ObjectiveTo analyze the differences in color， odor and volatile components of Citri Reticulatae Pericarpium（CRP） before and after being stir-fried with Halloysitum Rubrum， and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the volatile components were analyzed by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. According to the principle of variable importance in the projection（VIP） value>1.5， volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose， the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum， of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected， including α-pinene， β-myrcene， linalool， sabinene， ocimene isomer mixture， A-ocimene， and δ-elemene. After being processed with Halloysitum Rubrum， the brightness value（L^*）， yellow-blue value（b^*） and total chromatic value（E^*_ab） of CRP were decreased（P<0.01）， and red-green value（a^*） was increased（P<0.01）， the response values of S4， S5， S10 and S13 sensors were significantly increased（P<0.05）， and the response values of S3 and S8 sensors were significantly decreased（P<0.05）. Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L^* and E^*_ab， but positively correlated with a^*. Sabinene was positively correlated with L^* and E^*_ab. Linalool was positively correlated with L^* and E^*_ab， and negatively correlated with a^*. The ocimene isomer mixture was positively correlated with the L^*. ConclusionAfter being processed with Halloysitum Rubrum， the appearance color， odor and volatile components of CRP change significantly， and α-pinene， β-myrcene， sabinene， linalool and A-ocimene are the characteristic volatile components before and after processing， which can provide references for the quality evaluation and clinical application of CRP and its processed products.

ObjectiveTo analyze the differences in color， odor and volatile components of Citri Reticulatae Pericarpium（CRP） before and after being stir-fried with Halloysitum Rubrum， and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the volatile components were analyzed by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. According to the principle of variable importance in the projection（VIP） value>1.5， volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose， the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum， of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected， including α-pinene， β-myrcene， linalool， sabinene， ocimene isomer mixture， A-ocimene， and δ-elemene. After being processed with Halloysitum Rubrum， the brightness value（L^*）， yellow-blue value（b^*） and total chromatic value（E^*_ab） of CRP were decreased（P<0.01）， and red-green value（a^*） was increased（P<0.01）， the response values of S4， S5， S10 and S13 sensors were significantly increased（P<0.05）， and the response values of S3 and S8 sensors were significantly decreased（P<0.05）. Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L^* and E^*_ab， but positively correlated with a^*. Sabinene was positively correlated with L^* and E^*_ab. Linalool was positively correlated with L^* and E^*_ab， and negatively correlated with a^*. The ocimene isomer mixture was positively correlated with the L^*. ConclusionAfter being processed with Halloysitum Rubrum， the appearance color， odor and volatile components of CRP change significantly， and α-pinene， β-myrcene， sabinene， linalool and A-ocimene are the characteristic volatile components before and after processing， which can provide references for the quality evaluation and clinical application of CRP and its processed products.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

As the number of patients with compromised immune function increases and fungal resistance develops, so does the risk of contracting deadly fungi in humans. Both fungi and humans are eukaryotes, so identifying unique targets for antifungal drug development is difficult. In addition, the existing antifungal drugs are limited by toxicity, drug interaction and drug resistance in practical application, which leads to the increasing incidence and fatal rate of fungal infections. Therefore, it is urgent to develop new antifungal drugs. The semi-synthetic technology using microbial fermentation products from natural sources as lead compounds has become the most used method in structural modification of antifungal drugs due to its advantages of few reaction steps and easy operation. This paper will introduce the current status of natural antifungal drugs in clinical use, as well as the latest progress in the research and development of new semi-synthetic antifungal drugs, and summarize their mechanism of action, structural modifications, advantages and disadvantages, so as to provide reference for the subsequent development of new antifungal drugs.

[Objective] To conduct a retrospective statistical comparison of alanine aminotransferase (ALT) test values in blood donors prior to blood collection, aiming to analyze the objective characteristics of the population with elevated ALT levels (ALT>50 U/L) and provide reference data for adjusting the screening eligibility threshold for ALT. [Methods] The preliminary ALT screening data of 30 341 blood donor samples collected prior to blood donation from three smart blood donation sites at the Shenzhen Blood Center between 2022 and 2023 were extracted and compared with data from a health examination department of a tertiary hospital in Shenzhen (representing the general population, n=24 906). Both datasets were categorized and statistically described. A retrospective analysis was conducted to examine the associations between ALT test results and factors such as donors' gender, age, ethnicity, donation site, donation season, and frequency of blood donation. [Results] The ALT levels in both blood donors and the general population were non-normally distributed. The 95th percentile of ALT values was calculated as 61.4 U/L (male: 67.8 U/L, female: 39.3 U/L) for blood donors and 58.1 U/L (male: 63.7 U/L, female: 51.2 U/L) for the general population. The non-compliance rates (ALT>50 U/L) were 7.65% (2 321/30 341) in blood donors and 7.08% (1 763/24 906) in the general population. There were significant differences (P<0.05) in the ALT failure rate among blood donors based on gender, age, and donation site, but no significant differences (P>0.05) during the blood donation season. There was no statistically significant difference (P>0.05) in the positive rates of four serological markers (HBsAg, anti HCV, HIV Ag/Ab, anti TP) for blood screening pathogens between ALT unqualified and qualified individuals (2.05% vs 1.5%). If the ALT qualification threshold was raised from 50 U/L to 90 U/L, the non qualification rates of male and female blood donors would decrease from 9.82% (2 074/21 125) to 2.23% (471/21 125) and from 2.70% (249/9 216) to 0.75% (69/9 216), respectively. Among the 154 blood donors who donated blood more than 3 times, 88.31% of the 248 ALT test results were in the range of 50-90 U/L. Among them, 9 cases had ALT>130 U/L, and ALT was converted to qualified in subsequent blood donations. [Conclusion] There are differences in the ALT failure rate among blood donors of different genders and ages, and different blood donation sites and operators can also affect the ALT detection values of blood donors. The vast majority of blood donors with ALT failure are caused by transient and non pathological factors. With the widespread use of blood virus nucleic acid testing, appropriately increasing the ALT qualification threshold for blood donors can expand the qualified population and alleviate the shortage of blood sources, and the risk of blood safety will not increase.

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.