Miracle-dz/UniFAR-FTUs huggingface dataset:
Major Factors Influencing the Size Distribution Analysis of Cellulose Nanocrystals Imaged in Transmission Electron Microscopy

Size distributions of cellulose nanocrystals (CNCs), extracted from softwood pulp via strong sulfuric acid hydrolysis, exhibit large variability when analyzed from transmission electron microscopy (TEM) images. In this article, the causes of this variability are studied and discussed. In order to obtain results comparable with those reported, a reference material of CNCs (CNCD-1) was used to evaluate size distribution. CNC TEM specimens were prepared as-stained and dried with a rapid-flushing staining method or hydrated and embedded in vitreous ice with the plunge-freezing method. Several sets of bright-field TEM (BF-TEM), annular dark-field scanning TEM (ADF-STEM) and cryogenic-TEM (cryo-TEM) images were acquired for size distribution analysis to study the contributing factors. The rapid-flushing staining method was found to be the most effective for contrast enhancement of CNCs, not only revealing the helical structure of single CNCs but also resolving the laterally jointed CNCs. During TEM specimen preparation, CNCs were fractionated on TEM grids driven by the coffee-ring effect, as observed from contrast variation of CNCs with a stain-depth gradient. From the edge to the center of the TEM grids, the width of CNCs increases, while the aspect ratio (length to width) decreases. This fractionated dispersion of CNCs suggests that images taken near the center of a droplet would give a larger mean width. In addition to particle fractionation driven by the coffee-ring effect, the arrangement and orientation of CNC particles on the substrate significantly affect the size measurement when CNC aggregation cannot be resolved in images. The coexistence of asymmetric cross-section CNC particles introduces a large variation in size measurement, as TEM images of CNCs are mixed projections of the width and height of particles. As a demonstration of how this contributes to inflated size measurement, twisted CNC particles, rectangular cross-section particles and end-to-end jointed CNCs were revealed in reconstructed three-dimensional (3D) micrographs by electron tomography (ET).
Liquid-Crystal Ordering and Microphase Separation in the Lamellar Phase of Rod-Coil-Rod Triblock Copolymers. Molecular Theory and Computer Simulations

A molecular model of the orientationally ordered lamellar phase exhibited by asymmetric rod-coil-rod triblock copolymers has been developed using the density-functional approach and generalizing the molecular-statistical theory of rod-coil diblock copolymers. An approximate expression for the free energy of the lamellar phase has been obtained in terms of the direct correlation functions of the system, the Flory-Huggins parameter and the Maier-Saupe orientational interaction potential between rods. A detailed derivation of several rod-rod and rod-coil density-density correlation functions required to evaluate the free energy is presented. The orientational and translational order parameters of rod and coil segments depending on the temperature and triblock asymmetry have been calculated numerically by direct minimization of the free energy. Different structure and ordering of the lamellar phase at high and low values of the triblock asymmetry is revealed and analyzed in detail. Asymmetric rod-coil-rod triblock copolymers have been simulated using the method of dissipative particle dynamics in the broad range of the Flory-Huggins parameter and for several values of the triblock asymmetry. It has been found that the lamellar phase appears to be the most stable one at strong segregation. The density distribution of the coil segments and the segments of the two different rods have been determined for different values of the segregation strength. The simulations confirm the existence of a weakly ordered lamellar phase predicted by the density-functional theory, in which the short rods separate from the long ones and are characterized by weak positional ordering.
Unambiguous Stereochemical Assignment of Cyclo(Phe-Pro), Cyclo(Leu-Pro), and Cyclo(Val-Pro) by Electronic Circular Dichroic Spectroscopy

2,5-diketopiperazines (DKPs) are cyclic dipeptides ubiquitously found in nature. In particular, cyclo(Phe-Pro), cyclo(Leu-Pro), and cyclo(Val-Pro) are frequently detected in many microbial cultures. Each of these DKPs has four possible stereoisomers due to the presence of two chirality centers. However, absolute configurations of natural DKPs are often ambiguous due to the lack of a simple, sensitive, and reproducible method for stereochemical assignment. This is an important problem because stereochemistry is a key determinant of biological activity. Here, we report a synthetic DKP library containing all stereoisomers of cyclo(Phe-Pro), cyclo(Leu-Pro), and cyclo(Val-Pro). The library was subjected to spectroscopic characterization using mass spectrometry, NMR, and electronic circular dichroism (ECD). It turned out that ECD can clearly differentiate DKP stereoisomers. Thus, our ECD dataset can serve as a reference for unambiguous stereochemical assignment of cyclo(Phe-Pro), cyclo(Leu-Pro), and cyclo(Val-Pro) samples from natural sources. The DKP library was also subjected to a biological screening using assays for E. coli growth and biofilm formation, which revealed distinct biological effects of cyclo(D-Phe-L-Pro).
SAR Image Change Detection via Multiple-Window Processing with Structural Similarity

In this paper, a synthetic aperture radar (SAR) change detection approach is proposed based on a structural similarity index measure (SSIM) and multiple-window processing (MWP). The proposed scheme is performed in two steps: (1) generation of a coherence image based on MWP associated with SSIM and (2) gamma correction (GC) filtering. The proposed method is capable of providing a high-quality coherence image because the MWP operation based on SSIM has high sensitivity to the similarity measure for intensity between two SAR images. By finding an optimum value of order of GC, the proposed method can considerably reduce the effect of speckle noise on the coherence image, while retaining nearly all the information related to changed region involved in the change detection map. Several experimental results are presented to demonstrate the effectiveness of the proposed scheme.
Construction of Two Stable Co(II)-Based Hydrogen-Bonded Organic Frameworks as a Luminescent Probe for Recognition of Fe3+ and Cr2O72− in H2O

A pair of cobalt(II)-based hydrogen-bonded organic frameworks (HOFs), [Co(pca)2(bmimb)]n (1) and [Co2(pca)4(bimb)2] (2), where Hpca = p-chlorobenzoic acid, bmimb = 1,3-bis((2-methylimidazol-1-yl)methyl)benzene, and bimb = 1,4-bis(imidazol-1-ylmethyl)benzene were hydrothermally synthesized and characterized through infrared spectroscopy (IR), elemental and thermal analysis (EA), power X-ray diffraction (PXRD), and single-crystal X-ray diffraction (SCXRD) analyses. X-ray diffraction structural analysis revealed that 1 has a one-dimensional (1D) infinite chain network through the deprotonated pca− monodentate chelation and with a μ2-bmimb bridge Co(II) atom, and 2 is a binuclear Co(II) complex construction with a pair of symmetry-related pca− and bimb ligands. For both 1 and 2, each cobalt atom has four coordinated twisted tetrahedral configurations with a N2O2 donor set. Then, 1 and 2 are further extended into three-dimensional (3D) or two-dimensional (2D) hydrogen-bonded organic frameworks through C–H···Cl interactions. Topologically, HOFs 1 and 2 can be simplified as a 4-connected qtz topology with a Schläfli symbol {64·82} and a 4-connected sql topology with a Schläfli symbol {44·62}, respectively. The fluorescent sensing application of 1 was investigated; 1 exhibits high sensitivity recognition for Fe3+ (Ksv: 10970 M−1 and detection limit: 19 μM) and Cr2O72− (Ksv: 12960 M−1 and detection limit: 20 μM). This work provides a feasible detection platform of HOFs for highly sensitive discrimination of Fe3+ and Cr2O72− in aqueous media.
Initial Work on Sex-Specific Growth Curve Guidelines for Forensically Important Blow Flies Using Chrysomya megacephala (Diptera: Calliphoridae) Entire Age Cohorts

Abstract Sex is a factor influencing development in many insect species, but is not widely studied in forensically important blow flies. If sex influences blow fly development, knowing the sex of a larva from a corpse can increase precision in estimates of that larva's age. The improved prediction of larval age will make estimates of time since death using entomological evidence better. Larvae lack sexually dimorphic morphological characteristics, so sex is not immediately known visually. To generate sexually dimorphic reference growth curves, a subsample must be large enough to ensure enough males and females are present for comparison. Using two entire age Chrysomya megacephala (Fabricius) cohorts, we evaluated the minimum sample number needed to have enough individuals of both sexes for comparison using 95% prediction intervals. Through a simulation of three trials of 1000 random replicates, we determined that a sample size of 19 would prevent any instance of a comparison not occurring because of insufficient sampling from one sex. As the current method for molecular sex determination can be expensive, we also compared how the results of various subsampling percentages compare those of the entire age cohorts. We found that subsampling at least 50% of an entire cohort leads to almost identical results in comparison to the entire age cohort. Together, these findings will help establish guidelines for generating sex-specific reference growth curves. A uniform approach to generating these sex-specific growth curves will lead to more consistency in age estimates made from them.
Signaling by the inhibitory receptor CD200R is rewired by type I interferon

Description Type I interferon switches the receptor CD200R from inhibiting to potentiating inflammatory responses in immune cells. Interferon turns the tables The inhibitory immunoreceptor CD200R dampens the TLR-dependent production of inflammatory cytokines by myeloid cells. Ligand-dependent CD200R signaling depends on the recruitment of an adaptor and the protein p120-RasGAP to its cytoplasmic tail. van der Vlist et al. found that treatment of human PBMCs with IFN-α resulted in the cleavage of p120-GAP, thus dysregulating CD200R signaling. Compared to PBMCs from healthy donors, those from patients with systemic lupus erythematosus, a disease characterized by high serum concentrations of IFN-α, had increased cleavage of p120-RasGAP. Furthermore, CD200R engagement enhanced, rather than reduced, the TLR-stimulated production of inflammatory cytokines. These data suggest that the type I IFN–dependent rewiring of CD200R signaling may underlie the inflammation seen in SLE patients. CD200 receptor 1 (CD200R) is an inhibitory immunoreceptor that suppresses Toll-like receptor (TLR)–induced cytokine production through the adaptor protein Dok2 and the GTPase activating protein (GAP) p120-RasGAP, which can be cleaved during mild cellular stress. We found that in the presence of cleaved p120-RasGAP, CD200R lost its capacity to inhibit phosphorylation of ribosomal S6 protein (rpS6), suggesting the reduced activity of mammalian target of rapamycin complex 1 (mTORC1). Furthermore, treatment of human peripheral blood mononuclear cells (PBMC) with interferon-α (IFN-α) resulted in increased amounts of cleaved p120-RasGAP. Upon pretreatment of cells with increasing concentrations of IFN-α, CD200R switched from inhibiting to potentiating the TLR7- and TLR8-induced expression of the gene encoding IFN-γ, a cytokine that is important for innate and adaptive immunity and is implicated in systemic lupus erythematosus (SLE) pathogenesis. PBMC from patients with SLE, a prototypic type I IFN disease, had an increased abundance of cleaved p120-RasGAP compared to that in cells from healthy controls. In a subset of SLE patients, CD200R stopped functioning as an inhibitory receptor or potentiated TLR-induced IFNG mRNA expression. Thus, our data suggest that type I IFN rewires CD200R signaling to be proinflammatory, which could contribute to the perpetuation of inflammation in patients with SLE.
Integrated Network Pharmacology Analysis and In Vitro Validation Revealed the Potential Active Components and Underlying Mechanistic Pathways of Herba Patriniae in Colorectal Cancer

Herba Patriniae (HP) are medicinal plants commonly used in colorectal cancer (CRC) patients. In this study, network pharmacology was used to predict the active components and key signaling pathways of HP in CRC. Patrinia heterophylla, one type of HP, was chosen for validation of the network pharmacology analysis. The phytochemical profile of Patrinia heterophylla water extract (PHW) was determined by UHPLC-MS. MTT, RT-PCR, and Western blot assays were performed to evaluate the bioactivities of PHW in colon cancer cells. Results showed that 15 potentially active components of HP interacted with 28 putative targets of CRC in the compound–target network, of which asperglaucide had the highest degree. Furthermore, the ErbB signaling pathway was identified as the pathway mediated by HP with the most potential against CRC. Both RT-PCR and Western blot results showed that PHW significantly downregulated the mRNA and protein levels of EGFR, PI3K, and AKT in HCT116 cells. Asperglaucide, present in PHW, exhibited an anti-migratory effect in HCT116 cells, suggesting that it could be an active component of PHW in CRC treatment. In conclusion, this study has provided the first scientific evidence to support the use of PHW in CRC and paved the way for further research into the underlying mechanisms of PHW against CRC.
Cannabidiol Attenuates MK-801-Induced Cognitive Symptoms of Schizophrenia in the Passive Avoidance Test in Mice

Schizophrenia is a chronic mental disorder that disturbs feelings and behavior. The symptoms of schizophrenia fall into three categories: positive, negative, and cognitive. Cognitive symptoms are characterized by memory loss or attentional deficits, and are especially difficult to treat. Thus, there is intense research into the development of new treatments for schizophrenia-related responses. One of the possible strategies is connected with cannabidiol (CBD), a cannabinoid compound. This research focuses on the role of CBD in different stages of memory (acquisition, consolidation, retrieval) connected with fear conditioning in the passive avoidance (PA) learning task in mice, as well as in the memory impairment typical of cognitive symptoms of schizophrenia. Memory impairment was provoked by an acute injection of the N-methyl-D-aspartate (NMDA) receptor antagonist MK-801 (animal model of schizophrenia). Our results revealed that an acute injection of CBD (30 mg/kg; intraperitoneally (i.p.) improved all phases of long-term fear memory in the PA test in mice. Moreover, the acute injection of non-effective doses of CBD (1 or 5 mg/kg; i.p.) attenuated the memory impairment provoked by MK-801 (0.6 mg/kg; i.p.) in the consolidation and retrieval stages of fear memory, but not in the acquisition of memory. The present findings confirm that CBD has a positive influence on memory and learning processes in mice, and reveals that this cannabinoid compound is able to attenuate memory impairment connected with hypofunction of glutamate transmission in a murine model of schizophrenia.
Hydrophobic ion-pairing assembled liposomal Rhein with efficient loading for acute pancreatitis treatment

Abstract Aim The present study aimed to develop liposomal Rhein by employing a hydrophobic ion-pairing technique (HIP) for improved pancreatitis therapy. Methods F127 modified liposomal Rhein (F127-RPC-Lip) was prepared using a two-step process consisting of complexation first, followed by a film-ultrasonic dispersion step. The drug-phospholipid interaction was characterised by FT-IR and P-XRD. Particle size and morphology were investigated using DLS and TEM, respectively. Biodistribution and therapeutic efficacy of F127-RPC-Lip were evaluated in a rat model of acute pancreatitis. Results F127-RPC-Lip achieved efficient drug encapsulation after complexation with lipids through non-covalent interactions and had an average hydrodynamic diameter of about 141 nm. F127-RPC-Lip demonstrated slower drug release (55.90 ± 3.60%, w/w) than Rhein solution (90.27 ± 5.11%) within 24 h. Compared with Rhein, F127-RPC-Lip exhibited prolonged systemic circulation time, superior drug distribution, and attenuated injury in the pancreas of rats post-injection. Conclusions HIP-assembled liposomes are a promising strategy for Rhein in treating pancreatitis.
Effective Connectivity for Decoding Electroencephalographic Motor Imagery Using a Probabilistic Neural Network

Motor imagery (MI)-based brain–computer interfaces have gained much attention in the last few years. They provide the ability to control external devices, such as prosthetic arms and wheelchairs, by using brain activities. Several researchers have reported the inter-communication of multiple brain regions during motor tasks, thus making it difficult to isolate one or two brain regions in which motor activities take place. Therefore, a deeper understanding of the brain’s neural patterns is important for BCI in order to provide more useful and insightful features. Thus, brain connectivity provides a promising approach to solving the stated shortcomings by considering inter-channel/region relationships during motor imagination. This study used effective connectivity in the brain in terms of the partial directed coherence (PDC) and directed transfer function (DTF) as intensively unconventional feature sets for motor imagery (MI) classification. MANOVA-based analysis was performed to identify statistically significant connectivity pairs. Furthermore, the study sought to predict MI patterns by using four classification algorithms—an SVM, KNN, decision tree, and probabilistic neural network. The study provides a comparative analysis of all of the classification methods using two-class MI data extracted from the PhysioNet EEG database. The proposed techniques based on a probabilistic neural network (PNN) as a classifier and PDC as a feature set outperformed the other classification and feature extraction techniques with a superior classification accuracy and a lower error rate. The research findings indicate that when the PDC was used as a feature set, the PNN attained the greatest overall average accuracy of 98.65%, whereas the same classifier was used to attain the greatest accuracy of 82.81% with the DTF. This study validates the activation of multiple brain regions during a motor task by achieving better classification outcomes through brain connectivity as compared to conventional features. Since the PDC outperformed the DTF as a feature set with its superior classification accuracy and low error rate, it has great potential for application in MI-based brain–computer interfaces.
Sex comparisons in neuropsychological functioning and reported symptoms following a sports-related concussion among high school athletes

Abstract The aim of this study was to compare the neuropsychological functioning and symptoms of female and male high school athletes following a single concussion during the school year. The baseline test scores of the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) of 309 concussed athletes (169 females, 221 males) in varied sports were obtained. After a sport-related concussion, the athletes were re-administered the ImPACT, on the average, 7.25 days after the injury. MANCOVA compared the ImPACT baseline scores, post-concussion scores, and baseline-to-post-concussion changes of the female and male athletes, with p set at 0.01. The only significant sex comparison found females performing better on baseline visual motor speed (p < 0.001). Otherwise, no sex differences were found in baseline test scores, post-concussion scores, and baseline-to-post-concussion changes. The findings tentatively suggest that there are insignificant sex differences in the consequences of sport-related concussion after a week post-injury. Future studies on sex comparisons after a concussion are needed focusing on the acute and sub-acute phases of the recovery period.
A Safe Collaborative Chatbot for Smart Home Assistants

Smart home assistants, which enable users to control home appliances and can be used for holding entertaining conversations, have become an inseparable part of many people’s homes. Recently, there have been many attempts to allow end-users to teach a home assistant new commands, responses, and rules, which can then be shared with a larger community. However, allowing end-users to teach an agent new responses, which are shared with a large community, opens the gate to malicious users, who can teach the agent inappropriate responses in order to promote their own business, products, or political views. In this paper, we present a platform that enables users to collaboratively teach a smart home assistant (or chatbot) responses using natural language. We present a method of collectively detecting malicious users and using the commands taught by the malicious users to further mitigate activity of future malicious users. We ran an experiment with 192 subjects and show the effectiveness of our platform.
Ultrahigh Sensitivity Mach−Zehnder Interferometer Sensor Based on a Weak One-Dimensional Field Confinement Silica Waveguide

We report a novel Mach−Zehnder interferometer (MZI) sensor that utilizes a weak one-dimensional field confinement silica waveguide (WCSW). The WCSW has a large horizontal and vertical aspect ratio and low refractive index difference, which features easy preparation and a large evanescent field for achieving high waveguide sensitivity. We experimentally achieved WCSW ultrahigh waveguide sensitivity of 0.94, MZI sensitivity of 44,364 π/RIU and a low limit of detection (LOD) of 6.1 × 10−7 RIU.
Cross-validating the Dot Counting Test Among an Adult ADHD Clinical Sample and Analyzing the Effect of ADHD Subtype and Comorbid Psychopathology

This study cross-validated the dot counting test (DCT) as a performance validity test (PVT) in an adult attention-deficit/hyperactivity disorder (ADHD) clinical population and examined the effect of ADHD subtype and psychiatric comorbidity on accuracy for detecting invalidity. DCT performance was assessed among 210 consecutive adult ADHD referrals who underwent neuropsychological evaluation and were classified into valid (n = 175) or invalid (n = 35) groups based on seven independent criterion PVTs. The invalid group had significantly worse DCT performance than the valid group using both the standard and unrounded scoring procedure ( η p 2 = . 28 ). Classification accuracy was excellent, with 54.3% sensitivity/92% specificity at optimal cut-scores of ≥14 (rounded) and ≥13.38 (unrounded). Nonsignificant DCT performance differences emerged based on ADHD subtype or the presence/absence of comorbid psychopathology. The DCT functions well as a nonmemory-based PVT in an ethnoracially diverse ADHD population, supporting its clinical utility for detecting invalid neurocognitive performance during ADHD evaluations.