Objective To compare the dosimetric and radiobiological differences of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) in craniospinal irradiation. Methods The CT images of 15 patients who received craniospinal irradiation in our hospital were selected. The target volumes and organs at risk (OARs) were contoured, and HT and VMAT plans were designed. The dosimetric parameters of the two plans were compared. A Matlab program based on equivalent uniform dose was developed to calculate the normal tissue complication probability (NTCP). The NTCP values of the two plans were compared. Results The homogeneity index of the target volume in the HT group was better than that in the VMAT group, with values of 0.06 ± 0.01 and 0.08 ± 0.24, respectively, and the difference was statistically significant (P=0.03). However, there was no significant difference in the conformity index of the target volume (P>0.05). There were significant differences in key indicators (D_mean, V₅, D_max) of the lungs, liver, lens, and eyeballs between the two groups (P<0.05). Regarding OARs, the NTCP values of the lens, optic chiasm, lungs, and liver in the HT and VMAT groups were as follows: 0.04 ± 0.03 vs. 0.1 ± 0.06 in the left lens, 0.04 ± 0.06 vs. 0.1 ± 0.07 in the right lens, 0.16 (0.14-0.17) vs. 0.21 (0.18-0.24) in the optic chiasm, 3.89 × 10⁻⁴ (2.45 × 10⁻⁴-7.3 × 10⁻⁴) vs. 8.95 × 10⁻⁴ (5.19 × 10⁻⁴-1.75 × 10⁻³) in the lungs, and 3.45 × 10⁻⁸ (6.0 × 10⁻⁹-1.036 × 10⁻⁷) vs. 9.54 × 10⁻⁸ (1.70 × 10⁻⁸-2.056 × 10⁻⁷) in the liver; the HT group was superior to the VMAT group, and all differences were statistically significant (P<0.05). The NTCP values of the heart in the two groups were 1.35 × 10⁻⁸ (6.34 × 10⁻⁹-2.06 × 10⁻⁹) vs. 5.06 × 10⁻⁹ (2.29 × 10⁻⁹-7.9 × 10⁻⁹), significantly lower in the VMAT group than in the HT group (P<0.05). Conclusion HT has high homogeneity and consistency. The two plans have their own advantages in OAR protection. For OARs with no significant differences in physical dosimetry, NTCP results can be used as a reference. Therefore, comparing the dosimetric parameters and OAR NTCP of HT and VMAT plans can help select the optimal clinical treatment strategy.

Occupational pneumoconiosis remains the most common occupational disease in China, with occupational mineral dust exposure being its primary causative factor. Although national standards for online monitoring and early warning systems of coal mine dust concentrations have been established, national occupational health standards for rapid and online monitoring of dust concentration and particle size distribution in other industries are still limited. Among dust concentration sensor technologies, the light scattering method is the preferred choice for online dust monitoring owing to its wide measurement range and low cost. The beta-ray absorption method is mature but highly sensitive to humidity. The electrostatic induction method offers high sensitivity, simple structure, and low maintenance costs but exhibits high errors in low-concentration dust monitoring. The tapered element oscillating microbalance method is highly sensitive but costly. Multi-sensor data fusion technology can improve monitoring reliability, however, mature domestic products are not yet available. For monitoring dust particle size distribution, sieving and sedimentation methods are cumbersome. The aerodynamic method shows broad prospects in the online monitoring of respirable dust but has obvious measurement errors for larger dust particles. The use of optical measurement method is limited by dust morphology and is not suitable for monitoring coal dust particle size distribution. The electrical mobility method is primarily applicable to submicron dust. Future research should focus on promoting the application of monitoring technology for respirable dust particle size distribution in online monitoring of industrial dust. By integrating Internet of Things, data mining, and artificial intelligence technologies, along with multi-sensor data fusion and numerical simulation, dust concentration prediction models can be established to achieve accurate dust concentration monitoring and early warning of exceedances. The advancements of technologies will provide scientific support for the assessment of industrial dust hazards and the prevention and control of occupational pneumoconiosis.

Objective:To explore the application value of radiomics, deep learning, and their combined models in predicting the efficacy of radioiodine adjuvant therapy in patients with papillary thyroid cancer (PTC).Methods:A retrospective analysis was conducted on the clinical and imaging data of 131 PTC patients (38 males, 93 females; age 41(33, 48) years) who received first 131I treatment at the Affiliated Hospital of Guilin Medical University from January 2018 to March 2023. Patients were randomly divided into a training set ( n=105) and a test set ( n=26) at the ratio of 8∶2. Multivariate logistic regression analysis was used to screen clinical features to determine independent predictors affecting the efficacy of 131I therapy. Radiomics and deep learning features were extracted from the enhanced CT scans and were combined by using the extremely randomized trees (ExtraTrees) algorithm to construct radiomics, deep learning, and combined models. The predictive abilities of the models were evaluated by AUC, and the Delong test was applied to compare the difference between AUCs. Results:Higher pre-ablation stimulated thyroglobulin (ps-Tg) levels (odds ratio( OR)=1.060, 95% CI: 1.025-1.095, P=0.004) and bilateral lesions ( OR=5.085, 95% CI: 1.452-17.814, P=0.033) were independent predictors of the efficacy of 131I therapy in intermediate to high-risk PTC patients. In the training set, the radiomics model (AUC=0.853) and combined model (AUC=0.880) significantly outperformed the deep learning model (AUC=0.711; Z values: 2.48, 3.09, P values: 0.013, 0.002), while there was no statistically significant difference between the radiomics and combined models ( Z=0.51, P=0.610). In the test set, AUCs of the radiomics, deep learning, and combined models were 0.746, 0.624, and 0.876, respectively, and the AUC of the combined model was higher than that of the radiomics model or deep learning model ( Z values: 2.05, 1.99, P values: 0.040, 0.047). Conclusion:The combined model demonstrates superior performance over the standalone radiomics model and deep learning model in predicting the efficacy of 131I treatment in PTC patients.

Objective To establish a three-dimensional(3-D)structural mode-based nursing quality evaluation index system for the bleeding risk care in patients with deep venous thrombosis(DVT)of lower extremity receiving catheter-directed thrombolysis(CDT),so as to provide a reference for the normalization and standardization of bleeding risk care.Methods Based on the 3-D structural mode,through literature review,clinical practice research and group discussion,the first draft of nursing quality evaluation index system for CDT bleeding risk care was formulated.Using Delphi method,two rounds of letter inquiry were conducted,and the index content and index weighting were determined.Results The nursing quality evaluation index system included 3 level-Ⅰ indicators,11 level-Ⅱ indicators and 58 level-Ⅲ indicators.Two rounds of expert consultation were conducted,with 30 questionnaires for each round.The valid recovery rate of the questionnaire was 100.00％,indicating that expert's enthusiasm was higher.In the first round of letter inquiry,28 experts(93.3％)submitted suggestions for modification,and in the second round of letter inquiry,15 experts(50.0％)submitted suggestions for draft modification.The level of expert authority was as follows:the basis coefficient of expert judgment(Ca)was 0.93,the coefficient of expert familiarity with items(Cs)was 0.90,and the authority coefficient was 0.92.The degree of expert opinion coordination assessed by Kendall's harmony coefficient(Kendall's W)was 0.18-0.26(P＜0.05),and the coefficient of variation of each dimension was less than 0.15.Conclusion The nursing quality evaluation index system established in this study is scientific,reliable and practical.It can provide certain useful reference for the evaluation of CDT bleeding risk care quality.

ObjectiveObesity has been identified as one of the most important risk factors for cognitive dysfunction. Physical exercise can ameliorate learning and memory deficits by reversing synaptic plasticity in the hippocampus and cortex in diseases such as Alzheimer’s disease. In this study, we aimed to determine whether 8 weeks of treadmill exercise could alleviate hippocampus-dependent memory impairment in high-fat diet-induced obese mice and investigate the potential mechanisms involved. MethodsA total of sixty 6-week-old male C57BL/6 mice, weighing between 20-30 g, were randomly assigned to 3 distinct groups, each consisting of 20 mice. The groups were designated as follows: control (CON), high-fat diet (HFD), and high-fat diet with exercise (HFD-Ex). Prior to the initiation of the treadmill exercise protocol, the HFD and HFD-Ex groups were fed a high-fat diet (60% fat by kcal) for 20 weeks. The mice in the HFD-Ex group underwent treadmill exercise at a speed of 8 m/min for the first 10 min, followed by 12 m/min for the subsequent 50 min, totally 60 min of exercise at a 0° slope, 5 d per week, for 8 weeks. We employed Y-maze and novel object recognition tests to assess hippocampus-dependent memory and utilized immunofluorescence, Western blot, Golgi staining, and ELISA to analyze axon length, dendritic complexity, number of spines, the expression of c-fos, doublecortin (DCX), postsynaptic density-95 (PSD95), synaptophysin (Syn), interleukin-1β (IL-1β), and the number of major histocompatibility complex II (MHC-II) positive cells. ResultsMice with HFD-induced obesity exhibit hippocampus-dependent memory impairment, and treadmill exercise can prevent memory decline in these mice. The expression of DCX was significantly decreased in the HFD-induced obese mice compared to the control group (P<0.001). Treadmill exercise increased the expression of c-fos (P<0.001) and DCX (P=0.001) in the hippocampus of the HFD-induced obese mice. The axon length (P<0.001), dendritic complexity (P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P<0.001) in the hippocampus were significantly decreased in the HFD-induced obese mice compared to the control group. Treadmill exercise increased the axon length (P=0.002), dendritic complexity(P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P=0.001) of the hippocampus in the HFD-induced obese mice. Our study found a significant increase in MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of HFD-induced obese mice compared to the control group. Treadmill exercise was found to reduce the number of MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of obese mice induced by a HFD. ConclusionTreadmill exercise led to enhanced neurogenesis and neuroplasticity by increasing the axon length, dendritic complexity, dendritic spine numbers, and the expression of PSD95 and DCX, decreasing the number of MHC-II positive cells and neuroinflammation in HFD-induced obese mice. Therefore, we speculate that exercise may serve as a non-pharmacologic method that protects against HFD-induced hippocampus-dependent memory dysfunction by enhancing neuroplasticity and neurogenesis in the hippocampus of obese mice.

Objective:To explore the application value of radiomics, deep learning, and their combined models in predicting the efficacy of radioiodine adjuvant therapy in patients with papillary thyroid cancer (PTC).Methods:A retrospective analysis was conducted on the clinical and imaging data of 131 PTC patients (38 males, 93 females; age 41(33, 48) years) who received first 131I treatment at the Affiliated Hospital of Guilin Medical University from January 2018 to March 2023. Patients were randomly divided into a training set ( n=105) and a test set ( n=26) at the ratio of 8∶2. Multivariate logistic regression analysis was used to screen clinical features to determine independent predictors affecting the efficacy of 131I therapy. Radiomics and deep learning features were extracted from the enhanced CT scans and were combined by using the extremely randomized trees (ExtraTrees) algorithm to construct radiomics, deep learning, and combined models. The predictive abilities of the models were evaluated by AUC, and the Delong test was applied to compare the difference between AUCs. Results:Higher pre-ablation stimulated thyroglobulin (ps-Tg) levels (odds ratio( OR)=1.060, 95% CI: 1.025-1.095, P=0.004) and bilateral lesions ( OR=5.085, 95% CI: 1.452-17.814, P=0.033) were independent predictors of the efficacy of 131I therapy in intermediate to high-risk PTC patients. In the training set, the radiomics model (AUC=0.853) and combined model (AUC=0.880) significantly outperformed the deep learning model (AUC=0.711; Z values: 2.48, 3.09, P values: 0.013, 0.002), while there was no statistically significant difference between the radiomics and combined models ( Z=0.51, P=0.610). In the test set, AUCs of the radiomics, deep learning, and combined models were 0.746, 0.624, and 0.876, respectively, and the AUC of the combined model was higher than that of the radiomics model or deep learning model ( Z values: 2.05, 1.99, P values: 0.040, 0.047). Conclusion:The combined model demonstrates superior performance over the standalone radiomics model and deep learning model in predicting the efficacy of 131I treatment in PTC patients.

Odontogenic maxillary sinusitis(OMS)is a subtype of maxillary sinusitis(MS).It is actually inflammation of the maxillary sinus that secondary to adjacent infectious maxillary dental lesion.Due to the lack of unique clinical features,OMS is difficult to distinguish from other types of rhinosinusitis.Besides,the characteristic infectious pathogeny of OMS makes it is resistant to conventional therapies of rhinosinusitis.Its current diagnosis and treatment are thus facing great difficulties.The multi-disciplinary cooperation between otolaryngologists and dentists is absolutely urgent to settle these questions and to acquire standardized diagnostic and treatment regimen for OMS.However,this disease has actually received little attention and has been underrepresented by relatively low publication volume and quality.Based on systematically reviewed literature and practical experiences of expert members,our consensus focuses on characteristics,symptoms,classification and diagnosis of OMS,and further put forward multi-disciplinary treatment decisions for OMS,as well as the common treatment complications and relative managements.This consensus aims to increase attention to OMS,and optimize the clinical diagnosis and decision-making of OMS,which finally provides evidence-based options for OMS clinical management.

This study was designed to investigate the effect of graphene far-infrared irradiation on the relevant immune indexes of Lewis lung cancer tumor bearing mice after cisplatin chemotherapy.A lung cancer tumor-bearing mouse immune damage model was established in Lewis mice,and the model mice were divided into a model control group(CTL),a chemotherapy group(DDP),a low-power graphene group(G-Low,30℃),and a high-power graphene group(G-High,35℃).Mice in all groups were subjected to detect the tumor volume growth rate,thymus index and spleen index,spleen lymphocyte proliferation activity and NK cell killing activity,the number of white blood cells in the peripheral blood and the ratio of CD4+T/CD8+T in the peripheral blood.Compared with the CTL group,the thymus index and spleen index of the DDP group were significantly lower(P＜0.01);compared with the DDP group,the tumor inhibition rate of the G-Low group was significantly improved(P＜0.05),and the tumor inhibition rate of the G-High group was extremely significantly improved(P＜0.01).The thymus index,white blood cell count,peripheral blood CD4+T/CD8+T ratio,and NK cell killing activity of the spleen in the G-High group were significantly higher than those in the DDP group(P＜0.05).Taken together,Graphene far-infrared irradiation has a good repair effect on the immune damage caused by cisplatin chemotherapy in Lewis lung cancer tumor-bearing mice,and can significantly inhibit tumor growth.

Objective:This study aims to develop a country prioritization index system for China's international vaccine cooperation,providing a screening tool and referenceindicators.Method:Based on the PESTEL analysis model,the indicator system was preliminarily determined through literature review and expert interviews.Additional expert consultations were conducted to refine and finalize this system.The weight of the indicators was determined using the Analytic Hierarchy Process(AHP).Result:A comprehensive screening index system for identifying preferred countries in China's international vaccine cooperation has been established.This indicator system covers 5 factors including economy,politics,society,technology,law,and regulations,with 15 secondary indicators and 34 tertiary indicators subdivided.Legal and regulatory factors received the highest weight(0.48),followed by economic(0.23),political(0.15),social(0.095),and technological(0.045).The authority of the experts and the coordination of their opinions were both deemed satisfactory.All judgment matrices in the AHP passed the consistency tests,affirming the reliability of the indicator weight results.Conclusion:The study has established an evidence-based and reliable index system for prioritizing countries in China'sinternational vaccine cooperation,providing references for the selection process.

In order to investigate the regulatory effect of Codonopsis saponins on the immunosup-pression caused by H9N2 subtype avian influenza virus(AIV)infection,rat pulmonary microvas-cular endothelial cells(RPMECs)were incubated with different concentrations of Codonopsis sap-onins(5,10 and 20 mg/L).The expression level of PD-L1 was detected by RT-PCR and flow cy-tometry,and the contents of TNF-α,IFN-y and IL-10 in supernatant were detected by ELISA kit.The titer of H9N2 AIV in supernatant was detected by plaque method.Then,a co-culture system of RPMECs and T cells was established using a Transwell plate with an aperture of 8 &mu;m to mimic the migration of circulating T cells across microvessels to the site of viral infection.RPMECs were cultured in the upper chamber of Transwell,inoculated with H9N2 AIV,supplemented with 20 mg/L Codonopsis saponins 1 h later,and T cells 36 h later.After 8 h of treatment,T cells in the lower compartment were collected and the proportions of CD4+T cells and CD8+T cells were detected by flow cytometry,the expression levels of IL-2,IFN-y and granzyme B in the superna-tant were detected by ELISA,and the proportions of perforin-1 positive T cells were detected by flow cytometry.The proliferation activity of T cells was detected with the MTT cell proliferation and cytotoxicity assay kit,and the percentage of apoptotic cells was detected by flow cytometry af-ter staining of T cells with Annexin V-FITC/PI.The experimental results showed that Codonopsis saponins could significantly reduce the expression level of PD-L1,IL-10 and TNF-α in RPMECs in-duced by H9N2 AIV infection,and reduce the apoptosis rate of T cells.However,the expression levels of IL-2,IFN-y,perforin-1 and granzyme B in transendothelial migration T cells and the pro-liferation activity of T cells were significantly increased.In this study,Codonopsis saponins can sig-nificantly inhibit the expression of H9N2 AIV-induced PD-L1 in RPMECs,enhance the antiviral function of T cells migrating across the endothelial layer,and enhance the resistance of host to H9N2 AIV.