Ferroptosis and cuproptosis prognostic signature for prediction of prognosis, immunotherapy and drug sensitivity in hepatocellular carcinoma: development and validation based on TCGA and ICGC databases.

Background: Hepatocellular carcinoma (HCC) is a common malignancy. Ferroptosis and cuproptosis promote HCC spread and proliferation. While fewer studies have combined ferroptosis and cuproptosis to construct prognostic signature of HCC. This work attempts to establish a novel scoring system for predicting HCC prognosis, immunotherapy, and medication sensitivity based on ferroptosis-related genes (FRGs) and cuproptosis-related genes (CRGs). Methods: FerrDb and previous literature were used to identify FRGs. CRGs came from original research. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases included the HCC transcriptional profile and clinical information [survival time, survival status, age, gender, Tumor Node Metastasis (TNM) stage, etc.]. Correlation, Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses were used to narrow down prognostic genes and develop an HCC risk model. Using "caret", R separated TCGA-HCC samples into a training risk set and an internal test risk set. As external validation, we used ICGC samples. We employed Kaplan-Meier analysis and receiver operating characteristic (ROC) curve to evaluate the model's clinical efficacy. CIBERSORT and TIMER measured immunocytic infiltration in high- and low-risk populations. Results: TXNRD1 [hazard ratio (HR) =1.477, P<0.001], FTL (HR =1.373, P=0.001), GPX4 (HR =1.650, P=0.004), PRDX1 (HR =1.576, P=0.002), VDAC2 (HR =1.728, P=0.008), OTUB1 (HR =1.826, P=0.002), NRAS (HR =1.596, P=0.005), SLC38A1 (HR =1.290, P=0.002), and SLC1A5 (HR =1.306, P<0.001) were distinguished to build predictive model. In both the model cohort (P<0.001) and the validation cohort (P<0.05), low-risk patients had superior overall survival (OS). The areas under the curve (AUCs) of the ROC curves in the training cohort (1-, 3-, and 5-year AUCs: 0.751, 0.727, and 0.743), internal validation cohort (1-, 3-, and 5-year AUCs: 0.826, 0.624, and 0.589), and ICGC cohort (1-, 3-, and 5-year AUCs: 0.699, 0.702, and 0.568) were calculated. Infiltration of immune cells and immunological checkpoints were also connected with our signature. Treatments with BI.2536, Epothilone.B, Gemcitabine, Mitomycin.C, Obatoclax. Mesylate, and Sunitinib may profit high-risk patients. Conclusions: We analyzed FRGs and CRGs profiles in HCC and established a unique risk model for treatment and prognosis. Our data highlight FRGs and CRGs in clinical practice and suggest ferroptosis and cuproptosis may be therapeutic targets for HCC patients. To validate the model's clinical efficacy, more HCC cases and prospective clinical assessments are needed.

[Progress in diagnosis and therapy of thoracic outlet syndrome].

Thoracic outlet syndrome(TOS) are constellation of symptoms caused by compression of the neurovascular bundle including the brachial plexus, the subclavian artery and the subclavian vein at the thoracic outlet region. It includes neurogenic TOS, venus TOS, arterial TOS, and neurogenic TOS is the most common type. TOS has varied manifestations and lack of confirmatory testing, therefore, the diagnosis should be conbination with thorough history, physical examination and associated supplementary examinations. Conservative and surgical treatment can be choosed for TOS and the outcomes are generally good. Conservative management is the initial treatment strategy for neurogenic TOS. In cases of symptomatic vascular TOS and neurovascular TOS, which has been failed by conservative treatment, surgery should be considered more promptly.

Carbon-doped SnS2 nanostructure as a high-efficiency solar fuel catalyst under visible light.

Photocatalytic formation of hydrocarbons using solar energy via artificial photosynthesis is a highly desirable renewable-energy source for replacing conventional fossil fuels. Using an L-cysteine-based hydrothermal process, here we synthesize a carbon-doped SnS2 (SnS2-C) metal dichalcogenide nanostructure, which exhibits a highly active and selective photocatalytic conversion of CO2 to hydrocarbons under visible-light. The interstitial carbon doping induced microstrain in the SnS2 lattice, resulting in different photophysical properties as compared with undoped SnS2. This SnS2-C photocatalyst significantly enhances the CO2 reduction activity under visible light, attaining a photochemical quantum efficiency of above 0.7%. The SnS2-C photocatalyst represents an important contribution towards high quantum efficiency artificial photosynthesis based on gas phase photocatalytic CO2 reduction under visible light, where the in situ carbon-doped SnS2 nanostructure improves the stability and the light harvesting and charge separation efficiency, and significantly enhances the photocatalytic activity.