bluuebunny/crossref_metadata_2025 huggingface dataset:
A data management system for precision medicine
Authors: Jacobs John J. L. , Beekers Inés , Verkouter Inge , Richards Levi B. , Vegelien Alexandra , Bloemsma Lizan D. , Bongaerts Vera A. M. C. , Cloos Jacqueline , Erkens Frederik , Gradowska Patrycja , Hort Simon , Hudecek Michael , Juan Manel , Maitland-van der Zee Anke H. , Velázquez Sergio Navarro , Ngai Lok Lam , Rafiq Qasim A , Sanges Carmen , Tettero Jesse , van Os Hendrikus J. A. , Vos Rimke C. , de Wit Yolanda , van Dijk Steven
Published: February 2024

Introduction

Precision, or personalised medicine has advanced requirements for medical data management systems (MedDMSs). MedDMS for precision medicine should be able to process hundreds of parameters from multiple sites, be adaptable while remaining in sync at multiple locations, real-time syncing to analytics and be compliant with international privacy legislation. This paper describes the LogiqSuite software solution, aimed to support a precision medicine solution at the patient care (LogiqCare), research (LogiqScience) and data science (LogiqAnalytics) level. LogiqSuite is certified and compliant with international medical data and privacy legislations.

Method

This paper evaluates a MedDMS in five types of use cases for precision medicine, ranging from data collection to algorithm development and from implementation to integration with real-world data. The MedDMS is evaluated in seven precision medicine data science projects in prehospital triage, cardiovascular disease, pulmonology, and oncology.

Results

The P4O2 consortium uses the MedDMS as an electronic case report form (eCRF) that allows real-time data management and analytics in long covid and pulmonary diseases. In an acute myeloid leukaemia study data from different sources were integrated to facilitate easy descriptive analytics for various research questions. In the AIDPATH project, LogiqCare is used to process patient data, while LogiqScience is used for pseudonymous CAR-T cell production for cancer treatment. In both these oncological projects the data in LogiqAnalytics is also used to facilitate machine learning to develop new prediction models for clinical-decision support (CDS). The MedDMS is also evaluated for real-time recording of CDS data from U-Prevent for cardiovascular risk management and from the Stroke Triage App for prehospital triage.

Discussion

The MedDMS is discussed in relation to other solutions for privacy-by-design, integrated data stewardship and real-time data analytics in precision medicine.

Conclusion

LogiqSuite is used for multi-centre research study data registrations and monitoring, data analytics in interdisciplinary consortia, design of new machine learning / artificial intelligence (AI) algorithms, development of new or updated prediction models, integration of care with advanced therapy production, and real-world data monitoring in using CDS tools. The integrated MedDMS application supports data management for care and research in precision medicine.
X-chromosome loss rescues Sertoli cell maturation and spermatogenesis in Klinefelter syndrome
Authors: Winge Sofia B. , Skakkebaek Niels E. , Aksglaede Lise , Saritaş Gülizar , Rajpert-De Meyts Ewa , Goossens Ellen , Juul Anders , Almstrup Kristian
Published: February 2024

Klinefelter syndrome (47,XXY) causes infertility with a testicular histology comprising two types of Sertoli cell-only tubules, representing mature and immature-like Sertoli cells, and occasionally focal spermatogenesis. Here, we show that the immature Sertoli cells highly expressedXISTand have two X-chromosomes, while the mature Sertoli cells lackXISTexpression and have only one X-chromosome. Sertoli cells supporting focal spermatogenesis also lackXISTexpression and the additional X-chromosome, while the spermatogonia expressedXISTdespite having only one X-chromosome.XISTwas expressed in Sertoli cells until puberty, where a gradual loss was observed. Our results suggest that a micro-mosaic loss of the additional X-chromosome is needed for Sertoli cells to mature and to allow focal spermatogenesis.
Thermostability and binding properties of single-chained Fv fragments derived from therapeutic antibodies
Authors: Tadokoro Takashi , Tsuboi Harumi , Nakamura Kota , Hayakawa Tetsushi , Ohmura Reo , Kato Izumi , Inoue Masaki , Tsunoda Shin-ichi , Niizuma Sayaka , Okada Yukari , Otsuguro Satoko , Maenaka Katsumi
Published: February 2024

Small antibody fragments have recently been used as alternatives to full-length monoclonal antibodies in therapeutic applications. One of the most popular fragment antibodies is single-chain fragment variables (scFvs), consisting of variable heavy (VH) and variable light (VL) domains linked by a flexible peptide linker. scFvs have small molecular sizes, which enables good tissue penetration and low immunogenicity. Despite these advantages, the use of scFvs, especially for therapeutic purpose, is still limited because of the difficulty to regulate the binding activity and conformational stability. In this study, we constructed and analyzed 10 scFv fragments derived from 10 representatives of FDA-approved mAbs to evaluate their physicochemical properties. Differential scanning calorimetry analysis showed that scFvs exhibited relatively high but varied thermostability, from 50 to 70 °C of melting temperatures, and different unfolding cooperativity. Surface plasmon resonance analysis revealed that scFvs fragments that exhibit high stability and cooperative unfolding likely tend to maintain antigen binding. This study demonstrated the comprehensive physicochemical properties of scFvs derived from FDA-approved antibodies, providing insights into antibody design and development.
Unselfish meiotic drive maintains heterozygosity in a parthenogenetic ant
Authors: Lacy Kip D. , Hart Taylor , Kronauer Daniel J.C.
Published: February 2024

According to Mendel’s second law, chromosomes segregate randomly in meiosis. Non-random segregation is primarily known for cases of selfish meiotic drive in females, in which particular alleles bias their own transmission into the oocyte1,2. Here, we report a rare example of unselfish meiotic drive for crossover inheritance in the clonal raider ant,Ooceraea biroi. This species produces diploid offspring parthenogenetically via fusion of two haploid nuclei from the same meiosis3. This process should cause rapid genotypic degeneration due to loss of heterozygosity, which results if crossover recombination is followed by random (Mendelian) segregation of chromosomes4,5. However, by comparing whole genomes of mothers and daughters, we show that loss of heterozygosity is exceedingly rare, raising the possibility that crossovers are infrequent or absent inO. biroimeiosis. Using a combination of cytology and whole genome sequencing, we show that crossover recombination is, in fact, common, but that loss of heterozygosity is avoided because crossover products are faithfully co-inherited. This results from a programmed violation of Mendel’s law of segregation, such that crossover products segregate together rather than randomly. This discovery highlights an extreme example of cellular “memory” of crossovers, which could be a common yet cryptic feature of chromosomal segregation.
Microtubule-dependent orchestration of centriole amplification in brain multiciliated cells
Authors: Boudjema Amélie-Rose , Balagué Rémi , Jewett Cayla E , LoMastro Gina M , Mercey Olivier , Jord Adel Al , Faucourt Marion , Schaeffer Alexandre , Noûs Camille , Delgehyr Nathalie , Holland Andrew J , Spassky Nathalie , Meunier Alice
Published: February 2024

Centriole number must be restricted to two in cycling cells to avoid pathological cell divisions. Multiciliated cells (MCC), however, need to produce a hundred or more centrioles to nucleate the same number of motile cilia required for fluid flow circulation. These centrioles are produced by highjacking cell cycle and centriole duplication programs. However, how the MCC progenitor handles such a massive number of centrioles to finally organize them in an apical basal body patch is unclear. Here, using new cellular models and high-resolution imaging techniques, we identify the microtubule network as the bandleader, and show how it orchestrates the process in space and in time. Organized by the pre-existing centrosome at the start of amplification, microtubules build a nest of centriolar components from which procentrioles emerge. When amplification is over, the centrosome’s dominance is lost as new centrioles mature and become microtubule nucleators. Microtubules then drag all the centrioles to the nuclear membrane, assist their isotropic perinuclear disengagement and their subsequent collective apical migration. These results reveal that in brain MCC as in cycling cells, the same dynamics - from the centrosome to the cell pole via the nucleus-exists, is the result of a reflexive link between microtubules and the progressive maturation of new centrioles, and participates in the organized reshaping of the entire cytoplasm. On the other hand, new elements described in this work such as microtubule-driven organization of a nest, identification of a spatio-temporal progression of centriole growth and microtubule-assisted disengagement, may shed new light on the centriole duplication program.

Graphical Abstract
Genetic regulation of injury induced heterotopic ossification in adult zebrafish
Authors: Kaliya-Perumal Arun-Kumar , Celik Cenk , Carney Tom J. , Harris Matthew P. , Ingham Philip W.
Published: February 2024

Heterotopic ossification is the inappropriate formation of bone in soft tissues of the body. It can manifest spontaneously in rare genetic conditions or as a response to injury, known as acquired heterotopic ossification. There are several experimental models for studying heterotopic ossification from different sources of damage. However, their tenuous mechanistic relevance to the human condition, invasive and laborious nature and/or lack of amenability to chemical and genetic screens, limit their utility. To address these limitations, we developed a simple zebrafish injury model that manifests heterotopic ossification in response to micro-fractures in combination with muscle injury. These findings indicate that clinically-emulated injuries in zebrafish can lead to osteo-induction and proliferation as observed in heterotopic ossification inmyositis ossificans traumatica. Exploiting this model, we analysed the penetrance and expressivity of heterotopic ossification and defined the transcriptional response to trauma, identifying differentially regulated genes. Taking advantage of defined mutants in several of these candidates, we explored their impact on heterotopic bone formation. Our findings revealed that an increase in potassium channel Kcnk5b activity potentiates injury response. In contrast, we demonstrate that inflammatory responses are essential for the ectopic bone growth, as mutations in Interleukin 11 receptor paralogue (Il11ra) exhibit a drastically reduced ossification response. Based on these findings, we postulate that enhanced ionic signaling, specifically through Kcnk5b, regulates the intensity of the skeletogenic injury response, which, in part, requires immune response regulated by Il11ra.
Computational hemodynamic indices to identify Transcatheter Aortic Valve Implantation degeneration
Authors: Crugnola Luca , Vergara Christian , Fusini Laura , Fumagalli Ivan , Luraghi Giulia , Redaelli Alberto , Pontone Gianluca
Published: February 2024

Purpose

Structural Valve Deterioration (SVD) is the main limiting factor to the long-term durability of bioprosthetic valves, which are used for Transcatheter Aortic Valve Implantation (TAVI). The aim of this study is to perform a patient-specific computational analysis of post-TAVI blood dynamics to identify hemodynamic indices that correlate with a premature onset of SVD.

Methods

The study population comprises two subgroups: patients with and without SVD at long-term follow-up exams. Starting from pre-operative CT images, we created reliable post-TAVI scenarios by virtually inserting the bioprosthetic valve (stent and leaflets), and we performed numerical simulations imposing realistic inlet conditions based on patient-specific data. The numerical results were post-processed to build suitable synthetic scores based on normalized hemodynamic indices.

Results

We defined three synthetic scores, based on hemodynamic indices evaluated in different contexts: on the leaflets, in the ascending aorta, and in the whole domain. Our proposed synthetic scores are able to clearly isolate the SVD group. Notably, we found that leaflets’ OSI individually shows statistically significant differences between the two subgroups of patients.

Conclusion

The results of this computational study suggest that blood dynamics may play an important role in creating the conditions that lead to SVD. More-over, the proposed synthetic scores could provide further indications for clinicians in assessing and predicting TAVI valves’ long-term performance.
Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake
Authors: Krinos Arianna I. , Bowers Robert M. , Rohwer Robin R. , McMahon Katherine D. , Woyke Tanja , Schulz Frederik
Published: February 2024

Background

Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world’s best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last twenty years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community, and to hypothesize about their interactions with bacteria.

Results

Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Further, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g. ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota.

Conclusions

We demonstrate that metagenomic sequence-based community analysis can complement existing e↵orts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes, and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction.
Automated multimodal imaging ofCaenorhabditis elegansbehavior in multi-well plates
Authors: Ji Hongfei , Chen Dian , Fang-Yen Christopher
Published: February 2024

Assays of behavior in model organisms play an important role in genetic screens, drug testing, and the elucidation of gene-behavior relationships. We have developed an automated, high-throughput imaging and analysis method for assaying behaviors of the nematodeC. elegans. We use high-resolution optical imaging to longitudinally record the behaviors of 96 animals at a time in multi-well plates, and computer vision software to quantify the animals’ locomotor activity, behavioral states, and egg laying events. To demonstrate the capabilities of our system we used it to examine the role of serotonin inC. elegansbehavior. We found that egg-laying events are preceded by a period of reduced locomotion, and that this decline in movement requires serotonin signaling. In addition, we identified novel roles of serotonin receptors SER-1 and SER-7 in regulating the effects of serotonin on egg laying across roaming, dwelling, and quiescent locomotor states. Our system will be useful for performing genetic or chemical screens for modulators of behavior.
Impaired 26S proteasome causes learning and memory deficiency and induces neuroinflammation mediated by NF-κB in mice
Authors: Huber Christa C. , Callegari Eduardo , Paez Maria , Li Xiaoping , Dwamena Abena , Wang Hongmin
Published: February 2024

A reduction in proteasome activity, loss of synapses, and increased neuroinflammation in the brain are hallmarks of aging and many neurodegenerative disorders, including Alzheimer’s disease (AD); however, whether proteasome dysfunction is causative to neuroinflammation remains less understood. In this study, we investigated the impact of 26S proteasome deficiency on neuroinflammation in thePsmc1knockout (KO) mice deficient in a 19S proteasome subunit limited to the forebrain region. Our results revealed that impaired 26S proteasome causes reduced learning and memory capability and overt neuroinflammation in thePsmc1KO brain at eight weeks of age. Pronounced neuroinflammation was confirmed by increased levels of several key immune response-related proteins, including Stat1, Trem2, and NF-κB, and by activation of astrocytes and microglia in the KO brain. To validate NF-κB mediating neuroinflammation, we administered a selective NF-κB inhibitor to the KO animals, and following the treatment, the KO mice exhibited improved learning and memory behaviors and reduced neuroinflammation compared to the control animals. These data indicate that impaired 26S proteasome causes AD-like cognitive deficiency and induces neuroinflammation mediated largely by NF-κB. These results may aid the development of effective therapeutics for AD and other neurodegenerative disorders where impaired proteasome activity is consistently coupled with neuroinflammation.
Psilocybin induces dose-dependent changes in functional network organization in rat cortex
Authors: Silverstein Brian H. , Kolbman Nicholas , Nelson Amanda , Liu Tiecheng , Guzzo Peter , Gilligan Jim , Lee UnCheol , Mashour George A. , Vanini Giancarlo , Pal Dinesh
Published: February 2024

Psilocybin produces an altered state of consciousness in humans and is associated with complex spatiotemporal changes in brain networks. Given the emphasis on rodent models for mechanistic studies, there is a need for characterization of the effect of psilocybin on brain-wide network dynamics. Previous rodent studies of psychedelics, using electroencephalogram, have primarily been done with sparse electrode arrays that offered limited spatial resolution precluding network level analysis, and have been restricted to lower gamma frequencies. Therefore, in the study, we used electroencephalographic recordings from 27 sites (electrodes) across rat cortex (n=6 male, 6 female) to characterize the effect of psilocybin (0.1 mg/kg, 1 mg/kg, and 10 mg/kg delivered over an hour) on network organization as inferred through changes in node degree (index of network density) and connection strength (weighted phase-lag index). The removal of aperiodic component from the electroencephalogram localized the primary oscillatory changes to theta (4-10 Hz), medium gamma (70-110 Hz), and high gamma (110-150 Hz) bands, which were used for the network analysis. Additionally, we determined the concurrent changes in theta-gamma phase-amplitude coupling. We report that psilocybin, in a dose-dependent manner, 1) disrupted theta-gamma coupling [p<0.05], 2) increased frontal high gamma connectivity [p<0.05] and posterior theta connectivity [p≤0.049], and 3) increased frontal high gamma [p<0.05] and posterior theta [p≤0.046] network density. The medium gamma frontoparietal connectivity showed a nonlinear relationship with psilocybin dose. Our results suggest that high-frequency network organization, decoupled from local theta-phase, may be an important signature of psilocybin-induced non-ordinary state of consciousness.
A micro-RNA is the effector gene of a classic evolutionary hotspot locus
Authors: Tian Shen , Asano Yoshimasa , Banerjee Tirtha Das , Wee Jocelyn Liang Qi , Lamb Abigail , Wang Yehan , Murugesan Suriya Narayanan , Ui-Tei Kumiko , Wittkopp Patricia J , Monteiro Antonia
Published: February 2024

In Lepidoptera (butterflies and moths), a genomic region around the gene cortex is a hotspot locus, repeatedly used to generate intraspecific melanic wing color polymorphisms across 100-million-years of evolution. However, the identity of the effector gene regulating melanic wing color within this locus remains unknown. Here, we show that none of the four candidate protein-coding genes within this locus, including cortex, serve as major effectors. Instead, a micro-RNA (miRNA), mir-193, serves as the major effector across three deeply diverged lineages of butterflies, and its function is conserved in Drosophila. In Lepidoptera, mir-193 is derived from a gigantic long non-coding RNA, ivory, and it functions by directly repressing multiple pigmentation genes. We show that a miRNA can drive repeated instances of adaptive evolution in animals.
Bacterial Bloodstream Infections in Cameroon: A Systematic Review and Meta-Analysis of Prevalence and Antibiotic Resistance
Authors: Matakone Moise , Koudoum Patrice Landry , Zemtsa Ravalona Jessica , Ngomtcho Sen Claudine Henriette , Dah Isaac , Noubom Michel
Published: February 2024

Background

The paucity of data on the epidemiology of bloodstream infection (BSI) in low and middle-income countries (LMICs) limits its effective prevention and management. This review sought to determine the prevalence, bacteriological and antimicrobial resistance profiles of bacteria implicated in BSI in Cameroon.

Methods

PubMed and Google Scholar databases were searched to identify relevant articles, which were screened according to the PRISMA guidelines. The data were analysed using comprehensive meta-analysis software. The I2was used to evaluate heterogeneity between studies, Begg’s and Egger’s regression tests were used to evaluate publication bias, and random effects analysis was used to calculate the pooled prevalence.

Results

A total of 4223 blood cultures were obtained from the 10 included studies. The overall pooled prevalence of bacterial BSI was 26.31% (95% CI= 17.01%–38.35%).Escherichia coli(23.09%; 95% CI= 9.21%–47.05%),Klebsiellaspp. (22.95%; 95% CI= 13.09%–37.07%), andStaphylococcus aureus(16.09%; 95% CI= 8.11%–29.43%) were the most common bacteria species.E. coliandKlebsiellaspp. displayed the highest resistance to amoxicillin (82.65%; 95% CI= 63.25%–92.95% vs 86.42%; 95% CI= 55.90%–96.97%), amoxicillin + clavulanic acid (71.74%; 43.96–89.15% vs 73.06%; 95% CI= 38.70%–92.09%) and cotrimoxazole (76.22%; 95% CI= 51.33%–90.79% vs 65.81%; 95% CI= 45.08–81.86%). However, meropenem (26.73%; 95% CI= 20.76%–33.68%) and fosfomycin (14.85%; 95% CI= 9.07%–23.37%) were the least resistant inE. coliandKlebsiellaspp., respectively.Staphylococcus aureusstrains exhibited highest resistance to penicillin (84.37%; 95% CI= 68.13%–93.16%), erythromycin (44.80%; 95% CI= 33.37%–56.79%) and oxacillin (37.35%; 95% CI= 8.76%–78.74%) and lowest resistance to rifampicin (2.94%; 95% CI= 0.59%–13.39%), fusidic acid (6.73%; 95% CI= 2.55%–16.62%) and vancomycin (13.18%; 95% CI= 2.26%–49.86%).

Conclusion

This study reports a high prevalence of bacterial BSIs in Cameroon and the high resistance of these bacteria to common antibiotics. There is a pressing need to conduct BSI surveillance studies in all regions of Cameroon to generate data for evidence-based measures regarding BSI prevention and management.

Prospero registration number

CRD42023482760
Physicians’ experiences with telemedicine during the COVID-19 pandemic in India
Authors: Nagaraja Vikranth H. , Ghosh Dastidar Biswanath , Suri Shailesh , Jani Anant R.
Published: February 2024

Purpose

Digital health is an important factor in India’s healthcare system. Inclusive policy measures, a fertile technological landscape, and relevant infrastructural development with unprecedented levels of telemedicine adoption catalysed by the recent COVID-19 pandemic have thrown open new possibilities and opportunities for clinicians, end-users, and other stakeholders. Nevertheless, there are still several challenges to properly integrating and scaling telemedicine use in India. This study’s objective was to understand the views of practising physicians in India on the use of telemedicine and the challenges experienced during the accelerated rollout during the first wave of the COVID-19 pandemic.

Methods

We acquired data through an anonymous, cross-sectional, internet-based survey of physicians (n=444) across India on the COVID-19 frontline. These responses were subjected to qualitative data analysis (via inductive coding and thematic analyses) and descriptive statistics, as appropriate.

Results

Most responses (n=51) were categorised under a code indicating that telemedicine-led healthcare delivery compromised treatment quality. The second largest proportion of responses (n=22) suggested that ‘Accessibility, quality and maturity of software and hardware infrastructure’ was a considerable challenge.

Conclusions

Despite the considerable uptake, perceived benefits, and the foreseen positive role of telemedicine in India, several challenges of telemedicine use (viz., technical, user experience-based integration, and non-user-based integration challenges) have been identified. These must be addressed through suggested relevant opportunities to realise telemedicine’s potential and help inform the future design of effective telemedicine policy and practice in India.

Funding

No funding to report.

Declarations

None
Metabolomic Age (MileAge) predicts health and lifespan: a comparison of multiple machine learning algorithms
Authors: Mutz Julian , Iniesta Raquel , Lewis Cathryn M
Published: February 2024

Background

Molecular ageing clocks estimate an individual’s biological age. Our aim was to compare multiple machine learning algorithms for developing ageing clocks from nuclear magnetic resonance (NMR) spectroscopy metabolomics data. To validate how well each ageing clock predicted age-related morbidity and lifespan, we assessed their associations with multiple health indicators (e.g., telomere length and frailty) and all-cause mortality.

Methods

The UK Biobank is a multicentre observational health study of middle-aged and older adults. The Nightingale Health platform was used to quantify 168 circulating plasma metabolites at the baseline assessment from 2006 to 2010. We trained and internally validated 17 machine learning algorithms including regularised regression, kernel-based methods and ensembles. Metabolomic age (MileAge) delta was defined as the difference between predicted and chronological age.

Results

The sample included 101,359 participants (mean age = 56.53 years, SD = 8.10). Most metabolite levels varied by chronological age. The nested cross-validation mean absolute error (MAE) ranged from 5.31 to 6.36 years. 31.76% of participants had an age-bias adjusted MileAge more than one standard deviation (3.75 years) above or below the mean. A Cubist rule-based regression model overall performed best at predicting health outcomes. The all-cause mortality hazard ratio (HR) comparing individuals with a MileAge delta more than one standard deviation above and below the mean was HR = 1.52 (95% CI 1.41-1.64,p< 0.001) over a median follow-up of 13.87 years. Individuals with an older MileAge were frailer, had shorter telomeres, were more likely to have a chronic illness and rated their health worse.

Conclusions

Metabolomic ageing clocks derived from multiple machine learning algorithms were robustly associated with health indicators and mortality. Our metabolomic ageing clock (MileAge) derived from a Cubist rule-based regression model can be incorporated in research, and may find applications in health assessments, risk stratification and proactive health tracking.
Incidence of Mortality and Predictors Among Patients with Shock Managed in the Emergency Room of a Large Tertiary Referral Hospital in Ethiopia
Authors: Asfaw Kalsidagn Girma , Adugna Abel Getachew , Mekonen Nahom Mesfin , Leulseged Tigist Workneh , Merahi Merahi Kefyalew , Kejela Segni , Moges Fekadesilassie Henok
Published: February 2024

Background

Shock is a common emergency condition which can lead to organ failure and death if not diagnosed and managed timely. Despite its huge global impact, data is scarce in resource-limited settings, such as Ethiopia, which hinders the provision of quality care for improved patient outcomes. Hence, the aim of the study was to determine the incidence of death and predictors among adult patients with shock managed at the Emergency Department of St. Paul’s Hospital Millennium Medical College in Ethiopia.

Methods

A retrospective chart review study was conducted between July to September 2022 among 178 eligible adult patients who were managed at hospital between October 2021 and May 2022. The characteristics of the participants were summarized using frequency and median with interquartile range. The incidence of mortality was estimated using incidence density using person hour (PH) of observation. To identify predictors of mortality, a generalized linear model using poisson regression model with robust standard errors was run at 5% level of significance, where adjusted relative risk (ARR) with its 95% CI was used to interpret significant results

Result

The incidence of death was 6.87 deaths per 1000 PH (95% CI= 5.44 to 8.69). Significant predictors of death were being triaged orange (ARR=0.46, 95% CI=0.24-0.88, p=0.020), having a high shock index (ARR=1.59, 95% CI=1.07-2.36, p=0.021), being diagnosed with septic shock (ARR=3.66, 95% CI=1.20-11.17, p=0.023), taking vasopressors (ARR=3.18, 95% CI=1.09, 9.27, p=0.034), and developing organ failure (ARR=1.79, 95% CI=1.04-3.07, p=0.035).

Conclusion

The incidence of mortality among shock patients was found to be considerable but relatively lower than previous studies. To optimize patient care and improve outcomes, it is important to remain vigilant in the proper triage and early diagnosis of shock using more sensitive tools for prompt identification of high-risk cases, as well as to provide timely, prioritized and effective interventions.
In mice, discrete odors can selectively promote the neurogenesis of sensory neuron subtypes that they stimulate
Authors: Hossain Kawsar , Smith Madeline , Santoro Stephen W.
Published: February 2024

In mammals, olfactory sensory neurons (OSNs) are born throughout life, presumably solely to replace neurons lostviaturnover or injury. This assumption follows from the hypothesis that olfactory neurogenesis is strictly stochastic with respect to neuron subtype, as defined by the single odorant receptor allele that each neural precursor stochastically chooses out of hundreds of possibilities. This hypothesis is challenged by recent findings that the birthrates of a fraction of subtypes are selectively diminished by olfactory deprivation. These findings raise questions about how, and why, olfactory stimuli are required to promote the neurogenesis of some OSN subtypes, including whether the stimuli are generic (e.g., broadly activating odors or mechanical stimuli) or specific (e.g., discrete odorants). Based on RNA-seq and scRNA-seq analyses, we hypothesized that the neurogenic stimuli are specific odorants that selectively activate the same OSN subtypes whose birthrates are accelerated. In support of this, we have found, using subtype-specific OSN birthdating, that exposure to male and musk odors can accelerate the birthrates of responsive OSNs. Collectively, our findings reveal that certain odor experiences can selectively “amplify” specific OSN subtypes, and that persistent OSN neurogenesis may serve, in part, an adaptive function.
Simpler protein domain identification using spectral clustering
Authors: Cazals Frédéric , Herrmann Jules , Sarti Edoardo
Published: February 2024

The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is theSPECTRUSalgorithm, which provides a segmentation based on spectral clustering applied to a graph coding interatomic fluctuations derived from an elastic network model.

We presentSPECTRALDOM, which makes three straightforward and useful additions toSPECTRUS. For single structures, we show that high quality partitionings can be obtained from a graph Laplacian derived from pairwise interactions–without normal modes. For sets of homologous structures, we introduce a Multiple Sequence Alignment mode, exploiting both the sequence based information (MSA) and the geometric information embodied in experimental structures. Finally, we propose to analyse the clusters/- domains delivered using the so-calledD-family-matching algorithm, which establishes a correspondence between domains yielded by two decompositions, and can be used to handle fragmentation issues.

Our domains compare favorably to those of the originalSPECTRUS, and those of the deep learning based methodChainsaw. Using two complex cases, we show in particular thatSPECTRALDOMis the only method handling complex conformational changes involving several sub-domains. Finally, a comparison ofSPECTRALDOMandChainsawon the manually curated domain classificationECODas a reference shows that high quality domains are obtained without using any evolutionary related piece of information.

SPECTRALDOMis provided in the Structural Bioinformatics Library, seehttp://sbl.inria.frandhttps://sbl.inria.fr/doc/Spectral_domain_explorer-user-manual.html.
Far-red chemigenetic biosensors for multi-dimensional and super-resolved kinase activity imaging
Authors: Frei Michelle S. , Sanchez Samantha A. , Liu Longwei , Schneider Falk , Wang Zichen , Hakozaki Hiroyuki , Li Yajuan , Lyons Anne C. , Rohm Theresa V. , Olefsky Jerrold M. , Shi Lingyan , Schöneberg Johannes , Fraser Scott E. , Mehta Sohum , Wang Yingxiao , Zhang Jin
Published: February 2024

Fluorescent biosensors revolutionized biomedical science by enabling the direct measurement of signaling activities in living cells, yet the current technology is limited in resolution and dimensionality. Here, we introduce highly sensitive chemigenetic kinase activity biosensors that combine the genetically encodable self-labeling protein tag HaloTag7 with bright far-red-emitting synthetic fluorophores. This technology enables five-color biosensor multiplexing, 4D activity imaging, and functional super-resolution imaging via stimulated emission depletion (STED) microscopy.
Identification of a motif in TPX2 that regulates spindle architecture inXenopusegg extracts
Authors: Pena Guadalupe E. , Zhou Xiao , Slevin Lauren , Brownlee Christopher , Heald Rebecca
Published: February 2024

A bipolar spindle composed of microtubules and many associated proteins functions to segregate chromosomes during cell division in all eukaryotes, yet spindle size and architecture varies dramatically across different species and cell types. Targeting protein for Xklp2 (TPX2) is one candidate factor for modulating spindle microtubule organization through its roles in branching microtubule nucleation, activation of the mitotic kinase Aurora A, and association with the kinesin-5 (Eg5) motor. Here we identify a conserved nuclear localization sequence (NLS) motif,123KKLK126inX. laevisTPX2, which regulates astral microtubule formation and spindle pole morphology inXenopusegg extracts. Addition of recombinant TPX2 with this sequence mutated to AALA dramatically increased spontaneous formation of microtubule asters and recruitment of phosphorylated Aurora A, pericentrin, and Eg5 to meiotic spindle poles. We propose that TPX2 is a linchpin spindle assembly factor whose regulation contributes to the recruitment and activation of multiple microtubule polymerizing and organizing proteins, generating distinct spindle architectures.
A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs
Authors: Brown Caroline , Ghosh Snehasish , McAllister Rachel , Kumar Mukesh , Walker Gerard , Sun Eric , Aman Talat , Panda Aniruddha , Kumar Shailesh , Li Wenxue , Coleman Jeff , Liu Yansheng , Rothman James E , Bhattacharyya Moitrayee , Gupta Kallol
Published: February 2024

The intricate molecular environment of the native membrane profoundly influences every aspect of membrane protein (MP) biology. Despite this, the most prevalent method of studying MPs uses detergent-like molecules that disrupt and remove this vital local membrane context. This severely impedes our ability to quantitatively decipher the local molecular context and comprehend its regulatory role in the structure, function, and biogenesis of MPs. Using a library of membrane-active polymers we have developed a platform for the high-throughput analysis of the membrane proteome. The platform enables near-complete spatially resolved extraction of target MPs directly from their endogenous membranes into native nanodiscs that maintain the local membrane context. We accompany this advancement with an open-access database that quantifies the polymer-specific extraction variability for 2065 unique mammalian MPs and provides the most optimized condition for each of them. Our method enables rapid and near-complete extraction and purification of target MPs directly from their endogenous organellar membranes at physiological expression levels while maintaining the nanoscale local membrane environment. Going beyond the plasma membrane proteome, our platform enables extraction from any target organellar membrane including the endoplasmic reticulum, mitochondria, lysosome, Golgi, and even transient organelles such as the autophagosome. To further validate this platform, we took several independent MPs and demonstrated how our resource can enable rapid extraction and purification of target MPs from different organellar membranes with high efficiency and purity. Further, taking two synaptic vesicle MPs, we show how the database can be extended to capture multiprotein complexes between overexpressed MPs. We expect these publicly available resources to empower researchers across disciplines to efficiently capture membrane ‘nano-scoops’ containing a target MP and interface with structural, functional, and other bioanalytical approaches. We demonstrate an example of this by combining our extraction platform with single-molecule TIRF imaging to demonstrate how it can enable rapid determination of homo-oligomeric states of target MPs in native cell membranes.
Enhancing Bone Regeneration and Osseointegration using rhPTH(1-34) and DimericR25CPTH(1-34) in an Osteoporotic Beagle Model
Authors: Shin Jeong-Oh , Lee Jong-Bin , Lee Sihoon , Kim Jin-Woo
Published: February 2024

Introduction

Despite continuous parathyroid hormone (PTH) exposure potentially accelerating bone resorption, intermittent PTH administration has shown anabolic effects on bone microarchitecture. This study investigates the therapeutic impacts of two PTH analogs, rhPTH(1-34) and dimericR25CPTH(1-34) on bone regeneration and osseointegration in a postmenopausal osteoporosis animal model.

Methods

Twelve female beagles, osteoporotic post-ovariectomy, underwent implant surgeries. Animals were divided into three groups: control, daily rhPTH(1-34) injection, and daily dimericR25CPTH(1-34) injection. After 10 weeks, bone regeneration and implant osseointegration were evaluated using micro-CT, histological/histomorphometric analyses, and serum biochemical analysis.

Results

While the rhPTH(1-34) group demonstrated improved microarchitectural characteristics, such as BMD, BV, trabecular metrics, and osseointegration degree, the dimericR25CPTH(1-34) group showed similarly enhanced anabolic effects around the titanium implants, albeit these were less pronounced than the rhPTH(1-34), yet significantly better than the control group. Histologic and TRAP assays revealed that both PTH analogs significantly promoted bone regeneration and remodeling, especially in artificially created bone defects.

Conclusion

This study demonstrated the therapeutic effects of rhPTH(1-34) and dimericR25CPTH(1-34) on bone regeneration and titanium osseointegration in a beagle model with osteoporosis.
Proteomic profiling of intracranial atherosclerotic plaque in the human brain
Authors: Hao Qing , Wang Erming , Wang Ju , Wu Zhiping , Crary John F. , Sharma Shivangi , Thorn Emma L. , Elahi Fanny , Zhang Bin , Peng Junmin
Published: February 2024

Background

Intracranial atherosclerotic disease (ICAD) is one of the major causes of ischemic stroke and associated with high risk of stroke recurrence. There are no reliable and specific fluid biomarkers for ICAD, and little is known about the proteomic profiling of ICAD. In this study we aimed to explore the feasibility of applying proteomics technology to profile intracranial atherosclerotic plaques extracted from postmortem human brain arteries.

Methods

Eighteen segments (5-10mm in length) of major arteries from 10 postmortem brains were collected from the Mount Sinai Neuropathology Brain Bank. Among these segments, 5 had no evidence of atherosclerotic disease, and 13 had wall thickening or visible plaques with various degree of stenosis. Proteins were extracted from the vessel segments, quantified, and digested into peptides. Subsequently, the peptides underwent tandem mass tag (TMT) labeling, pooling, and analysis using two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS). Protein identification and quantification were performed using the JUMP software. Differentially expressed proteins (DEPs) were defined as proteins with p.adj < 0.05 and absolute log2 (fold change) > log2 (1.2).

Results

A total of 7,492 unique proteins were detected, and 6,726 quantifiable proteins were retained for further analysis. Among these, 265 DEPs, spanning on 252 unique gene, were found to be associated with ICAD by comparing the arterial segments with vs those without atherosclerotic disease. The top 4 most significant DEPs include LONP1, RPS19, MRPL12 and SNU13. Among the top 50 DEPs, FADD, AIFM1 and PGK1 were associated with atherosclerotic disease or cardiovascular events in previous studies. Moreover, the previously reported proteins associated with atherosclerosis such as APCS, MMP12, CTSD were elevated in arterial segments with atherosclerotic changes. Furthermore, the up-regulation of APOE and LPL, the ICAD GWAS risk genes, was shown to be associated with the plaque severity. Finally, gene set enrichment analysis revealed the DEP signature is enriched for biological pathways such as chromatin structure, plasma lipoprotein, nucleosome, and protein-DNA complex, peroxide catabolic and metabolic processes, critical in ICAD pathology.

Conclusions

Direct proteomic profiling of fresh-frozen intracranial artery samples by MS-based proteomic technology is a feasible approach to identify ICAD-associated proteins, which can be potential biomarker candidates for ICAD. Further plaque proteomic study in a larger sample size is warranted to uncover mechanistic insights into ICAD and discover novel biomarkers that may help to improve diagnosis and risk stratification in ICAD.
TTF1 control of LncRNA synthesis and cell growth delineates a tumour suppressor pathway acting directly on the ribosomal RNA Genes
Authors: Sibai Dany S. , Tremblay Michel G. , Lessard Frédéric , Tav Christophe , Sabourin-Félix Marianne , Robinson Mark D. , Moss Tom
Published: February 2024

The tumour suppressor p14/19ARF regulates ribosomal RNA (rRNA) synthesis by controlling the nucleolar localization of Transcription Termination Factor 1 (TTF1). However, the role played by TTF1 in regulating the rRNA genes and in potentially controlling growth has remained unclear. We now show that TTF1 expression regulates cell growth by determining the cellular complement of ribosomes. Unexpectedly, it achieves this by acting as a “roadblock” to synthesis of the non-coding LncRNA and pRNA that we show are generated from the “Spacer Promoter” duplications present upstream of the 47S pre-rRNA promoter on the mouse and human ribosomal RNA genes. Unexpectedly, the endogenous generation of these non-coding RNAs does not induce CpG methylation or gene silencing. Rather, it actsin cisto suppress 47S preinitiation complex formation and hencede novopre-rRNA synthesis by a mechanism reminiscent of promoter interference or occlusion. Taken together, our data delineate a pathway from p19ARF to cell growth suppression via the regulation of ribosome biogenesis by non-coding RNAs and validate a key cellular growth law in mammalian cells.
Predicting gene sequences with AI to study codon usage patterns
Authors: Sidi Tomer , Bahiri-Elitzur Shir , Tuller Tamir , Kolodny Rachel
Published: February 2024

Selective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained artificial intelligence (AI) models to predict the codons given their amino acid sequence in the eukaryotesSaccharomyces cerevisiaeandSchizosaccharomyces pombeand the bacteriaEscherichia coliandBacillus subtilis, to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins, and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels. Our models significantly outperformed naïve frequency-based approaches, demonstrating that there are dependencies between codons that can be learned to better predict evolutionary-selected codon usage. The prediction accuracy advantage of our models is greater for highly expressed genes and it is greater in bacteria than eukaryotes, supporting the hypothesis that there is a monotonic relationship between selective pressure for complex codon patterns and effective population size. Also, inS.cerevisiaeand bacteria, our models were more accurate for longer proteins, suggesting that the AI system may have learned patterns related to co-translational folding. Gene functionality and conservation were also important determinants that affect the performance of our models. Finally, we showed that using information encoded in homologous proteins has only a minor effect on prediction accuracy, perhaps due to complex codon-usage codes in genes undergoing rapid evolution. In summary, our study employing contemporary AI methods offers a new perspective on codon usage patterns and a novel tool to optimize codon usage in endogenous and heterologous proteins.

Significance statement

Can one predict codon sequences used by an organism to encode a given amino acid sequence? This is difficult, because there are exponentially many codon sequences that can encode the same amino acid sequence and evolution is stochastic. Indeed, codons frequencies vary, a phenomenon known as codon-bias, yet we improve upon frequency-based predictions using contemporary AI tools that learn complex patterns and capture interactions between codons. Because our predictions are tested fairly, on cases not seen during the training process, accurate predictions suggest that these learned patterns are not random, and may be related to the evolutionary process. Thus, studying where our predictions are more accurate, is expected to reveal novel insights related to the way evolution shapes coding regions.