Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeted Next-Generation Sequencing of Circulating Tumor DNA Mutations among Metastatic Breast Cancer Patients

Liquid biopsy through the detection of circulating tumor DNA (ctDNA) has potential advantages in cancer monitoring and prediction. However, most previous studies in this area were performed with a few hotspot genes, single time point detection, or insufficient sequencing depth. In this study, we performed targeted next-generation sequencing (NGS) with a customized panel in metastatic breast cancer (MBC) patients. Fifty-four plasma samples were taken before chemotherapy and after the third course of treatment for detection and analysis. Paired lymphocytes were also included to eliminate clonal hematopoiesis (CH)-related alternatives. A total of 1182 nonsynonymous mutations in 419 genes were identified. More ctDNA mutations were detected in patients with tumors > 3 cm (p = 0.035) and HER2(−) patients (p = 0.029). For a single gene, the distribution of ctDNA mutations was also correlated with clinical characteristics. Multivariate regression analysis revealed that HER2 status was significantly associated with mutation burden (OR 0.02, 95% CI 0–0.62, p = 0.025). The profiles of ctDNA mutations exhibited marked discrepancies between two time points, and baseline ctDNA was more sensitive and specific than that after chemotherapy. Finally, elevated ctDNA mutation level was positively correlated with poor survival (p < 0.001). Mutations in ctDNA could serve as a potential biomarker for the evaluation, prediction, and clinical management guidance of MBC patients with chemotherapy.
Methane Hydrate Nucleation Rates from Molecular Dynamics Simulations: Effects of Aqueous Methane Concentration, Interfacial Curvature, and System Size

Methane hydrate nucleation rates are reported from over 200 μs of molecular dynamics simulations across a range of thermodynamic conditions and varying degrees of methane–water interfacial curvature. Calculated nucleation rates increase with aqueous phase methane concentration (XCH4), consistent with experimental results. The effect of interfacial curvature on XCH4 is quantified, with dissolved methane concentration increasing with the degree of curvature (i.e., the number of dimensions in which curvature exists). Nucleation rates are reported for system sizes of 3456 and 13 824 molecules (H2O + CH4). Among the smaller simulation systems (which comprise the majority of the data), the calculated hydrate nucleation rates follow the same trend when plotted against XCH4 regardless of whether the predominant contribution to the effective system pressure is the simulation barostat or the methane–water interfacial curvature (Young–Laplace pressure). The incipient hydrate nuclei are destabilized in the immediate .
A Primer on the Clinical Aspects of Sarcoidosis for the Basic and Translational Scientist

The immunopathogenesis of sarcoidosis remains unclear. This failure in understanding has been clinically impactful, as it has impeded the accurate diagnosis, treatment, and prevention of this disease. Unraveling the mechanisms of sarcoidosis will require input from basic and translational scientists. In order to reach this goal, scientists must have a firm grasp of the clinical aspects of the disease, including its diagnostic criteria, the immunologic defects, clinical presentations, response to therapy, risk factors, and clinical course. This manuscript will provide an overview of the clinical aspects of sarcoidosis that are particularly relevant for the basic and translational scientist. The variable phenotypic expression of the disease will be described, which may be integral in identifying immunologic disease mechanisms that may be relevant to subgroups of sarcoidosis patients. Data concerning treatment and risk factors may yield important insights concerning germane immunologic pathways involved in the development of disease. It is hoped that this manuscript will stimulate communication between scientists and clinicians that will eventually lead to improved care of sarcoidosis patients.
Exploration of the Supraspinal Hypotheses about Spinal Cord Stimulation and Dorsal Root Ganglion Stimulation: A Systematic Review

Despite the established efficacy and effectiveness of Spinal Cord Stimulation (SCS), there is still no consensus on the supraspinal mechanisms of action of this therapy. The purpose of this study was to systematically review previously raised hypotheses concerning supraspinal mechanisms of action of SCS based on human, animal and computational studies. Searches were conducted using four electronic databases (PubMed, EMBASE, SCOPUS and Web of Science), backward reference searching and consultation with experts. The study protocol was registered prior to initiation of the review process (PROSPERO CRD42020161531). A total of 54 publications were included, 21 of which were animal studies, and 33 were human studies. The supraspinal hypotheses (n = 69) identified from the included studies could be categorized into six groups concerning the proposed supraspinal hypothesis, namely descending pathways (n = 24); ascending medial pathway (n = 13); ascending lateral pathway (n = 10); affective/motivational influences (n = 8); spinal–cerebral (thalamic)-loop (n = 3) and miscellaneous (n = 11). Scientific support is provided for the hypotheses identified. Modulation of the descending nociceptive inhibitory pathways, medial and lateral pathways were the most frequently reported hypotheses about the supraspinal mechanisms of action of SCS. These hypotheses were mainly supported by studies with a high or moderate confidence in the body of evidence.
Antioxidant Effects and Phytochemical Properties of Seven Taiwanese Cirsium Species Extracts

In the present investigation, we compared the radical-scavenging activities and phenolic contents of seven Taiwanese Cirsium species with a spectrophotometric method. We further analyzed their phytochemical profiles with high-performance liquid chromatography–photodiode array detection (HPLC–DAD). We found that the flower part of Cirsium japonicum var. australe (CJF) showed the best radical-scavenging activities against 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and the hypochlorite ion, for which the equivalents were 6.44 ± 0.17 mg catechin/g, 54.85 ± 0.66 mmol Trolox/g and 418.69 ± 10.52 mmol Trolox/g respectively. CJF also had the highest contents of total phenolics (5.23 ± 0.20 mg catechin/g) and phenylpropanoids (29.73 ± 0.72 mg verbascoside/g). According to the Pearson’s correlation coefficient, there was a positive correlation between the total phenylpropanoid content and ABTS radical-scavenging activities (r = 0.979). The radical-scavenging activities of the phenylpropanoids are closely related to their reducing power (r = 0.986). HPLC chromatograms obtained in validated HPLC conditions confirm that they have different phytochemical profiles by which they can be distinguished. Only CJF contained silicristin (0.66 ± 0.03 mg/g) and silydianin (9.13 ± 0.30 mg/g). CJF contained the highest contents of apigenin (5.56 ± 0.09 mg/g) and diosmetin (2.82 ± 0.10 mg/g). Among the major constituents, silicristin had the best radical-scavenging activities against DPPH (71.68 ± 0.66 mg catechin/g) and ABTS (3.01 ± 0.01 mmol Trolox/g). However, diosmetin had the best reducing power and radical-scavenging activity against the hypochlorite anion (41.57 ± 1.14 mg mmol Trolox/g). Finally, we found that flavonolignans (especial silicristin and silydianin) and diosmetin acted synergistically in scavenging radicals.
Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Remotely sensed data from both in situ and satellite platforms in visible, near-infrared, and shortwave infrared (VNIR–SWIR, 400–2500 nm) regions have been widely used to characterize and model soil properties in a direct, cost-effective, and rapid manner at different scales. In this study, we assess the performance of machine-learning algorithms including random forest (RF), extreme gradient boosting machines (XGBoost), and support vector machines (SVM) to model salt marsh soil bulk density using multispectral remote-sensing data from the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) platform. To our knowledge, use of remote-sensing data for estimating salt marsh soil bulk density at the vegetation rooting zone has not been investigated before. Our study reveals that blue (band 1; 450–520 nm) and NIR (band 4; 770–900 nm) bands of Landsat-7 ETM+ ranked as the most important spectral features for bulk density prediction by XGBoost and RF, respectively. According to XGBoost, band 1 and band 4 had relative importance of around 41% and 39%, respectively. We tested two soil bulk density classes in order to differentiate salt marshes in terms of their capability to support vegetation that grows in either low (0.032 to 0.752 g/cm3) or high (0.752 g/cm3 to 1.893 g/cm3) bulk density areas. XGBoost produced a higher classification accuracy (88%) compared to RF (87%) and SVM (86%), although discrepancies in accuracy between these models were small (<2%). XGBoost correctly classified 178 out of 186 soil samples labeled as low bulk density and 37 out of 62 soil samples labeled as high bulk density. We conclude that remote-sensing-based machine-learning models can be a valuable tool for ecologists and engineers to map the soil bulk density in wetlands to select suitable sites for effective restoration and successful re-establishment practices.
DNA Methylation Profiling for the Diagnosis and Prognosis of Patients with Nontuberculous Mycobacterium Lung Disease

The incidence of nontuberculous Mycobacterium (NTM) lung disease is rapidly increasing; however, its diagnosis and prognosis remain unclear while selecting patients who will respond to appropriate treatment. Differences in DNA methylation patterns between NTM patients with good or poor prognosis could provide important therapeutic targets. We used the Illumina MethylationEPIC (850k) DNA methylation microarray to determine the pattern between differentially methylated regions (DMRs) in NTM patients with good or poor prognosis (n = 4/group). Moreover, we merged and compared 20 healthy controls from previous Illumina Methylation450k DNA methylation microarray data. We selected and visualized the DMRs in the form of heatmaps, and enriched terms associated with these DMRs were identified by functional annotation with the “pathfinder” package. In total, 461 and 293 DMRs (|Log2 fold change| > 0.1 and P < 0.03) were more methylated in patients with four poor and four good prognoses, respectively. Furthermore, 337 and 771 DMRs (|Log2 fold change| > 0.08 and P < 0.001) were more methylated in eight NTM patients and 20 healthy controls, respectively. TGFBr1 was significantly less methylated, whereas HLA-DR1 and HLA-DR5 were more methylated in patients with poor prognosis (compared to those with good prognosis). LRP5, E2F1, and ADCY3 were the top three less-methylated genes in NTM patients (compared with the controls). The mTOR and Wnt signaling pathway-related genes were less methylated in patients with NTM. Collectively, genes related to Th1- cell differentiation, such as TGFBr1 and HLA-DR, may be used as biomarkers for predicting the treatment response in patients with NTM lung disease.
Ethanol Extract of Maclura tricuspidata Fruit Protects SH-SY5Y Neuroblastoma Cells against H2O2-Induced Oxidative Damage via Inhibiting MAPK and NF-κB Signaling

Free radical generation and oxidative stress push forward an immense influence on the pathogenesis of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Maclura tricuspidata fruit (MT) contains many biologically active substances, including compounds with antioxidant properties. The current study aimed to investigate the neuroprotective effects of MT fruit on hydrogen peroxide (H2O2)-induced neurotoxicity in SH-SY5Y cells. SH-SY5Y cells were pretreated with MT, and cell damage was induced by H2O2. First, the chemical composition and free radical scavenging properties of MT were analyzed. MT attenuated oxidative stress-induced damage in cells based on the assessment of cell viability. The H2O2-induced toxicity caused by ROS production and lactate dehydrogenase (LDH) release was ameliorated by MT pretreatment. MT also promoted an increase in the expression of genes encoding the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT). MT pretreatment was associated with an increase in the expression of neuronal genes downregulated by H2O2. Mechanistically, MT dramatically suppressed H2O2-induced Bcl-2 downregulation, Bax upregulation, apoptotic factor caspase-3 activation, Mitogen-activated protein kinase (MAPK) (JNK, ERK, and p38), and Nuclear factor-κB (NF-κB) activation, thereby preventing H2O2-induced neurotoxicity. These results indicate that MT has protective effects against H2O2-induced oxidative damage in SH-SY5Y cells and can be used to prevent and protect against neurodegeneration.
The Case for Whole-Person Integrative Care

Rationale: There is a need for medicine to deliver more whole-person care. This is a narrative review of several models of whole-person care and studies that illustrate the business case for whole-person models in primary care. Objectives: To provide an overview of what whole-person care models exist and explore evidence to support these models. Study Selection: Representative whole-person care models widely used in the United States are summarized and evaluated. Selected studies focused on outpatient primary care with examples from programs that integrate the delivery of conventional medical care, complementary and alternative medicine, and self-care within the context of social and cultural environments. Methods: Pubmed search conducted December 2020–February 2021. Two iterative searches using terms for “Whole Health Veterans Administration”, “integrative medicine”, “integrative health”, “complementary and alternative medicine”, and, as they related to the outcomes, of “health outcomes”, “cost-effectiveness”, “cost reduction”, “patient satisfaction”, and “physician satisfaction”. Additional studies were identified from an initial search and the authors’ experience of over 50 years. We looked for studies of whole-person care used in general primary care, those not using a single modality and only from United States practices. Results: A total of 125 (out of 1746) studies were found and met our inclusion criteria. We found that whole-person models of primary care exist, are quite heterogeneous in their approaches, and routinely report substantial benefits for improving the patient experience, clinical outcomes and in reducing costs. Conclusions: Evidence for the benefit of whole-person care models exist but definitions are quite heterogenous and unfocused. There is a need for more standardization of whole-person models and more research using whole systems approaches rather than reductionistic attempts using isolated components.
AKT Signaling Modifies the Balance between Cell Proliferation and Migration in Neural Crest Cells from Patients Affected with Bosma Arhinia and Microphthalmia Syndrome

Over the recent years, the SMCHD1 (Structural Maintenance of Chromosome flexible Hinge Domain Containing 1) chromatin-associated factor has triggered increasing interest after the identification of variants in three rare and unrelated diseases, type 2 Facio Scapulo Humeral Dystrophy (FSHD2), Bosma Arhinia and Microphthalmia Syndrome (BAMS), and the more recently isolated hypogonadotrophic hypogonadism (IHH) combined pituitary hormone deficiency (CPHD) and septo-optic dysplasia (SOD). However, it remains unclear why certain mutations lead to a specific muscle defect in FSHD while other are associated with severe congenital anomalies. To gain further insights into the specificity of SMCHD1 variants and identify pathways associated with the BAMS phenotype and related neural crest defects, we derived induced pluripotent stem cells from patients carrying a mutation in this gene. We differentiated these cells in neural crest stem cells and analyzed their transcriptome by RNA-Seq. Besides classical differential expression analyses, we analyzed our data using MOGAMUN, an algorithm allowing the extraction of active modules by integrating differential expression data with biological networks. We found that in BAMS neural crest cells, all subnetworks that are associated with differentially expressed genes converge toward a predominant role for AKT signaling in the control of the cell proliferation–migration balance. Our findings provide further insights into the distinct mechanism by which defects in neural crest migration might contribute to the craniofacial anomalies in BAMS.
phyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data

MOTIVATION Research shows that human microbiome is highly dynamic on longitudinal timescales, changing dynamically with diet, or due to medical interventions. In this paper, we propose a novel deep learning framework "phyLoSTM", using a combination of Convolutional Neural Networks and Long Short Term Memory Networks (LSTM) for feature extraction and analysis of temporal dependency in longitudinal microbiome sequencing data along with host's environmental factors for disease prediction. Additional novelty in terms of handling variable timepoints in subjects through LSTMs, as well as, weight balancing between imbalanced cases and controls is proposed. RESULTS We simulated 100 datasets across multiple time points for model testing. To demonstrate the model's effectiveness, we also implemented this novel method into two real longitudinal human microbiome studies: (i) DIABIMMUNE three country cohort with food allergy outcomes (Milk, Egg, Peanut and Overall) (ii) DiGiulio study with preterm delivery as outcome. Extensive analysis and comparison of our approach yields encouraging performance with an AUC of 0.897 (increased by 5%) on simulated studies and AUCs of 0.762 (increased by 19%) and 0.713 (increased by 8%) on the two real longitudinal microbiome studies respectively, as compared to the next best performing method, Random Forest. The proposed methodology improves predictive accuracy on longitudinal human microbiome studies containing spatially correlated data, and evaluates the change of microbiome composition contributing to outcome prediction. AVAILABILITY AND IMPLEMENTATION https://github.com/divya031090/phyLoSTM.
Automated Radiology Alert System for Pneumothorax Detection on Chest Radiographs Improves Efficiency and Diagnostic Performance

We aimed to set up an Automated Radiology Alert System (ARAS) for the detection of pneumothorax in chest radiographs by a deep learning model, and to compare its efficiency and diagnostic performance with the existing Manual Radiology Alert System (MRAS) at the tertiary medical center. This study retrospectively collected 1235 chest radiographs with pneumothorax labeling from 2013 to 2019, and 337 chest radiographs with negative findings in 2019 were separated into training and validation datasets for the deep learning model of ARAS. The efficiency before and after using the model was compared in terms of alert time and report time. During parallel running of the two systems from September to October 2020, chest radiographs prospectively acquired in the emergency department with age more than 6 years served as the testing dataset for comparison of diagnostic performance. The efficiency was improved after using the model, with mean alert time improving from 8.45 min to 0.69 min and the mean report time from 2.81 days to 1.59 days. The comparison of the diagnostic performance of both systems using 3739 chest radiographs acquired during parallel running showed that the ARAS was better than the MRAS as assessed in terms of sensitivity (recall), area under receiver operating characteristic curve, and F1 score (0.837 vs. 0.256, 0.914 vs. 0.628, and 0.754 vs. 0.407, respectively), but worse in terms of positive predictive value (PPV) (precision) (0.686 vs. 1.000). This study had successfully designed a deep learning model for pneumothorax detection on chest radiographs and set up an ARAS with improved efficiency and overall diagnostic performance.
Cytoplasmic Human TDP-43 Mislocalization Induces Widespread Dendritic Spine Loss in Mouse Upper Motor Neurons

Amyotrophic lateral sclerosis (ALS) is defined by the destruction of upper- and lower motor neurons. Post-mortem, nearly all ALS cases are positive for cytoplasmic aggregates containing the DNA/RNA binding protein TDP-43. Recent studies indicate that this pathogenic mislocalization of TDP-43 may participate in generating hyperexcitability of the upper motor neurons, the earliest detectable change in ALS patients, yet the mechanisms driving this remain unclear. We investigated how mislocalisation of TDP-43 could initiate network dysfunction in ALS. We employed a tetracycline inducible system to express either human wildtype TDP-43 (TDP-43WT) or human TDP-43 that cannot enter the nucleus (TDP-43ΔNLS) in excitatory neurons (Camk2α promoter), crossed Thy1-YFPH mice to visualize dendritic spines, the major site of excitatory synapses. In comparison to both TDP-43WT and controls, TDP-43ΔNLS drove a robust loss in spine density in all the dendrite regions of the upper motor neurons, most affecting thin spines. This indicates that TDP-43 is involved in the generation of network dysfunction in ALS likely through impacting the formation or durability of excitatory synapses. These findings are relevant to the vast majority of ALS cases, and provides further evidence that upper motor neurons may need to be protected from TDP-43 mediated synaptic excitatory changes early in disease.
Antimicrobial Peptides and Physical Activity: A Great Hope against COVID 19

Antimicrobial peptides (AMPs), α- and β-defensins, possess antiviral properties. These AMPs achieve viral inhibition through different mechanisms of action. For example, they can: (i) bind directly to virions; (ii) bind to and modulate host cell-surface receptors, disrupting intracellular signaling; (iii) function as chemokines to augment and alter adaptive immune responses. Given their antiviral properties and the fact that the development of an effective coronavirus disease 2019 (COVID-19) treatment is an urgent public health priority, they and their derivatives are being explored as potential therapies against COVID-19. These explorations using various strategies, range from their direct interaction with the virus to using them as vaccine adjuvants. However, AMPs do not work in isolation, specifically in their role as potent immune modulators, where they interact with toll-like receptors (TLRs) and chemokine receptors. Both of these receptors have been shown to play roles in COVID-19 pathogenesis. In addition, it is known that a healthy lifestyle accompanied by controlled physical activity can represent a natural weapon against COVID-19. In competitive athletes, an increase in serum defensins has been shown to function as self-protection from the attack of microorganisms, consequently a controlled physical activity could act as a support to any therapies in fighting COVID-19. Therefore, including information on all these players’ interactions would produce a complete picture of AMP-based therapies’ response.