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Gliomas are the most common primary brain malignancies. Accurate and robust tumor segmentation and prediction of patients' overall survival are important for diagnosis, treatment planning and risk factor identification. Here we present a deep learning-based framework for brain tumor segmentation and survival prediction in glioma, using multimodal MRI scans. For tumor segmentation, we use ensembles of three different 3D CNN architectures for robust performance through a majority rule. This approach can effectively reduce model bias and boost performance. For survival prediction, we extract 4,524 radiomic features from segmented tumor regions, then, a decision tree and cross validation are used to select potent features. Finally, a random forest model is trained to predict the overall survival of patients. The 2018 MICCAI Multimodal Brain Tumor Segmentation Challenge (BraTS), ranks our method at 2nd and 5th place out of 60+ participating teams for survival prediction tasks and segmentation tasks respectively, achieving a promising 61.0% accuracy on the classification of short-survivors, mid-survivors and long-survivors.

Group‐10 transition metal dichalcogenides (TMDs) with distinct optical and tunable electrical properties have exhibited great potential for various optoelectronic applications. Herein, a self‐powered photodetector is developed with broadband response ranging from deep ultraviolet to near‐infrared by combining FA1−xCsxPbI3 perovskite with PdSe2 layer, a newly discovered TMDs material. Optoelectronic characterization reveals that the as‐assembled PdSe2/perovskite Schottky junction is sensitive to light illumination ranging from 200 to 1550 nm, with the highest sensitivity centered at ≈800 nm. The device also shows a large on/off ratio of ≈104, a high responsivity (R) of 313 mA W−1, a decent specific detectivity (D*) of ≈1013 Jones, and a rapid response speed of 3.5/4 µs. These figures of merit are comparable with or much better than most of the previously reported perovskite detectors. In addition, the PdSe2/perovskite device exhibits obvious sensitivity to polarized light, with a polarization sensitivity of 6.04. Finally, the PdSe2/perovskite detector can readily record five “P,” “O,” “L,” “Y,” and “U” images sequentially produced by 808 nm. These results suggest that the present PdSe2/perovskite Schottky junction photodetectors may be useful for assembly of optoelectronic system applications in near future. A large‐area, highly polarization‐sensitive and broadband photodetector based on multilayered PdSe2/perovskite device is demonstrated. From optoelectronic characterization, the device achieves an impressive specific detectivity of ≈1013 Jones, a polarization sensitivity as high as 6.04, and a fast response speed of 3.5/4 µs. Further study reveals that the present device is potentially important for image sensor applications.

Building extraction from remote sensing (RS) images is a fundamental task for geospatial applications, aiming to obtain morphology, location, and other information about buildings from RS images, which is significant for geographic monitoring and construction of human activity areas. In recent years, deep learning (DL) technology has made remarkable progress and breakthroughs in the field of RS and also become a central and state-of-the-art method for building extraction. This paper provides an overview over the developed DL-based building extraction methods from RS images. Firstly, we describe the DL technologies of this field as well as the loss function over semantic segmentation. Next, a description of important publicly available datasets and evaluation metrics directly related to the problem follows. Then, the main DL methods are reviewed, highlighting contributions and significance in the field. After that, comparative results on several publicly available datasets are given for the described methods, following up with a discussion. Finally, we point out a set of promising future works and draw our conclusions about building extraction based on DL techniques.

Sjögren's syndrome is an autoimmune disease characterised by dry eyes and mouth, systemic features, and reduced quality of life. There are no disease-modifying treatments. A new biologic, ianalumab (VAY736), with two modes of suppressing B cells, has previously shown preliminary efficacy. This dose-finding trial aimed to assess the safety and efficacy of different subcutaneous doses of ianalumab in patients with moderate to severe primary Sjögren's syndrome. VAY736A2201 was a randomised, parallel, double-blind, placebo-controlled, phase 2b dose-finding study done in 56 centres in 19 countries. Patients aged 18–75 years with primary Sjögren's syndrome with moderate to severe disease activity (European Alliance of Associations for Rheumatology [EULAR] Sjögren's Syndrome Disease Activity Index [ESSDAI] score ≥6) and symptom severity (EULAR Sjögren's Syndrome Patient Reported Index score ≥5) were eligible. Participants were randomly assigned (1:1:1:1) to receive subcutaneous placebo or ianalumab (5 mg, 50 mg, or 300 mg) every 4 weeks for 24 weeks using a secure, online randomisation system. Randomisation was stratified by the ESSDAI score at baseline (≥10 or <10). Study personnel and patients were masked to treatment assignment. The primary outcome was the change in ESSDAI score from baseline to 24 weeks in all randomly assigned patients. Dose-related change in disease activity (ESSDAI) from baseline at week 24 was assessed by multiple comparison procedure with modelling analysis. Safety was measured in all patients who received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, NCT02962895. Between June 27, 2017, and Dec 06, 2018, 293 patients were screened, 190 of whom were randomly assigned (placebo n=49, ianalumab 5 mg n=47, ianalumab 50 mg n=47, ianalumab 300 mg n=47). Statistically significant dose-responses were seen for overall disease activity (ESSDAI score) in four of the five dose-response models tested (p<0·025 in four models, p=0·060 in one model). The ESSDAI score decreased from baseline in all ianalumab groups, with the maximal ESSDAI score change from baseline observed in the ianalumab 300 mg group: placebo-adjusted least-squares mean change from baseline −1·92 points (95% CI −4·15 to 0·32; p=0·092). There were four serious adverse events in three patients considered treatment-related (pneumonia [n=1] and gastroenteritis [n=1] in the placebo group; appendicitis plus tubo-ovarian abscess in the same patient in the ianalumab 50 mg group). The study met its primary objective, showing a dose-related decrease in disease activity as measured by ESSDAI at week 24. Overall, ianalumab was well tolerated and safe, with no increase in infections. To our knowledge, this is the first large, randomised, controlled trial in primary Sjögren's syndrome that met its primary endpoint, and its results mean there is potential for more studies of this mechanism in the future. Novartis.

Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb–herb or herb–drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals’ effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

HighlightsN-doped graphene-coated structure and mesoporous nano-sheet can efficiently boost active sites and stability for hydrogen and oxygen evolution reaction.NiCo@C-NiCoMoO/NF exhibits low overpotentials for HER (266 mV) and OER (390 mV) at ± 1000 mA cm−2.For water electrolysis, it can hold at 1000 mA cm−2 for 43 h in 6.0 M KOH + 60 °C condition.Developing highly effective and stable non-noble metal-based bifunctional catalyst working at high current density is an urgent issue for water electrolysis (WE). Herein, we prepare the N-doped graphene-decorated NiCo alloy coupled with mesoporous NiCoMoO nano-sheet grown on 3D nickel foam (NiCo@C-NiCoMoO/NF) for water splitting. NiCo@C-NiCoMoO/NF exhibits outstanding activity with low overpotentials for hydrogen and oxygen evolution reaction (HER: 39/266 mV; OER: 260/390 mV) at ± 10 and ± 1000 mA cm−2. More importantly, in 6.0 M KOH solution at 60 °C for WE, it only requires 1.90 V to reach 1000 mA cm−2 and shows excellent stability for 43 h, exhibiting the potential for actual application. The good performance can be assigned to N-doped graphene-decorated NiCo alloy and mesoporous NiCoMoO nano-sheet, which not only increase the intrinsic activity and expose abundant catalytic activity sites, but also enhance its chemical and mechanical stability. This work thus could provide a promising material for industrial hydrogen production.

Ferroptosis is a nonapoptotic form of cell death characterized by lipid peroxidation and intracellular iron accumulation. OA is a prevalent joint disease, and as OA progresses, inflammation or iron overload can induce ferroptosis in chondrocytes. However, research on genes that play important roles in this process remains insufficient. In this study, we identified the ferroptosis-related gene SAT1 by analyzing OA-associated GEO datasets. For in vivo experiments, we induced an OA mouse model by transecting the medial meniscus ligament. In vitro, we analyzed the biological functions of SAT1 in ATDC5 cells using Cell Counting Kit-8 (CCK-8), trypan blue staining, Western blot, and detection of ferroptosis-related indicators. Additionally, we explored the mechanisms underlying SAT1's role in OA progression through immunoblotting, ubiquitination, and acetylation immunoprecipitation experiments. Bioinformatics analysis revealed a close association between OA and ferroptosis. Our experimental results showed that overexpression of SAT1 effectively induced ferroptosis in ATDC5 cells. Mechanistically, SAT1 promoted p53 stability by downregulating TRIM33, which inhibits p53 acetylation. By suppressing TRIM33 expression, SAT1 enhanced p53 acetylation and stability, thereby increasing ferroptosis and exacerbating OA progression. In summary, our data indicate that SAT1 is a potential key gene in OA, revealing the crucial role of the SAT1-TRIM33-p53 axis in OA pathogenesis. This axis promotes ferroptosis by enhancing p53 acetylation, suggesting that targeting SAT1 may represent a novel therapeutic strategy for improving OA.

HighlightsThree-phase heterojunction can adjust the ∆G of H/O-intermediates to boost catalytic activity.At ± 1000 mA cm−2, Ni/MoO2@CN exhibits low hydrogen/oxygen evolution reaction overpotentials (267/420 mV).Ni/MoO2@CN used as bifunctional electrodes can work at 1000 mA cm−2 for 330 h in 6.0 M KOH + 60 °C condition.Constructing heterojunction is an effective strategy to develop high-performance non-precious-metal-based catalysts for electrochemical water splitting (WS). Herein, we design and prepare an N-doped-carbon-encapsulated Ni/MoO2 nano-needle with three-phase heterojunction (Ni/MoO2@CN) for accelerating the WS under industrial alkaline condition. Density functional theory calculations reveal that the electrons are redistributed at the three-phase heterojunction interface, which optimizes the adsorption energy of H- and O-containing intermediates to obtain the best ΔGH* for hydrogen evolution reaction (HER) and decrease the ΔG value of rate-determining step for oxygen evolution reaction (OER), thus enhancing the HER/OER catalytic activity. Electrochemical results confirm that Ni/MoO2@CN exhibits good activity for HER (ƞ-10 = 33 mV, ƞ-1000 = 267 mV) and OER (ƞ10 = 250 mV, ƞ1000 = 420 mV). It shows a low potential of 1.86 V at 1000 mA cm−2 for WS in 6.0 M KOH solution at 60 °C and can steadily operate for 330 h. This good HER/OER performance can be attributed to the three-phase heterojunction with high intrinsic activity and the self-supporting nano-needle with more active sites, faster mass diffusion, and bubbles release. This work provides a unique idea for designing high efficiency catalytic materials for WS.

Nanoporous metals and nanoporous metal oxide-based materials are representative type of porous and nanosized structure materials. They have many excellent performances (e.g., unique pore structure, large clear surface area and high electrical conductivity) to be prodigiously promising potentials, for a variety of significant applications (e.g., energy storage, sensing and catalysis). Therefore, this review summarized the recent advances in the development of nanoporous metals/metal oxide-based materials, with special emphasis on superior electrochemical applications: supercapacitors, lithium ion batteries, sensing, electrocatalysis and photocatalysis. The significant and representative studies in each area are comprehensively reviewed and discussed as a reference for researchers working in related areas. We also outline the key challenges and future opportunities in this exciting field.