Previous Datasets Research Articles

Investigation of the Cyclohexene Oxidation Mechanism Through the Direct Measurement of Organic Peroxy Radicals.

Monoterpenes, the second most abundant biogenic volatile organic compounds globally, are crucial in forming secondary organic aerosols, making their oxidation mechanisms vital for addressing climate change and air pollution. This study utilized cyclohexene as a surrogate to explore first-generation products from its ozonolysis through laboratory experiments and mechanistic modeling. We employed proton transfer reaction mass spectrometry with NH4+ ion sources (NH4+-CIMS) and a custom-built OH calibration source to quantify organic peroxy radicals (RO2) and closed-shell species. Under near-real atmospheric conditions in a Potential Aerosol Mass-Oxidation Flow Reactor, we identified 30 ozonolysis products, expanding previous data sets of low-oxygen compounds. Combined with simulations based on the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere and relevant literature, our results revealed that OH dominates over ozone in cyclohexene oxidation at typical atmospheric oxidant levels with H-abstraction contributing 30% of initial RO2 radicals. Highly oxidized molecules primarily arise from RO2 autoxidation initiated by ozone, and at least 15% of ozone oxidation products follow the overlooked nonvinyl hydroperoxides pathway. Gaps remain especially in understanding RO2 cross-reactions, and the structural complexity of monoterpenes further complicates research. As emissions decrease and afforestation increases, understanding these mechanisms becomes increasingly critical.

Contrasting the development of larval and adult body plans during the evolution of biphasic lifecycles in sea urchins.

Biphasic lifecycles are widespread among animals, but little is known about how the developmental transition between larvae and adults is regulated. Sea urchins are a unique system for studying this phenomenon because of the stark differences between their bilateral larval and pentaradial adult body plans. Here, we use single-cell RNA sequencing to analyze the development of Heliocidaris erythrogramma (He), a sea urchin species with an accelerated, non-feeding mode of larval development. The sequencing time course extends from embryogenesis to roughly a day before the onset of metamorphosis in He larvae, which is a period that has not been covered by previous datasets. We find that the non-feeding developmental strategy of He is associated with several changes in the specification of larval cell types compared to sea urchins with feeding larvae, such as the loss of a larva-specific skeletal cell population. Furthermore, the development of the larval and adult body plans in sea urchins may utilize largely different sets of regulatory genes. These findings lay the groundwork for extending existing developmental gene regulatory networks to cover additional stages of biphasic lifecycles.

Bias-aware face mask detection dataset

AbstractIn December 2019, a novel coronavirus (COVID-19) spread so quickly around the world that many countries had to set mandatory face mask rules in public areas to reduce the transmission of the virus. To monitor public adherence, researchers aimed to rapidly develop efficient systems that can detect faces with masks automatically. However, the lack of representative and novel datasets posed challenges for training efficient models. Early attempts to collect face mask datasets did not account for potential race, gender, and age biases. Therefore, the resulting models show inherent biases toward specific race groups, such as Asian or Caucasian. In this work, we present a novel face mask detection dataset that contains images posted on Twitter during the pandemic from around the world. Unlike previous datasets, the proposed Bias-Aware Face Mask Detection (BAFMD) dataset contains more images from underrepresented races and age groups to mitigate the problem of the face mask detection task. We perform experiments to investigate potential biases in widely used face mask detection datasets and illustrate that the BAFMD dataset yields models with better performance and generalization ability. The dataset is publicly available at https://github.com/Alpkant/BAFMD.

Podium to Publication: An Analysis of Papers Presented at the British Association of Paediatric Surgeons (BAPS) Congress (2009–19)

BackgroundThe British Association of Paediatric Surgeons (BAPS) annual congress is an opportunity to present clinical and scientific data that may influence future practice. The presentation of the Abstract is but the first step towards definitive publication in the medical literature. Our aim was to review what the success rate has been from previous congresses. MethodsAbstracts were reviewed for the 11-year-period 2009 to 2019. A MEDLINE search using keywords from title and authors’ names was used to identify subsequent publication. Comparison with a previous dataset [1] (1999-2008) was also carried out. Linear data were compared for trend using Mann-Whitney-U. P ≤ 0.05 was accepted as significant. Data were expressed as median (interquartile range). Results1061 abstracts were presented orally with 555 (52.3%) subsequently published. The number per year was 90 (81–106) compared to 81 (74–79) in 1999–2008 (P = 0.25), although with a higher number actually published thereafter [45 (32–54)% vs. 30 (27–35)%; P = 0.0003)]. Publication occurred in a wide range of journals (n = 99), with most being in the Journal of Pediatric Surgery (n = 251), albeit with a smaller proportion (49% vs. 69% formerly, P < 0.05). Overall, UK institutions contributed 52.6% (n = 558) of abstracts with 240 (43%) of them subsequently published at 19 (17–29)/year. The proportion of UK presentations had increased from 43% formerly (P = 0.016). Most UK presentations originated from institutions within London [41% vs. 45% formerly, P = 0.04]. There was a wide range of abstracts from institutions from outside of the UK (n = 49) with 38 (26–51) abstracts accepted each year and of these 62.4% were subsequently published at 20 (15–36)/year. ConclusionThere has been an increase in abstracts accepted for presentation over the period, together with a higher proportion actually reaching publication. A strong international contribution was noted which has also been maintained. London remains the primary source of abstracts and publications from within the UK, although there was a higher proportion from other UK centres noted over this period.Reference [1] Macdonald AL, Parsons C, Davenport M. Outcome of abstracts presented at the British Association of Paediatric Surgeons congresses (1999–2008). J Pediatr Surg. 2012; 47: 386-90. doi: 10.1016/j.jpedsurg.2011.09.043.

Sediment Dynamics in the Energetic Nearshore Zone: Acoustic Remote Sensing and Model Validation

AbstractAcoustic backscatter data were collected in the shallow nearshore environment under breaking and non‐breaking waves, using a multi‐frequency sonar at 0.5, 1.0, and 2.0 MHz. The data are used to develop and test an acoustic inverse model for measuring suspended sediment concentration (SSC) in the presence of bubbles generated by breaking waves. The model leverages the contrasting frequency dependence of acoustic scattering by bubbles and sand, to simultaneously estimate SSC and bubble void fraction. Validation against in situ sediment measurements shows the acoustic technique can recover sediment concentration with good accuracy in both breaking and non‐breaking waves, unlike existing algorithms which only perform well in non‐breaking waves. Finally, data from the experiment are used to validate existing theories for suspended sediment dynamics under breaking waves, for which few previous data sets exist.

Two distinct Dehalobacter metagenome-assembled genomes from anaerobic chloroform and dichloromethane degrading consortia.

Here we present two metagenomes and two Dehalobacter metagenome-assembled genomes from subcultures of an anaerobic chloroform and dichloromethane degrading microbial community used for bioremediation. Our objective was to assemble and curate the genome(s) of Dehalobacter, key biodegraders in the culture, through repeated sequencing and joint assembly with previous datasets.

Norms for 718 Persian Words in Emotional Dimensions, Animacy, and Familiarity.

Research frequently uses words as stimuli to assess cognitive and psychological processes. However, various attributes of these words, such as their semantic and emotional aspects, could potentially confound study results if not properly controlled. This study aims to establish a reliable foundation for the semantic and emotional aspects of words for research in Persian. To this end, the present study provided norms for 718 Persian nouns in arousal, valence, familiarity, and animacy dimensions. The words were selected from a previous English dataset (Warriner et al. in Behav Res Methods 45(4):1191-1207, 2013), translated into Persian, and rated by a total of 463 native Persian-speaking participants. The ratings were obtained through an online questionnaire using a 9-point Likert scale for emotional dimensions (i.e., valence and arousal) and a 5-point Likert scale for semantic dimensions (i.e., familiarity and animacy). The reliability of the ratings was measured using the split-half method, and the result indicated a high consistency of ratings in all dimensions. To assess the relationship between the emotional and semantic dimensions, Pearson correlation coefficient was conducted. Gender differences were investigated through the Mann-Whitney U test, and significant differences were observed in all dimensions. These results are compared with findings from previous studies that were conducted in various languages.

Spontaneous ignition and flame propagation in hydrogen/methane wrinkled laminar flames at reheat conditions: Effect of pressure and hydrogen fraction

Direct numerical simulations (DNS) with detailed chemical kinetics and chemical explosive mode analysis (CEMA) are performed to investigate the effect of operating pressure and hydrogen–methane blending on laminar wrinkled flames at reheat combustion conditions. Building upon previous three-dimensional DNS datasets of reheat hydrogen flames, the present work considers two-dimensional configurations that render computationally-feasible simulations of high-pressure combustion and significantly more complex hydrocarbon chemistry. A geometrically-simplified representation of the reheat combustor is adopted and the thermodynamic states considered in the simulations are carefully chosen to mimic gas turbine operation conditions, which are constrained to achieve a target flame position and flame temperature. The two-dimensional DNS results are first assessed against the available three-dimensional data and then analyzed to extract the main trends exhibited by the reheat combustion process with respect to the fraction of the fuel consumed by spontaneous ignition and flame propagation, for increasing pressures and hydrogen fractions. Due to significant differences in the characteristic features of the velocity and thermal boundary layers between the three-dimensional and the two-dimensional configurations, a different global flame shape is observed (V-shaped flame vs W-shape flame) together with a ∼10% bias in the fraction of fuel consumed by spontaneous ignition. Crucially, results from the scaling studies reveal very clear trends with a significant decrease in the fuel consumption by spontaneous ignition for increasing pressures and hydrogen fractions, at the conditions investigated. Finally, this study highlights the important role that first-principle direct numerical simulations, even when conducted in computationally affordable two-dimensional simplified geometrical configurations, can play in obtaining detailed insights and quantitative trends useful for the characterization of complex reactive flows.Novelty and significanceThe reheat burners of the two-stage sequential gas turbine combustors are designed to stabilize flames primarily due to spontaneous ignition. However, prior numerical simulations revealed the presence of an additional assisted-ignition mode aided by recirculation zones. In this study, we used practically feasible two-dimensional direct numerical simulations of premixed hydrogen–air mixtures under lean conditions to quantify the roles of the two flame stabilization modes at different operating pressures. Achieving fundamental understanding of the effect of pressure and hydrogen fraction on flame stabilization is crucial to the development of two-stage sequential combustion and the present two-dimensional calculations provide important new insights. We show that at high pressures, both modes consume fuel to a similar extent. We also investigated the effect of methane blending on flame stabilization. This study also discusses how two-dimensional direct numerical simulations can be leveraged in the design optimization of reheat burners at low technology readiness levels.

Vigilant Attention During Cognitive and Language Processing in Aphasia.

Persons with aphasia (PWA) experience differences in attention after stroke, potentially impacting cognitive/language performance. This secondary analysis investigated physiologically measured vigilant attention during linguistic and nonlinguistic processing in PWA and control participants. To evaluate performance and attention in a language task, seven PWA read sentences aloud (linguistic task) and were compared to a previous data set of 10 controls and 10 PWA. To evaluate performance and attention in a language-independent task, 11 controls and nine PWA completed the Bivalent Shape Task (nonlinguistic task). Continuous electroencephalogram (EEG) data were collected during each session. A previously validated EEG algorithm classified vigilant-attention state for each experiment trial into high, moderate, distracted, or no attention. Dependent measures were task accuracy and amount of time spent in each attention state (measured by the number of trials). PWA produced significantly more errors than controls on the linguistic task, but groups performed similarly on the nonlinguistic task. During the linguistic task, controls spent significantly more time than PWA in a moderate-attention state, but no statistically significant differences were found between groups for other attention states. For the nonlinguistic task, amount of time controls and PWA spent in each attention state was more evenly distributed. When directly comparing attention patterns between linguistic and nonlinguistic tasks, PWA showed significantly more time in a high-attention state during the linguistic task as compared to the nonlinguistic task; however, controls showed no significant differences between linguistic and nonlinguistic tasks. This study provides new evidence that PWA experience a heightened state of vigilant attention when language processing demands are higher (during a linguistic task) than when language demands are lower (during a nonlinguistic task). Collectively, results of this study suggest that when processing language, PWA may allocate more attentional resources than when completing other kinds of cognitive tasks.

Generative discovery of safer chemical alternatives using diffusion modeling: A case study in green solvent design for cyclohexane/benzene extractive distillation

Over the past century, advancements in chemistry have significantly propelled human innovation, enhancing both industrial and consumer products. However, this rapid progression has resulted in chemical pollution increasingly surpassing planetary boundaries, as production and release rates have outpaced our monitoring capabilities. To catalyze more impactful efforts, this study transitions from traditional chemical assessment to inverse chemical design, introducing a generative graph latent diffusion model aimed at discovering safer alternatives. In a case study on the design of green solvents for cyclohexane/benzene extraction distillation, we constructed a design database encompassing functional, environmental hazards, and process constraints. Virtual screening of previous design dataset revealed distinct trade-off trends between these design requirements. Based on the screening outcomes, an unconstrained generative model was developed, which covered a broader chemical space and demonstrated superior capabilities for structural interpolation and extrapolation. To further optimize molecular generation towards desired properties, a multi-objective latent diffusion method was applied, yielding 19 candidate molecules. Of these, 7 were identified in PubChem as the most viable green solvent candidates, while the remaining 12 as potential novel candidates. Overall, this study effectively designed green solvent candidates for safer and more sustainable industrial production, setting a promising precedent for the development of environmentally friendly alternatives in other areas of chemical research.

Transforming the Tradition of Discrete Milk Yield Correction Factors: A Continuous One-step DeLorenzo-Wiggans Method

Over the past decades, various methods have been proposed to estimate daily milk yields from partial yields. Many of these methods divide milking interval time into varied classes, assuming that the yield correction factors are constant within classes but vary between classes. The DeLorenzo and Wiggans (D-W) method has been widely used in the United States, typically following a 2-step process. It calculates discrete yield factors for segmented milking interval classes and then refines them through a follow-up smoothing step. Such a 2-step approach is computationally inefficient, and discrete yield correction factors introduce biases. This study explored strategies to integrate continuous yield factors into established methods, exemplified by the D-W method. The renovated method, also called the polynomial-interaction regression (PIR) model, postulates multiplicative yield correction factors as a linear or quadratic function of milking interval time, operating on interactions with partial yields. It utilizes all available data in a single step, exhibiting greater computability efficiency and higher estimation accuracy. A reparameterization leads to a linear model, making estimating the model parameters convenient. We evaluated the performance of the revised methods using a previous data set of milking records from Holstein cows compared with some existing methods. The results showed that the refurbished model gave more accurate estimates of daily milk yields.

Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex.

Functional and structural studies investigating macroscopic connectivity in the human cerebral cortex suggest that high-order associative regions exhibit greater connectivity compared to primary ones. However, the synaptic organization of these brain regions remains unexplored. In the present work, we conducted volume electron microscopy to investigate the synaptic organization of the human brain obtained at autopsy. Specifically, we examined layer III of Brodmann areas 17, 3b, and 4, as representative areas of primary visual, somatosensorial, and motor cortex. Additionally, we conducted comparative analyses with our previous datasets of layer III from temporopolar and anterior cingulate associative cortical regions (Brodmann areas 24, 38, and 21). 9,690 synaptic junctions were 3D reconstructed, showing that certain synaptic characteristics are specific to particular regions. The number of synapses per volume, the proportion of the postsynaptic targets, and the synaptic size may distinguish one region from another, regardless of whether they are associative or primary cortex. By contrast, other synaptic characteristics were common to all analyzed regions, such as the proportion of excitatory and inhibitory synapses, their shapes, their spatial distribution, and a higher proportion of synapses located on dendritic spines. The present results provide further insights into the synaptic organization of the human cerebral cortex.

PEL-PVP: Application of plant vacuolar protein discriminator based on PEFT ESM-2 and bilayer LSTM in an unbalanced dataset

Plant vacuoles, play a crucial role in maintaining cellular stability, adapting to environmental changes, and responding to external pressures. The accurate identification of vacuolar proteins (PVPs) is crucial for understanding the biosynthetic mechanisms of intracellular vacuoles and the adaptive mechanisms of plants. In order to more accurately identify vacuole proteins, this study developed a new predictive model PEL-PVP based on ESM-2. Through this study, the feasibility and effectiveness of using advanced pre-training models and fine-tuning techniques for bioinformatics tasks were demonstrated, providing new methods and ideas for plant vacuolar protein research. In addition, previous datasets for vacuolar proteins were balanced, but imbalance is more closely related to the actual situation. Therefore, this study constructed an imbalanced dataset UB-PVP from the UniProt database，helping the model better adapt to the complexity and uncertainty in real environments, thereby improving the model's generalization ability and practicality. The experimental results show that compared with existing recognition techniques, achieving significant improvements in multiple indicators, with 6.08 %, 13.51 %, 11.9 %, and 5 % improvements in ACC, SP, MCC, and AUC, respectively. The accuracy reaches 94.59 %, significantly higher than the previous best model GraphIdn. This provides an efficient and precise tool for the study of plant vacuole proteins.

A new Paleogene fossil and a new dataset for waterfowl (Aves: Anseriformes) clarify phylogeny, ecological evolution, and avian evolution at the K-Pg Boundary.

Despite making up one of the most ecologically diverse groups of living birds, comprising soaring, diving and giant flightless taxa, the evolutionary relationships and ecological evolution of Anseriformes (waterfowl) remain unresolved. Although Anseriformes have a comparatively rich, global Cretaceous and Paleogene fossil record, morphological datasets for this group that include extinct taxa report conflicting relationships for all known extinct taxa. Correct placement of extinct taxa is necessary to understand whether ancestral anseriform feeding ecology was more terrestrial or one of a set of diverse aquatic ecologies and to better understand avian evolution around the K-T boundary. Here, we present a new morphological dataset for Anseriformes that includes more extant and extinct taxa than any previous anseriform-focused dataset and describe a new anseriform species from the early Eocene Green River Formation of North America. The new taxon has a mediolaterally narrow bill which is rarely found in previously described anseriform fossils. The matrix created to assess the placement of this taxon comprises 41 taxa and 719 discrete morphological characters describing skeletal morphology, musculature, syringeal morphology, ecology, and behavior. We additionally combine the morphological dataset with published sequences using Bayesian methods and perform ancestral state reconstruction for select morphological, ecological and behavioral characters. We recover the new Eocene taxon as the sister taxon to (Anseranatidae+Anatidae) across all analyses, and find that the new taxon represents a novel ecology within known Anseriformes and the Green River taxa. Results provide insight into avian evolution during and following the K-Pg mass extinction and indicate that Anseriformes were likely ancestrally aquatic herbivores with rhamphothecal lamellae..

FHS-adapter: fine-grained hierarchical semantic adapter for Chinese landscape paintings generation

How to migrate text-to-image models based on pre-trained diffusion models to adapt them to domain generation tasks is a common problem. In particular, the generation task for Chinese landscape paintings with unique characteristics suffers from a scarcity of fine-grained contextual details specific to such artwork. Moreover, the use of substantial amounts of non-landscape painting data during pre-training predisposes the model to be swayed by alternative visual styles, thereby leading to generated images that inadvertently lack the distinctive traits inherent to Chinese paintings. In this paper, we propose a Fine-grained Hierarchical Semantic Adapter for Chinese landscape paintings generation, namely FHS-adapter. The method orchestrates the diffusion process in a batch-wise manner, leveraging external fine-grained multi-perspective information to guide it. It gradually diminishes the influence of other style images embedded in the pre-trained diffusion model, ultimately preserving a greater number of landscape painting elements. The encoder was also replaced with the Taiyi-CLIP encoder, which is adapted for Chinese. We propose T2ICLP, a multimodal dataset containing 10,000 high-quality image-text pairs of Chinese landscape paintings. Unlike previous datasets, this dataset extracts fine-grained textual information from four perspectives, including Meta, Description, Sentiment, Poem. We compared the proposed model with the mainstream diffusion-based T2I models. Through an anonymous user study, our FHS-adapter method performs well in simulating various aspects such as brushwork, e.g.‘Gou, Cun, Dian, Ran’ means hooking, texturing, dotting, and dyeing, compositional space, elemental proportions, and color usage of different painting genres and artists. Our dataset is available at https://github.com/T2ICLP/t2iclp.

Natural history in Malan syndrome: survey of 28 adults and literature review

BackgroundMalan syndrome (MALNS), previously referred to as “Sotos syndrome 2” due to its resemblance to Sotos syndrome (SS), is an ultra-rare neurodevelopmental disorder characterized by overgrowth, typical craniofacial features, intellectual disability (ID), and a range of psychobehavioral, musculoskeletal, vision and neurological signs. As MALNS and SS partly overlap, it is essential to more accurately profile their clinical presentations and highlight their differences in order to improve syndrome specific management. An increasing number of individuals with MALNS reach adult-age though the natural history of the disorder is poorly characterized due to the small number of adult individuals described so far. As a consequence, current guidelines are limited to the pediatric population. Further delineation of MALNS is essential to optimize care in adulthood.ResultsA mixed approach based on cross-sectional data collection with a survey disseminated to caregivers of adults with molecularly confirmed MALNS and literature review was conducted. Twenty-eight caregivers completed the survey. Clinical presentation in adulthood is multisystemic and defined by psychobehavioral comorbidities (96%), musculoskeletal involvement (96%), vision impairment (96%) and neurological complications (86%). The most common signs were anxiety (79%), hypotonia (75%), movement difficulty (75%), scoliosis (64%), problems with coordination (61%), strabismus (57%), constipation (54%), breastbone abnormalities (54%) and advanced bone age during childhood (54%). Impaired vision was complicated by vision decline (36%) and optic atrophy (32%). We report some previously unidentified features, including high pain threshold (46%), incontinence (25%), tremors (21%), muscle hypoplasia (18%) and tics (18%).ConclusionsThis survey in the adult population has allowed a more complete description of the natural history of MALNS. Our findings will contribute to the development and improvement of standards of care for adults with MALNS to assure optimal health monitoring and treatment of evolutive complications. We propose additional recommendations to the previous dataset of clinical evaluations specifically applied to adults. The comparison of MALNS and SS adult presentation highlights significant differences in terms of prevalence and severity of ID, behavioral issues, and vision problems, confirming that a proper differential diagnosis between the two conditions is indispensable to guide physicians and mental health professionals to syndrome specific management.

Modeling of scour hole characteristics under turbulent wall jets using machine learning

The novelty of the present study is to investigate the parameters that depict the scour hole characteristics caused by turbulent wall jets and develop new mathematical relationships for them. Four significant parameters i.e., depth of scouring, location of scour depth, height of the dune and location of dune crest are identified to represent a complete phenomenon of scour hole formation. From the gamma test, densimetric Froude number, apron length, tailwater level, and median sediment size are found to be the key parameters that affect these four dependent parameters. Utilizing the previous data sets, Multi Regression Analysis (linear and non-linear) has been performed to establish the relationships between the dependent parameters and influencing independent parameters. Further, artificial neural network-particle swarm optimisation (ANN-PSO) and gene expression programming (GEP) based models are developed using the available data. In addition, results obtained from these models are compared with proposed regression equations and the best models are identified employing statistical performance parameters. The performance of the ANN-PSO model (RMSE = 1.512, R2 = 0.605), (RMSE = 6.644, R2 = 0.681), (RMSE = 6.386, R2 = 0.727) and (RMSE = 1.754, R2 = 0.636) for predicting four significant parameters are more satisfactory than that of regression and other soft computing techniques. Overall, by analysing all the statistical parameters, uncertainty analysis and reliability index, ANN-PSO model shows good accuracy and predicts well as compared to other presented models.

The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1-linked chromatin opening

A mechanistic connection between aging and development is largely unexplored. Through profiling age-related chromatin and transcriptional changes across 22 murine cell types, analyzed alongside previous mouse and human organismal maturation datasets, we uncovered a transcription factor binding site (TFBS) signature common to both processes. Early-life candidate cis-regulatory elements (cCREs), progressively losing accessibility during maturation and aging, are enriched for cell-type identity TFBSs. Conversely, cCREs gaining accessibility throughout life have a lower abundance of cell identity TFBSs but elevated activator protein 1 (AP-1) levels. We implicate TF redistribution toward these AP-1 TFBS-rich cCREs, in synergy with mild downregulation of cell identity TFs, as driving early-life cCRE accessibility loss and altering developmental and metabolic gene expression. Such remodeling can be triggered by elevating AP-1 or depleting repressive H3K27me3. We propose that AP-1-linked chromatin opening drives organismal maturation by disrupting cell identity TFBS-rich cCREs, thereby reprogramming transcriptome and cell function, a mechanism hijacked in aging through ongoing chromatin opening.

A single-cell atlas of chromatin accessibility in mouse organogenesis.

Organogenesis is a highly complex and precisely regulated process. Here we profiled the chromatin accessibility in >350,000 cells derived from 13 mouse embryos at four developmental stages from embryonic day (E) 10.5 to E13.5 by SPATAC-seq in a single experiment. The resulting atlas revealed the status of 830,873 candidate cis-regulatory elements in 43 major cell types. By integrating the chromatin accessibility atlas with the previous transcriptomic dataset, we characterized cis-regulatory sequences and transcription factors associated with cell fate commitment, such as Nr5a2 in the development of gastrointestinal tract, which was preliminarily supported by the in vivo experiment in zebrafish. Finally, we integrated this atlas with the previous single-cell chromatin accessibility dataset from 13 adult mouse tissues to delineate the developmental stage-specific gene regulatory programmes within and across different cell types and identify potential molecular switches throughout lineage development. This comprehensive dataset provides a foundation for exploring transcriptional regulation in organogenesis.

Geneapp: A web application for visualizing alternative splicing for biomedicine

Alternative Splicing (AS) is an essential mechanism for eukaryotes. However, the consequences of deleting a single exon can be dramatic for the organism and can lead to cancer in humans. Additionally, alternative 5′ and 3′ splice sites, which define the boundaries of exons, also play key roles to human disorders. Therefore, Investigating AS events is crucial for understanding the molecular basis of human diseases and developing therapeutic strategies. Workflow for AS event analysis can be sampling followed by data analysis with bioinformatics to identify the different AS events in the control and case samples, data visualization for curation, and selection of relevant targets for experimental validation. The raw output of the analysis software does not favor the inspection of events by bioinformaticians requiring custom scripts for data visualization. In this work, we propose the Geneapp application with three modules: GeneappScript, GeneappServer, and GeneappExplorer. GeneappScript is a wrapper that assists in identifying AS in samples compared in two different approaches, while GeneappServer integrates data from AS analysis already performed by the user. In GeneappExplorer, the user visualizes the previous dataset by exploring AS events in genes with functional annotation. This targeted screens that Geneapp allows to perform helps in the identification of targets for experimental validation to confirm the hypotheses under study. The Geneapp is freely available for non-commercial use at https://geneapp.net to advance research on AS for bioinformatics.