatment options and outcomes. It is worth noting that several studies have identified gender disparities in both morbidity and mortality, which may suggest differing causes of HF. The purpose of this research is to investigate the influence of various factors, including demographics and comorbidities, on ejection fraction (EF). The objectives of this study involve implementing preventive measures, ensuring timely diagnosis, and implementing interventions that target risk factors and specific comorbidities. These efforts aim to improve the prognosis for individuals affected by heart failure. The main method consists of linear regression. The demographic factors under scrutiny are gender and education, while the comorbidities of interest encompass valvulopathy, ischemia, smoking, obesity, high cholesterol, and diabetes. The main results consist of the fact that high education is associated with a 12.8% better EF on average, while among the factors with a negative role analyzed, ischemia is the most harmful, being 12.8% lower on average. Factors with a smaller impact are smoking, obesity, and high cholesterol. Diabetes does not seem to affect EF. Full article

Background: Malnutrition in cardiovascular disease is associated with poor prognosis, especially in patients with heart failure and acute coronary syndrome (ACS). High bleeding risk is also linked to coronary artery disease prognosis, including ACS. However, whether the extent of malnutrition and high bleeding risk have a cumulative impact on the long-term prognosis of patients with ACS who undergo percutaneous coronary intervention remains unclear. Methods: We analyzed 275 patients with ACS treated with percutaneous coronary intervention. The Controlling Nutritional Status score and Japanese version of the Academic Research Consortium for High Bleeding Risk criteria (J-HBR) were retrospectively evaluated. The primary and secondary outcomes were adjusted using the inverse probability treatment weighting method. Results: The prevalence of moderate or severe malnutrition in this cohort was 16%. Kaplan–Meier analysis showed a significantly higher incidence of major adverse cardiovascular and cerebrovascular events in patients who were moderately or severely malnourished than in those who were not. Notably, the incidence of these major events was similar between severely malnourished patients with J-HBR and those without. Conclusion: Moderate or severe malnutrition has a significant impact on the long-term prognosis of patients with ACS who undergo percutaneous coronary intervention. Full article

As an alternative to animal use, computer simulations are useful for predicting pharmacokinetics and cardiovascular activities. For this purpose, we constructed a statistical model to simulate the effects of local anesthetic agents. To train the model, animal experiments were performed on 6-week-old male Hartley guinea pigs. Firstly, the guinea pigs’ backs were shaved, then local anesthetic agents were subcutaneously injected, with subsequent stimulation of the anesthetized site with a needle six times at regular intervals. The number of reactions (score value) was counted. In this statistical model, the probability of reacting to needle stimulation was calculated using the elapsed time, type of local anesthetic agent, and presence or absence of adrenaline. Score values were assumed to follow a binomial distribution at the calculated probability. Parameters were estimated using the Bayesian hierarchical model and Hamiltonian Monte Carlo method. The predicted curves using the estimated parameters fitted well the observed animal values. When score values were predicted using randomly generated parameters, the median of duration was similar between animal experiments and simulations (Procaine: 55 min vs. 50 min, Lidocaine: both 60 min, and Mepivacaine: both 85 min). This approach effectively modeled the effects of local anesthetic agents. It is possible to create the simulator using the parameter values estimated in this study. Full article

Background: There is a high prevalence of sleep disorders in Japan, and they are a factor in a decreased quality of life. The main objective of this study was to clarify the background factors of sleep disorders that affect sleep duration, such as subjective symptoms and working hours. Methods: We performed a cross-sectional study on the Japanese national statistics data. Answers from a household questionnaire were used to analyze risk factors for decreases in sleep duration. The subjects were a total of 3972 men and women aged 40–59 years, the age group that forms the core of the working population. For the analysis, a univariate analysis (contingency table) between sleep duration (two groups: sleep duration ≥ 6 h and <6 h) and 42 subjective symptoms was carried out. A multivariate analysis (binomial logistic regression) was conducted using sleep duration and subjective health assessment as objective variables, and odds ratios (ORs) adjusted for sex, working hours, and other factors were obtained. Results: The univariate analysis by subjective symptom showed significant ORs for eight symptoms, including poor sleep quality (OR: 2.24), constipation (OR: 2.24), and dizziness (OR: 1.77). In the multivariate analysis, the model with sleep duration as the objective variable showed significantly adjusted ORs for four variables, including constipation (1.72) and poor sleep quality (1.66). The model with subjective health assessment as the objective variable showed significantly adjusted ORs for eight variables, including dizziness (4.18), while poor sleep quality (1.45) was not significant. Conclusions: The present results suggest the presence of subjective symptoms that may be inferred to be related to decreases in sleep duration. Full article

Background: Early detection of elderly patients with COVID-19 who are at high risk of mortality is vital for appropriate clinical decisions. We aimed to evaluate the risk factors associated with all-cause in-hospital mortality among elderly patients with COVID-19. Methods: In this retrospective study, the medical records of elderly patients aged over 60 who were hospitalized with COVID-19 at Thammasat University Hospital from 1 July to 30 September 2021 were reviewed. Multivariate logistic regression was used to identify independent predictors of mortality. The sum of weighted integers was used as a total risk score for each patient. Results: In total, 138 medical records of patients were reviewed. Four identified variables based on the odds ratio (age, respiratory rate, glomerular filtration rate and history of stroke) were assigned a weighted integer and were developed to predict mortality risk in hospitalized elderly patients. The AUROC of the scoring system were 0.9415 (95% confidence interval, 0.9033–0.9716). The optimized scoring system was developed and a risk score over 213 was considered a cut-off point for high mortality risk. Conclusions: A simple predictive risk score provides an initial assessment of mortality risk at the time of admission with a high degree of accuracy among hospitalized elderly patients with COVID-19. Full article

The exponential growth of artificial intelligence (AI) has allowed for its integration into multiple sectors, including, notably, healthcare. Chatbots have emerged as a pivotal resource for improving patient outcomes and assisting healthcare practitioners through various AI-based technologies. In critical care, kidney-related conditions play a significant role in determining patient outcomes. This article examines the potential for integrating chatbots into the workflows of critical care nephrology to optimize patient care. We detail their specific applications in critical care nephrology, such as managing acute kidney injury, alert systems, and continuous renal replacement therapy (CRRT); facilitating discussions around palliative care; and bolstering collaboration within a multidisciplinary team. Chatbots have the potential to augment real-time data availability, evaluate renal health, identify potential risk factors, build predictive models, and monitor patient progress. Moreover, they provide a platform for enhancing communication and education for both patients and healthcare providers, paving the way for enriched knowledge and honed professional skills. However, it is vital to recognize the inherent challenges and limitations when using chatbots in this domain. Here, we provide an in-depth exploration of the concerns tied to chatbots’ accuracy, dependability, data protection and security, transparency, potential algorithmic biases, and ethical implications in critical care nephrology. While human discernment and intervention are indispensable, especially in complex medical scenarios or intricate situations, the sustained advancements in AI signal that the integration of precision-engineered chatbot algorithms within critical care nephrology has considerable potential to elevate patient care and pivotal outcome metrics in the future. Full article