Objective To explore the polymorphism of tyrosinase (TYR) and melanocortin 1 receptor (MC1R) genes and their mRNA expression levels in relation to coat-color phenotypes in guinea pigs, providing genetic markers for locating dominant traits in guinea pigs. Methods A total of 57 self-bred ordinary-level guinea pigs were selected and divided into three groups based on coat color: white (n=22), variegated (n=22) and black (n=13). The guinea pigs were euthanized with an overdose of pentobarbital sodium via intraperitoneal injection. DNA was then extracted from the dorsal skin tissue. Polymorphism in the coding sequence (CDS) of the exons of the TYR and MC1R genes in each group was detected by cloning and sequencing. The mRNA expression of the two genes in skin tissues was detected by real-time fluorescent quantitative PCR to investigate the relationship between these genes and guinea pig coat color. Results A single nucleotide polymorphism (SNP) site was found in the CDS region of TYR exon Ⅰ, where the base A was replaced by G. All white guinea pigs had the G/G genotype for TYR, while no deep-colored (variegated and black) guinea pigs exhibited the G/G genotype for TYR. Most deep-colored guinea pigs had the A/A genotype, and a few had A/G genotype. The A/A genotype frequency in black guinea pigs was higher than in variegated guinea pigs. A 2 760 bp sequence deletion was identified in the exon of the MC1R gene, marked as the - gene, with non-deleted samples marked as N gene. Most white guinea pigs had the -/- genotype for MC1R, variegated guinea pigs mainly had the -/N genotype, and black guinea pigs mainly had the N/N genotype, with a few showing the -/N. The TYR gene expression level was higher in white guinea pigs, lower in variegated guinea pigs, and intermediate in black guinea pigs, but there was no significant difference among the three groups (P>0.05). The MC1R gene expression level in white guinea pigs was extremely low, while both variegated and black guinea pigs showed significantly higher levels than white guinea pigs (P<0.01). Black guinea pigs showed significantly higher levels than variegated guinea pigs (P<0.05). ConclusionThe TYR and MC1R genes synergistically regulate coat color of guinea pigs. The G-site mutation in the TYR gene may lead to albinism, and the change of N-site in the MC1R gene affects the depth of the coat color.

Ten compounds were isolated and purified from the dichloromethane extract of stems of Ephedra intermedia by various chromatographic methods. Based on the analysis of physicochemical properties and spectral data, the structures of the ten compounds were identified as 1-allyl-3,4-dimethoxy-benzene-5-O-β-D-glucopyranoside (1), lyoniresinol (2), secoisolariciresinol (3), 4,3′,4′-trihydroxy-3-methoxylignan-9,9′-diyldiacetate (4), dehydroconiferyl alcohol (5), isocubebin (6), balanophonin B (7), sesquipinsapol B (8), crataegifin A (9), 1-(2-(4-hydroxy-3-methoxyphenyl)-3-(hydroxymethyl)-7-methoxy-2,3-dihydrobenzofuran-5-yl)ethan-1-one (10). Compound 1 is a new compound, named as 1-allyl-3,4-dimethhoxy-benzene-5-O-β-D-glucopyranosyl, compounds 2-10 are lignans and isolated from this plant for the first time. Compound 3, 4, 8 possess potentially anti-asthmatic activities.

Umbilical cord mesenchymal stem cells (UC-MSCs) have been widely used in regenerative medicine, but there is limited research on the stability of UC-MSCs formulation during production. This study aims to assess the stability of the cell stock solution and intermediate product throughout the production process, as well as the final product following reconstitution, in order to offer guidance for the manufacturing process and serve as a reference for formulation reconstitution methods. Three batches of cell formulation were produced and stored under low temperature (2-8 ℃) and room temperature (20-26 ℃) during cell stock solution and intermediate product stages. The storage time intervals for cell stock solution were 0, 2, 4, and 6 h, while for intermediate products, the intervals were 0, 1, 2, and 3 h. The evaluation items included visual inspection, viable cell concentration, cell viability, cell surface markers, lymphocyte proliferation inhibition rate, and sterility. Additionally, dilution and culture stability studies were performed after reconstitution of the cell product. The reconstitution diluents included 0.9% sodium chloride injection, 0.9% sodium chloride injection + 1% human serum albumin, and 0.9% sodium chloride injection + 2% human serum albumin, with dilution ratios of 10-fold and 40-fold. The storage time intervals after dilution were 0, 1, 2, 3, and 4 h. The reconstitution culture media included DMEM medium, DMEM + 2% platelet lysate, 0.9% sodium chloride injection, and 0.9% sodium chloride injection + 1% human serum albumin, and the culture duration was 24 h. The evaluation items were viable cell concentration and cell viability. The results showed that the cell stock solution remained stable for up to 6 h under both low temperature (2-8 ℃) and room temperature (20-26 ℃) conditions, while the intermediate product remained stable for up to 3 h under the same conditions. After formulation reconstitution, using sodium chloride injection diluted with 1% or 2% human serum albumin maintained a viability of over 80% within 4 h. It was observed that different dilution factors had an impact on cell viability. After formulation reconstitution, cultivation in medium with 2% platelet lysate resulted in a cell viability of over 80% after 24 h. In conclusion, the stability of cell stock solution within 6 h and intermediate product within 3 h meets the requirements. The addition of 1% or 2% human serum albumin in the reconstitution diluent can better protect the post-reconstitution cell viability.

AIM To identify the endophytic fungus G-(JK)-2 from Orixa japonica Thunb.and to study its secondary metabolites and their α-glucosidase inhibitory activities.METHODS Through the ITS sequence,the evolutionary tree that identifies the endophytic fungus G-(JK)-2 was established.Then 45 days rice solid medium of endophytic fungus G-(JK)-2 was extracted by methanol,and then by ethyl acetate.The ethyl acetate extract was separated and purified by silica gel chromatography,Sephadex LH-20,and semi-preparative HPLC.The structures of obtained compounds were identified by physicochemical properties and spectral data.Their α-glucosidase inhibitory activities were evaluated by PNPG method.RESULTS The endophytic fungus G-(JK)-2 from O.japonica was identified as Fusarium nematophilum.Thirteen compounds were isolated and identified as p-hydroxybenzaldehyde(G1),4-hydroxyacetophenone(G2),anhydromevalonolactone(G3),flazine(G4),salicylic acid(G5),p-hydroxybenzoic acid(G6),di-(2-ethylhexyl)-phthalate(G7),terephthalic acid bis(2-ethyl-hexyl)ester(G8),thymine(G9),uridine(G10),adenosine(G11),2′-deoxyuridine(G12),nicotinic acid(G13).The inhibitory effect of each compound on α-glucosidase was in sequence of G4>G11>G10>G13>G12.CONCLUSION All compounds are first isolated from the endophytic fungi of the O.japonica,and G10,G11,G13 are first isolated from the endophytic fungi of Fusarium.G4 and G11 have mild inhibition to α-glucosidase.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective To propose a sperm classification model based on convolutional neural network to enhance the accuracy of sperm morphological classification.Methods A FT-EfficientNet model was constructed using EfficientNetB0 as the base model,which was fine-tuned by data preprocessing enhancement,transfer learning and cosine decay.Classification experi-ments were performed on the sperm public datasets SCIAN-Morpho and HuSHeM,and the datasets were segmented and vali-dated using 5-fold cross-validation.The classification results by the FT-EfficientNet model were compared with those by the cascade ensemble of support vector machines(CE-SVM)model,the adaptive patch-based dictionary learning(APDL)model,fine tuning of visual geometry group(FT-VGG)model,morphological classification of human sperm heads(MH-HSH)model and transfer learning(TL)model.Ablation experiments were performed in the SCIAN-Morpho dataset to verify the effect of different fine-tuning methods on the model.Results The FT-EfficientNet model proposed had the accuracy,precision and F1 score on the SCIAN-Morpho validation set being 64.1％,63.8％and 64.8％,respectively,which were better than CE-SVM,APDL,FT-VGG and MC-HSH models.The recall rate of the model proposed(65.2％)was slightly lower than that of MC-HSH model(68.0％).The accuracy,precision,F1 score and recall rate on the HuSHeM validation set was 95.4％,95.8％,95.4％and 96.0％,respectively,which were slightly lower than those of TL model while better than those of CE-SVM,APDL,FT-VGG and MC-HSH models.Ablation experiments showed the FT-EfficientNet model behaved the best in fine-tuning.Conclusion The sperm classification model based on convolutional neural network facilitates sperm morphology classification with high accuracy and performance.[Chinese Medical Equipment Journal,2024,45(10):7-13]

AIM:To investigate the potential impact of mitoNEET[mitochondrial protein containing Asn-Glu-Glu-Thr(NEET)sequence]on mitochondrial metabolism in brown adipocytes,and to elucidate its underlying mecha-nism.METHODS:An in vitro model of primary mouse brown adipocytes was established.Western blot were utilized to detect relevant proteins,and iron ion and ATP content was measured using kits.Mitochondrial membrane potential and re-active oxygen species(ROS)were assessed by fluorescence microscopy and flow cytometry.RESULTS:The expression of the ferroptosis-related protein ACSL4 increased by 1.13 times in ferroptosis inducer erastin treatment group,whereas the expression of SLC7A11 and GPX4 decreased by 27.33%and 25.33%,respectively,compared with control group(P<0.05).The expression of Nrf1,PGC-1α,MFN2 and UCP1 proteins,related to mitochondrial energy metabolism,de-creased by 20.98%,15.17%,15.03%and 34.22%,respectively(P<0.05).Additionally,the mitoNEET protein con-tent was significantly reduced by 42.14%(P<0.05).The iron ion content in erastin group was substantially increased by 1.80 times compared with control group.However,a notable decrease in ATP content of 14.95%was seen(P<0.05).The results obtained from fluorescence microscopy and flow cytometry demonstrated a significant decrease in the mitochon-drial membrane potential of brown adipocytes in erastin group,with reductions of 52.18%and 61.31%(P<0.05),re-spectively.A substantial increase in mitochondrial ROS content of 80.97%was seen(P<0.05).Western blot analysis of overexpressed stable strains revealed a significant elevation in mitoNEET levels in brown adipocytes following lentivirus transfection,exhibiting an increase of 11.19 times(P<0.05),thus confirming successful transfection.The LV-mitoNEET group exhibited a significant decrease of 37.95%in the expression of ferroptosis-related protein ACSL4 in brown adipose cells compared with control group.Additionally,there was a notable increase of 77.82%and 66.3%in the expression of SLC7A11 and GPX4,respectively(P<0.05).Up-regulation was observed in the expression of MFN2(79.06%),PGC-1α(72.89%),Nrf1(40.14%),and UCP1(31.68%)(P<0.05).The test results demonstrated that the LV-mitoNEET group experienced a reduction of 43.5%in iron ion content compared with control group while exhibiting an increase of 33.5%in ATP content(P<0.05).The results obtained from fluorescence microscopy and flow cytometry demonstrated that mitoNEET overexpression led to a significant increase in the mitochondrial membrane potential of erastin-induced brown adipocytes,with increments of 17.61%and 96.05%,respectively.Additionally,mitoNEET overexpression effec-tively reduced the production of mitochondrial ROS by 24.48%(P<0.05).CONCLUSION:Our findings suggest that mitoNEET overexpression can effectively inhibit the disruption of mitochondrial energy metabolism caused by ferroptosis-induced death of brown adipocytes.