The biomechanical changes in the lower extremity caused by chronic ankle instability (CAI) are not restricted to the ankle joint, but also affect the proximal joints, increasing the risk of joint injury. This study aimed to systematically review the research on CAI and lower extremity angle and movements during side-cutting, stop jumping, and landing tasks, to provide a systematic and basic theoretical basis for preventing lower extremity injury. Literature published from exception to April 2022 were searched in the PubMed, Web of Science, and SPORTDiscus databases using the keywords of “chronic ankle instability,” “side-cut,” “stop jump,” and “landing.” Only studies that compared participants with chronic ankle instability with healthy participants and assessed lower extremity kinetics or kinematics during side-cutting, stop jumping, or landing were included. The risk of bias assessment was conducted using a modified version of the Newcastle-Ottawa checklist. After title, abstract, and full text screening, 32 studies were included and the average score of the quality evaluation was 7 points (range 6–8). Among them five studies were related to the side-cut task, three studies were the stop-jump task, and twenty-four studies were related to landing. Although the results of many studies are inconsistent, participants with CAI exhibit altered lower extremity proximal joint movement strategies during side cut, stop jump, and landings, however, such alterations may increase the risk of anterior cruciate ligament injury.

The association between thyroid nodules and adiposity remains controversial. We performed a cross-sectional, community-based study to examine whether thyroid nodules are associated with overweight and obesity, as defined with body mass index (BMI) and waist circumference. The study included 1482 subjects (≥20 years of age; residing in Nanjing, China) receiving questionnaire interview, anthropometric measurements, laboratory tests and thyroid ultrasonography in 2009–2010. Overweight and obesity were defined as BMI ≥24 and ≥28 kg/m2, respectively. Central obesity was defined as waist circumference at ≥90 cm in men and ≥80 cm in women. A sensitivity analysis was conducted using the American Diabetes Association (ADA) criteria for overweight and obesity (BMI ≥ 23 and ≥25 kg/m2). Thyroid nodules were identified in 12.6% of the subjects. A greater proportion of the subjects with thyroid nodules had a BMI at ≥24 kg/m2 (51.9% vs. 40.5% in those without thyroid nodules, P = 0.003) and central obesity (43.3% vs. 24.2%, P < 0.001). After adjustment for other confounders, central obesity was still associated with significantly elevated risk of thyroid nodules (OR 1.62, 95%CI 1.14–2.28), whereas obesity/overweight based on BMI was not in both the main analysis and sensitivity analysis with the alternative criteria. In the subgroup analysis, BMI ≥24 kg/m2 (OR 1.61, 95%CI 1.01–2.54), as well as BMI ≥25 kg/m2 (OR 1.95, 95%CI 1.14–3.34), was significantly associated with higher risk of thyroid nodules among women. Using the ADA criteria, overweight and obesity were associated with thyroid nodules (OR 5.59, 95%CI 1.39–22.51 and 5.15, 95%CI 1.30–20.37) in thyroid-stimulating hormone (TSH) > 4.2 mIU/L subgroup. Central obesity correlated with higher risk of thyroid nodules regardless of age (< 50 years: OR 1.87, 95%CI 1.05–3.32: ≥50 years: OR 1.54, 95%CI 1.00–2.37) and in the following subgroups: men (OR 1.91, 95%CI 1.14–3.20), TSH > 4.2 mIU/L (OR 3.05, 95%CI 1.01–9.22), and urine iodine ≥200 µg/L (OR 1.79, 95%CI 1.14–2.81). Waist circumference is superior to BMI for assessing risk of thyroid nodules in Chinese subjects.

Background: Evidence on the association between the non-high-density lipoprotein cholesterol (non-HDLc)-to-high-density lipoprotein cholesterol (HDLc) ratio (non-HDLc/HDLc) and carotid plaques is still limited. This study aims to assess the relationship between the non-HDLc/HDLc and carotid plaques in a population with a high risk of stroke. Methods: A cross-sectional study based on the community was conducted in Yangzhou, China. Residents (no younger than 40 years old) underwent questionnaire interviews, physical examinations, and laboratory testing during 2013–2014. The subjects with a high risk of stroke were further selected (at least three of eight risk factors including hypertension, atrial fibrillation, type 2 diabetes mellitus, dyslipidaemia, smoking, lack of exercise, overweight, and family history of stroke) or a transient ischaemic attack (TIA) or stroke history. Carotid ultrasonography was then performed on the high stroke risk participants. Carotid plaque was defined as a focal carotid intima-media thickness (cIMT) ≥1.5 cm or a discrete structure protruding into the arterial lumen at least 50% of the surrounding cIMT. Logistic regression was employed to evaluate the relationship between the non-HDLc/HDLc and carotid plaques. Results: Overall, 839 subjects with a high risk of stroke were ultimately included in the analysis, and carotid plaques were identified in 341 (40.6%) of them. Participants in the highest non-HDLc/HDLc tertile group presented a higher proportion of carotid plaques than did those in the other two groups. After adjustment for other confounders, each unit increase in the non-HDLc/HDLc was significantly associated with carotid plaques (OR 1.55, 95%CI 1.28–1.88). In the subgroup analysis, the non-HDLc/HDLc was positively and significantly associated with the presence of carotid plaques in most subgroups. Additionally, the non-HDLc/HDLc interacted significantly with three stratification variables, including sex (OR 1.31 for males vs. OR 2.37 for females, P interaction = 0.016), exercise (OR 1.18 for subjects without lack of exercise vs. OR 1.99 for subjects with lack of exercise, P interaction = 0.004) and heart diseases (OR 1.40 for subjects without heart diseases vs. OR 3.12 for subjects with heart diseases, P interaction = 0.033). Conclusion: The non-HDLc/HDLc was positively associated with the presence of carotid plaques in a Chinese high stroke risk population. A prospective study or randomized clinical trial of lipid-lowering therapy in the Chinese population is needed to evaluate their causal relationship.

Papillary thyroid cancer (PTC) is the most frequent type of thyroid malignancy. In this study, we investigated the mechanisms whereby long non-coding RNAs (lncRNAs) are associated with PTC pathogenesis. Microarray analysis was used to determine differentially expressed lncRNAs between paired PTC tissues and normal adjacent thyroid tissues. Quantitative RT-PCR was used for validation in 86 PTC cases. Small interfering RNA (siRNA) transfection assays were then performed to assess how a novel lncRNA affected key proliferation and cell death pathways in IHH4 PTC cells. We identified 1878 differentially expressed lncRNAs versus matched control samples (fold change ≥2.0, P < 0.05), of which 429 were upregulated and 1449 were downregulated. ENST00000539653.1 (ENS-653), one of the top hits in this microarray, was selected for further study. Higher ENS-653 expression was observed in PTC tissue samples versus adjacent normal tissues, and was associated with a larger tumor size and a more advanced clinical stage. In the Cancer Genome Atlas (TCGA) PTC cohort, higher ENS-653 expression was correlated with more frequent BRAF (V600E) mutation and poorer disease-free survival. Furthermore, ENS-653 downregulation reduced the proliferation of PTC cells and led to G1-S arrest, but had no impact on apoptosis. ENS-653 downregulation also inactivated ERK1/2 and ERK5, causing partial MAPK cascade suppression. ENS-653 exhibits oncogenic properties in PTC, and could be a diagnostic and/or prognostic PTC biomarker, in addition to possibly being a future target for therapy.

Low-grade gliomas (LGGs) are associated with neurological disability. The present study used microRNA (miRNA) expression profiles to identify risk miRNAs for potential prognosis of cerebral LGGs. miRNA expression profiles and clinical data from 408 patients with cerebral LGGs were obtained from the Cancer Genome Atlas database. Risk miRNAs were identified by plotting Kaplan‑Meier curves and Cox proportional hazard regression analysis with the survival and KMsurv packages in R. A regulatory network of miRNA‑targets was constructed, followed by gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery. A protein‑protein interaction (PPI) network of miRNA targets was built using Search Tool for the Retrieval of Interacting Genes software, and sub‑pathway identification was performed using the iSubpathwayMiner package in R. In total, 39 miRNAs had significant effect on survival curves. Following the Cox analysis and construction of miRNA‑targets regulatory network, hsa‑miRNA (miR)‑326 was identified to regulate 397 target genes. Additionally, targets of miR‑326 were primarily enriched in the GO terms of cell proliferation, epithelial growth factor receptor and nerve growth factor signaling pathways. Additionally, son of sevenless homolog 1 (SOS1), neuroblastoma RAS viral oncogene homolog (NRAS), vitamin D receptor (VDR) and mothers against decapentaplegic family member 3 (SMAD3) were most enriched in the PPI network. Targets of miR‑326 were primarily enriched in sub‑pathways including sphingolipid metabolism and arachidonic acid metabolism, in which sphingomyelin synthase 1 (SGMS1) and hematopoietic prostaglandin D synthase (HPGDS) were screened out. Hsa‑miR‑326 was identified as a risk miRNA for prognosis and may improve the outcome prediction of patients with cerebral LGG. This miRNA may regulate cancer cell proliferation by targeting SOS1, NRAS, VDR, SMAD3, SGMS1 and HPGDS.