Role of DNA damage response in cyclophosphamide-induced premature ovarian failure in mice.

AIM: To investigate the DNA damage response (DDR) in a cyclophosphamide (CTX)-induced mouse model of premature ovarian failure (POF). METHODS: The POF model was established by injecting mice with CTX. The body, ovarian weights, the estrus cycle, and pathological changes of the ovaries were recorded. The serum levels of 17 ß-estradiol (E2) and follicle-stimulating hormone (FSH) were measured. The expression of Ki67, ß-galactosidase (ß-gal), p21, p53, γH2AX, and pATM in ovarian tissues was detected by immunohistochemistry. The expression of ß-gal, γH2AX, and pATM was analyzed by immunofluorescence staining of primary cultured granulosa cells (GCs). RESULTS: The body and ovarian weights decreased, the estrus cycles were erratic, and the FSH level increased, whereas the E2 level decreased in POF mice compared to controls. The pathological consequences of POF revealed an increase in atretic follicles, corpus luteum, and primordial follicles and a decrease in the number of primary, secondary, and tertiary follicles. Ki67 expression was reduced, ß-gal, p21, p53, γH2AX, and pATM expression were elevated in the ovaries of POF mice. The expression of ß-gal, γH2AX, and pATM increased in GCs with the concentration in a time-dependent manner. CONCLUSION: In total, CTX induced POF in mice, which was mediated by the DDR pathway of ATM-P53-P21.

Electroweak Corrections to Double Higgs Production at the LHC.

We present the results for the complete next-to-leading order electroweak corrections to pp→HH at the Large Hadron Collider, focusing on the dominant gluon-gluon fusion process. While the corrections at the total cross-section level are approximately -4%, those near the energy of HH production threshold exceed +15%, and corrections at the high-energy region are around -10%, leading to a shape distortion for the differential distributions. Our findings substantially diminish the theoretical uncertainties associated with this pivotal process, providing valuable input for understanding the shape of the Higgs boson potential upon comparison with experimental measurements.

Comparison of conventional MRI analysis versus MRI-based radiomics to predict the circumferential margin resection involvement of rectal cancer.

BACKGROUND: To compare the application of conventional MRI analysis and MRI-based radiomics to identify the circumferential resection margin (CRM) status of rectal cancer (RC). METHODS: A cohort of 301 RC patients with 66 CRM invloved status and 235 CRM non-involved status were enrolled in this retrospective study between September 2017 and August 2022. Conventional MRI characteristics included gender, age, diameter, distance to anus, MRI-based T/N phase, CEA, and CA 19 - 9, then the relevant logistic model (Logistic-cMRI) was built. MRI-based radiomics of rectal cancer and mesorectal fascia were calculated after volume of interest segmentation, and the logistic model of rectal cancer radiomics (Logistic-rcRadio) and mesorectal fascia radiomics (Logistic-mfRadio) were constructed. And the combined nomogram (nomo-cMRI/rcRadio/mfRadio) containing conventional MRI characteristics, radiomics of rectal cancer and mesorectal fascia was developed. The receiver operator characteristic curve (ROC) was delineated and the area under curve (AUC) was calculated the efficiency of models. RESULTS: The AUC of Logistic-cMRI was 0.864 (95%CI, 0.820 to 0.901). The AUC of Logistic-rcRadio was 0.883 (95%CI, 0.832 to 0.928) in the training set and 0.725 (95%CI, 0.616 to 0.826) in the testing set. The AUCs of Logistic-mfRadio was 0.891 (95%CI, 0.838 to 0.936) in the training set and 0.820 (95%CI, 0.725 to 0.905) in the testing set. The AUCs of nomo-cMRI/rcRadio/mfRadio were the highest in both the training set of 0.942 (95%CI, 0.901 to 0.969) and the testing set of 0.909 (95%CI, 0.830 to 0.959). CONCLUSION: MRI-based radiomics of rectal cancer and mesorectal fascia showed similar efficacy in predicting the CRM status of RC. The combined nomogram performed better in assessment.

Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma.

BACKGROUND: Accurate prediction of visceral pleural invasion (VPI) in lung adenocarcinoma before operation can provide guidance and help for surgical operation and postoperative treatment. We investigate the value of intratumoral and peritumoral radiomics nomograms for preoperatively predicting the status of VPI in patients diagnosed with clinical stage IA lung adenocarcinoma. METHODS: A total of 404 patients from our hospital were randomly assigned to a training set (n = 283) and an internal validation set (n = 121) using a 7:3 ratio, while 81 patients from two other hospitals constituted the external validation set. We extracted 1218 CT-based radiomics features from the gross tumor volume (GTV) as well as the gross peritumoral tumor volume (GPTV5, 10, 15), respectively, and constructed radiomic models. Additionally, we developed a nomogram based on relevant CT features and the radscore derived from the optimal radiomics model. RESULTS: The GPTV10 radiomics model exhibited superior predictive performance compared to GTV, GPTV5, and GPTV15, with area under the curve (AUC) values of 0.855, 0.842, and 0.842 in the three respective sets. In the clinical model, the solid component size, pleural indentation, solid attachment, and vascular convergence sign were identified as independent risk factors among the CT features. The predictive performance of the nomogram, which incorporated relevant CT features and the GPTV10-radscore, outperformed both the radiomics model and clinical model alone, with AUC values of 0.894, 0.828, and 0.876 in the three respective sets. CONCLUSIONS: The nomogram, integrating radiomics features and CT morphological features, exhibits good performance in predicting VPI status in lung adenocarcinoma.

Heavy-Quark Pair Production at Lepton Colliders at NNNLO in QCD.

We compute the total cross section and invariant mass distribution for heavy-quark pair production in e^{+}e^{-} annihilation at the next-to-next-to-next-to-leading order in QCD. The obtained results are expressed as piecewise functions defined by several deeply expanded power series, facilitating a rapid numerical evaluation. Utilizing top-pair production at a collision energy of 500 GeV as a benchmark, we observe a correction of approximately 0.1% for the total cross section and around 10% for the majority of the invariant mass distribution range. These results play a crucial role in significantly reducing theoretical uncertainty: the scale dependence has been diminished to 0.06% for the total cross section and to 5% for the invariant mass distribution. This reduction of uncertainty meets the stringent requirements of future lepton colliders.

Multi-instance learning based lung nodule system for assessment of CT quality after small-field-of-view reconstruction.

Small-field-of-view reconstruction CT images (sFOV-CT) increase the pixel density across airway structures and reduce partial volume effects. Multi-instance learning (MIL) is proposed as a weakly supervised machine learning method, which can automatically assess the image quality. The aim of this study was to evaluate the disparities between conventional CT (c-CT) and sFOV-CT images using a lung nodule system based on MIL and assessments from radiologists. 112 patients who underwent chest CT were retrospectively enrolled in this study between July 2021 to March 2022. After undergoing c-CT examinations, sFOV-CT images with small-field-of-view were reconstructed. Two radiologists analyzed all c-CT and sFOV-CT images, including features such as location, nodule type, size, CT values, and shape signs. Then, an MIL-based lung nodule system objectively analyzed the c-CT (c-MIL) and sFOV-CT (sFOV-MIL) to explore their differences. The signal-to-noise ratio of lungs (SNR-lung) and contrast-to-noise ratio of nodules (CNR-nodule) were calculated to evaluate the quality of CT images from another perspective. The subjective evaluation by radiologists showed that feature of minimal CT value (p = 0.019) had statistical significance between c-CT and sFOV-CT. However, most features (all with p < 0.05), except for nodule type, location, volume, mean CT value, and vacuole sign (p = 0.056-1.000), had statistical differences between c-MIL and sFOV-MIL by MIL system. The SNR-lung between c-CT and sFOV-CT had no statistical significance, while the CNR-nodule showed statistical difference (p = 0.007), and the CNR of sFOV-CT was higher than that of c-CT. In detecting the difference between c-CT and sFOV-CT, features extracted by the MIL system had more statistical differences than those evaluated by radiologists. The image quality of those two CT images was different, and the CNR-nodule of sFOV-CT was higher than that of c-CT.

CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.

BACKGROUND: Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients. METHODS: This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts. RESULTS: Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869-0.906], 0.874 (95%CI 0.844-0.904) and 0.846 (95%CI 0.822-0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model. CONCLUSIONS: The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

Progress of MRI in predicting the circumferential resection margin of rectal cancer: A narrative review.

Rectal cancer (RC) is the third most frequently diagnosed cancer worldwide, and the status of its circumferential resection margin (CRM) is of paramount significance for treatment strategies and prognosis. CRM involvement is defined as tumor touching or within 1 mm from the outermost part of tumor or outer border of the mesorectal or lymph node deposits to the resection margin. The incidence of involved CRM varied from 5.4 % to 36 %, which may associate with an in consistent definition of CRM, the quality of surgeries, and the different examination modalities. Although T and N status are essential factors in determining whether a patient should receive neoadjuvant therapy before surgery, CRM status is a powerful predictor of local and distant recurrence as well as survival rate. This review explores the significance of CRM, the various assessment methods, and the role of magnetic resonance imaging (MRI) and artificial intelligence-based MRI in predicting CRM status. MRI showed potential advantage in predicting CRM status with a high sensitivity and specificity compared to computed tomography (CT). We also discuss MRI advancements in RC imaging, including conventional MRI with body coil, high-resolution MRI with phased-array coil, and endorectal MRI. Along with a discussion of artificial intelligence-based MRI techniques to predict the CRM status of RCs before and after treatments.

Myosin light chain 6 (Myl6) interacts with kindlin-3 and is required to support integrin αIIbß3 activation in platelets in mice.

BACKGROUND: Kindlin-3 in platelets plays an essential role in supporting integrin αIIbß3 activation, platelet spreading, aggregation, and clot retraction by binding to the integrin ß3 cytoplasmic tail. However, the mechanism by which kindlin-3 mediates the crosstalk between integrin αIIbß3 and myosin in platelets remains unknown. OBJECTIVES: To examine the role of myosin light chain 6 (Myl6) in supporting integrin αIIbß3 activation in platelets. METHODS: Myl6fl/flPF4-Cre mice with a deficiency of Myl6 in the megakaryocyte lineage were generated, and integrin αIIbß3 activation in Myl6-deficient platelets was analyzed. RESULTS: We identified a novel kindlin-3 binding protein, Myl6, an essential light chain of myosin in platelets. Myl6fl/flPF4-Cre mice exhibited significant macrothrombocytopenia resulting from defective proplatelet formation. In the absence of Myl6, integrin αIIbß3 activation in platelets was significantly suppressed, and platelet aggregation was substantially impaired. Interestingly, the deficiency of Myl6 in platelets preferentially affected the binding of a multivalent ligand compared to a monovalent ligand to integrin αIIbß3 upon activation, indicating that Myl6 may contribute to the avidity modulation of integrin αIIbß3 by binding to kindlin-3. Furthermore, blood coagulation ability was impaired in Myl6fl/flPF4-Cre mice, and consistently, these mice exhibited defects in both hemostatic and thrombotic functions. CONCLUSION: In summary, these results suggest that Myl6, as a novel kindlin-3 binding partner, is required to support integrin αIIbß3 activation in platelets, which plays an important role in both hemostasis and thrombosis.

An integrative clinical and CT-based tumoral/peritumoral radiomics nomogram to predict the microsatellite instability in rectal carcinoma.

BACKGROUND: Microsatellite instability (MSI) is detected in approximately 15% of colorectal carcinoma (CRC) patients, which has emerged as a predictor of patient response to adjuvant chemotherapy. Rectal carcinoma (RC) is the most common type of CRC. Therefore, prediction of MSI status of RC is significant for personalized medication. The purpose of this article was to develop an integrative model that combines clinical characteristics and computed tomography-based (CT-based) tumoral/peritumoral radiomics to predict the MSI status in RC. METHODS: A cohort of 788 RCs with 97 high-MSI status (MSI-H) and 691 microsatellite stable status (MSS) were enrolled between January 2015 and January 2021 in this retrospective study. Clinical characteristics were recorded, and CT-based tumoral/peritumoral radiomic features were calculated after segmenting volume of interests. The patients were randomly divided into training and validation sets in a 7:3 proportion. Logistic models of single tumoral radiomics (LM-tRadio), peritumoral radiomics (LM-ptRadio), and combined tumoral/peritumoral radiomics (LM-Radio) were constructed to distinguish MSI-H from MSS, and a relevant radiomic score was calculated. An integrative nomogram (LM-Nomo) was developed, including significant clinical characteristics and CT-based tumoral/peritumoral radiomics. The area under receiver operator curve (AUC) was calculated to evaluate the efficacy of prediction. RESULTS: The AUCs of LM-Radio were 0.785 (95%CI 0.732-0.837) in the training set and were 0.628 (95%CI 0.528-0.723) in the validation set, which were higher than those of LM-tRadio and LM-ptRadio. The AUCs of single LM-ptRadio were slightly higher than those of LM-tRadio (0.724 vs. 0.708 in the training set, 0.613 vs. 0.602 in the validation set). The LM-Nomo containing carcinoembryonic antigen (CEA), hypertension, and CT-based tumoral/peritumoral radiomic score showed the highest AUCs of 0.796 (95%CI 0.748-0.843) in the training set and 0.679 (95%CI 0.588-0.771) in the validation set in predicting the MSI-H status of RC. CONCLUSION: The AUCs of LM-ptRadio were slightly higher than LM-tRadio to evaluate the MSI-H status of RC. The LM-Nomo, which includes significant clinical characteristics and CT-based tumoral/peritumoral radiomics score, demonstrated the best performance in predicting MSI-H status of RC.

A novel leukocyte adhesion deficiency type III mutation manifests functional importance of the compact FERM domain in kindlin-3.

BACKGROUND: Leukocyte adhesion deficiency III (LAD-III) is a rare autosomal recessive syndrome characterized by functional deficiencies of platelets and leukocytes that occurs due to mutations in the FERMT3 gene encoding kindlin-3. Kindlin-3 is a FERM domain-containing adaptor protein that is essential in integrin activation. We have previously demonstrated that the FERM domain of kindlin-3 is structurally compact and plays an important role in supporting integrin activation in a mouse model. The impact of destabilizing the compact FERM domain in kindlin-3 on the development of LAD-III in humans remains uncertain. OBJECTIVES: To use primary cells from a patient with LAD-III to validate the role of the compact FERM domain in kindlin-3 function in platelets and leukocytes. METHODS: The patient is a 4-year-old girl who since infancy has displayed clinical features of LAD-III. Patient platelets and leukocytes were functionally analyzed, and structural analysis of the kindlin-3 variant was conducted. RESULTS: We identified a novel homozygous missense mutation in the FERMT3 (c.412G>A, p.E138K) FERM domain. Substantially reduced levels of kindlin-3 were detected in the proband's platelets and leukocytes. Functional evaluation verified that integrin αIIbß3-mediated platelet activation, spreading, and aggregation and ß2-integrin-mediated neutrophil adhesion and spreading were significantly compromised. Structural analysis revealed that this newly identified E138K substitution in kindlin-3 destabilizes the compacted FERM domain, resulting in poor expression of kindlin-3 in blood cells and subsequent LAD-III. CONCLUSION: We have identified a novel missense mutation and verified the functional significance of the compact kindlin-3 FERM domain in supporting integrin functions in platelets and leukocytes.

Antibacterial activity and mechanism of cinnamon essential oil nanoemulsion against Pseudomonas deceptionensis CM2.

This work aimed to evaluate the antibacterial activity and mechanism of cinnamon essential oil nanoemulsion (CON) against Pseudomonas deceptionensis CM2. The results revealed that CON could effectively inhibit the proliferation of P. deceptionensis CM2 cells in a time- and concentration-dependent manner. After 4 h of incubation with CON at the minimum inhibitory concentration (0.125 mg/mL), the relative fluorescence intensity of propidium iodide and 1-N-phenylnapthylamine (NPN) was increased by 32.0% and 351.4%, respectively. The membrane permeability of P. deceptionensis CM2 cells was significantly disrupted after CON treatment, resulting in the leakage of intracellular substances (such as proteins and electrolytes). CON also caused significant increases in the DiBAC4(3) fluorescence intensity of P. deceptionensis CM2 cells. These results demonstrate that CON induced inactivation of P. deceptionensis CM2 by destroying the integrity and function of bacterial membrane. A higher level of intracellular reactive oxygen species (ROS) was observed in CON-treated cells (p < 0.05), compared with control cells. Moreover, the addition of glutathione to the growth medium remarkably decreased the antimicrobial activity of CON against P. deceptionensis CM2, further confirming that oxidative stress played an important role in the antimicrobial activity of CON. Overall, CON may exhibit antibacterial effects by causing damage to the bacterial membranes and oxidative stress.

Retinoic acid delays murine palatal shelf elevation by inhibiting Wnt5a-mediated noncanonical Wnt signaling and downstream Cdc-42/F-actin remodeling in mesenchymal cells.

BACKGROUND: Mammalian palatal shelves erupted from maxillary prominences undergo vertical extention, transient elevation, and horizontal growth to fuse. Previous studies in mice reported that the retinoic acid (RA) contributed to cleft palate in high incidence by delaying the elevating procedure, but little was known about the underlying biological mechanisms. METHODS: In this study, hematoxylin-eosin and immunofluorescence staining were employed to evaluate the phenotypes and the expression of related markers in the RA-treated mice model. In situ hybridization and RT-qPCR were used to detect the expression of genes involved in Wnt signaling pathway. The palatal mesenchymal cells were cultured in vitro, and stimulated with RA or CASIN, and co-treated with Foxy5. Wnt5a and Ccd42 expression were evaluated by immunofluorescence staining. Phalloidin was used to label the microfilament cytoskeleton (F-actin) in cultured cells. RESULTS: We revealed that RA resulted in 100% incidence of cleft palate in mouse embryos, and the expression of genes responsible for Wnt5a-mediated noncanonical Wnt signal transduction were specifically downregulated in mesenchymal palatal shelves. The in vitro study of palatal mesenchymal cells indicated that RA treatment disrupted the organized remodeling of cytoskeleton, an indicative structure of cell migration regulated by the small Rho GTPase Cdc42. Moreover, we showed that the suppression of cytoskeleton and cell migration induced by RA was partially restored using the small molecule Foxy-5-mediated activation of Wnt5A, and this restoration was attenuated by CASIN (a selective GTPase Cdc42 inhibitor) again. CONCLUSIONS: These data identified a crucial mechanism for Wnt5a-mediated noncanonical Wnt signaling in acting downstream of Rho GTPase Cdc42 to regulate cytoskeletal remodeling and cell migration during the process of palate elevation. Our study provided a new explanation for the cause of cleft palate induced by RA.

Genomes of cultivated and wild Capsicum species provide insights into pepper domestication and population differentiation.

Pepper (Capsicum spp.) is one of the earliest cultivated crops and includes five domesticated species, C. annuum var. annuum, C. chinense, C. frutescens, C. baccatum var. pendulum and C. pubescens. Here, we report a pepper graph pan-genome and a genome variation map of 500 accessions from the five domesticated Capsicum species and close wild relatives. We identify highly differentiated genomic regions among the domesticated peppers that underlie their natural variations in flowering time, characteristic flavors, and unique resistances to biotic and abiotic stresses. Domestication sweeps detected in C. annuum var. annuum and C. baccatum var. pendulum are mostly different, and the common domestication traits, including fruit size, shape and pungency, are achieved mainly through the selection of distinct genomic regions between these two cultivated species. Introgressions from C. baccatum into C. chinense and C. frutescens are detected, including those providing genetic sources for various biotic and abiotic stress tolerances.

Corrigendum: Ethyl lauroyl arginate: an update on the antimicrobial potential and application in the food systems industry: a review.

[This corrects the article DOI: 10.3389/fmicb.2023.1125808.].

Radiomics-based Machine Learning Methods for Volume Doubling Time Prediction of Pulmonary Ground-glass Nodules With Baseline Chest Computed Tomography.

PURPOSE: Reliable prediction of volume doubling time (VDT) is essential for the personalized management of pulmonary ground-glass nodules (GGNs). We aimed to determine the optimal VDT prediction method by comparing different machine learning methods only based on the baseline chest computed tomography (CT) images. MATERIALS AND METHODS: Seven classical machine learning methods were evaluated in terms of their stability and performance for VDT prediction. The VDT, calculated by the preoperative and baseline CT, was divided into 2 groups with a cutoff value of 400 days. A total of 90 GGNs from 3 hospitals constituted the training set, and 86 GGNs from the fourth hospital served as the external validation set. The training set was used for feature selection and model training, and the validation set was used to evaluate the predictive performance of the model independently. RESULTS: The eXtreme Gradient Boosting showed the highest predictive performance (accuracy: 0.890±0.128 and area under the ROC curve (AUC): 0.896±0.134), followed by the neural network (NNet) (accuracy: 0.865±0.103 and AUC: 0.886±0.097). While regarding stability, the NNet showed the highest robustness against data perturbation (relative SDs [%] of mean AUC: 10.9%). Therefore, the NNet was chosen as the final model, achieving high accuracy of 0.756 in the external validation set. CONCLUSION: The NNet is a promising machine learning method to predict the VDT of GGNs, which would assist in the personalized follow-up and treatment strategies for GGNs reducing unnecessary follow-up and radiation dose.

Circulating LPS from gut microbiota leverages stenosis-induced deep vein thrombosis in mice.

OBJECTIVE AND DESIGN: An accumulating body of evidence has shown that gut microbiota is involved in regulating inflammation; however, it remains undetermined if and how gut microbiota plays an important role in modulating deep venous thrombosis (DVT), which is an inflammation-involved thrombotic event. SUBJECTS: Mice under different treatments were used in this study. METHODS AND TREATMENT: We induced stenosis DVT in mice by partially ligating the inferior vena cava. Mice were treated with antibiotics, prebiotics, probiotics, or inflammatory reagents to modulate inflammatory states, and their effects on the levels of circulating LPS and DVT were examined. RESULTS: Antibiotic-treated mice or germ-free mice exhibited compromised DVT. Treatment of mice with either prebiotics or probiotics effectively suppressed DVT, which was accompanied with the downregulation of circulating LPS. Restoration of circulating LPS in these mice with a low dose of LPS was able to restore DVT. LPS-induced DVT was blocked by a TLR4 antagonist. By performing proteomic analysis, we identified TSP1 as one of the downstream effectors of circulating LPS in DVT. CONCLUSION: These results suggest that gut microbiota may play a nonnegligible role in modulating DVT by leveraging the levels of LPS in circulation, thus shedding light on the development of gut microbiota-based strategies for preventing and treating DVT.

Nomograms Using CT Morphological Features and Clinical Characteristics to Identify COPD in Patients with Lung Cancer: A Multicenter Study.

Purpose: This study aimed to screen out computed tomography (CT) morphological features and clinical characteristics of patients with lung cancer to identify chronic obstructive pulmonary disease (COPD). Further, we aimed to develop and validate different diagnostic nomograms for predicting whether lung cancer is comorbid with COPD. Patients and Methods: This retrospective study examined data from 498 patients with lung cancer (280 with COPD, 218 without COPD; 349 in training cohort, 149 in validation cohort) from two centers. Five clinical characteristics and 20 CT morphological features were evaluated. Differences in all variables were assessed between COPD and non-COPD groups. Models were developed using multivariable logistic regression to identify COPD, including clinical, imaging, and combined nomograms. Receiver operating characteristic curves were used to evaluate and compare the performance of nomograms. Results: Age, sex, interface, bronchus cutoff sign, spine-like process, and spiculation sign were independent predictors of COPD in patients with lung cancer. In the training and validation cohorts, the clinical nomogram showed good performance to predict COPD in lung cancer patients (areas under the curves [AUCs] of 0.807 [95% CI, 0.761-0.854] and 0.753 [95% CI, 0.674-0.832]); while the imaging nomogram showed slightly better performance (AUCs of 0.814 [95% CI, 0.770-0.858] and 0.780 [95% CI, 0.705-0.856]). For the combined nomogram generated with clinical and imaging features, the performance was further improved (AUC=0.863 [95% CI, 0.824-0.903], 0.811 [95% CI, 0.742-0.880] in the training and validation cohort). At 60% risk threshold, there were more true negative predictions (48 vs 44) and higher accuracy (73.15% vs 71.14%) for the combined nomogram compared with the clinical nomogram in the validation cohort. Conclusion: The combined nomogram developed with clinical and imaging features outperformed clinical and imaging nomograms; this provides a convenient method to detect COPD in patients with lung cancer using one-stop CT scanning.

Analysis of gut microbiotal diversity in healthy young adults in Sunan County, Gansu Province, China.

Objective: To examine gut microbiotal diversity in the Han Chinese and Yugur populations of Sunan County, Gansu Province, living in the same environmental conditions, and to analyze possible causes of differences in diversity. Methods: We selected 28 people, ages 18-45 years old, all of whom were third-generation pure Yugur or Han Chinese from Sunan County. Fresh fecal samples were collected, and total bacterial deoxyribonucleic acid (DNA) was extracted. We performed 16S ribosomal ribonucleic acid (16S rRNA) high-throughput sequencing (HTS) and bioinformatics to study the relationships among between gut microbiota structure, genetics, and dietary habits in Yugur and Han Chinese subjects. Results: We found 350 differential operational taxonomic units (OTUs) in Han Chinese and Yugur gut microbiota, proving that gut microbiota differed between the two populations. That were less abundant among Yugurs than Han Chinese were Prevotella_9 and Alloprevotella. That were more abundant among Yugurs than Han Chinese were Anaerostipes and Christensenellaceae_R-7_group. And they were significantly associated with a high-calorie diet In addition. we found differences in predicted gut microbiota structural functions (The main functions were metabolic and genetic information) between the two populations. Conclusion: Yugur subjects demonstrated differences in gut microbiotal structure from Han Chinese subjects, and this difference influenced by dietary and may be influenced by genetic influences. This finding will provide a fundamental basis for further study of the relationships among gut microbiota, dietary factors, and disease in Sunan County.