A seven-gene signature predicts overall survival of patients with colorectal cancer

Colorectal cancer (CRC) is a major cause of global cancer mortality. Gene expression profiles can help predict prognosis of patients with CRC. In most of previous studies, disease recurrence was analyzed as the survival endpoint. Thus we aim to build a robust gene signature for prediction of overall survival (OS) in patients with CRC. Fresh frozen CRC tissues from 64 patients were analyzed using Affymetrix HG-U133plus 2.0 gene arrays. By performing univariate survival analysis, 6487 genes were found to be associated with the OS in our cohort. KEGG analysis revealed that these genes were mainly involved in pathways such as endocytosis, axon guidance, spliceosome, Wnt signalling and ubiquitin mediated proteolysis. A seven-gene signature was further selected by a robust likelihood-based survival modelling approach. The prognostic model of seven-gene signature (NHLRC3, ZDHHC21, PRR14L, CCBL1, PTPRB, PNPO, and PPIP5K2) was constructed and weighted by regression coefficient, which divided patients into high- and low-risk groups. The OS for patients in high-risk group was significantly poorer compared with patients in low-risk group. Moreover, all seven genes were found to be differentially expressed in CRC tissues as compared with adjacent normal tissues, indicating their potential role in CRC initiation and progression. This seven-gene signature was further validated as an independent prognostic marker for OS prediction in patients with CRC in other two independent cohorts. In short, we developed a robust seven-gene signature that can predict the OS for CRC patients, providing new insights into identification of CRC patients with high risk of mortality

Condensing Multilingual Knowledge with Lightweight Language-Specific Modules

Incorporating language-specific (LS) modules is a proven method to boost performance in multilingual machine translation. This approach bears similarity to Mixture-of-Experts (MoE) because it does not inflate FLOPs. However, the scalability of this approach to hundreds of languages (experts) tends to be unmanageable due to the prohibitive number of parameters introduced by full-rank matrices in fully-connected layers. In this work, we introduce the Language-Specific Matrix Synthesis (LMS) method. This approach constructs LS modules by generating low-rank matrices from two significantly smaller matrices to approximate the full-rank matrix. Furthermore, we condense multilingual knowledge from multiple LS modules into a single shared module with the Fuse Distillation (FD) technique to improve the efficiency of inference and model serialization. We show that our LMS method significantly outperforms previous LS methods and MoE methods with the same amount of extra parameters, e.g., 1.73 BLEU points over the Switch Transformer on many-to-many multilingual machine translation. Importantly, LMS is able to have comparable translation performance with much fewer parameters.Comment: Accepted at the main conference of EMNLP 202

Inverse Correlation Between Plasma Adropin and ET-1 Levels in Essential Hypertension: A Cross-Sectional Study

Adropin is a recently identified bioactive protein that promotes energy homeostasis by affecting glucose and lipid metabolism. Recently, adropin has also been reported to be associated with endothelial dysfunction. Also, ET-1, as a biomarker for endothelial dysfunction, is a key regulator in hypertension. Accordingly, the aim of the present study was to detect the relationship between plasma adropin and ET-1 levels in hypertension. A total of 123 participants, diagnosed with primary hypertension on the basis of World Health Organization criteria (systolic blood pressure [SBP] ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg), and 58 normotensive subjects were enrolled in the cross-sectional study from October 2011 to December 2013. All study participants were older than 18 years of age. Adropin and ET-1 levels were measured by enzyme-linked immunosorbent assay (ELISA). We found that plasma adropin levels were significantly lower in hypertensives compared with controls (3.18 ± 1.00 vs 4.21 ± 1.14 ng/mL, P \u3c 0.001). Plasma ET-1 levels were higher in hypertensives than controls (2.60 ± 1.14 vs 1.54 ± 0.66 pg/mL, P \u3c 0.001). Adropin had a negative correlation with DBP (r = -0.40, P \u3c 0.001), SBP (r = -0.49, P \u3c 0.001), and adjusted for age, body mass index, SBP, DBP, glucose, TC, TG, LDL, and Cr, there was a negative correlation between ET-1 and adropin (r = -0.20, P = 0.04). In multivariate logistic regression analysis of the variables, ET-1 (odds ratio [OR], 3.84; 95% CI, 2.16-6.81; P \u3c 0.001) and adropin (OR, 0.99; 95% CI, 0.99 -1.0; P \u3c  .001) were found to be independent predictors for hypertension.In conclusion, decreased plasma adropin levels are associated with increased blood pressure in hypertension. Adropin is an independent predictor for hypertension, and may influence blood pressure by protecting endothelial function

Antagonistic Actions of Juvenile Hormone and 20-Hydroxyecdysone Within the Ring Gland Determine Developmental Transitions in \u3cem\u3eDrosophila\u3c/em\u3e

In both vertebrates and insects, developmental transition from the juvenile stage to adulthood is regulated by steroid hormones. In insects, the steroid hormone, 20-hydroxyecdysone (20E), elicits metamorphosis, thus promoting this transition, while the sesquiterpenoid juvenile hormone (JH) antagonizes 20E signaling to prevent precocious metamorphosis during the larval stages. However, not much is known about the mechanisms involved in cross-talk between these two hormones. In this study, we discovered that in the ring gland (RG) of Drosophila larvae, JH and 20E control each other’s biosynthesis. JH induces expression of a Krüppel-like transcription factor gene Kr-h1 in the prothoracic gland (PG), a portion of the RG that produces the 20E precursor ecdysone. By reducing both steroidogenesis autoregulation and PG size, high levels of Kr-h1 in the PG inhibit ecdysteriod biosynthesis, thus maintaining juvenile status. JH biosynthesis is prevented by 20E in the corpus allatum, the other portion of the RG that produces JH, to ensure the occurrence of metamorphosis. Hence, antagonistic actions of JH and 20E within the RG determine developmental transitions in Drosophila. Our study proposes a mechanism of cross-talk between the two major hormones in the regulation of insect metamorphosis

Proteomics Analysis of the Spinal Dorsal Horn in Diabetic Painful Neuropathy Rats With Electroacupuncture Treatment

BackgroundClinical evidence demonstrates that electro-acupuncture (EA) of the Zu sanli (ST36) and Shen shu (BL23) acupoints is effective in relieving diabetic painful neuropathy (DPN); however, the underlying molecular mechanism requires further investigation, including the protein molecules associated with EA’s effects on DPN.MethodsSprague-Dawley adult male rats (n =36) were randomly assigned into control, DPN, and EA groups (n=12 each). After four weeks of EA treatment, response to mechanical pain and fasting blood glucose were analyzed. A tandem mass tag (TMT) labeling approach coupled with liquid chromatography with tandem mass spectrometry was used to identify potential biomarkers in the spinal dorsal horn. Further, proteomics analysis was used to quantify differentially expressed proteins (DEPs), and gene ontology, KEGG pathways, cluster, and string protein network interaction analyses conducted to explore the main protein targets of EA.ResultsCompared with the DPN model group, the mechanical pain threshold was significantly increased, while the fasting blood glucose levels were clearly decreased in EA group rats. Proteomics analysis was used to quantify 5393 proteins, and DEPs were chosen for further analyses, based on a threshold of 1.2-fold difference in expression level (P < 0.05) compared with control groups. Relative to the control group, 169 down-regulated and 474 up-regulated proteins were identified in the DPN group, while 107 and 328 proteins were up- and down-regulated in the EA treatment group compared with the DPN group. Bioinformatics analysis suggested that levels of proteins involved in oxidative stress injury regulation were dramatically altered during the EA effects on DPN.ConclusionsOur results provide the valuable protein biomarkers, which facilitates unique mechanistic insights into the DPN pathogenesis and EA analgesic, antioxidant stress and hypoglycemic effect

Pharmacoeconomic analysis (CER) of Dulaglutide and Liraglutide in the treatment of patients with type 2 diabetes

AimTo evaluate the treatment effect Fand pharmacoeconomic value of Dugaglutide in women with type 2 diabetes.MethodsWomen (n=96) with type 2 diabetes recruited from June 2019 to December 2021 were randomized into two equal groups. The control group was treated with Liraglutide, and the observation group was treated with Dulaglutide, both for 24 weeks. The blood glucose levels, biochemical index, insulin resistance index (HOMA-IR), cost-effect ratio (CER), and drug safety were determined and compared between the two groups.ResultsBlood glucose levels, the biochemical index, and HOMA-IR were lower in both groups after the treatment (P < 0.05), and there was no statistical difference in the blood glucose levels, biochemical index and HOMA-IR between the two groups (P > 0.05). The CER levels did not differ statistically between the two groups (P > 0.05). Both the cost and the incidence of drug side effects during solution injection were lower in the observation group than in the control group after 24 weeks of treatment (P < 0.05).ConclusionBoth Dulaglutide and Liraglutide can reduce blood glucose levels, improve biochemical index, and HOMA-IR levels in women with type 2 diabetes. Dulaglutide is more cost-effective and safe.Clinical trial registrationhttps://www.chictr.org.cn/index.aspx, identifier ChiCTR1900026514

A Novel Bioinspired PVDF Micro/Nano Hair Receptor for a Robot Sensing System

This paper describes the concept and design of a novel artificial hair receptor for the sensing system of micro intelligent robots such as a cricket-like jumping mini robot. The concept is inspired from the natural hair receptor of animals, also called cilium or filiform hair by different research groups, which is usually used as a vibration receptor or a flow detector by insects, mammals and fishes. The suspended fiber model is firstly built and the influence of scaling down is analyzed theoretically. The design of this artificial hair receptor is based on aligned suspended PVDF (polyvinylidene fluoride) fibers, manufactures with a novel method called thermo-direct drawing technique, and aligned suspended submicron diameter fibers are thus successfully fabricated on a flexible Kapton. In the post process step, some key problems such as separated electrodes deposition along with the fiber drawing direction and poling of micro/nano fibers to impart them with good piezoeffective activity have been presented. The preliminary validation experiments show that the artificial hair receptor has a reliable response with good sensibility to external pressure variation and, medium flow as well as its prospects in the application on sensing system of mini/micro bio-robots

Differential early diagnosis of benign versus malignant lung cancer using systematic pathway flux analysis of peripheral blood leukocytes

Early diagnosis of lung cancer is critically important to reduce disease severity and improve overall survival. Newer, minimally invasive biopsy procedures often fail to provide adequate specimens for accurate tumor subtyping or staging which is necessary to inform appropriate use of molecular targeted therapies and immune checkpoint inhibitors. Thus newer approaches to diagnosis and staging in early lung cancer are needed. This exploratory pilot study obtained peripheral blood samples from 139 individuals with clinically evident pulmonary nodules (benign and malignant), as well as ten healthy persons. They were divided into three cohorts: original cohort (n = 99), control cohort (n = 10), and validation cohort (n = 40). Average RNAseq sequencing of leukocytes in these samples were conducted. Subsequently, data was integrated into artificial intelligence (AI)-based computational approach with system-wide gene expression technology to develop a rapid, effective, non-invasive immune index for early diagnosis of lung cancer. An immune-related index system, IM-Index, was defined and validated for the diagnostic application. IM-Index was applied to assess the malignancies of pulmonary nodules of 109 participants (original + control cohorts) with high accuracy (AUC: 0.822 [95% CI: 0.75–0.91, p < 0.001]), and to differentiate between phases of cancer immunoediting concept (odds ratio: 1.17 [95% CI: 1.1–1.25, p < 0.001]). The predictive ability of IM-Index was validated in a validation cohort with a AUC: 0.883 (95% CI: 0.73–1.00, p < 0.001). The difference between molecular mechanisms of adenocarcinoma and squamous carcinoma histology was also determined via the IM-Index (OR: 1.2 [95% CI 1.14–1.35, p = 0.019]). In addition, a structural metabolic behavior pattern and signaling property in host immunity were found (bonferroni correction, p = 1.32e − 16). Taken together our findings indicate that this AI-based approach may be used for “Super Early” cancer diagnosis and amend the current immunotherpay for lung cancer