Miracle-dz/UniFAR-FTUs huggingface dataset:
Werner syndrome RECQ helicase participates in and directs maintenance of the protein complexes of constitutive heterochromatin in proliferating human cells

The WRN RECQ helicase is responsible for the Werner syndrome of premature aging and cancer predisposition. Substantial progress has been made in delineating WRN functions in multiple aspects of DNA metabolism, including DNA replication, repair, transcription, and telomere maintenance. Nevertheless, a complete mechanistic understanding of how loss of WRN accelerates aging in humans has not been achieved yet. Here we show that WRN is involved in the maintenance of constitutive heterochromatin, CH, in proliferating, immortalized human fibroblasts. WRN is found within a complex with histone deacetylase 2, HDAC2, and WRN/HDAC2 association is mediated by heterochromatin protein alpha, HP1α. WRN deficiency derepresses SATII pericentromeric satellite repeats and reduces a subset of protein-protein interactions that participate in the organization of CH in the nucleus. In particular, WRN deficiency reduces the complexes involving Lamin B1 and Lamin B receptor, LBR. Both mRNA level and subcellular distribution of LBR are affected by WRN deficiency, and the latter phenotype does not require WRN catalytic activities. At the mRNA level, WRN supports complete maturation of the LBR mRNA. All signs of heterochromatin disruption seen in WRN-deficient proliferating fibroblasts are also observed in WRN-proficient fibroblasts undergoing replicative or oncogene-induced senescence, and WRN complexes with HP1α and HDAC2 are also markedly downregulated in these senescing cells. The data suggest that WRN loss affects heterochromatin independently of the senescence program but can mimic aspects of it and thus sensitize cells to triggers of senescence.
The Flash Mode of Proton Irradiation in the Bragg Peak Partly Spares the Embryogenesis of the Quail

The study of biological effects of high-dose-rate ionizing radiation using animal models remains an urgent problem. In the work, a comparison of proton-induced damage to embryos (the 9th post-fertilization day) and 1-day-old baby chicks (the 18th post-fertilization day) from irradiated eggs of Japanese quail (Coturnix coturnix japónica) irradiated in and outside the Bragg peak with the conventional and ultra-high dose rate D (CONV D < 1 Gy/s, FLASH D ∼100 Gy/s and single-pulse flash - SPLASH D ∼106 Gy/s, respectively) was carried out. The following criteria were used: survival, body weight and body length of embryos, weight of chicks, percentage of erythrocytes with anomalies (with micronuclei, without nuclei, with two nuclei), and the speed of movement of 1-day-old chicks in the open field test. The largest number of dead embryos was recorded after irradiation with 7 and 14 Gy in the plateau region of the proton trajectory. By the criteria of body weight and length, as well as the number of erythrocytes with micronuclei in 9-day-old embryos from eggs irradiated with a dose of 8.5 Gy in the Bragg peak, FLASH and SPLASH modes were found to be the least traumatic compared with the CONV mode. The weight of chicks from eggs irradiated with a dose of 4 Gy in the Bragg peak did not differ from the control and did not depend on the irradiation mode. The lowest death incidence and the smallest number of abnormal erythrocytes were recorded after FLASH and SPLASH irradiation; in chicks that hatched from eggs irradiated in the CONV mode, a tendency for an increase in the number of abnormal erythrocytes was observed. The speed of movement of chicks from FLASH- and SPLASH-irradiated eggs was comparable with that from unirradiated eggs, and chicks from eggs irradiated in the CONV mode were less active than chicks from unirradiated eggs and eggs irradiated in the other regimes. Thus, the irradiation of eggs with a beam of accelerated protons in the Bragg peak in the FLASH/SPLASH modes is less damaging for healthy tissues and for the development of embryos and chicks on the cellular, anatomical, and physiological levels.
Cortical multi-area model with joint excitatory-inhibitory clusters accounts for spiking statistics, inter-area propagation, and variability dynamics

The primate brain uses billions of interacting neurons to produce macroscopic dynamics and behavior, but current methods only allow neuroscientists to investigate a subset of the neural activity. Computational modeling offers an alternative testbed for scientific hypotheses, by allowing full control of the system. Here, we test the hypothesis that local cortical circuits are organized into joint clusters of excitatory and inhibitory neurons by investigating the influence of this organizational principle on cortical resting-state spiking activity, inter-area propagation, and variability dynamics. The model represents all vision-related areas in one hemisphere of the macaque cortex with biologically realistic neuron densities and connectivities, expanding on a previous unclustered model of this system. Each area is represented by a square millimeter microcircuit including the full density of neurons and synapses, avoiding downscaling artifacts and testing cortical dynamics at the natural scale. We find that joint excitatory-inhibitory clustering normalizes spiking activity statistics in terms of firing rate distributions and inter-spike interval variability. A comparison with data from cortical areas V1, V4, FEF, 7a, and DP shows that the clustering enables the resting-state activity of especially higher cortical areas to be better captured. In addition, we find that the clustering supports signal propagation across all areas in both feedforward and feedback directions with reasonable latencies. Finally, we also show that localized stimulation of the clustered model quenches the variability of neural activity, in agreement with experimental observations. We conclude that joint clustering of excitatory and inhibitory neurons is a likely organizational principle of local cortical circuits, supporting resting-state spiking activity statistics, inter-area propagation, and variability dynamics.
Mimicking the breast metastatic microenvironment: characterization of a novel syngeneic model of HER2+ breast cancer

Preclinical murine models in which primary tumors spontaneously metastasize to distant organs are valuable tools to study metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line, NT2.5-lung metastasis (- LM), that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. Within one week of orthotopic implantation of NT2.5-LM in NeuN mice, distant metastases can be observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. Metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. We demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT) and enrichment in EMT-regulating pathways, suggestive of their enhanced metastatic potential. The new NT2.5-LM model provides more rapid and spontaneous development of widespread metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses targeting distant visceral metastases SUMMARY STATEMENT We characterize a new syngeneic, immune-competent murine model of breast cancer (NT2.5-LM) that yields rapid and widespread metastases, preserves spontaneous metastasis, and provides a model for studying novel therapeutic interventions.
Modulation of locomotion and motor neuron response by the cohesive effect of acute and chronic feeding states and acute d-amphetamine treatment in zebrafish larvae

Amphetamine (AMPH) increases locomotor activities in animals, and the locomotor response to AMPH is further modulated by caloric deficits such as food deprivation and restriction. The increment in locomotor activity regulated by AMPH-caloric deficit concomitance can be further modulated by varying feeding schedules (e.g. acute and chronic food deprivation and acute feeding after chronic food deprivation). However, the effects of different feeding schedules on AMPH-induced locomotor activity are yet to be explicated. Here, we have explored the stimulatory responses of acutely administered d-amphetamine in locomotion under systematically varying feeding states (fed/sated and food deprivation) and schedules (chronic and acute) in zebrafish larvae. We used wild-type and transgenic[Tg(mnx1:GCaMP5)] zebrafish larvae and measured swimming activity and spinal motor neuron activity in vivo in real-time in time-elapsed and cumulative manner pre- and post-AMPH treatment. Our results showed that locomotion and motor neuron activity increased in both chronic and acute food deprivation post-AMPH treatment cumulatively. A steady increase in locomotion was observed in acute food-deprivation compared to an immediate abrupt increase in chronic food-deprivation state. The ad libitum-fed larvae exhibited a moderate increase both in locomotion and motor neuron activity. Conversely to all other caloric states, food-sated (acute feeding after chronic food deprivation) larvae moved moderately less and exhibited a mild decrease in motor neuron activity after AMPH treatment. These results point to the importance of the feeding schedule in modulating amphetamine’s characteristic stimulatory response on behavior and motor neurons.
NEAR: Neural Embeddings for Amino acid Relationships

We present NEAR, a method based on representation learning that is designed to rapidly identify good sequence alignment candidates from a large protein database. NEAR’s neural embedding model computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of k-NN search, filtration, and neighbor aggregation. NEAR’s ResNet embedding model is trained using an N-pairs loss function guided by sequence alignments generated by the widely used HMMER3 tool. Benchmarking results reveal improved performance relative to state-of-the-art neural embedding models specifically developed for protein sequences, as well as enhanced speed relative to the alignment-based filtering strategy used in HMMER3’s sensitive alignment pipeline.
Anomalies in effectiveness: A mathematical model used in international volleyball (Anomalías de la efectividad: un modelo matemático utilizado en el voleibol internacional)

Based on the analysis of the mathematical statistical model "Effectiveness", internationally used to process technical-tactical performance in Volleyball, and also to determine its target under the concept "Effectiveness", including its basic characteristics, the paper demonstrates the existence of three mathematical anomalies in the formula. These anomalies are described through examples, including a population-based study that determined that the technical-tactical action Service, Dig and Block have more negative than positive actions, closely related to a fundamental anomaly that causes inaccurate interpretations of reality. Resumen. Partiendo del analisis del modelo matematico de “Efectividad”, utilizado internacionalmente para procesar el rendimiento tecnico-tactico del Voleibol, y luego de determinar su objetivo atendiendo al concepto “Efectividad”, asi como sus caracteristicas basicas, en el articulo se demuestra la existencia de tres anomalias en la formula. Dichas anomalias son expuestas a traves de ejemplos, donde se incluye un estudio poblacional que determina que los fundamentos tecnico-tacticos Saque, Defensa de Campo y Bloqueo presentan mas acciones negativas que positivas, aspecto estrechamente relacionado con una anomalia fundamental que provoca interpretaciones inexactas de la realidad.
QUAL-IF-AI: Quality Control of Immunofluorescence Images using Artificial Intelligence

Fluorescent imaging has revolutionized biomedical research, enabling the study of intricate cellular processes. Multiplex immunofluorescent imaging has extended this capability, permitting the simultaneous detection of multiple markers within a single tissue section. However, these images are susceptible to a myriad of undesired artifacts, which compromise the accuracy of downstream analyses. Manual artifact removal is impractical given the large number of images generated in these experiments, necessitating automated solutions. Here, we present QUAL-IF-AI, a multi-step deep learning-based tool for automated artifact identification and management. We demonstrate the utility of QUAL-IF-AI in detecting four of the most common types of artifacts in fluorescent imaging: air bubbles, tissue folds, external artifacts, and out-of-focus areas. We show how QUAL-IF-AI outperforms state-of-the-art methodologies in a variety of multiplexing platforms achieving over 85% of classification accuracy and more than 0.6 Intersection over Union (IoU) across all artifact types. In summary, this work presents an automated, accessible, and reliable tool for artifact detection and management in fluorescent microscopy, facilitating precise analysis of multiplexed immunofluorescence images.
Nephrectomy and high-salt diet inducing pulmonary hypertension and kidney damage by increasing Ang II concentration in rats

Background Pulmonary hypertension (PH) is a common complication in patients with chronic kidney disease (CKD), affecting prognosis. However, the pathogenesis is not clear, and the lack of a stable animal model is a significant factor. Methods In this study, a rat model of chronic kidney disease with pulmonary hypertension (CKD-PH) was developed through 5/6 nephrectomy combined with a high-salt diet. The model’s hemodynamics and pathological changes in multiple organs were dynamically assessed. Lung tissues and serum were collected from the model rats to measure the expression of ACE2, the expression levels of vascular active components related to the renin-angiotensin-aldosterone system (RAAS), and changes in the serum metabolic profile of the model. Results After 14 weeks post-surgery, the CKD-PH rat model exhibited significant changes in hemodynamic parameters indicative of pulmonary arterial hypertension, along with alterations such as right ventricular hypertrophy. However, no evidence of pulmonary vascular remodeling was observed. An imbalance in the renin-angiotensin-aldosterone system was identified in the CKD-PH rat models. Downregulation of ACE2 expression was observed in pulmonary tissues. The serum metabolic profile of the CKD-PH rat models showed distinct differences compared to the sham surgery group. Conclusions The development of pulmonary arterial hypertension in CKD-PH rats may be primarily attributed to the disruption of the renin-angiotensin-aldosterone system (RAAS), coupled with a decrease in ACE2 expression in pulmonary vascular endothelial tissues and metabolic disturbances.
Product Backlog Rating: A Case Study On Measuring Test Quality In Scrum

Agile software development methodologies focus on software projects which are behind schedule or highly likely to have a problematic development phase. In the last decade, Agile methods have transformed from cult techniques to mainstream methodologies. Scrum, an Agile software development method, has been widely adopted due to its adaptive nature. This paper presents a metric that measures the quality of the testing process in a Scrum process. As product quality and process quality correlate, improved test quality can ensure high quality products. Also, gaining experience from eight years of successful Scrum implementation at SoftwarePeople, we describe the Scrum process emphasizing the testing process. We propose a metric Product Backlog Rating (PBR) to assess the testing process in Scrum. PBR considers the complexity of the features to be developed in an iteration of Scrum, assesses test ratings and offers a numerical score of the testing process. This metric is able to provide a comprehensive overview of the testing process over the development cycle of a product. We present a case study which shows how the metric is used at SoftwarePeople. The case study explains some features that have been developed in a Sprint in terms of feature complexity and potential test assessment difficulties and shows how PBR is calculated during the Sprint. We propose a test process assessment metric that provides insights into the Scrum testing process. However, the metric needs further evaluation considering associated resources (e.g., quality assurance engineers, the length of the Scrum cycle).
Visitors' Cognition on Forest Issues and Environmental Attitudes in Forest Recreation Areas: The Case of Hsin-Hua and Hui-Sun Forest Stations

III 目錄. V 表目錄. VII 圖目錄. IX 第一章 前言. 1 第二章 文獻回顧. 4 第一節 臺灣森林經營的發展與趨勢. 4 第二節 林地分區的重要性及目前臺灣之林地分區. 10 第三節 民眾涉入林業政策及目前臺灣森林經營面臨的議題. 19 第四節 民眾對於環境態度的認知與重要性. 35 第五節 相關環境態度量表的應用與研究. 37 第三章 研究材料與方法. 49 第一節 研究區域. 49 第二節 問卷設計. 52 第三節 研究方法. 54 第四章 結果與討論. 60 第一節 預試問卷分析. 60 第二節 不同森林遊樂區遊客對森林議題與環境態度認知比較. 64
Structural Difﬁculty in Estimation of Distribution Genetic Programming

Estimation of Distribution Algorithms were introduced into Genetic Programming over 15 years ago, and have demonstrated good performance on a range of problems, but there has been little research into their limitations. We apply two such algorithms – scalar and vectorial Stochastic Grammar GP – to Daida’s well-known Lid problem, to better understand their ability to learn speciﬁc structures. The scalar algorithm performs poorly, but the vectorial version shows good overall performance. We then extended Daida’s problem to explore the vectorial algorithm’s ability to ﬁnd even more speciﬁc structures, ﬁnding that the performance fell oﬀ rapidly as the speciﬁcity of the required structure increased. Thus although this particular system has less severe structural diﬃculty issues than standard GP, it is by no means free of them.
Antivirus evasion by user mode unhooking on Windows 10

Several antivirus products place inline user mode hooks in an attempt to recognize malicious behaviour of processes. Removing these hooks is called unhooking and can make malicious activity invisible to the antivirus software. We applied unhooking on a Windows 10 system that was runningantivirussoftwarethatplacedusermodehooks.Ma-liciouspayloadsthatcallhookedfunctionswerecreatedas targetprocessesforfiveimplementedunhookingtechniques. These five techniques consist of three existing ones: Section Remapping, Prologue Restoring and Perun’s Fart, as well as two novel techniques introduced in this study: Interprocess Function Copying and Interprocess Section Copying. Wefoundthatallunhookingtechniqueswereabletoremovehooksandnoneofthemweredetected.Inmostcasesatrig-geredhookedfunctiondidnotleadtoanantivirusalert. Althoughthequantityofantivirusproductsandtestedhookedfunctionsdonotallowustomakestatementsingeneral, thisstudyshowsthatusermodeunhookingcanbeusedfor antivirusevasiontoday.Alternativestousermodehooking shouldbefoundinsecuritymechanismsthatdonotallow tamperingbyusinguserpermissions.
Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata

ABSTRACT Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.
Analysis and Improvement Plans on Visualization Systems for Word Analysis: Focused on Word2Vec

As a number of studies on big data have been conducted, a great deal of information is extracted and shared by analyzing data. Studies on extracting useful information through artificial neural network based machine learning from accumulated voluminous document data have been made. Recently, Word2Vec that has overcome complexity of natural language processing machine learning has appeared as an efficient model to extract a link between words. A study on extracting similar words and visualizing information through Word2Vec model is being conducted. Visualization system helps people to easily perceive information by maximizing understanding of information extracted from big data. This study will analyze visualization system cases of Word2Vec model to find visualization system which is easy for people to understand
The Turkish and South Korean automobile industries and the role of the state in their development

This paper is an attempt to identify the role of the state in the development of the Korean and Turkish automobile industries. South Korea and Turkey started to produce passenger cars at around the same time in the early 1960s. Turkey was the leader in production in the early 1970s, but from 1978 onwards Korea took the lead and finally became the fourth largest automobile manufacturer in the world in 1999. The Turkish automobile industry, on the other hand, was marginalized. This paper suggests that one of the main reasons for this has been the diminishing role of the state in the industrialization efforts in Turkey from the late 1970s on. In light of a comparative historical analysis of the development of Korean and Turkish automobile industries, it is argued that the pace of industrial transformation can be accelerated by well-directed pro-active state intervention.
Segmentac¸˜ao de Imagens de Fundo de Olho e Identificac¸˜ao de Padr˜ao ISNT para Aux´ılio ao Diagn ´ostico de Glaucoma

—O glaucoma ´e uma doenc¸a silenciosa e progressiva que pode levar os pacientes a total perda de vis˜ao, por essa raz˜ao o diagn´ostico precoce ´e importante. M´etodos de vis˜ao computacional podem servir como um aux´ılio aos especialistas na detecc¸˜ao precoce. Esse trabalho teve como objetivo utilizar um modelo de rede neural artificial para detectar a ´area de interesse para detecc¸˜ao do glaucoma, e tamb´em fazer anotac¸˜oes da ´area de escavac¸˜ao e disco ´optico. O modelo de detecc¸˜ao da ´area de interesse alcanc¸ou um mAP de 99,2%, e o modelo de detecc¸˜ao das ´areas de escavac¸˜ao e disco ´optico alcanc¸ou um mAP de 92%.