Cross-Sector Collaboration and Information Integration in Local Government One-Stop Services Centres: The Experiences and Lessons from a Case Studies in China

The government of China is experiencing a transformation from the control-oriented government to a service-oriented government. And the one-stop service centers established by local governments at all levels are exactly the practice aiming to integrate administrative resources and provide citizen with more convenient services. E-government implementation and public information integration is generally looked as a driving force to promote the one-stop service transformation. However, the new pattern of one-stop service and related information integration have been impacted by benefits division and power structure of the traditional sectors. Based on the Bryson’s framework in collaborative public administration research, the study conducted a case analysis of administrative structure and operation process of an information integration project, named “Quan-cheng-dai-ban”, in one-stop service centers in Beijing, attempting to reveal the key determinants of cross-sector collaboration and information integration in the local governments in China

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broad range of open-domain tasks. They can also generate high-level solution outlines for domain-specific tasks based on the common sense knowledge they have acquired. However, they still face difficulties with some specialized tasks because they lack enough domain-specific data during pre-training or they often have errors in their neural network computations on those tasks that need accurate executions. On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well. However, due to the different implementation or working mechanisms, they are not easily accessible or compatible with foundation models. Therefore, there is a clear and pressing need for a mechanism that can leverage foundation models to propose task solution outlines and then automatically match some of the sub-tasks in the outlines to the off-the-shelf models and systems with special functionalities to complete them. Inspired by this, we introduce TaskMatrix.AI as a new AI ecosystem that connects foundation models with millions of APIs for task completion. Unlike most previous work that aimed to improve a single AI model, TaskMatrix.AI focuses more on using existing foundation models (as a brain-like central system) and APIs of other AI models and systems (as sub-task solvers) to achieve diversified tasks in both digital and physical domains. As a position paper, we will present our vision of how to build such an ecosystem, explain each key component, and use study cases to illustrate both the feasibility of this vision and the main challenges we need to address next

Transcriptome profiling and digital gene expression by deep-sequencing in normal/regenerative tissues of planarian Dugesia japonica

AbstractPlanarians exhibit an extraordinary ability to regenerate lost body parts which is attributed to an abundance of pluripotent somatic stem cells called neoblasts. In this article, we report a transcriptome sequence of a Planaria subspecies Dugesia japonica derived by high-throughput sequencing. In addition, we researched transcriptome changes during different periods of regeneration by using a tag-based digital gene expression (DGE) system. Consequently, 11,913,548 transcriptome sequencing reads were obtained. Finally, these reads were eventually assembled into 37,218 unique unigenes. These assembled unigenes were annotated with various methods. Transcriptome changes during planarian regeneration were investigated by using a tag-based DGE system. We obtained a sequencing depth of more than 3.5million tags per sample and identified a large number of differentially expressed genes at various stages of regeneration. The results provide a fairly comprehensive molecular biology background to the research on planarian development, particularly with regard to its regeneration progress

miR-124 Suppresses Pancreatic Ductal Adenocarcinoma Growth by Regulating Monocarboxylate Transporter 1-Mediated Cancer Lactate Metabolism

Background/Aims: Increasing evidence shows that reprogramming of energy metabolism is a hallmark of cancer. Considering the emergence of microRNAs as crucial modulators of cancer, this study aimed to better understand the molecular mechanisms of miR-124 in regulating glycolysis in human pancreatic cancer. Methods: RT-PCR was used to investigate the expression of monocarboxylate transporters (MCTs) in pancreatic ductal adenocarcinoma (PDAC) patient samples and the PANC-1 cell line. A public database and immunochemistry were used for comprehensive analysis of MCT1 expression. The targeting of MCT1 by miR-124 was predicted by software and validated for the MCT1 3’-UTR by dual-luciferase reporter analysis. Cell proliferation, apoptosis, migration, xenografting, and the intracellular pH and L-lactate levels were assessed. Hypoxia-inducible factor-α (HIF-1α) and lactate dehydrogenase A (LDH-A) expression levels were determined by RT-PCR and western blotting. Results: MCT1 expression was higher in PDAC tissue than in normal tissue. Inhibition of MCT1 affected lactate metabolism, resulting in a higher intracellular pH and less proliferation of PANC-1 cells. MCT1 was the target gene of miR-124. In in vitro experiments, miR-124 inhibited the glycolytic activity of PANC-1 cells by targeting MCT1, further decreasing the tumor phenotype by increasing the intracellular pH through LDH-A and HIF-1α. In in vivo experiments, overexpression of miR-124 and silencing of MCT1 significantly inhibited tumor growth. Conclusion: miR-124 inhibits the progression of PANC-1 by targeting MCT1 in the lactate metabolic pathway. Our findings provide novel evidence for further functional studies of miR-124, which might be useful for future therapeutic approaches to PDAC

Neuropeptide Y-mediated sex- and afferent-specific neurotransmissions contribute to sexual dimorphism of baroreflex afferent function

BACKGROUND: Molecular and cellular mechanisms of neuropeptide-Y (NPY)-mediated gender-difference in blood pressure (BP) regulation are largely unknown. METHODS: Baroreceptor sensitivity (BRS) was evaluated by measuring the response of BP to phenylephrine/nitroprusside. Serum NPY concentration was determined using ELISA. The mRNA and protein expression of NPY receptors were assessed in tissue and single-cell by RT-PCR, immunoblot, and immunohistochemistry. NPY was injected into the nodose while arterial pressure was monitored. Electrophysiological recordings were performed on nodose neurons from rats by patch-clamp technique. RESULTS: The BRS was higher in female than male and ovariectomized rats, while serum NPY concentration was similar among groups. The sex-difference was detected in Y1R, not Y2R protein expression, however, both were upregulated upon ovariectomy and canceled by estrogen replacement. Immunostaining confirmed Y1R and Y2R expression in myelinated and unmyelinated afferents. Single-cell PCR demonstrated that Y1R expression/distribution was identical between A- and C-types, whereas, expressed level of Y2R was ~15 and ~7 folds higher in Ah- and C-types than A-types despite similar distribution. Activation of Y1R in nodose elevated BP, while activation of Y2R did the opposite. Activation of Y1R did not alter action potential duration (APD) of A-types, but activation of Y2R- and Y1R/Y2R in Ah- and C-types frequency-dependently prolonged APD. N-type ICa was reduced in A-, Ah- and C-types when either Y1R, Y2R, or both were activated. The sex-difference in Y1R expression was also observed in NTS. CONCLUSIONS: Sex- and afferent-specific expression of Neuropeptide-Y receptors in baroreflex afferent pathway may contribute to sexual-dimorphic neurocontrol of BP regulation

Tissue microarray analysis reveals a tight correlation between protein expression pattern and progression of esophageal squamous cell carcinoma

BACKGROUND: The development of esophageal squamous cell carcinoma (ESCC) progresses a multistage process, collectively known as precursor lesions, also called dysplasia (DYS) and carcinoma in situ (CIS), subsequent invasive lesions and final metastasis. In this study, we are interested in investigating the expression of a variety of functional classes of proteins in ESCC and its precursor lesions and characterizing the correlation of these proteins with ESCC malignant progression. METHODS: Fas, FADD, caspase 8, CDC25B, fascin, CK14, CK4, annexin I, laminin-5γ2 and SPARC were analyzed using immunohistochemistry on tissue microarray containing 205 ESCC and 173 adjacent precursor lesions as well as corresponding normal mucosa. To confirm the immunohistochemical results, three proteins, fascin, CK14 and laminin-5γ2, which were overexpressed in ESCC on tissue microarray, were detected in 12 ESCC cell lines by Western blot assay. RESULTS: In ESCC and its precursor lesions, FADD, CDC25B, fascin, CK14, laminin-5γ2 and SPARC were overexpressed, while Fas, caspase 8, CK4 and annexin I were underexpressed. The abnormalities of these proteins could be classified into different groups in relation to the stages of ESCC development. They were "early" corresponding to mild and moderate DYS with overexpression of fascin, FADD and CDC25B and underexpression of Fas, caspase 8, CK4 and annexin I, "intermediate" to severe DYS and CIS with overexpression of FADD and CK14, and "late" to invasive lesions (ESCC) and to advanced pTNM stage ESCC lesions with overexpression of CK14, laminin-5γ2 and SPARC. CONCLUSION: Analyzing the protein expression patterns of Fas, FADD, caspase 8, CDC25B, fascin, CK14, CK4, annexin I, laminin-5γ2 and SPARC would be valuable to develop rational strategies for early detection of lesions at risk in advance as well as for prevention and treatment of ESCC

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events42Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases