The necessity for new sources for greener and cleaner energy production to replace the existing ones has been increasingly growing in recent years. Of those new sources, the hydrogen evolution ...reaction has a large potential. In this work, for the first time, MoSe2/Mo core–shell 3D‐hierarchical nanostructures are created, which are derived from the Mo 3D‐hierarchical nanostructures through a low‐temperature plasma‐assisted selenization process with controlled shapes grown by a glancing angle deposition system.
The formation of PtSe2‐layered films is reported in a large area by the direct plasma‐assisted selenization of Pt films at a low temperature, where temperatures, as low as 100 °C at the applied ...plasma power of 400 W can be achieved. As the thickness of the Pt film exceeds 5 nm, the PtSe2‐layered film (five monolayers) exhibits a metallic behavior. A clear p‐type semiconducting behavior of the PtSe2‐layered film (≈trilayers) is observed with the average field effective mobility of 0.7 cm2 V−1 s−1 from back‐gated transistor measurements as the thickness of the Pt film reaches below 2.5 nm. A full PtSe2 field effect transistor is demonstrated where the thinner PtSe2, exhibiting a semiconducting behavior, is used as the channel material, and the thicker PtSe2, exhibiting a metallic behavior, is used as an electrode, yielding an ohmic contact. Furthermore, photodetectors using a few PtSe2‐layered films as an adsorption layer synthesized at the low temperature on a flexible substrate exhibit a wide range of absorption and photoresponse with the highest photocurrent of 9 µA under the laser wavelength of 408 nm. In addition, the device can maintain a high photoresponse under a large bending stress and 1000 bending cycles.
Phase‐engineered PtSe2‐layered films by a plasma‐assisted selenization process to highly sensitive, flexible, and wide‐spectrum photoresponse photodetectors are demonstrated. A full PtSe2 field effect transistor is also demonstrated where the thinner PtSe2, exhibiting a semiconducting behavior, is used as the channel material, and the thicker PtSe2, exhibiting a metallic behavior, is used as an electrode.
•Fatty liver disease (FLD) is a common clinical complication, is associated with high morbidity and mortality.•A machine learning model has been using to predict liver disease that could assist ...physicians in classifying high-risk patients and make a novel diagnosis.•The random forest model shows higher performance than other classification models.
Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for prevention, early diagnosis and treatment. We aimed to develop a machine learning model to predict FLD that could assist physicians in classifying high-risk patients and make a novel diagnosis, prevent and manage FLD.
We included all patients who had an initial fatty liver screening at the New Taipei City Hospital between 1st and 31st December 2009. Classification models such as random forest (RF), Naïve Bayes (NB), artificial neural networks (ANN), and logistic regression (LR) were developed to predict FLD. The area under the receiver operating characteristic curve (ROC) was used to evaluate performances among the four models.
A total of 577 patients were included in this study; of those 377 patients had fatty liver. The area under the receiver operating characteristic (AUROC) of RF, NB, ANN, and LR with 10 fold-cross validation was 0.925, 0.888, 0.895, and 0.854 respectively. Additionally, The accuracy of RF, NB, ANN, and LR 87.48, 82.65, 81.85, and 76.96%.
In this study, we developed and compared the four classification models to predict fatty liver disease accurately. However, the random forest model showed higher performance than other classification models. Implementation of a random forest model in the clinical setting could help physicians to stratify fatty liver patients for primary prevention, surveillance, early treatment, and management.
Animal coronaviruses (CoVs) have been identified to be the origin of Severe Acute Respiratory Syndrome (SARS)-CoV, Middle East respiratory syndrome (MERS)-CoV, and probably SARS-CoV-2 that cause ...severe to fatal diseases in humans. Variations of zoonotic coronaviruses pose potential threats to global human beings. To overcome this problem, we focused on the main protease (M
), which is an evolutionary conserved viral protein among different coronaviruses. The broad-spectrum anti-coronaviral drug, GC376, was repurposed to target canine coronavirus (CCoV), which causes gastrointestinal infections in dogs. We found that GC376 can efficiently block the protease activity of CCoV M
and can thermodynamically stabilize its folding. The structure of CCoV M
in complex with GC376 was subsequently determined at 2.75 Å. GC376 reacts with the catalytic residue C144 of CCoV M
and forms an (R)- or (S)-configuration of hemithioacetal. A structural comparison of CCoV M
and other animal CoV M
s with SARS-CoV-2 M
revealed three important structural determinants in a substrate-binding pocket that dictate entry and release of substrates. As compared with the conserved A141 of the S1 site and P188 of the S4 site in animal coronaviral M
s, SARS-CoV-2 M
contains N142 and Q189 at equivalent positions which are considered to be more catalytically compatible. Furthermore, the conserved loop with residues 46-49 in animal coronaviral M
s has been replaced by a stable α-helix in SARS-CoV-2 M
. In addition, the species-specific dimerization interface also influences the catalytic efficiency of CoV M
s. Conclusively, the structural information of this study provides mechanistic insights into the ligand binding and dimerization of CoV M
s among different species.
The development of an efficient catalyst for formic acid electrocatalytic oxidation reaction (FAEOR) is of great significance to accelerate the commercial application of direct formic acid fuel cells ...(DFAFC). Herein, palladium phosphide (PdxPy) porous nanotubes (PNTs) with different phosphide content (i.e., Pd3P and Pd5P2) are prepared by combining the self‐template reduction method of dimethylglyoxime‐Pd(II) complex nanorods and succedent phosphating treatment. During the reduction process, the self‐removal of the template and the continual inside–outside Ostwald ripening phenomenon are responsible for the generation of the one‐dimensional hollow and porous architecture. On the basis of the unique synthetic procedure and structural advantages, Pd3P PNTs with optimized phosphide content show outstanding electroactivity and stability for FAEOR. Importantly, the strong electronic effect between Pd and P promotes the direct pathway of FAEOR and inhibits the occurrence of the formic acid decomposition reaction, which effectively enhances the FAEOR electroactivity of Pd3P PNTs. In view of the facial synthesis, excellent electroactivity, high stability, and unordinary selectivity, Pd3P PNTs have the potential to be an efficient anode electrocatalyst for DFAFC.
Efficient formic acid oxidation reaction (FAEOR) electrocatalyst Pd3P porous nanotubes (PNTs) are synthesized by simple self‐template pyrolysis and phosphating treatment. Benefiting from the abundant defect atoms and excellent self‐stability, Pd3P PNTs reveal outstanding electroactivity and durability for FAEOR. The introduction of phosphorus could effectively improve the FAEOR electroactivity of Pd nanomaterials and simultaneously inhibit FADR, highlighting an efficient strategy for designing a DFAFC anode electrocatalyst.
Although pyroptosis is critical for macrophages against pathogen infection, its role and mechanism in cancer cells remains unclear. PD-L1 has been detected in the nucleus, with unknown function. Here ...we show that PD-L1 switches TNFα-induced apoptosis to pyroptosis in cancer cells, resulting in tumour necrosis. Under hypoxia, p-Stat3 physically interacts with PD-L1 and facilitates its nuclear translocation, enhancing the transcription of the gasdermin C (GSDMC) gene. GSDMC is specifically cleaved by caspase-8 with TNFα treatment, generating a GSDMC N-terminal domain that forms pores on the cell membrane and induces pyroptosis. Nuclear PD-L1, caspase-8 and GSDMC are required for macrophage-derived TNFα-induced tumour necrosis in vivo. Moreover, high expression of GSDMC correlates with poor survival. Antibiotic chemotherapy drugs induce pyroptosis in breast cancer. These findings identify a non-immune checkpoint function of PD-L1 and provide an unexpected concept that GSDMC/caspase-8 mediates a non-canonical pyroptosis pathway in cancer cells, causing tumour necrosis.
Statins have been shown to be a beneficial treatment as chemotherapy and target therapy for lung cancer. This study aimed to investigate the effectiveness of statins in combination with epidermal ...growth factor receptor‐tyrosine kinase inhibitor therapy for the resistance and mortality of lung cancer patients. A population‐based cohort study was conducted using the Taiwan Cancer Registry database. From January 1, 2007, to December 31, 2012, in total 792 non‐statins and 41 statins users who had undergone EGFR‐TKIs treatment were included in this study. All patients were monitored until the event of death or when changed to another therapy. Kaplan‐Meier estimators and Cox proportional hazards regression models were used to calculate overall survival. We found that the mortality was significantly lower in patients in the statins group compared with patients in the non‐statins group (4‐y cumulative mortality, 77.3%; 95% confidence interval (CI), 36.6%‐81.4% vs. 85.5%; 95% CI, 78.5%‐98%; P = .004). Statin use was associated with a reduced risk of death in patients the group who had tumor sizes <3 cm (hazard ratio HR, 0.51, 95% CI, 0.29‐0.89) and for patients in the group who had CCI scores <3 (HR, 0.6; 95% CI, 0.41‐0.88; P = .009). In our study, statins were found to be associated with prolonged survival time in patients with lung cancer who were treated with EGFR‐TKIs and played a synergistic anticancer role.
In this article, we describe the use of statins on the beneficial mortality of lung cancer patients with EGFR‐TKIs therapy. We found that statins were associated with prolonged survival time in patients with lung cancer who were taking EGFR‐TKIs. These could be playing a synergic anticancer role during the TKI treatment period, as well as improving quality of life worldwide and medical practice overall.
Background
Artificial intelligence approaches can integrate complex features and can be used to predict a patient’s risk of developing lung cancer, thereby decreasing the need for unnecessary and ...expensive diagnostic interventions.
Objective
The aim of this study was to use electronic medical records to prescreen patients who are at risk of developing lung cancer.
Methods
We randomly selected 2 million participants from the Taiwan National Health Insurance Research Database who received care between 1999 and 2013. We built a predictive lung cancer screening model with neural networks that were trained and validated using pre-2012 data, and we tested the model prospectively on post-2012 data. An age- and gender-matched subgroup that was 10 times larger than the original lung cancer group was used to assess the predictive power of the electronic medical record. Discrimination (area under the receiver operating characteristic curve AUC) and calibration analyses were performed.
Results
The analysis included 11,617 patients with lung cancer and 1,423,154 control patients. The model achieved AUCs of 0.90 for the overall population and 0.87 in patients ≥55 years of age. The AUC in the matched subgroup was 0.82. The positive predictive value was highest (14.3%) among people aged ≥55 years with a pre-existing history of lung disease.
Conclusions
Our model achieved excellent performance in predicting lung cancer within 1 year and has potential to be deployed for digital patient screening. Convolution neural networks facilitate the effective use of EMRs to identify individuals at high risk for developing lung cancer.
Background
Accurate glioma grading plays an important role in the clinical management of patients and is also the basis of molecular stratification nowadays.
Purpose/Hypothesis
To verify the ...superiority of radiomics features extracted from multiparametric MRI to glioma grading and evaluate the grading potential of different MRI sequences or parametric maps.
Study Type
Retrospective; radiomics.
Population
A total of 153 patients including 42, 33, and 78 patients with Grades II, III, and IV gliomas, respectively.
Field Strength/Sequence
3.0T MRI/T1‐weighted images before and after contrast‐enhanced, T2‐weighted, multi‐b‐value diffusion‐weighted and 3D arterial spin labeling images.
Assessment
After multiparametric MRI preprocessing, high‐throughput features were derived from patients' volumes of interests (VOIs). The support vector machine‐based recursive feature elimination was adopted to find the optimal features for low‐grade glioma (LGG) vs. high‐grade glioma (HGG), and Grade III vs. IV glioma classification tasks. Then support vector machine (SVM) classifiers were established using the optimal features. The accuracy and area under the curve (AUC) was used to assess the grading efficiency.
Statistical Tests
Student's t‐test or a chi‐square test were applied on different clinical characteristics to confirm whether intergroup significant differences exist.
Results
Patients' ages between LGG and HGG groups were significantly different (P < 0.01). For each patient, 420 texture and 90 histogram parameters were derived from 10 VOIs of multiparametric MRI. SVM models were established using 30 and 28 optimal features for classifying LGGs from HGGs and grades III from IV, respectively. The accuracies/AUCs were 96.8%/0.987 for classifying LGGs from HGGs, and 98.1%/0.992 for classifying grades III from IV, which were more promising than using histogram parameters or using the single sequence MRI.
Data Conclusion
Texture features were more effective for noninvasively grading gliomas than histogram parameters. The combined application of multiparametric MRI provided a higher grading efficiency. The proposed radiomic strategy could facilitate clinical decision‐making for patients with varied glioma grades.
Level of Evidence: 3
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;48:1518–1528
Recently, interest in aluminium ion batteries with aluminium anodes, graphite cathodes and ionic liquid electrolytes has increased; however, much remains to be done to increase the cathode capacity ...and to understand details of the anion-graphite intercalation mechanism. Here, an aluminium ion battery cell made using pristine natural graphite flakes achieves a specific capacity of ∼110 mAh g
with Coulombic efficiency ∼98%, at a current density of 99 mA g
(0.9 C) with clear discharge voltage plateaus (2.25-2.0 V and 1.9-1.5 V). The cell has a capacity of 60 mAh g
at 6 C, over 6,000 cycles with Coulombic efficiency ∼ 99%. Raman spectroscopy shows two different intercalation processes involving chloroaluminate anions at the two discharging plateaus, while C-Cl bonding on the surface, or edges of natural graphite, is found using X-ray absorption spectroscopy. Finally, theoretical calculations are employed to investigate the intercalation behaviour of choloraluminate anions in the graphite electrode.
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