Search

The main characteristics of Parkinson’s disease (PD) are the loss of dopaminergic (DA) neurons and abnormal aggregation of cytosolic proteins. However, the exact pathogenesis of PD remains unclear, with ferroptosis emerging as one of the key factors driven by iron accumulation and lipid peroxidation. Glial cells, including microglia, astrocytes, and oligodendrocytes, serve as supportive cells in the central nervous system (CNS), but their abnormal activation can lead to DA neuron death and ferroptosis. This paper explores the interactions between glial cells and DA neurons, reviews the changes in glial cells during the pathological process of PD, and reports on how glial cells regulate ferroptosis in PD through iron homeostasis and lipid peroxidation. This opens up a new pathway for basic research and therapeutic strategies in Parkinson’s disease.

Arthropod-borne viruses (arboviruses) are transmitted to humans by arthropod vectors and pose a serious threat to global public health. Neurotropic arboviruses including Sindbis virus (SINV) persistently infect the central nervous system (CNS) of vector insects without causing notable pathological changes or affecting their behavior or lifespan. However, the mechanisms by which vector insects evade these viral infections in the brains are poorly understood. In this study, we found that loss of the carbonyl reductase Sniffer (Sni) led to a significant increase in SINV infection in the Drosophila brain. Sni regulates reactive oxygen species (ROS) levels, and its depletion leads to elevated ROS, which in turn disrupts the septate junctions (SJs) between subperineurial glia (SPG) cells, compromising the integrity and barrier function of the blood-brain barrier (BBB). Genetic and pharmacological reduction of ROS restored BBB integrity and reduced viral load in the brains of Sni-depleted flies. Additionally, we identified Sni homologs and revealed that the antiviral function of Sni is highly conserved in mosquitoes, where it regulates ROS and protects BBB integrity. Our results revealed an evolutionarily conserved antiviral mechanism in which Sni acts as an antioxidant that protects BBB integrity and restricts viral infection in the vector insect brain.

Abstract Background SH3 and multiple ankyrin repeat domains protein 3 (SHANK3) monogenic mutations or deficiency leads to excessive stereotypic behavior and impaired sociability, which frequently occur in autism cases. To date, the underlying mechanisms by which Shank3 mutation or deletion causes autism and the part of the brain in which Shank3 mutation leads to the autistic phenotypes are understudied. The hypothalamus is associated with stereotypic behavior and sociability. p38α, a mediator of inflammatory responses in the brain, has been postulated as a potential gene for certain cases of autism occurrence. However, it is unclear whether hypothalamus and p38α are involved in the development of autism caused by Shank3 mutations or deficiency. Methods Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and immunoblotting were used to assess alternated signaling pathways in the hypothalamus of Shank3 knockout (Shank3 −/− ) mice. Home-Cage real-time monitoring test was performed to record stereotypic behavior and three-chamber test was used to monitor the sociability of mice. Adeno-associated viruses 9 (AAV9) were used to express p38α in the arcuate nucleus (ARC) or agouti-related peptide (AgRP) neurons. D176A and F327S mutations expressed constitutively active p38α. T180A and Y182F mutations expressed inactive p38α. Results We found that Shank3 controls stereotypic behavior and sociability by regulating p38α activity in AgRP neurons. Phosphorylated p38 level in hypothalamus is significantly enhanced in Shank3 −/− mice. Consistently, overexpression of p38α in ARC or AgRP neurons elicits excessive stereotypic behavior and impairs sociability in wild-type (WT) mice. Notably, activated p38α in AgRP neurons increases stereotypic behavior and impairs sociability. Conversely, inactivated p38α in AgRP neurons significantly ameliorates autistic behaviors of Shank3 −/− mice. In contrast, activated p38α in pro-opiomelanocortin (POMC) neurons does not affect stereotypic behavior and sociability in mice. Limitations We demonstrated that SHANK3 regulates the phosphorylated p38 level in the hypothalamus and inactivated p38α in AgRP neurons significantly ameliorates autistic behaviors of Shank3 −/− mice. However, we did not clarify the biochemical mechanism of SHANK3 inhibiting p38α in AgRP neurons. Conclusions These results demonstrate that the Shank3 deficiency caused autistic-like behaviors by activating p38α signaling in AgRP neurons, suggesting that p38α signaling in AgRP neurons is a potential therapeutic target for Shank3 mutant-related autism.

Background/Objectives: Since its emergence in 2019, the rapid spread of SARS-CoV-2 led to the global pandemic. Recent large-scale dengue fever outbreaks overlapped with the COVID-19 pandemic, leading to increased cases of co-infection and posing severe public health risks. Accordingly, the development of effective combined SARS-CoV-2 and dengue virus (DENV) vaccines is necessary to control the spread and prevalence of both viruses. Methods: In this study, we designed Sindbis virus (SINV) replicon-based SARS-CoV-2 and DENV chimeric vaccines using two delivery strategies: DNA-launched self-replicating RNA replicon (DREP) and viral replicon particle (VRP) systems. Results: Cellular and animal experiments confirmed that the vaccines effectively produced viral proteins and elicited strong immunogenicity. These vaccines induced robust immune responses and neutralizing activity against live SARS-CoV-2, DENV1, and DENV2 viruses. In addition, passively transferred sera from BALB/c mice immunized with these vaccines into AG129 mice provided significant protection against lethal DENV2 challenge. The transferred sera protected the mice from physical symptoms, reduced viral loads in the kidney, spleen, liver, and intestine, and prevented DENV2-induced vascular leakage in these tissues. Conclusions: Therefore, combined vaccines based on the SINV replicon system are promising candidates for pandemic control. These results lay a foundation for further development of a safe and effective combination vaccine against SARS-CoV-2 and DENV.

ObjectiveTo evaluate the clinical efficacy of different androgen deprivation therapies for prostate cancer (PCa) based on dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI).Methods104 patients with PCa were studied, all of whom were treated with androgen deprivation therapy. The patients were divided into a continuous group (continuous androgen deprivation therapy) and an intermittent group (intermittent androgen deprivation therapy) by random number table method, 52 cases/group. The therapeutic effect and DCE-MRI indices were compared and the relationship between DCE-MRI indices and clinical efficacy and the evaluation value of therapeutic efficacy were analyzed.ResultsThe objective response rate (ORR) of the intermittent group was higher than that of the continuous group (p < 0.05), and there was no significant difference in disease control rate (DCR) between the two groups (p > 0.05). After treatment, volume transfer coefficient (Ktrans), reverse transfer constant (Kep), volume fraction (Ve), blood volume (BV), and blood flow (BF) in both groups were lowered, and those in the intermittent group were lower than the continuous group (p < 0.05). Ktrans, Kep, Ve, BF, and BV in the ORR group were lower than those in the non-ORR group (p < 0.05). Ktrans, Kep, Ve, BF, and BV were correlated with the therapeutic effect of PCa (p < 0.05). The AUC value of the combined detection of DCE-MRI indices in evaluating the therapeutic effect of PCa was greater than that of each index alone (p < 0.05).ConclusionCompared with continuous androgen deprivation therapy, intermittent androgen deprivation therapy has better clinical efficacy in the treatment of PCa, and DCE-MRI indices are related to the treatment efficacy of PCa and have an evaluation value.

BackgroundDysregulation of feeding behavior leads to a variety of pathological manifestations ranging from obesity to anorexia. The foraging behavior of animals affected by food deficiency is not fully understood.MethodsHome-Cage system was used to monitor the behaviors. Immunohistochemical staining was used to monitor the trend of neuronal activity. Chemogenetic approach was used to modify neuronal activity.ResultsWe described here a unique mouse model of foraging behavior and unveiled that food deprivation significantly increases the general activities of mice with a daily rhythmic pattern, particularly foraging behavior. The increased foraging behavior is potentiated by food cues (mouthfeel, odor, size, and shape) and energy deficit, rather than macronutrient protein, carbohydrate, and fat. Notably, energy deficiency increases nocturnal neuronal activity in paraventricular hypothalamic nucleus (PVH), accompanying a similar change in rhythmic foraging behavior. Activating neuronal activity in PVH enhances the amplitude of foraging behavior in mice. Conversely, inactivating neuronal activity in PVH decreases the amplitude of foraging behavior and impairs the rhythm of foraging behavior.DiscussionThese results illustrate that energy status and food cues regulate the rhythmic foraging behavior via PVH neuronal activity. Understanding foraging behavior provides insights into the underlying mechanism of eating-related disorders.

BackgroundStroke is the second leading cause of death worldwide and a major cause of long-term neurological disability, imposing an enormous financial burden on families and society. This study aimed to identify the predictors in stroke patients and construct a nomogram prediction model based on these predictors.MethodsThis retrospective study included 11,435 participants aged >20 years who were selected from the NHANES 2011–2018. Randomly selected subjects (n = 8531; 75%) and the remaining subjects comprised the development and validation groups, respectively. The least absolute shrinkage and selection operator (LASSO) binomial and logistic regression models were used to select the optimal predictive variables. The stroke probability was calculated using a predictor-based nomogram. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 1000 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram.ResultsAccording to the minimum criteria of non-zero coefficients of Lasso and logistic regression screening, older age, lower education level, lower family income, hypertension, depression status, diabetes, heavy smoking, heavy drinking, trouble sleeping, congestive heart failure (CHF), coronary heart disease (CHD), angina pectoris and myocardial infarction were independently associated with a higher stroke risk. A nomogram model for stroke patient risk was established based on these predictors. The AUC (C statistic) of the nomogram was 0.843 (95% CI: 0.8186–0.8430) in the development group and 0.826 (95% CI: 0.7811, 0.8716) in the validation group. The calibration curves after 1000 bootstraps displayed a good fit between the actual and predicted probabilities in both the development and validation groups. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0–0.2 and 0–0.25, respectively.DiscussionThis study effectively established a nomogram including demographic characteristics, vascular risk factors, emotional factors and lifestyle behaviors to predict stroke risk. This nomogram is helpful for screening high-risk stroke individuals and could assist physicians in making better treatment decisions to reduce stroke occurrence.

BackgroundCancer as a deathly disease with high prevalence has impelled researchers to investigate its causative mechanisms in the search for effective therapeutics. Recently, the concept of phase separation has been introduced to biological science and extended to cancer research, which helps reveal various pathogenic processes that have not been identified before. As a process of soluble biomolecules condensed into solid-like and membraneless structures, phase separation is associated with multiple oncogenic processes. However, there are no bibliometric characteristics for these results. To provide future trends and identify new frontiers in this field, a bibliometric analysis was conducted in this study.MethodsThe Web of Science Core Collection (WoSCC) was used to search for literature on phase separation in cancer from 1/1/2009 to 31/12/2022. After screening the literature, statistical analysis and visualization were carried out by the VOSviewer software (version 1.6.18) and Citespace software (Version 6.1.R6).ResultsA total of 264 publications, covering 413 organizations and 32 countries, were published in 137 journals, with an increasing trend in publication and citation numbers per year. The USA and China were the two countries with the largest number of publications, and the University of Chinese Academy of Sciences was the most active institution based on the number of articles and cooperations. Molecular Cell was the most frequent publisher with high citations and H-index. The most productive authors were Fox AH, De Oliveira GAP, and Tompa P. Overlay, whilst few authors had a strong collaboration with each other. The combined analysis of concurrent and burst keywords revealed that the future research hotspots of phase separation in cancer were related to tumor microenvironments, immunotherapy, prognosis, p53, and cell death.ConclusionPhase separation-related cancer research remained in the hot streak period and exhibited a promising outlook. Although inter-agency collaboration existed, cooperation among research groups was rare, and no author dominated this field at the current stage. Investigating the interfaced effects between phase separation and tumor microenvironments on carcinoma behaviors, and constructing relevant prognoses and therapeutics such as immune infiltration-based prognosis and immunotherapy might be the next research trend in the study of phase separation and cancer.

Osteoarthritis (OA) is one of the most prevalent musculoskeletal disorders globally, and treating OA remains a significant challenge. Currently, pharmacological treatments primarily aim to alleviate the OA symptoms associated with inflammation and pain, and no disease-modifying therapies are available to delay OA development and progression. Reactive oxygen species (ROS) play an essential role in OA development and progression, which are a promising target for curing OA. In this study, it was found that photothermal properties of near-infrared (NIR) irradiation enhanced the ROS scavenging activity of molybdenum-based polyoxometalate (POM) nanoclusters. Because of enhanced ROS scavenging, NIR-responsive POM nanoclusters were developed as novel excellent nano-antioxidants for OA protection. The results demonstrated that NIR-responsive POM exhibited outstanding antioxidant activity and superexcellent anti-inflammatory effects, which could effectively alleviate the clinical symptoms of OA mice, diminish inflammatory cytokines, reduce catabolic proteases, and mitigate the progression of OA. Meanwhile, the local treatment had no side effects on normal tissues. Thus, this study pioneered the application of POM for alleviating OA with expected safety and efficiency.

Abstract Platelets may serve as a perfect peripheral source for exploring diagnostic biomarkers for Alzheimer's disease (AD); however, the molecular linkage between platelet and the brain is missing. To find the common altered and driving molecules in both brain and the platelet, we performed an integrated analysis of our platelet omics and brain omics reported in the literature, and analyzed their correlations with AD‐specific pathology and cognitive impairment. By integrating the gene and protein expression profiles from 269 AD patients, we deduced 239 differentially expressed proteins (DEPs) appeared in both brain and the platelet, and 70.3% of them had consistent changes. Further analysis demonstrated that the altered brain and peripheral regulations were pinpointed into 10 imbalanced pathways. We also found that 117 DEPs, including ADAM10, were closely associated to the AD‐specific β‐amyloid and tau pathologies; and the changes of IDH3B and RTN1 had a potential diagnostic value for cognitive impairment analyzed by machine learning. Finally, we identified that HMOX2 and SERPINA3 could serve as driving molecules in neurodegeneration, and they were increased and decreased in AD patients, respectively. Together, this integrated brain and platelet omics provides a valuable resource for establishing efficient peripheral diagnostic biomarkers and potential therapeutic targets for AD.

Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and thus identifying who among the increasing T2DM populations may develop into AD is important for early intervention. By using TMT-labeling coupled high-throughput mass spectrometry, we conducted a comprehensive plasma proteomic analysis in none-T2DM people (Ctrl, n = 30), and the age-/sex-matched T2DM patients with mild cognitive impairment (T2DM-MCI, n = 30) or T2DM without MCI (T2DM-nMCI, n = 25). The candidate biomarkers identified by proteomics and bioinformatics analyses were verified by ELISA, and their diagnostic capabilities were evaluated with machine learning. A total of 53 differentially expressed proteins (DEPs) were identified in T2DM-MCI compared with T2DM-nMCI patients. These DEPs were significantly enriched in multiple biological processes, such as amyloid neuropathies, CNS disorders, and metabolic acidosis. Among the DEPs, alpha-1-antitrypsin (SERPINA1), major viral protein (PRNP), and valosin-containing protein (VCP) showed strong correlation with AD high-risk genes APP, MAPT, APOE, PSEN1, and PSEN2. Also, the levels of PP2A cancer inhibitor (CIP2A), PRNP, corticotropin-releasing factor-binding protein (CRHBP) were significantly increased, while the level of VCP was decreased in T2DM-MCI patients compared with that of the T2DM-nMCI, and these changes were correlated with the Mini-Mental State Examination (MMSE) score. Further machine learning data showed that increases in PRNP, CRHBP, VCP, and rGSK-3β(T/S9) (ratio of total to serine-9-phosphorylated glycogen synthase kinase-3β) had the greatest power to identify mild cognitive decline in T2DM patients.

BackgroundAlthough non-motor symptoms of Parkinson’s disease (PD) are serious, effective treatments are still lacking. Acupuncture may have clinical benefits for non-motor symptoms of PD patients, but high-quality evidence supporting this possibility is still limited. Hence, we conducted this meta-analysis to evaluate the effect of acupuncture treatment on non-motor symptoms in patients with PD.MethodsRandomized controlled trials (RCTs) of acupuncture treatment for PD were retrieved from the following electronic databases: Medline (OVID), Embase (OVID), Cochrane Library, Web of Science, China National Knowledge Infrastructure, Chinese BioMedical Literature Database, Chonqing VIP (CQVIP), and Wangfang database. Studies evaluating non-motor symptoms of PD were retrieved. Methodological quality was assessed using the Cochrane Handbook for Systematic Reviews of Interventions.ResultsA total of 27 RCTs were included, among which 8 outcomes related to non-motor symptoms were evaluated. The results showed that acupuncture combined with medication had benefits for PD-related insomnia relative to medication alone or sham acupuncture [standardized mean difference (SMD) = 0.517; 95% confidence interval (CI) = 0.242–0.793; p = 0.000], and acupuncture treatment had benefits at 8 weeks (SMD = 0.519; 95% CI = 0.181–0.857; p = 0.003). Regarding depression, acupuncture treatment was more effective (SMD = −0.353; 95% CI = −0.669 to −0.037; p = 0.029) within 2 months (SMD = −0.671; 95% CI = −1.332 to −0.011; p = 0.046). Regarding cognition, quality of life, and Unified Parkinson’s Disease Rating Scale (UPDRS) I and II scores, acupuncture treatment was effective [SMD = 0.878, 95% CI = 0.046–1.711, p = 0.039; SMD = −0.690, 95% CI = −1.226 to −0.155, p = 0.011; weighted mean difference (WMD) = −1.536, 95% CI = −2.201 to −0.871, p = 0.000; WMD = −2.071, 95% CI = −3.792 to −0.351, p = 0.018; respectively]. A significant difference was not found in terms of PD-related constipation. Only one study evaluated PD-related fatigue.ConclusionThe results of the analysis suggested that acupuncture treatment could ameliorate the symptoms of depression, quality of life, cognition, total mentation, behavior and mood, and activities of daily living in PD patients. Nevertheless, more prospective, well-designed RCTs with larger sample sizes are required to confirm our findings.

The Mediterranean diet (MED), a dietary pattern rich in fruits and vegetables, whole grains, legumes, nuts, fish, and olive oil, has anti-oxidative and anti-inflammatory effects. Although some data suggest that MED adherence is associated with decreased manifestation of depressive symptoms, it remains necessary to further analyze this apparent non-linear association as well as the influence of different factors on the relationship between MED and depression. Here, we investigated associations between the alternate MED (aMED) score and depressive symptom via multivariate logistic regression, weighted generalized additive (GAM) and two-step linear regression models, analyzing data from the 2005–2018 National Health and Nutrition Examination Survey (NHANES). The most important factor relevant to aMED score that contributed to the prevalence of depressive symptom was assessed using random forest. Furthermore, we examined whether the relationship between aMED score and depressive symptom differs by age, race, sex, socioeconomic variables, lifestyle- and health-related variables, and chronic medical conditions, via subgroup analyses. A total of 19,477 participants (20–80 years of age) were included in this cross-sectional study. In crude and adjusted (1–5) multivariate logistic regression models, increased aMED score was noted to associate with non-depressive status, as defined using the Patient Health Questionnaire-9 (P < 0.05). Data analyses via GAM and two-piecewise linear regression revealed a non-linear association between aMED and depressive symptom, which had an inflection point of 3. Random forest results revealed that vegetable score contributes greatest to the relationship between aMED and depressive symptom. Subgroup analyses revealed that aMED score is significantly negatively related with depressive symptom in most different populations (P < 0.05) with the exception of high annual income, diabetes, borderline blood glucose level and Parkinson's disease (PD) (P > 0.05). In conclusion, we observed a non-linear association between aMED score and depressive symptom. Further studies are needed to validate our results.

Abstract Imbalance of macrophage polarization plays an indispensable role in acute lung injury (ALI), which is considered as a promising target. Matrix metalloproteinase-9 (MMP-9) is expressed in the macrophage, and has a pivotal role in secreting inflammatory cytokines. We reported that saquinavir (SQV), a first-generation human immunodeficiency virus-protease inhibitor, restricted exaggerated inflammatory response. However, whether MMP-9 could regulate macrophage polarization and inhibit by SQV is still unknown. We focused on the important role of macrophage polarization in CLP (cecal ligation puncture)-mediated ALI and determined the ability of SQV to maintain M2 over M1 phenotype partially through the inhibition of MMP-9. We also performed a limited clinical study to determine if MMP-9 is a biomarker of sepsis. Lipopolysaccharide (LPS) increased MMP-9 expression and recombinant MMP-9 (rMMP-9) exacerbated LPS-mediated M1 switching. Small interfering RNA to MMP-9 inhibited LPS-mediated M1 phenotype and SQV inhibition of this switching was reversed with rMMP-9, suggesting an important role for MMP-9 in mediating LPS-induced M1 phenotype. MMP-9 messenger RNA levels in peripheral blood mononuclear cells of these 14 patients correlated with their clinical assessment. There was a significant dose-dependent decrease in mortality and ALI after CLP with SQV. SQV significantly inhibited LPS-mediated M1 phenotype and increased M2 phenotype in cultured RAW 264.7 and primary murine bone marrow-derived macrophages as well as lung macrophages from CLP-treated mice. This study supports an important role for MMP-9 in macrophage phenotypic switching and suggests that SQV-mediated inhibition of MMP-9 may be involved in suppressing ALI during systemic sepsis.

Summary: Background: Glycogen synthase kinase-3β (GSK-3β) is one of the most effective kinases in promoting tau hyperphosphorylation and accumulation in Alzheimer's disease (AD). However, it is not clear how GSK-3β activity is regulated during AD progression. Methods: We firstly used mass spectrometry to identify the acetylation site of GSK-3β, and then established the cell and animal models of GSK-3β acetylation. Next, we conducted molecular, cell biological and behavioral tests. Finally, we designed a peptide to test whether blocking tau-mediated GSK-3β acetylation could be beneficial to AD. Findings: We found that GSK-3β protein levels increased in the brains of AD patients and the transgenic mice. Overexpressing tau increased GSK-3β protein level with increased acetylation and decreased ubiquitination-related proteolysis. Tau could directly acetylate GSK-3β at K15 both in vitro and in vivo. K15-acetylation inhibited ubiquitination-associated proteolysis of GSK-3β and changed its activity-dependent phosphorylation, leading to over-activation of the kinase. GSK-3β activation by K15-acetylation in turn exacerbated the AD-like pathologies. Importantly, competitively inhibiting GSK-3β K15-acetylation by a novel-designed peptide remarkably improved cognitive impairment and the AD-like pathologies in 3xTg-AD mice. Interpretation: Tau can directly acetylate GSK-3β at K15 which reveals a vicious cycle between tau hyperphosphorylation and GSK-3β activation. Funding: This study was supported in parts by grants from Science and Technology Committee of China (2016YFC1305800), Hubei Province (2018ACA142), Natural Science Foundation of China (91949205, 82001134, 31730035, 81721005), Guangdong Provincial Key S&T Program (018B030336001).

Introduction: Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and populations with mild cognitive impairment (MCI) have high incidence to suffer from AD. Therefore, discerning who may be more vulnerable to MCI, among the increasing T2DM populations, is important for early intervention and eventually decreasing the prevalence rate of AD. This study was to explore whether the change of plasma β-amyloid (Aβ) could be a biomarker to distinguish MCI (T2DM-MCI) from non-MCI (T2DM-nMCI) in T2DM patients.Methods: Eight hundred fifty-two T2DM patients collected from five medical centers were assigned randomly to training and validation cohorts. Plasma Aβ, platelet glycogen synthase kinase-3β (GSK-3β), apolipoprotein E (ApoE) genotypes, and olfactory and cognitive functions were measured by ELISA, dot blot, RT-PCR, Connecticut Chemosensory Clinical Research Center (CCCRC) olfactory test based on the diluted butanol, and Minimum Mental State Examination (MMSE) test, respectively, and multivariate logistic regression analyses were applied.Results: Elevation of plasma Aβ1-42/Aβ1-40 is an independent risk factor of MCI in T2DM patients. Although using Aβ1-42/Aβ1-40 alone only reached an AUC of 0.631 for MCI diagnosis, addition of the elevated Aβ1-42/Aβ1-40 to our previous model (i.e., activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging) significantly increased the discriminating efficiency of T2DM-MCI from T2DM-nMCI, with an AUC of 0.846 (95% CI: 0.794–0.897) to 0.869 (95% CI: 0.822–0.916) in the training cohort and an AUC of 0.848 (95% CI: 0.815–0.882) to 0.867 (95% CI: 0.835–0.899) in the validation cohort, respectively.Conclusion: A combination of the elevated plasma Aβ1-42/Aβ1-40 with activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging could efficiently diagnose MCI in T2DM patients. Further longitudinal studies may consummate the model for early prediction of AD.

Abstract Background Building brain reserves before dementia onset could represent a promising strategy to prevent Alzheimer’s disease (AD), while how to initiate early cognitive stimulation is unclear. Given that the immature brain is more sensitive to environmental stimuli and that brain dynamics decrease with ageing, we reasoned that it would be effective to initiate cognitive stimulation against AD as early as the fetal period. Methods After conception, maternal AD transgenic mice (3 × Tg AD) were exposed to gestational environment enrichment (GEE) until the day of delivery. The cognitive capacity of the offspring was assessed by the Morris water maze and contextual fear-conditioning tests when the offspring were raised in a standard environment to 7 months of age. Western blotting, immunohistochemistry, real-time PCR, immunoprecipitation, chromatin immunoprecipitation (ChIP) assay, electrophysiology, Golgi staining, activity assays and sandwich ELISA were employed to gain insight into the mechanisms underlying the beneficial effects of GEE on embryos and 7–10-month-old adult offspring. Results We found that GEE markedly preserved synaptic plasticity and memory capacity with amelioration of hallmark pathologies in 7–10-m-old AD offspring. The beneficial effects of GEE were accompanied by global histone hyperacetylation, including those at bdnf promoter-binding regions, with robust BDNF mRNA and protein expression in both embryo and progeny hippocampus. GEE increased insulin-like growth factor 1 (IGF1) and activated its receptor (IGF1R), which phosphorylates Ca2+/calmodulin-dependent kinase IV (CaMKIV) at tyrosine sites and triggers its nuclear translocation, subsequently upregulating histone acetyltransferase (HAT) and BDNF transcription. The upregulation of IGF1 mimicked the effects of GEE, while IGF1R or HAT inhibition during pregnancy abolished the GEE-induced CaMKIV-dependent histone hyperacetylation and BDNF upregulation. Conclusions These findings suggest that activation of IGF1R/CaMKIV/HAT/BDNF signaling by gestational environment enrichment may serve as a promising strategy to delay AD progression.

The motion information of blades is a key reflection of the operation state of an entire wind turbine unit. However, the special structure and operation characteristics of rotating blades have become critical obstacles for existing contact vibration monitoring technologies. Digital image correlation performs powerfully in non-contact, full-field measurements, and has increasingly become a popular method for solving the problem of rotating blade monitoring. Aiming at the problem of large-scale rotation matching for blades, this paper proposes a modified speeded-up robust features (SURF)-enhanced digital image correlation algorithm to extract the full-field deformation of blades. Combining an angle compensation (AC) strategy, the AC-SURF algorithm is developed to estimate the rotation angle. Then, an iterative process is presented to calculate the accurate rotation displacement. Subsequently, with reference to the initial state of rotation, the relative strain distribution caused by flaws is determined. Finally, the sensitivity of the strain is validated by comparing the three damage indicators including unbalanced rotational displacement, frequency change, and surface strain field. The performance of the proposed algorithm is verified by laboratory tests of blade damage detection and wind turbine model deformation monitoring. The study demonstrated that the proposed method provides an effective and robust solution for the operation status monitoring and damage detection of wind turbine blades. Furthermore, the strain-based damage detection algorithm is more advantageous in identifying cracks on rotating blades than one based on fluctuated displacement or frequency change.

Abstract Pyranose oxidase (POx) is a homotetrameric flavoprotein that catalyzes the oxidation of pyranose-configured sugars at position C-2 to corresponding 2-ketoaldoses. The wide substrate specificity makes POx potential for application in various biotechnological industries. In the present study we reported the gene cloning and heterologous expression of a POx from the basidiomycete Trametes sp. and functionally expressed the gene in Escherichia coli BL21(DE3). Based on sequence alignment, three residues were chosen for site-directed mutagenesis to obtain two single mutants (K312E and E539K) and two double mutants (T166A/E539K and K312E/E539K). In comparison to the wild-type, K312E shifted its optimal pH to 5.5 while the optimal temperature of E539K and K312E/E539K increased by 10 °C. The mutants retained more activities over broader pH ranges and higher temperatures and catalyzed d-glucose at higher efficiency (5800‒12,667 M−1 s−1 for the mutants versus 5083 M−1 s−1 for the wild-type). The recombinant POx and its mutants were all useful in gluten agglomeration and enlarging the loaf volume, which depends on the amounts of enzymes added. Interestingly, adding the same amount (0.5 nkat/g of flour) of wild-type and mutant enzymes differed in the change of loaf volumes, pinpointing that the catalytic activity is not the sole determinant in applying POx in breadmaking.

Abstract Increasing evidence suggests that glycogen synthase kinase-3β (GSK-3β) plays a crucial role in neurodegenerative/psychiatric disorders, while pan-neural knockout of GSK-3β also shows detrimental effects. Currently, the function of GSK-3β in specific type of neurons is elusive. Here, we infused AAV-CaMKII-Cre-2A-eGFP into GSK-3βlox/lox mice to selectively delete the kinase in excitatory neurons of hippocampal dentate gyrus (DG), and studied the effects on cognitive/psychiatric behaviors and the molecular mechanisms. We found that mice with GSK-3β deletion in DG excitatory neurons displayed spatial and fear memory defects with an anti-anxiety behavior. Further studies demonstrated that GSK-3β deletion in DG subset inhibited hippocampal synaptic transmission and reduced levels of GluN1, GluN2A and GluN2B (NMDAR subunits), GluA1 (AMPAR subunit), PSD93 and drebrin (postsynaptic structural proteins), and synaptophysin (presynaptic protein). GSK-3β deletion also suppressed the activity-dependent neural activation and calcium/calmodulin-dependent protein kinase II (CaMKII)/CaMKIV-cAMP response element binding protein (CREB) signaling. Our data suggest that GSK-3β in hippocampal DG excitatory neurons is essential for maintaining synaptic plasticity and memory.

Abstract Intracellular accumulation of abnormally phosphorylated tau in different types of neurons is a pathological characteristic of Alzheimer’s disease (AD). While tau modification and associated neuronal loss and hypometabolism start in the entorhinal cortex (EC) in early AD patients, the mechanism by which mutant P301L hTau leads to dementia is not fully elucidated. Here, we studied the effects of P301L hTau transduction in the medial EC (MEC) of mice on tau phosphorylation and accumulation, and cognitive deficit. We found that the exogenous mutant tau protein was restricted in MEC without spreading to other brain regions at one month after transduction. Interestingly, expression of the mutant tau in MEC induces endogenous tau hyperphosphorylation and accumulation in hippocampus and cortex, and inhibits neuronal activity with attenuated PP-DG synapse plasticity, leading to hippocampus-dependent memory deficit with intact olfactory function. These findings suggest a novel neuropathological mechanism of early AD, which is initiated by tau accumulation in MEC, and demonstrate a tau pathological model of early stage AD.

Digital image correlation (DIC) for displacement and strain measurement has flourished in recent years. There are integer pixel and subpixel matching steps to extract displacement from a series of images in the DIC approach, and identification accuracy mainly depends on the latter step. A subpixel displacement matching method, named the double-precision gradient-based algorithm (DPG), is proposed in this study. After, the integer pixel displacement is identified using the coarse-fine search algorithm. In order to improve the accuracy and anti-noise capability in the subpixel extraction step, the traditional gradient-based method is used to analyze the data on the speckle patterns using the computer, and the influence of noise is considered. These two nearest integer pixels in one direction are both utilized as an interpolation center. Then, two subpixel displacements are extracted by the five-point bicubic spline interpolation algorithm using these two interpolation centers. A novel combination coefficient considering contaminated noises is presented to merge these two subpixel displacements to obtain the final identification displacement. Results from a simulated speckle pattern and a painted beam bending test show that the accuracy of the proposed method can be improved by four times that of the traditional gradient-based method that reaches the same high accuracy as the Newton–Raphson method. The accuracy of the proposed method efficiently reaches at 92.67%, higher than the Newton-Raphon method, and it has better anti-noise performance and stability.

In this study, the complete sequence of the mitochondrial DNA (mtDNA) of Ctenolepisma villosa was obtained using next-generation sequencing approaches and de novo assembly. The molecule was found to be 15,488 bp in length. It is the fourth complete mt genome sequence from the Zygentoma. The mt genomes are circular and encode 37 genes and a large non-coding region. The overall structure (gene number, orientation, and order) of the mt genomes is the same as that found in three other sequenced species. All protein-coding sequences except cox1 start with the typical ATN codon. Cox1 begins with TTG, which may be a common codon in Zygentoma insects. Stem-loop structure can be observed in the largest non-coding region thought to be involved in the regulation of replication and transcription of the mitochondrial genome.

With only one piece of the power-spectrum pattern, the single-shot coherent power-spectrum imaging can provide a clear object image for real-time applications even if the object is hidden by opaque scattering media, in which the feedback coefficient β value for the reconstruction with least retrievals and fastest speed has to be pre-estimated through time-consuming iterative loops. Here we report a method for estimating the optimal β value from the captured raw power-spectrum images adaptively to optimize the single-shot coherent power-spectrum imaging for practical exposure conditions. The results demonstrate that, based on exposure level analysis of the captured raw power-spectrum images even of underexposure, moderate exposure, and overexposure cases, the β value could be quickly determined with a compact expression for the algorithm to achieve clear reconstruction output efficiently. The proposed method helps to push ahead of the coherent diffractive imaging devices for real-time imaging through turbid mediums in Artificial Intelligence (AI), driving assistance, and flight assistance applications.

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Abstract Mitochondria serve as the cellular powerhouse, and their distinct DNA makes them a prospective target for gene editing to treat genetic disorders. However, the impact of genome editing on mitochondrial DNA (mtDNA) stability remains a mystery. Our study reveals previously unknown risks of genome editing that both nuclear and mitochondrial editing cause discernible transfer of mitochondrial DNA segments into the nuclear genome in various cell types including human cell lines, primary T cells, and mouse embryos. Furthermore, drug-induced mitochondrial stresses and mtDNA breaks exacerbate this transfer of mtDNA into the nuclear genome. Notably, we observe that mitochondrial editors, including mitoTALEN and recently developed base editor DdCBE, can also enhance crosstalk between mtDNA and the nuclear genome. Moreover, we provide a practical solution by co-expressing TREX1 or TREX2 exonucleases during DdCBE editing. These findings imply genome instability of mitochondria during induced DNA breaks and explain the origins of mitochondrial-nuclear DNA segments.

PurposeEpidemiological studies have demonstrated the clinical link between Hunner interstitial cystitis (HIC) and autoimmune diseases (ADs), suggesting potential shared genetic bases for their comorbidity. We aimed to investigate the shared genetic architecture and causal relationships between HIC and ADs.MethodsWe conducted a genome-wide cross-trait study with ~170000 individuals of East Asian ancestry to investigate the shared architecture between HIC and ADs. Bidirectional Mendelian randomization (MR) was used to assess potential causal relationships and a multi-trait analysis of GWAS (MTAG) was conducted to identify their associated pleiotropic loci. Fine-mapping analysis narrowed candidate gene susceptibility loci and colocalization analysis was performed to identify shared variants at specific locus. Lastly, transcriptome-wide association (TWAS) and functional analysis were utilized to explore potential shared gene-tissue associations.ResultsThrough bidirectional MR analysis, we observed a positive causal effect of AIH(ORIVW=1.09, PIVW=1.00×10-3) and RA (ORIVW=1.47, PIVW

Biaxial rotary tillage in dryland (DBRT) can complete biaxial rotary tillage with straw incorporation, secondary suppression, and ditching, and it has been previously studied in direct-seeded rice and wheat. However, the effects of DBRT on the mechanically transplanted rice yield and greenhouse gas emissions remain unclear. To evaluate the effects of DBRT on improving the food security of mechanically transplanted rice and reducing the greenhouse gas emissions, we conducted an experiment for two years with wheat straw incorporation. Three tillage methods were set up: DBRT, uniaxial rotary tillage in dryland and paddy (DPURT), and uniaxial rotary tillage in paddy (PURT). The results showed that compared with DPURT and PURT, DBRT increased the yield of machine-transplanted rice by 7.5–11.0% and 13.3–26.7%, respectively, while the seasonal cumulative CH4 emissions were reduced by 13.9–21.2% and 30.2–37.0%, respectively, and the seasonal cumulative N2O emissions were increased by 13.5–28.6% and 50.0–73.1%, respectively. Consequently, DBRT reduced the global warming potential by 10.7–15.5% and 23.7–28.6%, respectively, and the yield-scaled global warming potential by 18.2–21.8% and 36.4–39.3%, respectively, compared to DPURT and PURT. These results were mainly related to the fact that DBRT significantly reduced soil bulk density and increased soil redox potential (Eh). Therefore, implementing DBRT in machine-transplanted rice fields is feasible, which cannot only increase the rice yield, but also reduce the greenhouse gas emissions.

Abstract Crack formation is a common phenomenon in engineering structures, which can cause serious damage to the safety and health of these structures. An important method of ensuring the safety and health of engineered structures is the prompt detection of cracks. Image threshold segmentation based on machine vision is a crucial technology for crack detection. Threshold segmentation can separate the crack area from the background, providing convenience for more accurate measurement and evaluation of the crack condition and location. The segmentation of cracks in complex scenes is a challenging task, and this goal can be achieved by means of multilevel thresholding. The arithmetic-geometric divergence combines the advantages of the arithmetic mean and the geometric mean in probability measures, enabling a more precise capture of the local features of an image in image processing. In this paper, a multilevel thresholding method for crack image segmentation based on the minimum arithmetic-geometric divergence is proposed. To address the issue of time complexity in multilevel thresholding, an enhanced particle swarm optimization algorithm with local stochastic perturbation is proposed. In crack detection, the thresholding criterion function based on the minimum arithmetic-geometric divergence can adaptively determine the thresholds according to the distribution characteristics of pixel values in the image. The proposed enhanced particle swarm optimization algorithm can increase the diversity of candidate solutions and enhance the global convergence performance of the algorithm. The proposed method for crack image segmentation is compared with seven state-of-the-art multilevel thresholding methods based on several metrics, including RMSE, PSNR, SSIM, FSIM, and computation time. The experimental results show that the proposed method outperforms several competing methods in terms of these metrics.