Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

ObjectiveTo investigate the protective effect and underlying mechanisms of Yishen Huayu prescription （YSHYP） on transdifferentiation of mouse renal tubular epithelial cells （TCMK-1） induced by transforming growth factor-β₁ （TGF-β₁）. MethodsA transdifferentiation model was established by treating TCMK-1 cells with 10 μg·L^-1 TGF-β₁. Experimental groups were established using 2 μmol·L^-1 silent information regulator 1 （SIRT1） inhibitor EX527. These included the blank group， model group， YSHYP group （treated with 10% YSHYP-medicated serum）， valsartan group （treated with 10% valsartan-medicated serum）， EX527+TGF-β₁ group， EX527+YSHYP group， and EX527 group. Immunofluorescence was used to detect the protein localization of α-smooth muscle actin （α-SMA）， E-cadherin， and microtubule-associated protein light chain 3 （LC3）. Western blot and Real-time polymerase chain reaction （Real-time PCR） were used to assess the expression of proteins and mRNA related to transdifferentiation， autophagy， and associated signaling pathways. ResultsThe results from Real-time PCR and Western blot indicate that compared with those in the blank group， expression levels of α-SMA， ubiquitin-binding protein p62 （p62）， and acetylated forkhead box protein O1（Ac-FoxO1） were significantly increased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. Compared with that in the model group， the expression of α-SMA and p62 were significantly downregulated in the YSHYP and valsartan groups （P<0.05， P<0.01）. Ac-FoxO1 protein levels were significantly reduced in the YSHYP group （P<0.05）， while the valsartan group showed no significant changes in Ac-FoxO1 levels. Compared with the YSHYP group， the valsartan group showed significant differences in p62 mRNA， α-SMA， and p62 protein expression （P<0.05）. Compared with those in the blank group， LC3， Beclin1， SIRT1， and forkhead box protein O1 （FoxO1） expression levels were significantly decreased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. In the model and EX527+TGF-β₁ groups， E-cadherin expression levels were significantly reduced （P<0.01）， while the EX527 group showed no statistically significant change. Compared with the model group， E-cadherin， LC3， Beclin1， SIRT1， and FoxO1 expression levels were significantly increased in both the YSHYP and valsartan groups （P<0.01， P<0.05）. Compared with the YSHYP group， the valsartan group exhibited significant differences in LC3， SIRT1， and FoxO1 mRNA expression （P<0.05， P<0.01）. Immunofluorescence results were consistent with those of Western blot and Real-time PCR. ConclusionYSHYP may protect TCMK-1 cells by activating the SIRT1/FoxO1 pathway， thereby promoting autophagy and restoring the autophagy flux to reduce the extent of transdifferentiation of TCMK-1 cells.

ObjectiveTo investigate the protective effect and underlying mechanisms of Yishen Huayu prescription （YSHYP） on transdifferentiation of mouse renal tubular epithelial cells （TCMK-1） induced by transforming growth factor-β₁ （TGF-β₁）. MethodsA transdifferentiation model was established by treating TCMK-1 cells with 10 μg·L^-1 TGF-β₁. Experimental groups were established using 2 μmol·L^-1 silent information regulator 1 （SIRT1） inhibitor EX527. These included the blank group， model group， YSHYP group （treated with 10% YSHYP-medicated serum）， valsartan group （treated with 10% valsartan-medicated serum）， EX527+TGF-β₁ group， EX527+YSHYP group， and EX527 group. Immunofluorescence was used to detect the protein localization of α-smooth muscle actin （α-SMA）， E-cadherin， and microtubule-associated protein light chain 3 （LC3）. Western blot and Real-time polymerase chain reaction （Real-time PCR） were used to assess the expression of proteins and mRNA related to transdifferentiation， autophagy， and associated signaling pathways. ResultsThe results from Real-time PCR and Western blot indicate that compared with those in the blank group， expression levels of α-SMA， ubiquitin-binding protein p62 （p62）， and acetylated forkhead box protein O1（Ac-FoxO1） were significantly increased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. Compared with that in the model group， the expression of α-SMA and p62 were significantly downregulated in the YSHYP and valsartan groups （P<0.05， P<0.01）. Ac-FoxO1 protein levels were significantly reduced in the YSHYP group （P<0.05）， while the valsartan group showed no significant changes in Ac-FoxO1 levels. Compared with the YSHYP group， the valsartan group showed significant differences in p62 mRNA， α-SMA， and p62 protein expression （P<0.05）. Compared with those in the blank group， LC3， Beclin1， SIRT1， and forkhead box protein O1 （FoxO1） expression levels were significantly decreased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. In the model and EX527+TGF-β₁ groups， E-cadherin expression levels were significantly reduced （P<0.01）， while the EX527 group showed no statistically significant change. Compared with the model group， E-cadherin， LC3， Beclin1， SIRT1， and FoxO1 expression levels were significantly increased in both the YSHYP and valsartan groups （P<0.01， P<0.05）. Compared with the YSHYP group， the valsartan group exhibited significant differences in LC3， SIRT1， and FoxO1 mRNA expression （P<0.05， P<0.01）. Immunofluorescence results were consistent with those of Western blot and Real-time PCR. ConclusionYSHYP may protect TCMK-1 cells by activating the SIRT1/FoxO1 pathway， thereby promoting autophagy and restoring the autophagy flux to reduce the extent of transdifferentiation of TCMK-1 cells.

Objective: To develop a modified calculation formula for renal tumor volume and tumor contact surface area (CSA) based on the modeling results of 3D Slicer software, and to create a webpage of the calculation formula for use. Methods: The general information and tumor anatomical data of 98 patients who underwent partial nephrectomy during Jan.2021 and Jul.2023 in the Second Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed.The imaging data were input into 3D Slicer software in the form of Dicom files for tumor and ipsilateral kidney modeling to obtain tumor anatomical data.The relationship between tumor anatomical parameters and tumor volume and CSA was analyzed using multifactorial linear regression.The initial modified formulas (V2, C2) and the optimized modified formulas (V3, C3) for tumor volume over CSA were established, respectively, after insignificant variables were eliminated.The mean square error (MSE) and Akaike information criterion (AIC) of the modified and traditional formulas (V1, C1) were compared, and the formula with the smallest MSE and AIC was selected as the optimal tumor volume and CSA calculation formula.The median tumor volume and CSA obtained from 3D modeling were used as the cutoff values.The optimal formula and conventional formula were applied to calculate tumor volume and CSA for all patients, and risk stratification was performed for all patients based on these cutoff values, and the perioperative indicators of patients in the upper and lower groups were compared.Finally, an online calculation tool was developed based on HTML. Results: Based on multifactorial linear regression analysis, we obtained the modified tumor volume calculation formula: V=0.382abc+2.488a+2.372b－4.146c+1.948（V2）, V=0.469abc－4.586c+13.816（V3）; the modified tumor CSA calculation formula CSA=2.469a －2.262L －19.23a+6.206b+1.212c+18.017L+1.616h－3.97h －2.185h/h －0.388（C2）, CSA=2.376a －2.144L －20.157a+5.024b+1.128c+17.578L+2.525h－2.634（C3）.Both of the modified volume formula (MSE=151.298 vs. 127.807 vs. 104.106) and modified CSA formula (MSE=309.878 vs.23.556 vs.30.388) had smaller errors compared to the conventional formula.The modified volume calculation formula showed that bleeding was more and thermal ischemia time was longer in patients with larger tumor volumes than in patients with smaller tumor volumes (P<0.05); and the modified CSA calculation formula showed that bleeding was more, surgery and thermal ischemia time were longer in patients with high CSA than in patients with low CSA (P＜0.05).Finally, V3 and C3 are selected as the best calculation formula, and a web page (https://lizihao-bot.github.io/RCC-Calculate/) was established for easy use. Conclusion: This study combined data from a medical information technology platform with numerical modeling methods to provide a faster and more accurate method to calculate the renal tumor volume and CSA.Meanwhile, a webpage version of the tool was developed to enhance its practicability.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Objective:To explore the changes in serum indoleamine 2, 3-dioxygenase (IDO) and kynurenic acid (KYNA) levels in preterm infants diagnosed with bronchopulmonary dysplasia (BPD).Methods:A nested case-control study was conducted. The inclusion criteria covered premature infants with less than 32 weeks of gestational age within 24 h post-birth, from December 1, 2021, to December 31, 2022, at Children's Hospital of Soochow University. Those diagnosed with BPD were allocated to the BPD group ( n=35). Non-BPD preterm infants matching the BPD cases in terms of gestational age (within one week difference) and birth weight (within a 150 g difference) were selected in a 1∶1 ratio for the control group ( n=35). Serum levels of IDO and KYNA were measured on days 1, 7, 14, and 28 postnatally. Differences in serum IDO and KYNA levels were analyzed between the BPD and control groups and among infants with mild BPD versus moderate-to-severe BPD. The association between serum IDO and KYNA levels with the severity of BPD was also assessed. Statistical analysis was conducted using independent samples t-tests and Spearman's correlation analysis. Results:Elevated levels of serum IDO on days 7, 14, and 28 postnatally [(60.68±9.37) vs. (50.66±10.46), (57.81±11.07) vs. (44.45±8.20), and (50.62±10.77) vs. (41.31±7.74) pg/ml; t=4.21, 5.73, and 4.15, respectively] as well as increased serum KYNA levels on days 14 and 28 [(439.31±41.22) vs. (368.99±68.79), (376.97±45.74) vs. (325.50±60.07) μmol/L; t=5.18 and 4.03, respectively] were observed in the BPD group compared to the control group, with all differences being statistically significant (all P<0.05). Furthermore, positive correlations were observed between serum IDO levels and BPD severity on the 7th, 14th, and 28th days ( r=0.546, 0.495, and 0.502, all P<0.05), as well as between serum KYNA levels and BPD severity on the 14th and 28th days ( r=0.536 and 0.458, both P<0.05). Conclusion:Elevated serum levels of IDO and KYNA in infants with BPD suggest these metabolites may play a role in the pathogenesis and progression of BPD.

The seat of human intelligence is the human cerebral cortex, which is responsible for our exceptional cognitive abilities. Identifying principles that lead to the development of the large-sized human cerebral cortex will shed light on what makes the human brain and species so special. The remarkable increase in the number of human cortical pyramidal neurons and the size of the human cerebral cortex is mainly because human cortical radial glial cells, primary neural stem cells in the cortex, generate cortical pyramidal neurons for more than 130 days, whereas the same process takes only about 7 days in mice. The molecular mechanisms underlying this difference are largely unknown. Here, we found that bone morphogenic protein 7 (BMP7) is expressed by increasing the number of cortical radial glial cells during mammalian evolution (mouse, ferret, monkey, and human). BMP7 expression in cortical radial glial cells promotes neurogenesis, inhibits gliogenesis, and thereby increases the length of the neurogenic period, whereas Sonic Hedgehog (SHH) signaling promotes cortical gliogenesis. We demonstrate that BMP7 signaling and SHH signaling mutually inhibit each other through regulation of GLI3 repressor formation. We propose that BMP7 drives the evolutionary expansion of the mammalian cortex by increasing the length of the neurogenic period.
Animals ; Mice ; Humans ; Ependymoglial Cells/metabolism* ; Hedgehog Proteins/metabolism* ; Ferrets/metabolism* ; Cerebral Cortex ; Neurogenesis ; Mammals/metabolism* ; Neuroglia/metabolism* ; Bone Morphogenetic Protein 7/metabolism*

Glutamate-ammonia ligase (GLUL, also known as glutamine synthetase) is a crucial enzyme that catalyzes ammonium and glutamate into glutamine in the ATP-dependent condensation. Although GLUL plays a critical role in multiple cancers, the expression and function of GLUL in gastric cancer remain unclear. In the present study, we have found that the expression level of GLUL was significantly lower in gastric cancer tissues compared with adjacent normal tissues, and correlated with N stage and TNM stage, and low GLUL expression predicted poor survival for gastric cancer patients. Knockdown of GLUL promoted the growth, migration, invasion and metastasis of gastric cancer cells in vitro and in vivo, and vice versa, which was independent of its enzyme activity. Mechanistically, GLUL competed with β-Catenin to bind to N-Cadherin, increased the stability of N-Cadherin and decreased the stability of β-Catenin by alerting their ubiquitination. Furthermore, there were lower N-Cadherin and higher β-Catenin expression levels in gastric cancer tissues compared with adjacent normal tissues. GLUL protein expression was correlated with that of N-Cadherin, and could be the independent prognostic factor in gastric cancer. Our findings reveal that GLUL stabilizes N-Cadherin by antagonizing β-Catenin to inhibit the progress of gastric cancer.

[Objective] To explore the clinical significance of the IgG1 and IgG3 subtypes of red blood cell unexpected antibodies. [Methods] The IgG1 and IgG3 typing tests were performed on the IgG type alloantibodies of Rh, Duffy and Kidd blood group systems detected in our hospital. Additionally, IgG1 and IgG3 titers were measured and monocyte monolayer assay was performed on 12 cases of anti-E to analyze the characteristics of different IgG subtypes of anti-E. [Results] Among the 115 cases of unexpected IgG antibodies, 81 cases of monospecific antibodies were predominantly IgG1 (58.02%, 47/81); 17 cases of mixed antibodies were predominantly IgG1+IgG3 (47.06%, 16/34). In monocyte monolayer assays, the phagocytic rate and antibody titer of IgG1 and IgG3 antibodies were positively correlated, while in IgG1+IgG3 complex antibodies, it was mainly associated with IgG3, with higher antibody titers correlating with higher phagocytic rates. When the anti-E titers were 32 for all, the IgG1+IgG3 complex had the highest phagocytosis rate, followed by IgG3 alone, and IgG1 alone had the lowest phagocytic rate. [Conclusion] Monospecific antibodies among unexpected antibodies are primarily IgG1, while mixed antibodies are mainly IgG1+IgG3. The results of MMA indicate that the immune response caused by the IgG1+IgG3 complex is more severe. Therefore, when antibodies like anti-E coexist with other antibodies, even if the titer is low, the immune response may still be severe, which should be taken seriously in clinical practice.