Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective To investigate the synergistic effect of Shugan Huatan Sanjie prescription(SHSF)and paclitaxel on MCF-7/PTX cells of breast cancer and its mechanism.Methods The PTX-resistant breast cancer cell line MCF-7/PTX was established by continuous induction of low concentration.The effects of different concentrations of PTX on MCF-7 and MCF-7/PTX cells.Then the proliferation of MCF-7/PTX cells by SHSF containing serum were detected by MTT assay,and the drug resistance index(RI)and reversion times were calculated according to the IC50 value.MCF-7/PTX cells were divided into blank control group,PTX group(45 nmol·L-1 PTX),SHSF group(7.5％SHSF drug-containing serum)and PTX+SHSF group(45 nmol·L-1 PTX+7.5％SHSF drug-containing serum).The cells were treated with drugs for 24 h.The apoptosis level of each group was detected by flow cytometry.The expression levels of apoptotic proteins Bax,Bcl-2,p-Akt(ser473),Akt,p-mTOR(Ser2448)and mTOR were detected by Western blot.Results The PTX-resistant cell line MCF-7/PTX was established successfully,and the RI value was 6.70.The proliferative activity of MCF-7/PTX cells decreased in a concentration-dependent manner with the increase of SHSF drug-containing serum concentration.And the resistance reversal ratio of 7.5％SHSF serum to MCF-7/PTX cells was 3.48.Compared with blank control group,the apoptosis levels of MCF-7/PTX cells in PTX group and SHSF group were significantly increased(P＜0.01),the protein expression level of Bax was significantly up-regulated(P＜0.01),and the protein expression levels of Bcl-2,p-Akt/Akt and p-mTOR/mTOR were significantly down-regulated(P＜0.05);Compared with PTX group,the apoptosis level in PTX+SHSF group was significantly increased(P＜0.01),the expression level of Bax protein was significantly up-regulated(P＜0.01),and the expression levels of Bcl-2,p-Akt and p-mTOR protein were significantly down-regulated(P＜0.01).Conclusion Shugan Huatan Sanjie Recipe promotes apoptosis by inhibiting Akt/mTOR pathway,and thus plays a synergistic effect with paclitaxel on MCF-7/PTX cells of breast cancer.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Objective To investigate the synergistic effect of Shugan Huatan Sanjie prescription(SHSF)and paclitaxel on MCF-7/PTX cells of breast cancer and its mechanism.Methods The PTX-resistant breast cancer cell line MCF-7/PTX was established by continuous induction of low concentration.The effects of different concentrations of PTX on MCF-7 and MCF-7/PTX cells.Then the proliferation of MCF-7/PTX cells by SHSF containing serum were detected by MTT assay,and the drug resistance index(RI)and reversion times were calculated according to the IC50 value.MCF-7/PTX cells were divided into blank control group,PTX group(45 nmol·L-1 PTX),SHSF group(7.5％SHSF drug-containing serum)and PTX+SHSF group(45 nmol·L-1 PTX+7.5％SHSF drug-containing serum).The cells were treated with drugs for 24 h.The apoptosis level of each group was detected by flow cytometry.The expression levels of apoptotic proteins Bax,Bcl-2,p-Akt(ser473),Akt,p-mTOR(Ser2448)and mTOR were detected by Western blot.Results The PTX-resistant cell line MCF-7/PTX was established successfully,and the RI value was 6.70.The proliferative activity of MCF-7/PTX cells decreased in a concentration-dependent manner with the increase of SHSF drug-containing serum concentration.And the resistance reversal ratio of 7.5％SHSF serum to MCF-7/PTX cells was 3.48.Compared with blank control group,the apoptosis levels of MCF-7/PTX cells in PTX group and SHSF group were significantly increased(P＜0.01),the protein expression level of Bax was significantly up-regulated(P＜0.01),and the protein expression levels of Bcl-2,p-Akt/Akt and p-mTOR/mTOR were significantly down-regulated(P＜0.05);Compared with PTX group,the apoptosis level in PTX+SHSF group was significantly increased(P＜0.01),the expression level of Bax protein was significantly up-regulated(P＜0.01),and the expression levels of Bcl-2,p-Akt and p-mTOR protein were significantly down-regulated(P＜0.01).Conclusion Shugan Huatan Sanjie Recipe promotes apoptosis by inhibiting Akt/mTOR pathway,and thus plays a synergistic effect with paclitaxel on MCF-7/PTX cells of breast cancer.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Bronchiolitis is the most common lower respiratory tract disorder in infants less than 12 months of age.Wide variation in the management of bronchiolitis exists between Australia and New Zealand, with up to 48% of infants admitted into hospital receiving treatment which is proved by high quality(Cochrane-level) evidence to be no benefit.For this reason, the Australian Guidelines Development Committee has developed the first high-quality Australian guidelines for bronchiolitis.The guideline provide suggestions for the management of children with bronchiolitis in emergency departments and general pediatric wards, and provide evidence for clinical practice.

Objective:To explore the mechanism of motor imagery training (MIT) combined with conventional rehabilitation to promote the functional recovery of upper limbs in stroke survivors. To explore the brain network reorganization resulting when motor imagery training (MIT) is combined with conventional rehabilitation to promote the motor recovery of stroke survivors.Methods:Fourteen hemiplegic patients were recruited as the MIT group. They underwent 4 weeks of MIT (30 min/day, 5 days/week) along with conventional rehabilitation treatment. The upper limb section of the Fugl-Meyer assessment (FMA-UE) and the modified Barthel Index (MBI) were used to assess all of the patients, and resting-state fMRI was performed before and after the treatment. Twenty-eight age- and sex-matched healthy subjects also received one-time resting-state fMRI scanning. Granger causal analysis was performed in the MIT group to calculate the changes in effective connection between the ipsilesional primary motor cortex and the whole brain before and after the treatment, and the results were compared with the healthy control group.Results:After the treatment, the average FMA-UE and MBI of the MIT group had increased significantly. Before the intervention, the effective connection mode of the ipsilesional M1 area in the MIT group was significantly different from that of the healthy controls. The causal flow from the ipsilesional M1 area to the bilateral prefrontal cortex had increased abnormally and the causal flow from the contralesional primary motor cortex, the inferior parietal lobule and the cerebellum to the ipsilesional M1 area had decreased significantly. After the treatment, the effective connection pattern of the stroke survivors was nearly normal, and the causal influence from contralesional motor imagery-related brain areas (the superior parietal lobule, inferior parietal lobule, thalamus and the fusiform gyrus) to the ipsilesional M1 area was enhanced. Effective connection from the ipsilesional M1 area to the contralesional cerebellum before the intervention was positively correlated with the improvement in FMA-UE scores, and the effective connection from the contralesional middle frontal gyrus to the ipsilesional M1 area was correlated negatively.Conclusions:The neural mechanism of MIT's effectiveness when it is combined with conventional rehabilitation might be related to the reorganization of effective connections. That would include enhanced causal flow between motor imagery-related brain areas and the contralesional cerebellum and ipsilesional M1 area. Down-regulation of the effective connection from the contralesional middle frontal gyrus to the ipsilesional M1 area also occurs.

Diarrhea is one of the main disease types of illness and death in children in developing countries, and infectious diarrhea is especially harmful to children′s health.A panel of multidisciplinary experts in management of infectious diarrhea in children and adults was convened in 2012.Panel participants included representatives from the Society for Healthcare Epidemiology of America (SHEA), Center for Disease Control and Prevention(CDC), and the Infectious Disease Society of America(IDSA) Standards and Practice Guidelines Committee (SPGC). In 2017, the panel issued a guideline for the diagnosis and treatment of infectious diarrhea, which was validated and recommended for the management of infectious diarrhea.Now, the part of the content on children in the guide was described.

Objective To measure the efficacy of combining motor imagery training ( MIT) with convention-al therapy in improving stroke patients′upper-extremity function. And to seek a cortical reorganization mechanism as-sociated with the improvement using resting-state functional magnetic resonance imaging ( rs-fMRI) . Methods Ten stroke survivors were selected as an experimental group. They were given motor imagery training for four weeks ( 30 minutes a day, 5 days a week) and conventional rehabilitation therapy ( 40 minutes a day, 5 days a week) . Another 10 healthy counterparts were the control group. Before and after the four weeks of treatment, both groups were as-sessed using the upper extremity Fugl-Meyer assessment ( FMA-UE) and the modified Barthel index ( MBI) . Moreo-ver, rs-fMRI was conducted to assess functional connectivity between cortical regions and the ipsilesional primary mo-tor cortex ( M1) before and after the intervention. The laterality index ( LI) of the primary motor or sensory cortex was also calculated. Results After the intervention, the average FMA-UE and MBI scores of the experimental group had increased significantly. After MIT and conventional therapy there was increased functional connectivity between the ip-silesional and contralesional M1 areas, and between the ipsilesional M1 and contralesional primary sensory cortex ( S1) and frontal lobe, the functional connection between the ipsilesional M1 and the ipsilesional paracentral lobule and the anterior cingutate was also increased. More specifically, the LI relating M1 and S1 decreased after the inter-vention, tending toward the normal level. LIMI decreased significantly. Conclusion The 4-week regimen of motor imagery training and conventional therapy resulted in functional improvement in the upper limbs and greater ability in the activities of daily living. The observed improvements may be due to cortical reorganization, including better func-tional connectivity between the bilateral M1 areas and increased connectivity between the ipsilesional M1 area and some non-motor areas. There is some recovery of symmetry in the bilateral primary motor cortex.