bluuebunny/crossref_metadata_2025 huggingface dataset:
FSP1 stem/progenitor cells are essential for TMJ growth and homeostasis
Authors: Tuwatnawanit Ticha , Wessman Wilma , Belisova Denisa , Sumbalova Zuzana , Tucker Abigail S , Anthwal Neal
Published: August 2024

The temporomandibular joint (TMJ) is one of the most used joints in the body. Defects and wear in the cartilage of the joint, condyle, and fibrocartilage disc lie at the heart of many common TMJ disorders. During postnatal development the condyle acts as a growth centre for the mandible with cells moving as a conveyor belt away from the top of the condyle as they differentiate. The superficial layers of the condyle have been proposed to contain stem/progenitor populations to allow growth and maintain homeostasis. Here we have focused on the role of FSP1 (also known as S100a4), as a key fibroblast stem/progenitor marker for the condyle. Lineage tracing using FSP1-Cre;mTmG mice revealed that FSP1-positive cells were restricted to the superficial fibroblast zone giving rise to all layers of the condyle over time. The FSP1-expressing cells overlapped with other putative stem cell markers of the condyle, Gli1 and Scleraxis. BrdU pulse chase experiments highlighted that a subset of FSP1 fibrocartilage were label-retaining, suggesting that FSP1 labels a novel stem/progenitor cell population in the condyle. Destruction of FSP1-expressing cells by conditional diphtheria toxin activity in FSP1-Cre;DTA mice resulted in severe TMJ osteoarthritis (TMJOA) with loss of the cartilage structure. Lgr5 expressing cells in the superficial layer of the condyle, have previously been shown to create a Wnt inhibitory niche. FSP1 expression postnatally was associated with a reduction in canonical Wnt activity in the condyle. Importantly, constitutive activation of Wnt/β catenin in FSP1 cells, led to a downregulation of FSP1 and progressive postnatal loss of TMJ condylar hyaline cartilage due to loss of the superficial stem/progenitor cells. These data demonstrate a novel role for FSP1-expressing cells in the superficial zone in growth and maintenance of the TMJ condylar cartilage and highlight the importance of regulating Wnt activity in this population.
Two distinct oscillatory auxin signals define the plasticity of lateral rooting inArabidopsis thaliana
Authors: Ren Chengzhi , Bodendorf Jule , Kleine-Vehn Jürgen
Published: August 2024

The so-called root clock defines lateral root pre-branch sites (PBS) but how these sites contribute to the root system architecture remains incompletely understood (1,2,3,4). Here we reveal in the model plantArabidopsis thalianathat two distinct oscillatory systems for the phytohormone auxin coordinate the spatial and temporal identity of PBS, jointly defining the lateral root density. We followed auxin signalling dynamics for days and thereby detected a systemic auxin signal oscillating in the mature primary root, which is distinct from the previously described root clock at the root tip. While the root clock spatially primes the PBS in the growing root tip, the systemic oscillatory auxin signal temporally controls the auxin-dependent identity of these PBS. Light perception in the shoot defines the strength of the systemic auxin signal and thereby controls the auxin-reliant ability of PBSs to develop into lateral roots. Moreover, PHYB and CRY1 mediate the light-dependent integration of other environmental signals, such as ambient temperature, into the control systemic auxin signalling and lateral root density. Our work reveals how two spatially distinct oscillatory auxin signals define the plasticity of plant root development in response to fluctuating conditions.
A virtual clinical trial of psychedelics to treat patients with disorders of consciousness
Authors: Alnagger Naji L.N. , Cardone Paolo , Martial Charlotte , Sanz Perl Yonatan , Mindlin Ivan , Sitt Jacobo D , Roseman Leor , Carhart-Harris Robin , Nutt David , Mallaroni Pablo , Mason Natasha L , Ramaekers Johannes G , Bonhomme Vincent , Laureys Steven , Deco Gustavo , Gosseries Olivia , Nunez Pablo , Annen Jitka
Published: August 2024

Disorders of consciousness (DoC), including the unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS), have limited treatment options. Recent research suggests that psychedelic drugs, known for their complexity-enhancing properties, could be promising treatments for DoC. This study uses whole-brain computational models to explore this potential. We created individualised models for DoC patients, optimised with empirical fMRI and diffusion-weighted imaging (DWI) data, and simulated the administration of LSD and psilocybin. We used an in-silico perturbation protocol to distinguish between different states of consciousness, including DoC, anaesthesia, and the psychedelic state, and assess the dynamical stability of the brains of DoC patients pre- and post-psychedelic simulation. Our findings indicate that LSD and psilocybin shift DoC patients' brains closer to criticality, with a greater effect in MCS patients. In UWS patients, the treatment response correlates with structural connectivity, while in MCS patients, it aligns with baseline functional connectivity. This virtual clinical trial lays a computational foundation for using psychedelics in DoC treatment and highlights the future role of computational modelling in drug discovery and personalised medicine.
The Rab7-Epg5 and Rab39-ema modules cooperately position autophagosomes for efficient lysosomal fusions
Authors: Boda Attila , Balázs Villő , Nagy Anikó , Hargitai Dávid , Lippai Mónika , Simon-Vecsei Zsófia , Molnár Márton , Fürstenhoffer Fanni , Juhász Gábor , Lőrincz Péter
Published: August 2024

Macroautophagy, a major self-degradation pathway in eukaryotic cells, utilizes autophagosomes to transport self-material to lysosomes for degradation. While microtubular transport is crucial for the proper function of autophagy, the exact roles of factors responsible for positioning autophagosomes remain incompletely understood. In this study, we performed a loss-of-function genetic screen targeting genes potentially involved in microtubular motility. A genetic background that blocks autophagosome-lysosome fusions was used to accurately analyze autophagosome positioning. We discovered that pre-fusion autophagosomes move towards the non-centrosomal microtubule organizing center (ncMTOC) inDrosophilafat cells, which requires a dynein-dynactin complex. This process is regulated by the small GTPases Rab7 and Rab39 together with their adaptors: Epg5 and ema, respectively. The dynein-dependent movement of vesicles toward the nucleus/ncMTOC is essential for efficient autophagosomal fusions with lysosomes and subsequent degradation. Remarkably, altering the balance of kinesin and dynein motors changes the direction of autophagosome movement, indicating a competitive relationship where normally dynein-mediated transport prevails. Since pre-fusion lysosomes were positioned similarly to autophagosomes, it indicates that pre-fusion autophagosomes and lysosomes converge at the ncMTOC, which increases the efficiency of vesicle fusions.
Development of SacB-based Counterselection for Efficient Allelic Exchange inFusobacterium nucleatum
Authors: Zhou Peng , Bibek G C , Hu Bo , Wu Chenggang
Published: August 2024

Fusobacterium nucleatum, prevalent in the oral cavity, is significantly linked to overall human health. Our molecular comprehension of its role in oral biofilm formation and its interactions with the host under various pathological circumstances has seen considerable advancements in recent years, primarily due to the development of various genetic tools for DNA manipulation in this bacterium. Of these, counterselection-based unmarked in-frame mutation methods have proved notably effective. Under suitable growth conditions, cells carrying a counterselectable gene die, enabling efficient selection of rare defined allelic exchange mutants. ThesacBgene fromBacillus subtilis, encoding levansucrase, is a widely used counterselective marker partly due to the easy availability of sucrose. Yet, its potential application inF. nucleatumgenetic study remains untested. We demonstrated thatF. nucleatumcells expressingsacBin either a shuttle or suicide plasmid exhibit a lethal sensitivity to supplemental sucrose. Utilizing sucrose counterselection, we created an in-frame deletion of theF. nucleatum tonBgene, a critical gene for energy-dependent transport processes in Gram-negative bacteria, and a precise knockin of the luciferase gene immediately following the stop codon of thehslOgene, the last gene of a five-gene operon possible related to the natural competence ofF. nucleatum. Post counterselection with 5% sucrose, chromosomal plasmid loss occurred in all colonies, leading to gene alternations in half of the screened isolates. ThissacB-based counterselection technique provides a reliable method for isolating unmarked gene mutations in wild-typeF. nucleatum, enriching the toolkit for fusobacterial research.

IMPORTANCE

Investigations intoFusobacterium nucleatum’s role in related diseases significantly benefit from the strategies of creating unmarked gene mutations, which hinge on using a counterselective marker. Previously, thegalk-based allelic exchange method, while effective, faced an inherent limitation – the need for a modified host. This study aims to surmount this limitation by substitutinggalKwithsacBfor gene modification inF. nucleatum. Our application of thesacB-based methodology successfully yielded atonBin-frame deletion mutant and a luciferase gene knockin at the precise chromosomal location in the wild-type background. The new method augments the existing toolkit forF. nucleatumresearch and has far-reaching implications due to the easy accessibility to the counterselection compound sucrose. We anticipate its broader adoption in further exploration, thereby reinforcing its critical role in propelling our understanding ofF. nucleatum.
Chaotic dynamics for homeostatic hematopoiesis
Authors: Jia Dongya , Salazar-Cavazos Emanuel , West Timothy , Liang Shen-Huan , Costa Raquel , Clavijo-Salomon Maria , Huang April , Trinchieri Giorgio , Lionakis Michail , Mukherjee Ratnadeep , Altan-Bonnet Grégoire
Published: August 2024

Hematopoiesis is a highly dynamical and stochastic process, challenging our understanding of homeostasis. Clinical studies of leukemia or neutropenic patients revealed that multiple blood cell types fluctuate spontaneously with large yet regular oscillations of their frequencies. Yet the stability of hematopoiesis in healthy individuals remains understudied. Here we report on both cross-sectional and longitudinal studies of dozens of healthy mice, through high-dimensional mass and spectral cytometry, to understand hematopoiesis at homeostasis. We found that all cell types in the bone marrow, blood, and spleen exhibit large variations of frequency (e.g., with coefficients of variation larger than 1). While the frequencies of individual cell type fluctuate, there existed extensive and robust correlations/anti-correlations between cell types, exemplified by the pronounced anti-correlation between blood neutrophils and B cells. Through longitudinal study of the blood content of healthy mice, we found that leukocyte fluctuations are ergodic yet subject to chaotic behaviors characterized by a broad spectrum of characteristic timescales. We then built a minimal mathematical model to capture these dynamical features of hematopoiesis (fluctuations, correlations, and chaos) and explain how the accumulation of B cells (e.g. during lymphoma development) would transition the blood cell dynamics from chaos to oscillations (as observed clinically). Finally, we demonstrated the ubiquity and consistency of the correlated fluctuations in hematopoiesis by comparing mouse cohorts of different genetic backgrounds and ages. To conclude, we discuss how study of hematopoiesis must factor in the newfound chaotic dynamics at homeostasis, towards better modeling the responses to perturbations.
An IL-17-DUOX2 axis controls gastrointestinal colonization byCandida albicans
Authors: Kakade Pallavi , Burgueno Juan F , Sircaik Shabnam , Ponde Nicole , Li Jinke , Ene Iuliana V , Kim Jiwoong , Liang Shen-Huan , Yunker Rebecca , Akiba Yasutada , Vaishnava Shipra , Kaunitz Jonathan D , Way Sing Sing , Koh Andrew Y , Gaffen Sarah , Abreu Maria T , Bennett Richard J
Published: August 2024

Candida albicansis a ubiquitous fungus in the human gut microbiome as well as a prevalent cause of opportunistic mucosal and systemic disease. There is currently little understanding, however, as to how crosstalk betweenC. albicansand the host regulates colonization of this key niche. Here, we performed expression profiling on ileal and colonic tissues in germ-free mice colonized withC. albicansto define the global response to this fungus. We reveal thatDuox2andDuoxa2, encoding dual NADPH oxidase activity, are upregulated in both the ileum and colon, and that induction requires theC. albicansyeast-hyphal transition and the hyphal-specific toxin candidalysin. Hosts lacking the IL-17 receptor failed to upregulateDuox2/Duoxa2in response toC. albicans, while addition of IL-17A to colonoids induced these genes together with the concomitant production of hydrogen peroxide. To directly define the role ofDuox2/Duoxa2in fungal colonization, antibiotic-treated mice lacking intestinal DUOX2 activity were evaluated forC. albicanscolonization and host responses. Surprisingly, loss of DUOX2 function reduced fungal colonization at extended time points (>17 days colonization) and increased the proportion of hyphal cells in the gut. IL-17A levels were also elevated inC. albicans-colonized mice lacking functional DUOX2 highlighting cross-regulation between this cytokine and DUOX2. Together, these experiments reveal novel links between fungal cells, candidalysin toxin and the host IL-17-DUOX2 axis, and that a complex interplay between these factors regulatesC. albicansfilamentation and colonization in the gut.
Extending the IICR to multiple genomes and identification of limitations of some demographic inferential methods
Authors: Chikhi Lounès , Rodríguez Willy , Paris Cyriel , Ha-Shan Marine , Jouniaux Alexane , Arredondo Armando , Noûs Camille , Grusea Simona , Corujo Josué , Lourenço Inês , Boitard Simon , Mazet Olivier
Published: August 2024

Reconstructing the demographic history of populations and species is one of the greatest challenges facing population geneticists. [50] introduced, for a sample of sizek= 2 haploid genomes, a time- and sample-dependent parameter which they called the IICR (inverse instantaneous coalescence rate). Here we extend their work to larger sample sizes and focus onTk, the time to the first coalescence event in a haploid sample of sizekwherek≥ 2. We define the IICRkas the Inverse Instantaneous Coalescence Rate amongklineages. We show that (i) under a panmictic populationis equivalent toNe, (ii) the IICRkcan be obtained by either simulatingTkvalues or by using theQ-matrix approach of [61] and we provide the corresponding Python and R scripts. We then study the properties of theunder a limited set ofn-island and stepping-stone models. We show that (iii) in structured models theis dependent on the sample size and on the sampling scheme, even when the genomes are sampled in the same deme. For instance, we find thatplots for individuals sampled in the same deme will be shifted towards recent times with a lower plateau askincreases. We thus show that (iv) thecannot be used to represent “the demographic history” in a general sense, (v) thecan be estimated from real or simulated genomic data using the PSMC/MSMC methods [44, 65] (vi) the MSMC2 method produces smoother curves that infer something that is not the, but are close to thein the recent past when all samples are obtained from the same deme. Altogether we argue that the PSMC, MSMC and MSMC2 plots are not expected to be identical even when the genomes are sampled from the same deme, that none can be said to represent the “demographic history of populations” and that they should be interpreted with care. We suggest that the PSMC, MSMC and MSMC2 could be used together with theto identify the signature of population structure, and to develop new strategies for model choice.
Modulating Neutrophil Extracellular Trap FormationIn Vivowith Locoregional Precision using Differently Charged Self-Assembled Hydrogels
Authors: Lopez-Silva Tania L. , Anderson Caleb F. , Schneider Joel P.
Published: August 2024

Neutrophil extracellular traps (NETs) are DNA networks released by neutrophils first described as a defense response against pathogens but have since been associated with numerous inflammatory diseases. The ability to induce NETs with locoregional specificityin vivocould facilitate studying this response in the context of disease and therapy with unprecedented control. We report the unexpected discovery that hydrogel charge predictably modulates the formation of NETs. Positively charged gels induce rapid NET release whereas negatively charged gels do not. This differential immune response to our self-assembled peptide gels enabled the development of a material platform that allows rheostat-like modulation over the degree of NET formation with anatomical and locoregional control.
Benchmarking DNA Foundation Models for Genomic Sequence Classification
Authors: Feng Haonan , Wu Lang , Zhao Bingxin , Huff Chad , Zhang Jianjun , Wu Jia , Lin Lifeng , Wei Peng , Wu Chong
Published: August 2024

The rapid advancement of DNA foundation language models has revolutionized the field of genomics, enabling the decoding of complex patterns and regulatory mechanisms within DNA sequences. However, the current evaluation of these models often relies on fine-tuning and limited datasets, which introduces biases and limits the assessment of their true potential. Here, we present a benchmarking study of three recent DNA foundation language models, including DNABERT-2, Nucleotide Transformer version-2 (NT-v2), and HyenaDNA, focusing on the quality of their zero-shot embeddings across a diverse range of genomic tasks and species through analyses of 57 real datasets. We found that DNABERT-2 exhibits the most consistent performance across human genome-related tasks, while NT-v2 excels in epigenetic modification detection. HyenaDNA stands out for its exceptional runtime scalability and ability to handle long input sequences. Importantly, we demonstrate that using mean token embedding consistently improves the performance of all three models compared to the default setting of sentence-level summary token embedding, with average AUC improvements ranging from 4.3% to 9.7% for different DNA foundation models. Furthermore, the performance differences between these models are significantly reduced when using mean token embedding. Our findings provide a framework for selecting and optimizing DNA language models, guiding researchers in applying these tools effectively in genomic studies.
Creating and leveraging bespoke large-scale knowledge graphs for comparative genomics and multi-omics drug discovery with SocialGene
Authors: Clark Chase M. , Kwan Jason C
Published: August 2024

The rapid expansion of multi-omics data has transformed biological research, offering unprecedented opportunities to explore complex genomic relationships across diverse organisms. However, the vast volume and heterogeneity of these datasets presents significant challenges for analyses. Here we introduce SocialGene, a comprehensive software suite designed to collect, analyze, and organize multi-omics data into structured knowledge graphs, with the ability to handle small projects to repository-scale analyses. Originally developed to enhance genome mining for natural product drug discovery, SocialGene has been effective across various applications, including functional genomics, evolutionary studies, and systems biology. SocialGene's concerted Python and Nextflow libraries streamline data ingestion, manipulation, aggregation, and analysis, culminating in a custom Neo4j database. The software not only facilitates the exploration of genomic synteny but also provides a foundational knowledge graph supporting the integration of additional diverse datasets and the development of advanced search engines and analyses. This manuscript introduces some of SocialGene's capabilities through brief case studies including targeted genome mining for drug discovery, accelerated searches for similar and distantly related biosynthetic gene clusters in biobank-available organisms, integration of chemical and analytical data, and more. SocialGene is free, open-source, MIT-licensed, designed for adaptability and extension, and available from github.com/socialgene.
Y chromosome-coded HSATII repeats may contribute to higher incidence of cancer in men
Authors: Hegyi Hedi , Lexa Matej
Published: August 2024

It has been observed that men have a shorter lifespan and higher incidence of certain cancers than women. We postulate here that this phenomenon may be attributed to the toxicity of the Y chromosome, owing to the expression of normally silent HSATII repeats in cancer, abundantly present on chromosome Y. Investigating the contribution of all repetitive elements to chromatin interactions using a genome-wide HiC set derived from a colon cancer cell line (HCT116), we found several anomalies regarding satellite HSATII elements when compared to other genomic repeat types: (i) HSATII repeats tend to form HiC pairs mostly with their own kind, and depleted in most heterologous repeat pairs, whereas other types of repeats readily form heterologous HiC pairs; (ii) when treated with 5-aza, a chemotherapeutic agent, the number of long-distance HSATII-overlapping HiC pairs significantly decreased when compared to the untreated samples; (iii) and most importantly, in the treated samples interchromosomal HiC read pairs involving a chromosome Y-located repeat and an HSATII repeat on either end almost completely disappear. (iv) We also found that HSATII repeats lack overlap with other types of repeats. To account for these anomalies we queried non-B DNA structure forming such as G-quadruplexes and transcription-related triplex forming. We found that Y chromosome-coded HSATII repeats form significantly stronger triplexes than HSATII repeats on other chromosomes, their strength significantly correlating with the number of HiC reads they overlap with. We surmise that the above phenomena may cause the higher incidence of cancer in men and may lead to the disappearance of the Y chromosome observed in cancerous cells in men.
Characterization and analysis of neuronal signaling using microelectrode array combined with rapid and localized cooling device for cryo-neuromodulation
Authors: Kim Jaehyun , Lee Jong Seung , Noh Soyeon , Seo Eunseok , Lee Jungchul , Kim Taesung , Cho Seung-Woo , Kim Gunho , Kim Sung Soo , Park Jungyul
Published: August 2024

Cryoanesthesia––a purely physical anesthesia treatment that freezes tissue and attenuate nerve activity––can provide fast treatment through freezing and thawing of cryo-machine and is inexpensive compared to other anesthetics. However, cryoanesthesia has not been widely adopted because securing safe and effective conditions requires quantitative measurement and analysis of neuronal signaling during freezing and recovery, for which research tools are limited. A lack of rapid and localized cooling technologies for quantitative cellular level analysis, in particular, hinders research on not only the optimal cryo-modulation of neuronal activities but also its influence to neighboring cells via cellular networks. Here, we introduce a novel cryo-neuromodulation platform, a high-speed precision probe-type cooling device (∼20°C/s at cooling) that provides localized cooling combined with a microelectrode array (MEA) system. We explored the temperature conditions for efficient silencing and recovery of neuronal activities without cell damage. We found that electrical activities of neurons were fully recovered within 1 minute of cooling duration with the maximum cooling speed, which was also confirmed with calcium imaging. The impact of silenced neurons on the neighboring neural network was explored using the localized cooling and we perceived that its influence can be transmitted if the neuronal network is well organized. Our new cryo-device provides rapid and reversible control of neural activities, which allows not just quantitative analysis of the network dynamics, but also new applications in clinical settings.
TAVI PACER: A two-step risk score for prediction of permanent pacemaker implantation after TAVI.
Authors: Janiszewski Alexandra , Lueg Julia Christina , Schulze Daniel , Juri Benjamin , Morell Louis , Hajduczenia Maria , Hennig Pierre , Erbay Aslihan , Lembcke Alexander , Niehues Stefan Markus , Landmesser Ulf , Stangl Karl , Leistner David Manuel , Dreger Henryk , Tscholl Verena
Published: August 2024

Background: The need for permanent pacemaker implantation (PPMI) remains one of the most frequent complications after transcatheter aortic valve implantation (TAVI). This study aimed to develop a novel, two-step risk score to predict PPMI probability after TAVI and to implement it into a user-friendly website. Our risk score addresses the gap in existing data on current prosthesis generations and provides a new and clinically motivated approach to calculating the risk for PPMI. Methods: Between January 2019 and December 2020, 1039 patients underwent TAVI at our institution. We retrospectively evaluated clinical, electrocardiographic, echocardiographic, computed tomographic, and periprocedural data. Patients with prior PPMI were excluded. We developed a prediction model for the occurrence of PPMI, initially using 55 patient and procedural characteristics. Results: We included 836 patients (mean age 80.2 ± 9.1 years, 50.5% female), among whom 140 patients (16.6%) needed PPMI within 30 days after TAVI. In the first step, the TAVI PACER score calculates an individual risk for PPMI, including 14 preprocedural risk factors such as preexisting right bundle branch block, atrioventricular block, left bundle branch block, bradycardia, interventricular septum thickness in diastole, NYHA class, and aortic annulus perimeter. In the second step, intraprocedural variables are included to demonstrate how PPMI risk can vary based on the chosen valve type and implantation depth. The TAVI PACER score can predict PPMI with a sensitivity of 76% and specificity of 72% (AUC = 0.8). Conclusions: The TAVI PACER score provides a novel tool for daily clinical practice, which predicts the individual risk for PPMI after TAVI based on various patient and two procedural characteristics.
Total plasma cfDNA methylation in kidney transplant recipients provides insight into acute allograft rejection pathophysiology
Authors: Spector Benjamin L , Koseva Boryana S , Sante Drinnan , Cheung Warren A , Alisch Reid S , Kats Alexander , Bergmann Phillip , Grundberg Elin , Wyckoff Gerald J , Willig Laurel K
Published: August 2024

Background: Acute rejection threatens kidney allograft longevity. Cell-free DNA (cfDNA) is a real-time marker of organ injury and immune response. Donor-derived cfDNA (dd-cfDNA) has been leveraged as a biomarker of rejection, however, its reliability as a screening tool is unclear. DNA methylation is an epigenetic marker that informs regulatory element activity. We aim to elucidate differential methylation of total plasma cfDNA derived from pediatric kidney transplant recipients in the presence compared to absence of acute rejection. In doing so, we hope to exploit the property of cfDNA as a real-time biomarker and build on available testing to identify genes and processes participating in acute rejection pathophysiology in kidney transplantation. Methods: Twenty plasma cfDNA samples from pediatric kidney transplant recipients were collected at the time of allograft biopsy. Using whole genome bisulfite sequencing, differentially methylated CpG residues (≥20% difference in methylation rate, q-value <0.05) were identified in presence (N = 7) vs absence (N = 9) of acute rejection. Separate analyses were performed comparing those with borderline rejection (N = 4) to those with rejection, and to those without rejection. Differentially methylated cytosines were then assessed for gene associations and pathway enrichments. Results: In the comparison of acute rejection to non-rejection samples, there were 34,356 differentially methylated cytosines corresponding to 1,269 associated genes, and 533 enriched pathways. These numbers were all substantially greater (4-13x) than the comparisons made between acute rejection against those with borderline rejection, and between non-rejection against borderline rejection. Prominently enriched pathways between samples of individuals with and without acute rejection were related to immune cell regulation, inflammatory response, lipid metabolism, and tryptophan-kynurenine metabolism. Conclusions: Our data suggest methylation plays a role in development of or response to acute kidney allograft rejection. Specifically, differentially methylated pathways associated with acute rejection include those related to immune and inflammatory responses.
Trust in Health Information Sources Among Patients with Systemic Lupus Erythematosus in the Social Networking Era: The TRUMP2-SLE Multicentre Study
Authors: Ichikawa Takanori , Kishida Dai , Shimojima Yasuhiro , Yajima Nobuyuki , Oguro Nao , Yoshimi Ryusuke , Sakurai Natsuki , Hidekawa Chiharu , Sada Ken-ei , Miyawaki Yoshia , Hayashi Keigo , Shidahara Kenta , Ishikawa Yuichi , Sekijima Yoshiki , Kurita Noriaki
Published: August 2024

Objectives The rise of social networking services (SNS) has significantly impacted how patients with systemic lupus erythematosus (SLE) acquire health information, potentially influencing their discussions with healthcare providers. This study aimed to identify the preferences, actual access, and trust levels in various health information sources among SLE patients, along with associated factors. Methods A cross-sectional study was conducted from June 2020 to August 2021 across five university medical centres in Japan, involving 510 SLE patients aged 20 years and older. The study measured access to and preferences for health information sources, including SNS, and assessed trust in these sources. Factors influencing, such as internet usage and health literacy (HL) (functional, communicative, and critical), were analyzed using Poisson regression with robust error variance. Results Among the respondents, 98.2% expressed trust in doctors, whereas lower trust was observed in websites/blogs (52.0%) and SNS (26.9%). Despite this, the internet was the most frequent initial source of health information (45.3%), encompassing medical institutions' homepages, patient blogs, Twitter, and Instagram. Longer internet use was linked to increased trust in homepages/blogs and SNS. Higher functional HL correlated with greater trust in doctors and lower trust in websites/blogs and SNS, while higher communicative HL was associated with increased trust in doctors, homepages, and blogs. Conclusion Many SLE patients seek online health information, including SNS, before consulting rheumatologists. Internet usage duration and multidimensional HL influence trust in online health information sources. Rheumatologists and healthcare providers should account for these factors when disseminating health information and engaging with patients.
RANDOM NUMBER GENERATION: A ANALYSIS OF BENFORD'S LAW IN UNDERGRADS STUDENTS AND GERIATRICS PATIENTS
Authors: Alves de Freitas Martins Pedro Henrique , Fernandes de Godoy Moacir
Published: August 2024

Objectives: Study the correlation between RNG by human cognition and Benford's Law in undergraduate students at a Medical School in the countryside of the state of Sao Paulo and geriatric clinic patients. Design: The study collected data from the students and patients from the Robust Elderly Clinic of a tertiary Hospital between August 2022 and July 2023. Data collection involved a questionnaire on age, gender, education, ethnicity, occupation, and a table with 5 rows and 10 columns for the insertion of 50 numbers, chosen by the participant. Results: A total of 263 forms were collected. The average age was 27.10 (IQR- 3) years, with 66.5% being female. Frequencies of the first significant digit were: 25.59% for 1; 15.35% for 2; 10.98% for 3; 8.65% for 4; 9.67% for 5; 7.02% for 6; 8.22% for 7; 6.81% for 8, and 7.70% for 9. Applying the Chi-Square test, no statistically significant difference was found (critical χ 2 15.507; obtained χ 2 5.36). Applying Pearson's Coefficient, the value of r was 0.98. Using the Euclidean distance, the P-value was 0.9284. Conclusion: A high correlation between RNG by the human mind, in students and Robust Elderly patients, and Benford's Law was detected.
Mortality is lowest in overweight followed by obese and morbid obese patients and is highest in cachexia compared to normal weight in patients with the diagnosis of aortic stenosis.
Authors: Hashemzadeh Mehrtash , Soltani Moghadam Arman , Soltani Moghadam Saman , Movahed Mohammad Reza
Published: August 2024

Introduction: The obesity paradox has been seen in many cardiovascular conditions. The goal of this study was to evaluate whether it exists in patients with a diagnosis of aortic stenosis. Method: We used the Nationwide Inpatients Sample (NIS) database and ICD-10 coding for adults in different weight categories and with aortic stenosis diagnoses for 2016-2020. We evaluated the effect of weight on mortality using multivariate adjustment and the cox-regression model. Results: A total of 2,330,584 patients were diagnosed with aortic stenosis. Mortality was lowest in overweight followed by obesity and morbid obesity (1.74% vs. 2.43% vs 3.2% in comparison to normal weight mortality of 4.4%, p<0.001) and it was highest in patients with cachexia (mortality of 14.5%). After adjusting for baseline characteristics and comorbid conditions, the relation between mortality and weights remained unaltered. Multivariate adjusted odds ratios (OR) were as follows: Overweight OR 0.4, CI 0.31-0.6, p<0.001, Obesity: OR 0.64, CI 06-0.68, p<0.001, morbid obesity OR: 0.88, CI 0.83-0.94, P<0.001, Cachexia OR 3.31 CI: 3.04-3.62, p<0.001). Conclusion: Using the largest database, we found that in patients with a diagnosis of aortic stenosis, overweight followed by obesity and morbid obesity have the lowest mortality whereas cachexia has the highest mortality compared to normal-weight patients.
Protocol for the development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data
Authors: Deng Jiawen , Heybati Kiyan , Yadav Hemang
Published: August 2024

Introduction

Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical benefits, propofol is associated with increased risks of hypertriglyceridemia. Early identification of patients at risk for propofol-associated hypertriglyceridemia is crucial for optimizing sedation strategies and preventing adverse outcomes. Machine learning (ML) models offer a promising approach for predicting individualized patient risks of propofol-associated hypertriglyceridemia.

Methods and analysis

We propose the development of a ML model aimed at predicting the risk of propofol-associated hypertriglyceridemia in ICU patients receiving IMV. The study will utilize retrospective data from four Mayo Clinic sites. Nested cross-validation (CV) will be employed, with a 10-fold inner CV loop for model tuning and selection as well as an outer loop using leave-one-site-out CV for external validation. Feature selection will be conducted using Boruta and LASSO-penalized logistic regression. Data preprocessing steps include missing data imputation, feature scaling, and dimensionality reduction techniques. Six ML algorithms will be tuned and evaluated. Bayesian optimization will be used for hyperparameter selection. Global model explainability will be assessed using permutation importance, and local model explainability will be assessed using SHapley Additive exPlanations (SHAP).

Ethics and dissemination

The proposed ML model aims to provide a reliable and interpretable tool for clinicians to predict the risk of propofol-associated hypertriglyceridemia in ICU patients. The final model will be deployed in a web-based clinical risk calculator. The model development process and performance measures obtained during nested cross-validation will be described in a study publication to be disseminated in a peer-reviewed journal. The proposed study has received ethics approval from the Mayo Clinic Institutional Review Board (IRB #23-007416).

Strengths and limitations of this study

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Robust external validation using a nested cross-validation (CV) framework will help assess the generalizability of models produced from the modeling pipeline across different hospital settings.

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A diverse set of machine learning (ML) algorithms and advanced hyperparameter tuning techniques will be employed to identify the most optimal model configuration.

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Integration of feature explainability will enhance the clinical applicability of the ML models by providing transparency in predictions, which can improve clinician trust and encourage adoption.

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Reliance on retrospective data may introduce biases due to inconsistent or erroneous data collection, and the computational intensity of the validation approach may limit replication and future model expansion in resource-constrained settings.
Ultraplex microscopy: versatile highly-multiplexed molecular labeling and imaging across scale and resolution
Authors: Perez-Garza Janeth , Orea Jairo , Deane Zachary , Raimondi Gianna , Tripp Rebecca , Charles Imani , Ostroff Linnaea
Published: August 2024

The molecular organization of cells and tissue is challenging to study due to the inefficiency of multiplexed molecular labeling methods and the limited options for combining microscopy modalities in a single specimen, especially when high spatial resolution is needed. Here we describe ultraplex microscopy, which combines serial multiplexing, ultrathin sectioning, and reversible embedding to circumvent incompatibilities between labeling and imaging techniques, enhance resolution, and expand multiplexing capacity within and across modalities. Samples can be labeled with antibodies, RNA probes, and tissue stains for imaging by brightfield, epifluorescence, super-resolution, and electron microscopy without specialized reagents or materials. We demonstrate applications in brain tissue including molecular profiling of single cells and axonal boutons, high-resolution molecular colocalization, and correlative imaging of fluorescent proteins with confocal and ultraplex microscopy. The power and versatility of ultraplex microscopy will be valuable in addressing currently intractable experimental questions in many systems and contexts.
Tissue determinants of the human T cell receptor repertoire.
Authors: Sureshchandra Suhas , Henderson James , Levendosky Elizabeth , Bhattacharyya Sankalan , Kastenschmidt Jenna M , Sorn Andrew M , Mitul Mahina Tabassum , Benchorin Aviv , Batucal Kyle , Daugherty Allyssa , Murphy Samuel JH , Thakur Chandrani , Trask Douglas , Ahuja Gurpreet , Moisan Annie , Tiffeau-Mayer Andreas , Saligrama Naresha , Wagar Lisa E
Published: August 2024

98% of T cells reside in tissues, yet nearly all human T cell analyses are performed from peripheral blood. We single-cell sequenced 5.7 million T cells from ten donors' autologous blood and tonsils and sought to answer key questions about T cell receptor biology previously unanswerable by smaller-scale experiments. We identified distinct clonal expansions and distributions in blood compared to tonsils, with surprisingly low (1-7%) clonal sharing. These few shared clones exhibited divergent phenotypes across bodily sites. Analysis of antigen-specific CD8 T cells revealed location as a main determinant of frequency, phenotype, and immunodominance. Finally, diversity estimates from the tissue recalibrates current repertoire diversity estimates, and we provide a refined estimate of whole-body repertoire. Given the tissue-restricted nature of T cell phenotypes, functions, differentiation, and clonality revealed by this dataset, we conclude that tissue analyses are crucial for accurate repertoire analysis and monitoring changes after perturbing therapies.
Recon8D: A metabolic regulome network from oct-omics and machine learning
Authors: Schildcrout Ryan , Smith Kirk , Bhowmick Rupa , Menon Suraj , Kapadia Minali , Kurtz Emily , Coffeen-Vandeven Anya , Chandrasekaran Sriram
Published: August 2024

The complexity and incompleteness of metabolic-regulatory networks make it challenging to predict metabolomes from other omics. Using machine learning, we predicted metabolomic variation across ~1000 different cancer cell lines from matched oct-omics data: genomics, epigenomics (histone post-translational modifications (PTMs) and DNA-methylation), transcriptomics, RNA splicing, miRNA-omics, proteomics, and phosphoproteomics. Overall, the metabolome is tightly associated with the transcriptome, while miRNAs, phosphoproteins and histone PTMs have the highest metabolic information per feature. Metabolites in peripheral metabolism are predictable via levels of corresponding enzymes, while those in central metabolism require combinatorial predictors in signaling and redox pathways, and may not reflect corresponding pathway expression. We reconstruct multiomic interaction subnetworks for highly predictable metabolites, and YAP1 signaling emerged as a top global predictor across 4 omic layers. We prioritize predictive multiomic features for single-cell and spatial metabolomics assays. Top predictors were enriched for synthetic-lethal interactions and synergistic combination therapies that target compensatory metabolic modulators.
Meta-analysis reveals limited reproducibility of lncRNA-related findings in hepatocellular carcinoma research
Authors: Necsulea Anamaria , Veber Philippe , Boldanova Tuyana , Ng Charlotte KY , Wieland Stefan , Heim Markus H
Published: August 2024

Background & Aims

The human genome comprises tens of thousands of long non-coding RNAs (lncRNAs), whose functionality is highly debated. In the field of hepatocellular carcinoma (HCC) research, as for other cancer types, lncRNAs are increasingly reported to act as oncogenes or tumor suppressors and are put forward as useful diagnostic or prognostic biomarkers. Here, we investigate the reliability of these claims by performing a meta-analysis of the associations between HCC and lncRNAs reported in the scientific literature, and by assessing lncRNA expression patterns in two HCC patient cohorts.

Approach & Results

While nowadays up to 6% of all HCC-related publications cite lncRNAs, we show that most reported associations between HCC and lncRNAs have not been reproduced. In general, lncRNAs are less often differentially expressed between HCC tissues and controls compared to protein-coding genes. However, HCC-associated lncRNAs are frequently up-regulated in tumor samples, consistent with the fact that they are often selected based on transcriptome-wide comparative analyses. We perform a detailed examination of the 25 lncRNAs that are most frequently cited in association with HCC. For 10 out of these 25 lncRNAs, including well known lncRNAs such asMALAT1,NEAT1,H19andXIST, we identify important conflicts between the biological roles and expression patterns previously reported for them in HCC and the expression patterns that we observe here. Finally, we observe that HCC-associated publications that cite lncRNAs are retracted three times more often than publications that cite protein-coding genes.

Conclusions

Our results thus highlight the poor reproducibility of lncRNA-related claims in association with HCC, which is problematic in a context where new biomarkers and molecular targets for therapy are greatly needed.
Chromosome breakage-replication/fusion enables rapid DNA amplification
Authors: Zhang Cheng-Zhong , Pellman David
Published: August 2024

DNA rearrangements are thought to arise from two classes of processes. The first class involves DNA breakage and fusion (“cut-and-paste”) without net DNA gain or loss. The second class involves aberrant DNA replication (“copy-and-paste”) and can produce either net DNA gain or loss. We previously demonstrated that the partitioning of chromosomes into aberrant structures of the nucleus, micronuclei or chromosome bridges, can generate cut-and-paste rearrangements by chromosome fragmentation and ligation. Surprisingly, in the progeny clones of single cells that have undergone chromosome bridge breakage, we identified large segmental duplications and short sequence insertions that are commonly attributed to copy-and-paste processes. Here, we demonstrate that both large duplications and short insertions are inherent outcomes of the replication and fusion of unligated DNA ends, a process we term breakage-replication/fusion (B-R/F). We propose that B-R/F provides a unifying explanation for complex rearrangement patterns including chromothripsis and chromoanasynthesis and enables rapid DNA amplification after chromosome fragmentation.
Benchmarking automated detection and classification approaches for monitoring of endangered species: a case study on gibbons from Cambodia
Authors: Clink Dena J. , Cross-Jaya Hope , Kim Jinsung , Ahmad Abdul Hamid , Hong Moeurk , Sala Roeun , Birot Hélène , Agger Cain , Vu Thinh Tien , Thi Hoa Nguyen , Chi Thanh Nguyen , Klinck Holger
Published: August 2024

Recent advances in deep and transfer learning have revolutionized our ability for the automated detection and classification of acoustic signals from long-term recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon (Nomascus gabriellae) calls collected using autonomous recording units (ARUs) in Andoung Kraleung Village, Cambodia. We compared the performance of support vector machines (SVMs), a quasi-DenseNet architecture (Koogu), transfer learning with pretrained convolutional neural network (ResNet50) models trained on the ‘ImageNet’ dataset, and transfer learning with embeddings from a global birdsong model (BirdNET) based on an EfficientNet architecture. We also investigated the impact of varying the number of training samples on the performance of these models. We found that BirdNET had superior performance with a smaller number of training samples, whereas Koogu and ResNet50 models only had acceptable performance with a larger number of training samples (>200 gibbon samples). Effective automated detection approaches are critical for monitoring endangered species, like gibbons. It is unclear how generalizable these results are for other signals, and future work on other vocal species will be informative. Code and data are publicly available for future benchmarking.