bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene mutations and molecular evolution of the chikungunya virus E1 and E2 from 2014 to 2019
Authors: Li Xiaoxia , Li Xinyue , Liu Jinyue , Liang Song , Chen Hanzong , Ke Changwen , Wan Chengsong 
Published: March 2022

ABSTRACTChikungunya virus (CHIKV), a mosquito-borne Alphavirus, is the etiological agent of chikungunya fever. To investigate the prevalence and genetic characteristics of CHIKV in China, we performed a molecular epidemiological study during the 2014–2019 period. Phylogenetic analysis of CHIKV in the 2014-2019 shows that it is currently clustered geographically, which means that CHIKV’s local adaptability is gradually strengthening. Focusing on CHIKV adaptive mutation E1-A226V is not obvious in our study. The CHIKV E1 amino acid non-synonymous mutation results revealed the common mutation site M343I. Most mutation sites belong to the American epidemic strains, and the mutation rate is 2.8%. In 31 sequences, 19 non-synonymous mutations were found in CHIKV E1 (total mutation rate 20/499 = 4%), and 37 non-synonymous mutations in CHIKV E2 (total mutation rate 30/425 = 7%). It is worth noting that the mutation of CHIKV E2 has changed more than that of CHIKV E1 between 2014 and 2019. CHIKV E2 screened out common mutation sites, and the results showed that there are five common mutation sites, namely S119G, L182M, G206D, S300N, and A345T. Eighty-three percent of the CHIKV E2 receptor binding domain mutations in the American strains, namely T3I and N6H, may cause immune escape.We constructed a new luciferase immunosorbent assay using CHIKV E2 antigen and mutant E2 antigen to test the serum of the CHIKV infected patients, and the detected samples and dilution ratios were different. The T3I, N6H, S119G, L182M, G206D, S300N, and A345T mutations in CHIKV E2 could explain these differences between patients.IMPORTANCECHIKV originated in Africa more than 500 years ago, with a common lineage dividing into two distinct branches called West Africa (West African, WA) and East/Central/South Africa (East/Central/South African, ECSA). Moreover, the E1-A226V mutation enhanced the replication and transmission capacity of CHIKV in Aedes albopictus. However, it should be noted that E1-A226V does not explain the CHIKV epidemic that has occurred in the Americas in recent years. We analyzed CHIKV samples in the 2014-2019, and the results showed that the mutation of CHIKV E1 protein occurred was not mainly concentrated in E1-A226V, but concentrated in M343I. This also means that CHIKV constantly mutates in the natural environment and is formed under natural conditions. Analysis of the common mutation sites of CHIKV E2 showed that there were seven common mutation sites S119G/L182M/ G206D /S300N/A345T, and the new mutation of CHIKV E2 may affect serological antibody detection.
Spatially constrained ICA enables robust detection of schizophrenia from very short resting-state fMRI data
Authors: Duda Marlena , Iraji Armin , Ford Judith M. , Lim Kelvin O. , Mathalon Daniel H. , Mueller Bryon A. , Potkin Steven G. , Preda Adrian , Van Erp Theo G.M. , Calhoun Vince D. 
Published: March 2022

ABSTRACTResting-state functional network connectivity (rsFNC) has shown utility for identifying characteristic functional brain patterns in individuals with psychiatric and mood disorders, providing a promising avenue for biomarker development. However, several factors have precluded widespread clinical adoption of rsFNC diagnostics, namely a lack of standardized approaches for capturing comparable and reproducible imaging markers across individuals, as well as the disagreement on the amount of data required to robustly detect intrinsic connectivity networks (ICNs) and diagnostically relevant patterns of rsFNC at the individual subject level. Recently, spatially constrained independent component analysis (scICA) has been proposed as an automated method for extracting ICNs standardized to a chosen network template while still preserving individual variation. Leveraging the novel scICA methodology, which solves the former challenge of standardized neuroimaging markers, we investigate the latter challenge of identifying a minimally sufficient data length for clinical applications of resting-state fMRI (rsfMRI). Using a dataset containing individuals with schizophrenia and controls (M = 310) as well as simulated rsfMRI, we evaluate the robustness of ICN and rsFNC estimates at both the subject- and group-level, as well as the performance of diagnostic classification, with respect to the length of the rsfMRI time course. We found individual estimates of ICNs and rsFNC from the full-length (5 minute) reference time course were sufficiently approximated with just 3-3.5 minutes of data (r = 0.85, 0.88, respectively), and significant differences in group-average rsFNC could be sufficiently approximated with even less data, just 2 minutes (r = 0.86). The results from the shorter clinical data were consistent with the results from the longer simulated data, reliably estimating both individual- and group-level metrics from the full-length (30 minute) reference with just 3-4 minutes of data (r = 0.85 - 0.88). Furthermore, we found a model trained on 2 minutes of data retained 97-98% classification accuracy relative to that of the full-length reference model. Our results suggest that clinical rsfMRI scans, when decomposed with scICA, could potentially be shortened to just 2-4 minutes without significant loss of individual rsFNC information or classification performance of longer scan lengths.
Suppression of de novo antibody responses against SARS-CoV2 and the Omicron variant after mRNA vaccination and booster in patients with B cell malignancies undergoing active treatment, but maintenance of pre-existing antibody levels against endemic viruses
Authors: Azar Joseph , Evans John P. , Sikorski Madison , Chakravarthy Karthik , McKenney Selah , Carmody Ian , Zeng Cong , Teodorescu Rachael , Song No Joon , Hamon Jamie , Bucci Donna , Velegraki Maria , Bolyard Chelsea , Weller Kevin P. , Reisinger Sarah , Bhat Seema A. , Maddocks Kami J. , Gumina Richard J. , Vlasova Anastasia N. , Oltz Eugene M. , Saif Linda J. , Chung Dongjun , Woyach Jennifer A. , Shields Peter G. , Liu Shan-Lu , Li Zihai , Rubinstein Mark P. 
Published: March 2022

AbstractThe impact of SARS-CoV2 vaccination in cancer patients remains incompletely understood given the heterogeneity of cancer and cancer therapies. We assessed vaccine-induced antibody response to the SARS-CoV2 Omicron (B.1.1.529) variant in 57 patients with B cell malignancies with and without active B cell-targeted therapy. Ancestral- and Omicron-reactive antibody levels were determined by ELISA and neutralization assays. In over one third of vaccinated patients at the pre-booster timepoint, there were no ELISA-detectable antibodies against either the ancestral strain or Omicron variant. The lack of vaccine-induced antibodies was predominantly in patients receiving active therapy such as anti-CD20 monoclonal antibody (mAb) or Bruton’s tyrosine kinase inhibitors (BTKi). While booster immunization was able to induce detectable antibodies in a small fraction of seronegative patients, the benefit was disproportionately evident in patients not on active therapy. Importantly, in patients with post-booster ELISA-detectable antibodies, there was a positive correlation of antibody levels against the ancestral strain and Omicron variant. Booster immunization increased overall antibody levels, including neutralizing antibody titers against the ancestral strain and Omicron variant; however, predominantly in patients without active therapy. Furthermore, ancestral strain neutralizing antibody titers were about 5-fold higher in comparison with those to Omicron, suggesting that even with booster administration, there may be reduced protection against the Omicron variant. Interestingly, in almost all patients regardless of active therapy, including those unable to generate detectable antibodies against SARS-CoV2 spike, we observed comparable levels of EBV, influenza, and common cold coronavirus reactive antibodies demonstrating that B cell-targeting therapies primarily impair de novo but not pre-existing antibody levels. These findings suggest that patients with B cell malignancies on active therapy may be at disproportionately higher risk to new versus endemic viral infection and suggest utility for vaccination prior to B cell-targeted therapy.
Characteristics of mental health stability during COVID-19: An online survey with people residing in the Liverpool City Region
Authors: Gomez Katalin Ujhelyi , Corcoran Rhiannon , Ring Adele , Hassan Shaima , Abba Katherine , Downing Jennifer , Goodall Mark , Gabbay Mark , Clarke Pam , Moran Paul , Obe Dorcas Akeju , Bennett Kate M 
Published: March 2022

AbstractBackground and aimDespite the significant mental health challenges the COVID-19 pandemic and its associated government measures have presented, research have shown that the majority of people have adapted and coped well. The aim of this study was i) to determine the proportion of people with mental stability and volatility during the pandemic in a North West urban environment sample and ii) to establish group differences in psychosocial variables. Mental stability and volatility refer to the extent to which individuals reported change in levels of common mental health symptoms over the course of 12 weeks.Methoda two-wave-online survey (N = 163) was used to explore the psychological and social impact of the pandemic on relatively disadvantaged neighbourhoods within the Liverpool City Region over 12 weeks. Kruskal-Wallis with post-hoc tests were used to determine how people with mental stability and volatility differed on factors categorised within an ecological framework of resilience (individual, community, societal, and COVID-19 specific).ResultsIndividuals categorised as ‘stable’ in terms of mental health symptoms (63.6%) had better mental and physical health; were more tolerant of uncertainty; reported higher levels of resilience and wellbeing compared to ‘very volatile’ people (19.8%). These individuals also reported feeling less socially isolated, experienced a greater sense of belonging to their community which was more likely to fulfil their needs, and were more likely to have access to green space nearby for their recommended daily exercise. ‘Stable’ individuals did not report worrying any more during the pandemic than usual and tolerated uncertainty better compared to those in the ‘volatile’ group.ImplicationsThe majority of participants in this sample were mentally stable and coping well with the challenges presented by the pandemic. The resilience of these individuals was related to key place-based factors such as a strong sense of community and useable local assets. The data showcase the role of place-based social determinants in supporting resilience and thereby highlight key preventative measures for public mental health during times of international crisis.
Protection of prior natural infection compared to mRNA vaccination against SARS-CoV-2 infection and severe COVID-19 in Qatar
Authors: Chemaitelly Hiam , Ayoub Houssein H. , AlMukdad Sawsan , Coyle Peter , Tang Patrick , Yassine Hadi M. , Al-Khatib Hebah A. , Smatti Maria K. , Hasan Mohammad R. , Al-Kanaani Zaina , Al-Kuwari Einas , Jeremijenko Andrew , Kaleeckal Anvar Hassan , Latif Ali Nizar , Shaik Riyazuddin Mohammad , Abdul-Rahim Hanan F. , Nasrallah Gheyath K. , Al-Kuwari Mohamed Ghaith , Butt Adeel A. , Al-Romaihi Hamad Eid , Al-Thani Mohamed H. , Al-Khal Abdullatif , Bertollini Roberto , Abu-Raddad Laith J. 
Published: March 2022

AbstractBACKGROUNDProtection conferred by natural SARS-CoV-2 infection versus COVID-19 vaccination has not been investigated in rigorously controlled studies. We compared head-to-head protection conferred by natural infection to that from the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines in Qatar, between February 28, 2020 and March 6, 2022.METHODSTwo national matched retrospective target-trial cohort studies were conducted to compare incidence of SARS-CoV-2 infection and COVID-19 hospitalization and death among those with a documented primary infection to incidence among those with a two-dose primary-series vaccination. Associations were estimated using Cox proportional-hazards regression models.RESULTSThe overall adjusted hazard ratio (AHR) for infection was 0.46 (95% CI: 0.45-0.48) comparing those with a prior infection to those vaccinated with BNT162b2, and 0.51 (95% CI: 0.48-0.53) comparing those with a prior infection to those vaccinated with mRNA-1273. For BNT162b2, the AHR decreased gradually from 0.55 (95% CI: 0.46-0.65) in the fourth month after primary infection/vaccination to 0.31 (95% CI: 0.27-0.37) in the eighth month, while for mRNA-1273, it decreased from 0.80 (95% CI: 0.59-1.07) to 0.35 (95% CI: 0.29-0.41) over the same time period. During the Omicron wave, the AHR was ∼0.50 for BNT162b2 and ∼0.60 for mRNA-1273. The overall AHR for any severe, critical, or fatal COVID-19 (against all variants) was 0.32 (95% CI: 0.10-1.00) for BNT162b2, and 0.58 (95% CI: 0.14-2.43) for mRNA-1273.CONCLUSIONSNatural infection was associated with stronger and more durable protection against infection, regardless of the variant, than mRNA primary-series vaccination. Nonetheless, vaccination remains the safest and optimal tool of protection against infection and COVID-19 hospitalization and death.
Gene Co-expression Connectivity Predicts Gene Targets Underlying High Ionic Liquid Tolerance in Yarrowia lipolytica
Authors: Walker Caleb , Ryu Seunghyun , Garcia Sergio , Dooley David , Mendoza Brian , Trinh Cong T. 
Published: March 2022

ABSTRACTMicrobial tolerance to organic solvents such as ionic liquids (ILs) is a robust phenotype beneficial for novel biotransformation. While most microbes become inhibited in 1%-5% (v/v) IL (e.g., 1-ethyl-3-methylimidazolium acetate), we engineered a robust Yarrowia lipolytica (YlCW001) that tolerates a record high of 18% (v/v) IL via adaptive laboratory evolution. Yet, genotypes conferring high IL tolerance in YlCW001 remain to be discovered. Using dynamic RNA-Seq data, we shed light on the underlying cellular processes that Y. lipolytica responds to IL. We introduced Gene Co-expression Connectivity (GeCCo) to discover genotypes conferring desirable phenotypes that might not be found by the conventional differential expression (DE) approaches. GeCCo selects genes based on their number of co-expressed genes in a sub-network of upregulated genes by the target phenotype. We experimentally validated GeCCo by reversely engineering high IL-tolerant phenotype in wildtype Y. lipolytica. We found that gene targets selected by both DE and GeCCo exhibited the best statistical chance at increasing IL tolerance when individually overexpressed. Remarkably, the best combination of dual-overexpressed genes were genes selected by GeCCo alone. This non-intuitive combination of genes, BRN1 and OYE2, are involved in guiding/regulating mitotic cell division, chromatin segregation/condensation, microtubule and cytoskeletal organization, and Golgi vesicle transport.
Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models
Authors: Heezen L.G.M. , Abdelaal T. , van Putten M. , Aartsma-Rus A. , Mahfouz A. , Spitali P. 
Published: March 2022

AbstractDuchenne muscular dystrophy (DMD) is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to develop effective therapies. Here we use spatial transcriptomics in two DMD mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathologies and directly link this to the muscle histology. Deconvolution analysis allowed the identification of cell types contributing to histological alterations. We show how the expression of specific genes is enriched in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). Finally, our analysis of differentiation dynamics in the severely affected D2-mdx muscle shows a subset of the muscle fibers are predicted to become affected in its future state. Genes associated with tissue remodeling could enable to design new diagnostic and therapeutic strategies for DMD.
Stability of asymmetric cell division under confinement: A deformable cell model of cytokinesis applied to C. elegans development
Authors: Cuvelier Maxim , Thiels Wim , Jelier Rob , Smeets Bart 
Published: March 2022

AbstractCell division during early embryogenesis has been linked to key morphogenic events such as embryo symmetry breaking and tissue patterning. It is thought that boundary conditions together with cell intrinsic cues act as a mechanical “mold”, guiding cell division to ensure these events are more robust. We present a novel computational mechanical model of cytokinesis, the final phase of cell division, to investigate how cell division is affected by mechanical and geometrical boundary conditions. The model reproduces experimentally observed furrow dynamics and predicts the volume ratio of daughter cells in asymmetric cell divisions based on the position and orientation of the mitotic spindle. We show that the orientation of confinement relative to the division axis modulates the volume ratio in asymmetric cell division and quantified the mechanical contribution of cortex mechanics, relative to the mechanical properties of the furrow ring. We apply this model to early C. elegans development, which proceeds within the confines of an eggshell, and simulate the formation of the three body axes via sequential (a)symmetric divisions up until the six cell stage. We demonstrate that spindle position and orientation alone can be used to predict the volume ratio of daughter cells during the cleavage phase of development. However, for compression perturbed egg geometries, the model predicts that the change in confinement alone is insufficient to explain experimentally observed differences in cell volume, inferring an unmodeled underlying spindle positioning mechanism. Finally, the model predicts that confinement stabilizes asymmetric cell divisions against bubble-instabilities, which can arise due to elevated mitotic cortical tension.Author summaryA crucial morphogenic step during early embryonic development is symmetry breaking in the embryo. For C. elegans the formation of the three body axes can be traced back to the six cell stage, where tissue-topology is the result of symmetric and asymmetric divisions. How cell mechanical boundary conditions and cell intrinsic cues influence this process of symmetry breaking is still an open question, as currently, a quantitative mechanical description of cytokinesis in complex architectures is lacking. We developed a simple mechanical model of cell division, incorporated in an existing mechanical cortex model, to simulate cytokinesis in geometrically confined environments. Our approach was able to both capture furrow ring dynamics and predict the volume ratio of daughter cells accurately. By simulating early C. elegans development with different geometrical boundary conditions, we were able to trace back the origin of volume discrepancies between the experimental setups to a quantifiable shift in spindle positioning during cytokinesis. Finally, we showed how embryo confinement partially stabilizes bubble-instabilities that arise during asymmetric cell division during the early cleavage phase.
The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks
Authors: Halvagal Manu Srinath , Zenke Friedemann 
Published: March 2022

AbstractDiscriminating distinct objects and concepts from sensory stimuli is essential for survival. Our brains accomplish this feat by forming disentangled internal representations in deep sensory networks shaped through experience-dependent synaptic plasticity. To elucidate the principles that underlie sensory representation learning, we derive a local plasticity model that shapes latent representations to predict future activity. This Latent Predictive Learning (LPL) rule conceptually extends Bienenstock-Cooper-Munro (BCM) theory by unifying Hebbian plasticity with predictive learning. We show that deep neural networks equipped with LPL develop disentangled object representations without supervision. The same rule accurately captures neuronal selectivity changes observed in the primate inferotemporal cortex in response to altered visual experience. Finally, our model generalizes to spiking neural networks and naturally accounts for several experimentally observed properties of synaptic plasticity, including metaplasticity and spike-timing-dependent plasticity (STDP). We thus provide a plausible normative theory of representation learning in the brain while making concrete testable predictions.
Inducible depletion of Scleraxis-lineage cells during tendon healing impairs multi-scale restoration of tendon structure
Authors: Korcari Antonion , Muscat Samantha , Buckley Mark R. , Loiselle Alayna E. 
Published: March 2022

AbstractTendons are composed of a heterogeneous cell environment, with Scleraxis-lineage (ScxLin) cells being the predominant population. Although ScxLin cells are required for maintenance of tendon homeostasis, their functions during tendon healing are unknown. To this end, we first characterized the spatiotemporal dynamics of ScxLin cells during tendon healing, and identified that the overall ScxLin pool continuously expands up to early remodeling healing phase. To better define the function of ScxLin cells during the late proliferative phase of healing, we inducibly depleted ScxLin cells from day 14-18 post-surgery using the Scx-Cre; Rosa-DTR mouse model, with local administration of diphtheria toxin inducing apoptosis of ScxLin cells in the healing tendon. At D28 post-surgery, ScxLin cell depleted tendons (DTR) had substantial impairments in structure and function, relative to WT, demonstrating the importance of ScxLin cells during tendon healing. Next, bulk RNAseq was utilized to identify the underlying mechanisms that were impaired with depletion and revealed that ScxLin depletion induced molecular and morphological stagnation of the healing process at D28. However, this stagnation was transient, such that by D56 tendon mechanics in DTR were not significantly different than wildtype repairs. Collectively, these data offer fundamental knowledge on the dynamics and roles of ScxLin cells during tendon healing.
Prefrontal PV interneurons facilitate attention and are linked to attentional dysfunction in a mouse model of absence epilepsy
Authors: Ferguson Brielle R. , Huguenard John R. 
Published: March 2022

AbstractAbsence seizures are characterized by brief periods of unconsciousness accompanied by a lapse in motor function that can occur hundreds of times throughout the day. Outside of these frequent moments of unconsciousness, approximately a third of patients experience treatment-resistant attention impairments. Convergent evidence suggests prefrontal cortex (PFC) dysfunction may underlie attention impairments in affected patients. To test this, we use a combination of slice physiology, fiber photometry, electrocorticography (ECoG), optogenetics, and behavior in theScn8a+/−mouse model of absence epilepsy. In these mice, we find decreased parvalbumin interneuron (PVIN) recruitment in the medial PFC (mPFC)in vitroand hypoactivity during cue presentationin vivothat is linked to attention dysfunction. Further, we find that low levels of mPFC PVIN activity are predictive of poorer performance in WT littermates. This highlights cue-evoked PVIN activity as an important mechanism for attention and suggests PVINs may represent a therapeutic target for cognitive comorbidities in absence epilepsy.