Objective:To analyze the epidemic trend of influenza-like illness（ILI）cases，etiological detection results，and the evolution of the hemagglutinin（HA）gene of the predominant strains in Hanzhong City，Shaanxi Province during the 2018-2024 influenza seasons.Methods:ILI sentinel surveillance data and network laboratory test results during the 2018-2024 influenza seasons in Hanzhong City，Shaanxi Province were collected for descriptive analysis. The HA gene sequences of 25 predominant strains were obtained through whole-genome deep sequencing method，and then compared with the vaccine strains recommended by the World Health Organization in the same period to analyze the evolution of the virus.Results:A total of 37 770 cases of ILI were reported in Hanzhong City during the 2018-2024 influenza seasons，and the proportion of total ILI cases（ILI%）was 2.87%（37 770/1 316 009）. The epidemic trend of ILI showed an obvious epidemic peak in winter and spring（from December of the current year to March of the following year）. The specimens with the highest positive rate were of type A（H3N2）（39.12%，365/933），and the predominant epidemic strains in each influenza season alternated among A（H1N1）pdm09（in the 2018-2019 and 2022-2023 influenza seasons），A（H3N2）（in the 2019-2020 and 2023-2024 influenza seasons）and B（Victoria）（in the 2021-2022 influenza season）. The phylogenetic relationship gradually became more distant over time across different influenza seasons. Among them，the epidemic strains of A（H1N1）pdm09 belonged to the 6B.1 clade，and the evolution mainly occurred in the Sa and Sb regions of the HA epitope. Meanwhile，the epidemic strains of A（H3N2）belonged to the 3C clade，and the evolution mainly took place in the A，B and C regions of the HA epitope. The strains of the B（Victoria）lineage belonged to the V1a.3a.2 clade，and the evolution mainly occurred in the 120-loop，150-loop，and 190-helix regions of the HA epitope.Conclusions:The influenza epidemic in Hanzhong City has obvious seasonality，and the amino acids of the epidemic strains have shown a certain degree of variation over the years. In future prevention and control work，influenza surveillance should be continuously strengthened，and the change trend of the predominant circulating strains should be closely monitored.

Image 1.

Eight new diterpenoids, Isodons A-H (1-8), comprising seco-abietane and abietane-type structures, together with 13 known analogues (9-21), were isolated from Isodon lophanthoides (Buch.-Ham. ex D. Don) Hara. The compounds (+)-3/(-)-3, (+)-4/(-)-4, and (+)-5/(-)-5 were identified as three enantiomeric pairs. The planar structures and absolute configurations of 1-8 were determined through high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), 1D & 2D nuclear magnetic resonance (NMR) spectroscopy, electronic circular dichroism (ECD) calculations, and X-ray diffraction crystallography. A cholesterol 7α-hydroxylase (Cyp7a1) luciferase reporter assay revealed significant anti-cholestatic activities for compounds 1, (+)-4, 6, 7, 12-14, and 16. Additionally, compound 6 demonstrated anti-cholestatic effects through the farnesoid X receptor (FXR)-associated signaling pathways in vitro and in vivo. These findings suggest potential applications for I. Lophanthoides in pharmaceutical development.
Abietanes/pharmacology* ; Molecular Structure ; Animals ; Isodon/chemistry* ; Humans ; Diterpenes/pharmacology* ; Plant Extracts/chemistry*

Neurodegenerative diseases are a group of chronic progressive diseases characterized by inflammation,degenera-tion and apoptosis.Chronic neuroinflammation is gradually becoming a potential pathogenic and predisposing factor.As a widely expressed non-histone nucleoprotein,HMGB1 participates in inflammatory process of human body through receptors of advanced glycation end products and Toll-like receptors while maintaining chromosome homeostasis.As a key factor of neuroinflammation,HMGB1 is widely involved in development of neurodegenerative diseases and may become a biomarker and a potential therapeutic target of neurodegenerative diseases.This article reviews the role of HMGB1 in neurodegenerative diseases and tries to provide ground-work for basic research and clinical application for targeting HMGB1 in the treatment of neurodegenerative diseases.

Objective:To investigate the risk factors of post-stroke cognitive impairment (PSCI) in patients with acute ischemic stroke, to establish a nomogram predictive model to help clinicians predict and intervene in the people who are prone to PSCI in advance, and to improve the recognition, intervention and prevention of the disease at an early stage, so as to provide a new way of thinking for the diagnosis and treatment of PSCI.Methods:Totally 330 patients with acute ischemic stroke hospitalized in the Department of Neurology, the First Bethune Hospital of Jilin University from January 2021 to June 2023 were collected. Their general clinical data, laboratory examination, imaging examination, and neuropsychological assessment data were collected. Neuropsychological scales assessment was completed within 7 days of the onset of acute ischemic stroke as a baseline value. The patients were followed up with neuropsychological scales assessment 6 months after the onset of stroke, and according to the results of the Montreal Cognitive Assessment (MoCA) scale assessment 6 months later, the patients were divided into PSCI group (143 patients) and post-stroke non-cognitive impairment (PSNCI) group (147 patients) (40 patients were removed from the study after 6 months, and a total of 290 patients were finally included in the study). Comparisons of general clinical information between the PSCI and PSNCI groups were first performed using statistical methods; then more influential predictors were selected using least absolute shrinkage and selection operator (LASSO) regression method and included in multifactor Logistic regression analyses to create a nomogram predictive model. Internal validation was performed by repeating the sampling 1 000 times using the bootstrap method; receiver operating characteristic (ROC) curve and area under the curve (AUC) were plotted to analyze the discrimination of the predictive model; the accuracy of the model was assessed using calibration curves; and a decision curve analysis (DCA) diagram was plotted to assess the clinical utility of the model.Results:Age, education level, critical area cerebral infarction, low-density lipoprotein-cholesterol (LDL-C), cerebral white matter hyperintensity (WMH), and cerebral atrophy were selected as the predictors of the nomogram predictive model by LASSO regression, and the results of multifactor Logistic regression analysis showed that these predictors were independent risk factors for PSCI in patients with acute ischemic stroke; the risk predictive model established was validated, and the results showed that the AUC of the present predictive model was 0.890, and the AUC of the internally validated predictive model was 0.940, suggesting that the model had a good degree of differentiation; the good fit between the calibration curve and the actual prediction results indicated that the model had good accuracy; the DCA results showed that the model can be well applied in clinical practice.Conclusion:The nomogram predictive model consisting of age, education level, critical area cerebral infarction, LDL-C, WMH, and cerebral atrophy has good differentiation, accuracy, and clinical utility, and can be used in practical clinical practice, which can help clinicians screen patients who are prone to PSCI, and intervene in a timely manner to achieve better clinical outcomes.

Neurodegenerative diseases are a group of chronic progressive diseases characterized by inflammation,degenera-tion and apoptosis.Chronic neuroinflammation is gradually becoming a potential pathogenic and predisposing factor.As a widely expressed non-histone nucleoprotein,HMGB1 participates in inflammatory process of human body through receptors of advanced glycation end products and Toll-like receptors while maintaining chromosome homeostasis.As a key factor of neuroinflammation,HMGB1 is widely involved in development of neurodegenerative diseases and may become a biomarker and a potential therapeutic target of neurodegenerative diseases.This article reviews the role of HMGB1 in neurodegenerative diseases and tries to provide ground-work for basic research and clinical application for targeting HMGB1 in the treatment of neurodegenerative diseases.

Objective:To analyze the epidemic trend of influenza-like illness（ILI）cases，etiological detection results，and the evolution of the hemagglutinin（HA）gene of the predominant strains in Hanzhong City，Shaanxi Province during the 2018-2024 influenza seasons.Methods:ILI sentinel surveillance data and network laboratory test results during the 2018-2024 influenza seasons in Hanzhong City，Shaanxi Province were collected for descriptive analysis. The HA gene sequences of 25 predominant strains were obtained through whole-genome deep sequencing method，and then compared with the vaccine strains recommended by the World Health Organization in the same period to analyze the evolution of the virus.Results:A total of 37 770 cases of ILI were reported in Hanzhong City during the 2018-2024 influenza seasons，and the proportion of total ILI cases（ILI%）was 2.87%（37 770/1 316 009）. The epidemic trend of ILI showed an obvious epidemic peak in winter and spring（from December of the current year to March of the following year）. The specimens with the highest positive rate were of type A（H3N2）（39.12%，365/933），and the predominant epidemic strains in each influenza season alternated among A（H1N1）pdm09（in the 2018-2019 and 2022-2023 influenza seasons），A（H3N2）（in the 2019-2020 and 2023-2024 influenza seasons）and B（Victoria）（in the 2021-2022 influenza season）. The phylogenetic relationship gradually became more distant over time across different influenza seasons. Among them，the epidemic strains of A（H1N1）pdm09 belonged to the 6B.1 clade，and the evolution mainly occurred in the Sa and Sb regions of the HA epitope. Meanwhile，the epidemic strains of A（H3N2）belonged to the 3C clade，and the evolution mainly took place in the A，B and C regions of the HA epitope. The strains of the B（Victoria）lineage belonged to the V1a.3a.2 clade，and the evolution mainly occurred in the 120-loop，150-loop，and 190-helix regions of the HA epitope.Conclusions:The influenza epidemic in Hanzhong City has obvious seasonality，and the amino acids of the epidemic strains have shown a certain degree of variation over the years. In future prevention and control work，influenza surveillance should be continuously strengthened，and the change trend of the predominant circulating strains should be closely monitored.

Objective:To investigate the risk factors of post-stroke cognitive impairment (PSCI) in patients with acute ischemic stroke, to establish a nomogram predictive model to help clinicians predict and intervene in the people who are prone to PSCI in advance, and to improve the recognition, intervention and prevention of the disease at an early stage, so as to provide a new way of thinking for the diagnosis and treatment of PSCI.Methods:Totally 330 patients with acute ischemic stroke hospitalized in the Department of Neurology, the First Bethune Hospital of Jilin University from January 2021 to June 2023 were collected. Their general clinical data, laboratory examination, imaging examination, and neuropsychological assessment data were collected. Neuropsychological scales assessment was completed within 7 days of the onset of acute ischemic stroke as a baseline value. The patients were followed up with neuropsychological scales assessment 6 months after the onset of stroke, and according to the results of the Montreal Cognitive Assessment (MoCA) scale assessment 6 months later, the patients were divided into PSCI group (143 patients) and post-stroke non-cognitive impairment (PSNCI) group (147 patients) (40 patients were removed from the study after 6 months, and a total of 290 patients were finally included in the study). Comparisons of general clinical information between the PSCI and PSNCI groups were first performed using statistical methods; then more influential predictors were selected using least absolute shrinkage and selection operator (LASSO) regression method and included in multifactor Logistic regression analyses to create a nomogram predictive model. Internal validation was performed by repeating the sampling 1 000 times using the bootstrap method; receiver operating characteristic (ROC) curve and area under the curve (AUC) were plotted to analyze the discrimination of the predictive model; the accuracy of the model was assessed using calibration curves; and a decision curve analysis (DCA) diagram was plotted to assess the clinical utility of the model.Results:Age, education level, critical area cerebral infarction, low-density lipoprotein-cholesterol (LDL-C), cerebral white matter hyperintensity (WMH), and cerebral atrophy were selected as the predictors of the nomogram predictive model by LASSO regression, and the results of multifactor Logistic regression analysis showed that these predictors were independent risk factors for PSCI in patients with acute ischemic stroke; the risk predictive model established was validated, and the results showed that the AUC of the present predictive model was 0.890, and the AUC of the internally validated predictive model was 0.940, suggesting that the model had a good degree of differentiation; the good fit between the calibration curve and the actual prediction results indicated that the model had good accuracy; the DCA results showed that the model can be well applied in clinical practice.Conclusion:The nomogram predictive model consisting of age, education level, critical area cerebral infarction, LDL-C, WMH, and cerebral atrophy has good differentiation, accuracy, and clinical utility, and can be used in practical clinical practice, which can help clinicians screen patients who are prone to PSCI, and intervene in a timely manner to achieve better clinical outcomes.

In this study, 34 deep eutectic solvents (DESs) were successfully prepared for the extraction of proanthocyanidin from Rhodiolae Crenulatae Radix et Rhizomes. The extraction process was optimized using single factor exploration and Box-Behnken design-response surface analysis. The extraction rate was significantly improved when the molar ratio of choline chloride to 1,3-propanediol was 1:3.5 and the water content was 30% (V/V) in DESs. AB-8 macroporous resin and ethyl acetate were used for separation and refining, and the oligomer-rich proanthocyanidin components were eventually obtained. The ultraviolet (UV) and infrared (IR) spectra showed that the proanthocyanidins were mainly composed of catechin and epicatechin. To further clarify the chemical composition of proanthocyanidin, an ion scan list containing 156 proanthocyanidins precursors was obtained by constructing a proanthocyanidins structural library and mass defect filtering (MDF) algorithm, combined with the full mass spectrometry (MS)/dd-MS² scan mode that turns on the "if idle pick others" function. By using ultra-high performance liquid chromatography and high-resolution MS (UHPLC/HRMS), the analysis used both targeted and non-targeted methods to detect proanthocyanidins. Finally, 50 oligomeric proanthocyanidin (OPC) compounds were identified, including 7 monomers, 22 dimers, 20 trimers, and 1 tetramer, most of which were procyanidins of proanthocyanidins (84%), and a small amount of prodelphinidin (14%) and other types of proanthocyanidins (2%), which enabled the systematic characterization of proanthocyanidin components from Rhodiolae Crenulatae Radix et Rhizomes. Meanwhile, the comparison with the grape seeds OPCs standard (United States Pharmacopeia) revealed that the proanthocyanidins in Rhodiolae Crenulatae Radix et Rhizomes were more abundant, suggesting that the proanthocyanidins in Rhodiolae Crenulatae Radix et Rhizomes has promising applications.

Plant-derived nanovesicles have gained attention given their similarity to mammalian exosomes and advantages such as low cost, sustainability, and tissue targeting. Thus, they hold promise for disease treatment and drug delivery. In this study, we proposed a time-efficient method, PEG 8000 combined with sucrose density gradient centrifugation to prepare ginger-derived nanovesicles (GDNVs). Subsequently, curcumin (CUR) was loaded onto GDNV by ultrasonic incubation. The optimum conditions for ginger-derived nanovesicles loaded with curcumin (CG) were ultrasound time of 3 min, a carrier-to-drug ratio (GDNV:CUR) of 1:1. The study achieved a high loading capacity (94.027% ± 0.094%) and encapsulation efficiency (89.300% ± 0.344%). Finally, the drugs' in vivo distribution and anti-colitis activity were investigated in mice. CG was primarily distributed in the colon after oral administration. Compared to CUR and GDNV, CG was superior in improving disease activity, colon length, liver and spleen coefficients, myeloperoxidase activity, and biochemical factor levels in ulcerative colitis (UC) mice. In addition, CG plays a protective role against UC by modulating serum metabolite levels and gut flora. In summary, our study demonstrated that GDNV can be used for CUR delivery with enhanced therapeutic potential.