Conserved transcriptional connectivity of regulatory T cells in the tumor microenvironment informs new combination cancer therapy strategies.

While regulatory T (Treg) cells are traditionally viewed as professional suppressors of antigen presenting cells and effector T cells in both autoimmunity and cancer, recent findings of distinct Treg cell functions in tissue maintenance suggest that their regulatory purview extends to a wider range of cells and is broader than previously assumed. To elucidate tumoral Treg cell 'connectivity' to diverse tumor-supporting accessory cell types, we explored immediate early changes in their single-cell transcriptomes upon punctual Treg cell depletion in experimental lung cancer and injury-induced inflammation. Before any notable T cell activation and inflammation, fibroblasts, endothelial and myeloid cells exhibited pronounced changes in their gene expression in both cancer and injury settings. Factor analysis revealed shared Treg cell-dependent gene programs, foremost, prominent upregulation of VEGF and CCR2 signaling-related genes upon Treg cell deprivation in either setting, as well as in Treg cell-poor versus Treg cell-rich human lung adenocarcinomas. Accordingly, punctual Treg cell depletion combined with short-term VEGF blockade showed markedly improved control of PD-1 blockade-resistant lung adenocarcinoma progression in mice compared to the corresponding monotherapies, highlighting a promising factor-based querying approach to elucidating new rational combination treatments of solid organ cancers.

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.

Single-cell RNA sequencing technologies suffer from many sources of technical noise, including under-sampling of mRNA molecules, often termed "dropout," which can severely obscure important gene-gene relationships. To address this, we developed MAGIC (Markov affinity-based graph imputation of cells), a method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. We validate MAGIC on several biological systems and find it effective at recovering gene-gene relationships and additional structures. Applied to the epithilial to mesenchymal transition, MAGIC reveals a phenotypic continuum, with the majority of cells residing in intermediate states that display stem-like signatures, and infers known and previously uncharacterized regulatory interactions, demonstrating that our approach can successfully uncover regulatory relations without perturbations.

Natural Genetic Variation Reveals Key Features of Epigenetic and Transcriptional Memory in Virus-Specific CD8 T Cells.

Stable changes in chromatin states and gene expression in cells of the immune system form the basis for memory of infections and other challenges. Here, we used naturally occurring cis-regulatory variation in wild-derived inbred mouse strains to explore the mechanisms underlying long-lasting versus transient gene regulation in CD8 T cells responding to acute viral infection. Stably responsive DNA elements were characterized by dramatic and congruent chromatin remodeling events affecting multiple neighboring sites and required distinct transcription factor (TF) binding motifs for their accessibility. Specifically, we found that cooperative recruitment of T-box and Runx family transcription factors to shared targets mediated stable chromatin remodeling upon T cell activation. Our observations provide insights into the molecular mechanisms driving virus-specific CD8 T cell responses and suggest a general mechanism for the formation of transcriptional and epigenetic memory applicable to other immune and non-immune cells.

Negative Co-stimulation Constrains T Cell Differentiation by Imposing Boundaries on Possible Cell States.

Co-stimulation regulates T cell activation, but it remains unclear whether co-stimulatory pathways also control T cell differentiation. We used mass cytometry to profile T cells generated in the genetic absence of the negative co-stimulatory molecules CTLA-4 and PD-1. Our data indicate that negative co-stimulation constrains the possible cell states that peripheral T cells can acquire. CTLA-4 imposes major boundaries on CD4+ T cell phenotypes, whereas PD-1 subtly limits CD8+ T cell phenotypes. By computationally reconstructing T cell differentiation paths, we identified protein expression changes that underlied the abnormal phenotypic expansion and pinpointed when lineage choice events occurred during differentiation. Similar alterations in T cell phenotypes were observed after anti-CTLA-4 and anti-PD-1 antibody blockade. These findings implicate negative co-stimulation as a key regulator and determinant of T cell differentiation and suggest that checkpoint blockade might work in part by altering the limits of T cell phenotypes.

The emergent landscape of the mouse gut endoderm at single-cell resolution.

Here we delineate the ontogeny of the mammalian endoderm by generating 112,217 single-cell transcriptomes, which represent all endoderm populations within the mouse embryo until midgestation. We use graph-based approaches to model differentiating cells, which provides a spatio-temporal characterization of developmental trajectories and defines the transcriptional architecture that accompanies the emergence of the first (primitive or extra-embryonic) endodermal population and its sister pluripotent (embryonic) epiblast lineage. We uncover a relationship between descendants of these two lineages, in which epiblast cells differentiate into endoderm at two distinct time points-before and during gastrulation. Trajectories of endoderm cells were mapped as they acquired embryonic versus extra-embryonic fates and as they spatially converged within the nascent gut endoderm, which revealed these cells to be globally similar but retain aspects of their lineage history. We observed the regionalized identity of cells along the anterior-posterior axis of the emergent gut tube, which reflects their embryonic or extra-embryonic origin, and the coordinated patterning of these cells into organ-specific territories.

Mechanistic insight into the functional role of human sinoatrial node conduction pathways and pacemaker compartments heterogeneity: A computer model analysis.

The sinoatrial node (SAN), the primary pacemaker of the heart, is responsible for the initiation and robust regulation of sinus rhythm. 3D mapping studies of the ex-vivo human heart suggested that the robust regulation of sinus rhythm relies on specialized fibrotically-insulated pacemaker compartments (head, center and tail) with heterogeneous expressions of key ion channels and receptors. They also revealed up to five sinoatrial conduction pathways (SACPs), which electrically connect the SAN with neighboring right atrium (RA). To elucidate the role of these structural-molecular factors in the functional robustness of human SAN, we developed comprehensive biophysical computer models of the SAN based on 3D structural, functional and molecular mapping of ex-vivo human hearts. Our key finding is that the electrical insulation of the SAN except SACPs, the heterogeneous expression of If, INa currents and adenosine A1 receptors (A1R) across SAN pacemaker-conduction compartments are required to experimentally reproduce observed SAN activation patterns and important phenomena such as shifts of the leading pacemaker and preferential SACP. In particular, we found that the insulating border between the SAN and RA, is required for robust SAN function and protection from SAN arrest during adenosine challenge. The heterogeneity in the expression of A1R within the human SAN compartments underlies the direction of pacemaker shift and preferential SACPs in the presence of adenosine. Alterations of INa current and fibrotic remodelling in SACPs can significantly modulate SAN conduction and shift the preferential SACP/exit from SAN. Finally, we show that disease-induced fibrotic remodeling, INa suppression or increased adenosine make the human SAN vulnerable to pacing-induced exit blocks and reentrant arrhythmia. In summary, our computer model recapitulates the structural and functional features of the human SAN and can be a valuable tool for investigating mechanisms of SAN automaticity and conduction as well as SAN arrhythmia mechanisms under different pathophysiological conditions.

Evaluating the impact of biodiversity offsetting on native vegetation.

Biodiversity offsetting is a globally influential policy mechanism for reconciling trade-offs between development and biodiversity loss. However, there is little robust evidence of its effectiveness. We evaluated the outcomes of a jurisdictional offsetting policy (Victoria, Australia). Offsets under Victoria's Native Vegetation Framework (2002-2013) aimed to prevent loss and degradation of remnant vegetation, and generate gains in vegetation extent and quality. We categorised offsets into those with near-complete baseline woody vegetation cover ("avoided loss", 2702 ha) and with incomplete cover ("regeneration", 501 ha), and evaluated impacts on woody vegetation extent from 2008 to 2018. We used two approaches to estimate the counterfactual. First, we used statistical matching on biophysical covariates: a common approach in conservation impact evaluation, but which risks ignoring potentially important psychosocial confounders. Second, we compared changes in offsets with changes in sites that were not offsets for the study duration but were later enrolled as offsets, to partially account for self-selection bias (where landholders enrolling land may have shared characteristics affecting how they manage land). Matching on biophysical covariates, we estimated that regeneration offsets increased woody vegetation extent by 1.9%-3.6%/year more than non-offset sites (138-180 ha from 2008 to 2018) but this effect weakened with the second approach (0.3%-1.9%/year more than non-offset sites; 19-97 ha from 2008 to 2018) and disappeared when a single outlier land parcel was removed. Neither approach detected any impact of avoided loss offsets. We cannot conclusively demonstrate whether the policy goal of 'net gain' (NG) was achieved because of data limitations. However, given our evidence that the majority of increases in woody vegetation extent were not additional (would have happened without the scheme), a NG outcome seems unlikely. The results highlight the importance of considering self-selection bias in the design and evaluation of regulatory biodiversity offsetting policy, and the challenges of conducting robust impact evaluations of jurisdictional biodiversity offsetting policies.

Evaluating the impact of private land conservation with synthetic control design.

Programs to protect biodiversity on private land are increasingly being used worldwide. To understand the efficacy of such programs, it is important to determine their impact: the difference between the program's outcome and what would have happened without the program. Typically, these programs are evaluated by estimating the average program-level impact, which readily allows comparisons between programs or regions, but masks important heterogeneity in impact across the individual conservation interventions. We used synthetic control design, statistical matching, and time-series data to estimate the impact of individual protected areas over time and combined individual-level impacts to estimate program-level impact with a meta-analytic approach. We applied the method to private protected areas governed by conservation covenants (legally binding on-title agreements to protect biodiversity) in the Goldfields region of Victoria, Australia using woody vegetation cover as our outcome variable. We compared our results with traditional approaches to estimating program-level impact based on a subset of covenants that were the same age. Our results showed an overall program-level impact of a 0.3-0.8% increase in woody vegetation cover per year. However, there was significant heterogeneity in the temporal pattern of impact for individual covenants, ranging from -4 to +7% change in woody vegetation cover per year. Results of our approach were consistent with results based on traditional approaches to estimating program-level impact. Our study provides a transparent and robust workflow to estimate individual and program-level impacts of private protected areas.

Evaluación del impacto del suelo privado de conservación con diseño de control sintético Resumen Los programas de protección de la biodiversidad en suelo privado se utilizan cada vez más en todo el mundo. Para entender la eficacia de estos programas, es importante determinar la diferencia entre el resultado del programa y lo que habría ocurrido sin él. Normalmente, estos programas se evalúan estimando el impacto medio a nivel de programa, lo que permite fácilmente las comparaciones entre programas o regiones, pero oculta una importante heterogeneidad en el impacto entre las intervenciones individuales de conservación. Utilizamos un diseño de control sintético, un emparejamiento estadístico y datos de series temporales para estimar el impacto de las áreas protegidas individuales a lo largo del tiempo y combinamos los impactos a nivel individual para estimar el impacto a nivel de programa con un enfoque meta-analítico. Aplicamos el método a áreas protegidas privadas regidas por acuerdos de conservación (acuerdos con vínculos jurídicos sobre la titularidad para proteger la biodiversidad) destinados a mejorar la cubierta vegetal leñosa en la región de Goldfields de Victoria, Australia. Comparamos nuestros resultados con los métodos tradicionales de estimación del impacto a nivel de programa basados en un subconjunto de pactos de la misma antigüedad. Nuestros resultados mostraron un impacto global a nivel de programa de un aumento del 0.3-0.8% de la cubierta vegetal leñosa al año. Sin embargo, hubo una heterogeneidad significativa en el patrón temporal del impacto para los pactos individuales, que osciló entre −4 y +7% de cambio en la cubierta vegetal leñosa por año. Los resultados de nuestra estrategia fueron consecuentes con los resultados basados en las estrategias tradicionales usadas para estimar el impacto a nivel de programa. Nuestro estudio proporciona un flujo de trabajo transparente y sólido para estimar el impacto individual a nivel de programa de las áreas protegidas privadas.

Combination anti-CTLA-4 plus anti-PD-1 checkpoint blockade utilizes cellular mechanisms partially distinct from monotherapies.

Immune checkpoint blockade therapy targets T cell-negative costimulatory molecules such as cytotoxic T lymphocyte antigen-4 (CTLA-4) and programmed cell death-1 (PD-1). Combination anti-CTLA-4 and anti-PD-1 blockade therapy has enhanced efficacy, but it remains unclear through what mechanisms such effects are mediated. A critical question is whether combination therapy targets and modulates the same T cell populations as monotherapies. Using a mass cytometry-based systems approach, we comprehensively profiled the response of T cell populations to monotherapy and combination anti-CTLA-4 plus anti-PD-1 therapy in syngeneic murine tumors and clinical samples. Most effects of monotherapies were additive in the context of combination therapy; however, multiple combination therapy-specific effects were observed. Highly phenotypically exhausted cluster of differentiation 8 (CD8) T cells expand in frequency following anti-PD-1 monotherapy but not combination therapy, while activated terminally differentiated effector CD8 T cells expand only following combination therapy. Combination therapy also led to further increased frequency of T helper type 1 (Th1)-like CD4 effector T cells even though anti-PD-1 monotherapy is not sufficient to do so. Mass cytometry analyses of peripheral blood from melanoma patients treated with immune checkpoint blockade therapies similarly revealed mostly additive effects on the frequencies of T cell subsets along with unique modulation of terminally differentiated effector CD8 T cells by combination ipilimumab plus nivolumab therapy. Together, these findings indicate that dual blockade of CTLA-4 and PD-1 therapy is sufficient to induce unique cellular responses compared with either monotherapy.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

OBJECTIVE: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma). METHODS: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis). RESULTS: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts. CONCLUSION: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.

Mapping CRISPR-Cas9 public and commercial innovation using The Lens institutional toolkit.

CRISPR-Cas9 is a revolutionary technology because it is precise, fast and easy to implement, cheap and components are readily accessible. This versatility means that the technology can deliver a timely end product and can be used by many stakeholders. In plant cells, the technology can be applied to knockout genes by using CRISPR-Cas nucleases that can alter coding gene regions or regulatory elements, alter precisely a genome by base editing to delete or regulate gene expression, edit precisely a genome by homology-directed repair mechanism (cellular DNA), or regulate transcriptional machinery by using dead Cas proteins to recruit regulators to the promoter region of a gene. All these applications can be for: 1) Research use (Non commercial), 2) Uses related product components for the technology itself (reagents, equipment, toolkits, vectors etc), and 3) Uses related to the development and sale of derived end products based on this technology. In this contribution, we present a prototype report that can engage the community in open, inclusive and collaborative innovation mapping. Using the open data at the Lens.org platform and other relevant sources, we tracked, analyzed, organized, and assembled contextual and bridged patent and scholarly knowledge about CRISPR-Cas9 and with the assistance of a new Lens institutional capability, The Lens Report Builder, currently in beta release, mapped the public and commercial innovation pathways of the technology. When scaled, this capability will also enable coordinated editing and curation by credentialed experts to inform policy makers, businesses and private or public investment.

Simulating urban expansion in a rapidly changing landscape in eastern Tarai, Nepal.

Understanding the spatiotemporal dynamics of urbanization and predicting future growth is now essential for sustainable urban planning and policy making. This study explores future urban expansion in the rapidly growing region of eastern lowland Nepal. We used the hybrid cellular automata-Markov (CA-Markov) model, which utilizes historical land use and land cover (LULC) maps and several biophysical change driver variables to predict urban expansion for the years 2026 and 2036. Transitional area matrices were generated based on historical LULC data from 1996 to 2006, from 2006 to 2016, and from 1996 to 2016. The approach was validated by cross comparing the actual and simulated maps for 2016. Evaluation gave satisfactory values of Kno (0.89), Kstandard (0.84), and Klocation (0.89) which verifies the accuracy of the model. Hence, the CA-Markov model was utilized to simulate the LULC map for the years 2026 and 2036. The study area experienced rapid peri/urban expansion and sharp decline in area of cultivated land during 1989-2016. Built-up area increased by 110.90 km2 over a period of 27 years at the loss of 87.59 km2 cultivated land. Simulation analysis indicates that urban expansion will continue with urban cover increasing to 230 km2 (8.95%) and 318.51 km2 (12.45%) by 2026 and 2036, respectively, with corresponding declines in cultivated land to 1453.83 km2 (56.86%) and 1374.93 km2 (53.77%) for the same years. The alarming increase in urban areas coupled with loss of cultivated land will have negative implications for food security and environmental equilibrium in the region.

Molecular detection of Listeria monocytogenes from different dairy and street food sources in North Karnataka, India.

BACKGROUND: Food-borne pathogen Listeria monocytogenes is abundantly present in nature and accountable for sporadic and epidemic cases of listeriosis in humans. The objective of this study was to screen common food sources for L. monocytogenes using biochemical and molecular methods to detect and characterise its toxin genes as well as for biofilm formation. METHODS: A total of 92 samples, comprising dairy and street food products, were randomly collected from various sources for this investigation. The collected samples were processed for biochemical and molecular methods to detect L. monocytogenes. Additionally, virulence factors associated genes, antibiogram profiles and biofilm formation related assays were determined. RESULTS: L. monocytogenes presence was confirmed using molecular detection methods targeting prs and lmo1030 genes, along with MALDI-TOF MS. Following 16 S rRNA sequencing, the identified Listeria species were further categorised into two groups. L. monocytogenes was detected in two (2.17%) food samples tested (L-23 and L-74). Multiplex PCR indicated the presence of seven virulence-related genes in L. monocytogenes isolates, i.e., inlA, inlB, prfA, iap, actA, plcB, and hlyA. In addition, 17 antibiotics were tested, whereby two isolates showed resistance to clindamycin and azithromycin, while one isolate (L-74) was also resistant to nalidixic acid, co-trimoxazole, ampicillin, norfloxacin, and cefotaxime. L-23 and L-74 isolates showed biofilm formation, especially at pH 8.6 and 37°C. CONCLUSIONS: Besides the demonstration of the presence of L. monocytogenes in some dairy and street food products, this study underscores the need to increase the standards of hygiene on the one hand and the importance of the surveillance of food-borne pathogens on the other.

An epigenetically distinct HSC subset supports thymic reconstitution.

Hematopoietic stem cells (HSCs) with multilineage potential are critical for effective T cell reconstitution and restoration of the adaptive immune system after allogeneic Hematopoietic Cell Transplantation (allo-HCT). The Kit lo subset of HSCs is enriched for multipotential precursors, 1, 2 but their T-cell lineage potential has not been well-characterized. We therefore studied the thymic reconstituting and T-cell potential of Kit lo HSCs. Using a preclinical allo-HCT model, we demonstrate that Kit lo HSCs support better thymic recovery, and T-cell reconstitution resulting in improved T cell responses to infection post-HCT. Furthermore, Kit lo HSCs with augmented BM lymphopoiesis mitigate age-associated thymic alterations, thus enhancing T-cell recovery in middle-aged hosts. We find the frequency of the Kit lo subset declines with age, providing one explanation for the reduced frequency of T-competent HSCs and reduced T-lymphopoietic potential in BM precursors of aged mice. 3, 4, 5 Chromatin profiling revealed that Kit lo HSCs exhibit higher activity of lymphoid-specifying transcription factors (TFs), including Zbtb1 . Deletion of Zbtb1 in Kit lo HSCs diminished their T-cell potential, while reinstating Zbtb1 in megakaryocytic-biased Kit hi HSCs rescued T-cell potential, in vitro and in vivo . Finally, we discover an analogous Kit lo HSC subset with enhanced lymphoid potential in human bone marrow. Our results demonstrate that Kit lo HSCs with enhanced lymphoid potential have a distinct underlying epigenetic program.

Patchy fibrosis promotes trigger-substrate interactions that both generate and maintain atrial fibrillation.

Fibrosis has been mechanistically linked to arrhythmogenesis in multiple cardiovascular conditions, including atrial fibrillation (AF). Previous studies have demonstrated that fibrosis can create functional barriers to conduction which may promote excitation wavebreak and the generation of re-entry, while also acting to pin re-entrant excitation in stable rotors during AF. However, few studies have investigated the role of fibrosis in the generation of AF triggers in detail. We apply our in-house computational framework to study the impact of fibrosis on the generation of AF triggers and trigger-substrate interactions in two- and three-dimensional atrial tissue models. Our models include a reduced and efficient description of stochastic, spontaneous cellular triggers as well as a simple model of heterogeneous inter-cellular coupling. Our results demonstrate that fibrosis promotes the emergence of focal excitations, primarily through reducing the electrotonic load on individual fibre strands. This enables excitation to robustly initiate within these single strands before spreading to neighbouring strands and inducing a full tissue focal excitation. Enhanced conduction block can allow trigger-substrate interactions that result in the emergence of complex, re-entrant excitation patterns. This study provides new insight into the mechanisms by which fibrosis promotes the triggers and substrate necessary to induce and sustain arrhythmia.

Mechanisms of pulmonary arterial hypertension-induced atrial fibrillation: insights from multi-scale models of the human atria.

This study aimed to use multi-scale atrial models to investigate pulmonary arterial hypertension (PAH)-induced atrial fibrillation mechanisms. The results of our computer simulations revealed that, at the single-cell level, PAH-induced remodelling led to a prolonged action potential (AP) (ΔAPD: 49.6 ms in the right atria (RA) versus 41.6 ms in the left atria (LA)) and an increased calcium transient (CaT) (ΔCaT: 7.5 × 10-2 µM in the RA versus 0.9 × 10-3 µM in the LA). Moreover, heterogeneous remodelling increased susceptibility to afterdepolarizations, particularly in the RA. At the tissue level, we observed a significant reduction in conduction velocity (CV) (ΔCV: -0.5 m s-1 in the RA versus -0.05 m s-1 in the LA), leading to a shortened wavelength in the RA, but not in the LA. Additionally, afterdepolarizations in the RA contributed to enhanced repolarization dispersion and facilitated unidirectional conduction block. Furthermore, the increased fibrosis in the RA amplified the likelihood of excitation wave breakdown and the occurrence of sustained re-entries. Our results indicated that the RA is characterized by increased susceptibility to afterdepolarizations, slow conduction, reduced wavelength and upregulated fibrosis. These findings shed light on the underlying factors that may promote atrial fibrillation in patients with PAH.

Chamber-specific wall thickness features in human atrial fibrillation.

Persistent atrial fibrillation (AF) is not effectively treated due to a lack of adequate tools for identifying patient-specific AF substrates. Recent studies revealed that in 30-50% of patients, persistent AF is maintained by localized drivers not only in the left atrium (LA) but also in the right atrium (RA). The chamber-specific atrial wall thickness (AWT) features underlying AF remain elusive, though the important role of AWT in AF is widely acknowledged. We aimed to provide direct evidence of the existence of distinguished RA and LA AWT features underlying AF drivers by analysing functionally and structurally mapped human hearts ex vivo. Coronary-perfused intact human atria (n = 7, 47 ± 14 y.o.; two female) were mapped using panoramic near-infrared optical mapping during pacing-induced AF. Then the hearts were imaged at approximately 170 µm3 resolution by 9.4 T gadolinium-enhanced MRI. The heart was segmented, and 3D AWT throughout atrial chambers was estimated and analysed. Optical mapping identified six localized RA re-entrant drivers in four hearts and four LA drivers in three hearts. All RA AF drivers were anchored to the pectinate muscle junctions with the crista terminalis or atrial walls. The four LA AF drivers were in the posterior LA. RA (n = 4) with AF drivers were thicker with greater AWT variation than RA (n = 3) without drivers (5.4 ± 2.6 mm versus 5.0 ± 2.4 mm, T-test p < 0.05; F-test p < 0.05). Furthermore, AWT in RA driver regions was thicker and varied more than in RA non-driver regions (5.1 ± 2.5 mm versus 4.4 ± 2.2 mm, T-test p < 0.05; F-test p < 0.05). On the other hand, LA (n = 3) with drivers was thinner than the LA (n = 4) without drivers. In particular, LA driver regions were thinner than the rest of LA regions (3.4 ± 1.0 mm versus 4.2 ± 1.0 mm, T-test p < 0.05). This study demonstrates chamber-specific AWT features of AF drivers. In RA, driver regions are thicker and have more variable AWT than non-driver regions. By contrast, LA drivers are thinner than non-drivers. Robust evaluation of patient-specific AWT features should be considered for chamber-specific targeted ablation.

Single-cell analysis of bidirectional reprogramming between early embryonic states reveals mechanisms of differential lineage plasticities.

Two distinct fates, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common progenitor cells, the inner cell mass (ICM), in mammalian embryos. To study how these sister identities are forged, we leveraged embryonic (ES) and eXtraembryonic ENdoderm (XEN) stem cells - in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses uncovered distinct rates, efficiencies and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4, KLF4 and SOX2-induced XEN-to-iPS reprogramming progressed with diminished efficiency and kinetics. The dominant PrE transcriptional program, safeguarded by Gata4, and globally elevated chromatin accessibility of EPI underscored the differential plasticities of the two states. Mapping in vitro trajectories to embryos revealed reprogramming in either direction tracked along, and toggled between, EPI and PrE in vivo states without transitioning through the ICM.

SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data.

Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here we present single-cell aggregation of cell states (SEACells), an algorithm for identifying metacells that overcome the sparsity of single-cell data while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying comprehensive, compact and well-separated metacells in both RNA and assay for transposase-accessible chromatin (ATAC) modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene-peak associations, compute ATAC gene scores and infer the activities of critical regulators during differentiation. Metacell-level analysis scales to large datasets and is particularly well suited for patient cohorts, where per-patient aggregation provides more robust units for data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a Coronavirus Disease 2019 (COVID-19) patient cohort.

Neurological Manifestations of Infectious Diseases: Insights From Recent Cases.

This narrative review examines the complex connection between infectious diseases and their neurological effects. It provides a detailed analysis of recent instances and insights derived from various pathogens. As we explore the realm of infectious agents, including viruses, bacteria, parasites, and fungi, a thorough and diverse analysis reveals the intricacies of neurological problems. The review begins by examining viral infections, specifically focusing on how viruses invade the neurological system and its subsequent effects. Significant instances from recent widespread disease outbreaks function as instructive benchmarks, highlighting the progressing comprehension of these ever-changing interconnections. The article examines the complex pathophysiology of neurological problems caused by bacterial infections. It presents current cases that illustrate the various ways these complications might manifest and the difficulties faced in their therapeutic management. Parasitic and fungal infections, which are typically overlooked, are being carefully examined to emphasize their distinct role in causing neurological complications. The mentioned cases highlight the importance of being thoroughly aware of these less-explored areas ranging from protozoan parasites to opportunistic fungal infections. In addition to the immediate effects caused by infectious agents, the review investigates autoimmune responses activated by infections. It provides a detailed examination of specific instances that shed light on the complex relationship between viral triggers and future neurological problems. This text elaborates on the intricacy of autoimmune-related neurological issues, highlighting the necessity for a comprehensive approach to diagnosing and treating them. The narrative next redirects its attention to the diagnostic difficulties that arise when interpreting the neurological symptoms of viral disorders. This article provides a thorough examination of existing diagnostic tools, along with an investigation into new technologies that have the potential to improve our capacity to identify and comprehend complex presentations. This debate connects to the following examination of treatment methods, where current cases that showcase successful interventions are carefully examined to extract valuable insights into good clinical management. The discussion focuses on the public health implications of preventive efforts against infectious infections, including their neurological consequences. The story emphasizes the link between infectious diseases and overall societal health, advocating for a proactive strategy to reduce the impact of neurological complications. The abstract concludes by providing a prospective viewpoint, highlighting areas of research that still need to be addressed, and suggesting potential future avenues. This narrative review seeks to provide a comprehensive resource for physicians, researchers, and public health professionals dealing with the complex field of neurological manifestations in infectious diseases. It combines recent examples, synthesizes current information, and offers a holistic perspective.