缺氧与复氧对不同血管α_1肾上腺素受体收缩效应的影响

本实验观察离体大鼠肾动脉(含α_(1V)亚型)、主动脉(含α_(1B)亚型)和肺动脉(含α_(1V)和α_(1B)亚型)在缺氧与复氧时由α_1肾上腺素受体激动所致收缩效应的改变。结果显示肾动脉在缺氧时pD值增大,最大收缩效应降低,复氧时pD值恢复;主动脉在缺氧时pD值减小,最大收缩效应不变,复氧时pD值不恢复:而肺动脉的改变为上述两者的综合。提示σ_1受体不同亚型在缺氧与复氧时发生的变化不同,这可能是不同血管对缺氧、复氧反应不同的机制之一。     

大鼠血小板中的神经肽Y及其对血管收缩的影响

特异性放射免疫分析显示大鼠血小板与富血小板血浆(PRP)分别含NPY免疫活性物质90±16ng/10~7血小板与93±19ng/ml,大大高于普通血浆(1.2±0.1ng/ml)与贫血小板血浆(PPP)(1.7±0.3 ng/ml)中的含量(P<0.001)。血小板样品HPLC各馏分的NPY放免活性峰位与标准NPY的峰位相符。PRP经胶原最大程度聚集后,血小板内的NPY浓度降为34±5 ng/10~7血小板,而PPP中的NPY浓度则升高到26±4 ng/ml。1.6 ml PRP经胶原作用产生最大程度聚集,由此分离所得的PPP引起离体灌流大鼠尾动脉收缩,张力上升380±80 mg;上述PPP经NPY抗血清处理后引起尾动脉收缩的幅度显著减小(190±40 mg,P<0.001)。而1 nmol/L人工合成NPY并不引起血管收缩。结果表明大鼠血小板中含有大量NPY,在不可逆聚集时可以释放,释放的NPY可能参与血小板聚集时释放物质的缩血管效应。     

基于肠道微生态改善的益生菌抗糖尿病作用机制研究进展

2型糖尿病(type 2 diabetes, T2D)会引起糖脂代谢紊乱,严重危害人类健康,为了防治这一流行病,急需寻找安全和无副作用的抗糖尿病的方法,其中,基于微生物方法治疗T2D最常见的策略是补充益生菌,其可通过对不同组织和代谢通路的调节来实现抗糖尿病的功效。益生菌摄入可通过降低慢性低度炎症,减少氧化应激,调节肠道菌群,增加短链脂肪酸含量来达到调控血糖的目的;通过增加胆固醇与胆盐的共沉淀作用,胆固醇在胃肠道内转化为粪甾醇,降低肝脏中3-羟基-3-甲基戊二酸单酰辅酶A还原酶活性,降低胆固醇转运体的表达及对脂肪细胞的调节来达到降脂的目的。本综述系统总结了益生菌抗糖尿病现状和基于肠道微生态的抗糖尿病分子机制,以期为益生菌作为降糖降脂等保健产品的开发利用提供理论依据。     

Zymosan-induced luminol-amplified chemiluminescence of whole blood phagocytes in experimental and human hyperthyroidism

Luminol-amplified CL of whole blood phagocytes was studied in rats given 3 consecutive doses of 0.1 mg L-triiodothyronine T₃/kg or in hyperthyroid patients, after stimulation by zymosan. In both cases, CL was significantly increased, in effect which was produced independently of the opsonization of the zymosan particles and markedly inhibited by azide. The in vitro addition of T₃ or L-thyroxine (T₄) to whole blood phagocytes from normal rats did not modify the opsonized zymosan-dependent CL, when assayed at the concentrations found in eutrhyroid subjects or in hyperthyroid patients. Administrations of propylthiouracil (400 mg/day for 2–3 months) to hyperthyroid patients reduced the CL response observed prior to treatment, to values comparable to those found in the euthyroid group. These data indicate that hyperthyroidism elicits an enhanced respiratory burst activity of whole blood phagocytes, probably related to adaptive changes induced by thyroid hormone on the mieloperoxidase-H₂O₂ system, rather than to direct actions of the hormone molecule or changes in the opsonic capacity of plasma.     

A carbon-13 nuclear magnetic resonance investigation of the metabolic fluxes associated withy glucose metabolism in human erythrocytes

We have used [2-¹³C]d-glucose and carbon-13 nuclear magnetic resonance (NMR) spectroscopy to investigate metabolic fluxes through the major pathways of glucose metabolism in intact human erythrocytes and to determine the interactions among these pathways under conditions that perturb metabolism. Using the method described, we have been able to measure fluxes through the pentose phosphate pathway, phosphofructokinase, the 2,3-diphosphoglycerate bypass, and phosphoglycerate kinase, as well as glucose uptake, concurrently and in a single experiment. We have measured these fluxes in normal human erythrocytes under the following conditions: (1) fully oxygenated; (2) treated with methylene blue; and (3) deoxygenated. This method makes it possible to monitor various metabolic effects of stresses in normal and pathological states. Not only has ¹³C-NMR spectroscopy proved to be a useful method for measuring in vivo flux through the pentose phosphate pathway, but it has also provided additional information about the cycling of metabolites through the non-oxidative portion of the pentose phosphate pathway. Our evidence from experiments with [1-¹³C]-, [2-¹³C]-, and [3-¹³C]d-glucoses indicates that there is an observable reverse flux of fructose 6-phosphate through the reactions catalyzed by transketolase and transaldolase, even in the presence of a net flux through the pentose phosphate pathway.     

汉族ABO血型的皮纹特征分析

作者对芜湖地区３８２例（男２２０人;女１６２人）汉族ＡＢＯ血型的皮纹特征进行了分析,其中Ｏ型１３０人,Ａ型１１３人,Ｂ型１０１人,ＡＢ型３８人。分析比较了指纹类型、指纹组合格局、指嵴纹计数、掌嵴纹计数、ａｔｄ角,掌部真实花纹,掌褶纹和拇趾球纹等项参数,结果表明,ＡＢＯ各血型的皮纹参数间有若干统计学差异。     

腺苷在低氧适应家兔脑血流调节中的作用

本研究观察了腺苷在低氧适应家兔脑血流(CBF)调节中的作用。结果表明:缺氧时适应组CBF改变不明显,对照组CBF明显增加;缺氧时适应组脑腺苷的含量明显低于对照组,而脑腺苷酸的含量明显高于对照组;适应组脑微血管对腺苷的反应与对照组相近。提示缺氧时低氧适应家兔CBF改变不明显,同低氧适应后脑腺苷含量较低、腺苷酸含量较高有关。     

Automatic Detection of Severely and Mildly Infected COVID-19 Patients with Supervised Machine Learning Models

ObjectivesWhen the prognosis of COVID-19 disease can be detected early, the intense-pressure and loss of workforce in health-services can be partially reduced. The primary-purpose of this article is to determine the feature-dataset consisting of the routine-blood-values (RBV) and demographic-data that affect the prognosis of COVID-19. Second, by applying the feature-dataset to the supervised machine-learning (ML) models, it is to identify severely and mildly infected COVID-19 patients at the time of admission.Material and methodsThe sample of this study consists of severely (n = 192) and mildly (n = 4010) infected-patients hospitalized with the diagnosis of COVID-19 between March-September, 2021. The RBV-data measured at the time of admission and age-gender characteristics of these patients were analyzed retrospectively. For the selection of the features, the minimum-redundancy-maximum-relevance (MRMR) method, principal-components-analysis and forward-multiple-logistics-regression analyzes were used. The features set were statistically compared between mild and severe infected-patients. Then, the performances of various supervised-ML-models were compared in identifying severely and mildly infected-patients using the feature set.ResultsIn this study, 28 RBV-parameters and age-variable were found as the feature-dataset. The effect of features on the prognosis of the disease has been clinically proven. The ML-models with the highest overall-accuracy in identifying patient-groups were found respectively, as follows: local-weighted-learning (LWL)-97.86%, K-star (K*)-96.31%, Naive-Bayes (NB)-95.36% and k-nearest-neighbor (KNN)-94.05%. Also, the most successful models with the highest area-under-the-receiver-operating-characteristic-curve (AUC) values in identifying patient groups were found respectively, as follows: LWL-0.95%, K*-0.91%, NB-0.85% and KNN-0.75%.ConclusionThe findings in this article have significant a motivation for the healthcare professionals to detect at admission severely and mildly infected COVID-19 patients.     

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%–19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.