Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

The study investigated the specific mechanism by which oxocrebanine, the anti-hepatic cancer active ingredient in Stephania hainanensis, inhibits the proliferation of hepatic cancer cells. Firstly, methyl thiazolyl tetrazolium(MTT) assay, 5-bromodeoxyuridine(BrdU) labeling, and colony formation assay were employed to investigate whether oxocrebanine inhibited the proliferation of HepG2 and Hep3B2.1-7 cells. Propidium iodide(PI) staining was used to observe the oxocrebanine-induced apoptosis of HepG2 and Hep3B2.1-7 cells. Western blot was employed to verify whether apoptotic effector proteins, such as cleaved cysteinyl aspartate-specific protease 3(c-caspase-3), poly(ADP-ribose) polymerase 1(PARP1), B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), Bcl-2 homologous killer(Bak), and myeloid cell leukemia-1(Mcl-1) were involved in apoptosis. Secondly, HepG2 cells were simultaneously treated with oxocrebanine and the autophagy inhibitor 3-methyladenine(3-MA), and the changes in the autophagy marker LC3 and autophagy-related proteins [eukaryotic translation initiation factor 4E-binding protein 1(4EBP1), phosphorylated 4EBP1(p-4EBP1), 70-kDa ribosomal protein S6 kinase(P70S6K), and phosphorylated P70S6K(p-P70S6K)] were determined. The results of MTT assay, BrdU labeling, and colony formation assay showed that oxocrebanine inhibited the proliferation of HepG2 and Hep3B2.1-7 cells in a dose-dependent manner. The results of flow cytometry suggested that the apoptosis rate of HepG2 and Hep3B2.1-7 cells increased after treatment with oxocrebanine. Western blot results showed that the protein levels of c-caspase-3, Bax, and Bak were up-regulated and those of PARP1, Bcl-2, and Mcl-1 were down-regulated in the HepG2 cells treated with oxocrebanine. The results indicated that oxocrebanine induced apoptosis, thereby inhibiting the proliferation of hepatic cancer cells. The inhibition of HepG2 cell proliferation by oxocrebanine may be related to the induction of protective autophagy in hepatocellular carcinoma cells. Oxocrebanine still promoted the conversion of LC3-Ⅰ to LC3-Ⅱ, reduced the phosphorylation levels of 4EBP1 and P70S6K, which can be reversed by the autophagy inhibitor 3-MA. It is prompted that oxocrebanine can inhibit the proliferation of hepatic cancer cells by inducing autophagy. In conclusion, oxocrebanine inhibits the proliferation of hepatic cancer cells by inducing apoptosis and autophagy.
Humans ; Apoptosis/drug effects* ; Autophagy/drug effects* ; Cell Proliferation/drug effects* ; Hep G2 Cells ; Liver Neoplasms/genetics* ; Carcinoma, Hepatocellular/genetics* ; Caspase 3/genetics*

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

ObjectiveThe nucleolar protein PES1 (Pescadillo homolog 1) plays critical roles in ribosome biogenesis and cell cycle regulation, yet its involvement in cellular senescence remains poorly understood. This study aimed to comprehensively investigate the functional consequences of PES1 suppression in cellular senescence and elucidate the molecular mechanisms underlying its regulatory role. MethodsInitially, we assessed PES1 expression patterns in two distinct senescence models: replicative senescent mouse embryonic fibroblasts (MEFs) and doxorubicin-induced senescent human hepatocellular carcinoma HepG2 cells. Subsequently, PES1 expression was specifically downregulated using siRNA-mediated knockdown in these cell lines as well as additional relevant cell types. Cellular proliferation and senescence were assessed by EdU incorporation and SA-β-gal staining assays, respectively. The expression of senescence-associated proteins (p53, p21, and Rb) and SASP factors (IL-6, IL-1β, and IL-8) were analyzed by Western blot or qPCR. Furthermore, Northern blot and immunofluorescence were employed to evaluate pre-rRNA processing and nucleolar morphology. ResultsPES1 expression was significantly downregulated in senescent MEFs and HepG2 cells. PES1 knockdown resulted in decreased EdU-positive cells and increased SA‑β‑gal-positive cells, indicating proliferation inhibition and senescence induction. Mechanistically, PES1 suppression activated the p53-p21 pathway without affecting Rb expression, while upregulating IL-6, IL-1β, and IL-8 production. Notably, PES1 depletion impaired pre-rRNA maturation and induced nucleolar stress, as evidenced by aberrant nucleolar morphology. ConclusionOur findings demonstrate that PES1 deficiency triggers nucleolar stress and promotes p53-dependent (but Rb-independent) cellular senescence, highlighting its crucial role in maintaining nucleolar homeostasis and regulating senescence-associated pathways.

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.

Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pre-training.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.

Acute respiratory distress syndrome(ARDS)is a common respiratory emergency,but current clinical treatment remains at the level of symptomatic support and there is a lack of effective targeted treatment measures.Our previous study confirmed that inhalation of hydrogen gas can reduce the acute lung injury of ARDS,but the application of hydrogen has flammable and explosive safety concerns.Drinking hydrogen-rich liquid or inhaling hydrogen gas has been shown to play an important role in scavenging reactive oxygen species and maintaining mitochondrial quality control balance,thus improving ARDS in patients and animal models.Coral calcium hydrogenation(CCH)is a new solid molecular hydrogen carrier prepared from coral calcium(CC).Whether and how CCH affects acute lung injury in ARDS re-mains unstudied.In this study,we observed the therapeutic effect of CCH on lipopolysaccharide(LPS)induced acute lung injury in ARDS mice.The survival rate of mice treated with CCH and hydrogen inhalation was found to be comparable,demonstrating a significant improvement compared to the untreated ARDS model group.CCH treatment significantly reduced pulmonary hemorrhage and edema,and improved pulmonary function and local microcirculation in ARDS mice.CCH promoted mitochon-drial peripheral division in the early course of ARDS by activating mitochondrial thioredoxin 2(Trx2),improved lung mitochondrial dysfunction induced by LPS,and reduced oxidative stress damage.The results indicate that CCH is a highly efficient hydrogen-rich agent that can attenuate acute lung injury of ARDS by improving the mitochondrial function through Trx2 activation.