肠道菌群与呼吸道感染患者免疫球蛋白的关系及其肠内营养的疗效

目的分析肠道菌群紊乱对呼吸道感染患者免疫球蛋白水平的影响,探讨肠内营养对此类患者的疗效。方法选取2016年2月至2018年12月在我院接受治疗的116例呼吸道感染患者作为观察组,进一步将其分为非菌群失调组(50例)和菌群失调组(66例),选取同期60例健康体检者作为对照组,比较各组对象肠道菌群失调情况和血清免疫球蛋白水平,同时对菌群失调患者在常规治疗基础上联合应用肠内营养治疗,观察其治疗效果。结果 (1)观察组患者肠道乳杆菌、双歧杆菌数量及双歧杆菌/大肠埃希菌比值(B/E)显著低于对照组,而肠球菌、大肠埃希菌数量显著高于对照组(均P0.05);观察组患者血清IgM、IgA、IgG水平均显著低于对照组(均P0.05);菌群失调组患者血清IgM、IgA、IgG水平均显著低于非菌群失调组(均P0.05)。(2)观察组患者肠道乳杆菌、双歧杆菌数量及B/E值与血清IgM、IgA、IgG水平呈显著正相关(均P0.05),而大肠埃希菌和肠球菌数量与之呈显著负相关(均P0.05)。(3)菌群失调组患者血清ALB、PA水平随治疗时间的延长而逐渐升高,CRP、PCT水平逐渐降低,IgM、IgA、IgG水平逐渐升高,乳杆菌、双歧杆菌数量和B/E值逐渐增加,大肠埃希菌和肠球菌数量逐渐减少(均P0.05)。结论呼吸道感染患者存在明显的肠道菌群失调情况,其与患者免疫球蛋白水平的降低有关,这可能是引发呼吸道感染的主要危险因素。肠内营养支持疗法能有效改善患者肠道菌群失调,降低血清炎性因子水平,增强机体免疫力,提高患者营养状况及治疗效果。     

Variability of qualitative and quantitative secondary metabolites traits among wild genetic resources of Lavandula stoechas L.

Lavandula stoechas L. (Lamiaceae) is an attractive shrub native to the Mediterranean regions used for ornamental, melliferous, aromatic and medicinal purposes. Furthermore, this species presents an increasing interest in cosmetics, perfumery and pharmaceutical industries. The variability of qualitative and quantitative metabolic traits among nine wild germplasms representing the distribution area of this species in Tunisia was undertaken. A total of 45 essential oil components were identified in the aerial parts of the studied germplasms. The main essential oil components were camphor (15.32–50.63%), fenchone (6.57–34.70%), 1,8-cineole (0.05–13.45%) and γ-gurjunene (1.10–12.15%). In addition to the well known chemotypes camphor/fenchone and camphor/1.8-cineole, a new chemotype camphor/γ-gurjunene was detected in Tunisian L. stoechas L. Six phenolic acids (quinic acid, gallic acid, p-coumaric acid, 4,5-di-O-caffeoyquinic acid, salviolinic acid and trans cinnamic acid) and five flavonoids (luteolin-7-o-glucoside, naringin, apegenin-7-o-glucoside, quercetin and kampherol) were identified in the ethanolic extracts. Salviolinic acid (46.30–615.18 μg/g) and luteolin-7-o-glucoside (5.98–38.54 μg/g) were the most abundant phenolic compounds. A high significant phytochemical variability (p ˂ 0.01) in the accumulation of volatile and phenolic secondary metabolites among the studied germplasms was recorded. The conducted multivariate (PCA) and clustering (HCA) analyses revealed different classification pattern for essential oil and phenolic compounds. The detected phytochemical polymorphism among the investigated lavender ecotypes didn't show accordance with bioclimatic and geographical areas which suggests genetic background as the main explaining factor. The detected secondary metabolites polymorphism valorises Tunisian L. stoechas L. genetic resources as valuable plant material in further breeding programs. Moreover, an urgent in situ and ex situ conservation measures are required for these wild germplasms threatened by human over-harvesting practices and the occurring dramatic changes in climatic conditions.     

Metabolic syndrome during gestation and lactation: An important renal problem in dams. selenium renal clearance

BackgroundMetabolic syndrome (MS) in lactating dams leads to several cardiometabolic changes related to selenium (Se) status and selenoproteins expression which produce hypertension. However, little is known about the state of these dams’ kidney functions and their Se deposits.MethodsTwo experimental groups of dam rats were used: control (Se: 0.1 ppm) and MS (Fructose 65 % and Se: 0.1 ppm). At the end of lactation (21d postpartum) kidney weight and protein content, Se deposits, and the activity of the antioxidant selenoprotein glutathione peroxidase (GPx) were measured in dams. Kidney functional parameters: albuminuria, creatinine clearance, serum aldosterone and uric acid levels and water and electrolyte (Na⁺ and K⁺) balance were also evaluated. Systolic blood pressure (SBP) was measured.ResultsIn MS dams at the end of lactation Se deposits and GPx activity are higher in the kidney; however, lipid renal peroxidation appears, relative Se clearance increases, and the dams have lost Se by urine. MS dams have polyuria and polydipsia, high uric acid serum levels, albuminuria and high creatinine clearance, implying glomerular renal malfunction with protein loss. They also present hypernatremia, hypokalemia and hyperaldosteronemia, leading to high SBP; however, a natriuretic process is taking place.ConclusionSince these alterations appear, at least in part, to be related to oxidative stress in renal cells, Se supplementation could be beneficial to avoiding greater lipid renal oxidation during lactation.     

Heavy metals and trace elements in scalp hair samples of children with severe autism spectrum disorder: A case-control study on Jordanian children

BackgroundElemental analysis has been increasingly used for biomonitoring heavy metals and trace elements.MethodsThis study monitored the levels of two heavy metals (Al and Pb), and seven trace elements (Macroelements Mg, K, P and Ca; Microelements Zn, Cu, Fe) in scalp hair of 57 children with severe autism spectrum disorder (ASD) and 50 age-matched controls, using Inductively Coupled Plasma Atomic Emission Spectrophotometry (ICP-AES).ResultsCompared to controls, significantly higher levels of Al (p = 0.001), Pb (p = 0.001) and K (p = 0.021), with lower levels of Mg and Zn (p = 0.038) were observed for the ASD group. ASD boys had higher levels of Al (p = 0.001), Pb (p = 0.001) and K (p = 0.017) than control boys, while ASD girls had higher Pb levels (p = 0.005) than control girls. The ASD subgroup exposed to passive smokers had higher levels of Al (p = 0.033) and Pb (p = 0.001, and the ASD subgroup not exposed to passive smoke had higher levels of Al (p = 0.011), Pb (p = 0.001), K (p = 0.003); and lower levels of Mg (p = 0.011) than their controls. Other confounding factors and the correlation between these elements were also investigated.ConclusionThis data suggests that exposure to Al and Pb, increase intake of K, and decreased intake of magnesium and zinc, may contribute to ASD etiology.     

Preface to the Special Issue “Presynaptic Dysfunction and Disease”

The synapse is formed between a presynapse (which releases neurotransmitter) and the postsynapse (which transduces this chemical signal). Over the past decade, presynaptic dysfunction has emerged as a key mediator of a series of neurodevelopmental and neurodegenerative disorders. This special issue will highlight some of the important presynaptic molecules and mechanisms that are disrupted in these conditions and reveal potential routes for therapy.     

Psychological processes mediating the association between developmental trauma and specific psychotic symptoms in adults: a systematic review and meta‐analysis

Experiencing psychological trauma during childhood and/or adolescence is associated with an increased risk of psychosis in adulthood. However, we lack a clear knowledge of how developmental trauma induces vulnerability to psychotic symptoms. Understanding the psychological processes involved in this association is crucial to the development of preventive interventions and improved treatments. We sought to systematically review the literature and combine findings using meta‐analytic techniques to establish the potential roles of psychological processes in the associations between developmental trauma and specific psychotic experiences (i.e., hallucinations, delusions and paranoia). Twenty‐two studies met our inclusion criteria. We found mediating roles of dissociation, emotional dysregulation and post‐traumatic stress disorder (PTSD) symptoms (avoidance, numbing and hyperarousal) between developmental trauma and hallucinations. There was also evidence of a mediating role of negative schemata, i.e. mental constructs of meanings, between developmental trauma and delusions as well as paranoia. Many studies to date have been of poor quality, and the field is limited by mostly cross‐sectional research. Our findings suggest that there may be distinct psy­chological pathways from developmental trauma to psychotic phenomena in adulthood. Clinicians should carefully ask people with psychosis about their history of developmental trauma, and screen patients with such a history for dissociation, emotional dysregulation and PTSD symptoms. Well conducted research with prospective designs, including neurocognitive assessment, is required in order to fully understand the biopsychosocial mechanisms underlying the association between developmental trauma and psychosis.     

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.     

Towards an understanding of the role of intrinsic protein disorder on plant adaptation to environmental challenges

Intrinsic protein disorder is an interesting structural feature where fully functional proteins lack a three-dimensional structure in solution. In this work, we estimated the relative content of intrinsic protein disorder in 96 plant proteomes including monocots and eudicots. In this analysis, we found variation in the relative abundance of intrinsic protein disorder among these major clades; the relative level of disorder is higher in monocots than eudicots. In turn, there is an inverse relationship between the degree of intrinsic protein disorder and protein length, with smaller proteins being more disordered. The relative abundance of amino acids depends on intrinsic disorder and also varies among clades. Within the nucleus, intrinsically disordered proteins are more abundant than ordered proteins. Intrinsically disordered proteins are specialized in regulatory functions, nucleic acid binding, RNA processing, and in response to environmental stimuli. The implications of this on plants’ responses to their environment are discussed.