Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.

Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.

Objective:To analyze the temporal distribution characteristics of hand, foot and mouth disease (HFMD) in Beijing and provide reference evidence in HFMD prevention and control.Methods:The monthly incidence data of HFMD in Beijing from 2008 to 2023 were collected from Notifiable Disease Management Information System of the Chinese Information System of Disease Control and Prevention, and the epidemiological characteristics of HFMD were analyzed by the methods of time series seasonal decomposition graph, concentration degree, and circular distribution.The WPS office software 2019 was used to clean the data, Python software 3.12 was used to analyze and make statistical charts.Results:The monthly incidence fluctuation of HFMD in Beijing from 2008 to 2015 was higher than that from 2016 to 2022. From 2016 to 2022, the fluctuation range of monthly incidence showed a gradually decreasing trend.From 2008 to 2015, the concentration ( M) was 0.58, indicating a relatively strong seasonality; the mean angle ( α) calculated by the circular distribution method was 174.95°, and the mean angle standard deviation ( s) was 60.43°. The annual incidence peak occurred on June 27, and the incidence peak period was from April 27 to August 27. From 2016 to 2019 and 2023, the M was 0.57, indicating a relatively strong seasonality. The α was 228.05°, and s was 61.44°. The annual incidence peak occurred on August 20, and the incidence peak period was from June 18 to October 21. From 2020 to 2022, the M was 0.42, indicating a seasonality, the α was 238.27° and s was 76.35°. The annual incidence peak occurred on July 15, and the incidence peak period was from June 14 to November 14. The α of 2008-2015, 2016-2019 and 2023, and 2020-2022 were tested by the Watson-Williams method and the difference was statistically significant ( F=33 443.09, P<0.001). In 2023, the M was 0.77, indicating a strong seasonality. The incidence peak occurred on September 16, and the incidence peak period was from August 5 to October 28. Conclusions:The seasonality of HFMD in Beijing was obvious from 2008 to 2023, and the incidence peak day and peak period overall had rearward shifts. It is necessary to strengthen the comprehensive analysis of the distribution characteristics at different dimensions and the comprehensive prevention and control in key areas, places, and populations during the peak incidence period.

Objective:To investigate the effects of preoperative pre-rehabilitation on early functional recovery after knee arthroplasty under the multidisciplinary collaboration mode of accelerated rehabilitation surgery.Methods:The clinical data of 51 patients who underwent total knee arthroplasty in the Department of Orthopedics, Jinjiang Hospital from September 2019 to December 2021 were retrospectively analyzed. These patients were divided into an observation group ( n = 24) and a control group ( n = 27). The observation group received pre-rehabilitation before knee replacement surgery, while the control group did not. After completing the admission procedures, patients in the observation group underwent rehabilitation evaluation in the rehabilitation clinic and received individualized rehabilitation training. The control group did not undergo preoperative pre-rehabilitation but underwent the same individualized rehabilitation training as the observation group. The rehabilitation specialist evaluated the patients' rehabilitation scores [hospital for special surgery knee (HSS) score, visual analog scale (VAS) score] at 2 and 5 days after surgery. The main outcome measures included the range of motion (ROM) of the patient's knee joint at 2 and 5 days after surgery, HSS score at 2 and 5 days after surgery, VAS score at 5 days after surgery, the number of days from surgery to discharge, the incidence of postoperative complications, and the rate of outpatient visits after surgery. Results:There was no significant difference in postoperative ROM of the knee joint between the observation and control groups at 2 days after surgery ( P > 0.05). However, there was a significant difference in score of ROM of the knee joint at 5 days after surgery between the two groups [(100.08 ± 7.75) points vs. (88.44 ± 16.09) points, t = 3.34, P = 0.002]. There was no significant difference in HSS score between the two groups at 2 days after surgery ( P > 0.05). However, there was a significant difference in HSS score between the two groups at 5 days after surgery [(62.84 ± 5.78) points vs. (57.09 ± 6.53) points, t = 3.31, P = 0.002]. There was a significant difference in VAS score (exercise) between the two groups at 5 days after surgery [(3.42 ± 1.02) points vs. (5.37 ± 1.15) points, t = -6.39, P < 0.001]. There was no significant difference in the number of days from surgery to discharge between the two groups ( P > 0.05). There was no significant difference in the incidence of postoperative complications between the two groups ( P > 0.05). However, there was a significant difference in the rate of outpatient visits between the two groups [7/17 vs. 1/26, χ2 = 4.45, P = 0.035]. Conclusion:Preoperative pre-rehabilitation in the accelerated rehabilitation surgery model under multidisciplinary collaboration can help improve the early function of patients undergoing total knee arthroplasty, reduce the pain of postoperative rehabilitation, improve the postoperative rehabilitation compliance, and ultimately enhance patient satisfaction with the surgery.

OBJECTIVE To analyze and identify the metabolites of isoimperatorin in normal rats in vivo. METHODS After the rats were intragastrically administered, the plasma, urine and feces samples of rats in normal and dosed groups were collected, and the samples were processed by solid phase extraction. Then, UHPLC-HRMS(Q-Exactive Orbitrap MS) high- resolution mass spectrometry was used to analyze biological samples, and the metabolites were screened and identified. RESULTS In both positive and negative ion modes, a total of 32 metabolites were accurately analyzed and identified based on the precise molecular masses obtained, chromatographic retention behavior, control mass spectral cleavage patterns, characteristic fragment ions, and relevant literature reports. The main metabolic pathways were furan ring opening, lactone hydrolysis, oxidation, methylation, glucuronidation, sulfation and their complex reactions. Among them, the glucuronidation product was discovered for the first time. CONCLUSION This study comprehensively clarifies the transformation pathways of isoimperatorin in rats, which can provide a basis for its pharmacodynamic study and metabolism study analysis of the other furocoumarins.

In this study, we cloned the complete coding sequence (CDS) of chicken foxp3 (chfoxp3) gene, analyzed its structure, and investigated its expression profile in different chicken tissues. To be specific, chfoxp3 was cloned from the splenic tissue of 50-day-old specific-pathogen-free chickens, and analyzed by using online bioinformatics tools or software. The expression profiles of the chfoxp3 gene in different chicken tissues were detected by quantitative real-time PCR (qRT-PCR). The results indicated that the chfoxp3 gene contains an 882-bp open reading frame, encoding 293 amino acids hydrophilic protein with a molecular weight of 33.44 kDa. The chFoxp3 protein has a forkhead domain and carries a nuclear localization signal, which is typical in the Fox transcription factor family. The secondary structure of chFoxp3 consists of α-helix (29.35%), extended chain (10.92%), β-turn (5.12%) and random coil (54.61%). The expression of chfoxp3 varied in different tissues. The expression levels of chfoxp3 in chicken heart and pancreas were higher than in spleen, bursa of Fabricius, thymus, and other immune organs (P < 0.01), which was quite different from that of mammals. Phylogenetic tree analysis showed that chFoxp3 belonged to the same clade as other wild birds did, but was far different from that of mammals. These results may facilitate further research on the role of chFoxp3 in immune regulation.
Amino Acid Sequence ; Animals ; Chickens/genetics* ; Cloning, Molecular ; Gene Expression Regulation ; Mammals/genetics* ; Phylogeny

Brain Injuries, Traumatic ; China ; Critical Care ; Cross-Sectional Studies ; Female ; Humans ; Intensive Care Units ; Male ; Renal Insufficiency

Objective: To analyze the epidemiological characteristics of infectious diseases at schools in Beijing from 2010 to 2020, providing evidence for the prevention and control strategies in school infectious diseases. Methods: Information on public health emergencies was collected from Public Health Emergency Reporting System (the subsystem of Chinese Disease Prevention and Control Information System) reported from 2010 to 2020. Results: A total of 146 public health emergencies and 138 public health emergencies of infectious diseases in schools were reported in Beijing from 2010 to 2020, including 4 291 cases with the rate of 2.32% and affected or exposed 185 179 cases. There were significant difference in mean annual incidence rates( χ 2=782.46, P <0.01). There were 71 events of respiratory infectious diseases and 66 events of intestinal infectious diseases, accounting for 51.45% and 47.83%, respectively. The annual incidence peaks of public health emergencies of infectious diseases were during March-June and October-December. The events mainly occurred in kindergartens and primary schools among each stage of school periods with 51 and 46 incidences respectively, which accounted for 70.29% of the total number of public health emergencies in schools. The leading infectious diseases among all the reported events in kindergartens and primary schools were hand foot mouth disease and varicella. Varicella and other infectious diarrhoeal diseases were at the top lists of infectious disease outbreaks at the secondary and university stages. Conclusion Infectious diseases events were the major type of public health emergencies at schools in Beijing from 2010 to 2020. Respiratory infectious diseases and intestinal infectious diseases were the keys to the prevention and control of public health emergencies related to school. It is necessary to strengthen the surveillance for public health emergencies especially for symptom surveillance. The prevention and control measures should be taken according to the characteristics of different age groups. At the same time, the prevention and control of school infectious diseases and the drill of the plan during peak periods need to be particularly strengthened.

Objective:To explore the effect of setting up an internal-cross disciplinary team (ICDT) in the intensive care unit (ICU) on a new model of overall treatment for patients with chronic critical illness (CCI).Methods:A 60-year-old male patient with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to ICU in the Second Affiliated Hospital of Fujian Medical University was introduced. The role of ICDT composed of physicians, nurses, respiratory therapists, physiotherapists, clinical dietitians and patients' family members in ventilator withdrawal and super-early rehabilitation was analyzed in this case.Results:The patient was diagnosed as AECOPD, type Ⅱ aspiration penumonia respiratory failure, septic shock. The ICDT in ICU carried out early rehabilitation treatment for the patient on the basis of traditional infection control and supportive treatment. Under the care of the ICDT, peripheral blood white blood cell count (WBC), neutrophil count (NEU), procalcitonin (PCT), arterial partial pressure of carbon dioxide (PaCO 2), maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), right excursion of diaphragm, sputum viscosity, tidal volume (VT) and respiratory rate (RR) were improved. Subsequently, the ventilator mode was gradually changed and the ventilator parameters were down-regulated. The ventilator was successfully weaned on the 10th day of treatment. After weaning, the patient's bedside pulmonary function indicators improved, and he was transferred out of ICU on the 15th day of treatment and discharged on the 20th day. The mental state of the patients was good and the quality of life was greatly improved in CCI outpatient follow-up. Conclusions:ICDT cooperation is very important for monitoring and treatment of CCI patients, which is beneficial to the super-early rehabilitation and prognosis improvement of critically ill patients.

The rapidly developing resistance of cancers to chemotherapy agents and the severe cytotoxicity of such agents to normal cells are major stumbling blocks in current cancer treatments. Most current chemotherapy agents have significant cytotoxicity, which leads to devastating adverse effects and results in a substandard quality of life, including increased daily morbidity and premature mortality. The death receptor of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can sidestep p53-dependent pathways to induce tumor cell apoptosis without damaging most normal cells. However, various cancer cells can develop resistance to TRAIL-induced apoptosis via different pathways. Therefore, it is critical to find an efficient TRAIL sensitizer to reverse the resistance of tumor cells to TRAIL, and to reinforce TRAIL's ability to induce tumor cell apoptosis. In recent years, traditional Chinese medicines and their active ingredients have shown great potential to trigger apoptotic cell death in TRAIL-resistant cancer cell lines. This review aims to collate information about Chinese medicines that can effectively reverse the resistance of tumor cells to TRAIL and enhance TRAIL's ability to induce apoptosis. We explore the therapeutic potential of TRAIL and provide new ideas for the development of TRAIL therapy and the generation of new anti-cancer drugs for human cancer treatment. This study involved an extensive review of studies obtained from literature searches of electronic databases such as Google Scholar and PubMed. "TRAIL sensitize" and "Chinese medicine" were the search keywords. We then isolated newly published studies on the mechanisms of TRAIL-induced apoptosis. The name of each plant was validated using certified databases such as The Plant List. This study indicates that TRAIL can be combined with different Chinese medicine components through intrinsic or extrinsic pathways to promote cancer cell apoptosis. It also demonstrates that the active ingredients of traditional Chinese medicines enhance the sensitivity of cancer cells to TRAIL-mediated apoptosis. This provides useful information regarding traditional Chinese medicine treatment, the development of TRAIL-based therapies, and the treatment of cancer.