bluuebunny/crossref_metadata_2025 huggingface dataset:
Encapsulation of AD-MSC- derived extracellular nanovesicles in an electrospun three-layer scaffold: characterization and controlled release analysis in vitro
Authors: Ghorbani Raziyeh , Abbaszadeh Hojjat Allah , Ramezani Reihaneh , Taghipour Niloofar , Rahimpour Azam , Hosseinzadeh Simzar
Published: December 2024

The combining of therapeutic agents with electrospun nanofibers boosts their regeneration potential; therefore, Researchers have increasingly turned towards the development of electrospun nanofiber scaffolds to encapsulate or surface-adsorb biological payloads, such as cytokines, exosomes, peptides, nucleic acids, and enzymes. Due to their high surface-to-volume ratio, ease of manufacturing, and drug-loading capacity, electrospun nanofibers are hopeful in tissue engineering and scaffold fabrication. Electrospun multilayer scaffolds offer a promising construction for preserving the integrity and bioactivity of therapeutic factors while permitting the controlled and prolonged release of biomolecules into the environment. The present study aimed to evaluate the mechanism of controlled release of electrospun exosomes from a three-layer nanofiber scaffold and its effect on the expression of DDR2 and VEGF genes in fibroblast cells in vitro. Adipose-derived mesenchymal stem cells were obtained and isolated from liposuction surgery samples, and their intrinsic nature was confirmed using flow cytometry. After the exosomes were separated from the cell supernatant, their size, shape, and index markers were identified. The cytotoxicity, biocompatibility, and mechanical characteristics of scaffolds were evaluated. The qRT-PCR results showed the upregulation of DDR2 and VEGF genes in the three-layer scaffold containing the exosomes was 2.04 and 1.47-fold compared to the control group. The design and construction of multi-layered electrospun nanofibers loaded with bioactive substances and favorable mechanical and biological properties for controlled and sustained release will be promising and effective scaffolds for therapeutic purposes.
Optimal parameter setting and evaluation for ultraviolet-assisted direct ink writing bioprinting of nHA/PEGDA scaffold
Authors: Li Yumeng , Ma Jiaqi , Wang Jing , Kong Yanlei , Wang Feng , Zhang Pengfei , Fan Yawei
Published: December 2024

Ultraviolet-assisted Direct Ink Writing (UV-DIW), an extrusion-based additive manufacturing technology, has emerged as a prominent 3D printing technique and is currently an important topic in bone tissue engineering research. This study focused on the printability of double-network bioink (Nano-hydroxyapatite/Polyethylene glycol diacrylate (nHA/PEGDA)). Next, we search for the optimal UV-DIW printing parameters for the scaffold formed by nHA-PEGDA. In the end, we developed a scaffold that has outstanding structural integrity and can repair bone defects. Achieving high-quality UV-DIW printing can be challenging due to a variety of factors (slurry solid content, rheology, printing conditions, etc.). At present, there are limited reports about precise parameter configurations for UV-DIW printing. We optimised the solid composition of the slurry by varying the quantities of nHA and PEGDA, establishing the maximum solid content (40 wt%) permissible for scaffold shaping. Consequently, we examined the influence of several factors (nozzle diameter, air pressure, and printing rate) on the surface morphology of the scaffolds and determined the ideal conditions to attain scaffolds with superior printing accuracy. The findings demonstrate excellent controllability, repeatability, and precision of the entire printing process. Finally, we evaluated the scaffolds that most effectively fulfilled the requirements for bone regeneration by examining their surface morphology and mechanical characteristics. The experimental findings indicate that nHA-PEGDA scaffolds fulfil the compressive strength requirements for bone tissue and possess promising applications in bone regeneration. This study demonstrates that the nHA-PEGDA bioink possesses significant potential as a scaffold material for bone tissue regeneration, exhibiting exceptional shape integrity and mechanical capabilities. The study found the optimal parameters for bio-3D printers and gave UV-DIW an exact data reference for making the nHA-PEGDA scaffold. In addition, it is a useful guide for 3D printing biomaterial scaffolds.
An ultra-thin organosiloxane film with excellent corrosion resistance based on self-crosslinking of multiple polymerization sites prepared by PECVD on copper alloy
Authors: Huang Meiru , Shen Luli , Yin Yuying , Liu Luqi , Zhou Guiping , Wang Gang , Zeng Zhixiang , Ma Fuliang
Published: December 2024

Intelligent, integrated, and environmentally sustainable electronic products have become a major trend, making the protection of electronic products a top priority. Low surface energy organosiloxane polymer films are very attractive for electronic protection, but their high porosity is not conducive to the protection of electronic devices. To solve this problem, an ultra-thin 2,4,6,8-tetravinyl-2,4,6,8-tetramethylcyclotetrasiloxane polymer film (p-V4D4) with very low porosity was deposited on a copper alloy by PECVD self-crosslinking. Compared with triethoxyvinylsilane polymer film (p-VTES) and divinyltetramethyldisiloxane polymer film (p-DVTMS), the p-V4D4 has more polymerization sites, higher cross-linking density, and lower porosity. Benefiting from the synergistic effect of good hydrophobicity and low porosity structure, the p-V4D4 offers 99.99% corrosion suppression efficiency, 48 h of salt spray corrosion resistance, and up to 23 days of immersion in 3.5 wt% NaCl. Moreover, the dense structure gives it good mechanical stability and low dielectric properties. These findings provide a new pathway for synthesizing films with efficient anti-corrosion properties and have potential application prospects in electronic protection and microelectronics.
Mechanical characterization and thermal investigation of nylon polymer matrix composites used in automotive power train systems
Authors: Shanmugam Thillikkani , D S Manoj Abraham , N Suresh , Obili Sathish
Published: December 2024

Failures may result from a variety of mechanical issues, including the improper composition of the components. This study synthesizes specific typical varying materials, including nylon 6/6 and glass fibers, with unique volume proportions to improve abrasion resistance and extend the lifespan of equipment. The research demonstrated that polymer gears have a lengthier longevity than gears that are entirely composed of nylon. The specimen samples undergo a variety of evaluations, including tensile, compressive, flexural, impact, Thermo Gravimetric analysis, and wear assessments. Nevertheless, the rate of depreciation remains constant. An experiment has been conducted that involves a composite of 90% nylon and 10% nylon with 10% glass fiber. Research indicates that the combination of 10% Nylon 6/6 produces optimistic outcomes. The research indicates that a composition that comprises 30% glass fiber and 70% Nylon 6/6 offers exceptional strength, wear resistance, and reduced wear.
Preliminary study on degradation mechanisms of plasma-treated DR1 by atomistic simulations
Authors: NABIYEVA Namunakhon , AKRAMOV Tohir , ABDUVOKHIDOV Davronjon , ZHANG 张 Yuantao 远涛 , YUSUPOV Maksudbek , RAZZOKOV Jamoliddin
Published: December 2024

Cold atmospheric plasma (CAP) has emerged as a promising technology for the degradation of organic dyes, but the underlying mechanisms at the molecular level remain poorly understood. Using density-functional tight-binding (DFTB)-based quantum chemical molecular dynamics at 300 K, we have performed numerical simulations to investigate the degradation mechanism of Disperse Red 1 (DR) interacting with CAP-generated oxygen radicals. One hundred direct-dynamics trajectories were calculated for up to 100 ps simulation time, after which hydrogen-abstraction, benzene ring-opening/expanding, formaldehyde formation and modification in the chromophoric azo group which can lead to color-losing were observed. The latter was obtained with yields of around 6% at the given temperature. These findings not only enhance our understanding of CAP treatment processes but also have implications for the development of optimized purification systems for sustainable wastewater treatment. This study underscores the utility of DFTB simulations in unraveling complex chemical processes and guiding the design of advanced treatment strategies in the context of CAP technology.
Effects of soil bund and landscape positions on selected soil physico-chemical properties at Anole watershed, Rift Valley Basin, Ethiopia
Authors: Mathewos Markos , Lukas Mesfin
Published: December 2024

Land degradation in the form of soil erosion and fertility reduction is a major environmental problem in Ethiopia. Various efforts to control soil erosion through the introduction of soil and water conservation measures have been underway for nearly five decades in Ethiopia. The purpose of this research was to assess the effects of soil bunds on selected soil physical and chemical properties in the Anole watershed of Rift Valley of Ethiopia. A reconnaissance survey was conducted to identify a representative soil sampling site. 18 composite soil samples were collected from soil bund and no conservation practice (control) with three replications at three slope positions from 0 to 30 cm depth, whereas, 18 undisturbed soil samples were collected for bulk density analysis from both land uses. The analysis was carried out using analysis of variance (ANOVA). Clay, sand, BD, CEC, TN, and OM showed significant variation (P < 0.05) between the soil bund and control plots. Whereas, for slope positions, sand, clay, BD, CEC, TN, and available phosphorus in the Anole watershed were found to be statistically significant (P < 0.05). In steep, middle, and lower slopes, contents of OC and exchangeable potassium were greater in fields with soil bunds than without. Lower slope fields showed greater clay, OM, and nutrients than steep slopes. Because of the implementation of soil bund in the study watershed, the majority of soil’s physical and chemical characteristics have shown improvement. Proper implementations of soil bunds in the study area have a pronounced positive impact and should be practiced and applied in adjacent watersheds and similar agroecologies in the Rift Valley of Ethiopia.
Neuromorphic, physics-informed spiking neural network for molecular dynamics
Authors: Pham Vuong Van , Muther Temoor , Kalantari Dahaghi Amirmasoud
Published: December 2024

Molecular dynamics (MD) simulations are used across many fields from chemical science to engineering. In recent years, Scientific Machine Learning (Sci-ML) in MD attracted significant attention and has become a new direction of scientific research. However, effectively integrating Sci-ML with MD simulations remains challenging. Compliance with the physical principles, comparable performance to a numerical method, and integration of start-of-the-art ML architectures are top-concerned examples of those gaps. This work addresses these challenges by introducing, for the first time, the neuromorphic physics-informed spiking neural network (NP-SNN) architecture to solve Newton’s equations of motion for MD systems. Unlike conventional Sci-ML methods that heavily rely on prior training data, NP-SNN performs without needing pre-existing data by embedding MD fundamentals directly into its learning process. It also leverages the enhanced representation of real biological neural systems through spiking neural network integration with molecular dynamic physical principles, offering greater efficiency compared to conventional AI algorithms. NP-SNN integrates three core components: (1) embedding MD principles directly into the training, (2) employing best practices for training physics-informed ML systems, and (3) utilizing a highly advanced and efficient SNN architecture. By integrating these core components, this proposed architecture proves its efficacy through testing across various molecular dynamics systems. In contrast to traditional MD numerical methods, NP-SNN is trained and deployed within a continuous time framework, effectively mitigating common issues related to time step stability. The results indicate that NP-SNN provides a robust Sci-ML framework that can make accurate predictions across diverse scientific molecular applications. This architecture accelerates and enhances molecular simulations, facilitating deeper insights into interactions and system dynamics at the molecular level. The proposed NP-SNN paves the way for foundational advancements across various domains of chemical and material sciences especially in energy, environment, and sustainability fields.
Machine and deep learning performance in out-of-distribution regressions
Authors: Shmuel Assaf , Glickman Oren , Lazebnik Teddy
Published: December 2024

Machine learning (ML) and deep learning (DL) models are gaining popularity due to their effectiveness in many computational tasks. These models are based on an intuitive, but frequently unsatisfied, assumption that the data used to train these models is well-representing the task at hand. This gives rise to the out-of-distribution (OOD) challenge which can cause an unexpected drop in the data-driven model’s performance. In this study, we evaluate the performance of various ML and DL models in in-distribution (ID) versus OOD prediction. While the degradation in OOD performance is well acknowledged, to the best of our knowledge, this is one of the first studies to quantify it for various models on a large benchmark n = 15 real-world regression datasets. We extensively (

n
>
40

000

runs) compare the ID versus OOD performance of XGBoost, random forest, K-nearest-neighbors, support vector machine, and linear regression models, as well as AutoML models (Tree-based Pipeline Optimization Tool and AutoKeras). In addition, to tackle this challenge, we propose to integrate a symbolic regression (SR) as a feature engineering method model with an ML or DL model to improve its performance for OOD samples. Our results show that the incorporation of SR-derived features significantly enhances the predictive capabilities of both ML and DL models with 3.70% and 10.20%, on average, of the OOD samples, respectively, without reducing ID performance and in fact improving it to a slightly lower extent. As such, this method can help produce more generalized and robust data-driven models.
Climate change impacts to extreme weather events associated with insured losses in New Zealand: a review
Authors: Aldridge Joanna , Bell Rob
Published: December 2024

In 2023, New Zealand experienced two consecutive weather-related events that exceeded previous insured losses by more than a factor of ten: the Auckland Anniversary Day floods and ex-Tropical Cyclone Gabrielle. Further, climate reporting for financial services becomes mandatory in this jurisdiction in 2024, yet established catastrophe models are not available for a range of perils in New Zealand. Insurers hence need to better understand weather-related catastrophes in New Zealand and the impact of climate change in this island nation exposed to strong marine influences and weather events of both tropical and temperate origin. This comprehensive review seeks to integrate and interpret the findings from a wide range of scientific literature into a cohesive summary useful for insurers evaluating climate risk in New Zealand. This review summarises the climate risk facing New Zealand, focussing on extreme events including heavy rainfall, floods, coastal hazards driven by weather systems on a range of spatiotemporal scales: atmospheric rivers, ex- and extra-tropical cyclones and severe convective storms, as well as wildfire weather. Potential changes to natural climate variability are also considered. The review shows that extreme rainfall over a range of durations, but particularly shorter durations, is projected to increase, and riverine and coastal flooding will also increase, although potential impacts are less well understood. Extreme weather systems such as ex-tropical and extra-tropical cyclones may be supported by warmer sea surface temperatures and the poleward shift in subtropical weather systems, although quantitative studies on their changing frequency and severity are not yet available. Key knowledge gaps in understanding sources of extreme rainfall, ex-tropical cyclones and other low-pressure systems and severe convective storms are identified. Further, focus areas for climate-related risk reduction that insurers could seek to promote to help protect the New Zealand community are discussed.
Optogenetic control of receptor-mediated growth cone dynamics in neurons
Authors: Tymanskyj Stephen R. , Escorce Althea , Karthikeyan Siddharth , Ma Le
Published: December 2024

Development of neuronal connections is spatially and temporally controlled by extracellular cues which often activate their cognate cell surface receptors and elicit localized cellular responses. Here, we demonstrate the use of an optogenetic tool to activate receptor signaling locally to induce actin-mediated growth cone remodeling in neurons. Based on the light-induced interaction between Cryptochrome 2 (CRY2) and CIB1, we generated a bicistronic vector to co-expresses CRY2 fused to the intracellular domain of a guidance receptor and a membrane-anchored CIB1. When expressed in primary neurons, activation of the growth inhibitory PlexA4 receptor induced growth cone collapse, while activation of the growth stimulating TrkA receptor increased growth cone size. Moreover, local activation of either receptor not only elicited the predicted response in light-activated growth cones but also an opposite response in neighboring no-light-exposed growth cones of the same neuron. Finally, this tool was used to reorient growth cones toward or away from the site of light activation and to stimulate local actin polymerization for branch initiation along axonal shafts. These studies demonstrate the use of an optogenetic tool for precise spatial and temporal control of receptor signaling in neurons and support its future application in investigating cellular mechanisms of neuronal development and plasticity.
DNA damage causes ATM-dependent heterochromatin loss leading to nuclear softening, blebbing, and rupture
Authors: Eskndir Nebiyat , Hossain Manseeb , Currey Marilena L , Pho Mai , Berrada Yasmin , Lin Katie , Manning Gianna , Prince Kelsey , Stephens Andrew D
Published: December 2024

The nucleus must maintain stiffness to preserve its shape and integrity to ensure proper function. Defects in nuclear stiffness caused from chromatin and lamin perturbations produce abnormal nuclear shapes common in aging, heart disease, and cancer. Loss of nuclear shape via protrusions called blebs lead to nuclear rupture that is well established to cause nuclear dysfunction, including DNA damage. However, it remains unknown how increased DNA damage affects nuclear stiffness, shape, and ruptures, which could create a feedback loop. To determine whether increased DNA damage alters nuclear physical properties, we treated mouse embryonic fibroblast cells with DNA damage drugs cisplatin and bleomycin. DNA damage drugs caused increased nuclear blebbing and rupture in interphase nuclei within a few hours and independent of mitosis. Micromanipulation force measurements reveal that DNA damage decreased chromatin-based nuclear mechanics but did not change lamin-based strain stiffening at long extensions relative to wild type. Immunofluorescence measurements of DNA damage treatments reveal the mechanism is an ATM-dependent decrease in heterochromatin leading to nuclear weaken, blebbing, and rupture which can be rescued upon ATM inhibition treatment. Thus, DNA damage drugs cause ATM-dependent heterochromatin loss resulting in nuclear softening, blebbing, and rupture.
Resolving the two-body problem: A postulated role for the V0 sector of the V0V1-ATPase in exosome biogenesis and multivesicular body fate
Authors: D'Souza-Schorey Crislyn , Stahl Philip D.
Published: December 2024

Because the discovery of the multivesicular body (MVB) as the origin of secreted vesicles or exosomes, the question arose and still looms—what distinguishes an MVB destined for fusion with the plasma membrane (EXO-MVB) facilitating exosome release from an MVB involved in transport of content to the lysosome (LYSO-MVB). Do they have independent origins? Hence, the two-body problem. We hypothesize that a key to this conundrum is the membrane spanning V0 sector of the proton pump, V0V1-ATPase. The V0V1-ATPase participates in the acidification of intracellular compartments, although V0 can function separately from V1 and different V0 isoforms are endowed with membrane binding capabilities that allow the V0V1-ATPase to selectively localize to different endocytic compartments including early and late endosomes and lysosomes. We propose that V0, in collaboration with cholesterol and phosphoinositides, plays a central role in the early endosome as a nucleation center to direct the de novo assembly of an EXO-MVB scaffold. The EXO-MVB scaffold may play multiple roles—operating as an assembly platform, participating in membrane fission as well as providing downstream navigational queues necessary for exosome secretion. Thus, V0 may represent an influential nexus, a starting point, in exosome biogenesis.
Antibiotic prescribing for care-home residents: a population-based, cross-classified multilevel analysis in Scotland, UK
Authors: De Souza Nicosha , Guthrie Bruce , Grant Suzanne , Lorencatto Fabiana , Dickson Jane , Herbec Aleksandra , Hughes Carmel , Sneddon Jacqueline , Donnan Peter T , Marwick Charis A
Published: December 2024

Background

There is wide variation in antibiotic prescribing across care-homes for older people, with implications for resident outcomes and antimicrobial resistance.

Objective

To quantify variation in antibiotic prescribing and associations with resident, care-home and general practice characteristics.

Design

Population-based analyses using administrative data.

Setting and subjects

148 care-homes in two Scottish regions, with 6633 residents registered with 139 general practices.

Methods

Prescriptions for any antibiotic and for broad-spectrum antibiotics between 1 April 2016 and 31 March 2017 were analysed using cross-classified multilevel negative binomial regression.

Results

For any antibiotics, the mean prescription rate was 6.61 (SD 3.06) per 1000 resident bed-days (RBD). In multivariate analysis, prescribing was associated with resident age [incidence rate ratio (IRR) 1.30 [95% confidence interval 1.19 to 1.41] for 90+ versus <80 years old] and comorbidity (1.88 [1.71 to 2.06] for Charlson Comorbidity Index 3+ versus 0), and the care-home’s sampling rate for microbiological culture (1.53 [1.28 to 1.84] for >7 versus <3.5 samples per 1000 RBD), with residual unexplained variation between care-homes (median IRR 1.29 [1.23 to 1.36]) and general practices (1.11 [1.05 to 1.18]). For broad-spectrum antibiotics, the mean rate was 0.98 (0.92) per 1000 RBD. Broad-spectrum prescribing was also associated with resident age, sex, comorbidity and sampling rate, with larger residual unexplained variation between care-homes (1.56 [1.36 to 1.77]) and general practices (1.51 [1.31 to 1.72]).

Conclusion

Variation in prescribing was influenced by resident case-mix, but there is significant unexplained variation between care-homes and between general practices, indicating a need for antibiotic stewardship to target both.
Trop-2 and Ephrin B2 expression in urothelial carcinoma with divergent differentiation and aggressive urothelial carcinoma subtypes
Authors: Case Katherine B , Martini Dylan J , Dababneh Melad N , Bidot Samuel , Nazha Bassel , Brown Jacqueline , Joshi Shreyas , Narayan Vikram , Parihar Vaunita , Saeed Faisal , Bilen Mehmet Asim , Harik Lara R
Published: December 2024

Objectives

Urothelial carcinomas (UCs) encompass a heterogeneous group of tumors. Several histopathologic features are associated with poor clinical outcomes and limited treatment options. With new rising therapeutic modalities, we aimed to determine the pattern of expression of Trop-2 and ephrin B2 in UC with aggressive subtype histology and/or divergent differentiation (SH/DD).

Methods

We performed a retrospective analysis of 113 UC samples with SH/DD at our institution from 2011 to 2021. Immunohistochemical staining for Trop-2 and ephrin B2 expression was performed on all cases. Expression was determined by the percentage of samples with a moderate or strong H-score.

Results

Our results show Trop-2 expression was the highest in squamous cell carcinoma and UC with squamous differentiation, adenocarcinoma and UC with glandular differentiation, and plasmacytoid subtype, while ephrin B2 expression was highest in adenocarcinoma, UC with glandular differentiation, and small cell carcinoma.

Conclusions

Expression of Trop-2 and ephrin B2 may demonstrate therapeutic possibilities for patients with SH/DD, who usually have limited treatment options, particularly in small cell carcinoma, in which few targets have been identified. Clinical trials to investigate the efficacy of these novel treatments are warranted.
A lossless reference-free sequence compression algorithm leveraging grammatical, statistical, and substitution rules
Authors: Roy Subhankar , Kumar Maity Dilip , Mukhopadhyay Anirban
Published: December 2024

Deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) sequence compressors for novel species frequently face challenges when processing wide-scale raw, FASTA, or multi-FASTA structured data. For years, molecular sequence databases have favored the widely used general-purpose Gzip and Zstd compressors. The absence of sequence-specific characteristics in these encoders results in subpar performance, and their use depends on time-consuming parameter adjustments. To address these limitations, in this article, we propose a reference-free, lossless sequence compressor called GraSS (Grammatical, Statistical, and Substitution Rule-Based). GraSS compresses sequences more effectively by taking advantage of certain characteristics seen in DNA and RNA sequences. It supports various formats, including raw, FASTA, and multi-FASTA, commonly found in GenBank DNA and RNA files. We evaluate GraSS’s performance using ten benchmark DNA sequences with reduced number of repeats, two highly repetitive RNA sequences, and fifteen raw DNA sequences. Test results indicate that the weighted average compression ratios (WACR) for DNA and RNA sequences are 4.5 and 19.6, respectively. Additionally, the entire DNA sequence corpus has a total compression time (TCT) of 246.8 seconds (s). These results demonstrate that the proposed compression method performs better than several advanced algorithms specifically designed to handle various levels of sequence redundancy. The decompression times, memory usage, and CPU usage are also very competitive. Contact:  anirban@klyuniv.ac.in
Higher order interaction analysis quantifies coordination in the epigenome revealing novel biological relationships in Kabuki syndrome
Authors: Cuvertino Sara , Garner Terence , Martirosian Evgenii , Walusimbi Bridgious , Kimber Susan J , Banka Siddharth , Stevens Adam
Published: December 2024

Complex direct and indirect relationships between multiple variables, termed higher order interactions (HOIs), are characteristics of all natural systems. Traditional differential and network analyses fail to account for the omic datasets richness and miss HOIs. We investigated peripheral blood DNA methylation data from Kabuki syndrome type 1 (KS1) and control individuals, identified 2,002 differentially methylated points (DMPs), and inferred 17 differentially methylated regions, which represent only 189 DMPs. We applied hypergraph models to measure HOIs on all the CpGs and revealed differences in the coordination of DMPs with lower entropy and higher coordination of the peripheral epigenome in KS1 implying reduced network complexity. Hypergraphs also capture epigenomic trans-relationships, and identify biologically relevant pathways that escape the standard analyses. These findings construct the basis of a suitable model for the analysis of organization in the epigenome in rare diseases, which can be applied to investigate mechanism in big data.
GAADE: identification spatially variable genes based on adaptive graph attention network
Authors: Zhang Tianjiao , Sun Hao , Wu Zhenao , Zhao Zhongqian , Zhao Xingjie , Zhang Hongfei , Gao Bo , Wang Guohua
Published: December 2024

The rapid advancement of spatial transcriptomics (ST) sequencing technology has made it possible to capture gene expression with spatial coordinate information at the cellular level. Although many methods in ST data analysis can detect spatially variable genes (SVGs), these methods often fail to identify genes with explicit spatial expression patterns due to the lack of consideration for spatial domains. Considering spatial domains is crucial for identifying SVGs as it focuses the analysis of gene expression changes on biologically relevant regions, aiding in the more accurate identification of SVGs associated with specific cell types. Existing methods for identifying SVGs based on spatial domains predefine spot similarity before training, which prevents adaptive learning and limits generalizability across different tissues or samples. This limitation may also lead to inaccurate identification of specific genes at boundary regions. To address these issues, we present GAADE, an unsupervised neural network architecture based on graph-structured data representation learning. GAADE stacks encoder/decoder layers and integrates a self-attention mechanism to reconstruct node attributes and graph structure, effectively capturing spatial domain structures of different sections. Consequently, we confine the identification of SVGs within spatial domains. By performing differential expression analysis on spots within the target spatial domain and their multi-order neighbors, GAADE detects genes with enriched expression patterns within defined domains. Comparative evaluations with five other popular methods on ST datasets across four different species, regions and tissues demonstrate that GAADE exhibits superior performance in detecting SVGs and capturing the extent of spatial gene expression variation.
A comparative analysis of gene expression profiling by statistical and machine learning approaches
Authors: Bontonou Myriam , Haget Anaïs , Boulougouri Maria , Audit Benjamin , Borgnat Pierre , Arbona Jean-Michel
Published: December 2024

Motivation

Many machine learning (ML) models developed to classify phenotype from gene expression data provide interpretations for their decisions, with the aim of understanding biological processes. For many models, including neural networks, interpretations are lists of genes ranked by their importance for the predictions, with top-ranked genes likely linked to the phenotype. In this article, we discuss the limitations of such approaches using integrated gradient, an explainability method developed for neural networks, as an example.

Results

Experiments are performed on RNA sequencing data from public cancer databases. A collection of ML models, including multilayer perceptrons and graph neural networks, are trained to classify samples by cancer type. Gene rankings from integrated gradients are compared to genes highlighted by statistical feature selection methods such as DESeq2 and other learning methods measuring global feature contribution. Experiments show that a small set of top-ranked genes is sufficient to achieve good classification. However, similar performance is possible with lower-ranked genes, although larger sets are required. Moreover, significant differences in top-ranked genes, especially between statistical and learning methods, prevent a comprehensive biological understanding. In conclusion, while these methods identify pathology-specific biomarkers, the completeness of gene sets selected by explainability techniques for understanding biological processes remains uncertain.

Availability and implementation

Python code and datasets are available at https://github.com/mbonto/XAI_in_genomics.
Naevoid hyperkeratosis of the nipple and/or areola
Authors: Zheng Lin , Bai Jingzhu , Fang Ruihua
Published: December 2024

We report an unusual case of naevoid hyperkeratosis of the nipple and/or areola. A 36-year-old woman presented with asymptomatic, dark, verrucous, hard plaques on both the nipples and areolas, which had developed over the preceding 19 years. Just over 100 cases have been reported globally in the past 100 years.
Large language models in cancer: potentials, risks, and safeguards
Authors: Zitu Md Muntasir , Le Tuan Dung , Duong Thanh , Haddadan Shohreh , Garcia Melany , Amorrortu Rossybelle , Zhao Yayi , Rollison Dana E , Thieu Thanh
Published: December 2024

This review examines the use of large language models (LLMs) in cancer, analysing articles sourced from PubMed, Embase, and Ovid Medline, published between 2017 and 2024. Our search strategy included terms related to LLMs, cancer research, risks, safeguards, and ethical issues, focusing on studies that utilized text-based data. 59 articles were included in the review, categorized into 3 segments: quantitative studies on LLMs, chatbot-focused studies, and qualitative discussions on LLMs on cancer. Quantitative studies highlight LLMs’ advanced capabilities in natural language processing (NLP), while chatbot-focused articles demonstrate their potential in clinical support and data management. Qualitative research underscores the broader implications of LLMs, including the risks and ethical considerations. Our findings suggest that LLMs, notably ChatGPT, have potential in data analysis, patient interaction, and personalized treatment in cancer care. However, the review identifies critical risks, including data biases and ethical challenges. We emphasize the need for regulatory oversight, targeted model development, and continuous evaluation. In conclusion, integrating LLMs in cancer research offers promising prospects but necessitates a balanced approach focusing on accuracy, ethical integrity, and data privacy. This review underscores the need for further study, encouraging responsible exploration and application of artificial intelligence in oncology.
In-depth mass-spectrometry reveals phospho-RAB12 as a blood biomarker of G2019S LRRK2-driven Parkinson’s disease
Authors: Cortés Adriana , Phung Toan K , de Mena Lorena , Garrido Alicia , Infante Jon , Ruíz-Martínez Javier , Galmés-Ordinas Miquel À , Glendinning Sophie , Pérez Jesica , Roig Ana , Soto Marta , Cosgaya Marina , Ravasi Valeria , Fernández Manel , Rubiano-Castro Alejandro , Díaz Ramón , Hernández-Eguiazu Haizea , Sánchez-Quintana Coro , Vinagre-Aragón Ana , Mondragón Elisabet , Croitoru Ioana , Rivera-Sánchez María , Corrales-Pardo Andrea , Sierra María , Tolosa Eduardo , Malagelada Cristina , Nirujogi Raja S , Fernández-Irigoyen Joaquín , Santamaría Enrique , Alessi Dario R , J Martí María , Ezquerra Mario , Fernández-Santiago Rubén
Published: December 2024

Leucine-rich repeat kinase 2 (LRRK2) inhibition is a promising disease-modifying therapy for LRRK2-associated Parkinson’s disease (L2PD) and idiopathic PD (iPD). However, pharmaco-dynamic readouts and progression biomarkers for clinical trials aiming for disease modification are insufficient since no endogenous marker reflecting enhanced kinase activity of the most common LRRK2 G2019S mutation has been reported yet in L2PD patients.

Employing phospho-/proteomic analyses we assessed the impact that LRRK2 activating mutations had in peripheral blood mononuclear cells (PBMCs) from a LRRK2 clinical cohort from Spain (n=174). The groups of study encompassed G2019S L2PD patients (n=37), non-manifesting LRRK2 mutation carriers of G2019S, here, G2019S L2NMCs (n=27), R1441G L2PD patients (n=14), R1441G L2NMCs (n=11), iPD patients (n=40), and healthy controls (n=45).

We identified 207 differential proteins in G2019S L2PD compared to controls (39 up/168 down) and 67 in G2019S L2NMCs (10 up/57 down). G2019S down-regulated proteins affected the endolysosomal pathway, proteostasis, and mitochondria, e.g., ATIC, RAB9A, or LAMP1. At the phospho-proteome level, we observed increases in endogenous phosphorylation levels of pSer106 RAB12 in G2019S carriers, which were validated by immunoblotting after 1 year of follow-up (n=48). Freshly collected PBMCs from 3 G2019S L2PD, 1 R1441G L2PD, 1 iPD, and 5 controls (n=10) showed strong diminishment of pSer106 RAB12 phosphorylation levels after in-vitro administration of the MLi-2 LRRK2 inhibitor. Using machine learning, we identified an 18-feature G2019S phospho-/protein signature discriminating G2019S L2PD, L2NMCs, and controls with 96% accuracy that correlated with disease severity, i.e., UPDRS-III motor scoring.

Using easily accessible PBMCs from a LRRK2 clinical cohort, we identified elevated levels of pSer106 RAB12 as an endogenous biomarker of G2019S carriers. Our data suggest that monitoring pSer106 RAB12 phosphorylation could be a relevant biomarker for tracking LRRK2 activation, particularly in G2019S carriers. Future work may determine whether pSer106 RAB12 could help with patient enrichment and monitoring drug efficacy in LRRK2 clinical trials.
Arousal effects on oscillatory dynamics in the non-human primate brain
Authors: Anand Shashank A , Sogukpinar Fatih , Monosov Ilya E
Published: December 2024

Arousal states are thought to influence many aspects of cognition and behavior by broadly modulating neural activity. Many studies have observed arousal-related modulations of alpha (~8 to 15 Hz) and gamma (~30 to 50 Hz) power and coherence in local field potentials across relatively small groups of brain regions. However, the global pattern of arousal-related oscillatory modulation in local field potentials is yet to be fully elucidated. We simultaneously recorded local field potentials in numerous cortical and subcortical regions in the primate brain and assessed oscillatory activity and inter-regional coherence associated with arousal state. In high arousal states, we found a uniquely strong and coherent gamma oscillation between the amygdala and basal forebrain. In low arousal rest-like states, a relative increase in coherence at alpha frequencies was present across sampled brain regions, with the notable exception of the medial temporal lobe. We consider how these patterns of activity may index arousal-related brain states that support the processing of incoming sensory stimuli during high arousal states and memory-related functions during rest.
Post–Coronavirus Disease 2019 (COVID-19) Condition Risk Factors and Symptom Clusters and Associations With Return to Pre–COVID-19 Health—Results From a 2021 Multistate Survey
Authors: Konkle Stacey L , Magleby Reed , Bonacci Robert A , Segaloff Hannah E , Dimitrov Lina V , Mahale Parag , Katic Bozena , Nji Miriam , Cadwell Betsy , Ko Jean Y , Bushman Dena , Rushmore Julie , Cope Jennifer , Saydah Sharon
Published: December 2024

Background

Little is known about how symptoms or symptom clusters of post–coronavirus disease 2019 (COVID-19) conditions (PCCs) impact an individual's return to pre–COVID-19 health.

Methods

We used 4 state-level COVID-19 case reporting systems and patient-reported survey data to identify patients with PCCs and associations with an individual's return to pre–COVID-19 health after laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Participants had a positive SARS-CoV-2 test between March 2020 and December 2020. Weighted regression models were used to estimate prevalence of PCCs, identify risk factors associated with developing PCCs, and examine associations between PCC symptom clusters and return to pre–COVID-19 health. Factor analysis was used to identify post–COVID-19 symptom clusters.

Results

Prevalence of PCCs in this population-based sample was 29.9% for persons with SARS-CoV-2 infection during the pre-Delta variant period (March 2020–December 2020); 77.2% of persons who experienced PCCs had not returned to pre–COVID-19 health within 8–60 weeks after infection. Female sex, acute COVID-19 illness severity, and number of preexisting comorbidities were significant risk factors associated with PCCs. Myalgic encephalomyelitis/chronic fatigue syndrome–like symptoms, upper respiratory symptoms, and gastrointestinal symptoms were significantly associated with not returning to pre–COVID-19 health.

Conclusions

Understanding PCC symptom clustering may provide insight into pathophysiology, severity of PCCs, and management for patients who have not returned to their usual state of health after SARS-CoV-2 infection. Tracking PCCs can help measure impacts of COVID-19 vaccination and acute COVID-19–specific treatments on reducing PCCs in the United States.
Performance of Diagnostic Algorithms in Patients With Invasive Pulmonary Aspergillosis
Authors: Hatzl Stefan , Geiger Christina , Kriegl Lisa , Scholz Laura , Reisinger Alexander C , Kreuzer Philipp , Fruhwald Sonja , Wölfler Albert , Reinisch Andreas , von Lewinski Dirk , Schilcher Gernot , Hoenigl Martin , Eller Philipp , Krause Robert
Published: December 2024

Background

Invasive pulmonary aspergillosis (IPA), once limited to immunocompromised patients, is now a severe complication in critically ill ICU patients without classic risk factors. Due to the difficulty of obtaining histological evidence, diagnosis relies on poorly tested algorithms in real-world settings.

Methods

We conducted a retrospective multicenter (n = 9) cohort study including 202 patients with IPA. Patients were classified using a multistep process based on the EuropeanOrganization- for-the-Research-and-Treatment-of-Cancer/Mycosis-Study Group (EORTC-MSG), Invasive-Fungal-Diseases-in-Adult-Patients-in-Intensive-Care-Unit (FUNDICU), Aspergillus-ICU (Asp-ICU), and Asp-ICU with biomarkers (Asp-ICU-BM) criteria. We then evaluated the predictive performance of these criteria against the clinical cohort and histologically proven cases.

Results

Among 202 patients, 78 had EORTC-MSG host factors and were classified accordingly, with EORTC-MSG criteria achieving 100% agreement in identifying clinical and histologically proven cases. In 112 ICU patients without EORTC-MSG host factors, overall agreement was 53% for FUNDICU, 4% for Asp-ICU, and 26% for Asp-ICU-BM versus the clinical cohort. Validation against histologically proven cases showed FUNDICU had 44% sensitivity and 75% specificity, Asp-ICU 6% sensitivity and 100% specificity, and Asp-ICU-BM 28% sensitivity and 63% specificity. Adding acute respiratory distress syndrome (ARDS) and post-cardiac surgery to the FUNDICU criteria improved sensitivity to 97% with a specificity of 63%. The remaining 12 patients lacked EORTC-MSG host factors and were not in the ICU, highlighting a novel classification system.

Conclusions

EORTC-MSG and FUNDICU IPA classification systems are useful for the assignment of most patients with IPA. Incorporating postoperative complications after cardiac surgery and ARDS enhanced the diagnostic accuracy of FUNDICU.
Congenital Toxoplasmosis: Fewer Clinical Signs at 3 Years of Age Over the Last 15 Years but Stable Risk of Materno-fetal Transmission
Authors: Wallon Martine , Ksiazek Elea , Journé Antoine , Dupont Damien , Menotti Jean , Peyron François , Binquet Christine
Published: December 2024

The risk and severity of congenital toxoplasmosis were estimated using data from 2455 consecutive mother–child pairs. Clinical signs at 3 years were halved in the 177 children born since 2009 compared with 1996–2008 (odds ratio = .49; 95% CI: .28–.85). Materno-fetal transmission rates remained stable from 1992 to 2021.
Optimal Cutoff Values and Utility of High-Sensitivity Troponin T and NT-proBNP for the Risk Stratification of Patients with Acute Pulmonary Embolism
Authors: Matthews Timothy M , Peters Gregory A , Wang Grace , Horick Nora , Chang Kyle E , Harshbarger Savanah , Prucnal Christiana , Birrenkott Drew A , Stannek Karsten , Lee Eun Sang , Dhar Isabel , Wrenn Jesse O , Stubblefield William B , Kabrhel Christopher
Published: December 2024

Background

Guidelines recommend using high-sensitivity troponin T (hsTnT) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) to risk stratify hemodynamically stable patients with acute pulmonary embolism (PE). However, there are no evidence-based cutoff values defined for this clinical application.

Methods

We performed a single-center, retrospective cohort study of patients with imaging-confirmed PE and hsTnT and/or NT-proBNP (ElecsysTM, Roche) measured 12 h before or 24 h after PE Response Team (PERT) activation. We excluded hypotensive patients. Our primary outcome was a composite of adverse outcomes or critical interventions within 7 days. We calculated the area under the receiver operating curve (AUC, ROC) for hsTnT and NT-proBNP and determined the optimal cutoffs using the distance from (0,1). We performed a subgroup analysis on patients with PE and right ventricular dysfunction on imaging.

Results

Two hundred thirty-four patients were included in the hsTnT analysis, and 727 in the NT-proBNP analysis. Mean age was 62 years (SD = 17) and 47% were female. The AUC for hsTnT was 0.64 (95% CI, 0.56–0.71) with an optimal cutoff of 46 ng/L, corresponding to a sensitivity of 59% (95% CI, 49–69) and a specificity of 61% (95% CI, 53–69). The AUC for NT-proBNP was 0.56 (95% CI, 0.51–0.61) with an optimal cutoff of 1092 pg/mL, corresponding to a sensitivity of 53% (95% CI, 45–61) and a specificity of 59% (95% CI, 55–63).

Conclusion

We identified an optimal cutoff of 46 ng/L for hsTnT and 1092 pg/mL for NT-proBNP, though the AUC for both markers suggests low to moderate performance for the risk stratification of initially hemodynamically stable PERT patients. Use of these biomarkers to risk stratify PE may require reconsideration.
Early Onset Active Inflammatory Bowel Disease Is Associated With Psychiatric Comorbidities: A Multi-Network Propensity-Matched Cohort Study
Authors: Nadeem Ahmed , Donohue Sydney , Shah Fatima Zehra , Perez Jaime Abraham , Harper Elleson , Sinh Preetika , Padival Ruthvik , Cooper Gregory , Katz Jeffry , Cominelli Fabio , Regueiro Miguel , Mansoor Emad
Published: December 2024

Background

Psychiatric disease burden in patients with Inflammatory bowel disease (IBD) has risen substantially over the past few decades. However, there is limited data on the relationship between IBD disease activity and the incidence of psychiatric comorbidities. We sought to conduct a population-based study to investigate the impact of early onset disease activity in newly diagnosed IBD patients on psychiatric disease diagnoses and medication usage.

Methods

We performed a retrospective cohort study using the TriNetX database. We identified all adult patients diagnosed with IBD and documented IBD-specific medication use. We stratified these IBD patients into 2 cohorts based on IBD Disease Activity, occurring 6 months to 1 year after initial IBD diagnosis. Active IBD was defined as the utilization of steroids and/or elevated fecal calprotectin [≥200 µg/g] occurring 6 months to 1 year after initial IBD diagnosis. We examined the outcomes of psychiatric disease diagnoses and psychotropic medication prescriptions occurring 1 year after the initial diagnosis.

Results

Out of 69 105 patients with an IBD diagnosis during the study period, after propensity score matching, 16 922 IBD patients each were included in the 2 cohorts based on disease activity. Patients with active IBD had significantly higher odds of developing major depressive disorder, anxiety disorder, bipolar disorder, alcohol use disorder, opiate use disorder, attention deficit hyperactivity disorder, and obsessive-compulsive disorder. Additionally, patients with active IBD also had significantly higher odds of using all studied psychotropic medications, including antidepressants, antipsychotic medications, anxiolytics, sedatives, hypnotic medications, mood stabilizers, stimulant medications, and medications used for substance use disorders (including alcohol, opioid, and tobacco use).

Conclusions

Active IBD shortly after the IBD diagnosis is associated with a higher incidence of psychiatric comorbidities. Awareness of behavioral health in IBD is important, and proper treatment is necessary.