bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cryo-EM analysis of Pseudomonas phage Pa193 structural components
Authors: Cingolani Gino , Iglesias Stephano , Hou Chun-Feng , Lemire Sebastien , Soriaga Angela , Kyme Pierre 
Published: April 2024

Abstract

The World Health Organization has designated Pseudomonas aeruginosa as a critical pathogen for the development of new antimicrobials. Bacterial viruses, or bacteriophages, have been used in various clinical settings, commonly called phage therapy, to address this growing public health crisis. Here, we describe a high-resolution structural atlas of a therapeutic, contractile-tailed Pseudomonas phage, Pa193. We used bioinformatics, proteomics, and cryogenic electron microscopy single particle analysis to identify, annotate, and build atomic models for 21 distinct structural polypeptide chains forming the icosahedral capsid, neck, contractile tail, and baseplate. We identified a putative scaffolding protein stabilizing the interior of the capsid 5-fold vertex. We also visualized a large portion of Pa193 ~ 500 Å long tail fibers and resolved the interface between the baseplate and tail fibers. The work presented here provides a framework to support a better understanding of phages as biomedicines for phage therapy and inform engineering opportunities.
Additive Manufacturing and Mechanics of Mathematically-generated Meta-structures
Authors: Huffman Brandon , Singh Anil , Koohbor Behrad , Youssef George 
Published: April 2024

Abstract

Advancements in additive manufacturing coincide with the influx of assiduous research in realizing complex structures using printable composite materials with tunable properties. In this research, photocurable resins with a broad range of mechanical properties were hybridized with ceramic particles to alter the overall response. The newly formulated printable resins comprised up to 20 wt.% glass microballoons, balancing between the tunability of the composite properties and manufacturability. The compressive and tensile bulk properties were first assessed using additively manufactured samples tested under quasi-static loading. Supplementary digital image correlation (DIC) was used to resolve the strain fields, revealing insights about the mechanical behavior and failure modes as a function of reinforcement weight ratio. Despite the expected hyperelastic constitutive behavior and shared macromolecular composition, the neat and hybridized photocurable resins exhibited distinctive mechanical behavior, leading to the characterization of the dynamic properties as a function of temperature to ascertain the underpinnings of respective responses. To demonstrate the utility of newly formulated printable composite resins, triply periodic minimal surface (TPMS) structures were also manufactured using the vat photopolymerization approach. The printed structures were tested under compression at a quasi-static loading rate. The DIC-resolved strains revealed the underlying structural mechanics as a function of the material properties. This case study correlates the mechanics governing particulate-reinforced elastomers with the observed variations in strain development, stiffness, load-bearing capacity, and specific energy absorption for TPMS structures. The outcomes of this research reveal the potential for tunable, 3D printed sports gear for impact mitigation in various biomechanical loading conditions.
The PPP2R1A cancer hotspot mutant p.R183W increases clofarabine resistance in uterine serous carcinoma cells by a gain-of-function mechanism
Authors: Remmerie Michiel , Dok Rüveyda , Wang Zhigang , Omella Judit Domènech , Alen Sophie , Cokelaere Célie , Lenaerts Lisa , Dreesen Erwin , Nuyts Sandra , Derua Rita , Janssens Veerle 
Published: April 2024

Abstract

Purpose: Uterine serous carcinoma (USC) is generally associated with poor prognosis due to a high recurrence rate and frequent treatment resistance; hence, there is a need for improved therapeutic strategies. Molecular analysis of USC identified several molecular markers, useful to improve current treatments or identify new druggable targets. PPP2R1A, encoding the Aα subunit of the tumor suppressive Ser/Thr phosphatase PP2A, is mutated in up to 40% of USC. Here, we investigated the effect of the p.R183W PPP2R1A hotspot variant on treatment response to the nucleoside analogue clofarabine.
Methods & Results: USC cells stably expressing p.R183W Aα showed increased resistance to clofarabine treatment in vitro and in vivo, corroborated by decreased clofarabine-induced apoptosis, G1 phase arrest, DNA-damage (γH2AX) and activation of ATM and Chk1/2 kinases. Phenotypic rescue by pharmacologic PP2A inhibition or dicer-substrate siRNA (dsiRNA)-mediated B56δ subunit knockdown supported a gain-of-function mechanism of Aα p.R183W, promoting dephosphorylation and inactivation of deoxycytidine kinase (dCK), the cellular enzyme responsible for the conversion of clofarabine into its bioactive form. Therapeutic assessment of related nucleoside analogues (gemcitabine, cladribine) revealed similar effects, but in a cell line-dependent manner. Expression of two other PPP2R1A USC mutants (p.P179R or p.S256F) did not affect clofarabine response in our cell models, arguing for mutant-specific effects on treatment outcome as well.
Conclusions: While our results call for PPP2R1A mutant and context-dependent effects upon clofarabine/nucleoside analogue monotherapy, combining clofarabine with a pharmacologic PP2A inhibitor proved synergistically in all tested conditions, highlighting a new generally applicable strategy to improve treatment outcome in USC.
Physics-Aware Tuning of Unscented Kalman Filter:Statistical Framework for Solving Inverse Problems Involving Nonlinear Dynamical Systems and Missing Data
Authors: Ghorbani Esmaeil , Dollon Quentin , Gosselin Frederick P. 
Published: April 2024

Abstract
The performance of the Unscented Kalman Filter (UKF) strongly depends on the proper choice of measurement and process uncertainty matrices, as well as on the scaling parameter of the unscented transform. To avoid cumbersome trial-and-error manual settings in finding the optimal hyperparameters, we introduce a hands-off meta-optimization framework, which incorporates a nonlinear mesh adaptive direct search optimization algorithm in an offline outer loop, paired with a physics-aware loss function. The novelty of this approach is twofold. First, a physics-aware loss function is used to optimize the UKF hyperparameters. It minimizes the physical discrepancy induced by the data-driven correction of the prior states during filtering. Notably, sensor data are not directly incorporated into the calculation of the loss function, which expedites the tuning of the filter in weakly informative data scenarios, especially when the underlying physics is well understood. Second, UKF relaxation is embedded in the optimization to make the measurement and process noise covariance matrices adaptive, which greatly reduces the dimension of the optimization space while remaining very general with respect to the structure of the matrices. We demonstrate the effectiveness of the proposed framework, as the cornerstone of a future digital twin technology combining data- and physics-based models, through various classical problems in solid mechanics, rotating machinery, civil engineering, and fluid-solid interaction.
Enhanced Medical Image Analysis: Leveraging 3D Visualization and VR-AR Technology
Authors: Prabha Navaneeth , Prasad Navya , Ziyad Naeema , Abraham Jisha P , T Pristy Paul , Paul Rini T 
Published: April 2024

Abstract

Modern healthcare depends heavily on medical imaging, but traditional 2D images frequently lack depth and detail. This paper introduces a novel approach, that turns 2D medical images, such as X-rays, MRIs, and CT scans, into immersive three-dimensional visualizations by utilizing virtual and augmented reality (VR/AR) technology. The process consists of four steps: acquiring DICOM medical data, converting the data into 3D models, applying the rendering modes and slicing planes, and deploying the data in VR/AR environments. Preprocessing methods evaluate and improve the quality of medical image data, which is essential for precise analysis and is guided by mathematical formulas. Advanced techniques like alpha shapes and Delaunay triangulation are used to transform 2D medical images into realistic 3D models. Mesh fidelity and clarity are optimized by surface reconstruction techniques, which are motivated by mathematical representations. The surface mesh is refined using Laplacian smoothing and surface subdivision algorithms, which guarantee geometric accuracy and visual quality. Furthermore, Hausdorff distance is used to evaluate the generated 3D models' accuracy, guaranteeing fidelity and dependability in medical visualization. This technology offers the potential to improve surgical planning accuracy, streamline medical education, and foster deeper understanding by facilitating interactive exploration of intricate anatomical structures.
Exploring the experiences of COVID-19 survivors with a history of admission to the respiratory intensive care unit (RICU): A phenomenological study in Iran
Authors: Mehni Esmaeil Barkhori , Rafati Foozieh , Abbasi Mohsen , Rafati Shideh , Ahmadidarrehsima Sudabeh 
Published: April 2024

Abstract
COVID-19 is still spreading around the world. To this end, the present study sought to explore the experiences of COVID-19 survivors with a history of admission to ICUs in southern Iran. This study was conducted using descriptive phenomenology on twelve COVID-19 survivors with a history of admission to the ICU. The patients were selected using purposive sampling. The data were collected through face-to-face semistructured interviews with the patients. The collected data were analyzed using the seven steps of Colaizzi analysis. Data analysis revealed 3 main themes: better resources and facilities, unpleasant physical and psychological experiences, and pain relievers. COVID-19 survivors who were admitted to the RICU reported that they had many positive and negative experiences. Thus, health officials, experts, nurses, and physicians need to pay special attention to the problems faced by COVID-19 patients admitted to ICUs.
Impact of Tent Shade on Heat Exposures and Simulated Heat Strain for People Experiencing Homelessness
Authors: Karanja Joseph , Vanos Jennifer , Joshi Ankit , Penner Scott , Echavvaria Gisel Guzman , Connor Dylan S. , Rycaczewski Konrad 
Published: April 2024

Abstract

Concurrent increases in homelessness and heat intensity, duration, and frequency translate to an urban heat risk trap for the unsheltered population. Homelessness is both a driver and consequence of poor health, co-creating distinct geographies with various risk factors that exacerbate heat vulnerability. We tested the efficacy of different tent shadings over identical tents often observed in the Phoenix area (white bedsheet, mylar, tarp, and aluminum foil) and compared them to a control tent (uncovered) and ambient conditions. We monitored all meteorological variables at all six locations, notably Mean Radiant Temperature (MRT). The in-tent microclimate variability was applied to complete statistical and physiological modeling including the use of behavioral or recreational drugs on heat strain. Findings indicate that tent shadings resulted in significantly lower in-tent MRT during the day (p < 0.05), but exacerbated in-tent thermal risk during the night compared to the control tent and ambient conditions. Furthermore, we found evidence that the temperature metric matters, and using only either MRT or air temperature (Tair) to assess “heat” could lead to inconsistent conclusions about in-tent microclimate. Interactions between shade types and time significantly amplified in-tent thermal risk. Physiological modeling indicates a higher risk of heat strain (core temperature beyond 40˚C) for those taking certain drugs. Decision makers should promote testing different heat intervening strategies toward realizing effective means of protecting human life and preventing heat illnesses. This study illuminates the need for an interdisciplinary approach to studying tents as shelters that considers the total heat load with heat strain modeling.
Reduced-order dynamics of coupled self-induced stochastic resonance quasiperiodic oscillators driven by varying noise intensities
Authors: Zhu Jinjie , Zhao Feng , Liu Xianbin 
Published: April 2024

Abstract
Noise can induce nontrivial behaviors in systems with multiple timescales. The dynamical reduction of fast-slow systems remains a challenging and intriguing problem. Self-induced stochastic resonance is a noise-induced coherent phenomenon that noise is introduced to the fast dynamics. By applying the embedding phase reduction approach, the synchronization behaviors of two non-identically coupled self-induced stochastic resonance oscillators are investigated. The first passage time distribution on the slow manifolds, which is crucial in the reduced phase equation, is well approximated by the Weibull distribution and is continuously estimated regarding the noise intensity by the polynomial interpolation. The effectiveness of the reduced phase equation is validated by the Monte Carlo simulations. The methods and results may motivate data-based investigations on other multiple timescale systems and experimental findings.
Explaining Midwives’ Experiences in Adjusting to the Role of Healthcare Providers in Health Transformation Plan in Iran: A Qualitative Study
Authors: moradali monireh rezaee , hajian sepideh , Majd Hamid Alavi , Rahbar Mohammadreza , Entezarmahdi Rasool 
Published: April 2024

Abstract

Background Due to their exhaustive tasks and multiple delegated responsibilities, midwives face numerous intricacies as healthcare providers after the implementation of the health transformation plan. This role shift compels them to fulfill their responsibilities in their new positions despite its incompatibility with the capacities of the academic field and the nature of the profession. The present study explains midwives’ experiences in adjusting to the role of healthcare providers in the health transformation plan in Iran. Methods This qualitative study collected data with open-ended questions In-depth semi-structured interviews with 18 midwives working in the healthcare centers of Urmia in West Azerbaijan and analyzed them using Zhang and Wildemuth’s 8-step conventional content analysis approach run in the MAXQDA software. Results Data analysis led to the emergence of two themes, seven main categories, and 19 subcategories. The first theme, namely ‘efficient adjustment’, encompassed two main categories: ‘providing high-quality services’ and ‘inner satisfaction’, and the second theme, i.e., ‘inefficient adjustment’, was explained by five main categories, including ‘low-quality services’, ‘reduced utilization’, ‘emotional fatigue’, ‘systemic bullying’, and ‘changes in social expectations’. Conclusion It seems that being satisfied with providing services to clients and accountability are the paramount factors associated with healthcare midwives’ adjustment, and this job satisfaction depends on the specialty of delegated responsibilities, correction of the rules in this plan, and preservation of midwives’ dignity and career grace.
Unlocking Forex Market Trends: Advanced Predictive Modeling with Tree Ensembles
Authors: Thao Nguyen Ngoc , Nguyen Hoa-Cuc. , Mach Bich-Ngoc. , Thuan Do Duc , Quynh Trinh Thi Nhu , Huong Tran Thu , Chi Duong Thi Kim , Nguyen Thanh Q. 
Published: April 2024

Abstract

In this study, the author constructed a draft model to assess and predict the fluctuations of the foreign exchange (Forex) market using the Tree Ensembles ensemble learning method, combining three main models: Random Forest, Gradient Boosting Machines (GBM), and XGBoost. The author focused on applying predictive indicators of Forex trading to develop techniques to help investors detect growth trends through market buy and sell prices. As a result, the model provided accurate predictions of market trends, ensuring stability and high accuracy, surpassing other machine learning methods currently being applied. Particularly, the forecasting method from the model demonstrated the ability to handle various types of data flexibly, including numerical and text data, without requiring excessive preprocessing. This opens the door for applying the model to real-life situations where data is often diverse and complex. In summary, this study not only provides an effective method for predicting Forex market fluctuations but also suggests significant potential for the development of assessment and prediction models in the currency field in the future.
Utilizing Graph Theory for Ecological Planning: Enhancing Connectivity of Urban Green Spaces in Bhopal, Madhya Pradesh, India
Authors: Rajput pradeep kumar 
Published: April 2024

Abstract
Graph theory and network analysis are efficient to explore landscape connectivity. Graph theory approach using in urban planning to facilities the municipal service in the urban landscape. The municipal service is an important and proper functional movement in the urban landscape. In this paper, the use of graph-theoretic approaches is operational within the urban landscape assessment, planning, and design. Urban landscape for proper planning and design of urban land without disturbance of an ecosystem. The connectivity is important to exchange their genetic material for the proper functioning of the ecosystem in the urban landscape. In particular, the network model uses to evaluate the contribution of landscape elements to uphold the connectivity. The importance of spatially and geographically area representation the network in urban & regional planning and design is stressed. The study moves the better connectivity of urban green space for the functional ecosystem. Graph theory approach identifies the Intra connectivity(IC), Betweeness centrality (BC), connector, a number of links (NL), Harry Index (HI), landscape coincide Probability (LCP), and integral index connectivity (IIC) in the urban landscape for systematic planning and order to increase the efficiency of monitoring and sustainable urban development. Using a graph theory approach for patch connectivity with integral index connectivity (IIC). Here threshold distance for connectivity is 2m, 20m, 44m, and 100m. Connectivity of urban green space for dispersal of species for one patch to the rest of other patches slightly increases and identifies the prioritize patches for ecological improvement. This paper Examine the protecting ecosystem and sustainable urban development and planning in the future prospectus
Failed Ahmed Glaucoma Valves: Trabeculectomy versus Repeat Shunt Surgery
Authors: Einollahi Neda , Doozandeh Azadeh , Sharifipour Farideh , Hassanpour Kiana , Rezaei Javad , Radmehr Hamed , Yazdani Shahin 
Published: April 2024

Abstract

Introduction: To investigate the outcomes of trabeculectomy (TRAB) versus repeat Ahmed glaucoma valve (re-AGV) implantation in eyes with Ahmed glaucoma valve (AGV) failure.
Methods: This quasi-experimental study reports patients with AGV failure requiring additional surgical intervention between 2018 and 2022. Patients in the TRAB group underwent a fornix-based procedure with mitomycin C 0.01% injection (0.1 mL). Eyes in the re-AGV group underwent repeat shunt surgery. The choice of the procedure was based on surgeon’s discretion. The primary outcome measure was surgical success rates based on various intraocular pressure (IOP) targets and percentages of reduction from baseline: IOP ≤ 21 mmHg and 20% reduction (conventional criteria), IOP ≤ 18 and 20% reduction (criterion A), IOP ≤ 15 and 25% reduction (criterion B), and IOP ≤ 12 and 30% reduction (criterion C).
Results: Forty-eight eyes of 48 patients are reported herein, consisting of 22 eyes of 22 patients undergoing TRAB and 26 eyes of 26 subjects undergoing re-AGV. No significant difference was observed between the study groups in terms of initial diagnoses, baseline IOP or the number of prior surgeries. The cumulative probability of survival at one year was significantly higher in the trabeculectomy group using the three stricter success definitions. In both study groups, IOP was significantly reduced from baseline at all postoperative visits, and was significantly lower in the TRAB group at all time points beyond one month. At 12 months, 5% of TRAB versus 48% of re-AGV eyes required glaucoma medications (P<0.001). The rate of complications was comparable between the study groups (P=0.76) but there was a trend toward a greater need for repeat surgery in the re-AGV group (4 eyes versus nil, P=0.07).
Conclusions: Trabeculectomy can be considered a safe and effective surgical option in eyes with failed AGV leading to significantly lower IOP levels and more favorable success rates than re-AGV in selected patients.
Action Unit-Based 3D Face Reconstruction Using Transformers
Authors: Kim Hyeonjin , Wang Pei , Lee Hyukjoon 
Published: April 2024

Abstract
The reconstruction of 3D face shapes and expressions from single 2D images remains unconquered due to the lack of detailed modeling of human facial movements such as the correlation between the different parts of faces. Facial action units (AUs), which represent detailed taxonomy of the human facial movements based on observation of activation of muscles or muscle groups, can be used to model various facial expression types. We present a novel 3D face reconstruction framework called AU feature-based 3D FAce Reconstruction using Transformer (AUFART) that can generate a 3D face model that is responsive to AU activation given a single monocular 2D image to capture expressions. AUFART leverages AU-specific features as well as facial global features to achieve accurate 3D reconstruction of facial expressions using transformers. We also introduce a loss function which is to force the learning toward the minimal discrepancy in AU activations between the input and rendered reconstruction. The proposed framework achieves an average F1 score of 0.39, outperforming state-of-the-art methods.