TCP family as plant specific transcription factor, plays an important role in different aspects of plant development. In order to screen TCP family members in tobacco, the homologous sequences of tobacco and Arabidopsis TCP family were identified by genome-wide homologous alignment. The physicochemical properties, phylogenetic relationships and cis-acting elements were analyzed by bioinformatics. The homologous genes of AtTCP3/AtTCP4 were screened, and RT-qPCR was used to detect the changes of gene expression upon 20% PEG6000 treatment. The results show that tobacco contains 63 TCP family members. Their amino acid sequence length ranged from 89 aa to 596 aa, and their protein hydropathicity grand average of hydropathicity (GRAVY) ranged from -1.147 to 0.125. The isoelectric point (pI) ranges from 4.42 to 9.94, the number of introns is 0 to 3, and the subcellular location is all located in the nucleus. The results of conserved domain and phylogenetic relationship analysis showed that the tobacco TCP family can be divided into PCF, CIN and CYC/TB1 subfamilies, and each subfamily has a stable sequence. The results of cis-acting elements in gene promoter region showed that TCP family genes contain low docile acting elements (LTR) and a variety of stress and metabolic regulation related elements (MYB, MYC). Analysis of gene expression patterns showed that AtTCP3/AtTCP4 homologous genes (NtTCP6, NtTCP28, NtTCP30, NtTCP33, NtTCP42, NtTCP57, NtTCP63) accounted for 20% PEG6000 treatment significantly up-regulated/down-regulated expression, and NtTCP30 and NtTCP57 genes were selected as candidate genes in response to drought. The results of this study analyzed the TCP family in the tobacco genome and provided candidate genes for the study of drought-resistance gene function and variety breeding in tobacco.
Nicotiana/genetics* ; Phylogeny ; Plant Breeding ; Amino Acid Sequence ; Arabidopsis ; Polyethylene Glycols

Objective:To assess the prognostic value of cerebrospinal fluid (CSF) neuron specific enolase (NSE) combined with protein content in predicting poor prognosis in patients with intraventricular hemorrhage after external ventricular drainage (EVD).Methods:The clinical data of 73 intraventricular hemorrhage patients underwent EVD in the Second Affiliated Hospital of Wenzhou Medical University from February 2019 to January 2022 were retrospectively analyzed. After 90 d of surgery, 37 patients (good prognosis group) had a modified Rankin score of 0 to 2, while 36 cases (poor prognosis group) had a score of 3 to 5. The baseline characteristics including gender, age, hypertension, diabetes and Glasgow coma score (GCS) upon admission were recorded. The peripheral blood samples were collected within 24 h of admission to measure C-reactive protein, white blood cell and blood potassium. The CSF samples were obtained within 24 h after EVD to measure NSE, protein content, white blood cell and red blood cell. Binary Logistic regression analysis was used to analyze the independent risk factors of poor prognosis in patients with intraventricular hemorrhage after EVD. The efficacy of CSF NSE combined with protein content in predicting the poor prognosis in patients with intraventricular hemorrhage after EVD was evaluated by the receiver operating characteristics (ROC) curve.Results:There were no statistical differences in gender distribution, age, hypertension, diabetes, blood C-reactive protein, white blood cell and blood potassium between two groups ( P>0.05); the GCS upon admission in poor prognosis group was significantly lower than that in good prognosis group: (5.83 ± 0.20) scores vs. (9.54 ± 0.43) scores, the CSF NSE, protein content, white blood cell and red blood cell were significantly higher than those in good prognosis group: (377.94 ± 21.91) μg/L vs. (86.43 ± 11.96) μg/L, (16.70 ± 2.07) g/L vs. (2.92 ± 0.74) g/L, (731.61 ± 141.36) × 10 6/L vs. (302.16 ± 90.99) × 10 6/L and (410 332 ± 88 584) × 10 6/L vs. (156 075 ± 61 387) × 10 6/L, and there were statistical differences ( P<0.01 or <0.05). Binary Logistic regression analysis result showed that elevated CFS NSE and higher CSF protein content were independent risk factors of poor prognosis in patients with intraventricular hemorrhage after EVD ( OR = 1.053 and 1.270, 95% CI 1.005 to 1.103 and 1.020 to 1.581, P<0.05). ROC curve analysis result showed that the area under the curve of CFS NSE combined with protein content detection to predict the poor prognosis in patients with intraventricular hemorrhage after EVD was larger than that of CFS NSE and protein content alone detection (0.982 vs. 0.971 and 0.903), and the optimal cutoff values of CSF NSE and protein content were 233.090 μg/L and 1.425 g/L, respectively. Conclusions:CSF NSE and protein content are significantly elevated in patients with intraventricular hemorrhage after EVD. The combined detection of CSF NSE and protein content provides valuable prognostic information for prognosis in patients with intraventricular hemorrhage after EVD, and it can provide important basis for prognosis evaluation.

Sirtuin2(SIRT2)is an NAD+dependent histone deacetylase that plays a key role in maintaining cellular REDOX potential and modulating pro-inflammatory immune responses.How-ever,its role in acute kidney injury(AKI)has not been proven.To explore the role of SIRT2 in AKI,AKI models were constructed in wild-type(WT)and SIRT2 knockout(SIRT2-/-)mice by injection of lipopolysaccharide(LPS).HE results showed that kidney damage in SIRT2-/-mice was more significant than that in LPS treated WT mice.qRT-PCR and Western blot results showed that more significant changes in inflammatory genes,proteins and oxidative stress proteins in SIRT2-/-mice.The results suggest that SIRT2 deficiency exacerbates LPS induced AKI.

Objective:To analyze the clinical characteristics of dengue fever patients, summarize the course and characteristics of the disease, and analyze the risk factors that affect the condition.Methods:Retrospective collection of general information, clinical symptoms, medical history, laboratory tests, prognosis and other clinical data of dengue fever patients that admitted to Jinghong First People's Hospital and severe dengue fever patients at People's Hospital of Xishuangbanna Dai Autonomous Prefecture from June to December 2023 was conducted using a case report form (CRF). According to the diagnostic criteria of the World Health Organization (WHO), patients were divided into dengue fever group, dengue fever with warning signs group, and severe dengue fever group. The differences in clinical data between different groups of patients were analyzed and compared. Binary multiple factor Logistic regression analysis was used to explore the risk factors affecting the severity of dengue fever in patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of prediction models constructed for various risk factors for severe dengue fever. Subgroup analysis was performed on the prognosis of severe dengue fever patients, and the differences in clinical data between two groups of patients with different prognoses were compared. Binary multivariate Logistic regression analysis was used to explore the risk factors affecting the prognosis of severe dengue fever patients. ROC curve was drawn to analyze the predictive value of prediction models constructed for various risk factors on the prognosis of severe dengue fever patients.Results:A total of 2 264 patients were included, including 499 cases in the dengue fever group, 1 379 cases in the dengue fever with warning signs group, and 386 in the severe dengue fever group (43 deaths and 343 survivors). The most common symptom of dengue fever patients was fever (94.70%), followed by muscle soreness (70.54%), headache (63.12%), fatigue (58.92%), and chills (46.02%). Compared with the dengue fever group and the dengue fever with warning signs group, the ratio of thalassemia and the levels of cardiac troponin (cTnI, cTnT), MB isoenzyme of creatine kinase (CK-MB), and myoglobin were significantly increased in patients with severe dengue fever group, albumin (Alb) was significantly decreased in patients with severe dengue fever group. The levels of cTnT and myoglobin in patients with dengue fever with warning signs group were significantly higher than those in the dengue fever group, and the level of Alb in patients with dengue fever with warning signs group was significantly lower than that in the dengue fever group, the differences were statistically significant (all P < 0.05). Binary multivariate Logistic regression analysis showed that thalassemia [odds ratio ( OR) = 6.214, 95% confidence interval (95% CI) was 2.337-16.524, P < 0.001], Alb ≤ 36 g/L ( OR = 6.297, 95% CI was 4.270-9.286, P < 0.001), and cTnT levels ( OR = 1.008, 95% CI was 1.002-1.015, P = 0.016) were risk factors for severe dengue fever. ROC curve analysis showed that the area under the ROC curve (AUC) for predicting severe dengue fever based on the prediction models constructed for the above risk factors was 0.856, with the best predictive value of 0.067, sensitivity of 67.1%, and specificity of 99.4%. In the subgroup analysis of patients with severe dengue fever, compared with the survival group, the levels of hematocrit (HCT), cTnT, and CK-MB in the death group patients were significantly increased, while the level of Alb was significantly decreased, and the differences were statistically significant. Binary multivariate Logistic regression analysis showed that Alb ( OR = 0.839, 95% CI was 0.755-0.932, P = 0.001), HCT ( OR = 1.086, 95% CI was 1.010-1.168, P = 0.025), elevated troponin level ( OR = 10.119, 95% CI was 2.596-39.440, P < 0.001), and CK-MB ( OR = 1.081, 95% CI was 1.032-1.133, P < 0.001) were risk factors for mortality in patients with severe dengue fever. ROC curve analysis showed that the AUC for predicting death in severe dengue fever patients based on the prediction models constructed for the above risk factors was 0.881, with the best predictive value of 0.113, sensitivity of 75.0%, and specificity of 88.9%. Conclusion:Thalassemia, Alb≤36 g/L, and cTnT level are risk factors for severe dengue fever, while HCT level, Alb level, CK-MB level, and elevated troponin level are risk factors for death in patients with severe dengue fever.

Objective:To compare the localization accuracy of interictal 18F-FDG and 18F-flumazenil (FMZ) PET/CT imaging for focal cortical dysplasia (FCD). Methods:A retrospective analysis was conducted on 22 patients (12 males, 10 females; age 8-36 years) with pathologically confirmed FCD who underwent surgical resection at Huashan Hospital, Fudan University from July 2021 to June 2023. All patients underwent 18F-FDG and 18F-FMZ PET/CT scans before surgery. Surgical pathological diagnosis was used as the gold standard. Visual scoring was used to analyze the images. The accuracy of the two imaging methods in the localization of FCD was compared, and subgroup analysis (FCD Ⅱa, FCD Ⅱb) of different pathological type was further performed. Paired- t test, χ2 test or Fisher′s exact test was used to analyze the data. Results:The visual score of 18F-FMZ PET/CT was higher than that of 18F-FDG (3.00±0.82 vs 2.27±0.92; t=4.17, P=0.020). The accuracy of interictal 18F-FMZ PET/CT was 77.27%(17/22), which was higher than that of 18F-FDG PET/CT (36.36%, 8/22; χ2=7.50, P=0.006). Subgroup analysis showed that within the cohort of patients diagnosed with FCD Ⅱa ( n=18), 18F-FMZ PET/CT outperformed 18F-FDG in terms of accuracy for localization (15/18 vs 6/18; P=0.006). Conclusion:Compared to 18F-FDG, 18F-FMZ PET/CT demonstrates clearer and more accurate identification of lesion borders, and exhibits higher precision, which provides valuable guidance for preoperative localization.

Objective    To construct a prognostic model of esophageal squamous cell carcinoma (ESCC) based on immune checkpoint-related genes and explore the potential relationship between these genes and the tumor microenvironment (TME). Methods     The transcriptome sequencing data and clinical information of immune checkpoint genes of samples from GSE53625 in GEO database were collected. The difference of gene expression between ESCC and normal paracancerous tissues was evaluated, and the drug sensitivity of differentially expressed genes in ESCC was analyzed. We then constructed a risk model based on survival-related genes and explored the prognostic characteristics, enriched pathway, immune checkpoints, immune score, immune cell infiltration, and potentially sensitive drugs of different risk groups. Results    A total of 358 samples from 179 patients were enrolled, including 179 ESCC samples and 179 corresponding paracancerous tissues. There were 33 males and 146 females, including 80 patients≤60 years and 99 patients>60 years. 39 immune checkpoint genes were differentially expressed in ESCC, including 14 low expression genes and 25 high expression genes. Drug sensitivity analysis of 8 highly expressed genes (TNFRSF8, CTLA4, TNFRSF4, CD276, TNFSF4, IDO1, CD80, TNFRSF18) showed that many compounds were sensitive to these immunotherapy targets. A risk model based on three prognostic genes (NRP1, ICOSLG, HHLA2) was constructed by the least absolute shrinkage and selection operator analysis. It was found that the overall survival time of the high-risk group was significantly lower than that of the low-risk group (P<0.001). Similar results were obtained in different ESCC subtypes. The risk score based on the immune checkpoint gene was identified as an independent prognostic factor for ESCC. Different risk groups had unique enriched pathways, immune cell infiltration, TME, and sensitive drugs. Conclusion     A prognostic model based on immune checkpoint gene is established, which can accurately stratify ESCC and provide potential sensitive drugs for ESCC with different risks, thus providing a possibility for personalized treatment of ESCC.

Objective     To investigate the biological characteristics and clinical significance of cuproptosis-related genes in lung adenocarcinoma (LUAD) based on the multi-omics data from The Cancer Genome Atlas. Methods     The cuproptosis-related genes were obtained from a study published in Science in March 2022. The whole genome data were used to reveal the mutation spectrum and copy number variation landscape of cuproptosis-related genes in LUAD and analyze its effects on transcriptome expression. Cuproptosis-related genes were annotated using Metascape analysis to further understand the pathways or functions in which these genes were involved. Subsequent univariate Cox analysis and Kaplan-Meier methods determined the prognosis of these genes in LUAD patients, and CellMiner analysis were used to identify those potential anticancer drugs for potentially targeting cuproptosis-related genes. Results     Cuproptosis-related genes were less frequently mutated in LUAD, and the effect of gene mutations on transcriptomic expression may depend on the type of mutation. Gene copy number variation was an important factor resulting in the disordered expression of cuproptosis-related genes. The 16 cuproptosis-related genes were mainly involved in glyoxylate metabolism and glycine degradation, copper ion entry, proteolitidylation, cellular amino acid catabolism process, oxidative stress response, etc. Among them, 6 genes (DLD, FDX1, DLAT, DLST, PDHA1, CDKN2A) were prognostic risk genes in LUAD. The CellMiner analysis suggested that 13 drugs were associated with 7 cuproptosis-related genes and they might be potential  anticancer drugs for potentially targeting cuproptosis. Conclusion     This study reveals the biological characteristics and clinical significance of cuproptosis-related genes in LUAD, and provides some reference and theoretical basis for the subsequent research of cuproptosis in cancer.

Objective:To establish mesenchymal cell bicaudal-C (Bicc1) gene conditional knockout mice models and analyze their phenotypes.Methods:Bicc1 f/+ mice were crossed with Pdgfra promoter-driven Cre mice to obtain the offspring mice. Genomic DNA was extracted from the toe and tail tissues from 1-2 weeks old mice, amplified by PCR and detected at the DNA level by agarose gel electrophoresis. Three Bicc1 gene conditional knockout mice (experimental group) and three wild-type mice (control group) were selected after identification and grew to 3 weeks of age for follow-up experiments. The Bicc1 gene was knocked out by the induction of tamoxifen intraperitoneal injection. After 1 week, the kidney, skeletal muscle, skin and adipose tissue samples were collected. Real-time quantitative PCR (RT-qPCR) was performed to determine the expression levels of Bicc1 mRNA in the collected tissue samples. HE and Masson staining were performed with tissue samples fixed in 10% paraformaldehyde, and observed with a light microscope. The SPSS 28.0 software was used to analyze the data, t-test was used for comparison between groups, and P<0.05 was considered statistically significant. Results:Mesenchymal cell Bicc1 gene conditional knockout mice models were obtained by breeding, and the genotype was Bicc1 f/fCre +/-. The genotype of the wild-type mice was Bicc1 f/fCre -/-. RT-qPCR showed that the expression levels of Bicc1 mRNA in kidney, skeletal muscle, skin and adipose tissue of the experimental mice were significantly lower than those of the control group (all P<0.01). HE staining and Masson staining showed that compared with the control group, glomerular atrophy could be observed in the experimental group, renal capsules were irregular in shape, and some renal capsules disappeared. The arrangement of skeletal muscle fibers were loose and scattered, and the accumulation of muscle fibers was not dense. There were no significant differences between the skin and adipose tissue. Conclusion:Mesenchymal cell Bicc1 gene conditional knockout mice models were successfully established, which could provide models for studying the mechanisms of action of Bicc1 gene in different tissues and organs. Mesenchymal cell conditional Bicc1 gene knockout affected the phenotypes of kidney and skeletal muscle in mice.

Objective:To establish mesenchymal cell bicaudal-C (Bicc1) gene conditional knockout mice models and analyze their phenotypes.Methods:Bicc1 f/+ mice were crossed with Pdgfra promoter-driven Cre mice to obtain the offspring mice. Genomic DNA was extracted from the toe and tail tissues from 1-2 weeks old mice, amplified by PCR and detected at the DNA level by agarose gel electrophoresis. Three Bicc1 gene conditional knockout mice (experimental group) and three wild-type mice (control group) were selected after identification and grew to 3 weeks of age for follow-up experiments. The Bicc1 gene was knocked out by the induction of tamoxifen intraperitoneal injection. After 1 week, the kidney, skeletal muscle, skin and adipose tissue samples were collected. Real-time quantitative PCR (RT-qPCR) was performed to determine the expression levels of Bicc1 mRNA in the collected tissue samples. HE and Masson staining were performed with tissue samples fixed in 10% paraformaldehyde, and observed with a light microscope. The SPSS 28.0 software was used to analyze the data, t-test was used for comparison between groups, and P<0.05 was considered statistically significant. Results:Mesenchymal cell Bicc1 gene conditional knockout mice models were obtained by breeding, and the genotype was Bicc1 f/fCre +/-. The genotype of the wild-type mice was Bicc1 f/fCre -/-. RT-qPCR showed that the expression levels of Bicc1 mRNA in kidney, skeletal muscle, skin and adipose tissue of the experimental mice were significantly lower than those of the control group (all P<0.01). HE staining and Masson staining showed that compared with the control group, glomerular atrophy could be observed in the experimental group, renal capsules were irregular in shape, and some renal capsules disappeared. The arrangement of skeletal muscle fibers were loose and scattered, and the accumulation of muscle fibers was not dense. There were no significant differences between the skin and adipose tissue. Conclusion:Mesenchymal cell Bicc1 gene conditional knockout mice models were successfully established, which could provide models for studying the mechanisms of action of Bicc1 gene in different tissues and organs. Mesenchymal cell conditional Bicc1 gene knockout affected the phenotypes of kidney and skeletal muscle in mice.

The negative effects of low temperature can readily induce a variety of diseases. We sought to understand the reasons why cold stress induces disease by studying the mechanisms of fine-tuning in macrophages following cold exposure. We found that cold stress triggers increased macrophage activation accompanied by metabolic reprogramming of aerobic glycolysis. The discovery, by genome-wide RNA sequencing, of defective mitochondria in mice macrophages following cold exposure indicated that mitochondrial defects may contribute to this process. In addition, changes in metabolism drive the differentiation of macrophages by affecting histone modifications. Finally, we showed that histone acetylation and lactylation are modulators of macrophage differentiation following cold exposure. Collectively, metabolism-related epigenetic modifications are essential for the differentiation of macrophages in cold-stressed mice, and the regulation of metabolism may be crucial for alleviating the harm induced by cold stress.
Acetylation ; Animals ; Cold-Shock Response ; Epigenesis, Genetic ; Macrophages/metabolism* ; Mice ; Mitochondria/metabolism*