Liver fibrosis is a pivotal and reversible stage in the progression of chronic liver disease. However, the mechanisms underlying fibrosis reversal remain unclear, and effective diagnostic biomarkers are lacking in clinical practice. In this study, we aimed to elucidate the role and molecular mechanisms of glutathione S-transferase Mu 3 (GSTM3) in liver fibrosis reversal, and preliminarily determine whether GSTM3 can serve as a novel biomarker for liver fibrosis reversal.

Carbon tetrachloride-induced mouse models of liver fibrosis and spontaneous reversal were established. Proteomic analysis was used to identify proteins shared between liver tissue and serum that were continuously downregulated during fibrosis reversal. The expression of GSTM3 was evaluated in the livers of mice undergoing fibrosis reversal and in clinical samples from patients with liver fibrosis. Hepatic stellate cells (HSCs) were transfected with Gstm3-silencing RNA or an overexpression plasmid to assess the effects on fibrosis markers. RNA sequencing analyses were performed, and the underlying molecular mechanisms were investigated.

Proteomic analysis revealed significantly decreased GSTM3 levels in both hepatic tissue and serum in mice undergoing fibrosis reversal, and its expression was negatively correlated with the extent of reversal. GSTM3 levels were markedly increased in the hepatic tissue and serum of patients with liver fibrosis. GSTM3 expression was upregulated in transforming growth factor-β-stimulated HSCs. GSTM3 knockdown inhibited the expression of fibrosis markers, such as collagen type I α1 and tissue inhibitor of metalloproteinase 1, whereas its overexpression promoted their expression. Mechanistic studies indicated that GSTM3 knockdown activated peroxisome proliferator-activated receptor γ (PPARγ) signaling and downregulated its downstream targets, cluster of differentiation 36 and fatty acid-binding protein 4, thereby suppressing HSC activation.

GSTM3 knockdown promotes liver fibrosis reversal via PPARγ signaling-mediated inhibition of HSC activation. Therefore, GSTM3 is a promising therapeutic target and diagnostic biomarker for liver fibrosis.

Infectious diarrhea is a gastrointestinal illness that results in around 1.7 billion cases and 525,000 deaths annually, particularly among children under five, according to the World Health Organization. While some Cameroonian medicinal plants show promise for treating diarrhea, many plants are used without established scientific evidence of their efficacy. These plants include Tithonia diversifolia (T. diversifolia) and Solanum torvum (S. torvum), which are traditionally used to treat diarrheal symptoms. This study sought to investigate the anti-Shigella activity of leaf extracts from T. diversifolia and S. torvum.

Extracts from T. diversifolia and S. torvum were obtained by successive maceration in solvents of increasing polarity, including hexane, dichloromethane, ethyl acetate, methanol, and water. The as-prepared extracts (10) were evaluated for antibacterial activity against selected Shigella species using an in vitro experiment. The mode of action of the bioactive extracts was determined in Shigella through growth kinetic analysis.

Hexane extract from S. torvum (St-HEX-F) and dichloromethane extract from T. diversifolia (Td-DCM-F) inhibited the growth of Shigella flexneri NR-518 and Shigella boydii NR-521 with minimum inhibitory concentration (MIC) values of 500 and 1,000 µg/mL, respectively. Shigella flexneri and Shigella boydii were the most sensitive strains, whereas Shigella sonnei was the most resistant strain. Bacterial growth kinetics revealed that St-HEX-F and Td-DCM-F are bacteriostatic at MIC and bactericidal at 2×MIC and 4×MIC.

Extracts from T. diversifolia and S. torvum possess anti-Shigella activity and could be used as a potential source of active ingredients for developing new treatments against diarrhea caused by multidrug-resistant Shigella.

Despite the emergence of new approaches in acute myeloid leukemia (AML) treatment in recent years, the overall prognosis remains poor. Particularly for elderly patients and relapsed/refractory cases, the five-year survival rate consistently remains below 30%. While traditional chemotherapy regimens can rapidly suppress tumor burden and alleviate clinical symptoms, they suffer from limitations such as insufficient targeting, prominent toxic side effects, and a tendency to induce drug resistance. Immunotherapy offers a novel therapeutic pathway for AML due to its advantages of precise targeting, long-lasting antitumor effects, and a controllable safety profile. However, single-agent immunotherapy demonstrates limited clinical response rates in AML and struggles to achieve complete tumor cell clearance. In this context, combination regimens of chemotherapy and immunotherapy are increasingly becoming the focus of research. This review aims to summarize the rationale and advances in the combination of immune checkpoint inhibitors, chimeric antigen receptor T-cell therapy, antibody-drug conjugates, bispecific antibodies, and cancer vaccines with chemotherapy for the treatment of AML. We have detailed the preclinical research and clinical trial progress of each combined regimen, analyzed the core challenges—including off-target toxicity, high tumor heterogeneity, and limited efficacy in specific AML subtypes—and further propose targeted solutions and future development directions, such as exploring novel specific antigens, developing multi-targeted drugs, and formulating precision individualized treatment plans. The clinical application of such combined strategies is attracting increasing attention. In conclusion, chemo-immunotherapy combinations represent a highly promising therapeutic paradigm for AML, harnessing the synergy of chemotherapy-mediated immune microenvironment remodeling and the specific antitumor activity of immunotherapies to overcome single-agent limitations and deliver meaningful survival benefits.

Infections are frequent and lethal complications of acute-on-chronic liver failure (ACLF). Reliable biomarkers to distinguish fungal from bacterial infections remain limited. Given the central role of immune dysfunction in ACLF, we aimed to evaluate the diagnostic value of serum cytokines in differentiating invasive pulmonary aspergillosis (IPA) from bacterial pneumonia (BP) in HBV-associated ACLF.

This retrospective case-control study enrolled ACLF patients admitted to the Tongji Hospital, between 2018 and 2022. Patients were categorized into IPA, BP, and non-infection groups. The BP and non-infection groups were propensity score-matched to the IPA cases. Serum cytokines levels (IL-1β, sIL-2R, IL-6, IL-8, IL-10, TNF-α) and clinical data were collected, with the diagnostic performance of these cytokines as biomarkers assessed via ROC curves.

A total of 32 IPA, 96 BP, and 96 non-infection patients were enrolled, with balanced baseline characteristics. Compared with the non-infection group, the IPA group had higher sIL-2R (1,606.00 vs. 1,211.50 U/mL, P = 0.019) and IL-6 (69.03 vs. 15.98 pg/mL, P < 0.001) levels, but lower IL-8 levels (62.20 vs. 132.00 pg/mL, P = 0.025). The BP group showed elevated sIL-2R (1,792.00 U/mL), IL-6 (49.42 pg/mL), IL-10 (13.40 pg/mL) levels compared to the non-infection group (all P < 0.001). Also, IL-8 was lower in the IPA group than in the BP group (62.20 vs. 176.00 pg/mL, P < 0.001) and its assessment could best distinguish IPA from BP (AUC = 0.743, cut-off = 76.60 pg/mL; sensitivity = 66.7%, specificity = 82.1%).

Serum IL-8 exhibited superior diagnostic value for IPA in patients with HBV-ACLF and could effectively discriminate Aspergillus infections from bacterial infections.

Breast cancer (BCA) is one of the most common cancers worldwide, with a high rate of mortality and morbidity in women. This review focuses on the applications of nanotechnology, nanomaterials, and nanoparticles (NPs) in BCA, encompassing diagnosis and therapy. Nanotechnologies, nanocarriers, and nano-encapsulations versus their corresponding counterparts for BCA diagnosis and therapy have been discussed. Various drug formulations into different nanocarriers (lipid NPs, nanoemulsions, polymeric NPs, and metal-based NPs) enhanced their bioavailability and therapeutic efficacy, overcoming the limitations of conventional formulations. Additionally, clinical specialists have achieved improved outcomes in the detection and monitoring of BCA at various stages using nanotechnology, ultimately leading to an improved quality of life for patients.

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.

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.

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.

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.

Metabolic dysfunction-associated fatty liver disease (MAFLD) represents a predominant cause of chronic liver disease, underscoring the demand for accessible, non-invasive diagnostic tools. Tongue diagnosis in Traditional Chinese Medicine provides a distinctive perspective on systemic health, though it remains largely subjective. This study aimed to develop an interpretable multimodal deep learning model for MAFLD screening by integrating quantitative tongue image features with routine clinical data.

From 904 screened candidates, 477 subjects (157 healthy, 320 MAFLD) were included and randomly allocated to training, validation, and test sets in an 8:1:1 ratio. All participants underwent standardized tongue imaging (International Commission on Illumination L*a*b color features) and comprehensive clinical evaluation. We constructed a dual-stream deep learning model, combining a ConvNeXt-Tiny network for tongue images and a multilayer perceptron for clinical variables. Feature fusion was achieved via a Dynamic Affine Feature Transformation module, and the model was trained using weighted cross-entropy loss.

MAFLD patients showed significant metabolic abnormalities compared to healthy controls. A progressive decrease in tongue yellowness (b* value) was observed with advancing fibrosis. On an independent test set (n = 48), the multimodal model achieved 97.92% accuracy, Quadratic Weighted Kappa of 0.9538, and 96.88% sensitivity, and 100% specificity, outperforming single-modality and serological models. Interpretability analyses confirmed the model’s focus on clinically relevant tongue regions and key metabolic drivers.

We developed an accurate and interpretable multimodal model that synergizes tongue image features with metabolic indicators for MAFLD screening. This approach presents a promising, low-cost tool potentially well-suited for resource-limited settings.