Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

Blue light inactivation technology, particularly at the 405 nm wavelength, has demonstrated distinct and multifaceted mechanisms of action against both Gram-positive and Gram-negative bacteria, offering a promising alternative to conventional antibiotic therapies. For Gram-positive pathogens such as Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus (MRSA), the bactericidal effects are primarily mediated by endogenous porphyrins (e.g., protoporphyrin III, coproporphyrin III, and uroporphyrin III), which exhibit strong absorption peaks between 400-430 nm. Upon irradiation, these porphyrins are photoexcited to generate cytotoxic reactive oxygen species (ROS), including singlet oxygen, hydroxyl radicals, and superoxide anions, which collectively induce oxidative damage to cellular components. Early studies by Endarko et al. revealed that (405±5) nm blue light at 185 J/cm² effectively inactivated L. monocytogenes without exogenous photosensitizers, supporting the hypothesis of intrinsic photosensitizer involvement. Subsequent work by Masson-Meyers et al. demonstrated that 405 nm light at 121 J/cm² suppressed MRSA growth by activating endogenous porphyrins, leading to ROS accumulation. Kim et al. further elucidated that ROS generated under 405 nm irradiation directly interact with unsaturated fatty acids in bacterial membranes, initiating lipid peroxidation. This process disrupts membrane fluidity, compromises structural integrity, and impairs membrane-bound proteins, ultimately causing cell death. In contrast, Gram-negative bacteria such as Salmonella, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa, and Acinetobacter baumannii exhibit more complex inactivation pathways. While endogenous porphyrins remain central to ROS generation, studies reveal additional photodynamic contributors, including flavins (e.g., riboflavin) and bacterial pigments. For instance, H. pylori naturally accumulates protoporphyrin and coproporphyrin mixtures, enabling efficient 405 nm light-mediated inactivation without antibiotic resistance concerns. Kim et al. demonstrated that 405 nm light at 288 J/cm² inactivates Salmonella by inducing genomic DNA oxidation (e.g., 8-hydroxy-deoxyguanosine formation) and disrupting membrane functions, particularly efflux pumps and glucose uptake systems. Huang et al. highlighted the enhanced efficacy of pulsed 405 nm light over continuous irradiation for E. coli, attributing this to increased membrane damage and optimized ROS generation through frequency-dependent photodynamic effects. Environmental factors such as temperature, pH, and osmotic stress further modulate susceptibility, sublethal stress conditions (e.g., high salinity or acidic environments) weaken bacterial membranes, rendering cells more vulnerable to subsequent ROS-mediated damage. The 405 nm blue light inactivates drug-resistant Pseudomonas aeruginosa through endogenous porphyrins, pyocyanin, and pyoverdine, with the inactivation efficacy influenced by bacterial growth phase and culture medium composition. Intriguingly, repeated 405 nm exposure (20 cycles) failed to induce resistance in A. baumannii, with transient tolerance linked to transient overexpression of antioxidant enzymes (e.g., superoxide dismutase) or stress-response genes (e.g., oxyR). For Gram-positive bacteria, porphyrin abundance dictates sensitivity, whereas in Gram-negative species, membrane architecture and accessory pigments modulate outcomes. Critically, ROS-mediated damage is nonspecific, targeting DNA, proteins, and lipids simultaneously, thereby minimizing resistance evolution. The 405 nm blue light technology, as a non-chemical sterilization method, shows promise in medical and food industries. It enhances infection control through photodynamic therapy and disinfection, synergizing with red light for anti-inflammatory treatments (e.g., acne). In food processing, it effectively inactivates pathogens (e.g., E. coli, S. aureus) without altering food quality. Despite efficacy against multidrug-resistant A. baumannii, challenges include device standardization, limited penetration in complex materials, and optimization of photosensitizers/light parameters. Interdisciplinary research is needed to address these limitations and scale applications in healthcare, food safety, and environmental decontamination.

Esophageal squamous cell carcinoma (ESCC) poses a significant global health challenge, necessitating early detection, timely diagnosis, and prompt treatment to improve patient outcomes. Endoscopic examination plays a pivotal role in this regard. However, despite the availability of various endoscopic techniques, certain limitations can result in missed or misdiagnosed ESCCs. Currently, artificial intelligence (AI)-assisted endoscopic diagnosis has made significant strides in addressing these limitations and improving the diagnosis of ESCC and precancerous lesions. In this review, we provide an overview of the current state of AI applications for endoscopic diagnosis of ESCC and precancerous lesions in aspects including lesion characterization, margin delineation, invasion depth estimation, and microvascular subtype classification. Furthermore, we offer insights into the future direction of this field, highlighting potential advancements that can lead to more accurate diagnoses and ultimately better prognoses for patients.
Humans ; Artificial Intelligence ; Esophageal Squamous Cell Carcinoma/diagnosis* ; Esophageal Neoplasms/diagnosis* ; Precancerous Conditions/diagnosis*

Objective: To evaluate the application value of a digital technology-based multiparameter vital signs monitoring system in perioperative comprehensive full-cycle surveillance. Methods: A comprehensive multidimensional vital signs monitoring system was developed through the integration of medical-grade wireless wearable devices, incorporating patch-type ambulatory electrocardiographic monitor, continuous glucose monitoring sensor, pulse oximeter, wireless digital thermometer, smart wristband, and bioelectrical impedance analyzer. This system facilitates continuous real-time acquisition of multiple physiological parameters including electrocardiogram, blood glucose, oxygen saturation, body temperature, physical activity, and body composition indices. The acquired data were systematically integrated and analyzed through a four-level digital architecture consisting of nurse mobile interfaces, bedside patient terminals, centralized ward monitoring displays, and hospital management information systems. One patient with gastric cancer complicated by diabetes mellitus was selected for full-cycle digital monitoring from preoperative evaluation to hospital discharge. The technical performance of the monitoring system was assessed in terms of data acquisition continuity and timeliness of abnormal event alerts. Results: The monitoring system effectively identified early postoperative abnormalities, such as decreased oxygen saturation and blood glucose fluctuations, providing timely guidance for clinical intervention. The built-in algorithm enabled visualization of perioperative stress levels through heart rate variability indices and continuous glucose monitoring data. The patient demonstrated good compliance with early postoperative mobilization, and the satisfaction score for monitoring management was 4 points based on the Likert 5-point scale. Conclusions: The multiparameter vital signs monitoring system enhanced the precision of perioperative management through continuous and dynamic physiological status assessment. Its modular design aligns with the principles of enhanced recovery after surgery, offering a novel technological solution for intelligent perioperative management.
Humans ; Stomach Neoplasms/physiopathology* ; Vital Signs ; Monitoring, Physiologic/instrumentation* ; Diabetes Mellitus ; Wearable Electronic Devices ; Perioperative Period

Coronavirus-related diseases pose a significant challenge to the global health system. Given the diversity of coronaviruses and the unpredictable nature of disease outbreaks, the traditional "one bug, one drug" paradigm struggles to address the growing number of emerging crises. Therefore, there is an urgent need for therapeutic agents with broad-spectrum anti-coronavirus activity. Here, we provide evidence that ATV006, an anti-SARS-CoV-2 nucleoside analog targeting RNA-dependent RNA polymerase (RdRp), has broad antiviral activity against human and animal coronaviruses. Using mouse hepatitis virus (MHV) and human coronavirus NL63 (HCoV-NL63) as a model, we show that ATV006 has potent prophylactic and therapeutic activity against murine coronavirus infection in vivo. Remarkably, ATV006 successfully inhibits viral replication in mice even when administered 96 h after infection. Due to its oral bioavailability and potency against multiple coronaviruses, ATV006 has the potential to become a useful antiviral agent against SARS-CoV-2 and other circulating and emerging coronaviruses in humans and animals.

Drug development remains a critical issue in the field of biomedicine. With the rapid advancement of information technologies such as artificial intelligence (AI) and the advent of the big data era, AI-assisted drug development has become a new trend, particularly in predicting drug-target associations. To address the challenge of drug-target prediction, AI-driven models have emerged as powerful tools, offering innovative solutions by effectively extracting features from complex biological data, accurately modeling molecular interactions, and precisely predicting potential drug-target outcomes. Traditional machine learning (ML), network-based, and advanced deep learning architectures such as convolutional neural networks (CNNs), graph convolutional networks (GCNs), and transformers play a pivotal role. This review systematically compiles and evaluates AI algorithms for drug- and drug combination-target predictions, highlighting their theoretical frameworks, strengths, and limitations. CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions. GCNs provide deep insights into molecular interactions via relational data, whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences. Network-based models offer a systematic perspective by integrating diverse data sources, and traditional ML efficiently handles large datasets to improve overall predictive accuracy. Collectively, these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy. This review summarizes the application of AI in drug development, particularly in drug-target prediction, and offers recommendations on models and algorithms for researchers engaged in biomedical research. It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Ethanol (EtOH) is a common trigger for gastric mucosal diseases, and mitigating oxidative stress is essential for attenuating gastric mucosal damage. Capsaicin (CAP) has been identified as a potential agent to counteract oxidative damage in the gastric mucosa; however, its precise mechanism remains unclear. This study demonstrates that CAP alleviates EtOH-induced gastric mucosal injuries through two primary pathways: by suppressing the chemokine receptor 4 (CCR4)/Src/p47phox axis, thereby reducing oxidative stress, and by inhibiting the phosphorylation and nuclear translocation of nuclear factor-κB p65 (NF-κB) p65, resulting in diminished inflammatory responses. These findings elucidate the mechanistic pathways of CAP and provide a theoretical foundation for its potential therapeutic application in the treatment of gastric mucosal injuries.
Ethanol/toxicity* ; Animals ; Gastric Mucosa/metabolism* ; Signal Transduction/drug effects* ; Oxidative Stress/drug effects* ; Capsaicin/pharmacology* ; Male ; NADPH Oxidases/genetics* ; Mice ; Humans ; src-Family Kinases/genetics*

Chemotherapy resistance plays a pivotal role in the prognosis and therapeutic failure of patients with colorectal cancer(CRC).Cisplatin(DDP)-resistant cells exhibit an inherent ability to evade the toxic chemotherapeutic drug effects which are characterized by the activation of slow-cycle programs and DNA repair.Among the elements that lead to DDP resistance,O6-methylguanine(O6-MG)-DNA-meth-yltransferase(MGMT),a DNA-repair enzyme,performs a quintessential role.In this study,we clarify the significant involvement of MGMT in conferring DDP resistance in CRC,elucidating the underlying mechanism of the regulatory actions of MGMT.A notable upregulation of MGMT in DDP-resistant cancer cells was found in our study,and MGMT repression amplifies the sensitivity of these cells to DDP treatment in vitro and in vivo.Conversely,in cancer cells,MGMT overexpression abolishes their sensi-tivity to DDP treatment.Mechanistically,the interaction between MGMT and cyclin dependent kinase 1(CDK1)inducing slow-cycling cells is attainted via the promotion of ubiquitination degradation of CDK1.Meanwhile,to achieve nonhomologous end joining,MGMT interacts with XRCC6 to resist chemotherapy drugs.Our transcriptome data from samples of 88 patients with CRC suggest that MGMT expression is co-related with the Wnt signaling pathway activation,and several Wnt inhibitors can repress drug-resistant cells.In summary,our results point out that MGMT is a potential therapeutic target and predictive marker of chemoresistance in CRC.

Nanozyme is novel nanoparticle with enzyme-like activity, which can be classified into peroxidase-like nanozyme, catalase-like nanozyme, superoxide dismutase-like nanozyme, oxidase-like nanozyme and hydrolase-like nanozyme according to the type of reaction they catalyze. Since researchers first discovered Fe₃O₄ nanoparticles with peroxidase-like activity in 2007, a variety of nanoparticles have been successively found to have catalytic activity and applied in bioassays, inflammation control, antioxidant damage and tumor therapy, playing a key role in disease diagnosis and treatment. We summarize the use of nanozymes with different classes of enzymatic activity in the diagnosis and treatment of diseases and describe the main factors influencing nanozyme activity. A Mn-based peroxidase-like nanozyme that induces the reduction of glutathione in tumors to produce glutathione disulfide and Mn²⁺, which induces the production of reative oxygen species (ROS) in tumor cells by breaking down H₂O₂ in physiological media through Fenton-like action, thereby inhibiting tumor cell growth. To address the limitation of tumor tissue hypoxia during photodynamic tumor therapy, the effect of photodynamic therapy is significantly enhanced by using hydrogen peroxide nanozymes to catalyze the production of oxygen from H₂O₂. In pathological states, where excess superoxide radicals are produced in the body, superoxide dismutase-like nanozymes are able to selectively regulate intracellular ROS levels, thereby protecting normal cells and slowing down the degradation of cellular function. Based on this principle, an engineered nanosponge has been designed to rapidly scavenge free radicals and deliver oxygen in time to save nerve cells before thrombolysis. Starvation therapy, in which glucose oxidase catalyzes the hydrolysis of glucose to gluconic acid and hydrogen peroxide in cancer cells with the involvement of oxygen, attenuates glycolysis and the production of intermediate metabolites such as nucleotides, lipids and amino acids, was used to synthesize an oxidase-like nanozyme that achieved effective inhibition of tumor growth. Furthermore, by fine-tuning the Lewis acidity of the metal cluster to improve the intrinsic activity of the hydrolase nanozyme and providing a shortened ligand length to increase the density of its active site, a hydrolase-like nanozyme was successfully synthesized that is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds and even biofilms with high efficiency in hydrolyzing the substrate. All these effects depend on the size, morphology, composition, surface modification and environmental media of the nanozyme, which are important aspects to consider in order to improve the catalytic efficiency of the nanozyme and have important implications for the development of nanozyme. Although some progress has been made in the research of nanozymes in disease treatment and diagnosis, there are still some problems, for example, the catalytic rate of nanozymes is still difficult to reach the level of natural enzymes in vivo, and the toxic effects of some heavy metal nanozymes material itself. Therefore, the construction of nanozyme systems with multiple functions, good biocompatibility and high targeting efficiency, and their large-scale application in diagnosis and treatment is still an urgent problem to be solved. (1) To improve the selectivity and specificity of nanozymes. By using antibody coupling, the nanoparticles are able to specifically bind to antigens that are overexpressed in certain cancer cells. It also significantly improves cellular internalization through antigen-mediated endocytosis and enhances the enrichment of nanozymes in target tissues, thereby improving targeting during tumor therapy. Some exogenous stimuli such as laser and ultrasound are used as triggers to control the activation of nanozymes and achieve specific activation of nanozyme. (2) To explore more practical and safer nanozymes and their catalytic mechanisms: biocompatible, clinically proven material molecules can be used for the synthesis of nanoparticles. (3) To solve the problem of its standardization and promote the large-scale clinical application of nanozymes in biomonitoring. Thus, it can go out of the laboratory and face the market to serve human health in more fields, which is one of the future trends of nanozyme development.