bluuebunny/crossref_metadata_2025_split huggingface dataset:
Encoding of inflammatory hyperalgesia in mouse spinal cord
Authors: Barkai Omer , Rayi Prudhvi Raj , Butterman Rachely , Katz Ben , Lev Shaya , Binshtok Alexander M. 
Published: July 2022

Abstract
Inflammation modifies the input–output properties of peripheral nociceptive neurons such that the same stimulus produces enhanced nociceptive firing. This increased nociceptive output enters the superficial dorsal spinal cord (SDH), an intricate neuronal network composed largely of excitatory and inhibitory interneurons and a small percentage of projection neurons. The SDH network comprises the first central nervous system network integrating noxious information. Using in vivo calcium imaging and a computational approach, we characterized the responsiveness of the SDH network in mice to noxious stimuli in normal conditions and investigated the changes in SDH response patterns after acute burn injury–induced inflammation. We show that the application of noxious heat stimuli to the hind paw of naïve mice results in an overall increase in SDH network activity. Single-cell response analysis reveals that 70% of recorded neurons increase or suppress their activity, while ∼30% of neurons remain nonresponsive. After acute burn injury and the development of inflammatory hyperalgesia, application of the same noxious heat stimuli leads to the activation of previously nonresponding neurons and desuppression of suppressed neurons. We further demonstrate that an increase in afferent activity mimics the response of the SDH network to noxious heat stimuli under inflammatory conditions. Using a computational model of the SDH network, we predict that the changes in SDH network activity result in overall increased activity of excitatory neurons, amplifying the output from SDH to higher brain centers. We suggest that during acute local peripheral inflammation, the SDH network undergoes dynamic changes promoting hyperalgesia.
Access to pediatric dermatology
Authors: Barry Kelly K. , Hawryluk Elena B. 
Published: July 2022

Purpose of review
To identify factors that impact accessibility to pediatric dermatology and review healthcare delivery models that improve access and address these barriers.

Recent findings
Up to one-third of pediatric primary care visits include a skin-related problem, yet pediatric dermatology subspecialist services are highly inaccessible. Workforce shortages and geographic, sociocultural, and economic barriers perpetuate inaccessibility. Teledermatology expands care, particularly to underserved or geographically remote communities, and reduces healthcare-related costs. Federal legislation to support telehealth services with adequate reimbursement for providers with parity between live, video, and phone visits will dictate the continued feasibility of virtual visits. Innovative care delivery models, such as language-based clinics, multidisciplinary teleconferencing, or embedded dermatology services within primary care are other promising alternatives.

Summary
Despite efforts to expand access, dermatology still ranks among the most underserved pediatric subspecialties. Improving access requires a multipronged approach. Efforts to expand exposure and mentorship within pediatric dermatology, diversify the workforce and clinical curriculum, recruit and retain clinicians in geographically underserved areas, and collaborate with policymakers to ensure adequate reimbursement for teledermatology services are necessary.
Comparison of Single-Dermatome Laparoscopic Appendectomy With Standard Laparoscopic Appendectomy in Terms of Postoperative Pain and Patient Satisfaction: A Randomized Controlled Trial
Authors: Ergin Anil , İşcan Yalin , Çiyiltepe Hüseyin , Fersahoğlu Mehmet M. , Esen Bulut Nuriye , Taşdelen İksan 
Published: July 2022

Background:
Laparoscopic appendectomy (LA), used since 1980, is a common surgical technique for acute appendicitis (AA) treatment. Laparoscopic surgical techniques can achieve higher patient satisfaction than conventional open surgery techniques. However, many patients complain of severe pain after laparoscopic abdominal surgeries. In this study, we compared single-dermatome laparoscopic appendectomy (SDLA), wherein all trocars were placed at the same dermatome field, with standard laparoscopic appendectomy (SLA), wherein trocars were placed at multiple dermatome sites, in terms of postoperative pain and patient satisfaction.

Materials and Methods:
The study was designed as a double-blind randomized controlled trial. Patients who underwent LA for AA between May 2019 and December 2019 were included in the study and randomized into 2 groups, wherein patients were included sequentially. The first group was operated with SLA surgery, whereas the second group was operated with SDLA surgery. All patients were assessed in terms of visual analog scale (VAS) scores, hemodynamic parameters, and patient satisfaction at postoperative 1, 2, 4, 6, 12, and 24 hours.

Results:
In the SLA technique, VAS values at postoperative 1, 2, and 4 hours were significantly higher than in the SDLA (P=0.009; P<0.05). No significant difference was observed between the surgical techniques in terms of VAS levels at postoperative 6, 12, and 24 hours (P>0.05). In the SDLA group, patient satisfaction was significantly higher than in the SLA group (P=0.024; P<0.05).

Conclusions:
In our study, SDLA caused less pain in AA cases during postoperative period than SLA. Further, the SDLA method achieved higher patient satisfaction during the postoperative period than the SLA method.
Long-Term Impact of Digital Media on Brain Development in Children
Authors: Nivins Samson , Sauce Bruno , Liebherr Magnus , Judd Nicholas , Klingberg Torkel 
Published: July 2022

AbstractDigital media (DM) takes an increasingly large part of children’s time, yet the long-term effect on brain development remains unclear. We investigated how individual effects of DM use (i.e., using social media, playing video games, or watching television/videos) on the development of the cortex (i.e., global cortical surface area), striatum, and cerebellum in children over four years, accounting for both socioeconomic status and genetic predisposition. We used a prospective, multicentre, longitudinal cohort of children from the Adolescent Brain and Cognitive Development Study, aged 9.9 years when entering the study, and who were followed for four years. Annually, children reported their DM usage through the Youth Screen Time Survey and underwent brain magnetic resonance imaging scans every two years. Quadratic-mixed effect modelling was used to investigate the relationship between individual DM usage and brain development. We found that individual DM usage did not alter the development of cortex or striatum volumes. However, high social media usage was associated with a statistically significant change in the developmental trajectory of cerebellum volumes, and the accumulated effect of high-vs-low social media users on cerebellum volumes over four years was only β= −0.03, which was considered insignificant. Nevertheless, the developmental trend for heavy social media users was accelerated at later time points. This calls for further studies and longer follow-ups on the impact of social media on brain development.
Impact of dementia, living in a long-term care facility, and physical activity status on COVID-19 severity in older adults
Authors: Tsuzuki Shinya , Akiyama Takayuki , Matsunaga Nobuaki , Ohmagari Norio 
Published: July 2022

AbstractBackgroundJapan is fast becoming an extremely aged society and older adults are known to be at risk of severe COVID-19. However, the impact of risk factors specific to this population for severe COVID-19 caused by the Omicron variant of concern (VOC) are not yet clear.MethodsWe performed an exploratory analysis using logistic regression to identify risk factors for severe COVID-19 illness among 4,868 older adults with a positive SARS-CoV-2 test result who were admitted to a healthcare facility between 1 January 2022 and 16 May 2022. We then conducted one-to-one propensity score (PS) matching for three factors—dementia, admission from a long-term care facility, and poor physical activity status—and used Fisher’s exact test to compare the proportion of severe COVID-19 cases in the matched data. We also estimated the average treatment effect on treated (ATT) in each PS matching analysis.ResultsOf the 4,868 cases analyzed, 1,380 were severe. Logistic regression analysis showed that age, male sex, cardiovascular disease, cerebrovascular disease, chronic lung disease, renal failure and/or dialysis, physician-diagnosed obesity, admission from a long-term care facility, and poor physical activity status were risk factors for severe disease. Vaccination and dementia were identified as factors associated with non-severe illness. The ATT for dementia, admission from a long-term care facility, and poor physical activity status was −0.04 (95% confidence interval −0.07, −0.01), 0.09 (0.06, 0.12), and 0.17 (0.14, 0.19), respectively.ConclusionsOur results suggest that poor physical activity status and living in a long-term care facility have a substantial impact on the risk of severe COVID-19 caused by the Omicron VOC, while dementia might be associated with non-severe illness.
Deep learning segmentation of the nucleus basalis of Meynert on 3T MRI
Authors: Doss Derek J. , Johnson Graham W. , Narasimhan Saramati , Jiang Jasmine W. , González Hernán F. J. , Paulo Danika L. , Lucas Alfredo , Davis Kathryn A. , Chang Catie , Morgan Victoria L. , Constantinidis Christos , Dawant Benoit M. , Englot Dario J. 
Published: July 2022

AbstractThe nucleus basalis of Meynert (NBM) is a key subcortical structure that is important in arousal, cognition, brain network modulation, and has been explored as a deep brain stimulation target. It has also been implicated in several disease states, including Alzheimer’s disease, Parkinson’s disease, and temporal lobe epilepsy (TLE). Given the small size of NBM and variability between patients, NBM is difficult to study; thus, accurate, patient-specific segmentation is needed. We investigated whether a deep learning network could produce accurate, patient-specific segmentations of NBM on commonly utilized 3T MRI. It is difficult to accurately segment NBM on 3T MRI, with 7T being preferred. Paired 3T and 7T MRI datasets of 21 healthy subjects were obtained, with 6 completely withheld for testing. NBM was expertly segmented on 7T MRI, providing accurate labels for the paired 3T MRI. An external dataset of 14 patients with TLE was used to test the model on brains with neurological disorders. A 3D-Unet convolutional neural network was constructed, and a 5-fold cross-validation was performed. The model was evaluated on healthy subjects using the held-out test dataset and the external dataset of TLE patients. The model demonstrated significantly improved dice coefficient over the standard probabilistic atlas for both healthy subjects (0.68MEAN±0.08SD vs. 0.47±0.06, p=0.0089, t-test) and TLE patients (0.63±0.08 vs. 0.38±0.19, p=0.0001). Additionally, the centroid distance was significantly decreased when using the model in patients with TLE (1.22±0.33mm, 3.25±2.57mm, p=0.0110). We developed the first model, to our knowledge, for automatic and accurate patient-specific segmentation of the NBM.
An ultra-sensitive bacterial pathogen and antimicrobial resistance diagnosis workflow using Oxford Nanopore adaptive sampling sequencing method
Authors: Cheng Hang , Sun Yuhong , Yang Qing , Deng Minggui , Yu Zhijian , Liu Lei , Yang Liang , Xia Yu 
Published: July 2022

AbstractMetagenomic sequencing analysis has been implemented as an alternative approach for pathogen diagnosis in recent years, which is independent on cultivation and able to identify all potential antibiotic resistant genes. However, current metagenomic sequencing analysis methods have to deal with low amounts of prokaryotic DNA and high amounts of host DNA in clinical samples, which significantly decrease the overall microbial detection resolution. The recently released nanopore adaptive sampling (NAS) technology facilitates immediate mapping of individual nucleotides to a given reference as each molecule is sequenced. User-defined thresholds allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. We developed a metagenomics workflow for ultra-sensitive diagnosis of bacterial pathogens and antibiotic resistance genes (ARGs) from clinic samples, which is based on the efficient selective ‘human host depletion’ NAS sequencing, real-time species identification and species-specific resistance gene prediction. Our method increased microbial sequence yield at least 8-fold in all 11 sequenced clinical Bronchoalveolar Lavage Fluid (BALF) samples (4.5h from sample to result), displayed 100% sensitivity and specificity for pathogen detection compared with cultivation method, and accurately detected antibiotic resistance genes at species level.
The physio-affective phenome of major depression is strongly associated with biomarkers of astroglial and neuronal projection toxicity which in turn are associated with peripheral inflammation, insulin resistance and lowered calcium
Authors: Al-Hakeim Hussein Kadhem , Al-Naqeeb Tabarek Hadi , Almulla Abbas F. , Maes Michael 
Published: July 2022

AbstractBackgroundMajor depressive disorder (MDD) is characterized by elevated activity of peripheral neuro-immune and neuro-oxidative pathways, which may cause neuro-affective toxicity by disrupting neuronal circuits in the brain. No study has explored peripheral indicators of neuroaxis damage in MDD in relation to serum inflammatory and insulin resistance (IR) biomarkers, calcium, and the physio-affective phenome consisting of depressive, anxious, chronic fatigue, and physiosomatic symptoms.MethodsSerum levels of phosphorylated tau protein 217 (P-tau217), platelet-derived growth factor receptor beta (PDGFR), neurofilament light chain (NF-L), glial fibrillary acidic protein (GFAP), C-reactive protein (CRP), calcium and the HOMA2-insulin resistance (IR) index were measured in 94 MDD patients and 47 controls.Results61.1% of the variance in the physio-affective phenome (conceptualized as a factor extracted from depression, anxiety, fatigue and physiosomatic symptoms) is explained by the regression on GFAP, NF-L, P-tau2017, PDGFRβ and HOMA2-IR (all positively associated), and decreased calcium. In addition, CRP and HOMA2-IR predicted 28.9% of the variance in the neuroaxis index. We observed significant indirect effects of CRP and calcium on the physio-affective phenome which were partly mediated by the four neuroaxis biomarkers. Annotation and enrichment analysis revealed that the enlarged GFAP, P-tau217, PDGFR, and NF-L network was enriched in glial cell and neuronal projections, the cytoskeleton and axonal transport, including a mitochondrion.ConclusionsPeripheral inflammation and IR may damage the astroglial and neuronal projections thereby interfering with mitochondrial transport. This toxicity, combined with inflammation, IR and lowered calcium, may, at least in part, induce the phenome of MDD.
Proteome dynamics of COVID-19 severity learnt by a graph convolutional network of multi-scale topology
Authors: Gauthier Samy , Tran-Dinh Alexy , Morilla Ian 
Published: July 2022

AbstractMany efforts have been recently done to characterise the molecular mechanisms of COVID-19 disease. These efforts resulted in a full structural identification of ACE2 as principal receptor of the Sars-CoV-2 spike protein in the cell. However, there are still important open questions related to other proteins involved in the progression of the disease. To this end, we have modelled the plasma proteome of 384 COVID patients. The model calibrated proteins measures at three time tags and make also use of the detailed clinical evaluation outcome of each patient after their hospital stay at day 28. Our analysis is able to discriminate severity of the disease by means of a metric based on available WHO scores of disease progression. Then, we identify by topological vectorisation those proteins shifting the most in their expression depending on that severity classification. Finally, the extracted topological invariants respect the protein expression at different times were used as base of a graph convolutional network. This model enabled the dynamical learning of the molecular interactions produced between the identified proteins.
Chiral Derivatization-enabled Discrimination and Visualization of Proteinogenic Amino Acids by Ion Mobility Mass Spectrometry
Authors: Xie Chengyi , Chen Yanyan , Wang Xiaoxiao , Song Yuanyuan , Shen Yuting , Diao Xin , Zhu Lin , Wang Jianing , Cai Zongwei 
Published: July 2022

AbstractThe importance of chiral amino acids (AAs) in living organisms has been widely recognized since the discovery of endogenous D-AAs as potential biomarkers in several metabolic disorders. Chiral analysis by ion mobility spectrometry-mass spectrometry (IMS-MS) has the advantages of high speed and sensitivity but is still in its infancy. Here, a Nα-(2,4-dinitro-5-fluorophenyl)-L-alaninamide (FDAA) derivatization is combined with trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) for chiral AA analysis. For the first time, we demonstrate the simultaneous separation of 19 pairs of chiral proteinogenic AAs in a single fixed condition TIMS-MS run. The utility of this approach presents for mouse brain extracts by direct-infusion TIMS-MS. The robust separation ability in complex biological sample was proven in MALDI TIMS mass spectrometry imaging (MSI) as well by directly depositing 19 pairs of AAs on a tissue slide following on-tissue derivatization. In addition, endogenous chiral amino acids were also detected and distinguished. The developed methods show compelling application prospects in biomarker discovery and biological research.Entry for the Table of ContentsThe combination of chiral derivatization and trapped ion mobility-mass spectrometry provides the first insights into the separation of 19 pairs of chiral proteinogenic D/L-amino acids in a single run and further visualization of chiral amino acids under complex biological matrix.
Large-scale expansions of Friedreich’s ataxia GAA•TTC repeats in human cells are prevented by LNA-DNA oligonucleotides and PNA oligomers
Authors: Rastokina Anastasia , Mozafari Negin , Cebrián Jorge , Smith C.I Edvard , Mirkin Sergei M. , Zain Rula 
Published: July 2022

AbstractThe human disease Friedreich’s ataxia (FRDA) is caused by expansions of GAA•TTC repeats in the first intron intron of the frataxin (FXN) gene, and both intergenerational and somatic expansions are crucial for disease development. We and others have shown earlier that expanded GAA•TTC repeats can form an intramolecular triplex structure (H-DNA). Here we studied the effects of locked nucleic acid (LNA)-DNA mixmer oligonucleotides and peptide nucleic acid (PNA) oligomers on the expansion of GAA•TTC repeats in cultured human cells. Our experimental system employes a mammalian/yeast shuttle plasmid containing a selectable cassette to detect repeat expansions. Using our in-house in vitro triplex-specific DNA cleavage assay, we first confirmed H-DNA formation by the (GAA)100•(TTC)100 repeat in the selectable cassette and demonstrated that the designed LNA-DNA oligonucleotides as well as PNA oligomers are able to disrupt this structure. We then found that both LNA-DNA mixmers and PNA oligomers prevent repeat expansions in human cells. In the accompanying paper, we show that expansions of GAA•TTC repeats in this experimental system occur during replication fork stalling, regression and restart at the repetitive run. We hypothesize, therefore, that triplex DNA formation by the GAA•TTC repeats is a key to their instability, while LNA-DNA oligonucleotides and PNA oligomers counteract repeat expansions by disrupting the triplex at the fork or preventing triplex formation upon fork reversal.
Evofosfamide and Gemcitabine Act Synergistically in Pancreatic Cancer Xenografts by Dual Action on Tumor Vasculature and Inhibition of Homologous Recombination DNA Repair
Authors: Otowa Yasunori , Kishimoto Shun , Saida Yu , Yamashita Kota , Yamamoto Kazutoshi , Chandramouli Gadisetti VR , Devasahayam Nallathamby , Mitchell James B. , Krishna Murali C. , Brender Jeffery R. 
Published: July 2022

AbstractAimsPancreatic ductal adenocarcinomas (PDACs) form hypovascular and hypoxic tumors which are difficult to treat with current chemotherapy regimens. Gemcitabine (GEM) is often used as a first line treatment for PDACs, but has issues with chemoresistance and penetration in the interior of the tumor. Evofosfamide, a hypoxia activated prodrug, has been shown to be effective in combination with GEM, although the mechanism of each drug on the other has not been established. We used two mouse xenografts from two cell lines (MIA Paca-2 and SU 86.86) with different tumor microenvironmental characteristics to probe the action of each drug on the other.ResultsGEM treatment enhanced survival times in mice with SU.86.86 xenografts (HR =0.35, 95% CI=0.13 to 0.90 p=0.03) but had no effect on MIA Paca-2 mice (HR =0.91, 95% CI=0.37 to 2.25, p=0.84). Conversely, evofosfamide had no effect on SU86.86 mice and did not improve survival times to a statistically significant degree (HR=0.57, 95% CI=0.23 to 1.42, p=0.22). In MIA Paca-2 tumors, which were initially poorly perfused, electron paramagnetic resonance (EPR) imaging showed that oxygenation worsened when treated with GEM, providing a direct mechanism for the activation of evofosfamide by GEM and the effectiveness of evofosfamide and GEM combinations. Sublethal amounts of either treatment enhanced the toxicity of other treatment in vitro in Su86.86 but not in MIAPaca-2. Repair of double stranded DNA lesions was enhanced in the combination treatment in Su86.86 but not MIA Paca-2.InnovationsA possible mechanism for the synergy between evofosfamide and GEM has been proposed.ConclusionThe synergy between GEM and evofosfamide appears to stem from the dual action of GEM’s effect on tumor vasculature and the GEM inhibition of the homologous recombination DNA repair process. The relative importance of each pathway is dependent on the tumor microenvironment and merits further study.
ELISA–on-Chip: High throughput antibody profiling using antigen microarrays
Authors: Levy Shlomia , Abd Alhadi Marwa , Azulay Asaf , Kahana Amit , Bujanover Nir , Gazit Roi , McGargill Maureen A. , Friedman Lilach M. , Hertz Tomer 
Published: July 2022

AbstractVaccination and natural infection both elicit potent humoral responses that provide protection from subsequent infections. The immune-history of an individual following such exposures is in part encoded by antibodies. While there are multiple immunoassays for measuring antibody responses, the majority of these methods measure responses to a single antigen. A commonly used method for measuring antibody responses is the enzyme-linked immunosorbent assay (ELISA) assay - a semi-quantitative assay that is simple to perform in research and clinical settings. Here we present the ELISA-on-Chip assay - a novel antigen microarray based assay for rapid high-throughput antibody profiling. The assay can be used for profiling IgG, IgA and IgM responses to multiple antigens simultaneously, requiring minimal amounts of sample and antigens. Using three different types of influenza antigen microarrays, we demonstrated the specificity and sensitivity of our novel assay and compared it to the traditional ELISA assay, using samples from mice, chickens and humans. We also showed that our assay can be readily used with dried blood spots, which can be collected from wild birds, as well as from newborns and children. The ELISA-on-Chip assay can be readily used to profile hundreds of samples against dozens of antigens in a single day, and therefore offers an attractive alternative to the traditional ELISA assay.