ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important source of bioactive natural products. The cross-links between aromatic amino acid side chains (cyclophane cross-links) confer structural diversity and complexity. These cross-links are primarily catalyzed by two major types of enzymes: radical S-adenosylmethionine (rSAM) enzymes and cytochrome P450 enzymes. This review focuses on the diverse cyclophane cross-linking patterns introduced by rSAM and P450 enzymes during RiPP biosynthesis, and summarizes the similarities and differences between these enzymatic transformations, aiming to provide some insights for the discovery, engineering, and mechanistic study of this class of natural products.

Cytochrome P450 enzymes represent a class of heme-containing protease widely distributed across the biological kingdom. Endowed with a broad substrate scope, diverse catalytic reaction profiles, high regio- and stereoselectivity toward substrates, and mild catalytic conditions, these enzymes stand out as superior biocatalysts with good potential of application. As one of the primary producers of natural products, Streptomyces harbors a wealth of P450 enzymes and natural product biosynthetic gene clusters (BGCs) in its genome, making it a versatile treasure trove for the generation of bioactive small-molecule compounds. This review summarizes the catalytic reactions by Streptomyces-derived P450 enzymes in natural product biosynthesis and delineates the engineering strategies for addressing the practical application challenges of P450 enzymes, aiming to provide some reference and guidance for in-depth research on P450 enzymes and their applications.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

Purpose To explore the application value of auto-prescription technique in CT portal venography and liver volume measurement.Materials and Methods A total of 180 patients who underwent contrast-enhanced abdominal CT in the First Affiliated Hospital of Dalian Medical University from April to November 2022 were prospectively collected and randomly divided into two groups,with 90 cases in each group.Group A(experimental group)was scanned with auto-prescription technique.Group B(conventional group)was scanned with 120 kVp,and the other imaging parameters kept the same as group A.In group A,the correlation between body mass index and tube voltage(kVp)recommended by auto-prescription technique was analyzed.The following values were compared between group A and group B,including the volume CT dose index,dose length product,CT value of portal vein and liver,standard deviation,contrast-to-noise ratio(CNR),image quality and subjective score of automatic segmentation.The liver volumes of group A and B were measured by Liver Segmentation software.The volumes measured by automatic segmentation software(Vsoft)were recorded,and then were compared with those segmented manually(gold standard)(Vstnd).Results Compared with group B,the volume CT dose index and dose length product in group A decreased by 22%and 25%(t=-4.654,-5.403,both P<0.05),respectively.The CT value and CNR of portal vein and liver in group A were higher than those in group B(t=4.857-6.011,all P<0.05).There was no significant difference in standard deviation,Vstnd and Vsoft between group A and group B(P>0.05).The consistency of subjective scores between the two observers was good(ICC=0.773-0.856,all P<0.05).The subjective scores of two-dimensional and three-dimensional images,as well as the automatic software segmentation scores in group A were higher than those in group B(Z=897.500,1 287.500,912.721,all P<0.05).The recommended kVp value in group A was positively correlated with body mass index(r=0.674,P<0.001).Conclusion The application of auto-prescription technique in CT portal venography can ensure the image quality,measure the liver volume accurately,and reduce the patient's radiation dose individually.

Objective·To develop a graph neural network(GNN)-based auxiliary diagnostic model for gallbladder cancer on CT images,and validate its accuracy and feasibility.Methods·From January 2010 to November 2023,1 774 contrast-enhanced CT arterial-phase images were acquired from 887 patients with normal gallbladder,benign gallbladder disease,or gallbladder cancer at Xinhua Hospital and Renji Hospital,Shanghai Jiao Tong University School of Medicine.These images were randomly divided into training and testing sets at a 4∶1 ratio to develop a hybrid GNN-convolutional neural network(CNN)model,named VJK-GIN.The model constructed a pixel-level graph in which each pixel served as a node,and spatial adjacency defined the edges,enabling extraction of local texture features.In the model architecture design,VJK-GIN integrated a three-layer graph isomorphism network,augmented with virtual nodes and jump-knowledge connections;global pooling compressed node features into a graph-level representation,which was classified by a multi-layer perceptron head.Five-fold cross-validation was used to compare VJK-GIN with GNN baselines(GCN,GraphSAGE,GAT,and GIN)and CNN baselines(ViT,EfficientNetV2,and ConvNeXt)in terms of accuracy,precision,recall,F1-score,and area under the receiver operating characteristic curve(AUC).Results·The results of five-fold cross-validation showed that VJK-GIN achieved an F1-score of 0.799(95%CI 0.775?0.823),recall of 0.795(95%CI 0.773?0.817),precision of 0.799(95%CI 0.775?0.823),AUC of 0.812(95%CI 0.792?0.832),and accuracy of 0.773(95%CI 0.748?0.798),surpassing all competing models across every metric.Conclusion·The VJK-GIN model exhibits high stability and accuracy in identifying contrast-enhanced CT images of normal,benign,and malignant gallbladder conditions.

Purpose To explore the application value of auto-prescription technique in CT portal venography and liver volume measurement.Materials and Methods A total of 180 patients who underwent contrast-enhanced abdominal CT in the First Affiliated Hospital of Dalian Medical University from April to November 2022 were prospectively collected and randomly divided into two groups,with 90 cases in each group.Group A(experimental group)was scanned with auto-prescription technique.Group B(conventional group)was scanned with 120 kVp,and the other imaging parameters kept the same as group A.In group A,the correlation between body mass index and tube voltage(kVp)recommended by auto-prescription technique was analyzed.The following values were compared between group A and group B,including the volume CT dose index,dose length product,CT value of portal vein and liver,standard deviation,contrast-to-noise ratio(CNR),image quality and subjective score of automatic segmentation.The liver volumes of group A and B were measured by Liver Segmentation software.The volumes measured by automatic segmentation software(Vsoft)were recorded,and then were compared with those segmented manually(gold standard)(Vstnd).Results Compared with group B,the volume CT dose index and dose length product in group A decreased by 22%and 25%(t=-4.654,-5.403,both P<0.05),respectively.The CT value and CNR of portal vein and liver in group A were higher than those in group B(t=4.857-6.011,all P<0.05).There was no significant difference in standard deviation,Vstnd and Vsoft between group A and group B(P>0.05).The consistency of subjective scores between the two observers was good(ICC=0.773-0.856,all P<0.05).The subjective scores of two-dimensional and three-dimensional images,as well as the automatic software segmentation scores in group A were higher than those in group B(Z=897.500,1 287.500,912.721,all P<0.05).The recommended kVp value in group A was positively correlated with body mass index(r=0.674,P<0.001).Conclusion The application of auto-prescription technique in CT portal venography can ensure the image quality,measure the liver volume accurately,and reduce the patient's radiation dose individually.

Objective·To develop a graph neural network(GNN)-based auxiliary diagnostic model for gallbladder cancer on CT images,and validate its accuracy and feasibility.Methods·From January 2010 to November 2023,1 774 contrast-enhanced CT arterial-phase images were acquired from 887 patients with normal gallbladder,benign gallbladder disease,or gallbladder cancer at Xinhua Hospital and Renji Hospital,Shanghai Jiao Tong University School of Medicine.These images were randomly divided into training and testing sets at a 4∶1 ratio to develop a hybrid GNN-convolutional neural network(CNN)model,named VJK-GIN.The model constructed a pixel-level graph in which each pixel served as a node,and spatial adjacency defined the edges,enabling extraction of local texture features.In the model architecture design,VJK-GIN integrated a three-layer graph isomorphism network,augmented with virtual nodes and jump-knowledge connections;global pooling compressed node features into a graph-level representation,which was classified by a multi-layer perceptron head.Five-fold cross-validation was used to compare VJK-GIN with GNN baselines(GCN,GraphSAGE,GAT,and GIN)and CNN baselines(ViT,EfficientNetV2,and ConvNeXt)in terms of accuracy,precision,recall,F1-score,and area under the receiver operating characteristic curve(AUC).Results·The results of five-fold cross-validation showed that VJK-GIN achieved an F1-score of 0.799(95%CI 0.775?0.823),recall of 0.795(95%CI 0.773?0.817),precision of 0.799(95%CI 0.775?0.823),AUC of 0.812(95%CI 0.792?0.832),and accuracy of 0.773(95%CI 0.748?0.798),surpassing all competing models across every metric.Conclusion·The VJK-GIN model exhibits high stability and accuracy in identifying contrast-enhanced CT images of normal,benign,and malignant gallbladder conditions.

Atherosclerosis and its complications are one of the diseases with the highest incidence and mortality in the world,and its early diagnosis and treatment are very important.At present,a variety of physiological and biochemical indicators have been used to diagnose atherosclerosis.However,the accuracy and ease of use of existing diagnostic indi-cators still cannot meet the clinical needs,and new,reliable and easy to measure biomarkers for early diagnosis and judg-ment of atherosclerosis and the risk of serious cardiovascular and cerebrovascular events caused by atherosclerosis are still very scarce.This article summarized the latest research progress of biomarkers related to atherosclerosis,such as hematol-ogy,genetics and omics,in order to provide basis for early diagnosis and treatment of atherosclerosis and related cardiovas-cular and cerebrovascular diseases induced by atherosclerosis.

Objective:To evaluate the accuracy and safety profile of a novel cuboid orientation-guided frontal horn ventriculostomy technique in patients with large hemispheric infarction (LHI).Methods:It was conducted a retrospective cohort study of 48 consecutive LHI patients who underwent the innovative ventriculostomy procedure between time period. Primary outcomes included procedural accuracy (success rates, catheter positioning) and safety indicators (complication rates).Results:All the punctured ventricles were small or of normal size. The success rate of puncture was 100%, the success rate of one-time puncture was 87% (42/48), and the average number of puncture was 1.13 times per case. The ratio of well-positioned tube heads was 87.5% (42/48). The actual angle of the inward deviation of the puncture ranged from -2o to 5o, with an average of 0o±0.3o. The depth of puncture was 7.0-8.0 cm ( 7.3±0.3) cm. The incidence of bleeding around the puncture path was 1.3% (2/48 ) and no massive bleeding occurred. At the 6-month follow-up, one case (2.94%) among the 34 survivors had epilepsy.Conclusions:The cuboid orientation-guided frontal horn ventriculostomy technique demonstrates exceptional procedural accuracy and an excellent safety profile in LHI patients, with high first-pass success rates (87.5%) and minimal complications (4.2% minor hemorrhage). These findings support its clinical adoption for this patient population.