bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping protein binding sites by photoreactive fragment pharmacophores
Authors: Ábrányi-Balogh Péter , Bajusz Dávid , Orgován Zoltán , Keeley Aaron B. , Petri László , Péczka Nikolett , Szalai Tibor Viktor , Pálfy Gyula , Gadanecz Márton , Grant Emma K. , Imre Tímea , Takács Tamás , Ranđelović Ivan , Baranyi Marcell , Marton András , Schlosser Gitta , Ashraf Qirat F. , de Araujo Elvin D. , Karancsi Tamás , Buday László , Tóvári József , Perczel András , Bush Jacob T. , Keserű György M. 
Published: July 2024

AbstractFragment screening is a popular strategy of generating viable chemical starting points especially for challenging targets. Although fragments provide a better coverage of chemical space and they have typically higher chance of binding, their weak affinity necessitates highly sensitive biophysical assays. Here, we introduce a screening concept that combines evolutionary optimized fragment pharmacophores with the use of a photoaffinity handle that enables high hit rates by LC-MS-based detection. The sensitivity of our screening protocol was further improved by a target-conjugated photocatalyst. We have designed, synthesized, and screened 100 diazirine-tagged fragments against three benchmark and three therapeutically relevant protein targets of different tractability. Our therapeutic targets included a conventional enzyme, the first bromodomain of BRD4, a protein-protein interaction represented by the oncogenic KRasG12D protein, and the yet unliganded N-terminal domain of the STAT5B transcription factor. We have discovered several fragment hits against all three targets and identified their binding sites via enzymatic digestion, structural studies and modeling. Our results revealed that this protocol outperforms screening traditional fully functionalized and photoaffinity fragments in better exploration of the available binding sites and higher hit rates observed for even difficult targets.
Simulation-based inference of developmental EEG maturation with the spectral graph model
Authors: Bernardo Danilo , Xie Xihe , Verma Parul , Kim Jonathan , Liu Virginia , Numis Adam L. , Wu Ye , Glass Hannah C. , Yap Pew-Thian , Nagarajan Srikantan S. , Raj Ashish 
Published: July 2024

AbstractThe spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unknown. Here, we assess the developmental maturation of electroencephalogram spectra via Bayesian model inversion of the spectral graph model, a parsimonious whole-brain model of spatiospectral neural activity derived from linearized neural field models coupled by the structural connectome. Simulation-based inference was used to estimate age-varying spectral graph model parameter posterior distributions from electroencephalogram spectra spanning the developmental period. This model-fitting approach accurately captures observed developmental electroencephalogram spectral maturation via a neurobiologically consistent progression of key neural parameters: long-range coupling, axonal conduction speed, and excitatory:inhibitory balance. These results suggest that the spectral maturation of macroscopic neural activity observed during typical development is supported by age-dependent functional adaptations in localized neural dynamics and their long-range coupling across the macroscopic structural network.
Dynamic quantitative phase microscopy: a single-shot approach using geometric phase interferometry
Authors: Espinosa-Momox Ana , Norton Brandon , Serrano-García David I. , Porras-Aguilar Rosario 
Published: July 2024

AbstractThere is a significant gap in cost-effective quantitative phase microscopy (QPM) systems for studying dynamic cellular processes while maintaining accuracy for long-term cellular monitoring. Current QPM systems often rely on complex and expensive voltage-controllable components like Spatial Light Modulators or two-beam interferometry. To address this, we introduce a QPM system optimized for time-varying phase samples using azobenzene liquid crystal as a Zernike filter with a polarization-sensing camera. This system operates without input voltage or moving components, reducing complexity and cost. Optimized for gentle illumination to minimize phototoxicity, it achieves a 1 Hz frame rate for prolonged monitoring. The system demonstrated accuracy with a maximum standard deviation of ±42 nm and low noise fluctuations of ±2.5 nm. Designed for simplicity and single-shot operations, our QPM system is efficient, robust, and precisely calibrated for reliable measurements. Using inexpensive optical components, it offers an economical solution for long-term, noninvasive biological monitoring and research applications.
The DNA repair protein DNA-PKcs modulates synaptic plasticity via PSD-95 phosphorylation and stability
Authors: Mollinari Cristiana , Cardinale Alessio , Lupacchini Leonardo , Martire Alberto , Chiodi Valentina , Martinelli Andrea , Rinaldi Anna Maria , Fini Massimo , Pazzaglia Simonetta , Domenici Maria Rosaria , Garaci Enrico , Merlo Daniela 
Published: July 2024

AbstractThe key DNA repair enzyme DNA-PKcs has several and important cellular functions. Loss of DNA-PKcs activity in mice has revealed essential roles in immune and nervous systems. In humans, DNA-PKcs is a critical factor for brain development and function since mutation of the prkdc gene causes severe neurological deficits such as microcephaly and seizures, predicting yet unknown roles of DNA-PKcs in neurons. Here we show that DNA-PKcs modulates synaptic plasticity. We demonstrate that DNA-PKcs localizes at synapses and phosphorylates PSD-95 at newly identified residues controlling PSD-95 protein stability. DNA-PKcs −/− mice are characterized by impaired Long-Term Potentiation (LTP), changes in neuronal morphology, and reduced levels of postsynaptic proteins. A PSD-95 mutant that is constitutively phosphorylated rescues LTP impairment when over-expressed in DNA-PKcs −/− mice. Our study identifies an emergent physiological function of DNA-PKcs in regulating neuronal plasticity, beyond genome stability.
Fatigue, Fogginess, and Sleep Complaints: Presence and Impact on Functioning After Childhood Traumatic Brain Injury
Authors: Riccardi Jessica Salley , Viola Nicole , Lundine Jennifer P. , Ciccia Angela H. 
Published: July 2024

Purpose:
The purpose of this study was to examine the occurrence and impact of fatigue, fogginess, and sleep complaints on functioning at 3, 6, 10, and 16 months after childhood traumatic brain injury (TBI).

Method:
Eighty-eight caregivers completed online surveys regarding their children with TBI, with 17 participants included at the final time point. Measures included questions related to demographic and injury characteristics, executive functioning, social relations, health-related quality of life, and fatigue, fogginess, and sleep complaints.

Results:
Fatigue, fogginess, and sleep complaints were persistent and ultimately increased at 16 months postinjury. Over half of the participants were experiencing each symptom at 16 months postinjury (i.e., 52.94% fatigue and fogginess, 58.82% sleep complaints). At 16 months postinjury, fatigue was significantly associated with female sex, and fatigue and sleep complaints were significantly associated with lower physical quality of life, but no other differences were found with symptoms and current functioning.

Conclusions:
The results of this study support that fatigue, fogginess, and sleep complaints can persist (from baseline, from postinjury, and in fluctuation) chronically for about half of the children with TBI but little association or impact on other domains of functioning. The present study supports the continued investigation of fatigue, fogginess, and sleep complaints after childhood brain injury, but further investigation with a larger sample size is necessary to inform clinical practices for assessment and management, particularly for speech-language pathologists in rehabilitation and educational settings.
Non-thermal radio emission in Sakurai’s Object
Authors: Hajduk M. , van Hoof P. A. M. , Zijlstra A. A. , Van de Steene G. , Kimeswenger S. , Barría D. , Tafoya D. , Toalá J. A. 
Published: July 2024

Context. The very late thermal pulse (VLTP) affects the evolution of ∼20% of 1–8 M⊙ stars, repeating the last red giant phases within a few years and leading to the formation of a new, but hydrogen-poor, nebula within the old planetary nebula. The strong dust formation in the latter obscures the optical and near-infrared radiation of the star.
Aims. We aimed to determine the reheating timescale of the central star in Sakurai’s Object, which is an important constraint for the poorly understood VLTP evolution.
Methods. We observed the radio continuum emission of Sakurai’s Object for almost 20 years, from 2004 to 2023. Continuous, multi-frequency observations proved to be essential for distinguishing between phases dominated by photoionization and shock ionization.
Results. The flux density fluctuates by more than a factor of 40 within months to years. The spectral index remained negative between 2006 and 2017 and has been close to zero since 2019. The emission region has been only barely resolved since 2021.
Conclusions. Non-thermal radio emission observed from 2004 to 2017 traces shocks induced by wind interactions due to discrete mass-loss events. Thermal emission dominates from 2019 to 2023 and may indicate photoionization of the nebula by the central star.
The YMDB catalog: Young massive detached binaries for the determination of high-precision absolute stellar parameters
Authors: Martín-Ravelo Pablo , Gamen Roberto , Arias Julia I. , Chené André-Nicolas , Barbá Rodolfo H. 
Published: July 2024

Context. Massive stars play a crucial role in the cosmic dynamics and chemical evolution of galaxies. Despite their significance, our understanding of their evolution and properties remains limited. An accurate determination of stellar parameters, such as the mass and radius, is essential for advancing our knowledge. Detached eclipsing binaries (DEBs) are particularly valuable for these determinations due to the minimal interaction between their stellar components, allowing for precise measurements.
Aims. This study aims to introduce the Young Massive Detached Binary (YMDB) catalog, designed to address the gap in the high-precision absolute parameter determination for young massive stars. By focusing on DEBs within the spectral range O9-B1, this catalog seeks to provide a reliable database for future astronomical studies and improve our understanding of massive star evolution.
Methods. We conducted a photometric analysis of 87 young massive stars in detached eclipsing systems using TESS light curves (LCs) that were processed through a custom pipeline. This analysis involved determining the amplitude of magnitude variations, orbital periods, times of minima, eccentricities, and the presence of apsidal motion and heartbeat phenomena. A thorough literature review was performed to obtain MK spectral classifications. We performed our own spectral classification of 19 systems to support the sample where a new classification was lacking or inconclusive.
Results. The analysis identified 20 previously unreported binary systems, with 13 newly recognized as variable stars. Among the 87 stars examined, 30 are confirmed as YMDB members, and 25 are candidates pending spectral classification. The exclusion of the remaining 32 stars is attributed to unsuitable spectral types or their nondetached binary nature. Notable findings include the identification of new LC classifications, eccentricities in 13 systems, and heartbeat phenomena in several targets.
Conclusions. The YMDB catalog offers a resource of high-quality LCs and reliable stellar classifications, serving as a valuable tool for the astronomical community.
Acute Onset, Relapsing–Remitting Choreiform Movement Disorder in A Girl with 22q11.2 Deletion Syndrome
Authors: Saottini Silvia , Brunetti Sara , Molinaro Anna , Accorsi Patrizia , Soresina Annarosa , Frigerio Michele , Fazzi Elisa Maria 
Published: July 2024

Abstract22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal microdeletion disorder, presenting after a broad spectrum of congenital abnormalities and neuropsychiatric symptoms. Movement disorder is one of the most common neurological manifestations of the syndrome. The literature reports that early Parkinson's disease and dystonia, in particular, are associated with the syndrome. We here describe the first known case of choreiform movement disorder in a girl suffering from 22q11.2DS, responsive to tetrabenazine after relapsing–remitting course.
Double Mini TightRope Suture Suspensionplasty with FCR to APL Imbrication for Thumb Basilar Joint Arthritis: Intermediate Outcomes
Authors: Meaike Joshua J. , Meaike Jesse D. , Kakar Sanjeev 
Published: July 2024

Abstract
Background We sought to evaluate the intermediate term outcomes of trapeziectomy with double Mini TightRope suture suspensionplasty and flexor carpi radialis to abductor pollicis longus imbrication for the treatment of basilar thumb joint arthritis.
Case Description We performed a retrospective review of patients from 2012 to 2021 at a single institution within a standardized protocol. Thirty-nine patients (46 thumbs) with a mean age of 61 years and clinical follow-up of 2.8 years met our inclusion criteria. Grip strength increased from 13.8 kg preoperatively to 20.3 kg postoperatively. Appositional pinch strength increased from 3.7 to 5.7 kg, while oppositional pinch strength also increased from 2.8 to 4.4 kg. Trapezial space ratio was well maintained at 0.36 postoperatively compared with 0.46 preoperatively at a mean radiographic follow-up of 2.2 years.
Literature Review and Clinical Relevance Results from our series demonstrate predictable outcomes with reduced pain levels, increased grip and pinch strengths, improved function, and preserved range of motion with few complications.
Level of Evidence III therapeutic.
Trial Registration Not applicable.
A Comparative Study of Peripheral Smear Findings with RBC Indices and Automated Analyzer Generated RBC Histograms in the Diagnosis of Anemia's
Authors: Thyagaraju Bhargavi , Doddagowda Shilpa Manigatta 
Published: July 2024

Abstract
Introduction The red blood cell (RBC) indices generated by cell counters help in the morphological classification of anemia. The importance of microscopic examination of peripheral blood smears (PBSs) stained by Leishman stain cannot be used alone when it comes to interpretation of the underlying cause of anemia. Hence, all three RBC histograms, indices, and microscopic examination of PBSs are very essential for a complete assessment of anemia.
Aims and Objectives To diagnose the type of anemia by examination of PBSs, automated cell-generated RBC histograms, and RBC indices and to compare and correlate the findings of RBC indices and automated cell-generated RBC histograms with PBS examination.
Materials and Methods This was a prospective comparative study done on 500 cases of anemia for a period of 5 months from August 2023 to December 2023 in a rural tertiary care teaching hospital and all the patients' RBC indices, RBC histogram findings, and PBS findings were noted and analyzed.
Results Among 500 samples, normocytic normochromic anemia consists of the majority of the cases 272 (54.4%), followed by microcytic hypochromic anemia cases 183 (36.6%), macrocytic anemia cases 27 (5.4%), normocytic hypochromic anemia were 10 (2%) cases, and dimorphic were 8 cases (1.6%). When compared with RBC histogram, 265 (53.0%) cases showed normal bell-shaped curve, 188 (37.6%) cases showed left shift, 27 (5.4%) cases showed broad based curve, 10 (2%) cases showed right shift, and 10 (2%) cases showed bimodal curve suggesting normocytic normochromic, microcytic hypochromic, normocytic hypochromic anemia, macrocytic, and dimorphic anemia, respectively.
Conclusion This study showed a well correlation in the findings of the automated hematology analyzer with the microscopic examination. Histogram alone could be used as a screening method but when combined with RBC indices and PBS findings, they act as useful supplements and by correlating findings of all three, we could diagnose the majority of anemia.
Leading the Way in Dementia Care: Embracing the Whole Person
Authors: Hickey Ellen M. , Douglas Natalie F. , Hopper Tammy , Bourgeois Michelle 
Published: July 2024

AbstractAudrey Holland was a leading innovator and speech-language pathologist (SLP) in adult neurological communication disabilities for over five decades. She was a pioneer in the involvement of SLPs with people with dementia, inspiring both knowledge development and clinical practice regarding language, functional communication, and quality of life in persons living with dementia. Dr. Holland was also an extraordinary mentor who has impacted many generations of researchers and clinicians. Here, four researchers in the area of dementia and communication discuss the lessons they learned from Dr. Holland that fundamentally shaped their careers and the field of dementia and speech-language pathology. Lessons learned include the following: (1) do not be afraid to stand out when you have a novel idea that will help people; (2) look for strengths to support functional communication; (3) use communication strategies to support identity, quality of life, and self-determination in adults with acquired communication disabilities, including those with dementia; (4) shift from pathologizing to coaching; and (5) challenge the status quo. This article concludes by discussing Dr. Holland's lasting legacy.
Energy-efficient synthetic antiferromagnetic skyrmion-based artificial neuronal device
Authors: Verma Ravi Shankar , Raj Ravish Kumar , Verma Gaurav , Kaushik Brajesh Kumar 
Published: July 2024

Abstract
Magnetic skyrmions offer unique characteristics such as nanoscale size, particle-like behavior, topological stability, and low depinning current density. These properties make them promising candidates for next-generation spintronics-based memory and neuromorphic computing. However, one of their distinctive features is their tendency to deviate from the direction of the applied driving force that may lead to the skyrmion annihilation at the edge of nanotrack during skyrmion motion, known as the skyrmion Hall effect (SkHE). To overcome this problem, synthetic antiferromagnetic (SAF) skyrmions that having bilayer coupling effect allows them to follow a straight path by nullifying SkHE making them alternative for ferromagnetic (FM) counterpart. This study proposes an integrate-and-fire (IF) artificial neuron model based on SAF skyrmions with asymmetric wedge-shaped nanotrack having self-sustainability of skyrmion numbers at the device window. The model leverages inter-skyrmion repulsion to replicate the IF mechanism of biological neuron. The device threshold, determined by the maximum number of pinned skyrmions at the device window, can be adjusted by tuning the current density applied to the nanotrack. Neuronal spikes occur when initial skyrmion reaches the detection unit after surpassing the device window by the accumulation of repulsive force that result in reduction of the device’s contriving current results to design of high energy efficient for neuromorphic computing. Furthermore, work implements a binarized neuronal network accelerator using proposed IF neuron and SAF-SOT-MRAM based synaptic devices for national institute of standards and technology database image classification. The presented approach achieves significantly higher energy efficiency compared to existing technologies like SRAM and STT-MRAM, with improvements of 2.31x and 1.36x, respectively. The presented accelerator achieves 1.42x and 1.07x higher throughput efficiency per Watt as compared to conventional SRAM and STT-MRAM based designs.
Self-normalization for a 1 mm3 resolution clinical PET system using deep learning
Authors: Chin Myungheon , Jafaritadi Mojtaba , Franco Andrew B , Nasir Ullah Muhammad , Chinn Garry , Innes Derek , Levin Craig S 
Published: July 2024

Abstract

Objective. This work proposes, for the first time, an image-based end-to-end self-normalization framework for positron emission tomography (PET) using conditional generative adversarial networks (cGANs). Approach. We evaluated different approaches by exploring each of the following three methodologies. First, we used images that were either unnormalized or corrected for geometric factors, which encompass all time-invariant factors, as input data types. Second, we set the input tensor shape as either a single axial slice (2D) or three contiguous axial slices (2.5D). Third, we chose either Pix2Pix or polarized self-attention (PSA) Pix2Pix, which we developed for this work, as a deep learning network. The targets for all approaches were the axial slices of images normalized using the direct normalization method. We performed Monte Carlo simulations of ten voxelized phantoms with the SimSET simulation tool and produced 26,000 pairs of axial image slices for training and testing. Main results. The results showed that 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the best performance among all the methods we tested. All approaches improved general image quality figures of merit peak signal to noise ratio (PSNR) and structural similarity index (SSIM) from ∼15 % to ∼55 %, and 2.5D PSA Pix2Pix showed the highest PSNR (28.074) and SSIM (0.921). Lesion detectability, measured with region of interest (ROI) PSNR, SSIM, normalized contrast recovery coefficient, and contrast-to-noise ratio, was generally improved for all approaches, and 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the highest ROI PSNR (28.920) and SSIM (0.973). Significance. This study demonstrates the potential of an image-based end-to-end self-normalization framework using cGANs for improving PET image quality and lesion detectability without the need for separate normalization scans.
Machine learning-based simple and fast approach for the real-time characterization of laser-induced plasma
Authors: Mahmood Mudassir , Hassan Muhammad Umair , Khurshid Muhammad Farhan , Kalyar M A 
Published: July 2024

Abstract
We report a simple approach to estimate the fast and real-time pulse-to-pulse prediction of plasma parameters, specifically electron temperature and electron number density, using an Artificial Neural network (ANN) in combination with Laser-induced breakdown spectroscopy (LIBS). In a variety of spectroscopic applications, it is essential to have real-time observation of plasma parameters. However, direct measurement of these parameters is challenging and requires complex and time-consuming calculations. Artificial Neural Network (ANN) can be used to model the relation between spectral features from recorded LIBS emission spectra and plasma parameters. The ANN is trained on a suitable preprocessed spectroscopic dataset with corresponding plasma parameters to predict electron temperature and electron number density. The accuracy of Artificial Neural Network (ANN) in predicting the plasma parameters is evaluated, and results are validated with existing conventional methods of calculating plasma parameters, namely the Boltzmann Plot Method for plasma temperature and the Stark Broadening Method for electron number density. The present results show that ANN is an effective method in accurately predicting the plasma parameters directly from the spectral features. The ability to fine-tune plasma in real time enhances control and accuracy in Pulsed Laser Deposition (PLD) process and other plasma coating techniques.