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Abstract Mitogen-activated protein kinase inhibitors (MAPKi) were the first line drugs for advanced melanoma patients with BRAF mutation. Targeted therapies have significant therapeutic effects; however, drug resistance hinders their long-term efficacy. Therefore, the development of new therapeutic strategies against MAPKi resistance is critical. Our previous results showed that MAPKi promote feedback activation of STAT3 signaling in BRAF-mutated cancer cells. Studies have shown that alantolactone inhibited the activation of STAT3 in a variety of tumor cells. Our results confirmed that alantolactone suppressed cell proliferation and promoted apoptosis by inhibiting STAT3 feedback activation induced by MAPKi and downregulating the expression of downstream Oct4 and Sox2. The inhibitory effect of alantolactone combined with a MAPKi on melanoma cells was significantly stronger than that on normal cells. In vivo and in vitro experiments showed that combination treatment was effective against drug-resistant melanomas. Our research indicates a potential novel combination therapy (alantolactone and MAPKi) for patients with BRAF-mutated melanoma.

ObjectiveTo investigate the associations of Insulin-like growth factor-II (IGF2) gene, Insulin-like growth factor-II receptor (IGF2R) gene and Insulin-like growth factor-II binding protein 2 (IGF2BP2) gene polymorphisms with the susceptibility to gestational diabetes mellitus (GDM) in Chinese population.MethodsA total of 1703 pregnant women (835 GDM and 868 Non-GDM) were recruited in this case-control study. All participants underwent prenatal 75 g oral glucose tolerance test (OGTT) examinations during 24-28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. Genotyping of candidate SNPs (IGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs1374910, rs11705701, rs6777038, rs16860234, rs7651090) was performed on Sequenom MassARRAY platform. Logistic regression analysis was conducted to investigate the associations between candidate SNPs and risk of GDM. In addition, multifactor dimensionality reduction (MDR) method was applied to explore the effects of gene-gene interactions on GDM risk.ResultsThere were significant distribution differences between GDM group and non-GDM group in age, pre-pregnancy BMI, education level and family history of diabetes (P < 0.05). After adjusted for age, pre-pregnancy BMI, education level and family history of diabetes, there were no significant associations of the candidate SNPs polymorphisms and GDM risk (P > 0.05). Furthermore, there were no gene-gene interactions on the GDM risk among the candidate SNPs (P > 0.05). However, the fasting blood glucose (FBG) levels of rs6777038 CT carriers were significantly lower than TT carriers (4.69±0.69 vs. 5.03±1.57 mmol/L, P < 0.01), and the OGTT-2h levels of rs6777038 CC and CT genotype carriers were significantly lower than TT genotype carriers (8.10±1.91 and 8.08±1.87 vs. 8.99±2.90 mmol/L, P < 0.01).ConclusionsIGF2 rs680, IGF2R rs416572, IGF2BP2 rs4402960, rs1470579, rs11705701, rs6777038, rs16860234, rs7651090 polymorphisms were not significantly associated with GDM risk in Wuhan, China. Further lager multicenter researches are needed to confirm these results.

Abstract Background Gastrointestinal (GI)‐neuroendocrine neoplasms (NENs) are subclassified in neuroendocrine tumors (NETs), neuroendocrine carcinomas (NECs), and mixed neuroendocrine–non‐neuroendocrine neoplasms (MiNENs). The genetic characteristics of GI‐NEN has been a hot issue in recent years, but more studies are needed to provide further details. This study aims to provide additional data about genomic characteristics of GI‐NENs and the genetic differences between NETs and NECs. Patients and Methods Thirteen samples were selected for next‐generation sequencing (NGS) analysis with a 425‐gene panel. Microsatellite instability (MSI) and tumor mutational burden (TMB) were calculated as well as immunohistochemistry (IHC) was used to test for protein expression. Results Genetic alterations were very common in NECs, but rare in NETs. The average TMB of NETs and NECs was 2.3 and 6.9, respectively. The TMB of NECs was significantly higher compared to NETs. The TP53 mutation rate was significantly higher in NECs than in NETs (100% vs. 20%), other mutations involved MTOR (n = 2, 15.4%), DDR2 (n = 3, 23.1%), ERBB4 (n = 1, 7.7%), BRCA1 (n = 1, 7.7%), BRCA2 (n = 1, 7.7%), ATM (n = 1, 7.7%), and SMAD4 (n = 1, 7.7%). Deep loss of SMAD4 (1/3, 33.3%), SDHB (1/3, 33.3%), RB1 (1/3, 33.3%), and BRCA2 (1/3, 33.3%), high‐level amplification of CRKL (1/3, 33.3%), CCNE1(1/3, 33.3%), and MCL1(1/3, 33.3%) were found in NECs. The integrated analysis found these genetic alterations frequently involve DNA repair and cell cycle, PI3K/AKT/mTOR and TGF‐β/SMAD4 signaling pathways. Conclusion Genetic alterations were very common in NECs and rare in NETs, and frequently involved three main signaling pathways. NEC patients harboring these genetic alterations may benefit from targeted therapy and PD‐1/PD‐L1 immunotherapy.

Background: Procyanidins have antioxidative properties that may protect against age-related brain oxidative stress. Previous studies indicated that procyanidin-rich foods could improve cognitive function and prevent neurodegenerative diseases. This study hypothesized that grape seed procyanidins extract (GSPE) would have a favorable effect on cognitive function in elderly people with mild cognitive impairment (MCI). Methods: A community-based, randomized, double-blind, placebo-controlled trial was conducted. Participants aged 60 years or older with MCI were randomly assigned into the GSPE group (n = 35, 320 mg/d) or placebo group (n = 36), and received capsules for 6 months. Cognitive function was assessed using the Montreal Cognitive Assessment Scale (MoCA). The change in MoCA scores between groups were tested by the time ✕ treatment interaction in mixed-design ANOVA. Results: After 6 months of intervention, the MoCA score was higher than the baseline both in the intervention group and placebo control group, while the there was no significant difference for mean change in MoCA score from baseline between the intervention group and the placebo group (2.35 ± 3.20 vs. 1.28 ± 2.93, P = 0.192). Conclusions: Present study showed that 6-month supplementation with GSPE did not significantly improve cognitive function in subjects with MCI. Further investigations regarding the longer-term intervention effect of procyanidins extract on mild or moderate cognitive disorders are needed.

Introduction To identify the association of the cyclin-dependent kinase 5 regulatory subunit associated protein 1-like 1 (CDKAL1) gene polymorphism with gestational diabetes mellitus (GDM) in the Chinese population.Research design and methods This case-control study enrolled 835 pregnant women with GDM and 870 pregnant women without diabetes who underwent antenatal examination during 24 to 28 gestational weeks at the Maternal and Child Health Hospital of Hubei Province from January 15, 2018 to March 31, 2019. Trained nurses collected their clinical information and blood samples. CDKAL1 gene rs10440833, rs10946398, rs4712523, rs4712524, rs7754840, rs7756992 and rs9465871 loci were genotyped by Agena MassARRAY system. SPSS V.26.0 software and online SHesis were used to analyze the relationship between CDKAL1 gene polymorphism and GDM susceptibility.Results After being adjusted for maternal age, prepregnancy body mass index (BMI), parity and family history of type 2 diabetes mellitus (T2DM), CDKAL1 gene rs10440833 (AA vs TT, OR=1.631, 95% CI 1.192 to 2.232), rs10946398 (CC vs AA, OR=1.400, 95% CI 1.028 to 1.905), rs4712523 (GG vs AA, OR=1.409, 95% CI 1.038 to 1.913), rs4712524 (GG vs AA, OR=1.418, 95% CI 1.043 to 1.929) and rs7754840 (CC vs GG, OR=1.407, 95% CI 1.036 to 1.911) polymorphisms were all associated with the increased risk of GDM. In addition, there was a powerful linkage disequilibrium (LD) among rs10946398, rs4712523, rs4712524 and rs7754840 (D′>0.900, r2>0.900). And there were significant differences in haplotype CGGC (OR=1.207, 95% CI 1.050 to 1.387) and AAAG (OR=0.829, 95% CI 0.721 o 0.952, p=0.008) between the GDM group and the control group.Conclusions rs10440833, rs10946398, rs4712523, rs4712524 and rs7754840 of CDKAL1 gene are associated with GDM susceptibility in central Chinese population.

Background: Type 2 diabetes mellitus (T2DM) is a crucial risk factor for cognitive impairment. Accurate assessment of patients’ cognitive function and early intervention is helpful to improve patient’s quality of life. At present, neuropsychiatric screening tests is often used to perform this task in clinical practice. However, it may have poor repeatability. Moreover, several studies revealed that machine learning (ML) models can effectively assess cognitive impairment in Alzheimer’s disease (AD) patients. We investigated whether we could develop an MRI-based ML model to evaluate the cognitive state of patients with T2DM.Objective: To propose MRI-based ML models and assess their performance to predict cognitive dysfunction in patients with type 2 diabetes mellitus (T2DM).Methods: Fluid Attenuated Inversion Recovery (FLAIR) of magnetic resonance images (MRI) were derived from 122 patients with T2DM. Cognitive function was assessed using the Chinese version of the Montréal Cognitive Assessment Scale-B (MoCA-B). Patients with T2DM were separated into the Dementia (DM) group (n = 40), MCI group (n = 52), and normal cognitive state (N) group (n = 30), according to the MoCA scores. Radiomics features were extracted from MR images with the Radcloud platform. The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were used for the feature selection. Based on the selected features, the ML models were constructed with three classifiers, k-NearestNeighbor (KNN), Support Vector Machine (SVM), and Logistic Regression (LR), and the validation method was used to improve the effectiveness of the model. The area under the receiver operating characteristic curve (ROC) determined the appearance of the classification. The optimal classifier was determined by the principle of maximizing the Youden index.Results: 1,409 features were extracted and reduced to 13 features as the optimal discriminators to build the radiomics model. In the validation set, ROC curves revealed that the LR classifier had the best predictive performance, with an area under the curve (AUC) of 0.831 in DM, 0.883 in MIC, and 0.904 in the N group, compared with the SVM and KNN classifiers.Conclusion: MRI-based ML models have the potential to predict cognitive dysfunction in patients with T2DM. Compared with the SVM and KNN, the LR algorithm showed the best performance.

ObjectiveTo investigate the correlation between transcription factor 7-like 2 (TCF7L2) gene polymorphisms and gestational diabetes mellitus (GDM) risk in the central Chinese population.MethodsThis case–control study examined the association of seven TCF7L2 gene single-nucleotide polymorphisms (SNPs) (rs11196218, rs4506565, rs7895340, rs7901695, rs11196205, rs12243326, and rs290487) with GDM risk in the central Chinese population (843 GDM and 877 controls). The clinical information and blood samples were collected by trained interviewers and nurses. Genotyping of SNPs was conducted on the Sequenom MassARRAY platform. Statistical analyses including t-test, ANOVA, chi-square test, Fisher’s exact test, and logistic regression were performed.ResultsDifferences in age, pre-pregnant body mass index (BMI), and family history of type 2 diabetes mellitus (T2DM) between the case and control groups were significant (p < 0.05). Compared with the wild-type genotype, pregnant women with genotypes of rs4506565-AT (OR = 1.89, 95%CI: 1.18–3.02), rs7895340 GA (OR = 1.93, 95%CI: 1.06–3.54), rs7901695-TC (OR = 1.79, 95%CI: 1.11–2.88), and rs11196205-GC (OR = 2.15, 95%CI: 1.16–3.98) had a significantly higher risk of GDM, adjusted by age, pre-pregnant BMI, and family history of T2DM. Functional annotation showed that all these four SNPs fell in the functional elements of human pancreatic islets. Further cumulative effects analysis concluded that when participants carried all these four risk genotypes, the risk of GDM was 3.51 times (OR = 3.51, 95%CI: 1.38–8.90) than that of those without any risk genotypes.ConclusionsThe findings of this study suggested that rs4506565, rs7895340, rs7901695, and rs11196205 were the genetic susceptibility SNPs of GDM in the central Chinese population. Further studies are needed to validate our findings and clarify the underlying mechanisms.

Abstract Background Gestational diabetes mellitus (GDM) increased risk of perinatal complications for both the women and the fetuses. The association between the vitamin D receptor (VDR) gene polymorphism and GDM has not been thoroughly investigated in Chinese pregnant women. Therefore, we aimed to determine whether VDR gene single nucleotide polymorphisms (SNPs) rs154410, rs7975232, rs731236, rs2228570 and rs739837 contribute to GDM risk in Wuhan, China. Moreover, we aimed to explore their combined effects on the risk of GDM. Methods Pregnant women who had prenatal examinations at 24 to 28 weeks’ gestation in our hospital from January 15, 2018 to March 31, 2019 were included in this case-control study. After exclusion, a total of 1684 pregnant women (826 GDM patients and 858 non-diabetic controls) were recruited. The clinical information and blood samples were collected by trained interviewers and nurses. Genotyping of candidate SNPs was conducted on the Sequenom MassARRAY platform. Statistical analyses including t-test, ANOVA, chi-square test and logistic regression were performed to the data with SPSS Software to evaluate differences in genotype distribution and associations with GDM risk. Multifactor dimensionality reduction method was used to explore the gene-gene interactions on the risk of GDM. Results Differences in age, pre-pregnancy BMI, family history of diabetes and previous history of GDM between the case and control groups were statistically significant (P 0.05). There were no significant differences at genotype distributions of the examined VDR gene SNPs (P > 0.05). After adjusting by age, pre-pregnancy BMI, family history of diabetes, the results of logistic regression analysis showed no associations of the five SNPs with GDM in all the four genotype models(P > 0.05). Furthermore, there were no gene-gene interactions on the GDM risk among the five examined VDR gene SNPs. Conclusions The VDR gene SNPs rs154410, rs7975232, rs731236, rs2228570 and rs739837 showed neither significant associations nor gene-gene interactions with GDM in Wuhan, China.

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor developing from the esophageal squamous epithelium, and is the most common histological subtype of esophageal cancer (EC). EC ranks 10th in morbidity and sixth in mortality worldwide. The morbidity and mortality rates in China are both higher than the world average. Current treatments of ESCC are surgical treatment, radiotherapy, and chemotherapy. Neoadjuvant chemoradiotherapy plus surgical resection is recommended for advanced patients. However, it does not work in the significant promotion of overall survival (OS) after such therapy. Research on targeted therapy in ESCC mainly focus on EGFR and PD-1, but neither of the targeted drugs can significantly improve the 3-year and 5-year survival rates of disease. Phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway is an important survival pathway in tumor cells, associated with its aggressive growth and malignant progression. Specifically, proliferation, apoptosis, autophagy, and so on. Related genetic alterations of this pathway have been investigated in ESCC, such as PI3K, AKT and mTOR-rpS6K. Therefore, the PI3K/AKT/mTOR pathway seems to have the capability to serve as research hotspot in the future. Currently, various inhibitors are being tested in cells, animals, and clinical trials, which targeting at different parts of this pathway. In this work, we reviewed the research progress on the PI3K/AKT/mTOR pathway how to influence biological behaviors in ESCC, and discussed the interaction between signals downstream of this pathway, especially eukaryotic translation initiation factors (eIFs) and the development and progression of ESCC, to provide reference for the identification of new therapeutic targets in ESCC.

The scale of log data produced by the large scale information system is growing rapidly.It leads to the big challenge of line-speed compressing and saving the large scale log data.By analysis on massive network log data,it is found that the log data has redundant pattern in terms of log structure and time local similarity in terms of log content.A differential log compression architecture based on template is proposed.Fine-grained differential compressive strategies in the architecture can be configured for a special log data.Experimental results show that,compared with gizp,the proposed log compressing architecture improves 2～10 times’ compressive speed and gain a better compressing ratio approaching to 10%.

The source region of the Yangtze River (SRYR) on the central Tibetan Plateau has seen one of the most significant increases in temperature in the world. Climate warming has altered the temporal and spatial characteristics of precipitation in the SRYR. In this study, we analyzed the temporal trends and spatial distributions of extreme precipitation in the SRYR during 1960⁻2016 using 11 extreme precipitation indices (EPIs) derived from daily precipitation data collected at five meteorological stations in the region. The trends in the EPIs were estimated using the linear least squares method, and their statistical significance was assessed using the Mann⁻Kendall test. The results show the following. Temporally, the majority of SRYR EPIs (including the simple daily intensity index, annual maximum 1-day precipitation (RX1day), annual maximum 5-day precipitation (RX5day), very wet day precipitation, extremely wet day precipitation, number of heavy precipitation days, number of very heavy precipitation days, and number of consecutive wet days) exhibited statistically nonsignificant increasing trends during the study period, while annual total wet-day precipitation (PRCPTOT) and the number of wet days exhibited statistically significant increasing trends. In addition, the number of consecutive dry days (CDD) exhibited a statistically significant decreasing trend. For the seasonal EPIs, the PRCPTOT, RX1day, and RX5day all exhibited nonsignificant increasing trends during the wet season, and significant increasing trends during the dry season. Spatially, changes in the annual and wet season EPIs in the study area both exhibited significant differences in their spatial distribution. By contrast, changes in dry season PRCPTOT, RX1day, and RX5day exhibited notable spatial consistency. These three indices exhibited increasing trends at each station. Moreover, there was a statistically significant positive correlation between the annual PRCPTOT and each of the other EPIs (except CDD). However, the contribution of extreme precipitation to annual PRCPTOT exhibited a nonsignificant decreasing trend.