bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlating fluorescence microscopy, optical and magnetic tweezers to study single chiral biopolymers such as DNA
Authors: Shepherd Jack W , Guilbaud Sebastien , Zhou Zhaokun , Howard Jamieson , Burman Matthew , Schaefer Charley , Kerrigan Adam , Steele-King Clare , Noy Agnes , Leake Mark C 
Published: January 2024

AbstractBiopolymer topology is critical for determining interactions inside cell environments, exemplified by DNA where its response to mechanical perturbation is as important as biochemical properties to its cellular roles. The dynamic structures of chiral biopolymers exhibit complex dependence with extension and torsion, however the physical mechanisms underpinning the emergence of structural motifs upon physiological twisting and stretching are poorly understood due to technological limitations in correlating force, torque and spatial localization information. We present COMBI-Tweez (Combined Optical and Magnetic BIomolecule TWEEZers), a transformative tool that overcomes these challenges by integrating optical trapping, time-resolved electromagnetic tweezers, and fluorescence microscopy, demonstrated on single DNA molecules, that can controllably form and visualise higher order structural motifs including plectonemes. This technology combined with cutting-edge MD simulations provides quantitative insight into complex dynamic structures relevant to DNA cellular processes and can be adapted to study a range of filamentous biopolymers.
A robust and inducible precise genome editing via an all-in-one prime editor in human pluripotent stem cells
Authors: Wu Youjun , Zhong Aaron , Sidharta Mega , Kim Tae Wan , Ramirez Bernny , Persily Benjamin , Studer Lorenz , Zhou Ting 
Published: January 2024

AbstractPrime editing (PE) allows for precise genome editing in human pluripotent stem cells (hPSCs), such as introducing single nucleotide modifications, small deletions, or insertions at a specific genomic locus, a strategy that shows great promise for creating “Disease in a dish” models. To improve the effectiveness of prime editing in hPSCs, we systematically compared and combined the “inhibition of mismatch repair pathway and p53” on top of the “PEmax” to generate an all-in-one “PE-Plus” prime editor. We show that PE-Plus conducts the most efficient editing among the current PE tools in hPSCs. We further established an inducible prime editing platform in hPSCs by incorporating the all-in-one PE vector into a safe-harbor locus and demonstrated temporal control of precise editing in both hPSCs and differentiated cells. By evaluating disease-associated mutations, we show that this platform allows efficient creation of both monoallelic and biallelic disease-relevant mutations in hPSCs. In addition, this platform enables the efficient introduction of single or multiple edits in one step, demonstrating potential for multiplex editing. Therefore, our method presents an efficient and controllable multiplex prime editing tool in hPSCs and their differentiated progeny.
Self-Supervised Transformer Model Training for a Sleep-EEG Foundation Model
Authors: Ogg Mattson , Coon William G. 
Published: January 2024

AbstractThe American Academy of Sleep Medicine (AASM) recognizes five sleep/wake states (Wake, N1, N2, N3, REM), yet this classification schema provides only a high-level summary of sleep and likely overlooks important neurological or health information. New, data-driven approaches are needed to more deeply probe the information content of sleep signals. Here we present a self-supervised approach that learns the structure embedded in large quantities of neurophysiological sleep data. This masked transformer training procedure is inspired by high performing self-supervised methods developed for speech transcription. We show that self-supervised pre-training matches or outperforms supervised sleep stage classification, especially when labeled data or compute-power is limited. Perhaps more importantly, we also show that our pre-trained model is flexible and can be fine-tuned to perform well on new EEG recording montages not seen in training, and for new tasks including distinguishing individuals or quantifying “brain age” (a potential health biomarker). This suggests that modern methods can automatically learn information that is potentially overlooked by the 5-class sleep staging schema, laying the groundwork for new sleep scoring schemas and further data-driven exploration of sleep.
Laying the Foundation: Modern Transformers for Gold-Standard Sleep Analysis and Beyond
Authors: Coon William G. , Ogg Mattson 
Published: January 2024

AbstractAccurate sleep assessment is critical to the practice of sleep medicine and sleep research. The recent availability of large quantities of publicly available sleep data, alongside recent breakthroughs in AI like transformer architectures, present novel opportunities for data-driven discovery efforts. Transformers are flexible neural networks that not only excel at classification tasks, but also can enable data-driven discovery through un-or self-supervised learning, which requires no human annotations to the input data. While transformers have been extensively used in supervised learning scenarios for sleep stage classification, they have not been fully explored or optimized in forms designed from the ground up for use in un-or self-supervised learning tasks in sleep. A necessary first step will be to study these models on a canonical benchmark supervised learning task (5-class sleep stage classification). Hence, to lay the groundwork for future data-driven discovery efforts, we evaluated optimizations of a transformer-based architecture that has already demonstrated substantial success in self-supervised learning in another domain (audio speech recognition), and trained it to perform the canonical 5-class sleep stage classification task, to establish foundational baselines in the sleep domain. We found that small transformer models designed from the start for (later) self-supervised learning can match other state-of-the-art automated sleep scoring techniques, while also providing the basis for future data-driven discovery efforts using large sleep data sets.
Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change
Authors: Copperman Jeremy , Mclean Ian C. , Gross Sean M. , Singh Jalim , Chang Young Hwan , Zuckerman Daniel M. , Heiser Laura M. 
Published: January 2024

AbstractExtracellular signals induce changes to molecular programs that modulate multiple cellular phenotypes, including proliferation, motility, and differentiation status. The connection between dynamically adapting phenotypic states and the molecular programs that define them is not well understood. Here we develop data-driven models of single-cell phenotypic responses to extracellular stimuli by linking gene transcription levels to “morphodynamics” – changes in cell morphology and motility observable in time-lapse image data. We adopt a dynamics-first view of cell state by grouping single-cell trajectories into states with shared morphodynamic responses. The single-cell trajectories enable development of a first-of-its-kind computational approach to map live-cell dynamics to snapshot gene transcript levels, which we term MMIST, Molecular and Morphodynamics-Integrated Single-cell Trajectories. The key conceptual advance of MMIST is that cell behavior can be quantified based on dynamically defined states and that extracellular signals alter the overall distribution of cell states by altering rates of switching between states. We find a cell state landscape that is bound by epithelial and mesenchymal endpoints, with distinct sequences of epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET) intermediates. The analysis yields predictions for gene expression changes consistent with curated EMT gene sets and provides a prediction of thousands of RNA transcripts through extracellular signal-induced EMT and MET with near-continuous time resolution. The MMIST framework leverages true single-cell dynamical behavior to generate molecular-level omics inferences and is broadly applicable to other biological domains, time-lapse imaging approaches and molecular snapshot data.SummaryEpithelial cells change behavior and state in response to signals, which is necessary for the function of healthy tissue, while aberrant responses can drive diseases like cancer. To decode and potentially steer these responses, there is a need to link live-cell behavior to molecular programs, but high-throughput molecular measurement is generally destructive or requires fixation. Here we present a novel method which connects single-cell morphology and motility over time to bulk molecular readouts. Our model predicts gene expression from the observation of label-free live-cell imaging, as a step toward understanding and ultimately controlling cell state change.
Evaluation of the potential food allergy risks of recombinant human lactoferrin expressed inKomagataella phaffii
Authors: Anaya Yanisa , Rosario Martinez Raysa , Goodman Richard E. , Johnson Philip , Vajpeyi Shashwat , Lu Xiaoning , Peterson Ross , Weyers Sarah M. , Breen Bella , Newsham Kahler , Scottoline Brian , Clark Anthony , Malinczak Carrie-Anne 
Published: January 2024

ABSTRACTPrior to the introduction of novel food ingredients into the food supply, safety risk assessments are required, and numerous prediction models have been developed and validated to evaluate safety. The allergenic risk potential of Helaina recombinant human lactoferrin (rhLF, Effera™), produced inKomagataella phaffii(K. phaffii) was assessed by literature search, bioinformatics sequence comparisons to known allergens, glycan allergenicity assessment, and a simulated pepsin digestion model. The literature search identified no allergenic risk for Helaina rhLF,K. phaffii, or its glycans. Bioinformatics search strategies showed no significant risk for cross-reactivity or allergenicity between rhLF or the 36 residual host proteins and known human allergens. Helaina rhLF was also rapidly digested in simulated gastric fluid and its digestibility profile was comparable to human milk lactoferrin (hmLF), further demonstrating a low allergenic risk and similarity to the hmLF protein. Collectively, these results demonstrate a low allergenic risk potential of Helaina rhLF and do not indicate the need for further clinical testing or serum IgE binding to evaluate Helaina rhLF for risk of food allergy prior to introduction into the food supply.
Characterization of transcriptional heterogeneity and novel therapeutic targets using single cell RNA-sequencing of primary and circulating Ewing sarcoma cells
Authors: Goodspeed Andrew , Bodlak Avery , Duffy Alexis B. , Nelson-Taylor Sarah , Oike Naoki , Porfilio Timothy , Shirai Ryota , Walker Deandra , Treece Amy , Black Jennifer , Donaldson Nathan , Cost Carrye , Garrington Tim , Greffe Brian , Luna-Fineman Sandra , Demedis Jenna , Lake Jessica , Danis Etienne , Verneris Michael , Adams Daniel L , Hayashi Masanori 
Published: January 2024

AbstractEwing sarcoma is the second most common bone cancer in children, accounting for 2% of pediatric cancer diagnoses. Patients who present with metastatic disease at the time of diagnosis have a dismal prognosis, compared to the >70% 5-year survival of those with localized disease. Here, we utilized single cell RNA-sequencing to characterize the transcriptional landscape of primary Ewing sarcoma tumors and surrounding tumor microenvironment (TME). Copy-number analysis identified subclonal evolution within patients prior to treatment. Primary tumor samples demonstrate a heterogenous transcriptional landscape with several conserved gene expression programs, including those composed of genes related to proliferation and EWS targets. Single cell RNA-sequencing and immunofluorescence of circulating tumor cells at the time of diagnosis identified TSPAN8 as a novel therapeutic target.
Fluorescent tools for the standardized work in Gram-negative bacteria
Authors: Delgadillo-Guevara Mario , Halte Manuel , Erhardt Marc , Popp Philipp F. 
Published: January 2024

AbstractStandardized and thoroughly characterized genetic tools are a prerequisite for studying cellular processes to ensure the reusability and consistency of experimental results. The discovery of fluorescent proteins (FPs) represents a milestone in the development of genetic reporters for monitoring transcription or protein localizationin vivo. FPs have revolutionized our understanding of cellular dynamics by enabling the real-time visualization and tracking of biological processes. Despite these advancements, challenges remain in the appropriate use of FPs, specifically regarding their proper application, protein turnover dynamics, and the undesired disruption of cellular functions. Here, we systematically compared a comprehensive set of 16 FPs and assessed their performancein vivoby focusing on key parameters, such as signal over background ratios and protein stability rates, using the gram-negative model organismSalmonella entericaas a representative host. We evaluated four protein degradation tags in both plasmid- and genome-based systems and our findings highlight the necessity of introducing degradation tags to analyze time-sensitive cellular processes. We demonstrate that the gain of dynamics mediated by the addition of degradation tags impacts the cell-to-cell heterogeneity of plasmid-based but not genome-based reporters. Finally, we probe the applicability of FPs for protein localization studies in living cells using super-resolution microscopy. In summary, our study underscores the importance of careful FP selection and paves the way for the development of improved genetic reporters to enhance the reproducibility and reliability of fluorescence-based research in gram- negative bacteria and beyond.
Counter-balancing X-linkedMecp2hypofunction by hyperfunction ameliorates disease features in a model of Rett syndrome: implications for genetic therapies
Authors: McGraw Christopher M , Soriano Sirena , Shuang Hao , Connolly Daniel R , Chahrour Ali , Wu Zhenyu , Liang Agnes J , Sun Yaling , Tang Jianrong , Samaco Rodney C 
Published: January 2024

ABSTRACTTreating monogenic neurodevelopmental disorders remains challenging and mostly symptomatic. X-linked disorders affecting women such as the postnatal neurodevelopmental disorder Rett syndrome (caused by mutations in the geneMECP2) have additional challenges due to dosage sensitivity and to cellular mosaicism caused by random X-chromosome inactivation. An approach to augmentMECP2expression from wild-type cells in RTT may be feasible and simpler than gene replacement but has never been tested due to known toxicity ofMECP2over-expression, as evidenced by the distinct neurological condition known asMECP2Duplication Syndrome. Here, using genetic techniques, we find that “counter-balancing”Mecp2-null cells in femaleMecp2-null/+ mice by a complementary population of cells harboring an X-linked transgene associated with 3X normal levels ofMECP2leads to normalization of multiple whole animal phenotypic outcomes without noticeable toxicity. In addition,in vivoLFP recordings demonstrate that counter-balancingMecp2loss-of-function improves select within-region and between-region abnormalities. By comparing the counter-balance approach with an approach based on cell autonomous restoration of MeCP2 using an autosomal transgene expressing 2X normal levels ofMECP2in all cells (mimicking gene replacement), we identify neurobehavioral and electrographic features best suited for preclinical biomarkers of a therapeutic response to cell autonomous versus non-cell autonomous correction. Notably, these proof-of-concept findings demonstrate how non-cell autonomous suppression of MeCP2 deficiency by boosting overall wild-type MeCP2 levels may be a viable disease-modifying therapy for RTT, with potential implications for genetic-based therapies of monogenic X-linked disorders.One Sentence SummaryIn a mouse model of Rett syndrome, counterbalancing mosaic LOF with complementary mosaic GOF improves phenotypic outcome.
Effects of High Fat Diet on Metabolic Health Vary by Age of Menopause Onset
Authors: Salinero Abigail E. , Venkataganesh Harini , Abi-Ghanem Charly , Riccio David , Kelly Richard D. , Gannon Olivia J. , Sura Avi , Brooks Heddwen L. , Zuloaga Kristen L. 
Published: January 2024

ABSTRACTMenopause accelerates metabolic dysfunction, including (pre-)diabetes, obesity and visceral adiposity. However, the effects of endocrine vs. chronological aging in this progression are poorly understood. We hypothesize that menopause, especially in the context of middle-age, will exacerbate the metabolic effects of a high fat diet. Using young-adult and middle-aged C57BL/6J female mice, we modeled diet-induce obesity via chronic administration of high fat (HF) diet vs. control diet. We modeled peri-menopause/menopause via injections of 4-vinylcyclohexene diepoxide, which accelerates ovarian failure vs. vehicle. We performed glucose tolerance tests 2.5 and 7 months after diet onset, during the peri-menopausal and menopausal phases, respectively. Peri-menopause increased the severity of glucose intolerance and weight gain in middle-aged, HF-fed mice. Menopause increased weight gain in all mice regardless of age and diet, while chronological aging drove changes in adipose tissue distribution towards more visceral vs. subcutaneous adiposity. These data are in line with clinical data showing that post-menopausal women are more susceptible to metabolic dysfunction and suggest that greater chorological age exacerbates the effects of endocrine aging (menopause). This work highlights the importance of considering both chronological and endocrine aging in studies of metabolic health.
Δ9-tetrahydrocannabinol (THC) Increases the Rewarding Value of Oxycodone During Self-Administration in Rats
Authors: Nguyen Jacques D. , Grant Yanabel , Yang Celine , Taffe Michael A. 
Published: January 2024

AbstractBackgroundCannabis may reduce the nonmedical use of prescription opioids. Causality of polydrug use is difficult to establish from epidemiological data, and thus controlled laboratory models can test whether cannabinoid co-use with opioids can modulate opioid intake.MethodsMale and female rats were trained to intravenously self-administer (IVSA) oxycodone (0.15 mg/kg/infusion) during 6 h sessions. Separate groups were injected with the vehicle or with THC (5 mg/kg, i.p.; N=10) 30 minutes before sessions for the first three weeks. Treatments were swapped in the fourth week. One male group was trained in the intracranial self-stimulation (ICSS) procedure and assessed for brain reward thresholds prior to each IVSA session.ResultsTHC treated animals self-administered less oxycodone during acquisition, with a larger differential expressed in the female group. Tolerance to the THC effect developed over the initial weeks, and increasing the dose of THC (10 mg/kg, i.p.) prolonged the suppressing effect on IVSA. While ICSS thresholds increased with sequential IVSA sessions, no differences between THC- and Vehicle-treated groups were observed. Oxycodone IVSA was increased following the first 60 h abstinence interval in THC-treated, but not vehicle-treated, rats. Acute injection of THC, when all animals had been THC abstinent for several weeks,increasedbreakpoints in a Progressive Ratio procedure.ConclusionThese data support the interpretation that THC enhances the reinforcing efficacy of a given dose of oxycodone and may therefore increase the addiction liability.
Sac1 links phosphoinositide turnover to cryptococcal virulence
Authors: Gaylord Elizabeth A. , Choy Hau Lam , Chen Guohua , Briner Sydney L. , Doering Tamara L. 
Published: January 2024

ABSTRACTCryptococcus neoformansis an environmentally-acquired fungal pathogen that causes over 140,000 deaths per year. Cryptococcal infection occurs when infectious particles are deposited into the lung, where they encounter host phagocytic cells.C. neoformansmay be engulfed by these phagocytes, an important step of infection that leads to outcomes ranging from termination of infection to cryptococcal dissemination. To study this critical process, we screened approximately 4,700 cryptococcal gene deletion mutants for altered uptake, using primary mouse and human phagocytic cells. Among the hits of these two screens, we identified 93 mutants with perturbed uptake in both systems, as well as others with differences in uptake by only one cell type. We further screened the hits for changes in thickness of the capsule, a protective polysaccharide layer around the cell which is an important cryptococcal virulence factor. The combination of our three screens yielded 45 mutants, including one lacking the phosphatidylinositol-4-phosphate phosphatase Sac1. In this work, we implicate Sac1 in both host cell uptake and capsule production. We found thatsac1mutants exhibit lipid trafficking defects, reductions in secretory system function, and changes in capsule size and composition. Many of these changes occur specifically in tissue culture media, highlighting the role of Sac1 phosphatase activity in responding to the stress of host-like conditions. Overall, these findings show how genome-scale screening can identify cellular factors that contribute to our understanding of cryptococcal biology and demonstrate the role of Sac1 in determining fungal virulence.IMPORTANCECryptococcus neoformansis a fungal pathogen with significant impact on global health. Cryptococcal cells inhaled from the environment are deposited into the lungs, where they first contact the human immune system. The interaction betweenC. neoformansand host cells is critical because this step of infection can determine whether the fungal cells die or proliferate within the human host. Despite the importance of this stage of infection, we have limited knowledge of cryptococcal factors that influence its outcome. In this study, we identify cryptococcal genes that affect uptake by both human and mouse cells. We also identify mutants with altered capsule, a protective coating that surrounds the cells to shield them from the host immune system. Finally, we characterize the role of one gene,SAC1, in these processes. Overall, this study contributes to our understanding of howC. neoformansinteracts with and protects itself from host cells.
Intranasally Administered EVs from hiPSC-derived NSCs Alter the Transcriptomic Profile of Activated Microglia and Conserve Brain Function in an Alzheimer’s Model
Authors: Madhu Leelavathi N , Kodali Maheedhar , Upadhya Raghavendra , Rao Shama , Shuai Bing , Somayaji Yogish , Attaluri Sahithi , Kirmani Maha , Gupta Shreyan , Maness Nathaniel , Rao Xiaolan , Cai James , Shetty Ashok K. 
Published: January 2024

AbstractAntiinflammatory extracellular vesicles (EVs) derived from human induced pluripotent stem cell (hiPSC)-derived neural stem cells (NSCs) hold promise as a disease-modifying biologic for Alzheimer’s disease (AD). This study directly addressed this issue by examining the effects of intranasal administrations of hiPSC-NSC-EVs to 3-month-old 5xFAD mice. The EVs were internalized by all microglia, which led to reduced expression of multiple genes associated with disease-associated microglia, inflammasome, and interferon-1 signaling. Furthermore, the effects of hiPSC-NSC-EVs persisted for two months post-treatment in the hippocampus, evident from reduced microglial clusters, inflammasome complexes, and expression of proteins and/or genes linked to the activation of inflammasomes, p38/mitogen-activated protein kinase, and interferon-1 signaling. The amyloid-beta (Aβ) plaques, Aβ-42, and phosphorylated-tau concentrations were also diminished, leading to better cognitive and mood function in 5xFAD mice. Thus, early intervention with hiPSC-NSC-EVs in AD may help maintain better brain function by restraining the progression of adverse neuroinflammatory signaling cascades.