Tian Liang

Dr. Tian Liang


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 November 2022 in Nutrients
Verified
Journal Article
Open access
PDF file
TLTian Liang
Tian Liang
DLDan Li
Dan Li
JZJiawulan Zunong
Jiawulan Zunong
MLMenglong Li
Menglong Li
NANubiya Amaerjiang
Nubiya Amaerjiang
Yifei HuYifei Hu
Yifei Hu
Abnormally high lymphocyte counts are seen in persons with nonalcoholic fatty liver disease (NAFLD). Gut microbiota dysbiosis is a risk factor for NAFLD. We assessed the gut microbiota of 63 healthy children and 63 children with NAFLD using 16S rRNA gene and metagenomic sequencing to explore the relationships. Compared with healthy children (HC group), the Bacteroidetes, Verrucomicrobia, and Akkermansia were less abundant, while the Actinobacteria were more abundant in children with NAFLD (FLD group). To understand the effect of lymphocytes on the gut microbiota of children with NAFLD, we compared the microbiota of 41 children with NAFLD and high numbers of lymphocytes (FLD_HL group) and 22 children with NAFLD and low numbers of lymphocytes (FLD_LL group). The abundances of Bacteroidetes, Verrucobacterium, and Akkermansia increased and Actinobacteria decreased in the FLD_LL group compared to the FLD_HL group. Akkermansia was negatively correlated with lymphocyte count. NAFLD may disturb the gut microbiota in children through reducing the abundance of Akkermansia and increasing the abundance of proinflammatory bacteria, such as Escherichia-Shigella. Conclusions: High lymphocyte counts are associated with disturbances of gut microbiota and emergence of opportunistic pathogens in children with NAFLD.

6 April 2026 in Metabolites
Verified
Journal Article
Open access
PDF file
TLTian Liang
Tian Liang
ZZZhengmao Zhuang
Zhengmao Zhuang
LWLizhi Wu
Lizhi Wu
XLXueqing Li
Xueqing Li
ZCZhijian Chen
Zhijian Chen
mingluan xingmingluan xing
mingluan xing
Background: Psychological distress has been increasingly recognized as an important determinant of sleep quality in children and adolescents. However, susceptible subgroups have not been clearly identified. This study aimed to examine the associations between psychological distress and sleep quality in children and adolescents. Methods: We conducted a cross-sectional study among 5771 school-aged children and adolescents (6–18 years) in Zhejiang Province. Psychological status was assessed using the Chinese version of the Depression Anxiety Stress Scale-21, and sleep quality was evaluated using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Thyroid-related biomarkers were measured via chemiluminescence immunoassay. Associations between psychological distress and sleep quality were analyzed using generalized linear models. In addition, stratified analyses were performed to identify potentially susceptible subgroups by age, sex, and BMI-for-age z score. Results: Each one-point increase in depression, anxiety, and stress scores was associated with an increase in PSQI scores of 0.18 (95% CI: 0.16, 0.19), 0.20 (95% CI: 0.18, 0.21), and 0.20 (95% CI: 0.19, 0.22), respectively. Subgroup analyses showed that the associations were more pronounced among older children (age > 12 years) and pediatric females. Exploratory mediation analyses suggested a possible but very limited indirect role of T3 in the associations of depression, anxiety, and stress with sleep quality, with all estimated proportions mediated below 1%. Conclusions: Psychological distress was significantly associated with poorer sleep quality in children and adolescents, particularly among older individuals and pediatric females. These findings highlight the importance of early identification and intervention for psychological distress to improve sleep health in younger populations. Further longitudinal studies are needed to clarify underlying mechanisms.