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: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

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: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

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: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

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.

Objective To analyze the adverse reaction reports （ADRs） of drug-induced liver injury in recent ten years, explore the characteristics and related rules of drug-induced liver injury, and provide reference for clinical safe drug use. Methods ADRs in our hospital from 2011 to 2021 which belonged to drug-induced liver injuries were collected, and Pareto analysis was carried on. Results In 259 ADR reports, the most common type of drug-induced liver injury was hepatocellular injury （37.84%）. The age of drug-induced liver injury was mainly over 46 years, totaling 195 （75.28%）. Drugs were mainly distributed in cardiovascular system medicine （44.02%）, anti-infective medicine （23.94%）and anti-tumor medicine （11.58%）. Among the cardiovascular drugs, atorvastatin calcium 40mg and over 40mg were the highest proportion, with 53 cases （46.49%）. The main anti-infectious drugs were cephalosporins （29.03%）, carbapenem （19.35%）， antifungal （17.74%）and quinolones （11.29%）. Adverse reactions occurred within 6 days （69.88%）, the duration of adverse reactions was 1-2 weeks （31.66%）, and most patients were improved （47.88%） or cured （37.07%）. Conclusion For middle-aged and elderly patients, when the application of cardiovascular system drugs, anti-infective drugs or anti-tumor drugs, it is necessary to monitor the liver function changes of patients for at least 6 days. If there are abnormalities, the drugs should be stopped or given treatment in time, to avoid the progress of drug-induced liver injury.

ObjectiveEarly blight is a common destructive disease in the growth process of Solanaceae crops, which can lead to crop failure and serious losses. Traditional crop disease detection methods are difficult to detect disease characteristics in a timely manner during the incubation period of disease, and thus take scientific and effective prevention and control measures. This study obtained hyperspectral images of early blight of peppers at different infection stages through continuous monitoring with a hyperspectral imager. The earliest identifiable time during the incubation period of early blight in peppers (the earliest identifiable time during the incubation period in this experiment was 24 h after inoculation) was determined using the spectral angle cosine-correlation coefficient and Chebyshev distance. MethodsTaking the symptoms of the latent period of early blight in peppers as the research object, 13 characteristic wavelengths were selected using a genetic algorithm. An identification model of crop disease latent period symptoms based on spectral features was established through optimized combinations of characteristic wavelengths combined with a logistic regression model. Simultaneously, a recognition model of the latent period of early blight in peppers based on image texture features was established using local binary patterns. ResultsThe experiment was tested with 120 samples. The accuracy of the identification model of crop disease latent period symptoms based on spectral features reached over 93% in both the training set and the test set. The accuracy of the identification model of crop disease latent period symptoms based on texture features reached 98.96% and 100% in the training set and test set, respectively. ConclusionBoth spectral features and texture features can be used to detect and identify crop disease latent period symptoms. Texture features more significantly revealed the characteristics of the latent period of the disease compared to spectral features, effectively improving the detection performance of the model. The research results in this article can provide theoretical references for monitoring and identifying other crop disease latent period symptoms.

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.