bluuebunny/crossref_metadata_2025 huggingface dataset:
BZR1 promotes pluripotency acquisition and callus development through direct regulation of ARF7 and ARF19
Authors: Ebstrup E , Ammitsøe T , Blanco-Touriñán N , Hansen J , Hardtke CS , Rodriguez E , Petersen M
Published: April 2024

Plants have the remarkable ability to regenerate whole organisms through formation of pluripotent cell masses from somatic cells. Cellular programs leading to fate change of somatic to pluripotent cells resembles lateral root (LR) formation and both are chiefly regulated by auxin. Brassinosteroid signalling also plays an important role during LR formation but little is known about the direct link between auxin and brassinosteroid components, such as BZR1 and BES1, in relation to pluripotency acquisition. Here we show that gain-of-function mutantsbzr1-Dandbes1-Dexhibit altered callus formation, yet disruption of these transcription factors does not produce major changes to callus formation orde novo organogenesis. Moreover, our data reveals that BZR1 displays enhanced expression in callus tissue and directly binds to the promoters of ARF7 and ARF19, two master pluripotency regulators, leading to their enhanced transcription. Remarkably, we see abrogation of callus formation inbzr1-Dupon disruption of ARF7 and ARF19, emphasizing that BZR1 callus phenotype is dependent on these two auxin signalling components. In conclusion, we depict a link between ARF7, ARF19 and BZR1 in the promotion of pluripotency acquisition, portraying BZR1 as a major supporting factor in callus formation.

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Genome-wide association study of glucocerebrosidase activity modifiers
Authors: Somerville Emma N. , Krohn Lynne , Senkevich Konstantin , Yu Eric , Ahmad Jamil , Asayesh Farnaz , Ruskey Jennifer A. , Spiegelman Dan , Fahn Stanley , Waters Cheryl , Sardi S. Pablo , Alcalay Roy N. , Gan-Or Ziv
Published: April 2024

One of the most common genetic risk factors for Parkinson’s disease (PD) are variants inGBA1, which encodes the lysosomal enzyme glucocerebrosidase (GCase). GCase deficiency has been associated with an increased PD risk, but not all individuals with low GCase activity are carriers ofGBA1mutations, suggesting other factors may be acting as modifiers. We aimed to discover common variants associated with GCase activity, as well as replicate previously reported associations, by performing a genome-wide association study using two independent cohorts: a Columbia University cohort consisting of 697 PD cases and 347 controls and the Parkinson’s Progression Markers Initiative (PPMI) cohort consisting of 357 PD cases and 163 controls. As expected,GBA1variants have the strongest association with decreased activity, led by p.N370S (beta = -4.36, se = 0.32, p = 5.05e-43). We also identify a novel association in theGAAlocus (encoding for acid alpha-glucosidase, beta = -0.96, se = 0.17, p = 5.23e-09) that may be the result of an interaction between GCase and acid alpha-glucosidase based on various interaction analyses. Lastly, we show that several PD-risk loci are potentially associated with GCase activity. Further research will be needed to replicate and validate our findings and to uncover the functional connection between acid alpha-glucosidase and GCase.
Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage
Authors: Börner Katy , Blood Philip D. , Silverstein Jonathan C. , Ruffalo Matthew , Satija Rahul , Teichmann Sarah A. , Pryhuber Gloria , Misra Ravi S. , Purkerson Jeffrey , Fan Jean , Hickey John W. , Molla Gesmira , Xu Chuan , Zhang Yun , Weber Griffin , Jain Yashvardhan , Qaurooni Danial , Kong Yongxin ,   HRA Team, Bueckle Andreas , Herr Bruce W.
Published: April 2024

The Human BioMolecular Atlas Program (HuBMAP) aims to construct a reference 3D structural, cellular, and molecular atlas of the healthy adult human body. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) serves experimental datasets and supports data processing, search, filtering, and visualization. The Human Reference Atlas (HRA) Portal (https://humanatlas.io) provides open access to atlas data, code, procedures, and instructional materials. Experts from more than 20 consortia are collaborating to construct the HRA’s Common Coordinate Framework (CCF), knowledge graphs, and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes, and biomarkers) and to use the HRA to understand changes that occur at each of these levels with aging, disease, and other perturbations. The 6th release of the HRA v2.0 covers 36 organs with 4,499 unique anatomical structures, 1,195 cell types, and 2,089 biomarkers (e.g., genes, proteins, lipids) linked to ontologies and 2D/3D reference objects. New experimental data can be mapped into the HRA using (1) three cell type annotation tools (e.g., Azimuth) or (2) validated antibody panels (OMAPs), or (3) by registering tissue data spatially. This paper describes the HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interface (APIs), flexible hybrid cloud infrastructure, and previews atlas usage applications.
Medical students’ and educators’ opinions of teleconsultation in practice and undergraduate education: a UK-based mixed-methods study
Authors: Wetzlmair Lisa-Christin , O’Malley Andrew , O’Carroll Veronica
Published: April 2024

Introduction

As information and communication technology continues to shape the healthcare landscape, future medical practitioners need to be equipped with skills and competencies that ensure safe, high-quality, and person-centred healthcare in a digitised healthcare system. This study investigated undergraduate medical students’ and medical educators’ opinions of teleconsultation practice in general and their opinions of teleconsultation education.

Methods

This study used a cross-sectional, mixed-methods approach, utilising the additional coverage design to sequence and integrate qualitative and quantitative data. An online questionnaire was sent out to all medical schools in the UK, inviting undergraduate medical students and medical educators to participate. Questionnaire participants were given the opportunity to take part in a qualitative semi-structured interview. Descriptive and correlation analyses and a thematic analysis were conducted.

Results

A total of 248 participants completed the questionnaire and 23 interviews were conducted. Saving time and the reduced risks of transmitting infectious diseases were identified as common advantages of using teleconsultation. However, concerns about confidentiality and accessibility to services were expressed by students and educators. Eight themes were identified from the thematic analysis. The themes relevant to teleconsultation practice were (1) The benefit of teleconsultations, (2) A second-best option, (3) Patient choice, (4) Teleconsultations differ from in-person interactions, and (5) Impact on the healthcare system. The themes relevant to teleconsultation education were (6) Considerations and reflections on required skills, (7) Learning and teaching content, and (8) The future of teleconsultation education.

Discussion

The results of this study have implications for both medical practice and education. Patient confidentiality, safety, respecting patients’ preferences, and accessibility are important considerations for implementing teleconsultations in practice. Education should focus on assessing the appropriateness of teleconsultations, offering accessible and equal care, and developing skills for effective communication and clinical reasoning. High-quality teleconsultation education can influence teleconsultation practice.
Sensitive Pathogen Detection and Drug Resistance Characterization Using Pathogen-Derived Enzyme Activity Amplified by LAMP or CRISPR-Cas
Authors: Wang Qin , Kline Enos C. , Gilligan-Steinberg Shane D. , Lai James J. , Hull Ian T. , Olanrewaju Ayokunle O. , Panpradist Nuttada , Lutz Barry R.
Published: April 2024

Pathogens encapsulate or encode their own suite of enzymes to facilitate replication in the host. The pathogen-derived enzymes possess specialized activities that are essential for pathogen replication and have naturally been candidates for drug targets. Phenotypic assays detecting the activities of pathogen-derived enzymes and characterizing their inhibition under drugs offer an opportunity for pathogen detection, drug resistance testing for individual patients, and as a research tool for new drug development. Here, we used HIV as an example to develop assays targeting the reverse transcriptase (RT) enzyme encapsulated in HIV for sensitive detection and phenotypic characterization, with the potential for point-of-care (POC) applications. Specifically, we targeted the complementary (cDNA) generation activity of the HIV RT enzyme by adding engineered RNA as substrates for HIV RT enzyme to generate cDNA products, followed by cDNA amplification and detection facilitated by loop-mediated isothermal amplification (LAMP) or CRISPR-Cas systems. To guide the assay design, we first used qPCR to characterize the cDNA generation activity of HIV RT enzyme. In the LAMP-mediated Product-Amplified RT activity assay (LamPART), the cDNA generation and LAMP amplification were combined into one pot with novel assay designs. When coupled with direct immunocapture of HIV RT enzyme for sample preparation and endpoint lateral flow assays for detection, LamPART detected as few as 20 copies of HIV RT enzyme spiked into 25μL plasma (fingerstick volume), equivalent to a single virion. In the Cas-mediated Product-Amplified RT activity assay (CasPART), we tailored the substrate design to achieve a LoD of 2e4 copies (1.67fM) of HIV RT enzyme. Furthermore, with its phenotypic characterization capability, CasPART was used to characterize the inhibition of HIV RT enzyme under antiretroviral drugs and differentiate between wild-type and mutant HIV RT enzyme for potential phenotypic drug resistance testing. Moreover, the CasPART assay can be readily adapted to target the activity of other pathogen-derived enzymes. As a proof-of-concept, we successfully adapted CasPART to detect HIV integrase with a sensitivity of 83nM. We anticipate the developed approach of detecting enzyme activity with product amplification has the potential for a wide range of pathogen detection and phenotypic characterization.
Neural processing of rhythmic speech by children with developmental language disorder (DLD): An EEG study
Authors: Keshavarzi Mahmoud , Richards Susan , Feltham Georgia , Parvez Lyla , Goswami Usha
Published: April 2024

Sensitivity to rhythmic and prosodic cues in speech has been described as a precursor of language acquisition. Consequently, atypical rhythmic processing during infancy and early childhood has been considered a risk factor for developmental language disorders. Despite many behavioural studies, the neural processing of rhythmic speech has not yet been explored in children with developmental language disorder (DLD). Here we utilise EEG to investigate the neural processing of rhythmic speech by 9-year-old children with and without DLD. In the current study, we investigate phase entrainment, angular velocity, power, event related potentials (ERPs), phase-amplitude coupling (PAC) and phase-phase coupling (PPC), at three frequency bands selected on the basis of the prior literature, delta, theta and low gamma. We predicted a different phase of entrainment in the delta band in children with DLD, and also greater theta power, atypical cross-frequency coupling and possibly atypical gamma-band responses. Contrary to prediction, children with DLD demonstrated significant and equivalent phase entrainment in the delta and theta bands to control children. However, only the control children showed significant phase entrainment in the low gamma band. The children with DLD also exhibited significantly more theta and low gamma power compared to the control children, and there was a significant gamma-band difference in angular velocity between the two groups. Finally, group resultant phase analyses showed that low-frequency phase (delta and theta) affected gamma oscillations differently by group. These EEG data show important differences between children with and without DLD in the neural mechanisms underpinning the processing of rhythmic speech. The findings are discussed in terms of auditory theories of DLD, particularly Temporal Sampling theory.
Gluconeogenesis in the YSL-like tissue of cloudy catshark (Scyliorhinus torazame)
Authors: Shimizu Marino , Takagi Wataru , Sakai Yuki , Kayanuma Isana , Furukawa Fumiya
Published: April 2024

Glucose has important roles in the development of hematopoietic stem cells and brain of zebrafish, the vertebrate animal model; however, in most oviparous animals, the amount of maternally provided glucose in the yolk is scarce. For these reasons, developing animals need some ways to supplement glucose. Recently, it was found that developing zebrafish, a teleost fish, undergo gluconeogenesis in the yolk syncytial layer (YSL), an extraembryonic tissue that surrounds the yolk, utilizing yolk nutrients as substrates. However, teleost YSL is evolutionarily unique, and it is not clear how other vertebrates supplement glucose. In this study, we used cloudy catshark, an elasmobranch species which possesses a YSL-like tissue during development, and sought for possible gluconeogenic activities in this tissue. In the catshark yolk sac, an increase in glucose level was found, and our isotope tracking by13C-labeled substrate combined with LC/MS analysis detected gluconeogenic activities with glycerol most preferred substrate. In addition, expression analysis for gluconeogenic genes showed that many of these were expressed at the YSL-like tissue, suggesting that cloudy catshark engages in gluconeogenesis in this tissue. The gluconeogenesis in teleost YSL and a similar tissue in elasmobranch species implies conservation of the mechanisms of yolk metabolism between these two lineages. Future studies on other vertebrate taxa will be helpful to understand the evolutionary changes in the modes of yolk metabolism that vertebrates have experienced.
Targeting the expansion of myeloid-derived suppressor cells in liver cirrhosis
Authors: Flint Emilio , Ercan Caner , Mitchell Eoin , Pop Oltin T , Geng Anne , Jorzik Paul OG , Possamai Lucia , Brenig Robert G , Morel Sarah , Sieber Pablo , Singanayagam Arjuna , Matter Matthias S , Semela David , Heim Markus H , Demougin Philippe , Roux Julien , Terracciano Luigi M , Triantafyllou Evangelos , Bernsmeier Christine
Published: April 2024

Background and aims

Previously, we identified immune-suppressive circulating monocytic myeloid-derived suppressor cells (M-MDSC) in patients with cirrhosis and liver failure, which increased with disease severity and were associated with infections and mortality. Impaired immune responses and M-MDSC expansion were reversed byex vivopolyinosinic:polycytidylic acid (poly(I:C)) treatment. Here, we aimed to investigate hepatic MDSC subsets in liver biopsies of cirrhotic patients and identify MDSC subsets in murine models to assess the safety and efficacy of poly(I:C)in vivo.

Methods

22 cirrhotic patients and 4 controls were clinically characterised. MDSC were identified in liver biopsies (immunofluorescence) and in the circulation (flow cytometry). M- MDSC phenotype and function following poly(I:C) stimulation were assessedex vivo. Carbon tetrachloride-based murine models of liver fibrosis were used. Poly(I:C) was administered therapeutically. MDSC biology was investigated with flow cytometry, immunofluorescence and T-cell proliferation assay. Hepatic histopathology, transcriptomics (BulkRNAseq) and serum markers were assessed.

Results

Besides circulating M-MDSC, hepatic CD14+CD84+M-MDSC and CD15+CD84+polymorphonuclear-MDSC expanded in cirrhotic patients and indicated disease severity, infections and poor survival. Poly(I:C) treatment reversed phenotype and function of circulating M-MDSCex vivo. Circulating and hepatic MDSC expanded in our murine models of liver fibrosis and suppressed T-cell proliferation. Lipopolysaccharide andE.colichallenge exacerbated hepatic MDSC and fibrosis compared to CCl4controls. Poly(I:C) therapy reduced MDSC expansion in fibrotic mice with bacterial infection and CCl4-induced fibrosis.

Conclusion

Hepatic MDSC expanded in cirrhotic patients and were linked with disease severity and poor prognosis. Poly(I:C) reversed frequency and function of M-MDSCex vivo. Poly(I:C) therapy reversed MDSC expansion and fibrosis in a murine model of liver fibrosis with infection. Thus, we highlighted poly(I:C) as a potential immunotherapy for the treatment of immuneparesis in cirrhosis.
Reconstructing and comparing signal transduction networks from single cell protein quantification data
Authors: Stohn Tim , van Eijl Roderick , Mulder Klaas W. , Wessels Lodewyk F.A. , Bosdriesz Evert
Published: April 2024

Motivation

Signal transduction networks regulate a multitude of essential biological processes and are frequently aberrated in diseases such as cancer. Developing a mechanistic understanding of such networks is essential to understand disease or cell population specific signaling and to design effective treatment strategies. Typically, such networks are computationally reconstructed based on systematic perturbation experiments, followed by quantification of signaling protein activity. Recent technological advances now allow for the quantification of the activity of many (signaling) proteins simultaneously in single cells. This makes it feasible to reconstruct signaling networks from single cell data.

Results

Here we introduce single cell Comparative Network Reconstruction (scCNR) to derive signal transduction networks by exploiting the heterogeneity of single cell (phospho)protein measurements. scCNR treats stochastic variation in total protein abundances as natural perturbation experiments, whose effects propagate through the network. scCNR reconstructs cell population specific networks of the same underlying topology for cells from diverse populations. We extensively validated scCNR on simulated single cell data, and we applied it to a dataset of EGFR-inhibitor treated keratinocytes to recover signaling differences downstream of EGFR and in protein interactions associated with proliferation. scCNR will help to unravel the mechanistic signaling differences between cell populations by making use of single-cell data, and will subsequently guide the development of well-informed treatment strategies.

Availability and implementation

scCNR is available as a python module athttps://github.com/ibivu/scmra. Additionally, code to reproduce all figures is available athttps://github.com/tstohn/scmra_analysis.

Supplementary information

Supplementary information and data are available at Bioinformatics online.
Functional ultrasound (fUS) imaging of displacement-guided focused ultrasound (FUS) neuromodulation in mice
Authors: Kim Seongyeon , Kwon Nancy , Hossain Md Murad , Bendig Jonas , Konofagou Elisa E.
Published: April 2024

Focused ultrasound (FUS) stimulation is a promising neuromodulation technique with the merits of non-invasiveness, high spatial resolution, and deep penetration depth. However, simultaneous imaging of FUS-induced brain tissue displacement and the subsequent effect of FUS stimulation on brain hemodynamics has proven challenging thus far. In addition, earlier studies lack in situ confirmation of targeting except for the magnetic resonance imaging-guided FUS system-based studies. The purpose of this study is 1) to introduce a fully ultrasonic approach to in situ target, modulate neuronal activity, and monitor the resultant neuromodulation effect by respectively leveraging displacement imaging, FUS, and functional ultrasound (fUS) imaging, and 2) to investigate FUS-evoked cerebral blood volume (CBV) response and the relationship between CBV and displacement. We performed displacement imaging on craniotomized mice to confirm the in targeting for neuromodulation site. We recorded hemodynamic responses evoked by FUS and fUS revealed an ipsilateral CBV increase that peaks at 4 s post-FUS. We saw a stronger hemodynamic activation in the subcortical region than cortical, showing good agreement with the brain elasticity map that can also be obtained using a similar methodology. We observed dose-dependent CBV response with peak CBV, activated area, and correlation coefficient increasing with ultrasonic dose. Furthermore, by mapping displacement and hemodynamic activation, we found that displacement colocalizes and linearly correlates with CBV increase. The findings presented herein demonstrated that FUS evokes ipsilateral hemodynamic activation in cortical and subcortical depths and the evoked hemodynamic responses colocalized and correlate with FUS-induced displacement. We anticipate that our findings will help consolidate accurate targeting as well as an understanding of how FUS displaces brain tissue and affects cerebral hemodynamics.
A comparison of wild boar and domestic pig microbiota does not reveal a loss of microbial species but an increase in alpha diversity and opportunistic genera in domestic pigs
Authors: Rahman Rajibur , Fouhse Janelle M. , Ju Tingting , Fan Yi , Marcolla Camila S. , Pieper Robert , Brook Ryan K. , Willing Benjamin P.
Published: April 2024

The microbiome of wild animals is believed to be co-evolved with host species, which may play an important role in host physiology. It has been hypothesized that the rigorous hygienic practice in combination with antibiotics and diets with simplified formulas used in the modern swine industry may negatively affect the establishment and development of the gut microbiome. In this study, we evaluated the fecal microbiome of 90 domestic pigs sampled from 9 farms in Canada and 39 wild pigs sampled from three different locations on two continents (North America and Europe) using 16S rRNA gene amplicon sequencing. Surprisingly, the gut microbiome in domestic pigs exhibited higher alpha-diversity indices than wild pigs (P<0.0001). The wild pig microbiome showed a lower Firmicutes to Bacteroidetes ratio and a higher presence of bacterial phyla Elusimicrobiota, Verrucomicrobiota, Cyanobacteria, and Fibrobacterota compared to their domestic counterparts. At the genus level, wild pig microbiome had enriched genera that were known for fibre degradation and short-chained fatty acids production. Interestingly, the phylum Fusobacteriota was only observed in domestic pigs. We identified 31 ASVs that were commonly found in the pig gut microbiome regardless of host sources, which could be recognized as members of the core gut microbiome. Interestingly, we found a few ASVs missing in domestic pigs that were prevalent in wild ones, whereas domestic pigs harbored 59 ASVs that were completely absent in wild pigs. The present study sheds light on the impact of domestication on the pig gut microbiome, including the gain of new genera.

Importance

The microbiome of pigs plays a crucial role in shaping host physiology and health. This study looked to identify if domestication and current rearing practices have resulted in a loss of co-evolved bacterial species by comparing the microbiome of wild boar and conventionally raised pigs. It represents a comparison of domestic and wild pigs with the largest sample sizes, and is the first to examine wild boars from multiple sites and continents. We were able to identify core microbiome members that were shared between wild and domestic populations, and counter to expectation, few microbes were identified to be lost from wild boar. Nevertheless, the microbiome of wild boars was distinct from domestic pigs, with notably lower abundance of important pathogenic genera. The differences in microbial composition may identify an opportunity to shift the microbial community of domestic pigs towards that of wild boar with the intent to reduce pathogen load.
Robotic-inspired approach to multi-domain membrane receptor conformation space: theory and SARS-CoV-2 spike protein case study
Authors: Mathew Alen T. , Sikora Mateusz , Hummer Gerhard , Mehdipour A. Reza
Published: April 2024

1

The spike protein of SARS-CoV-2 is a highly flexible membrane receptor that triggers the translocation of the virus into cells by attaching to the human receptors. Like other type I membrane receptors, this protein has several extracellular domains connected by flexible hinges. The presence of these hinges results in high flexibility, which consequently results in challenges in defining the conformation of the protein. Here, We developed a new method to define the conformational space based on a few variables inspired by the robotic field’s methods to determine a robotic arm’s forward kinematics. Using newly performed atomistic molecular dynamics (MD) simulations and publicly available data, we found that the Denavit-Hartenberg (DH) parameters can reliably show the changes in the local conformation. Furthermore, the rotational and translational components of the homogenous transformation matrix constructed based on the DH parameters can identify the changes in the global conformation of the spike and also differentiate between the conformation with a similar position of the spike head, which other types of parameters, such as spherical coordinates, fail to distinguish between such conformations. Finally, the new method will be beneficial for looking at the conformational heterogeneity in all other type I membrane receptors.
Rapid differentiation of estrogen receptor status in patient biopsy breast cancer aspirates with an optical nanosensor
Authors: Gaikwad Pooja V. , Rahman Nazifa , Ghosh Pratyusha , Ng Dianna , Williams Ryan M.
Published: April 2024

Breast cancer is a substantial source of morbidity and mortality worldwide. It is particularly more difficult to treat at later stages, and treatment regimens depend heavily on both staging and the molecular subtype of the tumor. However, both detection and molecular analyses rely on standard imaging and histological method, which are costly, time-consuming, and lack necessary sensitivity/specificity. The estrogen receptor (ER) is, along with the progesterone receptor (PR) and human epidermal growth factor (HER-2), among the primary molecular markers which inform treatment. Patients who are negative for all three markers (triple negative breast cancer, TNBC), have fewer treatment options and a poorer prognosis. Therapeutics for ER+ patients are effective at preventing disease progression, though it is necessary to improve the speed of subtyping and distribution of rapid detection methods. In this work, we designed a near-infrared optical nanosensor using single-walled carbon nanotubes (SWCNT) as the transducer and an anti-ERα antibody as the recognition element. The nanosensor was evaluated for its response to recombinant ERα in buffer and serum prior to evaluation with ER- and ER+ immortal cell lines. We then used a minimal volume of just 10 µL from 26 breast cancer biopsy samples which were aspirated to mimic fine needle aspirates. 20 samples were ER+, while 6 were ER-, representing 13 unique patients. We evaluated the potential of the nanosensor by investigating several SWCNT chiralities through direct incubation or fractionation deployment methods. We found that the nanosensor can differentiate ER-from ER+ patient biopsies through a shift in its center wavelength upon sample addition. This was true regardless of which of the three SWCNT chiralities we observed. Receiver operating characteristic area under the curve analyses determined that the strongest classifier with an AUC of 0.94 was the (7,5) chirality after direct incubation and measurement, and without further processing. We anticipate that further testing and development of this nanosensor may push its utility toward field-deployable, rapid ER subtyping with potential for additional molecular marker profiling.
Intron retention as an excellent marker for diagnosing depression and for discovering new potential pathways for drug intervention
Authors: Okada Norihiro , Oshima Kenshiro , Maruko Akiko , Sekine Mariko , Ito Naoki , Wakasugi Akino , Mori Eiko , Odaguchi Hiroshi , Kobayashi Yoshinori
Published: April 2024

BACKGROUND

Peripheral inflammation is often associated with depressive disorders, and immunological biomarkers of depression remain a focus of investigation.

METHODS

We performed RNA-seq analysis of RNA transcripts of human peripheral blood mononuclear cells from a case-control study including subjects with self-reported depression in the pre-symptomatic state of major depressive disorder and analyzed differentially expressed genes (DEGs) and the frequency of intron retention (IR) using rMATS.

RESULTS

Among the statistically significant DEGs identified, 651 upregulated and 820 downregulated genes were enriched in the Gene Ontology term ‘innate and adaptive immunity’. The upregulated DEGs were particularly enriched in the term ‘bacterial infection and phagocytosis’, whereas the downregulated DEGs were enriched in the terms ‘antigen presentation’ and ‘T-cell proliferation and maturation’. We also analyzed 158 genes for which IR was increased (IncIR) and 211 genes for which IR was decreased (DecIR) among the depressed subjects. The Gene Ontology terms associated with IncIR and DecIR were very similar to those of the up- and downregulated genes, respectively, with a preponderance of the term ‘ciliary assembly and function’ for DecIR. Moreover, the results of the network analysis also showed that a Japanese herbal medicine could partially mitigate the severity of depression among depressed patients. Inclusion of both IncIR and DecIR genes in the network analysis revealed several pathways related to the ability of patients to recover from depression.

CONCLUSION

Depression was found to be associated with activation of the innate immune response and relative inactivation of T-cell signaling. The DEGs we identified reflect physiological demands that are controlled at the transcriptional level, whereas the IR results reflect a more direct mechanism for monitoring protein homeostasis. Accordingly, an overall increase in IR is a stress response, and intron-retained transcripts are sensors of the physiological state of the cytoplasm. In particular, detection of increased IR in cilia-specific genes apparently correlates with defects in ciliary function or immunological synapse in depressed subjects. The results demonstrate the potential of relative IR as a biomarker for the immunological stratification of depressed patients and the utility of IR for the discovery of novel pathways involved in recovery from depression.
Diagnostic test accuracy of clinical scores in diagnosing Acute appendicitis in Right Iliac Fossa Pain
Authors: Desai Dev , Patel Rajan B. , Patel Jyot
Published: April 2024

Introduction

For patients presenting to the Emergency room or OPD with acute severe right iliac fossa pain, the clinicians mostly prefer acute appendicitis as the first diagnosis, though many other differential diagnoses are there. Usually, in ER or OPD, clinical scores such as Alvarado Score, Ripasa scoring, and Tzanakis Scoring to diagnose Acute appendicitis. All these scores have different overlapping parameters and variable amounts of weightage. It is important to understand how sensitive and specific these scores are to determine the most accurate score to accurately diagnose acute appendicitis.

Objectives

Determine the Diagnostic accuracy of Alvarado Scoring, Ripasa Scoring, and Tzanakis Scoring compared to the Gold Standard Histopathology report.

Methodology

A Retrospective observational design was formulated where data of patients coming to the ER and OPD of the affiliated tertiary care hospital with right iliac fossa pain were enrolled. From the data, all clinical scores were calculated as per the standard guideline and the results of the scores were correlated with the gold standard Intraoperative Surgeon’s opinion and the patient’s histopathological report to determine the sensitivity, specificity, Youden Index and Accuracy of all the scores. Statistical software like EXCEL and SPSS along with Medcalc was used to produce the ROC Curve (Receiver Operating Characteristic Curve) & AUC of ROC and Fagan’s Nomogram.

Results

A total of 237 patients were enrolled who presented with right iliac fossa pain of which 156 were confirmed from the Histopathology report as patients with Acute Appendicitis. The Sensitivity was calculated for Alvarado (0.487), Ripasa (0.641), and Tzanakis(0.8269) whereas the Calculated Specificity was for Alvarado(0.8148), Ripasa(0.8395), Tzanakis(0.9699). The Younden Index was highest for Tzanakis score at 0.7968.

Conclusion

The Tzanakis Score is the most accurate Scoring method to diagnose Acute Appendicitis in patients presenting with RIF pain as it includes Ultrasonography. When USG is not available, the Ripasa score is the best scoring method while we do not recommend the use of Alvarado scoring due to poor sensitivity.
Predictors of positive remodeling in patients with acute ischemia stroke
Authors: Li Gen , Xu Di-hao , Xie Jing-wen , Ma Li-ping , Shu Min , Zeng Zhi-bin
Published: April 2024

Objective

This study aimed to delineate the differences in plaques characteristics between positive remodeling (PR) and non-positive remodeling (NPR) in patients with Acute ischemia stroke (AIS), and to assess the associated relative risk factors for PR in intracranial atherosclerosis (ICAS).

Methods

Patients with AIS were enrolled and underwent high-resolution magnetic resonance vessel wall imaging (HR-VWI) within two weeks of symptom onset. We compared plaque morphologies and clinical variables between the PR and NPR cohorts. Binary logistic regression was employed to isolate independent predictors of PR, and the predictive model’s sensitivity and specificity were gauged using the receiver operating characteristic curve.

Results

A total of 84 patients (mean age 58.07±1.35 years, 78.6% male) were categorized into PR (n=28, 33.3%) or NPR (n=56, 66.4%) groups based on the remodeling index (RI). The PR group exhibited a significantly higher percent plaque burden (P<0.001), wall area (WA) (P<0.001), plaque length (P=0.018), and RI (P<0.001), alongside elevated fasting blood glucose (P=0.01) and a higher prevalence of hypertension and diabetes mellitus (P=0.16, 0.025). Logistic regression analysis identified percent plaque burden as an independent predictor of PR (odds ratio, 4.19, per 10% increase; [95% CI, 1.79-9.8];P=0.001).

Conclusion

HR-VWI is an effective tool for identifying PR in AIS caused by ICAS, with a high plaque burden being an independent correlate of PR.
DeepSS2GO: protein function prediction from secondary structure
Authors: Song Fu V. , Su Jiaqi , Huang Sixing , Zhang Neng , Li Kaiyue , Ni Ming , Liao Maofu
Published: April 2024

Predicting protein function is crucial for understanding biological life processes, preventing diseases, and developing new drug targets. In recent years, methods based on sequence, structure, and biological networks for protein function annotation have been extensively researched. Although obtaining a protein in three-dimensional structure through experimental or computational methods enhances the accuracy of function prediction, the sheer volume of proteins sequenced by high-throughput technologies presents a significant challenge. To address this issue, we introduce a deep neural network model DeepSS2GO (Secondary Structure to Gene Ontology). It is a predictor incorporating secondary structure features along with primary sequence and homology information. The algorithm expertly combines the speed of sequence-based information with the accuracy of structure-based features, while streamlining the redundant data in primary sequences and bypassing the timeconsuming challenges of tertiary structure analysis. The results show that the prediction performance surpasses state-ofthe-art algorithms. It has the ability to predict key functions by effectively utilizing secondary structure information, rather than broadly predicting general Gene Ontology terms. Additionally, DeepSS2GO predicts five times faster than advanced algorithms, making it highly applicable to massive sequencing data. The source code and trained models are available athttps://github.com/orca233/DeepSS2GO.
G-S-M: A Comprehensive Framework for Integrative Feature Selection in Omics Data Analysis and Beyond
Authors: Yousef Malik , Allmer Jens , İnal Yasin , Gungor Burcu Bakir
Published: April 2024

The treatment of human diseases is a major research question in many fields related to medicine. It has become clear that patient stratification is of utmost importance so that patients receive the best possible treatment. Bio/disease markers are critical to achieve stratification. Markers can come from many different sources such as genomics, transcriptomics, and proteomics. Establishing markers from such measurements often involves data analysis, machine learning, and feature selection. Traditional feature selection techniques often rely on the estimation of individual feature importance or significance by assigning a score to each feature, disregarding the inter-feature relationships. In contrast, the G-S-M (grouping scoring modeling) approach considers a group of features as a set that is organized based on prior knowledge. This approach takes into account the interdependence among features, providing a more meaningful evaluation of feature relevance and utility. Prior knowledge can encompass much compiled information such as microRNA-target interactions and protein-protein interactions. Here we present a new tool called G-S-M that presents the generalization of our previous works such as maTE, CogNet, and PriPath. The G-S-M tool combines machine learning and prior knowledge to group and score features based on their association with a binary-labeled target such as control and disease. This approach is unique in that computational and domain knowledge is utilized concurrently. Embedded feature selection, repeatedly employing machine learning during the selection process results in the identification of the most discriminative groups.

Furthermore, the G-S-M tool allows for a more holistic understanding of the underlying mechanisms of a given system to be achieved through the combination of machine learning and prior domain knowledge, which can lead to new insights and discoveries. The implementation of the G-S-M workflow is freely available for download from our GitHub repository:https://github.com/malikyousef/The-G-S-M-Grouping-Scoring-Modeling-Approach. With this generalized approach we aim to make the feature selection approach available to a broader audience and hope it will be employed in medical practice. An example of such an approach is the TextNetTopics that is based on the G-S-M approach. TextNetTopics uses Latent Dirichlet Allocation (LDA) to detect topics of words, where those topics serve as groups. In the future, we aim to extend the approach to enable the incorporation of multiple lines of evidence for biomarker detection and patient stratification via combining multi-omics data.
Partitioning changes in ecosystem productivity by effects of species interactions in biodiversity experiments
Authors: Tao Jing , Nock Charles A. , Searle Eric B. , Huang Shongming , Man Rongzhou , Yang Hua , Freschet Grégoire T. , Violle Cyrille , Zheng Ji
Published: April 2024

Species interactions affect ecosystem productivity. Positive interactions (resource partitioning and facilitation) increase productivity while negative interactions (species interference) decrease productivity relative to the null expectations defined by monoculture yields. Effects of competitive interactions (resource competition) can be either positive or negative. Distinguishing effects of species interactions is therefore difficult, if not impossible, with current biodiversity experiments involving mixtures and full density monocultures.

To partition changes in ecosystem productivity by effects of species interactions, we modify null expectations with competitive growth responses, i.e., proportional changes in individual size (biomass or volume) expected in mixture based on species differences in growth and competitive ability. We use partial density (species density in mixture) monocultures and the competitive exclusion principle to determine maximum competitive growth responses and full density monoculture yields to measure species ability to achieve maximum competitive growth responses in mixture. Deviations of observed yields from competitive expectations represent the effects of positive/negative species interactions, while the differences between competitive and null expectations reflect the effects of competitive interactions.

We demonstrate the effectiveness of our competitive partitioning model in distinguishing effects of species interactions using both simulated and experimental species mixtures. Our competitive partitioning model enables meaningful assessments of species interactions at both species and community levels and helps disentangle underlying mechanisms of species interactions responsible for changes in ecosystem productivity and identify species mixtures that maximize positive effects.
Empowering Student Authorship in Synthetic Biology
Authors: Roberts Louis A. , Farny Natalie G.
Published: April 2024

Women and racial minorities are underrepresented in the synthetic biology community. Developing a scholarly identity by engaging in a scientific community through writing and communication is an important component for STEM retention, particularly for underrepresented individuals. Several excellent pedagogical tools have been developed to teach scientific literacy and to measure competency in reading and interpreting scientific literature. However, fewer tools exist to measure learning gains with respect to writing, or that teach the more abstract processes of peer review and scientific publishing, which are essential for developing scholarly identity and publication currency. Here we describe our approach to teaching scientific writing and publishing to undergraduate students within a synthetic biology course. Using gold standard practices in project-based learning, we created a writing project in which students became experts in a specific application area of synthetic biology with relevance to an important global problem or challenge. To measure learning gains associated with our learning outcomes, we adapted and expanded the Student Attitudes, Abilities, and Beliefs (SAAB) concept inventory to include additional questions about the process of scientific writing, authorship, and peer review. Our results suggest the project-based approach was effective in achieving the learning objectives with respect to writing and peer reviewed publication, and resulted in high student satisfaction and student self-reported learning gains. We propose that these educational practices will contribute directly to the development of scientific identity of undergraduate students as synthetic biologists, and will be useful in creating a more diverse synthetic biology research enterprise.
Donanemab outperformed Aducanumab and Lecanemab on cognitive, but not on biomarker and safety outcomes: systematic review, frequentist and Bayesian network meta-analyses
Authors: Jeremic Danko , Navarro-López Juan D. , Jiménez-Díaz Lydia
Published: April 2024

INTRODUCTION

Questions remain regarding safety and clinical relevance of anti-amyloid antibodies in Alzheimer’s disease (AD), with no scientific basis for choosing between different therapies.

METHODS

Systematic review, frequentist and Bayesian network meta-analyses of phase III randomized placebo-controlled trials were performed to comparatively evaluate cognitive, functional and biomarker efficacy and safety of anti-amyloid antibodies in sporadic AD. Treatments were ranked with P- and SUCRA scores, with rank robustness measured by Cohen’skappa, and uncertainty in ranking probabilities estimated with Shannon’s normalized entropy.

RESULTS

Based on data from 16,971 patients (16 studies), we found Donanemab the best-ranked antibody on cognitive measures. Lecanemab was the most effective at reducing amyloid burden. Caution is needed concerning brain edema and microbleeding, with clinically important risks for Donanemab, Aducanumab and Lecanemab.

DISCUSSION

Risk/benefit profile of anti-amyloid antibodies remains unfavorable. Patients in Donanemab study were stratified bytauload, with greater effects observed in low/mediumtaupopulation.

Highlights

No single therapy ranked the best among all outcomes.

Donanemab was the most effective antibody at reducing cognitive decline across all primary outcomes, while Lecanemab ranked the highest on amyloid PET removal.

Consistently greater cognitive, functional and biomarker effects of Donanemab were observed in patients with low/mediumtauload, suggesting more promising effects in earlier AD stages.

All antibodies, except Solanezumab, were significantly less tolerable than Placebo.

The risk of cerebral edema and microbleeding may outweigh the benefits, independently of APOE status.
Wastewater surveillance of antibiotic resistant bacteria for public health action: Potential and Challenges
Authors: Foxman Betsy , Salzman Elizabeth , Gesierich Chelsie , Gardner Sarah , Ammerman Michelle , Eisenberg Marisa , Wigginton Krista
Published: April 2024

Antibiotic resistance is an urgent public health threat. Actions to reduce this threat include requiring prescriptions for antibiotic use, antibiotic stewardship programs, educational programs targeting patients and healthcare providers, and limiting antibiotic use in agriculture, aquaculture, and animal husbandry. Wastewater surveillance might complement clinical surveillance by tracking time/space variation essential for detecting outbreaks and evaluating efficacy of evidence-based interventions; identifying high-risk populations for targeted monitoring; providing early warning of the emergence and spread of antibiotic resistant bacteria and identifying novel antibiotic resistant threats. Wastewater surveillance was an effective early warning system for SARS-CoV-2 spread and detection of the emergence of new viral strains. In this data-driven commentary we explore whether monitoring wastewater for antibiotic resistant genes and/or bacteria resistant to antibiotics might provide useful information for public health action. Using carbapenem resistance as an example, we highlight technical challenges associated with using wastewater to quantify temporal/spatial trends in antibiotic resistant bacteria (ARBs) and antibiotic resistant genes (ARGs) and compare with clinical information. While ARGs and ARBs are detectable in wastewater enabling early detection of novel ARGs, quantitation of ARBs and ARGs with current methods is too variable to reliably track space/time variation.