bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regulation of Hedgehog Signaling Through Arih2-Mediated Smoothened Ubiquitination and Endoplasmic Reticulum-Associated Degradation
Authors: Lv Bo , Zhang Xiao-Ou , Pazour Gregory J. 
Published: February 2022

AbstractDuring Hedgehog signaling, the ciliary levels of Ptch1 and Smo are regulated by pathway activity. At the basal state, Ptch1 localizes to cilia and prevents the ciliary accumulation and activation of Smo. Upon stimulation with Hedgehog ligand, Ptch1 exits cilia and relieves the inhibition of Smo. Uninhibited Smo concentrates in cilia, becomes activated, and activates the downstream steps of the pathway. Loss of the ubiquitin E3 ligase Arih2 elevates the cellular level of Smo, causes Smo to inappropriately localize to cilia at the at the basal state, and elevates basal expression of Hedgehog responsive genes. Mice express two isoforms of Arih2 with different N-termini, but neither isoform localizes to cilia. Instead, Arih2α is found in the nucleus and Arih2β is found on the cytoplasmic face of the endoplasmic reticulum. Re-expression of endoplasmic reticulum-localized Arih2β, but not nuclear-localized Arih2α returns the cellular Smo levels back to normal and rescues the ciliary Smo accumulation phenotype. When Arih2β is missing, protein aggregates accumulate in the endoplasmic reticulum and the unfolded protein response is activated. Inhibitor studies suggest that Arih2β functions to mark excess or misfolded Smo for degradation by endoplasmic reticulum-associated degradation. When Arih2β is defective, excess Smo, possibly misfolded, is delivered to the cell surface and cilium where it interferes with pathway regulation. These findings add another level of complexity to the Hedgehog pathway.
Differential roles of neural crest- and endothelial-derived FOXC2 in trabecular meshwork and Schlemm’s Canal in glaucomatous pathology
Authors: Norden Pieter R. , Beckmann Lisa , Fang Raymond , Ujiie Naoto , Cai Zhen , Zhang Xian , Kweon Junghun , Liu Ting , Aoto Kazushi , Quaggin Susan E. , Zhang Hao F. , Kume Tsutomu 
Published: February 2022

AbstractImpaired development and maintenance of the Schlemm’s Canal (SC) is associated with perturbed aqueous humor outflow regulation and glaucoma progression. Key molecular mechanisms, such as ANGPT/TIE2, PROX1, and VEGF-C/VEGFR-3 regulate SC development and maintenance, but mechanisms of paracrine signaling from neighboring tissues, including the trabecular meshwork (TM) are poorly understood. Here, we show Foxc2 is critical within the neural crest (NC)-derived TM and SC endothelium for development of the aqueous humor outflow pathway. In mice, NC- specific deletion of Foxc2 results in abnormal anterior eye segment development, including impaired SC morphogenesis and functional maintenance, loss of SC identity, and impaired maintenance of intraocular pressure (IOP). Visible light optical coherence tomography angiography analysis also demonstrated functional impairment of the SC in response to changes in IOP in NC-Foxc2-/- mice, suggesting increased TM stiffness. Utilization of single-cell RNA-sequencing (scRNA-seq) analysis then identified that this phenotype is predominately characterized by transcriptional changes associated with extracellular matrix organization and stiffness in TM-associated cell clusters, including increased matrix metalloproteinase (MMP) expression, which can generate soluble TIE2 that acts as an ANGPT trap. As FOXC2 is also critically involved in development of the lymphatic vasculature in other tissues, we also show that endothelial-specific deletion of Foxc2 resulted in impaired SC morphogenesis due to loss of TIE2 expression, which was rescued by deletion of the TIE2 phosphatase VE-PTP. Thus, NC-Foxc2 is critical for development of the TM, and both NC- and endothelial-Foxc2 are key for maintenance of SC identity and its morphogenesis.
Improved Heat Tolerance in Heat-acclimated Mice: The Probable Role of the PD-L1 Pathway
Authors: Qiu Minyue , Zhou Yuxin , Ye Nan , Guo Hongxia , Zhou Xiaoyang , Ding Xiaoyan , Li Jintao 
Published: February 2022

AbstractHeat stroke is a life-threatening illness and is related to systematic inflammation-induced multiple organ dysfunction. Available evidence indicates that the severity of the systematic inflammatory response in heat stroke may be related to the changes in immune regulation brought by heat acclimation. However, the mechanisms of heat acclimation are still unclear. Here, we assessed the differences in immunocyte subsets in the spleen and lymph nodes of heat-acclimated and unacclimated mice. A higher frequency of CD4+Foxp3+ Tregs was observed in heat-acclimated mice. Our results indicated that the improved heat tolerance exhibited during acute heat stress exposure was related to an increased number of Tregs. In heat-acclimated mice, an increase in the number of Tregs was able to mitigate the recruitment of neutrophils, inhibit the activation of neutrophils, and suppress the severity of acute inflammation. Increased differentiation and development of Tregs in peripheral immune organs in heat-acclimated mice might stem from enhanced expression of Foxp3 and PD-L1. Our results strongly suggest that the regulatory function of increased Tregs on neutrophils may be regulated through the PD-1/PD-L1 pathway. The anti-inflammatory effects of Tregs have never been studied in the context of heat stress-induced systemic inflammation. Thus, our results on immunoregulation involving Tregs in heat-acclimated mice might be significant for devising a potential treatment for systemic inflammatory response syndrome and heatstroke.
Zn-dependent structural transition of SOD1 modulates its ability to undergo liquid-liquid phase separation
Authors: Das Bidisha , Roychowdhury Sumangal , Mohanty Priyesh , Rizuan Azamat , Mittal Jeetain , Chattopadhyay Krishnananda 
Published: February 2022

AbstractThe toxic gain of function of Cu/Zn superoxide dismutase (SOD1) associated with the neurodegenerative disease - Amyotrophic lateral sclerosis (ALS), is believed to occur via misfolding and/or aggregation. SOD1 is also associated with stress granules (SGs) which are a type of membraneless organelle believed to form via liquid-liquid phase separation (LLPS) of several proteins containing low-complexity, disordered regions. Using a combination of experiments and computer simulations, we report here that structural disorder in two loop regions of SOD1 induced by the absence of metal cofactor - Zn, triggers its LLPS. The phase-separated droplets give rise to aggregates which eventually form toxic amyloids upon prolonged incubation. The addition of exogenous Zn to immature, metal-free SOD1 and the severe ALS mutant - I113T, stabilized the loops and restored the folded structure, thereby inhibiting LLPS and subsequent aggregation. In contrast, the Zn-induced inhibition of LLPS and aggregation was found to be partial in the case of another severe ALS-associated mutant - G85R, which exhibits reduced Zn-binding. Moreover, a less-severe ALS mutant - G37R with perturbed Cu binding does not undergo LLPS. In conclusion, our work establishes a role for Zn-dependent modulation of SOD1 disorder and LLPS as a precursor phenomenon which may lead to the formation of toxic amyloids associated with ALS.Significance StatementThe formation of membraneless organelles such as stress granules (SGs) is believed to occur through the process of liquid-liquid phase separation (LLPS) and involves numerous proteins containing intrinsically disordered regions. Whether SOD1, which is also associated with SGs and whose aggregation is associated with Amyotrophic lateral sclerosis (ALS), can independently undergo LLPS, is not known. SOD1 is a metalloenzyme which is stabilized by the metal co-factor - Zn. In this work, we utilize experimental and simulation techniques to highlight the modulation of SOD1 LLPS propensity in a Zn-dependent manner due to underlying conformational transitions between folded and partially disordered states. Our work establishes a link between SOD1 LLPS and aggregation, which is relevant to ALS pathogenesis.
Probabilistic inversions of electrical resistivity tomography data with a machine learning‐based forward operator
Authors: Aleardi Mattia , Vinciguerra Alessandro , Stucchi Eusebio , Hojat Azadeh 
Published: February 2022

ABSTRACTCasting a geophysical inverse problem into a Bayesian setting is often discouraged by the computational workload needed to run many forward modelling evaluations. Here we present probabilistic inversions of electrical resistivity tomography data in which the forward operator is replaced by a trained residual neural network that learns the non‐linear mapping between the resistivity model and the apparent resistivity values. The use of this specific architecture can provide some advantages over standard convolutional networks as it mitigates the vanishing gradient problem that might affect deep networks. The modelling error introduced by the network approximation is properly taken into account and propagated onto the estimated model uncertainties. One crucial aspect of any machine learning application is the definition of an appropriate training set. We draw the models forming the training and validation sets from previously defined prior distributions, while a finite element code provides the associated datasets. We apply the approach to two probabilistic inversion frameworks: A Markov chain Monte Carlo algorithm is applied to synthetic data, while an ensemble‐based algorithm is employed for the field measurements. For both the synthetic and field tests, the outcomes of the proposed method are benchmarked against the predictions obtained when the finite element code constitutes the forward operator. Our experiments illustrate that the network can effectively approximate the forward mapping even when a relatively small training set is created. The proposed strategy provides a forward operator that is three orders of magnitude faster than the accurate but computationally expensive finite element code. Our approach also yields the most likely solutions and uncertainty quantifications comparable to those estimated when the finite element modelling is employed. The presented method allows solving the Bayesian electrical resistivity tomography with a reasonable computational cost and limited hardware resources.
Reducing the income tax burden for households with children: an assessment of the child tax credit reform in Austria
Authors: Christl Michael , De Poli Silvia , Varga Janos 
Published: February 2022

AbstractIn this paper, we analyse the impact of the implementation of a child tax credit in Austria in 2018. We combine microsimulation techniques, labour supply modelling and dynamic general equilibrium modelling to make an ex ante evaluation of the reform, accounting also for behavioural responses of individuals. We show that although the macroeconomic effect of the Austrian reform is expected to be relatively small, accounting for feedback effects on a micro‐level is very important, especially when analysing socioeconomic and policy‐relevant indicators, such as poverty and inequality. When focusing on the distributional implications and the impact on poverty, our analysis highlights that the first‐round effects of the child tax credit substantially underestimate the increase in household income for households with children. Additionally, we find that when accounting for second‐round effects, the loss in tax revenues is partly offset. The estimated self‐financing effect of the reform is estimated to be about 13 per cent. Our results also indicate that part of the associated tax decrease can be potentially captured by the employer, meaning that gross wages are expected to fall slightly. Therefore, in the medium term, some households without children might suffer a small reduction in their disposable income. Overall, our analysis highlights the importance of accounting for second‐round effects when analysing tax reforms ex ante.
Unmanned aerial vehicles as a useful tool for investigating animal movements
Authors: Iwamoto Masamichi , Nogami Shonosuke , Ichinose Tomohiro , Takeda Keiji 
Published: February 2022

Abstract

Determining animal abundance is crucial for assessing the effectiveness of management measures against pest animals. Meanwhile, investigating animal movements has become important for conducting abundance estimations of unmarked animals since the random encounter model (REM) was published. REM is a camera trapping method that derives animal density by using contact ratio between camera traps and targeted animals that randomly move at a certain speed in a given area. However, it requires an independent value, which is animal speed. For investigating animal speed, camera traps with video recording and GPS tagging are the commonly used tools.

Unmanned aerial vehicles (UAVs) are currently used in wildlife monitoring to investigate the abundance of target species. It is evaluated as a tool that is non‐invasive and suitable for surveys in inaccessible landscapes. Considering these characteristics, we regarded a distant survey using this technology as suitable for investigating animal movements. Therefore, we proposed a method for estimating animal movements using UAVs and conducted a case study that aimed to investigate wild boars' movements.

We collected 11 video samples that successfully followed the movements of wild boars from 26 UAV flights in total, and the average speed of their movements derived from all the samples was 1.54 km/24 hr.

We found that issues can be improved, including species identification, video sample length, and animal behaviours or activity patterns. On the other hand, our method showed potential for applying to species with specific characteristics in their body size, shape or activity patterns. With improvements in the issues mentioned above, UAVs would become an alternative tool for investigating animal movements.
treetop: A Shiny‐based application and R package for extracting forest information from LiDAR data for ecologists and conservationists
Authors: Silva Carlos Alberto , Hudak Andrew T. , Vierling Lee A. , Valbuena Ruben , Cardil Adrian , Mohan Midhun , de Almeida Danilo Roberti Alves , Broadbent Eben N. , Almeyda Zambrano Angelica M. , Wilkinson Ben , Sharma Ajay , Drake Jason B. , Medley Paul B. , Vogel Jason G. , Prata Gabriel Atticciati , Atkins Jeff W. , Hamamura Caio , Johnson Daniel J. , Klauberg Carine 
Published: February 2022

Abstract

Individual tree detection (ITD) and crown delineation are two of the most relevant methods for extracting detailed and reliable forest information from LiDAR (Light Detection and Ranging) datasets. However, advanced computational skills and specialized knowledge have been normally required to extract forest information from LiDAR.

The development of accessible tools for 3D forest characterization can facilitate rapid assessment by stakeholders lacking a remote sensing background, thus fostering the practical use of LiDAR datasets in forest ecology and conservation. This paper introduces the treetop application, an open‐source web‐based and R package LiDAR analysis tool for extracting forest structural information at the tree level, including cutting‐edge analyses of properties related to forest ecology and management.

We provide case studies of how treetop can be used for different ecological applications, within various forest ecosystems. Specifically, treetop was employed to assess post‐hurricane disturbance in natural temperate forests, forest homogeneity in industrial forest plantations and the spatial distribution of individual trees in a tropical forest.

treetop simplifies the extraction of relevant forest information for forest ecologists and conservationists who may use the tool to easily visualize tree positions and sizes, conduct complex analyses and download results including individual tree lists and figures summarizing forest structural properties. Through this open‐source approach, treetop can foster the practical use of LiDAR data among forest conservation and management stakeholders and help ecological researchers to further understand the relationships between forest structure and function.
Outstanding challenges and future directions for biodiversity monitoring using citizen science data
Authors: Johnston Alison , Matechou Eleni , Dennis Emily B. 
Published: February 2022

Abstract

There is increasing availability and use of unstructured and semi‐structured citizen science data in biodiversity research and conservation. This expansion of a rich source of ‘big data’ has sparked numerous research directions, driving the development of analytical approaches that account for the complex observation processes in these datasets.

We review outstanding challenges in the analysis of citizen science data for biodiversity monitoring. For many of these challenges, the potential impact on ecological inference is unknown. Further research can document the impact and explore ways to address it. In addition to outlining research directions, describing these challenges may be useful in considering the design of future citizen science projects or additions to existing projects.

We outline challenges for biodiversity monitoring using citizen science data in four partially overlapping categories: challenges that arise as a result of (a) observer behaviour; (b) data structures; (c) statistical models; and (d) communication. Potential solutions for these challenges are combinations of: (a) collecting additional data or metadata; (b) analytically combining different datasets; and (c) developing or refining statistical models.

While there has been important progress to develop methods that tackle most of these challenges, there remain substantial gains in biodiversity monitoring and subsequent conservation actions that we believe will be possible by further research and development in these areas. The degree of challenge and opportunity that each of these presents varies substantially across different datasets, taxa and ecological questions. In some cases, a route forward to address these challenges is clear, while in other cases there is more scope for exploration and creativity.
Flouroscopic versus conventional epidural blood patch in obstetrics: A retrospective cohort study
Authors: Orbach‐Zinger Sharon , Lekar Leibzon Margarita , Gonen Ophir , Zribi Benjamin , Wazwaz Susan A. , Binyamin Yair , Heesen Michael , Matatov Yuri , Shimon Orit , Eidelman Leonid A. 
Published: February 2022

AbstractBackgroundEpidural blood patch is a common effective treatment for postdural puncture headache after accidental dural puncture during labor and may be done in conventional or fluoroscopy‐guided methods. The aim of this study was to compare intensity of headache at the time of discharge from the hospital and to compare blood volumes injected in conventional epidural blood patches versus fluoroscopic‐guided blood patches and evaluate the side effects of both method of treatment.MethodsBetween the years 2010 and 2020, 84 patients who were diagnosed with postdural puncture headache received either a conventional epidural blood patch or a fluoroscopic‐guided blood patch. Blood volumes were compared and evaluation of side effects was made based on data collected during and after the procedure.ResultsEighty‐four patients were included in this study. Fifty‐two women in the conventional epidural blood patch group and 32 in the fluoroscopic‐guided blood patch group. Women in the conventional epidural blood patch group received statistically significantly higher doses of blood than women in the fluoroscopic‐guided blood patch group: conventional method 29 ml IQR [23‐36] versus fluoroscopic method 16 ml, IQR [12‐18], p < .001 with no difference in headache pain intensity at hospital release. There was no difference between groups in hospital length of stay, or persistent PDPH. There was also no difference chronic headache or backache between the two groups.ConclusionsWomen who received fluoroscopic epidural blood patch required a much lower volume of blood injected while there was no difference between groups in headache pain intensity at discharge.
Point‐of‐care ultrasound‐first for the evaluation of small bowel obstruction: National cost savings, length of stay reduction, and preventable radiation exposure
Authors: Brower Charles H. , Baugh Christopher W. , Shokoohi Hamid , Liteplo Andrew S. , Duggan Nicole , Havens Joaquim , Askari Reza , Rehani Madan M. , Kapur Tina , Goldsmith Andrew J. 
Published: February 2022

AbstractObjectivesComputed tomography (CT) has long been the gold standard in diagnosing patients with suspected small bowel obstruction (SBO). Recently, point‐of‐care ultrasound (POCUS) has demonstrated comparable test characteristics to CT imaging for the diagnosis of SBO. Our primary objective was to estimate the annual national cost saving impact of a POCUS‐first approach for the evaluation of SBO. Our secondary objectives were to estimate the reduction in radiation exposure and emergency department (ED) length of stay (LOS).MethodsWe created and ran 1000 trials of a Monte Carlo simulation. The study population included all patients presenting to the ED with abdominal pain who were diagnosed with SBO. Using this simulation, we modeled the national annual cost savings in averted advanced imaging from a POCUS‐first approach for SBO. The model assumes that all patients who require surgery or have non‐diagnostic POCUS exams undergo CT imaging. The model also conservatively assumes that a subset of patients with diagnostic POCUS exams undergo additional confirmatory CT imaging. We used the same Monte Carlo model to estimate the reduction in radiation exposure and total ED bed hours saved.ResultsA POCUS‐first approach for diagnosing SBO was estimated to save a mean (±SD) of $30.1 million (±8.9 million) by avoiding 143,000 (±31,000) CT scans. This resulted in a national cumulative decrease of 507,000 bed hours (±268,000) in ED LOS. The reduction in radiation exposure to patients could potentially prevent 195 (±56) excess annual cancer cases and 98 (±28) excess annual cancer deaths.ConclusionsIf adopted widely and used consistently, a POCUS‐first algorithm for SBO could yield substantial national cost savings by averting advanced imaging, decreasing ED LOS, and reducing unnecessary radiation exposure in patients. Clinical decision tools are needed to better identify which patients would most benefit from CT imaging for SBO in the ED.