Large time asymptotics for the density of a branching Wiener process

Given an R^d-valued supercritical branching Wiener process, let D(A,T) be the number of particles in a subset A of R^d at time T, (T=0,1,2,...). We provide a complete asymptotic expansion of D(A,T) as T goes to infinity, generalizing the work of X.Chen

Frequently visited sets for random walks

We study the occupation measure of various sets for a symmetric transient random walk in $Z^d$ with finite variances. Let $\mu^X_n(A)$ denote the occupation time of the set $A$ up to time $n$. It is shown that $\sup_{x\in Z^d}\mu_n^X(x+A)/\log n$ tends to a finite limit as $n\to\infty$. The limit is expressed in terms of the largest eigenvalue of a matrix involving the Green's function of $X$ restricted to the set $A$. Some examples are discussed and the connection to similar results for Brownian motion is given.Comment: 19 page

CRISPR-Cas9 Gene Editing of Hematopoietic Stem Cells from Patients with Friedreich's Ataxia.

Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by expansion of GAA repeats in intron 1 of the frataxin (FXN) gene, leading to significant decreased expression of frataxin, a mitochondrial iron-binding protein. We previously reported that syngeneic hematopoietic stem and progenitor cell (HSPC) transplantation prevented neurodegeneration in the FRDA mouse model YG8R. We showed that the mechanism of rescue was mediated by the transfer of the functional frataxin from HSPC-derived microglia/macrophage cells to neurons/myocytes. In this study, we report the first step toward an autologous HSPC transplantation using the CRISPR-Cas9 system for FRDA. We first identified a pair of CRISPR RNAs (crRNAs) that efficiently removes the GAA expansions in human FRDA lymphoblasts, restoring the non-pathologic level of frataxin expression and normalizing mitochondrial activity. We also optimized the gene-editing approach in HSPCs isolated from healthy and FRDA patients' peripheral blood and demonstrated normal hematopoiesis of gene-edited cells in vitro and in vivo. The procedure did not induce cellular toxic effect or major off-target events, but a p53-mediated cell proliferation delay was observed in the gene-edited cells. This study provides the foundation for the clinical translation of autologous transplantation of gene-corrected HSPCs for FRDA

Auditing SNOMED CT Hierarchical Relations Based on Lexical Features of Concepts in Non-Lattice Subgraphs

Objective—We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. Methods—Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT’s IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. Results—A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the “Clinical Finding” and “Procedure” sub-hierarchies. Two domain experts confirmed 185 (among 223) missing IS-A relations, a precision of 82.96%. Conclusions—Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT

Low density carbon nanotube forest as an index-matched and near perfect absorption coating

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98687/1/ApplPhysLett_99_211103.pd

A hybrid G-quadruplex structure formed between RNA and DNA explains the extraordinary stability of the mitochondrial R-loop

In human mitochondria the transcription machinery generates the RNA primers needed for initiation of DNA replication. A critical feature of the leading-strand origin of mitochondrial DNA replication is a CG-rich element denoted conserved sequence block II (CSB II). During transcription of CSB II, a G-quadruplex structure forms in the nascent RNA, which stimulates transcription termination and primer formation. Previous studies have shown that the newly synthesized primers form a stable and persistent RNA-DNA hybrid, a R-loop, near the leading-strand origin of DNA replication. We here demonstrate that the unusual behavior of the RNA primer is explained by the formation of a stable G-quadruplex structure, involving the CSB II region in both the nascent RNA and the non-template DNA strand. Based on our data, we suggest that G-quadruplex formation between nascent RNA and the non-template DNA strand may be a regulated event, which decides the fate of RNA primers and ultimately the rate of initiation of DNA synthesis in human mitochondria

Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception

Personalized chatbot-based teaching assistants can be crucial in addressing increasing classroom sizes, especially where direct teacher presence is limited. Large language models (LLMs) offer a promising avenue, with increasing research exploring their educational utility. However, the challenge lies not only in establishing the efficacy of LLMs but also in discerning the nuances of interaction between learners and these models, which impact learners' engagement and results. We conducted a formative study in an undergraduate computer science classroom (N=145) and a controlled experiment on Prolific (N=356) to explore the impact of four pedagogically informed guidance strategies and the interaction between student approaches and LLM responses. Direct LLM answers marginally improved performance, while refining student solutions fostered trust. Our findings suggest a nuanced relationship between the guidance provided and LLM's role in either answering or refining student input. Based on our findings, we provide design recommendations for optimizing learner-LLM interactions

A Role for Casein Kinase 2 in the Mechanism Underlying Circadian Temperature Compensation

SummaryTemperature compensation of circadian clocks is an unsolved problem with relevance to the general phenomenon of biological compensation. We identify casein kinase 2 (CK2) as a key regulator of temperature compensation of the Neurospora clock by determining that two long-standing clock mutants, chrono and period-3, displaying distinctive alterations in compensation encode the β1 and α subunits of CK2, respectively. Reducing the dose of these subunits, particularly β1, significantly alters temperature compensation without altering the enzyme's Q10. By contrast, other kinases and phosphatases implicated in clock function do not play appreciable roles in temperature compensation. CK2 exerts its effects on the clock by directly phosphorylating FREQUENCY (FRQ), and this phosphorylation is compromised in CK2 hypomorphs. Finally, mutation of certain putative CK2 phosphosites on FRQ, shown to be phosphorylated in vivo, predictably alters temperature compensation profiles effectively phenocopying CK2 mutants

Developing the surgeon-machine interface: Using a novel instance-segmentation framework for intraoperative landmark labelling

Introduction: The utilisation of artificial intelligence (AI) augments intraoperative safety, surgical training, and patient outcomes. We introduce the term Surgeon-Machine Interface (SMI) to describe this innovative intersection between surgeons and machine inference. A custom deep computer vision (CV) architecture within a sparse labelling paradigm was developed, specifically tailored to conceptualise the SMI. This platform demonstrates the ability to perform instance segmentation on anatomical landmarks and tools from a single open spinal dural arteriovenous fistula (dAVF) surgery video dataset. Methods: Our custom deep convolutional neural network was based on SOLOv2 architecture for precise, instance-level segmentation of surgical video data. Test video consisted of 8520 frames, with sparse labelling of only 133 frames annotated for training. Accuracy and inference time, assessed using F1-score and mean Average Precision (mAP), were compared against current state-of-the-art architectures on a separate test set of 85 additionally annotated frames. Results: Our SMI demonstrated superior accuracy and computing speed compared to these frameworks. The F1-score and mAP achieved by our platform were 17% and 15.2% respectively, surpassing MaskRCNN (15.2%, 13.9%), YOLOv3 (5.4%, 11.9%), and SOLOv2 (3.1%, 10.4%). Considering detections that exceeded the Intersection over Union threshold of 50%, our platform achieved an impressive F1-score of 44.2% and mAP of 46.3%, outperforming MaskRCNN (41.3%, 43.5%), YOLOv3 (15%, 34.1%), and SOLOv2 (9%, 32.3%). Our platform demonstrated the fastest inference time (88ms), compared to MaskRCNN (90ms), SOLOV2 (100ms), and YOLOv3 (106ms). Finally, the minimal amount of training set demonstrated a good generalisation performance -our architecture successfully identified objects in a frame that were not included in the training or validation frames, indicating its ability to handle out-of-domain scenarios. Discussion: We present our development of an innovative intraoperative SMI to demonstrate the future promise of advanced CV in the surgical domain. Through successful implementation in a microscopic dAVF surgery, our framework demonstrates superior performance over current state-of-the-art segmentation architectures in intraoperative landmark guidance with high sample efficiency, representing the most advanced AI-enabled surgical inference platform to date. Our future goals include transfer learning paradigms for scaling to additional surgery types, addressing clinical and technical limitations for performing real-time decoding, and ultimate enablement of a real-time neurosurgical guidance platform.</p

Circadian Rhythmicity by Autocatalysis

The temperature compensated in vitro oscillation of cyanobacterial KaiC phosphorylation, the first example of a thermodynamically closed system showing circadian rhythmicity, only involves the three Kai proteins (KaiA, KaiB, and KaiC) and ATP. In this paper, we describe a model in which the KaiA- and KaiB-assisted autocatalytic phosphorylation and dephosphorylation of KaiC are the source for circadian rhythmicity. This model, based upon autocatalysis instead of transcription-translation negative feedback, shows temperature-compensated circadian limit-cycle oscillations with KaiC phosphorylation profiles and has period lengths and rate constant values that are consistent with experimental observations