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.

Aim To investigate the regulatory role and mechanism of resveratrol in inhibiting autophagy and promoting apoptosis in choroidal melanoma cells. Methods Choroidal melanoma cells (MUM2B) were divided into control and experimental groups, and treated with different concentrations of resveratrol (0, 10, 20,40,60,80 μmol ·L

Human exhaled breath has great application prospects,e.g.,monitoring pharmacokinetics,disease diagnosis,due to its advantages such as non-invasive and high-frequency sampling.Breath samples can be collected from the oral and nasal cavity.However,the oral and nasal environment affect the chemical composition of breath sample.Therefore,the investigation on the chemical composition of mouth-exhaled breath and nose-exhaled breath is crucial for selection of appropriate sampling strategy for individual studies.In this work,secondary electrospray ionization-high resolution mass spectrometry(SESI-HRMS)was applied to analysis of respiratory metabolomics in real time.A quantitative analysis approach was established for 9 kinds of volatile organic compounds(VOCs)e.g.2-butanone,2-pentanone,ethyl acetate,methyl methacrylate,toluene,styrene,mesitylene,isoprene and limonene.The limit of detection was 2.3?240.8 ng/m3.The intra-day(n=6)and inter-day(n=18)relative standard deviations were 0.6%?4.6%and 4.3%?12.2%,respectively.Nine healthy subjects were recruited to investigate the chemical composition of mouth-exhaled and nose-exhaled breath.The results showed the good performance in quantitative analysis of 9 VOCs in breath air.It was found that the number of unique component(m/z)detected in mouth-exhaled breath(167)was 2.2 times greater than that detected in nose-exhaled breath(76),which might result from the complex environment in oral cavity.The signal intensity of commun component(163)was significantly different between mouth-exhaled breath and nose-exhaled breath.Additionally,the elemental composition analysis showed that the proportion of polar compounds detected in nose-exhaled breath was higher than that in mouth-exhaled breath.This study demonstrated that there was significant differences in the chemical composition between mouth-exhaled and nose-exhaled breath,which provided a theoretical basis for selection of exhalation mode.

Objective To summarize the prescription and medication rules for the treatment of diabetes mellitus by contemporary Lingnan famous Chinese medical practitioners through data mining analysis.Methods The literature on treating diabetes mellitus by contemporary Lingnan famous Chinese medical practitioners were retrieved from the databases of CNKI,Wanfang and VIP,and the collections of clinical experience and medical cases of contemporary Lingnan famous practitioners were also reviewed to screen the relevant medical records of diabetes mellitus treated by Lingnan famous practitioners.The information of Chinese medicine prescriptions for diabetes mellitus in the medical records was input to Excel to establish a database,and then the frequency analysis was performed in terms of the nature,flavors and meridian tropism,therapeutic-action classification of the Chinese herbal medicines and traditional Chinese medicine(TCM)syndrome types.Moreover,the association rule analysis and cluster analysis were carried out using IBM SPSS Modeler 18.0 and SPSS Statistics 26.0.Results A total of 62 medical records of diabetes mellitus treated by the 24 contemporary Lingnan famous Chinese medical practitioners such as DENG Tie-Tao,LIU Shi-Chang,XIONG Man-Qi,LI Sai-Mei,ZHU Zhang-Zhi,LIU Min,and FAN Guan-Ji were screened out for the analysis.And a total of 101 prescriptions involving 210 Chinese herbal medicines were included.There were 29 commonly-used Chinese medicines with a frequency being or more than 15 times,and they were Glycyrrhizae Radix et Rhizoma Praeparata cum Melle,Astragali Radix,Bupleuri Radix,Puerariae Lobatae Radix,Poria,Atractylodis Macrocephalae Rhizoma,Codonopsis Radix,Scutellariae Radix,etc.According to the therapeutic action,the Chinese medicines were mainly classified into the categories of drugs for supplementing the deficiency,drugs for clearing heat,and drugs for dispelling wind-damp.The primary syndrome types were syndrome of deficiency of both spleen and kidney and syndrome of liver stagnation and spleen deficiency,and the syndromes were usually complicated with the syndrome elements of qi deficiency,yin deficiency,yang deficiency,cold-damp,phlegm-damp,and damp-heat.The association rule analysis yielded 28 core drug combinations consisting of 2-4 herbs,and the cluster analysis yielded 5 new candidate prescriptions,which were mainly derived from the modification of classical formulas such as Xiao Chaihu Decoction,Fuzi Lizhong Decoction,Yuquan Pills plus Zengye Decoction,and Zuogui Pills.Conclusion For the treatment of diabetes mellitus,contemporary Lingnan famous Chinese medical practitioners primarily adopt the methods of invigorating spleen and warming kidney,and soothing liver,draining dampness and resolving turbidity,which has more distinctive regional characteristics of Lingnan and can provide a reference for syndrome differentiation and treatment of diabetes mellitus in the Lingnan area.

OBJECTIVE Optimizing the water extraction technology of Xiangqin jiere granules. METHODS The orthogonal test of 3 factors and 3 levels was designed， and comprehensive scoring was conducted for the above indexes by using G1-entropy weight to obtain the optimized water extraction technology of Xiangqin jiere granules with water addition ratio， extraction time and extraction times as factors， using the contents of forsythoside A， baicalin， phillyrin， oroxylin A-7-O-β-D-glycoside， wogonoside， baicalein and wogonin， and extraction rate as evaluation indexes. BP neural network modeling was used to optimize the network model and water extraction process using the results of 9 groups of orthogonal tests as test and training data， the water addition multiple， decocting time and extraction times as input nodes， and the comprehensive score as output nodes. Then the two analysis methods were compared by verification test to find the best water extraction process parameters. RESULTS The water extraction technology optimized by the orthogonal test was 8-fold water， extracting 3 times， extracting for 1 h each time. Comprehensive score was 96.84 （RSD＝0.90%）. The optimal water extraction technology obtained by BP neural network modeling included 12-fold water， extracting 4 times， extracting for 0.5 h each time. The comprehensive score was 92.72 （RSD＝0.77%）， which was slightly lower than that of the orthogonal test. CONCLUSIONS The water extraction technology of Xiangqin jiere granules is optimized successfully in the study， which includes adding 8-fold water， extracting 3 times， and extracting for 1 hour each time.

Sesquiterpenoids are widely found in nature, while nitrobenzoyl sesquiterpenoids are relatively rare. Twelve natural nitrobenzoyl sesquiterpenoids were all derived from marine Aspergillus fungi, which are typical natural products with marine characteristics. These natural products exhibit good antitumor, antiviral, and inhibition of osteoclast differentiation activity, especially in the treatment of osteoclast-related diseases, showing good medicinal development value. This article reviews the natural product sources, chemical structure, chemical synthesis, biosynthesis, bioactivity, and pharmacological mechanisms of nitrobenzoyl sesquiterpenoids and predicts and discusses their absorption, distribution, metabolism, excretion, toxicity (ADME/T), and drug-likeness, providing a comprehensive understanding of the natural products of nitrobenzoyl sesquiterpenoids from marine sources and their potential for pharmaceutical development.