Objective To understand the situation of corn mycotoxins contamination in Heilongjiang Province , and to analyze the causes of pollution and propose prevention and control measures. Methods Among the 473 corn samples were collected from various regions in Heilongjiang Province , and 16 mycotoxins , including aflatoxins , fumonisins, deoxynivalenol and their metabolites , zearalenone , ochratoxin A , alternariol , alternariol monomethyl ether , tentoxin , and tenuazonic acid , were detected in the corn samples. The detection and quantification were carried out using ultra-high performance liquid chromatography tandem mass spectrometry isotope internal standard method. Results All samples were detected with mycotoxins, the detection rate was 100%, and each sample was contaminated by one or more mycotoxins. The detection rate of 16 mycotoxins ranged from 0.21% to 98.31%. The average contamination level ranged from 0.67 μ g/kg-259.19 μ g/kg. Three types of toxins exceeded the standard, with exceeding rates of deoxynivalenol (2.54%, 12/473), zearalenone (4.02% ,19/473), and fumonisins (2.54%,12/473), respectively. The samples exceeding the standard were distributed in Mudanjiang, Shuangyashan, Jixi, Harbin, and Qiqihar. Conclusion Corn in Heilongjiang Province is contaminated by a combination of mycotoxins. It is necessary to strengthen monitoring from multiple links and adopt a variety of ways and control measures to reduce corn contamination.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

ObjectiveTo investigate the possible mechanism of Shenfuhuang Formula （参附黄配方） in prevention and treatment of epsis-associated encephalopathy from the perspective of brain genomics. MethodsC57BL/6 mice were randomly divided into sham surgery group， sepsis group， and Shenfuhuang group， with 20 mice in each group. The sepsis group and Shenfuhuang group were induced to develop sepsis by cecal ligation and puncture （CLP） procedure. At 4 hours after modelling， Shenfuhuang group were gavaged with 2.5 g/（kg·d） of Shenfuhuang Formula， 0.5 ml each time， at 12 hours intervals， for a total of 4 times after modelling. Sepsis group and sham surgery group were given 0.5 ml of purified water orally. At 48 hours after modeling， the transcriptome sequencing was used to explore the differential gene expression in the effects of Shenfuhuang Formula on the brain regions of septic mice， and real-time PCR and ELISA were later used to further validate the differential gene and proteins expression. ResultsA total of 4605 genes were differentially expressed in Shenfuhuang group compared with sepsis group， of which 2353 genes were up-regulated and 2252 genes were down-regulated. According to the results of previous publications， six key genes were screened， including serine/threonine-protein kinase （Nek1）， myelin-associated glycoprotein （Mag）， endothelial cell-specific tyrosine kinase receptor （Tek）， a disintegrin and metalloproteinase with thrombospondin motifs 20 （Adamts20）， lymphocyte antigen 86 （Ly86）， and E3 ubiquitin-protein ligase （Traip）. Further genetic and protein validation revealed that， compared to the sham surgery group， the mRNA levels and corresponding protein levels of Nek1， Mag， Tek， Adamts20， Ly86， and Traip in the brain tissue of septic mice significantly reduced （P＜0.05）. In comparison to the sepsis group， Shenfuhuang group showed significantly increased mRNA levels and corresponding protein levels of Nek1， Mag， Tek， Adamts20， Ly86， and Traip （P＜0.05）. ConclusionThe potential therapeutic targets of Shenfuhuang Formula for treating sepsis-associated encephalopathy may be related to the Nek1， Mag， Tek， Adamts20， Ly86， and Traip genes and their encoded proteins.

Objective: To investigate the implementation and evaluate the effectiveness of health management services for patients with type 2 diabetes mellitus (T2DM) in Urumqi City from 2017 to 2021, so as to provide the reference for enhancing T2DM patients management. Methods: Data on the rates of record establishment, health management and standardized management for T2DM patients, and blood glucose control rate in managed patients in Urumqi City from 2017 to 2021 were collected through the quarterly reports on basic public health service management from the Weining Health Platform System. The trends in the four management indicators, and the differences between urban and rural areas were analyzed. Results: The rates of record establishment, health management and blood glucose control rate in managed patients in Urumqi City were 46.94%, 38.37% and 59.92%, respectively, showing upward trends from 2017 to 2021 (all P<0.05). The rate of standardized management was 75.89%, showing a downward trend (P<0.05). The rate of record establishment was higher in urban areas than in rural areas (47.76% vs. 40.56%, P<0.05). The rates of standardized management and blood glucose control in managed patients were lower in urban areas than in rural areas (75.18% vs. 81.46%, 58.93% vs. 67.64%, both P<0.05). The rate of health management was 38.39% in urban areas and 38.24% in rural areas, with no statistically significant difference (P>0.05). The trends in the rates of record establishment, health management and standardized management in both urban and rural areas were consistent with those in the overall population. Conclusions From 2017 to 2021, the rates of record establishment, health management and blood glucose control in managed patients in Urumqi City showed upward trends, while the rate of standardized management exhibited a downward trend. There were urban-rural differences in the rates of record establishment, standardized management and blood glucose control in managed patients.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

ObjectiveTo understand the seropositivity of neutralizing antibodies (NAb) and low-level NAb against SARS-CoV-2 infection in the community residents, and to explore the impact of COVID-19 vaccination and SARS-CoV-2 infection on the levels of NAb in human serum. MethodsOn the ground of surveillance cohort for acute infectious diseases in community populations in Shanghai, a proportional stratified sampling method was used to enroll the subjects at a 20% proportion for each age group (0‒14, 15‒24, 25‒59, and ≥60 years old). Blood samples collection and serum SARS-CoV-2 NAb concentration testing were conducted from March to April 2023. Low-level NAb were defined as below the 25^th percentile of NAb. ResultsA total of 2 230 participants were included, the positive rate of NAb was 97.58%, and the proportion of low-level NAb was 25.02% (558/2 230). Multivariate logistic regression analysis indicated that age, infection history and vaccination status were correlated with low-level NAb (all P<0.05). Individuals aged 60 years and above had the highest risk of low-level NAb. There was a statistically significant interaction between booster vaccination and one single infection (aOR=0.38, 95%CI: 0.19‒0.77). Compared to individuals without vaccination, among individuals infected with SARS-CoV-2 once, both primary immunization (aOR=0.23, 95%CI: 0.16‒0.35) and booster immunization (aOR=0.12, 95%CI: 0.08‒0.17) significantly reduced the risk of low-level NAb; among individuals without infections, only booster immunization (aOR=0.28, 95%CI: 0.14‒0.52) showed a negative correlation with the risk of low-level NAb. ConclusionsThe population aged 60 and above had the highest risk of low-level NAb. Regardless of infection history, a booster immunization could reduce the risk of low-level NAb. It is recommended that eligible individuals , especially the elderly, should get vaccinated in a timely manner to exert the protective role of NAb.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.