Citations

Abstract Background Diabetic retinopathy (DR) is the leading cause of preventable blindness among working-age adults worldwide, yet screening coverage remains inadequate, particularly in low-and middle-income countries. Automated deep learning systems offer potential to address the global shortage of expert graders, but most existing models lack lesion-level interpretability and are not aligned with established clinical referral frameworks. We developed and validated DRAGS (Diabetic Retinopathy Automated Grading System), a hybrid deep learning model that grades DR according to the UK Diabetic Eye Screening Programme (DESP) classification and provides lesion-level explainability. Methods We trained and validated a DenseNet-201-based convolutional neural network on 20,281 anonymised fundus images from two tertiary eye care institutions in Bangladesh. Images were graded by fellowship-trained retinal specialists using the UK DESP framework, resulting in 10 clinically interpretable classes that combine retinopathy grade (R0–R3) and maculopathy status (M0/M1). A companion dataset of 2,936 pixel-level lesion masks spanning nine pathological categories was used to train a parallel multi-label lesion-detection head. The dataset was partitioned 70:15:15 (patient-stratified). Performance was evaluated using macro-averaged AUROC (DeLong estimator), sensitivity, specificity, F1 score, quadratically weighted Cohen’s κ, and expected calibration error (ECE), with 95% CIs from 2000 bootstrap resamples. Grad-CAM spatial alignment with ground-truth lesion masks was assessed using Dice and IoU. This study follows the TRIPOD+AI reporting guidelines. Findings On the held-out test set (Component I: n = 3,044; Component II: n ≈ 440), DRAGS achieved class-wise precision, recall, and F1 scores ranging from 0·88 to 0·99 across all ten UK DESP grades, with advanced proliferative stages (R3–M0, R3–M1) consistently exceeding 0·95. Overall accuracy was approximately 91·1% and quadratically weighted Cohen’s κ was approximately 0·90. For referable versus non-referable DR, sensitivity was 90·7% and specificity was 91·9%. The companion lesion-detection head achieved macro-averaged sensitivity of 93·9%, specificity of 99·5%, and AUC of 0·997 across nine lesion classes; seven of nine classes achieved AUC = 1·00. Grad-CAM activations showed progressive spatial shift from diffuse (normal) to lesion-dense peripheral patterns (proliferative DR), with maximal agreement for microaneurysms and exudates. Mean inference time was 110–160 ms per image. Interpretation DRAGS demonstrates high diagnostic accuracy for nine-class UK DESP-aligned DR grading, with clinically interpretable lesion-level explainability on a large real-world LMIC dataset. External validation and prospective clinical evaluation are warranted before deployment. Funding The present study received no funding.

Abstract Importance Decline in olfactory function may be used as a predictor of cognitive decline, to enhance early detection models, improve risk stratification, and enable early intervention. Objective To assess the longitudinal association between olfactory decline, cognitive decline, and postmortem neuropathology. Design, setting and participants Retrospective longitudinal analysis with clinicopathological correlations of a prospective population-based cohort study using data from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) and its Brain and Body Donation Program. Participants included cognitively unimpaired individuals without parkinsonism that converted to mild cognitive impairment (MCI) and/or dementia or remained cognitively stable. Main Outcomes and Measures longitudinal change in olfaction, neuropsychiatric symptoms, motor function and memory, conversion to MCI/dementia, postmortem neuropathology Results Over a mean follow-up period of 7.7 ± 5.4 years, out of 922 participants who were cognitively unimpaired at the first cognitive conference, 643 remained cognitively unimpaired, 279 converted to MCI, and 82 developed dementia. Of these, 633 individuals had at least 2 olfactory tests. Converters showed reduced olfactory function (t=-12.6, p <0.0001), faster progression in neuropsychiatric symptom burden (t=3.42, p < 0.001), and faster decline in memory (t= -7.33, p <0.0001) prior to conversion while no significant differences were observed in motor scores between converters and non-converters. Using ROC analysis, olfactory decline, increased neuropsychiatric symptom burden, as well as motor and memory decline predicted conversion to MCI with a consistent accuracy of ∼ 70% up to 5 years before conversion, while UPSIT alone had an accuracy of ∼ 60%. Longitudinal decline in olfaction was associated with a higher burden of a-synuclein (t= -8.21, p <0.0005), tau tangle (t= -2.66, p < 0.01) and amyloid plaque burden (t= -2.85, p < 0.005) and a faster decline over time was associated with a higher burden of tau (t=5.66, p<0.0001). Conclusions and Relevance A reduction in olfactory identification ability is observed up to a decade prior to conversion to MCI and is associated with underlying burden of neuropathology markers, underscoring the value of incorporating olfactory testing in cognitively unimpaired individuals to identify those at-risk of future cognitive decline.

Poststenotic dilatation in renal artery stenosis, evaluated at abdominal CT, might be related to stenotic kidney damage and inflammation, particularly to monocyte chemoattractant protein-1 release.

Abstract Pain treatments have modest effects. Health outcomes might be improved if treatments are matched to mechanisms underlying the persistence and biopsychosocial impact of an individual's pain. The International Association for the Study of Pain (IASP) defines 3 mechanistic pain descriptors presumed to involve different mechanisms—nociceptive, neuropathic, and nociplastic. Although treatments to address each descriptor have been proposed, there is no consensus on how to assign descriptors to clinical presentations. A recent consensus identified candidate clinical features to discriminate between descriptors in clinical practice and research. These need refinement to progress towards a tool. This study aimed to determine the rank and relative weight of identified clinical features to aid discrimination between mechanistic pain descriptors. Candidate clinical features (n = 196) were refined by the IASP Terminology Task Force to converge similar and remove redundant features. The Task Force (n = 24) and an expert panel (n = 39) ranked features using 1000minds conjoint analysis software and assigned weights based on discrete pairwise choices. Participants nominated from pairs of scenarios, which most likely indicated that pain aligned predominantly to a descriptor. Highest ranked features for neuropathic and nociplastic pain were aligned with IASP Clinical Criteria. Criteria for nociceptive pain have not been established. A ranked list of features shared by 2 mechanisms (indicating mixed mechanisms) was also identified. This study identified expert consensus on the highest ranked clinical features with potential to discriminate between pain descriptors, reflective of different underlying mechanisms. This study extends current frameworks by identifying and refining key discriminators for future operationalisation and validation.

Measles virus (MeV) infection is mediated by two cellular receptors: signaling lymphocytic activation molecule family member 1 (SLAMF1, also known as CD150), expressed by immune cells, and nectin-4, expressed by epithelial cells. Infection of immune cells causes systemic disease and immune suppression, while infection of airway epithelial cells results in efficient transmission. In rare cases, MeV reaches the brain and slowly spreads in cells that do not express bona fide receptors, causing subacute sclerosing panencephalitis (SSPE). In the brains of persons with SSPE, multiple mutations of the MeV membrane fusion apparatus are selected that enable its triggering by host proteins acting as surrogate receptors. These mutations favor cell-to-cell spread, which promotes population-based MeV genome evolution and the formation of collective infectious units (CIUs). CIUs, which can rebalance their components and rapidly adapt to new environments, may support neuropathogenesis of other nonintegrating RNA viruses, in particular those with nonsegmented negative-strand genomes.

Abstract Purpose: Familial adenomatous polyposis (FAP) confers a significant risk of colorectal/duodenal cancer. Encapsulated rapamycin (eRapa) has demonstrated promise as FAP chemoprevention in early clinical studies. Patients and Methods: Thirty patients with FAP enrolled to three dosing regimens of eRapa (0.5 mg): cohort 1—every other day, cohort 2—daily every other week, or cohort 3—daily. The primary endpoints were safety/tolerability, pharmacokinetics, and percentage change from baseline (PCFB) in colorectal polyp burden (CPB) at 6 months. Secondary endpoints included PCFB total (TPB) and duodenal (DPB) polyp burden and change in International Society for Gastrointestinal Hereditary Tumors stage and Spigelman score at 6 and 12 months. Results: Twenty nine of thirty patients (97%) completed the 12-month study with predictable bioavailability. Low-grade adverse events were frequent but most pronounced in daily dosing. Two patients discontinued treatment related to toxicity. Cohort 1 had the largest decrease median PCFB CPB, DPB, and TPB at 6 months: −39.4 % (IQR, 108.9; P = 0.28), −33.33 % (IQR, 90; P = 0.04), and −38.6 % (IQR, 88.5; P = 0.26), respectively. At 12 months, cohort 2 had the largest decrease median PCFB CPB and TPB: −29.3 % (IQR, 67.6; P = 0.37) and −26.3 % (IQR, 49.5; P = 0.29), respectively. Intermittent dosing cohorts (1 and 2) reduced DPB at 6 months (P = 0.04) and improved TPB at 12 months (P = 0.05) compared with daily dosing. Conclusions: eRapa was safe, tolerable, and showed preliminary efficacy for FAP chemoprevention. The 0.5 mg daily every-other-week schedule will be evaluated in an upcoming phase III trial.

Patients with inflammatory bowel disease (IBD) frequently modify their diet and use complementary medicine, but inconsistent evidence and persistent myths complicate clinical guidance. Our aim was to critically evaluate the evidence for dietary and complementary strategies in IBD and to clarify common misconceptions, supporting evidence-based, patient-centred management. A narrative synthesis of randomised trials, systematic reviews and international guidelines was conducted. Interventions that were evaluated included dietary strategies encompassing the Mediterranean diet, low-FODMAP (Fermentable Oligosaccharides, Disaccharides, Monosaccharides and Polyols) diet, exclusive enteral nutrition, Crohn’s disease exclusion diet and the specific carbohydrate diet. Other interventions included complementary modalities such as probiotics, curcumin, herbal medicine, mind-body interventions and physical activity. The Mediterranean diet shows moderate evidence for improving quality of life and inflammatory biomarkers. A low-FODMAP diet can relieve functional symptoms but does not reduce inflammation. Exclusive enteral nutrition remains first-line induction therapy in paediatric Crohn’s disease. The Crohn’s disease exclusion diet/partial enteral nutrition shows promise in adults. Among complementary therapies, specific probiotics and curcumin demonstrate benefits in certain cases of ulcerative colitis, but evidence for their use in Crohn’s disease remains limited. Personalised, multidisciplinary supervised dietary and complementary approaches may support symptom control and quality of life in IBD patients. However, they should complement rather than replace evidence-based pharmacologic therapy, and high-quality trial and clinical studies are needed to define optimal, evidence-based nutritional strategies.