Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.

Objective To construct a clinical-radiological nomo-gram model for severe mycoplasma pneumoniae pneumonia coinfec-tion with other pathogens(Co-SMPP)in children.Methods The clinical and radiological data of children with severe mycoplasma pneumoniae pneumonia(SMPP)who underwent nucleic acid testing or bronchoalveolar lavage(BAL)were analyzed retrospectively.The data analysis were performed by using SPSS 27.0 software.The group comparison between simple SMPP and Co-SMPP children was conducted by using t-tests,Mann-Whitney U tests,or chi-square tests.Nomogram analysis was performed by using R software and rms packages.The predictive performance of the model was evaluated by using the receiver operating characteristic(ROC)curve.Results A total of 194 SMPP children were included in the study,including 136 cases(70.1％)with simple SMPP,58 cases(29.9％)with Co-SMPP.The fibrinogen and albumin levels were lower in Co-SMPP children[(3.53±0.85)g/L,41.00(39.03,43.68)g/L]than in simple SMPP children[(3.79±0.80)g/L,42.80(41.00,44.40)g/L],with P values of 0.047 and 0.036,respec-tively.The probability of bronchial stenosis and grid shadow were higher in Co-SMPP children than in simple SMPP children,and there were significant differences between the two groups(P＜0.001,P=0.010).The odds ratio of bronchial stenosis in predicting Co-SMPP children was 14.085.The clinical-radiological nomogram model had an area under the curve(AUC)of 0.840,with sensi-tivity and specificity of 0.756 and 0.848,respectively.Conclusion The nomogram model based on clinical-radiological features can effectively predict Co-SMPP.

Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.

AIM:This study aims to investigate the mechanism by which Qingfei-Jiedu-Huatan Formula(QJHF)regulates autophagy in alveolar macrophages through mTOR in the treatment of severe pneumonia(SP)in rats.METHODS:Sixty SPF-grade male rats were randomly assigned to six groups:control,model,QJHF,moxifloxacin(MOX),rapamycin(RAPA),and QJHF+RAPA,with ten rats in each group.An SP rat model was established using Klebsiella pneumoniae.After seven days of treatment,changes in IL-33 and IFN-γ levels in bronchoalveolar lavage fluid(BALF)were measured using ELISA.Histopathological alterations in lung tissue were assessed via HE staining,and the autophagy of alveolar macrophages was detected using immunofluorescence co-localization methods.The expression levels of mTOR,beclin-1,and LC3 mRNA in lung tissue were analyzed using qPCR,while Western blot was employed to assess the protein levels of p-mTOR/mTOR,beclin-1,and LC3-II/LC3-I.RESULTS:Compared to the control group,the model group exhibited a deteriorated condition,characterized by alveolar wall rupture and thickening,significant inflammatory cell infiltration in the alveolar cavity,and extensive lung tissue damage(P<0.01).Elevated levels of IL-33 and IFN-γ in BALF were also observed(P<0.01),along with increased colocalization of CD68 and LC3 in immunofluorescence analy-sis.The mTOR mRNA expression in lung tissue decreased(P<0.01),while LC3 and beclin-1 mRNA expressions in-creased(P<0.01).Additionally,the protein expression ratio of p-mTOR/mTOR decreased(P<0.01),whereas LC3-II/LC3-I and beclin-1 protein levels increased(P<0.01).In comparison to the model group,significant improvements were noted after treatment with QJHF and MOX(P<0.01),while RAPA treatment led to a worsening of these indicators(P<0.05).A slight improvement was observed with the QJHF combined with RAPA intervention,though this was not statisti-cally significant.No significant differences were found between the MOX and QJHF groups.However,the QJHF+RAPA group displayed notable improvements in various indicators compared to the RAPA group(P<0.05).CONCLUSION:The QJHF can mitigate the inflammatory response associated with severe pneumonia,potentially by activating mTOR phos-phorylation activity,which in turn inhibits excessive autophagy in alveolar macrophages.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals ; NFATC Transcription Factors/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Ovariectomy ; Osteoclasts/metabolism* ; Female ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; NF-kappa B/genetics* ; Osteoporosis/genetics* ; Signal Transduction/drug effects* ; Bone Resorption/genetics* ; Cell Differentiation/drug effects* ; Humans ; RANK Ligand/metabolism* ; Mitogen-Activated Protein Kinases/genetics* ; Transcription Factors

OBJECTIVE: To determine the prevalence of lumbar spondylolysis (LS) and the proportion of spondylolytic spondylolisthesis (SS) in China, and to evaluate the musculoskeletal status of patients with LS and SS. METHODS: Spine Computed Tomography (CT) images were collected from community populations aged 40 and above in a nationwide multi-center project. LS was diagnosed, and SS was graded by an experienced radiologist. Bone mineral density (BMD) and paraspinal muscle parameters were quantified based on CT images. RESULTS: One hundred and seventeen patients of a total of 3,317 individuals were diagnosed with LS, corresponding to a prevalence rate of 3.53%. 63 of the 1,214 males (5.18%) and 54 of the 2,103 females (2.57%) were diagnosed with LS. SS occurred in 64/121 vertebrae (52.89%). BMD was not associated with LS ( P = 0.341). The L5 extensor paraspinal muscle density was higher in the LS group than in the non-LS group. In the LS group, patients with SS had a smaller L5 paraspinal extensor muscle cross-sectional area than those without SS ( P = 0.003). CONCLUSION The prevalence of LS in Chinese adults was 3.53%, with prevalence rates of 5.18% in males and 2.57% in females. Patients with LS have higher muscle density, whereas those with SS have smaller muscle cross-sectional areas at the L5 level.
Humans ; Male ; Female ; Middle Aged ; China/epidemiology* ; Prevalence ; Adult ; Lumbar Vertebrae/diagnostic imaging* ; Spondylolysis/diagnostic imaging* ; Aged ; Bone Density ; Tomography, X-Ray Computed ; Aged, 80 and over ; Spondylolisthesis/epidemiology* ; East Asian People

Objective : To explore the risk factors of prognosis in patients with severe community-acquired pneumonia(SCAP) in different age groups. Methods : A multi-center and prospective study was conducted at 11 teaching hospitals in China from December 2017 to October 2021. Patients who met the criteria were assigned to the elderly group(≥65 years) and the non-elderly group(18-64 years) to demonstrate the clinical characteristics of SCAP. Patients were divided into survival group and death group according to whether they died in hospital, to determine the risk factors associated with mortality by multivariate logistic regression analysis. Results: A total of 170 patients with SCAP were included in the study. The age of SCAP was 20-93(65.75±15.23) years old, and the proportion of SCAP in the elderly was 58.82%(100/170). In-hospital mortality of non-elderly SCAP was 24.3%(17/70), and the in-hospital mortality of elderly SCAP was 28%(28/100). Compared with non-elderly group, patients in elderly group had higher severity score and more complications on admission, but the symptoms of fever and respiratory rate at admission were less obvious. In multivariable logistic regression analysis, the factors significantly associated with in-hospital mortality of non-elderly SCAP were pneumonia severity index(PSI) score(P=0.016,OR=1.022, 95%CI1.004-1.041) and invasive mechanical ventilation(P=0.037,OR=4.543, 95%CI1.092-18.898) on admission, and the risk factors associated with in-hospital mortality in elderly SCAP were sequential organ failure assessment(SOFA) score(P=0.006,OR=1.240, 95%CI1.063-1.446) and combined with coronary artery disease on admission(P=0.037,OR=2.834, 95%CI1.066-7.534). Conclusion In-hospital mortality for SCAP is high. PSI score and invasive mechanical ventilation are risk factors for in-hospital mortality of non-elderly patients with SCAP, and SOFA score and combined with coronary artery disease on admission are risk factors for in-hospital mortality of elderly patients with SCAP.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

Objective To explore the anatomical landmarks and segmentation method for the intraoperative identification of the cervical segment of the internal carotid artery by studying cadaveric dissections with an endoscopic transoral medial pterygomandibular fold approach and to investigate its clinical significance.Methods The head specimens of five fresh frozen cadavers were dissected in the anatomical laboratory of the Surgical Treatment Technology Innovation Unit of Nasal Skull Base Tumor in Eye&ENT Hospital of Fudan University.The parapharyngeal space was dissected layer by layer through the endoscopic transoral medial pterygomandibular fold approach,and the location marks of parapharyngeal internal carotid artery(ppICA)and adjacent structures of ppICA were anatomically studied.The anatomical landmarks associated with ppICA were observed and characterized,and the ppICA was segmented anatomically according to its adjacent structures.Then,the length of each ppICA segment was measured.Results Muscle structures were essential anatomical landmarks for an endoscopic transoral pterygoid medial approach that identifies mandibular folds.The first layer of muscles included the superior pharyngeal constrictor,tensor veli palatini,and medial pterygoid muscles.The second layer includes the stylopharyngeus,styloglossus,longus capitis,and levator veli palatini muscles.The stylopharyngeal and levator veli palatini muscles were close to the ppICA and were reliable landmarks for locating the ppICA.Furthermore,the ppICA was divided into three segments according to their positional relationship with the ppICA.The first segment of ppICA(P1 ICA)was located between the greater horn plane of the hyoid bone and the intersection plane between the upper margin of stylopharyngeal muscle and ppICA.The second segment of ppICA(P2 ICA)was between the plane where the upper edge of the stylopharyngeal muscle intersected with the ppICA and the plane where the projection of inferior edge of the levator veli palatini muscle intersected with the ppICA.The third segment of ppICA(P3 ICA)was between the intersection of the lower margin projection of the levator veli palatini muscle and ppICA and the external orifice of the carotid canal.The P2 ICA was within an anatomical region bounded by the levator veli palatini muscle,longus capitis muscle,and stylopharyngeus muscle.This region was termed"ICA window"in this paper measured under the cadaver head specimen,the lengths of P1 ICA,P2 ICA,and P3 ICA were(36.5±7.3)mm,(15.5±1.6)mm,(7.4±1.7)mm respectively.Conclusion The muscular structure refers to the relatively constant anatomical reference landmarks within the endoscopic transoral medial pterygomandibular fold.The stylopharyngeus and levator veli palatini muscles are reliable landmarks for precisely locating and segmenting the ppICA,thus having essential clinical implications.