Reporting of pre-existing multiple long-term conditions in physical rehabilitation for long COVID: a scoping review.

Background: Physical rehabilitation may improve health and wellbeing outcomes for some adults living with long COVID. However, individuals living with pre-existing multiple long-term conditions (MLTCs) and long COVID may have additional rehabilitation challenges. This scoping review aims to identify the available evidence describing physical rehabilitation interventions for adults living with long COVID, to systematically map the reporting of pre-existing MLTCs, and to describe the characteristics of physical rehabilitation interventions used in adults with both pre-existing long-term conditions (LTCs) and long COVID.

AutoXAI4Omics: an automated explainable AI tool for omics and tabular data.

Machine learning (ML) methods offer opportunities for gaining insights into the intricate workings of complex biological systems, and their applications are increasingly prominent in the analysis of omics data to facilitate tasks, such as the identification of novel biomarkers and predictive modeling of phenotypes. For scientists and domain experts, leveraging user-friendly ML pipelines can be incredibly valuable, enabling them to run sophisticated, robust, and interpretable models without requiring in-depth expertise in coding or algorithmic optimization. By streamlining the process of model development and training, researchers can devote their time and energies to the critical tasks of biological interpretation and validation, thereby maximizing the scientific impact of ML-driven insights.

DGCNN approach links metagenome-derived taxon and functional information providing insight into global soil organic carbon.

Metagenomics can provide insight into the microbial taxa present in a sample and, through gene identification, the functional potential of the community. However, taxonomic and functional information are typically considered separately in downstream analyses. We develop interpretable machine learning (ML) approaches for modelling metagenomic data, combining the biological representation of species with their associated genetically encoded functions within models.

Network Analysis of Women in Otolaryngology and Demographic Trends.

Objective: This study analyzes gender disparities between men and women otolaryngology faculty in the top 20 otolaryngology departments ranked by research output and discusses the implications of these disparities.

Methods: This was a cross-sectional study of all articles published by faculty from January 2020 to December 2021 at the top 20 otolaryngology departments as ranked by Doximity's 2022 research output report. Integrated data from Web of Science, faculty directories, and NIH RePORT were used to collect data on faculty.

Protected characteristics reported in pulmonary rehabilitation: a scoping review.

Background: An individual's characteristics are reported to influence access, completion and outcomes of pulmonary rehabilitation and may contribute to health inequalities. Many countries have policies to promote equity among individuals' characteristics, including the UK Equality Act 2010 which lists nine protected characteristics (age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex and sexual orientation).

Objectives: To describe the extent to which UK Equality Act 2010 protected characteristics have been collected and reported in UK studies and audits of pulmonary rehabilitation.

Long-term outcomes in virtual surgical planning for mandibular reconstruction: A cost-effectiveness analysis.

Objective: This study is an economic evaluation comparing virtual surgical planning (VSP) utilization to free hand mandibular reconstruction (FHR) for advanced oral cavity cancer, for which the cost effectiveness remains poorly understood. The proposed clinical benefits of VSP must be weighed against the additional upfront costs.

Methods: A Markov decision analysis model was created for VSP and FHR based on literature review and institutional data over a 35-year time horizon.

The Role of Clinic Preparedness to Support Patients and Strengthen the Medical System During and After a Pandemic.

Pediatric clinic preparedness is essential to improve the care and health outcomes for children during a pandemic and to decrease the burden on hospital systems. Clinic preparedness is a process that involves a well thought out plan that includes coordination with staff, open communication between the clinic and patient families, and collaboration with community partners. Planning for disasters can decrease some of the risks for our most vulnerable patients, including children and youth with special health care needs.

Neighborhood Deprivation and Symptoms, Psychological Distress, and Quality of Life Among Head and Neck Cancer Survivors.

Importance: Socioeconomic deprivation is associated with increased risk of poor health and quality-of-life (QOL) outcomes in head and neck cancer (HNC) survivors. However, there are few data on how neighborhood deprivation affects patient-reported outcome measures (PROMs) in HNC survivors.

Objective: To investigate whether neighborhood socioeconomic deprivation is associated with symptom burden, psychological distress, and QOL among HNC survivors.

A Systematic Review of the Effectiveness of Interventions to Promote Referral; Adherence; and Uptake of Pulmonary Rehabilitation for Patients with Chronic Obstructive Pulmonary Disease.

Background: Pulmonary rehabilitation (PR) is an effective treatment for patients with chronic obstructive pulmonary disease (COPD). However, referral, uptake, and adherence remain low.

Objective: To determine effectiveness of interventions to increase patient referral, uptake, and adherence to PR programs for patients with COPD.

The Role of Nasal Endoscopy in the Preoperative Evaluation of Nasal Airway Obstruction.

Objective: To examine the prevalence and nature of nasal endoscopic findings in patients referred for structural nasal obstruction, and analyze how such findings influence the preoperative evaluation or operative plan.

Study Design: Cross-sectional study.

Setting: University-based academic otolaryngology practice.

Arable soil nitrogen dynamics reflect organic inputs via the extended composite phenotype.

Achieving food security requires resilient agricultural systems with improved nutrient-use efficiency, optimized water and nutrient storage in soils, and reduced gaseous emissions. Success relies on understanding coupled nitrogen and carbon metabolism in soils, their associated influences on soil structure and the processes controlling nitrogen transformations at scales relevant to microbial activity. Here we show that the influence of organic matter on arable soil nitrogen transformations can be decoded by integrating metagenomic data with soil structural parameters.

Madagascar's extraordinary biodiversity: Threats and opportunities.

Madagascar's unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar's terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.

Inequality in Pulmonary Rehabilitation - The challenges magnified by the COVID-19 pandemic.

The COVID-19 pandemic has served to expose and amplify existing inequalities in chronic respiratory disease and the social determinants of health. In this article, we summarise evidence of existing disparities associated with chronic obstructive pulmonary disease and pulmonary rehabilitation; highlighting limitations of existing data. To reduce health inequalities in pulmonary rehabilitation, there is a need to identify and target factors influencing fair access and personal agency to engage.

Scalable in-memory processing of omics workflows.

We present a proof of concept implementation of the in-memory computing paradigm that we use to facilitate the analysis of metagenomic sequencing reads. In doing so we compare the performance of POSIX™file systems and key-value storage for omics data, and we show the potential for integrating high-performance computing (HPC) and cloud native technologies. We show that in-memory key-value storage offers possibilities for improved handling of omics data through more flexible and faster data processing.

Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease.

Inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, affect several million individuals worldwide. These diseases are heterogeneous at the clinical, immunological and genetic levels and result from complex host and environmental interactions. Investigating drug efficacy for IBD can improve our understanding of why treatment response can vary between patients.

Poor treatment tolerance in head and neck cancer patients with low muscle mass.

Background: We ascertain the role of a low cervical paraspinal skeletal muscle index (CPSMI) as a biomarker for poor treatment tolerance in patients with operable mucosal head and neck squamous cell carcinoma (HNSCC).

Methods: A prospective cohort of patients with operable HNSCC requiring microvascular reconstruction was evaluated. Low CPSMI was calculated using preoperative CT neck imaging.

Cost analysis of sialendoscopy for the treatment of salivary gland disorders in children.

Introduction: Recent advances in Otolaryngology have changed the diagnosis and therapy for salivary gland disorders. Sialendoscopy-assisted surgery is a minimally invasive, conservative procedure for functional preservation of the affected gland. The goals of this study are to assess the indications, use, and outcomes of pediatric sialendoscopy at a tertiary pediatric institution as well as to analyze the direct cost related to the diagnosis and treatment of patients with sialolithiasis and Juvenile Recurrent Parotitis managed with sialendoscopy.

Bluster or Lustre: Can AI Improve Crops and Plant Health?

In a changing climate where future food security is a growing concern, researchers are exploring new methods and technologies in the effort to meet ambitious crop yield targets. The application of Artificial Intelligence (AI) including Machine Learning (ML) methods in this area has been proposed as a potential mechanism to support this. This review explores current research in the area to convey the state-of-the-art as to how AI/ML have been used to advance research, gain insights, and generally enable progress in this area.

Cervical paraspinal skeletal muscle index outperforms frailty indices to predict postoperative adverse events in operable head and neck cancer with microvascular reconstruction.

Objective: Sarcopenia is increasingly being recognized as a negative prognostic factor in patients with head and neck cancer (HNC). We associate a sarcopenia biomarker measured radiographically from computed tomography (CT) of the neck to postoperative adverse events in patients with operable HNC.

Patients And Methods: A prospective cohort of treatment-naïve HNC patients undergoing surgery with microvascular reconstruction was performed.

Relationship between socioeconomic status, exposure to airborne pollutants, and chronic rhinosinusitis disease severity.

Background: Air pollution directly interacts with airway mucosa, yet little is known about how pollutants affect upper airway inflammation. Studies have shown increased incidence of chronic rhinosinusitis (CRS), rhinitis, and asthma in areas with higher traffic pollution, and these neighborhoods are often associated with lower socioeconomic status (SES). The Area Deprivation Index (ADI) assesses neighborhood-level SES by zip code.

Significance of High-Containment Biological Laboratories Performing Work During the COVID-19 Pandemic: Biosafety Level-3 and -4 Labs.

High containment biological laboratories (HCBL) are required for work on Risk Group 3 and 4 agents across the spectrum of basic, applied, and translational research. These laboratories include biosafety level (BSL)-3, BSL-4, animal BSL (ABSL)-3, BSL-3-Ag (agriculture livestock), and ABSL-4 laboratories. While SARS-CoV-2 is classified as a Risk Group 3 biological agent, routine diagnostic can be handled at BSL-2.