ObjectiveTo explore the mechanism of Shouhui Tongbian capsules in treating constipation based on the research foundation of its active components combined with network pharmacology and animal experiments. MethodsThe drug components were imported into SwissTargetPrediction to predict the targets of Shouhui Tongbian capsules， and constipation-related targets were collected from disease databases. A protein-protein interaction （PPI） network was constructed for the common targets shared by Shouhui Tongbian capsules and constipation to screen key targets， which was followed by gene ontology （GO） function and Kyoto encyclopedia of genes and genomes （KEGG） pathway enrichment analyses. A "bioactive component-target-pathway" network was constructed， and the core components of Shouhui Tongbian capsules in treating constipation were screened based on the topological parameters of this network. Molecular docking was employed to predict the binding affinity of core components to key targets. A mouse model of constipation was constructed to screen the key pathways and targets of the drug intervention in constipation. ResultsThe PPI network revealed six key constipation-related targets： protein kinase B （Akt1）， B-cell lymphoma-2 （Bcl-2）， glycogen synthase kinase-3β （GSK-3β）， cyclooxygenase-2 （PTGS2）， estrogen receptor 1 （ESR1）， and epidermal growth factor receptor （EGFR）. The KEGG pathway analysis showed that the phosphatidylinositol 3-kinase （PI3K）/Akt signaling pathway was the most enriched. The topological parameter analysis of the "bioactive component-target-pathway" network screened out the top 10 core components： auranetin， isosinensetin， naringin， diosmetin， quercetin， apigenin， luteolin， hesperidin， isorhapontigenin， and chrysophanol. Molecular docking results showed that the 10 core components had strong binding affinity with the 6 key targets. Animal experiments showed that after intervention with different doses of Shouhui Tongbian capsules， the time to the first black stool excretion was reduced and the fecal water content and small intestine charcoal propulsion rate of mice were improved. After treatment with Shouhui Tongbian capsules， the colonic mucosal injury and glandular arrangement were alleviated， and the muscle layer thickness was increased. Western blot results showed that Shouhui Tongbian capsules recovered the expression of apoptosis-related molecules mediated by the PI3K/Akt pathway in the colonic tissue of constipated mice. Terminal-deoxynucleotidyl transferase-mediated nick end labeling （TUNEL） results showed that the cell apoptosis rate of the colon significantly reduced after intervention with Shouhui Tongbian capsules. ConclusionThe results of network pharmacology and animal experiments confirmed that Shouhui Tongbian capsules can treat constipation through multiple targets and pathways. The capsules can effectively intervene in loperamide-induced constipation in mice by regulating the constipation indicators and reducing cell apoptosis in the colon tissue via activating the PI3K/Akt signaling pathway.

ObjectiveTo investigate the optimal ratio of goat horn replacing antelope horn in Fufang Lingjiao Jiangya pills and the blood pressure-lowering mechanism of this medicine. MethodsThe blood pressure-lowering efficacy of Fufang Lingjiao Jiangya pills with varying proportions of goat horn replacing antelope horn was evaluated on spontaneous hypertensive rats （SHR）. In this experiment， 50 SHR rats were randomly grouped as follows： model （n=8）， captopril （0.01 g·kg^-1） （n=6）， low-dose blank Fufang Lingjiao Jiangya pills （0.342 g·kg^-1） （n=6）， high-dose blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1） （n=6）， low-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， high-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）， low-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， and high-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）. Additionally， 8 WKY rats were used as the normal group. Drugs were administered by gavage for 4 weeks while an equal volume of distilled water was administered for the normal and model groups. Blood pressure was measured before administration， 3 h post administration， and biweekly thereafter. In the experiment for Fufang Lingjiao Jiangya pills with goat horn replacing antelope horn in different proportions， 48 SHR rats were randomly grouped as follows： model， blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1）， antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1）， 2× goat horn-containing Fufang Lingjiao Jiangya pills （0.824 g·kg^-1）， 4× goat horn Fufang Lingjiao Jiangya pills （0.969 g·kg^-1）， and 6× goat horn Fufang Lingjiao Jiangya pills （1.112 g·kg^-1）. The normal group included 8 WKY rats， and the normal group and model group received an equal volume of distilled water. The treatment lasted for 2 weeks， and blood pressure was recorded at various time points （pre-administration， 3 h post administration， and on days 4， 7， 10， and 14 of administration）. Serum levels of angiotensin-converting enzyme （ACE）， angiotensin Ⅱ（Ang Ⅱ）， renin， and interleukin-6 （IL-6） were measured by enzyme-linked immunosorbent assay. Histopathological changes in the heart， kidney， and thoracic aorta were observed by hematoxylin-eosin staining. The protein levels of ACE2， angiotensin Ⅱ type 1 receptor （AT1R）， and angiotensinogen （AGT） in the kidney tissue were determined by Western blot， while the expression of nuclear factor （NF）-κB p65 and Toll-like receptor 4 （TLR4） in the thoracic aorta tissue was assessed by immunohistochemistry. ResultsCompared with the model group， all treatment groups showed lowered blood pressure （P<0.05， P<0.01）， and the 6× goat horn-containing Fufang Lingjiao Jiangya pills group showed consistent blood pressure-lowering effect with the antelope horn-containing Fufang Lingjiao Jiangya pills group. Compared with the normal group， the model group showed elevated serum levels of ACE， Ang Ⅱ， renin， and IL-6， while the elevations were declined in the Fufang Lingjiao Jiangya pills groups （P<0.05， P<0.01）. Pathological changes in the heart， kidney， and thoracic aorta were alleviated in all the treatment groups， with the 6× goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups exhibited the best effect. Western blot and immunohistochemistry results showed that all the treatment groups exhibited down-regulated protein levels of AT1R， AGT， NF-κB p65， and TLR4 and up-regulated protein levels of ACE2 （P<0.05， P<0.01） compared with model group， with the 6×goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups showcasing the best effect. ConclusionReplacing antelope horn with 6×goat horn in Fufang Lingjiao Jiangya pills can achieve consistent blood pressure-lowering effect with the original prescription. The prescription may exert the effect by inhibiting the renin-angiotensin-aldosterone system （RAAS） and TLR4/NF-κB signaling pathways.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To explore the incidence rate and independent risk factors of synchronous multiple early gastric cancer (SMEGC) in patients with early gastric cancer, and to provide evidence for early screening and intervention of high-risk population. Methods A retrospective analysis was performed on 308 patients with early gastric cancer who received treatment in the hospital from March 2019 to March 2024. The incidence rate of SMEGC was counted, and the risk factors were analyzed by univariate and multivariate Logistic regression analyses. Results Among the 308 patients with early gastric cancer in this study, 23 cases were SMEGC and 285 were single early gastric cancer, which were included in the SMEGC group and the single group respectively. The incidence rate of SMEGC was 7.47% (23/308). Compared with the single group, the proportions of male, smoking history, tumor diameter≤2 mm, chronic atrophic gastritis and intestinal metaplasia degree were higher in the SMEGC group (2=4.331、8.608、4.618、6.490、4.897，P=0.037、0.003、0.032、0.001、0.027). Logistic regression analysis suggested that chronic atrophic gastritis (OR=3.133, 95%CI: 1.240-7.918) and moderate-to-severe intestinal metaplasia (OR=3.171, 95%CI: 1.252-8.029) were independent risk factors for SMEGC (P<0.05). Conclusion Some patients with early gastric cancer are SMEGC. Chronic atrophic gastritis and moderate-to-severe intestinal metaplasia are independent risk factors affecting the occurrence of SMEGC. It is recommended to regularly screen high-risk patients and optimize management strategies to reduce the risk of SMEGC.

ObjectiveTo characterize the seasonal patterns of influenza in Kunming City, Yunnan Province before, during, and after the COVID-19 pandemic, and provide scientific evidence for optimizing influenza prevention and control strategies. MethodsInfluenza-like illness (ILI) and etiological surveillance data for influenza from the 14^th week of 2010 to the 13^th week of 2024 in Kunming City of Yunnan Province were collected. Harmonic regression models were constructed to analyze the epidemic characteristics and seasonal patterns of influenza before (2010/2011‒2019/2020 influenza seasons), during (2020/2021‒2022/2023 influenza seasons), and after (2023/2024 influenza season) the COVID-19 pandemic. ResultsBefore the COVID-19 pandemic, influenza in Kunming City mainly exhibited an annual cyclic pattern without a significant semi-annual periodicity, peaking from December to February of the next year, with an epidemic duration of 20‒30 weeks. During the pandemic, influenza seasonality shifted, with an increase in semi-annual periodicity and an approximate one month delay in annual peaks. However, after the pandemic, the annual amplitude of influenza increased compared with that before the pandemic, and the epidemic duration extended by about one month. Although the annual peak largely reverted to the pre-pandemic levels, the annual peaks for different influenza subtypes/lineages had not fully recovered. ConclusionInfluenza seasonality in Kunming City underwent substantial alterations following the COVID-19 pandemic and has not yet fully reverted to pre-pandemic levels. Continuous surveillance on different subtypes/lineages of influenza viruses remains essential, and prevention and control strategies should be adjusted and optimized in a timely manner based on current epidemic trends.