bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors and outcome of concurrent and sequential multiviral cytomegalovirus, Epstein–Barr virus, BK virus, adenovirus and other viral reactivations in transplantation
Authors: Sim Beatrice Z. , Yong Kar Yee , Slavin Monica A. , Yong Michelle K. 
Published: October 2022

Purpose of review
Reactivation of viral infections occurs frequently in immunosuppressed populations, particularly in solid organ (SOT) or allogeneic haematopoietic cell (HCT) transplant patients. Concurrent and sequential multivirus infections are common, yet risk factors and outcomes remain unclear. This review aims to identify the patients vulnerable to multivirus infections and characterize the impact of increased viral burden to formulate prevention and treatment strategies.

Recent findings
Incidences of up to 89% in SOT and 36% in HCT have been reported for two viruses, and 32% in SOT and 28% in HCT for at least three viruses. Risk factors appear related to an increased burden of immunosuppression, with most viral coinfections occurring within 12 months of transplantation. Direct viral complications such as cytomegalovirus disease are more frequent in coinfected patients, with documented prolonged duration of viraemia, higher viral load and increased end-organ disease. Graft dysfunction, acute rejection and graft-vs.-host disease (GVHD) have also been associated. Increased mortality is reported in the HCT population.

Summary
Multivirus infections occur in a significant proportion of transplant patients and is linked to immunosuppressive burden. There is increasing evidence that this leads to worse graft and patient outcomes. Further prospective studies are required to further comprehensively characterise viral epidemiology, mechanisms and treatment strategies to ameliorate this risk.
Similar Findings on 68Ga-Pentixafor PET/CT and 18F-FDG PET/CT in a Patient With Widespread Metastatic Hepatic Neuroendocrine Carcinoma
Authors: Deng Maoxue , Shu Qiaoqiao , Hu Mei , Chen Yue , Cai Liang 
Published: October 2022

Abstract
A patient with suspected malignant tumor underwent 18F-FDG PET/CT. Based on the findings, the patient was suspected of having multiple myeloma. Then the patient underwent 68Ga-pentixafor PET/CT, which showed similar results to 18F-FDG PET/CT. Finally, the patient was eventually diagnosed with neuroendocrine carcinoma.
203Pb-VMT-α-NET Scintigraphy of a Patient With Neuroendocrine Tumor
Authors: Müller Dirk , Herrmann Hendrik , Schultz Michael K. , Solbach Christoph , Ettrich Thomas , Prasad Vikas 
Published: October 2022

Abstract
In an end-stage midgut neuroendocrine tumor patient with carcinoid heart disease, right ventricular dysfunction, mildly reduced renal function, and refractory to 6 cycles of 177Lu-HA-DOTATATE therapy, planar, and 22 hours SPECT/CT images were acquired after injection of 224 MBq of 203Pb-VMT-α-NET to assess the feasibility of performing 212Pb-VMT-α-NET therapy. A comparison of the 1.5 and 22 hours SPECT/CT images with 68Ga-HA-DOTATATE PET/CT showed high uptake of 203Pb-VMT-α-NET in liver metastases matching with the results of the PET/CT investigation.
Incorporation of Genetic Studies in the Kidney Transplant Evaluation Clinic: The Value of a Multidisciplinary Approach
Authors: El Ters Mireille , Pinto e Vairo Filippo , Prochnow Carri , Schinstock Carrie , Dean Patrick , Kemppainen Jennifer , Lazaridis Konstantinos , Cosio Fernando , Fervenza Fernando C. , Cornell Lynn , Amer Hatem , Hogan Marie C. 
Published: October 2022

Background.
Recent studies identified underlying genetic causes in a proportion of patients with various forms of kidney disease. In particular, genetic testing reclassified some focal segmental glomerulosclerosis (FSGS) cases into collagen type 4 (COL4)-related nephropathy. This knowledge has major implications for counseling prospective transplant recipients about recurrence risk and screening biologically related donors. We describe our experience incorporating genetic testing in our kidney transplant multidisciplinary practice.

Methods.
Patients’ DNA was analyzed using whole exome sequencing for a comprehensive kidney gene panel encompassing 344 genes associated with kidney diseases and candidate genes highly expressed in the kidney. Results were correlated with phenotype by a multidisciplinary committee of nephrologists, renal pathologists, geneticists, and genetic counselors. Between October 2018 and July 2020, 30 recipient and 5 donor candidates completed testing.

Results.
Among recipient candidates, 24 (80%) carried the diagnosis of FSGS, 2 (6.7%) tubulointerstitial nephritis, and 1 (3.3%) nephrolithiasis, and 3 (10%) had an unknown cause of kidney disease. The yield for pathogenic/likely pathogenic variants was 43.3%, with majority being COL4 variants (53.8%). Among those with FSGS diagnosis, the yield was 10 of 24 (41.6%), with 29% reclassified into a COL4-related nephropathy. Family history of kidney disease was the only clinical characteristic difference between recipients with positive and negative results (76.9 versus 29.4%; P = 0.025). One of 5 donors tested positive for a pathogenic/likely pathogenic variant and was excluded from donation.

Conclusions.
We conclude that thoughtful use of genetic testing can be valuable for kidney donor selection and transplant recipient management.
Retinal Neurodegeneration Measured With Optical Coherence Tomography and Neuroimaging in Alzheimer Disease: A Systematic Review
Authors: Carazo-Barrios Lina , Cabrera-Maestre Andrés , Alba-Linero Carmen , Gutiérrez-Bedmar Mario , Garzón-Maldonado Francisco J. , Serrano Vicente , de la Cruz-Cosme Carlos , García-Casares Natalia 
Published: October 2022

Background:
Optical coherence tomography (OCT) has enabled several retinal alterations to be detected in patients with Alzheimer disease (AD), alterations that could be potential biomarkers. However, the relationship between the retina and other biomarkers of AD has been underresearched. We gathered and analyzed the literature about the relationship between retinal and cerebral alterations detected via neuroimaging in patients with AD, mild cognitive impairment (MCI), and preclinical AD.

Methods:
This systematic review followed the PRISMA Statement guidelines through the 27 items on its checklist. We searched in PubMed, BVS, Scopus, and the Cochrane Library, using the keywords: Alzheimer's disease, optical coherence tomography, white matter, cortex, atrophy, cortical thickness, neuroimaging, magnetic resonance imaging, and positron emission tomography. We included articles that studied the retina in relation to neuroimaging in patients with AD, MCI, and preclinical AD. We excluded studies without OCT, without neuroimaging, clinical cases, opinion articles, systematic reviews, and animal studies.

Results:
Of a total of 35 articles found, 23 were finally included. Although mixed results were found, most of these corroborate the relationship between retinal and brain disorders.

Conclusions:
More rigorous research is needed in the field, including homogenized, longitudinal, and prolonged follow-up studies, as well as studies that include all stages of AD. This will enable better understanding of the retina and its implications in AD, leading to the discovery of retinal biomarkers that reflect brain alterations in AD patients in an accessible and noninvasive manner.
Cancer incidence and mortality estimates in Arab countries in 2018: A GLOBOCAN data analysis
Authors: Al-Muftah Mariam , Al-Ejeh Fares 
Published: October 2022

AbstractArab countries are projecting continuing growth in cancer incidence and mortality which require improvements in cancer policies and management. However, there are limited studies that investigate and compare the epidemiology of cancer incidence in Arab countries with only few studies addressing the age-specific rates across cancers. Based on the 2018 estimates from the Global Cancer Observatory, this study provides a comprehensive perspective of cancer burden in 2018 in Arab-speaking countries compared to the rest of the world. The age standardized rates for incidence and mortality for all cancers combined in Arab countries were lower than the global rates but the incidence rates of non-Hodgkin and Hodgkin lymphoma, bladder, breast, and liver cancers were higher. The top-most common cancers and incidence rates, even in age-specific groups, varied between sub-regions of Arab countries (the Levant, Arabian Gulf and Arab African sub-regions), and Iraq and Egypt, suggesting some common and unique environmental factors and possible ethnic or genetic heritages. Arab countries generally had higher mortality-to-incidence ratio than the world’s ratio. This study data is essential reference parameter to evaluate and monitor progress of national initiatives for surveillance programs and clinical management improvements tailored towards reducing cancer incidence and mortality in Arab countries.
MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics
Authors: Polasky Daniel A. , Geiszler Daniel J. , Yu Fengchao , Li Kai , Ci Teo Guo , Nesvizhskii Alexey I. 
Published: October 2022

AbstractPost-translational modifications of proteins play essential roles in defining and regulating the functions of the proteins they decorate, making identification of these modifications critical to understanding biology and disease. Methods for enriching and analyzing a wide variety of biological and chemical modifications of proteins have been developed using mass spectrometry (MS)-based proteomics, largely relying on traditional database search methods to annotate resulting mass spectra of modified peptides. These database search methods treat modifications as static attachments of a mass to particular position in the peptide sequence, but many modifications undergo fragmentation in tandem MS experiments alongside, or instead of, the peptide backbone. While this fragmentation can confound traditional search methods, it also offers unique opportunities for improved searches that incorporate modification-specific fragment ions. Here, we present a new Labile Mode in the MSFragger search engine that can tailor modification-centric searches to the fragmentation observed. We show that labile mode can dramatically improve spectrum annotation rates of phosphopeptides, RNA-crosslinked peptides, and ADP-ribosylated peptides. Each of these modifications presents distinct fragmentation characteristics, showcasing the flexibility of MSFragger labile mode to improve search for a wide variety of biological and chemical modifications.
Physics-informed Deep Learning Approach to Quantification of Human Brain Metabolites from Magnetic Resonance Spectroscopy Data
Authors: Shamaei Amir M , Starcukova Jana , Starcuk Zenon 
Published: October 2022

AbstractPurpose:While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MRSI) data recently showed encouraging results; however, supervised learning requires ground truth fitted spectra, which is not practical. Moreover, this work investigates the feasibility and efficiency of the LCM-based self-supervised DL method for the analysis of MRS data.Method:We present a novel DL-based method for the quantification of relative metabolite concentrations, using quantum-mechanics simulated metabolite responses and neural networks. We trained, validated, and evaluated the proposed networks with simulated and publicly accessible in-vivo human brain MRS data and compared the performance with traditional methods. A novel adaptive macromolecule fitting algorithm is included. We investigated the performance of the proposed methods in a Monte Carlo (MC) study.Result:The validation using low-SNR simulated data demonstrated that the proposed methods could perform quantification comparably to other methods. The applicability of the proposed method for the quantification of in-vivo MRS data was demonstrated. Our proposed networks have the potential to reduce computation time significantly.Conclusion:The proposed model-constrained deep neural networks trained in a self-supervised manner can offer fast and efficient quantification of MRS and MRSI data. Our proposed method has the potential to facilitate clinical practice by enabling faster processing of large datasets such as high-resolution MRSI datasets, which may have thousands of spectra.HighlightsA novel self-supervised deep learning method for quantifying metabolite concentrations in MR spectroscopy signals.Providing a unique opportunity to quantify complex-valued MRS data in the time domain.Faster MR spectroscopy quantification with comparable accuracy to traditional methods.Investigating the impacts of the dataset size and neural network design on our proposed model
Representations in human primary visual cortex drift over time
Authors: Roth Zvi N. , Merriam Elisha P. 
Published: October 2022

AbstractPrimary sensory regions are believed to instantiate stable neural representations, yet a number of recent rodent studies suggest instead that representations drift over time. We analyzed a massive fMRI dataset using an image-computable encoding model and found systematic changes in model fits that exhibited cumulative drift over many months. Convergent analyses pinpoint changes in neural responsivity as the source of the drift, while population-level representational dissimilarities between visual stimuli were unchanged, suggesting that downstream cortical areas may read-out a stable representation, even as representations within V1 drift.
Masking effects onIso-valeric Acid Recognition by Sub-threshold Odor Mixture
Authors: Huang J. , Lin J. , Yueng R. , Wu S. , Solla L. , Acree T. 
Published: October 2022

AbstractMasking unpleasant odors with high levels of pleasant-smelling odorants is an ancient practice that has evolved into many enterprises, from perfumery to consumer products. However, effective odor masking turns out to be idiosyncratic and impermanent. Here, we used Sniff Olfactometry (SO)(Rochelle et al., 2017; Wyckoff & Acree, 2017) to investigate the psychophysics of masking during 70ms-stimulations with mixtures of the mal-odorantiso-valeric Acid (IVA) and different masking agents. IVA is a component of human sweat that can dominate its smell, and is often described in unpleasant terms, e.g., “gym locker”, “smelly feet”, “dirty clothes”, etc. Conventionally, high concentrations of positive smelling odorants are used to reduce the unpleasantness of IVA in clothing or environments contaminated with IVA. To investigate the masking effects of sub-threshold levels of masking agents (neohivernal, geraniol, florhydral, decanal,iso-longifolanone, methyliso-eugenol, ands-limonene) on IVA, we used SO to measure the probability of recognizing IVA after 70ms stimulations with headspaces containing mixtures of super-threshold concentrations of IVA and sub-threshold concentrations of IVA-suppressors for 9 subjects. On average, the single masking agent could decrease IVA-recognition probability by 14% to 72%, and a subthreshold odor mixture consisting of 6 masking agents decreased IVA recognition by 96%.
The Physiological Response of Salt and Drought-Stressed Plant to Exogenous Application of Salicylic Acid
Authors: Adebanjo Oluwatosin , Setordjie Elikplim Aku , Almat Anelya 
Published: October 2022

ABSTRACTSalinity and osmotic stress affect crop growth and yield. To meet the food demand of the increasing global population, there is a need to continually study the plant-stress factor relationship. This experiment studies the physiological response of salt and drought-stressed plant to exogenous application of salicylic acid. Tomato plants were grown in medium, under controlled conditions. The six treatments (T1 - control, T2 - MgSO4for salinity stress, T3 - 5% PEG 8000 for osmotic stress, T4 - control + salicylic acid, T5 - MgSO4+ salicylic acid, T6 - 5% PEG 8000 + salicylic acid) were replicated six times to make a total of 36 plants. The treatments were assessed for parameters associated with photosynthetic parameters and yield: chlorophyll content, net photosynthetic rate, leaf water potential, fresh arial weight, leaf ion content, intercellular carbon dioxide concentration, transpiration rate and gaseous exchange. The result showed that the exogenous application of salicylic acid increased the leaf water potential of both the stressed and non-stressed plants. However, for other parameters, the role of MgSO4 and %PEG in inducing salinity stress and drought stress. Respectively, was not clearly observed. Likewise, the exogenous application of salicylic acid showed no clear effect in stressed plants, relative to unstressed plants. Hence, the observations from this experiment showed a high variation in physiological responses and a repeat of the experiment can be considered to further investigate the validation of the role of salicylic acid in plants under salt and osmotic stress conditions.
rBahadur: Efficient simulation of high-dimensional genotype data with global dependence structures
Authors: Border Richard , Malik Osman Asif 
Published: October 2022

SummaryExisting methods for generating synthetic genotype data are ill-suited for replicating the effects of assortative mating (AM). We proposerb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution.Availability and implementationTherBahadurR library is available athttps://github.com/rborder/rBahadur.
Widespread coding of navigational variables in prefrontal cortex
Authors: Maisson David J-N. , Voloh Benjamin , Cervera Roberto Lopez , Conover Indirah , Zambre Mrunal , Zimmermann Jan , Hayden Benjamin Y. 
Published: October 2022

ABSTRACTTo navigate, we must represent information about our place in the environment. Traditional research highlights the role of the hippocampal complex in this process. Spurred by recent research highlighting the widespread cortical encoding of cognitive and motor variables previously thought to have localized function, we hypothesized that navigational variables would be likewise encoded widely, especially in the prefrontal cortex, which is often associated with control of volitional behavior. We recorded neural activity from six prefrontal structures while macaques performed a foraging task in an open enclosure. In all six regions, we found strong encoding of allocentric position, head direction, egocentric boundary distance, and linear and angular velocity. These encodings were not accounted for by distance or time to reward. Strength of coding of all variables increase along a ventral-to-dorsal gradient. Together these results argue that encoding of navigational variables is not localized to the hippocampal complex and support the hypothesis that navigation is continuous with other forms of flexible cognition in the service of action.
A Local Hebbian Rule Based Neural Network Model of Invariant Object Representation and Classification
Authors: Raj Rishabh , Yu C. Ron 
Published: October 2022

SUMMARYOur recognition of an object is consistent across conditions, unaffected by motion, perspective, rotation, and corruption. This robustness is thought to be enabled by invariant object representations, but how the brain achieves it remains unknown1. In artificial neural networks, learning to represent objects is simulated as an optimization process2. The system reduces discrepancies between actual and desired outputs by updating specific connections through mechanisms such as error backpropagation3. These operations are biologically implausible primarily because they require individual connections at all levels to be sensitive to errors found at the late stages of the network4,5. On the other hand, learning in the nervous system occurs locally, and synaptic changes depend only on pre- and post-synaptic activities6,7. It is unclear how local updates translate into coordinated changes across large populations of neurons and lead to sophisticated cognitive functions. Here we demonstrate that it is possible to achieve robust and invariant object representations in naturally observed network architectures using only biologically realistic local learning rules. Adopting operations fundamentally different from current ANN models, unsupervised recurrent networks can learn to represent and categorize objects through sensory experiences without propagating or detecting errors. This white box, fully interpretable networks can extract clean images from their corrupted forms and produce representations prospectively robust against unfamiliar perturbations. Continuous learning does not cause catastrophic forgetting commonly observed in ANNs. Without explicit instructions, the networks can classify objects and represent the identity of 3D objects regardless of perspective, size, or position. These findings have substantial implications for understanding how biological brains achieve invariant object representation and for developing biologically realistic intelligent networks that are efficient and robust.
Cyclosporin A delays the terminal disease stage inTfamKO mice without improving mitochondrial energy production
Authors: Chatel Benjamin , Varlet Isabelle , Ogier Augustin C. , Pecchi Emilie , Bernard Monique , Gondin Julien , Westerblad Håkan , Bendahan David , Gineste Charlotte 
Published: October 2022

AbstractMitochondrial myopathies are rare genetic disorders characterized by muscle weakness and exercise intolerance. Currently, no effective treatment exists for these myopathies. Interestingly, the pharmacological cyclophilin inhibitor cyclosporine A (CsA) extended lifespan and prevented loss of force and mitochondrial Ca2+overload in muscle fibers in the skeletal muscle-specificTfamknockout mouse model of lethal mitochondrial myopathy (TfamKO). The unaffected expression of proteins involved in mitochondrial energy metabolism suggests that these improvements occurred without improvement in metabolism. In this study, we aimed at investigating the effects of four weeks of CsA administration onin vivocontractile function and mitochondrial energy production inTfamKO mice. The treatment started before the terminal phase with severe muscle weakness and weight loss. Our results show that CsA treatment delayed progression into the terminal disease phase. This occurred without any obvious positive effects on mitochondrial energy production at rest or during fatigue induced by repeated contractions. In conclusion, cyclophilin inhibitors may have the potential of counteracting devastating muscle weakness in patients with mitochondrial myopathies most probably by preventing deleterious effects triggered by excessive mitochondrial Ca2+uptake rather than by improving mitochondrial energy production.