Conduct a systematic review of clinical practice guidelines for sudden sensorineural hearing loss (SSNHL) to identify interventions related to the diagnosis and management of SSNHL. Results from this review will inform the development of the World Health Organisation (WHO) Package for Ear and Hearing Care Interventions (PEHCI).

We searched for clinical practice guidelines, published from 2014 onwards, across four databases and websites for audiology/otolaryngology professional organisations, that report recommendations on diagnosis and management of SSNHL. We assessed the quality of the clinical practice guidelines using the AGREE II tool. All review processes were performed by two independent reviewers.

Following the screening and quality appraisal, we identified three high-quality clinical practice guidelines relevant to SSNHL.

Specific interventions focused on the (1) diagnosis of SSNHL with clinical tests, (2) management of SSNHL with patient education, medical management with steroid use with hyperbaric oxygen therapy (when warranted), and (3) follow-up in terms of outcomes assessment with clinical tests and accompanied by rehabilitation when warranted.

The clinical practice guidelines detailed recommendations on the diagnosis, management, and follow-up of patients with SSNHL. The interventions derived from these guidelines will inform the selection of interventions for inclusion in the WHO PEHCI.

Chronic, low-grade inflammation is increasingly recognized as a fundamental driver of non-communicable diseases - including obesity, metabolic dysfunction-associated steatotic liver disease (MASLD), and neurodegeneration - yet the initiating events remain incompletely understood. Accumulating evidence implicates gut barrier dysfunction and bacterial translocation as pivotal mechanisms linking environmental and metabolic stressors to systemic inflammation. Mechanistically, obesity-associated depletion of typically beneficial taxa (e.g., Faecalibacterium, Roseburia, Akkermansia muciniphila) and enrichment of proinflammatory Enterobacteriaceae reduce expression of tight junction proteins - including, occludin, claudins, and ZO-1 - and increase the vascular permeability marker, PV-1. Combined with diminished secretion of host defense peptides (e.g., Reg3γ, lysozyme) and mucus thinning, these changes facilitate LPS-driven activation of TLR4 and downstream cytokines. We integrate preclinical and clinical data demonstrating how these processes propagate systemic inflammation via the gut-liver and gut-vascular axes, contributing to MASLD, insulin resistance, and vascular dysfunction. Finally, we highlight emerging interventions aimed at restoring barrier integrity - ranging from SCFA supplementation and GLP-2 receptor agonists to host defense peptide-based therapies - and discuss methodological advances for assessing gut permeability in vivo. Understanding the gut as a dynamic interface between host and environment, and its crucial role in mediating inflammation, will be pivotal for the development of effective interventions targeting the global epidemic of obesity-related disease.

The study investigated the potential association between tumor size and inflammation from the standpoint of apparent diffusion coefficient (ADC) and the prognostic significance of ADC in hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitors (ICIs).

This retrospective study ultimately included 255 HCC patients receiving ICIs, among whom 168 underwent posttreatment diffusion-weighted imaging at three months. The study analyzed the correlations among pretreatment tumor maximum diameter, inflammatory markers (neutrophil to lymphocyte ratio, NLR; platelet to lymphocyte ratio, PLR), and ADC (substantial tumor ADC, sADC; whole tumor ADC, wADC), as well as exploring the association between tumor maximum diameter and inflammatory markers regarding ADC. This study further focused on the prognostic value of baseline and relative change in ADC in HCC patients receiving ICIs.

The study found a potential relationship between tumor maximum diameter and inflammatory markers regarding sADC. Multivariate Cox regression showed that higher sADC was associated with longer overall survival (OS) (HR: 0.63, 95% CI: 0.43-0.91, p = 0.015). Additionally, the relative change in sADC (ΔsADC) positive group exhibited better progression-free survival (12 vs 6.4 months, p < 0.001) and OS (20.5 vs 13.3 months, p < 0.001) compared to the ΔsADC non-positive group, serving as an independent prognostic factor for HCC patients receiving ICIs.

The association between tumor burden and inflammatory markers was observed regarding sADC, with baseline sADC and relative change promising as prognostic imaging biomarkers in HCC patients receiving ICIs.

The substantial tumor ADC is an important imaging feature revealing the potential association between tumor burden and inflammation, and its prognostic role for patients with HCC receiving ICIs.

The sADC could indirectly reflect tumor microenvironment characteristics. The association between tumor burden and inflammatory markers was observed regarding sADC. Baseline sADC and its change predict prognosis in ICI-treated HCC patients.

Asthma is one of the most common chronic respiratory diseases, persisting across the life course and affecting approximately 300 million people worldwide. Severe asthma, defined as asthma remaining uncontrolled despite adherence to optimised high-dose inhaled corticosteroids/long-acting β2-agonist therapy and management of contributory factors, worsens upon dose reduction. In China, 3.4%-8.3% of patients with asthma have severe asthma, characterised by heterogeneity, frequent exacerbations, and considerable medical and economic burdens. Recent advances in the understanding of its pathogenesis, especially the development of biologics, have enabled new treatment strategies. This review incorporates recent progress from China regarding the epidemiology, pathogenesis, and biologic therapy for severe asthma.

Neoadjuvant chemoimmunotherapy (NACI) has significantly improved survival in patients with resectable non-small cell lung cancer (NSCLC). However, with the currently available methods (PD-L1, RECIST), it is difficult to predict who will benefit from treatment before therapy and who will achieve pathological complete response (pCR) before surgery. Non-invasive methods to predict treatment response to NACI could be used to further personalize treatment.

In the multicenter retrospective study, we enrolled 534 patients with NSCLC who received NACI followed by surgical resection at three Chinese hospitals between January 2019 and December 2024 (193 patients from Center A, 193 patients from Center B, and 148 patients from Center C). We developed and validated Lung Cancer Neo-adjuvant Immuno-Chemotherapy Response Predictor (LC-NICER), a CT-based Artificial Intelligence (AI) system that integrates longitudinal radiomics (tumor texture), deep learning (microenvironmental context), and habitat imaging (tumor and peritumoral subregional dynamics) to predict pCR by analyzing tumor spatiotemporal heterogeneity. The LC-NICER system consists of two complementary predictive models: LC-NICER_α, a pretreatment model that identifies patients likely to benefit from NACI to guide personalized therapy, and LC-NICER_δ, a preoperative model that evaluates tumor regression and resection feasibility to inform surgical planning. This study is registered at ClinicalTrials.gov (NCT06285058).

Among the 386 patients from Center A and B, 308 were randomly assigned to the training dataset and 78 to the internal validation dataset, following an 8:2 split ratio. The 148 patients from Center C formed an independent and external test dataset. LC-NICER prediction system demonstrated excellent performance with the area under the curves (AUCs) of 0.950 (0.927-0.970) in the training cohort, 0.889 (0.796-0.961) in the internal validation cohort, and 0.870 (0.803-0.927) in the external test cohort. The LC-NICER_α achieved an accuracy of 0.722 (0.668-0.772) before therapy, while LC-NICER_δ showed significantly improved accuracy of 0.831 (0.800-0.861) before surgery. Notably, LC-NICER outperformed current clinical standards, with absolute accuracy improvements of 10% over PD-L1 testing (0.622 [0.564-0.683], p = 0.002) and 18% over RECIST 1.1 criteria (0.651 [0.610-0.693], p = 0.008). For easy clinical utility and research reproducibility, we developed and openly published a software.

As a non-invasive AI system for predicting NACI response in NSCLC, LC-NICER may offer future clinical personalized therapeutic strategies, accelerate adaptive clinical trials, and optimize treatment decisions, potentially reducing reliance on invasive procedures.

This work was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0531100, 2024ZD0531101), the National Natural Science Foundation of China (82472062, 62102103, 82473298, 82202148, 82502479), the National Key Research and Development Program of China (2023YFC2508603), the Natural Science Foundation of Guangdong Province of China (2024A1515011672), Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (U22A20345), Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (2022B1212010011).

Metformin, as a drug for treating type 2 diabetes, has been found to have a positive impact on mental health. This study will assess the potential causal relationship between metformin exposure and the risk of bipolar disorder (BD). We used publicly available genome-wide association studies statistical data to conduct 2-sample bidirectional Mendelian randomization (MR) analysis to determine the causal relationship between genetic susceptibility to metformin and BD risk. Genome-wide significant single nucleotide polymorphisms, that are associated with metformin use were selected as the instrumental variables. To determine the causal relationship between metformin exposure and BD, MR analysis was conducted, employing methods such as instrumental variable weighting. We applied complementary methods, including weighted median, weighted mode, simple mode, MR-Egger regression, and MR-pleiotropy residual sum and outlier to detect and correct for the effect of horizontal pleiotropy. Cochran Q statistics were used to assess instrument heterogeneity. The leave-one-out method was conducted for sensitivity analysis. The instrumental variable weighting analysis demonstrated that there was a significant causal relationship between the metformin exposure and BD risk [odds ratio [OR] (95% confidence interval [CI]) = 0.032 (0.002-0.593), P = .021] (ebi-a-GCST003724), [OR (95% CI) = 1.452E-04 (1.442E-07 to 1.463E-01), P = .012] (ieu-a-800), [OR (95% CI) = 0.33 (0.27-0.404), P = .000] (ieu-a-808). The sensitivity analysis revealed no heterogeneity in the individual results (P > .05), and no significant publication bias. This study reveals that metformin may serve as a protective factor for BD, providing new theoretical basis for the application of metabolic intervention in the prevention and treatment of mental illness.

Phase angle (PhA), as a nutritional and metabolic indicator, can reflect the integrity of cell membranes and the functional status of cells, and may have a predictive effect on the prognosis of patients with newly diagnosed type 2 diabetes mellitus (T2DM) undergoing very low-calorie diet (VLCD). This study aims to investigate the predictive value of bioelectrical impedance PhA for assessing the therapeutic efficacy of VLCD in newly diagnosed T2DM patients. Additionally, we seek to explore whether PhA can serve as an early biomarker for metabolic improvements following VLCD intervention. A total of 223 newly diagnosed T2DM patients who received 9-day VLCD intervention (300-600 kcal/day) at the Xiamen Hospital of Traditional Chinese Medicine from July 2021 to December 2023 were enrolled. Baseline PhA was measured using multifrequency bioelectrical impedance analysis. Therapeutic efficacy was defined as posttreatment homeostasis model assessment of insulin resistance <2.5. Logistic regression and receiver operating characteristic curve analyses were performed. After VLCD intervention, 139 patients (62.3%) achieved the primary endpoint (homeostasis model assessment of insulin resistance < 2.5) with significant improvements in body weight and glycemic parameters. All participants completed the intervention with good compliance. No severe adverse events (including hypoglycemia or hepatorenal dysfunction) occurred. PhA was identified as an independent predictor (males: OR = 6.34, 95% CI = 3.025-13.291; females: OR = 1.82, 95% CI = 1.05-3.15). Receiver operating characteristic analysis showed optimal predictive accuracy in males (area under the curve = 0.728, P = .001; sensitivity 66.7%, specificity 76.5% at cutoff 6.45), but limited value in females (area under the curve = 0.586, P = .089). The reduction of PhA can be considered as an independent risk factor for the prognosis of newly diagnosed T2DM patients undergoing VLCD intervention and may serve as a predictive indicator for the efficacy of dietary restriction therapy in male patients with newly diagnosed T2DM, which has potential clinical application value.

Strong relationships exist between immune factors and hyperglycemia, particularly proinflammatory factors such as interleukin (IL)-1β protein levels and genetics, which significantly correlate with the development of type 2 diabetes mellitus (T2DM). Exposure of pancreatic cells to IL-1β for an extended period enhances β-cell apoptosis, thereby affecting glucose metabolism. The study objective is to assess the functional role of IL-1β protein levels and the IL-1β rs16944 gene polymorphism in T2DM. A case-control study was conducted, involving 86 participants with T2DM and 74 controls. Blood samples were collected from the participants to assess their IL-β1 levels, fasting blood sugar levels, and fasting insulin levels. IL-1β (rs16944) was analyzed using conventional polymerase chain reaction. IL-1β rs16944 variations in the control group showed 32 (43%) of AA, 27 (36%) of AG, and 15 (20%) of GG, while T2DM patients showed 30 (35%) of AA, 34 (40%) of AG and 22 (26%) of GG variation. The logistic regression analysis showed a non-significant association between each variation and T2DM. The genome variation in patients with insulin resistance (IR) and T2DM was 8 (33%) AA, 6 (25%) AG, and 10 (42%) GG. The logistic regression test showed a non-significant association between each variation and patients with IR and T2DM. In conclusion, IL-1β levels and genetic variations of the IL-1β rs16944 gene do not affect blood sugar metabolism and I nsulin resistance in Iraqi diabetic patients.

The link between benzodiazepines (BZs) use and lung cancer remains unclear. This paper investigates this association by analyzing data from 34,084 adults, aged approximately 47.08 ± 0.22 years, from the National Health and Nutrition Examination Survey study conducted between 2001 and 2016. Multiple logistic regression is employed to control for various factors including age, sex, ethnicity, education, poverty to income ratio, diabetes mellitus, smoke, alcohol user, hypertension, body mass index, hyperlipidemia, chronic obstructive pulmonary disease and other cancer, in order to explore the impact of BZs on lung cancer prevalence. The findings indicate that the risk of lung cancer is 4.643 times higher in BZs users compared to nonusers (95% CI: 2.096, 10.283), and this association remains significant (OR: 2.575, 95% CI: 1.015, 6.529) after adjusting for all variables. Our research indicates that among the American population, especially men aged 60 or above, with a normal weight BMI and no hypertension, the prevalence of lung cancer is relatively high among BZs users. This requires further research to verify these findings.