Through a comprehensive analysis combining network pharmacology prediction and transcriptomics, this study systematically explained the multi-target mechanism of Cyanotis arachnoidea(CA) Gel in improving melasma. A melasma model was induced in female SD rats by progesterone injection combined with ultraviolet B(UVB) irradiation for 40 consecutive days, while the blank control group was only fed routinely. After successful model establishment, the rats were randomly divided into five groups and administered different doses of CA ethanol extract gel(high, medium, and low doses) or arbutin Gel(positive control), which were applied once daily for 28 consecutive days. Subsequently, the levels of superoxide dismutase(SOD), malondialdehyde(MDA), and tyrosinase(TYR) in the skin, serum, and liver tissues were measured. Hematoxylin-eosin(HE) staining and Masson-Fontana staining were used to observe the pathological changes in the tissues. Network pharmacology combined with transcriptomics was employed to identify core targets and pathways, and the differential gene expression was validated by quantitative real-time PCR(qPCR). Pharmacodynamic experiments showed that CA Gel significantly increased SOD activity and decreased MDA and TYR levels in the skin, serum, and liver of model rats. It also improved epidermal thickening, inflammatory infiltration, collagen loss, and melanin deposition. Network pharmacology analysis showed that CA mainly regulated core targets such as signal transducer and activator of transcription 3(STAT3), epidermal growth factor receptor(EGFR), and interleukin-6(IL-6), and modulated the phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT) and interleukin-17(IL-17) signaling pathways. Transcriptomic analysis showed that CA Gel significantly downregulated the gene expression of heat shock protein 90β family member 1(Hsp90b1), heat shock protein 90α family member 1(Hsp90aa1), and the key steroid synthesis enzyme cytochrome P450 family 17 subfamily A member 1(Cyp17a1), while upregulating thioredoxin 1(Txn1). qPCR results confirmed that CA Gel regulated oxidative stress and inflammatory response by inhibiting the IL-17 signaling pathway and steroid hormone synthesis. This study, for the first time, reveals the molecular mechanism of CA Gel in improving melasma through multi-target synergistic regulation of oxidative stress, inflammatory response, and hormone metabolism pathways, providing a scientific basis for the treatment of pigmentation diseases with traditional Chinese medicine.
Animals ; Rats ; Female ; Rats, Sprague-Dawley ; Network Pharmacology ; Drugs, Chinese Herbal/administration & dosage* ; Melanosis/metabolism* ; Transcriptome/drug effects* ; Humans ; Superoxide Dismutase/genetics* ; Signal Transduction/drug effects* ; Malondialdehyde/metabolism*

Retrieving keyframes most relevant to text from small intestine videos with given labels can efficiently and accurately locate pathological regions. However, training directly on raw video data is extremely slow, while learning visual representations from image-text datasets leads to computational inconsistency. To tackle this challenge, a small bowel video keyframe retrieval based on multi-modal contrastive learning (KRCL) is proposed. This framework fully utilizes textual information from video category labels to learn video features closely related to text, while modeling temporal information within a pretrained image-text model. It transfers knowledge learned from image-text multimodal models to the video domain, enabling interaction among medical videos, images, and text data. Experimental results on the hyper-spectral and Kvasir dataset for gastrointestinal disease detection (Hyper-Kvasir) and the Microsoft Research video-to-text (MSR-VTT) retrieval dataset demonstrate the effectiveness and robustness of KRCL, with the proposed method achieving state-of-the-art performance across nearly all evaluation metrics.
Humans ; Video Recording ; Intestine, Small/diagnostic imaging* ; Machine Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To analyze the risk factors for chronic mountain sickness(CMS)in young male migrants living in high-altitude areas and to construct a diagnostic model and evaluate its diagnostic efficacy.Methods From June 10 to December 29,2023,a cross-sectional study was conducted on young male migrants subjected with convenience sampling who had been living in high-altitude areas(4 500～5 000 m)for 6 months or longer.Their demographic data were collected and blood samples were collected for laboratory test.According to the Qinghai Score for Chronic Mountain Sickness,they were divided into CMS group and non-CMS group.Then the participants were randomly divided into a training set and a test set in a ratio of 8∶2.Independent risk factors for CMS occurrence were screened out,through random forest variable importance ranking,univariate and multivariable logistic regression analysis,and a diagnostic model was constructed based on these factors.Receiver operating characteristic(ROC)curve analysis,calibration curve analysis,clinical decision curve analysis,and influence curve analysis were used to comprehensively evaluate the diagnostic performance of the model.Results According to the inclusion and exclusion criteria,308 out of 376 participants were finally subjected,and 17.53%of them were diagnosed with CMS.The major clinical symptoms of the CMS patients were dyspnea or palpitations(79.63%)and sleep disorders(85.19%).Further analysis revealed that creatine kinase-MB/creatine kinase(CK-MB/CK,OR=2.17,95%CI:1.43～3.28),high-altitude residence time(OR=2.44,95%CI:1.08～5.54),and body mass index(BMI,OR=1.62,95%CI:1.05～2.50)were 3 major independent risk factors for CMS.The area under the curve(AUC)value of the CMS diagnostic model in the training set and test set was 0.821(95%CI:0.756～0.886)and 0.821(95%CI:0.700～0.944),the specificity was 66.30%and 73.90%,the sensitivity was 89.50%and 81.20%,respectively,indicating good discrimination ability.Hosmer-Lemeshow goodness-of-fit test showed consistency between predicted results and actual observations(χ2=10.029,P=0.263;χ2=4.477,P=0.812).Clinical decision curve analysis demonstrated that within the threshold probability range from 0.1 to 0.7,the net benefit of the model exceeded both full intervention and no intervention strategies.The influence curve analysis showed high consistency between the model predictions and actual incidence when the threshold probability exceeded 0.4.These two analyses together confirmed the clinical application value of the model.Conclusion CK-MB/CK,high-altitude residence time and BMI are independent risk factors for CMS,and their diagnostic model helps identify potential individuals at risk for CMS.Early intervention can prevent the harm of CMS to the health of young men migrating to high-altitude areas.

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.