端粒长度与认知障碍及其中药治疗的研究现况

认知障碍是指记忆、语言、理解和判断等一个或多个方面的功能障碍,包括轻度认知障碍和各种类型的痴呆症。痴呆症是认知障碍最严重的表现,是一种导致患者日常生活、社会交往和工作能力发生显著变化的综合征。阿尔茨海默病(AD)是最常见的痴呆症类型,其次是血管性痴呆(VD)和其他神经退行性痴呆[1]。已知年龄与认知功能的退化密切相关。     

Alzheimer's Disease THErapy With NEuroaid (ATHENE): A Randomized Double-Blind Delayed-Start Trial

ObjectivesPreclinical and clinical studies indicate a role for MLC901 (NeuroAiD II) in Alzheimer's disease (AD). The primary aim was to investigate its safety as add-on therapy to standard treatment and the secondary aims its effect on cognition and slowing disease progression.DesignRandomized double-blind placebo-controlled delayed-start study.Setting and ParticipantPatients with mild to moderate probable AD by NINCDS-ADRDA criteria, stable on acetylcholinesterase inhibitors or memantine (n = 125), were randomized to receive MLC901 (early starters) or placebo (delayed starters) for 6 months, followed by a further 6 months when all patients received MLC901, in a delayed-start design (clinical trial registration: ClinicalTrials.gov, NCT03038035).MethodsThe primary outcome measure was occurrence of serious adverse events (SAEs) at 6 months. Secondary outcomes included the Alzheimer's Disease Assessment Scale–Cognitive subscale (ADAS-Cog) and other assessment scales.ResultsThere was no significant difference in the risk of SAEs between early and delayed starters at month (M) 6 (22.6% vs 27.0%, risk difference ?4.4%, 90% CI –16.9% to 8.3%). Similarly, there was no significant difference in the risk of adverse events and the occurrence of stroke or vascular events between early and delayed starters throughout the 12-month study period. Early starters did not differ significantly on ADAS-Cog from delayed starters at M6 [mean difference (MD) ?1.0, 95% CI –3.3 to 1.3] and M12 (MD –2.35, 95% CI –5.45 to 0.74) on intention-to-treat analysis. Other cognitive assessment scales did not show significant differences.Conclusions and ImplicationsThis study of 125 persons with dementia found no evidence of a significant increase in adverse events between MLC901 and placebo, thus providing support for further studies on both efficacy and safety. Analyses suggest the potential of MLC901 in slowing down AD progression, but this requires further confirmation in larger and longer studies using biomarkers for AD.     

Transient left bundle branch block after posture change to the prone position during general anesthesia: A case report

Rationale:The prone position is commonly used in spinal surgery. There have been many studies on hemodynamic changes in the prone position during general anesthesia. We report a rare case of transient left bundle branch block (LBBB) in a prone position.Patient concern:Electrocardiogram (ECG) of a 64-year-old man scheduled for spinal surgery showed normal sinus rhythm change to LBBB after posture change to the prone position.Diagnosis:Twelve lead ECG revealed LBBB. His coronary angio-computed tomography results showed right coronary artery with 30% to 40% stenosis and left circumflex artery with 40% to 50% stenosis. The patient was diagnosed with stable angina and second-degree atrioventricular block of Mobitz type II.Intervention:Nitroglycerin was administered intravenously during surgery. Adequate oxygen was supplied to the patient. After surgery, the patient was prescribed clopidogrel, statins, angiotensin II receptor blocker, and a permanent pacemaker was inserted.Outcome:Surgery was completed without complications. After surgery, the transient LBBB changed to a normal sinus rhythm. The patient did not complain of chest pain or dyspnea.Lesson:The prone position causes significant hemodynamic changes. A high risk of cardiovascular disease may cause ischemic heart disease and ECG changes. Therefore, careful management is necessary.     

Risk factors for falls in older people with cognitive impairment living in the community: Systematic review and meta-analysis

PurposeThis systematic review aimed to identify risk factors for prospectively ascertained falls, focusing on those that are potentially modifiable (physical and neuropsychological factors), in older people with cognitive impairment living in the community.ResultsA comprehensive search of five databases identified 16 high quality (Newcastle-Ottawa Scale ≥8/9) relevant articles. Meta-analyses were undertaken for five potential fall risk factors. Of these, fallers had significantly poorer balance (standardized mean difference = 0.62, 95 %CI 0.45, 0.79) with low heterogeneity. Global cognition was not significantly associated with faller status in a meta-analysis with low heterogeneity. Meta-analyses of mobility (Timed Up-and-Go), gait speed and depressive symptoms had high heterogeneity and were not statistically significant or were borderline significant (p = 0.05). Sensitivity analyses (removing one study sample’s results that differed markedly from the other included samples) reduced heterogeneity to 0% and revealed fallers had significantly poorer mobility and more depressive symptoms than non-fallers. Fallers also walked significantly slower, but heterogeneity remained high.ConclusionsIn older people with cognitive impairment, fallers presented with balance deficits, poor mobility, slow gait speed and depressive symptoms. Reduced global cognition was not associated with falls. These findings suggest that interventions should target balance impairment and reveal that more high-quality research is needed.     

Risk of seizures and subclinical epileptiform activity in patients with dementia: A systematic review and meta-analysis

BackgroundSeizures and subclinical epileptiform activity are common yet easily overlooked among demented patients. We aimed to investigate their epidemiological characteristics in patients with dementia from various aspects.MethodsWe retrieved relevant observational studies from PubMed and Embase Library until March 2021. Pooled estimate effects were calculated using random-effects models. This study is registered with PROSPERO, number CRD42020200949.ResultsOf the 19144 identified studies, 27 were eligible for inclusion. The pooled period prevalence rates of seizures were 4.86% (95%CI: 3.43–6.51%), 2.68% (95%CI: 2.13–3.28%), 2.81% (95%CI: 2.02–3.71%）and 7.13% (95%CI: 2.67–13.14%) among patients with Alzheimer’s disease (AD), Dementia of Lewy Body (DLB), Frontotemporal dementia (FTD) and Vascular dementia (VaD), respectively. The pooled incidence rate of seizures was [8.4 (95%CI: 4.2–12.7) per 1000 person-years] in AD patients. And the pooled relative risk of seizures in patients with AD was 3.35 (95%CI: 2.69–4.19). Besides, the pooled cumulative incidence rate and prevalence rate of subclinical epileptiform activity among AD patients were [21.41% (95%CI: 0.001–63.60%)] and 9.73% (95%CI: 0.26–28.38%), respectively.ConclusionsThe accurate rates of seizures and subclinical epileptiform activities in the four major dementia types are high. Besides, patients with AD are likely at a higher risk of seizures.     

Diffusion-weighted MRI and PET/CT reproducibility in epithelial ovarian cancers during neoadjuvant chemotherapy

PurposeTo investigate the reproducibility of diffusion-weighted (DW) MRI and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG)-Positron emission tomography/CT (PET/CT) in monitoring response to neoadjuvant chemotherapy in epithelial ovarian cancer.Materials and methodsTen women (median age, 67 years; range: 41.8–77.3 years) with stage IIIC-IV epithelial ovarian cancers were included in this prospective trial (NCT02792959) between 2014 and 2016. All underwent initial laparoscopic staging, four cycles of carboplatine-paclitaxel-based chemotherapy and interval debulking surgery. PET/CT and DW-MRI were performed at baseline (C0), after one cycle (C1) and before surgery (C4). Two nuclear physicians and two radiologists assessed five anatomic sites for the presence of ≥ 1 lesion. Target lesions in each site were defined and their apparent diffusion coefficient (ADC), maximal standardized uptake value (SUV-max), SUV-mean, SUL-peak, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were monitored (i.e., 10 patients × 5 sites × 3 time-points). Their relative early and late changes were calculated. Intra/inter-observer reproducibilities of qualitative and quantitative analysis were estimated with Kappa and intra-class correlation coefficients (ICCs).ResultsFor both modalities, inter- and intra-observer agreement percentages were excellent for initial staging but declined later for DW-MRI, leading to lower Kappa values for inter- and intra-observer variability (0.949 and 1 at C0, vs. 0.633 and 0.643 at C4, respectively) while Kappa values remained > 0.8 for PET/CT. Inter- and intra-observer ICCs were > 0.75 for SUV-max, SUL-peak, SUV-mean and their change regardless the time-point. ADC showed lower ICCs (range: 0.013–0.811). ANOVA found significant influences of the evaluation time, the measurement used (ADC, SUV-max, SUV-mean, SUV-max, SUL-peak, MTV or TLG) and their interaction on ICC values (P = 0.0023, P< 0.0001 and P =0.0028, respectively).ConclusionWhile both modalities demonstrated high reproducibility at baseline, only SUV-max, SUL-peak, SUV-mean and their changes maintained high reproducibility during chemotherapy.     

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimeŕs, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.