To identify metabolic-inflammatory profiles in US adults and assess their cross-sectional associations with self-reported osteoarthritis (OA) and lower-extremity functional limitation. We analyzed six National Health and Nutrition Examination Survey cycles from 2007–2008 to 2017–2018. Latent class analysis used body mass index, waist circumference, systolic blood pressure, diabetes, and log-transformed neutrophil-to-lymphocyte ratio. Survey-weighted logistic regression assessed prevalent OA in 9770 adults and lower-extremity functional limitation in 2189 adults with available Physical Functioning Questionnaire data. Among 9770 participants, 559 met the study definition of OA. Three profiles were identified: relatively healthy, intermediate metabolic, and highest metabolic-inflammatory burden. After full adjustment, the intermediate profile was not associated with OA (OR 1.34, 95

PURPOSE:Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease with a median survival of only 2-3 years after diagnosis. Yinfenidone (HEC585) possesses the potential to inhibit the proliferation of pulmonary fibroblasts, making it a promising candidate for the treatment of IPF. This study assessed the safety, tolerability, pharmacokinetics, and metabolic profile of Yinfenidone hydrochloride capsule in healthy Chinese subjects. METHODS:This single-center, randomized, double-blind, placebo-controlled, single ascending-dose trial included seven dose groups(20, 50, 100, 200, 400, 600, and 800 mg). Each group enrolled8 healthy subjects: 6 received Yinfenidone hydrochloride capsules and 2 received matching placebo under fasting conditions. Serial pharmacokinetic (PK) blood samples were collected pre-dose and post-dose, liquid chromatography-tandem mass spectrometry was used to analyze the plasma concentrations of Yinfenidone. Additionally, metabolic biotransformation of Yinfenidone in plasma were conducted in the 100 mg dose group. Safety and tolerability endpoints were monitored via physical examinations, vital signs measurements, clinical laboratory tests, 12-lead electrocardiography (ECG), and adverse events (AEs) documentation throughout the trial. FINDINGS:Yinfenidone was rapidly absorbed, with a median maximum plasma concentration (Tmax) of 1.8-3.0 hours, and had a mean half-life (t1/2) ranging from 31.9 to 62.0 hours. Within the 20-100 mg dose range, systemic drug exposure generally increased with ascending dose, above 100 mg, exposure increased less than proportionally to dose. Metabolite profiling in the 100 mg group revealed that the parentcompound predominated in plasma, with metabolic pathways including mono-oxygenation and N-dealkylation. All reported AEswere mild, classified as Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 grade 1. No serious AEs observed; no subject discontinued the trial due to AEs. Single oral doses of 20-800 mg Yinfenidone hydrochloride capsules administered under fasting conditions demonstrated favorable safety and tolerability profiles in healthy Chinese subjects. IMPLICATIONS:Yinfenidone exhibited rapid absorption (median Tmax, 1.8-3.0 hours) and a long terminal t1/2 ranging from 31.9 to 62.0 hours in this single ascending-dose study, indicating that Yinfenidone can be taken once a day in subsequent clinical studies. Yinfenidone mainly exists in human plasma as the original drug and is metabolized through a variety of metabolic pathways. The AEs observed with Yinfenidone in this study, such as diarrhea, nausea, and dizziness, were similar to those reported with pirfenidone. Overall, Yinfenidone demonstrated a favorable safety and tolerability profile in this cohort of healthy subjects.

IntroductionUnder chronic infections or in tumors, persistent antigen exposure drives CD8+ T cell exhaustion, a heterogeneous state encompassing a differentiation continuum from stem-like progenitor (Tpex) cells through transitory effector-like (Tex-int) cells to terminally exhausted (Tex-term) subsets. Among these T cell subsets, Tex-int cells serve as the primary population responsible for direct tumor cell killing. However, the intrinsic regulatory mechanisms that govern the Tpex-to-Tex-int transition remain incompletely defined.MethodsIn this study, we explore the role of special AT-rich sequence-binding protein 1 (SATB1) in the differentiation of Tex-int cells from their precursors. We observed downregulation of SATB1 during Tpex-to-Tex-int differentiation in tumors. Notably, the genetic ablation of Satb1 in T cells markedly expanded the population of tumor-infiltrating CD8+ T cells (CD8+ TILs).ResultsAblating Satb1 not only promoted the differentiation of Tex-int cells from Tpex cells within the tumor microenvironment but also remodeled T cell differentiation in tumor-draining lymph nodes (TdLNs) by expanding the Tpex pool from tumor-specific memory CD8+ T cells (TTSM) and driving the Tpex1 to Tpex2 transition, thereby augmenting Tex-int production in tumors. Although early-stage Tex-int cells in Satb1-deficient mice displayed transient functional impairment relative to controls, this difference was no longer evident in late-stage tumors, where sustained Tex-int accumulation correlated with significantly suppressed tumor growth and prolonged survival.DiscussionOur results identify SATB1 as a pivotal regulator of exhausted CD8+ T cell subset differentiation and suggest its targeting as a promising strategy to expand the Tex-int population for enhanced cancer immunotherapy.

Pulmonary fibrosis (PF) following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a life-threatening complication. Despite growing concerns about PF after SARS-CoV-2 infection, early recognition remains challenging. Additionally, the role of changes in respiratory and intestinal microbiota in PF progression remains insufficiently understood. To address this gap, this study uses a multi-omics approach to analyze microbiota and clinical changes in PF patients following SARS-CoV-2 infection, developing a predictive model for PF progression with risk stratification to enable early interventions and improve outcomes. A total of 68 patients with confirmed SARS-CoV-2 infection were included in the study, divided into two subgroups: patients with PF (COVID-PF) and patients without PF (COVID-non PF). Metagenomic sequencing of bronchoalveolar lavage fluid (BALF) and fecal specimens was performed to profile respiratory and intestinal microbiota. Peripheral blood mononuclear cells (PBMCs) were collected for transcriptome sequencing. A random forest classifier was developed to predict PF risk based on integrated respiratory-intestinal microbiota profiles as well as clinical indicators. Our findings suggest that there are significant differences in the respiratory and intestinal microbiota between COVID-non PF and COVID-PF patients. Transcriptomic analysis of PBMCs revealed significant activation of immunomodulatory pathways associated with PF development. The machine learning model further allowed early PF risk stratification, demonstrating that changes in both microbiomes, along with clinical indicators, can predict the progression and prognosis of PF. Overall, these results offer new insights into disease and suggest options for early detection and personalized treatment strategies for PF in SARS-CoV-2-infected patients.

OBJECTIVES:Based on surveillance data from Chinese livestock and poultry farms between 2011 and 2021, we analysed the antimicrobial resistance and transmission characteristics of diarrheagenic Escherichia coli (DEC) and non-diarrheagenic strains. METHODS:Phenotypic antibiotic resistance testing, antibiotic resistance gene screening, plasmid typing, and multilocus sequence typing were performed using 1114 identified isolates, and a phylogenetic tree was constructed to assess genetic relationships. RESULTS:DEC accounted for 2.7% of all strains, with enterotoxin-producing E. coli being the predominant subtype. DEC strains exhibited significantly higher rates of antimicrobial resistance phenotypes, resistance genes, and plasmid carriage than non-DEC strains (P < 0.001), primarily attributable to the host source. Pig-derived DEC strains exhibited significantly higher resistance rates to apramycin, tobramycin, kanamycin, and colistin, as compared with non-DEC strains (P < 0.01), as well as increased carriage rates of mcr-1.1, blaOXA-1, and aac(3)-IVa and a higher prevalence of IncI and IncHI2. Multilocus sequence typing analysis indicated that DEC strains predominantly comprised ST10 and ST29. The phylogenetic tree revealed that strains clustered according to pathogenicity types; the enterotoxin-producing E. coli branch carried blaCTX-M-55, consistent with the ceftiofur-resistant phenotype, which was primarily localized to IncF family fusion plasmids. CONCLUSIONS:DEC showed a low prevalence in healthy farmed animals, with the host source having a greater impact on the transmission of antibiotic resistance than the pathogenic type itself. The present findings provide a scientific basis for the rational use of antibiotics and monitoring of antibiotic resistance risks in the Livestock Farming industry.

Introduction:Post-COVID-19 respiratory infection dynamics require updated epidemiological characterization to inform clinical surveillance and public health strategy. Methods:We analyzed 2484 patients with respiratory tract infections (September 2023-February 2024) using comprehensive pathogen screening (29 viral, bacterial, and atypical targets) and cytokine quantification (12 cytokines). Results:Overall pathogen detection was 70.73%, with viral and bacterial identification in 40.42%(1004/2484), 51.45%(1278/2484) of cases respectively, and co-infections in 31.88% (predominantly Haemophilus influenzae-virus). Pediatric patients (<18 years) showed significantly higher positivity (74.1% vs. 63.2%, P < 0.05) with viral predominance (41.57% vs. 37.84%), while adults showed bacterial predominance (57.38% vs. 38.23%). Pneumonia risk exhibited age-pathogen specificity: Mycoplasma pneumoniae posed the highest risk in children (41.1% pneumonia rate) versus influenza B in adults (10.2% detection rate). Retrospective cytokine analysis (pre-pandemic 2018-2019 vs. post-pandemic 2023-2024) revealed post-pandemic suppression of IL-6 (6.12 vs.3.82 pg/mL) and IL-8 (37.98 vs. 18.35 pg/mL), with resurgence in 2024, particularly in pediatric and pneumonia cases (P<0.05). Discussion:Post-pandemic respiratory pathogen epidemiology is characterized by heightened pediatric susceptibility to viral co-infections, bacterial pathogen persistence despite control measures, and dysregulated inflammatory responses. These findings warrant age-stratified diagnostic and surveillance approaches with adaptive public health strategies to reduce respiratory infection morbidity.

Uncontrolled pneumonia induced by influenza virus infection results in severe lung pathology. Timely and proper tissue self-repair is critical to improve survival. This study aimed to identify probiotic strains that confer protection against acute lung injury induced by influenza virus infection and to elucidate the underlying molecular mechanisms. Significant structural alterations in the gut microbiota were observed in influenza patients, characterized by a marked depletion in Faecalibacterium prausnitzii, whose abundance was negatively correlated with disease severity. In a murine model of influenza infection, oral administration of Faecalibacterium prausnitzii and its culture supernatant markedly alleviated lung injury. Targeted metabolomic analysis identified butyrate as the principal metabolite produced by Faecalibacterium prausnitzii that mediates lung tissue protection. Single-cell RNA sequencing further revealed that butyrate promotes the differentiation of pulmonary CD4⁺T cells into a reparative phenotype with enhanced interleukin-22 (IL-22) production. Mechanistically, butyrate facilitates IL-22 secretion through monounsaturated fatty acid biosynthesis via a histone-acetylation-dependent NR4A1-SCD1 axis. Accumulated monounsaturated fatty acids further enhance mitochondrial activities, which are essential for robust IL-22 production. Utilizing an IL-22 knockout mouse model, we confirmed the indispensable protective role of IL-22 in this gut-lung axis during influenza infection. Our findings demonstrate that butyrate, derived from intestinal commensal Faecalibacterium prausnitzii, plays a crucial role in maintaining pulmonary tissue homeostasis during influenza infection by modulating intrinsic lipid metabolism in CD4+T cells. This study underscores the promising translational potential of Faecalibacterium prausnitzii supplementation as an innovative therapeutic strategy for severe influenza-associated lung injury.

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis worldwide, with climate warming facilitating its spread to high-latitude areas. In this study, we analyzed 212 genomes of environmental and seafood-associated isolates collected from seven cities in Zhejiang Province, China (2019-2024), alongside 228 clinical genomes from public databases. The 212 isolates were assigned to 172 sequence types (STs), with ST490 being the most frequent (5/212, 2.36%). Forty-four serotypes were identified, dominated by OL3:KUT (12.68%). High ST and serotype diversity were observed across different sample types and sources, with median pairwise single nucleotide polymorphisms (SNPs) ranging from 57,431 to 58,378, indicating comparable genetic diversity across groups. All isolates carried tlh and T3SS1 but lacked tdh and T3SS2. Resistance rates against ampicillin and cefazolin were 54.72% (116/212) and 44.34% (94/212), respectively, with multidrug resistance (MDR) detected in nine isolates, predominantly from seafood (7/9). A total of 63 distinct antimicrobial resistance genes (ARGs) spanning seven classes were identified. Isolates from aquaculture farms and wet markets exhibited greater resistance category diversity and higher ARG carriage than those from coastal or riverine sites. In contrast, the 228 clinical isolates harbored only 25 ARGs across two classes, with a significantly lower proportion of isolates carrying multiple ARG classes (0.44% vs. 6.13%, P < 0.001). Human isolates formed tighter phylogenetic clusters, although a minority were closely related to environmental/foodborne strains. Overall, our findings demonstrate the genetic diversity and resistance potential of V. parahaemolyticus across environmental, seafood, and clinical sources, highlighting the importance of the One Health approach to comprehensive public health risk assessment.

Bacteria colonize nearly every part of the human body and various environments, displaying remarkable diversity. Traditional population-level transcriptomics measurements provide only average population behaviors, often overlooking the heterogeneity within bacterial communities. To address this limitation, we have developed a droplet-based, high-throughput single-microorganism RNA sequencing method (smRandom-seq) that offers highly species specific and sensitive gene detection. Here we detail procedures for microbial sample preprocessing, in situ preindexed cDNA synthesis, in situ poly(dA) tailing, droplet barcoding, ribosomal RNA depletion and library preparation. The main smRandom-seq workflow, including sample processing, in situ reactions and library construction, takes ~2 days. This method features enhanced RNA coverage, reduced doublet rates and minimized ribosomal RNA contamination, thus enabling in-depth analysis of microbial heterogeneity. smRandom-seq is compatible with microorganisms from both laboratory cultures and complex microbial community samples, making it well suited for constructing single-microorganism transcriptomic atlases of bacterial strains and diverse microbial communities. This Protocol requires experience in molecular biology and RNA sequencing techniques, and it holds promising potential for researchers investigating bacterial resistance, microbiome heterogeneity and host–microorganism interactions. This Protocol outlines the steps for high-throughput single microorganism isolation and microfluidic droplet-based encapsulation and barcoding to obtain single cell transcriptomes from both cultured and complex microbial community samples.

Respiratory virus including influenza A virus (IAV) infection induces alterations in gut microbiota structure and function, which in turn plays an essential role in the pathogenic process. Alterations in gut microbiota are usually accompanied with changes in metabolites. The specific relationship between dynamic changes in gut microbiota and serum metabolites in influenza remains unclear. In this study, we depicted dynamic changes in composition of gut microbiota by using metagenomic sequencing in an influenza mouse model. Through mass spectrometry based metabolomic, we identified (S)-Equol as a notable protective metabolite derived from intestinal flora. Serum (S)-Equol level decreased from the initial infection phase and increased gradually during the convalescence phase, which was positively associated with the changes in some Eggerthella and Bifidobacterium species. Antibiotic treatment reduced serum (S)-Equol level and exacerbated lung pathological damage. Oral administration of (S)-Equol relieved disease severity and controlled inflammatory infiltration. Mechanistically, (S)-Equol activated Nrf2 in macrophages, thereby inhibited AKT, ERK and NF-κB phosphorylation. The inhibition of these signaling pathways ultimately restrained pro-inflammatory cytokines release and repressed pro-inflammatory macrophage polarization. Moreover, serum (S)-Equol level was lower in influenza patients at progressed phase and was negatively correlated with serum levels of IL-6, IL-1β, and TNF-α. Collectively, our data highlighted gut derived (S)-Equol a promising postbiotic for alleviating influenza pneumonia.

Objective:Early and precise diagnosis of tuberculous serous effusions is a huge challenge. Nanopore sequencing is a potentially efficient assay. The objective of the current study was to evaluate the diagnostic accuracy of nanopore sequencing for tuberculous serous effusions using clinical specimens directly, and to provide a new pathway for the early and precise diagnosis of tuberculous serous effusions. Methods:This was a retrospective analysis of the effectiveness of nanopore sequencing as a diagnostic method for tuberculous serous effusions using clinical specimens (pleural fluid, pericardial effusion, and ascitic fluid). Using clinical diagnosis as reference standard, the diagnostic accuracy indicators such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) for the tests in question were evaluated. Results:In total, 132 patients were eligible for inclusion. Nanopore sequencing showed sensitivity of 93.3%, specificity of 85.2%, PPV of 96.1%, NPV of 76.7%, and AUC of 0.89 for tuberculous serous effusions. The diagnostic accuracy of nanopore sequencing was significantly superior than that of Xpert MTB/RIF and culture. Similar results were observed in different types of tuberculous serous effusions (pleural tuberculosis, pericardial tuberculosis, and peritoneal tuberculosis). Conclusion:Nanopore sequencing was efficient for the rapid diagnosis of tuberculous serous effusions and had a very positive effect. For paucibacillary tuberculous serous effusions, nanopore sequencing might become an effective method for detecting pathogenic bacteria.

Postoperative nausea and vomiting (PONV) is a common complication following surgery. Despite various preventive measures, satisfactory outcomes have not been achieved. This study explores the potential of gut microbiota interactions with the host in understanding and preventing PONV, using 16S absolute quantitative sequencing technology to uncover new insights. Patients who experienced nausea and vomiting within 24 h after surgery were divided into a PONV group (n = 22) and a non-PONV group (n = 22). Microbial communities linked to PONV were assessed through bioinformatics analysis. Fecal samples from both groups were transplanted into rats, which were then anesthetized with isoflurane for 100 min. Pica behavior was monitored over the next 24 h to assess nausea and vomiting in the rats. Significant differences in α- and β-diversity were observed between the PONV and non-PONV groups. Six key microorganisms were identified, with Bifidobacterium, Bilophila, and Oscillibacter showing a negative correlation with PONV severity. Receiver operating characteristic (ROC) analysis demonstrated that Bifidobacterium could reliably predict PONV. Rats receiving feces from the PONV group exhibited significantly higher kaolin consumption within 24 h post-anesthesia compared to those receiving feces from the non-PONV group. These results suggest a potential new mechanism for PONV involving gut microbiota, offering a theoretical basis for preoperative prediction of PONV based on gut microbial composition.

Rapid identification of Clostridioides difficile sequence type 37 (ST37), also known as RT017, is crucial due to its association with severe infections and antibiotic resistance. Existing methodologies are labor-intensive and costly. The modeling approach combining matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) with machine learning offers a promising alternative for fast and cost-effective subtyping. This work gathered 1,155 mass spectra representing 385 distinct clinical C. difficile isolates from multiple regions, including 118 ST37 isolates (30.65%) and 267 non-ST37 isolates (69.35%). An artificial neural network (ANN) model was created using MALDI-TOF MS data, trained on 80% of the data set and validated on the remaining 20%. The constructed ANN model demonstrated exceptional diagnostic precision and reliable generalizability, achieving an area under the receiver operating characteristic curve of 0.96 and an area under the precision-recall curve of 0.94 for detecting C. difficile ST37 in the validation set. Furthermore, we identified the top 15 potential biomarkers of C. difficile ST37 strains with mass-to-charge ratios of 6,729, 12,013, 12,012, 6,731, 7,296, 12,085, 14,716, 7,292, 3,104, 7,293, 16,966, 15,360, 7,259, 18,488, and 14,660 Da. Our model provides a rapid, reliable, and economical option for identifying C. difficile ST37. Once species-level identification is completed using MALDI-TOF MS, our ANN model enables rapid subtype classification of ST37 within approximately 10 seconds, significantly reducing overall turnaround time. This facilitates accurate clinical diagnosis, mitigating the risk of severe C. difficile infections. IMPORTANCE:C. difficile ST37 (RT017) is a highly virulent strain that often causes severe infections and is frequently resistant to antibiotics such as fluoroquinolones and clindamycin, which are known to promote C. difficile infection. Rapid identification of this strain is essential to ensure timely clinical intervention and effective infection control. Current detection methods rely on lengthy and labor-intensive procedures, delaying treatment decisions. This study introduces a new, rapid identification method combining mass spectrometry with machine learning. The developed artificial neural network can accurately distinguish the ST37 strain in approximately 10 seconds, significantly reducing diagnostic time compared to traditional methods. Implementing this fast, reliable, and economical diagnostic tool in clinical laboratories will enhance patient care by facilitating quicker diagnosis and targeted therapy, thus minimizing the risk of severe complications associated with C. difficile infections.

Background:Human papillomavirus (HPV) vaccination is expected to reduce the burden of cervical cancer and other HPV-related diseases. However, if competition exists among HPV types, type replacement may occur following the reduction of vaccine-targeted types. Here, we conducted the study to explore natural HPV type competition in unvaccinated women. Methods:HPV DNA test results from cervical samples collected between January 2013 and July 2023 at Xiamen University's Women and Children's Hospital were analyzed. In cross-sectional study, first-visit HPV genotyping results were used, and logistic regression model was constructed to evaluate interactions between vaccine-targeted and other HPV types. In cohort of women with multiple visits, the risk of acquiring other HPV types was compared between women infected with vaccine-targeted types and those HPV-negative using Cox proportional hazards model. Results:Among 159,049 women, 19.8% tested HPV-positive, with 5.1% having multiple types. Significant negative associations were observed between HPV-6 and HPV-72 (OR: < 0.01; 95%CI: < 0.01-0.03), HPV-18 and HPV-72 (OR: < 0.01; 95%CI: < 0.01-0.02), HPV-31 and HPV-83 (OR: < 0.01; 95%CI: < 0.01-0.55), HPV-33 and HPV-26 (OR: < 0.01; 95%CI: < 0.01-0.81), HPV-45 and HPV-55 (OR: < 0.01; 95%CI: < 0.01- < 0.01), HPV-56 and HPV-26 (OR: < 0.01; 95%CI: < 0.01-0.09), as well as HPV-59 and HPV-69 (OR: < 0.01; 95%CI: < 0.01-0.68), suggesting potential type competition. However, no type competition pair was found in the cohort study. Conversely, women with vaccine-targeted types had a higher risk of acquiring other types (HR > 1.0). Conclusions:Our findings suggested that HPV-6 and HPV-72, HPV-18 and HPV-72, HPV-31 and HPV-83, HPV-33 and HPV-26, HPV-45 and HPV-55, HPV-56 and HPV-26, HPV-59 and HPV-69 were potential type competition pairs.

Since 2021, the novel H10N3 has caused four cases of human infection in China, the most recent of which occurred in December 2024, posing a potential threat to public health. Our previous studies indicated that several avian H10N3 strains are highly pathogenic in mice and can be transmitted between mammals via respiratory droplets without prior adaptation. By analyzing the genome sequence, we found that these H10N3 viruses carry the PB2-E627V mutation, which is becoming increasingly common in several subtypes of avian influenza viruses (AIV); however, its mechanism in mammalian adaptation remains unclear. Using a reverse genetics system, we investigated the role of PB2-E627V in the adaptation of H10N3 to mammals and poultry. Our findings demonstrate that the PB2-E627V mutation is critical for the high pathogenicity of novel H10N3 in mice and its ability to be transmitted through the air among mammals. Additionally, we found that the role of PB2-627 V in promoting AIV adaptation to mammals is comparable to that of PB2-627 K. More importantly, PB2-627 V appears to be equally suited to long-term persistence in poultry. Therefore, using PB2-627 V as a novel molecular marker to assess the epidemic potential of AIV is of great significance for preventing possible influenza pandemics in the future.

Background & Aims: In this study, we aimed to evaluate the incidence, predictors, and prognostic significance of recompensation in autoimmune hepatitis (AIH)-related decompensated cirrhosis following immunosuppressive therapy (IST). Methods: We retrospectively analyzed patients with AIH at first decompensation. Recompensation, defined using modified Baveno VII criteria, required clinical resolution (≥12 months without ascites, variceal bleeding, or hepatic encephalopathy, with liver function restored to Child-Pugh A) along with aetiological suppression (complete biochemical response under IST). Predictors of recompensation were identified using multivariate regression, and survival outcomes were compared among compensated, recompensated, and non-recompensated groups. Results: A total of 258 patients with AIH-related decompensated cirrhosis were included (median follow-up: 47 months, IQR 28-75). Clinical resolution was achieved by 124 patients (48.1%), while 68 patients (30.9% of 220 treated with IST) met criteria for recompensation. Predictors of recompensation included ascites as the only complication (hazard ratio [HR] 14.40, 95% CI 4.17-49.64, p <0.001), lower IgG levels (HR 0.90, 95% CI 0.89-0.96, p <0.001), higher bilirubin levels (HR 1.04, 95% CI 1.00-1.08, p = 0.030), and higher platelet counts (HR 1.01, 95% CI 1.00-1.01, p = 0.039). Patients achieving recompensation experienced a significantly reduced risk of liver transplantation or death (HR 0.07, 95% CI 0.01-0.50, p = 0.009), with survival outcomes comparable to those of compensated patients. Conclusions: Recompensation was achieved in approximately one-third of patients with AIH-related decompensated cirrhosis undergoing IST, leading to markedly improved transplant-free survival. Predictors of recompensation included having ascites as the sole complication, lower IgG levels, higher bilirubin levels, and higher platelet counts. Impact and implications: The predictors and long-term prognostic implications of recompensation in patients with autoimmune hepatitis (AIH)-related decompensated cirrhosis remain unclear. This study demonstrates that recompensation is achievable in patients with AIH-related decompensated cirrhosis and is associated with significant long-term benefits, including improved survival and reduced transplantation needs. We identified ascites (as the sole decompensating event), lower IgG levels, higher bilirubin levels and higher platelet counts as independent predictors of recompensation. These findings can be used by clinicians to identify the patients most likely to benefit from immunosuppressive therapy.