bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of Arctic environments on human cerebral blood flow
Authors: Liu Feifeng , Zheng Tianheng , Chen Jian , Liang Huazheng , Li Gang , Hao Junjie
Published: March 2024

Background

The Arctic environment represents an extreme living condition that has significant impact on life. But research on alterations of human cerebral blood flow (CBF) in a high-latitude and low-temperature environment in the Arctic is still lacking.

Methods

Members of the 12th Chinese National Arctic Research Expedition team who took the icebreaker R/VXuelong2 to the Arctic were recruited. Transcranial colour doppler (TCD) examination was performed at the beginning of the voyage (lower latitude and higher temperature, LLHT) and during the Arctic scientific expedition period (higher latitude and lower temperature, HLLT) respectively. The spectral pattern and parameters of cerebral arteries were compared.

Results

Among 16 healthy individuals, 13 completed the TCD examination twice. They had a significantly lower mean velocity (Vm) (63.5 cm/s HLLT vs. 68.4cm/s LLHT;P=0.028) and peak systolic velocity (PSV) (94.6cm/s HLLT vs. 107.0cm/s LLHT;P=0.038) of the left middle cerebral artery (LMCA) and higher pulsatility index (PI) of the right middle cerebral artery (RMCA) (0.83 HLLT vs. 077 LLHT;P=0.011) in the HLLT environment compared to the LLHT one.

Conclusions

Changes in human CBF may occur in higher-latitude and lower-temperature environments in the Arctic.
COVID-19-associated acute renal failure in critically ill patients correlates with microthrombosis and renal loss of thrombomodulin
Authors: Koskinen Matilda , Englund Elisabet , Korkut Gül Gizem , Schwarz Angelina , Jeansson Marie
Published: March 2024

Critically ill COVID-19 patients have a high degree of acute kidney injury which develops in up to 85% of patients. We have previously shown that circulating levels of angiopoietin-2 increased in critically ill COVID-19 patients correlated to kidney injury, coagulopathy, and mortality. Furthermore, our experiments showed a causal effect on coagulopathy from angiopoietin-2 binding and inhibition of thrombomodulin mediated anticoagulation. In the current study we hypothesize that renal microthrombi may be a mechanism for reduced renal function in critically ill COVID-19 patients, and that local dysregulation of thrombomodulin and angiopoietin-2 may be involved.

To investigate our hypothesis, we utilized postmortem kidney tissue from seven COVID-19 patients treated at the intensive care unit. We evaluated kidney function, thrombosis, tubular injury, fibrosis, glomerulosclerosis, glomerular size as well as renal expression of thrombomodulin and angiopoietin-2. Proximity ligation assay was utilized to evaluate the presence of angiopoietin-2 binding to thrombomodulin. Normal kidney tissue came from the healthy part of six nephrectomies due to cancer.

Our experiments show renal thrombosis in 6/7 COVID-19 patients, on average 14.7 (6.9-22.5) thrombi per mm2. Most COVID-19 kidneys had extensive kidney injury, especially tubular necrosis, but also glomerular enlargement, glomerulosclerosis, and tubulointerstitial fibrosis which in some cases most likely resulted from underlying disease. Thrombomodulin expression was reduced in glomeruli and peritubular capillaries in kidneys from COVID-19 patients, whereas no change was found for angiopoietin-2.

In summary, our study describes a high degree of acute renal failure, renal microthrombosis, and loss of thrombomodulin in postmortem tissue from critically ill COVID-19 patients.
The Impact of Cognitive Function on Health-Related Quality of Life in Persons with Post-COVID-19 Condition: A Randomized Controlled Trial on Vortioxetine
Authors: Kwan Angela T.H. , Lakhani Moiz , Le Gia Han , Singh Gurkaran , Teopiz Kayla M. , Guo Ziji , Manku Arshpreet Singh , Rosenblat Joshua D. , McIntyre Roger S.
Published: March 2024

Background

Post-Covid-19 Condition (PCC) manifests in persistent, debilitating symptoms that affect multiple cognitive domains. These symptoms can negatively impact an affected individual’s health-related quality of life (HRQoL). Herein, we investigate the effects of cognitive function on HRQoL in persons with PCC. Secondarily, we determine whether vortioxetine modulates cognitive function on HRQoL.

Methods

Participants aged 18-65 years were randomized to receive vortioxetine or placebo for 8 weeks. HRQoL was measured using the World Health organization Wellbeing Scale 5-item, cognition was measured using the Digit Symbol Substitution Test and the Trail-Making Test A/B. Generalized estimating equations were used to model the relationship of cognition to HRQoL for each treatment group.

Results

147 participants, 75.5% of which were female, were included in the analysis. At baseline, there was a statistically significant positive association between WHO-5 scores and combined DSST z-scores (β = 0.090, 95% CI [0.051, 0.129],p< 0.001), and a statistically significant negative association with TMT-A (β = −0.007, 95% CI [-0.011, −0.003],p< 0.001) and -B (β = −0.002, 95% CI [-0.003, 0.000],p= 0.024) scores, respectively. A significant treatment, time, and combined DSST z-score interaction on changes in overall WHO-5 total score (χ2= 15.481,p= 0.004) was reported. After adjusting for the type of cognitive test, there was a significant between-group difference (mean change = 1.77, SEM = 0.868,p= 0.042) favoring vortioxetine.

Conclusion

Cognitive function is significantly associated with HRQoL in persons with PCC where enhanced cognitive functioning is associated with a better HRQoL. Vortioxetine is effective in improving HRQoL through enhancing cognitive function. Cognitive function in persons with PCC provides the impetus for future therapeutic targets for persons with PCC. Future studies should aim to investigate pro-cognitive therapeutic strategies.
Developing a deep learning model to predict the breast implant texture types with ultrasonography image: feasibility study
Authors: Kim Ho Heon , Jeong Won Chan , Pi Kyungran , Lee Angela Soeun , Kim Min Soo , Kim Hye Jin , Kim Jae Hong
Published: March 2024

Introduction Breast implants, including textured variants, have been widely used in aesthetic and reconstructive mammoplasty. However, the textured type, which is one of the shell types of breast implants, has been identified as a possible carcinogenic factor for lymphoma, specifically breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Identifying the texture type of the implant is critical to the diagnosis of BIA-ALCL. However, distinguishing the shell type can be difficult due to human memory or loss of medical history. An alternative approach is to use ultrasonography, but this method also has limitations in quantitative assessment. Objective The objective of this study is to determine the feasibility of using a deep learning model to classify the textured shell type of breast implants and make robust predictions from ultrasonography images from heterogeneous sources. Methods A total of 19,502 breast implant images were retrospectively collected from heterogeneous sources, including images from both Canon (D1) and GE (D2), images of ruptured implants (D3), and images without implants (D4), as well as publicly available images (D5). The Canon (D1) images were trained using Resnet-50. The performance of the model on D1 was evaluated using stratified 5-fold cross-validation. Additionally, external validation was conducted using D2 and D5. The AUROC and PRAUC were calculated based on the contribution of the pixels with Grad-CAM. To identify the significant pixels for classification, we masked the pixels that contributed less than 10%, up to a maximum of 100%. To assess model robustness to uncertainty, Shannon entropy was calculated for four image groups: Canon (D1), GE (D2), ruptured implant (D3), and without implants (D5). Results The deep learning model achieved an average AUROC of 0.98 and a PRAUC of 0.88 in the Canon dataset (D1). For images captured with GE (D2), the model achieved an AUROC of 0.985 and a PRAUC of 0.748. Additionally, the model predicted an AUROC of 0.909 and a PRAUC of 0.958 for a dataset available online. For quantitative validation, this model maintained PRAUC up to 90% masking of less contributing pixels, and the remnant pixels located in breast shell layers. Furthermore, the prediction uncertainty increased in the following order: Canon (D1), GE (D2), ruptured implant (D3), no implant (D5) (0.066; 0072; 0.371; 0.777, respectively). Conclusion We have demonstrated the feasibility of using deep learning to predict the shell types of breast implants. With this approach, the textured shell types of breast implants can be quantified, supporting the first step in the diagnosis of BIA-ALCL.
Precision and efficacy of RNA-guided DNA integration in high-expressing muscle loci
Authors: Padmaswari Made Harumi , Bulliard Gabrielle N , Agrawal Shilpi , Jia Mary S , Nelson Christopher E
Published: March 2024

Gene replacement therapies in genetic medicine primarily rely on adeno-associated viral (AAV) vectors for transgene expression. However, episomal expression can decline over time due to epigenetic silencing. CRISPR-based integration methods offer promise for long-term transgene insertion. While the development of transgene integration methods has made substantial progress, identifying optimal insertion loci remains challenging. Skeletal muscle is a promising tissue for gene replacement owing to the ease of access, relative proportion of body mass, the multinucleated nature of muscle, and the potential for reduced adverse effects. Leveraging endogenous promoters in skeletal muscle, we evaluated two high-expressing loci using homology-independent targeted integration (HITI) to integrate reporter or therapeutic genes in mouse myoblasts. We hijacked the muscle creatine kinase (Ckm) and myoglobin (Mb) promoters by co-delivering CRISPR-Cas9 and a donor plasmid with promoterless constructs encoding green fluorescent protein (GFP) or human Factor IX (hFIX). Additionally, we deeply profiled our genome and transcriptome outcomes from targeted integration and evaluated the safety of the proposed sites. This study introduces a proof-of-concept technology for achieving high-level therapeutic gene expression in skeletal muscle, with potential applications in targeted integration-based medicine and synthetic biology.
Genomic insights on the potential role of the accessory genome in the emergence of a novel geographically restrictedK. pneumoniaelineage as a high-risk clone
Authors: Bighi Nathália , Freitas Fernanda , Morgado Sérgio , Cipriano Rosângela , Vicente Ana Carolina , Fonseca Érica L.
Published: March 2024

Klebsiella pneumoniaecauses life-threatening nosocomial infections and is featured by a remarkable propensity for multidrug resistance acquisition. Infections caused by multidrug- (MDR) and extensively drug-resistant (XDR) strains lead to a limitation of therapeutic options and an increase in persistent infections, and they are usually represented by high-risk lineages. Based on these features and their relevance to global public health, most of the studies focused on such high-risk clones, and little is known about the epidemiological and evolutionary dynamics of new/geographically restricted lineages. This study aimed to unveil the antimicrobial resistance and virulence genetic repertoire of a clinical XDRK. pneumoniae(Kp199) strain belonging to geographically-restricted ST, not linked to any known clonal complex. Its intrinsic (gyrA, parC, ramR, soxRandsoxSmutations) and acquired resistome agreed with the observed XDR phenotype. An extensive arsenal of both antibiotic and heavy metal resistance genes was observed, as well as genes involved with resistance to several antiseptics currently used in clinical settings. The co-occurrence ofblaKPC-2andblaNDM-1carbapenemase genes in Kp199 was an alarming finding since it could contribute to increased carbapenem resistance. Kp199 virulome was associated with bacterial survival and replication during infections. This study raises concern about a novel, geographically restrictedK. pneumoniaelineage harbouring a huge resistome and virulome, which may strongly contribute to its successful establishment as an epidemic lineage. Therefore, our findings underscore the importance of vigilant surveillance and control measures to mitigate the threat posed by the potential emergence of new high-risk pandemic clones.
Enhancing the Robustness of OPLS Modelling in Small Cohorts by Leveraging Permutation Analysis Prior to Variable Selection
Authors: Ström Marika , Wagner Nicole , Kolosenko Iryna , Wheelock Åsa M.
Published: March 2024

The R-workflow ropls-ViPerSNet (R orthogonalprojections oflatentstructures withVariablePermutationSelection and ElasticNet) facilitates variable selection, model optimization and significance testing using permutations of OPLS-DA models, with the scaled loadings (p[corr]) as the main metric of significance cutoff. Permutations including (over) the variable selection procedure, prior to (pre-), as well as post variable selection are performed. The resulting p-values for the correlation of the model (R2) and the cross-validated correlation of the model (Q2) pre-, post- and over-variable selection are provided as additional model statistics. These model statistics are useful for determining the true significance level of OPLS models, which otherwise have proven difficult to assess particularly for small sample sizes. Furthermore, a means for estimating the background noise level based on permuted false positive rates of R2and Q2is proposed. This novel metric is then used to calculate an adjusted Q2value. Using a publicly available metabolomics dataset, the advantage of performing permutations over variable selection was demonstrated for small sample sizes. Iteratively reducing the sample sizes resulted in overinflated models with increasing R2and Q2and permutations post variable selection indicated falsely significant models. In contrast, the adjusted Q2was marginally affected by sample size, and represents a robust estimate of model predictability, and permutations over variable selection showed true significance of the models. An additional Elastic Net variable selection option is included in the workflow for variable selection by coefficient value penalization using an iterative approach to reduce noise while avoiding overfitting.
Investigating the interactions of the cucumber mosaic virus 2b protein with the viral 1a replicase component and the cellular RNA silencing factor Argonaute 1
Authors: Crawshaw Sam , Murphy Alex M. , Rowling Pamela J. E. , Nietlispach Daniel , Itzhaki Laura S. , Carr John P.
Published: March 2024

The cucumber mosaic virus (CMV) 2b protein is a suppressor of plant defenses and a pathogenicity determinant. Amongst the 2b protein’s host targets is the RNA silencing factor Argonaute 1 (AGO1), which it binds to and inhibits. InArabidopsis thaliana, if 2b-induced inhibition of AGO1 is too efficient it induces reinforcement of antiviral silencing by AGO2, and triggers increased resistance against aphids, CMV’s insect vectors. These effects would be deleterious to CMV replication and transmission, respectively, but are moderated by the CMV 1a protein by sequestering sufficient 2b protein molecules into P-bodies to prevent excessive inhibition of AGO1. Mutant 2b protein variants were generated and red and green fluorescent protein fusions used to investigate subcellular colocalization with AGO1 and the 1a protein, and the effects of mutations on complex formation with the 1a protein and AGO1 were investigated using bimolecular fluorescence complementation and co-immunoprecipitation assays. Although we found that residues 56-60 influenced the 2b protein’s interactions with the 1a protein and AGO1, it appears unlikely that any single residue or sequence domain is solely responsible.In silicopredictions of intrinsic disorder within the 2b protein secondary structure were supported by circular dichroism (CD) but not by nuclear magnetic resonance (NMR) spectroscopy. Intrinsic disorder provides a plausible model to explain the 2b protein’s ability to interact with AGO1, the 1a protein and other factors. However, the reasons for the conflicting conclusions provided by CD and NMR must first be resolved.
Increased ‘selfness’ in the tumor emerges as a possible immune sculpting mechanism: A pan-cancer data analysis of 32 solid tumors in TCGA
Authors: Sakthivel Naren Chandran , Chinmayi Anoushka , Chandra Nagasuma
Published: March 2024

Tumors pose a unique challenge to the immune system since they straddle the boundary between ‘self’ and ‘non-self’. T-cells recognize tumors that contain ‘non-self’ neo-antigens. They can also recognize tumors that contain aberrantly expressed self-antigens, highlighting the importance of the central tolerance and the tuning of the T-cell repertoire in the thymus. Therefore, the similarity to the thymic expression profiles must have information in it to influence the T-cell repertoire and what self-peptides are recognized. We utilize this principle in a pan-cancer analysis and develop a thymus-like or ‘selfness’ score (TLS) based on the gene-expression similarity to thymi, indicative of recognizability of tumors by T-cells. We show that the TLS is indicative of patient survival in 8 different TCGA cohorts, indicating gene expression modulation to mimic that in thymi as a potential immune sculpting mechanism. Surprisingly, we also see an inverse relationship between TLS and the degree of immune infiltration.
New specimens ofBunaia woodwardi, Clarke 1919 (Euchelicerata): A new member of Offacolidae providing insight supporting the Arachnomorpha
Authors: Lustri Lorenzo , Antcliffe Jonathan B. , Gueriau Pierre , Daley Allison C.
Published: March 2024

The rapid early diversification of arthropods has made understanding internal relationships within the group fiendish. Particularly unresolved is the origin of Euchelicerata, a clade consisting of the Prosomapoda (comprising the extant Xiphosura and Arachnida and the extinct Chasmataspidida, Eurypterida and synziphosurines) and the extinct Offacolidae. Here we describe new material of the Silurian ‘synziphosurine’Bunaia woodwardithat reveals previously unknown features of its ventral anatomy: a pair of elongated chelicerae in the prosoma, followed posteriorly by five pairs of biramous appendages, a first pre-abdomen somite bearing a pair of paddle-like uniramous appendages (exopods), and a ventral pretelsonic process. Phylogenetic analyses retrieveB. woodwardias an Offacolidae closely related toSetapedites abundantisfrom the early Ordovician Fezouata Biota. An anatomical comparison of the pretelsonic process ofB. woodwardi, also present inSetapedites, with the posterior trunk morphologies of other Offacolidae, Habeliida and Vicissicaudata, suggests a possible homologous appendicular origin. This proposed apomorphic character supports a monophyletic Arachnomorpha, formed of Vicissicaudata, Habeliida and Euchelicerata. The establishment of this new homology could help to clarify the highly enigmatic phylogeny at the base of the euchelicerates as well as the sequence of character acquisition during their early evolution.
A Novel Tool for Multi-Omics Network Integration and Visualization: A Study of Glioma Heterogeneity
Authors: Coletti Roberta , Carrilho João , Martins Eduarda P. , Gonçalves Céline S. , Costa Bruno M. , Lopes Marta B.
Published: March 2024

Gliomas are highly heterogeneous tumors with generally poor prognoses. Leveraging multi-omics data and network analysis holds great promise in uncovering crucial signatures and molecular relationships that elucidate glioma heterogeneity. However, the complexity of the problem and the high dimensionality of the data increase the challenges of integrating information across various biological levels. In this study, we developed a framework comprising two steps for variable selection based on sparse network estimation from various omics. Subsequently, we introduced MINGLE (Multi-omics Integrated Network for GraphicaL Exploration), a novel methodology designed to merge distinct multi-omics information into a single network, enabling the identification of underlying relations through an innovative integrated visualization. Applying this method to glioma data, with patients grouped according to the newest glioma classification guidelines, led to the selection of variables as potential candidates for novel glioma-type-specific biomarkers.
A molecularly engineered lectin destroys EGFR and inhibits the growth of non-small cell lung cancer
Authors: Chan Susana M. , Raglow Zoe , Pal Anupama , Gitlin Scott D. , Legendre Maureen , Thomas Dafydd , Mehta Ranjit K , Tan Mingjia , Nyati Mukesh K. , Rehemtulla Alnawaz , Markovitz David M.
Published: March 2024

Survival rates for non-small cell lung cancer (NSCLC) remain low despite the advent of novel therapeutics. Tyrosine kinase inhibitors (TKIs) targeting mutant epidermal growth factor receptor (EGFR) in NSCLC have significantly improved mortality but are plagued with challenges--they can only be used in the small fraction of patients who have susceptible driver mutations, and resistance inevitably develops.

Aberrant glycosylation on the surface of cancer cells is an attractive therapeutic target as these abnormal glycosylation patterns are typically specific to cancer cells and are not present on healthy cells. H84T BanLec (H84T), a lectin previously engineered by our group to separate its antiviral activity from its mitogenicity, exhibits precision binding of high mannose, an abnormal glycan present on the surface of many cancer cells, including NSCLC.

Here, we show that H84T binds to and inhibits the growth of diverse NSCLC cell lines by inducing lysosomal degradation of EGFR and leading to cancer cell death through autophagy. This is a mechanism distinct from EGFR TKIs and is independent of EGFR mutation status; H84T inhibited proliferation of both cell lines expressing wild type EGFR and those expressing mutant EGFR that is resistant to all TKIs. Further, H84T binds strongly to multiple and diverse clinical samples of both pulmonary adenocarcinoma and squamous cell carcinoma. H84T is thus a promising potential therapeutic in NSCLC, with the ability to circumvent the challenges currently faced by EGFR TKIs.
Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations
Authors: Klindt David A. , Hyvärinen Aapo , Levy Axel , Miolane Nina , Poitevin Frédéric
Published: March 2024

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.
Light-gated Integrator for Highlighting Kinase Activity in Living Cells
Authors: Lin Wei , Phatarphekar Abhishek , Zhong Yanghao , Liu Longwei , Kwon Hyung-Bae , Gerwick William H. , Wang Yingxiao , Mehta Sohum , Zhang Jin
Published: March 2024

Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into “permanent” fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GαsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.
Incretin hormones and pharmacomimetics rapidly inhibit AgRP neuron activity to suppress appetite
Authors: McMorrow Hayley E. , Lorch Carolyn M. , Hayes Nikolas W. , Fleps Stefan W. , Frydman Joshua A. , Xia Jessica L. , Samms Ricardo J. , Beutler Lisa R.
Published: March 2024

Analogs of the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) have become mainstays of obesity and diabetes management. However, both the physiologic role of incretin hormones in the control of appetite and the pharmacologic mechanisms by which incretin-mimetic drugs suppress caloric intake remain incompletely understood. Hunger-promoting AgRP-expressing neurons are an important hypothalamic population that regulates food intake. Therefore, we set out to determine how incretins analogs affect their activityin vivo. Using fiber photometry, we observed that both GIP receptor (GIPR) and GLP-1 receptor (GLP-1R) agonism acutely inhibit AgRP neuron activity in fasted mice and reduce the response of AgRP neurons to food. Moreover, optogenetic stimulation of AgRP neurons partially attenuated incretin-induced feeding suppression, suggesting that AgRP neuron inhibition is necessary for the full appetite-suppressing effects of incretin-based therapeutics. Finally, we found that GIP but not GLP-1 is necessary for nutrient-mediated AgRP neuron inhibition, representing a novel physiologic role for GIP in maintaining energy balance. Taken together, these findings reveal neural mechanisms underlying the efficacy of incretin-mimetic obesity therapies. Understanding these drugs’ mechanisms of action is crucial for the development of next-generation obesity pharmacotherapies with an improved therapeutic profile.
Asymmetric triangular body-cover model of the VFs with bilateral intrinsic muscle activation
Authors: Parra Jesús , Calvache Carlos , Alzamendi Gabriel , Ibarra Emiro , Soláque Leonardo , Peterson Sean D. , Zañartu Matías
Published: March 2024

Many voice disorders are linked to imbalanced muscle activity and known to exhibit asymmetric vocal fold vibration. However, the relation between imbalanced muscle activation and asymmetric vocal fold vibration is not well understood. This study introduces an asymmetric triangular body-cover model of the vocal folds, controlled by the activation of intrinsic laryngeal muscles, to investigate the effects of muscle imbalance on vocal fold oscillation. Various scenarios were considered, encompassing imbalance in individual muscles and muscle pairs, as well as accounting for asymmetry in lumped element parameters. The results highlight the antagonistic effect between the thyroarytenoid and cricothyroid muscles on the elastic and mass components of the vocal folds, as well as the impact on the vocal process from the imbalance in the lateral cricoarytenoid and interarytenoid adductor muscles. Measurements of amplitude and phase asymmetry were employed to emulate the oscillatory behavior of two pathological cases: unilateral paralysis and muscle tension dysphonia. The resulting simulations exhibit muscle imbalance consistent with expectations in the composition of these voice disorders, yielding asymmetries exceeding 30% for paralysis and below 5% for dysphonia. This underscores the versatility of muscle imbalance in representing phonatory scenarios and its potential for characterizing asymmetry in vocal fold vibration.
Pro-cognitive Effects of Dual Tacrine Derivatives Acting as Cholinesterase Inhibitors and NMDA Receptor Antagonists
Authors: Chvojkova Marketa , Kolar David , Kovacova Katarina , Cejkova Lada , Misiachna Anna , Hakenova Kristina , Gorecki Lukas , Horak Martin , Korabecny Jan , Soukup Ondrej , Vales Karel
Published: March 2024

Therapeutic options for Alzheimer’s disease are limited. Dual compounds targeting two pathophysiological pathways concurrently may enable enhanced effect. The study focuses on tacrine derivatives acting as acetylcholinesterase (AChE) inhibitors and simultaneously as subunit-dependent N-methyl-D-aspartate (NMDA) receptor antagonists. Compounds with balanced inhibitory potencies for target proteins (K1578 and K1599) or with increased inhibitory potency for AChE (K1592 and K1594) were studied. We aimed to identify the most promising pro-cognitive compound.

The pro-cognitive effects of the compounds were studied in cholinergic (scopolamine-induced) and glutamatergic (MK-801-induced) rat models of cognitive deficits in the Morris water maze. Moreover, the effect on locomotion in open field and on AChE activity in relevant brain structures were investigated. The effect of the most promising compound on NMDA receptors was explored byin vitroelectrophysiology.

The cholinergic antagonist scopolamine induced a deficit of memory acquisition, however was unaffected by the compounds, and a deficit of reversal learning, that was alleviated by K1578 and K1599. K1578 and K1599 significantly inhibited AChE in striatum, potentially explaining the behavioral observations.

Glutamatergic antagonist dizocilpine (MK-801) induced a deficit of memory acquisition, which was alleviated by K1599. K1599 also mitigated the MK-801-induced hyperlocomotion in the open field. The electrophysiology study corroborated the K1599-associated NMDA receptor inhibitory effect.

K1599 emerged as the most promising compound, demonstrating pro-cognitive efficacy in both models, consistently with intended dual effect. Our findings contributed to elucidation of structural and functional properties of tacrine derivatives associated with optimalin vivopro-cognitive effects, which further research may benefit from.
The role of rat prelimbic cortex in decision making
Authors: Palmer Jensen A. , White Samantha R. , Lopez Kevin Chavez , Laubach Mark
Published: March 2024

The frontal cortex plays a critical role in decision-making. One specific frontal area, the anterior cingulate cortex, has been identified as crucial for setting a threshold for how much evidence is needed before a choice is made (Domenech & Dreher, 2010). Threshold is a key concept in drift diffusion models, a popular framework used to understand decision-making processes. Here, we investigated the role of the prelimbic cortex, part of the rodent cingulate cortex, in decision making. Male and female rats learned to choose between stimuli associated with high and low value rewards. Females learned faster, were more selective in their responses, and integrated information about the stimuli more quickly. By contrast, males learned more slowly and showed a decrease in their decision thresholds during choice learning. Inactivating the prelimbic cortex in female and male rats sped up decision making without affecting choice accuracy. Drift diffusion modeling found selective effects of prelimbic cortex inactivation on the decision threshold, which was reduced with increasing doses of the GABA-A agonist muscimol. Stimulating the prelimbic cortex through mu opioid receptors slowed the animals’ choice latencies and increased the decision threshold. These findings provide the first causal evidence that the prelimbic cortex directly influences decision processes. Additionally, they suggest possible sex-based differences in early choice learning.
Canopy2: tumor phylogeny inference by bulk DNA and single-cell RNA sequencing
Authors: Weideman Ann Marie K. , Wang Rujin , Ibrahim Joseph G. , Jiang Yuchao
Published: March 2024

Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-sourceRpackage available athttps://github.com/annweideman/canopy2.
A single theory for the evolution of sex chromosomes and the two rules of speciation
Authors: Lenormand Thomas , Roze Denis
Published: March 2024

Sex chromosomes are involved in three major empirical patterns: Y (or W) chromosomes are often non-recombining and degenerate; heterogametic offspring (XY or ZW) from interspecific crosses are more often sterile or inviable than homogametic offspring (Haldane's rule); the X (or Z) has a disproportionately large effect on reproductive isolation between species compared to autosomes (the large X effect). Each observation has received its own tailored explanation involving multiple genetic and evolutionary causes. Here, we show that these empirical patterns all emerge from a single theory for sex chromosome evolution incorporating the co-evolution of cis and trans-acting regulators of gene expression, and leading to systematic misexpression of dosage-compensated genes in heterogametic F1 hybrids, for both young and old sex chromosomes.
Pollination services to crops of watermelon (Citrullus lanatus) and green tomato (Physalis ixocarpa) in the coastal region of Jalisco, Mexico
Authors: Delgado-Carrillo Oliverio , Martén-Rodríguez Silvana , Ramírez-Mejía Diana , Novais Samuel , Quevedo Alexander , Ghilardi Adrian , Sayago Roberto , Lopezaraiza-Mikel Martha , Pérez-Trujillo Erika , Quesada Mauricio
Published: March 2024

Bees play a pivotal role as pollinators in crops crucial for human consumption. However, the global decline in bee populations poses a significant threat to pollination services and food security worldwide. The loss and fragmentation of habitats due to land-use change are primary factors contributing to bee declines, particularly in tropical forests facing high deforestation rates. Here we evaluate the pollination services on crops of watermelon (Citrullus lanatus) and green tomato (Physalis ixocarpa) in the Tropical Dry Forest of Jalisco, Mexico during 2008, and 2014 to 2017. We describe pollinator community composition and visitation frequency and evaluate pollinator contribution to plant reproductive success and degree of pollinator dependence for each crop species. We also assess how landscape configuration influences the abundance and richness of pollinators, and we use the model Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) to map and value the pollination service in both crops. Our findings reveal that the main pollinator of both crops wasApis mellifera, one of the few abundant pollinators in the study region during the dry season, when watermelon and green tomato are cultivated. Results revealed that in the absence of pollinators, watermelon yielded no fruits, while green tomato experienced a 65% reduction in production. For green tomato, fruit set was positively correlated with pollinator abundance. A positive association between forest cover and total pollinator abundance was observed in green tomato in 2008, but not in watermelon. We also found a positive relationship between the abundance of bees predicted by the InVEST model and the abundance of bees observed in green tomato flowers in 2008. In the study region, green tomato and watermelon rely on pollinators for fruit production, with honeybees (from feral and managed colonies) acting as the most importante provider of pollination services for these crops. Consequently, the conservation of natural protected areas is crucial for sustaining pollinators and ensuring food security.
Evaluating the position of the uncal apex as a predictor of episodic memory across the adult lifespan
Authors: Bahrd Philip , Andersson Micael , Kalpouzos Grégoria , Salami Alireza , Nordin Kristin
Published: March 2024

Structural decline of the hippocampus follows heterogeneous spatial patterns, and is an important determinant of episodic memory dysfunction in aging. However, evidence indicate that the anatomical landmark uncal apex, used to demarcate anterior and posterior hippocampal subregions, changes position as the hippocampus atrophies. This risks misclassifying gray matter into the incorrect subregion when using standard demarcation methods, potentially contributing to over– and underestimation of age-related anterior and posterior hippocampal volume loss, respectively. Yet, it remains unexplored whether inter-individual differences in uncal apex position itself predict episodic memory performance. Here, we manually identified the uncal apex in anatomical MRI data from a healthy adult-lifespan sample (n=180; 20-79 years), analyzed age differences in its position, and examined associations with word recall performance. Increasing age was linked to a more anteriorly located uncal apex (retracting ∼0.04 mm/year), and this anterior shift was linked to lower memory performance. Using the manually identified uncal apex for subregion segmentation in native space revealed a lower proportion of anterior hippocampal volume compared to segmentation in MNI space (y = –21), with effects of age on volumes differing between methods. Memory performance was not predicted by hippocampal subregion volumes, but the ratio of posterior to anterior volume was significantly linked to memory when accounting for tissue misclassification due to uncal apex variation. These results indicate that uncal apex position may provide an estimate of hippocampal integrity sensitive to inter-individual differences in memory, independent of limitations associated with different segmentation methods.
Allele Sails: launching traits and fates into wild populations with DNA sequence modifiers
Authors: Johnson Michelle L , Hay Bruce , Maselko Maciej
Published: March 2024

Population-scale genome editing can be used to alter the composition or fate of wild populations. One approach to achieving these aims utilizes a synthetic gene drive element-a multi-gene cassette-to bring about an increase in the frequency of an existing allele. However, the use of gene drives is complicated by the multiple scientific, regulatory, and social issues associated with transgene persistence and gene flow. Alternatives in which transgenes are not driven could potentially avoid some of these issues. Here we propose an approach to population scale gene editing using a system we refer to as an Allele Sail. An Allele Sail consists of a genome editor (the Wind) that introduces DNA sequence edits (the Sail) at one or more sites, resulting in progeny that are viable and fertile. The editor, such as a sequence-specific nuclease, or a prime- or base-editor, is inherited in a Mendelian fashion. Meanwhile, the edits it creates experience an arithmetic, Super-Mendelian increase in frequency. We explore this system using agent-based modeling, and identify contexts in which a single, low frequency release of an editor brings edits to a very high frequency. We also identify conditions in which manipulation of sex determination can be used to bring about population suppression. Current regulatory frameworks often distinguish between transgenics as genetically modified organisms (GMOs), and their edited non-transgenic progeny as non-GMO. In this context an Allele Sail provides a path to alter traits and fates of wild populations in ways that may be considered more acceptable.
Changes in rest-activity rhythms in adolescents as they age: associations with brain changes and behavior in the ABCD study
Authors: Zhang Rui , Schwandt Melanie , Vines Leah , Volkow Nora D.
Published: March 2024

Background

Adolescents with disrupted rest-activity rhythms (RAR) including shorter sleep duration, later sleep timing and low physical activity levels have higher risk for mental and behavioral problems. However, it remains unclear whether the same associations can be observed for within-subject changes in RAR.

Methods

Our longitudinal investigation on RAR used Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year (FL2: aged 10-13 years) and 4-year follow-up (FL4: aged 13-16 years). 963 youths had good-quality Fitbit data at both time points. In this study we examined changes in RAR from FL2 to FL4, their environmental and demographic contributors as well as brain and behavioral correlates.

Results

From FL2 to FL4, adolescents showed decreases in sleep duration and physical activity as well as delayed sleep timing (Cohen’s d .44-.75). The contributions of environmental and demographic factors to RAR changes were greatest to sleep timing (explained 10% variance) and least to sleep duration (explained 1% variance). Delays in sleep timing had stronger correlations with behavioral problems including greater impulsivity and poor academic performance than reductions in sleep duration or physical activity. Additionally, the various brain measures differed in their sensitivity to RAR changes. Reductions in sleep duration were associated with decreased brain functional connectivity between subcortical regions and sensorimotor and cingulo-opercular networks and with enhanced functional connectivity between sensorimotor, visual and auditory networks. Delays in sleep timing were mainly associated with grey matter changes in subcortical regions.

Conclusions

The current findings corroborate the role of sleep and physical activity in adolescent’s brain neurodevelopment and behavior problems. RAR might serve as biomarkers for monitoring behavioral problems in adolescents and to serve as potential therapeutic targets for mental disorders.
Transition from Acute to Chronic Low Back Pain in a Community-Based Cohort
Authors: Burke Colleen , Fillipo Rebecca , George Steven Z. , Goode Adam P.
Published: March 2024

The transition from acute to chronic low back pain (LBP) in community settings has yet to be well understood. We recruited n=131 participants with acute LBP from the community and followed them for 3 and 6-month outcomes. Acute LBP was defined by a duration of < 4 weeks, and participants must have reported a 30-day LBP-free period before the current acute episode. Chronic LBP was defined as pain most or every day over the past 3 months. Baseline psychological, social, and demographic factors were examined as predictors of transition to chronic LBP at 3 months or continuation of chronic LBP at 6 months. The transition from acute to chronic LBP at 3 months was 32.2% ( 38/118). At 6 months, 80.7% (25/111) of participants who transitioned at 3 months continued to have chronic LBP. At 6 months, participants who identified as Black or African American were more likely than white participants to transition to chronic LBP (RR=1.76, 95% CI 1.05, 2.95) and more likely to continue to have chronic LBP (RR=2.19, 95% CI 1.14, 4.21). Those classified at baseline by both LBP most or every day and intensity of at least 30/100 were more likely to transition to chronic LBP (RR=3.13, 95% CI 1.84, 5.30) and continue to have chronic LBP at 6 months (RR=2.58, 95% CI 1.43, 4.16). The STarT Back Screening Tool and the OSPRO-YF were associated with the transition to chronic LBP at 3 months and continuation at 6 months. Participants with higher PROMIS General Health and PROMIS Physical Health scores were less likely to transition to chronic LBP or continue to have chronic LBP at 6 months. These findings identify factors of acute LBP in the community that may predict the transition to chronic LBP. Larger studies are needed to confirm these findings and better understand the mechanisms driving the transition to chronic LBP.
Biglycan Promotes Glioma Cell Line Epithelial-Mesenchymal Transition and Temozolomide Resistance in Vitro
Authors: Han Xiangming , Zheng Yan
Published: March 2024

Gliomas are aggressive brain tumors associated with high mortality and treatment resistance. This study investigates the role of Biglycan (BGN) in glioma progression and its potential as a prognostic marker and therapeutic target. Analysis of data from The Cancer Genome Atlas (TCGA) reveals dysregulated BGN expression in low-grade gliomas (LGG) and glioblastoma (GBM) with positive correlation to tumor grade. High BGN expression is associated with poor prognosis. Functional analysis highlights BGN’s involvement in ECM regulation and EMT, driving glioma invasion and drug resistance. Silencing BGN reduces EMT-related gene expression and invasion capacity. Moreover, BGN expression is upregulated upon TMZ treatment, implicating its role in TMZ resistance. Targeting BGN may be a promising strategy to overcome glioma treatment resistance.