BACKGROUND:Naringin has been shown to promote the proliferation and osteogenic differentiation of bone marrow derived mesenchymal stem cells,making it a potential candidate for treating osteoporosis andenhancing fracture healing.However,its clinical application is limited by its low bioavailability.OBJECTIVE:To prepare chitosan/β-tricalcium phosphate scaffolds loaded with naringin and characterize their biological properties.METHODS:Chitosan/β-tricalcium phosphate scaffolds were prepared by freeze-drying and chemical crosslinking.The chitosan/β-tricalcium phosphate scaffolds were immersed in anhydrous ethanol solution containing naringin for 3 hours.After vacuum cold drying,chitosan/β-tricalcium phosphate/naringin scaffolds were obtained.The pore size,porosity,swelling rate,degradation rate,mechanical properties,and in vitro release capacity of naringin of the scaffolds were characterized.Rat bone marrow mesenchymal stem cells were inoculated on the surface of chitosan/β-tricalcium phosphate scaffolds and chitosan/β-tricalcium phosphate/naringin scaffolds,respectively,and cell proliferation,adhesion,activity and alkaline phosphatase activity after osteogenic differentiation were detected.RESULTS AND CONCLUSION:(1)The results of scanning electron microscopy showed that the naringin-chitosan/β-tricalcium phosphate composite scaffold had a porous mesh structure.The average pore diameter was(106.82±25.22)μm;the porosity was(76.26±4.81)％;24-hour swelling rate was(796.17±31.76)％;in vitro degradation rate of 7.71％at 4 weeks,and naringin could be slowly released in vitro for 9 days.There was no significant difference in the average pore size,porosity,24-hour swelling rate,in vitro degradation rate,compression strength and compression modulus at 4 weeks between the chitosan/β-tricalcium phosphate scaffold and the chitosan/β-tricalcium phosphate scaffold(P＞0.05).(2)Rat bone marrow mesenchymal stem cells adhered well to the surfaces of the two scaffolds and had good activity.Compared with the chitosan/β-tricalcium phosphate scaffold,the chitosan/β-tricalcium phosphate/naringin scaffold promoted the proliferation of rat bone marrow mesenchymal stem cells(P＜0.05),and increased the alkaline phosphatase activity of bone marrow mesenchymal stem cells after osteogenic differentiation(P＜0.05).(3)The results show that the chitosan/β-tricalcium phosphate/naringin scaffolds exhibit favorable physical properties and can effectively promote the adhesion,proliferation,and osteogenic differentiation of bone marrow-derived mesenchymal stem cells.

BACKGROUND:Naringin has been shown to promote the proliferation and osteogenic differentiation of bone marrow derived mesenchymal stem cells,making it a potential candidate for treating osteoporosis andenhancing fracture healing.However,its clinical application is limited by its low bioavailability.OBJECTIVE:To prepare chitosan/β-tricalcium phosphate scaffolds loaded with naringin and characterize their biological properties.METHODS:Chitosan/β-tricalcium phosphate scaffolds were prepared by freeze-drying and chemical crosslinking.The chitosan/β-tricalcium phosphate scaffolds were immersed in anhydrous ethanol solution containing naringin for 3 hours.After vacuum cold drying,chitosan/β-tricalcium phosphate/naringin scaffolds were obtained.The pore size,porosity,swelling rate,degradation rate,mechanical properties,and in vitro release capacity of naringin of the scaffolds were characterized.Rat bone marrow mesenchymal stem cells were inoculated on the surface of chitosan/β-tricalcium phosphate scaffolds and chitosan/β-tricalcium phosphate/naringin scaffolds,respectively,and cell proliferation,adhesion,activity and alkaline phosphatase activity after osteogenic differentiation were detected.RESULTS AND CONCLUSION:(1)The results of scanning electron microscopy showed that the naringin-chitosan/β-tricalcium phosphate composite scaffold had a porous mesh structure.The average pore diameter was(106.82±25.22)μm;the porosity was(76.26±4.81)％;24-hour swelling rate was(796.17±31.76)％;in vitro degradation rate of 7.71％at 4 weeks,and naringin could be slowly released in vitro for 9 days.There was no significant difference in the average pore size,porosity,24-hour swelling rate,in vitro degradation rate,compression strength and compression modulus at 4 weeks between the chitosan/β-tricalcium phosphate scaffold and the chitosan/β-tricalcium phosphate scaffold(P＞0.05).(2)Rat bone marrow mesenchymal stem cells adhered well to the surfaces of the two scaffolds and had good activity.Compared with the chitosan/β-tricalcium phosphate scaffold,the chitosan/β-tricalcium phosphate/naringin scaffold promoted the proliferation of rat bone marrow mesenchymal stem cells(P＜0.05),and increased the alkaline phosphatase activity of bone marrow mesenchymal stem cells after osteogenic differentiation(P＜0.05).(3)The results show that the chitosan/β-tricalcium phosphate/naringin scaffolds exhibit favorable physical properties and can effectively promote the adhesion,proliferation,and osteogenic differentiation of bone marrow-derived mesenchymal stem cells.

AIM: To investigate the expression changes and significance of serum microRNA-34a-5p(miR-34a-5p)and silent information regulator T1(SIRT1)in patients with endophthalmitis after cataract surgery.METHODS: Patients with endophthalmitis after cataract surgery from May 2020 to May 2024 were selected as infection group(20 cases), and patients without endophthalmitis were selected as control group(74 cases). Serum SIRT1 levels were detected by ELISA; the serum level of serum miR-34a-5p was detected by qRT-PCR; the correlation between miR-34a-5p and SIRT1 was analyzed by Pearson method; Logistic regression was used to analyze the influencing factors of endophthalmitis after cataract operation. Receiver operating characteristic(ROC)curve was drawn to analyze the diagnostic value of serum miR-34a-5p and SIRT1 levels in postoperative endophthalmitis.RESULTS: Compared with the control group, the serum level of miR-34a-5p in the infected group was significantly increased(P<0.001), and the serum level of SIRT1 was significantly decreased(P<0.001). Correlation analysis showed that miR-34a-5p was negatively correlated with SIRT1(r=-0.421, P<0.001). Logistic multivariate regression analysis showed that miR-34a-5p was an independent risk factor affecting endophthalmitis infection after cataract surgery(OR=3.532, P<0.05), and SIRT1 was a protective factor affecting endophthalmitis infection after cataract surgery(OR=0.875, P<0.05). The ROC curve showed that the area under curve(AUC)of serum miR-34a-5p combined with SIRT1 in the diagnosis of postoperative endophthalmitis was 0.933(95%CI: 0.861-0.975).CONCLUSION:Serum levels of miR-34a-5p are highly expressed and SIRT1 is lowly expressed in postoperative endophthalmitis, they are closely related to the occurrence and development of endophthalmitis after cataract surgery.

AIM: To explore the value of changes in the serum expression levels of triggering receptor expressed on myeloid cells-1(TREM-1)and matrix metalloproteinase-9(MMP-9)in early clinical diagnosis of postoperative endophthalmitis in patients with cataract surgery.METHODS: A total of 21 patients who underwent cataract surgery with infectious endophthalmitis in our hospital from May 2021 to May 2023 were selected as the study subjects(endophthalmitis group), and another 100 patients who underwent cataract surgery without endophthalmitis were selected as the non-endophthalmitis group. The serum levels of TREM-1, MMP-9, and the expression levels of inflammatory factors such as interleukin-1β(IL-1β), IL-17, and tumor necrosis factors-α(TNF-α)were detected and compared between the endophthalmitis group and the non-endophthalmitis group. The correlation between TREM-1 and MMP-9 was analyzed by Pearson method. Logistic regression was applied to analyze the factors that affected the occurrence of endophthalmitis in cataract patients after surgery. Receiver operating characteristic(ROC)curve was applied to analyze the early clinical diagnostic efficacy of TREM-1 and MMP-9 levels for postoperative endophthalmitis in cataract patients.RESULTS: Compared with the non-endophthalmitis group after cataract surgery, the expression levels of serum TREM-1, MMP-9, and inflammatory factors IL-1β, IL-17, and TNF-α in the endophthalmitis group were obviously increased(all P<0.05), and the TREM-1 was positively correlated with MMP-9(r=0.389, P<0.001). Logistic regression results showed that elevated levels of serum TREM-1 and MMP-9 expression, and vitreous overflow were independent risk factors for postoperative endophthalmitis in cataract patients(all P<0.05). ROC curve showed that the area under the curve(AUC)of TREM-1, MMP-9, and their combination in diagnosing postoperative endophthalmitis in cataract patients was 0.845, 0.844, and 0.935, respectively, and the clinical efficacy of the combination of the two in early diagnosis of postoperative endophthalmitis in cataract patients was better than that of serum TREM-1 and MMP-9 alone(all P<0.05).CONCLUSION: The expression levels of serum TREM-1 and MMP-9 in patients with endophthalmitis after cataract surgery are abnormally elevated, and the combination of the two has high clinical application value in early diagnosis of endophthalmitis after cataract surgery.

The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

AIM: To investigate the predictive value of serum histone deacetylase 1(HDAC1)and endothelial nitric oxide synthase(eNOS)for infectious endophthalmitis after cataract surgery.METHODS: A total of 362 cataract patients(362 eyes)admitted to our hospital from January 2020 to January 2023 were selected as the research objects. According to the occurrence of postoperative infectious endophthalmitis, they were divided into infection group(15 cases, 15 eyes)and non-infection group(347 cases, 347 eyes). Enzyme linked immunosorbent assay(ELISA)was applied to detect the levels of serum HDAC1 and eNOS in all subjects, and the levels of serum HDAC1 and eNOS in both groups were compared; the influencing factors of infectious endophthalmitis were analyzed by multivariate Logistic regression; the receiver operative curve(ROC)was applied to analyze the predictive value of serum HDAC1 and eNOS levels for postoperative infectious endophthalmitis in cataract patients.RESULTS: The levels of serum HDAC1 and eNOS in the infected group were obviously higher than those in the uninfected group(all P<0.01). Surgical time, vitreous overflow, HDAC1, and eNOS were all risk factors for postoperative infectious endophthalmitis(all P<0.05). ROC results showed that the AUC of HDAC1 and eNOS in predicting postoperative infectious endophthalmitis in cataract patients was 0.878 and 0.877, respectively, with sensitivity of 88.7% and 87.7%, specificity of 70.4% and 7.8%, respectively, while the AUC of the two combination in predicting postoperative infectious endophthalmitis in cataract patients was 0.978, with a sensitivity of 86.7% and a specificity of 85.3%.CONCLUSION:The serum levels of HDAC1 and eNOS in patients with infectious endophthalmitis after cataract surgery are obviously increased, and the combined detection of serum HDAC1 and eNOS can improve the predictive efficacy of infectious endophthalmitis in cataract patients after surgery. Both can provide reference for clinical diagnosis and treatment.

AIM: To investigate the predictive value of serum histone deacetylase 1(HDAC1)and endothelial nitric oxide synthase(eNOS)for infectious endophthalmitis after cataract surgery.METHODS: A total of 362 cataract patients(362 eyes)admitted to our hospital from January 2020 to January 2023 were selected as the research objects. According to the occurrence of postoperative infectious endophthalmitis, they were divided into infection group(15 cases, 15 eyes)and non-infection group(347 cases, 347 eyes). Enzyme linked immunosorbent assay(ELISA)was applied to detect the levels of serum HDAC1 and eNOS in all subjects, and the levels of serum HDAC1 and eNOS in both groups were compared; the influencing factors of infectious endophthalmitis were analyzed by multivariate Logistic regression; the receiver operative curve(ROC)was applied to analyze the predictive value of serum HDAC1 and eNOS levels for postoperative infectious endophthalmitis in cataract patients.RESULTS: The levels of serum HDAC1 and eNOS in the infected group were obviously higher than those in the uninfected group(all P<0.01). Surgical time, vitreous overflow, HDAC1, and eNOS were all risk factors for postoperative infectious endophthalmitis(all P<0.05). ROC results showed that the AUC of HDAC1 and eNOS in predicting postoperative infectious endophthalmitis in cataract patients was 0.878 and 0.877, respectively, with sensitivity of 88.7% and 87.7%, specificity of 70.4% and 7.8%, respectively, while the AUC of the two combination in predicting postoperative infectious endophthalmitis in cataract patients was 0.978, with a sensitivity of 86.7% and a specificity of 85.3%.CONCLUSION:The serum levels of HDAC1 and eNOS in patients with infectious endophthalmitis after cataract surgery are obviously increased, and the combined detection of serum HDAC1 and eNOS can improve the predictive efficacy of infectious endophthalmitis in cataract patients after surgery. Both can provide reference for clinical diagnosis and treatment.

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.