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BackgroundCirculating aminotransferases (ALT and AST) have been used as biomarkers for liver injury. The causal relationships between aminotransferases and metabolic syndrome remain ambiguous.MethodsWe conducted bidirectional and multivariable Mendelian randomization (MR) analyses between aminotransferases and traits related to metabolic syndrome using genetic variants obtained from genome-wide association studies (GWASs). MR-PRESSO tests were adopted to remove outliers and eliminate pleiotropy. MR steiger tests were conducted to ensure the correct direction of the causal effects.ResultsBoth aminotransferases were risk factors for essential hypertension. ALT is a risk factor for type 2 diabetes. The bidirectional causal relationship between ALT and hyperglycemia, serum lipids, and obesity was demonstrated. The effect of fasting glucose on AST was demonstrated, while type 2 diabetes did not affect AST. The effect of HDL-C on ALT and the effect of triglycerides on AST were found in multivariable MR analyses.ConclusionsOur bidirectional MR analyses suggest that ALT and AST are causally associated with several metabolic syndrome-related traits, especially hypertension and type 2 diabetes. These findings highlight the potential role of aminotransferases as biomarkers and therapeutic targets for metabolic syndrome.

This Letter reports a highly scaled 90 nm gate length β-Ga2O3 (Ga2O3) T-gate MOSFET with a power gain cutoff frequency (fMAX) of 55 GHz. The 60 nm thin epitaxial Ga2O3 channel layer was grown by molecular beam epitaxy, while the highly doped (n++) source/drain regions were regrown using metal organic chemical vapor deposition. Maximum on current (IDS,MAX) of 160 mA/mm and trans-conductance (gm) around 36 mS/mm were measured at VDS = 10 V for LSD = 1.5 μ m device. Transconductance and on current are limited by high channel sheet resistance (Rsheet). Gate/drain breakdown voltage of 125 V was measured for LGD = 1.2 μ m. We extracted 27 GHz current gain cutoff frequency (fT) and 55 GHz fMAX for 20 V drain bias for unpassivated devices. While no current collapse was seen initially for both drain and gate lag measurements for 500 ns pulse, moderate current collapse was observed after DC, RF measurements caused by electrical stressing. We calculated a high fT. VBR product of 3.375 THz V, which is comparable to the state-of-the-art GaN HEMTs. This figure of merit suggests that Ga2O3 could be a potential candidate for X-band application. [ABSTRACT FROM AUTHOR]

We report on the growth of Si-doped homoepitaxial β-Ga2O3 thin films on (010) Ga2O3 substrates via metal-organic chemical vapor deposition (MOCVD) utilizing triethylgallium (TEGa) and trimethylgallium (TMGa) precursors. The epitaxial growth achieved an impressive 9.5 μm thickness at 3 μm/h using TMGa, a significant advance in material growth for electronic device fabrication. This paper systematically studies the Schottky barrier diodes fabricated on the three MOCVD-grown films, each exhibiting variations in the epilayer thickness, doping levels, and growth rates. The diode from the 2 μm thick Ga2O3 epilayer with TEGa precursor demonstrates promising forward current densities, the lowest specific on-resistance, and the lowest ideality factor, endorsing TEGa's potential for MOCVD growth. Conversely, the diode from the 9.5 μm thick Ga2O3 layer with TMGa precursor exhibits excellent characteristics in terms of lowest leakage current, highest on-off ratio, and highest reverse breakdown voltage of −510 V without any electric field management, emphasizing TMGa's suitability for achieving high growth rates in Ga2O3 epilayers for vertical power electronic devices. [ABSTRACT FROM AUTHOR]

In order to improve the surface performance of engineering components, a Ni60-Ti-B4C hard coating was prepared in-situ on the surface of Q235 using laser cladding method based on Ni60-Ti-B4C powder. The effect of process parameters (laser power and scanning speed) on the microstructure, dilution rate, microhardness and wear resistance of the coatings was investigated in detail. The highest microhardness and lower dilution rate coatings were obtained by process optimization. A laser power of 1000 W and scanning speed of 6 mm/s were found to be the optimum parameters. The optimized Ni60-Ti-B4C coating mainly consists of in-situ rod-like TiB2 and block-like TiC of different sizes with TiB2-TiC eutectic structure and small amounts of FeNi, Ni3Cr and NiSi phases. The optimized Ni60-Ti-B4C coating has a dilution rate of 27.1% and a wear loss of 2.1 mg. The microhardness is 1278 HV0.3, which is about 7 times of the microhardness of Q235 steel substrate, and 2.5 times the microhardness of laser cladding coated Ni60 coating. The abrasion of the Ni60-Ti-B4C coating is mainly adhesive abrasion. This study can provide a reference value for the use of surface technology to improve the overall performance of metal parts. [ABSTRACT FROM AUTHOR]

Background: The hip joint capsule is an essential component of hip joint function and stability, and its thickness is closely associated with certain medical conditions, surgical outcomes, and rehabilitation treatments. Currently, in clinical practice, hip joint capsule thickness is predominantly measured using magnetic resonance imaging (MRI), with limited utilization of ultrasound examinations for this purpose. Methods: We retrospectively evaluated patients who visited our Sports Medicine Department between February 2017 and March 2023 and underwent both hip joint MRI and ultrasound imaging on the same side. All patients had undergone preoperative hip joint MRI and ultrasound examinations, with the time gap between the two examinations not exceeding three months. Measurements of hip joint capsule thickness were taken on both MRI and ultrasound images for the same patients to analyze their consistency. Additionally, we measured the alpha angle, lateral center-edge angle, acetabular anteversion angle, and femoral anteversion angle of the patients' hip joints and analyzed their correlation with hip joint capsule thickness measure by ultrasound. Results: A total of 307 patients were included in this study, with hip joint capsule thickness measured by MRI and ultrasound being 5.0 ± 1.2 mm and 5.0 ± 1.5 mm, respectively. The Bland-Altman analysis demonstrates good agreement or consistency. The paired t-test resulted in a p-value of 0.708, indicating no significant statistical difference between the two methods. The correlation analysis between acetabular anteversion angle and ultrasound-measured capsule thickness yielded a p-value of 0.043, indicating acetabular anteversion angle and capsular thickness may have negative correlation. Conclusions: The measurements of joint capsule thickness obtained through ultrasound and MRI showed good consistency, suggesting that ultrasound can be used in clinical practice as a replacement for MRI in measuring hip joint capsule thickness. There was a significant correlation between acetabular anteversion angle and hip joint capsule thickness, indicating potential for further research in this area. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is one of the most malignant cancers with rapid progression and poor prognosis. The use of transcriptional data can be effective in finding new biomarkers for pancreatic cancer. Many network-based methods used to identify cancer biomarkers are proposed, among which the combination of network controllability appears. However, most of the existing methods do not study RNA, rely on priori and mutations information, or can only achieve classification tasks. In this study, we propose a method combined Relational Graph Convolutional Network and Deep Q-Network called RDDriver to identify pancreatic cancer biomarkers based on multi-layer heterogeneous transcriptional regulation network. Firstly, we construct a regulation network containing long non-coding RNA, microRNA, and messenger RNA. Secondly, Relational Graph Convolutional Network is used to learn the node representation. Finally, we use the idea of Deep Q-Network to build a model, which score and prioritize each RNA with the Popov-Belevitch-Hautus criterion. We train RDDriver on three small simulated networks, and calculate the average score after applying the model parameters to the regulation networks separately. To demonstrate the effectiveness of the method, we perform experiments for comparison between RDDriver and other eight methods based on the approximate benchmark of three types cancer drivers RNAs.