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Background: The World Health Organization encourages the development of novel diagnostic tools based on 'non-sputum' samples to meet global goals for tuberculosis (TB) control. We aimed to develop a machine learning-driven model for TB diagnosis, using long non-coding RNAs (lncRNAs) as biomarkers.

Methods: Peripheral blood mononuclear cells (PBMCs) from 10 TB patients, 10 latent TB infection individuals (LTBI), and 10 healthy controls (HCs) underwent microarray analysis, and the TB-related lncRNA modules were identified by weighted gene co-expression network analysis (WGCNA). Key lncRNAs were validated by qPCR and selected using LASSO regression. Five machine learning algorithms were employed to construct a diagnostic model, with the ROC analysis assessing its performance.

Results: Based on the differential lncRNA profile, WGCNA identified 12 key modules associated with TB. From the most significant modules, 45 candidate lncRNAs were validated by qPCR, with 14 showing differential expression among TB (n = 192), LTBI (n = 55), HC (n = 66), and NTB (n = 78) groups. Five lncRNAs demonstrating the greatest contribution to TB diagnosis were further selected by LASSO analysis. AdaBoost algorithm incorporating these five lncRNAs achieved optimal diagnostic performance, with an area under the curve (AUC) of 0.97 (95%CI: 0.95-0.98) in the training cohort (n = 272) and 0.91 (95%CI: 0.86-0.96) in the validation cohort (n = 119). Independent validation of the model in another cohort (n = 206) showed an AUC of 0.92 (95%CI: 0.88-0.95).

Conclusions: This study established a novel, blood-based diagnostic model incorporating five host-derived lncRNAs with an AdaBoost algorithm, offering a non-sputum approach to enhance TB diagnosis.

Background: Tension-type headache (TTH) is the most common neurological disorder. The comparative effect of pharmacological interventions for TTH prophylaxis remains unclear. We aimed to assess the comparative effects of pharmacological interventions in the prophylactic treatment of TTH.

Methods: Ovid Medline, Embase, and Cochrane were searched from inception to 12 December, 2025. Randomized controlled trials (RCTs) of medications compared to placebo or another medication for preventing TTH were included. The primary outcome was headache days per month. A Bayesian random-effect model was employed as the primary analysis of chronic TTH.

Results: Thirty-five RCTs were included, 33 (88.6%) RCTs involved chronic TTH patients, and 24 RCTs provided available data for meta-analysis. Amitriptyline 100 mg presented more reduction of monthly headache days than placebo at 4 and 8 weeks (4 weeks: MD -6.59, 95% CrI -11.22 to -0.64; 8 weeks: MD -6.14, 95% CrI -10.27 to -0.87). BTX-A 100 U can reduce monthly headache days (MD -3.79, 95% CrI -7.16 to -0.33). Amitriptyline 100 mg was the highest-ranked treatment for monthly headache days at 4 (SUCRA 0.85), 8 (SUCRA 0.85), and 24 (SUCRA 0.87) weeks; 12 weeks was lidocaine 25 ml (SUCRA 0.75). Amitriptyline 100 mg and BTX-A 500 U showed a higher adverse event rate than placebo.

Conclusion: Amitriptyline 100 mg and BTX-A 100 U may be options to reduce monthly headache days in patients with chronic TTH. Given the low to very low certainty of evidence, high risk of bias, and high heterogeneity, more studies are needed.

Trial registration: PROSPERO (CRD42025639586).

Introduction: Large-scale real-world data (RWD) are increasingly used in clinical and epidemiological research, although database-specific structures and limitations may affect study validity and applicability. The Taiwan National Health Insurance Research Database (NHIRD) and the TriNetX network are two widely used RWD sources. This review compares their key features, strengths, and limitations and discusses approaches to address methodological challenges in real-world studies.

Discussion: The NHIRD comprises comprehensive, population-based, longitudinal claims data covering nearly the entire Taiwanese population. Its strengths include minimal selection bias and broad follow-up capacity. However, limitations include infrequent updates, limited clinical detail, and a Taiwan-specific context that may restrict generalizability. In contrast, TriNetX is a multinational federated network of electronic medical records from diverse healthcare systems, offering larger and more heterogeneous populations, richer clinical variables, and near real-time analytic capability, but with potential hospital-based selection bias and limited flexibility due to its fixed analytic interface. Representative studies published between 2010 and 2024 demonstrate the application of both databases across multiple medical disciplines. To mitigate data-related limitations, commonly used strategies include refined inclusion and exclusion criteria, proxy variables for unavailable measures, and triangulation with external datasets, which can strengthen study validity and interpretability.

Conclusions: NHIRD and TriNetX are complementary real-world data sources, each with distinct strengths and limitations. Aligning research objectives with database characteristics is essential for appropriate study design. Recognition of platform-specific trade-offs and application of targeted methodological strategies support the validity and generalizability of real-world evidence.

Background: Rosacea is a common chronic inflammatory skin disease. Mast cells are implicated in the pathogenesis of rosacea. However, the therapeutic potential of tranilast, a mast cell membrane stabilizer, remains unexplored. This study aims to evaluate the efficacy and safety of tranilast monotherapy and in combination with minocycline in patients with moderate-to-severe rosacea.

Methods: This study has been registered on ClinicalTrials.gov (Registration No. NCT06307223). All enrolled patients with rosacea were randomly assigned to receive tranilast, minocycline, or a combination of both. Tranilast (0.1 g, three times daily) and minocycline (50 mg, once daily) were administered for 12 weeks, with follow-up every two weeks.

Results: Forty-five patients completed the study. At week 12, the combination group showed a significantly higher IGA success rate (93.33%) compared to the tranilast (53.33%) and minocycline (46.67%) groups (p < 0.05). The secondary endpoints, such as CEA success rate, erythema index, and erythema score, also favored the combination group over minocycline group (p = 0.021, 0.030, and 0.024, respectively).

Conclusion: In our study, patients with moderate to severe rosacea treated with tranilast showed a favorable clinical response and experienced no serious adverse events. The combination therapy yielded better outcomes than minocycline monotherapy, especially in improving facial erythema.

Background & aims: Sickle cell disease (SCD) leads to recurrent vaso-occlusive crises (VOC) and hospitalizations, imposing a substantial healthcare burden. Hydroxyurea (HU) is known to reduce VOC frequency and hospitalization rates in SCD; however, data comparing the impact of different HU doses on length of stay (LOS) and clinical outcomes in adults are limited.

Methods: This retrospective study assessed the effect of high- versus low-dose HU on LOS among adults with SCD admitted to medical wards. Secondary endpoints included VOC frequency and hemoglobin electrophoresis findings. Pearson's chi-square and Mann-Whitney tests were used, with significance set at p < 0.05.

Results: A total of 141 patients were analyzed (26 on low-dose, 115 on high-dose HU), with a median age of 31 years; 52.5% were female. The overall median LOS was 3 days (IQR 1-10). The low-dose group had a significantly longer median LOS (7 days [IQR 7-9]) compared with the high-dose group (2 days [IQR 2-3]; p < 0.001). Higher HU doses were also associated with improved Hgb F% and Hgb S% (p < 0.001), while annual VOC rates showed no significant difference (p = 0.132).

Conclusion: High-dose HU was linked to shorter hospital stays and favorable hematologic outcomes in adults with SCD.