Spexin mRNA and protein are widely expressed in rat tissues and associate with weight loss in rodents of diet-induced obesity. Its location in endocrine and epithelial cells has also been suggested. Spexin is a novel peptide that involves weight loss in rodents of diet-induced obesity. Therefore, we aimed to examine its expression in human tissues and test whether spexin could have a role in glucose and lipid metabolism in type 2 diabetes mellitus (T2DM). The expression of the spexin gene and immunoreactivity in the adrenal gland, skin, stomach, small intestine, liver, thyroid, pancreatic islets, visceral fat, lung, colon, and kidney was higher than that in the muscle and connective tissue. Immunoreactive serum spexin levels were reduced in T2DM patients and correlated with fasting blood glucose (FBG, r=-0.686, P<0.001), hemoglobin A1c (HbA1c, r=-0.632, P<0.001), triglyceride (TG, r=-0.236, P<0.001) and low density lipoprotein-cholesterol (LDL-C, r=-0.382, P<0.001). A negative correlation of blood glucose with spexin was observed during oral glucose tolerance test (OGTT). Spexin is intensely expressed in normal human endocrine and epithelial tissues, indicating that spexin may be involved in physiological functions of endocrine and in several other tissues. Circulating spexin levels are low in T2DM patients and negatively related to blood glucose and lipids suggesting that the peptide may play a role in glucose and lipid metabolism in T2DM.

Tumor-associated macrophages (TAMs) play an important role in the progression and prognostication of numerous cancers. However, the role and clinical significance of TAM markers in oral squamous cell carcinoma (OSCC) has not been elucidated. The present study was designed to investigate the correlation between the expression of TAM markers and pathological features in OSCC by tissue microarray. Tissue microarrays containing 16 normal oral mucosa, 6 oral epithelial dysplasia, and 43 OSCC specimens were studied by immunohistochemistry. We observed that the protein expression of the TAM markers CD68 and CD163 as well as the cancer stem cell (CSC) markers ALDH1, CD44, and SOX2 increased successively from the normal oral mucosa to OSCC. The expressions of CD68 and CD163 were significantly associated with lymph node status, and SOX2 was significantly correlated with pathological grade and lymph node status, whereas ALDH1 was correlated with tumor stage. Furthermore, CD68 was significantly correlated with CD163, SOX2, and ALDH1 (P < 0.05). Kaplan-Meier analysis revealed that OSCC patients overexpressing CD163 had significantly worse overall survival (P < 0.05). TAM markers are associated with cancer stem cell marker and OSCC overall survival, suggesting their potential prognostic value in OSCC.

With the development of functional genomics studies, a mass of long non‐coding RNAs (LncRNA) were discovered from the human genome. Long non‐coding RNAs serve as pivotal regulators of genes that are able to generate LncRNA–binding protein complexes to modulate a great number of genes. Recently, the LncRNA urothelial carcinoma‐associated 1 (UCA1) has been revealed to be dysregulated, which plays a critical role in the development of a few cancers. However, the role of the biology and clinical significance of UCA1 in the tumorigenesis of oral squamous cell carcinoma (OSCC) remain unknown. We found that UCA1 expression levels were upregulated aberrantly in tongue squamous cell carcinoma tissues and associated with lymph node metastasis and TNM stage. We explored the expression, function, and molecular mechanism of LncRNA UCA1 in OSCC. In the present work, we revealed that UCA1 silencing suppressed proliferation and metastasis and induced apoptosis of OSCC cell lines in vitro and in vivo, which might be related to the activation level of the WNT/β‐catenin signaling pathway. Our research results emphasize the pivotal role of UCA1 in the oncogenesis of OSCC and reveal a novel LncRNA UCA1–β‐catenin–WNT signaling pathway regulatory network that could contribute to our understanding in the pathogenesis of OSCC and assist in the discovery of a viable LncRNA‐directed diagnostic and therapeutic strategy for this fatal disease.

After the 2019 novel coronavirus (2019-nCoV) outbreak, we estimated the distribution and scale of more than 5 million migrants residing in Wuhan after they returned to their hometown communities in Hubei Province or other provinces at the end of 2019 by using the data from the 2013-2018 China Migrants Dynamic Survey (CMDS). We found that the distribution of Wuhan's migrants is centred in Hubei Province (approximately 75%) at a provincial level, gradually decreasing in the surrounding provinces in layers, with obvious spatial characteristics of circle layers and echelons. The scale of Wuhan's migrants, whose origins in Hubei Province give rise to a gradient reduction from east to west within the province, and account for 66% of Wuhan's total migrants, are from the surrounding prefectural-level cities of Wuhan. The distribution comprises 94 districts and counties in Hubei Province, and the cumulative percentage of the top 30 districts and counties exceeds 80%. Wuhan's migrants have a large proportion of middle-aged and high-risk individuals. Their social characteristics include nuclear family migration (84%), migration with families of 3-4 members (71%), a rural household registration (85%), and working or doing business (84%) as the main reason for migration. Using a quasi-experimental analysis framework, we found that the size of Wuhan's migrants was highly correlated with the daily number of confirmed cases. Furthermore, we compared the epidemic situation in different regions and found that the number of confirmed cases in some provinces and cities in Hubei Province may be underestimated, while the epidemic situation in some regions has increased rapidly. The results are conducive to monitoring the epidemic prevention and control in various regions.

Background The overall prognosis of oral cancer remains poor because over half of patients are diagnosed at advanced-stages. Previously reported screening and earlier detection methods for oral cancer still largely rely on health workers’ clinical experience and as yet there is no established method. We aimed to develop a rapid, non-invasive, cost-effective, and easy-to-use deep learning approach for identifying oral cavity squamous cell carcinoma (OCSCC) patients using photographic images. Methods We developed an automated deep learning algorithm using cascaded convolutional neural networks to detect OCSCC from photographic images. We included all biopsy-proven OCSCC photographs and normal controls of 44,409 clinical images collected from 11 hospitals around China between April 12, 2006, and Nov 25, 2019. We trained the algorithm on a randomly selected part of this dataset (development dataset) and used the rest for testing (internal validation dataset). Additionally, we curated an external validation dataset comprising clinical photographs from six representative journals in the field of dentistry and oral surgery. We also compared the performance of the algorithm with that of seven oral cancer specialists on a clinical validation dataset. We used the pathological reports as gold standard for OCSCC identification. We evaluated the algorithm performance on the internal, external, and clinical validation datasets by calculating the area under the receiver operating characteristic curves (AUCs), accuracy, sensitivity, and specificity with two-sided 95% CIs. Findings 1469 intraoral photographic images were used to validate our approach. The deep learning algorithm achieved an AUC of 0·983 (95% CI 0·973–0·991), sensitivity of 94·9% (0·915–0·978), and specificity of 88·7% (0·845–0·926) on the internal validation dataset ( n = 401), and an AUC of 0·935 (0·910–0·957), sensitivity of 89·6% (0·847–0·942) and specificity of 80·6% (0·757–0·853) on the external validation dataset ( n = 402). For a secondary analysis on the internal validation dataset, the algorithm presented an AUC of 0·995 (0·988–0·999), sensitivity of 97·4% (0·932–1·000) and specificity of 93·5% (0·882–0·979) in detecting early-stage OCSCC. On the clinical validation dataset ( n = 666), our algorithm achieved comparable performance to that of the average oral cancer expert in terms of accuracy (92·3% [0·902–0·943] vs 92.4% [0·912–0·936]), sensitivity (91·0% [0·879–0·941] vs 91·7% [0·898–0·934]), and specificity (93·5% [0·909–0·960] vs 93·1% [0·914–0·948]). The algorithm also achieved significantly better performance than that of the average medical student (accuracy of 87·0% [0·855–0·885], sensitivity of 83·1% [0·807–0·854], and specificity of 90·7% [0·889–0·924]) and the average non-medical student (accuracy of 77·2% [0...

BackgroundTriglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) has been recommended as a surrogate marker for insulin resistance. In the present study, we aimed to investigate the relationship between TG/HDL-C and NAFLD in an apparently healthy population.MethodsA total of 18,061 subjects who participated in a health checkup program were included. NAFLD was diagnosed by ultrasonography.ResultsThe prevalence rate of NAFLD was 24.8% in the whole population, and progressively increased across the quartiles of TG/HDL-C (4.9, 14.1, 26.8 and 53.5%, respectively, P <  0.001). After adjustment for confounding factors, TG/HDL-C was independently associated with the risk of NAFLD. Compared with the first quartile of TG/HDL-C (Q1), the odds ratios (95% confidence intervals) for NAFLD in the increasing quartiles (Q2-Q4) were 2.1(1.8–2.6), 3.6 (3.0–4.3) and 9.2(7.6–11.1), respectively. In addition, the area under receiver operator characteristic curve (95% confidence interval) of TG/HDL-C for NAFLD was 0.85 (0.84–0.86) in women and 0.79 (0.78–0.80) in men, significantly higher than that of TG, TC, LDL-C, HDL-C, ALT and AST (P <  0.05). The optimal cutoff point of TG/HDL-C for detection of NAFLD was 0.9 in women (sensitivity = 78.8%, specificity = 77.3%) and 1.4 in men (sensitivity = 70.7%, specificity = 73.5%).ConclusionsTG/HDL-C is independently associated with NAFLD in apparently healthy individuals and may be used as a surrogate for NAFLD.

Obesity is associated with a state of chronic low-grade inflammation, which contributes to insulin resistance and type 2 diabetes. However, the molecular mechanisms that link obesity to inflammation are not fully understood. Follistatin-like 1 (FSTL1) is a novel proinflammatory cytokine that is expressed in adipose tissue and secreted by preadipocytes/adipocytes. We aimed to test whether FSTL1 could have a role in obesity-induced inflammation and insulin resistance. It was found that FSTL1 expression was markedly decreased during differentiation of 3T3-L1 preadipocytes but reinduced by TNF-α. Furthermore, a significant increase in FSTL1 levels was observed in adipose tissue of obese ob/ob mice, as well as in serum of overweight/obese subjects. Mechanistic studies revealed that FSTL1 induced inflammatory responses in both 3T3-L1 adipocytes and RAW264.7 macrophages. The expression of proinflammatory mediators including IL-6, TNF-α, and MCP-1 was upregulated by recombinant FSTL1 in a dose-dependent manner, paralleled with activation of the IKKβ-NFκB and JNK signaling pathways in the two cell lines. Moreover, FSTL1 impaired insulin signaling in 3T3-L1 adipocytes, as revealed by attenuated phosphorylation of both Akt and IRS-1 in response to insulin stimulation. Together, our results suggest that FSTL1 is a potential mediator of inflammation and insulin resistance in obesity.

Owing to the growing infectious diseases caused by eukaryotic and prokaryotic pathogens, it is urgent to develop novel antimicrobial agents against clinical pathogenic infections. Biofilm formation and invasion into the host cells are vital processes during pathogenic colonization and infection. In this study, we tested the inhibitory effect of Au nanoparticles (AuNPs) on pathogenic growth, biofilm formation and invasion. Interestingly, although the synthesized AuNPs had no significant toxicity to the tested pathogens, Candida albicans and Pseudomonas aeruginosa, the nanoparticles strongly inhibited pathogenic biofilm formation and invasion to dental pulp stem cells (DPSCs). Further investigations revealed that AuNPs abundantly bound to the pathogen cells, which likely contributed to their inhibitory effect on biofilm formation and invasion. Moreover, treatment of AuNPs led to activation of immune response-related genes in DPSCs, which may enhance the activity of host immune system against the pathogens. Zeta potential analysis and polyethylene glycol (PEG)/polyethyleneimine (PEI) coating tests further showed that the interaction between pathogen cells and AuNPs is associated with electrostatic attractions. Our findings shed novel light on the application of nanomaterials in fighting against clinical pathogens, and imply that the traditional growth inhibition test is not the only way to evaluate the drug effect during the screening of antimicrobial agents.