ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

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.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

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.

Background With economic development and globalization, shift work has become prevalent across industries. Its relationship with type 2 diabetes mellitus (T2DM) attracts increasing attention. Objective To thoroughly explore the relationship between shift work and T2DM, and analyze the impacts of specific shift patterns on T2DM, so as to provide a basis for formulating reasonable shift schedules. Methods We conducted a 1:2 matched case-control study among adults (20-60 years) who ordered occupational health examinations at the Wuxi No.8 People's Hospital from November to December 2023. The case group comprised 200 T2DM patients, while the controls were 400 age-stratified matched non-diabetic individuals. General demographic characteristics, behavioral habits, medical history, and shift work exposure data (including shift patterns, frequency, and length of service) 5 years prior to diagnosis were collected through standardized questionnaires. Logistic regression adjusted for selected confounders was employed to evaluate the association between shift work and T2DM. Results The logistic regression analysis demonstrated that shift work was associated with an increased risk of T2DM. After adjusting for confounding factors, shift workers had a 3.55 times higher risk of being diagnosed T2DM compared to non-shift workers (OR=3.55, 95%CI: 1.026, 12.263). The risk varied across different shift patterns, and the three-shift two-rotation system showed the highest risk (OR=4.17, 95%CI: 1.921, 9.035), followed by the two-shift system (OR=2.94, 95%CI: 2.016, 4.281) and four-shift three-rotation system (OR=2.66, 95%CI: 1.611, 6.093). Workers with more than 3 monthly shift days had a 2.74-fold increased risk (95%CI: 1.658, 4.512) compared to non-shift workers. Additionally, working more than 8 h daily (OR=1.74, 95%CI: 1.185, 2.562) and having more than 20 years of service (OR=2.51, 95%CI: 1.581, 3.976) were both significantly associated with a higher T2DM risk. The trend tests revealed that each incremental increase in monthly shift days and length of service elevated T2DM risk by 2.61 times (95%CI: 1.813, 3.765) and 1.49 times (95%CI: 1.147, 1.931), respectively (P<0.05). Conclusion Shift work is an independent risk factor for T2DM, with three-shift two-rotation system posing the highest risk. Shift frequency, daily working hours, and length of service are all significant factors affecting the risk of T2DM. These findings support industry-specific shift policy reform and targeted glucose monitoring and health interventions are recommended for workers engaged in high-risk shift patterns (e.g., three-shift two-rotation system, frequent shifts) and those with prolonged shift work history (>20 years).

ObjectiveTo analyze the adverse reactions associated with the clinical use of Banxia （Rhizoma Pinelliae）- Wutou （Aconitum） in the same formula， with the aim of providing a reference for the safety of their clinical application. MethodsLiterature on the clinical application of antagonistic herbs "Banxia-Wutou" used in the same formula， published from January 1st， 2014， to June 30th， 2023， was retrieved from databases including CNKI， VIP， Wanfang， SinoMed， PubMed， Cochrane Library， and Embase. A database was established， and information related to adverse reactions was extracted， including descriptions， classifications， specific manifestations， management and outcomes， patients' primary diseases （western medicine diseases and traditional Chinese medicine diagnoses and syndromes）， and medication information （dosage， ratio， administration routes， and dosage forms）. ResultsA total of 79 researches simultaneously used antagonistic herbs Banxia-Wutou in the same formula and reported associated advers reactions. Gastrointestinal adverse reactions were the most common， with 8 studies reporting management of adverse reactions and 3 studies reporting improvement with no intervention. Among the 11 researches， the adverse reaction relieved to extant， while other 69 researches didn't report the managment of adverse reaction and its prognosis. For the primary disease in western medicine system， chronic bronchitis and chronic obstructive pulmonary disease （COPD） were most common， while gastric pain was the most common symptom in traditional Chinese medicine with spleen and kidney deficiency and spleen stomach cold deficiency being the most frequent syndromes. The most common Banxia dosage was 10 g， while for the Wutou， Fuzi （Radix Aconiti Lateralis Praeparata） was predominant with the highest dose at 15 g. The most frequent herbal combination was Banxia-fuzi， with a 1∶1 ratio. The main administration route was oral， and the primary dosage form was decoction. ConclusionGastrointestinal adverse reactions are the most common in the clinical use of Banxia-Wutou antagonistic herb combinations. Research on the safety of "Banxia-Wutou" combinations should focus on respiratory system diseases and spleen-stomach related conditions.

OBJECTIVES: To evaluate the clinical value of CD4⁺ cell percentage (CD4⁺%) and NK cell percentage (NK%) in predicting treatment outcomes in children with aplastic anemia (AA), providing a reference for precise diagnosis and treatment. METHODS: This retrospective study analyzed the clinical data of AA children treated with cyclosporine A at the First Affiliated Hospital of Xinjiang Medical University from January 2019 to April 2024. The study involved 48 AA children as the observation group and 50 children undergoing medical check-ups during the same period as the control group. Lymphocyte subset data were collected from both groups to analyze differences and their relationship with treatment efficacy. Based on hematological responses, the observation group was divided into an effective group of 18 patients (HR group, including complete and partial remission) and an ineffective group of 30 patients (NHR group, including non-remission). RESULTS: Univariate analysis showed that NK% in the observation group was significantly lower than that in the control group (P<0.05). The observation group was followed up for 3 months. The HR group had a lower CD4⁺% than the NHR group (P=0.018) and a higher NK% than the NHR group (P=0.029). Multivariate logistic regression analysis indicated that a high CD4⁺% was a risk factor for poor treatment efficacy (OR=1.062), whereas a high NK% was a protective factor (OR=0.820). The area under the curve for the prediction of HR in pediatric AA by combining CD4⁺% and NK% was 0.812. CONCLUSIONS A higher CD4⁺% at diagnosis is a predictor of poor treatment response, whereas a higher NK% is associated with better outcomes.
Humans ; Anemia, Aplastic/blood* ; Male ; Female ; Killer Cells, Natural ; Child ; Retrospective Studies ; Child, Preschool ; Prognosis ; Adolescent ; CD4-Positive T-Lymphocytes ; Infant

OBJECTIVES: To investigate the causal relationship between Helicobacter pylori (Hp) infection and immune thrombocytopenia (ITP) using Mendelian randomization (MR), as well as the association between Hp infection and chronic ITP (cITP) through a clinical study. METHODS: The datasets from genome-wide association studies were used to select the single nucleotide polymorphism loci significantly associated with Hp infection as genetic instrumental variables. The MR analysis model was used to investigate the causal relationship between ITP and Hp infection. A retrospective analysis was conducted on the medical data of 316 children with newly diagnosed ITP at the First Affiliated Hospital of Xinjiang Medical University from January 2020 to December 2023. The children were followed up for 1 year, and a multivariate logistic regression analysis was used to investigate the risk factors for cITP. RESULTS: The inverse variance weighted analysis revealed that Hp infection was significantly associated with an increased risk of ITP (OR=1.280, 95%CI: 1.098-1.492, P=0.002). There was no heterogeneity or pleiotropy in this MR study (P>0.05), and the model was stable. The "leave-one-out" sensitivity analysis verified the reliability of the results. The multivariate logistic regression analysis demonstrated that Hp infection was an independent risk factor for progression to cITP (OR=7.916, 95%CI: 3.327-18.832, P<0.001). CONCLUSIONS Hp infection is a risk factor for the onset of ITP and is an independent risk factor for cITP in children.
Humans ; Helicobacter Infections/complications* ; Purpura, Thrombocytopenic, Idiopathic/etiology* ; Child ; Male ; Female ; Helicobacter pylori ; Prognosis ; Child, Preschool ; Logistic Models ; Retrospective Studies ; Risk Factors ; Polymorphism, Single Nucleotide ; Adolescent ; Infant

Colorectal cancer (CRC) poses a severe global health challenge with high incidence and mortality rates. USP37 has been identified as the bona fide deubiquitinase of SND1, playing a critical role in stabilizing SND1, thereby augmenting its oncogenic potential. The interaction between USP37 and SND1 was confirmed through extensive proteomics, ubiquitinomics, and interactomics, underscoring their synergistic effects on CRC proliferation and metastasis. Additionally, CDK1 has emerged as a pivotal regulator of USP37, phosphorylating it at threonine 631 rather than serine 628, enhancing its deubiquitinase activity, and consequently stabilizing SND1 to drive CRC malignancy further. Histological analyses of human CRC samples linked the upregulation of CDK1 and USP37 with increased SND1 levels and poor patient prognosis. High-throughput virtual screening and subsequent experimental validation identified Dacarbazine as a pharmacological inhibitor of USP37, and its inhibition disrupted SND1 stability, hindering CRC cell proliferation and metastasis. This study reveals a novel and promising molecular mechanism driving CRC progression through the CDK1-USP37-SND1 axis, highlighting the clinical importance of targeting this pathway to improve patient outcomes.

Although a single nucleotide polymorphism for N-acetyltransferase 10 (NAT10) has been identified in patients with early-onset stroke, the role of NAT10 in ischemic injury and the related underlying mechanisms remains elusive. Here, we provide evidence that NAT10, the only known RNA N4-acetylcytidine (ac4C) modification "writer", is increased in the damaged cortex of patients with acute ischemic stroke and the peri-infarct cortex of mice subjected to photothrombotic (PT) stroke. Pharmacological inhibition of NAT10 with remodelin on Days 3-7 post-stroke or astrocytic depletion of NAT10 via targeted virus attenuates ischemia-induced infarction and improves functional recovery in PT mice. Mechanistically, NAT10 enhances ac4C acetylation of the inflammatory cytokine tissue inhibitor of metalloproteinase 1 (Timp1) mRNA transcript, which increases TIMP1 expression and results in the accumulation of microtubule-associated protein 1 light chain 3 (LC3) and progression of astrocyte autophagy. These findings demonstrate that NAT10 regulates astrocyte autophagy by targeting Timp1 ac4C after stroke. This study highlights the critical role of ac4C in the regulation of astrocyte autophagy and proposes a promising strategy to improve post-stroke outcomes via NAT10 inhibition.