Ultra-Rapid Electrocatalytic H2O2 Fabrication over Mono-Species and High-Density Polypyrrolic-N Sites.

Electrocatalytic hydrogen peroxide (H2O2) production via two-electron oxygen reduction reaction (2e--ORR) features energy-saving and eco-friendly characteristics, making it a promising alternative to the anthraquinone oxidation process. However, the common existence of numerous 2e--ORR-inactive sites/species on electrocatalysts tends to catalyze side reactions, especially under low potentials, which compromises energy efficiency and limits H2O2 yield. Addressing this, a high surface density of mono-species pyrrolic nitrogen configurations is formed over a polypyrrole@carbon nanotube composite. Thermodynamic and kinetic calculation and experimental investigation collaboratively confirm that these densely distributed and highly selective active sites effectively promote high-rate 2e--ORR electrocatalysis and inhibit side reactions over a wide potential range. Consequently, an ultra-high and stable H2O2 yield of up to 67.9/51.2 mol g-1 h-1 has been achieved on this material at a current density of 200/120 mA cm-1, corresponding Faradaic efficiency of 72.8/91.5%. A maximum H2O2 concentration of 13.47 g L-1 can be accumulated at a current density of 80 mA cm-1 with satisfactory stability. The strategy of surface active site densification thus provides a promising and universal avenue toward designing highly active and efficient electrocatalysts for 2e--ORR as well as a series of other similar electrochemical processes.

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.

Dual Active Sites with Charge-asymmetry in Organic Semiconductors Promoting C-C Coupling for Highly Efficient CO2 Photoreduction to Ethanol.

Selective CO2 photoreduction into high-energy-density and high-value-added C2 products is an ideal strategy to achieve carbon neutrality and energy shortage, but it is still highly challenging due to the large energy barrier of the C-C coupling step and severe exciton annihilation in photocatalysts. Herein, strong and localized charge polarization is successfully induced on the surface of melon-based organic semiconductors by creating dual active sites with a large charge asymmetry. Confirmed by multiscale characterization and theoretical simulations, such asymmetric charge distribution, originated from the oxygen dopants and nitrogen vacancies over melon-based organic semiconductors, reduces exciton binding energy and boosts exciton dissociation. The as-formed charge polarization sites not only donate electrons to CO2 molecules but also accelerate the coupling of asymmetric *CO*CO intermediates for CO2 photoreduction into ethanol by lowering the energy barrier of this process. Consequently, an exceptionally high selectivity of up to 97% for C2H5OH and C2H5OH yield of 0.80 mmol g-1 h-1 have been achieved on this dual active sites organic semiconductor. This work, with its potential applicability to a variety of non-metal multi-site catalysts, represents a versatile strategy for the development of advanced catalysts tailored for CO2 photoreduction reactions.

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.

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.

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.

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.

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.

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 novel nomogram for predicting the risk of persistent hyperparathyroidism after kidney transplantation.

PURPOSE: Persistent hyperparathyroidism (PTHPT) in kidney transplant recipients is associated with bone loss, graft dysfunction and cardiovascular mortality. There is no clear consensus on the management of PTHPT. Accurate risk prediction of the disease is needed to support individualized treatment decisions. We aim to develop a useful predictive model to provide early intervention for hyperparathyroidism in these patients. METHODS: We retrospectively analyzed 263 kidney transplantations in the urology department of China-Japan Friendship Hospital from January 2018 to December 2022. The overall cohort was randomly assigned 70% of the patients to the training cohort and 30% to the validation cohort. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for PTHPT and to construct the predictive model. This model was assessed regarding discrimination, consistency, and clinical benefit. RESULTS: The occurrence of PTHPT was 25.9% (68 out of 263 patients) in this study. Dialysis duration, postoperative 3-month intact parathyroid hormone (iPTH), 3-month corrected calcium (cCa), and 3-month phosphorus (P) are independent risk factors for the development of PTHPT. The nomogram showed good discrimination with the area under the curve (AUC) value of 0.926 in the training cohort and 0.903 in the validation cohort. The calibration curve and decision curve also showed that the model was well-evaluated. CONCLUSION: We developed a validated nomogram model to predict PTHPT after kidney transplantation. This can help the clinic prevent and control PTHPT early and improve patients' prognosis.

Nanomaterials: leading immunogenic cell death-based cancer therapies.

The field of oncology has transformed in recent years, with treatments shifting from traditional surgical resection and radiation therapy to more diverse and customized approaches, one of which is immunotherapy. ICD (immunogenic cell death) belongs to a class of regulatory cell death modalities that reactivate the immune response by facilitating the interaction between apoptotic cells and immune cells and releasing specific signaling molecules, and DAMPs (damage-associated molecular patterns). The inducers of ICD can elevate the expression of specific proteins to optimize the TME (tumor microenvironment). The use of nanotechnology has shown its unique potential. Nanomaterials, due to their tunability, targeting, and biocompatibility, have become powerful tools for drug delivery, immunomodulators, etc., and have shown significant efficacy in clinical trials. In particular, these nanomaterials can effectively activate the ICD, trigger a potent anti-tumor immune response, and maintain long-term tumor suppression. Different types of nanomaterials, such as biological cell membrane-modified nanoparticles, self-assembled nanostructures, metallic nanoparticles, mesoporous materials, and hydrogels, play their respective roles in ICD induction due to their unique structures and mechanisms of action. Therefore, this review will explore the latest advances in the application of these common nanomaterials in tumor ICD induction and discuss how they can provide new strategies and tools for cancer therapy. By gaining a deeper understanding of the mechanism of action of these nanomaterials, researchers can develop more precise and effective therapeutic approaches to improve the prognosis and quality of life of cancer patients. Moreover, these strategies hold the promise to overcome resistance to conventional therapies, minimize side effects, and lead to more personalized treatment regimens, ultimately benefiting cancer treatment.

Extrachromosomal circular DNA orchestrates genome heterogeneity in urothelial bladder carcinoma.

Rationale: Extrachromosomal circular DNA is a hallmark of cancer, but its role in shaping the genome heterogeneity of urothelial bladder carcinoma (UBC) remains poorly understood. Here, we comprehensively analyzed the features of extrachromosomal circular DNA in 80 UBC patients. Methods: We performed whole-genome/exome sequencing (WGS/WES), Circle-Seq, single-molecule real-time (SMRT) long-read sequencing of circular DNA, and RNA sequencing (RNA-Seq) on 80 pairs of tumor and AT samples. We used our newly developed circular DNA analysis software, Circle-Map++ to detect small extrachromosomal circular DNA from Circle-Seq data. Results: We observed a high load and significant heterogeneity of extrachromosomal circular DNAs in UBC, including numerous single-locus and complex chimeric circular DNAs originating from different chromosomes. This includes highly chimeric circular DNAs carrying seven oncogenes and circles from nine chromosomes. We also found that large tumor-specific extrachromosomal circular DNAs could influence genome-wide gene expression, and are detectable in time-matched urinary sediments. Additionally, we found that the extrachromosomal circular DNA correlates with hypermutation, copy number variation, oncogene amplification, and clinical outcome. Conclusions: Overall, our study provides a comprehensive extrachromosomal circular DNA map of UBC, along with valuable data resources and bioinformatics tools for future cancer and extrachromosomal circular DNA research.

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.

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.

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.

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.

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.

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.

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.

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.