bluuebunny/crossref_metadata_2025_split huggingface dataset:
Placebo's invisible brother: a restricted scoping review of the biomedical literature on the nocebo effect
Authors: Sweeney Owen J. , Parepalli Sai Arathi , Mirtorabi Neginsadat , Loo Yong Kee Kimberley , Feakins Benjamin G. , Aronson Jeffrey K. , Wartolowska Karolina A. 
Published: March 2022

Abstract
Placebos and their beneficial clinical and psychological effects are well-researched, but nocebo effects receive far less attention, despite being highly undesirable. The aim of this restricted scoping review was to examine how nocebo effects are represented in the biomedical literature and to identify the trends and gaps in existing knowledge. After searching 5 biomedical databases and 2 clinical trials registries (from their inception to December 23, 2020) for articles on nocebo effects or negative placebo effects, 1161 eligible publications were identified. The 2 main publication types were nonsystematic reviews (37.7%) and primary research studies (35.6%); only 85 publications (7.3%) were systematic reviews and meta-analyses. The nonsystematic reviews, many of them heavily opinion-based, may contribute to the amplification of narratives, attitudes, and beliefs about nocebo effects that do not objectively reflect the primary research. The primary research articles often used nocebo effects to explain results, rather than as the primary phenomenon under investigation. Most publications were concerned with both positive and negative placebo effects, rather than just nocebo effects. Over half of the abstracts were in the field of neurology, psychiatry, psychology, or neuroscience (52.8%). The nocebo effect was most frequently investigated in the context of pain. Studies were almost exclusively in adults and more often in healthy participants than in patients. In conclusion, in the biomedical literature, there is an overabundance of nonsystematic reviews and expert opinions and a lack of primary research and high-quality systematic reviews and meta-analyses specifically dealing with nocebo effects.
‘‘Now, I know my life is not over!’: Introduction and Adaptation of the RESPECT HIV Intervention, OraQuick, and Trauma-Informed Care for Female Victims of Non-Partner Sexual Violence in Haiti
Authors: Rahill Guitele J. , Joshi Manisha , Blaise Berlande , Carrington Cherelle , Paul Phycien , Zlotnick Caron 
Published: March 2022

IntroductionIn the Cite Soleil (CS) shantytown of Haiti, non-partner sexual violence (NPSV) is widespread, involves multiple assailants who do not use condoms and inflict intentional coital injuries. HIV prevalence in Haiti is 2.2%, CS HIV prevalence is 3.6% shame, guilt, self-blame and societal stigma impede access to HIV testing/treatment in a context of low confidentiality. In that context, NPSV victims often succumb to AIDS. Culturally adapted evidence-based HIV interventions (EBIs) can increase HIV awareness and reduce HIV risk.MethodsFollowing the ADAPT-ITT model, we used purposive sampling to recruit and interview key stakeholders (age 18 and older) in four focus groups (Victims and health providers, as part of adaptation of an EBI HIV (RESPECT) with an orally administered RAPID HIV antibody test (OraQuick) to increase HIV awareness and testing and to reduce HIV risk for victims of NPSV (N=32, 8/focus group). We also introduced trauma-informed care (TIC) to address the post-assault trauma of NPSV victims. Stakeholders were introduced to RESPECT, participated in RESPECT role plays, interpreted OraQuick HIV screen results after viewing a demonstration of a sample collection, and provided feedback on TIC. ATLAS.ti facilitated thematic content analysis of focus group transcripts.ResultsParticipants unanimously (100%) reported that RESPECT, OraQuick, and TIC were acceptable, feasible, and useful for increasing HIV awareness, reducing shame, guilt, and trauma, and empowering NPSV victims to reduce the risk of HIV acquisition/transmission in future consensual relationships.ConclusionEstablishing the acceptability, feasibility and effectiveness of RESPECT, OraQuick, and TIC in CS is a crucial first step towards responding to the HIV prevention and trauma needs of NPSV victims.
A novel automated morphological analysis of microglia activation using a deep learning assisted model
Authors: Lucas Stetzik , Gabriela Mercado , Lindsey Smith , Sonia George , Emmanuel Quansah , Katarzyna Luda , Emily Schulz , Lindsay Meyerdirk , Allison Lindquist , Alexis Bergsma , Jones Russell G , Lena Brundin , Henderson Michael X , Andrew Pospisilik John , Patrik Brundin 
Published: March 2022

AbstractThere is growing evidence for the key role of microglial activation in brain pathophysiology. Consequently, there is a need for efficient automated methods to measure the morphological changes distinctive of microglia functional states in research settings. Currently, many commonly used automated methods can be subject to sample representation bias, time consuming imaging, specific hardware requirements, and difficulty in maintaining an accurate comparison across research environments. To overcome these issues, we use commercially available deep learning tools (Aiforia® Cloud (Aifoira Inc., Cambridge, United States) to quantify microglial morphology and cell counts from histopathological slides of Iba1 stained tissue sections. We provide evidence for the effective application of this method across a range of independently collected datasets in mouse models of viral infection and Parkinson’s disease. Additionally, we provide a comprehensive workflow with training details and annotation strategies by feature layer that can be used as a guide to generate new models. In addition, all models described in this work are shared within the Aiforia® platform and are available for study-specific adaptation and validation.
A low-power communication scheme for wireless, 1000 channel brain-machine interfaces
Authors: Costello Joseph T. , Nason Samuel R. , An Hyochan , Lee Jungho , Mender Matthew J. , Temmar Hisham , Wallace Dylan M. , Lim Jongyup , Willsey Matthew S. , Patil Parag G. , Jang Taekwang , Phillips Jamie D. , Kim Hun-Seok , Blaauw David , Chestek Cynthia A. 
Published: March 2022

AbstractObjectiveBrain-machine interfaces (BMIs) have the potential to restore motor function but are currently limited by electrode count and long-term recording stability. These challenges may be solved through the use of free-floating “motes” which wirelessly transmit recorded neural signals, if power consumption can be kept within safe levels when scaling to thousands of motes. Here, we evaluated a pulse-interval modulation (PIM) communication scheme for infrared (IR)-based motes that aims to reduce the wireless data rate and system power consumption.ApproachTo test PIM’s ability to efficiently communicate neural information, we simulated the communication scheme in a real-time closed-loop BMI with non-human primates. Additionally, we performed circuit simulations of an IR-based 1000-mote system to calculate communication accuracy and total power consumption.Main ResultsWe found that PIM at 1kb/s per channel maintained strong correlations with true firing rate and matched online BMI performance of a traditional wired system. Closed-loop BMI tests suggest that lags as small as 30 ms can have significant performance effects. Finally, unlike other IR communication schemes, PIM is feasible in terms of power, and neural data can accurately be recovered on a receiver using 3mW for 1000 channels.SignificanceThese results suggest that PIM-based communication could significantly reduce power usage of wireless motes to enable higher channel-counts for high-performance BMIs.
Improved basic cytogenetics challenges holocentricity of butterfly chromosomes
Authors: Dutrillaux Bernard , Dutrillaux Anne-Marie , McClure Mélanie , Gèze Marc , Elias Marianne , Bed’hom Bertrand 
Published: March 2022

AbstractMitotic chromosomes of butterflies, which look like dots or short filaments in most published data, are generally considered to lack localised centromeres and thus to be holokinetic. This particularity, observed in a number of other invertebrates, is associated with meiotic particularities known as “inverted meiosis”, in which the first division is equational, i.e., centromere splitting-up and segregation of sister chromatids instead of that of homologous chromosomes. However, the accurate analysis of butterfly chromosomes is difficult. 1) Their size is very small, equivalent to a single band of a mammalian metaphase chromosome. 2) They lack satellite DNA/heterochromatin in putative centromere regions and therefore marked primary constrictions. Our improved conditions for chromosome preparations in six butterfly species belonging to the Nymphalidae and Pieridae families challenges the holocentricity of their chromosomes: in spite of the absence of primary constriction, sister chromatids are recurrently held together at definite positions during mitotic metaphase, which makes possible to establish karyotypes composed of acrocentric and sub-metacentric chromosomes. The total number of chromosomes per karyotype is roughly inversely proportional to that of non-acrocentric chromosomes, which suggests the occurrence of frequent Robertsonian-like fusions or fissions during evolution. Furthermore, the behaviour and morphological changes of chromosomes along the various phases of meiosis do not differ much from those of canonical meiosis. In particular at metaphase II, chromosomes clearly have two sister chromatids, which refutes that anaphase I was equational. Thus, we propose an alternative mechanism to holocentricity for explaining the large variations in chromosome numbers in butterflies: 1) in the ancestral karyotype, composed of about 60-62 acrocentric chromosomes, the centromeres, devoid of centromeric heterochromatin/satellite DNA, were located at contact with telomeric heterochromatin; 2) the instability of telomeric heterochromatin largely contributed to drive the multiple chromosome rearrangements, which occurred during butterfly evolution.
DeepSCM: an efficient convolutional neural network surrogate model for the screening of therapeutic antibody viscosity
Authors: Lai Pin-Kuang 
Published: March 2022

AbstractPredicting high concentration antibody viscosity is essential for developing subcutaneous administration. Computer simulations provide promising tools to reach this aim. One such model is the spatial charge map (SCM) proposed by Agrawal and coworkers (mAbs. 2015, 8(1):43–48). SCM applies molecular dynamics simulations to calculate a score for the screening of antibody viscosity at high concentrations. However, molecular dynamics simulations are computationally costly and require structural information, a significant application bottleneck. In this work, high throughput computing was performed to calculate the SCM scores for 6596 nonredundant antibody variable regions. A convolutional neural network surrogate model, DeepSCM, requiring only sequence information, was then developed based on this dataset. The linear correlation coefficient of the DeepSCM and SCM scores achieved 0.9 on the test set (N=1320). The DeepSCM model was applied to screen the viscosity of 38 therapeutic antibodies that SCM correctly classified and resulted in only one misclassification. The DeepSCM model will facilitate high concentration antibody viscosity screening. The code and parameters are freely available at https://github.com/Lailabcode/DeepSCM.
Plakoglobin is a mechanoresponsive regulator of naïve pluripotency
Authors: Kohler Timo N. , De Jonghe Joachim , Ellerman Anna L. , Yanagida Ayaka , Herger Michael , Slatery Erin M. , Fischer Katrin , Mulas Carla , Winkel Alex , Ross Connor , Bergmann Sophie , Franze Kristian , Chalut Kevin , Nichols Jennifer , Boroviak Thorsten E. , Hollfelder Florian 
Published: March 2022

AbstractBiomechanical cues are instrumental in guiding embryonic development and cell differentiation. Understanding how these physical stimuli translate into transcriptional programs could provide insight into mechanisms underlying mammalian pre-implantation development. Here, we explore this by exerting microenvironmental control over mouse embryonic stem cells (ESCs). Microfluidic encapsulation of ESCs in agarose microgels stabilized the naïve pluripotency network and specifically induced expression of Plakoglobin (Jup), a vertebrate homologue of β-catenin. Indeed, overexpression of Plakoglobin was sufficient to fully re-establish the naïve pluripotency gene regulatory network under metastable pluripotency conditions, as confirmed by single-cell transcriptome profiling. Finally, we found that in the epiblast, Plakoglobin was exclusively expressed at the blastocyst stage in human and mouse embryos – further strengthening the link between Plakoglobin and naïve pluripotency in vivo. Our work reveals Plakoglobin as a mechanosensitive regulator of naïve pluripotency and provides a paradigm to interrogate the effects of volumetric confinement on cell-fate transitions.Highlights3D agarose spheres stabilize the naïve pluripotency network in mouse ESCs.Volumetric confinement induces expression of Plakoglobin, a vertebrate homologue of β-catenin.Plakoglobin expression in the epiblast is specific to pre-implantation human and mouse embryos.Plakoglobin overexpression maintains naïve pluripotency independently of β-catenin.
Hyperglycemic O-GlcNAc transferase activity drives cancer stem cell induction in TNBC
Authors: Ayodeji Saheed , Bao Bin , Teslow Emily A. , Polin Lisa A. , Dyson Greg , Bollig-Fischer Aliccia , Fehl Charlie 
Published: March 2022

AbstractEnhanced glucose metabolism is a feature of almost all cancers, but downstream functional effects of aberrant glucose flux are difficult to mechanistically determine. The objective of this study is to characterize a mechanism by which elevated glucose level drives a tumorigenic pathway in triple negative breast cancer (TNBC). We used chemical biology methods to track how a metabolite of glucose, N-acetylglucosamine (GlcNAc), is linked to the transcriptional regulatory protein tet-methylcytosine dioxygenase 1 (TET1) as an O-linked GlcNAc post translational modification (O-GlcNAc). In this work, we revealed that intracellular protein glycosylation by O-GlcNAc is driven by high glucose levels in TNBC models, including on TET1. A single enzyme, O-GlcNAc transferase (OGT), is responsible for catalyzing protein modification of O-GlcNAc. We showed that OGT activity is higher in TNBC cell lines compared to non-tumor breast cell lines and is associated with hyperglycemia. Furthermore, enhanced OGT activity activated a pathway for cancer stem-like cell (CSC) reprogramming in TNBC cells. In our model, O-GlcNAcylated TET1 upregulated expression of splicing factor TAR-DNA binding protein (TARDBP), which drives CSC induction as well as higher OGT levels. We show that this OGT-TET1-TARDBP axis “feeds-forward” in hyperglycemic conditions both in cell lines and diet-induced obese mice, which displayed higher blood glucose levels and tumor O-GlcNAc levels than lean littermates. This data converges on a novel pathway whereby hyperglycemia drives aberrant OGT activity, activating a pathway for CSC induction in TNBC. Our findings partially explain a key aspect of how obesity is associated with TNBC risk and negative outcomes.Statement of ImplicationThis work presents a novel mechanism to explain how obesity is a risk factor for triple-negative breast cancer via elevated sugar-transfer activity by O-GlcNAc transferase in hyperglycemia, leading to the induction of a cancer stem-like cells and revealing a targetable pathway in obesity-associated tumors.
High salinity activates CEF and attenuates state transitions in both psychrophilic and mesophilic Chlamydomonas species
Authors: Kalra Isha , Wang Xin , Zhang Ru , Morgan-Kiss Rachael 
Published: March 2022

ABSTRACTIn the last decade, studies have revealed the importance of PSI-driven cyclic electron flow (CEF) in stress acclimation in model organisms like C. reinhardtii; however, these studies focused on transient, short-term stress. In addition, PSI-supercomplexes are associated with CEF during state transition response to short-term stress. On the other hand, the role of CEF during long-term stress acclimation is still largely unknown. In this study, we elucidate the involvement of CEF in acclimation response to long-term high salinity in three different Chlamydomonas species displaying varying salinity tolerance. We compared CEF rates, capacity for state transitions, and formation of supercomplexes after salinity acclimation in the model mesophile C. reinhardtii and two psychrophilic green algae C. priscuii (UWO241) and C. sp. ICE-MDV. CEF was activated under high salt in all three species, with the psychrophilic Chlamydomonas spp. exhibiting the highest CEF rates. High salt acclimation was also correlated with reduced state transition capacity and a PSI-supercomplex was associated with high CEF. We propose that under long-term stress, CEF is constitutively activated through assembly of a stable PSI-supercomplex. The proteomic composition of the long-term PSI-supercomplex is distinct from the supercomplex formed during state transitions, and its presence attenuates the state transition response.
TopOMetry systematically learns and evaluates the latent dimensions of single-cell atlases
Authors: Sidarta-Oliveira Davi , Domingos Ana , Velloso Licio A. 
Published: March 2022

AbstractA core task in single-cell data analysis is recovering the latent dimensions encoding the genetic and epigenetic landscapes inhabited by cell types and lineages. However, consensus is lacking for optimal modeling and visualization approaches. Here, we propose these landscapes are ideally modeled as Riemannian manifolds, and present TopOMetry, a computational toolkit based on Laplacian-type operators to learn these manifolds. TopOMetry learns and evaluates dozens of possible representations systematically, eliminating the need to choose a single dimensional reduction methoda priori. The learned visualizations preserve more original information than current PCA-based standards across single-cell and non-biological datasets. TopOMetry allows users to estimate intrinsic dimensionalities and visualize distortions with the Riemannian metric, among other challenging tasks. Illustrating its hypothesis generation power, TopOMetry suggests the existence of dozens of novel T cell subpopulations consistently found across public datasets that correspond to specific clonotypes. TopOMetry is available athttps://github.com/davisidarta/topometry.
HCLC-FC: a novel statistical method for phenome-wide association studies
Authors: Liang Xiaoyu , Cao Xuewei , Sha Qiuying , Zhang Shuanglin 
Published: March 2022

AbstractThe emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association studies (PheWAS). In PheWAS, the whole phenome can be divided into numerous phenotypic categories according to the genetic architecture across phenotypes. Currently, statistical analyses for PheWAS are mainly univariate analyses, which test the association between one genetic variant and one phenotype at a time. In this article, we derived a novel and powerful multivariate method for PheWAS. The proposed method involves three steps. In the first step, we apply the bottom-up hierarchical clustering method to partition a large number of phenotypes into disjoint clusters within each phenotypic category. In the second step, the clustering linear combination method is used to combine test statistics within each category based on the phenotypic clusters and obtain p-values from each phenotypic category. In the third step, we propose a new false discovery rate (FDR) control approach. We perform extensive simulation studies to compare the performance of our method with that of other existing methods. The results show that our proposed method controls FDR very well and outperforms other methods we compared with. We also apply the proposed approach to a set of EMR-based phenotypes across more than 300,000 samples from UK Biobank. We find that the proposed approach not only can well-control FDR at a nominal level but also successfully identify 1,244 significant SNPs that are reported to be associated with some phenotypes in the GWAS catalog. Our open-access tools and instructions on how to implement HCLC-FC are available at https://github.com/XiaoyuLiang/HCLCFC.Author summaryAs a complementary approach to genome-wide association studies, phenome-wide association studies (PheWAS) have been an efficient tool for testing associations between genetic variations and a wide range of phenotypes utilizing all available phenotypic information. For instance, the first PheWAS has demonstrated that rs3135388 on HLA-DRB1 associated with atrial fibrillation and multiple sclerosis. A challenging step in performing large-scale multiple testing of PheWAS is to control the false discovery rate (FDR). In this work, we propose a novel and powerful multivariate method, HCLC-FC, to test the association between a genetic variant with a large number of phenotypes simultaneously controlling FDR. Within each phenotypic category, a newly proposed method clusters phenotypes into different groups and the combined test statistic within each category based on the phenotypic clusters has an asymptotic distribution which avoids the computational burden of simulation. Furthermore, the newly developed FDR controlling process is based on p-values and does not depend on test statistics. Therefore, it is more general and can be applied to other multiple testing procedures to control FDR.