OBJECTIVE To explore the effect and mechanism of embryonic intervention with Zuogui pill on the glucose tolerance in offsprings of pregnant rats with gestational diabetes mellitus. METHODS Pregnant rats were randomly divided into blank group， model group， positive control group （insulin glargine）， Zuogui pill low-， medium- and high-dose groups （4.725， 9.45， 18.9 g/kg）. In addition to the blank group， streptozotocin was injected intraperitoneally to establish a gestational diabetes mellitus rat model. From day 6 to day 18 of pregnancy， each group was given relevant medicine and distilled water intragastrically， once a day. After 21 days of birth， the body weight and body length of offsprings were recorded， and the area under the curve （AUC） was calculated through a glucose tolerance test. After 22 days of birth， fasting blood glucose （FBG）， fasting insulin （FINS） levels in serum， insulin sensitivity index （ISI）， and homeostasis model assessment of insulin resistance （HOMA-IR） were measured， and the morphological structure of pancreatic tissue was observed. The protein spectrum of pancreatic tissue was analyzed by tandem mass tag-based proteomics， and protein and mRNA expression levels of apolipoprotein A1（ApoA1）， solute carrier family 27 member 1 （Slc27a1）， kininogen 1（Kng1） and sodium/potassium-transporting ATPase subunit alpha 2 （Atp1a2）， solute carrier family 7 member 5 （Slc7a5）， solute carrier family 3 member 2 （Slc3a2）， bile acid-coenzyme A： amino acid N- acyltransferase （Baat）， eukaryotic translation initiation factor 2 subunit gamma （Eif2s3） were detected. RESULTS Compared with the model group， the body weight， body length and ISI of offsprings in the positive control group and Zuogui pill medium-dose group were significantly increased （P＜0.05）， while the glucose tolerance and islet cell proliferation were significantly improved， and the AUC， FBG， FINS and HOMA-IR were significantly decreased （P＜0.05）. There were 88 potential target proteins for the embryonic intervention of Zuogui pill in offsprings of pregnant rats with gestational diabetes mellitus，involving multiple pathways such as peroxisome proliferator-activated receptor （PPAR）， cyclic guanosine monophosphate-protein kinase G （cGMP-PKG）， fat digestion and absorption， and bile secretion. The proteins closely related to glucose metabolism and insulin resistance mainly included ApoA1， Slc27a1， Kng1， Atp1a2， Slc7a5， Slc3a2， Baat， and Eif2s3. Among them， compared with the model group， protein and mRNA expressions of Slc7a5， Slc3a2， and Baat in the pancreatic tissues of pregnant rat offsprings in the Zuogui pill medium-dose group were significantly up-regulated （P＜0.05）； protein and mRNA expressions of ApoA1， Slc27a1， Kng1， Atp1a2 and Eif2s3 were all significantly down-regulated （P＜0.05）. CONCLUSIONS The intervention of Zuogui pill in the embryonic period on offsprings of pregnant rats with gestational diabetes mellitus can improve their blood glucose levels and pancreatic pathological morphology. The mechanism may be related to the upregulation of the expressions of Slc7a5， Slc3a2， and Baat and the down-regulation of ApoA1， Slc27a1， Kng1， Atp1a2 and Eif2s3 expressions in the PPAR， cGMP-PKG， fat digestion and absorption， and bile secretion pathways.

Objective To identify the exact locations of the brain being irradiated in advanced nasopharyngeal carcinoma(NPC)patients during radiotherapy,and to analyze the differences in brain dose distribution between advanced NPC patients treated with intensity-modulated radiotherapy(IMRT)and volumetric modulated arc therapy(VMAT).Methods Based on the CT brain template provided by the Montreal Neurological Institute,the brain dose distribution was analyzed with voxel-based method.Results For advanced NPC patients,VMAT plans did not demonstrate superiority in normal brain tissue sparing,while IMRT performed better,with advantages observed in regions such as the brainstem,the posterior lobe of the cerebellum,the anterior lobe of the cerebellum,temporal lobes,occipital lobes,limbic lobes,and certain areas of the subcortical regions.Conclusion IMRT is advantageous over VMAT in protecting the normal brain tissues in advanced NPC patients.

Osteoporotic proximal humeral fracture (OPHF) is one of the common osteoporotic fractures in the aged, with an incidence only lower than vertebral compression fracture, hip fracture, and distal radius fracture. OPHF, secondary to osteoporosis and characterized by poor bone quality, comminuted fracture pattern, slow healing, and severely impaired shoulder joint function, poses a big challenge to the current clinical diagnosis and treatment. In the field of diagnosis, treatment, and rehabilitation of OPHF, traditional Chinese and Western medicine have accumulated rich experience and evidence from evidence-based medicine and achieved favorable outcomes. However, there is still a lack of guidance from a relevant consensus as to how to integrate the advantages of the two medical systems and achieve the integrated diagnosis and treatment. To promote the diagnosis and treatment of OPHF with integrated traditional Chinese and Western medicine, relevant experts from Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine have been organized to formulate Expert consensus on the diagnosis and treatment of osteoporotic proximal humeral fracture with integrated traditional Chinese and Western medicine ( version 2024) by searching related literatures and based on the evidences from evidence-based medicine. This consensus consists of 13 recommendations about the diagnosis, treatment and rehabilitation of OPHF with integrated traditional Chinese medicine and Western medicine, aimed at standardizing, systematizing, and personalizing the diagnosis and treatment of OPHF with integrated traditional Chinse and Western medicine to improve the patients ′ function.

Objective:To evaluate the application of a multi-task learning-based light-weight convolution neural network (MTLW-CNN) for the automatic segmentation of organs at risk (OARs) in thorax.Methods:MTLW-CNN consisted of several layers for sharing features and 3 branches for segmenting 3 OARs. 497 cases with thoracic tumors were collected. Among them, the computed tomography (CT) images encompassing lung, heart and spinal cord were included in this study. The corresponding contours delineated by experienced radiation oncologists were ground truth. All cases were randomly categorized into the training and validation set ( n=300) and test set ( n=197). By applying MTLW-CNN on the test set, the Dice similarity coefficients (DSCs) of 3 OARs, training and testing time and space complexity (S) were calculated and compared with those of Unet and DeepLabv3+ . To evaluate the effect of multi-task learning on the generalization performance of the model, 3 single-task light-weight CNNs (STLW-CNNs) were built. Their structures were totally the same as the corresponding branches in MTLW-CNN. After using the same data and algorithm to train STLW-CNN, the DSCs were statistically compared with MTLW-CNN on the testing set. Results:For MTLW-CNN, the averages (μ) of lung, heart and spinal cord DSCs were 0.954, 0.921 and 0.904, respectively. The differences of μ between MTLW-CNN and other two models (Unet and DeepLabv3+ ) were less than 0.020. The training and testing time of MTLW-CNN were 1/3 to 1/30 of that of Unet and DeepLabv3+ . S of MTLW-CNN was 1/42 of that of Unet and 1/1 220 of that of DeepLabv3+ . The differences of μ and standard deviation (σ) of lung and heart between MTLW-CNN and STLW-CNN were approximately 0.005 and 0.002. The difference of μ of spinal cord was 0.001, but σof STLW-CNN was 0.014 higher than that of MTLW-CNN.Conclusions:MTLW-CNN spends less time and space on high-precision automatic segmentation of thoracic OARs. It can improve the application efficiency and generalization performance of the models.

During the occurrence, development and treatment of gynecological tumors, mainly including cervical cancer, endometrial cancer and ovarian cancer, patients are prone to sleep disorders which seriously affect the quality of life. At present, there are few relevant studies on gynecological tumors associated with sleep disorders, and there is a lack of research on TCM syndromes, so there is no targeted treatment plan. This article mainly introduces the present situation of diagnosis and treatment of sleep disorders caused by gynecological tumors in Chinese and western medicine, to provide reference for further study.

Objective:To explore a three-dimensional dose distribution prediction method for the left breast cancer radiotherapy planning based on full convolution network (FCN), and to evaluate the accuracy of the prediction model.Methods:FCN was utilized to achieve three-dimensional dose distribution prediction. First, a volumetric modulated arc therapy (VMAT) plan dataset with 60 cases of left breast cancer was built. Ten cases were randomly chosen from the dataset as the test set, and the remaining 50 cases were used as the training set. Then, a U-Net model was built with the organ structure matrix as inputs and dose distribution matrix as outputs. Finally, the model was adopted to predict the dose distribution of the cases in the test set, and the predicted 3D doses were compared with actual planned results.Results:The mean absolute differences of PTV, ipsilateral lung, heart, whole lung and spinal cord for 10 cases were (119.95±9.04) cGy, (214.02±9.04) cGy, (116.23±30.96) cGy, (127.67±69.19) cGy, and (37.28±18.66) cGy, respectively. The Dice similarity coefficient (DSC) of the prediction dose and the planned dose in the 80% and 100% prescription dose range were 0.92±0.01 and 0.92±0.01. The γ rate of 3 mm/3% in the area of 80% and 10% prescription dose range were 0.85±0.03 and 0.84±0.02. Conclusion:FCN can be used to predict the three-dimensional dose distribution of left breast cancer patients undergoing VMAT.

Objective: To study a lung dose prediction method for the early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy based on machine learning algorithm, and to evaluate the feasibility of application in planning quality assurance. Methods: A machine learning algorithm was utilized to achieve DVH prediction. First, an expert plan dataset with 125 cases was built, and the geometric features of ROI, beam angle and dose-volume histogram(DVH) parameters in the dataset were extracted. Following a correlation model was established between the features and DVHs. Second, the geometric and beam features from 10 cases outside the training pool were extracted, and the model was adopted to predict the achievable DVHs values of the lung. The predicted DVHs values were compared with the actual planned results. Results: The mean squared errors of external validation for the 10 cases in mean lung dose (MLD)MLD and V₂₀ of the lung were 91.95 cGy and 3.12%, respectively. Two cases whose lung doses were higher than the predicted values were re-planned, and the results showed that the the lung doses were reduced. Conclusion It is feasible to utilize the anatomy and beam angle features to predict the lung DVH parameters for plan evaluation and quality assurance in early stage NSCLC patients treated with stereotactic body radiotherapy

Objective: To investigate the clinical efficacy and adverse effects of stereotactic body radiotherapy (SBRT) in the treatment of T₂N₀M₀ non-small cell lung cancer (NSCLC) patients. Methods: By retrospectively analyzing the clinical data of 30 inoperable patients with stage T₂N₀M₀ NSCLC treated by SBRT, the overall survival, progression-free survival, cancer-specific survival and adverse effects were determined. Results: The median follow-up was 18.4 months. The 1-, 2-, and 3-year overall survival rates were 92.2%, 92.2% and 80.6%, respectively. The corresponding cause-specific survivals were 95.7%, 95.7% and 83.7%. The progression-free survivals were 70.2%, 54.1% and 40.6%. The local control rates were 100%, 94.4%, and 94.4%. The regional controls were 84.2%, 72.1%, and 54.1%; and distant controls were 84.6%, 72.4% and 64.3%, respectively. Twenty patients (66.7%) developed symptoms of grade 1 radiation-related toxicities: dyspnea, chest pain, fatigue, cough, esophagitis, or pneumonia. Among these, 5 patients suffered grade ≥2 radiation pneumonitis, and one patient experienced grade 4 radiation pneumonitis. Conclusions SBRT was efficient and safe for patients with inoperable T₂N₀M₀ NSCLC, imposing tolerable toxicities.

Objective: To investigate the feasibility and dosimetric characteristics of using dual-arc volumetric modulated arc therapy and multiple partial-arc VMAT for T3 lung cancer. Methods: From June 2016 to May 2018, thirteen lung cancer patients with large planning target volume were replanned with dual full arcs VMAT(F-VMAT) and six partial-arc s VMAT(P-VMAT)on RayStation v4.5 RayArc function.PTV volume median was 550.9cm³(ranged 402.2-834.8cm³) and to a prescribed dose of 60 Gy in 30 fractions.Equivalent target coverage was required for all plans, and clinical goals were evaluated using various dose-volume metrics.These included PTV dose conformity, mean lung/heart dose, lung V₅, V₁₀, V₂₀, V₃₀, heart V₃₀ and V₄₀, and Dmax of spinal canal.The total monitor units (MUs) were also examined. Results: All VMAT plans satisfied the treatment criteria.F-VMAT achieved better homogeneity index(HI) and MUs than P-VMRT(t=-3.904, P=0.002), and the conformal number(CN) of tumor volumes was likely clinically indistinguishable.However, F-VMAT significantly reduced lung V₅, V₁₀ and mean lung dose[V5: (51.31±5.36)% vs.(43.44±5.28)%, t=6.908, P=0.00; V10: (38.34±3.26)% vs.(34.05±3.74)%, t=4.632, P=0.001; Dmean: (1 449±117.19)cGy vs.(1 375.38±148.98)cGy, t=4.93, P=0.00], and heart dosimetric parameters were also observed in favor of P-VMRT[V₃₀: (20.6±10.4)% vs.(16.4±8.9)%, t=3.822, P=0.02; V₄₀: (14.6±7.5)% vs.(11.88±7.1)%, t=3.096, P=0.009; Dmean: (1 442.9±651.2)cGy vs.(1 263.5±605.6)cGy, t=3.986, P=0.02], and there were no statistically significant differences in lung V₂₀, V₃₀ and spinal cord Dmax between the two groups(all P>0.05). Conclusion VMAT is an effective treatment for stage T3 lung cancer patients.The primary advantage of P-VMAT was the reduction in low dose area and decreased risk of symptomatic radioactive lung injury.It may be a priority for pulmonary malignancy patients with the large planning target volume.