Naked mesoporous rhodium nanospheres with glutathione depletion and photothermal capabilities for tumor therapy.

Pancreatic and colon cancer are malignant tumors of the digestive system that currently lack effective treatments. In cancer cells, a high level of glutathione (GSH) is indispensable to scavenge excessive reactive oxygen species (ROS) and detoxify xenobiotics, which make it a potential target for cancer therapy. GSH depletion has been proved to improve the therapeutic efficacy of photodynamic therapy. Here, we reported that naked mesoporous rhodium nanospheres (Rh MNs), prepared by soft template redox method, can act as GSH depletion agent and photothermal conversion agent to achieve synergistic therapy respectively. Different from conventional nanoagents, Rh MNs with the characteristics of easy synthesis, simple structure and multiple functions can decrease the GSH level in tumor and depict excellent photothermal ability with a high photothermal conversion efficiency (PTCE) up to 39%. Notably, multiple anti-tumor mechanisms in CT26 and BxPC-3 tumor models, include inhibited anti-apoptosis, DNA replication repair, and GSH synthesis are revealed, and the pancreatic tumor cure rate of the cooperative treatment group is 80%. Collectively, we developed Rh MNs to combine GSH depletion with photothermal therapy for cancer treatment.

Rapid and unbiased enrichment of extracellular vesicles via a meticulously engineered peptide.

Extracellular vesicles (EVs) have garnered significant attention in biomedical applications. However, the rapid, efficient, and unbiased separation of EVs from complex biological fluids remains a challenge due to their heterogeneity and low abundance in biofluids. Herein, we report a novel approach to reconfigure and modify an artificial insertion peptide for the unbiased and rapid isolation of EVs in 20 min with ∼80% recovery in neutral conditions. Moreover, the approach demonstrates exceptional anti-interference capability and achieves a high purity of EVs comparable to standard ultracentrifugation and other methods. Importantly, the isolated EVs could be directly applied for downstream protein and nucleic acid analyses, including proteomics analysis, exome sequencing analysis, as well as the detection of both epidermal growth factor receptor (EGFR) and V-Ki-ras2 Kirsten Rat Sarcoma Viral Oncogene Homologue (KRAS) gene mutation in clinical plasma samples. Our approach offers great possibilities for utilizing EVs in liquid biopsy, as well as in various other biomedical applications.

Stability, Inheritance, Cross-Resistance, and Fitness Cost of Resistance to λ-Cyhalothrin in Cydia pomonella.

Insecticides are commonly utilized in agriculture and forestry for pest control, but their dispersal can pose hazards to humans and environment. Understanding resistance, inheritance patterns, and fitness costs can help manage resistance. A λ-cyhalothrin-resistant population (LCR) of Cydia pomonella, a global pest of pome fruits and walnuts, was obtained through selective insecticide breeding for 15 generations, showing stable moderate resistance (23.85-fold). This population was cross-resistant to deltamethrin (4.26-fold) but not to ß-cypermethrin, chlorantraniliprole, chlorpyrifos, and avermectin. Genetic analysis revealed the resistance was autosomal, incompletely dominant, and controlled by multiple genes. Increased activity of glutathione S-transferases and cytochrome P450 monooxygenases (P450s) played a primary role in resistance, with specific genes up-regulated in LCR, and exhibited significant expression in midgut. LCR also exhibited fitness costs, including delays in development, reduced fecundity, and slower population growth. These findings contribute to understanding λ-cyhalothrin resistance in C. pomonella and can guide resistance management strategies.

Gut microbiota-derived acetate promotes long-term recovery through angiogenesis guided by lymphatic ingrowth in older adults with stroke.

Introduction: Ischemic stroke is a leading cause of morbidity and mortality in older adults. Therefore, in this study, we sought to understand the interplay between the microbiota, gut, and brain in the context of stroke in older adults. Objective: To determine whether gut microbiota from younger individuals promotes recovery through angiogenesis in both elderly stroke patients and aged stroke mice, we explored the changes in gut microbiota and the correlation between short-chain fatty acids (SCFAs) and angiogenesis in the aged stroke population. Then, we altered the gut microbiome in aged mice by transplanting microbiota from younger donors before inducing experimental stroke to explore the mechanism by which gut microbiota-derived SCFAs promote angiogenesis. Methods: Part I: We conducted a single-center, double-blind trial to compare gut microbiota diversity and SCFA levels in fecal samples from older stroke patients with those from younger stroke patients. Additionally, we measured levels of vascular endothelial growth factor (VEGF) and VEGFC levels in plasma to assess their correlation with SCFA levels. Part II: We performed fecal microbiota transplantation (FMT) 3 days before inducing ischemic stroke in aged male mice (16-18) via distal middle cerebral artery occlusion (dMCAO). The FMT was conducted using gut microbiomes from either young donors (2-3 months) or aged donors (16-18 months). Results: In older stroke patients, gut microbiota diversity was significantly reduced compared to that in younger stroke patients. Furthermore, levels of acetate, a bacterially derived SCFA, were lower and positively correlated with angiogenesis markers (VEGF and VEGF-C). In aged stroke mice, transplantation of young microbiota improved stroke outcomes by promoting angiogenesis, which was facilitated by lymphatic ingrowth into the cortex. This protective effect was linked to gut microbiota-derived acetate, which enhanced lymphangiogenesis by replenishing acetyl coenzyme A. Conclusions: (a) Gut microbiota-derived acetate promotes angiogenesis post-stroke and (b) lymphatic ingrowth into the cerebral cortex was observed in post-dMCAO mice. These findings suggest that selectively promoting SCFA-producing bacteria, particularly acetate-producers, could be a promising therapeutic strategy to reduce functional impairments in older stroke subjects.

High-Performance Multicolor Organic Light-Emitting Diodes Based on a Pt(II) Carbene Complex Featuring Hemiligand Interaction.

Utilizing a single organic light-emitting diode (OLED) architecture for multicolor emissions can significantly simplify manufacturing progress and broaden applications. Here, we report on a carbene-based Pt(II) complex, designated as Pt(pyiOppy), which exhibits an unusual dimeric packing mode solely by hemiligand π···π stacking. This feature is distinct from the well-known Pt···Pt or Pt···ligand interactions. The dimer persists in new types of orbital combinations, along with its triplet transition state, which are evidenced for the first time. Pt(pyiOppy), under various doping concentrations in a solid matrix, demonstrates multicolor emissions ranging from green to red, all exhibiting high photoluminescent quantum efficiencies (48-97%). The devices incorporating Pt(pyiOppy) can emit green, yellow, orange, and red lights, covering a CIE coordinate range of (0.28-0.65, 0.61-0.34). All the devices also achieve appreciable maximum external quantum efficiencies (9.4-17.2%) and impressive lifetimes of hundreds of hours (LT70 at 1000 cd/m2). These findings showcase a new type of Pt(II) aggregate enabling well-controlled, multicolor high-performance phosphorescent OLEDs.

Diagnosing skin cancer using social spider optimization (SSO) and error correcting output codes (ECOC) with weighted hamming distance.

Skin cancer is a common disease resulting from genetic defects, and early detection is critical to improve treatment outcomes. Diagnostic programs that use computer aid especially those that use supervised learning are very useful in early diagnosis of skin cancer. This research therefore presents a new approach that integrates optimization methods with supervised learning to improve skin cancer diagnosis using machine vision approach. The presented method is initiated by data pre-processing that involves the removal of unnecessary data. Then, to segment the images, a combination of K-means clustering and social spider optimization technique is employed. The region of interest is then extracted from the segmented image and from this region a convolutional neural network extracts the significant features. To enhance the classification performance as compared with the standard classifiers, this research introduces a new concept of error correcting output codes coupled with a weighted Hamming distance in the group of gamma classifiers. The ability of the proposed approach in segmentation of skin lesions and classifying them was tested using samples from the ISIC-2017 and ISIC-2016 databases. The introduced method obtained state-of-the-art accuracy on both datasets (ISIC-2016: 97.10%, ISIC-2017: 95.17%). In particularly, the accuracy of the introduced approach for both these databases is at least 1.17% higher than the compared methods. This proves the high performance of the suggested method based on the usage of the convolutional neural networks for feature extraction and gamma classifiers with error correcting output codes for classification in skin cancer detection.

DCAF2 is essential for the development of uterine epithelia and mouse fertility.

Introduction: The successful outcome of a pregnancy depends on the proper functioning uterine epithelium. DNA damage binding protein 1 and cullin 4-associated factor 2 (DCAF2), a conserved substrate receptor for the cullin 4-RING E3 ubiquitin ligase (CRL4) complex, is essential for maintaining genome stability by facilitating ubiquitin-mediated degradation of substrates. Methods: To better understand the physiological role of DCAF2 in female reproduction, we conducted a study using mice with conditional knockout (cKO) of DCAF2 in the uterus using the progesterone receptor Cre (Pgr Cre/+) mouse model. Results: Our results showed the cKO mice were completely infertile, despite having ovarian function. The cKO mice exhibited severely thin uteri, demonstrating notable defects in both the uterine epithelium and a lack of glands. In addition, there were impaired proliferation and differentiation of epithelial cells in the cKO mice, ultimately resulting in failed implantation. Moreover, through deciphering the uterine transcriptome of cKO mice, we revealed crucial differentially expressed genes associated with steroid signaling. Further experiments have demonstrated cKO mice exhibit elevated uterine PGR signaling and reduced estrogen receptor signaling, although the levels of progesterone and estrogen remained unaltered. These alterations may contribute to defects in epithelium. Discussion: Overall, our findings highlight a previously unrecognized but indispensable role for DCAF2 in the development of uterine luminal and glandular epithelium by orchestrating PGR and estrogen receptor responses. Its deficiency in the uterus leads to mouse infertility.

Gold Self-Relay Catalysis Enabling Regioselective Bicyclization toward [5]Azahelicenes.

A gold self-relay catalysis driving a double annulation cascade starting from soft electron-biased 1,2-di(o-aminoaryl)alkynes and aldehydes is reported, enabling regioselective access to produce a series of [5]azahelicenes depending on the substitution pattern in generally good yields under mild conditions. This protocol exploits and unifies the π- and σ-Lewis acid capability of gold catalysts, featuring high molecular convergence, broad substrate flexibility, and good functional group compatibility and regioselectivity.

Macrophage activation syndrome in Sepsis: from pathogenesis to clinical management.

BACKGROUND: Sepsis represents a significant global health and hygiene challenge. Excessive activation of macrophages in sepsis can result in certain patients displaying characteristics akin to those observed in Macrophage Activation Syndrome (MAS). MAS represents a grave immune system disorder characterized by persistent and severe inflammation within the body. In the context of sepsis, MAS presents atypically, leading some researchers to refer to it as Macrophage Activation-Like Syndrome (MALS). However, there are currently no effective treatment measures for this situation. The purpose of this article is to explore potential treatment methods for sepsis-associated MALS. OBJECTIVE: The objective of this review is to synthesize the specific pathophysiological mechanisms and treatment strategies of MAS to investigate potential therapeutic approaches for sepsis-associated MALS. METHOD: We searched major databases (including PubMed, Web of Science, and Google Scholar etc.) for literature encompassing macrophage activation syndrome and sepsis up to Mar 2024 and combined with studies found in the reference lists of the included studies. CONCLUSION: We have synthesized the underlying pathophysiological mechanism of MALS in sepsis, and then summarized the diagnostic criteria and the effects of various treatment modalities utilized in patients with MAS or MALS. In both scenarios, heterogeneous treatment responses resulting from identical treatment approaches were observed. The determination of whether the patient is genuinely experiencing MALS significantly impacts the ultimate outcomes of therapeutic efficacy. In order to tackle this concern, additional clinical trials and research endeavors are imperative.

A cross-linguistic review of citation tone production studies: Methodology and recommendations.

The study of citation tones, lexical tones produced in isolation, is one of the first steps towards understanding speech prosody in tone languages. However, methodologies for investigating citation tones vary significantly, often leading to limited comparability of tone inventories, both within and across languages. This paper presents a systematic review of research methods and practices in 136 citation tone studies on 129 tonal language varieties in China, including 99 studies published in Chinese, which are therefore not easily available to an international scientific readership. The review provides an overview of possible analytical decisions along the research pipeline, and unveils considerable variation in data collection, analysis, and reporting conventions, particularly in how f0, the primary acoustic correlate for tone, is operationalised and reported across studies. Key methodological issues are identified, including small sample sizes and inadequate transparency in communicating methodological decisions and procedure. This paper offers a clear road map for citation tone production research and proposes a range of recommendations on speaker sampling, experimental design, acoustic processing techniques, f0 analysis, and result reporting, with the goal of facilitating future tonal research and enhancing resources for underrepresented tonal varieties.

Multifunctional MnGA Nanozymes for the Treatment of Ulcerative Colitis by Reducing Intestinal Inflammation and Regulating the Intestinal Flora.

In ulcerative colitis (UC), the formation of an inflammatory environment is due to the combined effects of excess production of reactive oxygen species (ROS) and reactive nitrogen species (RNS), overproduction of proinflammatory cytokines, and disruption of immune system function. There are many kinds of traditional drugs for the clinical treatment of UC, but long-term drug use can cause toxic side effects and drug resistance and can also reduce patient compliance and other drawbacks. Hence, in light of the clinical challenges associated with UC, including the limitations of existing treatments, intense adverse reactions and the development of resistance to medications, no novel therapeutic agents that offer effective relief and maintain a high level of biosafety are urgently needed. Although many anti-inflammatory nanomedicines have been developed by researchers, the development of efficient and nontoxic nanomedicines is still a major challenge in clinical medicine. Using the natural product gallic acid and the metal compound manganese chloride, a highly effective and nontoxic multifunctional nanoenzyme was developed for the treatment of UC. Nanozymes can effectively eliminate ROS and RNS to reduce the inflammation of intestinal epithelial cells caused by oxidation, facilitate the restoration of the intestinal epithelial barrier through the upregulation of tight junction protein expression, and balance the intestinal microbiota to maintain the stability of the intestinal environment. Using a rodent model designed to mimic UC, we monitored body weight, colon length, the spleen index, and the degree of tissue damage and demonstrated that manganese gallate (MnGA) nanoparticles can reduce intestinal inflammation by clearing ROS and active nitrogen. Intestinal flora sequencing revealed that MnGA nanoparticles could regulate the intestinal flora, promote the growth of beneficial bacteria and decrease the levels of detrimental bacteria within the intestinal tract in a mouse model of UC. Thus, MnGA nanoparticles can maintain the balance of the intestinal flora. This study demonstrated that MnGA nanoparticles are excellent antioxidant and effective anti-inflammatory agents, have good biosafety, and can effectively treat UC.

Lightweight monocular depth estimation using a fusion-improved transformer.

The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transformers as the feature extraction and encoding layers for images, enabling the network to capture both local geometric and global semantic features for depth estimation. First, depth-separable convolution is used to construct a dilated convolution residual module based on a shallow network to improve the shallow CNN feature extraction receptive field. In the transformer, a multidepth separable convolution head transposed attention module is proposed to reduce the computational burden of spatial self-attention. In the feedforward network, a two-step gating mechanism is proposed to improve the nonlinear representation ability of the feedforward network. Finally, the CNN and transformer are integrated to implement a depth estimation network with a local-global context interaction function. Compared with other lightweight models, this model has fewer model parameters and higher estimation accuracy. It also has better generalizability for different outdoor datasets. Additionally, the inference speed can reach 87 FPS, achieving better real-time performance and accounting for both inference speed and estimation accuracy.

DEHP regulates ferritinophagy to promote testicular ferroptosis via suppressing SIRT1/PGC-1α pathway.

To increase elasticity and flexibility, di-2-ethylhexyl phthalate (DEHP) is used in a variety of industrial products, but excessive exposure to it can pose a threat to human health. In epidemiological studies of population exposure to DEHP, attention has been paid to damage to the male reproductive system. However, the toxicological mechanism of DEHP regarding testicular injury is not well understood. We used Western blot analysis, transmission electron microscopy, fluorescence staining, transient transfection and assay kit to detect relevant indicators, and the results were as follows: After DEHP exposure, the expression levels of ACSL4, COX2, TF, FTH1, LC3, AMPK, p-AMPK, ULK1, p-ULK1, serum iron, tissue iron and MDA in the exposure group were significantly increased. The expression levels of GPX4, NCOA4, p62, SIRT1, and PGC-1α, as well as the contents of GSH and ATP, decreased. Electron microscopy showed that more autophagosomes were observed. Our findings suggest that exposure to DEHP induced ferritinophagy and ferroptosis in the testis. In vitro, the promoting effect of ferritinophagy on ferroptosis was verified by applying the autophagy inhibitor (3-MA) and si-NCOA4. Moreover, Mono-(2-ethylhexyl) phthalate (MEHP) inhibited the mitochondrial regulatory protein SIRT1/PGC-1α, leading to mitochondrial dysfunction. Changes in mitochondrial reactive oxygen species (MtROS) and energy over-activated AMPK/ULK1 autophagy pathway, and then promoted ferritinophagy, which increased the sensitivity of TM4 cells to ferroptosis. This research offers a theoretical framework for the prevention and management of DEHP-induced harm.

Ru3@Mo2CO2 MXene single-cluster catalyst for highly efficient N2-to-NH3 conversion.

Single-cluster catalysts (SCCs) representing structurally well-defined metal clusters anchored on support tend to exhibit tunable catalytic performance for complex redox reactions in heterogeneous catalysis. Here we report a theoretical study on an SCC of Ru3@Mo2CO2 MXene for N2-to-NH3 thermal conversion. Our results show that Ru3@Mo2CO2 can effectively activate N2 and promotes its conversion to NH3 through an association mechanism, in which the rate-determining step of NH2* + H* → NH3* has a low energy barrier of 1.29 eV. Notably, with the assistance of Mo2CO2 support, the positively charged Ru3 cluster active site can effectively adsorb and activate N2, leading to 0.74 |e| charge transfer from Ru3@Mo2CO2 to the adsorbed N2. The supported Ru3 also acts as an electron reservoir to regulate the charge transfer for various intermediate steps of ammonia synthesis. Microkinetic analysis shows that the turnover frequency of the N2-to-NH3 conversion on Ru3@Mo2CO2 is as high as 1.45 × 10-2 s-1 site-1 at a selected thermodynamic condition of 48 bar and 700 K, the performance of which even surpasses that of the Ru B5 site and Fe3/θ-Al2O3(010) reported before. Our work provides a theoretical understanding of the high stability and catalytic mechanism of Ru3@Mo2CO2 and guidance for further designing and fabricating MXene-based metal SCCs for ammonia synthesis under mild conditions.

Nicotinamide Mononucleotide: Research Process in Cardiovascular Diseases.

Nicotinamide adenine dinucleotide (NAD+) is an essential metabolite that plays a crucial role in diverse biological processes, including energy metabolism, gene expression, DNA repair, and mitochondrial function. An aberrant NAD+ level mediates the development of cardiovascular dysfunction and diseases. Both in vivo and in vitro studies have demonstrated that nicotinamide mononucleotide (NMN), as a NAD+ precursor, alleviates the development of cardiovascular diseases such as heart failure, atherosclerosis, and myocardial ischemia/reperfusion injury. Importantly, NMN has suggested pharmacological activities mostly through its involvement in NAD+ biosynthesis. Several clinical studies have been conducted to investigate the efficacy and safety of NMN supplementation, indicating its potential role in cardiovascular protection without significant adverse effects. In this review, we systematically summarize the impact of NMN as a nutraceutical and potential therapeutic drug on cardiovascular diseases and emphasize the correlation between NMN supplementation and cardiovascular protection.

Bayesian Landmark-based Shape Analysis of Tumor Pathology Images.

Medical imaging is a form of technology that has revolutionized the medical field over the past decades. Digital pathology imaging, which captures histological details at the cellular level, is rapidly becoming a routine clinical procedure for cancer diagnosis support and treatment planning. Recent developments in deep-learning methods have facilitated tumor region segmentation from pathology images. The traditional shape descriptors that characterize tumor boundary roughness at the anatomical level are no longer suitable. New statistical approaches to model tumor shapes are in urgent need. In this paper, we consider the problem of modeling a tumor boundary as a closed polygonal chain. A Bayesian landmark-based shape analysis model is proposed. The model partitions the polygonal chain into mutually exclusive segments, accounting for boundary roughness. Our Bayesian inference framework provides uncertainty estimations on both the number and locations of landmarks, while outputting metrics that can be used to quantify boundary roughness. The performance of our model is comparable with that of a recently developed landmark detection model for planar elastic curves. In a case study of 143 consecutive patients with stage I to IV lung cancer, we demonstrated the heterogeneity of tumor boundary roughness derived from our model effectively predicted patient prognosis (p-value < 0.001).

Relationship between weight-adjusted-waist index and all-cause and cardiovascular mortality in individuals with type 2 diabetes.

AIM: To investigate the relationship between the weight-adjusted-waist index (WWI) and all-cause mortality as well as cardiovascular mortality in individuals with type 2 diabetes. METHODS: We used data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 and the UK Biobank database. Restricted cubic spline curves and Cox proportional hazards models were employed to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality. RESULTS: In the UK Biobank database, compared with the lowest WWI quartile, the HR for all-cause and cardiovascular death in the highest quartile was 1.846 (95% CI 1.687-2.019) and 2.118 (95% CI 1.783-2.517), respectively, in the fully adjusted model. In the NHANES database, compared with the lowest WWI quartile, the highest quartile had an HR of 1.727 (95% CI 1.378-2.163) for all-cause death and 1.719 (95% CI 1.139-2.595) for cardiovascular death in the fully adjusted model. CONCLUSIONS: Our study indicates that WWI has a long-term synergistic negative impact on all-cause mortality and cardiovascular mortality in individuals with type 2 diabetes. The WWI is an independent predictor of mortality in individuals with type 2 diabetes.

Selenium-enriched yeast regulates aquaporins to alleviate atrazine-induced hepatic ionic homeostasis disturbance in Japanese quails.

Atrazine (ATR), a commonly used herbicide, carries a risk to the health of humans and animals due to its persistence in the environment and accumulation in the body. The main metabolic processes of ATR was occurred in the liver. Therefore, the accumulation of ATR in the body can cause serious hepatic injury. This research aimed to clarify the toxicological effect of ATR and explore the potential protective benefits of selenium-enriched yeast (Yeast-Se) in alleviating liver toxicity induced by ATR. Quails were treated with ATR and Yeast-Se for 28 days. The results indicated that ATR inhibited quail growth and development and caused liver dysfunction. Pathological analysis showed that ATR led to central vein congestion and gallbladder epithelial cells shedding and necrosis. In addition, ATR significantly changed hepatic ion content (Na+, K+, Cl-, Ca2+, Mg2+) and decreased Na+-K+-ATPase and Ca2+/Mg2+-ATPase activities. Notably, supplementary Yeast-Se protects against ATR-induced liver ionic disorder by reversing ATPase activity and increasing ATPase subunits expression. In addition, supplementary Yeast-Se significantly up-regulated the expression of aquaporins (AQPs). In summary, these results indicated that Yeast-Se may regulates AQPs to alleviate ATR-induced ionic homeostasis disturbance in liver.

Artificial intelligence in ovarian cancer drug resistance advanced 3PM approach: subtype classification and prognostic modeling.

Background: Ovarian cancer patients' resistance to first-line treatment posed a significant challenge, with approximately 70% experiencing recurrence and developing strong resistance to first-line chemotherapies like paclitaxel. Objectives: Within the framework of predictive, preventive, and personalized medicine (3PM), this study aimed to use artificial intelligence to find drug resistance characteristics at the single cell, and further construct the classification strategy and deep learning prognostic models based on these resistance traits, which can better facilitate and perform 3PM. Methods: This study employed "Beyondcell," an algorithm capable of predicting cellular drug responses, to calculate the similarity between the expression patterns of 21,937 cells from ovarian cancer samples and the signatures of 5201 drugs to identify drug-resistance cells. Drug resistance features were used to perform 10 multi-omics clustering on the TCGA training set to identify patient subgroups with differential drug responses. Concurrently, a deep learning prognostic model with KAN architecture which had a flexible activation function to better fit the model was constructed for this training set. The constructed patient subtype classifier and prognostic model were evaluated using three external validation sets from GEO: GSE17260, GSE26712, and GSE51088. Results: This study identified that endothelial cells are resistant to paclitaxel, doxorubicin, and docetaxel, suggesting their potential as targets for cellular therapy in ovarian cancer patients. Based on drug resistance features, 10 multi-omics clustering identified four patient subtypes with differential responses to four chemotherapy drugs, in which subtype CS2 showed the highest drug sensitivity to all four drugs. The other subtypes also showed enrichment in different biological pathways and immune infiltration, allowing for targeted treatment based on their characteristics. Besides, this study applied the latest KAN architecture in artificial intelligence to replace the MLP structure in the DeepSurv prognostic model, finally demonstrating robust performance on patients' prognosis prediction. Conclusions: This study, by classifying patients and constructing prognostic models based on resistance characteristics to first-line drugs, has effectively applied multi-omics data into the realm of 3PM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00374-4.

Supercapacitively Liquid-Solid Dual-State Optoelectronics.

Photo-transduction of solid-state optoelectronics occurs in semiconductors or their interfaces. Considering the confined active area and interfacial capacitance of solid-state materials, solid-state optoelectronics faces inherent limitations in photo-transduction, especially for bionic vision, and the performance is lower than that of living systems. For example, a photoreceptor generates pA-level photocurrent when absorbing a single photon. Here, a liquid-solid dual-state phototransistor is demonstrated, in which photo-transduction and modulation take place at the microporous interface between semiconductors and water, mimicking principles of the photoreceptor. When operating in the water, an orderly stacked photo-harvesting covalent organic framework layer generates supercapacitively photogating modulation of the channel conductivity via a dual-state interface, achieving responsivity of 4.6 × 1010 A W-1 and detectivity of 1.62 × 1016 Jones at room temperature, several orders of magnitude higher than other photodetectors. Such bio-inspired dual-state optoelectronics enables high-contrast scotopic neuromorphic imaging with responsivity greater than photoreceptors, holding promise for constructing optoelectronic systems with performance beyond conventional solid-state optoelectronics.