Luteolin is a dietary flavonoid widely distributed in fruits and vegetables. It has attracted substantial preclinical interest due to its pleiotropic hepatoprotective effects against hepatic steatosis, inflammation, fibrosis, and hepatocellular carcinoma. By reviewing data from in vitro and in vivo studies, this review comprehensively synthesizes the full spectrum of liver-directed pharmacology of luteolin, covering metabolic and toxic liver injury, fibrosis, cancer, and viral hepatitis, while critically mapping each mechanism to specific disease contexts and systematically identifying the key challenges limiting its clinical translation. The underlying mechanisms of luteolin action involve activation of Nrf2-mediated antioxidant defense, suppression of NF-κB- and NLRP3-driven inflammatory responses, inhibition of hepatic stellate cell activation via the TGF-β/Smad and STAT3 pathways, and regulation of metabolic homeostasis through liver X receptor (LXR)/SREBP-1c and AMPK signaling. Despite well-characterized mechanisms in preclinical models, several critical gaps hinder its clinical translation: (1) Rigorous randomized controlled trials in well-defined patient populations are scarce, with only one combination supplement study reported. (2) The relative contribution of luteolin metabolites to its overall bioactivity remains poorly understood, even though derivatives such as luteolin-7-diglucuronide exhibit distinct pharmacological properties. Cell-type-specific delivery systems, which show promise in preclinical fibrosis and cancer models, have not been evaluated clinically. (3) Systematic studies on the synergistic effects of luteolin with standard-of-care drugs remain largely exploratory. Overall, luteolin is a promising multi-target nutraceutical for liver diseases, and its clinical translation requires optimized delivery strategies, investigation of metabolite activity, and well-designed human clinical trials.

Comparative data on sequential transarterial chemoembolization (TACE) after stereotactic body radiation therapy (SBRT) in recurrent hepatocellular carcinoma (HCC) remain limited. This study aimed to evaluate the efficacy of this combination.

We retrospectively reviewed 152 patients with recurrent HCC who met predefined eligibility criteria; 109 received SBRT alone and 43 received SBRT plus TACE. To minimize selection bias, a 2:1 propensity score matching was performed, resulting in 68 patients in the SBRT-alone group and 36 in the SBRT plus TACE group for the final comparative analysis. Overall survival, progression-free survival, and local control were assessed using the Kaplan-Meier method.

The SBRT plus TACE group was associated with numerically higher survival rates, although this difference did not reach statistical significance. The cumulative one-, three-, and five-year overall survival rates were 91.2%, 76.3%, and 61.8% for SBRT alone, compared to 100.0%, 86.1%, and 77.5% for the combination therapy ( p = 0.069). The corresponding progression-free survival rates were 73.1%, 51.1%, and 32.3% versus 88.9%, 58.1%, and 52.3% ( p = 0.091). No acute grade ≥3 toxicities were observed in either group.

In this exploratory analysis of recurrent HCC, the combination of SBRT and TACE demonstrated a favorable trend toward improved survival compared with SBRT alone, without an increase in severe toxicity. While these findings did not reach statistical significance, they establish the safety profile of the combined approach and provide preliminary evidence supporting its potential therapeutic role. This hypothesis-generating study justifies and informs the design of larger, prospective trials to definitively evaluate the efficacy of this regimen.

The long-term clinical outcomes of patients with hepatitis B virus (HBV)-related cirrhosis receiving nucleos(t)ide analog (NA) therapy according to virological response patterns remain inadequately defined. This study aimed to investigate the association between virological response patterns and clinical outcomes in a large, long-term, real-world cohort.

This retrospective–prospective cohort study enrolled patients with HBV-related cirrhosis receiving NA therapy from 2009 to 2019. According to the serum HBV DNA levels during the initial two years of antiviral treatment, patients were categorized as having a complete (CVR) or partial virological response (PVR). Patients with CVR were further stratified according to their dynamic HBV DNA changes during follow-up into maintained virological response (MVR) or virological breakthrough (VBT) patterns. The primary clinical outcomes included hepatocellular carcinoma (HCC), acute-on-chronic liver failure, and liver-related death. Secondary endpoints included recompensation and progression to decompensation. Cox proportional hazards regression was used to assess the association between virological response patterns and clinical endpoints.

In total, 1,869 patients were enrolled. During a median follow-up of seven years, the MVR, VBT, and PVR rates were 65.4%, 26.5%, and 8.1%, respectively. The cumulative serum hepatitis B surface antigen (HBsAg) clearance rate was 9.8%. Moreover, 34.9% of patients with HBsAg < 100 IU/mL at baseline experienced HBsAg clearance. Compared with patients with VBT and PVR, those with MVR had a lower five- and ten-year cumulative incidence of HCC in both the compensated (five-year: 10.1% vs. 17.0%; ten-year: 14.2% vs. 33.6%; P < 0.001) and decompensated cirrhosis subgroups (five-year: 19.5% vs. 36.7%; ten-year: 25.7% vs. 49.7%; P < 0.001). Similarly, patients with MVR also had a lower cumulative incidence of liver-related death. Additionally, a higher hepatic recompensation rate was observed in patients with MVR than in those with VBT (34.1% vs. 22.5%, P < 0.001). Importantly, patients achieving HBsAg clearance and undetectable serum HBV DNA levels (“functional cure” during ongoing NA therapy) had the lowest five- and ten-year cumulative incidence of HCC (3.9% and 8.7%, respectively).

Patients with long-term MVR exhibited a lower incidence of HCC and liver-related death in both compensated and decompensated HBV-related cirrhosis subgroups, especially those achieving “functional cure.” However, more than 30% of patients experienced PVR or VBT during long-term NA antiviral therapy. These findings highlight the importance of long-term, rigorous monitoring after initial CVR to optimize outcomes and support clinical decision-making.

Insulin resistance is a common extrahepatic manifestation of hepatitis C virus (HCV) infection (HCVi), but its mechanism is poorly understood. While systemic insulin resistance is documented, portal insulin dynamics, a key regulator of hepatic metabolism, remain unexplored. This study aimed to investigate the relationship between insulin, the gut-liver axis, and immunometabolic changes in patients with HCV.

HCV patients were evaluated before (HCVi; n = 29) and after sustained virologic response (SVR) achieved with sofosbuvir/velpatasvir treatment (SVR, n = 23) (NCT02400216). Liver biopsies, portal blood, and peripheral blood were collected at both phases. Statistical analyses were conducted using Wilcoxon rank-sum tests, Mann-Whitney tests, and Pearson’s correlation coefficients to assess differences and associations across insulin, glucose, cytokines, metabolites, immune cells, and hepatic liver transcriptomics to elucidate impaired insulin homeostasis in HCVi.

HCV patients had significantly reduced portal insulin compared to SVR (p = 0.02), while peripheral insulin, portal glucose, and peripheral glucose remained unchanged. Portal insulin correlated positively with proinflammatory cytokines and vascular injury markers and negatively with CD8/CD62L/CD45RA/CD3 cells (naive cytotoxic T-cells) and non-standard nucleotides. Hepatic transcriptomic analysis revealed portal insulin correlated positively with immune and negatively with amino acid pathways, reflecting insulin’s role in the perturbations of immunometabolism during HCVi.

Lower portal insulin during HCVi is associated with changes consistent with altered pancreatic insulin secretion and decreased hepatic insulin extraction. The observed correlations support a potential relationship between the immune response and insulin dynamics, indicating an interplay between the immune system, metabolism, and insulin in HCVi, with clinical implications for the management of dysglycemia.

Cervical cancer, driven mainly by persistent high-risk human papillomavirus infection, remains a major public health problem in Bangladesh, with 9,640 new cases and 5,826 deaths in 2022. Early detection of pre-cancerous cervical lesions (PCL) is essential, yet limited evidence exists on factors associated with PCL among Bangladeshi women. This study aimed to identify factors associated with PCL among women attending cervical cancer screening centers at selected tertiary hospitals.

An age-matched (±5 years) case-control study was conducted in two tertiary hospitals. Cases were women who tested colposcopy-positive for PCL, and controls were visual inspection with acetic acid-negative women attending the same screening centers. A total of 38 cases and 76 controls were included. Data were collected through face-to-face interviews using a structured questionnaire. Multivariable logistic regression identified factors associated with PCL, with significance set at p < 0.05.

A history of sexually transmitted infections (adjusted odds ratio (AOR) = 36.73; 95% confidence interval (CI): 3.25–414.83), pelvic infections (AOR = 6.48; 95% CI: 1.24–33.85), not living with a husband (AOR = 4.48; 95% CI: 1.06–18.90), and overweight/obesity (AOR = 3.58; 95% CI: 1.14–11.22) were significantly associated with higher odds of PCL. Menstrual irregularity, genital ulcer history, and number of lifetime sexual partners showed no significant association.

Sexually transmitted infections, pelvic infections, overweight/obesity, and not living with husband were identified as factors associated with PCL. Strengthened infection prevention, lifestyle counseling, and targeted health education may support ongoing cervical cancer prevention efforts in Bangladesh.

Human papillomavirus (HPV) is a double-stranded circular DNA virus with a genome of approximately 7–8 kb. This study aimed to establish an overlapping extension polymerase chain reaction method for the amplification of the entire genome of HPV16.

The HPV16 genome was divided into two larger fragments (with lengths of 3.9 kilobases and 5.3 kilobases, respectively), each of which had overlapping regions of more than 500 base pairs. A nested primer (outer primer: Fout/Rout; inner primer: Fin/Rin) was used to amplify each fragment. The key reaction parameters were optimized, including the selection of two highly accurate DNA polymerases; and a series of diluted samples (initial concentration of 2,000 copies/microliter, diluted to 2, 20, 200, and 2,000 copies/microliter) were used for amplification tests to evaluate the sensitivity of this method.

This study demonstrated high sensitivity for HPV16 detection, with effective amplification of samples as low as 2 copies/µL. For low-concentration samples (<200 copies/µL), the Thermo Fisher enzyme showed 50% and 75% effective amplification success rates at 2 copies/µL and 20 copies/µL, respectively, while the Vazyme enzyme achieved 0% success at both concentrations. Both enzymes enabled stable amplification of high-concentration samples (≥200 copies/µL). The amplified products matched the theoretical size, and Illumina sequencing confirmed Q30 ≥ 96% and >98% identity with the HPV16 reference sequence (K02718.1).

This study provides a highly sensitive and specific method for the full-genome sequence analysis of HPV16, which is applicable to HPV16 full-genome sequencing, variation analysis, and other research.

Colorectal polyp detection from endoscopic images is critical for the early diagnosis of colorectal cancer. However, traditional deep learning methods often suffer from limited generalization when deployed across datasets containing different polyp morphologies. This work aimed to investigate whether vision-language foundation models can facilitate zero-shot generalization across multiple polyp datasets without target-domain fine-tuning.

We introduced a zero-shot colorectal polyp detection framework based on Contrastive Language-Image Pretraining (CLIP) to improve cross-dataset detection performance. Key innovations include: (1) a background patch contrastive loss using pseudo-normal tissue patches to teach the model to distinguish normal mucosa from polyps; (2) attribute-enhanced text prompts that incorporate domain-specific descriptors of polyp appearance, improving the model’s semantic generalization to novel polyp morphologies; and (3) an enhanced CLIP visual adapter with per-layer adaptive feature fusion and generalized mean pooling to capture multi-scale features for better polyp localization. During training, we use one annotated colorectal polyp dataset (e.g., CVC-ColonDB) to learn patch-level image-text correspondence. The model is then evaluated in a zero-shot manner on different polyp datasets (CVC-ClinicDB, Kvasir-SEG, and CVC-300), where we evaluate pixel-level anomaly detection performance.

The framework demonstrated robust zero-shot generalization on unseen test cohorts. Without any dataset-specific fine-tuning, the model achieved a mean pixel-level AUROC of 0.94 and a mean average precision of 0.81 across the 12 leave-one-dataset-out zero-shot transfer settings. In the CVC-ColonDB-source benchmark, the model achieved a mean Dice coefficient of 0.84 across CVC-ClinicDB, Kvasir-SEG, and CVC-300. This high level of performance was consistent across datasets with distinct visual characteristics, underscoring the ability of the model to detect diverse polyp morphologies that it had not been explicitly trained to recognize.

Our findings demonstrate that an anomaly-aware vision-language model significantly improves cross-dataset polyp detection generalization without requiring normal images for training. This multimodal strategy may facilitate the robust deployment of artificial intelligence-based colorectal screening systems by enabling reliable detection of diverse polyp morphologies across different clinical settings. Extension to non-polyp colorectal pathologies (e.g., ulcerative colitis and colorectal tumors) remains an important direction for future work, pending the availability of pixel-level annotated datasets for these lesion categories.

The optimal management strategy for adults with immune-tolerant (IT) chronic hepatitis B infection remains undefined. This study aimed to investigate the efficacy and predictive factors of a pegylated interferon (Peg-IFN)-based treatment strategy in IT patients with chronic HBV infection.

In this pilot, open-label, prospective study, 286 patients aged 18 to 60 years with IT characteristics were enrolled and allocated to one of three groups. The combination group received Peg-IFN for 48–96 weeks, with tenofovir disoproxil fumarate (TDF) initiated at week 12 and continued through week 96 (n = 103). The monotherapy group received TDF monotherapy alone (n = 125), and the control group was monitored without therapeutic intervention (n = 58).

No patients in the control group met any predefined efficacy endpoints. Intention-to-treat analysis showed that patients in the combination group achieved significantly higher virological response rates (71.8% vs. 53.6%, p = 0.005), hepatitis B e antigen seroconversion rates (15.5% vs. 1.6%, p < 0.001), and hepatitis B surface antigen (HBsAg) loss rates (10.7% vs. 0%, p < 0.001) compared with those in the monotherapy group at week 96. In the combination group, the cumulative rate of HBsAg loss was 5.4% at week 48 and increased to 11.8% by week 96. Independent predictors of achieving either hepatitis B e antigen seroconversion or HBsAg loss were baseline age under 30 years (odds ratio = 0.217, 95% confidence interval: 0.048–0.976, p = 0.046) and a decline in HBsAg level greater than 1 log10 IU/mL by week 24 (odds ratio = 13.976, 95% confidence interval: 2.506–77.932, p = 0.003).

A Peg-IFN-based treatment strategy significantly increases response rates compared with TDF monotherapy or observation in patients with IT characteristics.

Reporting quality in clinical research is critical for evidence-based medicine and reproducibility of clinical studies. Previous work has mostly focused on the reporting quality of clinical trials and observational longitudinal studies. However, few studies have examined the reporting quality of trend analyses. Moreover, the reporting of recommended statistical metrics in trend analyses remains largely unclear. Therefore, we assessed the reporting quality of trend analyses based on reporting of recommended statistical metrics. We systematically searched the PubMed for the trend-analysis articles published in 10 leading medicine and oncology journals over an 11-year period (2008–2018). Studies published after 2019 were excluded due to a sudden, significant increase in publication numbers during and immediately after the COVID-19 pandemic. Only original articles, research letters, and meta-analyses/systematic reviews were included. We scored the reporting quality of these articles based on whether they reported p-values, effect sizes, beta/coefficient/slope/annual-percentage-change (APC). 297 articles met the inclusion criteria. Among these, 193 (66.0%) reported p-values and 216 (72.7%) reported effect sizes. Only 13 (5.8%) analyses reported neither p-values/effect sizes nor beta/coefficient/slope/APC. In multivariable regression models, authors affiliated with epidemiology departments were less likely to report effect sizes, whereas those from statistics departments were more likely to do so. Interestingly, U.S.-based senior authors (versus non-U.S.) more likely reported p-values. No factors were independently associated with reporting APC. Overall, the reporting quality of trend analyses in leading medicine and oncology journals appears moderate and warrants improvement. We thus call for increased awareness and further research on reporting quality in trend analyses in oncology research and beyond.