Disease States Research Articles

Association of Obesity, Inflammation, and Hypogonadism: A Cross-Sectional Study in Males Under 60 Years of Age.

Background Obesity is a significant global health issue closely associated with numerous metabolic disorders, including hypogonadism. Male obesity-related secondary hypogonadism (MOSH) is characterized by reduced testosterone levels, leading to various health complications. The bidirectional relationship between obesity and hypogonadism creates a vicious cycle, with obesity exacerbating hypogonadism and hypogonadism contributing to further obesity. Chronic inflammation, indicated by elevated C-reactive protein (CRP) levels, plays a crucial role in this interplay. The primary aim of this study is to investigate the role of obesity as an isolated factor contributing to hypogonadism. Materials and methods This observational, cross-sectional study was conducted from September 2022 to July 2024 at Dr. D.Y. Patil Medical College and Hospitals in Pune, India. A total of 80 male participants, all under 60 years of age with a BMI greater than 25 kg/m², were included in the study and classified as overweight or obese according to WHO criteria. Exclusion criteria included diabetes, age over 60 years, a BMI less than 25 kg/m², any testicular pathologies, and significant risk factors. After obtaining informed consent, participants underwent thorough clinical examinations and laboratory investigations. Patients who met the criteria were included in the study, with measurements taken for central obesity (waist circumference (WC) and waist-hip ratio (WHR)) and BMI. CRP levels were measured as an inflammatory marker indicative of chronic disease states. Statistical analyses, including correlation and regression analyses, were performed using SPSS software, version 22 (IBM SPSS Statistics, Version 22). Statistical significance was set at p < 0.05. Results The majority of participants fell within the 50-59 age group, with a mean age of 45.95 years. The study found strong positive correlations between BMI (r = 0.76), WC (r = 0.81), and WHR (r = 0.78) with CRP levels, indicating that central obesity is closely linked to systemic inflammation. Additionally, there were significant negative correlations between free testosterone and these anthropometric measures: BMI (r = -0.65), WC (r = -0.70), and WHR (r = -0.67), suggesting that increased adiposity is associated with lower testosterone levels. The strongest negative correlation observed was between CRP and free testosterone (r = -0.82), highlighting the impact of chronic inflammation on hypogonadism. Regression analysis further confirmed that CRP was a significant predictor of free testosterone levels (R-squared = 0.674), emphasizing the crucial role of inflammation in the pathophysiology of hypogonadism in obese individuals. Conclusion This study underscores the intricate relationship between obesity, chronic inflammation, and hypogonadism in men. The bidirectional nature of this relationship suggests that managing obesity and reducing systemic inflammation could potentially alleviate hypogonadism. Interventions focusing on weight loss, improving insulin sensitivity, and anti-inflammatory treatments may thus hold promise in restoring normal testosterone levels in obese men. Understanding and addressing the impact of obesity on male reproductive health is crucial, given the rising prevalence of obesity worldwide. Future research should explore therapeutic avenues and further elucidate the underlying mechanisms of this complex interplay.

The Important Role of Aquaglyceroporin 7 in Health and Disease.

Aquaporins (AQPs) are highly conserved small transmembrane proteins that facilitate the transport of water and small solutes across cell membranes. Aquaglyceroporin 7 (AQP7), a significant member of the AQP family, is widely distributed throughout the body. For years, AQP7 was predominantly recognized for its role as a small-molecule transporter, facilitating the passage of small molecular substances. However, growing studies have revealed that AQP7 is also involved in the regulation of lipid synthesis, gluconeogenesis, and energy homeostasis, and it is intimately linked to a variety of diseases, such as obesity, type 2 diabetes mellitus, cardiovascular diseases, cancer, and inflammatory bowel disease. This article presents a comprehensive overview of the structure of AQP7, its regulatory mechanisms, its vital roles in both healthy and diseased states, and potential therapeutic advancements. We hope that these studies will serve as a valuable reference for the development of future treatments and diagnostic protocols targeting AQP7.

Macular Pigment Optical Density as a Measurable Modifiable Clinical Biomarker.

Carotenoids are present throughout retina and body its dense deposition leads to an identifiable yellow spot in the macula. Macular pigment optical density (MPOD) measured in the macula is vital to macular well-being and high-resolution visual acuity. MPOD has also been associated with various health and disease states. We sought to review the literature on this topic and summarize MPODs role as a measurable modifiable clinical biomarker, particularly as a measure of the eye's antioxidant capacity in the context of oxidative damage and retinal ischemia. A literature review collated the articles relevant to MPOD, carotenoid intake or supplementation, and their influence on various health and disease states. Literature reveals that MPOD can serve as a reliable biomarker for assessing the retinal defense mechanisms against oxidative stress and the deleterious effects of excessive light exposure. Elevated MPOD levels offer robust protection against the onset and progression of age-related macular degeneration (AMD), a prevalent cause of vision impairment among the elderly population. MPOD's implications in diverse ocular conditions, including diabetic retinopathy and glaucoma, have been explored, underscoring the real need for clinical measurement of MPOD. The integration of MPOD measurement into routine eye examinations presents an unparalleled opportunity for early disease detection, precise treatment planning, and longitudinal disease monitoring. Longitudinal investigations underscore the significance of MPOD in the context of age-related ocular diseases. These studies show promise and elucidate the dynamic nuances of MPOD's status and importance as a measurable, modifiable clinical biomarker.

Emergent ecological patterns and modelling of gut microbiomes in health and in disease.

Recent advancements in next-generation sequencing have revolutionized our understanding of the human microbiome. Despite this progress, challenges persist in comprehending the microbiome's influence on disease, hindered by technical complexities in species classification, abundance estimation, and data compositionality. At the same time, the existence of macroecological laws describing the variation and diversity in microbial communities irrespective of their environment has been recently proposed using 16s data and explained by a simple phenomenological model of population dynamics. We here investigate the relationship between dysbiosis, i.e. in unhealthy individuals there are deviations from the "regular" composition of the gut microbial community, and the existence of macro-ecological emergent law in microbial communities. We first quantitatively reconstruct these patterns at the species level using shotgun data, and addressing the consequences of sampling effects and statistical errors on ecological patterns. We then ask if such patterns can discriminate between healthy and unhealthy cohorts. Concomitantly, we evaluate the efficacy of different statistical generative models, which incorporate sampling and population dynamics, to describe such patterns and distinguish which are expected by chance, versus those that are potentially informative about disease states or other biological drivers. A critical aspect of our analysis is understanding the relationship between model parameters, which have clear ecological interpretations, and the state of the gut microbiome, thereby enabling the generation of synthetic compositional data that distinctively represent healthy and unhealthy individuals. Our approach, grounded in theoretical ecology and statistical physics, allows for a robust comparison of these models with empirical data, enhancing our understanding of the strengths and limitations of simple microbial models of population dynamics.

PTMD 2.0: an updated database of disease-associated post-translational modifications.

Various post-translational modifications (PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently associated with human diseases. Here, we present a comprehensive database of PTMs associated with diseases (PTMD 2.0), including 342 624 PTM-disease associations (PDAs) in 15 105 proteins for 93 types of PTMs and 2083 diseases.Based on the distinct PTM states in diseases, we classified all PDAs into six categories: upregulation (U) or downregulation (D) of PTM levels, absence (A) or presence (P) of PTMs, and creation (C) or disruption (N) of PTM sites. We provided detailed annotations for each PDA and carefully annotated disease-associated proteins by integrating the knowledge from 101 additional resources that covered 13 aspects, including disease-associated information, variation and mutation, protein-protein interaction, protein functional annotation, DNA and RNA element, protein structure, chemical-target relationship, mRNA expression, protein expression/proteomics, subcellular localization, biological pathway annotation, functional domain annotation and physicochemical property. With a data volume of ∼8 GB, we anticipate that PTMD 2.0 will serve as a fundamental resource for further analysing the relationships between PTMs and diseases. The online service of PTMD 2.0 is freely available at https://ptmd.biocuckoo.cn/.

Review of the Influences of Sex Differences on Health and Disease: What Is the Role of Journals?

➢ Sex-based differences are understudied, which has potential consequences for the health of everyone.➢ Women's health is particularly affected given a lack of sex-specific data across many disease states.➢ Journals do not consistently require the inclusion of both sexes and the disaggregation of data by sex in cell, animal model, and human studies.➢ Instructions for investigators and journals regarding the inclusion of sex-specific data are found in guidelines such as those by the Sex and Gender Equity in Research (SAGER) group, but these guidelines are underutilized.➢ Consistency in the inclusion of both sexes in studies (except in studies on diseases affecting only 1 sex), as well as in the disaggregation and reporting of results by sex, has the potential to improve health for all people.

Divergent synthesis of amino acid-linked O-GalNAc glycan core structures.

O-GalNAc glycans, also known as mucin-type O-glycans, are primary constituents of mucins on various mucosal sites of the body and also ubiquitously expressed on cell surface and secreted proteins. They have crucial roles in a wide range of physiological and pathological processes, including tumor growth and progression. In addition, altered expression of O-GalNAc glycans is frequently observed during different disease states. Research dedicated to unraveling the structure-function relationships of O-GalNAc glycans has led to the discovery of disease biomarkers and diagnostic tools and the development of O-glycopeptide-based cancer vaccines. Many of these efforts require amino acid-linked O-GalNAc core structures as building blocks to assemble complex O-glycans and glycopeptides. There are eight core structures (cores one to eight), from which all mucin-type O-glycans are derived. In this protocol, we describe the first divergent synthesis of all eight cores from a versatile precursor in practical scales. The protocol involves (i) chemical synthesis of the orthogonally protected precursor (3 days) from commercially available materials, (ii) chemical synthesis of five unique glycosyl donors (1-2 days for each donor) and (iii) selective deprotection of the precursor and assembly of the eight cores (2-4 days for each core). The procedure can be adopted to prepare O-GalNAc cores linked to serine, threonine and tyrosine, which can then be utilized directly for solid-phase glycopeptide synthesis or chemoenzymatic synthesis of complex O-glycans. The procedure empowers researchers with fundamental organic chemistry skills to prepare gram scales of any desired O-GalNAc core(s) or all eight cores concurrently.

Simultaneous Periprosthetic Joint Infection and Infective Endocarditis: Prevalence, Risk Factors, and Clinical Presentation

BackgroundInfective endocarditis (IE) and periprosthetic joint infections (PJI) occur due to hematogenous bacterial spread, theoretically increasing the risk for concurrent infections. There is a scarcity of literature investigating this specific association. We aimed to assess the prevalence, comorbidities, and clinical presentation of patients who have simultaneous PJI and IE. MethodsWe retrospectively identified 655 patients (321 men, 334 women; 382 total hip arthroplasty, 273 total knee arthroplasty) who developed a PJI from July 1, 2015, to December 31, 2020, at one institution. There were two groups created: patients diagnosed with PJI with IE (PJI + IE) and PJI patients who did not have IE (PJI). We analyzed clinical outcomes and comorbidities. ResultsThere were nine patients who had PJI with IE (1.4% of PJI patients). The C-reactive protein (170.9 versus 78, P = 0.026), Elixhauser comorbidity score (P = 0.002), length of hospital stay (LOS) (10.9 versus 5.7 days, P = 0.043), and the two-year post-discharge mortality rate (55.6 versus 9.0%, P = 0.0007) were significantly greater in the PJI+IE group. Comorbidities such as iron deficiency anemia (P = 0.03), coagulopathy (P = 0.02), complicated diabetes mellitus (P = 0.02), electrolyte disorders (P = 0.01), neurological disease (P = 0.004), paralysis (P = 0.04), renal failure (P = 0.0001), and valvular disease (P = 0.0008) occurred more frequently in the PJI + IE group. Modified Duke’s criteria were met for possible or definite IE in 8 of the 9 patients (88.9%). ConclusionConcurrent PJIs and IE, although rare, are a potentially devastating disease state with increased LOS and two-year mortality rates. This emphasizes the need for appropriate IE workups in patients who have a PJI. The modified Duke’s criteria is effective in establishing a diagnosis for IE in this scenario.

Investigating the Interplay between Cardiovascular and Neurodegenerative Disease.

Neurological diseases, including neurodegenerative diseases (NDDs), are the primary cause of disability worldwide and the second leading cause of death. The chronic nature of these conditions and the lack of disease-modifying therapies highlight the urgent need for developing effective therapies. To accomplish this, effective models of NDDs are required to increase our understanding of underlying pathophysiology and for evaluating treatment efficacy. Traditionally, models of NDDs have focused on the central nervous system (CNS). However, evidence points to a relationship between systemic factors and the development of NDDs. Cardiovascular disease and related risk factors have been shown to modify the cerebral vasculature and the risk of developing Alzheimer's disease. These findings, combined with reports of changes to vascular density and blood-brain barrier integrity in other NDDs, such as Huntington's disease and Parkinson's disease, suggest that cardiovascular health may be predictive of brain function. To evaluate this, we explore evidence for disruptions to the circulatory system in murine models of NDDs, evidence of disruptions to the CNS in cardiovascular disease models and summarize models combining cardiovascular disruption with models of NDDs. In this study, we aim to increase our understanding of cardiovascular disease and neurodegeneration interactions across multiple disease states and evaluate the utility of combining model systems.

Higher frequency of peripheral blood CD103+CD8+ T cells with lower levels of PD-1 and TIGIT expression related to favorable outcomes in leukemia patients.

Leukemia is a prevalent pediatric life-threatening hematologic malignancy with a poor prognosis. Targeting immune checkpoints (ICs) to reverse T cell exhaustion is a potentially effective treatment for leukemia. Tissue resident memory T (TRM) cells have been found to predict the efficacy of programmed death receptor-1 inhibitor (anti-PD-1) therapy in solid tumors. However, the IC characteristics of TRM cells in leukemia and their relationship with prognosis remain unclear. We employed multi-color flow cytometry to evaluate the frequencies of CD103+CD4+ and CD103+CD8+ T cells in the peripheral blood (PB) of patients with acute myeloid leukemia and B-cell acute lymphoblastic leukemia compared to healthy individuals. We examined the expression patterns of PD-1 and T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT) within the circulating CD103+ T cell subsets affected by leukemia. To further elucidate the immunological landscape, we assessed the differentiation status of CD103+ T cells across various disease states in patients with leukemia. Our findings showed a significant increase in the frequency of CD103+CD8+ T cells in the PB of patients with leukemia who had achieved complete remission (CR) compared to those in the de novo (DN) and relapsed/refractory (RR) stages. This increase was accompanied by a notable decrease in the expression levels of PD-1 and TIGIT in CD103+CD8+ T cells in the CR stage. Additionally, our analysis revealed a higher proportion of CD103+CD8+ T cells in the central memory (TCM) and effector memory (TEM) subsets of the immune profile. Notably, the proportions of CD103+ naïve T cells, CD103+ TEM, and CD103+ terminally differentiated T cells within the CD8+ T cell population were significantly elevated in patients with CR compared to those in the DN/RR stages. The data indicate that circulating higher frequency of CD103+CD8+ T cells with lower expression of PD-1 and TIGIT are associated with favorable outcomes in patients with leukemia. This suggests a potential role of TRM cells in leukemia prognosis and provides a foundation for developing targeted immunotherapies.

Pseudomonas aeruginosa LasR-deficient mutants have increased methylglyoxal and hydrogen peroxide sensitivity due to low intracellular glutathione.

Methylglyoxal is a highly reactive metabolite that is detected in various disease states, including those where Pseudomonas aeruginosa is present and MG resistance requires the glutathione-dependent glyoxalase enzyme GloA3 enzyme. This study reveals that P . aeruginosa strains with LasR mutations, which are commonly found in clinical isolates, are more sensitive to methylglyoxal (MG) and hydrogen peroxide due to lower intracellular glutathione levels and high activity of the CbrAB-Crc regulatory pathway. This could be significant for understanding the selective pressures that drive P. aeruginosa evolution in infection sites, as well as a better understanding of LasR-strain metabolism in infections such as those associated with cystic fibrosis.

Extragustatory bitter taste receptors in head and neck health and disease.

Taste receptors, first described for their gustatory functions within the oral cavity and oropharynx, are now known to be expressed in many organ systems. Even intraoral taste receptors regulate non-sensory pathways, and recent literature has connected bitter taste receptors to various states of health and disease. These extragustatory pathways involve previously unexplored, clinically relevant roles for taste signaling in areas including susceptibility to infection, antibiotic efficacy, and cancer outcomes. Among other physicians, otolaryngologists who manage head and neck diseases should be aware of this growing body of evidence and its relevance to their fields. In this review, we describe the role of extragustatory taste receptors in head and neck health and disease, highlighting recent advances, clinical implications, and directions for future investigation. Additionally, this review will discuss known TAS2R polymorphisms and the associated implications for clinical prognosis.

Stepwise Isolation of Diverse Metabolic Cell Populations Using Sorting by Interfacial Tension (SIFT).

We present here a passive and label-free droplet microfluidic platform to sort cells stepwise by lactate and proton secretion from glycolysis. A technology developed in our lab, Sorting by Interfacial Tension (SIFT), sorts droplets containing single cells into two populations based on pH by using interfacial tension. Cellular glycolysis lowers the pH of droplets through proton secretion, enabling passive selection based on interfacial tension and hence single-cell glycolysis. The SIFT technique is expanded here by exploiting the dynamic droplet acidification from surfactant adsorption that leads to a concurrent increase in interfacial tension. This allows multiple microfabricated rails at different downstream positions to isolate cells with distinct glycolytic levels. The device is used to correlate sorted cells with three levels of glycolysis with a conventional surface marker for T-cell activation. As glycolysis is associated with both disease and cell state, this technology facilitates the sorting and analysis of crucial cell subpopulations for applications in oncology, immunology and immunotherapy.

Comprehensive Analysis of Garcin Syndrome: A Systematic Review of the Etiology, Diagnosis, and Treatment.

Garcin syndrome is a rare neurological condition characterized by progressive unilateral involvement of multiple cranial nerves, without typical intracranial hypertension. It is often linked with aggressive malignancies and invasive infections; hence, it presents significant diagnostic and therapeutic challenges. Despite the advances in medical technology, the prognosis still remains poor, and there is limited literature on comprehensive reviews regarding its etiology, diagnosis, and management. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-based systematic review was performed in order to compile updated evidence related to Garcin syndrome. The PubMed and Scopus databases were comprehensively searched using the search terms "Garcin syndrome" AND ("etiology" OR "diagnosis" OR "treatment" OR "management"). Information was obtained from case reports and focused on common etiologies, clinical presentations, diagnostic methodologies, treatment protocols, and outcomes. The review discussed very diverse etiologies of Garcin syndrome. The most common among these were skull base tumors, metastatic lesions, and invasive infections like mucormycosis. Most of these were multiple cranial nerve (CN) involvements in which CN V (trigeminal nerve), CN VII (facial nerve), or CN XII (hypoglossal nerve) involvement was common. Advanced imaging, especially MRI, played a very crucial role in diagnosis, showing the presence of extensive bony destruction with the involvement of cranial nerves. Treatment was varied according to the etiology, ranging from chemotherapy and radiotherapy in neoplastic cases to active surgical intervention supported by antifungal therapy in infected cases. Garcin syndrome is a clinical challenge due to its diverse etiologies and complex management profile. While early diagnosis and intervention are emphasized, the prognosis remains grave, especially in cases presenting with metastatic disease or immunocompromised states. Future research should focus on better, more sensitive diagnostic modalities and the investigation of newer therapeutic approaches for Garcin syndrome patients.

Applications of Artificial Intelligence in Microbiome Analysis and Probiotic Interventions—An Overview and Perspective Based on the Current State of the Art

The gut microbiota plays a crucial role in maintaining human health and influencing disease states. Recent advancements in artificial intelligence (AI) have opened new avenues for exploring the intricate functionalities of the gut microbiota. This article aims to provide an overview of the current state-of-the-art applications of AI in microbiome analysis, with examples related to metabolomics, transcriptomics, proteomics, and genomics. It also offers a perspective on the use of such AI solutions in probiotic interventions for various clinical settings. This comprehensive understanding can lead to the development of targeted therapies that modulate the gut microbiota to improve health outcomes. This article explores the innovative application of AI in understanding the complex interactions within the gut microbiota. By leveraging AI, researchers aim to uncover the microbiota’s role in human health and disease, particularly focusing on CIDs and probiotic interventions.

Autophagy and the pancreas: Healthy and disease states.

Macroautophagy/autophagy is an intracellular degradation pathway that has an important effect on both healthy and diseased pancreases. It protects the structure and function of the pancreas by maintaining organelle homeostasis and removing damaged organelles. A variety of pancreas-related diseases, such as diabetes, pancreatitis, and pancreatic cancer, are closely associated with autophagy. Genetic studies that address autophagy confirm this view. Loss of autophagy homeostasis (lack or overactivation) can lead to a series of adverse reactions, such as oxidative accumulation, increased inflammation, and cell death. There is growing evidence that stimulating or inhibiting autophagy is a potential therapeutic strategy for various pancreatic diseases. In this review, we discuss the multiple roles of autophagy in physiological and pathological conditions of the pancreas, including its role as a protective or pathogenic factor.

Dual color carbon dots for simultaneous dynamic fluorescence tracking of mitochondria and lysosomes

The development of fluorescent probes to monitor mitochondria and lysosomes will be helpful not only to realize the status monitoring of the organelles, but also to gain insights into their functions in both healthy and diseased states. Carbon Dots (CDs), as a nanomaterial with excellent properties, have provided new tools and methods for research in organelle imaging in recent years. In this study, we synthesized green fluorescence-emitting carbon dots (G-CDs) with mitochondria-targeting ability and red fluorescence-emitting carbon dots (R-CDs) with lysosome-targeting ability by using the same precursors. G-CDs are brightly with a quantum yield of up to 51.8 % and R-CDs have a long-wavelength emission of 611 nm. Based on the unique properties of G-CDs and R-CDs, we observed the changes of mitochondria during apoptosis and mitochondrial autophagy in HeLa cells by using G-CDs. And the dynamics of lysosomes in the inhibition of cellular autophagy and cellular necrosis were observed by utilizing the R-CDs. Furthermore, we observed human intestinal organoids samples stained by G-CDs and R-CDs, extending the relevant applications of carbon dots imaging to the organoids field, which brings forth new possibilities for research and drug development of related diseases.

Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease

Translating findings from animal models to human disease is essential for dissecting disease mechanisms, developing and testing precise therapeutic strategies. The coronavirus disease 2019 (COVID-19) pandemic has highlighted this need, particularly for models showing disease severity-dependent immune responses. Single-cell transcriptomics (scRNAseq) is well poised to reveal similarities and differences between species at the molecular and cellular level with unprecedented resolution. However, computational methods enabling detailed matching are still scarce. Here, we provide a structured scRNAseq-based approach that we applied to scRNAseq from blood leukocytes originating from humans and hamsters affected with moderate or severe COVID-19. Integration of data from patients with COVID-19 with two hamster models that develop moderate (Syrian hamster, Mesocricetus auratus) or severe (Roborovski hamster, Phodopus roborovskii) disease revealed that most cellular states are shared across species. A neural network-based analysis using variational autoencoders quantified the overall transcriptomic similarity across species and severity levels, showing highest similarity between neutrophils of Roborovski hamsters and patients with severe COVID-19, while Syrian hamsters better matched patients with moderate disease, particularly in classical monocytes. We further used transcriptome-wide differential expression analysis to identify which disease stages and cell types display strongest transcriptional changes. Consistently, hamsters' response to COVID-19 was most similar to humans in monocytes and neutrophils. Disease-linked pathways found in all species specifically related to interferon response or inhibition of viral replication. Analysis of candidate genes and signatures supported the results. Our structured neural network-supported workflow could be applied to other diseases, allowing better identification of suitable animal models with similar pathomechanisms across species. This work was supported by German Federal Ministry of Education and Research, (BMBF) grant IDs: 01ZX1304B, 01ZX1604B, 01ZX1906A, 01ZX1906B, 01KI2124, 01IS18026B and German Research Foundation (DFG) grant IDs: 14933180,431232613.

Practical Use of Ultrasound in Modern Rheumatology-From A to Z.

During the past 20 years, the use of ultrasound (US) in rheumatology has increased tremendously, and has become a valuable tool in rheumatologists' hands, not only for assessment of musculoskeletal structures like joints and peri-articular tissues, but also for evaluation of nerves, vessels, lungs, and skin, as well as for increasing the accuracy in a number of US-guided aspirations and injections. The US is currently used as the imaging method of choice for establishing an early diagnosis, assessing disease activity, monitoring treatment efficacy, and assessing the remission state of inflammatory joint diseases. It is also used as a complementary tool for the assessment of patients with degenerative joint diseases like osteoarthritis, and in the detection of crystal deposits for establishing the diagnosis of metabolic arthropathies (gout, calcium pyrophosphate deposition disease). The US has an added value in the diagnostic process of polymyalgia rheumatica and giant-cell arteritis, and is currently included in the classification criteria. A novel use of US in the assessment of the skin and lung involvement in connective tissue diseases has the potential to replace more expensive and risky imaging modalities. This narrative review will take a close look at the most recent evidence-based data regarding the use of US in the big spectrum of rheumatic diseases.

ScPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets.

Single-cell RNA sequencing (scRNA-seq) technologies can generate transcriptomic profiles at a single-cell resolution in large patient cohorts, facilitating discovery of gene and cellular biomarkers for disease. Yet, when the number of biomarker genes is large, the translation to clinical applications is challenging due to prohibitive sequencing costs. Here, we introduce scPanel, a computational framework designed to bridge the gap between biomarker discovery and clinical application by identifying a sparse gene panel for patient classification from the cell population(s) most responsive to perturbations (e.g. diseases/drugs). scPanel incorporates a data-driven way to automatically determine a minimal number of informative biomarker genes. Patient-level classification is achieved by aggregating the prediction probabilities of cells associated with a patient using the area under the curve score. Application of scPanel to scleroderma, colorectal cancer, and COVID-19 datasets resulted in high patient classification accuracy using only a small number of genes (<20), automatically selected from the entire transcriptome. In the COVID-19 case study, we demonstrated cross-dataset generalizability in predicting disease state in an external patient cohort. scPanel outperforms other state-of-the-art gene selection methods for patient classification and can be used to identify parsimonious sets of reliable biomarker candidates for clinical translation.