Integrated SegFlow, µSIA, and UPLC for Online Sialic Acid Quantitation of Glycoproteins Directly from Bioreactors.

This study emphasizes the critical importance of closely monitoring and controlling the sialic acid content in therapeutic glycoproteins, including EPO, interferon-γ, Orencia, Enbrel, and others, as the level of sialylation directly impacts their pharmacokinetics (PK), immunogenicity, potency, and overall clinical performance due to its influence on protein clearance via hepatic asialoglycoprotein receptors (ASGPR). The ASGPR recognizes and binds to glycoproteins exposed to terminal galactose or N-acetylgalactosamine residues, leading to receptor-mediated endocytosis. Recent studies have demonstrated that sialylation of O-linked glycan plays a role in protecting against macrophage galactose lectin (MGL)-mediated clearance.

Joint fluid multi-omics improves diagnostic confidence during evaluation of children with presumed septic arthritis.

Background: An accurate diagnosis of septic versus reactive or autoimmune arthritis remains clinically challenging. A multi-omics strategy comprising metagenomic and proteomic technologies were undertaken for children diagnosed with presumed septic arthritis to advance clinical diagnoses and care for affected individuals.

Methods: Twelve children with suspected septic arthritis were prospectively enrolled to compare standard of care tests with a rapid multi-omics approach.

Impact of Subsequent Fellowship on Urology Chief Resident Case Log Volumes.

Objective: To characterize the impact of subsequent fellowship on the case log experience of trainees throughout their residency and specifically their chief resident year.

Materials And Methods: Urology resident case logs from 2010 to 2022 were obtained from 13 institutions for total residency and chief years. Five categorized index procedures were included for analysis: General Urology; Endourology; Reconstructive Urology; Urologic Oncology; and Pediatric Urology.

Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.

Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.

High-dimensional multiple imputation (HDMI) for partially observed confounders including natural language processing-derived auxiliary covariates.

Multiple imputation (MI) models can be improved with auxiliary covariates (AC), but their performance in high-dimensional data remains unclear. We aimed to develop and compare high-dimensional MI (HDMI) methods using structured and natural language processing (NLP)-derived AC in studies with partially observed confounders. We conducted a plasmode simulation with acute kidney injury as outcome and simulated 100 cohorts with a null treatment effect, incorporating creatinine labs, atrial fibrillation (AFib), and other investigator-derived confounders in the outcome generation.

Which Lenke type curve is most appropriate for vertebral body tethering in adolescent idiopathic scoliosis?

Purpose: Clinical trials have studied the effects of curve magnitude and flexibility, age, and skeletal immaturity on the outcomes of VBT. No studies have assessed the effect of Lenke curve type on the outcomes of VBT. This study compares outcomes in patients who underwent VBT with Lenke type 1, 3, 5, and 6 curves.

The Renal Effect of 20% Human Albumin Solution Fluid Bolus Therapy in Patients After Cardiac Surgery. A Secondary Analysis of the HAS FLAIR II Randomized Clinical Trial.

Objective: To compare the effects of fluid bolus therapy (FBT) with 20% albumin to crystalloid FBT on the incidence of cardiac surgery-associated acute kidney injury (CSA-AKI) and its severity and duration.

Design: Secondary analysis of the multicenter, parallel-group, open-label, randomized HAS FLAIR-II trial.

Setting: Six intensive care units.

Cortical reorganization following dorsal spinal injuries in newborn monkeys reveals a critical period in the development of the somatosensory cortex.

Lesions of the dorsal columns of the spinal cord in adult macaque monkeys lead to the loss of hand inputs and large-scale expansion of the face inputs in the hand region of the somatosensory cortex. Inputs from alternate spinal pathways do not reactivate the deafferented regions of area 3b. Here, we determined how transections of the dorsal columns done within a few days after birth affect the developing somatosensory cortex.

Long term health outcomes in people with diabetes 12 months after hospitalisation with COVID-19 in the UK: a prospective cohort study.

Background: People with diabetes are at increased risk of hospitalisation, morbidity, and mortality following SARS-CoV-2 infection. Long-term outcomes for people with diabetes previously hospitalised with COVID-19 are, however, unknown. This study aimed to determine the longer-term physical and mental health effects of COVID-19 in people with and without diabetes.

Prospective Evaluation of Remote Software Based Surveillance Supplementing Clinical Monitoring For Hemodialysis Vascular Access.

Background And Hypothesis: Efficient arteriovenous access (VA) surveillance is vital for early identification of dysfunctional access, allowing timely intervention to prevent thrombosis. This study compares the efficacy of adding remote software surveillance to standard clinical care across our units.

Methods: We conducted a 12-month prospective study on maintenance hemodialysis (HD) patients using Vasc-Alert software technology to assist clinical decision-making in 2 satellite HD units (Group 1) and standard care in the remaining 3 HD units (Group 2) .

Impact of Genomic Classifiers on Risk Stratification and Treatment Intensity in Patients With Localized Prostate Cancer : A Systematic Review.

Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.

Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.

Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.

Subspecies phylogeny in the human gut revealed by co-evolutionary constraints across the bacterial kingdom.

The human gut microbiome contains many bacterial strains of the same species ("strain-level variants") that shape microbiome function. The tremendous scale and molecular resolution at which microbial communities are being interrogated motivates addressing how to describe strain-level variants. We introduce the "Spectral Tree"-an inferred tree of relatedness built from patterns of co-evolutionary constraint between greater than 7,000 diverse bacteria.

Response to neoadjuvant chemotherapy leads to better survival outcomes in upper tract urothelial carcinoma.

Objectives: To evaluate the benefit of neoadjuvant chemotherapy (NAC) for patients with high-risk upper tract urothelial carcinoma (UTUC) using a large, well-curated multi-institutional database.

Patients And Methods: This study was a multi-institutional retrospective analysis conducted by the UTUC Collaborative Network (UCAN), combining data from 2276 patients with UTUC who underwent radical nephroureterectomy at seven high-volume tertiary care centres in the United States. The UCAN data were analysed to evaluate the impact of response to NAC on survival outcomes in patients with UTUC.

Performance of MR fusion biopsy, systematic biopsy and combined biopsy on prostate cancer detection rate in 1229 patients stratified by PI-RADSv2 score on 3T multi-parametric MRI.

Purpose: We analyzed the additional value of systematic biopsy (SB) to MR-Ultrasound fusion biopsy (MRgFbx) for detection of clinically significant prostate cancer (csPCa), as increased sampling may cause increased morbidity.

Materials And Methods: This retrospective study cohort was comprised of 1229 biopsy sessions between July 2016 and May 2020 in men who had a Prostate Imaging-Reporting and Data System (PI-RADSv2) category ≥ 3 lesion on 3 Tesla multiparametric MRI (3TmpMRI) and subsequent combined biopsy (CB; MRgFbx and SB) for suspected prostate cancer (PCa). Cancer detection rates (CDR) were calculated for CB, MRgFbx and SB in the study cohort and sub-cohorts stratified by biopsy history and PI-RADSv2 category.

Preclinical model of Mycobacteroides abscessus lung disease by nose-only exposure of mice to bacterial powder aerosol.

The limitations of existing mouse models of lung infection with Mycobacteroides abscessus impede drug discovery and development. In contrast to current animal models that introduce NTM intravenously or by intranasal/intra-tracheal instillation or via bronchoscopy-guided insufflation, we developed a dry powder inhalation (DPI) of M. abscessus ATCC 19977 that generated paucibacillary lung infection and histopathology in immunocompetent mice.

Distinct structural and functional heterochromatin partitioning of lamin B1 and lamin B2 revealed using genome-wide nicking enzyme epitope targeted DNA sequencing.

Gene expression is regulated by chromatin DNA methylation and other features, including histone post-translational modifications (PTMs), chromatin remodelers and transcription factor occupancy. A complete understanding of gene regulation will require the mapping of these chromatin features in small cell number samples. Here we describe a novel genome-wide chromatin profiling technology, named as Nicking Enzyme Epitope targeted DNA sequencing (NEED-seq).

Comparison of Random Forest and Stepwise Regression for Variable Selection Using Low Prevalence Predictors: A case Study in Paediatric Sepsis.

Introduction: Variable selection is a common technique to identify the most predictive variables from a pool of candidate predictors. Low prevalence predictors (LPPs) are frequently found in clinical data, yet few studies have explored their impact on model performance during variable selection. This study compared the Random Forest (RF) algorithm and stepwise regression (SWR) for variable selection using data from a paediatric sepsis screening tool, where 18 out of 32 predictors had a prevalence < 10%.

Systematic review of machine learning applications using nonoptical motion tracking in surgery.

This systematic review explores machine learning (ML) applications in surgical motion analysis using non-optical motion tracking systems (NOMTS), alone or with optical methods. It investigates objectives, experimental designs, model effectiveness, and future research directions. From 3632 records, 84 studies were included, with Artificial Neural Networks (38%) and Support Vector Machines (11%) being the most common ML models.

Clinical criteria for limbic-predominant age-related TDP-43 encephalopathy.

Limbic predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is highly prevalent in late life and a common co-pathology with Alzheimer's disease neuropathologic change (ADNC). LATE-NC is a slowly progressive, amnestic clinical syndrome. Alternatively, when present with ADNC, LATE-NC is associated with a more rapid course.

Evaluating the role of serum cystatin C as a circulating biomarker of diabetic retinopathy from a rural Indian population.

Purpose: This study aimed to evaluate serum cystatin C as a potential biomarker for diabetic retinopathy (DR) in a rural Indian population, addressing the urgent need for effective screening tools amidst rising diabetes prevalence.

Materials And Methods: A cross-sectional study recruited 112 patients with diabetes mellitus from Sambalpur, Odisha, India, categorized into groups with and without DR. Serum cystatin C levels were measured alongside clinical and demographic parameters, using established diagnostic methods.

Phenotype and genetic spectrum of six Indian patients with bestrophinopathy.

The aim of this study is to describe genotype and phenotype of patients with bestrophinopathy. The case records were reviewed retrospectively, findings of multimodal imaging such as color fundus photograph, optical coherence tomography (OCT), fundus autofluorescence, electrophysiological, and genetic tests were noted. Twelve eyes of six patients from distinct Indian families with molecular diagnosis were enrolled.

From Crisis to Cure: The Resilient Recovery of a Patient With Tetanus.

Tetanus is a severe neurological condition triggered by the toxin of , resulting in extreme muscle stiffness and spasms. Although vaccination can prevent it, without treatment, tetanus carries a high risk of death due to respiratory failure and autonomic disturbances. This case report describes a 24-year-old Indian male who developed tetanus after branding (a traditional procedure for jaundice in rural India) on his wrist.

Artificial intelligence-enabled safety monitoring in Alzheimer's disease clinical trials.

Background: Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by expert clinicians.

Objectives: Our study explores the use of natural language processing (NLP) and artificial intelligence (AI) methods to streamline and standardize clinician coding of adverse event data in Alzheimer's disease (AD) clinical trials.

Limosilactobacillus reuteri fermented brown rice alleviates anxiety improves cognition and modulates gut microbiota in stressed mice.

Chronic stress disrupts gut microbiota homeostasis, contributing to anxiety and depression. This study explored the effects of Limosilactobacillus reuteri fermented brown rice (FBR) on anxiety using an ICR mouse chronic mild stress (CMS) model. Anxiety was assessed through body weight, corticosterone levels, neurotransmitter profiles, and behavioral tests.

Integrating Model-Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation.

The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate intricate processes involved in drug absorption, distribution, metabolism, and excretion, as well as pharmacokinetics and pharmacodynamics. Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug-target interactions from big data, enabling more accurate predictions and novel hypothesis generation.