bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping the FF domain folding pathway via structures of transiently populated folding intermediates
Authors: De Debajyoti , Thapliyal Nemika , Prakash Tiwari Ved , Toyama Yuki , Flemming Hansen D. , Kay Lewis E. , Vallurupalli Pramodh
Published: December 2024

Despite the tremendous accomplishments of AlpaFold2/3 in predicting biomolecular structure, the protein folding problem remains unsolved in the sense that accurate atomistic models of how protein molecules fold into their native conformations from an unfolded ensemble are still elusive. Here, using chemical exchange saturation transfer (CEST) NMR experiments and a comprehensive four-state kinetic model of the folding trajectory of a 71 residue four-helix bundle FF domain from human HYPA/FBP11 we present an atomic resolution structure of a transiently formed intermediate, I2, that along with the structure of a second intermediate, I1, provides a description of the FF domain folding trajectory. By recording CEST profiles as a function of urea concentration the extent of compaction along the folding pathway is evaluated. Our data establish that unlike the partially disordered I1 state, the I2 intermediate that is also formed before the rate-limiting folding barrier is well ordered and compact like the native conformer, while retaining nonnative interactions similar to those found in I1. The slow-interconversion from I2 to F, involving changes in secondary structure and the breaking of nonnative interactions, proceeds via a compact transition-state. Interestingly, the native state of the FF1 domain from human p190-A Rho GAP resembles the I2 conformation, suggesting that well-ordered folding intermediates can be repurposed by nature in structurally related proteins to assume functional roles. It is anticipated that the strategy for elucidation of sparsely populated and transiently formed structures of intermediates along kinetic pathways described here will be of use in other studies of protein dynamics.
Widespread neuroanatomical integration and distinct electrophysiological properties of glioma-innervating neurons
Authors: Hsieh Annie L. , Ganesh Sanika , Kula Tomasz , Irshad Madiha , Ferenczi Emily A. , Wang Wengang , Chen Yi-Ching , Hu Song-Hua , Li Zongyu , Joshi Shakchhi , Haigis Marcia C. , Sabatini Bernardo L.
Published: December 2024

Gliomas are the most common malignant primary brain tumor and are often associated with severe neurological deficits and mortality. Unlike many cancers, gliomas rarely metastasize outside the brain, indicating a possible dependency on unique features of brain microenvironment. Synapses between neurons and glioma cells exist, suggesting that glioma cells rely on neuronal inputs and synaptic signaling for proliferation. Yet, the locations and properties of neurons that innervate gliomas have remained elusive. In this study, we utilized transsynaptic tracing with an EnvA-pseudotyped, glycoprotein-deleted rabies virus to specifically infect TVA and glycoprotein-expressing human glioblastoma cells in an orthotopic xenograft mouse model, allowing us to identify the neurons that form synapses onto the gliomas. Comprehensive whole-brain mapping revealed that these glioma-innervating neurons (GINs) from brain regions, including diverse neuromodulatory centers and specific cortical layers, known to project to the glioma locations. Molecular profiling revealed that long-range cortical GINs are predominantly glutamatergic, and subsets express both glutamatergic and GABAergic markers, whereas local striatal GINs are largely GABAergic. Electrophysiological studies demonstrate that while GINs share passive intrinsic properties with cortex-innervating neurons, their action potential waveforms are altered. Our study introduces a method for identifying and mapping GINs and reveals their consistent integration into existing location-dependent neuronal networks involving diverse neurotransmitters and neuromodulators. The observed intrinsic electrophysiological differences in GINs lay the groundwork for future investigations into how these alterations relate to the postsynaptic characteristics of glioma cells.
The effects of different pellet shapes on streamer dynamics in patterned dielectric barrier discharges
Authors: Berger B , Mujahid Z , Neuroth C , Azhar M , Wang L , Zhang Q-Z , Mussenbrock T , Korolov I , Schulze J
Published: December 2024

Dielectric barrier discharges (DBDs) are frequently used for gas conversion for environmental protection by removing harmful components from gas streams and converting them into value added products. DBD operation is typically combined with catalysts placed on spherical dielectric beads in the plasma volume to enhance conversion rates and energy efficiency. However, the presence of such pellets blocks the gas flow and their random arrangement leads to unstable discharges. In this work, we use an advanced plasma source, the patterned DBD, where dielectric pellets are immersed into an electrode at fixed and controllable positions to enhance plasma stability and control. Based on experiments and simulations we study the effects of the pellet shape and the driving voltage on the spatio-temporally resolved dynamics of volume and surface streamers, that ultimately determine the generation of reactive species, plasma-catalyst coupling, and conversion rates/efficiencies via electron heating. The pellet shape is found to influence the streamer speed and the generation of energetic electrons. Via their effects on the effective capacitance of the pellet, shapes with a flatter plasma facing apex are polarized more strongly by approaching volume streamers. This results in a stronger local enhancement of the electric field at the apex, higher volume streamer speed, and more electron heating at this position. Depending on the surface topology maximum electron impact excitation of the background gas is observed at different locations along the pellet’s surface. Changing the polarity of the rectangular driving voltage waveform provides control of the direction of positive/negative streamer propagation and selectivity towards anode or cathode directed streamer movement.
Thermoelectric properties of type-I and type-II nodal line semimetals: a comparative study
Authors: Laksono Mohammad Norman Gaza , Majidi M Aziz , Nugraha Ahmad R T
Published: December 2024

We investigate the thermoelectric (TE) properties of nodal line semimetals (NLSs) using a combination of semi-analytical calculations within Boltzmann's linear transport theory and the relaxation time approximation along with first-principles calculations for the so-called type-I and type-II NLSs. We consider the conduction and valence bands that cross near the Fermi level of these materials through first-principles calculations of typical type-I (TiS) and type-II (Mg3Bi2) NLSs and use the two-band model fit to find the Fermi velocity v

F
and effective mass m that will be employed as the initial energy dispersion parameters. The optimum curvature value for each energy band is searched by tuning both v

F
and m to improve the TE properties of the NLSs. By systematically analyzing the calculation results, we observe that tuning v

F
significantly improves TE properties in both types of NLS compared to tuning m. We also find that in all TE metrics, the type-I NLS surprisingly can surpass the type-II NLS, which seems counter-intuitive to the fact that within the two-band model, the type-I NLS contains a parabolic band while the type-II NLS possesses a higher-order, Mexican-hat band. Our study demonstrates that optimizing the curvature of energy bands by tuning v

F
can significantly improve the TE performance of NLSs. This approach could guide future efforts in exploring other semimetals as potential TE materials by manipulating their band structures.
Reconstruction of the fast-ion deuterium distribution in a tritium-rich plasma in the JET DTE2 campaign
Authors: Järleblad H. , Reman B.C.G. , Dong Y. , Nocente M. , Eriksson J. , Valentini A. , Rud M. , Dal Molin A. , Garcia J. , Kazakov Ye.O. , Keeling D. , King D. , Lerche E.A. , Lorenzini R. , Maggi C. , Maslov M. , Moseev D. , Rigamonti D. , Schmidt Bo S. , Štancar Ž. , Tardocchi M. , Salewski M. , Contributors JET ,   the EUROfusion Tokamak Exploitation Team
Published: December 2024

An important step on the way to future fusion power plants was the 2021 deuterium–tritium experimental campaign (DTE2) at the Joint European Torus (JET), in which crucial DT physics was investigated. In this study, we have reconstructed the fast-ion deuterium distribution function in JET discharge 99971 which broke the former fusion energy record. It is the first time that the fast-ion distribution has been reconstructed from experimental data in a DT discharge. The reconstruction shows that the fast-ion deuterium distribution is anisotropic, with a bias towards co-going ions (p > 0). The fast-ion deuterium distribution likely peaks in energy (E) at around

E
∼
60

–70 keV and has a marginal high-energy tail (

E
≳
180

 keV). Furthermore, an orbit analysis shows that the fast-ion distribution is composed of mostly co-passing orbits (

50
%

), trapped orbits (

21
%

) and counter-passing orbits (

27
%

), as well as a small population of potato orbits (

1.7
%

) and counter-stagnation orbits (

0.3
%

). The orbit-type constituents of the neutron measurements are distributed in similar fractions.
Defect detection and size classification in CdTe samples in 3D
Authors: Väänänen M. , Kalliokoski M. , Turpeinen R. , Bezak M. , Luukka P. , Karjalainen A. , Karadzhinova-Ferrer A.
Published: December 2024

Defects in semiconductor crystals can have significant detrimental effects on their performance as radiation detectors. Defects cause charge trapping and recombination, leading to lower signal amplitudes and poor energy resolution. We have designed and built a modular 3D scanner for analyzing these defects in semiconductor samples using commercial off-the-shelf components. Previous solutions offer great spatial resolution, but have limited sample holding capacity and use continuum light sources which can cause difficulty differentiating between different materials within samples. Our design also includes a modular sample holder allowing for easy changing of samples. In this paper, we showcase first results achieved with this custom built scanner as well as planned developments.
A comprehensive guide to volatolomics data analysis
Authors: Skawinski M , Schooten F J van , Smolinska A
Published: December 2024

Volatolomics (or volatilomics), the study of volatile organic compounds, has emerged as a significant branch of metabolomics due to its potential for non-invasive diagnostics and disease monitoring. However, the analysis of high-resolution data from mass spectrometry and gas sensor array-based instruments remains challenging. The careful consideration of experimental design, data collection, and processing strategies is essential to enhance the quality of results obtained from subsequent analyses. This comprehensive guide provides an in-depth exploration of volatolomics data analysis, highlighting the essential steps, such as data cleaning, pretreatment, and the application of statistical and machine learning techniques, including dimensionality reduction, clustering, classification, and variable selection. The choice of these methodologies, along with data handling practices, such as missing data imputation, outlier detection, model validation, and data integration, is crucial for identifying meaningful metabolites and drawing accurate diagnostic conclusions. By offering researchers the tools and knowledge to navigate the complexities of volatolomics data analysis, this guide emphasizes the importance of understanding the strengths and limitations of each method. Such informed decision-making enhances the reliability of findings, ultimately advancing the field and improving the understanding of metabolic processes in health and disease
Thin film sputter-deposition of AlN crystals in oxygenated chamber: a pilot study
Authors: Abd Samad Muhammad Izzuddin , Badrudin Syazwani Izrah , Mansor Marwan , Nayan Nafarizal , Abu Bakar Ahmad Shuhaimi , Yusop Mohd Zamri , Latif Rhonira
Published: December 2024

Aluminium nitride (AIN) is a promising thin film electrical insulation material layer in electronic devices. The magnetron sputtering method is usually employed to sputter-deposit AlN thin film on silicon (Si) substrate using a pure aluminium (Al) metallic target in a low base pressure vacuum condition. In many cases, the thin film deposition of high quality AlN crystals requires the application of heat and bias to the substrate, highly pure nitrogen reactant gas, argon sputtering gas and Al target, low sputtering pressure, high sputtering power, post-deposition AlN annealing, ultra-low base pressure of the sputtering chamber and a distinctive crystal orientation of the nucleation layer or substrate underneath. In our work, the utilisation of AlN ceramic target instead of pure Al metallic target has allegedly facilitated the growth of AlN crystals without the need to conform to these requirements. Non-amorphous AlN〈100〉 and AlN〈002〉 thin film crystals have been successfully sputtered from AlN ceramic target on Si〈100〉 substrate in a relatively high sputtering chamberbase pressure and at a moderate 200 W - 250 W of sputtering power. Additionally, 250 W of sputtering power has been observed to assist in the growth of AlN〈002〉 crystals. The presence of AlN〈002〉 may have reduced the leakage/tunnel current density in AlN thin film layer to 46.33 pA cm−2 and modified the small-scale surface height characteristics. A high degree of AlN〈002〉 crystallisation may suggest good electrical insulating properties in AlN thin film layer, which can be applied in electronic devices that critically require a low leakage current specification.
Vitiligo is associated with lower body mass index: a retrospective case–control study
Authors: Sharifzadeh Afsheen , Wetstone Rachel , Chen Li-Chi , Guilarte-Walker Yurima , Flahive Julie , Harris John E
Published: December 2024

Our study demonstrated that adults with vitiligo had a 1.5-unit lower BMI [mean (SD) 27.8 (6.1) vs. 29.3 (7.2) kg m–2; P = 0.001], but higher risk of hyperlipidaemia [aOR 1.40, 95% CI (1.12–1.70)] and hypercholesterolaemia [aOR 1.44, 95% CI (1.10–1.90)] compared with age-, sex- and race-matched subjects without vitiligo. The inverse association between BMI and vitiligo was independent of the presence of concomitant cardiometabolic diseases. Additionally, we contextualized these findings in relation to other immune-mediated skin disorders, including alopecia areata and psoriasis, to explore underlying pathogenesis and guide the development of appropriate screening criteria.
Comprehensive technical evaluation and optimization of a carbon-neutral biomass-based power system integrating supercritical CO2 combustion and CO2 liquefaction with hydrogen production
Authors: Zou Qunyan , Jaffar Hussein A , El-Shafay A S , Agarwal Diwakar , Munshid Luma Sabah , Ahmed Mohsen , Rajab Husam , Mir Ahmed , Kolsi Lioua , Almeshaal Mohammed A
Published: December 2024

The increasing reliance on fossil fuels poses critical challenges for energy systems. A novel power generation system integrating electricity/hydrogen production, oxy-fuel combustion, and CO2 liquefaction is evaluated through technical analysis and multi-objective optimization. Further, biomass-derived syngas powers the system, while a solid oxide electrolyzer (SOE) converts surplus energy into hydrogen, enhancing flexibility and efficiency. CO2 liquefaction reduces the levelized cost of electricity, contributing to economic feasibility. In addition, the system achieves optimized results with a cost of $0.37/kWh and $4.9 million in cash flow, demonstrating its potential as an efficient, sustainable energy solution with a 5.4% reduction in power.
The Brussels effect in Africa: is it beneficial for intra-regional trade in digital services?
Authors: Ferracane Martina F , González Ugarte Simón , van der Marel Erik
Published: December 2024

With cross-border data flows being central to the African Union’s digital transformation, African countries have adopted varied approaches to governing data transfers. We categorize these approaches into three regulatory models—open, conditional, and control—reflecting frameworks promoted by the USA, the European Union, and China, respectively. Using a gravity model, we assess how these models, along with comprehensive data protection laws, influence intra-regional trade in digital services. Our findings show that countries following the US-inspired open model experience higher trade volumes with other African trade partners, while the widespread adoption of the EU-inspired conditional model negatively impacts intra-regional digital trade. We do not find significant effects for the China-inspired control model. Additionally, we find that the adoption of a comprehensive data protection law, which in the region is often modelled after the EU’s General Data Protection Regulation, correlates negatively with trade, particularly for lower-income countries, potentially due to the cost burden of compliance. In the context of the recent commitment to open data flows undertaken by African Union members in the African Continental Free Trade Area’s Digital Trade Protocol, we estimate that open data flows could boost intra-regional digital services trade by 10.3%, or around 125 million USD. When developing regional data rules, we recommend that policymakers consider the unique needs of lower-income countries and provide technical assistance to face compliance costs.
Metabolic Profiles of Critical Care Patients to Confirm Sepsis and Further Understand the Metabolic Phenotype of Sepsis
Authors: Graham Julie-Kathryn , Westcott Anova , Smith Shawn , Mann Emlyn , Daniels Ray , Quillin-McEwan Molly , Bahena Angel , Bello Dwight , Kelley Christina
Published: December 2024

Sepsis remains a major concern in health care globally. Despite decades of research, incidence is on the rise, and mortality remains high. Costs are staggering. Additionally, the outdated sepsis bundle established based on SIRS, remains the standard by which providers are held accountable. It is now accepted that organ dysfunction in sepsis is secondary to cellular metabolic dysregulation. Technology for metabolic monitoring should be explored for improved, early recognition of sepsis. We sought to investigate the underlying metabolic profile of patients with sepsis, to determine the value of continuous metabolic monitoring technology. The investigators partnered with industry, to trial noninvasive monitoring of the cellular metabolite carbon dioxide, under a prospective, observational design. During the 6-month trial, the investigators collected data from the electronic medical record of patients using the technology, to determine the specific metabolic differences between patients with and without sepsis. The investigators found serum carbon dioxide (paCO2) was significantly lower in patients with sepsis, and, low paCO2 had a significant inverse relationship to serum lactate. This finding supports the notion that paCO2 is low in sepsis secondary to metabolic dysregulation and not hyperventilation, which had historically explained low paCO2 under the SIRS model. Metabolic monitoring is available, easy to apply and manage, and contributes valuable information in the detection of sepsis. Further research should be done to understand trends in serum CO2 and its relationship to the development of sepsis. This study also provides important further support for the emerging understanding of the dysregulated host response in sepsis.
Temporal Incision Super-high Superficial Musculoaponeurotic System Face Lift for Chinese Patients
Authors: Wang Jingang , Xie Lining , Zhang Ning , Hu Lijuan , Zhang Siqing , Liu Jingchun , Wang Xihua , Yan Xiaofeng
Published: December 2024

Background:

This investigation assessed patient satisfaction with a temporal incision technique using a super-high superficial musculoaponeurotic system (SMAS) flap for midface lifting in a Chinese patient cohort.

Methods:

From July 2019 to July 2023, 95 patients underwent midface lifts via a temporal incision approach at our institution. The extent of SMAS flap dissection spanned 2 cm above the outer canthus, to the lower margin of the zygomatic arch inferiorly, and medially to the zygomaticus major muscle. The technique involved anchoring the elevated SMAS flap to the deep temporal fascia to elevate the malar fat pads, correct sagging tissues, and ameliorate the appearance of nasolabial folds.

Results:

Among the 95 patients, 61 completed a follow-up ranging from 6 months to 2 years postsurgery, with a majority reporting satisfaction with the aesthetic results of their midface lift. No significant complications, including permanent facial nerve injury, were reported.

Conclusions:

The temporal incision super-high SMAS face lift technique demonstrated high patient satisfaction and clinical effectiveness in improving the appearance of nasolabial fold and midface aesthetics. However, the success of this technique hinges on a comprehensive understanding of facial anatomy due to the confined operative field, highlighting its technical demands and the need for surgical expertise.
The Effect of Foot Reflexology and Knee Massage With Black Cumin Seed Oil on Knee Osteoarthritis Symptoms
Authors: Bakir Ercan , Baglama Sevgin S.
Published: December 2024

This study aimed to examine the effect of foot reflexology and knee massage with black cumin seed oil on pain and fatigue symptoms in elderly individuals with knee osteoarthritis and assess which of these 2 applications is more effective. Our randomized controlled trial was conducted with 150 participants. Study data were collected from participants over 65 years who received outpatient treatment in a university hospital’s physical therapy and rehabilitation unit and were determined to have no perception problems based on the Mini-Mental Test. After randomization, the study sample was classified into 5 groups, each including 30 participants: (1) foot reflexology with black cumin seed oil, (2) foot reflexology with a placebo, (3) knee massage with black cumin oil, (4) knee massage with a placebo, and (5) control. Participants were administered a Patient Descriptive Information Form, the Lequesne Knee Osteoarthritis Index, the Pain-Visual Analog Scale, the Fatigue Severity Scale, and the Western Ontario and McMaster Universities Osteoarthritis Index. Control group participants received standard of care, while participants in treatment groups received the studied interventions for 6 weeks. Data were collected by administering questionnaires to the participants in the first and sixth weeks and analyzed using IBM Statistical Package for Social Sciences 22.0 software. The study showed that foot reflexology and knee massage administered using black cumin oil effectively reduced pain and fatigue severity in Osteoarthritis (OA) patients, and overall, foot reflexology administered using black cumin oil was the most effective treatment to reduce pain and fatigue.
Diet and special educational needs (SENs) among children and adolescents: a systematic review
Authors: Nova Lúcia , Poínhos Rui , Teixeira Beatriz
Published: December 2024

Special educational needs (SENs) refer to children and adolescents needing additional educational support. Diet during pregnancy and pediatric age can influence the prevalence/severity of symptoms in SEN-related conditions/disabilities. This review aims to summarize associations between (i) pregnant women's diet and the prevalence of SEN-related conditions/disabilities among children/adolescents and (ii) the diet of children/adolescents with SEN-related conditions/disabilities and their symptomatology/well-being. A literature search was performed on Medline and Scopus, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following inclusion criteria were considered, for each aim: (i) children/adolescents aged 19 years and younger, pregnant women's diet/nutrition, and diagnosis of SEN-related conditions/disabilities in children/adolescents; (ii) children/adolescents aged 19 years and younger, children/adolescents' diet/nutrition, and symptomatology/well-being of children/adolescents with SEN-related conditions/disabilities. 87 articles were included, referring to 10 different SEN-related conditions/disabilities, from which attention-deficit/hyperactivity disorder (ADHD) (41 articles) and autism spectrum disorder (ASD) (34 articles) stand out. Noteworthy results were seen regarding maternal caffeine consumption; pregnant woman multivitamin supplementation, high-sugar foods, and beverage intake during childhood/adolescence; maternal breastfeeding; and vitamin D supplementation. Despite the notable associations, further research using more standardized and homogeneous methodologies is needed to strengthen these findings. PROSPERO registration number: CRD42022313235.
Collective effect of self-learning and social learning on language dynamics: a naming game approach in social networks
Authors: Wen Tao , Chen Yu-wang , Lambiotte Renaud
Published: December 2024

Linguistic rules form the cornerstone of human communication, enabling people to understand and interact with one another effectively. However, there are always irregular exceptions to regular rules, with one of the most notable being the past tense of verbs in English. In this work, a naming game approach is developed to investigate the collective effect of social behaviours on language dynamics, which encompasses social learning, self-learning with preference and forgetting due to memory constraints. Two features that pertain to individuals’ influential ability and affinity are introduced to assess an individual’s role of social influence and discount the information they communicate in the Bayesian inference-based social learning model. Our findings suggest that network heterogeneity and community structure significantly impact language dynamics, as evidenced in synthetic and real-world networks. Furthermore, self-learning significantly enhances the process of language regularization, while forgetting has a relatively minor impact. The results highlight the substantial influence of network structure and social behaviours on the transition of opinions, from consensus to polarization, demonstrating its importance in language dynamics. This work sheds new light on how individual learners adopt language rules through the lenses of complexity science and decision science, advancing our understanding of language dynamics.
Uncovering heterogeneous inter-community disease transmission from neutral allele frequency time series
Authors: Okada Takashi , Isacchini Giulio , Yu QinQin , Hallatschek Oskar
Published: December 2024

The COVID-19 pandemic has underscored the critical need for accurate epidemic forecasting to predict pathogen spread and evolution, anticipate healthcare challenges, and evaluate intervention strategies. The reliability of these forecasts hinges on detailed knowledge of disease transmission across different population segments, which may be inferred from within-community transmission rates via proxy data, such as contact surveys and mobility data. However, these approaches are indirect, making it difficult to accurately estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp up of genome sequencing surveillance during the pandemic can be leveraged todirectlyidentify transmission patterns between communities. Specifically, our approach uses a hidden Markov model to infer the fraction of infections a community imports from other communities based on how rapidly the allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the U.S., we uncover networks of inter-community disease transmission that, while broadly reflecting geographical relationships, also expose epidemiologically significant long-range interactions. We provide evidence that transmission between regions can substantially change between waves of variants of concern, both in magnitude and direction, and analyze how the inferred plasticity and heterogeneity in inter-community transmission impact evolutionary forecasts. Overall, our study high-lights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.
A Phylogeny-Based Approach to Discover Mutational Processes in Primates
Authors: Kitch James C. , Seplyarskiy Vladimir
Published: December 2024

The accumulation of germline mutations underpins population diversity and drives genetic evolution. Despite the availability of extensive phylogenetic data, the lack of suitable methodologies has hindered the comprehensive characterization of germline mutational processes across evolutionary trees. To address this, we develop a robust three-step methodology that extracts germline mutational processes from alignments of closely related species. First, we estimate regional, branch-specific trinucleotide mutational spectra from a multispecies alignment. Second, we extract mutational processes jointly across an evolutionary clade by analyzing mutation rate variation along the genome using Reciprocal Principal Components Analysis (RPCA). Finally we filter artifactual mutational signatures using DNA symmetry. Applying this method to five primate clades and a rodent outgroup clade revealed nine distinct mutational processes. Notably, five of these processes were consistently observed across all six groups. We identified underling biological mechanism for at least seven of the processes, highlighting phenomena such as biased gene conversion, bulky lesion resolution, and maternal mutagenesis. We validated identified processes using human and non-human polymorphism data. This study offers new insights into the biology and evolution of mutagenesis in primates and introduces a methodological toolkit to investigate mutational processes across phylogenies.
DORIAT:A Bayesian framework for interpreting and annotating docking runs
Authors: Maniatis Christos , Ouaray Zahra , Xiao Kai , Dixon Thomas P.E. , Snowden James , Teng Michelle , Hurst Jacob
Published: December 2024

The advent of sequence-to-structure deep-learning models have transformed protein engineering landscape by providing an accurate and cost effective way to determine crystal structures. Despite their accuracy, deep-learning predictions tend to give limited insights around protein dynamics. To improve conformation exploration we have developed a machine learning pipeline that combines deep-learning predictions with molecular docking. In this report, we proposeDockingRunIntepretation andAnnotationTool (DoRIAT). In contrast to frameworks that score models based on interface interactions, DoRIAT uses a set of parameters that summarize binding conformation. We use DoRIAT to score output from docking runs, identify complexes close to the native structure and create ensembles of models with similar binding conformations. Our results demonstrate that the single structural model DoRIAT selects to be the closest representation of the crystal structure lies within the top 10 of docked models, ranked by RMSD, in around 80% of cases.
A TROP2/Claudin Program Mediates Immune Exclusion to Impede Checkpoint Blockade in Breast Cancer
Authors: Wu Bogang , Thant Win , Bitman Elena , Liu Ting , Liu Jie , Paschalis Eleftherios I. , Xu Katherine H. , Nieman Linda T. , Ting David T. , Thimmiah Nayana , Sun Sheng , Abelman Rachel O. , Isakoff Steven J. , Spring Laura M. , Bardia Aditya , Ellisen Leif W.
Published: December 2024

Immune exclusion inhibits anti-tumor immunity and response to immunotherapy, but its mechanisms remain poorly defined. Here, we demonstrate that Trophoblast Cell-Surface Antigen 2 (TROP2), a key target of emerging anti-cancer Antibody Drug Conjugates (ADCs), controls barrier-mediated immune exclusion in Triple-Negative Breast Cancer (TNBC) through Claudin 7 association and tight junction regulation. TROP2 expression is inversely correlated with T cell infiltration and strongly associated with outcomes in TNBC. Loss-of-function and reconstitution experiments demonstrate TROP2 is sufficient to drive tumor progression in vivo in a CD8 T cell-dependent manner, while its loss deregulates expression and localization of multiple tight junction proteins, enabling T cell infiltration. Employing a humanized TROP2 syngeneic TNBC model, we show that TROP2 targeting via hRS7, the antibody component of Sacituzumab govitecan (SG), enhances the anti-PD1 response associated with improved T cell accessibility and effector function. Correspondingly, TROP2 expression is highly associated with lack of response to anti-PD1 therapy in human breast cancer. Thus, TROP2 controls an immune exclusion program that can be targeted to enhance immunotherapy response.

Synopsis

This study defines a new mechanism of barrier-mediated immune exclusion in cancer controlled by TROP2-dependent tight junctions. This mechanism drives tumor progression but can be targeted via TROP2-directed antibody drug conjugates to activate anti-tumor immunity and enhance immunotherapy response.
Alzheimer’s Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset
Authors: Leung Yuk Yee , Lee Wan-Ping , Kuzma Amanda B , Nicaretta Heather , Valladares Otto , Gangadharan Prabhakaran , Qu Liming , Zhao Yi , Ren Youli , Cheng Po-Liang , Kuksa Pavel P , Wang Hui , White Heather , Katanic Zivadin , Bass Lauren , Saravanan Naveen , Greenfest-Allen Emily , Kirsch Maureen , Cantwell Laura , Iqbal Taha , Wheeler Nicholas R , Farrell John J. , Zhu Congcong , Turner Shannon L , Gunasekaran Tamil I , Mena Pedro R , Jin Jimmy , Carter Luke ,   Alzheimer’s Disease Sequencing Project, Zhang Xiaoling , Vardarajan Badri N , Toga Arthur , Cuccaro Michael , Hohman Timothy J , Bush William S , Naj Adam C , Martin Eden , Dalgard Clifton , Kunkle Brian W , Farrer Lindsay A , Mayeux Richard P , Haines Jonathan L , Pericak-Vance Margaret A , Schellenberg Gerard D , Wang Li-San
Published: December 2024

The Alzheimer’s Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer’s Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer’s Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.
Where and how can WASH work? Understanding limited impacts from a randomized control trial of water, sanitation, and hygiene interventions in a high burden setting
Authors: Kraay Alicia N. M. , Brouwer Andrew F. , Zahid Mondal H. , Njenga Sammy , Colford John M. , Freeman Matthew C. , Eisenberg Joseph N.S.
Published: December 2024

Background

Despite their strong theoretical basis, water, sanitation, and hygiene (WASH) interventions have had inconsistent benefits on diarrhea in low- and middle-income settings. The WASH Benefits (WASH-B) Kenya randomized controlled trial evaluated a set of WASH interventions targeted at children under age 2 and found no effect on diarrheal prevalence.

Objectives

We explored whether and how changes to intervention and contextual factors could impact health gains as a means to inform future WASH interventions.

Methods

We implemented a compartmental transmission model with environmental pathways and water (W), sanitation (S), and hygiene (H) interventions fit to WASH-B Kenya trial data (n=11,856) using a Bayesian sampling approach. We developed counterfactual simulations to predict how a trial might perform given improved 1) local contextual factors (i.e., reduced transmission, and increased completeness of transmission pathways targeted) and/or 2) intervention factors (i.e., increased intervention efficacy, compliance, and community coverage). We considered change in intervention effectiveness in the counterfactual scenarios for each intervention alone and in combination (WSH). We determined what combinations would be needed to achieve 50% reduction in child diarrhea compared to the control arm.

Results

We found that high diarrheal prevalence in the WASH-B Kenya trial was likely the primary reason for ineffectiveness. While none of the tested counterfactual factors greatly impacted intervention effectiveness in isolation, we estimated that 50% reduction in child diarrhea in the combined WSH treatment arm could be achieved through a combination of substantial intervention improvements (i.e., 50% intervention efficacy, 100% compliance, and 60% community coverage), but could not be attained for the single intervention arms. With improvements to contextual factors (consistent, 7.5% diarrheal prevalence, 50% increase in completeness) coupled with more modest increases in intervention factors (i.e., 50% efficacy and 100% compliance but only 20% community coverage), could achieve a 50% reduction in diarrhea in the combined WSH arm.

Conclusions

In settings with high enteric pathogen prevalence, WASH interventions must be used by a substantial fraction the population and block all main transmission routes to achieve substantial reductions in diarrheal disease burden, including those over age 2. The WASH interventions and targeting strategy for the WASH-B Kenya trial were unlikely to appreciably reduce diarrheal disease because of the high burden. In settings with more modest transmission, there are intervention factor targets that could result in measurable reductions in diarrhea. Application of this simulation-based approach could inform WASH policies and programs, as well as the design of future trials.
Turncoat antibodies unmasked in a model of autoimmune demyelination: from biology to therapy
Authors: Taghipour-Mirakmahaleh Reza , Morin Françoise , Zhang Yu , Bourhoven Louis , Béland Louis-Charles , Zhou Qun , Jaworski Julie , Park Anna , Dominguez Juan Manuel , Corbeil Jacques , Flanagan Eoin P. , Marignier Romain , Larochelle Catherine , Kerfoot Steven , Vallières Luc
Published: December 2024

Autoantibodies contribute to many autoimmune diseases, yet there is no approved therapy to neutralize them selectively. A popular mouse model, experimental autoimmune encephalomyelitis (EAE), could serve to develop such a therapy, provided we can better understand the nature and importance of the autoantibodies involved. Here we report the discovery of autoantibody-secreting extrafollicular plasmablasts in EAE induced with specific myelin oligodendrocyte glycoprotein (MOG) antigens. Single-cell RNA sequencing reveals that these cells produce non-affinity-matured IgG antibodies. These include pathogenic antibodies competing for shared binding space on MOG’s extracellular domain. Interestingly, the synthetic anti-MOG antibody 8-18C5 can prevent the binding of pathogenic antibodies from either EAE mice or people with MOG antibody disease (MOGAD). Moreover, an 8-18C5 variant carrying the NNAS mutation, which inactivates its effector functions, can reduce EAE severity and promote functional recovery. In brief, this study provides not only a comprehensive characterization of the humoral response in EAE models, but also a proof of concept for a novel therapy to antagonize pathogenic anti-MOG antibodies.
Two Key Actinomycetota Taxa in the Human Gut Microbiota are Associated withSchistosoma mansoniInfection Burden
Authors: Appiah-Twum Francis , Okyere Lydia , Sumboh Jeffrey Gabriel , Osabutey Dickson , Ismail Rahmat Bint Yusif , Darko Hilda , Ashong Yvonne , Wilson Michael D. , Akorli Jewelna
Published: December 2024

In this study, we sought to identify key microbial taxa associated with human gut dysbiosis duringS. mansoniinfection and whether the changes are linked to the intensity of helminth infection. Stool samples were obtained from 20 persons infected with schistosomiasis and an equal number of uninfected persons from an endemic rural community in Ghana. Infection intensity was scored as egg count per gram (EPG) using the Kato-Katz method. Positive stool samples were further stratified as low-moderate (<400 EPG, n=15) and high (>400 EPG, n=5) infection burden. The composition and diversity of the gut microbiota and potential microbial markers associated withS. mansoniinfection intensity were determined from 16S rRNA amplicon sequence analyses. No difference in ß-diversity was observed between positives and negatives (PERMANOVA: R2= 0.012,p= 0.723), although there was an increased abundance ofBifidobacterium(p= 0.008) in infected stool samples compared to the negatives. Further analyses showed thatBifidobacterium(p= 0.003) andCollinsella(p= 0.029) were elevated considerably among the low-moderate infected samples, while the pathobiontEscherichia-Shigellawas reduced (p= 0.0078). Our findings show that intestinal schistosomiasis results in human gut microbiota dysbiosis, which is only distinguished when the intensity of infection is considered, with two keyActinomycetotaspecies assuming importance depending on the infection burden.

Author Summary

This study investigates the relationship between Schistosoma mansoni infections, a major cause of intestinal schistosomiasis, and the human gut microbiome. Using samples from an endemic region in Ghana, the research examines how infection intensity impacts gut bacteria. The findings reveal that certain beneficial bacteria, such as Bifidobacterium and Collinsella, become more abundant in cases of low to moderate infection, potentially maintaining immune regulation and gut health. However, these effects are not seen in high-infection instances, possibly due to the aggressive hallmarks of high-intensity helminth infections. Understanding these dynamics could be pivotal for developing microbiome-based interventions to improve treatment outcomes for schistosomiasis and similar parasitic infections. This study sheds light on the complex interplay between infectious parasites and gut microbes, emphasising the promise of microbiome research in enhancing public health efforts in areas where parasitic diseases persist.
Between-movie variability severely limits generalizability of “naturalistic” neuroimaging
Authors: Leipold Simon , Ravi Rao Rajat , Schoffelen Jan-Mathijs , Bögels Sara , Toni Ivan
Published: December 2024

“Naturalistic imaging” paradigms, where participants watch movies during fMRI, have gained popularity over the past two decades. Many movie-watching studies measure inter-subject correlation (ISC), which refers to the correlation between participants’ neural activation time series. Previous research has focused on explaining ISC differences during movie-watching based on individual states and traits, such as social distance, personality, and political orientation. For example, friends show higher ISC than strangers while watching movies.

However, movies are not natural categories but cultural artifacts that evoke varying levels of ISC depending on content, directing style, or editing methods. This raises questions about how much trait- or state-like differences in ISC depend on the specific movies chosen, potentially limiting the generalizability of findings across different movies.

Here, we used an fMRI dataset of 112 participants watching eight animated movies to (a) quantify between-movie variability in ISC across the brain and (b) assess the implications for the generalizability of trait- or state-like effects on ISC. We found substantial between-movie variability in ISC, with this variability differing across brain regions. Crucially, brain regions with the highest ISC exhibited the greatest variability, indicating that trait- or state-like differences in ISC from one movie may not generalize to others.

We conclude that variability between movies limits the generalizability of trait- or state-like ISC differences. Using a specific movie in neuroscience should be treated similarly to using a particular task, requiring a comparable characterization of the constituent cognitive elements. Broad generalizations about “naturalistic imaging” or “movie watching” are not warranted.
Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics
Authors: Martorell-Marugán Jordi , López-Domínguez Raúl , Villatoro-García Juan Antonio , Toro-Domínguez Daniel , Chierici Marco , Jurman Giuseppe , Carmona-Sáez Pedro
Published: December 2024

Recent advances in single-cell RNA-Seq (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phenotypes, such as diseases, at the level of individual cells. The analysis of the resulting data poses significant challenges due to their sparsity and large volume, and proper statistical methods are required to analyze and extract information from scRNA-Seq datasets. Sample classification based on gene expression data has proven effective and valuable for precision medicine applications. However, standard classification schemas are often not suitable for scRNA-Seq due to its unique characteristics, and new algorithms are required to effectively analyze and classify samples at the single-cell level. In this article, we introduce singleDeep, an end-to-end pipeline that streamlines the analysis of scRNA-Seq data training deep neural networks, enabling robust prediction and characterization of sample phenotypes. To validate the effectiveness of singleDeep, we applied it to make predictions on scRNA-Seq datasets from different conditions, including systemic lupus erythematosus and Alzheimer's disease. Our results demonstrate strong diagnostic performance, validated both internally and externally. Moreover, compared with traditional machine learning methods applied to pseudobulk data, singleDeep consistently outperformed these approaches. In addition to prediction accuracy, singleDeep provides valuable insights into cell types and gene importance estimation for phenotypic characterization. This functionality provided additional and valuable information in our use cases. For instance, we corroborated that some interferon signature genes are consistently relevant for autoimmunity across all immune cell types in lupus. On the other hand, we discovered that genes linked to dementia have relevant roles in specific brain cell populations, such as APOE in astrocytes.