Biomaterial Wettability Impacts Fibrin Clog Composition as well as Fibrinolysis

Whereas folding of genomes at the large scale of epigenomic compartments and topologically associating domains (TADs) is now relatively well understood, how chromatin is folded at finer scales remains largely unexplored in mammals. Here, we overcome some limitations of conventional 3C-based methods by using high-resolution Micro-C to probe links between 3D genome organization and transcriptional regulation in mouse stem cells. Combinatorial binding of transcription factors, cofactors, and chromatin modifiers spatially segregates TAD regions into various finer-scale structures with distinct regulatory features including stripes, dots, and domains linking promoters-to-promoters (P-P) or enhancers-to-promoters (E-P) and bundle contacts between Polycomb regions. E-P stripes extending from the edge of domains predominantly link co-expressed loci, often in the absence of CTCF and cohesin occupancy. Acute inhibition of transcription disrupts these gene-related folding features without altering higher-order chromatin structures. Our study uncovers previously obscured finer-scale genome organization, establishing functional links between chromatin folding and gene regulation. Cell-selective gene expression comprises a critical element of many adeno-associated virus (AAV) vector-based gene therapies, and to date achieving this goal has focused on AAV capsid engineering, cell-specific promoters, or cell-specific enhancers. Recently, we discovered that the capsid of AAV9 exerts a differential influence on constitutive promoters of sufficient magnitude to alter cell type gene expression in the rat CNS. For AAV9 vectors chicken β-actin (CBA) promoter-driven gene expression exhibited a dominant neuronal gene expression in the rat striatum. Surprisingly, for otherwise identical AAV9 vectors, the truncated CBA hybrid (CBh) promoter shifted gene expression toward striatal oligodendrocytes. In contrast, AAV2 vector gene expression was restricted to striatal neurons, regardless of the constitutive promoter used. Furthermore, a six-glutamate residue insertion immediately after the VP2 start residue shifted CBA-driven cellular gene expression from neurons to oligodendrocytes. Conversely, a six-alanine insertion in the same AAV9 capsid region reversed the CBh-mediated oligodendrocyte expression back to neurons without changing AAV9 capsid access to oligodendrocytes. Given the preponderance of AAV9 in ongoing clinical trials and AAV capsid engineering, this AAV9 capsid-promoter interaction reveals a previously unknown novel contribution to cell-selective AAV-mediated gene expression in the CNS. Excitation in neural circuits must be carefully controlled by inhibition to regulate information processing and network excitability. During development, cortical inhibitory and excitatory inputs are initially mismatched but become co-tuned or balanced with experience. However, little is known about how excitatory-inhibitory balance is defined at most synapses or about the mechanisms for establishing or maintaining this balance at specific set points. Here we show how coordinated long-term plasticity calibrates populations of excitatory-inhibitory inputs onto mouse auditory cortical pyramidal neurons. Pairing pre- and postsynaptic activity induced plasticity at paired inputs and different forms of heterosynaptic plasticity at the strongest unpaired synapses, which required minutes of activity and dendritic Ca2+ signaling to be computed. Theoretical analyses demonstrated how the relative rate of heterosynaptic plasticity could normalize and stabilize synaptic strengths to achieve any possible excitatory-inhibitory correlation. Thus, excitatory-inhibitory balance is dynamic and cell specific, determined by distinct plasticity rules across multiple excitatory and inhibitory synapses. BACKGROUND Integrated antimicrobial resistance (AMR) surveillance programmes require regular evaluation to ensure they are fit-for-purpose and that all actors understand their responsibilities. This will strengthen their relevance for the clinical setting which depends heavily on continued access to effective treatment options. Several evaluation tools addressing different surveillance aspects are available. OBJECTIVES To understand the strengths and weaknesses of three evaluation tools, and to improve guidance on how to choose a fit-for-purpose tool. SOURCES Three tools were assessed 1) AMR-PMP - The Progressive Management Pathway tool on AMR developed by the Food and Agriculture Organization (FAO) of United Nations, 2) NEOH developed by the EU COST Action 'Network for Evaluation of One Health', and 3) SURVTOOLS developed in an FP7-EU project 'RISKSUR'. Each tool was assessed with regard to contents, required evaluation processes including stakeholder engagement and resource demands, integration coverage acrcts to varying degrees. This study provides guidance on aspects to consider when choosing between available tools and embarking on an evaluation of integrated surveillance. BACKGROUND Microbiologists are valued for their time-honed skills in image analysis including identification of pathogens and inflammatory context in Gram stains, ova and parasite preparations, blood smears, and histopathological slides. They also must classify colonial growth on a variety of agar plates for triage and workup. Recent advances in image analysis, in particular application of artificial intelligence (AI), have the potential to automate these processes and support more timely and accurate diagnoses. OBJECTIVES To review current artificial intelligence-based image analysis as applied to clinical microbiology and discuss future trends in the field. SOURCES Material sourced for this review included peer-reviewed literature annotated in the PubMed or Google Scholar databases and preprint articles from bioRxiv. Articles describing use of AI for analysis of images used in infectious disease diagnostics were reviewed. CONTENT We describe application of machine learning towards analysis of different types of microbiological image data. 3',3'-cGAMP price Specifically, we outline progress in smear and plate interpretation and potential for AI diagnostic applications in the clinical microbiology laboratory. IMPLICATIONS Combined with automation, we predict that AI algorithms will be used in the future to pre-screen and pre-classify image data, thereby increasing productivity and enabling more accurate diagnoses through collaboration between the AI and microbiologist. Once developed, image-based AI analysis is inexpensive and amenable to local and remote diagnostic use.