bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of repetitive transcranial magnetic stimulation on the kynurenine pathway in stroke patients
Authors: Niimi Masachika , Ishima Tamaki , Hashimoto Kenji , Hara Takatoshi , Yamada Naoki , Abo Masahiro 
Published: May 2020

Objective
Repetitive transcranial magnetic stimulation (rTMS) improves depressive symptoms and motor function in stroke patients. While metabolic derangement of the kynurenine pathway has been reported in stroke patients, the effect of rTMS on this pathway remains unknown. This study was performed to investigate the effect of rTMS on serum levels of kynurenine and tryptophan in stroke patients.

Methods
Sixty-two stroke patients received rTMS in addition to intensive rehabilitation and 33 stroke patients received intensive rehabilitation alone for 14 days. The rTMS involved low-frequency stimulation (at 1 Hz) of the primary motor cortex on the unaffected side of the cerebrum. The depressive state of the patients was evaluated with the Beck Depression Inventory (BDI) before and after treatment. Motor function of the patients was evaluated with Fugl-Meyer Assessment (FMA). Serum levels of kynurenine and tryptophan levels were also measured before and after treatment.

Results
The serum tryptophan level decreased in the group receiving rTMS to the right brain and increased in the group receiving rTMS to the left brain. The serum kynurenine/tryptophan ratio was elevated in the group receiving rTMS to the right brain. The BDI indicated improvement of depressive symptoms in the rehabilitation alone group and the group receiving rTMS to the right brain plus rehabilitation. The FMA improved in all groups.

Conclusions
The effect of low-frequency rTMS on the kynurenine pathway may differ depending on whether it is applied to the right or left cerebral hemisphere.
Revisiting neoantigen depletion signal in the untreated cancer genome
Authors: Wang Shixiang , Wang Xuan , Wu Tao , He Zaoke , Li Huimin , Sun Xiaoqin , Liu Xue-Song 
Published: May 2020

AbstractThis study is arising from Van den Eynden J. et al. Nature Genetics. Lack of detectable neoantigen depletion signals in the untreated cancer genome. Van den Eynden J.et al.tried to address a very important scientific question: could the immune system eliminate cancer cells with immunogenic mutations in untreated situation? Van den Eynden J.et al.first annotated the human exome into “HLA-binding regions” and “non HLA-binding regions” based on the predicted binding affinity of nonapeptides translated from the un-mutated reference coding genome with type I HLA alleles. They hypothesized that if neoantigen depletion signal exist, the nonsynonymous mutations in “HLA-binding regions” will be negatively selected during cancer evolution, while nonsynonymous mutation in “non HLA-binding regions” will not be negatively selected. This will lead to decreased nonsynonymous vs synonymous mutation ratio (n/s) in “HLA-binding regions” compared with “non HLA-binding regions”. They defined HLA-binding mutation ratio (HBMR) as the ratio of n/s in “HLA-binding regions” to “non HLA-binding regions”, and reported that HBMRs are close to 1 in different types of cancer after background corrections, meaning neoantigen depletion signals are not detectable in different types of cancer. The fundamental problem of their hypothesis lies in that the actual neoantigens with immunogenicity do not overlap with their defined “HLA-binding regions”. Actually, most neoantigens with immunogenicity are not located in “HLA-binding regions”, when dissimilarity between mutant and wild type peptide are considered. It is the neoantigen with immunogenicity, but not nonsynonymous mutation in their defined “HLA-binding regions” undergo immunoediting based negative selection. Thus the results reported in that study are fundamentally flawed, and at this current stage we could not draw a solid conclusion as to whether the neoantigen depletion signal exists or not.
Limited transgenerational effects of environmental temperatures on thermal performance of a cold-adapted salmonid
Authors: Penney Chantelle M. , Burness Gary , Robertson Joshua , Wilson Chris C. 
Published: May 2020

AbstractThe capacity of ectotherms to cope with rising temperatures associated with climate change is a significant conservation concern as the rate of warming is likely too fast for adaptation to occur in some populations. Transgenerational plasticity, if present, could potentially buffer some of the negative impacts of warming on future generations. We examined transgenerational plasticity in lake trout to assess their inter-generational potential to cope with anticipated warming. We acclimated adult lake trout to cold or warm temperatures for several months, then bred them to produce offspring from parents of matched and mismatched temperatures. At the fry stage, offspring were also acclimated to cold or warm temperatures and their thermal performance was assessed by measuring their critical thermal maximum and metabolic rate during an acute temperature challenge. Overall, transgenerational plasticity was evident: thermal performance of offspring reflected both maternal and paternal environmental conditions, and offspring performed better when their environment matched that of their parents. There was little variation in offspring critical thermal maximum or peak metabolic rate, although cold-acclimated offspring from warm-acclimated parents exhibited elevated standard metabolic rates, suggesting that transgenerational effects can be detrimental when parent and offspring environments mismatch. These results demonstrate both the occurrence and limitations of transgenerational plasticity in a coldwater salmonid in response to elevated temperature, as well as potential ecological risks associated with transgenerational plasticity when an environmental change experienced by the parents does not persist with the next generation.
Topologically associating domains and their role in the evolution of genome structure and function inDrosophila
Authors: Liao Yi , Zhang Xinwen , Chakraborty Mahul , Emerson J.J. 
Published: May 2020

AbstractTopologically associating domains (TADs) were recently identified as fundamental units of three-dimensional eukaryotic genomic organization, though our knowledge of the influence of TADs on genome evolution remains preliminary. To study the molecular evolution of TADs inDrosophilaspecies, we constructed a new reference-grade genome assembly and accompanying high-resolution TAD map forD. pseudoobscura. Comparison ofD. pseudoobscuraandD. melanogaster, which are separated by ∼49 million years of divergence, showed that ∼30-40% of their genomes retain conserved TADs. Comparative genomic analysis of 17Drosophilaspecies revealed that chromosomal rearrangement breakpoints are enriched at TAD boundaries but depleted within TADs. Additionally, genes within conserved TADs exhibit lower expression divergence than those located in nonconserved TADs. Furthermore, we found that a substantial proportion of long genes (>50 kbp) inD. melanogaster(42%) andD. pseudoobscura(26%) constitute their own TADs, implying transcript structure may be one of the deterministic factors for TAD formation. Using structural variants (SVs) identified from 14D. melanogasterstrains, its 3 closest sibling species from theD. simulansspecies complex, and two obscura clade species, we uncovered evidence of selection acting on SVs at TAD boundaries, but with the nature of selection differing between SV types. Deletions are depleted at TAD boundaries in both divergent and polymorphic SVs, suggesting purifying selection, whereas divergent tandem duplications are enriched at TAD boundaries relative to polymorphism, suggesting they are adaptive. Our findings highlight how important TADs are in shaping the acquisition and retention of structural mutations that fundamentally alter genome organization.
A Chemical-genetics and Nanoparticle Enabled Approach forin vivoProtein Kinase Analysis
Authors: Chen Fengqian , Liu Qi , Hilliard Terrell , Wang Tingzeng , Liang Hongjun , Gao Weimin , Huang Leaf , Wang Degeng 
Published: May 2020

AbstractThe human kinome contains >500 protein kinases, and regulates up to 30% of the proteome. Kinase study is currently hindered by a lack ofin vivoanalysis approaches due to two factors: our inability to distinguish the kinase reaction of interest from those of other kinases in live cells and the cell impermeability of the ATP analogs. Herein, we tackled this issue by combining the widely used chemical genetic method developed by Dr. Kevan Shokat and colleagues with nanoparticle-mediated intracellular delivery of the ATP analog. The critical AKT1 protein kinase, which has been successfully studied with the method, was used as our initial prototype. Briefly, enlargement of the ATP binding pocket, by mutating the gate-keeper Methionine residue to a Glycine, prompted the mutant AKT1 to preferentially use the bulky ATP analog N6-Benzyl-ATP-γ-S (A*TPγS) and, thus, differentiating AKT1-catalyzed and other phosphorylation events. The lipid/calcium/phosphate (LCP) nanoparticle was used for efficient intracellular delivery of A*TPγS, overcoming the cell impermeability issue. The mutant, but not wild-type, AKT1 used the delivered A*TPγS for autophosphorylation and phosphorylating its substrates in live cells. Thus, anin vivoprotein kinase analysis method has been developed. The strategy should be widely applicable to other protein kinases.
Robust Hierarchical Co-clustering to Explore Toxicogenomic Biomarkers and Their Regulatory Doses of Chemical Compounds
Authors: Hasan Mohammad Nazmol , Badsha Md. Bahadur , Mollah Md. Nurul Haque 
Published: May 2020

AbstractToxicogenomics combines high throughput molecular technologies with statistical and machine learning approaches to discover a similar group of doses of chemical compounds (DCCs) and genes to explore toxicogenomic biomarkers and their regulatory DCCs. This is also very important in the toxicity study of environmental stressors, synthetic chemicals and drug discovery and development process. Different clustering algorithms are concerned with the discovering of interesting clusters/groups of row or column entities of a dataset. Among those hierarchical clustering (HC) and logistic probabilistic hidden variable model (LPHVM) can identify toxicogenomic biomarkers and their regulatory DCCs forming co-cluster. However, the HC method is very sensitive to outlying observations. On the other hand, though LPHVM is a robust approach, it consumes more time for calculation since it is Expectation-Maximization (EM) based iterative approach. Additionally, the LPHVM creates artificiality problem taking absolute value of the data matrix. Therefore, to overcome these problems in this paper, we proposed a robust hierarchical co-clustering (RHCOC) algorithm to co-cluster genes and DCCs simultaneously with a view to explore toxicogenomic biomarkers and their regulatory DCCs. The performance of the proposed RHCOC algorithm over the conventional HC for clustering genes and DCCs of toxicogenomic data has been investigated based on the simulation study. The results of the simulation study have shown that the RHCOC approaches produce far lower clustering error rate (ER) than the conventional HC approaches in presence of outlying observations in the dataset. Otherwise they perform equally in absence of outlier in the dataset. To explore biomarker co-clusters consisting of toxicogenomic biomarker genes and their regulatory DCCs we used control chart for individual measurement (CCIM). We have also investigated the performance of the proposed approach in the case of the pathway level real life fold change gene expression (FCGE) toxicogenomic data analysis. The biomarker co-clusters consisting of toxicogenomic biomarker genes and their regulatory DCCs and biomarker genes explored by the proposed approaches have been validated by the literature and functional annotation. Our method is implemented in R package “rhcoclust” available on github (https://github.com/mdbahadur/rhcoclust).
Efficacy of moist heat decontamination against various pathogens for the reuse of N95 respirators in the COVID-19 emergency
Authors: Oral Ebru , Wannomae Keith K , Gil Dmitry , Connolly Rachel , Gardecki Joseph A , Leung Hui Min , Muratoglu Orhun K , Tsurumi Amy , Rahme Laurence , Jaber Tareq , Collins Cassidy , Gjore Julian , Budzilowicz Amanda 
Published: May 2020

Decontamination of N95 respirators has become critical to alleviate PPE shortages for healthcare workers in the current COVID-19 emergency. The factors that are considered for the effective reuse of these masks are the fit, filter efficiency and decontamination/disinfection level both for SARS-CoV2, which is the causative virus for COVID-19, and for other organisms of concern in the hospital environment such as Staphylococcus aureus or Clostridium difficile.The efficacy of inactivation or eradication against various pathogens should be evaluated thoroughly to understand the level of afforded disinfection. Methods commonly used in the sterilization of medical devices such as ionizing radiation, vaporized hydrogen peroxide, and ethylene oxide can provide a high level of disinfection, defined as a 6 log10 reduction, against bacterial spores, considered the most resistant microorganisms. CDC guidance on the decontamination and reuse of N95s also includes the use of moist heat (60°C, 80% relative humidity, 15-30 min) as a possible recommendation based on literature showing preservation of fit efficiency and inactivation of H1N1 on spiked masks.Here, we explored the efficacy of using moist heat under these conditions as a decontamination method for an N95 respirator (3M 1860S, St. Paul, MN) against various pathogens with different resistance; enveloped RNA viruses, Gram (+/-) bacteria, and non-enveloped viruses.
Transmission onset distribution of COVID-19
Authors: Chun June Young , Baek Gyuseung , Kim Yongdai 
Published: May 2020

AbstractObjectivesThe distribution of the transmission onset of COVID-19 relative to the symptom onset is a key parameter for infection control. It is often not easy to study the transmission onset time, as is difficult to know who infected whom exactly when.MethodsWe inferred transmission onset time from 72 infector-infectee pairs in South Korea, either with known or inferred contact dates by means of incubation period. Combining this data with known information of infector’s symptom onset, we could generate the transmission onset distribution of COVID-19, using Bayesian methods. Serial interval distribution could be automatically estimated from our data.ResultsWe estimated the median transmission onset to be 1.31 days (standard deviation, 2.64 days) after symptom onset with peak at 0.72 days before symptom onset. The pre-symptomatic transmission proportion was 37% (95% credible interval [CI], 16–52%). The median incubation period was estimated to be 2.87 days (95% CI, 2.33–3.50 days) and the median serial interval to be 3.56 days (95% CI, 2.72–4.44 days).ConclusionsConsidering the transmission onset distribution peaked with the symptom onset and the pre-symptomatic transmission proportion is substantial, the usual preventive measure might be too late to prevent SARS-CoV-2 transmission.
Distribution of ACE2, CD147, cyclophilins, CD26 and other SARS-CoV-2 associated molecules in human tissues and immune cells in health and disease
Authors: Radzikowska U. , Ding M. , Tan G. , Zhakparov D. , Peng Y. , Wawrzyniak P. , Wang M. , Li S. , Morita H. , Altunbulakli C. , Reiger M. , Neumann AU. , Lunjani N. , Traidl-Hoffmann C. , Nadeau K. , O’Mahony L. , Akdis CA. , Sokolowska M. 
Published: May 2020

AbstractBackgroundMorbidity and mortality from COVID-19 caused by novel coronavirus SARS-CoV-2 is accelerating worldwide and novel clinical presentations of COVID-19 are often reported. The range of human cells and tissues targeted by SARS-CoV-2, its potential receptors and associated regulating factors are still largely unknown. The aim of our study was to analyze the expression of known and potential SARS-CoV-2 receptors and related molecules in the extensive collection of primary human cells and tissues from healthy subjects of different age and from patients with risk factors and known comorbidities of COVID-19.MethodsWe performed RNA sequencing and explored available RNA-Seq databases to study gene expression and co-expression of ACE2, CD147 (BSG), CD26 (DPP4) and their direct and indirect molecular partners in primary human bronchial epithelial cells, bronchial and skin biopsies, bronchoalveolar lavage fluid, whole blood, peripheral blood mononuclear cells (PBMCs), monocytes, neutrophils, DCs, NK cells, ILC1, ILC2, ILC3, CD4+and CD8+T cells, B cells and plasmablasts. We analyzed the material from healthy children and adults, and from adults in relation to their disease or COVID-19 risk factor status.ResultsACE2andTMPRSS2were coexpressed at the epithelial sites of the lung and skin, whereas CD147 (BSG), cyclophilins (PPIA and PPIB), CD26 (DPP4) and related molecules were expressed in both, epithelium and in immune cells. We also observed a distinct age-related expression profile of these genes in the PBMCs and T cells from healthy children and adults. Asthma, COPD, hypertension, smoking, obesity, and male gender status generally led to the higher expression of ACE2- and CD147-related genes in the bronchial biopsy, BAL or blood. Additionally, CD147-related genes correlated positively with age and BMI. Interestingly, we also observed higher expression of ACE2- and CD147-related genes in the lesional skin of patients with atopic dermatitis.ConclusionsOur data suggest different receptor repertoire potentially involved in the SARS-CoV-2 infection at the epithelial barriers and in the immune cells. Altered expression of these receptors related with age, gender, obesity and smoking, as well as with the disease status might contribute to COVID-19 morbidity and severity patterns.
Evaluating assembly and variant calling software for strain-resolved analysis of large DNA-viruses
Authors: Deng Z.-L. , Dhingra A. , Fritz A. , Götting J. , Münch P. C. , Steinbrück L. , Schulz T. F. , Ganzenmüller T. , McHardy A. C. 
Published: May 2020

AbstractInfection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and six variant callers on ten lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data.Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive (FP) variant calls, which were strongly enriched in T to G changes in a “G.G” context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo,QuasispeciesMetricdeterminationonomics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.
High-fat diet-induced activation of SGK1 promotes Alzheimer’s disease-associated tau pathology
Authors: Elahi Montasir , Motoi Yumiko , Shimonaka Shotaro , Ishida Yoko , Hioki Hiroyuki , Takanashi Masashi , Ishiguro Koichi , Imai Yuzuru , Hattori Nobutaka 
Published: May 2020

AbstractType2 diabetes mellitus (T2DM) has long been considered a risk factor for Alzheimer’s disease (AD). However, the molecular links between T2DM and AD remain obscure. Here, we reported that serum/glucocorticoid-regulated kinase1 (SGK1) is activated by administering a chronic high-fat diet (HFD), which increases the risk of T2DM, and thus promotes Tau pathology via the phosphorylation of tau at Ser214 and the activation of a key tau kinase, namely, GSK-3ß, forming SGK1-GSK-3ß-tau complex. SGK1 was activated under conditions of elevated glucocorticoid and hyperglycemia associated with HFD, but not of fatty acid-mediated insulin resistance. Elevated expression of SGK1 in the mouse hippocampus led to neurodegeneration and impairments in learning and memory. Upregulation and activation of SGK1, SGK1-GSK-3ß-tau complex were also observed in the hippocampi of AD cases. Our results suggest that SGK1 is a key modifier of tau pathology in AD, linking AD to corticosteroid effects and T2DM.
Fast lightweight accurate xenograft sorting
Authors: Zentgraf Jens , Rahmann Sven 
Published: May 2020

AbstractMotivationWith an increasing number of patient-derived xenograft (PDX) models being created and subsequently sequenced to study tumor heterogeneity and to guide therapy decisions, there is a similarly increasing need for methods to separate reads originating from the graft (human) tumor and reads originating from the host species’ (mouse) surrounding tissue. Two kinds of methods are in use: On the one hand, alignment-based tools require that reads are mapped and aligned (by an external mapper/aligner) to the host and graft genomes separately first; the tool itself then processes the resulting alignments and quality metrics (typically BAM files) to assign each read or read pair. On the other hand, alignment-free tools work directly on the raw read data (typically FASTQ files). Recent studies compare different approaches and tools, with varying results.ResultsWe show that alignment-free methods for xenograft sorting are superior concerning CPU time usage and equivalent in accuracy. We improve upon the state of the art sorting by presenting a fast lightweight approach based on three-way bucketed quotiented Cuckoo hashing. Our hash table requires memory comparable to an FM index typically used for read alignment and less than other alignment-free approaches. It allows extremely fast lookups and uses less CPU time than other alignment-free methods and alignment-based methods at similar accuracy.AvailabilityOur software xengsort is available under the MIT license at http://gitlab.com/genomeinformatics/xengsort. It is written in numba-compiled Python and comes with Snakemake workflows for hash table construction and dataset processing.ContactSven.Rahmann@uni-due.de