Objective:To evaluate the diagnostic value of non-targeted detection of metabolic fingerprinting in pulmonary nodules and to analyze the clinical effective model of multi-omics for assessing the malignant risk of pulmonary nodules.Methods:A total of 73 patients who underwent chest CT and completed pathological diagnosis and non-targeted detection of metabolic fingerprinting at Shandong Provincial Hospital Affiliated to Shandong First Medical University from November 2021 to October 2024 were selected as the research subjects. According to the postoperative histopathological diagnosis, the patients were divided into the lung malignant nodule group (61 cases) and the lung benign nodule group (12 cases). General clinical data of the patients, including sex, age, smoking history, and family history of tumors, as well as imaging data, including nodule density, nodule size, nodule location, nodule number, and special imaging manifestations (spiculation, lobulation, vacuole sign, vascular convergence sign, etc.), and non-targeted detection of metabolic fingerprinting results were collected. The above data were compared between the two groups of patients, and the receiver operator characteristic (ROC) curve was drawn to evaluate the predictive value of each model. Results:There were statistically significant differences in age ( t=4.41, P<0.001), nodule size ( Z=2.67, P=0.008), nodule density ( χ2=4.64, P=0.031), and spiculation ( χ2=7.67, P=0.006) between the lung malignant nodule group and the lung benign nodule group. There were no statistically significant differences in sex, smoking history, family history of lung cancer, nodule number, nodule location, lobulation, vacuole sign, vascular convergence sign, pleural indentation sign, calcification sign, bronchial truncation sign, vascular supply sign, and bronchial air sign (all P>0.05). The number of non-targeted detection of metabolic fingerprinting high-risk patients in the lung malignant nodule group (36 cases) was significantly higher than that in the lung benign nodule group (0 case) ( χ2=13.97, P<0.001). ROC curve analysis showed that the area under the curve of the Brock model combined with non-targeted detection of metabolic fingerprinting was 0.930 (95% CI: 0.872-0.988), which was greater than that of the Brock model (0.856, 95% CI: 0.769-0.942, Z=0.27, P=0.040) and non-targeted detection of metabolic fingerprinting (0.768, 95% CI: 0.650-0.887, Z=0.30, P=0.004) alone. Conclusions:Non-targeted detection of metabolic fingerprinting risk assessment may serve as a non-invasive method to assist the Brock model in the diagnosis of pulmonary nodules and has good application value. The combination of the Brock model and non-targeted detection of metabolic fingerprinting can more accurately distinguish the benign and malignant nature of pulmonary nodules.

Objective:To establish HPLC fingerprint and methods for determining the contents of four iridoid glycosides of Gentiana rigescens; To evaluate the quality of Gentiana rigescens from different origins; To improve the quality control level of Gentiana rigescens medicinal materials.Methods:Using 15 batches of Gentiana rigescens from the main production areas and authentic production areas as raw materials, the common mode of HPLC fingerprints of Gentiana rigescens was established, and the chemical components of the common peaks were identified. Referring to the common mode of fingerprints, similarity analysis was conducted on the fingerprints of Gentiana rigescens from different origins. Using chemometric methods, cluster analysis (HCA), principal component analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed on 15 batches of Gentiana rigescens, with the common peak area of fingerprint as the variable. The contents of four types of iridoid glycosides in Gentiana rigescens were determined. Combined with the fingerprints and the content results of four types of iridoid glycosides, the quality of Gentiana rigescens from different origins was evaluated.Results:The fingerprints of Gentiana rigescens contained 9 common peaks, with 4 identified iridoid glycosides. The similarity of the fingerprints of 15 batches of Gentiana rigescens ranged from 0.962 to 0.999. HCA and PCA divided the 15 batches of Gentiana rigescens into two categories. OPLS-DA analyzed 3 significantly different components, namely gentiopicroside, peak 7, and loganic acid. The content determination results showed that the average contents of loganic acid, swertiamarin, and gentiopicroside in Gentiana rigescens from Dali Bai Autonomous Prefecture and Yunnan Province were the highest, and the total amount of four iridoid glycosides was also significantly higher than that from other regions, indicating that the overall quality of Gentiana rigescens from Dali Bai Autonomous Prefecture and Yunnan Province was relatively good.Conclusion:This method is simple, fast, accurate, and can provide reference for improving the quality standards of Gentiana rigescens.

Guided by molecular networking, nine novel curvularin derivatives (1-9) and 16 known analogs (10-25) were isolated from the hydrothermal vent sediment fungus Penicillium sp. HL-50. Notably, compounds 5-7 represented a hybrid of curvularin and purine. The structures and absolute configurations of compounds 1-9 were elucidated via nuclear magnetic resonance (NMR) spectroscopy, X-ray diffraction, electronic circular dichroism (ECD) calculations, ¹³C NMR calculation, modified Mosher's method, and chemical derivatization. Investigation of anti-inflammatory activities revealed that compounds 7-9, 11, 12, 14, 15, and 18 exhibited significant suppressive effects against lipopolysaccharide (LPS)-induced nitric oxide (NO) production in murine macrophage RAW264.7 cells, with IC₅₀ values ranging from 0.44 to 4.40 μmol·L^-1. Furthermore, these bioactive compounds were found to suppress the expression of inflammation-related proteins, including inducible NO synthase (iNOS), cyclooxygenase-2 (COX-2), NLR family pyrin domain-containing protein 3 (NLRP3), and nuclear factor kappa-B (NF-κB). Additional studies demonstrated that the novel compound 7 possessed potent anti-inflammatory activity by inhibiting the transcription of inflammation-related genes, downregulating the expression of inflammation-related proteins, and inhibiting the release of inflammatory cytokines, indicating its potential application in the treatment of inflammatory diseases.
Penicillium/chemistry* ; Mice ; Animals ; Anti-Inflammatory Agents/isolation & purification* ; RAW 264.7 Cells ; Nitric Oxide/metabolism* ; Hydrothermal Vents/microbiology* ; Macrophages/immunology* ; Molecular Structure ; Nitric Oxide Synthase Type II/immunology* ; Cyclooxygenase 2/immunology* ; Geologic Sediments/microbiology* ; NF-kappa B/immunology* ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology*

Stearoyl-coenzyme A desaturase 1 (SCD1) catalyzes the rate-limiting step of de novo lipogenesis and modulates lipid homeostasis. Although numerous SCD1 inhibitors were tested for treating metabolic disorders both in preclinical and clinic studies, the tissue-specific roles of SCD1 in modulating obesity-associated metabolic disorders and determining the pharmacological effect of chemical SCD1 inhibition remain unclear. Here a novel role for intestinal SCD1 in obesity-associated metabolic disorders was uncovered. Intestinal SCD1 was found to be induced during obesity progression both in humans and mice. Intestine-specific, but not liver-specific, SCD1 deficiency reduced obesity and hepatic steatosis. A939572, an SCD1-specific inhibitor, ameliorated obesity and hepatic steatosis dependent on intestinal, but not hepatic, SCD1. Mechanistically, intestinal SCD1 deficiency impeded obesity-induced oxidative stress through its novel function of inducing metallothionein 1 in intestinal epithelial cells. These results suggest that intestinal SCD1 could be a viable target that underlies the pharmacological effect of chemical SCD1 inhibition in the treatment of obesity-associated metabolic disorders.

Objective To determine the effect of limb dominance on landing biomechanics and lower limb functional outcomes in patients with anterior cruciate ligament reconstruction(ACLR).Methods Forty-nine participants were recruited and divided into the ACLR on dominant limb(ACLR-D)group,ACLR on nondominant limb(ACLR-ND)group and healthy control group.Single-leg jump landing,knee isokinetic muscle strength,Y balance,and single-leg hop distance were tested on both limbs of all participants.Kinematics and kinetics data during the single-leg jump landing were collected by an infrared motion capture system and a force platform,and knee joint muscle strength was collected using the isokinetic muscle strength testing system.Two-way mixed-design ANOVAs were used to observe the effects of limb and group on the outcomes of each test.Results The non-surgical limbs had greater knee valgus,knee external rotation angles and knee valgus moments during single-leg jump landing in the ACLR-D group compared with those in the ACLR-ND group,and the ACLR-D group had significantly smaller bilateral knee flexion angles than the control group.There were no differences in knee muscle strength,Y-balance composite scores and single-leg hop distance between ACLR-D and ACLR-ND groups,but the Y balance scores in the ACLR-ND group were smaller than those in the control group.Conclusions Limb dominance has no effects on knee muscle strength,dynamic postural control,and single-leg hop function in ACLR patients.The non-surgical limbs of ACLR-D patients are at a higher risk of ACL injury due to the presence of greater knee valgus and external rotation angles and knee valgus moments.

Objective:To explore the value of deep learning (DL) models based on conventional MRI in differentiating orbital solitary fibrous tumors (SFT) from schwannomas.Methods:This was a case-control study. A retrospective analysis was conducted on patients with pathologically confirmed orbital SFT and schwannoma admitted to Eye & ENT Hospital, Fudan University (institution 1) from December 2014 to January 2022 and Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine (institution 2) from July 2015 to May 2022. A total of 140 patients were included, with 104 patients from institution 1 comprising the training cohort for building DL models and 36 patients from institution 2 comprising the external validation cohort for assessing model performance. Based on the preoperative cross-sectional fat-suppressed T 2WI and contrast-enhanced T 1WI (ceT 1WI), tumor contours were outlined on all tumor-containing slices. Six diagnostic models were constructed using residual networks (ResNet) and split-attention residual networks (ResNeSt) with 18 layers (ResNet-18 and ResNeSt-18), based solely on individual T 2WI and ceT 1WI, as well as a combination of both. A radiology resident and an attending radiologist independently reviewed conventional MRI images to determine the tumor type. The performance of the DL models and radiologists in differentiating orbital SFT from schwannoma in the external validation cohort was evaluated using receiver operating characteristic curves, and the areas under the curves (AUC) were compared using the DeLong test. Results:In the external validation cohort, the AUC (95% CI) of the ResNet-18 models based on T 2WI, ceT 1WI, and their combination were 0.861 (0.719-1), 0.896 (0.774-1), and 0.885 (0.755-1), respectively, while the AUC (95% CI) of the ResNeSt-18 models were 0.889 (0.748-1), 0.872 (0.726-1), and 0.910 (0.801-1), respectively. Among these, the ResNeSt-18 model based on the combined sequences achieved the best performance in differentiating the two tumors. The AUC (95% CI) for the individual interpretation of the radiology resident and attending radiologist were 0.729 (0.571-0.887) and 0.771 (0.618-0.923), respectively. The AUC of the ResNeSt-18 model based on the combined sequences was statistically significantly higher than those of the resident and attending radiologist ( Z=1.96, P=0.049; Z=2.00, P=0.045). Conclusion:The ResNeSt-18 model based on conventional MRI can effectively differentiate orbital SFT from schwannoma, demonstrating better performance than those of the radiology resident and the attending radiologist.

BACKGROUND:The re-injury rate of the anterior cruciate ligament continues to be high and the unclear relationship between neuromuscular function and biomechanical risk factors may be one of the reasons for poor injury prevention and rehabilitation.OBJECTIVE:To evaluate the biomechanics and neuromuscular function characteristics of the knee joint during landing movements after anterior cruciate ligament reconstruction,and to further explore the effects of muscle strength,proprioception,and dynamic postural control on the risk indicators of anterior cruciate ligament injury during landing maneuver.METHODS:Twenty-six male anterior cruciate ligament reconstruction patients and 26 healthy control males at the age of 18-35 years were recruited and randomized to undergo joint kinesthesia test,Y-balance test,and isometric muscle strength tests.Kinematic and kinetic data of the knee joints during single-legged jump landing tasks were collected using an infrared motion capture system and force plates.RESULTS AND CONCLUSION:(1)Compared with the healthy control group,patients after anterior cruciate ligament reconstruction demonstrated higher knee valgus angle(P=0.021),lower hamstring muscle strength(P＜0.001),lower quadriceps muscle strength(P＜0.001)and Y-balance anterior reach distance(P＜0.001),and worse knee flexion kinesthesia(P＜0.001)and extension kinesthesia(P=0.001).(2)The predictor variables of knee extension moment were quadriceps strength and knee flexion kinesthesia(R2=0.298,P=0.007).The predictor variable of knee varus and valgus angle was hamstring strength(R2=0.117,P=0.048).The predictor variable of knee internal and external rotation angle was the hamstring-to-quadriceps peak torque ratio(R2=0.134,P=0.037).(3)The results showed that after anterior cruciate ligament reconstruction,patients still had abnormal biomechanical action patterns and neuromuscular function defects in the frontal plane of the knee joint,and elevating the muscle strength of the hamstrings,avoiding excessive quadriceps muscle strength and enhancing the proprioception of the knee joint were helpful to improve the biomechanical patterns of the sagittal plane,frontal plane and horizontal plane of the knee joint and reduce the risk of anterior cruciate ligament injury during landing maneuvers.

Objective To determine the effect of limb dominance on landing biomechanics and lower limb functional outcomes in patients with anterior cruciate ligament reconstruction(ACLR).Methods Forty-nine participants were recruited and divided into the ACLR on dominant limb(ACLR-D)group,ACLR on nondominant limb(ACLR-ND)group and healthy control group.Single-leg jump landing,knee isokinetic muscle strength,Y balance,and single-leg hop distance were tested on both limbs of all participants.Kinematics and kinetics data during the single-leg jump landing were collected by an infrared motion capture system and a force platform,and knee joint muscle strength was collected using the isokinetic muscle strength testing system.Two-way mixed-design ANOVAs were used to observe the effects of limb and group on the outcomes of each test.Results The non-surgical limbs had greater knee valgus,knee external rotation angles and knee valgus moments during single-leg jump landing in the ACLR-D group compared with those in the ACLR-ND group,and the ACLR-D group had significantly smaller bilateral knee flexion angles than the control group.There were no differences in knee muscle strength,Y-balance composite scores and single-leg hop distance between ACLR-D and ACLR-ND groups,but the Y balance scores in the ACLR-ND group were smaller than those in the control group.Conclusions Limb dominance has no effects on knee muscle strength,dynamic postural control,and single-leg hop function in ACLR patients.The non-surgical limbs of ACLR-D patients are at a higher risk of ACL injury due to the presence of greater knee valgus and external rotation angles and knee valgus moments.

BACKGROUND:The re-injury rate of the anterior cruciate ligament continues to be high and the unclear relationship between neuromuscular function and biomechanical risk factors may be one of the reasons for poor injury prevention and rehabilitation.OBJECTIVE:To evaluate the biomechanics and neuromuscular function characteristics of the knee joint during landing movements after anterior cruciate ligament reconstruction,and to further explore the effects of muscle strength,proprioception,and dynamic postural control on the risk indicators of anterior cruciate ligament injury during landing maneuver.METHODS:Twenty-six male anterior cruciate ligament reconstruction patients and 26 healthy control males at the age of 18-35 years were recruited and randomized to undergo joint kinesthesia test,Y-balance test,and isometric muscle strength tests.Kinematic and kinetic data of the knee joints during single-legged jump landing tasks were collected using an infrared motion capture system and force plates.RESULTS AND CONCLUSION:(1)Compared with the healthy control group,patients after anterior cruciate ligament reconstruction demonstrated higher knee valgus angle(P=0.021),lower hamstring muscle strength(P＜0.001),lower quadriceps muscle strength(P＜0.001)and Y-balance anterior reach distance(P＜0.001),and worse knee flexion kinesthesia(P＜0.001)and extension kinesthesia(P=0.001).(2)The predictor variables of knee extension moment were quadriceps strength and knee flexion kinesthesia(R2=0.298,P=0.007).The predictor variable of knee varus and valgus angle was hamstring strength(R2=0.117,P=0.048).The predictor variable of knee internal and external rotation angle was the hamstring-to-quadriceps peak torque ratio(R2=0.134,P=0.037).(3)The results showed that after anterior cruciate ligament reconstruction,patients still had abnormal biomechanical action patterns and neuromuscular function defects in the frontal plane of the knee joint,and elevating the muscle strength of the hamstrings,avoiding excessive quadriceps muscle strength and enhancing the proprioception of the knee joint were helpful to improve the biomechanical patterns of the sagittal plane,frontal plane and horizontal plane of the knee joint and reduce the risk of anterior cruciate ligament injury during landing maneuvers.

Objective:To explore the value of deep learning (DL) models based on conventional MRI in differentiating orbital solitary fibrous tumors (SFT) from schwannomas.Methods:This was a case-control study. A retrospective analysis was conducted on patients with pathologically confirmed orbital SFT and schwannoma admitted to Eye & ENT Hospital, Fudan University (institution 1) from December 2014 to January 2022 and Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine (institution 2) from July 2015 to May 2022. A total of 140 patients were included, with 104 patients from institution 1 comprising the training cohort for building DL models and 36 patients from institution 2 comprising the external validation cohort for assessing model performance. Based on the preoperative cross-sectional fat-suppressed T 2WI and contrast-enhanced T 1WI (ceT 1WI), tumor contours were outlined on all tumor-containing slices. Six diagnostic models were constructed using residual networks (ResNet) and split-attention residual networks (ResNeSt) with 18 layers (ResNet-18 and ResNeSt-18), based solely on individual T 2WI and ceT 1WI, as well as a combination of both. A radiology resident and an attending radiologist independently reviewed conventional MRI images to determine the tumor type. The performance of the DL models and radiologists in differentiating orbital SFT from schwannoma in the external validation cohort was evaluated using receiver operating characteristic curves, and the areas under the curves (AUC) were compared using the DeLong test. Results:In the external validation cohort, the AUC (95% CI) of the ResNet-18 models based on T 2WI, ceT 1WI, and their combination were 0.861 (0.719-1), 0.896 (0.774-1), and 0.885 (0.755-1), respectively, while the AUC (95% CI) of the ResNeSt-18 models were 0.889 (0.748-1), 0.872 (0.726-1), and 0.910 (0.801-1), respectively. Among these, the ResNeSt-18 model based on the combined sequences achieved the best performance in differentiating the two tumors. The AUC (95% CI) for the individual interpretation of the radiology resident and attending radiologist were 0.729 (0.571-0.887) and 0.771 (0.618-0.923), respectively. The AUC of the ResNeSt-18 model based on the combined sequences was statistically significantly higher than those of the resident and attending radiologist ( Z=1.96, P=0.049; Z=2.00, P=0.045). Conclusion:The ResNeSt-18 model based on conventional MRI can effectively differentiate orbital SFT from schwannoma, demonstrating better performance than those of the radiology resident and the attending radiologist.