Miracle-dz/UniFAR-FTUs huggingface dataset:
Two weeks smoking cessation reverses cigarette smoke-induced skeletal muscle atrophy and mitochondrial dysfunction in mice.

INTRODUCTION Apart from its adverse effects on the respiratory system, cigarette smoking also induces skeletal muscle atrophy and dysfunction. Whether short-term smoking cessation can restore muscle mass and function is unknown. We therefore studied the impact of 1- and 2-weeks smoking cessation on skeletal muscles in a mouse model. METHODS Male mice were divided into 4 groups: Air-exposed (14 weeks); cigarette smoke (CS)-exposed (14 weeks); CS-exposed (13 weeks) followed by 1-week cessation; CS-exposed (12 weeks) followed by 2 weeks cessation to examine exercise capacity, physical activity levels, body composition, muscle function, capillarization, mitochondrial function and protein expression in the soleus, plantaris and diaphragm muscles. RESULTS CS-induced loss of body and muscle mass was significantly improved within 1 week of cessation due to increased lean and fat mass. Mitochondrial respiration and protein levels of the respiratory complexes in the soleus were lower in CS-exposed mice, but similar to control values after 2 weeks of cessation. Exposing isolated soleus muscles to CS extracts reduced mitochondrial respiration that was reversed after removing the extract. While physical activity was reduced in all groups, exercise capacity, limb muscle force, fatigue resistance, fiber size and capillarization and diaphragm cytoplasmic HIF-1α were unaltered by CS-exposure. However, CS-induced diaphragm atrophy and increased capillary density was not seen after 2 weeks of smoking cessation. CONCLUSION In male mice, two weeks smoking cessation reversed smoking-induced mitochondrial dysfunction, limb muscle mass loss and diaphragm muscle atrophy, highlighting immediate benefits of cessation on skeletal muscles.
De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Significance Here we provide the most diverse human de novo mutation call set to date, and use it to quantify the genome-wide relationship between local mutation rate and population-level rare genetic variation. While we demonstrate that the human single-nucleotide mutation rate is similar across numerous human ancestries and populations, we also discovered a reduced mutation rate in the Amish founder population, which shows that mutation rates can shift rapidly. Finally, we find that variation in mutation rates is not heritable, which suggests that the environment may influence mutation rates more significantly than previously realized. De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.
Far-field midinfrared superresolution imaging and spectroscopy of single high aspect ratio gold nanowires

Significance Traditional optical microscopy methods are limited by diffraction. This makes it hard to image and study nanostructures in the midinfrared, a relatively unexplored spectral region of chemical significance. Here we use infrared (IR) photothermal heterodyne imaging (IR-PHI), a far-field superresolution optical technique, to study the Fabry–Pérot resonances of single gold nanowires in the 2,800 to 4,000-cm−1 region. Because the spatial resolution of IR-PHI is on the order of a few hundred nanometers, we are able to directly resolve the structure of the Fabry–Pérot resonances and assign the mode order. This cannot be done with traditional optical measurements. IR absorption spectra recorded using IR-PHI show narrow linewidths, in several cases below the limit imposed by Au’s Drude relaxation parameter. Limited approaches exist for imaging and recording spectra of individual nanostructures in the midinfrared region. Here we use infrared photothermal heterodyne imaging (IR-PHI) to interrogate single, high aspect ratio Au nanowires (NWs). Spectra recorded between 2,800 and 4,000 cm−1 for 2.5–3.9-μm-long NWs reveal a series of resonances due to the Fabry–Pérot modes of the NWs. Crucially, IR-PHI images show structure that reflects the spatial distribution of the NW absorption, and allow the resonances to be assigned to the m = 3 and m = 4 Fabry–Pérot modes. This far-field optical measurement has been used to image the mode structure of plasmon resonances in metal nanostructures, and is made possible by the superresolution capabilities of IR-PHI. The linewidths in the NW spectra range from 35 to 75 meV and, in several cases, are significantly below the limiting values predicted by the bulk Au Drude damping parameter. These linewidths imply long dephasing times, and are attributed to reduction in both radiation damping and resistive heating effects in the NWs. Compared to previous imaging studies of NW Fabry–Pérot modes using electron microscopy or near-field optical scanning techniques, IR-PHI experiments are performed under ambient conditions, enabling detailed studies of how the environment affects mid-IR plasmons.
Genome-Wide Identification and Characterization of the NAC Transcription Factor Family in Musa Acuminata and Expression Analysis during Fruit Ripening

Banana (Musa acuminata, AAA group) is a representative climacteric fruit with essential nutrients and pleasant flavors. Control of its ripening determines both the fruit quality and the shelf life. NAC (NAM, ATAF, CUC2) proteins, as one of the largest superfamilies of transcription factors, play crucial roles in various functions, especially developmental processes. Thus, it is important to conduct a comprehensive identification and characterization of the NAC transcription factor family at the genomic level in M. acuminata. In this article, a total of 181 banana NAC genes were identified. Phylogenetic analysis indicated that NAC genes in M. acuminata, Arabidopsis, and rice were clustered into 18 groups (S1–S18), and MCScanX analysis disclosed that the evolution of MaNAC genes was promoted by segmental duplication events. Expression patterns of NAC genes during banana fruit ripening induced by ethylene were investigated using RNA-Seq data, and 10 MaNAC genes were identified as related to fruit ripening. A subcellular localization assay of selected MaNACs revealed that they were all localized to the nucleus. These results lay a good foundation for the investigation of NAC genes in banana toward the biological functions and evolution.
Poly(L-Glutamic Acid)-Based Brush Copolymers: Fabrication, Self-assembly, and Evaluation as Efficient Nanocarriers for Cationic Protein Drug Delivery

Protein drugs were considered to be the first choice to treat many human diseases, but their clinical application was usually limited by their short half-life and lack of validated targeted therapy. Here, a series of folate-functionalized poly(ethylene glycol)-b-(poly(2-aminoethyl-L-glutamate)-g-poly(L-glutamic acid))s (FA-PEG-b-(PELG-g-PLGA)s) were designed as tumor-targeted carriers for cationic protein delivery. Compared with traditional copolymers consisting of PEG and linear charged hydrophilic blocks, FA-PEG-b-(PELG-g-PLGA) with brush-like polyelectrolyte segments were beneficial to improving their electrostatic interactions with loading protein molecules, thus increasing drug-loading stability and protecting encapsulated proteins from degradation. The designed polymer brushes could efficiently encapsulate cytochrome C (CytC), a cationic model protein, to form polyion complex (PIC) micelles with an average particle size of approximately 200 nm. An in vitro drug release study showed that the drug-loading stability of the formed PIC micelles was largely improved. The functionalization of the block copolymer carriers with a targeting folate group enhanced the tumor cell growth inhibition and total apoptotic rates induced by CytC. Our results shed light on the unique advantages of brush-like polymer carriers in delivering cationic proteins, and the poly(L-glutamic acid)-based linear-brush diblock copolymers could be applied as a versatile delivery platform for molecular targeting in cancer therapy.
New Records of Bark and Ambrosia Beetles (Coleoptera: Scolytinae) from Cuba with Description of a New Species

Abstract We present a reassessment of the diversity of bark and ambrosia beetles in Cuba. For the first time in decades, an official Cuban-American binational collaboration allowed us to re-visit all known entomology collections in Cuba, and collect in the field. There are at least 94 species of scolytine beetles in Cuba. We report a new species, Xylosandrus aurinegro Gomez & Hulcr (Coleoptera: Curculionidae), and 7 new species records, including the first genus record for Dryocoetoides Hopkins and Tricolus Blandford (both Coleoptera: Curculionidae) for the island. In terms of species with potential concern to the USA, we corroborate a subspecies of Ips calligraphus Wood & Bright (Coleoptera: Curculionidae) that acts as a pine pest in Cuba and is not yet present in North America.
Identifying spinal afferent (sensory) nerve endings that innervate the marrow cavity and periosteum using anterograde tracing

While sensory and sympathetic neurons are known to innervate bone, previous studies have found it difficult to unequivocally identify and characterize only those that are of sensory origin. In this study, we have utilized an in vivo anterograde tracing technique to selectively label spinal afferent (sensory) nerve endings that innervate the periosteum and marrow cavity of murine long bones. Unilateral injections of dextran–biotin (anterograde tracer; 20% in saline, 50–100 nl) were made into L3–L5 dorsal root ganglia. After a 10‐day recovery period to allow sufficient time for selective anterograde transport of the tracer to nerve terminal endings in bone, the periosteum (whole‐mount) and underlying bone were collected, processed to reveal anterograde labeling, and immuno‐labeled with antibodies directed against protein gene product (pan‐neuronal marker; PGP9.5), tyrosine hydroxylase (sympathetic neuron marker; TH), calcitonin gene‐related protein (peptidergic nociceptor marker; CGRP), and/or neurofilament 200 (myelinated axon marker; NF200). Anterograde‐labeled nerve endings were dispersed throughout the periosteum and marrow cavity and could be identified in close apposition to blood vessels and at sites distant from them. The periosteum and the marrow cavity were each innervated by myelinated (NF200+) sensory neurons, and unmyelinated (NF200‑) sensory neurons that were either peptidergic (CGRP+) or nonpeptidergic (CGRP‑). Spinal afferent nerve endings did not express TH, and lacked the cylindrical morphology around blood vessels characteristic of sympathetic innervation. This approach to selective labeling of sensory nerve terminal endings will help to better identify how different sub‐populations of sensory neurons, and their peripheral nerve terminal endings, interact with bone.
Semi-Autonomous Robotic Arm Reaching With Hybrid Gaze–Brain Machine Interface

Recent developments in the non-muscular human–robot interface (HRI) and shared control strategies have shown potential for controlling the assistive robotic arm by people with no residual movement or muscular activity in upper limbs. However, most non-muscular HRIs only produce discrete-valued commands, resulting in non-intuitive and less effective control of the dexterous assistive robotic arm. Furthermore, the user commands and the robot autonomy commands usually switch in the shared control strategies of such applications. This characteristic has been found to yield a reduced sense of agency as well as frustration for the user according to previous user studies. In this study, we firstly propose an intuitive and easy-to-learn-and-use hybrid HRI by combing the Brain–machine interface (BMI) and the gaze-tracking interface. For the proposed hybrid gaze-BMI, the continuous modulation of the movement speed via the motor intention occurs seamlessly and simultaneously to the unconstrained movement direction control with the gaze signals. We then propose a shared control paradigm that always combines user input and the autonomy with the dynamic combination regulation. The proposed hybrid gaze-BMI and shared control paradigm were validated for a robotic arm reaching task performed with healthy subjects. All the users were able to employ the hybrid gaze-BMI for moving the end-effector sequentially to reach the target across the horizontal plane while also avoiding collisions with obstacles. The shared control paradigm maintained as much volitional control as possible, while providing the assistance for the most difficult parts of the task. The presented semi-autonomous robotic system yielded continuous, smooth, and collision-free motion trajectories for the end effector approaching the target. Compared to a system without assistances from robot autonomy, it significantly reduces the rate of failure as well as the time and effort spent by the user to complete the tasks.
A Vision-based Human Action Recognition System for Moving Cameras Through Deep Learning

This study presents a vision-based human action recognition system using a deep learning technique. The system can recognize human actions successfully when the camera of a robot is moving toward the target person from various directions. Therefore, the proposed method is useful for the vision system of indoor mobile robots. The system uses three types of information to recognize human actions, namely, information from color videos, optical flow videos, and depth videos. First, Kinect 2.0 captures color videos and depth videos simultaneously using its RGB camera and depth sensor. Second, the histogram of oriented gradient features is extracted from the color videos, and a support vector machine is used to detect the human region. Based on the detected human region, the frames of the color video are cropped and the corresponding frames of the optical flow video are obtained using the Farnebäck method (https://docs.opencv=.org/3.4/d4/dee/ tutorial_optical_flow.html). The number of frames of these videos is then unified using a frame sampling technique. Subsequently, these three types of videos are input into three modified 3D convolutional neural networks (3D CNNs) separately. The modified 3D CNNs can extract the spatiotemporal features of human actions and recognize them. Finally, these recognition results are integrated to output the final recognition result of human actions. The proposed system can recognize 13 types of human actions, namely, drink (sit), drink (stand), eat (sit), eat (stand), read, sit down, stand up, use a computer, walk (horizontal), walk (straight), play with a phone/tablet, walk away from each other, and walk toward each other. The average human action recognition rate of 369 test human action videos was 96.4%, indicating that the proposed system is robust and efficient.
Vague Gesture Control: Implications for Burns Patients

In the rehabilitation of burns patients, remedial exercises are an important part of maintaining and regaining range-of-motion. To encourage patient rehabilitation and reduce discomfort, this paper presents the preliminary stages of a project which makes use of both vision based sensors and virtual reality technologies to create an immersive environment. The goal of our research is to design and develop effective vague gesture control. Hand gesture detection may lack clarity/resolution or otherwise be vague due to various reasons including patients' difficulty to enact gestures fully due to injuries, interference with the visual detection of gestures due to bandages, and the difficulty that vision based sensors have detecting small details like fingers at range. Extra environmental and situational information can enhance gesture recognition and provide better gestural classification. To achieve this, temporal machine learning is used to develop an application which uses past environmental interactions to help clarify present vague gestures. A gesture recognition system that can handle imperfect gestures in an intuitive way contributes towards naturalistic computer human interactions, in particular for gamified burns rehabilitation systems.
Extracting 4-Attributes Vessel Courses from AIS Data with PQK-Means and Topic Model

AIS (Automatic Identification System) data received from moving vessels over an area of interest can be of very much interest for deriving maritime trajectory patterns. In this paper, a novel approach to extract course patterns from AIS data of vessels is presented. From machine learning and natural language processing principles, a topic model might be used for extracting implicit patterns underlying massive and unstructured collection of incoming data. To apply topic model to AIS data, PQk-means vector quantization to convert AIS data record to code documents is introduced. Then, a topic model is applied to extract course patterns from AIS data. In fact, courses, not only encompasses trajectory locations, but also headings and speeds, are recognized by the proposed algorithm. The performance of PQk-means is evaluated using the relative root mean square error and elapsed time. The potential of the approach is illustrated by a series of experimental results derived from practical AIS data set in a region of North West France.
Multi-Objective Particle Swarm Optimization for ROI based Video Coding

In this paper, we propose a new algorithm for High Efficiency Video Coding(HEVC) based on multi-objective particle swarm optimization (MOPSO) to enhance the visual quality of ROI while ensuring a certain overall quality. According to the R-λ model of detected ROI, the fitness function in MOPSO can be designed as the distortion of ROI and that of the overall frame. The particle consists of ROI's rate and other region's rate. After iterating through the multi-objective particle swarm optimization algorithm, the Pareto front is obtained. Then, the final bit allocation result which are the appropriate bit rate for ROI and non-ROI is selected from this set. Finally, according to the R-λ model, the coding parameters could be determined for coding. The experimental results show that the proposed algorithm improves the visual quality of ROI while guarantees overall visual quality.
The use of Local Binary Pattern (LBP) feature extraction Members of the mud crab genus Scylla

In the member of mud crab, species of Scylla are the most traded seafood commodity in Asia and the culturing practice is already done in most of Asia country a few years ago. The demand for mud crabs has increased rapidly over the last decade, providing great potential for the development of the mud crab aquaculture industry. But, there is still unsolved problem where limitation of knowledge in identification is limited due to similar colours and feature characteristic. Thus, this study proposed an automatic technique that can evaluate and produce the subset of mud crab genus Scylla features by using Local Binary Pattern (LBP) as a feature extraction tool. The main objective of the study is to find the optimal subset of mud crab genus Scylla features from a carapace images dataset. Based on 153 extracted features chosen by LBP features selection methods, the accuracy rates of three classification algorithms were obtained for analysis. The results from the MatLab experiment demonstrated that, the LBP method produced an accuracy under 60% for entire classifier.
Perceived stress and social support influence anxiety symptoms of Chinese family caregivers of community‐dwelling older adults: a cross‐sectional study

Chinese family members always take care of older adults because of obligations stemming from the culture of filial piety and the paucity of a long‐term care system. These caregivers usually perceive high levels of stress that could compromise their psychological health and consequently result in anxiety impairments. This study aimed to assess the anxiety symptoms of Chinese family caregivers of older adults, explore factors associated with these symptoms, and provide theoretical evidence on improving their mental health.
The Emerging Roles of Fox Family Transcription Factors in Chromosome Replication, Organization, and Genome Stability

The forkhead box (Fox) transcription factors (TFs) are widespread from yeast to humans. Their mutations and dysregulation have been linked to a broad spectrum of malignant neoplasias. They are known as critical players in DNA repair, metabolism, cell cycle control, differentiation, and aging. Recent studies, especially those from the simple model eukaryotes, revealed unexpected contributions of Fox TFs in chromosome replication and organization. More importantly, besides functioning as a canonical TF in cell signaling cascades and gene expression, Fox TFs can directly participate in DNA replication and determine the global replication timing program in a transcription-independent mechanism. Yeast Fox TFs preferentially recruit the limiting replication factors to a subset of early origins on chromosome arms. Attributed to their dimerization capability and distinct DNA binding modes, Fkh1 and Fkh2 also promote the origin clustering and assemblage of replication elements (replication factories). They can mediate long-range intrachromosomal and interchromosomal interactions and thus regulate the four-dimensional chromosome organization. The novel aspects of Fox TFs reviewed here expand their roles in maintaining genome integrity and coordinating the multiple essential chromosome events. These will inevitably be translated to our knowledge and new treatment strategies of Fox TF-associated human diseases including cancer.