bluuebunny/crossref_metadata_2025 huggingface dataset:
Safety and immunogenicity of four sequential doses of NVX-CoV2373 in adults and adolescents: a phase 3, randomized, placebo-controlled trial (PREVENT-19)
Authors: Añez Germán , McGarry Alice , Woo Wayne , Kotloff Karen L , Gay Cynthia L. , Zhu Mingzhu , Cloney-Clark Shane , Nelson Joy , Dunbar Haoua , Cai Mirand R , Cho Iksung , Cai Zhaohui , Kalkeri Raj , Plested Joyce S , Smith Katherine , Marchese Anthony M , Glenn Gregory M , Mallory Raburn M , Dunkle Lisa M
Published: November 2024

Background NVX-CoV2373, a recombinant SARS-CoV-2 spike (rS) protein vaccine with Matrix-M™ adjuvant, has been authorized for use in adults and adolescents. PREVENT-19 (NCT04611802/2019nCoV-301), a pivotal phase 3, randomized, placebo-controlled trial demonstrated robust efficacy of a primary, 2-dose series of NVX-CoV2373 against COVID-19. Methods Protocol expansions to PREVENT-19 included enrollment of adolescents (aged 12 to <18 years) and administration of 3rd and 4th doses of NVX-CoV2373 to adults and adolescents. Participants randomized 2:1 received NVX-CoV2373 or placebo 21 days apart; 3rd and 4th doses were administered ≥6 months after the preceding dose. Secondary and additional assessments included post-3rd- and 4th-dose immune responses (neutralizing antibody [nAb], anti-rS IgG, human angiotensin-converting enzyme-2-receptor binding inhibition [hACE2-RBI]) and response durability (post-3rd dose) to ancestral virus; cross-reactivity to Omicron subvariants; safety; and reactogenicity. Results Immune responses were observed against ancestral virus after two doses of NVX-CoV2373 but not after placebo. In both adults and adolescents, additional doses of NVX-CoV2373 increased nAb titers, anti-rS IgG levels, and hACE2-RBI; durable responses were recorded 8 months post 3rd dose. nAb responses post 3rd dose were noninferior to those post primary series. Cross-reactivity to BA.5 and BQ.1.1 variants was also observed, with anti-rS IgG levels post 3rd or 4th dose exceeding previously reported correlates of protection. Additional doses of NVX-CoV2373 were well tolerated, with no new safety signals. Conclusions NVX-CoV2373 elicited robust and durable humoral immune responses to ancestral SARS-CoV 2 as a 3rd and 4th dose after the primary series in adults and adolescents. Cross-reactivity to relevant variants provides insight into potential protection against antigenically related, but shifted, viral strains. Additional doses of NVX-CoV2373 were well tolerated with no new safety signals. These results support the utility of this vaccine platform and continued updates, based on currently circulating strains, to help effectively combat SARS-CoV-2 infection.
The Association of Long-Term Body Mass Index Variability with the Development of HFpEF and HFrEF Across Patterns of Weight Change
Authors: Yu Zeshui , Chen Yuqing , Miranda Oshin , Qi Meiyuzhen , Zhang Manling , Feng Ning , Ryan Timothy P , Schloot Nanette Cathrin , Chen Yu , Sam Flora , Wang Lirong
Published: November 2024

Background

Recent studies have shown BMI variability is risk factor for various adverse cardiovascular outcomes. However, the specific associations between BMI variability and the risk of developing HFpEF versus HFrEF, particularly across multiple weight change trends, remain unexplored.

Methods and Results

We identified a cohort of 52,286 eligible patients with overweight or obesity grouped into three categories based on their BMI change patterns over five years: weight loss, stable weight, and weight gain. BMI variability was assessed in the same 5-year period using average successive variability (ASV). These patients were subsequently followed to monitor the incidence of HFpEF and HFrEF. Cox regression models were applied to examine the differential association between BMI variability and HFpEF and HFrEF risk. Over a median follow-up of 4.81 years, 2,295 patients developed HFpEF, and 1,189 developed HFrEF. After adjusting for relevant confounders, elevated BMI variability was associated with an increased risk of HFpEF. The hazard ratios (HRs) of HFpEF for each 1-SD increment in ASV of BMI were 1.27 (95% CI, 1.10-1.47) in the weight loss group and 1.22 (95% CI, 1.09-1.37) in the stable weight group. Additionally, when analyzed as a binary variable divided by the median, BMI variability above the median was associated with higher risks of HFpEF compared to those below the median, with the corresponding HRs being 1.46 (95% CI, 1.20-1.77) for the weight loss group and 1.17 (95% CI, 1.04-1.31) for the stable weight group.

Conclusions

In this large cohort of patients living with overweight or obesity, greater BMI variability was significantly associated with a higher risk of developing HFpEF compared to patients with reduced and stable weight over time.

Clinical Perspective What’s new?

1. In patients with weight loss and stable weight, those with higher BMI variability have an increased risk of developing incident HFrEF compared to those experiencing lower BMI variability, after adjusting all potential confounding variables.

2. In patients with weight gain, BMI variability was not significantly linked to the risk of developing HFpEF or HFrEF. However, a larger increase in delta BMI was significantly associated with a higher risk of incident HFpEF and HFrEF in this group.

What are the clinical implications?

1. Promoting the importance of stable and consistent weight management strategies to reduce heart failure risk, particularly by minimizing BMI variability in patients undergoing weight loss or maintaining stable weight.
Late Quaternary millennial-scale stability of the feeding strategy of the gray brocket deer [Subulo gouazoubira(G. Fisher, 1814); Mammalia] in Southeastern Brazil
Authors: Hubbe Alex , Pestle William J. , Hubbe Mark , Amirali Avaaz , Chim Eliane Nunes , Oliveira Rodrigo Elias , Pinto Sandoval Eluzai Dinai , Duarte José Maurício Barbanti , Neves Walter A
Published: November 2024

There is limited evidence, both contemporary and archaeological/paleontological, regarding the feeding ecology of the gray brocket deer (Subulo gouazoubira) in Brazil’s Cerrado biome. Using stable carbon (δ13C) and oxygen (δ18O) isotope analyses of dental enamel bioapatite from individuals recovered from Cuvieri Cave, Minas Gerais, we explore dietary and environmental changes between the Late Pleistocene and Holocene epochs in this biome. The average Pleistocene δ13C was -10.9±1.7‰ and δ18Odwwas -7.9±0.4‰, while Holocene individuals averaged a δ13C of -10.5±1.2‰ and δ18Odwof -5.8±0.9‰. The δ13C data suggest no significant shift in feeding strategy between the Late Pleistocene and Holocene, with both sets of individuals displaying δ13C values consistent with browsing in environments other than closed canopy forests. However, δ18Odwvalues indicate an approximate temperature increase of 3.5°C between the two epochs and/or a reduction in precipitation. This study highlights the stability in the feeding behavior of the gray brocket deer despite biotic and abiotic changes between the epochs.
Integrative proteo-genomic profiling uncovers key biomarkers of lapatinib resistance in HER2-positive breast cancer
Authors: Steggall J , Rajeeve V , Al-Subaie N , Hayat A
Published: November 2024

Drug resistance is a major obstacle to the long-term effectiveness of cancer therapies. Approximately 70% of breast cancer patients relapse after 5 years of treatment, and the lack of biomarkers associated with drug resistance translates to poor prognosis in clinic. Previous research has utilised omics approaches to uncover biomarkers driving drug resistance, with a strong emphasis on genetic mutations. Here, we identified a nine-marker signature associated with resistance to lapatinib in a HER2-positive breast cancer model using a target discovery approach by employing an integrative multi-omics strategy, combining ATAC-seq, RNA-seq, and proteomics. We found that 7 markers in the drug resistance-signature had not been previously found to be implicated in HER2 positive breast cancer. We counterintuitively found that drug resistant cells have restrictive chromatin accessibility with reduced gene expression associated with limited total proteome changes. However, upon closer look, we identified that the drug resistance-signature had increased chromatin accessibility closer to the transcriptional start sites of those genes and are highly differentially expressed across the three datasets. Our data show that despite the overall transcriptional and proteomic landscape showing limited changes, there are several markers that are highly expressed, which correlate with increased anchorage-independent and invasive phenotypein vitroin lapatinib resistant cells compared to cancer cells. Our results demonstrate that disease aggressiveness can be related to reduced chromatin and gene expression dynamics. We anticipate that the resistant signature identified here using integrative target discovery approach can be applied to complex, representative models and validated before they can be targeted by suitable therapeutic agents.
Healthy B cells: allies or adversaries of CAR-T cell immunotherapy?
Authors: Paixão Emanuelle A. , Barros Luciana R. C. , Fassoni Artur C. , Almeida Regina C.
Published: November 2024

Chimeric antigen receptor (CAR)-T cell immunotherapy has achieved significant success against various haematological cancers, including B-cell malignancies. Its efficacy against B-cell cancers is influenced by the presence of healthy B-cells expressing the target antigen, and B-cell aplasia (BCA) serves as an indicator of successful therapy outcome. However, the precise influence of healthy B-cells on thein vivodynamics of CAR-T cells and their ultimate impact on therapy outcomes remain unclear. Here, we propose a mathematical model to describe CAR-T cell immunotherapy in B-cell cancer patients. Our model successfully captured the interactions between different CAR-T cell phenotypes, tumour cells, and healthy B cells in patients who achieved a complete response. Using these cases, we constructed virtual scenarios to investigate how variations in baseline tumour and healthy B-cell populations, along with patient-specific factors related to CAR-T cell expansion and B-cell influx from the bone marrow, affect treatment outcomes. Our results suggest that the onset and duration of BCA is a patient-specific feature that depends primarily on the continuous influx of newly generated B cells, their proliferative capacity, and the expansion and cytotoxicity of CAR-T cells.

Statement of significance

This study presents a significant advancement in understanding the dynamics of CAR-T cell immunotherapy in B-cell malignancies by introducing a mathematical model that captures the complex interactions between CAR-T cells, tumour cells, and healthy B cells. The model provides crucial insights into how patient-specific factors, such as baseline tumour burden, B-cell populations, and CAR-T cell expansion, influence treatment outcomes, including the onset and duration of B-cell aplasia (BCA), a key marker of therapeutic success. Healthy B cells can act as allies, adversaries, or have a neutral effect on the therapy, depending on the tumour burden. These findings highlight the importance of personalised approaches in CAR-T cell immunotherapy, offering potential pathways to optimise treatment strategies for improved efficacy and patient outcomes.
MAGE: Monte Carlo method for Aberrant Gene Expression
Authors: Beltran Matthew , Joh Richard I.
Published: November 2024

Identifying genes that are aberrantly expressed is an important first step in the diagnosis and treatment of many diseases. Conventionally, differential expression (DE) analysis is used to screen gene expression profiles to identify functionally associated genes. DE often relies on the variance and fold change in expression from individual genes, which does not consider the expression of all other genes within the profile. When the overall gene expression is skewed, DE does not capture outliers in gene expression. To address this, we have developed a non-parametric DE method based on the probability density for an entire expression profile to select genes that deviate from the global distribution between two gene expression profiles with multiple replicates. Rather than assuming a particular distribution of expression per gene, our method assumes that aberrantly expressed genes (AEGs) will exhibit expression patterns distinguishable from non-AGEs which make up the majority of the profile.

Here we introduce our nonparametric method (MAGE: Monte Carlo method for aberrant gene expression) and demonstrate that MAGE can identify AEGs that are not found by conventional DE analyses. The main feature of MAGE is (1) identifying outliers based on the expression profile of all genes rather than performing DE analyses on a per-gene basis and (2) consideration of the variance in expression between two different conditions. We also compared our results with traditional DE analysis as well as density-based clustering methods. MAGE produces consistent results in a variety of conditions and performs conservatively with the addition of noise. We also applied MAGE to single-cell RNA-seq samples and demonstrated that the analysis is robust with subsampling.
ScisTree2: An Improved Method for Large-scale Inference of Cell Lineage Trees and Genotype Calling from Noisy Single Cell Data
Authors: Zhang Haotian , Zhang Yiming , Gao Teng , Wu Yufeng
Published: November 2024

In a multicellular organism, cell lineages share a common evolutionary history, which has important applications in the study of development, aging, and cancer. Cell lineage tree is a model for the evolutionary history of cells sampled from an organism. The inference of cell lineage trees has been made possible by recent developments in single-cell sequencing. However, single-cell data is well known to be sparse and noisy. Moreover, the size of single cell data is increasing rapidly, both in the number of assayed cells and the amount of genomic information captured per cell. Thus, accurate inference of cell lineage tree from large single-cell data is a computational challenge. In this paper, we present ScisTree2, a fast and accurate cell lineage tree inference and genotype calling approach based on the infinite sites model. Similar to existing maximum likelihood-based inference approaches such as ScisTree, ScisTree2 relies on local search for finding optimal trees. Compared to the original ScisTree, the main new feature of ScisTree2 is a local search based on subtree prune and regraft (SPR) that is not implemented in the original ScisTree due to its high computational cost. This new local search is more general than that in ScisTree and significantly improves the accuracy of cell lineage tree inference. The key technical contributions of this work are the efficient SPR local search algorithms that can scale to very large data. ScisTree2 can call single cell genotypes based on the inferred cell lineage tree. Experiments on simulated and real biological data show that ScisTree2 achieves better overall accuracy while significantly outperforms in efficiency when compared with existing methods. To the best of our knowledge, ScisTree2 is the first model-based cell lineage tree inference and genotype calling approach that can infer trees with very large data with, e.g., tens of thousands of cells.
AI Assisted Native Proteomics: Delineating Ribosomal Protein Conformations Pre- and Post-Assembly
Authors: Zhang Wenjing , Sun Chen , Xu Zhang , Xu Wei
Published: November 2024

The simultaneous identification of proteins as well as their conformations in a biological system would greatly enhance our understanding of cellular mechanisms and disease. As an emerging technique, native proteomics analyzes proteins in their native states, facilitating the acquisition of protein stoichiometry, post-translational modifications (PTMs), and interactions with ligands. However, revealing protein conformations at the proteome scale remains a significant challenge. In this study, we propose an AI-assisted native proteomics method that integrates a protein structure prediction (PSP) module with top-down proteomics (TDP) and native mass spectrometry (nMS) to acquire both proteome identity and conformations. First, protein sequences and PTMs are obtained using the TDP method, while protein solvent-accessible surface area (SASA) is measured in parallel by nMS. These data are then input into the PSP module to acquire the most probable conformation of the protein under nMS experimental conditions. We validate the feasibility and accuracy of this method through the analysis of both a globular protein and an intrinsically disordered protein. Additionally, we apply this approach to delineate the conformations of ribosomal proteins pre- and post-assembly. Interactions of ribosomal proteins with drug molecules are also explored. By enabling proteome identification and conformation characterization from relatively small amounts of endogenous proteins, this method would bridge the gap between structural biology and conventional proteomics technologies.
Multi-source photographic evidence to assess corridor use, crop-raiding behaviour, and body injuries in Asian elephants
Authors: Anoop NR , Muneer PK , Madhavan M , Hatwar Anikethan , Ganesh T
Published: November 2024

This study investigated the use of multi-sourced photographs, such as those from social media, camera traps, and field surveys, for individual identification of male Asian elephants to study their corridor use, crop-raiding behaviour, occurrence of musth, ranging and external body injuries in the Thirunelli-Kudrakote elephant corridor in India’s Western Ghats. A total of 330 images and videos were analysed over 11 years (January 2014 to March 2024), leading to the identification of 27 male elephants from the corridor. Eleven individuals were observed across multiple years, demonstrating their fidelity to the area. Ten elephants were observed engaging in crop-raiding, with four consistently raiding crops within the corridor. The study also assessed the home range of 6 individuals in the corridor and adjacent landscapes based on individual identification. Overall, the study shows that identifying individual elephants across different locations and times provides valuable data and is a practical, cost-effective method for investigating a wide range of questions concerning the ecology and behaviour of Asian elephants. The findings underscore the potential of citizen science initiatives to enhance elephant research across elephant-range countries.
Dual Enzyme Inhibition Strategy for Type 2 Diabetes: Targeting LDH-A and α-Amylase with Flavonoid-Acarbose Combinations
Authors: Bose Adrija , Gupta Suvroma
Published: November 2024

Diabetes mellitus is a complex and widespread disease affecting over 100 million people globally. It increases the risk of severe complications such as heart attack, neuropathy, and retinopathy. While various therapies aim to manage the disease, one effective approach involves reducing the activity of starch-degrading enzymes, such as α-amylase, to limit the amount of free glucose in the body. Another target is lactate dehydrogenase-A (LDH-A), an enzyme involved in gluconeogenesis through its role in generating pyruvate.

In recent years, flavonoids have gained significant attention for their potential to inhibit both α-amylase and LDH-A. This study investigates the flavonoids present in green and black tea for their ability to inhibit porcine pancreatic amylase (PPA) and LDH-A, comparing their efficacy to established anti-diabetic drugs such as Acarbose and Metformin using computational methods.

In vitro experiments demonstrated that Quercetin shows potent anti-LDHA-A activity with an IC50of 4.161 µM. Quercetin inhibits PPA with an IC50value of 20 µM, while eriodyctiol and myricetin exhibit IC50values of 22 µM and 24 µM, respectively. Additionally, quercetin was found to synergistically enhance the inhibitory effects of the commonly used α-amylase inhibitor, Acarbose.
Integrative Modeling of the Spread of Serious Infectious Diseases and Corresponding Wastewater Dynamics
Authors: Schmid Nina , Bicker Julia , Hofmann Andreas F. , Wallrafen-Sam Karina , Kerkmann David , Wieser Andreas , Kühn Martin J. , Hasenauer Jan
Published: November 2024

The COVID-19 pandemic has emphasized the critical need for accurate disease modeling to inform public health interventions. Traditional reliance on confirmed infection data is often hindered by reporting delays and under-reporting, while widespread antigen and antibody testing can be costly and impractical. Wastewater-based surveillance offers a promising alternative by detecting viral concentrations from fecal shedding, potentially providing a more accurate estimate of true infection prevalence. However, challenges remain in optimizing sampling protocols, locations, and normalization strategies, particularly in accounting for environmental factors like precipitation.

We present an integrative model that simulates the spread of serious infectious diseases by linking detailed infection dynamics with wastewater processes through viral shedding curves. Through comprehensive simulations, we examine how virus characteristics, precipitation events, measurement protocols, and normalization strategies affect the relationship between infection dynamics and wastewater measurements. Our findings reveal a complex relationship between disease prevalence and corresponding wastewater concentrations, with key variability sources including upstream sampling locations, continuous rainfall, and rapid viral decay. Notably, we find that flow rate normalization can be unreliable when rainwater infiltrates sewer systems. Despite these challenges, our study demonstrates that wastewater-based surveillance data can serve as a leading indicator of disease prevalence, predicting outbreak peaks before they occur. The proposed integrative model can thus be used to optimize wastewater-based surveillance, enhancing its utility for public health monitoring.

Graphical Abstract

Highlights

Integration of infection and wastewater models to simulate disease spread.

Identification of factors affecting wastewater measurements.

Illustration of ability of wastewater-based surveillance to predict outbreaks before case reporting.

Demonstration of unreliability of flow rate normalization in case of rainwater infiltration.

Optimization of wastewater-based surveillance for improved public health monitoring.
Spatially mismatched cerebral blood flow and neuronal activity by intracortical microstimulation
Authors: Isis Yonza Alexandra Katherine , Tao Lechan , Kucharz Krzysztof , Lind Barbara , Zhang Xiao , Kim Kayeon , Cai Changsi
Published: November 2024

Intracortial microstimulation (ICMS) is widely used in brain-machine interface for neuroprosthetics, particularly with aims of restoring lost sensory and motor functions. However, it remains poorly understood whether neuronal and blood flow responses by ICMS are spatially and temporally matched, as well as their underlying mechanism. Neurovascular coupling (NVC) is the process by which neuronal activity regulates blood flow in the brain to meet local metabolic demands. A hypothetically suboptimal NVC by ICMS may exacerbate the neuronal survival near electrode, contributing to neurodegeneration. In this study, we used wide-field imaging, laser speckle imaging and two-photon imaging in transgenic mice expressing calcium fluorescent indicators in neurons or vascular mural cells to examine this hypothesis. Our results showed blood flow responses are delayed at peak time and prolonged in duration compared with neuronal responses. By varying the stimulation amplitudes, we found that low stimulation intensity lower than 50μA preserved NVC. In contrast, high intensity stimulation caused spatially mismatched NVC, i.e. in the adjacent range within 200∼400 μm from electrode tip, elicited blood flow compromises but neuronal activities increase. Ca2+is the key regulator of contractile tone of vascular mural cells. Our results showed that Ca2+sensitivity at vascular mural cells, i.e. vessel diameter change per unit of Ca2+change, was decreased in the adjacent region of electrode, which partially explained the compromised and mismatched NVC, and which likely further lead to ischemia and neurodegeneration. This study offers a new insight into ICMS-associated neuronal and vascular physiology, and provides an important implication towards optimal design of ICMS: low intensities is more neuroprotective than high intensities by preserving NVC and preventing ischemia. Our discoveries pave the way for new research consideration and contribute to the development of more advanced brain-machine interface.
Multi-omics Analysis Reveals Important Role for Microbial-derived Metabolites fromBotryllus schlosseriin Metal Interactions
Authors: Guillén Matus Dulce G. , Donaghy Caroline M. , Vijayan Nidhi , Lane Zachary T. , Howell Matthew , Glavin George G. , Angeles-Boza Alfredo M. , Nyholm Spencer V. , Balunas Marcy J.
Published: November 2024

Marine microbial communities govern many of the biological and chemical processes in the ocean, including element cycles, ecosystem health, and disease. Marine organisms are surrounded by microbes and complex molecular interactions occur between bacterial symbionts, eukaryotic hosts, and their pathogens or prey. Trace metals in the ocean can be either beneficial or detrimental to marine life depending on their concentrations and bioavailability. Multiple marine tunicate species are known to bioaccumulate trace metals in their mantel, and research suggests tunicate microbiota plays an important role in this process.Botryllus schlosseri, a marine colonial tunicate, has become a model organism for cellular and developmental studies, yet its ecological interactions are still not well understood. Using an integrated multidisciplinary approach, we established a comprehensive baseline and explored correlations between members of theB. schlosserimicrobiome, metabolome, and metallome to elucidate the ecological effects of trace metals in host-microbe-pathogen interactions. We identified significant correlations between metals, including manganese, nickel, cerium, zinc, and cobalt, with various metabolites and bacterial taxa. These findings offer insights intoB. schlosseribiological and chemical interactions with their symbionts and their environment, contributing to bridging the knowledge gap of host-microbiome-environment interactions and establishing a foundation for continuing research on the ecological effects of trace metals in these biological systems.

Highlights

Botryllus schlosseritissue was highly enriched in metals compared to seawater

B. schlosserimicrobiome ß-diversity significantly different from seawater

Pan-metabolome indicated microbial metabolites in core and flexible metabolome

Multi-omics revealed interactions between metals, metabolites, and microbes

Graphical Abstract
Free water elimination tractometry for aging brains
Authors: Chang Kelly , Burke Luke , LaPiana Nina , Howlett Bradley , Hunt David , Dezelar Margaret , Andre Jalal B. , Curl Patti , Ralston James D. , Rokem Ariel , MacDonald Christine L.
Published: November 2024

Tractometry of diffusion-weighted magnetic resonance imaging (dMRI) non-invasively quantifies tissue properties of brain connections. It is widely used in aging studies but could be less reliable in aging brains due to increased white matter free water. We demonstrate that computational free water elimination (FWE) increases reliability and accuracy of tractometry in a large (n = 339) cohort of older adults (66 – 103 y.o.). We found substantial (up to ∼37%) improvements in reliability in a split-half comparison at every stage of the pipeline: estimation of voxel-level fiber orientation distribution functions, delineation of major pathway trajectories, and assessment of tissue properties along the pathways. FWE also improves inferences from tractometry, producing more accurate cross-validated predictions of clinician Fazekas scores. By sub-sampling a multi-b-value dataset, we demonstrated that these findings generalize to both single-b-value data, which is important for many datasets where only one b-value may be available. Overall, the results highlight the importance of accounting for free water in tractometry studies, especially in aging brains. We provide opensource software for free-water elimination that can be applied to a wide range of clinical and research datasets (https://github.com/nrdg/fwe).
Architecture of a pentameric assembly of the tail tube protein in SPR phages
Authors: Zhu Hongtao , Wang Lin , He Yuhang , Zhu Kaixiang , Cui Sheng , Gao Xiaopan , Shang Kun
Published: November 2024

The majority of phages, viruses that infect prokaryotes, deliver their genomic material into host cells via a tail structure. Previous research has established that the central tube of these phages, composed of tail tube protein (TTP), is structurally conserved, typically forming either hexameric or trimeric rings. In this study, we revealed a novel pentameric assembly of TTP and present two cryo-EM structures at resolutions of 3.5 angstrom and 3.7 angstrom, respectively. Our detailed structural analysis demonstrates that the inner surface of the pentameric tube is highly negatively charged. Critical residues located on the loop between β3 and β4 play pivotal roles in the formation of the pentameric rings, and mismatches of the interactions between the stacked layers can induce the curvature of the tube. The cryo-EM structure of the TTP polymer at the tube's end uncovered that the β-strands that span amino acids 27-65 move towards the central tunnel, potentially blocking the tunnel through which the phage genome is released. Our study provides new structural insights into a novel assembly of TTP, which will extend the understanding of phage assembly.
Long-term serum spike protein persistence but no correlation with post-COVID syndrome
Authors: Fehrer Annick , Sotzny Franziska , Hoheisel Friederike , Stein Elisa , Kim Laura , Kedor Claudia , Freitag Helma , Heindrich Cornelia , Bauer Sandra , Rust Rebekka , Seifert Martina , Grabowski Patricia , Babel Nina , Scheibenbogen Carmen , Wittke Kirsten
Published: November 2024

According to the World Health Organization (WHO) and the Centers for Diseases Control and Prevention (CDC), currently an estimated 3 – 6 % of people suffer from post-COVID condition or syndrome (PCS). A subset meets diagnostic criteria for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Several studies have reported persistence of SARS-CoV-2 proteins or RNA in serum or tissues of both recovered individuals and PCS patients.

In this exploratory study, we investigated whether serum spike protein is associated with PCS and whether it correlates with symptom severity and laboratory biomarkers. We analyzed serum spike protein levels in 121 PCS patients following mild-to-moderate COVID-19, 72 of whom met diagnostic criteria for ME/CFS (post-COVID ME/CFS, pcMECFS). Pre-pandemic seronegative healthy controls (ppHC, n = 32) and post-COVID recovered healthy controls (pcHC, n = 37) after SARS-CoV-2 infection were also included in the study.

We found persistent serum SARS-CoV-2 spike protein in a subset of pcHC (11 %), PCS non-ME/CFS patients (2 %), and pcMECFS patients (14 %). There was no significant association with disease severity, symptoms, or laboratory markers. The spike protein concentration was independent of the time since last spike exposure (infection or vaccination). In five spike-positive out of a total of 22 patients who underwent immunoglobulin depletion via immunoadsorption (IA), spike protein was reduced or completely removed after treatment, indicating binding to immunoglobulins.

In summary, our study identified serum spike protein in a subset of patients after SARS-CoV-2 infection without evidence for a role in the pathogenesis of PCS.
Modelling complete dynamics of SARS-CoV-2 pandemics of Germany and its federal states using multiple levels of data
Authors: Kheifetz Yuri , Kirsten Holger , Schuppert Andreas , Scholz Markus
Published: November 2024

Epidemiological modelling is a key method of pandemic management including that of SARS-CoV-2. New insights into epidemiologic mechanics and new data resources require continuous adaptions of modelling approaches. We here present a revised and considerably extended version of our previous SARS-CoV- 2 model implemented as input-output non-linear dynamical systems (IO-NLDS). We now include integration of age-dependent contact patterns, immune waning, and new data resources such as seropositivity studies, hospital dynamics, variant dynamics, non-pharmaceutical intervention measures and dynamics of the vaccination campaigns.

With this modelling framework, we explain the dynamics of several data resources for the complete pandemics in Germany as well as its 16 federal states. The latter also allows us to investigate the heterogeneity of model parameters in Germany for the first time. To achieve this goal, we extend our estimation approach by constraining variation of parameters among the federal states. This allows reliable estimation of a few thousand parameters using hundreds of thousands of data points.

Our approach can be generalized to other epidemic situations or even other areas of application, thus, supporting general pandemic preparedness.
Beyond Letters: Optimal Transport as a Model for Sub-Letter Orthographic Processing
Authors: Taylor Jack E. , Sinn Rasmus , Iaia Cosimo , Fiebach Christian J.
Published: November 2024

Letter processing plays a key role in visual word recognition. However, word recognition models typically overlook or greatly simplify early perceptual processes of letter recognition. We suggest that optimal transport theory may provide a computational framework for describing letter shape processing. We use representational similarity analysis to show that optimal transport cost (Wasserstein distance) between pairs of letters aligns with neural activity elicited by visually presented letters <225 ms after stimulus onset, outperforming an existing approach based on shape overlap. We additionally show that optimal transport can capture the emergence of geometric invariances (e.g., to position or size) observed in letter perception. Finally, we demonstrate that Wasserstein distance predicts neural activity similarly well to features from artificial networks trained to classify images and letters. However, whereas representations in artificial neural networks emerge in a computationally unconstrained manner, our proposal provides a computationally explicit route to modeling the earliest orthographic processes.
Young adults’ pathway to digital entrepreneurship: from ideas to innovation
Authors: Çela Arjona , Mansi Egla , Morina Fatbardha
Published: November 2024

Purpose

This study aims to investigate the digital entrepreneurial intentions of Albanian youth, identify the obstacles they face in starting digital businesses and examine their preferences regarding the types of businesses they aspire to establish. The Theory of Planned Behavior (TPB) is used as a framework to analyze these factors.

Design/methodology/approach

Primary data were collected via questionnaires distributed in public and private universities. In a sample of 325 students, Structural Equation Modeling with Confirmatory Factor Analysis, path analysis and machine learning-based text analysis were used.

Findings

This study reveals significant impacts of innovativeness, attitude towards entrepreneurship, subjective norms, perceived behavioral control and self-efficacy on digital entrepreneurial intentions among Albanian students. Additionally, text mining highlights a strong preference for digital entrepreneurship.

Research limitations/implications

The theoretical contributions of this study include applying Structural Equation Modeling to reveal insights into the impact of entrepreneurial factors and obstacles. The findings can inform policymakers and educators in designing targeted interventions to support student entrepreneurship. Meanwhile, the limitations of this study encompass a small sample size, lack of time series and panel data and the absence of an evaluation of the impact of education system practices, along with the need to investigate the effects of young population emigration from Albania to the EU.

Originality/value

This research contributes to the understanding of digital entrepreneurial intentions and behavior by using TPB in the Albanian context, offering access to a diverse dataset from Albanian universities, testing the direct impact of innovativeness on entrepreneurial behavior and pioneering the use of machine learning techniques for text analysis. Thus, it provides novel insights into the entrepreneurial landscape in Albania. In addition, this work can drive initiatives to support student entrepreneurship and bridge the gap between academia and industry in Albania.
Technological intensity and innovation capability: evidence from an emerging country
Authors: Tello-Gamarra Jorge , Mayorga Gutierrez David Jesus , Hernani-Merino Martin , Zevallos Julio
Published: November 2024

Purpose

In general, it is believed that firms belonging to the high technological intensity stratum have a more innovation capability. However, evidence has begun to appear in the literature demonstrating that firms in the low-tech stratum also have the innovation capability. This paper seeks to solve this dilemma. Through an analysis of industrial firms in an emerging country, this study aims to identify the existence of innovation capability in all strata of technological intensity.

Design/methodology/approach

The authors empirically assessed the impact of innovation capability on the performance of firms in all strata of technological intensity. The authors studied a sample of 910 firms from different industries and technology intensities operating in Peru, by applying a partial least squares structural equation model (PLS-SEM).

Findings

This study obtained three important findings. First, the authors show that innovation capability is present in all strata of technological intensity. Second, innovation capability differs according to the technological stratum. Third, firms in the lowest technological stratum can use more capabilities than those in the other strata.

Originality/value

This study pioneers the empirical analysis of innovation capability and technological intensity simultaneously to verify that innovation capability exists in the four strata of technological intensity.
An aftercare intervention programme for employees returning from substance use rehabilitation in South Africa
Authors: Braaf Eldene , Roman Nicolette
Published: November 2024

Purpose

Employee assistance programmes (EAPs) and wellness practitioners (WPs) are the first line of support for employees returning from substance use rehabilitation. However, many workplaces need more guidance and support provisions to address these needs effectively. The purpose of this paper is to present a 10-week aftercare intervention programme that EAPs and WPs can use to support employees returning to work after a period of substance use rehabilitation.

Design/methodology/approach

The qualitative methodological approach involved two distinct stages of data collection and consensus search activities. Stage 1 involved three data collection activities with three stakeholder groups, and Stage 2 consisted of two consensus-seeking engagements with the intended audience of the intervention programme.

Findings

Participants in the consensus-seeking activities endorsed the inclusion of content in the proposed intervention programme and structural and organisational arrangements. Specific recommendations were made, namely, increased reliance on faith-based and spiritual support, the need to include community support structures and ensuring that workplace interventions include counselling, skills training and motivational speakers.

Practical implications

Those working in the EAP environment are offered a systematic and holistic plan for managing and supporting employees recovering from substance abuse disorders (SUDs) to maintain their recovery and return to productive work.

Originality/value

Implementing the intervention programmes can reduce the ad hoc nature of current approaches to workplace aftercare. The WPs are placed in a central role while stressing the valuable input of other key role players within the workplace or part of the family and community networks of the employee.
Understanding community perspective on the heritage of locality: memory map methodology
Authors: Zaleckis Kestutis , Vitkuviene Jurga , Jankauskaite-Jureviciene Laura , Grazuleviciute-Vileniske Indre , Karvelyte-Balbieriene Vilma
Published: November 2024

Purpose

Community involvement in heritage preservation requires appropriate approaches. Sanciai (in Lithuanian: Šanciai) historic district in Kaunas (Lithuania) has long-lasting military and industrial heritage, valuable urban structure and connections to the natural frame of the city. Sanciai residents’ willingness to participate in heritage preservation and urban planning prompted the aim of this research – to develop, test and present the mapping methodology, that would be applicable in the process of community involvement into heritage identification, preservation, interpretation and creation process.

Design/methodology/approach

The methods of research included analysis of literature and theoretical research, development and testing of the methodology for the community involvement in heritage identification, preservation, interpretation and creation process. The workshop methodology and interactive online map are presented in this research. The memory map methodology developed and presented in this research includes the elements of mental mapping, design thinking and citizen science.

Findings

The methodology was tested in spring of 2021 in two-day online workshops with the students of pro-gymnasium located in Sanciai. Workshop participants together with workshop coordinator and moderators created different layers of the mental map, collected stories from the members of community and gathered the data for online interactive Sanciai memory map. The evaluation of the methodology and workshop results allowed concluding that memory map methodology is a functioning participant, community and research-oriented approach that can be applied in diverse heritage and community related circumstances.

Originality/value

The originality of the research is determined by the synergistic nature of developed memory map methodology which complements traditional mental mapping with creative hands-on techniques, empathy-oriented tasks and interactive online tool. Moreover, the research reveals the importance of local-global connections in urban studies as active local community became the stimulus for memory map methodology. The two-fold aim of the methodology – community cohesion and empowerment as well as research data collection – contributes to the originality of the research as well.
Integrating servitisation into the halal supply chain: a roadmap for sustainable business growth
Authors: Hassan Ibrahim Saleh , Fernando Yudi
Published: November 2024

Purpose

The limited existing literature on the future research direction regarding how servitisation and the halal supply chain interact motivates this study. The paper aims to integrate servitisation into the halal supply chain by proposing an integration roadmap for successful adoption in the halal industry.

Design/methodology/approach

The study used the preferred reporting items for systematic reviews and meta-analyses method. Initially, 1,830 documents from Scopus and Web of Science were reviewed. After screening and refining, 1,241 documents remained. The authors then assessed these in full text, narrowing it down to 61 papers for the study.

Findings

The study discovered that the literature concerning servitisation and halal supply chains lacks essential conceptualisation, presenting an opportunity for exploration within the halal industry. Furthermore, it revealed that integrating servitisation into the halal supply chain can foster sustainable business growth and enhance customer satisfaction. Additionally, the study indicated that the interaction between servitisation and the halal supply chain may impact customers’ purchasing decisions and improve profit generation performance.

Practical implications

The study confirmed that integrating servitisation into the halal supply chain is crucial. The proposed roadmap aims to enhance the firm’s service delivery performance and impact customer purchasing behaviour through increased brand loyalty. In terms of industrial implications, the study offers guidance for industries transitioning to servitisation. The integration of servitisation in the halal supply chain can enhance efficiency and the ability to provide halal products that align with customer preferences and requirements.

Originality/value

This study suggests integrating servitisation into halal supply chains and provides a roadmap for exploring future research directions towards sustainable business growth. It not only offers thematic research direction but also practical insights. The roadmap can guide future research and development, enhancing business efficiency and customer experiences. This study reveals the potential of servitisation in halal supply chains and encourages further research on their interaction.
Revealing consumers’ hedonic buying in social media: the roles of social status recognition, perceived value, immersive engagement and gamified incentives
Authors: Shao Zhucheng
Published: November 2024

Purpose

This study aims to explore how social status recognition, perceived value and immersive enjoyment drive attachment to influencers and endorsements, thus triggering consumers’ hedonic buying towards influencer endorsements in social media.

Design/methodology/approach

By following a purposive sampling strategy and collecting cross-sectional data from 379 valid responses in the UK, this study adopts structural equation modelling, artificial neural networks and fuzzy set qualitative comparative analysis (SEM-ANN-fsQCA) as integrated methods for analysis.

Findings

This study reveals that social status recognition, immersive enjoyment, gamified incentives, attachment to influencers and endorsements are critical antecedents that drive hedonic buying.

Originality/value

In knowledge, this study concurrently adopts the perceived value theory and attachment theory that can enrich the inner elements and reveal the underlying connections under the theories. In method, the integrated analytical approach can explore deeper and more convincing results without the limitations of a single approach. In practice, this study helps practitioners ascertain customer perceptions of influencer endorsements and their attachment in the context of buying hedonically, thus developing effective strategies for employing influencers and marketing strategies to foster consumers’ hedonic buying behaviours.