Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

The incidence of lumbar degenerative diseases is increasing year by year,and MRI is often used in clinical diagnosis.In recent years,artificial intelligence(AI)has rapidly developed in medical field and can be used for image segmentation and auxiliary diagnosis of lumbar degenerative diseases.The research progresses of AI in MRI of lumbar degenerative diseases were reviewed in this article.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

Osteoporotic vertebral compression fracture (OVCF) can lead to lower back pain and may be even accompanied by scoliosis, neurological dysfunction and other complications, which will affect the daily activities and life quality of patients. Vertebral augmentation is an effective treatment method for OVCF, but it cannot correct unbalance of bone metabolism or improve the osteoporotic status, causing complications like lower back pain, limited spinal activities and vertebral refracture. The post-operative systematic and standardized rehabilitation treatments can improve curative effect and therapeutic efficacy of anti-osteoporosis, reduce risk of vertebral refracture, increase patient compliance and improve quality of life. Since there still lack relevant clinical treatment guidelines for postoperative rehabilitation treatments following vertebral augmentation for OVCF, the current treatments are varied with uneven therapeutic effect. In order to standardize the postoperative rehabilitation treatment, the Spine Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized relevant experts to refer to relevant literature and develop the "Guideline for postoperative rehabilitation treatment following vertebral augmentation for osteoporotic vertebral compression fracture (2022 version)" based on the clinical guidelines published by the American Academy of Orthopedic Surgeons (AAOS) as well as on the principles of scientificity, practicality and advancement. The guideline provided evidence-based recommendations on 10 important issues related to postoperative rehabilitation treatments of OVCF.

Objective:To analyze the molecular characteristics of Echovirus 11 (Echo11) strains isolated in Xiangyang, Hubei Province from 2016 to 2017 based on the sequences of VP1 gene.Methods:Rectal and throat swab specimens were collected from children with hand, foot and mouth disease (HFMD) in Xiangyang from 2016 to 2017. Echo11 strains were detected by real-time reverse transcriptase PCR (RT-PCR) and isolated after cultured in human rhabdosarcoma (RD) cells. The VP1 regions of Echo11 strains isolated from RD cells and the whole genomes of three representative Echo11 strains were amplified by conventional RT-PCR and the sequences were analyzed. DNAStar7.0 (MegAlign) and MEGA6.0 (Data) were used to analyze the homology and mutation sites in nucleotide and amino acid sequences. Neighbor-joining method was used to construct phylogenetic trees. Recombination analysis was performed with SimPlot software (BootScanning).Results:A total of 11 Echo11 strains were isolated from 3 494 HFMD cases, accounting for 0.31%. They were highly homologous in the VP1 gene. These strains shared 98.4%-100.0% homology in nucleotide sequences and 98.3%-100.0% homology in amino acid sequences. The homology between the 11 Echo11 strains and the prototype strain (Echo11/Gregory, X80059) was 73.9%-74.8% in nucleotide sequences and 87.7%-88.7% in amino acid sequences. All of the Echo11 strains circulating in Xiangyang were classified into lineage D, having a similarity to the strains circulating in some regions of mainland China since 2013. In multiple regions of the genome, the Echo11 strains isolated in Xiangyang were highly similar to the Henan Echo1 strains in 2010 and the Hubei Echo6 strains in 2015, suggesting there was recombination within the genome of Echo11 strains in Xiangyang.Conclusions:The Echo11 strains circulating in Xiangyang from 2016 to 2017 belonged to lineage D and were recombinant strains.

Objective To understand the epidemiological characteristics of the novel coronavirus diseases 2019 (COVID-19), and to scientifically guide the prevention and control of COVID-19 in Hubei Province. Methods All COVID-19 cases reported online in Hubei Province as of March 31, 2020 were extracted from Hubei^'s Infectious Disease Information System. The epidemic curve, age and sex characteristics, and spatiotemporal distribution characteristics of the COVID-19 cases were analyzed. Results As of March 31, 2020, a total of 70 764 cases were reported in Hubei Province, including 49 195 confirmed cases. A total of 4 579 deaths occurred among the confirmed cases, and the reported case fatality rate was 6.47%. The peak of the onset of symptoms occurred from January 20 to February 14, 2020. The sex ratio of male to female of the confirmed cases was 0.99: 1, and most were 30-69 years old. The cases diagnosed before January 5 were mainly reported by Wuhan City. From January 6 to January 31, all counties and districts in the province reported that the incidence of confirmed COVID-19 cases began to rise, and about 50% counties reported that the morbidity rate of confirmed COVID-19 cases was over 10 cases per 100 000. The morbidity rate of COVID-19 cases rose rapidly between February 1-15, and then gradually reached its peak after February 16. Conclusion Wuhan City of Hubei Province first discovered and reported the COVID-19 outbreak. The onset of symptoms peaked in January 20 to February 14, and the 30-69 years old group was the key population. Many measures such as restricting personnel movement, reducing contact, and strengthening health education played an important role in controlling the outbreak of COVID-19 in Hubei.

OBJECTIVE： To establish the method for the rapidly non-destructive quality control of Liuwei dihuang capsule. METHODS： AOTF-NIR spectrometry was adopted. Taking 80 batches of Liuwei dihuang capsule produced by a manufacturer in recent three years as samples， HPLC chromatogram was adopted to determine the contents of loganin， morroniside， paeonol， paeoniflorin and ursolic acid； the content of water was determined according to general principles stated in 2015 edition of Chinese Pharmacopeia （part Ⅰ）. Taking 70 batches of samples as correction set， the partial least square method and the cross-validation algorithm were used to establish the NIR quantitative model of 6 indexes in Liuwei dihuang capsules with the Unscrambler quantitative analysis software. Taking residual 10 batches of samples as validation set， external validation was conducted for the model. RESULTS： The correlation coefficients （R2） of internal and external validation of loganin， morroniside， paeonol， paeoniflorin， the content of water quantitative model were all greater than 0.9； the correction of standand deviation （RMSEC） were 0.372 8， 0.025 4， 0.263 3， 0.288 5， 0.186 7 and 0.037 7； the prediction of standard deviation （RMSEP） were 0.462 2， 0.077 5， 0.472 1， 0.634 9， 0.293 4 and 0.206 9； the external verification showed that mean deviations of preclicted value to actual value were 6.04％， 6.05％， 5.87％， 6.97％， 5.62％ and 4.83％， with the mean deviation less than 10％.CONCLUSIONS：The established method can achieve rapidly non-destructive analysis Liuwei dihuang capsule.

Objective: The effect of total flavonoids of litchi (TFL) on nuclear translocation of nuclear factor-kappa B (NF- kappa B) in rat hepatic stellate cell line (HSC-T6) induced by transforming growth factor - beta 1 (TGF- beta 1) in vitro was studied to explore the mechanism of action of anti-hepatic fibrosis drugs. Methods: HSC-T6 was cultured in vitro, induced by TGFβ1 for 24 h, and then treated with TFL at 125, 250 and 500 μg/ml for 48 h. The effect of TFL on NF-κB nuclear translocation in HSC-T6 was observed by confocal laser microscopy. The effects of TFL on the expression of TLR4, p-IκB ɑ, p-NF-κB p65, NF-κB and Collagen I protein were detected by western blot. The expressions of TLR4 and p-NF-κB p65 were detected by immunofluorescence. Data were presented as mean±SEM. Homogeneity test of variance was performed and then followed by one-way analysis of variance (ANOVA). The multiple comparisons between groups were performed by LSD test. P < 0.05 was considered statistically significant. Results: Confocal laser scanning microscopy showed TFL inhibited the nuclear translocation of NF-κB in activated HSC-T6 in a concentration-dependent manner and TFL down regulated the protein expression levels of TLR4, p-IκB ɑ, p-NF-κB p65, NF-κB and collagen I protein in HSC-T6 in a concentration-dependent manner. Conclusion The mechanism of TFL against hepatic fibrosis may be related to the inhibition of nuclear translocation of NF-κb in the activated HSC-T6 and the expression of TLR4, P-iκbɑ, P-nf-κb p65, NF-κb and collagen I protein in HSC-T6.

OBJECTIVE:To establish the method for rapid quality evaluation of Astragali Radix.METHODS:The moisture of medicinal material was determined by oven drying method;the content of astragaloside Ⅳ was determined by HPLC-ELSD;the content of isoflavone glucoside was determined by HPLC (as reference value).The partial least squares (PLS) method combined with acousto-optic turnable filter-NIDRS was adopted to build quantitative model of above indexes in Astragali Radix (as predict value).According to reference value,60 batches of sample were collected.The spectra pretreatment was conducted by first derivative method combined with Savitzky golay.The optimal bands of moisture,astragaloside Ⅳ and isoflavone glucoside were 1 100-2 300 nm,1 080-2 160 nm,1 170-2 230 nm,respectively.RESULTS:The content determination of moisture,astragaloside Ⅳ and isoflavone glucoside in samples were all in line with methodology requirements.The corrected mean square root deviation of quantitative model for moisture,astragaloside Ⅳ,calycosin glucoside were 0.132 3,0.006 6,0.002 5,respectively;predicted mean square root deviation were 0.237 1,0.016 3,0.004 7;internal cross validation coefficient of correction set were 0.975 9,0.953 3,0.968 0;internal verification deviation of quantitative model were 1.43％,1.90％,1.84％;external verification deviation were 1.73 ％,2.68 ％,2.71％,respectively.CONCLUSIONS:The method is rapid,accurate,simple,pollution-free,and can be used for rapid quality evaluation of Astragali Radix.