Search

Abstract Background This study aimed to assess the factors influencing health-related quality of life (HRQoL) in patients experiencing adverse drug reactions (ADRs) at a tertiary care public sector hospital. A cross-sectional study was conducted over a period of 18 months, and included both male and female patients aged 18 years and above. Patients who visited the outpatient and inpatient departments with complaints associated with ADRs were included in this study. HRQoL data were collected using the EuroQol—5 Dimension—5 Level (EQ-5D-5L) questionnaire to assess five dimensions of health on a five-level scale. Descriptive statistics, t-tests, and analysis of variance were used to analyze the data. Multivariate regression analysis was performed to identify the potential determinants of HRQoL. Results A total of 316 patients were included in the study among these participants, of which 54% were female, and 65% were from rural areas. The majority (68%) of the patients had moderately severe ADRs, and 63% of the participants had an income

Background: Antibiotics are the most commonly used drugs to treat bacterial infections; however, these life-saving drugs can also cause adverse drug reactions. In several pharmacovigilance studies, adverse drug reactions are a cause of prolonged hospitalization. The development of hypersensitivity reactions even after a negative skin test and patch test makes antibiotic-associated adverse reactions unpredictable. Owing to the scarcity of data on antibiotic desensitization, these drugs are important for pharmacovigilance. Most of the previous studies conducted were retrospective and lacked data regarding the duration of adverse drug reactions. Aim: This study aimed to examine adverse drug reactions associated with antibiotics and to provide knowledge on the duration of these reactions. Method: A prospective observational study was conducted on patients receiving antibiotics at a tertiary care hospital. The patients were followed until discharge, and causality and severity assessments were performed. Descriptive statistical analyses were performed to summarize the data. Results: The study results show the median duration of adverse drug reactions was two days, with an interquartile range of two to four days. Most (21,3%) of the reactions were caused by cephalosporins. The majority (44.7%) of the reactions were skin and subcutaneous tissue disorders. The majority (78.7%) of the reactions were moderately severe and were not responsible for prolonged hospital stay. Conclusion: The patients receiving antibiotics require close monitoring for early detection and management of adverse reactions to reduce the duration of hospital stay and the duration of adverse drug reactions.

The objective of this work was to examine the impact of conventional and RAFT-modified SiO₂ nanoparticles on the mechanical characteristics and crystallinity of poly(ethylene oxide) (PEO) composites. Preparation of PEO composites included the incorporation of 5 wt% of both unaltered SiO₃ and SiO₃ that had been changed via reversible addition-fragmentation chain transfer (RAFT) polymerization. We assessed the mechanical characteristics, such as strain at fracture, ultimate tensile strength, and Young’s modulus. The inclusion of unaltered SiO₂ decreased the strain at fracture (570 ± 18%) and ultimate tensile strength (22.5 ± 0.8 MPa) in comparison to pure PEO (850 ± 25%, 32.0 ± 1.2 MPa). Nevertheless, the inclusion of RAFT-modified SiO₂ led to improved tensile characteristics, including a strain at break of 800 ± 30%, ultimate tensile strength of 35.2 ± 2.5 MPa, and Young’s modulus of 260 ± 13 MPa. The effective dispersion of RAFT- modified SiO₂ in the PEO matrix was verified by X-ray diffraction (XRD), leading to enhanced mechanical characteristics. This research points that the using the RAFT polymerization to alter the surface of nanoparticles is a good strategy to enhance the efficiencies of PEO composite for potential application in versatile electronics, membranes and other polymers technologies.

Treatment-resistant depression (TRD) is one of the most debilitating conditions that does not respond to conventional pharmacotherapy. Ketamine is a recently used effective treatment option in depressive disorders with a novel mechanism of action. Still, studies estimating the improvement of depressive symptoms in TRD with multiple doses of ketamine are limited. Hence, we report 5 TRD cases that received six open-label intravenous (IV) infusions of ketamine. Five cases of TRD, diagnosed by a clinician defined as the persistence of significant depressive symptoms despite being treated with two different antidepressant regimens, each used for more than 6 weeks were evaluated to identify the need for ketamine infusion and were administered six open-label IV infusions of ketamine which were done at the rate of 0.5 mg/kg body weight, thrice weekly, on alternative days for 2 weeks, following standard protocol. The Montgomery–Åsberg Depression Rating Scale (MADRS) scores were administered by the clinician before the infusion and were repeated after 2 weeks post-infusion. The response was recorded and was seen as a more than 50% decrease in MADRS scores and our cases showed significant improvement clinically. Our low infusion rate and serial dosing trial with ketamine support the efficacy of this drug in TRD. Approximately 30% of patients with major depressive disorder are treatment-resistant. New treatment strategies are needed to address that portion of cases. Subanesthetic doses of IV ketamine have a rapid antidepressant effect in TRD, this signifies the potential of ketamine to be used in this regard.

Abstract Background Glycosylation is an enzyme-catalyzed post-translational modification that is distinct from glycation and is present on a majority of plasma proteins. N-glycosylation occurs on asparagine residues predominantly within canonical N-glycosylation motifs (Asn-X-Ser/Thr) although non-canonical N-glycosylation motifs Asn-X-Cys/Val have also been reported. Albumin is the most abundant protein in plasma whose glycation is well-studied in diabetes mellitus. However, albumin has long been considered a non-glycosylated protein due to absence of canonical motifs. Albumin contains two non-canonical N-glycosylation motifs, of which one was recently reported to be glycosylated. Methods We enriched abundant serum proteins to investigate their N-linked glycosylation followed by trypsin digestion and glycopeptide enrichment by size-exclusion or mixed-mode anion-exchange chromatography. Glycosylation at canonical as well as non-canonical sites was evaluated by liquid chromatography–tandem mass spectrometry (LC–MS/MS) of enriched glycopeptides. Deglycosylation analysis was performed to confirm N-linked glycosylation at non-canonical sites. Albumin-derived glycopeptides were fragmented by MS3 to confirm attached glycans. Parallel reaction monitoring was carried out on twenty additional samples to validate these findings. Bovine and rabbit albumin-derived glycopeptides were similarly analyzed by LC–MS/MS. Results Human albumin is N-glycosylated at two non-canonical sites, Asn68 and Asn123. N-glycopeptides were detected at both sites bearing four complex sialylated glycans and validated by MS3-based fragmentation and deglycosylation studies. Targeted mass spectrometry confirmed glycosylation in twenty additional donor samples. Finally, the highly conserved Asn123 in bovine and rabbit serum albumin was also found to be glycosylated. Conclusions Albumin is a glycoprotein with conserved N-linked glycosylation sites that could have potential clinical applications.

IntroductionThe prevalence of Renal cell carcinoma (RCC) is increasing among adults. Histopathologic samples obtained after surgical resection or from biopsies of a renal mass require subtype classification for diagnosis, prognosis, and to determine surveillance. Deep learning in artificial intelligence (AI) and pathomics are rapidly advancing, leading to numerous applications such as histopathological diagnosis. In our meta-analysis, we assessed the pooled diagnostic performances of deep neural network (DNN) frameworks in detecting RCC subtypes and to predicting survival.MethodsA systematic search was done in PubMed, Google Scholar, Embase, and Scopus from inception to November 2023. The random effects model was used to calculate the pooled percentages, mean, and 95% confidence interval. Accuracy was defined as the number of cases identified by AI out of the total number of cases, i.e. (True Positive + True Negative)/(True Positive + True Negative + False Positive + False Negative). The heterogeneity between study-specific estimates was assessed by the I2 statistic. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to conduct and report the analysis.ResultsThe search retrieved 347 studies; 13 retrospective studies evaluating 5340 patients were included in the final analysis. The pooled performance of the DNN was as follows: accuracy 92.3% (95% CI: 85.8–95.9; I2 = 98.3%), sensitivity 97.5% (95% CI: 83.2–99.7; I2 = 92%), specificity 89.2% (95% CI: 29.9–99.4; I2 = 99.6%) and area under the curve 0.91 (95% CI: 0.85–0.97.3; I2 = 99.6%). Specifically, their accuracy in RCC subtype detection was 93.5% (95% CI: 88.7–96.3; I2 = 92%), and the accuracy in survival analysis prediction was 81% (95% CI: 67.8–89.6; I2 = 94.4%).DiscussionThe DNN showed excellent pooled diagnostic accuracy rates to classify RCC into subtypes and grade them for prognostic purposes. Further studies are required to establish generalizability and validate these findings on a larger scale.

ABSTRACT Copious amounts of methane, a major constituent of greenhouse gases currently driving climate change, are emitted by livestock, and efficient methods that curb such emissions are urgently needed to reduce global warming. When fed to cows, the red seaweed Asparagopsis taxiformis (AT) can reduce enteric methane emissions by up to 80%, but the achieved results can vary widely. Livestock produce methane as a byproduct of methanogenesis, which occurs during the breakdown of feed by microbes in the rumen. The ruminant microbiome is a diverse ecosystem comprising bacteria, protozoa, fungi, and archaea, and methanogenic archaea work synergistically with bacteria to produce methane. Here, we find that an effective reduction in methane emission by high-dose AT (0.5% dry matter intake) was associated with a reduction in methanol-utilizing Methanosphaera within the rumen, suggesting that they may play a greater role in methane formation than previously thought. However, a later spike in Methanosphaera suggested an acquired resistance, possibly via the reductive dehalogenation of bromoform. While we found that AT inhibition of methanogenesis indirectly impacted ruminal bacteria and fermentation pathways due to an increase in spared H2, we also found that an increase in butyrate synthesis was due to a direct effect of AT on butyrate-producing bacteria such as Butyrivibrio, Moryella, and Eubacterium. Together, our findings provide several novel insights into the impact of AT on both methane emissions and the microbiome, thereby elucidating additional pathways that may need to be targeted to maintain its inhibitory effects while preserving microbiome health and animal productivity.IMPORTANCELivestock emits copious quantities of methane, a major constituent of the greenhouse gases currently driving climate change. Methanogens within the bovine rumen produce methane during the breakdown of feed. While the red seaweed Asparagopsis taxiformis (AT) can significantly reduce methane emissions when fed to cows, its effects appear short-lived. This study revealed that the effective reduction of methane emissions by AT was accompanied by the near-total elimination of methane-generating Methanosphaera. However, Methanosphaera populations subsequently rebounded due to their ability to inactivate bromoform, a major inhibitor of methane formation found in AT. This study presents novel findings on the contribution of Methanosphaera to ruminal methanogenesis, the mode of action of AT, and the possibility for complementing different strategies to effectively curb methane emissions.

Introduction: Cholesterol is considered a core component of the central nervous system, essential for cell membrane stability and the correct functioning of neurotransmitters. Cholesterol plays a vital role in the brain’s second messenger system related to the mechanism of action of antidepressant drugs and mood stabilizers. It may be involved in the etiology and pathogenesis of mood disorders. Aim: This study aims to explicate facts and views about the role of cholesterol levels in depressive disorder and suicidality. Materials and Methods: This was a cross-sectional comparative study where the patients were divided into two groups, i.e., subjects with first-episode major depressive disorder (MDD) with a recent suicide attempt and without suicide attempt. A detailed psychiatric interview, their sociodemographic characteristics, and clinical details were noted on a structured pro forma. MDD diagnosis in the patients was made using the Diagnostic and Statistical Manual of Mental Disorders V. Hamilton Depression Rating Scale was used on subjects to determine the patient’s level of depression. After the overnight fast, blood samples are collected between 6 am and 7 am. Total cholesterol (TC), triglyceride, high-density lipid levels, and low-density lipid levels were measured on the Cobas c311 machine. Results: In the current study, a positive correlation was noted in TC (r = 0.488) and low-density lipid (LDL) levels (r = 0.549) in subjects with depression and suicide attempts. Conclusion: The present study results add to the other studies that support an association between serum cholesterol with depression and suicide. Understanding the significance of lower cholesterol levels is central for future treatments of depressive disorder.

(1) Background: Renal insufficiency is a risk factor for cardiac implantable electronic device (CIED) infection. (2) Methods: A comprehensive search was conducted from multiple electronic databases to identify studies. Using the random effects model, we calculated the pooled rates of CIED infection and their 95% confidence intervals. We also calculated the pooled odds ratios to determine the risk of CIED infections due to chronic kidney disease (CKD) and end-stage renal disease (ESRD). We utilized the Cochran Q and I2 statistics to detect and quantify heterogeneity. (3) Results: A total of 17 studies comprising 359,784 patients with renal insufficiency were added to the meta-analysis. Out of these, 263,819 were CKD patients and 89,617 were ESRD patients. The pooled rate of CIED infection in patients with CKD was 4.3% (95% CI: 2–8.8; I2: 95.7), and in patients with ESRD, it was 4.8% (95% CI: 2.6–8.7; I2: 99.4). The pooled risk of CIED infection in the CKD population was OR 2.5 (95% CI: 1.9–3.3; p < 0.001; I2: 21.1), and in the ESRD population, it was OR 2.4 (95% CI: 1.01–5.7; p = 0.046; I2: 88.8). ESRD was associated with higher mortality, OR 2.5 (95% CI: 1.4–4.4.8; p = 0.001; I2: 95). (4) Conclusions: The presence of renal insufficiency increases the number of CIED infections. In particular, patients with ESRD have an increased risk of mortality.

Background: Nikshay Poshan Yojana was launched by MoH&FW, a centrally sponsored scheme under National Health Mission (NHM)on April 2018. Under the programme financial incentive of Rs.500/- per month is given for each notified TB patient, whether treated in public or private sector notified on the Nikshay platform. This study aims to understand the utilization of NPY. Objectives: 1. To know the purpose of utilizing the NPY by the TB patients. 2. To assess the gaps for delay in credit the amount. Methodology: It’s a cross-sectional study done among patients who were registered at DTC-TB unit of Government Medical College Kakinada through telephonic interview. Sample size was estimated to be 64 taking prevalence of NPY as 80% with absolute error of 10%. Data was collected by using questionnaire in November 2023 and analyzed by SPSS 21.0. Prior permission from Institutional Ethics committee was obtained. Results: Mean age of participants was 41.4+12.4yrs. Males contributing 85.4% and females 14.6%. Nearly half (48%) has taken 2months of treatment, 97.9%were under category I treatment and all were enrolled under NPY. Awareness on NPY was 79.2% and 95.8% reported irregularity in getting NPY. Out of those who received NPY, only 42.1% utilized it for nutrition. Conclusion: DBT enrolment was good. Availability of DBT to the patients was very minimal.

Sieve analysis tests are frequently used to determine the grain size distribution of granular materials. This project proposes an ImageJbased image analysis approach for evaluating aggregate particle size distribution. Grain size in image analysis should be estimated to compare the graduation curves between the two methods.. Black sheets were more effective than white sheets for particle placement, perhaps due to light effects. This technology may be utilized for in-suit testing, as it requires a camera and computer. The study used monochromatic light and a highdefinition camera to capture grain photos while controlling for background, light direction, and intensity. A ground truth was established to evaluate errors in determining grain areas. All grain shape parameters are obtained using the ImageJ program. The grain size distribution curve is generated using image analysis.