bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing sequential gene expression modulation for cellular reprogramming - Coupled Boolean modeling and Reinforcement Learning based method
Authors: Singh Vivek
Published: March 2024

Regenerative medicine entails regenerating damaged cells and tissues from healthy cells through the process of cellular reprogramming. The most common method to achieve reprogramming of cells of one type to another is by modulating the activity of specific genes. However, identifying the most suitable genes for reprogramming is a challenge due to their large number in humans and their complex interactions.

This study describes a computational method to predict sequential gene expression modulation for reprogramming a starting cell type to a target cell type. The proposed method integrates: (1) a Boolean model of the concerned gene regulatory network (GRN); and (2) a reinforcement learning (RL) based model for optimization. The Boolean model is used to capture the dynamic behavior of the GRN and to understand how the gene expression modulation alters its behavior. RL model is used to optimize sequential decision-making of predicting the suitable sequence of gene expression modulation.

Coupling of the Boolean model and RL plays a crucial role in the proposed computational method. Boolean model captures the GRN dynamics, and thereby, constrains the combinatorially large state space. The RL model operates in this constrained state space and uses the Boolean model to evaluate the effect of modulations on GRN dynamics to predict the sequence of suitable gene expression modulations.

Applicability of the proposed method is demonstrated using a toy network of 4 genes, and a biological network of heart development representing the dynamics of 15 genes.
Cancer-Associated Hypercalcemia Signals Through the Hindbrain to cause Anorexia
Authors: Grinman Diego Y. , Takyar Farzin M. , Dann Pamela , Shanabrough Marya , Brown Stacey , Clemenceau Alisson , Hens Julie R. , Stutz Bernardo , Chodosh Lewis A. , Chang Wenhan , Shulman Gerald I. , Horvath Tamas L. , Wysolmerski John J.
Published: March 2024

Hypercalcemia, caused by tumor secretion of parathyroid hormone-related protein (PTHrP), is associated with anorexia and weight loss. We demonstrate that overexpression of PTHrP by tumor cells in a transgenic model of breast cancer causes anorexia and rapid weight loss. These changes are accompanied by activation of neurons in the area postrema (AP), the nucleus tractus solitarius (NTS) and the parabrachial nucleus (PBN), a hindbrain circuit regulating food intake. Blocking hypercalcemia prevents anorexia and activation of these brain centers in tumor bearing mice, whereas injecting calcium activates the same circuit in wild-type mice. Neurons in the AP express the calcium-sensing receptor (CaSR) and the same AP/NTS/PBN circuit is stimulated by treating WT mice with cinacalcet, an allosteric activator of the CaSR. Finally, treating diet-induced obese mice with cinacalcet reduces food intake and causes weight loss. These results suggest that CaSR-expressing neurons in the AP might be a pharmacologic target for obesity.
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures
Authors: Ellis Charles A. , Lapera Sancho Martina , Miller Robyn L. , Calhoun Vince D.
Published: March 2024

Deep learning methods are increasingly being applied to raw electro-encephalogram (EEG) data. However, if these models are to be used in clinical or research contexts, methods to explain them must be developed, and if these models are to be used in research contexts, methods for combining explanations across large numbers of models must be developed to counteract the inherent randomness of existing training approaches. Model visualization-based explainability methods for EEG involve structuring a model architecture such that its extracted features can be characterized and have the potential to offer highly useful insights into the patterns that they uncover. Nevertheless, model visualization-based explainability methods have been underexplored within the context of multichannel EEG, and methods to combine their explanations across folds have not yet been developed. In this study, we present two novel convolutional neural network-based architectures and apply them for automated major depressive disorder diagnosis. Our models obtain slightly lower classification performance than a baseline architecture. However, across 50 training folds, they find that individuals with MDD exhibit higher β power, potentially higher δ power, and higher brain-wide correlation that is most strongly represented within the right hemisphere. This study provides multiple key insights into MDD and represents a significant step forward for the domain of explainable deep learning applied to raw EEG. We hope that it will inspire future efforts that will eventually enable the development of explainable EEG deep learning models that can contribute both to clinical care and novel medical research discoveries.
srahunter: a user-friendly tool to speed up and simplify data downloading from NCBI SRA
Authors: Bortoletto Enrico , Frizzo Riccardo , Venier Paola , Rosani Umberto
Published: March 2024

Easy access and use of vast datasets are paramount for advancing scientific discovery in steadily expanding studies based on high-throughput sequencing (HTS). The Sequence Read Archive (SRA) is a publicly accessible repository currently holding a huge amount of HTS reads, as part of the International Nucleotide Sequence Database Collaboration (INSDC). However, accessing, downloading, and managing data and metadata efficiently can be challenging. Here, we introducesrahunter, a tool designed to simplify data and metadata acquisition from SRA. Developed with Python,srahunterleverages the core functionalities ofSRA ToolkitandEntrez Direct, to enable automated downloading, smart data management, and user-friendly metadata integration through an interactive HTML tablehttps://github.com/GitEnricoNeko/srahunter. Compared to existing tools,srahunterincreases the efficiency of metadata retrieval by reducing the technical barriers to SRA data and streamlining the handling of SRA datasets, and can therefore accelerate the development of genomics and multiple ‘omics research.
Protein Retrieval via Integrative Molecular Ensembles (PRIME) through extended similarity indices
Authors: Chen Lexin , Mondal Arup , Perez Alberto , Miranda-Quintana Ramón Alain
Published: March 2024

Molecular dynamics (MD) simulations are ideally suited to describe conformational ensembles of biomolecules such as proteins and nucleic acids. Microsecond-long simulations are now routine, facilitated by the emergence of graphical processing units. Processing such ensembles on the basis of statistical mechanics can bring insights about different biologically relevant states, their representative structures, states, and even dynamics between states. Clustering, which groups objects based on structural similarity, is typically used to process ensembles, leading to different states, their populations, and the identification of representative structures. For some purposes, such as in protein structure prediction, we are interested in identifying the representative structure that is more similar to the native state of the protein. The traditional pipeline combines hierarchical clustering for clustering and selecting the cluster centroid as representative of the cluster. However, even when the first cluster represents the native basin, the centroid can be several angstroms away in RMSD from the native state – and many other structures inside this cluster could be better choices of representative structures, reducing the need for protein structure refinement. In this study, we developed a module—Protein Retrieval via Integrative Molecular Ensemble (PRIME), that consists of tools to determine the most prevalent states in an ensemble using extended continuous similarity. PRIME is integrated with our Molecular Dynamics Analysis withN-ary Clustering Ensembles (MDANCE) package and can be used as a post-processing tool for arbitrary clustering algorithms, compatible with several MD suites. PRIME was validated with ensembles of different protein and protein complex systems for their ability to reliably identify the most native-like state, which we compare to their experimental structure, and to the traditional approach. Systems were chosen to represent different degrees of difficulty such as folding processes and binding which require large conformational changes. PRIME predictions produced structures that when aligned to the experimental structure were better superposed (lower RMSD). A further benefit of PRIME is its linear scaling – rather than the traditional O(N2) traditionally associated to comparisons of elements in a set.
Targeting Diffuse Midline Glioma with a novel anti-CD99 Antibody
Authors: Balakrishnan Ilango , Madhavan Krishna , Pierce Angela M , Michlin Joshua , Brunt Breauna , Chetty Senthilnath Lakshmana , Wang Dong , DeSisto John , Nuss Zachary , Davidson Nathan , Donson Andrew , Jones Kenneth , Mitra Siddhartha , Green Adam , Dahl Nathan , Vibhakar Rajeev , Venkataraman Sujatha
Published: March 2024

Diffuse midline gliomas (DMGs) are devastating brain tumors that occur primarily in children. The salient feature of these tumors is the presence of a H3K27M mutation (K27M), associated with the worst prognosis. We identified the cell surface antigen CD99 as notably expressed in DMGs, particularly in K27M+DMGs. We found that the increased expression of CD99 in K27M+DMGs was a result of the onco-histone K27M mutation. In K27M+DMG cells, CD99 inactivation impaired tumor growth by inducing cell differentiation, indicating an oncogenic role of CD99 enabled by blocking differentiation. We then developed a novel therapeutic anti-CD99 chimeric antibody, 10D1, with a membrane-proximal binding epitope, and evaluated its antitumor efficacy in preclinical models of K27M+DMG. 10D1 suppressed DMG growthin vitroandin vivoby inducing apoptosis. When combined with radiation treatment, 10D1 exhibited improved antitumor efficiency and xenograft survival, providing a strong justification for its clinical development as a therapy for DMGs.

Statement of Significance

This study emphasizes that CD99 overexpression occurs due to the H3K27M mutation in Diffuse Midline Gliomas (DMGs). This heightened expression suppresses apoptosis, inhibits differentiation, and induces radio-resistance in DMGs. This research justifies using a novel CD99 antibody alone or combined with radiation therapy in human pediatric clinical trials.
Brief Physical Activity Selectively Modulates the Performance of Serial Subtract 7 in Young Adults – A Wearable Sensor-based, Randomized, Control Study
Authors: Chu Xin Ran , Newaz Tanmoy , Tom Elbert , Yang Allison , Chomiak Taylor , Hu Bin
Published: March 2024

OBJECTIVE

This study explores the effects of physical activities on cognitive performance in healthy subjects, specifically evaluating Serial Subtract 7 Test (SST) performance during a cognitive-stepping dual task influenced by the 6-Minute Walking Test (6MWT) with and without music.

METHODS

A controlled experiment was conducted using the Ambulosono device to standardize walking exercises. 54 high school students participated, undergoing the 6MWT in different scenarios: Verbal 6-Minute Walking Test (6MWT) or Music-Guided Walking (MU). Final data from 43 students was used in the analysis. The SST measured cognitive changes in both single-task and dual-task conditions.

RESULTS

The 6MWT significantly enhanced cognitive performance in both single and dual-task conditions. However, the addition of music did not show a substantial improvement in cognitive performance. The findings indicated the positive impact of 6MWT on cognitive abilities, irrespective of musical accompaniment.

CONCLUSIONS

This research contributes to the understanding of how physical exercises can modulate cognitive functions in healthy individuals. It highlights the potential of 6MWT in enhancing cognitive performance, suggesting further exploration into the role of physical activity in cognitive health.
A multicenter evaluation of a novel microfluidic rapid AST assay for Gram-negative bloodstream infections
Authors: Berinson Benjamin , Davies Emma , Torpner Jessie , Flinkfeldt Linnea , Fernberg Jenny , Åman Amanda , Bergqvist Johan , Öhrn Håkan , Ångström Jonas , Johansson Cecilia , Jäder Klara , Andersson Helena , Ghaderi Ehsan , Rolf Maria , Sundqvist Martin , Rohde Holger , Fernandez-Zafra Teresa , Malmberg Christer
Published: March 2024

Objectives

Common phenotypic methods for antibiotic susceptibility testing (AST) of bacteria are slow, labour intensive and display considerable technical variability. The QuickMIC system provides rapid AST using a microfluidic linear gradient. Here we evaluate the performance of QuickMIC at four different laboratories with regards to speed, precision, accuracy, and reproducibility in comparison to broth microdilution (BMD).

Methods

Spiked blood cultures (n=411) and clinical blood cultures (n=148) were tested with the QuickMIC Gram negative (GN) panel and compared with BMD for the 12 on-panel antibiotics, and 10 defined strains were run at each site to measure reproducibility. Logistic and linear regression analysis was applied to explore factors affecting assay performance.

Results

The overall essential agreement (EA) and categorical agreement (CA) between QuickMIC and BMD were 95.6% and 96.0%, respectively. Very major error (VME), Major error (ME) and minor error (mE) rates were 1.0, 0.6 and 2.4%, respectively. Inter-laboratory reproducibility between the sites was high at 98.9% using the acceptable standard of ±1 log2 unit. The mean in-instrument analysis time overall was 3h 13 min (SD: 29 min). Regression analysis indicated that QuickMIC is robust with regards to initial inoculate and delay time after blood culture positivity.

Conclusions

We conclude that QuickMIC can be used to rapidly measure MIC directly from blood cultures in clinical settings, with high reproducibility, precision, and accuracy. The microfluidics-generated linear gradient ensures high repeatability and reproducibility between laboratories, thus allowing a high level of trust in MIC values from single testing, at the cost of reduced measurement range compared to BMD.
Identifying associations ofde novononcoding variants with autism through integration of gene expression, sequence and sex information
Authors: Li Runjia , Ernst Jason
Published: March 2024

Whole-genome sequencing (WGS) data is facilitating genome-wide identification of rare noncoding variants, while elucidating their roles in disease remains challenging. Towards this end, we first revisit a reported significant brain-related association signal of autism spectrum disorder (ASD) detected fromde novononcoding variants attributed to deep-learning and show that local GC content can capture similar association signals. We further show that the association signal appears driven by variants from male proband-female sibling pairs that are upstream of assigned genes. We then develop Expression Neighborhood Sequence Association Study (ENSAS), which utilizes gene expression correlations and sequence information, to more systematically identify phenotype-associated variant sets. Applying ENSAS to the same set ofde novovariants, we identify gene expression-based neighborhoods showing significant ASD association signal, enriched for synapse-related gene ontology terms. For these top neighborhoods, we also identify chromatin states annotations of variants that are predictive of the proband-sibling local GC content differences. Our work provides new insights into associations of non-codingde novomutations in ASD and presents an analytical framework applicable to other phenotypes.
Exploring Inflammatory Dysregulation in Alveolar Macrophages: Implications for Novel Therapeutic Targets in Chronic Obstructive Pulmonary Disease
Authors: Adeyanju Saheed
Published: March 2024

Chronic obstructive pulmonary disease is a severe lung disease characterized by tissue destruction and limited airflow mainly caused by exposure to harmful environmental substances. Primary symptoms of this lung disorder include dyspnea, sputum production, and cough, which leads to respiratory failure. Prevalence increases with age, making it the most common cause of death worldwide. The primary objective of this study was to identify novel therapeutic targets via gene expression meta-analysis and to utilize them for drug reprofiling of FDA-approved drugs in treating chronic obstructive pulmonary disease. Multiple microarray and RNA-seq datasets from alveolar macrophages comprising healthy and diseased patients were processed to pinpoint significant dysregulated genes involved in this disease. Next, a meta-analysis was performed to identify the consistently differentially expressed genes in all datasets. Functional enrichment and protein-protein interaction analyses were conducted to single out the hub genes. Moreover, 3D structure prediction, virtual screening, and molecular dynamics simulations were utilized to explore the selected hub gene for drug repurposing. The number of significantly dysregulated genes identified via RNA-seq and microarray meta-analysis was found to be 104 and 57, respectively. Interestingly, VGLL3, ITIH5, ELOVL7, ACOD1, LAMB1, CXCL9, and GBP5 were common between the two sets revealing their significant association with the disease. CXCL9 and CCL3L3 were identified as the common hub genes between both sets. However, CXCL9, a chemokine, was prioritized for drug repurposing endeavors as it exhibits remarkable involvement in immune response and inflammation. Virtual screening of CXCL9 against selected drugs disclosed that CXCL9 has the highest binding affinity of −7.3 kcal/mol for Nintedanib, and binding affinities ranged from −2.4 kcal/mol to −7.3 kcal/mol. Moreover, Tepotinib and Crizotinib were found to be the second and third top-scoring drugs of −6.8 kcal/mol and −6.2 kcal/mol, respectively. Furthermore, the molecular dynamics simulation revealed that Crizotinib showed the most prominent results; however, its binding affinity is lower than Nintedanib. Therefore, Nintedanib is suggested as the better therapeutic agent to inhibit CXCL9 for treating chronic obstructive pulmonary disease.

Highlights

Meta-analysis of microarray and RNA-Seq datasets of alveolar macrophages from healthy and diseased patients disclosed novel therapeutic targets.

Common significantly dysregulated hub gene CXCL9 is a novel drug target for COPD.

CXCL9 is a chemokine responsible for inflammatory and immune responses utilized for drug reprofiling.

Nintedanib, Tepotinib, and Crizotinib exhibited strong binding affinities against CXCL9.

Virtual screening and simulation results revealed that inhibition of CXCL9 may be a potential treatment for COPD.
Co-translational sorting enables a single mRNA to generate distinct polysomes with different localizations and protein fates
Authors: Salloum Soha , Séveno Martial , El Koulali Khadija , Rialle Stephanie , George Simon , Lemmers Benedicte , Zibara Kazem , Eliscovich Carolina , Hahne Michael , Bertrand Edouard
Published: March 2024

β-catenin is a multi-functional protein playing essential roles in tissue homeostasis and cancer. It bridges E-cadherin to the cytoskeleton and also activates transcription in response to Wnt. Plasma membrane β-catenin is stable whereas without Wnt, cytoplasmic β-catenin is degraded by the destruction complex, composed of APC and Axin. Here, we show that APC and Axin associate with many mRNAs and that this occurs via the nascent protein chains. Notably, APC and Axin bind β-catenin mRNAs present as either single polysome or polysome condensates, and co-translational interactions constitute the major fraction of their binding to the β-catenin protein. Remarkably, E-cadherin also binds β-catenin co-translationally, and β-catenin mRNAs localize either with APC in the cytosol or E-cadherin at the plasma membrane. Thus, co-translational interactions sort β-catenin mRNAs into distinct polysome populations that spatially segregate in cells and synthesize proteins with different functions. Co-translational polysome sorting provides a mechanism to regulate the fate of multi-functional proteins.
Ultrasound as a reliable guide for lumbar intrathecal injection in rats: A pilot study
Authors: Pryambodho  , Dilogo Ismail Hadisoebroto , Tantri Aida R. , Aman Renindra Ananda , Tjokorda Gde A. S. , Purba Jan S. , Siregar Nuryati C.
Published: March 2024

Lumbar intrathecal administration provides an ideal route for drug delivery into the central nervous system, especially when dorsal root ganglions are the main target for the therapy in rat model of chronic pain. Two main methods of lumbar intrathecal administrations are chronic catheter implantation and the acute needle puncture. Chronic catheter implantation involves surgical manipulation to insert micro indwelling catheter into the intrathecal space. However, this method is invasive, produces inflammatory reactions, and generates more surgical stress. Acute needle puncture is less invasive and cheaper but is technically challenging to perform. We performed an ultrasound-guided lumbar intrathecal injection in six male Sprague Dawley rat cadavers, on average weighing 250–300 grams. Fresh rat cadavers were positioned in a sternal recumbent position, vertebrae were palpated and scanned using a linear probe ultrasound. A 25G needle insertion was advanced with real-timeultrasound guidance, and placement was confirmed prior to dye injection (Methylene blue, Sigma Aldrich). Cadavers were then dissected, and the vertebrae were visually inspected for dye staining. All three cadavers that underwent intrathecal injection with sagittal and axial plane ultrasound guidance showed positive dye staining within the intrathecal space, confirming successful acute intrathecal administration. There was one successful intrathecal injection under sagittal plane-only ultrasound guidance. Ultrasound is a useful, operator-dependent tool to guide acute needle puncture intrathecal administration.
Baraitser–Winter Syndrome Hotspot Mutation R196H in Cytoskeletal β–actin Reduces F–actin Stability and Perturbs Interaction with the Arp2/3 Complex
Authors: Greve Johannes N. , Manstein Dietmar J.
Published: March 2024

Baraitser–Winter cerebrofrontofacial syndrome (BWCFF) is the most common and best–defined clinical entity associated with heterozygous single–point missense mutations in cytoskeletal β–actin. Patients present with distinct craniofacial anomalies and neurodevelopmental disabilities of variable severity. To date, the most frequently observed variants affect residue R196 of cytoskeletal β–actin, with the variant p.R196H being the most common. Patients carrying the p.R196H variant are likely to suffer from pachygyria, probably due to neuronal migration defects contributing to the development of abnormally thick convolutions of the cerebral cortex. Here, we describe the recombinant production, purification and biochemical characterization of the BWCFF hotspot variant p.R196H. The stability and nucleotide interaction of monomeric p.R196H are unaffected, indicating a disease mechanism involving incorporation of p.R196H protomers into actin filaments. Incorporation of the variant strongly affects F–actin stability and polymerization dynamics, consistent with the position of residue R196 close to the helical axis of the actin filament and an important interstrand contact. The changes observed include an increased critical concentration of polymerization, a reduced elongation rate and an increase in the rate of filament depolymerization. In the Arp2/3–generated branch junction complex, which is essential for cell migration and endocytosis, R196 is located at the interface between the first protomer of the nucleated daughter filament and the Arp2 subunit of the Arp2/3 complex. Assays probing the interaction of p.R196H filaments with the Arp2/3 complex show a reduced efficiency of branch generation. Branch stability is impaired, as evidenced by a reduction in the number of branches and spontaneous debranching events. Furthermore, in their interaction with different types of cytoskeletal myosin motors, p.R196H filaments show isoform–specific differences. While p.R196H filaments move WT–like on lawns of surface–immobilized non–muscle myosin–2A, motility on myosin–5A is 30 % faster.
Template Learning: Deep Learning with Domain Randomization for Particle Picking in Cryo-Electron Tomography
Authors: Harastani Mohamad , Patra Gurudatt , Kervrann Charles , Eltsov Mikhail
Published: March 2024

Cryo-electron tomography (cryo-ET) enables the three-dimensional visualization of biomolecules and cellular components in their near-native state. Particle picking, a crucial step in cryo-ET data analysis, is traditionally performed by template matching—a method utilizing cross-correlations with available biomolecular templates. Despite the effectiveness of recent deep learning-based particle picking approaches, their dependence on initial data annotation datasets for supervised training remains a significant limitation. Here, we propose a technique that combines the accuracy of deep learning particle identification with the convenience of the model training on biomolecular templates enabled through a tailored domain randomization approach. Our technique, named Template Learning, automates the simulation of training datasets, incorporating considerations for molecular crowding, structural variabilities, and data acquisition variations. This reduces or even eliminates the dependence of supervised deep learning on annotated experimental datasets. We demonstrate that models trained on simulated datasets, optionally fine-tuned on experimental datasets, outperform those exclusively trained on experimental datasets. Also, we illustrate that Template Learning used as an alternative to template matching, can offer higher precision and better orientational isotropy, especially for picking small non-spherical particles. Template Learning software is open-source, Python-based, and GPU and CPU parallelized.
Comparing the effect of multi gradient echo and multi band fMRI during a semantic task
Authors: Halai Ajay D. , Henson Richard N. , Finoia Paola , Correia Marta M.
Published: March 2024

The Blood Oxygenation Level Dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is known to vary in sensitivity across the brain due to magnetic susceptibility artefacts. In particular, the ventral anterior temporal lobes (vATL) have been implicated with semantic cognition using convergent methods (i.e., neuropsychology, PET, MEG, brain stimulation) but less so with fMRI using conventional gradient-echo protocols. There are methods to alleviate signal loss but multi-echo fMRI has gained popularity. Here, additional volumes are collected that span across a range of T2* values, however, this results sub-optimum parameters (i.e., repetition times, resolution, acceleration). “Multi-band” imaging has been used with multi-echo to speed up data acquisition; however, it is unclear how these modifications contribute to fMRI sensitivity across the brain and for univariate/multivariate analyses. In the current study, we used a factorial design where we manipulated the echo and/or band to assess how well the semantic network can be detected. When comparing the precision with which activations were detected (i.e, average T-statistics), we found that multi-band protocols were beneficial, with no evidence of signal leakage artefacts. When comparing the magnitude of activations, multi-echo protocols increased activations in regions prone to susceptibility artefacts (specifically the anterior temporal lobes, ATLs). Both multi-banding and independent component analysis (ICA)-denoising of multi-echo data tended to improve multi-voxel decoding of conditions. However, multi-echo protocols reduced activation magnitude in more central regions, such as the medial temporal lobes, possibly due to higher in-plane acceleration required to collect multiple-echoes. Nonetheless, the multi-echo multi-band protocol is a promising default option for fMRI on most regions, particularly those that suffer from susceptibility artefacts, as well as offering the potential to apply advanced post-processing methods to take advantage of the increased temporal (or spatial) resolution of multi-band protocols and more principled ICA-denoising based on TE-dependence of BOLD signals.
Frequent intertrophic transmission ofWolbachiaby parasitism but not predation
Authors: Yan Zhi-Chao , Qi Lan-Da , Ji Han-Le , Wang Xiao-Xiang , Hong Xiao-Yue , Li Yuan-Xi
Published: March 2024

Wolbachiais one of the most pervasive symbionts, estimated to infect ∼50% of arthropod species. It is primarily transmitted vertically, inducing a variety of fascinating reproductive manipulations to promote its spread within host populations. However, incongruences between host andWolbachiaphylogenies indicate substantial horizontal transmissions, the mechanisms of which are largely unexplored. By systematically analyzingWolbachiasurface protein (wsp) sequences on NCBI, we found that parasitism, not predation, is the primary route of intertrophicWolbachiatransmission. This conclusion held after accounting sampling bias. One example of frequentWolbachiatransfers is between egg parasitoid wasps,Trichogramma, and their lepidopteran hosts. Moreover, both bioinformatics and experimental results showed thatWolbachiafrom the parasitoid waspEncarsia formosacan be transmitted to its whitefly hostBemisia tabaci, through unsuccessful parasitism. OnceEn. formosa Wolbachiais transferred to whiteflies, it can be vertically transmitted within whiteflies and induce fitness costs. To our knowledge, this is the first compelling evidence thatWolbachiacan be transmitted from parasitoid wasps to their hosts, revealing the bidirectional nature ofWolbachiatransfers between parasitoids and their hosts. Overall, our findings enrich the current understanding of the horizontal transmission ofWolbachiaand shed new light on its ecology and evolution.
In-depth investigation of the mechanisms of high and low residual feed intake regulating hens during the late laying period via liver and gut microbiota
Authors: Gao Zhouyang , Zheng Chuanwei , Mao Zhiqiong , Zheng Jiangxia , Liu Dan , Xu Guiyun
Published: March 2024

Residual feed intake (RFI) is a more accurate indicator of feed efficiency than the feed conversion ratio (FCR) and is widely used to measure the efficiency of livestock and poultry feed utilization. Typically, Low RFI (LRFI) implies higher feed conversion efficiency, while high RFI (HRFI) indicates lower feed conversion efficiency. This study systematically explored the differences between high and low RFI and the function of the liver and cecum microbes of hens during the late laying period by multiple-omics techniques and further explored the interaction among microorganisms, the function of tissues and organs, and body metabolism. The results showed that the length and mass of the digestive organs in the LRFI group were higher than those in the HRFI group as well as the chest width. Additionally, the key genes and metabolites regulating RFI in hens during the late laying phase were found to beADCY2, ADCY8, CCKAR, ACSS2, FABP1, FABP4, and LysoPI (18:2(9Z,12Z)/0:0) in the liver. The levels of AST, HDL-C and ACTH in the serum were considered candidate markers influencing RFI. By conducting a microbiome-metabolome association analysis, we have identified the dominant and beneficial microbial community in the gut of LRFI groups, such asOscillospirales,Ruminococcaceae, andButyricicoccaceae, which offers a theoretical basis for understanding how the gut microbiota regulates RFI. These results will provide a scientific basis for the molecular mechanism of RFI phenotypic variation in late laying hens.
Theta transcranial alternating current stimulation is not effective in improving working memory performance
Authors: Kasanov Dauren , Dorogina Olga , Mushtaq Faisal , Pavlov Yuri G.
Published: March 2024

There is an extensive body of research showing a significant relationship between frontal midline theta activity in the 4-8 Hz range and working memory (WM) performance. Transcranial alternating current stimulation (tACS) is recognized for inducing lasting changes in brain oscillatory activity. Across two experiments, we tested whether WM could be improved through tACS of dorsomedial prefrontal cortex and anterior cingulate cortex, by affecting executive control networks associated with frontal midline theta. In Experiment 1, following either a 20-minute verum or sham stimulation applied to Fpz-CPz at 1 mA and 6 Hz, 31 participants performed WM tasks, while EEG was recorded. The tasks required participants to either mentally manipulate memory items or retain them in memory as they were originally presented. No significant effects were observed in behavioral performance, and we found no change in theta activity during rest and task following stimulation. However, alpha activity during retention or manipulation of information in WM was less strongly enhanced during the delay period following verum stimulation as compared with sham. In Experiment 2 (N = 25), tACS was administered during the task in two separate sessions. Here, we changed the order of the stimulation blocks: a 25-minute task block was either accompanied first by sham stimulation and then by verum stimulation, or vice versa. Again, we found no improvements in WM through either tACS after-effects or online stimulation. Taken together, our results demonstrate that theta frequency tACS applied at the midline is not an effective method for enhancing WM.
Assessment of DNA quality for whole genome library preparation
Authors: Jansson Linda , Fagerholm Siri Aili , Börkén Emelie , Gynnå Arvid Hedén , Sidstedt Maja , Forsberg Christina , Ansell Ricky , Hedman Johannes , Tillmar Andreas
Published: March 2024

In recent years, more sophisticated DNA technologies for genotyping have enabled considerable progress in various fields such as clinical genetics, archaeogenetics and forensic genetics. DNA samples previously rejected as too challenging to analyze due to low amounts of degraded DNA can now provide useful information. To increase the chances of success with the new methodologies, it is crucial to know the fragment size of the template DNA molecules, and whether the DNA in a sample is mostly single or double stranded. With this knowledge, an appropriate library preparation method can be chosen, and the DNA shearing parameters of the protocol can be adjusted to the DNA fragment size in the sample. In this study, we first developed and evaluated a user-friendly fluorometry-based protocol for estimation of DNA strandedness. We also evaluated different capillary electrophoresis methods for estimation of DNA fragmentation levels. Next, we applied the developed methodologies to a broad variety of DNA samples processed with different DNA extraction protocols. Our findings show that both the applied DNA extraction method and the sample type affect the DNA strandedness and fragmentation. The established protocols and the gained knowledge will be applicable for future sequencing-based high-density SNP genotyping in various fields.
mRNA display in cell lysates enables identification of cyclic peptides targeting the BRD3 extraterminal domain
Authors: Hurd Catherine A. , Bush Jacob T. , Powell Andrew J. , Walport Louise J.
Published: March 2024

mRNA display is a powerful technology to screen libraries of >1012cyclic peptides against a protein target, enabling the rapid discovery of high affinity ligands. These cyclic peptides are particularly well suited to challenging protein targets that have been difficult to drug with small molecules. However, target choice can still be limited as screens are typically performed against purified proteins which often demands the use of isolated domains and precludes the use of aggregation-prone targets. Here, we report a method to perform mRNA display selections in mammalian cell lysates without the need for prior target purification, vastly expanding the potential target scope of mRNA display. We have applied the methodology to identify low to sub-nanomolar peptide binders for two targets; a NanoLuc subunit (LgBiT) and full-length bromodomain-containing protein 3 (BRD3). Our cyclic peptides for BRD3 were found to bind to the extraterminal (ET) domain of BRD3 and the closely related BRD proteins, BRD2 and BRD4. While many chemical probes exist for the bromodomains of BRD proteins, the ET domain is relatively underexplored, making these peptides valuable additions to the BRD toolbox.
How clinically relevant are prostate cancer cell lines? A comprehensive characterisation and multiomics comparison
Authors: Ahmed Zahra , Mosabbir Warda , Tandon Devansh , Pereira Snehal Pinto , Cheema Umber , Loizidou Marilena , Withington John , Moore Caroline , Okoli Uzoamaka , Heavey Susan
Published: March 2024

Cell line experiments arguably remain the most used tool in preclinical cancer research, despite their limitations. With almost 95% drugs entering human trials failing, and up to 90% preclinical research failing before even being tested in humans, we must shift the pre-clinical paradigm. A range of in silico, in vitro, in vivo and ex vivo approaches are gaining popularity, with the aim of potentially replacing cell line use. However, we cannot ignore the plethora of historical data from cell lines, nor write off their future use– especially within advanced bioengineered models. Therefore, we must question if and how cell lines hold clinical relevance. This study evaluates the clinical characteristics of 46 prostate cancer cell lines against worldwide data and investigates the biological features of seven cell lines in depth, comparing them to over 10,000 well characterised human cases from 24 studies in nine countries. Clinical features compared included age, ethnicity, Gleason grade, cancer type, treatment history and multiomics variables included mutations, copy number alterations, structural variants, microsatellite instability, mRNA and protein expression, and tumour mutational burden. We found that the most used cell lines accurately represent a minute proportion of prostate cancer patients. Furthermore, we recommend a pipeline for tailoring selection of clinically relevant cell lines with the ultimate aim of increasing the scientific methodology behind choosing a cell line.
Bioorthogonal labeling and enrichment of histone monoaminylation reveal its accumulation and regulatory function in cancer cell chromatin
Authors: Zhang Nan , Wu Jinghua , Hossain Farzana , Peng Haidong , Li Huapeng , Gibson Connor , Chen Min , Zhang Huan , Gao Shuaixin , Zheng Xinru , Wang Yongdong , Zhu Jiangjiang , Wang Jing J. , Maze Ian , Zheng Qingfei
Published: March 2024

Histone monoaminylation (i.e., serotonylation and dopaminylation) is an emerging category of epigenetic mark occurring on the fifth glutamine (Q5) residue of H3 N-terminal tail, which plays significant roles in gene transcription. Current analysis of histone monoaminylation is mainly based on site-specific antibodies and mass spectrometry, which either lacks high resolution or is time-consuming. In this study, we report the development of chemical probes for bioorthogonal labeling and enrichment of histone serotonylation and dopaminylation. These probes were successfully applied for the monoaminylation analysis ofin vitrobiochemical assays, cells, and tissue samples. The enrichment of monoaminylated histones by the probes further confirmed the crosstalk between H3Q5 monoaminylation and H3K4 methylation. Finally, combining theex vivoandin vitroanalyses based on the developed probes, we have shown that both histone serotonylation and dopaminylation are highly enriched in tumor tissues that overexpress transglutaminase 2 (TGM2) and regulate the three-dimensional architecture of cellular chromatin.

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pSPObooster: a plasmid system to improve sporulation efficiency ofSaccharomyces cerevisiaelab strains
Authors: Loll-Krippleber Raphael , Jiang Yangyang Kate , Brown Grant W.
Published: March 2024

CommonS. cerevisiaelab yeast strains derived from S288C have meiotic defects and therefore are poor sporulators. Here, we developed a plasmid system containing corrected alleles of theMKT1andRME1genes to rescue the meiotic defects and show that standard BY4741 and BY4742 strains containing the plasmid display faster and more efficient sporulation. The plasmid, pSPObooster, can be maintained as an episome and easily cured or stably integrated into the genome at a single locus. We demonstrate the use of pSPObooster in low- and high-throughput yeast genetic manipulations and show that it can expedite both procedures without impacting strain behavior.

Take Away

pSPObooster contains corrected alleles orRME1andMKT1.

pSPObooster can be maintained as an episome or integrated.

pSPObooster increases sporulation efficiency by up to 13-fold.

pSPObooster can be used to speed up high-throughput yeast strain engineering.
New understanding of nuclei spectra properties observed by the AMS-02 experiment
Authors: Dong Xu-Lin , Yao Yu-Hua , Guo Yi-Qing , Cui Shu-Wang
Published: March 2024

The AMS-02 experiment has observed new properties of primary cosmic rays (CRs) categorized into two groups: He-C-O-Fe and Ne-Mg-Si-S, which are independent of CR propagation. In this study, we investigate the unexpected properties of these nuclei using a spatial propagation model. All nuclei spectra are accurately reproduced and separated into primary and secondary contributions. Our findings include: 1. Primary CR spectra are identical. 2. Our calculations align with AMS-02 results for primary-dominated nuclei within a 10% difference, but show significant discrepancies for the secondary-dominated nuclei. 3. The primary element abundance at around 200 GeV is presented and compared with previous solar and Galactic results. We hope that future DAMPE experiments can provide more experimental observational evidence to validate our model calculations.

Published by the American Physical Society
2024
Quantum Entangled States of a Classically Radiating Macroscopic Spin
Authors: Somech Ori , Shahmoon Ephraim
Published: March 2024

Entanglement constitutes a main feature that distinguishes quantum from classical physics. Here, however, we show that entanglement may also serve as the essential ingredient for the emergence of classical behavior in a radiating spin system. We consider the relation between the state of a macroscopic spin, such as an atomic ensemble, and the radiation it emits. We introduce a new class of macroscopic spin states, the coherently radiating spin states (CRSSs), defined as the asymptotic eigenstates of the SU(2) lowering operator. We find that a spin emitter in a CRSS radiates classical coherent light, although the CRSS itself is a quantum entangled state exhibiting spin squeezing. We further show that the CRSS is naturally realized in Dicke superradiance and underlies the dissipative Dicke phase transition, hence predicting the optimal scaling of spin squeezing in superradiance. More generally, the CRSS emerges as the ground state of a collective spin Hamiltonian. The CRSS thus provides a promising concept for studying many-body spin systems in various platforms, with applications ranging from quantum metrology and lasing to phase transitions.

Published by the American Physical Society
2024
DLSIA: Deep Learning for Scientific Image Analysis
Authors: Roberts Eric J. , Chavez Tanny , Hexemer Alexander , Zwart Petrus H.
Published: March 2024

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.
Wetting of alginate aerogels, from mesoporous solids to hydrogels: a small-angle scattering analysis
Authors: Balogh Zoltán , Kalmár József , Gommes Cedric J.
Published: March 2024

Mesoporous polysaccharide aerogels are versatile functional materials for drug delivery and wound dressing devices. The hydration and wetting of these aerogels control their application-related performance, e.g. the release of encapsulated drugs. Reported here is a detailed small-angle neutron scattering (SANS) analysis of the hydration mechanism of a calcium alginate aerogel, based on mathematical modelling of the scattering. The model accounts for the hierarchical structure of the material comprising a mesoporous structure, the solid skeleton of which is made up of water-swollen polymers. At large scale, the mesoporous structure is modelled as a random collection of elongated cylinders, which grow in size as they absorb water and aggregate. The small-scale inner structure of the skeleton is described as a Boolean model of polymer coils, which captures the progressive transition from a dense dry polymer to a fully hydrated gel. Using known physico-chemical characteristics of the alginate, the SANS data are fitted using the size of the cylinders as the only adjustable parameter. The alginate aerogel maintains a nanometre-scale, albeit altered, structure for low water contents but it collapses into micrometre-sized structures when the water content approaches one gram of water per gram of alginate. In addition to the wetting of aerogels, the model might be useful for the small-angle scattering analysis of the supercritical drying of gels.
Tomo Live: an on-the-fly reconstruction pipeline to judge data quality for cryo-electron tomography workflows
Authors: Comet Maxime , Dijkman Patricia M. , Boer Iwema Reint , Franke Tilman , Masiulis Simonas , Schampers Ruud , Raschdorf Oliver , Grollios Fanis , Pryor Edward E. , Drulyte Ieva
Published: March 2024

Data acquisition and processing for cryo-electron tomography can be a significant bottleneck for users. To simplify and streamline the cryo-ET workflow, Tomo Live, an on-the-fly solution that automates the alignment and reconstruction of tilt-series data, enabling real-time data-quality assessment, has been developed. Through the integration of Tomo Live into the data-acquisition workflow for cryo-ET, motion correction is performed directly after each of the acquired tilt angles. Immediately after the tilt-series acquisition has completed, an unattended tilt-series alignment and reconstruction into a 3D volume is performed. The results are displayed in real time in a dedicated remote web platform that runs on the microscope hardware. Through this web platform, users can review the acquired data (aligned stack and 3D volume) and several quality metrics that are obtained during the alignment and reconstruction process. These quality metrics can be used for fast feedback for subsequent acquisitions to save time. Parameters such as Alignment Accuracy, Deleted Tilts and Tilt Axis Correction Angle are visualized as graphs and can be used as filters to export only the best tomograms (raw data, reconstruction and intermediate data) for further processing. Here, the Tomo Live algorithms and workflow are described and representative results on several biological samples are presented. The Tomo Live workflow is accessible to both expert and non-expert users, making it a valuable tool for the continued advancement of structural biology, cell biology and histology.