bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dysregulation of mTOR Signaling Mediates Common Neurite and Migration Defects in Both Idiopathic and 16p11.2 Deletion Autism Neural Precursor Cells
Authors: Prem Smrithi , Dev Bharati , Peng Cynthia , Mehta Monal , Alibutud Rohan , Connacher Robert J. , Thomas Madeline St , Zhou Xiaofeng , Matteson Paul , Xing Jinchuan , Millonig James H. , DiCicco-Bloom Emanuel 
Published: September 2022

ABSTRACTAutism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD-subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD-subtypes, and mTOR modulation rescued ASD phenotypes and reproduced autism defects in controls. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation.
Whole genome sequencing of ‘mutation-negative’ individuals with Cornelia de Lange Syndrome
Authors: Ansari Morad , Halachev Mihail , Parry David , Campos Jose L. , D’Souza Elston N. , Barnett Christopher , Wilkie Andrew O. M. , Barnicoat Angela , Patel Chirag V. , Sukarova-Angelovska Elena , Girisha Katta M. , Firth Helen V. , Prescott Katrina , Wilson Louise C. , McEntagart Meriel , Davidson Rosemarie , Lynch Sally Ann , Joss Shelagh , Holden Simon T. , Lam Wayne K. , Sisodiya Sanjay M. , Green Andrew J. , Poke Gemma , Whiffin Nicola , FitzPatrick David R. , Meynert Alison 
Published: September 2022

AbstractAimsThis study assesses the diagnostic utility of whole genome sequence analysis in a well-characterised research cohort of individuals referred with a clinical suspicion of Cornelia de Lange syndrome (CdLS) in whom prior genetic testing had not identified a causative variant.MethodsShort read, whole genome sequencing was performed in 195 individuals from 105 families, 108 of whom were affected. 100/108 of the affected individuals had prior relevant genetic testing with no pathogenic variant being identified. The study group comprised 42 trios (affected individuals with both unaffected parents), 61 singletons (unrelated affected individuals) and two families with more than one affected individual.Results32/105 (30.5%) unrelated probands had likely causative coding region disrupting variants. 4 loci were identified in >1 proband; NIPBL (10), ANKRD11 (6), EP300 (3), EHMT1 (2). Single alleles were detected in the remaining genes (EBF3, KMT2A, MED13L, NLGN3, NR2F1, PHIP, PUF60, SET, SETD5, SMC1A, TBL1XR1). Possibly causative variants in non-coding regions of NIPBL were identified in four individuals. Single de novo variants were identified in five genes not previously reported to be associated with any developmental disorder: ARID3A, PIK3C3, MCM7, MIS18BP1 and WDR18.ConclusionsClustering of de novo non-coding variants implicate a single uORF and a small region in intron 21 in NIPBL regulation. Causative variants in genes encoding chromatin-associated proteins, with no defined influence on cohesin function, appear to result in CdLS-like clinical features.
Effects of the Variance in Prevalence of the DASH Diet in Nursing Homes on Seniors With Elevated Blood Pressure or Hypertension
Authors: Liu Ryan , Chui Tsz-Kiu 
Published: September 2022

1.ABSTRACTThe DASH diet is a dietary pattern designed to help treat or prevent hypertension. The diet includes foods rich in potassium, calcium, and magnesium while limiting foods high in sodium, saturated fat, and added sugars. The DASH diet’s relationship with hypertension in adults is well defined, but the effect of its variance in prevalence in nursing homes on seniors is not. We performed a mixed-methods observational study incorporating a survey collecting anonymized nursing home data regarding the number of servings of various food groups provided to senior residents per day. The data were analyzed using the Fung et al. DASH diet scoring method. We then conducted an interview with nursing home dieticians to investigate the public health effect of the DASH diet on hypertension in residents. Lastly, a content analysis was performed of nursing home menus to support the data from the surveys. In a pool of 11 nursing homes, 100% of the facilities incorporated some aspect of the DASH diet, and in a pool of five nursing homes, 60% achieved high adherence to the DASH diet. We additionally confirmed a previously observed negative relationship between red meat consumption in seniors to higher risk and poorer prognosis of hypertension. These analyses bolster the DASH diet’s potential role as a hypertension prevention mechanism in nursing homes, suggesting that future DASH diet interventions may hold promise.
Are the relevant risk factors being adequately captured in empirical studies of smoking initiation? A machine learning analysis based on the Population Assessment of Tobacco and Health study
Authors: Le Thuy T. T. , Issabakhsh Mona , Li Yameng , Sánchez-Romero Luz María , Tan Jiale , Meza Rafael , Levy David , Mendez David 
Published: September 2022

AbstractCigarette smoking continues to pose a threat to public health. Identifying individual risk factors for smoking initiation is essential to further mitigate this epidemic. To our knowledge, no study today has used Machine Learning (ML) techniques to automatically uncover informative predictors of smoking onset among adults using the Population Assessment of Tobacco and Health (PATH) study. In this work, we employed Random Forest paired with Recursive Feature Elimination to identify relevant PATH variables that predict smoking initiation among adult never smokers at baseline between two consecutive PATH waves. We included all potentially informative baseline variables in wave 1 (wave 4) to predict past 30-day smoking status in wave 2 (wave 5). Using the first and most recent pairs of PATH waves was found sufficient to identify the key risk factors of smoking initiation and test their robustness over time. As a result, classification models suggested about 60 informative PATH variables among more than 200 candidate variables in each baseline wave. With these selected predictors, the resulting models have a high discriminatory power with the area under the Specificity-Sensitivity curves of around 80%. We examined the chosen variables and discovered important features. Across the considered waves, three factors, (i) BMI, (ii) dental/oral health status, and (iii) taking anti-inflammatory or pain medication, robustly appeared as significant predictors of smoking initiation, besides other well-established predictors. Our work demonstrates that ML methods are useful to predict smoking initiation with high accuracy, identify novel smoking initiation predictors, and enhance our understanding of tobacco use behaviors.
Large-scale deployment of SIT-based technology in a Brazilian city prevented Dengue outbreak
Authors: de Castro Poncio Lisiane , dos Anjos Filipe Apolinário , de Oliveira Deborah A. , Rosa Aline , Silva Bianca Piraccini , Rebechi Débora , da Costa Franciscato Diego Alan , de Souza Cláudio , Paiva Uilson , Mazurechen Marilu , de Araújo Ribeiro Rafael , Basile Priscila , Rezende Erikon Leandro , Paldi Nitzan 
Published: September 2022

AbstractBackgroundDengue is a global problem that seems to be worsening, as hyper-urbanization associated with climate change has led to a significant increase in the abundance and geographical spread of its principal vector, the Aedes aegypti mosquito. The current available solutions, including vaccines and traditional vector-control methods, have not been able to stop the spread of dengue which shows the urgent need to implement alternative technologies as practical solutions. We recently presented ‘Natural Vector Control’ (NVC), a new Sterile Insect Technology-based method that uses massive releases of sterile male mosquitoes produced from the combined treatment with dsRNA and thiotepa. In a previous pilot trial, two intervention periods over two epidemiological seasons were carried out, in which the control and treated areas were alternated between the epidemiological seasons, and we demonstrated the efficacy and safety of the method in suppressing the Ae. aegypti vector population and in blocking the occurrence of an outbreak of dengue in the treated areas. Here, we expand the use of the “Natural Vector Control” program in a large-scale 2-year period intervention carried out in an entire city located in southern Brazil.MethodsSterile male mosquitoes were produced from locally sourced Ae. aegypti mosquitoes by using a treatment that includes double-stranded RNA and thiotepa. Weekly massive releases of sterile male mosquitoes were performed in predefined areas of Ortigueira from December 2020 to July 2022. Mosquito monitoring was performed by using ovitraps during the entire period of intervention. Dengue incidence data in Ortigueira and neighboring cities was obtained from the Brazilian National Disease Surveillance system.ResultsDuring the two epidemiological seasons, the intervention in Ortigueira resulted in up to 98.7% suppression of live progeny of field Ae. aegypti mosquitoes recorded over time. More importantly, the program protected Ortigueira from a dengue outbreak that occurred in the neighboring cities: the dengue incidence in Ortigueira was 97% lower compared to 4 control cities.ConclusionsThe Natural Vector Control method has again been shown to be a safe and efficient way to suppress Ae. aegypti field populations and prevent the occurrence of a dengue outbreak. Importantly, it has been shown to be applicable for large-scale, real-life conditions.
Widespread, perception-related information in the human brain scales with levels of consciousness
Authors: Vigotsky Andrew D. , Jabakhanji Rami , Branco Paulo , Iannetti Gian Domenico , Baliki Marwan N. , Apkarian A. Vania 
Published: September 2022

SummaryHow does the human brain generate coherent, subjective perceptions—transforming yellow and oblong visual sensory information into the perception of an edible banana1? This is a hard problem. The standard viewpoint posits that anatomical and functional networks integrate local, specialized processing across the brain to somehow construct unique percepts. Here, we provide evidence for a novel organizational concept by uncovering task-specific information distributed across the human brain. First, we show that functional magnetic resonance imaging (fMRI) can uncover task-specific information throughout the neocortex, even across voxels traditionally discarded as “noise” (t-statistics ≈ 0), challenging the sensitivity of traditional linear, univariate analytical approaches. Remarkably, task-specific signals could also be uncovered from across-subject variances and were ubiquitous even in the subcortex and cerebellum. Finally, we show that the widespread signal in regions remote from a task’s primary and secondary sensory cortices depends on the level of sedation, suggesting it is related to perception†rather than sensory stimulus encoding. We hypothesize that these widespread, task-specific, and consciousness level-dependent signals may be the basis for coherent, subjective perceptions.
Synthetic maize centromeres transmit chromosomes across generations
Authors: Dawe R. Kelly , Gent Jonathan I. , Zeng Yibing , Zhang Han , Fu Fang-Fang , Swentowsky Kyle W. , Kim Dong won , Wang Na , Liu Jianing , Piri Rebecca D. 
Published: September 2022

AbstractCentromeres are long, often repetitive regions of genomes that bind kinetochore proteins and ensure normal chromosome segregation. Engineering centromeres that function in vivo has proven to be difficult. Here we describe a LexA-CENH3 tethering approach that activates functional centromeres at maize synthetic repeat arrays containing LexO binding sites. The synthetic centromeres are sufficient to cause chromosome breakage and release of chromosome fragments that are passed through meiosis and into progeny. Several independent chromosomes were identified, each with newly created centromeres localized over the repeat arrays where they were directed. The new centromeres were self-sustaining and stably transmitted chromosomes to progeny in the absence of the LexA-CENH3 activator. Our results demonstrate the feasibility of using synthetic centromeres for karyotype engineering applications.
A novel mechanobiological model of bone metastasis reveals that mechanical stimulation inhibits the pro-osteoclastogenic effects of breast cancer cells
Authors: Kumar Vatsal , Naqvi Syeda M. , Verbruggen Anneke , McEvoy Eoin , McNamara Laoise M. 
Published: September 2022

AbstractBone is highly susceptible to cancer metastasis, and both tumour and bone cells enable tumour invasion through a “vicious cycle” of biochemical signalling. Tumor metastasis into bone also alters biophysical cues to both tumour and bone cells, which are highly sensitive to their mechanical environment. However, the mechanobiological feedback between these cells that perpetuates this cycle has not been studied. Here, we develop highly novel in vitro and computational models to provide an advanced understanding of how tumor growth is regulated by the synergistic influence of tumour-bone cell signaling and mechanobiological cues. In particular, we develop the first multicellular healthy and metastatic bone models, which can account for physiological mechanical signals within a custom bioreactor. These models successfully recapitulated mineralization, mechanobiological responses, osteolysis and metastatic activity. Ultimately we demonstrate that mechanical stimulus provided protective effects against tumor-induced osteolysis, confirming the importance of mechanobiological factors in bone metastasis development.
Loss of estrogen unleashing neuro-inflammation increases the risk of Alzheimer’s disease in women
Authors: Li Fuhai , Oh Inez , Kumar Sayantan , Eteleeb Abdallah , Gupta Aditi , Buchser William , Xiong Chengjie , Cole Sessions F. , McDade Eric , Karch Celeste M. , Harari Oscar , Payne Philip R. , Cruchaga Carlos 
Published: September 2022

AbstractThe risk of Alzheimer’s disease (AD) in women is about 2 times greater than in men. The estrogen hypothesis is being accepted as the essential sex factor causing the sex difference in AD. Also, the recent meta-analysis using large-scale medical records data indicated estrogen replacement therapy. However, the underlying molecular targets and mechanisms explaining this sex difference in AD disease development remain unclear. In this study, we identified that estrogen treatment can strongly inhibition of neuro-inflammation signaling targets, using the systems pharmacology model; and identified ESR1/ESR2 (the receptors of estrogen) are topologically close to the neuroinflammation biomarker genes using signaling network analysis. Moreover, the estrogen level in women decreased to an extremely lower level than in men after age 55. Pooling together the multiple pieces of evidence, it is concluded that the loss of estrogen unleashing neuro-inflammation increases the women’s risk of Alzheimer’s disease. These analysis results provide novel supporting evidence explaining the potential mechanism of the anti-neuroinflammation role of estrogen causing the sex difference of AD. Medications boosting the direct downstream signaling of ESR1/ESR2, or inhibiting upstream signaling targets of neuroinflammation, like JAK2 inhibitors, on the signaling network can be potentially effective or synergistic combined with estrogen for AD prevention and treatment.
Interrogating endothelial barrier regulation by temporally resolved kinase network generation
Authors: Wei Ling , Dankwa Selasi , Vijayan Kamalakannan , Smith Joseph D. , Kaushansky Alexis 
Published: September 2022

AbstractVascular leak is a common disease complication, yet the signaling networks regulating barrier integrity are incompletely understood. We developed a novel methodology, Temporally REsolved KInase Network Generation (TREKING), which combines a 28-kinase inhibitor screen with machine learning and network reconstruction to build time-resolved, functional phosphosignaling networks. We demonstrated the utility of TREKING for identifying pathways mediating barrier integrity following thrombin stimulation with or without tumor necrosis factor (TNF) activation in brain endothelial cells. TREKING assigned distinct barrier phenotypes to mitogen-activated protein kinase (MAPK) pathways and revealed a condition-specific MAPKAPK2/MK2 switch kinase pathway with early barrier-disruptive activity in both inflammatory conditions, but late barrier-restorative activity exclusively in the absence of TNF pre-conditioning. MAPKAPK2/MK2 was activated with expected distinct kinetics under the two inflammatory conditions and late activation was linked to a MAP3K20/ZAK-MAPK14/p38α-MAPKAPK2/MK2 pathway. Beyond MAPKs, TREKING predicts extensive interconnected networks that control barrier integrity and is a tool for dissecting complex temporal phosphosignaling networks across biological systems.
Detection of rifampicin resistance in sputum samples by PCR-ELISA
Authors: Bellido-Pantoja Rosa , Pacheco-Ascencio Edson , Valencia-Torres Eddy , Caceres-Rey Omar 
Published: September 2022

ABSTRACTIntroductionTuberculosis caused by Mycobacterium tuberculosis shows resistance to anti-tuberculosis drugs like Rifampicin and Isoniazid generating a public health problem. Using molecular techniques, such as PCR-ELISA, is an alternative that will detect resistance to RIF easily and economically.ObjectiveOptimize a PCR-ELISA that can detect resistance to RIF in sputum samples.MethodA PCR-ELISA was standardized to amplify a 255bp of rpoB gene that encodes resistance to RIF. Different parameters were optimized: hybridization temperatures, and probe concentration, among others. The technique’s analytical sensitivity, specificity, and concordance against GenotypeMTBDRplus v2 were evaluated using 20 samples in a pilot assay.ResultsA PCR-ELISA was optimized for the detection of resistance mutations; the analytical sensitivity of the PCR-ELISA was 4ng of PCR product for the H445D and H445Y probes while for the S450L probe the sensitivity was 0.4 ng of PCR product respectively. The technique has a specificity of 100%. Two mutations, S450W and L452P, were not detected by our system. In the pilot assay, a “good agreement” (k=0.737) was obtained between both techniques.ConclusionsA PCR-ELISA was standardized for the detection of the 3 more frequent mutations in Peru associated with resistance to RIF simultaneously, the most frequent being S450L.
Wildfire smoke exposure and early childhood respiratory health: a study of prescription claims data
Authors: Dhingra Radhika , Keeler Corinna , Staley Brooke S. , Jardel Hanna V. , Ward-Caviness Cavin , Rebuli Meghan E. , Xi Yuzhi , Rappazzo Kristen , Hernandez Michelle , Chelminski Anne , Jaspers Ilona , Rappold Ana G. 
Published: September 2022

AbstractWildfire smoke is associated with short-term respiratory outcomes including asthma exacerbation in children. As investigations into developmental wildfire smoke exposure on children’s longer-term respiratory health are sparse, we investigated associations between developmental WSE and first use of respiratory medications. Prescription claims from IBM MarketScan Commercial Claims and Encounters database were linked with wildfire smoke plume data from NASA satellites based on Metropolitan Statistical Area (MSA). A retrospective cohort of live infants (2010-2016) born into MSAs in six western states, having prescription insurance, and whose birthdate was estimable from claims data was constructed (N=184,703); of these, gestational age was estimated for 113,154 infants. MSA, gestational age, and birthdate were used to estimate average weekly smoke exposure days (smoke-day) for each developmental period: three trimesters, and two sequential 12-week periods post-birth. Medications treating respiratory tract inflammation were classified using active ingredient and mode of administration into three categories: : ‘upper respiratory’, ‘lower respiratory’, ‘systemic anti-inflammatory’. To evaluate associations between wildfire smoke exposure and medication usage, Cox models associating smoke-days with first observed prescription of each medication category were adjusted for infant sex, birth-season, and birthyear with a random intercept for MSA. Smoke exposure during postnatal periods was associated with earlier first use of upper respiratory medications (1-12 weeks: hazard ratio (HR)=1.094 per 1-day increase in average weekly smoke-day, 95%CI: (1.005,1.191); 13-24 weeks: HR=1.108, 95%CI: (1.016,1.209)); sex-specific HRs varied by post-birth exposure window. Protective associations were observed during gestational windows for both lower respiratory and systemic anti-inflammatory medications; it is possible that these associations may be a consequence of live-birth bias. These findings suggest wildfire smoke exposure during early postnatal developmental periods impact subsequent early life respiratory health.
The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants
Authors: Thompson R.N. , Southall E. , Daon Y. , Lovell-Read F.A. , Iwami S. , Thompson C.P. , Obolski U. 
Published: September 2022

AbstractA key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures. Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out. If cross- reactive immunity is complete (i.e. someone infected by the previously circulating virus is no longer susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population. Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses on novel SARS-CoV-2 variants is an essential component of novel variant risk assessments.