Biomedical subjects

Rui Huang

Publications and source records attributed to Rui Huang.

4 recordsLinked to original sources

PubMed2026

Insights into the fate and dynamics of antibiotic resistance in multidrug-resistant Bacillus cereus during in vitro simulated gastrointestinal digestion.

Bacillus cereus, an important pathogen responsible for causing foodborne diseases worldwide, releases pore-forming enterotoxins, which target host epithelial cells, leading to osmotic lysis and ultimately manifesting as diarrheal syndrome. Moreover, some B. cereus strains carry antimicrobial resistance genes that confer multidrug resistance against a spectrum of antibiotics. Characterizing the survival traits of multidrug-resistant (MDR) B. cereus strains in the intestinal microenvironment is essential for developing targeted strategies to effectively manage diarrheal foodborne diseases caused by this pathogen. This study used whole-genome sequencing (WGS) to evaluate the pre- and post-digestion toxigenic potential, antimicrobial resistance profiles, and genetic diversity of MDR B. cereus strains isolated from food samples in Guangdong Province, China. The four B. cereus isolates investigated in this study exhibited a genetic diversity, as determined by multilocus sequence typing analysis of WGS data. All four isolates produced the diarrheal toxins Hbl, Nhe, and CytK to varying levels, indicative of their potential to cause outbreaks of foodborne diseases. Each of the four isolates exhibited resistance to more than three classes of antibiotics, fulfilling the criterion for multidrug resistance. At an initial concentration of 9 log colony-forming units (CFU)/mL, the intestinal concentration of these four isolates crossed the threshold required to induce widespread diarrhea in the general population. Under rice slurry protection, all tested isolates maintained intestinal concentration beyond the threshold when the initial concentration was increased to ≥8 log CFU/mL. Moreover, the upregulations of genes associated with acid tolerance, bile tolerance and stress response were observed in the surviving MDR B. cereus isolates. Digestion markedly altered the antibiotic resistance profiles of the MDR B. cereus isolates. In the absence of a food matrix, the MDR isolates lost their resistance to imipenem, meropenem, amoxicillin-clavulanic acid, and trimethoprim-sulfamethoxazole post-digestion and was influenced by the initial concentration of the strains. In the presence of food matrix rice slurry, the effects of digestion on the antibiotic resistance of MDR B. cereus isolates can be mitigated, enabling them to maintain their antibiotic resistance to the greatest extent. Most remarkably, after digestion, the isolates Bce055 and Bce166 exhibited newly emergent resistance to cefotetan and trimethoprim-sulfamethoxazole, respectively. Our findings clarify the fate of MDR B. cereus isolates in the gastrointestinal tract and inform the development of prevention and control strategies for foodborne diseases caused by this pathogen.

Drug Resistance, Multiple, Bacterial↗

PubMed2026

Risk factors for lung metastasis in children and adolescent patients with papillary thyroid cancer: A retrospective cohort study.

BACKGROUND: Pediatric papillary thyroid cancer (pPTC) exhibits a higher incidence of lung metastasis (LM) compared to its adult counterpart. This study supplements the gap in pediatric management guidelines by exploring factors associated with LM in pPTC and characterizing relevant genetic alterations. METHODS: We retrospectively analyzed pPTC patients under 20 years who underwent initial surgery at our center between December 2008 and December 2022. Clinicopathological features, treatment approaches, outcomes, and target-gene sequencing were reviewed to identify risk factors and genetic variations. RESULTS: Among 114 pPTC cases, 17 developed LM. Risk factors associated with LM included younger age, male gender, larger tumor size, multifocality, extrathyroidal extension, lymphatic invasion, and the number of metastatic lymph nodes (NMLNs), with NMLNs > 14 identified as an independent predictor (OR = 18.20, p = 0.037). Treatment responses with radioiodine related to postoperative stimulated thyroglobulin (sTg) levels (p = 0.003). Genomic analysis identified 1007 somatic mutations, including in the BRAF, APC, RET, and ATM genes, with RET-NCOA4 fusions observed in the LM subgroup. CONCLUSION: LM is common in pPTC, and NMLNs > 14 is a critical risk indicator. The genetic profile, particularly RET mutations, highlights potential therapeutic targets. Further large-scale studies are needed to validate these findings.

Humans↗

PubMed2025

Causal relationship between white matter structural connectivity and epilepsy.

White matter structural connectivity has recently been linked to epilepsy pathogenesis, yet its causal role remains unclear. This study used Mendelian randomization (MR) to investigate the causal relationship between white matter structural connectivity and epilepsy. GWAS summary statistics for white matter structural connectivity were sourced from the UK Biobank, while epilepsy data were obtained from FinnGen R10 and the International League Against Epilepsy (ILAE). Our MR analysis revealed significant causal links between white matter structural connectivity and epilepsy risk. Increased connectivity between the right hemisphere visual and salience/ventral attention networks (RH Vis to RH Sal/VentAttn WMSC) was associated with higher epilepsy risk in FinnGen_R10_FE_STRICT (OR = 2.25, 95 % CI = 1.43-3.56, p < 0.01, FDR P = 0.019). Conversely, increased connectivity between left and right hemisphere salience/ventral attention networks (LH Sal/VentAttn to RH Sal/VentAttn WMSC) was linked to reduced epilepsy risk in FinnGen_R10_GE_STRICT (OR = 0.17, 95 % CI = 0.07-0.46, p < 0.01, FDR P = 0.033). A total of 15 nominally significant associations were identified across datasets. These findings suggest a causal relationship between white matter structural connectivity and epilepsy, offering insights into disease mechanisms and potential therapeutic targets.

Humans↗

PubMed2025

Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.

BACKGROUND & AIMS: Metabolic dysfunction- and alcohol-associated liver disease (MetALD) is a poorly understood condition that bridges cardiometabolic and alcohol-related pathological characteristics. We aimed to differentiate patients with MetALD whose molecular signatures more closely resemble either alcohol-related liver disease (ALD) or metabolic dysfunction-associated steatotic liver disease (MASLD), and to assess their relative risks of complications and mortality. METHODS: We analysed data from 443,453 European participants in the UK Biobank, including 34,147 with MetALD, 11,220 with ALD, and 124,034 with MASLD. Elastic net regression was used to classify ALD and MASLD based on 249 plasma metabolites and/or 2,941 plasma proteins, with multiple sensitivity analyses. We then applied the resulting concise model to patients with MetALD to identify an alcohol-predominant group (classified as ALD) and a cardiometabolic-predominant group (classified as MASLD). Finally, we evaluated their 15-year risk of major outcomes (heart failure, myocardial infarction, stroke, cirrhosis, hepatocellular carcinoma, and mortality) using Cox regression. RESULTS: The metabolome alone discriminated ALD from MASLD with an AUC of 0.86, while the proteome alone achieved an AUC of 0.96. Adding age, sex, BMI, liver enzymes, or metabolome information did not enhance the AUC of the proteome model. A 10-protein model differentiated ALD from MASLD with an AUC of 0.93. This model identified that patients with alcohol-predominant MetALD had significantly higher risks of mortality, and cirrhosis, along with elevated fibrosis scores and higher fibrosis stages, compared to patients with cardiometabolic-predominant MetALD. CONCLUSIONS: This study highlights the value of proteomic subtyping in MetALD, enabling more personalized treatment strategies and improved prognostic assessment. IMPACT AND IMPLICATIONS: This study underscores the critical importance of distinguishing subtypes of metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic data, providing a foundation for personalized treatment strategies. The findings hold significant relevance for healthcare providers, researchers, and policymakers by highlighting the differing risks associated with alcohol-predominant vs. cardiometabolic-predominant MetALD. Clinicians can apply the classification model developed in this study to more accurately assess patients and guide targeted therapies and preventive measures based on individual profiles. However, limitations of the study, such as reliance on self-reported alcohol consumption and the specificity of diagnostic criteria, necessitate further validation in diverse cohorts.

Humans↗