Risk prediction and early intervention strategies for persistent SARS-CoV-2 infection in patients with non-Hodgkin lymphoma: a retrospective cohort study.

Background: Patients with non-Hodgkin lymphoma (NHL) face heightened mortality and accelerated disease progression when persistently infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This critical situation underscores the urgent need to identify risk factors and establish early intervention strategies tailored to this vulnerable population. The primary aim of this study was to investigate the risk factors associated with persistent SARS-CoV-2 infection in NHL patients during the COVID-19 pandemic.

Transcriptomic and metabolomic analysis reveal the cold tolerance mechanism of common beans under cold stress.

Background: Common bean (Phaseolus vulgaris L.) is a thermophilic crop, and exposure to cold stress can significantly impact their yield and quality. To elucidate the impact of cold stress on cold-tolerant 'Wei Yuan' (WY) and cold-sensitive 'Bai Bu Lao' (BBL) of common bean, the mechanism of cold tolerance was studied by physiological and biochemical and multi-omics analysis.

The comparative efficacy of L-glutamine, celecoxib, and glucosamine sulfate in osteoarthritis management.

To explore the therapeutic efficacy of L-glutamine (L-Gln) on pathological progression and clinical symptoms of osteoarthritis (OA), and compare with glucosamine sulfate (GS), and celecoxib (CXB). Rats were administered sodium chloride, L-Gln, GS, or CXB via gavage for eight weeks starting from the fifth week after sham operation or Anterior Cruciate Ligament Transection (ACLT) + Medial Meniscectomy (MMx). Then the severity of knee OA in rats was evaluated by serological analysis, histological examination and imaging examination.

Scale-Adaptive viable tumor burden estimation via histopathological microscopy image segmentation.

Cancer segmentation in whole-slide images is a fundamental step for estimating tumor burden, which is crucial for cancer assessment. However, challenges such as vague boundaries and small regions dissociated from viable tumor areas make it a complex task. Considering the usefulness of multi-scale features in various vision-related tasks, we present a structure-aware, scale-adaptive feature selection method for efficient and accurate cancer segmentation.

Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests.

Hyperuricemia has seen a continuous increase in incidence and a trend towards younger patients in recent years, posing a serious threat to human health and highlighting the urgency of using technological means for disease risk prediction. Existing risk prediction models for hyperuricemia typically include two major categories of indicators: routine blood tests and biochemical tests. The potential of using routine blood tests alone for prediction has not yet been explored.