Multiplex signal amplification for ultrasensitive CRP assay via integrated electrochemical biosensor array using MOF-derived carbon material and aptamers.

Accurate and precise detection of disease-associated proteins, such as C-reactive protein (CRP), remains a challenge in biosensor development. Herein, we present a novel approach－an integrated disposable aptasensor array－designed for precise, ultra-sensitive, and parallel detection of CRP in plasma samples. This integrated biosensing array platform enables multiplex parallel testing, ensuring the accuracy and reliability in sample analysis. The ultra-sensitivity of this biosensor is achieved through multiplex signal amplification. Leveraging the superior conductivity and extensive surface area of MOF-derived nanoporous carbon material (CMOF), the biosensor enhances recognition elements (aptamers) by catalyzing the horseradish peroxidase (HRP) label enzyme reaction to multiply the number of probe molecules. Optimized conditions yielded exceptional performance, exhibiting high accuracy (relative standard deviation, RSD≤10.0 %), a low detection limit (0.3 pg/mL, S/N = 3), ultra-sensitivity (0.16 µA/ng mL-1 mm-2), and a rapid response (seven parallel tests within 60 min). Importantly, this multi-unit integrated disposable aptasensor array accurately quantified CRP in human serum, demonstrating comparable results to commercial enzyme-linked immunosorbent assay (ELISA). This technology showcases promise for detecting various biomarkers using a unified approach, presenting an appealing strategy for early disease diagnosis and biological analysis.

Visual Deprivation Alters Functional Connectivity of Neural Networks for Voice Recognition: A Resting-State fMRI Study.

Humans recognize one another by identifying their voices and faces. For sighted people, the integration of voice and face signals in corresponding brain networks plays an important role in facilitating the process. However, individuals with vision loss primarily resort to voice cues to recognize a person's identity. It remains unclear how the neural systems for voice recognition reorganize in the blind. In the present study, we collected behavioral and resting-state fMRI data from 20 early blind (5 females; mean age = 22.6 years) and 22 sighted control (7 females; mean age = 23.7 years) individuals. We aimed to investigate the alterations in the resting-state functional connectivity (FC) among the voice- and face-sensitive areas in blind subjects in comparison with controls. We found that the intranetwork connections among voice-sensitive areas, including amygdala-posterior "temporal voice areas" (TVAp), amygdala-anterior "temporal voice areas" (TVAa), and amygdala-inferior frontal gyrus (IFG) were enhanced in the early blind. The blind group also showed increased FCs of "fusiform face area" (FFA)-IFG and "occipital face area" (OFA)-IFG but decreased FCs between the face-sensitive areas (i.e., FFA and OFA) and TVAa. Moreover, the voice-recognition accuracy was positively related to the strength of TVAp-FFA in the sighted, and the strength of amygdala-FFA in the blind. These findings indicate that visual deprivation shapes functional connectivity by increasing the intranetwork connections among voice-sensitive areas while decreasing the internetwork connections between the voice- and face-sensitive areas. Moreover, the face-sensitive areas are still involved in the voice-recognition process in blind individuals through pathways such as the subcortical-occipital or occipitofrontal connections, which may benefit the visually impaired greatly during voice processing.

Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI.

BACKGROUND: Although stratifying autism spectrum disorder (ASD) into different subtypes is a common effort in the research field, few papers have characterized the functional connectivity alterations of ASD subgroups classified by their clinical presentations. METHODS: This is a case-control rs-fMRI study, based on large samples of open database (Autism Brain Imaging Data Exchange, ABIDE). The rs-MRI data from n = 415 ASD patients (males n = 357), and n = 574 typical development (TD) controls (males n = 410) were included. Clinical features of ASD were extracted and classified using data from each patient's Autism Diagnostic Interview-Revised (ADI-R) evaluation. Each subtype of ASD was characterized by local functional connectivity using regional homogeneity (ReHo) for assessment, remote functional connectivity using voxel-mirrored homotopic connectivity (VMHC) for assessment, the whole-brain functional connectivity, and graph theoretical features. These identified imaging properties from each subtype were integrated to create a machine learning model for classifying ASD patients into the subtypes based on their rs-fMRI data, and an independent dataset was used to validate the model. RESULTS: All ASD participants were classified into Cluster-1 (patients with more severe impairment) and Cluster-2 (patients with moderate impairment) according to the dimensional scores of ADI-R. When compared to the TD group, Cluster-1 demonstrated increased local connection and decreased remote connectivity, and widespread hyper- and hypo-connectivity variations in the whole-brain functional connectivity. Cluster-2 was quite similar to the TD group in both local and remote connectivity. But at the level of whole-brain functional connectivity, the MCC-related connections were specifically impaired in Cluster-2. These properties of functional connectivity were fused to build a machine learning model, which achieved ∼75% for identifying ASD subtypes (Cluster-1 accuracy = 81.75%; Cluster-2 accuracy = 76.48%). CONCLUSIONS: The stratification of ASD by clinical presentations can help to minimize disease heterogeneity and highlight the distinguished properties of brain connectivity in ASD subtypes.

The impact of digital inclusive finance on corporate ESG performance: based on the perspective of corporate green technology innovation.

Enterprises are important subjects in the transformation of national green development, while financial support is an important thrust to promote the fulfillment of environmental responsibility. In the dual context of building a digital inclusive financial system and green transformation of corporate production, this paper explores the impact of digital inclusive finance on corporate ESG performance and its mechanism of action through theoretical and empirical analyses using data of Chinese A-share listed enterprises from 2011 to 2020. It is found that the development of digital inclusive finance significantly contributes to the improvement of corporate ESG performance, and the impact of digital inclusive finance on corporate ESG performance has a marginal decreasing effect, while corporate green technology innovation has a marginal increasing effect on corporate ESG performance. The mechanism analysis found that corporate green technology innovation has a mediating effect. The development of digital inclusive finance can enhance the green technology innovation ability of enterprises, and the green technology innovation of enterprises enhances the green sustainability ability of enterprises and improves the ESG performance of corporates. Further research shows that the effects of digital inclusive finance and corporate green technology innovation on corporate ESG performance are industry heterogeneous and pollution degree heterogeneous. How to promote financial services to better promote the combination of corporate green development and fulfillment of social and environmental responsibility is the most direct research implication of this paper.

Digital inclusive finance, financial mismatch and the innovation capacity of small and medium-sized enterprises: Evidence from Chinese listed companies.

As the main driver of innovation, enterprises can effectively promote the level of social innovation. This paper incorporates digital inclusive finance into the research framework of innovation in Small and Medium-sized enterprises, and investigates the impact of digital inclusive finance on the innovation ability of Small and Medium-sized enterprises through theoretical and empirical analyses. The theoretical analysis finds that digital inclusive finance can compensate for the "long-tail effect" in the financing process and help enterprises obtain financing loans. In terms of empirical analysis, this paper has conducted empirical tests by selecting the innovation data of Chinese A-share listed companies from 2010 to 2021, and the results show that: (1) Digital inclusive finance still has a facilitating effect on the technological innovation capability of Small and Medium-sized enterprises after the robustness test. (2)The mechanism evaluation finds that the digital inclusive finance segmentation indicators, i.e., the depth of use, the breadth of coverage and the degree of digitalization, are also important ways to enhance the technological innovation capability of Small and Medium-sized enterprises. (3)The innovative introduction of financial mismatch variables reveals that the financial mismatch problem in the financial market has a suppressive effect on the technological innovation capability of Small and Medium-sized enterprises. (4)Further analysis of the mediation effect of digital inclusive finance reveals that digital inclusive finance can effectively correct the financial mismatch problem in the traditional financial model and promote the technological innovation capability of Small and Medium-sized enterprises. This paper enriches the analysis of the economic effects of digital inclusive finance, while providing Chinese empirical support for digital inclusive finance to promote the innovation ability of Small and Medium-sized enterprises.

Activity-Dependent Differential Regulation of Auts2 Isoforms In Vitro and In Vivo.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder of unknown cause, although one hypothesis suggests a potential imbalance between excitation and inhibition that leads to changes in neuronal activity and a disturbance in the brain network. However, the mechanisms through which neuronal activity contributes to the development of ASD remain largely unexplained. In this study, we described that neuronal activity at the transcriptional and translational levels regulated the expression of Auts2 isoforms. The prolonged stimulation of cultured cortical neurons significantly reduced the auts2 transcripts, accompanied by the decrease of FL-Auts2 protein, as well as one of the short isoforms (S-Auts2 var.1). Blocking neuronal activity increased the number of auts2 transcripts but not protein levels. Furthermore, blocking the NMDA receptors during stimulation could partially restore the FL-Auts2 and S-Auts2 var.1 at protein level, but not at mRNA level. Finally, Auts2 expression in the hippocampus was reduced in mice exposed to an enriched environment, a behavior paradigm designed to increase the brain activity through abundant sensory and social stimulations. Thus, our study revealed a novel regulatory effect of neuronal activity on the transcription and translation of ASD-risk gene auts2.

Untangle the Multi-Facet Functions of Auts2 as an Entry Point to Understand Neurodevelopmental Disorders.

Neurodevelopmental disorders are psychiatric diseases that are usually first diagnosed in infancy, childhood and adolescence. Autism spectrum disorder (ASD) is a neurodevelopmental disorder, characterized by core symptoms including impaired social communication, cognitive rigidity and repetitive behavior, accompanied by a wide range of comorbidities such as intellectual disability (ID) and dysmorphisms. While the cause remains largely unknown, genetic, epigenetic, and environmental factors are believed to contribute toward the onset of the disease. Autism Susceptibility Candidate 2 (Auts2) is a gene highly associated with ID and ASD. Therefore, understanding the function of Auts2 gene can provide a unique entry point to untangle the complex neuronal phenotypes of neurodevelpmental disorders. In this review, we discuss the recent discoveries regarding the molecular and cellular functions of Auts2. Auts2 was shown to be a key-regulator of transcriptional network and a mediator of epigenetic regulation in neurodevelopment, the latter potentially providing a link for the neuronal changes of ASD upon environmental risk-factor exposure. In addition, Auts2 could synchronize the balance between excitation and inhibition through regulating the number of excitatory synapses. Cytoplasmic Auts2 could join the fine-tuning of actin dynamics during neuronal migration and neuritogenesis. Furthermore, Auts2 was expressed in developing mouse and human brain regions such as the frontal cortex, dorsal thalamus, and hippocampus, which have been implicated in the impaired cognitive and social function of ASD. Taken together, a comprehensive understanding of Auts2 functions can give deep insights into the cause of the heterogenous manifestation of neurodevelopmental disorders such as ASD.

Superiority of blind over sighted listeners in voice recognition.

The current study examined whether the blind are superior to sighted listeners in voice recognition. Three subject groups, including 17 congenitally blind, 18 late blind, and 18 sighted, showed no significant differences in the immediate voice recognition test. In the delayed test conducted two weeks later, however, both congenitally blind and late blind groups performed better than the sighted with no significant difference between the two blind groups. These results partly confirmed the anecdotal observation about the blind's superiority in voice recognition, which resides mainly in delayed memory phase but not in immediate recall and generalization phase.

Altered connectivity of the visual word form area in the low-vision population: A resting-state fMRI study.

The present study investigated the resting-state functional connectivity (FC) of the visual word form area (VWFA) in low-vision people. Participants were 25 sighted and 37 low-vision individuals. During the experiment, participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. FC maps of the VWFA for sighted and low-vision participants were calculated separately and were contrasted with each other. Our results revealed a stronger FC between the VWFA and the inferior occipital cortex (IOC) but a weaker FC between the VWFA and the posterior central gyrus (PostCG) in the sighted people compared to the people with low vision. The region-of-interest-based analyses showed that the FC between the VWFA and PostCG in low-vision individuals who learned Braille was stronger relative to those who did not learn Braille, and that the FC between the VWFA and IOC was correlated with the onset age of Braille learning. These results suggest that the VWFA in people with low vision has a functional reorganization between visual and tactile processing, which was modulated by the experience of Braille reading.