bluuebunny/crossref_metadata_2025_split huggingface dataset:
American College of Surgeons Cancer Program Annual Report from 2021 Participant User File
Authors: Habermann Elizabeth B , Day Courtney N , Palis Bryan E , Plichta Jennifer K , Wasif Nabil , Weigel Ronald J , Boughey Judy C 
Published: December 2024

The National Cancer Database (NCDB) collects data from approximately 1,500 Commission on Cancer (CoC) facilities and represent 73.7% of newly diagnosed cancers nationwide.
The American College of Surgeons Cancer Program developed it first annual report from the NCDB 2021 participant user file reporting new observations and recent trends of cancer diagnoses, patient demographics, and treatments as well as an in-depth report on treatment and outcomes in breast, pancreas, and colon cancers.
Of the 1,328,131 cancers diagnosed in 2021 at 1,281 reporting CoC hospitals, one-fifth continue to be female breast cancer. In 2021, the NCDB’s 5 most common adult cancers were breast, prostate, lung, colon, and melanoma and varied by patient sex. Use of neoadjuvant systemic therapy increased in recent years in pancreas, breast, and urinary bladder cancer, although a slight decrease in pancreas and breast cancer was observed in 2021.
Breast cancer has high survival rates, especially in lower-stage disease and estrogen receptor-positive/human epidermal growth factor receptor 2-negative disease. There is increase in neoadjuvant systemic therapy use, especially in human epidermal growth factor receptor 2-positive disease and estrogen receptor-negative disease.
Colon cancer presents most commonly as stage III or II with a primary in the cecum or ascending colon in 38.9%. The majority are microsatellite instability stable, Kirsten rat sarcoma viral oncogene homologue normal, and CEA positive. Survival is most dependent on stage but also associated with microsatellite instability stability, abnormal Kirsten rat sarcoma viral oncogene homologue, and positive CEA.
Pancreatic cancer presents with stage IV disease in nearly half, although an increase in stage I disease is seen. The most common location is pancreatic head. Survival is relatively low and most dependent on stage.
GAGER: gene regulatory network assisted gene expression restoration
Authors: Chowdhury Md Zarzees Uddin Shah , Any Sumaiya Sultana , Samee Md. Abul Hasan , Rahman Atif 
Published: December 2024

AbstractGene regulatory networks are crucial for cellular function, and disruptions in transcription factor (TF) regulation often lead to diseases. However, identifying TFs to transition a source cell state to a desired target state remains challenging. We present a method to identify key TFs whose perturbation can restore gene expressions in a source state to target levels. Its effectiveness is demonstrated on datasets from yeast TF knockouts, cardiomyocytes from hypoplastic left heart syndrome patients, and mouse models of neurodegeneration. The method accurately identifies knocked-out TFs in the yeast dataset. In the cardiomyocyte dataset, it pinpoints TFs that, though not differentially expressed in many cases, exert significant regulatory influence on downstream differentially expressed genes. Finally, in the mouse model dataset, it identifies disease stage-specific TFs, improving similarity between healthy and diseased states at various time points. Unlike traditional approaches relying on differential expression analysis, our method uses network-based prioritization for more targeted and biologically relevant TF selection. These findings highlight its potential as a therapeutic tool for precise TF targeting to normalize gene expressions in diseased states.
Impact of land cover and climate change on habitat of Indian birds
Authors: Diengdoh Vishesh L. , Srinivasan Umesh 
Published: December 2024

AbstractBirds play an important role in multiple ecosystems and face significant threats from both land-cover and climate change, the effects of which remain insufficiently understood. This study projected the impact of these global changes on habitat suitability of 478 birds in India, which has the 9thhighest number of bird species globally, under present conditions (2015) and future scenarios (2100) using an ensemble of machine learning algorithms. The results project the average amount of suitable habitat to decrease for non-forest and non-specialised habitat birds but not for forest birds. Suitable habitat was projected to decrease in desert and xeric shrublands and tropical and subtropical-broadleaf forest and grasslands, savannas, and shrublands biomes. We recommend conservation strategies to focus more than they currently do on non-forest birds as well as desert and xeric shrublands and tropical and subtropical broadleaf forest biomes.
Poka: a necro-robot beetle with a measured payload ratio of 6847 %
Authors: Tsvetkov Yordan , Alam Parvez 
Published: December 2024

ABSTRACTThis paper is concerned with the design, manufacture and validation of ‘Poka’, a novel millimetre-scale necro-robot aimed at bridging the performance gap between miniature robots and insects. To create Poka, we use the exoskeleton of a deceased five-horned rhinoceros beetle (Eupatorus gracilicornis) as a mechanical chassis, which is mechatronically functionalised to enable ambulation. When comparing the payload ratio,PR, of Poka against reported values of the rhinoceros beetleXyloryctes thestalus, we find that Poka’sPRis more than 2-fold higher, reaching a measured maximum of 6847% (i.e. 68.47 times its own body weight). The specific power at maximum payload,Ps,t, is nevertheless of the same order of magnitude in bothXyloryctes thestalus(0.21 W/kg) and Poka (0.28 W/kg). Poka’s highest average speed,is achieved at aPR= 2739%, after which it progressively decreases with increasing payload ratio, reaching its minimumat maximum payload ratio. When comparing Poka’s maximum measuredPRof 6847% against those of sixteen other ambulating robots, we find that Poka’sPRfar exceeds that of any other robot to date, the highest being otherwise from SuperBot who has aPR= 530%. Poka’s payload ratio is therefore the highest robot payload ratio recorded to date and we attribute this to (a) the use of the beetle body as a natural composite chassis with high specific properties, and (b) the additive manufacture of bionic beetle parts using low density but stiff polylactic acid, designed with structurally stable geometries.
Cell-type specific subtyping of epigenomes improves prognostic stratification of cancer
Authors: Luo Qi , Teschendorff Andrew E. 
Published: December 2024

AbstractBackgroundMost molecular classifications of cancer are based on bulk-tissue profiles that measure an average over many distinct cell-types. As such, cancer subtypes inferred from transcriptomic or epigenetic data are strongly influenced by cell-type composition and do not necessarily reflect subtypes defined by cell-type specific cancer-associated alterations, which could lead to suboptimal cancer classifications.MethodsTo address this problem, we here propose the novel concept of cell-type specific combinatorial clustering (CELTYC), which aims to group cancer samples by the molecular alterations they display in specific cell-types. We illustrate this concept in the context of DNA methylation data of liver and kidney cancer, deriving in each case novel cancer subtypes and assessing their prognostic relevance against current state-of-the-art prognostic models.ResultsIn both liver and kidney cancer, we reveal improved cell-type specific prognostic models, not discoverable using standard methods. In the case of kidney cancer, we show how combinatorial indexing of epithelial and immune-cell clusters define improved prognostic models driven by synergy of high mitotic age and altered cytokine signaling. We validate the improved prognostic models in independent datasets, and identify underlying cytokine-immune-cell signatures driving poor outcome.ConclusionsIn summary, cell-type specific combinatorial clustering is a valuable strategy to help dissect and improve current prognostic classifications of cancer in terms of the underlying cell-type specific epigenetic and transcriptomic alterations.
Planktonic oyster larvae optimize settlement decisions in complex sensory landscapes
Authors: Schmidlin Sarah , Treherne Yliam , Mees Jan , Hablützel Pascal I. 
Published: December 2024

AbstractThe settlement of pelagic larvae constitutes a pivotal phase in the life cycle of benthic aquatic species. The choice of settlement location is critical for the recruitment to established populations and the colonization of unoccupied habitats. Consequently, the cues governing settlement decisions in larvae become particularly pertinent for human activities such as habitat restoration, mariculture, or biofouling prevention. Our study aims to enhance our comprehension of the underlying principles of how larvae optimize settlement decisions when exposed to multiple natural chemical cues simultaneously. Through a series of laboratory experiments, we investigate settlement patterns of Pacific oysterMagallana gigaslarvae when exposed to different combinations of attractant and repellent cues. Our findings reveal additive increases in settlement rates in the presence of attractant cues originating from conspecifics and biofilms. Conversely, settlement attraction by conspecific water-borne cues was reduced in the presence of repellent cues emanating from predators. Notably, when repellent predator cues were presented alongside attractant cues linked to substrates (biofilms or shells from conspecific adults), the repellent effect was nullified.
Optimizing therapeutic outcomes with Mechanotherapy and Ultrasound Sonopermeation in solid tumors
Authors: Koutsi Marina , Stylianopoulos Triantafyllos , Mpekris Fotios 
Published: December 2024

AbstractMechanical solid stress plays a pivotal role in tumor progression and therapeutic response. Elevated solid stress compresses intratumoral blood vessels, leading to hypoperfusion, and hypoxia, which impair oxygen and drug delivery. These conditions hinder the efficacy of drugs and promote tumor progression and treatment resistance compromising therapeutic outcomes. To enhance treatment efficacy, mechanotherapeutics and ultrasound sonopermeation have been developed to improve tumor perfusion and drug delivery. Mechanotherapy aims to reduce tumor stiffness and mechanical stress within tumors to normal levels leading to decompression of vessels while simultaneously improving perfusion. On the other hand, ultrasound sonopermeation strategy focuses on increasing non-invasively and transiently tumor vessel wall permeability to boost perfusion and thus, improve drug delivery. Within this framework and aiming to replicate published experimental data in silico, we developed a mathematical model designed to derive optimal conditions for the combined use of mechanotherapeutics and sonopermeation, with the goal of optimizing efficacy of nano-immunotherapy. The model incorporates complex interactions among diverse components that are crucial in the multifaceted process of tumor progression. These components encompass a variety of cell populations in tumor, such as tumor cells and immune cells, as well as components of the tumor vasculature including endothelial cells, angiopoietins, and the vascular endothelial growth factor. A comprehensive validation of the predictions generated by the mathematical model was carried out in conjunction with published experimental data, wherein a strong correlation was observed between the model predictions and the actual experimental measurements of critical parameters, which are essential to reinforce the overall accuracy of the mathematical framework employed. In addition, a parametric analysis was performed with primary objective to investigate the impact of various critical parameters that influence sonopermeation. The analysis provided optimal guidelines for the use of sonopermeation in conjunction with mechanotherapy, that contribute to identify optimal conditions for sonopermeation.
Transient transcription factor depletions explain diverse single-cell responses of LexA target promoters to mild DNA damage
Authors: Galbusera Luca , Bellement-Theroue Gwendoline , Julou Thomas , van Nimwegen Erik 
Published: December 2024

AbstractIn bacteria, the effects of transcription factors (TFs) on the expression of their target genes are highly stochastic at the single-cell level. Not only do TF concentrations fluctuate in time and from cell to cell, in each cell the actual binding and unbinding of TFs to promoters is also stochastic. However, how this ‘noise propagation’ from TFs to their targets determines the expression fluctuations in target genes of the same TF has so far not been quantitatively characterized. Here we use fluorescence time-lapse microscopy in combination with microfluidics and automated image analysis to quantitatively track the single-cell growth and gene expression dynamics of different target promoters of the LexA SOS response regulator inE. coliunder mild DNA damage induced by the antibiotic ciprofloxacin (CIP).We find that, at the single-cell level, LexA target promoters exhibit stochastic bursts in protein production with specific quantitative characteristics. First, the durations of protein production bursts are short, identical for all promoters, and independent of CIP levels. Second, the heights of the production peaks are exponentially distributed for each promoter, and independent of CIP level, but with different average heights for different promoters. Third, the frequency of the production bursts increases with CIP level for all promoters, but differs across promoters.Importantly, we show that these observations are inconsistent with popular ‘equilibrium’ models of bacterial gene regulation that assume that the dynamics of binding and unbinding of TFs is fast relative to the time-scale of TF concentration fluctuations. Instead, all observations can be quantitatively fit by a relatively simple model in which DNA damage events lead to short transient dips in LexA concentration, and an expression burst occurs in a cell whenever LexA unbinds from the target promoter during such a short dip in LexA concentration. Moreover, because these transient dips in LexA concentration occur on the same time-scale as the stochastic unbinding of LexA from promoters, the response of a target promoter to an individual DNA damage event is stochastic and depends in a complex manner on the strengths of its LexA binding sites and the duration of the event. Consequently, the expression levels of different LexA target genes in a given cell reflect distinct statistics of the frequency and durations of DNA damage events in the recent history of that cell.Our results show that, even in the simple scenario where a single TF is induced, different target promoters can exhibit distinct stochastic responses that depend on the precise kinetics of the induction events.
Editingcis-elements ofOsPHO1;2improved phosphate transport and yield in rice
Authors: Maurya Kanika , Mani Balaji , Singh Bhagat , Sirohi Ujjwal , Jaskolowski Aime , Sharma Sandeep , Tatiparthi Harsha Vardhan , Mangrauthia Satendra Kumar , Pandey Renu , Poirier Yves , Giri Jitender 
Published: December 2024

AbstractIncreasing grain yield is the main aim of crop improvement, which is globally impacted by the low availability of soil phosphate (Pi). Overexpressing Pi transporters for increasing Pi uptake often result in Pi toxicity and growth retardation. Despite advancements in genetic engineering, targetingcis-regulatory motifs of Pi transporters remains underexplored for understanding plant mechanisms and improving Pi status. Here, we demonstrated that the excision of the transcription inhibitor motif from the promoter of Pi transporter,OsPHO1;2,enhanced its expression and increased root-to-shoot Pi transport, leading to improved grain yield. Using,in-silicoand DNA-protein interaction studies, we show the role of OsWRKY6 transcription factor in the negative regulation ofOsPHO1;2expression by binding to thecis-regulatory element (W-box) present in its promoter.oswrky6knockout lines displayed a higherOsPHO1;2expressions, and improved shoot Pi levels. Further, we engineered theOsPHO1;2promoter for precisely removing the W-box and enhancingOsPHO1;2expression. The phenotypic and physiological evaluation at the vegetative stage shows thatOsPHO1;2promoter edited (OsPHO1;2:PE) lines have increased shoot length, plant biomass and more root-shoot Pi export under low and normal P conditions. Notably, the33Pi uptake assay reveals thatOsPHO1;2:PElines exhibited enhanced root Pi uptake, supported by higher root-associated Pi transporters (OsPHTs) expression. An extensive agronomical assessment revealed thatOsPHO1;2:PElines acquire increased seed and panicle numbers, thereby increasing yield without affecting seed quality. Our findings offer valuable insight into the potential of promoter editing to raise plants with better Pi use and improved crop yield.
SafeguardingIguanadiversity: Enabling rapid and low-effort tracking of non-native iguanas through terrestrial eDNA innovations
Authors: van Kuijk Jeroen L. , van den Burg Matthijs P. , Didaskalou Emilie A. , de Boer Mark , Debrot Adolphe O. , Wielstra Ben , Stewart Kathryn A. 
Published: December 2024

AbstractReptiles have among the highest extinction risk across terrestrial vertebrates, with habitat fragmentation, habitat destruction, and invasive alien species being the primary causes of reptile species loss on a global scale. Invasive hybridization (i.e. hybridization between native and invasive alien species) is increasing globally, causing the extinction of native genotypes, and this phenomenon is particularly pervasive in Caribbean iguanas. The Lesser Antillean Iguana (Iguana delicatissima), a keystone species of Caribbean coastal ecosystems, has become critically endangered mainly due to ongoing hybridization with the invasive Common Green Iguana (I. iguana). For impactful conservation intervention, the need for early detection of invasive animals and their progeny, or detection of surviving pure native animals, is urgent. We aimed to develop a novel environmental DNA (eDNA) toolkit using Kompetitive Allele Specific PCR (KASP) technology, a method of allele-specific amplification for cost-effective and efficient sampling of terrestrial substrates to aid in mapping the distribution of nativeI. delicatissima, invasiveI. iguana, and signal potential invasive hybridization. We demonstrate proof-of-concept and successfully identifiedI. delicatissima, I. iguana,and their hybrids via blood samples using our primer sets, as well as successful detection ofI. delicatissimain several ex-situ (Rotterdam Zoo) and in-situ (St. Eustatius) eDNA samples, collected with environmental swabs and tape-lifting. We found that sampling potential perching spots yielded the highest number of positive detections via environmental swabbing and tape-lifting. Our toolkit demonstrates the potential of terrestrial eDNA sampling for iguana conservation, enabling faster detection of potential invasive hybridization. Additionally, the method holds promise for other terrestrial cryptic species, contributing to broader collection of population-level information.
ReSCU-Nets: recurrent U-Nets for segmentation of multidimensional microscopy data
Authors: Hawkins Raymond , Balaghi Negar , Rothenberg Katheryn E. , Ly Michelle , Fernandez-Gonzalez Rodrigo 
Published: December 2024

ABSTRACTSegmenting multi-dimensional microscopy data requires high accuracy across many images (e.g. timepoints or Z slices) and is thus a labour-intensive part of biological image processing pipelines. We present ReSCU-Nets, recurrent convolutional neural networks that use the segmentation results from the previous frame as a prompt to segment the current frame. We demonstrate that ReSCU-Nets outperform state-of-the-art image segmentation models in different segmentation tasks on time-lapse microscopy sequences.
Deconvolution of omics data in Python with Deconomix – cellular compositions, cell-type specific gene regulation, and background contributions
Authors: Mensching-Buhr Malte , Sterr Thomas , Seifert Nicole , Völkl Dennis , Tauschke Jana , Rayford Austin , Zacharias Helena U. , Grellscheid Sushma Nagaraja , Beissbarth Tim , Görtler Franziska , Altenbuchinger Michael 
Published: December 2024

AbstractSummaryGene expression profiles of heterogeneous bulk samples contain signals from multiple cell populations. Studying variations in their composition can help to identify cell populations relevant for disease. Moreover, analyses, such as the identification of differentially expressed genes, can be confounded by cellular composition, as differences in gene expression may arise from both variations in cellular composition and gene regulation. Here, we present Deconvolution of omics data (Deconomix) – a comprehensive toolbox for the cell-type deconvolution of bulk transcriptomics data. Deconomix stands apart from competing solutions with rich functionality and highly efficient implementations. It facilitates (A) the inference of cellular compositions from bulk transcriptomics data, (B) the machine learning-based optimization of gene weights to resolve small cell populations and to disentangle phenotypically related cells, (C) the inference of background contributions which otherwise would deteriorate cell-type deconvolution, and (D) population estimates of cell-type specific gene regulation.AvailabilityDeconomix is available athttps://gitlab.gwdg.de/MedBioinf/MedicalDataScience/Deconomixunder GPLv3 licensing. The Python package can be easily installed via pip. It comes with a comprehensive documentation of all user-relevant functions and example workflows provided as Jupyter notebooks.
Cell-sheet shape transformation by internally-driven, oriented forces
Authors: Huang Junrou , Chen Juan , Luo Yimin 
Published: December 2024

AbstractDuring morphogenesis, cells collectively execute directional forces that drive programmed folding and growth of the layers, forming tissues and organs. The ability to recapitulate aspects of these processesin vitrowould constitute a significant leap forward in the field of tissue engineering. Free-standing, self-organizing, cell-laden matrices are fabricated using a sequential deposition approach that uses liquid crystal-templated hydrogel fibers to direct cell arrangements. The orientation of hydrogel fibers is controlled using flow or boundary cues, while their microstructures are controlled by depletion interaction and probed by scattering and microscopy. These fibers effectively direct cells embedded in a collagen matrix, creating multilayer structures through contact guidance and by leveraging steric interactions amongst the cells. In uniformly aligned cell matrices, oriented cells exert traction forces that can induce preferential contraction of the matrix. Simultaneously, the matrix densifies and develops anisotropy through cell remodeling. Such an approach can be extended to create cell arrangements with arbitrary in-plane patterns, allowing for coordinated cell forces and pre-programmed, macroscopic shape changes. This work reveals a fundamentally new path for controlled force generation, emphasizing the role of a carefully designed initial orientational field for manipulating shape transformations of reconstituted matrices.