bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sex differences in parental response to offspring begging are associated with pair bond strength across birds
Authors: Caro Shana M. , Wu Karleen , Hofmann Hans A 
Published: October 2021

AbstractMothers, fathers, and offspring regularly clash over how much care offspring receive. Offspring beg to solicit for more resources—but how much begging is rewarded can depend on who is listening. While both parents benefit from provisioning offspring, each would benefit from their partner shouldering more of the burden of care, leading to sexual conflict. Additionally, if the costs and benefits of provisioning differ by sex, parent-offspring conflict should vary by sex. How these evolutionary conflicts influence sex differences in parent-offspring communication is unknown. To determine whether the sexes differ in their response to offspring signals, we conducted a meta-analysis on 30 bird species, comparing responsiveness to social and physiological traits affecting conflict. We found that a species’ typical pair bond strength predicts whether males or females respond more to offspring begging. In species with stable and/or monogamous bonds, and thus lower sexual and paternal-offspring conflict, males’ provisioning effort is more strongly correlated with offspring begging than females’. The opposite holds for species with weak pair bonds: females respond more to begging, perhaps compensating for males’ lower responsiveness. These results demonstrate that sex differences in parental care can arise via sex differences in parent-offspring communication, driven by evolutionary conflicts.
A Novel 3D Co-culture Platform for Integrating Tissue Interfaces for Tumor Growth, Migration and Therapeutic Sensitivity: “PP-3D-S”
Authors: Garakani Mansoureh Mohseni , Ahangar Pouyan , Watson Sean , Nisol Bernard , Wertheimer Michael R. , Rosenzweig Derek H. , Ajji Abdellah 
Published: October 2021

ABSTRACTMetastatic cancers can be highly heterogeneous, show large patient variability and are typically hard to treat due to chemoresistance. Personalized therapies are therefore needed to suppress tumor growth and enhance patient’s quality of life. Identifying appropriate patient-specific therapies remains a challenge though, due mainly to non-physiological in vitro culture systems. Therefore, more complex and physiological in vitro human cancer microenvironment tools could drastically aid in development of new therapies. We developed a plasma-modified, electro-spun 3D scaffold (PP-3D-S) that can mimic the human cancer microenvironment for customized-cancer therapeutic screening. The PP-3D-S were characterized for optimal plasma-modifying treatment and scaffolds morphology including fiber diameter and pore size. PP-3D-S was then seeded with human fibroblasts to mimic a stromal tissue layer; cell adhesion on plasma-modified poly (lactic acid), PLA, electrospun mats vastly exceeded that on untreated controls. The cell-seeded scaffolds were then overlaid with alginate/gelatin-based hydrogel embedded with MDA-MB231 human breast cancer cells, representing a tumor-tissue interface. Among three different plasma treatments, we found that NH3 plasma promoted the most tumor cell migration to the scaffold surfaces after 7 days of culture. For all treated and non-treated mats, we observed a significant difference in tumor cell migration between small-sized and either medium- or large-sized scaffolds. In addition, we found that the PP-3D-S was highly comparable to the standard Matrigel® migration assays in two different sets of doxorubicin screening experiments, where 75% reduction in migration was achieved with 0.5μM doxorubicin for both systems. Taken together, our data indicate that PP-3D-S is an effective, low-cost, and easy-to-use alternate 3D tumor migration model which may be suitable as a physiological drug screening tool for personalized medicine against metastatic cancers.
Heat shock chaperone HSPB1 regulates cytoplasmic TDP-43 phase separation and liquid-to-gel transition
Authors: Lu Shan , Hu Jiaojiao , Aladesuyi Bankhole , Goginashvili Alexander , Vazquez-Sanchez Sonia , Diedrich Jolene , Gu Jinge , Blum Jacob , Oung Spencer , Yu Haiyang , Ravits John , Liu Cong , Yates John , Cleveland Don W. 
Published: October 2021

SummaryWhile the RNA binding protein TDP-43 reversibly phase separates within nuclei into complex droplets (anisosomes) with TDP-43-containing liquid outer shells and liquid centers of HSP70 family chaperones, cytoplasmic aggregates of TDP-43 are hallmarks of multiple neurodegenerative diseases, including ALS. Here we show that transient oxidative stress, proteasome inhibition, or inhibition of HSP70’s ATP-dependent chaperone activity provokes reversible cytoplasmic TDP-43 de-mixing and transition from liquid to gel/solid, independent of RNA binding or stress granules. Isotope labeling mass spectrometry is used to identify that phase separated cytoplasmic TDP-43 is primarily bound by the small heat shock protein HSPB1. Binding is direct, mediated through TDP-43’s RNA binding and low complexity domains. HSPB1 partitions into TDP-43 droplets, inhibits TDP-43 assembly into fibrils, and is essential for disassembly of stress-induced, TDP-43 droplets. Decrease of HSPB1 promotes cytoplasmic TDP-43 de-mixing and mislocalization. HSPB1 depletion is identified within ALS-patient spinal motor neurons containing aggregated TDP-43. These findings identify HSPB1 to be a regulator of cytoplasmic TDP-43 phase separation and aggregation.
Reproducible, high-dimensional imaging in archival human tissue by Multiplexed Ion Beam Imaging by Time-of-Flight (MIBI-TOF)
Authors: Liu Candace C. , Bosse Marc , Kong Alex , Kagel Adam , Kinders Robert , Hewitt Stephen M. , Bendall Sean C. , Angelo Michael 
Published: October 2021

AbstractMultiplexed ion beam imaging by time-of-flight (MIBI-TOF) is a form of mass spectrometry imaging that uses metal labeled antibodies and secondary ion mass spectrometry to image dozens of proteins simultaneously in the same tissue section. Working with the National Cancer Institute’s (NCI) Cancer Immune Monitoring and Analysis Centers (CIMAC), we undertook a validation study, assessing concordance across a dozen serial sections of a tissue microarray of 21 samples that were independently processed and imaged by MIBI-TOF or single-plex immunohistochemistry (IHC) over 12 days. Pixel-level features were highly concordant across all 16 targets assessed in both staining intensity (R2 = 0.94 ± 0.04) and frequency (R2 = 0.95 ± 0.04). Comparison to digitized, single-plex IHC on adjacent serial sections revealed similar concordance (R2 = 0.85 ± 0.08) as well. Lastly, automated segmentation and clustering of eight cell populations found that cell frequencies between replicates yielded an average correlation of R2 = 0.92 ± 0.06. Taken together, we demonstrate that MIBI-TOF, with well-vetted reagents and automated analysis, can generate consistent and quantitative annotations of clinically relevant cell states in archival human tissue, and more broadly, present a scalable framework for benchmarking multiplexed IHC approaches.
Decoding of cortex-wide brain activity from local recordings of neural potentials
Authors: Liu Xin , Ren Chi , Huang Zhisheng , Wilson Madison , Kim Jeong-Hoon , Lu Yichen , Ramezani Mehrdad , Komiyama Takaki , Kuzum Duygu 
Published: October 2021

AbstractObjectiveElectrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions.ApproachTo investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings.Main resultsThe mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials.SignificanceThese results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.
Ultraviolet radiation modulates DNA methylation in melanocytes
Authors: Preston-Alp Sarah , Jelinek Jaroslav , Issa Jean-Pierre , Zaidi M. Raza 
Published: October 2021

AbstractUltraviolet radiation (UVR) is the principal causal factor for melanoma; albeit the underlying mechanisms remain unclear. While the mutagenic properties of UVR are irrefutable, the role of UVR-induced mutations in the initiation of melanoma is controversial which highlights the gap in our knowledge of the initial critical molecular mechanisms of UVR-induced melanomagenesis. To investigate the potential non-mutational mechanisms of UVR-induced melanomagenesis, we studied the role of UVR in modulating DNA methylation changes in melanocytes via next-generation sequencing-based methodologies. Here we show that UVR directly causes stable changes in the DNA methylome and transcriptome, one month after exposure. Genomic features associated with transcription were protected from 5mC alterations whereas CpG sites found in intergenic regions were more likely to be affected. Additionally, the long-term effects of UVR seem to perturb signaling pathways important for melanocyte biology. Interestingly, UVR-sensitive CpG sites were found to be prognostic of overall patient survival and highlighted a subset of CpG sites that may be relevant in melanomagenesis.SignificanceWe report a novel finding that ultraviolet radiation (UVR) induces DNA methylation changes along with stable alterations in gene expression in cultured melanocytes. Our results provide experimental evidence of UVR-induced epigenetic rewiring, which may be implicated in the susceptibility to melanomagenesis, independently of its mutational effects. These findings offer novel insight into the role of UVR in the initiation and pathogenesis of melanoma via a currently underappreciated mechanism.
Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets
Authors: Stern Jacob , Hedelius Bryce , Fisher Olivia , Billings Wendy M. , Corte Dennis Della 
Published: October 2021

AbstractThe field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures, however, it has a prohibitively long inference time for applications that require the folding of hundreds of sequences. The prediction of protein structure annotations, such as amino acid distances, can be achieved at a higher speed with existing tools, such as the ProSPr network. Here, we report on important updates to the ProSPr network, its performance on the recent Critical Assessment of Structure Prediction (CASP14) competition, and an evaluation of its accuracy dependency on multiple sequence alignment depth. We also provide a detailed description of the architecture and the training process, accompanied by reusable code. This work is anticipated to provide a solid foundation for the further development of protein distance prediction tools.
Application of Machine Learning in Prediction of COVID-19 Diagnosis for Indonesian Healthcare Workers
Authors: Sonthalia Shreyash , Muharoom Muhammad Aji , Sumulyo Sinta Amalia Kusumastuti , Kamilah Fariza Zahra , Aldila Fatma , Rabbani Bijak , Tirtawisata Andhika , Herlinda Olivia , Khaimani Jatin , Sani Levana , Irwanto Astrid , Hapsari Rebriarina , Luntungan Nurul , Saminarsih Diah , Taher Akmal 
Published: October 2021

ABSTRACTThe COVID-19 pandemic poses a heightened risk to health workers, especially in low- and middle-income countries such as Indonesia. Due to the limitations of implementing mass RT-PCR testing for health workers, high-performing and cost-effective methodologies must be developed to help identify COVID-19 positive health workers and protect the spearhead of the battle against the pandemic. This study aimed to investigate the application of machine learning classifiers to predict the risk of COVID-19 positivity (by RT-PCR) using data obtained from a survey specific to health workers. Machine learning tools can enhance COVID-19 screening capacity in high-risk populations such as health workers in environments where cost is a barrier to the accessibility of adequate testing and screening supplies. We built two sets of COVID-19 Likelihood Meter (CLM) models: one trained on data from a broad population of health workers in Jakarta and Semarang (full model) and tested on the same, and one trained on health workers from Jakarta only (Jakarta model) and tested on both the same and an independent population of Semarang health workers. The area under the receiver-operating-characteristic curve (AUC), average precision (AP), and the Brier score (BS) were used to assess model performance. Shapely additive explanations (SHAP) were used to analyse future importance. The final dataset for the study included 5,393 healthcare workers. For the full model, the random forest was selected as the algorithm choice. It achieved cross-validation of mean AUC of 0.832 ± 0.015, AP of 0.513 ± 0.039, and BS of 0.124 ± 0.005, and was high performing during testing with AUC and AP of 0.849 and 0.51, respectively. The random forest classifier also displayed the best and most robust performance for the Jakarta model, with AUC of 0.856 ± 0.015, AP of 0.434 ± 0.039, and BS of 0.08 ± 0.0003. The performance when testing on the Semarang healthcare workers was AUC of 0.745 and AP of 0.694. Meanwhile, the performance for Jakarta 2022 test set was an AUC of 0.761 and AP of 0.535. Our models yielded high predictive performance and can be used as an alternative COVID-19 methodology for healthcare workers in Indonesia, therefore helping in predicting an increased trend of transmission during the transition into endemic.
Systematic review and meta-analyses on the prevalence of dementia in Latin America and Caribbean countries: Exploring sex, rurality, age, and education as possible determinants
Authors: Ribeiro Fabiana , Teixeira-Santos Ana C. , Caramelli Paulo , Leist Anja K. 
Published: October 2021

AbstractBackgroundStudies have shown that the prevalence of dementia in Latin America and the Caribbean (LAC) may be higher than in high-income countries. Thus, we sought to systematically analyse the prevalence of dementia and explore possible drivers that lead to this disparity in LAC countries.MethodWe searched Pubmed, Web of Knowledge, Scopus, Lilacs, and SciELO for studies on dementia in LAC countries in English, Spanish, and Portuguese languages. Random-effects model was applied.ResultsTwenty-nine studies from 12 LAC countries were included. Pooled prevalence of all-cause dementia was 11%. Further analyses with studies providing raw prevalence by sex, area, and educational level showed a higher prevalence for women (9%) than for men (5%). Also, dementia prevalence was higher for rural than urban residents (12% vs 8%, respectively). Participants without formal education presented more than double the prevalence of dementia (22%) compared to those with at least one year of formal education (10%). Studies with more recent data collection showed higher dementia prevalence.ConclusionOur findings suggest a high global dementia prevalence in LAC countries and an unequal burden of dementia for women, lower-educated, and rural residents. Secular raises in dementia prevalence call for increased public health efforts for preventative action.HighlightsRigorous and most comprehensive review of dementia prevalence in Latin America and the Caribbean (LAC) to date.Pooled dementia prevalence estimates are higher in LAC countries compared to high-income countries.Higher prevalence of dementia among women and lower-educated adults.Higher prevalence among older adults living in rural compared to urban areas.Qualitative analyses suggest a modest increase in dementia prevalence in LAC countries over time.
Updated Model for the USA Summer 2021 CoVID-19 Resurgence
Authors: Eng Genghmun 
Published: October 2021

AbstractOver the course of the CoVID-19 pandemic, we utilized widely-available real-time data to create models for predicting its spread, and to estimate the time evolution for each of the USA CoVID-19 waves. Our recent medrxiv.org preprint (10.1101_2021.08.16.21262150) examined the USA Summer 2021 resurgence, from ∼6/7/2021 up through ∼8/15/2021 (Stage 1). Our preprint covering this period showed that CoVID-19 could infect virtually all susceptible non-vaccinated persons, who were practicing minimal Social Distancing and NO Mask-Wearing.The most recent USA Summer 2021 resurgence data, from ∼8/13/2021 up through 10/7/2021 (Stage 2), shows a significant “flattening of the curve”. Since no new government mandates were involved, our interpretation is that some vaccine-hesitant people have now elected to become vaccinated. The Social Distancing parameter in our model showed a ∼6.67X increase between Stage 1 and Stage 2, indicating that this parameter also can serve as an indicator of vaccination rates. The other parameter in our model, which is associated with Mask-Wearing, increased from zero to a finite but relatively small value. Using the 10/7/2021 USA CoVID-19 overall mortality rate of ∼1.60942 % gives these updated predictions for the total number of USA CoVID-19 cases and deaths:NTOTAL(3/21/2022) ≈ 52, 188, 000 ; NDeaths(3/21/2022) ≈ 839, 900, NTOTAL(3/21/2024) ≈ [52, 787, 000 ; NDeaths(3/21/2024) ≈ 849, 600, assuming no new 2021 Winter Resurgence occurs (with 3 Figures).
Ubiquitin E3 ligases Atrogin-1 and MuRF1 protein contents are differentially regulated in the rapamycin-sensitive mTOR-S6K1 signaling pathway in C2C12 myotubes
Authors: Nishimura Yusuke , Musa Ibrahim , Dawson Peter , Holm Lars , Lai Yu-Chiang 
Published: October 2021

AbstractMuscle-specific ubiquitin E3 ligases, Atrogin-1 and MuRF1, are highly expressed in multiple conditions of skeletal muscle atrophy. The PI3K/Akt/FoxO signaling pathway is well known to regulate Atrogin-1 and MuRF1 gene expressions. Evidence supporting this is largely based on stimuli by insulin and IGF-1, that activate anabolic signaling, including Akt and Akt-dependent transcription factors. However, Akt activation also activates the mammalian target of rapamycin complex 1 (mTORC1) which induces skeletal muscle hypertrophy. However, whether mTORC1-dependent signaling has a role in regulating Atrogin-1 and/or MuRF1 gene and protein expression is currently unclear. In this study, we confirmed that activation of insulin-mediated Akt signaling suppresses both Atrogin-1 and MuRF1 protein content and that inhibition of Akt increases both Atrogin-1 and MuRF1 protein content in C2C12 myotubes. Interestingly, inhibition of mTORC1 using a specific mTORC1 inhibitor, rapamycin, increased Atrogin-1, but not MuRF1, protein content. Furthermore, activation of AMP-activated protein kinase (AMPK), a negative regulator of the mTORC1 signaling pathway, also showed distinct time-dependent changes between Atrogin-1 and MuRF1 protein content, suggesting differential regulatory mechanisms between Atrogin-1 and MuRF1 protein content. To further explore the downstream of mTORC1 signaling, we employed a specific S6K1 inhibitor, PF-4708671, and found that Atrogin-1 protein content was dose-dependently increased with PF-4708671 treatment, whereas MuRF1 protein content was not significantly altered. Overall, our results indicate that Atrogin-1 and MuRF1 protein contents are regulated by different mechanisms, the downstream of Akt, and that Atrogin-1 protein content can be regulated by rapamycin-sensitive mTOR-S6K1 dependent signaling pathway.
A New Mouse Model of Diffuse Midline Glioma to Test Targeted Immunotherapies
Authors: Seblani M , Zannikou M , Duffy J.T. , Levine R.N. , Liu Q , Horbinski C.M. , Becher O.J. , Balyasnikova I.V. 
Published: October 2021

ABSTRACTBACKGROUNDDiffuse midline gliomas remain incurable, with consistently poor outcomes in children despite radiotherapy. Immunotherapeutic approaches hold promise, with the integration of the host’s immune system fundamental to their design. Here, we describe a new, genetically engineered immunocompetent model that incorporates interleukin 13 receptor alpha 2 (IL13Rα2), a tumor-associated antigen, which is suitable for further evaluation of the antitumor activity of IL13Rα2-targeted immunotherapeutics in preclinical studies.METHODSThe RCAS-Tv-a delivery system was used to induce gliomagenesis through overexpression of PDGFB and p53 deletion with and without human IL13Rα2 in Nestin-Tva; p53fl/fl mice. Hindbrain or cerebral cortex nestin progenitors of neonatal pups were infected with Cre recombinase and PDGFB+IL13Rα2 or Cre recombinase and PDGFB to model diffuse midline glioma and supratentorial high-grade glioma, respectively. Immunoblotting and flow cytometry was used to confirm target expression. Kaplan-Meier survival curves were established to compare tumor latency in both models. Tumor tissue was analyzed through immunohistochemistry and H&E staining. Cell lines generated from tumor-bearing mice were used for in vitro studies and orthotopic injections.RESULTSThe protein expression of PDGFB and IL13Rα2 was confirmed by flow cytometry and western blot. In both groups, de novo tumors developed without significant difference in median survival between PDGFB and p53 loss (n=25, 40 days) and PDGFB, IL13Rα2, and p53 loss (n=33, 38 days, p=0.62). Tumors demonstrated characteristics of high-grade glioma such as infiltration, palisading necrosis, microvascular proliferation, high Ki-67 index, heterogeneous IL13Rα2 expression, and CD11b+ macrophages, along with a low proportion of CD3+ T cells. Orthotopic tumors developed from cell lines retained histopathological characteristics of de novo tumors. Mice orthotopically implanted with cells in the hindbrain or right cortex showed a median survival of 42 days and 41 (p=0.56) days, respectively.CONCLUSIONGeneration of de novo tumors using the RCAS-Tv-a delivery system was successful, with tumors possessing histopathologic features common to pediatric diffuse gliomas. The development of these models opens the opportunity for preclinical assessment of IL13Rα2-directed immunotherapies with the potential for clinical translation.