Objective This study compared organ doses and effective doses in typical adult patients during dental CBCT examinations using a head-and-neck anthropomorphic phantom and a whole-body phantom. It aimed to determine an appropriate method for evaluating effective dose in dental CBCT. Methods A domestically manufactured dental CBCT unit was used to scan an adult male anthropomorphic phantom under simulated clinical conditions. Thermoluminescent dosimeters were placed on organs and tissues of a whole-body anthropomorphic phantom. Organ equivalent doses were measured, and effective doses were calculated using two approaches: one based on all organ doses from the whole-body phantom, and the other based only on head-and-neck organ doses. Entrance surface air kerma (K_a,e) was also measured at the lens of the eye, thyroid, thymus, and gonads. Results The effective dose estimated with the whole-body phantom was 382.03 μSv. The effective dose estimated with the head-and-neck phantom was 354.03 μSv. The radiation dose to head-and-neck organs and tissues accounted for 92.7% of the total effective dose. The highest K_a,e values were found in the parotid glands, followed by the lens of the eye. Conclusion During dental CBCT scanning, the contribution of organ below the head and neck to the total effective dose is limited. To simplify dose assessment procedures, the effective dose for the patient can be evaluated using only a head-and-neck phantom.

ObjectiveBased on the TCM theory of "Yang transforms materials to Qi while Yin constitutes material form"， this paper explored the effects of Zuogui Wan and Yougui Wan on the molecular mechanism of mitochondrial biogenesis during the adipogenic differentiation process of rat bone marrow mesenchymal stem cells （BMSCs） by mediating peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α） and peroxisome proliferators-activated receptor γ （PPARγ）， providing theoretical support for the prevention and treatment of postmenopausal osteoporosis （PMOP） using Zuogui Wan and Yougui Wan. MethodsBMSCs were divided into a blank group， Zuogui Wan （ZGW） group， Yougui Wan （YGW） group， and Progynova group. Cell identification was performed using flow cytometry. The growth curves of BMSCs were plotted using the methylthiazolyldiphenyl-tetrazolium bromide （MTT） method， and the effects of Zuogui Wan and Yougui Wan on the proliferation of BMSCs were detected. The Oil red O staining method was used to detect lipid droplet formation. The Western blot method was used to detect the expression of adipogenesis-related factors PPARγ， CCAAT/enharcer-binding protein （C/EBP）α， C/EBPβ， lipoprotein lipase （LPL） protein， brown adipose tissue-related （BAT） proteins PGC-1α， uncoupcing protein 1 （UCP1）， PR domdin-containing protein 16 （PRDM16）， mitochondrial biogenesis-related PGC-1α， nuclear respiratory factor 1 （Nrf1）， nuclear factor E₂-related factor 2 （Nrf2）， and mitochondrial transcription factor A （TFAM）. The expression of adipogenesis-related factors PPARγ， C/EBPα， C/EBPβ， LPL genes， and the copy number of cytochrome B （CytoB mtDNA） gene was detected using real-time polymerase chain reaction （Real-time PCR）. Mitochondrial ultrastructure was detected using transmission electron microscopy. ResultsCompared with that in the blank group， the proliferation ability of BMSCs in each treatment group increased continuously as the intervention progressed， and lipid droplets significantly decreased after the drug intervention. The mRNA and protein expression levels of adipogenesis-related factors PPARγ， C/EBPα， C/EBPβ， and LPL were significantly downregulated （P<0.01）， while those of the BAT-related factors PGC-1α， UCP1， PRDM16 were significantly upregulated （P<0.01）. The number of mitochondria increased， accompanied by reduced swelling. The double membrane and cristae structure were clear， and the internal cristae rupture was reduced. The copy number of CytoB mtDNA in each treatment group was significantly increased （P<0.01）. The protein expression levels of mitochondrial biogenesis-related PGC-1α， Nrf1， Nrf2， and TFAM in each treatment group were significantly increased （P<0.01）. ConclusionBoth Zuogui Wan and Yougui Wan can prevent and treat PMOP by intervening in mitochondrial biogenesis in BMSCs through PGC-1α/PPARγ.

Objective:To investigate how gut microbiota changes during prostate cancer radiotherapy and decipher the relationship of gut microbiota with disease progression and chronic radiation enteritis.Methods:Thirty-one patients with prostate cancer were included in this study,admitted to The First Affiliated Hospital of Xinjiang Medical University from September 2022 to December 2023.The clinical data and stool samples of the patients were collected,and patients were followed up.The collected stool specimens were subjected to 16S rRNA se-quencing to detect gut microbiota and bioinformatics analysis.Results:The relative abundance of phyla such as Firmicutes and Actinobac-teria increased,and that of Bacteroidetes decreased(P<0.05)with an increasing radiotherapeutic dose,while beta diversity was significantly higher(P=0.001).The relative abundance of the phylum Actinobacteria was significantly higher in the prostate cancer progression group than in the non-progression group(P<0.05),the relative abundances of genera such as Sutterella and Haemophilus were significantly higher in the progression group(P<0.05).That of Verrucomicrobia and its offshoots in Akkermansia was higher in the chronic radiation enteritis than in the non-enteritis group(P<0.05),while the relative abundances of Coprococcus_1 and Catabacter in the non-enteritis group were higher than those in the enteritis group(P<0.05).Conclusions:Radiotherapy dose accumulation significantly remodeled the floral structure.Sutterella and Haemophilus of the phylum Proteobacteria might be key flora in prostate cancer recurring early after treatment.An augmen-ted abundance of Akkermansia might increase the risk of chronic radiation enteritis,whereas the flora under the Lachnospiraceae branch might exert aprotective effect against chronic radiation enteritis.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

This paper summarizes the progress of theoretical research and practice of One Health in China,and discusses the paradigm of One Health governance to improve the prevention and control of infectious diseases in China and the world,and provide an example for the improvement of the public health system.In particular,China has long history to apply the concept of One Health in the national schistosomiasis control programmes and patriotic health campaigns,which were not only focusing on human health,but also emphasizing the sustainable development of animal health and ecological environment.At the same time,the application of tools such as system dynamics model,eDNA technology,One Health economic assessment and global One Health index(GOHI)in the field of disease control and environmental health provides technical support for the concept of One Health.Despite the challenges of practical application of these tools,the One Health concept will play a greater role in providing sustainable solutions for human-animal-environmental health by strengthening interdisciplinary collaboration,improving standardization protocols and promoting inter-national cooperation.

Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.

Objective:To investigate the prevalence of flight fatigue among helicopter flying personnel and analyze its contributors in order to provide data for related interventions.Methods:A cross-sectional study was conducted among 404 helicopter flying personnel between October 8, 2021 and July 31, 2022. Data was collected using a self-designed questionnaire, involving the demography of these subjects, sleep-related factors, flight fatigue, perceived causes of fatigue and coping strategies. The Pittsburgh Sleep Quality Index (PSQI), National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Modified Fatigue Impact Scale (MFI-20) were used to assess sleep quality, mental workload, and levels of flight fatigue over the past month. The total scores of MFI-20 were compared across demographic groups, and correlations with PSQI and NASA-TLX scores were analyzed. Multiple linear regression was performed to identify the determinants of flight fatigue.Results:①Demography: among the 404 helicopter flying personnel, 92.8% (375/404) were pilots and 7.2% (29/404) navigators. As for years of service, 41.6% (168/404) served less than 5 years, while 58.4% (236/404) served more than 5 years. 37.9% (153/404) had a family history of insomnia. 18.8% (76/404) did not habitually nap, 68.9% (226/328) napped for ≤30 min, 31.1% (102/328) napped over 30 min, and 18.3% (74/404) had insomnia over the past month. As for helicopter flying personnel, 75.5% (305/404) reported experiencing fatigue, with 69.1% (279/404) attributing it to flight-related factors and 51.5% (208/404) using coffee as a countermeasure.②Scale scores: the total score of PSQI was [5 (3, 7)], while the highest daytime dysfunction score was [1(0, 2)]. The total score of NASA-TLX was [39.19 (26.57, 51.97)], and the effort score was the highest [10.31(5.07, 14.60)]. The total score of MFI-20 averaged (47.28±14.88), with the mental fatigue score being the highest [(10.03±4.42)]. ③Comparisons of MFI-20 total scores: flying personnel with ≤5 years of flying experience had higher MFI-20 total scores than those with >5 years, and those with a family history of insomnia had higher scores than those without ( t=3.35, 2.44, P=0.001, 0.015). Individuals with insomnia over the past month had higher scores than non-insomniacs ( t=3.33, P=0.001). Significant differences in MFI-20 scores were observed based on nap duration ( F=19.95, P<0.001). Non-nappers had higher scores than those napping for ≤30 min ( P=0.005). Flying personnel who napped for >30 min had higher scores than those did not ( P=0.043) or napped for ≤30 min ( P<0.001). ④Correlation analysis: the total score of MFI-20 was positively correlated with sleep quality, sleep latency, sleep disturbances, hypnotic medications, daytime dysfunction, and the total score of PSQI ( r=0.118-0.226, all P<0.05), but negatively with sleep duration ( r=-0.136, P=0.006). The total score of MFI-20 was positively correlated with mental demand, physical demand, and the total score of NASA-TLX ( r=0.119, 0.168, 0.184, P=0.017, 0.001, <0.001). ⑤Multiple linear regression analysis: the determinants of flight fatigue included aircraft types ( B=-4.956, 95% CI:-8.124--1.788), nap duration ( B=3.693, 95% CI: 1.267-6.119), sleep latency ( B=2.371, 95% CI: 0.229-4.513), sleep duration ( B=-7.383, 95% CI:-10.008--4.758), daytime dysfunction ( B=5.003, 95% CI: 2.967-7.039) and physical workload ( B=0.611, 95% CI: 0.324-0.898). Conclusions:Helicopter flying personnel are vulnerable to flight fatigue, which is strongly linked to sleep quality and mental workload. It is crucial to address flying personnel′s self-perceived fatigue, care about fatigue manifestations across aircraft types, and implement targeted interventions to improve sleep quality and reduce mental workload.

Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.

Objective:To investigate how gut microbiota changes during prostate cancer radiotherapy and decipher the relationship of gut microbiota with disease progression and chronic radiation enteritis.Methods:Thirty-one patients with prostate cancer were included in this study,admitted to The First Affiliated Hospital of Xinjiang Medical University from September 2022 to December 2023.The clinical data and stool samples of the patients were collected,and patients were followed up.The collected stool specimens were subjected to 16S rRNA se-quencing to detect gut microbiota and bioinformatics analysis.Results:The relative abundance of phyla such as Firmicutes and Actinobac-teria increased,and that of Bacteroidetes decreased(P<0.05)with an increasing radiotherapeutic dose,while beta diversity was significantly higher(P=0.001).The relative abundance of the phylum Actinobacteria was significantly higher in the prostate cancer progression group than in the non-progression group(P<0.05),the relative abundances of genera such as Sutterella and Haemophilus were significantly higher in the progression group(P<0.05).That of Verrucomicrobia and its offshoots in Akkermansia was higher in the chronic radiation enteritis than in the non-enteritis group(P<0.05),while the relative abundances of Coprococcus_1 and Catabacter in the non-enteritis group were higher than those in the enteritis group(P<0.05).Conclusions:Radiotherapy dose accumulation significantly remodeled the floral structure.Sutterella and Haemophilus of the phylum Proteobacteria might be key flora in prostate cancer recurring early after treatment.An augmen-ted abundance of Akkermansia might increase the risk of chronic radiation enteritis,whereas the flora under the Lachnospiraceae branch might exert aprotective effect against chronic radiation enteritis.

Objective:This study aims to explore the risk factors of Multi-center Investigator-Initiated Clinical Trials (MIITs), and provide a basis for developing study management strategies.Methods:The original draft of MIIT risk evaluation factors was determined through literature analysis and internal discussions of the research group. Thirty five experts were consulted using the Delphi method, and then the MIIT risk evaluation elements were finally determined. Analytic Hierarchy Process (AHP) was used to calculate the weights of each index.Results:The recovery rates of both rounds of expert consultation were 100%, and the degree of expert authority was 0.856. The study ultimately formed an MIIT risk evaluation framework consisting of three first-class indexes, twelve second-class indexes, and thirty-eight third-class indexes. The weight values of the first-class indexes (start-up period, implementation period, and summary period) were 0.209 8, 0.710 6, and 0.079 6, respectively. Meanwhile, the weight values of the second-class indexes and third-class indexes were determined.Conclusions:Exploring the risk evaluation factors of MIIT provides valuable insights into identifying critical risk points, which, in turn, contributes to enhancing MIIT management efficiency, research progress, and quality.