bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunofilaments Provide a Nanoscale Platform for In Vivo T Cell Expansion and Cancer Immunotherapy
Authors: Weiss Lea , Weiden Jorieke , Dölen Yusuf , Grad Emilia M. , van Dinther Eric A.W. , Schluck Marjolein , Eggermont Loek J. , van Mierlo Guido , Gileadi Uzi , Bartoló-Ibars Ariadna , Raavé René , Gorris Mark A.J. , Verrijp Kiek , Valente Michael , Deplancke Bart , Verdoes Martijn , Benitez-Ribas Daniel , Cerundolo Vincenzo , Heskamp Sandra , van Spriel Annemiek B. , Figdor Carl G. , Hammink Roel 
Published: October 2022

AbstractAdoptive T cell therapy has successfully been implemented for the treatment of cancer. Nevertheless, the precarious ex vivo expansion of T cells by artificial antigen-presenting cells (aAPCs) remains cumbersome and can compromise T cell functionality, thereby limiting their therapeutic potential. Here, we propose a radically different approach aiming at direct expansion of T cells in vivo, thereby omitting the need for large-scale ex vivo T cell production. We engineered nanosized immunofilaments (IFs), consisting of a soluble semiflexible polyisocyanopeptide polymer backbone that presents peptide-loaded major histocompatibility complexes and co-stimulatory molecules in a multivalent fashion. We demonstrate that IFs readily activate and expand antigen-specific T cells in a manner highly similar to natural APCs, as evidenced by transcriptomic analyses of T cells. Upon intravenous injection, IFs reach lymphoid organs including spleen and lymph nodes and induce antigen-specific T cell responses in vivo. Moreover, IFs display remarkable anti-tumor efficacy resulting in inhibition of melanoma metastases formation and reduction of primary tumor growth in synergy with immune checkpoint blockade. In conclusion, nanosized IFs represent a powerful new type of aAPC that provide a modular platform for direct activation and expansion of antigen-specific T cells in vivo, which can greatly contribute to cancer immunotherapy.
Identifying dynamic reproducible brain states using a predictive modelling approach
Authors: O’Connor D , Horien C , Mandino F , Constable RT 
Published: October 2022

AbstractConceptually brain states reflect some combination of the internal mental process of a person, and the influence of their external environment. Importantly, for neuroimaging, brain states may impact brain-behavior modeling of a person’s traits, which should be independent of moment-to-moment changes in behavior. A common way to measure both brain states and traits is to use functional connectivity based on functional MRI data. Brain states can fluctuate in time periods shorter than a typical fMRI scan, and a family of methods called dynamic functional connectivity analyses, have been developed to capture these short time estimates of brain states. There has been a rise in the use of dynamic functional connectivity in order to find temporally specific spatial patterns of connectivity which reflect brain states, that can yield further insight into traits and behaviors. It has previously been shown that brain state can be manipulated through the use of continuous performance tasks that put the brain in a particular configuration while the task is performed. Here we focus on moment-to-moment changes in brain state and test the hypothesis that there are particular brain-states that maximize brain-trait modeling performance. We use a regression-based brain-behavior modelling framework, Connectome-based Predictive Modelling, allied to a resample aggregating approach, to identify behavior and trait related short time brain states, as represented by dynamic functional connectivity maps. We find that there is not a particular brain state that is optimal for trait-based prediction, and drawing data from across the scan is better. We also find that this not the case for in-magnet behavioral prediction where more isolated and temporally specific parts of the scan session are better for building predictive models of behavior. The resample aggregated dynamic functional connectivity models of behavior replicated within sample using unseen HCP data. The modelling framework also showed success in the estimating variance behavior in the ABCD dataset when using data from that dataset. The method detailed here may prove useful for both the study of behaviorally related brain states, and for short time predictive modelling.
Weekly dance training over eight months reduces depression and correlates with fMRI brain signals in subcallosal cingulate gyrus (SCG) for people with Parkinson’s Disease: An observational study
Authors: Barnstaple Rebecca E , Bearss Karolina , Bar Rachel J , DeSouza Joseph F 
Published: October 2022

AbstractDepression affects 280 million people globally and is considered a prodromal feature for increasingly prevalent neurodegenerative conditions including Parkinson’s disease (PD). With age-related neurodegeneration on the rise, it’s important to consider non-invasive, inexpensive interventions such as dance. Dance has emerged as a complementary treatment that may support adaptive neuroplasticity while diminishing motor and non-motor symptoms including depression. Although dance has been shown to impact brain structures and functions with improvements in motor and psychological symptoms, the neural mechanisms underlying depression/mood remain elusive. Our observational study tracks the relationship between depression scores and functional neuroimaging measures for subgenual cingulate gyrus (SCG). While learning choreography over an 8-month period, 34 dancers [23 people with PD] completed GDS questionnaires before and after their community dance classes. Seventeen of these dancers had BOLD fMRI scans conducted using learning-related protocols to examine underlying neural mechanisms for moving to music over 4 times points of learning. A significant decrease in depression scores correlated with a reduced BOLD signal from SCG, a putative node in the neural network of depression. Conclusions: This is the first study to clearly find a correlation with a neural substrate involved in mood changes as a function of dance for PD. Not only do the results contribute to understanding neural mechanisms involved in adaptive plasticity with a learning task, but they also uncover reduced activity within SCG during longitudinal therapeutic dance interventions. These results are especially illuminating since SCG is a controversial target in deep brain stimulation (DBS) used in the treatment of major depressive disorder (MDD).
Herb-paths, a network and statistical model to explore health-beneficial effects of herbs and herbal constituents
Authors: van der Voet Monique , Xu Zhiyi , van Rijnberk Lotte , Wu Huihui , Liang Wen , Sun Pengyue , Wang Mei , Wildwater Marjolein , Poppelaars Eefje S. 
Published: October 2022

ABSTRACTPredictions on bioactivities of herbs and herbal compounds could greatly aid drug development, but require integration of available information on herb and compound effects from various databases. We present Herb-paths, an integrated network connecting information on health-beneficial effects of herbs and herbal constituents. The statistical models included in Herb-paths allow for the calculation of the association strength of herbal (constituents) with health-beneficial effects, for both known and novel effects, and give insight into the major bioactive compounds and molecular mechanisms driving the effects.Herb-paths’ predictions were tested and validated using a case-study ofPanax notoginsengand its derived medicinal extract of Panaxatriol saponins (PTS), used in traditional Chinese medicine to treat stroke and other cardiovascular and cerebrovascular thromboembolic (CCT) disorders.Results showed that Herb-paths predicted known and novel associations between PTS/Notoginsengand CCT phenotypes and diseases, including stroke. Predicted novel associations, such as MoyaMoya disease, are promising putative leads for treatment with PTS/Notoginseng, to be tested in further studies.
Tracking the behavioral and neural dynamics of semantic representations through negation
Authors: Zuanazzi Arianna , Ripollés Pablo , Lin Wy Ming , Gwilliams Laura , King Jean-Rémi , Poeppel David 
Published: October 2022

AbstractCombinatoric linguistic operations underpin human language processes, but how meaning is composed and refined in the mind of the reader is not well understood. We address this puzzle by exploiting the ubiquitous function of negation. We track the online effects of negation (“not”) and intensifiers (“really”) on the representation of scalar adjectives (e.g., “good”) in parametrically designed behavioral and neurophysiological (MEG) experiments. The behavioral data show that participants first interpret negated adjectives as affirmative and later modify their interpretation towards, but never exactly as, the opposite meaning. Decoding analyses of neural activity further reveal significant above chance decoding accuracy for negated adjectives within 600 ms from adjective onset, suggesting that negation does not invert the representation of adjectives (i.e., “not bad” represented as “good”); furthermore, decoding accuracy for negated adjectives is found to be significantly lower than that for affirmative adjectives. Overall, these results suggest that negation mitigates rather than inverts the neural representations of adjectives. This putative suppression mechanism of negation is supported by increased synchronization of beta-band neural activity in sensorimotor areas. The analysis of negation provides a steppingstone to understand how the human brain represents changes of meaning over time.
Inference of gene-environment interaction from heterogeneous case-parent trios
Authors: Ratnasekera Pulindu , Graham Jinko , McNeney Brad 
Published: October 2022

ABSTRACTIn genetic epidemiology, log-linear models of population risk may be used to study the effect of genotypes and exposures on the relative risk of a disease. Such models may also include gene-environment interaction terms that allow the genotypes to modify the effect of the exposure, or equivalently, the exposure to modify the effect of genotypes on the relative risk. When a measured test locus is in linkage disequilibrium with an unmeasured causal locus, exposure-related genetic structure in the population can lead to spurious gene-environment interaction; that is, to apparent gene-environment interaction at the test locus in the absence of true gene-environment interaction at the causal locus. Exposure-related genetic structure occurs when the distributions of exposures and of haplotypes at the test and causal locus both differ across population strata. A case-parent trio design can protect inference of genetic main effects from confounding bias due to genetic structure in the population. Unfortunately, when the genetic structure is exposure-related, the protection against confounding bias for the genetic main effect does not extend to the gene-environment interaction term. We show that current methods to reduce the bias in estimated gene-environment interactions from case-parent trio data can only account for simple population structure involving two strata. To fill this gap, we propose to directly accommodate multiple population strata by adjusting for genetic principal components. We evaluate our approach through simulation and illustrate it on data from a study of genetic modifiers of cleft palate.
Gaucher Disease Protects Against Tuberculosis
Authors: Fan Jingwen , Hale Victoria L. , Lelieveld Lindsey T , Whitworth Laura J. , Busch-Nentwich Elisabeth M. , Troll Mark , Edelstein Paul H. , Cox Timothy M. , Roca Francisco J. , Aerts Johannes M.F.G. , Ramakrishnan Lalita 
Published: October 2022

AbstractBiallelic mutations in the glucocerebrosidase (GBA1) gene cause Gaucher disease, characterized by lysosomal accumulation of glucosylceramide and glucosylsphingosine in macrophages. This and other lysosomal diseases occur with high frequency in Ashkenazi Jews. It has been proposed that the underlying mutations confer a selective advantage, in particular conferring protection against tuberculosis. Here, using a zebrafish Gaucher disease model, we find that the mutationGBA1N370S, predominant among Ashkenazi Jews, increases resistance to tuberculosis through the microbicidal activity of glucosylsphingosine in macrophage lysosomes. Consistent with lysosomal accumulation occurring only in homozygotes, heterozygotes remain susceptible to tuberculosis. Thus, our findings reveal a mechanistic basis for protection against tuberculosis byGBA1N370S and provide biological plausibility for its selection if the relatively mild deleterious effects in homozygotes were offset by significant protection against tuberculosis, a rampant killer of the young in Europe through the Middle Ages into the 19thcentury.Significance StatementGaucher disease is a recessively inherited disorder in which the lipids glucosylceramide and glucosylsphingosine accumulate in lysosomes of macrophages. Macrophages are the first immune cells to engulf infecting bacteria and we find that glucosylsphingosine increases their ability to killMycobacterium tuberculosisthat causes tuberculosis. Gaucher disease due to a particular mutation is frequent in Ashkenazi Jews. Since from the middle ages they were often confined to areas of high tuberculosis prevalence, it has been proposed that the mutation prevailed because heterozygotes, who do not accumulate lipids nor manifest Gaucher disease, were protected. Our findings raise the possibility that selection operated on homozygotes manifesting mild forms of Gaucher disease who were protected against tuberculosis which would often have been fatal.
A survey of naturally-occurring molecules as new endoplasmic reticulum stress activators with selective anticancer activity
Authors: da Silva Daniela Correia , Valentão Patrícia , Pereira David M. 
Published: October 2022

AbstractThe last century has witnessed the establishment of neoplastic disease as the second cause of death in the world. Nonetheless, the road towards desirable success rates of cancer treatments is still long and paved with uncertainty. With this work, we aim to select natural products that actviaendoplasmic reticulum (ER) stress, since the latter is known to be a vulnerability of malignant cells, and display selective toxicity against cancer cell lines.Starting from a chemical library of over 90 natural products, nontoxic molecules towards non-cancer cells were selected to be assessed for their toxicity towards cancer cells, namely the human gastric adenocarcinoma cell line AGS and the lung adenocarcinoma cell line A549. The active molecules towards at least one of these cell lines were studied in a battery of ensuing assays designed to show the involvement of ER stress in the observed cytotoxic effect, for instance, by evaluating ER stress-related gene expression or caspase activation. We show that several natural products are selectively cytotoxic against malignant cell lines, with their cytotoxicity relying on ER stress and activation of the unfolded protein response (UPR). Berberine and emodin are proposed as potential leads for the development of more potent ER stressors to be used as selective anticancer agents. Berberine was effective against the two cell models we worked with, disrupting Ca2+homeostasis, inducing UPR target gene expression and ER-resident caspase-4 activation, standing out as the most promising candidate to aid in the development of novel ER stress-based strategies against neoplastic disease.
Identification of a weight loss-associated causal eQTL inMTIF3and the effects ofMTIF3deficiency on human adipocyte function
Authors: Huang Mi , Coral Daniel , Ardalani Hamidreza , Spégel Peter , Saadat Alham , Claussnitzer Melina , Mulder Hindrik , Franks Paul W. , Kalamajski Sebastian 
Published: October 2022

AbstractBackgroundGenetic variation at theMTIF3(Mitochondrial Translational Initiation Factor 3) locus has been robustly associated with obesity in humans, but the functional basis behind this association is not known.MethodsHere, we applied luciferase reporter assay to map potential functional variants in the haplotype block tagged by rs1885988 and used CRISPR-Cas9 to edit the potential functional variants to confirm the regulatory effects onMTIF3expression. We further conducted functional studies on MTIF3-deficient differentiated human white adipocyte cell line (hWAs-iCas9), generated through inducible expression of CRISPR-Cas9 combined with delivery of syntheticMTIF3-targeting guide RNA.ResultsWe demonstrate that rs67785913-centered DNA fragment (in LD with rs1885988, r2>0.8) enhances transcription in a luciferase reporter assay, and CRISPR/Cas9 edited rs67785913 CTCT cells show significantly higherMTIF3expression than rs67785913 CT cells. PerturbedMTIF3expression changed the expression of mitochondrial DNA-encoded genes, and reduced mitochondrial respiration, as well as altered endogenous fatty acid oxidation. Furthermore, after glucose restriction, theMTIF3knockout cells retained more triglycerides than control cells.ConclusionsThis study demonstrates an adipocyte function-specific role ofMTIF3, which originates in the maintenance of mitochondrial function, providing potential explanations for whyMTIF3genetic variation at rs67785913 is associated with body corpulence and response to weight loss interventions.
The Impact of Protein Dynamics on Residue-Residue Coevolution and Contact Prediction
Authors: Fung Alexander , Koehl Antoine , Jagota Milind , Song Yun S. 
Published: October 2022

AbstractThe need to maintain protein structure constrains evolution at the sequence level, and patterns of coevolution in homologous protein sequences can be used to predict their 3D structures with high accuracy. Our understanding of the relationship between protein structure and evolution has traditionally been benchmarked by computational models’ ability to predict contacts from a single representative, experimentally determined structure per protein family. However, proteinsin vivoare highly dynamic and can adopt multiple functionally relevant conformations. Here we demonstrate that interactions that stabilize alternate conformations, as well those that mediate conformational changes, impose an underappreciated but significant set of evolutionary constraints. We analyze the extent of these constraints over 56 paralogous G protein coupled receptors (GPCRs),β-arrestin and the human SARS-CoV2 receptor ACE2. Specifically, we observe that contacts uniquely found in molecular dynamics (MD) simulation data and alternate-conformation crystal structures are successfully predicted by unsupervised language models. In GPCRs, adding these contacts as positives increases the percentage of top contacts classified as true positives, as predicted by a state-of-the-art language model, from 69% to 87%. Our results show that protein dynamics impose constraints on molecular evolution and demonstrate the ability of unsupervised language models to measure these constraints.
Dynamic Modulation of Pulsatile Activities of Oxytocin Neurons in Lactating Wild-type Mice
Authors: Yaguchi Kasane , Hagihara Mitsue , Konno Ayumu , Hirai Hirokazu , Yukinaga Hiroko , Miyamichi Kazunari 
Published: October 2022

AbstractBreastfeeding, which is essential for the survival of mammalian infants, is critically mediated by pulsatile secretion of the pituitary hormone oxytocin from the central oxytocin neurons located in the paraventricular and supraoptic hypothalamic nuclei of mothers. Despite its importance, the molecular and neural circuit mechanisms of the milk ejection reflex remain poorly understood, in part because a mouse model to study lactation was only recently established. In our previous study, we successfully introduced fiber photometry-based chronic imaging of the pulsatile activities of oxytocin neurons during lactation. However, the necessity of Cre recombinase-based double knock-in mice substantially compromised the use of various Cre-dependent neuroscience toolkits. To overcome this obstacle, we developed a simple Cre-free method for monitoring oxytocin neurons by an adeno-associated virus vector driving GCaMP6s under a 2.6 kb mouseoxytocinmini-promoter. Using this method, we monitored calcium ion transients of oxytocin neurons in the paraventricular nucleus in wild-type C57BL/6N and ICR mothers without genetic crossing. By combining this method with video recordings of mothers and pups, we found that the pulsatile activities of oxytocin neurons require physical mother–pup contact for the milk ejection reflex. Notably, the frequencies of photometric signals were dynamically modulated by mother–pup reunions after isolation and during natural weaning stages. Collectively, the present study illuminates the temporal dynamics of pulsatile activities of oxytocin neurons in wild-type mice and provides a tool to characterize maternal oxytocin functions.
Efficient simulation of neural development using shared memory parallelization
Authors: De Schutter Erik 
Published: October 2022

AbstractThe Neural Development Simulator, NeuroDevSim, is a Python module that simulates the most important aspects of development: growth, migration and pruning. It uses an agent-based modeling approach inherited from the NeuroMaC software. Each cycle, agents called fronts execute code. In the case of a growing dendritic or axonal front this will be a choice between extension, branching or growth termination. Somatic fronts can migrate to new positions and any front can be retracted to prune parts of neurons.NeuroDevSim is a multi-core program that uses an innovative shared memory approach to achieve parallel processing without messaging. We demonstrate close to linear strong scaling for medium size models for up to 32 cores and have run large models successfully on 128 cores. Most of the shared memory parallelism is achieved without memory locking. Instead cores have write privileges to private sections of arrays only, while being able to read the entire shared array. Memory conflicts are avoided by a coding rule that allows only active fronts to use methods that need writing access. The exception is collision detection, which is needed to avoid growth of physically overlapping structures. Here a locking mechanism was necessary to control access to grid points that register the location of nearby fronts. A custom approach using a serialized lock broker was able to manage both read and write locking.NeuroDevSim allows easy modeling of neural development for models ranging from a few complex to thousands of simple neurons or a mixture of both.
Killer Toxins for the Control of Diastatic Yeasts in Brewing
Authors: Zhong Victor , Garcia Ximena , Ketchum Nicholas , Rowley Paul A. 
Published: October 2022

AbstractSecondary fermentation in craft beers by diastatic yeasts can result in undesirable consequences, such as off-flavors, increased alcohol content, gushing, and the explosion of packaging. Currently, there are no strategies for inhibiting diastatic yeasts once they have invaded a commercial brewing process. Many strains of yeasts can naturally produce “killer” toxins that inhibit the growth of competing yeasts. Testing the effectiveness of canonical toxins against diastatic yeasts revealed that most (90%) strains are susceptible to the K1 killer toxin. Only two diastatic strains’ resistance to killer toxins was due to toxin production and associated immunity. Four diastatic strains resistant to K1 and K2 toxins were screened against a library of 192 novel killer yeasts to discover novel antifungal activities. This identified novel K2 killer yeasts that were more potent at inhibiting diastatic yeasts than the canonical killer yeast. As proof-of-principle for the control of diastatic yeasts during fermentation, killer yeasts were found to be effective at inhibiting hyperattenuation after a simulated diastatic contamination in a 1,000-liter industrial-style fermentation.