bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractFocused 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

AbstractThe 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.ImportanceThe 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

1SummaryThe 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

AbstractBreast 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

AbstractBACKGROUNDPeripheral inflammation is often associated with depressive disorders, and immunological biomarkers of depression remain a focus of investigation.METHODSWe 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.RESULTSAmong 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.CONCLUSIONDepression 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

AbstractIntroductionFor 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.ObjectivesDetermine the Diagnostic accuracy of Alvarado Scoring, Ripasa Scoring, and Tzanakis Scoring compared to the Gold Standard Histopathology report.MethodologyA 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.ResultsA 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.ConclusionThe 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

AbstractObjectiveThis 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).MethodsPatients 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.ResultsA 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).ConclusionHR-VWI is an effective tool for identifying PR in AIS caused by ICAS, with a high plaque burden being an independent correlate of PR.
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

AbstractThe 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

AbstractSpecies 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

AbstractWomen 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.