Miracle-dz/UniFAR-FTUs huggingface dataset:
Building a Functional Salivary Gland for Cell-Based Therapy: More than Secretory Epithelial Acini.

Few treatment options exist for patients experiencing xerostomia due to hyposalivation that occurs as a result of disease or injury to the gland. An opportunity for a permanent solution lies in the field of salivary gland replacement through tissue engineering. Recent success emboldens in the vision of producing a tissue engineered salivary gland composed of differentiated salivary epithelial cells able to differentiate to form functional units that produce and deliver saliva to the oral cavity. This vision is augmented by advances in understanding cellular mechanisms that guide branching morphogenesis and salivary epithelial cell polarization in both acinar and ductal structures. Growth factors and other guidance cues introduced into engineered constructs help to develop a more complex glandular structure that seeks to mimic native salivary gland tissue. This review describes the separate epithelial phenotypes that make up the gland, and describes their relationship with the other cell types such as nerve and vasculature that surround them. The review is organized around the links between the native components that form and contribute to various aspects of salivary gland development, structure and function and how this information can drive design of functional tissue engineered constructs. Additionally, we discuss the attributes of various biomaterials commonly used to drive function and form in engineered constructs. The review also contains a current description of the state-of-the-art of the field, including successes and challenges in creating materials for preclinical testing in animal models. The ability to integrate biomolecular cues in combination with a range of materials opens the door to the design of increasingly complex salivary gland structures, that, once accomplished can lead to breakthroughs in other fields of tissue engineering of epithelial-based exocrine glands or oral tissues.
Crosstalk between Cell Adhesion Complexes in Regulation of Mechanotransduction

Physical forces regulate numerous biological processes during development, physiology, and pathology. Forces between the external environment and intracellular actin cytoskeleton are primarily transmitted through integrin‐containing focal adhesions and cadherin‐containing adherens junctions. Crosstalk between these complexes is well established and modulates the mechanical landscape of the cell. However, integrins and cadherins constitute large families of adhesion receptors and form multiple complexes by interacting with different ligands, adaptor proteins, and cytoskeletal filaments. Recent findings indicate that integrin‐containing hemidesmosomes oppose force transduction and traction force generation by focal adhesions. The cytolinker plectin mediates this crosstalk by coupling intermediate filaments to the actin cytoskeleton. Similarly, cadherins in desmosomes might modulate force generation by adherens junctions. Moreover, mechanotransduction can be influenced by podosomes, clathrin lattices, and tetraspanin‐enriched microdomains. This review discusses mechanotransduction by multiple integrin‐ and cadherin‐based cell adhesion complexes, which together with the associated cytoskeleton form an integrated network that allows cells to sense, process, and respond to their physical environment.
Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best Practices

Artificial intelligence algorithms based on principles of deep learning (DL) have made a large impact on the acquisition, reconstruction, and interpretation of MRI data. Despite the large number of retrospective studies using DL, there are fewer applications of DL in the clinic on a routine basis. To address this large translational gap, we review the recent publications to determine three major use cases that DL can have in MRI, namely, that of model‐free image synthesis, model‐based image reconstruction, and image or pixel‐level classification. For each of these three areas, we provide a framework for important considerations that consist of appropriate model training paradigms, evaluation of model robustness, downstream clinical utility, opportunities for future advances, as well recommendations for best current practices. We draw inspiration for this framework from advances in computer vision in natural imaging as well as additional healthcare fields. We further emphasize the need for reproducibility of research studies through the sharing of datasets and software.
Nanoparticles in cancer immunotherapies: An innovative strategy

Cancer has been one of the most significant causes of mortality, worldwide. Cancer immunotherapy has recently emerged as a competent, cancer‐fighting clinical strategy. Nevertheless, due to the difficulty of such treatments, costs, and off‐target adverse effects, the implementation of cancer immunotherapy described by the antigen‐presenting cell (APC) vaccine and chimeric antigen receptor T cell therapy ex vivo in large clinical trials have been limited. Nowadays, the nanoparticles theranostic system as a promising target‐based modality provides new opportunities to improve cancer immunotherapy difficulties and reduce their adverse effects. Meanwhile, the appropriate engineering of nanoparticles taking into consideration nanoparticle characteristics, such as, size, shape, and surface features, as well as the use of these physicochemical properties for suitable biological interactions, provides new possibilities for the application of nanoparticles in cancer immunotherapy. In this review article, we focus on the latest state‐of‐the‐art nanoparticle‐based antigen/adjuvant delivery vehicle strategies to professional APCs and engineering specific T lymphocyte required for improving the efficiency of tumor‐specific immunotherapy.
Double-duty solutions for optimising maternal and child nutrition in urban South Africa: a qualitative study

Abstract Objective: To obtain a community perspective on key nutrition-specific problems and solutions for mothers and children. Design: A qualitative study comprising nine focus group discussions (FGD) following a semi-structured interview guide. Setting: The township of Soweto in South Africa with a rising prevalence of double burden of malnutrition. Participants: Men and women aged ≥18 years (n 66). Three FGD held with men, six with women. Results: Despite participants perceived healthy diet to be important, they felt their ability to maintain a healthy diet was limited. Inexpensive, unhealthy food was easier to access in Soweto than healthier alternatives. Factors such as land use, hygiene and low income played a fundamental role in shaping access to foods and decisions about what to eat. Participants suggested four broad areas for change: health sector, social protection, the food system and food environment. Their solutions ranged from improved nutrition education for women at clinic visits, communal vegetable gardens and government provision of food parcels to regulatory measures to improve the healthiness of their food environment. Conclusions: South Africa’s current nutrition policy environment does not adequately address community-level needs that are often linked to structural factors beyond the health sector. Our findings suggest that to successfully address the double burden of malnutrition among women and children, a multifaceted approach is needed combining action on the ground with coherent policies that address upstream factors, including poverty. Further, there is a need for public engagement and integration of community perspectives and priorities in developing and implementing double-duty actions to improve nutrition.
The case for re-examining glycosylation inhibitors, mimetics, primers and glycosylation decoys as antivirals and anti-inflammatories in COVID19

The SARS COV2 and other SARS viruses employ a heavily glycosylated spike S protein (Watanabe et al. 2020; Shajahan et al. 2020a) to bind to the ACE2 cellular receptor, also heavily glycosylated (Shajahan et al. 2020b), on host cells. Historically, there is abundant information of glycosylation inhibitors for antiviral activity to stimulate their investigation for COVID19 treatment. While there are certain to be side effects by interfering systematically with glycosylation, a short-term dose of primers, decoys or glycosylation inhibitors might be sufficient to stop or slow the COVID19 infection cycle with minimal or temporary side effects. For example, castanospermine derivative celgosivir (6-O-butanoylcastanospermine) (Sels et al. 1999) and Miglitol, Miglustat (N-butyl −1-deoxynojirimycin) (Campo et al. 2013; Zamoner et al. 2019) are already FDA approved for type 2 diabetes and Gaucher’s disease (Rosenbloom and Weinreb 2013), passing safety and effectivity phases. This article is to stimulate repurpose testing of these already-approved compounds and others for COVID19 therapeutics.
Suppression of Bacterial Wilt in Eggplant by Non-pathogenic Ralstonia solanacearum

植物病原細菌Ralstonia solanacearumは植物，土壌および培地中で非病原性株（PC株）に変異する．本研究では，PC株（E-PCstr）の接種によるナス青枯病の発病抑制効果を調査した．さらに，罹病性ナス12品種を供試し，PC株の接種による青枯病発病抑制効果の品種間差異を調査した．罹病性ナスに20 mLのE-PCstr（106 cfu（colony forming units）・mL−1の生菌，108 cfu・mL−1の生菌または108 cfu・mL−1の死菌）を接種し，7日後に，107 cfu・mL−1の病原性株8238rif（野生株8238のリファンピシン自然耐性株）20 mLを接種した．E-PCstrの死菌および生菌106 cfu・mL−1を接種した個体では，発病抑制効果はなかった．一方，高濃度のE-PCstrの生菌108 cfu・mL−1を接種した個体では，発病抑制効果が認められた．発病が抑制された個体では，E-PCstrの確実な定着が認められ，8238rifの垂直方向への移行抑制があった．E-PCstrの接種による発病抑制効果は，供試品種の中で比較的に青枯病抵抗性が弱い品種では防除効果が低く，比較的に強い品種では防除効果が高くなる傾向にあり，PC株の発病抑制効果に品種間差異が認められた．
Development and Validation of a High Sensitivity Assay for Measuring p217 + tau in Cerebrospinal Fluid

Background: Early and accurate detection and staging is critical to managing Alzheimer’s disease (AD) and supporting clinical trials. Cerebrospinal fluid (CSF) biomarkers for amyloid-β peptides, tau species, and various neurodegenerative and inflammatory analytes are leading the way in this regard, yet there is room for improved sensitivity and specificity. In particular tau is known to be present in many different fragments, conformations, and post-translationally modified forms. While the exact tau species that might best reflect AD pathology is unknown, a growing body of evidence suggests that forms with high levels of phosphorylation in the mid-region may be especially enriched in AD. Objective: Develop an assay for measuring p217tau in CSF. Methods: Here we describe the development and validation of a novel sELISA for measuring CSF tau species containing phosphorylation at threonines 212 & 217, aka p217 + tau, using the PT3 antibody. Results: While the analyte is present at extremely low levels the assay is sufficiently sensitive and specific to quantitate p217 + tau with excellent precision, accuracy, and dilution linearity, allowing good differentiation between diagnostic subgroups. The p217 + tau measurements appear to track AD pathology better than the commonly used p181tau epitope, suggesting superior diagnostic and staging performance. Finally, the assay can also be configured to differentiate antibody-bound versus antibody-free tau, and therefore can be used to measure target engagement by p217 + tau-targeting immunotherapeutics. Conclusion: The assay for measuring p217 + tau described here is highly sensitive, accurate, precise, dilution linear, and shows good potential for identifying and staging AD.
Tracking the motion of the KV1.2 voltage sensor reveals the molecular perturbations caused by a de novo mutation in a case of epilepsy

KV1.2 channels, encoded by the KCNA2 gene, regulate neuronal excitability by conducting K+ upon depolarization. A new KCNA2 missense variant was discovered in a patient with epilepsy, causing amino acid substitution F302L at helix S4, in the KV1.2 voltage‐sensing domain. Immunocytochemistry and flow cytometry showed that F302L does not impair KCNA2 subunit surface trafficking. Molecular dynamics simulations indicated that F302L alters the exposure of S4 residues to membrane lipids. Voltage clamp fluorometry revealed that the voltage‐sensing domain of KV1.2‐F302L channels is more sensitive to depolarization. Accordingly, KV1.2‐F302L channels opened faster and at more negative potentials; however, they also exhibited enhanced inactivation: that is, F302L causes both gain‐ and loss‐of‐function effects. Coexpression of KCNA2‐WT and ‐F302L did not fully rescue these effects. The proband's symptoms are more characteristic of patients with loss of KCNA2 function. Enhanced KV1.2 inactivation could lead to increased synaptic release in excitatory neurons, steering neuronal circuits towards epilepsy.
Mitochondrial dysfunction in skeletal muscle of fukutin‐deficient mice is resistant to exercise‐ and 5‐aminoimidazole‐4‐carboxamide ribonucleotide‐induced rescue

What is the central question of this study? Does fukutin deficiency in skeletal muscle cause mitochondrial dysfunction, and if so, can AMP‐activated protein kinase (AMPK) stimulation via 5‐aminoimidazole‐4‐carboxamide ribonucleotide attenuate this through regulation of mitochondrial biogenesis and autophagy? What is the main finding and its importance? Mitochondrial dysfunction is associated with fukutin deficiency and AMPK stimulation may benefit muscle contractility to a greater extent than mitochondrial function.
On the Generalized Hamming Weights of (r, δ)-Locally Repairable Codes

Locally repairable codes (LRCs) have attracted a lot of interests recently due to their important applications in distributed storage systems. An <inline-formula> <tex-math notation="LaTeX">$(n,k,r,\delta )$ </tex-math></inline-formula>-LRC <inline-formula> <tex-math notation="LaTeX">$(\delta \ge 2)$ </tex-math></inline-formula> is an <inline-formula> <tex-math notation="LaTeX">$[n,k,d]$ </tex-math></inline-formula> linear code such that each of the <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> code symbols satisfies <inline-formula> <tex-math notation="LaTeX">$(r,\delta )$ </tex-math></inline-formula>-locality and is said to be optimal if it has minimum distance <inline-formula> <tex-math notation="LaTeX">$d = n-k-(\lceil {k/r}\rceil -1)(\delta -1)+1$ </tex-math></inline-formula>. The generalized Hamming weights (GHWs) are fundamental parameters of linear codes. Prakash <italic>et al</italic>. firstly applied GHWs to study linear codes with locality properties. In this article, we study the GHWs of <inline-formula> <tex-math notation="LaTeX">$(n,k,r,\delta )$ </tex-math></inline-formula>-LRCs <inline-formula> <tex-math notation="LaTeX">$(\delta \ge 2)$ </tex-math></inline-formula>. Firstly, for a general <inline-formula> <tex-math notation="LaTeX">$(n,k,r, \delta )$ </tex-math></inline-formula>-LRC, an upper bound on the <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>-th (<inline-formula> <tex-math notation="LaTeX">$1 \le i \le k$ </tex-math></inline-formula>) GHW is presented. Then, for an optimal <inline-formula> <tex-math notation="LaTeX">$(n,k,r, \delta )$ </tex-math></inline-formula>-LRC and its dual code, a lower bound on the <inline-formula> <tex-math notation="LaTeX">$[i(\delta -1)]$ </tex-math></inline-formula>-th GHW, for <inline-formula> <tex-math notation="LaTeX">$1 \le i \le \lceil k/r \rceil - 1$ </tex-math></inline-formula>, of the dual code is given. Specially, when <inline-formula> <tex-math notation="LaTeX">$r \mid k$ </tex-math></inline-formula>, we determine the <inline-formula> <tex-math notation="LaTeX">$[i(\delta -1)]$ </tex-math></inline-formula>-th GHW, for <inline-formula> <tex-math notation="LaTeX">$1 \le i \le \lceil k/r \rceil - 1$ </tex-math></inline-formula>, of the dual code of an optimal <inline-formula> <tex-math notation="LaTeX">$(n,k,r, \delta )$ </tex-math></inline-formula>-LRC. For the case of <inline-formula> <tex-math notation="LaTeX">$\delta =2$ </tex-math></inline-formula>, we obtain a lower bound on the <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>-th GHW for all <inline-formula> <tex-math notation="LaTeX">$1 \le i \le k$ </tex-math></inline-formula> of an optimal <inline-formula> <tex-math notation="LaTeX">$(n,k,r,2)$ </tex-math></inline-formula>-LRC. Moreover, it is shown that the weight hierarchy of an optimal <inline-formula> <tex-math notation="LaTeX">$(n,k,r,2)$ </tex-math></inline-formula>-LRC with <inline-formula> <tex-math notation="LaTeX">$r \mid k$ </tex-math></inline-formula> can be completely determined.
A Self-Supervised Learning Framework for Road Centerline Extraction From High-Resolution Remote Sensing Images

Road extraction from the high-resolution remote sensing image is significant for the land planning, vehicle navigation, etc. The existing road extraction methods normally need many preprocessing and subsequent optimization steps. Therefore, an automatic road centerline extraction method based on the self-supervised learning framework for high-resolution remote sensing image is proposed. This proposed method does not need to manually select training samples and other optimization steps, such as the nonroad area removing. First, the positive sample selection method combining the spectral and shape features is proposed to extract the road sample. Then, the one-class classifier framework is introduced and the random forest positive unlabeled learning classifier is constructed to get the posterior probability of the pixel belonging to road. The shape feature and the posterior probability are combined to form the final road network in the object-oriented way. Finally, the road centerline is obtained through the tensor voting algorithm. In order to verify the effectiveness of the proposed algorithm, high-resolution remote sensing images and benchmark datasets are used to do experiments. The indexes of the completeness ratio, the correctness ratio, and the detection quality are used for the quantitative accuracy evaluation. Compared with the supervised, the unsupervised, and the one-class classification road extraction algorithms, this proposed algorithm achieves high accuracy and efficiency. For the deep learning method comparison, the deep learning method performs well in most cases especially in the complex urban area. However, the deep learning method needs a large number of samples and a long training time, and our self-supervised learning framework does not need the training samples.
Estimation of Bearing Remaining Useful Life Based on Hybrid Deep Learning Framework

Estimation of bearing remaining useful life (RUL) aims to accurately estimate the RUL using sensor data, it is essential for maintaining the safety of the equipment. However, most of the existing prognostic methods based on data-driven have the following two drawbacks: (1) Knowledge of experts are required to select multiple features. (2) The complex spatial-temporal sequence relationship between the sensor data and RUL is difficult to captured. To overcome these drawbacks, a hybrid deep learning framework for construct the health indicator (HI) and predict the RUL is proposed. In the data processing phase, a new feature extraction method based on complex morlet wavelet transform (CMWT) is presented to convert the sensor data to image, and the image is named as the power-spectrum-energy image. In the estimation of HI phase, a new hybrid neural network model based on two conventional neural network (CNN) models that combined with bidirectional gated recurrent unit (BiGRU) network is proposed to capture the spatial-temporal features of the power-spectrum-energy image. Compared to the other methods, the proposed framework can efficiently extract the spatial-temporal features of sensor data and require no prior expert knowledge on prognostic and signal processing. The bearing dataset provided by PRONOSTIA verifies the usability of the framework. The results confirm that the framework can effectively reduce the error value of RUL estimation.
Culture and Identification of Mesenchymal Stem Cells Derived from Umbilical Cord Blood

Objective: To establish a method of purification and culturing of mesenchymal stem cells(MSCs) derived from umbilical cord blood and to investigate their biological characteristics.Methods: MSCs were obtained from umbilical cord blood of term deliveries after the mothers signed a donation form.The culture bottles were pretreated coating with self plasma.After 72-96 hours of primary culture,one half of the medium was renewed and non-adherent cells were removed.The medium was renewed by half in every 3-5 days until MSCs reached 80%-90% fusion,then they were subcultured with a propotion of 1∶2.After the third passage,the cells were analyzed with flow cytometry.The following monocloned antibodies as CD29,CD34,CD44 and CD45 were used.The growth cycle and morphological changes of MSCs were monitored by phase contrast microscopy.Results: A cell line derived from umbilical cord blood was acquired which possessed morphological and immunophenotypical characteristics similar to those of MSCs isolated from bone marrow.The potential of proliferation remained unchanging over five passages when the cells were cultured and maintained at low differentiation.By the flow cytometric analysis,CD29 and CD44 were expressed on MSCs while no expression of CD34 and CD45 were found.Conclusion: The presence of MSCs in umbilical cord blood of term infants has been demonstrated,and MSCs can be purified and cultured in vitro for the further studies of the stem cells.
Performance comparison of reconstruction algorithm based on non-uniform sampling system

For sparse ultra-wideband signals in frequency domain, the non-uniform adoption system is used to sample the signals at different rates. OMP algorithm, LASSO algorithm and BCS algorithm are used to recover the non-uniformly sampled signal. According to the analysis and comparison of the simulation results, the following conclusions are drawn: BSC algorithm has little change in time-consuming and robustness with the increase of the number of observations, and has better reconstruction performance when the number of observations is low and the noise is included.
The Lodgepole Pine Zone in Colorado

Vegetation and habitat characteristics are described in lodgepole pine forests on the east slopes of the Colorado Front Range where invasion by Douglas fir, subalpine fir, or Engelmann spruce has not occurred after 65-100 years of pine dominance. Absolute mortality of Douglas fir seedlings on plots cleared of pine litter was observed in 1967, and absolute mortality on uncleared plots was observed in 1966 and 1967. The lack of advanced reproductive stages of trees normally considered climax in adjacent Douglas fir and Spruce-Fir forest zones suggests that a lodgepole pine zone can be recognized between these other zones. Stands of lodgepole pine occurring on deep soils and normal relief within this zone may be climax or in a prolonged seral stage under present environmental conditions.
Interface Defect Shielding of Electron Trapping in a-InGaZnO Thin Film Transistors

In this work, an abnormal lowering of subthreshold swing (SS) after self-heating stress in a device with thick channel is observed. A model of interface defect shielding is proposed, based on electron trapping at the channel/gate insulator interface. The phenomenon is discussed systematically through the band diagram and extractions of the field effective mobility. Results suggest that a depletion region appears after electron trapping at the front channel, which then prevents the carriers from reaching the interface defects. Therefore, an abnormal superior electrical performance after stress is observed. Finally, a dual gate amorphous InGaZnO (a-IGZO) thin film transistor (TFT) is used to clarify the phenomenon. Results from different top gate bias voltage confirms the bulk accumulation and better gate control.