Synaptic vesicle glycoprotein 2 A in serum is an ideal biomarker for early diagnosis of Alzheimer's disease.

BACKGROUND: Previous studies have demonstrated that early intervention was the best plan to inhibit the progression of Alzheimer's disease (AD), which relied on the discovery of early diagnostic biomarkers. In this study, synaptic vesicle glycoprotein 2 A (SV2A) was examined to improve the early diagnostic efficiency in AD. METHODS: In this study, biomarker testing was performed through the single-molecule array (Simoa). A total of 121 subjects including cognitively unimpaired controls, amnestic mild cognitive impairment (aMCI), AD and other types of dementia underwent cerebrospinal fluid (CSF) SV2A testing; 430 subjects including health controls, aMCI, AD and other types of dementia underwent serum SV2A, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL) and p-tau217 testing; 92 subjects including aMCI and AD underwent both CSF SV2A and serum SV2A testing; 115 cognitively unimpaired subjects including APOE ε4 carriers and APOE ε4 non-carriers were tested for serum SV2A, GFAP, NfL and p-tau217. Then, the efficacy of SV2A for the early diagnosis of AD and its ability to identify those at high risk of AD from a cognitively unimpaired population were further analyzed. RESULTS: Both CSF and serum SV2A significantly and positively correlated with cognitive performance in patients with AD, and their levels gradually decreased with the progression of AD. Serum SV2A demonstrated excellent diagnostic efficacy for aMCI, with a sensitivity of 97.8%, which was significantly higher than those of NfL, GFAP, and p-tau217. The SV2A-positive rates ranged from 92.86 to 100% in aMCI cases that were negative for the above three biomarkers. Importantly, of all the biomarkers tested, serum SV2A had the highest positivity rate (81.82%) in individuals at risk for AD. CONCLUSIONS: Serum SV2A was demonstrated to be a novel and ideal biomarker for the early diagnosis of AD, which can effectively distinguish those at high risk of AD in cognitively unimpaired populations.

Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau.

The vertical structural complexity (VSC) of plant communities reflects the occupancy of spatial niches and is closely related to resource utilization and environmental adaptation. However, understanding the large-scale spatial pattern of VSC and its underlying mechanisms remains limited. Here, we systematically investigate 2013 plant communities through grid sampling on the Tibetan Plateau. VSC is quantified as the maximum plant height within a plot (Height-max), coefficient of variation of plant height (Height-var), and Shannon evenness of plant height (Height-even). Precipitation dominates the spatial variation in VSC in forests and shrublands, supporting the classic physiological tolerance hypothesis. In contrast, for alpine meadows, steppes, and desert grasslands in extreme environments, non-resource limiting factors (e.g., wide diurnal temperature ranges and strong winds) dominate VSC variation. Generally, with the shifting of climate from favorable to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors gradually increases, and that the physiological tolerance hypothesis only applicable in favorable conditions. With the help of machine learning models, maps of VSC at 1-km resolution are produced for the Tibetan Plateau. Our findings and maps of VSC provide insights into macroecological studies, especially for adaptation mechanisms and model optimization.

Effect of Aggregation Structure on Capacitive Energy Storage in Conducting Polymer Films.

Conducting polymers (CPs), a significant class of electrochemical capacitor electrode materials, exhibit exceptional capacitive energy storage performance in aqueous electrolytes. Current research primarily concentrates on enhancing the electrical conductivity and capacitive performance of CPs via molecular design and structural control. However, the absence of a comprehensive understanding of the impact of molecular chain spatial order on ion/electron transport and capacitive performance impedes the development and optimization of advanced electrode materials. Here, a solvent treatment strategy is employed to modulate the molecular chain spatial order of PEDOT:PSS films. The results of electrochemical performance tests and Grazing Incidence Wide Angle X-ray Scattering (GIWAXS) show that PEDOT:PSS films with both face-on and edge-on orientations exhibit exceptional electronic conductivity and ion diffusion efficiency, with capacitive performance 1.33 times higher than that of PEDOT:PSS films with only edge-on orientation. Consequently, molecular chain orientations conducive to charge transport not only enhance inter-chain coupling, but also effectively reduce ion transport resistance, enabling efficient capacitive energy storage. This research provides novel insights for the design and development of higher performance CPs-based electrode materials.

DPP: deep phase prior for parallel imaging with wave encoding.

Objective.In Magnetic Resonance (MR) parallel imaging with virtual channel-expanded Wave encoding, limitations are imposed on the ability to comprehensively and accurately characterize the background phase. These limitations are primarily attributed to the calibration process relying solely on center low-frequency Auto-Calibration Signals (ACS) data for calibration.Approach.To tackle the challenge of accurately estimating the background phase in wave encoding, a novel deep neural network model guided by deep phase priors is proposed with integrated virtual conjugate coil (VCC) extension. Concretely, within the proposed framework, the background phase is implicitly characterized by employing a carefully designed decoder convolutional neural network, leveraging the inherent characteristics of phase smoothness and compact support in the transformed domain. Furthermore, the proposed model with wave encoding benefits from additional priors, which incorporate transmission sparsity of the latent image and coil sensitivity smoothness.Main results.Ablation experiments were conducted to ascertain the proposed method's capability to implicitly represent CSM and the background phase. Subsequently, the superiority of the proposed method is demonstrated through confidence comparisons with competing methods, employing 4-fold and 5-fold acceleration experiments. In achieving 4-fold and 5-fold acceleration, the optimal quantitative metrics (PSNR/SSIM/NMSE) are 44.1359 dB/0.9863/0.0008 (4-fold) and 41.2074/0.9846/0.0017 (5-fold), respectively. Furthermore, the generalizability of the proposed method is further validated by conducting acceleration experiments with T1, T2, T2*, and various undersampling patterns. In addition, the DPP delivered much better performance than the conventional methods by exploring accelerated phase-sensitive SWI imaging. In SWI accelerated imaging, it also surpasses the optimal competing method in terms of (PSNR/SSIM/NMSE) with 0.096%/0.009%/0.0017%.Significance.The proposed method enables precise characterization of the background phase in the integrated VCC and wave encoding framework, supported via theoretical analysis and empirical findings. Our code is available at:https://github.com/sober235/DPP.

Research status and challenges of Mycoplasma pneumoniae pneumonia in children: A bibliometric and visualization analysis from 2011 to 2023.

BACKGROUND: Mycoplasma pneumoniae (MP) infections occur in regional outbreaks every 3 to 7 years, lasting up to 2 years. Since this fall, there has been a significant rise in MP infections among children in China, indicating a regional epidemiological trend that imposes an increased national public health burden. To date, bibliometric methods have not been applied to studies on MP infection in children. METHODS: We searched for all relevant English publications on MP pneumonia in children published from 2011 to 2023 using Web of Science. Analytical software tools such as Citespace and VOSviewer were employed to analyze the collected literature. RESULTS: 993 articles on MP pneumonia in children were published in 338 academic journals by 5062 authors affiliated with 1381 institutions across 75 countries/regions. China led in global productivity with 56.19%. Among the top 10 prolific organizations, 8 were Chinese institutions, with Soochow University being the most active, followed by Capital Medical University and Zhejiang University. Zhimin Chen from Zhejiang University School of Medicine exhibited the highest H-index of 32. Keyword co-occurrence network analysis revealed 7 highly relevant clusters. CONCLUSION: The current research hotspots and frontiers in this field are primarily MP pneumonia, refractory MP pneumonia, lactate dehydrogenase, asthma, and biomarker. We anticipate that this work will provide novel insights for advancing scientific exploration and the clinical application of MP pneumonia in children.

Operando Studies of Bismuth Nanoparticles Embedded in N, O-Doped Porous Carbon for High-Performance Potassium-Ion Hybrid Capacitor.

A highly viable alternative to lithium-ion batteries for stationary electrochemical energy-storage systems is the potassium dual-ion hybrid capacitor (PIHC), especially toward fast-charging capability. However, the sluggish reaction kinetics of negative electrode materials seriously impedes their practical implementation. In this paper, a new negative electrode Bi@RPC (Nano-bismuth confined in nitrogen- and oxygen-doped carbon with rationally designed pores, evidenced by advanced characterization) is developed, leading to a remarkable electrochemical performance. PIHCs building with the active carbon YP50F positive electrode result in a high operation voltage (0.1-4 V), and remarkably well-retained energy density at a high-power density (11107 W kg-1 at 98 Wh kg-1 ). After 5000 cycles the proposed PHICs still show a superior capacity retention of 92.6%. Moreover, a reversible mechanism of "absorption-alloying" of the Bi@RPC nanocomposite is revealed by operando synchrotron X-ray diffraction and Raman spectroscopy. With the synergistic potassium ions storage mechanism arising from the presence of well-structured pores and nano-sized bismuth, the Bi@RPC electrode exhibits an astonishingly rapid kinetics and high energy density. The results demonstrate that PIHCs with Bi@RPC-based negative electrode is the promising option for simultaneously high-capacity and fast-charging energy storage devices.

Natural Disinfection-like Process Unveiled in Soil Microenvironments by Enzyme-Catalyzed Chlorination.

Substantial natural chlorination processes are a growing concern in diverse terrestrial ecosystems, occurring through abiotic redox reactions or biological enzymatic reactions. Among these, exoenzymatically mediated chlorination is suggested to be an important pathway for producing organochlorines and converting chloride ions (Cl-) to reactive chlorine species (RCS) in the presence of reactive oxygen species like hydrogen peroxide (H2O2). However, the role of natural enzymatic chlorination in antibacterial activity occurring in soil microenvironments remains unexplored. Here, we conceptualized that heme-containing chloroperoxidase (CPO)-catalyzed chlorination functions as a naturally occurring disinfection process in soils. Combining antimicrobial experiments and microfluidic chip-based fluorescence imaging, we showed that the enzymatic chlorination process exhibited significantly enhanced antibacterial activity against Escherichia coli and Bacillus subtilis compared to H2O2. This enhancement was primarily attributed to in situ-formed RCS. Based on semiquantitative imaging of RCS distribution using a fluorescence probe, the effective distance of this antibacterial effect was estimated to be approximately 2 mm. Ultrahigh-resolution mass spectrometry analysis showed over 97% similarity between chlorine-containing formulas from CPO-catalyzed chlorination and abiotic chlorination (by sodium hypochlorite) of model dissolved organic matter, indicating a natural source of disinfection byproduct analogues. Our findings unveil a novel natural disinfection process in soils mediated by indigenous enzymes, which effectively links chlorine-carbon interactions and reactive species dynamics.

Phenotypic and genomic characteristics of clinical IMP-producing Klebsiella spp. Isolates in China.

BACKGROUND: IMP-producing Klebsiella spp. (IMPKsp) strains have spread globally, including in China. Currently, the prevalence and genomic characterization of IMPKsp is largely unknown nationwide. Here we aimed to provide a general overview of the phenotypic and genomic characteristics of IMPKsp strains. METHODS: 61 IMPKsp strains were obtained from 13 provinces in China during 2016-2021. All strains were tested for their susceptibility to antimicrobial agents by the microdilution broth method and sequenced with Illumina next-generation sequencing. We performed conjugation experiments on thirteen representative strains which were also sequenced by Oxford nanopore sequencing technology to characterize blaIMP-encoding plasmids. RESULTS: We find that all IMPKsp strains display multidrug-resistant (MDR) phenotypes. All strains belong to 27 different STs. ST307 emerges as a principal IMP-producing sublineage. blaIMP-4 is found to be the major isoform, followed by blaIMP-38. Seven incompatibility types of blaIMP-encoding plasmids are identified, including IncHI5 (32/61, 52.5%), IncN-IncR (10/61, 16.4%), IncFIB(K)-HI1B (7/61, 11.5%), IncN (5/61, 8.2%), IncN-IncFII (2/61, 3.3%), IncFII (1/61, 1.6%) and IncP (1/61, 1.6%). The strains carrying IncHI5 and IncN plasmids belong to diverse ST types, indicating that these two plasmids may play an important role in the transmission of blaIMP genes among Klebsiella spp. strains. CONCLUSIONS: Our results highlight that multi-clonal transmission, multiple genetic environments and plasmid types play a major role in the dissemination process of blaIMP genes among Klebsiella spp. IncHI5 type plasmids have the potential to be the main vectors mediating the spread of the blaIMP genes in Klebsiella spp.

Antibiotic resistance occurs when bacteria evolve to withstand antibiotic drugs. We are aware that a bacteria called Klebsiella is rapidly becoming resistant to carbapenems, a class of broad-spectrum antibiotics. In this study, we conducted a genetic and microbiological surveillance study across 13 provinces of China to understand factors that contribute to the growing bacterial drug resistance. We find that the way the multiple bacterial types interact with each other and swap certain genetic material may be the main cause of growing resistance. These findings call for close monitoring of genetic evolution as a matter of public health management strategy.

Sacubitril/valsartan ameliorates tubulointerstitial fibrosis by restoring mitochondrial homeostasis in diabetic kidney disease.

BACKGROUND: Tubulointerstitial fibrosis plays an important role in the progression of diabetic kidney disease (DKD). Sacubitril/valsartan (Sac/Val) exerts a robust beneficial effect in DKD. However, the potential functional effect of Sac/Val on tubulointerstitial fibrosis in DKD is still largely unclear. METHODS: Streptozotocin-induced diabetic mice were given Sac/Val or Val by intragastric administration once a day for 12 weeks. The renal function, the pathological changes of tubule injury and tubulointerstitial fibrosis, as well as mitochondrial morphology of renal tubules in mice, were evaluated. Genome-wide gene expression analysis was performed to identify the potential mechanisms. Meanwhile, human tubular epithelial cells (HK-2) were cultured in high glucose condition containing LBQ657/valsartan (LBQ/Val). Further, mitochondrial functions and Sirt1/PGC1α pathway of tubular epithelial cells were assessed by Western blot, Real-time-PCR, JC-1, MitoSOX or MitoTracker. Finally, the Sirt1 specific inhibitor, EX527, was used to explore the potential effects of Sirt1 signaling in vivo and in vitro. RESULTS: We found that Sac/Val significantly ameliorated the decline of renal function and tubulointerstitial fibrosis in DKD mice. The enrichment analysis of gene expression indicated metabolism as an important modulator in DKD mice with Sac/Val administration, in which mitochondrial homeostasis plays a pivotal role. Then, the decreased expression of Tfam and Cox IV;, as well as changes of mitochondrial function and morphology, demonstrated the disruption of mitochondrial homeostasis under DKD conditions. Interestingly, Sac/Val administration was found to restore mitochondrial homeostasis in DKD mice and in vitro model of HK-2 cells. Further, we demonstrated that Sirt1/PGC1α, a crucial pathway in mitochondrial homeostasis, was activated by Sac/Val both in vivo and in vitro. Finally, the beneficial effects of Sac/Val on mitochondrial homeostasis and tubulointerstitial fibrosis was partially abolished in the presence of Sirt1 specific inhibitor. CONCLUSIONS: Taken together, we demonstrate that Sac/Val ameliorates tubulointerstitial fibrosis by restoring Sirt1/PGC1α pathway-mediated mitochondrial homeostasis in DKD, providing a theoretical basis for delaying the progression of DKD in clinical practice.

High-fat and high-sucrose diet impairs female reproduction by altering ovarian transcriptomic and metabolic signatures.

BACKGROUND: Excessive energy intake in modern society has led to an epidemic surge in metabolic diseases, such as obesity and type 2 diabetes, posing profound threats to women's reproductive health. However, the precise impact and underlying pathogenesis of energy excess on female reproduction remain unclear. METHODS: We established an obese and hyperglycemic female mouse model induced by a high-fat and high-sucrose (HFHS) diet, then reproductive phenotypes of these mice were evaluated by examing sexual hormones, estrous cycles, and ovarian morphologies. Transcriptomic and precise metabolomic analyses of the ovaries were performed to compare the molecular and metabolic changes in HFHS mice. Finally, orthogonal partial least squares discriminant analysis was performed to compare the similarities of traits between HFHS mice and women with polycystic ovary syndrome (PCOS). RESULTS: The HFHS mice displayed marked reproductive dysfunctions, including elevated serum testosterone and luteinizing hormone levels, irregular estrous cycles, and impaired folliculogenesis, mimicking the clinical manifestations of women with PCOS. Precise metabolomic overview suggested that HFHS diet disrupted amino acid metabolism in the ovaries of female mice. Additionally, transcriptional profiling revealed pronounced disturbances in ovarian steroid hormone biosynthesis and glucolipid metabolism in HFHS mice. Further multi-omics analyses unveiled prominent aberration in ovarian arginine biosynthesis pathway. Notably, comparisons between HFHS mice and a cohort of PCOS patients identified analogous reproductive and metabolic signatures. CONCLUSIONS: Our results provide direct in vivo evidence for the detrimental effects of overnutrition on female reproduction and offer insights into the metabolic underpinnings of PCOS.

Annihilation-Net: Learned annihilation relation for dynamic MR imaging.

BACKGROUND: Deep learning methods driven by the low-rank regularization have achieved attractive performance in dynamic magnetic resonance (MR) imaging. The effectiveness of existing methods lies mainly in their ability to capture interframe relationships using network modules, which are lack interpretability. PURPOSE: This study aims to design an interpretable methodology for modeling interframe relationships using convolutiona networks, namely Annihilation-Net and use it for accelerating dynamic MRI. METHODS: Based on the equivalence between Hankel matrix product and convolution, we utilize convolutional networks to learn the null space transform for characterizing low-rankness. We employ low-rankness to represent interframe correlations in dynamic MR imaging, while combining with sparse constraints in the compressed sensing framework. The corresponding optimization problem is solved in an iterative form with the semi-quadratic splitting method (HQS). The iterative steps are unrolled into a network, dubbed Annihilation-Net. All the regularization parameters and null space transforms are set as learnable in the Annihilation-Net. RESULTS: Experiments on the cardiac cine dataset show that the proposed model outperforms other competing methods both quantitatively and qualitatively. The training set and test set have 800 and 118 images, respectively. CONCLUSIONS: The proposed Annihilation-Net improves the reconstruction quality of accelerated dynamic MRI with better interpretability.

Glymphatic Imaging in Pediatrics.

The glymphatic system, which facilitates cerebrospinal fluid (CSF) flow through the brain parenchyma, is important for brain development and waste clearance. Advances in imaging techniques, particularly magnetic resonance imaging, have make it possible to evaluate glymphatic structures and functions in vivo. Recently, several studies have focused on the development and alterations of the glymphatic system in pediatric disorders. This review discusses the development of the glymphatic system, advances of imaging techniques and their applications in pediatric disorders. First, the results of the reviewed studies indicate that the development of the glymphatic system is a long-lasting process that continues into adulthood. Second, there is a need for improved glymphatic imaging techniques that are non-invasive and fast to improve suitability for pediatric applications, as some of existing methods use contrast injection and are susceptible to motion artifacts from long scanning times. Several novel techniques are potentially feasible for pediatric patients and may be used in the future. Third, the glymphatic dysfunction is associated with a large number of pediatric disorders, although only a few have recently been investigated. In conclusion, research on the pediatric glymphatic system remains an emerging field. The preliminary applications of glymphatic imaging techniques have provided unique insight into the pathological mechanism of pediatric diseases, but mainly limited in visualization of enlarged perivascular spaces and morphological measurements on CSF volumes. More in-depth studies on glymphatic functions are required to improve our understanding of the mechanisms underlying brain development and pediatric diseases. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

TOX3 deficiency mitigates hyperglycemia by suppressing hepatic gluconeogenesis through FoxO1.

BACKGROUND: Excessive hepatic glucose production is a hallmark that contributes to hyperglycemia in type 2 diabetes (T2D). The regulatory network governing this process remains incompletely understood. Here, we demonstrate that TOX3, a high-mobility group family member, acts as a major transcriptional driver for hepatic glucose production. METHODS: Tox3-overexpressed and knockout mice were constructed to explore its metabolic functions. Transcriptomic and chromatin-immunoprecipitation sequencing (ChIP-seq) were used to identify downstream targets of TOX3. Both FoxO1 silencing and inhibitor approaches were used to assess the contribution of FoxO1. TOX3 expression levels were examined in the livers of mice and human subjects. Finally, Tox3 was genetically manipulated in diet-induced obese mice to evaluate its therapeutic potential. RESULTS: Hepatic Tox3 overexpression activates the gluconeogenic program, resulting in hyperglycemia and insulin resistance in mice. Hepatocyte-specific Tox3 knockout suppresses gluconeogenesis and improves insulin sensitivity. Mechanistically, integrated hepatic transcriptomic and ChIP-seq analyses identify FoxO1 as a direct target of TOX3. TOX3 stimulates FoxO1 transcription by directly binding to and activating its promoter, whereas FoxO1 silencing abrogates TOX3-induced dysglycemia in mice. In human subjects, hepatic TOX3 expression shows a significant positive correlation with blood glucose levels under normoglycemic conditions, yet is repressed by high glucose during T2D. Importantly, hepatic Tox3 deficiency markedly protects against and ameliorates the hyperglycemia and glucose intolerance in diet-induced diabetic mice. CONCLUSIONS: Our findings establish TOX3 as a driver for excessive gluconeogenesis through activating hepatic FoxO1 transcription. TOX3 could serve as a promising target for preventing and treating hyperglycemia in T2D.

A centromere map based on super pan-genome highlights the structure and function of rice centromeres.

Rice (Oryza sativa) is a significant crop worldwide with a genome shaped by various evolutionary factors. Rice centromeres are crucial for chromosome segregation, and contain some unreported genes. Due to the diverse and complex centromere region, a comprehensive understanding of rice centromere structure and function at the population level is needed. We constructed a high-quality centromere map based on the rice super pan-genome consisting of a 251-accession panel comprising both cultivated and wild species of Asian and African rice. We showed that rice centromeres have diverse satellite repeat CentO, which vary across chromosomes and subpopulations, reflecting their distinct evolutionary patterns. We also revealed that long terminal repeats (LTRs), especially young Gypsy-type LTRs, are abundant in the peripheral CentO-enriched regions and drive rice centromere expansion and evolution. Furthermore, high-quality genome assembly and complete telomere-to-telomere (T2T) reference genome enable us to obtain more centromeric genome information despite mapping and cloning of centromere genes being challenging. We investigated the association between structural variations and gene expression in the rice centromere. A centromere gene, OsMAB, which positively regulates rice tiller number, was further confirmed by expression quantitative trait loci, haplotype analysis and clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9 methods. By revealing the new insights into the evolutionary patterns and biological roles of rice centromeres, our finding will facilitate future research on centromere biology and crop improvement.

Developing a Dynamic Graph Network for Interpretable Analysis of Multi-Modal MRI Data in Parkinson's Disease Diagnosis.

Following the aging of the population, Parkinson's disease (PD) poses a severe challenge to public health. For the diagnosis of PD and the prediction of its progression, numerous computer-aided diagnosis procedures have been developed. Recently, Graph Convolutional Networks (GCN) are widely applied in deep learning to effectively integrate multi-modal features and model subject correlation. However, many GCNs which are used for node classification build large-scale fixed graph topologies using the entire dataset, which could make them impossible to verify independently. Furthermore, past GCN algorithms would need more interpretability, limiting their real-world applications. In this paper, an Interpretable Graph-Learning Convolutional Network (iGLCN) is proposed to enhance the performance of personalized diagnosis for PD while simultaneously producing interpretable results. The proposed method can dynamically adjust the graph structure for GCN to better diagnose outcomes by learning the optimal underlying latent graph. Through interpretable feature learning, the proposed network can interpret diagnosis outcomes. The experiments showed that the proposed method increased flexibility while maintaining a high level of classification performance and could be interpretable for PD diagnosis.Clinical Relevance- The proposed method is expected to have good performance in its strong practicability, feasibility, and interpretability for Parkinson's disease diagnosis.

Trust toward humans and trust toward artificial intelligence are not associated: Initial insights from self-report and neurostructural brain imaging.

The present study examines whether self-reported trust in humans and self-reported trust in [(different) products with built-in] artificial intelligence (AI) are associated with one another and with brain structure. We sampled 90 healthy participants who provided self-reported trust in humans and AI and underwent brain structural magnetic resonance imaging assessment. We found that trust in humans, as measured by the trust facet of the personality inventory NEO-PI-R, and trust in AI products, as measured by items assessing attitudes toward AI and by a composite score based on items assessing trust toward products with in-built AI, were not significantly correlated. We also used a concomitant dimensional neuroimaging approach employing a data-driven source-based morphometry (SBM) analysis of gray-matter-density to investigate neurostructural associations with each trust domain. We found that trust in humans was negatively (and significantly) correlated with an SBM component encompassing striato-thalamic and prefrontal regions. We did not observe significant brain structural association with trust in AI. The present findings provide evidence that trust in humans and trust in AI seem to be dissociable constructs. While the personal disposition to trust in humans might be "hardwired" to the brain's neurostructural architecture (at least from an individual differences perspective), a corresponding significant link for the disposition to trust AI was not observed. These findings represent an initial step toward elucidating how different forms of trust might be processed on the behavioral and brain level.

Tubular TMEM16A promotes tubulointerstitial fibrosis by suppressing PGC-1α-mediated mitochondrial homeostasis in diabetic kidney disease.

Tubulointerstitial fibrosis (TIF) plays a crucial role in the progression of diabetic kidney disease (DKD). However, the underlying molecular mechanisms remain obscure. The present study aimed to examine whether transmembrane member 16A (TMEM16A), a Ca2+-activated chloride channel, contributes to the development of TIF in DKD. Interestingly, we found that TMEM16A expression was significantly up-regulated in tubule of murine model of DKD, which was associated with development of TIF. In vivo inhibition of TMEM16A channel activity with specific inhibitors Ani9 effectively protects against TIF. Then, we found that TMEM16A activation induces tubular mitochondrial dysfunction in in vivo and in vitro models, with the evidence of the TMEM16A inhibition with specific inhibitor. Mechanically, TMEM16A mediated tubular mitochondrial dysfunction through inhibiting PGC-1α, whereas overexpression of PGC-1α could rescue the changes. In addition, TMEM16A-induced fibrogenesis was dependent on increased intracellular Cl-, and reducing intracellular Cl- significantly blunted high glucose-induced PGC-1α and profibrotic factors expression. Taken together, our studies demonstrated that tubular TMEM16A promotes TIF by suppressing PGC-1α-mediated mitochondrial homeostasis in DKD. Blockade of TMEM16A may serve as a novel therapeutic approach to ameliorate TIF.

The yeast prion protein Sup35 initiates α-synuclein pathology in mouse models of Parkinson's disease.

Parkinson's disease (PD) is characterized by the pathologic aggregation and prion-like propagation of α-synuclein (α-syn). Emerging evidence shows that fungal infections increase the incidence of PD. However, the molecular mechanisms by which fungi promote the onset of PD are poorly understood. Here, we show that nasal infection with Saccharomyces cerevisiae (S. cerevisiae) in α-syn A53T transgenic mice accelerates the aggregation of α-syn. Furthermore, we found that Sup35, a prion protein from S. cerevisiae, is the key factor initiating α-syn pathology induced by S. cerevisiae. Sup35 interacts with α-syn and accelerates its aggregation in vitro. Notably, injection of Sup35 fibrils into the striatum of wild-type mice led to α-syn pathology and PD-like motor impairment. The Sup35-seeded α-syn fibrils showed enhanced seeding activity and neurotoxicity compared with pure α-syn fibrils in vitro and in vivo. Together, these observations indicate that the yeast prion protein Sup35 initiates α-syn pathology in PD.