bluuebunny/crossref_metadata_2025 huggingface dataset:
Tumor microenvironment noise-induced polarization: the main challenge in macrophages’ immunotherapy for cancer
Authors: Sierra Jesus , Avila-Ponce de León Ugo , Padilla-Longoria Pablo
Published: May 2024

Disturbance of epigenetic processes can lead to altered gene function and malignant cellular transformation. In particular, changes in the epigenetic landscape are a central topic in cancer biology. The initiation and progression of cancer are now recognized to involve both epigenetic and genetic alterations. In this paper, we study the epigenetic mechanism (related to the tumor microenvironment) responsible for increasing tumor-associated macrophages that promote the occurrence and metastasis of tumor cells, support tumor angiogenesis, inhibit T cell-mediated anti-tumor immune response, and lead to tumor progression. We show that the tumor benefits from the macrophages’ high degree of plasticity and larger epigenetic basins corresponding to phenotypes that favor cancer development through a process that we call noise-induced polarization. Moreover, we propose a mechanism to promote the appropriate epigenetic stability for immunotherapies involving macrophages, which includes p53 and APR-246 (eprenetapopt). Our results show that a combination therapy may be necessary to ensure the proper epigenetic stability of macrophages, which otherwise will contribute to cancer progression. On the other hand, we conclude that macrophages may remain in the anti-tumoral state in types of cancer that exhibit less TP53 mutation, like colorectal cancer; in these cases, macrophages’ immunotherapy may be more suitable. We finally mention the relevance of the epigenetic potential (Waddington’s landscape) as the backbone for our study, which encapsulates the biological information of the system.
Cortical circuit principles predict patterns of trauma induced tauopathy in humans
Authors: Barbas Helen , Garcia-Cabezas Miguel Angel , John Yohan , Bautista Julied , McKee Ann , Zikopoulos Basilis
Published: May 2024

Connections in the cortex of diverse mammalian species are predicted reliably by the Structural Model for direction of pathways and signal processing (reviewed in1,2). The model is rooted in the universal principle of cortical systematic variation in laminar structure and has been supported widely for connection patterns in animals but has not yet been tested for humans. Here, inpostmortembrains of individuals neuropathologically diagnosed with chronic traumatic encephalopathy (CTE) we studied whether the hyperphosphorylated tau (p-tau) pathology parallels connection sequence in time by circuit mechanisms. CTE is a progressive p-tau pathology that begins focally in perivascular sites in sulcal depths of the neocortex (stages I-II) and later involves the medial temporal lobe (MTL) in stages III-IV. We provide novel quantitative evidence that the p-tau pathology in MTL A28 and nearby sites in CTE stage III closely follows the graded laminar patterns seen in homologous cortico-cortical connections in non-human primates. The Structural Model successfully predicted the laminar distribution of the p-tau neurofibrillary tangles and neurites and their density, based on the relative laminar (dis)similarity between the cortical origin (seed) and each connection site. The findings were validated for generalizability by a computational progression model. By contrast, the early focal perivascular pathology in the sulcal depths followed local columnar connectivity rules. These findings support the general applicability of a theoretical model to unravel the direction and progression of p-tau pathology in human neurodegeneration via a cortico-cortical mechanism. Cortical pathways converging on medial MTL help explain the progressive spread of p-tau pathology from focal cortical sites in early CTE to widespread lateral MTL areas and beyond in later disease stages.
Repurposing mitochondrial-targeting anthelmintic agents with GLUT1 inhibitor BAY-876 for cancer therapy
Authors: Schumacher Tanner J. , Iyer Ananth V. , Rumbley Jon , Ronayne Conor T. , Mereddy Venkatram R.
Published: May 2024

Cancer cells alter their metabolic phenotypes with nutritional change. Single agent approaches targeting mitochondrial metabolism in cancer have failed due to either dose limiting off target toxicities, or lack of efficacyin vivo. To mitigate these clinical challenges, we investigated the potential utility of repurposing FDA approved mitochondrial targeting anthelmintic agents, niclosamide and pyrvinium pamoate, to be combined with GLUT1 inhibitor BAY-876 to enhance the inhibitory capacity of the major metabolic phenotypes exhibited by tumors. To test this, we used breast cancer cell lines MDA-MB-231 and 4T1 which exhibit differing basal metabolic rates of glycolysis and mitochondrial respiration, respectively. Here, we found that specific responses to mitochondrial and glycolysis targeting agents elicit responses that correlate with tested cell lines basal metabolic rates and fuel preference, highlighting the potential to cater metabolism targeting treatment regimens based on specific tumor nutrient handling. Inhibition of GLUT1 with BAY-876 potently inhibited glycolysis in both MDA-MB-231 and 4T1 cells, and niclosamide and pyrvinium pamoate perturbed mitochondrial respiration that resulted in potent compensatory glycolysis in the cell lines tested. In this regard, combination of BAY-876 with both mitochondrial targeting agents resulted in inhibition of compensatory glycolysis and subsequent metabolic crisis. These studies warrant further investigation into targeting tumor metabolism as a combination treatment regimen that can be tailored by basal and compensatory metabolic phenotypes.
Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues
Authors: Rodríguez Cristina , Pan Daisong , Natan Ryan G. , Mohr Manuel A. , Miao Max , Chen Xiaoke , Northen Trent R. , Vogel John P. , Ji Na
Published: May 2024

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plantBrachypodium distachyon. In all instances, aberration correction led to significant enhancements in image quality.
Untargeted Plasma Metabolomics Unveils Distinct Metabolite Profiles in Parkinson’s Disease Subtypes: A Focus on idiopathic REM Sleep Behavior Disorders
Authors: Lee Sunjae , Kim Jihyun , Baek Jaewoo , Jung Ki-Young , Lee Yunjong , Koh Ara , Kim Han-Joon
Published: May 2024

Background

Parkinson’s disease (PD) is characterized by diverse clinical presentations and etiological complexities, with rapid eye movement (REM) sleep behavior disorder (RBD) serving as a prodromal marker. While extensive unbiased metabolic profiling of plasma samples from PD subjects has been conducted to identify novel PD metabolic biomarkers, comprehensive metabolic profiling of PD subtypes based on RBD status remains limited.

Methods

We conducted a comprehensive metabolic profiling of PD subtypes at disease onset, considering the presence or absence of RBD, utilizing an untargeted metabolomics approach. Plasma samples were collected from subjects with PD with and without RBD at the initial stages of disease, idiopathic RBD, and healthy controls to elucidate similarities and differences among PD subtypes. Based on ordination analysis and metabolome-wide association study (Wilcoxon rank-sum tests and generalized fold changes), we identified specific groups of metabolites enriched in the PD_Only group and RBD groups (iRBD & PD_RBD+), with few metabolites shared between groups. Furthermore, pathway enrichment analysis (hypergeometric tests) identified specific groups enriched with metabolites from specific origins and associated biospecimens, as well as disease-associated metabolites. Finally, we evaluated the biomarker potential of the identified disease metabolites by ROC curves and proposed logistic regression models of key biomarkers and clinical parameters for predicting disease status.

Results

Metabolomic analysis revealed distinct metabolic profiles between PD subtypes with and without RBD. Our analysis confirmed previously reported PD metabolic markers, such as a reduction in caffeine and urate, as well as an increase in cortisol, secondary bile acids, and p-cresol sulfate. However, our stratified analyses based on the presence of RBD discriminated RBD-associated metabolites from those associated with PD_Only (without RBD). PD patients with RBD exhibited enrichment of gut microbial-origin metabolites, including secondary bile acids and p-cresol sulfate, compared to PD patients without RBD. Conversely, metabolites associated with neuro-psychiatric diseases were enriched in PD patients without RBD.

Conclusions

Our study elucidates the heterogeneous nature of PD subtypes, particularly differentiated with the presence of RBD. The metabolic features of PD with RBD subtype supports the “body-first” concept of PD pathogenesis originating from the gut.
Daily consumption of ketone ester, bis-octanoyl (R)-1,3-butanediol, is safe and tolerable in healthy older adults, a randomized, parallel arm, double-blind, placebo-controlled, pilot study
Authors: Stubbs Brianna J. , Stephens Elizabeth B. , Senadheera Chatura , Peralta Sawyer , Roa-Diaz Stephanie , Alexander Laura , Silverman-Martin Wendie , Garcia Thelma Y. , Yukawa Michi , Morris Jenifer , Blonquist Traci M. , Johnson James B. , Newman John C.
Published: May 2024

Objectives

Ketone bodies are endogenous metabolites produced during fasting or a ketogenic diet that have pleiotropic effects on aging pathways. Ketone esters (KEs) are compounds that induce ketosis without dietary changes, but KEs have not been studied in an older adult population. The primary objective of this trial was to determine tolerability and safety of KE ingestion in older adults.

Design

Randomized, placebo-controlled, double-blinded, parallel-arm trial, with a 12-week intervention period (NCT05585762).

Setting

General community, Northern California, USA.

Participants

Community-dwelling older adults, independent in activities of daily living, with no unstable acute medical conditions (n=30) were randomized and n=23 (M= 14, F=9) completed the protocol.

Intervention

Participants were randomly allocated to consume either KE (bis-octanoyl (R)-1,3-butanediol) or a taste, appearance, and calorie-matched placebo (PLA) containing canola oil.

Measurements

Tolerability was assessed using a composite score from a daily log for 2-weeks, and then via a bi-weekly phone interview. Safety was assessed by vital signs and lab tests at screening and weeks 0, 4 and 12, along with tabulation of adverse events.

Results

There was no difference in the prespecified primary outcome of proportion of participants reporting moderate or severe nausea, headache, or dizziness on more than one day in a two-week reporting period (KE n =2 (14.3% [90% CI = 2.6 – 38.5]); PLA n=1 (7.1% [90% CI = 0.4 – 29.7]). Dropouts numbered four in the PLA group and two in the KE group. A greater number of symptoms were reported in both groups during the first two weeks; symptoms were reported less frequently between 2 – 12 weeks. There were no clinically relevant changes in safety labs or vital signs in either group.

Conclusions

This KE was safe and well-tolerated in healthy older adults. These results provide a foundation for use of KEs in aging research.

Highlights

Ketones esters induce ketosis without dietary changes and may target aging biology

Studies of ketone esters were limited in duration and focused on younger adults

We found ketone esters were safe and tolerable for 12 weeks in healthy older adults
Machine Learning for Prediction of Childhood Mental Health Problems in Social Care
Authors: Crowley Ryan , Parkin Katherine , Rocheteau Emma , Massou Efthalia , Friedmann Yasmin , John Ann , Sippy Rachel , Liò Pietro , Moore Anna
Published: May 2024

Background

Rates of childhood mental health problems are increasing in the United Kingdom. Early identification of childhood mental health problems is challenging but critical to future psycho-social development of children, particularly those with social care contact. Clinical prediction tools could improve these early identification efforts.

Aims

Characterise a novel cohort of children in social care and develop and validate effective Machine Learning (ML) models for prediction of childhood mental health problems.

Method

We used linked, de-identified data from the Secure Anonymised Information Linkage (SAIL) Databank to create a cohort of 26,820 children in Wales, UK, receiving social care services. Integrating health, social care, and education data, we developed several ML models. We assessed the performance, interpretability, and fairness of these models.

Results

Risk factors strongly associated with childhood mental health problems included substance misuse, adoption disruption, and autism. The best-performing model, a Support Vector Machine (SVM) model, achieved an area under the receiver operating characteristic curve (AUROC) of 0.743, with 95% confidence intervals (CI) of 0.724-0.762. Assessments of algorithmic fairness showed potential biases within these models.

Conclusion

ML performance on this prediction task was promising but requires refinement before clinical implementation. Given its size and diverse data, the SAIL Databank is an important childhood mental health database for future work.
Preparing for the Postpartum Medicaid Extension Evaluation in Illinois
Authors: Handler Arden , Krause Caitlin Meyer , Rankin Kristin
Published: May 2024

Background

Given increased attention to the maternal health crisis, its heavy toll on Black birthing persons, and recognition that most pregnancy-related deaths occur in the extended postpartum period, Illinois implemented a Postpartum Medicaid Extension (PME).

Objectives

The purpose of this study was to use baseline data from the pre-PME period to ascertain which groups of eligible persons can be expected to experience improved outcomes as a result of PME implementation in Illinois.

Methods

We focused on the Well-Woman Visit (WWV) as it can be measured in the later postpartum period and is relevant for non-pregnant women. We provide baseline prevalence estimates for WWV receipt using PRAMS and BRFSS data within income strata and within combined income-insurance strata with particular attention to the income group most likely to be affected by the PME. Using multivariable binomial regression, we generate adjusted prevalence differences across income and insurance strata overall and by race/ethnicity.

Results

The Illinois PME has the potential to improve the receipt of well-woman care in the 138-213% FPL income group, the group most likely to be affected by the PME. The analysis also suggests that Black women in Illinois may not be the group most likely to benefit from the enhanced access to care made available by the PME without additional focused attention to their particular needs and experiences. Conclusions and Implications for Practice and Policy:

The PME is necessary but not sufficient for addressing racial/ethnic inequities in maternal health. Leveraging the opportunity that the PME provides to design and support delivery models that maximize the effects of such coverage will be essential to address the maternal health crisis in Illinois. Without extra attention to the needs and experiences of Black women, focused on the delivery of care as well as the structural determinants of health including institutional and interpersonal racism, the benefits of the PME for Black women may not be fully realized.

Recommendations for Practice

An extensive outreach and communications campaign focused on the Postpartum Medicaid Extension in Illinois is necessary so that all birthing persons covered by Medicaid and their providers know that postpartum coverage now continues through 12 months.

New approaches to care are needed to maximize the benefits of the PME, including elevation of the medical care home for women’s primary/interconception care, efforts to reduce provider bias in the delivery of care, and implementation of postpartum care models such as the Two-Generation approach.

Development of a Performance Measurement System within Medicaid focused on the extended postpartum period is essential to ensure that Medicaid providers are aware of the PME and pay particular attention to the extended postpartum period.

Promotion of enhanced postpartum care packages that include reimbursement for services to address the structural/social determinants of health is essential.
Empirical Sample Size Determination for Popular Classification Algorithms in Clinical Research
Authors: Silvey Scott , Liu Jinze
Published: May 2024

Motivation

The performance of a classification algorithm eventually reaches a point of diminishing returns, where additional sample added does not improve results. Thus, there is a need for determining an optimal sample size that both maximizes performance, while accounting for computational burden or budgetary concerns.

Methods

Sixteen large open-source datasets were collected, each containing a binary clinical outcome. Four machine learning algorithms were assessed: XGBoost (XGB), Random Forest (RF), Logistic Regression (LR), and Neural Networks (NN). For each dataset, the cross-validated AUC was calculated at increasing sample sizes, and learning curves were fit. Sample sizes needed to reach the full-dataset AUC minus 2% (or, 0.02) were calculated from the fitted learning curves and compared across the datasets and algorithms. Dataset-level characteristics: minority class proportion, full-dataset AUC, strength/number/type of features, and degree of nonlinearity, were examined. Negative binomial regression models were used to quantify relationships between these characteristics and expected sample sizes within each algorithm. Four multivariable models were constructed which selected the best combination of dataset-specific characteristics that minimized out-of-sample prediction error. Additional models were fitted which allowed for prediction of the expected gap in performance at a given sample size using the same empirical learning curve data.

Results

Among the sixteen datasets (full-dataset sample sizes ranging from 70,000-1,000,000), median sample sizes were 9,960 (XGB), 3,404 (RF), 696 (LR), and 12,298 (NN) to reach AUC convergence. For all four algorithms, more balanced classes (multiplier: 0.93-0.96 for 1% increase in minority class proportion) were associated with decreased sample size. Other characteristics varied in importance across algorithms - in general, more features, weaker features, and more complex relationships between the predictors and the response increased expected sample sizes. In multivariable analysis, top selected predictors were minority class proportion, full-dataset AUC, and dataset nonlinearity (XGB and RF). For LR, top predictors were minority class proportion, percentage of strong linear features, and number of features. For NN, top predictors were minority class proportion, percentage of numeric features, and dataset nonlinearity.

Conclusions

The sample sizes needed to reach convergence among four popular classification algorithms vary by dataset and method and are associated with dataset-specific characteristics that can be influenced or estimated prior to the start of a research study.
Locomotion Efficiency of Elephants: Mechanical work and energetics
Authors: Genin Joakim G. , Dewolf Arthur H. , Willems Patrick A. , Heglund Norman C
Published: May 2024

The size scaling of energy expenditure during locomotion has long puzzled researchers seeking biological invariants. Existing data, most of it from animals smaller than 200 kg, show that the mass specific mechanical work of locomotion is nearly independent of size, yet the metabolic cost of locomotion decreases with increasing size. Major questions remain concerning heavier animals: extrapolating mechanical work and metabolic cost to animals the size of an elephant comes to the uncomfortable conclusion that elephants would produce more energy than they would consume. Our study addresses this longstanding size-scaling conundrum by focusing on the locomotion mechanics and energetics of elephants, the largest extant land animals. In this study, the work required to move the limbs relative to the centre of mass of the whole body (COM) was measured in 27 Asian elephants (872-4000 kg). The total mechanical work was calculated by adding the external work required to maintain the movements theCOM. Our investigation challenges the belief that mass-specific mechanical work of locomotion is independent of size. Furthermore, our study unveils a surprising aspect of elephant locomotion—the substantial fraction of total mechanical work dedicated to limb swinging. At high speeds, elephants allocate ∼75% of their work to limb swinging. Also, by quantifying the metabolic cost and mechanical work, we provide the first estimation of the efficiency of converting metabolic energy into mechanical work in elephants. Elephants exhibit an efficiency of at best 45%, which is similar to that in other large mammals such as horses and humans. This study not only addresses a significant gap in our understanding of size scaling in locomotion but also opens new avenues for exploring the evolution of energy expenditure across diverse animal sizes.
MAIA: An open-source, modular, bioreactor for cities
Authors: Rico Andres , Kong David , Larson Kent
Published: May 2024

This work presents the design and fabrication of MAIA, an open-source, modular, low-cost, and portable bioreactor for democratizing the development of synthetic biology based projects for urban settings. The integration of open-source synthetic biology (synbio) tools in a city’s infrastructure planning and design is crucial for addressing the great challenges related to urbanization. Synbio tools have great potential to help us complement our current sensing and actuating urban infrastructure. The MAIA reactor controls bacterial growth variables, making it suitable for cell-based experiments while reducing the need for expensive laboratory equipment. Its low-cost and open-source design allow for easy replication and modification, making it accessible to a broader audience. Its portability makes it suitable for use outside of traditional laboratory settings. We qualitatively and quantitatively validated the reactor’s capability to support cell growth, stimulate gene expression, and act as a creative tool for students and users.
A Deep Learning-Based Segmentation of Cells and Analysis (DL-SCAN)
Authors: Bhattarai Alok , Meyer Jan , Petersilie Laura , Shah Syed I , Rose Christine R. , Ullah Ghanim
Published: May 2024

With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to study cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises, if fluorophores employed exhibit low brightness and low Signal-to-Noise ratio (SNR). As a consequence, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we have developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using a Deep Learning algorithm called Stardist. We demonstrate the program’s ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na+and Ca2+imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types.

Statement of Significance

Fluorescence microscopy is widely used to study the functional and morphological features of living cells. However, various factors, such as low SNR, background noise, drift in the signal, movement of the tissue, and the large size of the resulting imaging data, make the processing of fluorescence microscopy data prone to errors, user bias, and extremely time-consuming. These and other issues hinder the full utilization of these powerful experimental techniques. Our novel Deep Learning-based tool overcomes these issues by processing and analyzing fluorescence imaging data, e.g., enabling automated visualization of ion changes in living cells in brain slices. Yet the tool remains easy to use with a streamlined workflow.
Development of the overlapping network modules in the human brain
Authors: Lei Tianyuan , Liao Xuhong , Liang Xinyuan , Sun Lianglong , Xia Mingrui , Xia Yunman , Zhao Tengda , Chen Xiaodan , Men Weiwei , Wang Yanpei , Ma Leilei , Liu Ningyu , Lu Jing , Zhao Gai , Ding Yuyin , Deng Yao , Wang Jiali , Chen Rui , Zhang Haibo , Tan Shuping , Gao Jia-Hong , Qin Shaozheng , Tao Sha , Dong Qi , He Yong
Published: May 2024

Developmental connectomic studies have shown that the modular organization of functional networks in the human brain undergoes substantial reorganization with age to support cognitive growth. However, these studies implicitly assume that each brain region belongs to one and only one specific network module, ignoring the potential spatial overlap between functional modules. How the overlapping functional modular architecture develops and whether this development is related to structural signatures remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6–14 years), we investigated the development of the overlapping modular architecture of functional networks, and further explored their structural associations. Specifically, an edge-centric network model was used to identify the overlapping functional modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a remarkable regional inhomogeneity in module overlap in children, with higher entropy in the ventral attention, somatomotor, and subcortical networks and lower entropy in the visual and default-mode networks. Furthermore, the overlapping modules developed in a linear, spatially dissociable manner from childhood to adolescence, with significantly reduced entropy in the prefrontal cortex and putamen and increased entropy in the parietal lobules. Personalized overlapping modular patterns capture individual brain maturity as characterized by brain age. Finally, the overlapping functional modules can be significantly predicted by integrating gray matter morphology and white matter network properties. Our findings highlight the maturation of overlapping network modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.
Tri-omic mapping revealed concerted dynamics of 3D epigenome and transcriptome in brain cells
Authors: Chai Haoxi , Huang Xingyu , Xiong Guangzhou , Huang Jiaxiang , Pels Katarzyna Karolina , Meng Lingyun , Han Jin , Tang Dongmei , Pan Guanjing , Deng Liang , Xiao Qin , Wang Xiaotao , Zhang Meng , Banecki Krzysztof , Plewczynski Dariusz , Wei Chia-Lin , Ruan Yijun
Published: May 2024

Exploring the genomic basis of transcriptional programs has been a longstanding research focus. Here, we report a high-throughput single-cell tri-omic method to capturechromatinaccessibility, interaction, andRNA simultaneously (ChAIR). After validating in cultured cells, we applied ChAIR to brain cells across mouse lifespan and delineated the concerted dynamics of 3D-epigenomic architecture and transcription during maturation and aging. Particularly, ultra-long chromatin megacontacts and promoter-associated 3D-epigenomic states are effective in defining cell identity and revealing spatially-resolved anatomic specificity. Importantly, we found that neurons in different brain regions and non-neuronal cells may undergo divergent genomic mechanisms during differentiation and aging. Our results demonstrated ChAIR’s robustness of connecting chromatin folding architecture with cellular property and its potential applications to address complex questions in single-cell resolution and spatial specificity.
Genomes of two indigenous clamsAnomalocardia flexuosa(Linnaeus, 1767) andMeretrix petechialis(Lamarck, 1818)
Authors: Law Sean Tsz Sum , Nong Wenyan , Au Ming Fung Franco , Cheung Leni Hiu Tong , Shum Cheryl Wood Yee , Lee Shing Yip , Cheung Siu Gin , Hui Jerome Ho Lam
Published: May 2024

Clam digging has a long history in Hong Kong, but unregulated clam digging activities depletes clam populations and threatens the ecosystem. Population genomics is useful to unravel the connectivity of clams at different geographical locations and to provide necessary conservation measures; and yet, only limited number of clams in Hong Kong have genomic resources. Here, we present chromosomal-level genome assemblies for two clams commonly found in Hong Kong,Anomalocardia flexuosaandMeretrix petechialis, using a combination of PacBio HiFi and Omni-C reads. We assembled each genome (∼1.04-1.09 Gb) into 19 pseudochromosomes with high sequence continuity (scaffold N50 = 58.5 Mb and 53.5 Mb) and high completeness (BUSCO scores 94.4% and 95.7%). A total of 20,881 and 20,084 gene models were also predicted forA. flexuosaandM. petechialisrespectively using transcriptomes generated in this study. The two new genomic resources established in this study will be useful for further study of the biology, ecology, and evolution of clams, as well as setting up a foundation for evidence-informed decision making in conservation measures and implementation.
Effects of cognitive load and years of experience on phase-amplitude coupling in simultaneous interpretation
Authors: Yagura Haruko , Tanaka Hiroki , Nakamura Satoshi
Published: May 2024

Simultaneous interpretation is a highly cognitively demanding task that requires constant attention switching between languages. Interest continues to grow in the contribution of phase-amplitude coupling (PAC), which involves the cooperative interaction of multiple oscillations and working memory. In this study, we established subjective definitions for cognitive load levels based on the subjective word familiarity of simultaneous interpretation, categorizing them as low, medium, or high. We then compared the changes in the PAC patterns between experienced interpreters and beginners. Experienced interpreters exhibited an increase in PAC, including theta-gamma PAC, which is linked to working memory, as well as theta-beta PAC, alpha-beta PAC and alpha-gamma PAC, with rising cognitive load levels in simultaneous interpreting. This suggests that experienced simultaneous interpreters choose a more adaptive neural processing strategy in response to the cognitive demands of interpretation language. In contrast, beginner interpreters do not show such changes in PACs, indicating either an underdeveloped or a different neurological approach to the cognitive load levels of interpretation language. The difference in PAC responses between the two groups reflects varying cognitive and interpretive strategies in the brain, where experienced interpreters might utilize more advanced neural mechanisms to manage higher levels of difficulty in simultaneous interpretation.
Flexible Cell Modeling Using Frequency Modulation
Authors: Jacob Jerry , Patel Nitish , Sehgal Sucheta
Published: May 2024

Computational models of the cell can be used to study the impact of drugs and assess pathological risks. Typically, computational models are computationally demanding or difficult to implement in dedicated hardware for real-time emulation. A new Frequency Modulation (FM) model is proposed to address these limitations. This new model utilizes a single sine generator with constant amplitude, but phase/frequency is modulated to emulate an action potential (AP). The crucial element of this model is the identification of the modulating signal. Focusing on FPGA implementation, we have utilized a piecewise linear polynomial with a fixed number of breakpoints to serve as a modulating signal. The ability to adapt this modulating signal permits the emulation of dynamic properties and coupling of cells. We have introduced a state controller that handles both of these requirements. The building blocks of the FM model have direct integer equivalents and are amenable to implementation on digital platforms like Field Programming Gate Arrays (FPGA).

We have demonstrated wavefront propagation of our model in 1-D and 2-D models of a tissue. Various parameters were used to quantify the wavefront propagation in 2-D tissues. We also emulate some cellular dysfunctions. The FM model can replicate any detailed cell model and emulate its corresponding tissue model. Overall, the results depict that the FM model has the potency for real-time cell and tissue emulation on an FPGA.
Fibre type differences in the organisation of mononuclear cells and myonuclei at the tips of human myofibres
Authors: Hoegsbjerg Christian , Møbjerg Ask , Yeung Ching-Yan Chloé , Schjerling Peter , Krogsgaard Michael R. , Koch Manuel , Kjaer Michael , von Keudell Arvind G. , Mackey Abigail L.
Published: May 2024

The myotendinous junction (MTJ) is a weak link in the musculoskeletal system. Here, we isolated the tips of single myofibres from healthy human hamstring muscles for confocal microscopy (n=6) and RNAscopein situhybridization (n=6) to gain insight into the profiles of cells and myonuclei in this region. A marked presence of mononuclear cells was observed coating the fibre tips, with a median of 29 (range 16-63) and 16 (9-23) cells per fibre for type I and II myofibres, respectively (p<0.05). The number and density of myonuclei gradually increased from the myofibre proper towards the tip (p<0.05), similarly for both fibre types, and a greater number ofCOL22A1-expressing nuclei was seen in type II vs type I myofibres (p<0.05). These divergent fibre type-specific characteristics of the MTJ reflect the respective demands for remodelling of the tendon and myofibre sides of the junction according to loading patterns. This insight refines our fundamental understanding of the human MTJ at the cell and structural levels.

Summary statement

At the site of attachment to tendon, type I and II human myofibre tips display divergent numbers of mononuclear cells and COL22A1+ nuclei, changing our understanding of myotendinous junction biology.
The tricellular junctional protein Ildr2 helps maintain glomerular podocyte architecture
Authors: Gerlach Gary F. , Xiong Yubin , O’Brien Lori L.
Published: May 2024

Podocytes are highly specialized epithelial cells of the glomerular filtration barrier essential for maintaining proper kidney function. Their intricate cellular projections, called foot processes, wrap around the capillary endothelium, interdigitate, and connect to one another via slit diaphragm intercellular junctions to form a sieve-like barrier. Compromise to this unique podocyte architecture can lead to altered glomerular function and eventual kidney disease. We previously identified Immunoglobulin-like domain containing receptor 2 (Ildr2) as a component of the podocyte foot process through proteomic analyses. Ildr2 is a tricellular tight junction constituent and localizes to distinct puncta in podocytes that likely represent these specialized junctions. However, the significance of tricellular tight junctions and Ildr2 to podocyte integrity is unknown. To this end, we generated a conditional knockout mouse with podocyte-specific deletion ofIldr2(Podocin-Cretg/+;Ildr2fl/florIldr2PodKO). Kidneys fromIldr2PodKOadult animals show disruptions to podocyte foot process architecture including effacement and the unique formation of electron dense strands connecting subsets of processes. Additionally, the glomerular basement membrane was significantly thicker in conditional knockouts and histological analyses revealed glomerular collagen and glycoprotein accumulation. Surprisingly,Ildr2PodKOanimals displayed no significant albuminuria. WhenIldr2PodKOmice were challenged with a stress to kidney function, immunohistochemistry revealed podocyte loss from a subset of glomeruli with concomitant detection of podocytes in urine, although function was still preserved. Collectively, our data provide novel insights into the function of Ildr2 and suggest tricellular junctions help preserve podocyte architecture but are likely not necessary to maintain proper filtration in no or low stress physiological states.
Desmosomal Cadherin Tension Loss in Pemphigus Vulgaris Mediated by the Inhibition of Active RhoA at Cell-Cell Adhesions
Authors: Jin Xiaowei , Rosenbohm Jordan , Moghaddam Amir Ostadi , Kim Eunju , Seiffert-Sinha Kristina , Leiker Merced , Zhai Haiwei , Baddam Sindora R. , Minnick Grayson , Huo Yucheng , Safa Bahareh Tajvidi , Wahl James K. , Meng Fanben , Huang Changjin , Lim Jung Yul , Conway Daniel E. , Sinha Animesh A. , Yang Ruiguo
Published: May 2024

Binding of autoantibodies to keratinocyte surface antigens, primarily desmoglein 3 (Dsg3) of the desmosomal complex, leads to the dissociation of cell-cell adhesion in the blistering disorder pemphigus vulgaris (PV). After the initial disassembly of desmosomes, cell-cell adhesions actively remodel in association with the cytoskeleton and focal adhesions. Growing evidence highlights the role of adhesion mechanics and mechanotransduction at cell-cell adhesions in this remodeling process, as their active participation may direct autoimmune pathogenicity. However, a large part of the biophysical transformations after antibody binding remains underexplored. Specifically, it is unclear how tension in desmosomes and cell-cell adhesions changes in response to antibodies, and how the altered tensional states translate to cellular responses. Here, we showed a tension loss at Dsg3 using fluorescence resonance energy transfer (FRET)-based tension sensors, a tension loss at the entire cell-cell adhesion, and a potentially compensatory increase in junctional traction force at cell-extracellular matrix adhesions after PV antibody binding. Further, our data indicate that this tension loss is mediated by the inhibition of RhoA at cell-cell contacts, and the extent of RhoA inhibition may be crucial in determining the severity of pathogenicity among different PV antibodies. More importantly, this tension loss can be partially restored by altering actomyosin based cell contractility. Collectively, these findings provide previously unattainable details in our understanding of the mechanisms that govern cell-cell interactions under physiological and autoimmune conditions, which may open the window to entirely new therapeutics aimed at restoring physiological balance to tension dynamics that regulates the maintenance of cell-cell adhesion.
Impacts of dietary fat on multi tissue gene expression in the desert-adapted cactus mouse
Authors: Blumstein Danielle M. , MacManes Matthew D.
Published: May 2024

Understanding the relationship between dietary fat and physiological responses is crucial in species adapted to arid environments where water scarcity is common. In this study, we present a comprehensive exploration of gene expression across five tissues (kidney, liver, lung, gastrointestinal tract, and hypothalamus) and 19 phenotypic measurements, investigating the effects of dietary fat in the desert-adapted cactus mouse (Peromyscus eremicus). We show impacts on immune function, circadian gene regulation, and mitochondrial function for mice fed a lower-fat diet compared to mice fed a higher-fat diet. In arid environments with severe water scarcity, even subtle changes in organismal health and water balance can affect physical performance, potentially impacting survival and reproductive success. The study sheds light on the complex interplay between diet, physiological processes, and environmental adaptation, providing valuable insights into the multifaceted impacts of dietary choices on organismal well-being and adaptation strategies in arid habitats.
Application of Supervised Machine Learning Models for Drug-Action Prediction Towards Nuclear Type I Receptors
Authors: Jaundoo Rajeev , Tuszynski Jack A. , Craddock Travis J.A.
Published: May 2024

1.

Interactions between drugs can lead to adverse side effects for patients taking combination therapies to treat complex diseases such as cancer. Knowledge of drug-action towards a receptor would allow these drug-drug interactions to be predicted, and in this study, we trained a total of 5 different machine learning models to classify whether a given drug was an agonist (activator), antagonist (blocker), or a decoy (non-binder) to each of the androgen, estrogen, glucocorticoid, and progesterone receptors. The classification performance and efficiency, measured in training time, of the decision tree, naïve Bayes, neural network, random forest, and support vector machine models for each receptor were then compared. The results showed that the decision tree and naïve Bayes models were best suited for drug-action prediction across all receptors while only requiring minutes of training time at most. Future work will focus on increasing the prediction accuracy of antagonist drugs, integrating experimental data during training, and using other targets outside of nuclear type I receptors.
Analysis ofAmblyomma americanummicroRNAs in response toEhrlichia chaffeensis infection and their potential role in vectorial capacity
Authors: Kumar Deepak , Budachetri Khemraj , Rikihisa Yasuko , Karim Shahid
Published: May 2024

Background

MicroRNAs (miRNAs) represent a subset of small noncoding RNAs and carry tremendous potential for regulating gene expression at the post-transcriptional level. They play pivotal roles in distinct cellular mechanisms including inhibition of bacterial, parasitic, and viral infections via immune response pathways. Intriguingly, pathogens have developed strategies to manipulate the host’s miRNA profile, fostering environments conducive to successful infection. Therefore, changes in an arthropod host’s miRNA profile in response to pathogen invasion could be critical in understanding host-pathogen dynamics. Additionally, this area of study could provide insights into discovering new targets for disease control and prevention. The main objective of the present study is to investigate the functional role of differentially expressed miRNAs uponEhrlichia chaffeensis, a tick-borne pathogen, infection in tick vector,Amblyomma americanum.

Methods

Small RNA libraries from uninfected andE. chaffeensis-infectedAm. americanummidgut and salivary gland tissues were prepared using the Illumina Truseq kit. Small RNA sequencing data was analyzed using miRDeep2 and sRNAtoolbox to identify novel and known miRNAs. The differentially expressed miRNAs were validated using a quantitative PCR assay. Furthermore, a miRNA inhibitor approach was used to determine the functional role of selected miRNA candidates.

Results

The sequencing of small RNA libraries generated >147 million raw reads in all four libraries and identified a total of >250 miRNAs across the four libraries. We identified 23 and 14 differentially expressed miRNAs in salivary glands, and midgut tissues infected withE. chaffeensis, respectively. Three differentially expressed miRNAs (miR-87, miR-750, and miR-275) were further characterized to determine their roles in pathogen infection. Inhibition of target miRNAs significantly decreased theE. chaffeensisload in tick tissues, which warrants more in-depth mechanistic studies.

Conclusions

The current study identified known and novel miRNAs and suggests that interfering with these miRNAs may impact the vectorial capacity of ticks to harborEhrlichia. This study identified several new miRNAs for future analysis of their functions in tick biology and tick-pathogen interaction studies.
Stochastic to Deterministic: A straightforward approach to create serially perfusable multiscale capillary beds
Authors: Donzanti Michael J. , Mhatre Omkar , Chernokal Brea , Renteria Diana C. , Gleghorn Jason P.
Published: May 2024

Generation ofin vitrotissue models with serially perfused hierarchical vasculature would allow greater control of fluid perfusion throughout the network and enable direct mechanistic investigation of vasculogenesis, angiogenesis, and vascular remodeling. In this work, we have developed a method to produce a closed, serially perfused, multiscale vessel network embedded within an acellular hydrogel. We confirmed that the acellular and cellular gel-gel interface was functionally annealed without preventing or biasing cell migration and endothelial self-assembly. Multiscale connectivity of the vessel network was validated via high-resolution microscopy techniques to confirm anastomosis between self-assembled and patterned vessels. Lastly, using fluorescently labeled microspheres, the multiscale network was serially perfused to confirm patency and barrier function. Directional flow from inlet to outlet man-dated flow through the capillary bed. This method for producing closed, multiscale vascular networks was developed with the intention of straightforward fabrication and engineering techniques so as to be a low barrier to entry for researchers who wish to investigate mechanistic questions in vascular biology. This ease of use offers a facile extension of these methods for incorporation into organoid culture, organ-on-a-chip (OOC) models, and bioprinted tissues.
Novel clock neuron subtypes regulate temporal aspects of sleep
Authors: Ma Dingbang , Le Jasmine Quynh , Dai Xihuimin , Díaz Madelen M. , Abruzzi Katharine C. , Rosbash Michael
Published: May 2024

Circadian neurons within animal brains orchestrate myriad physiological processes and behaviors, But the contribution of these neurons to the regulation of sleep is not well understood. To address this deficiency, we leveraged single-cell RNA sequencing to generate a new and now comprehensive census of transcriptomic cell types ofDrosophilaclock neurons. We focused principally on the enigmatic DN3s, which constitute about half of the 75 pairs of clock neurons in the fly brain and were previously almost completely uncharacterized. These DN3s are organized into 12 clusters with unusual gene expression features compared to the more well-studied clock neurons. We further show that different DN3 subtypes with distinct projection patterns promote sleep at specific times of the day through a common G protein–coupled receptor,TrissinR. Our findings indicate an intricate regulation of sleep behavior by clock neurons and highlight their remarkable diversity in gene expression, projection patterns and functional properties.