Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive and Negative Species Interactions Shape Recruitment Patterns of a Range Expanding Native Alga

A species’ ability to spread is in part governed by the extent to which recipient habitats either resist, tolerate or promote the species’ recruitment. In disturbed marine environments, there is a general trend for the loss of algal canopies, thought to resist invasion, toward algal turf or rock barrens habitat. This study tested whether the spread of the range-expanding native macroalga Caulerpa filiformis was resisted by algal canopies but facilitated by algal turf or barrens habitats. Large-scale field surveys generally supported the predicted recruitment patterns, with C. filiformis recruits being most abundant on turf (but not barrens) and absent under kelp canopies. However, a discrepancy existed between different structural forms of turf, with the positive association holding true only for geniculate corallines, not filamentous turf. Secondly, a laboratory experiment tested whether the physical structure and/or the sediment-trapping properties of coralline turf influenced the recruitment success of C. filiformis. Whilst the structural complexity of turf aided overall recruitment performance (i.e., increased rhizoid production, attachment speed, success, and strength), a positive influence of turf-derived sediment on recruits’ growth was less obvious, at least over 10 days. The high morphological plasticity of C. filiformis propagules resulted in possible benefits of faster or stronger attachment of more developed propagules being only temporary, and that recruitment may be regulated in accordance with habitat preference. Finally, a field experiment confirmed the observed positive role of turf and the negative influence of algal canopies in the short-term, however, adverse environmental conditions in the longer-term resulted in the loss of most fragments. In conclusion, this study demonstrated the importance of both positive and negative species interactions for the recruitment success of a native alga, suggesting that a shift from kelp to turf algae can initiate further community change.
Alterations of White Matter Network Properties in Patients With Functional Constipation

Background: The abnormalities in brain function and structure of patients with functional constipation (FC) have been identified using multiple neuroimaging studies and have confirmed the abnormal processing of visceral sensation at the level of the central nervous system (CNS) as an important reason for FC. As an important basis for central information transfer, the role of the white matter (WM) networks in the pathophysiology of FC has not been investigated. This study aimed to explore the topological organization of WM networks in patients with FC and its correlation with clinical variables. Methods and Analysis: In this study, 70 patients with FC and 45 age- and gender-matched healthy subjects (HS) were recruited. Diffusion tensor imaging (DTI) data and clinical variables were acquired from each participant. WM networks were constructed using the deterministic fiber tracking approach, and the global and nodal properties of the WM networks were compared using graph theory analysis between patients with FC and HS. The relationship between the representative nodal characteristics–nodal betweenness and clinical parameters was assessed using partial correlation analysis. Results: Patients with FC showed increased nodal characteristics in the left superior frontal gyrus (orbital part), right middle frontal gyrus (orbital part), and right anterior cingulate and paracingulate (P < 0.05, corrected for false discovery rate) and decreased nodal characteristics in the left caudate and left thalamus (P < 0.05, corrected for false discovery rate) compared with HS. The duration of FC was negatively correlated with the nodal betweenness of the left thalamus (r = −0.354, P = 0.04, corrected for false discovery rate). Conclusion: The results indicated the alternations in WM networks of patients with FC and suggested the abnormal visceral sensation processing in the CNS from the perspective of large-scale brain WM network.
Simultaneous Measurement of the BOLD Effect and Metabolic Changes in Response to Visual Stimulation Using the MEGA-PRESS Sequence at 3 T

The blood oxygen level dependent (BOLD) effect that provides the contrast in functional magnetic resonance imaging (fMRI) has been demonstrated to affect the linewidth of spectral peaks as measured with magnetic resonance spectroscopy (MRS) and through this, may be used as an indirect measure of cerebral blood flow related to neural activity. By acquiring MR-spectra interleaved with frames without water suppression, it may be possible to image the BOLD effect and associated metabolic changes simultaneously through changes in the linewidth of the unsuppressed water peak. The purpose of this study was to implement this approach with the MEGA-PRESS sequence, widely considered to be the standard sequence for quantitative measurement of GABA at field strengths of 3 T and lower, to observe how changes in both glutamate (measured as Glx) and GABA levels may relate to changes due to the BOLD effect. MR-spectra and fMRI were acquired from the occipital cortex (OCC) of 20 healthy participants whilst undergoing intrascanner visual stimulation in the form of a red and black radial checkerboard, alternating at 8 Hz, in 90 s blocks comprising 30 s of visual stimulation followed by 60 s of rest. Results show very strong agreement between the changes in the linewidth of the unsuppressed water signal and the canonical haemodynamic response function as well as a strong, negative, but not statistically significant, correlation with the Glx signal as measured from the OFF spectra in MEGA-PRESS pairs. Findings from this experiment suggest that the unsuppressed water signal provides a reliable measure of the BOLD effect and that correlations with associated changes in GABA and Glx levels may also be measured. However, discrepancies between metabolite levels as measured from the difference and OFF spectra raise questions regarding the reliability of the respective methods.
SMIXnorm: Fast and Accurate RNA-Seq Data Normalization for Formalin-Fixed Paraffin-Embedded Samples

RNA-sequencing (RNA-seq) provides a comprehensive quantification of transcriptomic activities in biological samples. Formalin-Fixed Paraffin-Embedded (FFPE) samples are collected as part of routine clinical procedure, and are the most widely available biological sample format in medical research and patient care. Normalization is an essential step in RNA-seq data analysis. A number of normalization methods, though developed for RNA-seq data from fresh frozen (FF) samples, can be used with FFPE samples as well. The only extant normalization method specifically designed for FFPE RNA-seq data, MIXnorm, which has been shown to outperform the normalization methods, but at the cost of a complex mixture model and a high computational burden. It is therefore important to adapt MIXnorm for simplicity and computational efficiency while maintaining superior performance. Furthermore, it is critical to develop an integrated tool that performs commonly used normalization methods for both FF and FFPE RNA-seq data. We developed a new normalization method for FFPE RNA-seq data, named SMIXnorm, based on a simplified two-component mixture model compared to MIXnorm to facilitate computation. The expression levels of expressed genes are modeled by normal distributions without truncation, and those of non-expressed genes are modeled by zero-inflated Poisson distributions. The maximum likelihood estimates of the model parameters are obtained by a nested Expectation-Maximization algorithm with a less complicated latent variable structure, and closed-form updates are available within each iteration. Real data applications and simulation studies show that SMIXnorm greatly reduces computing time compared to MIXnorm, without sacrificing the performance. More importantly, we developed a web-based tool, RNA-seq Normalization (RSeqNorm), that offers a simple workflow to compute normalized RNA-seq data for both FFPE and FF samples. It includes SMIXnorm and MIXnorm for FFPE RNA-seq data, together with five commonly used normalization methods for FF RNA-seq data. Users can easily upload a raw RNA-seq count matrix and select one of the seven normalization methods to produce a downloadable normalized expression matrix for any downstream analysis. The R package is available at https://github.com/S-YIN/RSEQNORM. The web-based tool, RSeqNorm is available at http://lce.biohpc. swmed.edu/rseqnorm with no restriction to use or redistribute.
Volume‐selective determination of the spin‐lattice relaxation time in the rotating frame, T1ρ, and T1ρ, imaging

A method for the volume‐and resonance line‐selective determination of the longitudinal relaxation time in the rotating frame, T1ρ, is described. The spin‐lock pulse intrinsic to the T1ρ sequence simultaneously replaces the first slice‐selective pulse of the VOSY method for localized spectroscopy. This is a further parameter suitable for the local characterization of tissue. On the same basis, T1ρ, can be used as a new contrast parameter for biomedical imaging purposes. An appropriate pulse sequence for T1ρ imaging is presented. Test experiments which promise some striking advantages compared with conventional magnetic resonance imaging are reported. © 1989 Academic Press, Inc.
Manipulation of Capillary Force by Electrowetting for Micromanipulation

The objective of this paper is to study the utility of capillary forces for micromanipulation. Due to the scaling effect adhesion forces like capillary force and surface tension force are prominent in the micro scale. Control and proper exploitation of these adhesion forces are an important issue for a design of a capillary gripper prototype. In this paper a novel method to control the capillary force by using electrowetting is proposed. Electrowetting is a process by which contact angle of surface is changed by application of electrical energy. Contact angle change facilitates the control of the capillary force and surface tension forces. A Numerical study of formation of the liquid bridge with volume constraint is presented and the feasibility of the micromanipulation scheme is discussed.
Are HFOs in the Intra-operative ECoG Related to Hippocampal Sclerosis, Volume and IQ?

Temporal lobe epilepsy (TLE) is the most common form of refractory focal epilepsy and is often associated with hippocampal sclerosis (HS) and cognitive disturbances. Over the last decade, high frequency oscillations (HFOs) in the intraoperative electrocorticography (ioECoG) have been proposed to be biomarkers for the delineation of epileptic tissue but hippocampal ripples have also been associated with memory consolidation. Healthy hippocampi can show prolonged ripple activity in stereo- EEG. We aimed to identify how the HFO rates [ripples (80–250 Hz, fast ripples (250–500 Hz); prolonged ripples (80–250 Hz, 200–500 ms)] in the pre-resection ioECoG over subtemporal area (hippocampus) and lateral temporal neocortex relate to presence of hippocampal sclerosis, the hippocampal volume quantified on MRI and the severity of cognitive impairment in TLE patients. Volumetric measurement of hippocampal subregions was performed in 47 patients with TLE, who underwent ioECoG. Ripples, prolonged ripples, and fast ripples were visually marked and rates of HFOs were calculated. The intellectual quotient (IQ) before resection was determined. There was a trend toward higher rates of ripples and fast ripples in subtemporal electrodes vs. the lateral neocortex (ripples: 2.1 vs. 1.3/min; fast ripples: 0.9 vs. 0.2/min). Patients with HS showed higher rates of subtemporal fast ripples than other patients (Z = −2.51, p = 0.012). Prolonged ripples were only found in the lateral temporal neocortex. The normalized ratio (smallest/largest) of hippocampal volume was correlated to pre-resection IQ (r = 0.45, p = 0.015). There was no correlation between HFO rates and hippocampal volumes or HFO rates and IQ. To conclude, intra-operative fast ripples were a marker for HS, but ripples and fast ripples were not linearly correlated with either the amount of hippocampal atrophy, nor for pre-surgical IQ.
Trans Fat Free by 2023—A Building Block of the COVID-19 Response

COVID-19 has brought to center stage the most important health issue of our era, largely ignored by policymakers and the public to date: non-communicable diseases (NCDs), the cause of 71% of deaths per year worldwide. People living with NCDs, and particularly those living with cardiovascular disease (CVD), are at higher risk of severe symptoms and death from COVID-19. As a result, the urgent need for policy measures to protect cardiovascular health is more apparent than ever. One example of “low-hanging fruit” in the prevention of CVD is the elimination of industrially-produced trans fatty acids (iTFA). Their removal from the global food supply could prevent up to 17 million deaths by 2040 and would be the first time an NCD risk factor has been eliminated.
Isolation and Identification of Antibacterial Bioactive Compounds From Bacillus megaterium L2

Bacterial metabolites exhibit a variety of biologically active compounds including antibacterial and antifungal activities. It is well known that Bacillus is considered to be a promising source of bioactive secondary metabolites. Most plant pathogens have an incredible ability to mutate and acquire resistance, causing major economic losses in the agricultural field. Therefore, it is necessary to use the natural antibacterial compounds in microbes to control plant pathogens. This study was conducted to investigate the bio-active compounds of Bacillus megaterium L2. According to the activity guidance of Agrobacterium tumefaciens T-37, Erwinia carotovora EC-1 and Ralstonia solanacearum RS-2, five monomeric compounds, including erucamide (1), behenic acid (2), palmitic acid (3), phenylacetic acid (4), and β-sitosterol (5), were fractionated and purified from the crude ethyl acetate extract of B. megaterium. To our knowledge, all compounds were isolated from the bacterium for the first time. To understand the antimicrobial activity of these compounds, and their minimum inhibitory concentrations (MICs) (range: 0.98∼500 μg/mL) were determined by the broth microdilution method. For the three tested pathogens, palmitic acid exhibited almost no antibacterial activity (>500 μg/mL), while erucamide had moderate antibacterial activity (MIC = 500 μg/mL). Behenic acid showed MICs of 250 μg/mL against T-37 and RS-2 strains with an antibacterial activity. β-sitosterol showed significant antimicrobial activity against RS-2. β-sitosterol showed remarkable antimicrobial activity against RS-2 with an MIC of 15.6 μg/mL. In addition, with the antimicrobial activity, against T-37 (62.5 μg/mL) and against EC-1 (125 μg/mL) and RS-2 (15.6 μg/mL) strains notably, phenylacetic acid may be interesting for the prevention and control of phytopathogenic bacteria. Our findings suggest that isolated compounds such as behenic acid, β-sitosterol, and phenylacetic acid may be promising candidates for natural antimicrobial agents.
Overcoming Chemoresistance via Extracellular Vesicle Inhibition

With the ever-growing number of cancer deaths worldwide, researchers have been working hard to identify the key reasons behind the failure of cancer therapies so the efficacy of those therapies may be improved. Based on extensive research activities and observations done by researchers, chemoresistance has been identified as a major contributor to the drastic number of deaths among cancer patients. Several factors have been linked to formation of chemoresistance, such as chemotherapy drug efflux, immunosuppression, and epithelial-mesenchymal transition (EMT). Lately, increasing evidence has shed light on the role of extracellular vesicles (EVs) in the regulation of chemoresistance. However, there is limited research into the possibility that inhibiting EV release or uptake in cancer cells may curb chemoresistance, allowing chemotherapy drugs to target cancer cells without restriction. Prominent inhibitors of EV uptake and release in cancer cells have been compiled and contrasted in this review. This is in the hope of sparking greater interest in the field of EV-mediated chemoresistance, as well as to provide an overview of the field for fundamental and clinical research communities, particularly in the field of cancer resistance research. In-depth studies of EV-mediated chemoresistance and EV inhibitors in cancer cells would spur significant improvement in cancer treatments which are currently available.
The Effects of Social Perception on Moral Judgment

When people express a moral judgment, others make inferences about their personality, such as whether they are warm or competent. People may use this interpersonal process to present themselves in a way that is socially acceptable in the current circumstances. Across four studies, we investigated this hypothesis in Chinese culture and showed that college student participants tended to associate others’ deontological moral judgments with warmth and utilitarian moral judgments with competence (Study 1, Mage = 21.1, SD = 2.45; Study 2, Mage = 20.53, SD = 1.87). In addition, participants made more deontological judgments after preparing to be interviewed for a job requiring them to be in a warm social role, and more utilitarian judgments after preparing for a job requiring them to be in a competent social role (Study 3, Mage = 19.5, SD = 1.63). This effect held true in moral dilemmas involving different degrees of hypothetical personal involvement, and appeared to be mediated by the perception of others’ expectations (Study 4, Mage = 19.92, SD = 1.97). The results suggest an important role for social cognition as an influence on moral judgments in Chinese culture.
Injectable Poly(ethylene glycol) Dimethacrylate-based Hydrogels with Hydroxyapatite

Injectable hydrogels are attractive materials for tissue engineering as they provide fast reaction rates, low heat release, and biocompatibility for cell proliferation and permanent interface with surrounding tissue. A series of injectable poly(ethylene glycol) dimethacrylate (PEGDMA) hydrogels with four different weight fractions of hydroxyapatite (HA) particles were prepared and thermal and mechanical properties evaluated. The cytocompatibility was assessed by examining the viability and morphology of human mesenchymal stem cells (hMSCs) seeded on the hydrogels. The in situ crosslink process displayed a vast decrease in the maximal temperature and an increase in the maximal temperature time. Cytocompatibility evaluation by MTT assay, scanning electron microscopy (SEM) and laser scanning confocal microscopy (LSCM) showed that the cells on the composite hydrogels possessed better viability and adherence than the hydrogels without HA. The results indicated that composite hydrogels have potential as injectable materials for tissue engineering application.
Influence of Hypoxia on the Epithelial-Pathogen Interactions in the Lung: Implications for Respiratory Disease

Under normal physiological conditions, the lung remains an oxygen rich environment. However, prominent regions of hypoxia are a common feature of infected and inflamed tissues and many chronic inflammatory respiratory diseases are associated with mucosal and systemic hypoxia. The airway epithelium represents a key interface with the external environment and is the first line of defense against potentially harmful agents including respiratory pathogens. The protective arsenal of the airway epithelium is provided in the form of physical barriers, and the production of an array of antimicrobial host defense molecules, proinflammatory cytokines and chemokines, in response to activation by receptors. Dysregulation of the airway epithelial innate immune response is associated with a compromised immunity and chronic inflammation of the lung. An increasing body of evidence indicates a distinct role for hypoxia in the dysfunction of the airway epithelium and in the responses of both innate immunity and of respiratory pathogens. Here we review the current evidence around the role of tissue hypoxia in modulating the host-pathogen interaction at the airway epithelium. Furthermore, we highlight the work needed to delineate the role of tissue hypoxia in the pathophysiology of chronic inflammatory lung diseases such as asthma, cystic fibrosis, and chronic obstructive pulmonary disease in addition to novel respiratory diseases such as COVID-19. Elucidating the molecular mechanisms underlying the epithelial-pathogen interactions in the setting of hypoxia will enable better understanding of persistent infections and complex disease processes in chronic inflammatory lung diseases and may aid the identification of novel therapeutic targets and strategies.
Investigation of a Novel Deep Learning-Based Computed Tomography Perfusion Mapping Framework for Functional Lung Avoidance Radiotherapy

Functional lung avoidance radiation therapy aims to minimize dose delivery to the normal lung tissue while favoring dose deposition in the defective lung tissue based on the regional function information. However, the clinical acquisition of pulmonary functional images is resource-demanding, inconvenient, and technically challenging. This study aims to investigate the deep learning-based lung functional image synthesis from the CT domain. Forty-two pulmonary macro-aggregated albumin SPECT/CT perfusion scans were retrospectively collected from the hospital. A deep learning-based framework (including image preparation, image processing, and proposed convolutional neural network) was adopted to extract features from 3D CT images and synthesize perfusion as estimations of regional lung function. Ablation experiments were performed to assess the effects of each framework component by removing each element of the framework and analyzing the testing performances. Major results showed that the removal of the CT contrast enhancement component in the image processing resulted in the largest drop in framework performance, compared to the optimal performance (~12%). In the CNN part, all the three components (residual module, ROI attention, and skip attention) were approximately equally important to the framework performance; removing one of them resulted in a 3–5% decline in performance. The proposed CNN improved ~4% overall performance and ~350% computational efficiency, compared to the U-Net model. The deep convolutional neural network, in conjunction with image processing for feature enhancement, is capable of feature extraction from CT images for pulmonary perfusion synthesis. In the proposed framework, image processing, especially CT contrast enhancement, plays a crucial role in the perfusion synthesis. This CTPM framework provides insights for relevant research studies in the future and enables other researchers to leverage for the development of optimized CNN models for functional lung avoidance radiation therapy.
Glomerular Endothelial Cell Crosstalk With Podocytes in Diabetic Kidney Disease

Diabetes is the main cause of renal failure worldwide. Complications of the kidney micro-and macro-circulation are common in diabetic patients, leading to proteinuria and can progress to end-stage renal disease. Across the complex interplays aggravating diabetes kidney disease progression, lesions of the glomerular filtration barrier appear crucial. Among its components, glomerular endothelial cells are known to be central safeguards of plasma filtration. An array of evidence has recently pinpointed its intricate relations with podocytes, highly specialized pericytes surrounding glomerular capillaries. During diabetic nephropathy, endothelial cells and podocytes are stressed and damaged. Besides, each can communicate with the other, directly affecting the progression of glomerular injury. Here, we review recent studies showing how in vitro and in vivo studies help to understand pathological endothelial cells-podocytes crosstalk in diabetic kidney disease.