Flexo-/Piezoelectric Polarization Boosting Exciton Dissociation in Curved Two-Dimensional Carbon Nitride Photocatalyst.

Two-dimensional (2D) carbon nitride (CN) materials have received tremendous attention as photocatalysts for clean energy and environmental treatment. However, the photocatalytic efficiency of CN is constrained by the high exciton binding energy and sluggish charge kinetics due to weak dielectric screening, impeding the overall process. Herein, localized flexo-/piezoelectric polarization is introduced via strain engineering, boosting exciton dissociation and promoting charge separation to enhance the multielectron photocatalytic process. Consequently, the exciton binding energy of polarized CN is reduced from 52 to 34 meV, and the hydrogen evolution yield increased by 2.9 times compared to that of the pristine CN. For other photocatalytic reactions (e.g., H2O2 production), the polarized CN also maintained a 2.1-fold increase compared to the pristine CN. This strategy of inducing localized polarization via strain engineering provides new insights for boosting photocatalytic reactions involving electrons.

MSA-YOLO: A Remote Sensing Object Detection Model Based on Multi-Scale Strip Attention.

Remote sensing image object detection holds significant research value in resources and the environment. Nevertheless, complex background information and considerable size differences between objects in remote sensing images make it challenging. This paper proposes an efficient remote sensing image object detection model (MSA-YOLO) to improve detection performance. First, we propose a Multi-Scale Strip Convolution Attention Mechanism (MSCAM), which can reduce the introduction of background noise and fuse multi-scale features to enhance the focus of the model on foreground objects of various sizes. Second, we introduce the lightweight convolution module GSConv and propose an improved feature fusion layer, which makes the model more lightweight while improving detection accuracy. Finally, we propose the Wise-Focal CIoU loss function, which can reweight different samples to balance the contribution of different samples to the loss function, thereby improving the regression effect. Experimental results show that on the remote sensing image public datasets DIOR and HRRSD, the performance of our proposed MSA-YOLO model is significantly better than other existing methods.

Facilitating two-electron oxygen reduction with pyrrolic nitrogen sites for electrochemical hydrogen peroxide production.

Electrocatalytic hydrogen peroxide (H2O2) production via the two-electron oxygen reduction reaction is a promising alternative to the energy-intensive and high-pollution anthraquinone oxidation process. However, developing advanced electrocatalysts with high H2O2 yield, selectivity, and durability is still challenging, because of the limited quantity and easy passivation of active sites on typical metal-containing catalysts, especially for the state-of-the-art single-atom ones. To address this, we report a graphene/mesoporous carbon composite for high-rate and high-efficiency 2e- oxygen reduction catalysis. The coordination of pyrrolic-N sites -modulates the adsorption configuration of the *OOH species to provide a kinetically favorable pathway for H2O2 production. Consequently, the H2O2 yield approaches 30 mol g-1 h-1 with a Faradaic efficiency of 80% and excellent durability, yielding a high H2O2 concentration of 7.2 g L-1. This strategy of manipulating the adsorption configuration of reactants with multiple non-metal active sites provides a strategy to design efficient and durable metal-free electrocatalyst for 2e- oxygen reduction.

Efficient-Lightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images.

The most significant technical challenges of current aerial image object-detection tasks are the extremely low accuracy for detecting small objects that are densely distributed within a scene and the lack of semantic information. Moreover, existing detectors with large parameter scales are unsuitable for aerial image object-detection scenarios oriented toward low-end GPUs. To address this technical challenge, we propose efficient-lightweight You Only Look Once (EL-YOLO), an innovative model that overcomes the limitations of existing detectors and low-end GPU orientation. EL-YOLO surpasses the baseline models in three key areas. Firstly, we design and scrutinize three model architectures to intensify the model's focus on small objects and identify the most effective network structure. Secondly, we design efficient spatial pyramid pooling (ESPP) to augment the representation of small-object features in aerial images. Lastly, we introduce the alpha-complete intersection over union (α-CIoU) loss function to tackle the imbalance between positive and negative samples in aerial images. Our proposed EL-YOLO method demonstrates a strong generalization and robustness for the small-object detection problem in aerial images. The experimental results show that, with the model parameters maintained below 10 M while the input image size was unified at 640 × 640 pixels, the APS of the EL-YOLOv5 reached 10.8% and 10.7% and enhanced the APs by 1.9% and 2.2% compared to YOLOv5 on two challenging aerial image datasets, DIOR and VisDrone, respectively.

Robust Carbon Nitride Homojunction Photoelectrode for Solar-Driven Water Splitting.

Achieving intimate particle-to-particle and particle-to-substrate contacts is the first priority for fabricating high-quality photoelectrodes to ensure sufficient visible light absorption and efficient charge separation/transport. To achieve this goal, a seeding strategy is designed to construct a robust carbon nitride (CN) homojunction photoelectrode, in which vaporized precursors are condensed into a compact seeding layer at low temperatures, inducing the further deposition of the top layer. This optimized photoelectrode displays an excellent photocurrent density of 320 µA cm-2 in 0.1 M NaOH electrolyte at 1.23 VRHE (V vs reversible hydrogen electrode) under AM 1.5G illumination, with H2 and O2 evolution rates of 2.98 and 1.47 µmol h-1 cm-2, respectively. Characterizations show that both the robust contact and the homojunction of the double-layered CN film contribute to enhanced photoelectrochemical performance. This work may provide a new strategy for the design of high-performing CN photoelectrodes.

Gate-Modulated High-Response Field-Effect Transistor-Type Gas Sensor Based on the MoS2/Metal-Organic Framework Heterostructure.

The high surface-to-volume ratio and decent material properties of two-dimensional (2D) transition metal dichalcogenides (TMDs) make them advantageous as an active channel in field-effect transistor (FET)-type gas sensing devices. However, most existing TMD gas sensors are based on a two-terminal resistance-type structure and suffer from low responsivity and slow response, which has urged materials optimization as well as device engineering. Metal-organic frameworks (MOFs) have a large number of ordered binding sites in the pores that can specifically bind to gas molecules and can be decorated on TMD surfaces to enhance gas sensing capabilities. In this work, we successfully realize the FET-type gas sensor with MoS2-MOF as the channel. The fabricated gas sensor exhibits enhanced NH3 sensing performance (22.475 times higher in responsivity) as compared to the device with a bare MoS2 channel. In addition, the FET-type gas sensor geometry enables effective tuning of sensitivity through electrical gating based on the modulation over the channel carrier concentration. Furthermore, the dependence of responsivity on the MoS2 thickness is investigated as well to achieve an in-depth understanding of the electrical modulation mechanism of the MOF-decorated MoS2 gas sensors. The demonstrated results can pave an attractive pathway toward the realization of advanced high-response and tunable TMD-based gas sensing devices.

Engineered bispecific antibodies targeting the interleukin-6 and -8 receptors potently inhibit cancer cell migration and tumor metastasis.

Simultaneous inhibition of interleukin-6 (IL-6) and interleukin-8 (IL-8) signaling diminishes cancer cell migration, and combination therapy has recently been shown to synergistically reduce metastatic burden in a preclinical model of triple-negative breast cancer. Here, we have engineered two novel bispecific antibodies that target the IL-6 and IL-8 receptors to concurrently block the signaling activity of both ligands. We demonstrate that a first-in-class bispecific antibody design has promising therapeutic potential, with enhanced selectivity and potency compared with monoclonal antibody and small-molecule drug combinations in both cellular and animal models of metastatic triple-negative breast cancer. Mechanistic characterization revealed that our engineered bispecific antibodies have no impact on cell viability, but profoundly reduce the migratory potential of cancer cells; hence they constitute a true anti-metastatic treatment. Moreover, we demonstrate that our antibodies can be readily combined with standard-of-care anti-proliferative drugs to develop effective anti-cancer regimens. Collectively, our work establishes an innovative metastasis-focused direction for cancer drug development.

Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study.

BACKGROUND: A large training dataset with high-quality annotations is necessary for building an accurate and generalisable deep learning system, which can be difficult and expensive to prepare in medical applications. We present a novel deep-learning-based system, requiring no annotator but weak annotation from a diagnosis report, for accurate and generalisable performance in detecting multiple head disorders from CT scans, including ischaemia, haemorrhage, tumours, and skull fractures. METHODS: Our system was developed on 104 597 head CT scans from the Chinese PLA General Hospital, with associated textual diagnosis reports. Without expert annotation, we used keyword matching on the reports to automatically generate disorder labels for each scan. The labels were inaccurate because of the unreliable annotator-free strategy and inexact because of scan-level annotation. We proposed RoLo, a novel weakly supervised learning algorithm, with a noise-tolerant mechanism and a multi-instance learning strategy to address these issues. RoLo was tested on retrospective (2357 scans from the Chinese PLA General Hospital), prospective (650 scans from the Chinese PLA General Hospital), cross-centre (1525 scans from the Brain Hospital of Hunan Province), cross-equipment (1484 scans from the Chinese PLA General Hospital), and cross-nation (CQ500 public dataset from India) test datasets. Four radiologists were tested on the prospective test dataset before and after viewing system recommendations to assess whether the system could improve diagnostic performance. FINDINGS: The area under the receiver operating characteristic curve for detecting the four disorder types was 0·976 (95% CI 0·976-0·976) for retrospective, 0·975 (0·974-0·976) for prospective, 0·965 (0·964-0·966) for cross-centre, and 0·971 (0·971-0·972) for cross-equipment test datasets, and 0·964 (0·964-0·966) for CQ500 (with only haemorrhage and fracture). The system achieved similar performance to four radiologists and helped to improve sensitivity and specificity by 0·109 (95% CI 0·086-0·131) and 0·022 (0·017-0·026), respectively. INTERPRETATION: Without expert annotated data, our system achieved accurate and generalisable performance for head disorder detection. The system improved the diagnostic performance of radiologists. Because of its accuracy and generalisability, our computer-aided diganostic system could be used in clinical practice to improve the accuracy and efficiency of radiologists in different hospitals. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

LAG: Layered Objects to Generate Better Anchors for Object Detection in Aerial Images.

You Only Look Once (YOLO) series detectors are suitable for aerial image object detection because of their excellent real-time ability and performance. Their high performance depends heavily on the anchor generated by clustering the training set. However, the effectiveness of the general Anchor Generation algorithm is limited by the unique data distribution of the aerial image dataset. The divergence in the distribution of the number of objects with different sizes can cause the anchors to overfit some objects or be assigned to suboptimal layers because anchors of each layer are generated uniformly and affected by the overall data distribution. In this paper, we are inspired by experiments under different anchors settings and proposed the Layered Anchor Generation (LAG) algorithm. In the LAG, objects are layered by their diagonals, and then anchors of each layer are generated by analyzing the diagonals and aspect ratio of objects of the corresponding layer. In this way, anchors of each layer can better match the detection range of each layer. Experiment results showed that our algorithm is of good generality that significantly uprises the performance of You Only Look Once version 3 (YOLOv3), You Only Look Once version 5 (YOLOv5), You Only Learn One Representation (YOLOR), and Cascade Regions with CNN features (Cascade R-CNN) on the Vision Meets Drone (VisDrone) dataset and the object DetectIon in Optical Remote sensing images (DIOR) dataset, and these improvements are cost-free.

Power-Efficient Gas-Sensing and Synaptic Diodes Based on Lateral Pentacene/a-IGZO PN Junctions.

Function convergence of gas sensing and neuromorphic computing is attracting much research attention due to the promising potential in electronic olfactory, artificial intelligence, and internet of everything systems. However, the current neuromorphic gas-sensing systems are either realized via integration of gas detectors and neuromorphic devices or operating with three-terminal synaptic transistors at high voltages, leading to a rather high system complexity or power consumption. Herein, gas-modulated synaptic diodes with lateral structures are developed to converge sensing, processing, and storage functions into a single device. The lateral synaptic diode is based on a p-n junction of an organic semiconductor (OSC) and amorphous In-Ga-Zn-O, in which the upper OSC layer can directly interact with the gas molecules in the atmosphere. Typical synaptic behaviors triggered by ammonia, including inhibitory postsynaptic current and paired-pulse depression, are successfully demonstrated. Meanwhile, a low power consumption of 6.3 pJ per synaptic event has been achieved, which benefits from the simple device structure, the decent chemosensitivity of the OSC, and the low operation voltage. A simulated ammonia analysis in human exhaled breath is further conducted to explore the practical application of the synaptic diode. Therefore, this work provides a gas-modulated synaptic diode for circuit-compact and power-efficient artificial olfactory systems.

Integrative Analysis of MALT1 as a Potential Therapeutic Target for Prostate Cancer and its Immunological Role in Pan-Cancer.

Background: Mucosa-associated lymphoma antigen 1 (MALT1) is an oncogene in subsets of diffuse large B cell lymphoma (DLBCL) and mucosa-associated lymphoid tissue type (MALT) lymphoma. However, the role of MALT1 across cancers, especially in prostate cancer is still poorly understood. Methods: Here, we used several public datasets to evaluate MALT1 expression. Then, PCa cell lines and nude mice were used to investigate the cellular functions in vitro and in vivo. Microarray data were downloaded from The Cancer Genome Atlas and MALT1 was subjected to gene set enrichment analysis (GSEA) and Gene Ontology (GO) analysis to identify the biological functions and relevant pathways. Additionally, the correlations between MALT1 expression and mismatch repair (MMR) gene mutation, immune checkpoint gene expression, tumor mutational burden (TMB), and microsatellite instability (MSI) were investigated by Pearson correlation analysis. Moreover, the correlation between MALT1 expression and tumor immune infiltration was analyzed by the Tumor Immune Evaluation Resource (TIMER) database. Results: MALT1 overexpression was significantly correlated with MMR gene mutation levels and crucially promoted proliferation and colony genesis while reducing PCa cell apoptosis levels in vivo and in vitro. MALT1 expression showed strong correlations with immune checkpoint genes, TMB, and MSI in most cancers. The GO analysis indicated that MALT1-coexpressed genes were involved in heterotypic cell-cell adhesion, actin filament-based movement regulation, and action potential regulation. GSEA revealed that MALT1 expression was associated with several signaling pathways, including the NF-κB signaling, Wnt/ß-catenin and TGF-ß signaling pathways, in PCa. Additionally, MALT1 expression was significantly correlated with the infiltration of immune cells, including B cells, CD8+ T cells, dendritic cells and macrophages, and negatively correlated with CD4+ cell infiltration in PCa. Conclusion: MALT1 expression is higher in pancancer samples than in normal tissues. MALT1 promoted proliferation and colony genesis while reducing PCa cell apoptosis levels, and MALT1 suppression could inhibit xenograft tumor establishment in nude mice. Furthermore, MALT1 expression is closely related to the occurrence and development of multiple tumors in multiple ways. Therefore, MALT1 may be an emerging therapeutic target for a variety of cancers especially PCa.

Assessment of Three-Dimensional Reconstruction in Percutaneous Nephrolithotomy for Complex Renal Calculi Treatment.

Introduction: Three-dimensional (3D) reconstruction is a novel imaging technique widely used to improve surgical operations. Some studies have identified its role in Urology for percutaneous nephrolithotomy (PCNL). Objective: To explore the potential benefits of 3D reconstruction technology in PCNL for complex renal calculi treatment. Methods: A retrospective study involving 139 patients with complex kidney stones who underwent PCNL was conducted between September 30, 2018, to September 30, 2019. Group A patients (72) underwent the 3D reconstruction technique before PCNL, while group B (67) did not. The operation time, the duration of the hospital stay, the puncture accuracy, the decrease in hemoglobin concentration, the stone clearance rate, and the postoperative complications were noted and compared between the two groups. Results: The initial stone clearance rates 2 weeks after PCNL were 81.9 and 64.2% in groups A and B, respectively (P < 0.05). The first-time puncture success rates were 87.5 and 47.8 % in groups A and B, respectively (P < 0.05). Group A had a shorter operation time than group B (62 vs. 79 min, P < 0.05). Besides, the 3D reconstructive technique-assisted patients (91.7%) had no or mild complications, compared with (74.6%) group B patients. There was no significant difference in hemoglobin decline and hospital stay between the two groups. Conclusions: The 3D reconstruction technology is an effective adjunct to PCNL in the complex renal calculi treatment.

A systematic review and meta-analysis of randomized controlled trials of "on-demand" use of tramadol vs "on-demand" use of paroxetine in the management of patients with premature ejaculation.

AIM: To evaluate the effect of "on-demand" use of tramadol vs "on-demand" use of paroxetine in the management of patients with premature ejaculation (PE). MATERIALS AND METHODS: A systematic search of PubMed, EMBASE, Cochrane Library databases and original references of the included articles was performed. PRISMA checklist was followed. The Cochrane Handbook was used to evaluate the quality of the included research. RESULTS: A total of seven articles including 663 patients were studied. The results indicated that patients who received on-demand therapy of tramadol or paroxetine showed significant improvement compared with those treated with placebo, as assessed by intravaginal ejaculatory latency time (IELT) (P < .00001 and P = .02, respectively) and sexual satisfaction score (P < .00001 and P < .00001, respectively). Furthermore, Patients who were treated with on-demand tramadol had a better effect than those treated with on-demand paroxetine in respect of IELT (P = .01) and sexual satisfaction score (P = .03). With regard to safety, the most common adverse event for the tramadol group was sleep disturbance and the most common adverse event for the paroxetine group was a headache. No serious adverse event was observed in both groups. CONCLUSIONS: Compared with placebo, on-demand therapy of tramadol or paroxetine showed a better improvements in IELT and sexual satisfaction scores. Besides, on-demand tramadol revealed a better effect than on-demand paroxetine for patients with PE, and patients in both groups showed good tolerance.

Clinical application of percutaneous nephrolithotomy in a patient with kyphoscoliosis.

This case report describes the performance of ultrasound-guided percutaneous nephrolithotomy in a 50-year-old woman who had scoliosis with kyphosis and a history of tuberculosis of the lumbar spine. The operation was performed with the patient under general anesthesia and in the prone position. Residual stones were found in the right lower kidney calyx postoperatively, resulting in a second-phase surgery using the same approach 2 weeks later. All stones were successfully removed during the second surgery. No complications occurred in either operation, and the patient recovered well. This study suggests that ultrasound-guided percutaneous nephrolithotomy is a safe and effective approach in treating renal calculi in patients with scoliosis.

Effect of upregulation of DD3 on early detection and prognosis in prostate cancer.

BACKGROUND: Expression of prostate cancer antigen 3 (PCA3 OR DD3) in the blood has been reported to be significantly higher in prostate cancer (PCa) than in benign prostate hyperplasia (BPH). To confirm whether DD3 expression is significantly different between PCa and BPH tissues, DD3 expression was tested in the blood both preoperatively and postoperatively and in the paired tissues of PCa patients. METHODS: Expression levels of DD3 mRNA in the blood of patients who did not undergo surgery (PCa, n=102; BPH, n=53), those underwent surgery (preoperative, n=35; postoperative, n=35), and in PCa tissue specimens (tumor, n=41; adjacent normal, n=21) were determined by real-time quantitative PCR. Sensitivity and specificity for DD3 in PCa patients were validated by receiver operating characteristic (ROC) curve analysis. RESULTS: Our data suggest that expression level of DD3 in blood samples was significantly higher in PCa patients than in BPH patients (P=0.005). Expression of DD3 mRNA was also significantly elevated in PCa tissues compared with adjacent normal tissues (P=0.013). The increase in DD3 expression in PCa patients was further validated using a dataset from The Cancer Genome Atlas (n=549). Postoperative DD3 expression decreased following surgical intervention (P<0.001). Moreover, low DD3 expression was associated with improved overall survival (OS). Using gene set enrichment analysis, DD3 expression was correlated with specific PCa target genes including carcinogenesis-related and cancer proliferation-related genes. CONCLUSIONS: This study demonstrated that expression of DD3 was upregulated in blood and PCa tumor tissues and was associated with prognosis. The oncogenic role of DD3 was further validated in the TCGA database, indicating that DD3 is a potential therapeutic target for PCa. Furthermore, this study suggests that DD3 expression could be considered as a prognostic biomarker for PCa.

Facile synthesis of macroporous zwitterionic hydrogels templated from graphene oxide-stabilized aqueous foams.

HYPOTHESIS: Conventional strategies based on emulsion templates to produce porous materials are complicated and not environmental-friendly, thus inspiring a facile and novel approach via polymerization of aqueous foams. Graphene oxide (GO) has been proved as a very efficient Pickering stabilizer for oil-in-water or water-in-oil emulsions, however, it has rarely (if any) been used to stabilize aqueous foams. It is of high interest to prepare GO-stabilized aqueous foams and subsequent porous hydrogels after polymerization of the aqueous phase. EXPERIMENTS: GO was slightly hydrophobized with cetyltrimethylammonium bromide (CTAB) and then used to stabilize aqueous foams containing a water-soluble monomer, N-(3-Sulfopropyl)-N-methacroyloxyethyl-N,N-dimethylammonium betaine (SBMA). After polymerizing the aqueous phase, macroporous zwitterionic hydrogels (PSBMA) were prepared. The pore morphology of macroporous PSBMA were observed by a field-emission scanning electron microscope. FINDINGS: The wettability of modified GO by both water and air, indeed has a significant influence on the air bubble size and size distribution as well as the pore size of resulting macroporous PSBMA hydrogels. The pore size and pore interconnectivity of the hydrogels can be tailored by simply varying the surface property and concentration of GO in water. PSBMA hydrogels exhibit a pronounced uptake of aqueous NaCl solutions and efficient separation of oil-in-water emulsions.

Ultralight Silica Foams with a Hierarchical Pore Structure via a Surfactant-Free High Internal Phase Emulsion Process.

An ultralight silica aerogel is among the most versatile materials available for technical applications; however, it remains a huge challenge to reduce its manufacturing cost. Here, we report on a simple approach for the preparation of silica foam monoliths with ultrahigh porosity up to 99.5% and specific surface area as high as 755 m2 g-1, which are similar to those of an aerogel. Our strategy is based on the effective stabilization of water-in-oil high internal phase emulsions by a hydrophobic silica precursor polymer, hyperbranched polyethoxysiloxane because of its hydrolysis-induced amphiphilicity. After conversion of this precursor polymer to silica, the emulsions are solidified without significant volume shrinkage. Thus, mechanically strong macroporous silica monoliths are obtained after removal of its liquid components. According to nitrogen sorption data, the resulting silica foams exhibit a high specific surface area and a foam skeleton consisting of both micropores (<2 nm) and mesopores (2-50 nm). The pore size, porosity, and surface area can be regulated by varying pH as well as the concentration of the silica precursor in the oil phase. In addition, the pore size can be adjusted by controlling shear force during emulsification. This work opens a new avenue for producing ultralight porous materials amenable to numerous applications.

A simple and environment-friendly approach for synthesizing macroporous polymers from aqueous foams.

We propose a facile and environment-friendly approach for the preparation of macroporous polyacrylamide (PAM) via thermal-initiated polymerization of aqueous foams that are stabilized by surface-modified silica nanoparticles. Cetyltrimethylammonium bromide (CTAB) is used to delicately adjust the surface amphiphilicity of silica to stabilize aqueous foams. The air bubble size and size distribution is affected by the wettability of silica particles, solid content and air volume fraction in the foams. The morphology of macroporous polymers is observed by a scanning electron microscope (SEM). The pore and pore throat size can be tailored effectively by varying the silica content and air volume fraction. A high porosity of 83% is achieved when the air volume fraction of the aqueous foam is 65%. PAM hydrogels obtained via polymerizing aqueous foams show pronounced advantage over the ones prepared from oil-in-water (O/W) emulsions in wastewater treatment because of their unique pore structure. This strategy would also be extended to prepare other macroporous polymers with well-defined pore structures.