Double-edged sword of diabetes mellitus for abdominal aortic aneurysm

IntroductionDiabetes mellitus (DM) has been proved to contribute to multiple comorbidities that are risk factors for abdominal aortic aneurysm (AAA). Remarkably, evidences from epidemiologic studies have demonstrated a negative association between the two disease states. On the other hand, hyperglycemic state was linked to post-operative morbidities following AAA repair. This review aims to provide a thorough picture on the double-edged nature of DM and major hypoglycemic medications on prevalence, growth rate and rupture of AAA, as well as DM-associated prognosis post AAA repair.MethodsWe performed a comprehensive search in electronic databases to look for literatures demonstrating the association between DM and AAA. The primary focus of the literature search was on the impact of DM on the morbidity, enlargement and rupture rate, as well as post-operative complications of AAA. The role of antidiabetic medications was also explored.ResultsRetrospective epidemiological studies and large database researches associated the presence of DM with decreased prevalence, slower expansion and limited rupture rate of AAA. Major hypoglycemic drugs exert similar protective effect as DM against AAA by targeting pathological hallmarks involved in AAA formation and progression, which were demonstrated predominantly by animal studies. Nevertheless, presence of DM or postoperative hyperglycemia was linked to poorer short-term and long-term prognosis, primarily due to greater risk of infection, longer duration of hospital stays and death.ConclusionWhile DM is a positive factor in the formation and progression of AAA, it is also associated with higher risk of negative outcomes following AAA repair. Concomitant use of antidiabetic medications may contribute to the protective mechanism of DM in AAA, but further studies are still warranted to explore their role following AAA repair

Generation and Characterization of Novel Human IRAS Monoclonal Antibodies

Imidazoline receptors were first proposed by Bousquet et al., when they studied antihypertensive effect of clonidine. A strong candidate for I1R, known as imidazoline receptor antisera-selected protein (IRAS), has been cloned from human hippocampus. We reported that IRAS mediated agmatine-induced inhibition of opioid dependence in morphine-dependent cells. To elucidate the functional and structure properties of I1R, we developed the newly monoclonal antibody against the N-terminal hIRAS region including the PX domain (10–120aa) through immunization of BALB/c mice with the NusA-IRAS fusion protein containing an IRAS N-terminal (10–120aa). Stable hybridoma cell lines were established and monoclonal antibodies specifically recognized full-length IRAS proteins in their native state by immunoblotting and immunoprecipitation. Monoclonal antibodies stained in a predominantly punctate cytoplasmic pattern when applied to IRAS-transfected HEK293 cells by indirect immunofluorescence assays and demonstrated excellent reactivity in flow immunocytometry. These monoclonal antibodies will provide powerful reagents for the further investigation of hIRAS protein functions

Association Analysis of IL-17A and IL-17F Polymorphisms in Chinese Han Women with Breast Cancer

Background: Research into the etiology of breast cancer has recently focused on the role of the immunity and inflammation. The proinflammatory cytokines IL-17A and IL-17F can mediate inflammation and cancer. To evaluate the influences of IL-17A and IL-17F gene polymorphisms on the risk of sporadic breast cancer, a case-control study was conducted in Chinese Han women. Methodology and Principal Findings: We genotyped three single-nucleotide polymorphisms (SNPs) in IL-17A (rs2275913, rs3819025 and rs3748067) and five SNPs in IL-17F (rs7771511, rs9382084, rs12203582, rs1266828 and rs763780) to determine the haplotypes in 491 women with breast cancer and 502 healthy individuals. The genotypes were determined using the SNaPshot technique. The differences in the genotypic distribution between breast cancer patients and healthy controls were analyzed with the Chi-square test for trends. For rs2275913 in IL-17A, the frequency of the AA genotype was higher in patients than controls (P = 0.0016). The clinical features analysis demonstrated significant associations between IL-17 SNPs and tumor protein 53 (P53), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2) and triple-negative (ER-/PR-/Her-2-) status. In addition, the haplotype analysis indicated that the frequency of the haplotype A rs2275913G rs3819025G rs3748067, located in the IL-17A linkage disequilibrium (LD) block, was higher in patients than in controls (P = 0.0471 after correction for multiple testing)

Reconstructing historical forest fire risk in the non-satellite era using the improved forest fire danger index and long short-term memory deep learning-a case study in Sichuan Province, southwestern China

Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management approaches, enhancing forest fire warnings and emergency response capabilities, and accurately budgeting potential carbon emissions resulting from fires. However, due to the unavailability of spatial information technology, such databases are extremely difficult to build reliably and completely in the non-satellite era. This study presented an improved forest fire risk reconstruction framework that integrates a deep learning-based time series prediction model and spatial interpolation to address the challenge in Sichuan Province, southwestern China. First, the forest fire danger index (FFDI) was improved by supplementing slope and aspect information. We compared the performances of three time series models, namely, the autoregressive integrated moving average (ARIMA), Prophet and long short-term memory (LSTM) in predicting the modified forest fire danger index (MFFDI). The best-performing model was used to retrace the MFFDI of individual stations from 1941 to 1970. Following this, the Anusplin spatial interpolation method was used to map the distributions of the MFFDI at five-year intervals, which were then subjected to weighted overlay with the distance-to-river layer to generate forest fire risk maps for reconstructing the forest fire danger database. The results revealed LSTM as the most accurate in fitting and predicting the historical MFFDI, with a fitting determination coefficient (R2) of 0.709, mean square error (MSE) of 0.047, and validation R2 and MSE of 0.508 and 0.11, respectively. Independent validation of the predicted forest fire risk maps indicated that 5 out of 7 historical forest fire events were located in forest fire-prone areas, which is higher than the results determined from the original FFDI (2 out of 7). This proves the effectiveness of the improved MFFDI and indicates a high level of reliability of the historical forest fire risk reconstruction method proposed in this study

Characterization of NaA Zeolite Oxygen Permeable Membrane on TiO2/α-Al2O3 Composite Support

The NaA zeolite membrane was synthesized on the surface of TiO2/α-Al2O3 composite support with TiO2 as modifier of α-Al2O3 porous tubular ceramic membrane support by crystallization method. The structure characterization indicated that the TiO2 of the support surface could effectively improve the surface properties of the support. It didn’t affect the crystallization of NaA synthesis liquid and synthesis process of NaA zeolite membrane. There were no obvious defects between the crystal particles with size of approximate 6μm. The perfect and complete membrane with thickness of approximate 15μm combined closely with support to connection together by TiO2 modified. The oxygen permeability of the membrane on TiO2/α-Al2O3 composite support improves of 47% compared with that of α-Al2O3 support. So the process of TiO2 modifying the surface of α-Al2O3 support should increase the oxygen permeability of the NaA zeolite membrane

Characterization of NaA Zeolite Oxygen Permeable Membrane on TiO

The NaA zeolite membrane was synthesized on the surface of TiO2/α-Al2O3 composite support with TiO2 as modifier of α-Al2O3 porous tubular ceramic membrane support by crystallization method. The structure characterization indicated that the TiO2 of the support surface could effectively improve the surface properties of the support. It didn’t affect the crystallization of NaA synthesis liquid and synthesis process of NaA zeolite membrane. There were no obvious defects between the crystal particles with size of approximate 6μm. The perfect and complete membrane with thickness of approximate 15μm combined closely with support to connection together by TiO2 modified. The oxygen permeability of the membrane on TiO2/α-Al2O3 composite support improves of 47% compared with that of α-Al2O3 support. So the process of TiO2 modifying the surface of α-Al2O3 support should increase the oxygen permeability of the NaA zeolite membrane

A Preliminary Study of Spectral CT in Predicting Pfirrmann Grading of Lumbar Intervertebral Disc

Objective: To investigate the predictive value of material separation technology of spectral CT in Pfirrmann grading of lumbar intervertebral disc degeneration. Methods: Retrospective analysis was performed on 30 patients with lumbar disc herniation in our hospital from October 2020 to February 2021. Spectral CT scan and MRI scan were performed respectively. Grade 1-3 of Pfirrmann grading was classified into low grade group, while grade 4-5 was classified into high grade group. Water (calcium) concentration, water (HAP) concentration, calcium (water) concentration, HAP (water) concentration and Eff-Z of intervertebral disc were measured by spectral post-processing analysis software in the same ROI. Independent sample t est was used to compare the differences among parameters, furthermore, the ROC curve was drawn. The area under the curve was used to evaluate the diagnostic efficiency and select the optimal diagnostic threshold. Results: The concentrations of water (calcium) and water (HAP) in low-grade intervertebral discs were higher than those in high-grade intervertebral discs, while the concentrations of water (calcium), water (HAP) and Eff-Z in low-grade intervertebral discs, were lower than those in high-grade intervertebral discs, which held statistical significance. The ROC curve showed that water (calcium) concentration and water (HAP) concentration were less effective in diagnosing the difference between low-grade and high-grade discs. Calcium concentration holds certain diagnostic efficacy. HAP and Eff-Z hold high diagnostic efficacy. while Eff-Z shows better diagnostic efficacy with AUC of 0.97. Taking 7.69 as the standard, the sensitivity and specificity of differentiating low-grade and high-grade intervertebral discs are respectively 96.25% and 96.00%. Conclusion: Spectral CT with multi-parameters quantitative analysis holds certain value in distinguishing low grade and high grade intervertebral discs