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BACKGROUND: The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a significant challenge in neurology, with conventional methods often limited by subjectivity and variability in interpretation. Integrating deep learning with artificial intelligence (AI) in magnetic resonance imaging (MRI) analysis emerges as a transformative approach, offering the potential for unbiased, highly accurate diagnostic insights. OBJECTIVE: A meta-analysis was designed to analyze the diagnostic accuracy of deep learning of MRI images on AD and MCI models. METHODS: A meta-analysis was performed across PubMed, Embase, and Cochrane library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, focusing on the diagnostic accuracy of deep learning. Subsequently, methodological quality was assessed using the QUADAS-2 checklist. Diagnostic measures, including sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUROC) were analyzed, alongside subgroup analyses for T1-weighted and non-T1-weighted MRI. RESULTS: A total of 18 eligible studies were identified. The Spearman correlation coefficient was -0.6506. Meta-analysis showed that the combined sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.84, 0.86, 6.0, 0.19, and 32, respectively. The AUROC was 0.92. The quiescent point of hierarchical summary of receiver operating characteristic (HSROC) was 3.463. Notably, the images of 12 studies were acquired by T1-weighted MRI alone, and those of the other 6 were gathered by non-T1-weighted MRI alone. CONCLUSION: Overall, deep learning of MRI for the diagnosis of AD and MCI showed good sensitivity and specificity and contributed to improving diagnostic accuracy.

ANTECEDENTES: O diagnóstico precoce da doença de Alzheimer (DA) e do comprometimento cognitivo leve (CCL) continua sendo um desafio significativo na neurologia, com métodos convencionais frequentemente limitados pela subjetividade e variabilidade na interpretação. A integração da aprendizagem profunda com a inteligência artificial (IA) na análise de imagens de ressonância magnética surge como uma abordagem transformadora, oferecendo o potencial para insights diagnósticos imparciais e altamente precisos. OBJETIVO: Uma metanálise foi projetada para analisar a precisão diagnóstica do aprendizado profundo de imagens de ressonância magnética em modelos de DA e CCL. MéTODOS: Uma metanálise foi realizada nos bancos de dados das bibliotecas PubMed, Embase e Cochrane seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), com foco na precisão diagnóstica do aprendizado profundo. Posteriormente, a qualidade metodológica foi avaliada por meio do checklist QUADAS-2. Medidas diagnósticas, incluindo sensibilidade, especificidade, razões de verossimilhança, razão de chances diagnósticas e área sob a curva característica de operação do receptor (area under the receiver operating characteristic curve [AUROC]) foram analisadas, juntamente com análises de subgrupo para ressonância magnética ponderada em T1 e não ponderada em T1. RESULTADOS: Um total de 18 estudos elegíveis foram identificados. O coeficiente de correlação de Spearman foi de -0,6506. A metanálise mostrou que a sensibilidade e a especificidade combinadas, a razão de verossimilhança positiva, a razão de verossimilhança negativa e a razão de chances de diagnóstico foram 0,84, 0,86, 6,0, 0,19 e 32, respectivamente. A AUROC foi de 0,92. O ponto quiescente do resumo hierárquico da característica de operação do receptor (hierarchical summary of receiver operating characteristic [HSROC]) foi 3,463. Notavelmente, as imagens de 12 estudos foram adquiridas apenas por ressonância magnética ponderada em T1, e as dos outros 6 foram obtidas apenas por ressonância magnética não ponderada em T1. CONCLUSãO: Em geral, a aprendizagem profunda da ressonância magnética para o diagnóstico de DA e CCL mostrou boa sensibilidade e especificidade e contribuiu para melhorar a precisão diagnóstica.

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Phthorimaea operculella is a major potato pest of global importance, early warning and detection of which are of significance. In this study, we analyzed the climate niche conservation of P. operculella during its invasion by comparing the overall climate niche from three dimensions, including the differences between native range (South America) and entire invaded region (excluding South America), the differences bwtween native range (South America) and five invaded continents (North America, Oceania, Asia, Africa, and Europe), as well as the differences between native region (South America) and an invaded region (China). We constructed ecological niche models for its native range (South America) and invaded region (China). The results showed that the climatic niche of the pest has expanded to varying degrees in different regions, indicating that the pest could well adapt to new environments during the invasion. Almost all areas of South America are suitable for P. operculella. In China, its suitable area is mainly concentrated in Shandong, Hebei, Tianjin, Beijing, Henan, Hubei, Yunnan, Guizhou, Sichuan, Hainan, northern Guangxi, southern Hunan, Anhui, Guangdong, Jiangsu, southern Shanxi, and southern Shaanxi. With increasing greenhouse gas emissions and global temperature, its suitable area will decrease at low latitude and increase gradually at high latitude. Specifically, the northern boundary will extend to Liaoning, Jilin, and the southeastern region of Inner Mongolia, while the western boundary extends to Sichuan and the southeast Qinghai-Tibet Plateau. The suitable area in the southeast Yunnan-Guizhou Plateau, Hainan Island, and the south of Yangtze River, will gradually decrease. The total suitable habitat area for P. operculella in China is projected to increase under future climate condition. From 2081 to 2100, under the three greenhouse gas emissions scenarios of ssp126, ssp370, and ssp585, the suitable area is expected to increase by 27.78, 165.54, and 140.41 hm2, respectively. Therefore, it is crucial to strengtehen vigilance and implement strict measures to prevent the further expansion of P. operculella.

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PURPOSE: The purpose of the study was to evaluate the prognostic value of low T3 syndrome in peripheral T-cell lymphomas (PTCLs). METHODS: One hundred and seventy-four patients of newly diagnosed PTCLs were enrolled in the study. We performed statistical analysis based on the clinical data collected. RESULTS: Thirty-Six (20.69%) patients had low T3 syndrome at first admission. Results suggested that the patients with higher score of ECOG PS, International Prognostic Index (IPI) and Prognostic Index for T-cell lymphoma (PIT), bone marrow involvement and lower level of albumin tended to develop low T3 syndrome. The median progression-free survival (PFS) and overall survival (OS) were 10 months and 36 months, respectively, for all patients. Pre-existing low T3 syndrome was in correlation with worse PFS and OS. Patients with low T3 syndrome showed worse PFS (4 months vs 13 months, P = 0.0001) and OS (7 months vs 83 months, P < 0.0001) than patients without low T3 syndrome. IPI and PIT, respectively, combined with low T3 syndrome improved the ability to predict OS and PFS of PTCLs. CONCLUSIONS: The study indicated that low T3 syndrome may be a good candidate for predicting prognosis of peripheral T-cell lymphomas.

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ABSTRACT: Patients with multiple myeloma (MM) treated with B-cell maturation antigen (BCMA)-specific chimeric antigen receptor (CAR) T cells usually relapse with BCMA+ disease, indicative of CAR T-cell suppression. CD200 is an immune checkpoint that is overexpressed on aberrant plasma cells (aPCs) in MM and is an independent negative prognostic factor for survival. However, CD200 is not present on MM cell lines, a potential limitation of current preclinical models. We engineered MM cell lines to express CD200 at levels equivalent to those found on aPCs in MM and show that these are sufficient to suppress clinical-stage CAR T-cells targeting BCMA or the Tn glycoform of mucin 1 (TnMUC1), costimulated by 4-1BB and CD2, respectively. To prevent CD200-mediated suppression of CAR T cells, we compared CRISPR-Cas9-mediated knockout of the CD200 receptor (CD200RKO), to coexpression of versions of the CD200 receptor that were nonsignaling, that is, dominant negative (CD200RDN), or that leveraged the CD200 signal to provide CD28 costimulation (CD200R-CD28 switch). We found that the CD200R-CD28 switch potently enhanced the polyfunctionality of CAR T cells, and improved cytotoxicity, proliferative capacity, CAR T-cell metabolism, and performance in a chronic antigen exposure assay. CD200RDN provided modest benefits, but surprisingly, the CD200RKO was detrimental to CAR T-cell activity, adversely affecting CAR T-cell metabolism. These patterns held up in murine xenograft models of plasmacytoma, and disseminated bone marrow predominant disease. Our findings underscore the importance of CD200-mediated immune suppression in CAR T-cell therapy of MM, and highlight a promising approach to enhance such therapies by leveraging CD200 expression on aPCs to provide costimulation via a CD200R-CD28 switch.

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PURPOSE: The International Extranodal Lymphoma Study Group (IELSG) score is widely used in clinical practice to stratify the risk of primary central nervous system lymphoma (PCNSL) patients. Our study aims to confirm and improve the IELSG score in PCNSL patients based on Chinese populations. MATERIALS AND METHODS: A total of 79 PCNSL patients were retrospectively analyzed. All patients treated with high-dose methotrexate (HD-MTX)-based therapy collected clinical data. The receiver-operating characteristic (ROC) curve was used to determine the optimal cut-off values for the factors in IELSG score. Progression of disease (POD) at the most landmark time point was determine by Epanechnikov kernel and the area under the ROC curve (AUROC). Kaplan-Meier and multivariable regression methods were used to analyze survival data. Nomogram was generated for calculating the weight of each selected factor. RESULTS: The traditional IELSG score had no significant difference on OS and PFS except ECOG ≥ 2 and could not stratify the risk groups in PCNSL. The improved IELSG scoring system was established, which incorporated age ≥ 54 years, ECOG ≥ 2, deep brain structure, elevated CSF protein, and LDH/ULN > 0.75. On the other hand, POD18 was identified as a new powerful prognostic factor for PCNSL. In multivariate analysis, POD18 and the improved IELSG scoring system were independent prognostic factors for OS. Nomogram including the two significant variables showed the best performance (C-index = 0.828). CONCLUSIONS: In this study, the IELSG score was improved and a new prognostic indicator POD18 was incorporated to construct a nomogram prognostic model, thereby further improving the predictive ability of the model.

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Abstract Background The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a significant challenge in neurology, with conventional methods often limited by subjectivity and variability in interpretation. Integrating deep learning with artificial intelligence (AI) in magnetic resonance imaging (MRI) analysis emerges as a transformative approach, offering the potential for unbiased, highly accurate diagnostic insights. Objective A meta-analysis was designed to analyze the diagnostic accuracy of deep learning of MRI images on AD and MCI models. Methods A meta-analysis was performed across PubMed, Embase, and Cochrane library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, focusing on the diagnostic accuracy of deep learning. Subsequently, methodological quality was assessed using the QUADAS-2 checklist. Diagnostic measures, including sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUROC) were analyzed, alongside subgroup analyses for T1-weighted and non-T1-weighted MRI. Results A total of 18 eligible studies were identified. The Spearman correlation coefficient was -0.6506. Meta-analysis showed that the combined sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.84, 0.86, 6.0, 0.19, and 32, respectively. The AUROC was 0.92. The quiescent point of hierarchical summary of receiver operating characteristic (HSROC) was 3.463. Notably, the images of 12 studies were acquired by T1-weighted MRI alone, and those of the other 6 were gathered by non-T1-weighted MRI alone. Conclusion Overall, deep learning of MRI for the diagnosis of AD and MCI showed good sensitivity and specificity and contributed to improving diagnostic accuracy.

Resumo Antecedentes O diagnóstico precoce da doença de Alzheimer (DA) e do comprometimento cognitivo leve (CCL) continua sendo um desafio significativo na neurologia, com métodos convencionais frequentemente limitados pela subjetividade e variabilidade na interpretação. A integração da aprendizagem profunda com a inteligência artificial (IA) na análise de imagens de ressonância magnética surge como uma abordagem transformadora, oferecendo o potencial para insights diagnósticos imparciais e altamente precisos. Objetivo Uma metanálise foi projetada para analisar a precisão diagnóstica do aprendizado profundo de imagens de ressonância magnética em modelos de DA e CCL. Métodos Uma metanálise foi realizada nos bancos de dados das bibliotecas PubMed, Embase e Cochrane seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), com foco na precisão diagnóstica do aprendizado profundo. Posteriormente, a qualidade metodológica foi avaliada por meio do checklist QUADAS-2. Medidas diagnósticas, incluindo sensibilidade, especificidade, razões de verossimilhança, razão de chances diagnósticas e área sob a curva característica de operação do receptor (area under the receiver operating characteristic curve [AUROC]) foram analisadas, juntamente com análises de subgrupo para ressonância magnética ponderada em T1 e não ponderada em T1. Resultados Um total de 18 estudos elegíveis foram identificados. O coeficiente de correlação de Spearman foi de -0,6506. A metanálise mostrou que a sensibilidade e a especificidade combinadas, a razão de verossimilhança positiva, a razão de verossimilhança negativa e a razão de chances de diagnóstico foram 0,84, 0,86, 6,0, 0,19 e 32, respectivamente. A AUROC foi de 0,92. O ponto quiescente do resumo hierárquico da característica de operação do receptor (hierarchical summary of receiver operating characteristic [HSROC]) foi 3,463. Notavelmente, as imagens de 12 estudos foram adquiridas apenas por ressonância magnética ponderada em T1, e as dos outros 6 foram obtidas apenas por ressonância magnética não ponderada em T1. Conclusão Em geral, a aprendizagem profunda da ressonância magnética para o diagnóstico de DA e CCL mostrou boa sensibilidade e especificidade e contribuiu para melhorar a precisão diagnóstica.

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Pelvic inflammatory disease (PID) is an inflammation of the upper genital tract. PID is the leading cause of some severe sequelae in the absence of timely and accurate diagnosis and treatment. An appropriate animal model is needed to explore the underlying mechanism of PID sequelae. This study introduced an animal model of PID by vaginal injection of liquid Ureaplasma urealyticum combined with fatigue and hunger (UVF). This study was designed to test the feasibility of a rat model. A rat model was established using UVF irradiation. Levels of some inflammatory cytokines in the serum and the homogenates of the fallopian tubes were measured by ELISA, RT-PCR, and flow cytometry and compared with another rat model of Ureaplasma urealyticum liquids injected into the two uterus horns during laparotomy. Inflammatory alterations and adhesions were observed after hematoxylin and eosin (H&E) staining and detected using the Blauer scoring system. The results showed that the combined UVF and rat model caused apparent obstruction, edema, and adhesion in the fallopian tubes and connective tissues. The rat model showed upregulated CD4, CD8, and CD4/CD8 in peripheral blood mononuclear cells (PBMCs) and significantly increased levels of IL-4, IL-6, IL-10, and IL-17. UVF also enhanced the expression of tumor necrosis factor (TNF)-α, transforming growth factor (TGF)-ß, vascular endothelial growth factor (VEGF) ß, and matrix metalloproteinase (MMP)-2 (P<0.05). The UVF rat model can induce inflammatory alterations in the fallopian tubes and connective tissues, and can be used as a model of PID.

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OBJECTIVE: This study aimed to investigate the sex-specific association between hyperuricemia and the risk of hypertension and whether obesity mediates this association. METHODS: This study included 31,395 (47.0% women) adults without hypertension, cardiovascular disease, or cancer at baseline who completed at least one follow-up annual examination between 2009 and 2016. Cox regression models were performed to calculate hazard ratios and 95% confidence intervals. Mediation analysis was conducted to estimate the effect of body mass index on the association between hyperuricemia and hypertension. RESULTS: During a median 2.9-year follow-up, hyperuricemia was significantly associated with a higher risk of hypertension (HR 1.15, 95%CI 1.07-1.24 for all participants; HR 1.12, 95%CI 1.03-1.22 for men; and HR 1.23, 95%CI 1.02-1.48 for women) after adjustment for potential confounders. Additional adjustment for body mass index attenuated this association (HR 1.09, 95%CI 1.08-1.10 for all participants; HR 1.07; 95%CI 0.98-1.16 for men; HR 1.18; 95%CI 0.96-1.44 for women). Mediation analysis showed that BMI partially mediated the relationship between hyperuricemia and incident hypertension (indirect effect HR 1.09, 95%CI 1.08-1.10; direct effect: HR 1.08, 95%CI 1.02-1.15). The percentage of the mediation effect was 53.2% (95%CI 37.9-84.5). CONCLUSION: Hyperuricemia is associated with a risk of hypertension in both sexes, and BMI partially mediates hyperuricemia-related incident hypertension.

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BACKGROUND: Follicular lymphoma (FL) is the most common indolent B cell lymphoma in the world. The clinical features of extranodal involvement in FL were never extensively described. METHODS: We enrolled 1090 patients diagnosed as newly diagnosed FL at ten medical institutions in China from 2000 to 2020 and conducted this analysis and retrospectively explored clinical characteristics and outcomes of FL patients with extranodal involvement. RESULTS: 400 (36.7%) patients with newly diagnosed FL had no extranodal involvement, 388 (35.6%) patients had one site of extranodal involvement, and 302 (27.7%) had two or more sites of involvement. Patients with >1 extranodal site had significantly worse PFS (p<0.001), as well as OS (p=0.010). The most common site of extranodal involvements was bone marrow (33%), followed by spleen (27.7%) and intestine (6.7%). In patients with extranodal involvement, multivariate Cox analysis found that male patients (p=0.016), poor performance status (p=0.035), increased LDH (p<0.001) and pancreas involvement (p<0.001) was associated with poor PFS, while the latter three factors were also associated with poor OS. Compared to patients with one site of extranodal involvement, patients with >1 site involvement (p=0.012) had 2.04-fold risk to develop POD24. In addition, multivariate Cox analysis found that the usage of rituximab was not associated with better PFS (p=0.787) or OS (p=0.191). CONCLUSIONS: Our cohort is large enough to have statistical significance in FL patients with extranodal involvement. Male sex, increased LDH, poor performance status, >1 extranodal site, as well as pancreas involvement indicated useful prognostic factors in the clinical setting.

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PURPOSE: The efficacy of etch-and-rinse, selective enamel-etching, and self-etching protocols for universal adhesives in follow-ups of over 12 months was compared in a network meta-analysis. STUDY SELECTION: Randomized controlled trials (RCTs) published from 1998 to 2022 that compared marginal staining, marginal adaptation, retention and fractures, post-operative sensitivity, or recurrence of caries that took place over 12-months post-restoration were selected. A network meta-analysis determined the performance of each adhesive protocol. RESULTS: After screening 981 articles, 16 RCTs were subjected to data extraction. Of which, 674 patients with 2816 restorations, were included in the network meta-analysis. The pooled risk of marginal discoloration following self-etching was significantly higher than that following etch-and-rinse at over 12, 24, and 36 months, which was time-dependent. The pooled risks of unfavorable marginal adaptation and unfavorable retention and fractures following self-etching were also significantly higher than that following etch-and-rinse, with the rates of unfavorable retention and fractures in non-carious cervical lesions increasing in a time-dependent manner. The pooled risks of marginal discoloration, unfavorable marginal adaptation, retention and fractures were similar between etch-and-rinse and selective enamel-etching protocols. Post-operative hypersensitivity and recurrence of caries were not significantly different among etch-and-rinse, selective enamel-etching, and self-etching protocols. CONCLUSIONS: In follow-ups over 12 months, esthetic and functional outcomes of restorations completed with an etch-and-rinse adhesive protocol were superior to the ones achieved with a self-etching strategy without selective enamel-etching. Selective enamel etching is recommended for self-etching systems. Biological responses were similar for all three adhesive strategies.

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SUMMARY OBJECTIVE: This study aimed to investigate the sex-specific association between hyperuricemia and the risk of hypertension and whether obesity mediates this association. METHODS: This study included 31,395 (47.0% women) adults without hypertension, cardiovascular disease, or cancer at baseline who completed at least one follow-up annual examination between 2009 and 2016. Cox regression models were performed to calculate hazard ratios and 95% confidence intervals. Mediation analysis was conducted to estimate the effect of body mass index on the association between hyperuricemia and hypertension. RESULTS: During a median 2.9-year follow-up, hyperuricemia was significantly associated with a higher risk of hypertension (HR 1.15, 95%CI 1.07-1.24 for all participants; HR 1.12, 95%CI 1.03-1.22 for men; and HR 1.23, 95%CI 1.02-1.48 for women) after adjustment for potential confounders. Additional adjustment for body mass index attenuated this association (HR 1.09, 95%CI 1.08-1.10 for all participants; HR 1.07; 95%CI 0.98-1.16 for men; HR 1.18; 95%CI 0.96-1.44 for women). Mediation analysis showed that BMI partially mediated the relationship between hyperuricemia and incident hypertension (indirect effect HR 1.09, 95%CI 1.08-1.10; direct effect: HR 1.08, 95%CI 1.02-1.15). The percentage of the mediation effect was 53.2% (95%CI 37.9-84.5). CONCLUSION: Hyperuricemia is associated with a risk of hypertension in both sexes, and BMI partially mediates hyperuricemia-related incident hypertension.

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OBJECTIVE: Dysglycemia influences hospital outcomes and resource utilization. Clinical decision support (CDS) holds promise for optimizing care by overcoming management barriers. This study assessed the impact on hospital length of stay (LOS) of an alert-based CDS tool in the electronic medical record that detected dysglycemia or inappropriate insulin use, coined as gaps in care (GIC). RESEARCH DESIGN AND METHODS: Using a 12-month interrupted time series among hospitalized persons aged ≥18 years, our CDS tool identified GIC and, when active, provided recommendations. We compared LOS during 6-month-long active and inactive periods using linear models for repeated measures, multiple comparison adjustment, and mediation analysis. RESULTS: Among 4,788 admissions with GIC, average LOS was shorter during the tool's active periods. LOS reductions occurred for all admissions with GIC (-5.7 h, P = 0.057), diabetes and hyperglycemia (-6.4 h, P = 0.054), stress hyperglycemia (-31.0 h, P = 0.054), patients admitted to medical services (-8.4 h, P = 0.039), and recurrent hypoglycemia (-29.1 h, P = 0.074). Subgroup analysis showed significantly shorter LOS in recurrent hypoglycemia with three events (-82.3 h, P = 0.006) and nonsignificant in two (-5.2 h, P = 0.655) and four or more (-14.8 h, P = 0.746). Among 22,395 admissions with GIC (4,788, 21%) and without GIC (17,607, 79%), LOS reduction during the active period was 1.8 h (P = 0.053). When recommendations were provided, the active tool indirectly and significantly contributed to shortening LOS through its influence on GIC events during admissions with at least one GIC (P = 0.027), diabetes and hyperglycemia (P = 0.028), and medical services (P = 0.019). CONCLUSIONS: Use of the alert-based CDS tool to address inpatient management of dysglycemia contributed to reducing LOS, which may reduce costs and improve patient well-being.

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Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern United States, Canada, and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

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Brassinolide (BR) plays an important role in plant growth, development, and the adaptation adversity process. Moreover, BRI1-EMS-SUPPRESSOR 1 (BES1) genes are crucial transcription factors (TFs) in the BR signaling pathway. To realize the function of HbBES1 family is helpful to improve genetic resources for rubber tree breeding. Based on the rubber tree database, we used bioinformatics to characterize physicochemical properties, gene structure, cis-elements, and expression patterns. These results indicated that there were nine BES1 members in rubber tree, which we named HbBES1-1 to HbBES1-9 and divided into two groups (I and II) based on their genetic relationships. HbBES1 genes in the same group shared similar gene structures and motifs. Cis-acting element analysis showed that the promoter sequences of HbBES1 genes contained many regulator elements that were related to hormone and stress, indicating that HbBES1 genes might be involved in the regulation of hormone and stress signal pathways. Our analysis of tissue specificity revealed that all of the nine HbBES1 members expressed highly in branches. Gene expression profiles under different hormone treatments showed that the HbBES1 gene family was induced to varying degrees under different hormones, HbBES1-3 and HbBES1-9 were extremely induced by ethylene (ETH). These results lay the foundation for further exploration of the molecular mechanism of the BES1 gene family, especially HbBES1-3 and HbBES1-9, regulating plant stress tolerance in rubber tree.

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PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is a major public health problem with a huge economic burden worldwide. Ulinastatin (UTI), a serine protease inhibitor, has been reported to be anti-inflammatory, immune regulation, and organ protection by reducing reactive oxygen species production, and inflammation. Necroptosis is a programmed cell death mechanism that plays a vital role in neuronal cell death after ICH. However, the neuroprotection of UTI in ICH has not been confirmed, and the potential mechanism is unclear. The present study aimed to investigate the neuroprotection and potential molecular mechanisms of UTI in ICH-induced EBI in a C57BL/6 mouse model. METHODS: The neurological score, brain water content, neuroinflammatory cytokine levels, and neuronal damage were evaluated. The anti-inflammation effectiveness of UTI in ICH patients also was evaluated. RESULTS: UTI treatment markedly increased the neurological score, alleviate the brain edema, decreased the inflammatory cytokine TNF-α, interleukin­1ß (IL­1ß), IL­6, NF­κB levels, and RIP1/RIP3, which indicated that UTI-mediated inhibition of neuroinflammation, and necroptosis alleviated neuronal damage after ICH. UTI also can decrease the inflammatory cytokine of ICH patients. The neuroprotective capacity of UTI is partly dependent on the MAPK/NF-κB signaling pathway. CONCLUSIONS: UTI improves neurological outcomes in mice and reduces neuronal death by protecting against neural neuroinflammation, and necroptosis.

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Abstract Objectives: Dexmedetomidine (DEX) is a highly selective alpha-2 adrenergic receptor agonist, which is the main sedative in the intensive care unit. This study aims to investigate the effectiveness and adverse events of DEX in maintaining hemodynamic stability in pediatric cardiac surgery. Sources: Databases such as PubMed, Cochrane, Web of Science, WANFANG STATA and China National Knowledge Infrastructure were searched for articles about the application of DEX in maintaining hemodynamic stability during and after pediatric cardiac surgery up to 18th Feb. 2021. Only randomized controlled trials were included and random-effects model meta-analysis was applied to calculate the standardized mean deviation (SMD), odds ratio (OR) and 95% confidence interval (CI). Summary of the findings: Fifteen articles were included for this meta-analysis, and 9 articles for qualitative analysis. The results showed that preoperative prophylaxis and postoperative recovery of DEX in pediatric patients undergoing cardiac surgery were effective in maintaining systolic blood pressure (SBP), mean arterial pressure (MAP), diastolic blood pressure (DBP) and reducing heart rate (HR) (SBP: SMD = -0.35,95% CI: -0.72, 0.01; MAP: SMD = -0.83, 95% CI: -1.87,0.21; DBP: SMD = -0.79,95% CI: -1.66,0.08; HR: SMD = -1.71,95% CI: -2.29, -1.13). In addition, the frequency of Junctional Ectopic Tachycardia in the DEX treatment group was lower than that in the placebo group. Conclusions: The application of DEX for preoperative prophylaxis and postoperative recovery in pediatric cardiac surgery patients are effective in maintaining hemodynamic stability, and the clinical dose of DEX is not significantly related to the occurrence of pediatric adverse events which may be related to individual differences.

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OBJECTIVES: Dexmedetomidine (DEX) is a highly selective alpha-2 adrenergic receptor agonist, which is the main sedative in the intensive care unit. This study aims to investigate the effectiveness and adverse events of DEX in maintaining hemodynamic stability in pediatric cardiac surgery. SOURCES: Databases such as PubMed, Cochrane, Web of Science, WANFANG STATA and China National Knowledge Infrastructure were searched for articles about the application of DEX in maintaining hemodynamic stability during and after pediatric cardiac surgery up to 18th Feb. 2021. Only randomized controlled trials were included and random-effects model meta-analysis was applied to calculate the standardized mean deviation (SMD), odds ratio (OR) and 95% confidence interval (CI). SUMMARY OF THE FINDINGS: Fifteen articles were included for this meta-analysis, and 9 articles for qualitative analysis. The results showed that preoperative prophylaxis and postoperative recovery of DEX in pediatric patients undergoing cardiac surgery were effective in maintaining systolic blood pressure (SBP), mean arterial pressure (MAP), diastolic blood pressure (DBP) and reducing heart rate (HR) (SBP: SMD = -0.35,95% CI: -0.72, 0.01; MAP: SMD = -0.83, 95% CI: -1.87,0.21; DBP: SMD = -0.79,95% CI: -1.66,0.08; HR: SMD = -1.71,95% CI: -2.29, -1.13). In addition, the frequency of Junctional Ectopic Tachycardia in the DEX treatment group was lower than that in the placebo group. CONCLUSIONS: The application of DEX for preoperative prophylaxis and postoperative recovery in pediatric cardiac surgery patients are effective in maintaining hemodynamic stability, and the clinical dose of DEX is not significantly related to the occurrence of pediatric adverse events which may be related to individual differences.

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Purpose: Spontaneous intracerebral hemorrhage (ICH) is a major public health problem with a huge economic burden worldwide. Ulinastatin (UTI), a serine protease inhibitor, has been reported to be anti-inflammatory, immune regulation, and organ protection by reducing reactive oxygen species production, and inflammation. Necroptosis is a programmed cell death mechanism that plays a vital role in neuronal cell death after ICH. However, the neuroprotection of UTI in ICH has not been confirmed, and the potential mechanism is unclear. The present study aimed to investigate the neuroprotection and potential molecular mechanisms of UTI in ICH-induced EBI in a C57BL/6 mouse model. Methods: The neurological score, brain water content, neuroinflammatory cytokine levels, and neuronal damage were evaluated. The anti-inflammation effectiveness of UTI in ICH patients also was evaluated. Results: UTI treatment markedly increased the neurological score, alleviate the brain edema, decreased the inflammatory cytokine TNF-α, interleukin­1ß (IL­1ß), IL­6, NF­κB levels, and RIP1/RIP3, which indicated that UTI-mediated inhibition of neuroinflammation, and necroptosis alleviated neuronal damage after ICH. UTI also can decrease the inflammatory cytokine of ICH patients. The neuroprotective capacity of UTI is partly dependent on the MAPK/NF-κB signaling pathway. Conclusions: UTI improves neurological outcomes in mice and reduces neuronal death by protecting against neural neuroinflammation, and necroptosis.

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Resumo Fundamento Doenças cardiovasculares são a principal causa de morte na China. Entretanto, os esforços atuais para se identificar os fatores de risco de morte em pacientes hospitalizados com insuficiência cardíaca (IC) estão direcionados principalmente para a mortalidade durante a internação e a mortalidade após 30 dias nos Estados Unidos. Dessa forma, é necessário um modelo semelhante ao modelo utilizado para prever o risco considerado para procedimentos cirúrgicos cardiovasculares em pacientes para avaliar o risco de pacientes internados com diagnóstico de IC. Objetivo Identificar variáveis que podem prever a mortalidade por IC um ano após a alta hospitalar, e desenvolver um escore de risco para avaliar o risco de morte no período de um ano. Métodos No presente estudo, 1.742 pacientes chineses com IC foram divididos aleatoriamente em dois grupos: um grupo de amostra de derivação e um grupo de amostra de teste. O método de simulação Monte Carlo via Cadeias de Markov foi usado para identificar variáveis que podem prever a mortalidade um ano após a alta hospitalar. Variáveis com uma frequência >1% na análise bivariada, e que foram consideradas clinicamente significativas, foram qualificadas para análises de modelagens posteriores. A probabilidade posterior de que uma variável estava estatística e significativamente associada ao resultado foi calculada como o número total de vezes em que o IC de 95% da variável não coincidiu com 1 (ou seja, o ponto de referência), dividido pelo número total de iterações. Uma variável com uma probabilidade de 0,9 ou mais alta foi considerado um fator de risco robusto para prever o resultado, e foi incluída na lista final de variáveis. O nível de significância estatística adotado foi 5%. Resultados Cinco variáveis que pudessem prever de maneira robusta a mortalidade um ano após a alta hospitalar foram identificadas: idade, sexo feminino, escore da New York Heart Association (Associação de Cardiologia de Nova Iorque) >3, diâmetro do átrio esquerdo, e índice de massa corporal. Os modelos de derivação e de teste tiveram uma área de curva característica de operação do receptor de 0,79. Essas variáveis selecionadas foram utilizadas para avaliar o escore de risco de mortalidade por IC após um ano, e este foi dividido em três grupos (baixo, moderado e alto). O grupo de alto risco corresponde a aproximadamente 86% das mortes, e o grupo de risco moderado corresponde a 12% das mortes. Conclusão Um escore de risco de 5 variáveis simples pode ser utilizado para avaliar a mortalidade um ano após a alta hospitalar de pacientes internados com IC.

Abstract Background Cardiovascular diseases are the leading causes of death in China. However, present efforts to identify the risk factors for death in patients hospitalized with heart failure (HF) are primarily focused on in-hospital mortality and 30-day mortality in the United States. Thus, a model similar to the model used for predicting the risk in patients considered for cardiovascular surgical procedures is needed to evaluate the risk of the patients admitted with a diagnosis of HF. Objective To identify variables that can predict post-discharge one-year HF mortality and develop a risk score to assess the risk of dying within one year. Methods In the present study, 1,742 Chinese patients with HF were randomly divided into two groups: a derivation sample group and a test sample group. A Markov Chain Monte Carlo simulation method was used to identify variables that can predict the one-year post-discharge mortality. Variables with a frequency of >1% in the bivariate analysis and that were considered clinically meaningful were eligible for further modeling analyses. The posterior probability that a variable was statistically and significantly associated with the outcome was calculated as the total number of times that the variable's 95% CI did not overlap with 1 (i.e., the reference point) divided by the total number of iterations. A variable with a probability of 0.9 or higher was considered a robust risk factor for predicting the outcome, and this was included in the final variable list. The level of statistical significance adopted was 5%. Results Five variables that could robustly predict the one-year post-discharge mortality were identified: age, female gender, New York Heart Association functional classification score >3, left atrial diameter, and body mass index. Both derivation and test models had a receiver operating curve area of 0.79. These selected variables were used to assess the one-year HF mortality risk score, and these were divided into three groups (low, moderate, and high). The high-risk group corresponds to nearly 86% of the deaths, while the moderate group corresponds to 12% of the deaths. Conclusion A simple 5-variable risk score can be used to assess the one-year post-discharge mortality of hospitalized Chinese patients with HF.

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BACKGROUND: Cardiovascular diseases are the leading causes of death in China. However, present efforts to identify the risk factors for death in patients hospitalized with heart failure (HF) are primarily focused on in-hospital mortality and 30-day mortality in the United States. Thus, a model similar to the model used for predicting the risk in patients considered for cardiovascular surgical procedures is needed to evaluate the risk of the patients admitted with a diagnosis of HF. OBJECTIVE: To identify variables that can predict post-discharge one-year HF mortality and develop a risk score to assess the risk of dying within one year. METHODS: In the present study, 1,742 Chinese patients with HF were randomly divided into two groups: a derivation sample group and a test sample group. A Markov Chain Monte Carlo simulation method was used to identify variables that can predict the one-year post-discharge mortality. Variables with a frequency of >1% in the bivariate analysis and that were considered clinically meaningful were eligible for further modeling analyses. The posterior probability that a variable was statistically and significantly associated with the outcome was calculated as the total number of times that the variable's 95% CI did not overlap with 1 (i.e., the reference point) divided by the total number of iterations. A variable with a probability of 0.9 or higher was considered a robust risk factor for predicting the outcome, and this was included in the final variable list. The level of statistical significance adopted was 5%. RESULTS: Five variables that could robustly predict the one-year post-discharge mortality were identified: age, female gender, New York Heart Association functional classification score >3, left atrial diameter, and body mass index. Both derivation and test models had a receiver operating curve area of 0.79. These selected variables were used to assess the one-year HF mortality risk score, and these were divided into three groups (low, moderate, and high). The high-risk group corresponds to nearly 86% of the deaths, while the moderate group corresponds to 12% of the deaths. CONCLUSION: A simple 5-variable risk score can be used to assess the one-year post-discharge mortality of hospitalized Chinese patients with HF.

FUNDAMENTO: Doenças cardiovasculares são a principal causa de morte na China. Entretanto, os esforços atuais para se identificar os fatores de risco de morte em pacientes hospitalizados com insuficiência cardíaca (IC) estão direcionados principalmente para a mortalidade durante a internação e a mortalidade após 30 dias nos Estados Unidos. Dessa forma, é necessário um modelo semelhante ao modelo utilizado para prever o risco considerado para procedimentos cirúrgicos cardiovasculares em pacientes para avaliar o risco de pacientes internados com diagnóstico de IC. OBJETIVO: Identificar variáveis que podem prever a mortalidade por IC um ano após a alta hospitalar, e desenvolver um escore de risco para avaliar o risco de morte no período de um ano. MÉTODOS: No presente estudo, 1.742 pacientes chineses com IC foram divididos aleatoriamente em dois grupos: um grupo de amostra de derivação e um grupo de amostra de teste. O método de simulação Monte Carlo via Cadeias de Markov foi usado para identificar variáveis que podem prever a mortalidade um ano após a alta hospitalar. Variáveis com uma frequência >1% na análise bivariada, e que foram consideradas clinicamente significativas, foram qualificadas para análises de modelagens posteriores. A probabilidade posterior de que uma variável estava estatística e significativamente associada ao resultado foi calculada como o número total de vezes em que o IC de 95% da variável não coincidiu com 1 (ou seja, o ponto de referência), dividido pelo número total de iterações. Uma variável com uma probabilidade de 0,9 ou mais alta foi considerado um fator de risco robusto para prever o resultado, e foi incluída na lista final de variáveis. O nível de significância estatística adotado foi 5%. RESULTADOS: Cinco variáveis que pudessem prever de maneira robusta a mortalidade um ano após a alta hospitalar foram identificadas: idade, sexo feminino, escore da New York Heart Association (Associação de Cardiologia de Nova Iorque) >3, diâmetro do átrio esquerdo, e índice de massa corporal. Os modelos de derivação e de teste tiveram uma área de curva característica de operação do receptor de 0,79. Essas variáveis selecionadas foram utilizadas para avaliar o escore de risco de mortalidade por IC após um ano, e este foi dividido em três grupos (baixo, moderado e alto). O grupo de alto risco corresponde a aproximadamente 86% das mortes, e o grupo de risco moderado corresponde a 12% das mortes. CONCLUSÃO: Um escore de risco de 5 variáveis simples pode ser utilizado para avaliar a mortalidade um ano após a alta hospitalar de pacientes internados com IC.

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