With the rapid advancement of hemodynamic indices and monitoring technologies, their classification methods and application processes have become increasingly complex. Currently, no unified standard hasbeen established, making it difficult to fully meet the clinical requirements for hemodynamic management. To assist in hemodynamic monitoring assessment and therapeutic decision-making in critically ill patients, the Critical Hemodynamic Therapy Collaborative Group, in conjunction with the Critical Ultrasound Study Group, has jointly developed the Standard for the Application of Hemodynamic Monitoring Techniques in Critical Care. The first part of this standard systematically categorizes hemodynamic indicators into flow indicators, pressure and its derivative indicators, and tissue perfusion indicators, while elaborating on the clinical application of each. The second part establishes a standardized clinical implementation pathway for hemodynamic monitoring. It proposes a tiered monitoring strategy-comprising basic, advanced, indication-specific, and special scenario monitoring-tailored to different clinical settings. It emphasizes the central role of critical care ultrasound across all levels of monitoring and establishes hemodynamic assessment standards for organs such as the brain, kidneys, and gastrointestinal tract. This standard aims to provide a unified framework for clinical practice, teaching, training, and research in critical care medicine, thereby promoting standardized development within the discipline.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

The aim of this study was to identify the Salmonella strains isolated from an outbreak of foodborne illness in a seafood buffet restaurant and analyze their pathogenic characteristics.Epidemiological data,fecal samples from patients and chefs,and food/environmental samples from the restaurant were analyzed.Research methods included bacterial culture,serotyping,quadruple fluo-rescence PCR identification,whole-genome sequencing and antibiotic susceptibility testing.The results showed that 4 S.Java strains(serotype 1,4,12∶b∶1,2;ST42)were isolated from two outbreak cases and two sporadic cases.All isolates exhibited similar genomic features,harboring 9 virulence islands and 98 virulence genes.Antimicrobial resistance profiling revealed streptomycin monoresis-tance,mediated by aac(6′)-Iy and aac(6′)-Iaa genes.In conclusion,this event was the first reported outbreak of foodborne illness caused by S.Java in China,indicating that S.Java may be prevalent in the surveyed district.The catering industry should optimize food handling and processing procedures and enhance the surveillance of high risk pathogens.Meanwhile,further studies should ad-dress differential diagnosis and pathogenic mechanism differences between S.Java and S.paratyphi B,which will facilitate evidence-based monitoring in China.

Objective:Observation of the therapeutic effect of Yugu Ju detergent combined with fusidic acid cream on the repair of wounds infected with Staphylococcus aureus,as well as its impact on serum inflammatory markers TNF-α,IL-6,IL-1β,oxidative stress markers MDA,ROS,SOD and Nrf2 levels.Methods:96 patients with skin defects and SA U infection caused by trauma admitted to the hospital from June 2021 to December 2023 were randomly divided into a control group and an observation group.Both groups were treated with debridement,while the control group was treated with external application of fusidic acid cream.The treatment group received external washing with Yugu Ju detergent in addition to the control group.One course of treatment lasted for 7 days,with three consecutive courses of treatment.Observe the wound healing rate,bacterial clearance rate,and changes in TNF-α,IL-6,IL-1β,SOD,MDA,ROS,and Nrf2 before and after treatment to evaluate clinical efficacy and safety.Results:The total clinical effective rate of the observation group after treatment was 93.75％(45/48),while that of the control group was 75％(36/48).The observation group was significantly better than the control group(P＜0.05);The wound healing rate and bacterial clearance rate of the observation group at each time point after treatment were higher than those of the control group(P＜0.05);After treatment,the Nrf2 and SOD values in the observation group were higher than those in the control group,while the TNF-α,IL-6,IL-1β,MDA,and ROS values were lower than those in the control group(P＜0.05).No adverse reactions occurred during the treatment of both groups.Conclusion:The combination of Yugu Ju detergent and Fusidic acid cream can inhibit SA U and promote the healing of infectious wounds,which may be related to the activation of Nrf2 expression to inhibit oxidative stress and inflammatory response.It is safe and effective,and worthy of promotion and application.

Objective To analyze the prevalence and risk factors of underscreening among cervical cancer screening participants in Wuxiang County,Shanxi Province in 2019,providing evidence-based support for optimizing mobilization strategies.Methods Data from cervical cancer screening programs conducted between 2019 and 2024 in Wuxiang County were retrospectively collected.The follow-up screening behaviors of women screened in 2019 were analyzed,and factors associated with underscreening were identified.Results A total of 3759 women underwent cervical cancer screening in 2019.Among them,492 women(13.09％)with abnormal primary screening results requiring follow-up in 12 months,yet only 43(8.74％)completed;2154 women(57.30％)with negative liquid-based cytology testing(LCT)results needed re-screening after 3 years,701(32.54％)completed;1113 women(29.61％)with negative HPV/combined results needed re-screening after 5 years,734(65.95％)completed.Overall,2299 women(60.69％)exhibited underscreening.Multivariate analysis showed that underscreening was more likely among community residents than rural residents(OR=2.309,P=0.018),older women(OR=1.065,P＜0.001),those in organized screening compared to opportunistic screening(OR=3.789,P＜0.001),those undergoing LCT(OR=4.607,P＜0.001)or combined screening instead of human papillomavirus testing(OR=3.624,P＜0.001),and those with abnormal screening results(OR=6.859,P＜0.001).Conclusion Substantial proportions of cervical cancer screening participants demonstrate poor adherence to guideline-recommended screening intervals,and particularly need to focus on older women and those with abnormal screening results.Implementation of electronic screening record systems and emphasizing knowledge of periodical screening in health education could enhance compliance with"70％screening coverage"target for cervical cancer prevention.

Objective:To explore the efficacy and safety of sivelestat sodium in patients with acute respiratory distress syndrome (ARDS) in the intensive care unit (ICU).Methods:Sixty patients with ARDS admitted to the ICU of the Fuyang Hospital Affiliated to Anhui Medical University from August 1, 2023 to November 1, 2024 were selected and divided into the control group (conventional treatment, 30 cases) and the sivelestat sodium group (treated with sivelestat sodium in addition to conventional treatment, 30 cases) by the random number table method. The clinical data such as inflammatory factors, blood gas analysis indicators, Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score and Sequential Organ Failure Assessment (SOFA) score of the two groups of patients before treatment and 3 days after treatment were compared. The prognostic indicators such as mechanical ventilation time, ICU stay time, total hospital stay time, 28-day mortality rate and clinical efficacy of the two groups of patients were compared.Results:Before treatment, there were no statistically significant differences in inflammatory factors, blood gas analysis indicators, APACHE Ⅱ score and SOFA score between the two groups of patients (all P>0.05). After 3 days of treatment, the improvement degrees of APACHE Ⅱ score, SOFA score, arterial partial pressure of oxygen (PaO 2), oxygenation index (PaO 2/FiO 2), procalcitonin (PCT), interleukin-6 (IL-6), and C-reactive protein (CRP) in the sivelestat sodium group were all greater than those in the control group. The differences were all statistically significant (all P<0.05); The mechanical ventilation time [(5.31±4.12) d vs (7.17±2.32)d] and ICU stay [(6.31±3.42)d vs (8.93±5.26)d] of patients in the sivelestat sodium group were significantly shorter than those in the control group, and the differences were statistically significant (all P<0.05). There was no statistically significant difference in the 28-day mortality rate between the sivelestat sodium group [20.00%(6/30)] and the control group [43.33%(13/30)] ( P>0.05). The total effective rate of treatment in the sivelestat sodium group was significantly higher than that in the control group [80.00%(24/30) vs 56.67%(17/30)], and the difference was statistically significant (χ 2=4.167, P=0.041). Conclusions:Sivelestat sodium is helpful in improving the physiological parameters of patients with ARDS, effectively reducing the levels of inflammatory factors in the body, shortening the duration of mechanical ventilation and ICU stay, but has no significant effect on the 28-day mortality rate.

The aim of this study was to identify the Salmonella strains isolated from an outbreak of foodborne illness in a seafood buffet restaurant and analyze their pathogenic characteristics.Epidemiological data,fecal samples from patients and chefs,and food/environmental samples from the restaurant were analyzed.Research methods included bacterial culture,serotyping,quadruple fluo-rescence PCR identification,whole-genome sequencing and antibiotic susceptibility testing.The results showed that 4 S.Java strains(serotype 1,4,12∶b∶1,2;ST42)were isolated from two outbreak cases and two sporadic cases.All isolates exhibited similar genomic features,harboring 9 virulence islands and 98 virulence genes.Antimicrobial resistance profiling revealed streptomycin monoresis-tance,mediated by aac(6′)-Iy and aac(6′)-Iaa genes.In conclusion,this event was the first reported outbreak of foodborne illness caused by S.Java in China,indicating that S.Java may be prevalent in the surveyed district.The catering industry should optimize food handling and processing procedures and enhance the surveillance of high risk pathogens.Meanwhile,further studies should ad-dress differential diagnosis and pathogenic mechanism differences between S.Java and S.paratyphi B,which will facilitate evidence-based monitoring in China.