14C diamond as energy converting material in betavoltaic battery: A first principles study

The application of radioactive semiconductors is a potential way to improve the performance of betavoltaic battery. The stability and band structure of decayed 14C diamond are investigated by density functional theory. After the decay, the 14C atoms are substituted by nitrogen atoms, and it can be seen that the corresponding C63N1 and C62N2 structures have larger lattice constants and become more unstable. The C63N1 structure is a metallic system instead of an indirect bandgap semiconductor. Different C62N2 configurations have either metallic or indirect bandgap semiconductor properties, and the bandgaps are significantly lower than those of pure diamond. The 14C diamond–12C diamond betavoltaic battery switches between a pn-junction and p-type Schottky diode with higher short-circuit current

Turing structuring with multiple nanotwins to engineer efficient and stable catalysts for hydrogen evolution reaction

Abstract Low-dimensional nanocrystals with controllable defects or strain modifications are newly emerging active electrocatalysts for hydrogen-energy conversion and utilization; however, a crucial challenge remains in insufficient stability due to spontaneous structural degradation and strain relaxation. Here we report a Turing structuring strategy to activate and stabilize superthin metal nanosheets by incorporating high-density nanotwins. Turing configuration, realized by constrained orientation attachment of nanograins, yields intrinsically stable nanotwin network and straining effects, which synergistically reduce the energy barrier of water dissociation and optimize the hydrogen adsorption free energy for hydrogen evolution reaction. Turing PtNiNb nanocatalyst achieves 23.5 and 3.1 times increase in mass activity and stability index, respectively, compared against commercial 20% Pt/C. The Turing PtNiNb-based anion-exchange-membrane water electrolyser with a low Pt mass loading of 0.05 mg cm−2 demonstrates at least 500 h stability at 1000 mA cm− 2, disclosing the stable catalysis. Besides, this new paradigm can be extended to Ir/Pd/Ag-based nanocatalysts, illustrating the universality of Turing-type catalysts

FASN Protein Overexpression Indicates Poor Biochemical Recurrence-Free Survival in Prostate Cancer

Backgrounds. Fatty acid synthase (FASN) has been regarded as a prognostic marker in prostate cancer (PCa). In this study, we evaluated FASN expression at both mRNA and protein levels and assessed the association between FASN expression and prognosis in male Han Chinese with PCa treated with radical prostatectomy (RP). Methods. Expression profile and prognostic value of FASN were analyzed in tissue microarray (TMA) and data retrieved from databases including TCGA public database, GEO database, and our sequencing data with whole clinicopathological characteristics. Results. FASN expression was associated with clinical parameters and biochemical recurrence of prostate cancer. The relative expression of FASN mRNA was higher in the tumor tissue in all public databases and our sequencing data (p<0.001). A similar result was seen in tissue microarray (TMA) (p<0.001). Analysis of our sequencing data indicated that FASN’s relative expression was associated with tumor stage (p=0.048), and FASN expression was positively associated with the Gleason score (p=0.004) and seminal vesicle invasion (p=0.011) in TMA. We found that high FASN expression was an independent predictor of shorter BCR-free survival with univariate and multivariate survival analysis (p<0.05), rendering FASN an optimal prognostic biomarker in male Han Chinese with prostate cancer. Conclusions. Our study demonstrated that FASN was overexpressed at mRNA and protein levels in PCa. We found that patients with high FASN expression had a shorter BCR-free survival, showing its value as a prognostic biomarker in male Han Chinese with PCa

A new criteria for acute on preexisting kidney dysfunction in critically ill patients

AbstractCritically ill patients with preexisting kidney dysfunction (PKD) are at high risk for acute kidney injury (AKI). Nevertheless, there is no criteria for screening and classifying AKI in patients with PKD. In this study, after assessing relationship between the change in SCr from baseline and in-hospital mortality, a new criteria, named APKD, for identifying AKI in PKD was proposed. APKD defined AKI in critically ill patients with PKD as an absolute increase of ≥ 0.2 mg/dL in SCr within 48 h or an increase in SCr ≥ 1.1 times over baseline within 7 d. APKD detected more AKI among PKD patients compared with the other criteria. Additionally, the AKI patients identified by APKD but missed by the other criteria had higher mortality than those without AKI. APKD shows higher sensitivities than KDIGO criteria in predicating in-hospital mortality. APKD, but not the KDIGO, is effective for staging the severity of AKI in patients with PKD. In conclusion, APKD is more effective in screening and classifying AKI in critically ill patients with PKD compared with the earlier criteria, and it may helpful in guiding clinical treatment and predicting prognosis

Integration of lipidomics and transcriptomics unravels aberrant lipid metabolism and defines cholesteryl oleate as potential biomarker of prostate cancer

In-depth delineation of lipid metabolism in prostate cancer (PCa) is significant to open new insights into prostate tumorigenesis and progression, and provide potential biomarkers with greater accuracy for improved diagnosis. Here, we performed lipidomics and transcriptomics in paired prostate cancer tumor (PCT) and adjacent nontumor (ANT) tissues, followed by external validation of biomarker candidates. We identified major dysregulated pathways involving lipogenesis, lipid uptake and phospholipids remodeling, correlated with widespread lipid accumulation and lipid compositional reprogramming in PCa. Specifically, cholesteryl esters (CEs) were most prominently accumulated in PCa, and significantly associated with cancer progression and metastasis. We showed that overexpressed scavenger receptor class B type I (SR-BI) may contribute to CEs accumulation. In discovery set, CEs robustly differentiated PCa from nontumor (area under curve (AUC) of receiver operating characteristics (ROC), 0.90-0.94). In validation set, CEs potently distinguished PCa and non-malignance (AUC, 0.84-0.91), and discriminated PCa and benign prostatic hyperplasia (BPH) (AUC, 0.90-0.96), superior to serum prostate-specific antigen (PSA) (AUC = 0.83). Cholesteryl oleate showed highest AUCs in distinguishing PCa from non-malignance or BPH (AUC = 0.91 and 0.96). Collectively, our results unravel the major lipid metabolic aberrations in PCa and imply the potential role of CEs, particularly, cholesteryl oleate, as molecular biomarker for PCa detection

8-Br-cGMP activates HSPB6 and increases the antineoplastic activity of quinidine in prostate cancer

Abstract Heat shock protein family B [small] member 6 (HSPB6), widely found in various muscles, has been recently identified as a tumor suppressor gene. However, its role in prostate cancer remains unexplored. Herein, we investigated the expression of HSPB6 in prostate cancer and its association with prognosis. Our findings revealed that HSPB6 downregulation in prostate cancer correlated with a poor prognosis. Moreover, we discovered that HSPB6 can be phosphorylated and activated by 8-Br-cGMP, leading to apoptosis in prostate cancer cells by activating Cofilin. Additionally, we demonstrated that knocking down E2F1 by quinidine administration enhances the transcriptional level of HSPB6. Furthermore, we evaluated the combination of quinidine and 8-Br-cGMP as a potential therapeutic strategy for prostate cancer. Our results revealed that the combined treatment was more effective than either treatment alone in inhibiting the growth of prostate cancer through the HSPB6 pathway, both in vitro and in vivo. Overall, our study provides compelling evidence that HSPB6 suppresses malignant behavior in prostate cancer by inducing apoptosis. The combination of quinidine and 8-Br-cGMP emerges as a promising approach for the treatment of prostate cancer

Artificial intelligence for the diagnosis of clinically significant prostate cancer based on multimodal data: a multicenter study

Abstract Background The introduction of multiparameter MRI and novel biomarkers has greatly improved the prediction of clinically significant prostate cancer (csPCa). However, decision-making regarding prostate biopsy and prebiopsy examinations is still difficult. We aimed to establish a quick and economic tool to improve the detection of csPCa based on routinely performed clinical examinations through an automated machine learning platform (AutoML). Methods This study included a multicenter retrospective cohort and two prospective cohorts with 4747 cases from 9 hospitals across China. The multimodal data, including demographics, clinical characteristics, laboratory tests, and ultrasound reports, of consecutive participants were retrieved using extract-transform-load tools. AutoML was applied to explore potential data processing patterns and the most suitable algorithm to build the Prostate Cancer Artificial Intelligence Diagnostic System (PCAIDS). The diagnostic performance was determined by the receiver operating characteristic curve (ROC) for discriminating csPCa from insignificant prostate cancer (PCa) and benign disease. The clinical utility was evaluated by decision curve analysis (DCA) and waterfall plots. Results The random forest algorithm was applied in the feature selection, and the AutoML algorithm was applied for model establishment. The area under the curve (AUC) value in identifying csPCa was 0.853 in the training cohort, 0.820 in the validation cohort, 0.807 in the Changhai prospective cohort, and 0.850 in the Zhongda prospective cohort. DCA showed that the PCAIDS was superior to PSA or fPSA/tPSA for diagnosing csPCa with a higher net benefit for all threshold probabilities in all cohorts. Setting a fixed sensitivity of 95%, a total of 32.2%, 17.6%, and 26.3% of unnecessary biopsies could be avoided with less than 5% of csPCa missed in the validation cohort, Changhai and Zhongda prospective cohorts, respectively. Conclusions The PCAIDS was an effective tool to inform decision-making regarding the need for prostate biopsy and prebiopsy examinations such as mpMRI. Further prospective and international studies are warranted to validate the findings of this study. Trial registration Chinese Clinical Trial Registry ChiCTR2100048428. Registered on 06 July 2021