Activation of an AMP-activated protein kinase is involved in post-diapause development of Artemia franciscana encysted embryos

<p>Abstract</p> <p>Background</p> <p>Cysts of <it>Artemia </it>can remain in a dormant state for long periods with a very low metabolic rate, and only resume their development with the approach of favorable conditions. The post-diapause development is a very complicated process involving a variety of metabolic and biochemical events. However, the intrinsic mechanisms that regulate this process are unclear.</p> <p>Results</p> <p>Herein we report the specific activation of an AMP-activated protein kinase (AMPK) in the post-diapause developmental process of <it>Artemia</it>. Using a phospho-AMPKα antibody, AMPK was shown to be phosphorylated in the post-diapause developmental process. Results of kinase assay analysis showed that this phosphorylation is essential for AMPK activation. Using whole-mount immunohistochemistry, phosphorylated AMPK was shown to be predominantly located in the ectoderm of the early developed embryos in a ring shape; however, the location and shape of the activation region changed as development proceeded. Additionally, Western blotting analysis on different portions of the cyst extracts showed that phosphorylated AMPKα localized to the nuclei and this location was not affected by intracellular pH. Confocal microscopy analysis of immunofluorescent stained cyst nuclei further showed that AMPKα localized to the nuclei when activated. Moreover, cellular AMP, ADP, and ATP levels in developing cysts were determined by HPLC, and the results showed that the activation of <it>Artemia </it>AMPK may not be associated with cellular AMP:ATP ratios, suggesting other pathways for regulation of <it>Artemia </it>AMPK activity.</p> <p>Conclusion</p> <p>Together, we report evidence demonstrating the activation of AMPK in <it>Artemia </it>developing cysts and present an argument for its role in the development-related gene expression and energy control in certain cells during post-diapause development of <it>Artemia</it>.</p

Chloridobis[N′-(2-meth­oxy­benzyl­idene)-4-nitro­benzohydrazidato-κ2 O,N′](4-methyl­pyridine-κN)cobalt(III)

In the title complex, [Co(C15H12N3O4)2Cl(C6H7N)], the CoIII ion is coordinated by two N atoms and two O atoms from two deprotonated Schiff base ligands, one N atom from a 4-methyl­pyridine ligand and one Cl atom, forming a distorted octa­hedral geometry. The CoIII ion is displaced by 0.038 (2) Å from the equatorial plane towards the axial Cl atom

BAG5 Interacts with DJ-1 and Inhibits the Neuroprotective Effects of DJ-1 to Combat Mitochondrial Oxidative Damage

Loss-of-function mutations in gene encoding DJ-1 contribute to the pathogenesis of autosomal recessive early-onset familial forms of Parkinson’s disease (PD). DJ-1 is a multifunctional protein and plays a protective role against oxidative stress-induced mitochondrial damage and cell death, but the exact mechanism underlying this is not yet clearly understood. Here, using coimmunoprecipitation (Co-IP) and immunofluorescence methods, we prove that Bcl-2-associated athanogene 5 (BAG5), a BAG family member, interacts with DJ-1 in mammalian cells. Moreover, we show that BAG5 could decrease stability of DJ-1 and weaken its role in mitochondrial protection probably by influencing dimerization in stress condition. Our study reveals the relationship of BAG5 and DJ-1 suggesting a potential role for BAG5 in the pathogenesis of PD through its functional interactions with DJ-1

Clinical and biomarker trajectories in sporadic Alzheimer's disease: A longitudinal study.

Introduction: Amyloid beta (Aβ) deposition was identified to precede tau pathology and neurodegeneration in familial Alzheimer's disease (AD). But the divergence between sporadic and familial AD limits the extension of these findings to sporadic AD. Methods: Longitudinal changes of biomarkers among different stages were assessed using linear mixed-effects models. The slopes of the models were used to estimate rates of change to calculate the biomarker trajectories in sporadic AD. Results: Cerebrospinal fluid (CSF) Aβ was estimated to decline 45.2 years (abnormal: 27.8 years) before dementia, and Aβ deposition seemed to increase 31.7 years (abnormal: 26.7 years) before dementia. It was estimated to take 29.0 years (CSF t-tau), 12.2 years (memory), 11.6 years (hippocampus), 9.3 years (hypometabolism), and 6.1 years (cognition) to move from normal to dementia. Discussion: The trajectory in sporadic AD is led by Aβ accumulation, followed by CSF t-tau increase, memory deficits, brain atrophy, hypometabolism, and cognitive decline

TREML2 Mutation Mediate Alzheimer’s Disease Risk by Altering Neuronal Degeneration

A coding missense mutation (rs3747742) in triggering receptor expressed on myeloid cell-like 2 (TREML2) has been recently proposed as an important protective factor against Alzheimer’s disease (AD). However, the link between TREML2 and AD pathology remains unclear. Therefore, we explored the association of TREML2 rs3747742 with cognitive function, neuroimaging biomarkers and cerebrospinal fluid (CSF) biomarkers related to AD, including CSF total-tau (T-tau), phosphor-tau (P-tau), and amyloid-β (Aβ1-42). As for cognitive function, related cognitive scores of Clinical Dementia Rating Sum of Boxes (CDRSB), Alzheimer’s Disease Assessment Scale-cognitive section 11 (ADAS-cog 11), Mini-Mental State Examination (MMSE), and Rey Auditory-Verbal Learning Test (RAVLT) were extracted. We used a multiple linear regression model to examine the association of TREML2 rs3747742 with the baseline variables. Furthermore, we also calculated the change rate of above variables influenced by TREML2 rs3747742 via applying a mixed-effects model over a 4-year follow-up. In this analysis, a total of 1,306 individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were included. Finally, we observed that only in AD patients, but not in normal controls or mild cognitive impairment (MCI) individuals, TREML2 rs3747742 exhibited a strong association with CSF total-tau levels at baseline (β = -22.1210, p = 0.0166) and 4-year follow-up (β = -0.3961, p = 0.0115). Furthermore, no associations were found with CSF Aβ1-42 levels, P-tau levels, neuroimaging biomarkers and cognitive function neither for baseline variables nor for longitudinal data. Thus, this study indicated that TREML2 mediated the risk of AD through influencing AD-related neurodegeneration (abnormal T-tau levels) but not P-tau levels and Aβ pathology

Frequency and longitudinal clinical outcomes of Alzheimer's AT(N) biomarker profiles: A longitudinal study.

INTRODUCTION: We aimed to estimate the frequency of each AT(N) (β-amyloid deposition [A], pathologic tau [T], and neurodegeneration [N]) profile in different clinical diagnosis groups and to describe the longitudinal change in clinical outcomes of individuals in each group. METHODS: Longitudinal change in clinical outcomes and conversion risk of AT(N) profiles are assessed using linear mixed-effects models and multivariate Cox proportional-hazard models, respectively. RESULTS: Participants with A+T+N+ showed faster clinical progression than those with A-T-N- and A+T±N-. Compared with A-T-N-, participants with A+T+N± had an increased risk of conversion from cognitively normal (CN) to incident prodromal stage of Alzheimer's disease (AD), and from MCI to AD dementia. A+T+N+ showed an increased conversion risk when compared with A+T±N-. DISCUSSION: The 2018 research framework may provide prognostic information of clinical change and progression. It may also be useful for targeted recruitment of participants with AD into clinical trials

Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction

ObjectivesThe purpose of this study was to evaluate available evidence on the association between the human oral microbiota and coronavirus disease 2019 (COVID-19) and summarize relevant data obtained during the pandemic.MethodsWe searched EMBASE, PubMed, and the Cochrane Library for human studies published up to October 2022. The main outcomes of the study were the differences in the diversity (α and β) and composition of the oral microbiota at the phylum and genus levels between patients with laboratory-confirmed SARS-CoV-2 infection (CPs) and healthy controls (HCs). We used the Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA) database, Protein−protein interaction (PPI) network (STRING) and Gene enrichment analysis (Metascape) to evaluate the expression of dipeptidyl peptidase 4 (DPP4) (which is the cell receptor of SARS CoV-2) in oral tissues and evaluate its correlation with viral genes or changes in the oral microbiota.ResultsOut of 706 studies, a meta-analysis of 9 studies revealed a significantly lower alpha diversity (Shannon index) in CPs than in HCs (standardized mean difference (SMD): -0.53, 95% confidence intervals (95% CI): -0.97 to -0.09). Subgroup meta-analysis revealed a significantly lower alpha diversity (Shannon index) in older than younger individuals (SMD: -0.54, 95% CI: -0.86 to -0.23/SMD: -0.52, 95% CI: -1.18 to 0.14). At the genus level, the most significant changes were in Streptococcus and Neisseria, which had abundances that were significantly higher and lower in CPs than in HCs based on data obtained from six out of eleven and five out of eleven studies, respectively. DPP4 mRNA expression in the oral salivary gland was significantly lower in elderly individuals than in young individuals. Spearman correlation analysis showed that DPP4 expression was negatively correlated with the expression of viral genes. Gene enrichment analysis showed that DPP4-associated proteins were mainly enriched in biological processes, such as regulation of receptor-mediated endocytosis of viruses by host cells and bacterial invasion of epithelial cells.ConclusionThe oral microbial composition in COVID-19 patients was significantly different from that in healthy individuals, especially among elderly individuals. DPP4 may be related to viral infection and dysbiosis of the oral microbiome in elderly individuals

Lyn mediates FIP1L1-PDGFRA signal pathway facilitating IL-5RA intracellular signal through FIP1L1-PDGFRA/JAK2/Lyn/Akt network complex in CEL

The Fip1-like1 (FIP1L1)–platelet-derived growth factor receptor alpha (PDGFRA) (F/P) oncogene can cause chronic eosinophilic leukemia (CEL), but requires IL-5 cytokine participation. In this study, we investigate the mechanism of F/P in collaboration with IL-5 in CEL. The results showed that Lyn, a key effector in the IL-5-motivated eosinophil production, is extensively activated in F/P-positive CEL cells. Lyn can associate and phosphorylate IL-5 receptor α (IL-5RA) in F/P-positive cells. Moreover, the activation of Lyn and IL-5R kinase were strengthened when the cells were stimulated by IL-5. Lyn inhibition in F/P-positive CEL cells attenuated cellular proliferation, induced apoptosis, and blocked cell migration and major basic protein (MBP) release. We identified the FIP1L1-PDGFRA/JAK2/Lyn/Akt complex in the F/P-expressing cells which can be disrupted by dual inhibition of JAK2 and Lyn, repressing cell proliferation in both EOL-1(F/P-positive human eosinophilic cell line) and imatinib-resistance (IR) cells. Altogether, our data demonstrate that Lyn is a vital downstream kinase activated by F/P converged with IL-5 signals in CEL cells. Lyn activate and expand IL-5RA intracellular signaling through FIP1L1-PDGFRA/JAK2/Lyn/Akt network complex, provoking eosinophils proliferation and exaggerated activation manifested as CEL

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort.Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package “Seurat” was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the “ssGSEA” algorithm. In order to develop possible medications for patients with high-risk ccRCC, the “pRRophetic” package is employed.Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature’s biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications.Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient’s prognosis for ccRCC and reflect the disease’s complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment

Clinical Features and Correlates of Excessive Daytime Sleepiness in Parkinson's Disease

Objective: To explore the clinical features and correlates of excessive daytime sleepiness (EDS) in a Chinese population of Parkinson's disease (PD) patients.Methods: Patients with clinically established or clinically probable PD were recruited. Clinical and demographic data were collected, and participants were evaluated using standardized assessment protocols. Patients were divided into PD with EDS and PD without EDS groups based on the Epworth sleepiness scale (ESS) scores, with a cutoff score of 10. Clinical manifestations were compared between patients with and without EDS, and correlates of EDS were also studied. In addition, the relationship between EDS and poor nighttime sleep quality was analyzed.Results: A total of 1,221 PD patients were recruited in our study. The mean ESS (min, max) score was 7.6 ± 6.1 (0, 24), and 34.1% of the patients had ESS scores ≥10. No difference was seen in lifestyle (except for alcohol consumption), environmental factors, BMI, levodopa equivalent dose (LED), initial presentation of motor symptoms, motor subtype, and wearing off between patients with and without EDS. The PD with EDS group had a higher proportion of male patients and a higher average patient age. Moreover, the PD with EDS group showed older age at PD onset, lower educational level, and longer disease duration. Patients with EDS had higher scores on the Hoehn-Yahr scale and the Unified Parkinson's Disease Rating Scale (UPDRS) parts I, II, and III score, more severe non-motor symptoms, and poorer quality of sleep and life. Logistic regression analyses demonstrated that EDS was associated with male sex, age, cognitive impairment, PD-related sleep problems, rapid eye movement sleep behavior disorder (RBD), and worse quality of life (QoL).Conclusion: EDS is a general clinical manifestation in PD, and there were significant differences in clinical features between patients with and without EDS. Moreover, our study proved that many factors were associated with EDS, including male sex, age, cognitive impairment, PD-related sleep problems, RBD, and worse QoL. Understanding the clinical characteristics of EDS in PD patients may help identify EDS early, improve QoL, and reduce the occurrence of accidents