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Abstract In recent years, the preservation and conservation of ancient cultural heritage necessitate the advancement of sophisticated non-destructive testing methodologies to minimize potential damage to artworks. Therefore, this study aims to develop an advanced method for detecting defects in ancient polyptychs using infrared thermography. The test subjects are two polyptych samples replicating a 14th-century artwork by Pietro Lorenzetti (1280/85–1348) with varied pigments and artificially induced defects. To address these challenges, an automatic defect detection model is proposed, integrating numerical simulation and image processing within the Faster R-CNN architecture, utilizing VGG16 as the backbone network for feature extraction. Meanwhile, the model innovatively incorporates the efficient channel attention mechanism after the feature extraction stage, which significantly improves the feature characterization performance of the model in identifying small defects in ancient polyptychs. During training, numerical simulation is utilized to augment the infrared thermal image dataset, ensuring the accuracy of subsequent experimental sample testing. Empirical results demonstrate a substantial improvement in detection performance, compared with the original Faster R-CNN model, with the average precision at the intersection over union = 0.5 increasing to 87.3% and the average precision for small objects improving to 54.8%. These results highlight the practicality and effectiveness of the model, marking a significant progress in defect detection capability, providing a strong technical guarantee for the continuous conservation of cultural heritage, and offering directions for future studies.

Background: Diabetic bone healing remains a great challenge due to its pathological features including biochemical disturbance, excessive inflammation, and reduced blood vessel formation. In previous studies, small intestine submucosa (SIS) has been demonstrated for its immunomodulatory and angiogenic properties, which are necessary to diabetic bone healing. However, the noticeable drawbacks of SIS such as fast degradation rate, slow gelling time, and weak mechanical property seriously impede the 3D printing of SIS for bone repair. Method: In this study, we developed a novel kind of 3D-printed scaffold composed of alginate, nano-hydroxyapatite, and SIS. The morphological characterization, biocompatibility, and in vitro biological effects of the scaffolds were evaluated, and an established diabetic rat model was used for testing the in vivo biological effect of the scaffold after implantation. Results: The in vitro and in vivo results show that the addition of SIS can tune the immunomodulatory properties and angiogenic and osteogenic performances of 3D-printed scaffold, where the macrophages polarization of M2 phenotype, migration and tube formation of HUVECs, as well as osteogenic expression of ALP, are all improved, which bode well with the functional requirements for treating diabetic bone nonunion. Furthermore, the incorporation of alginate substantially improves the printability of composites with tunable degradation properties, thereby broadening the application prospect of SIS-based materials in the field of tissue engineering. Conclusion: The fabricated 3D-printed Alg/HA/SIS scaffold provides desirable immunomodulatory effect, as well as good osteogenic and angiogenic performances in vitro and in vivo, which properties are well-suited with the requirement for treating diabetic bone defects. Translational potential of this article: The incorporation of SIS and alginate acid not only provides good printability of the newly fabricated 3D-printed Alg/HA/SIS scaffold, but also improves its immunoregulatory and angiogenic properties, which suits well with the requirement for treating diabetic bone disease and opens up new horizons for the development of implants associating diabetic bone healings.

The Advanced Geosynchronous Radiation Imager (AGRI) is a mission-critical instrument for the Fengyun series of satellites. AGRI acquires full-disk images every 15 min and views East Asia every 5 min through 14 spectral bands, enabling the detection of highly variable aerosol optical depth (AOD). Quantitative retrieval of AOD has hitherto been challenging, especially over land. In this study, an AOD retrieval algorithm is proposed that combines deep learning and transfer learning. The algorithm uses core concepts from both the Dark Target (DT) and Deep Blue (DB) algorithms to select features for the machine-learning (ML) algorithm, allowing for AOD retrieval at 550 nm over both dark and bright surfaces. The algorithm consists of two steps: ① A baseline deep neural network (DNN) with skip connections is developed using 10 min Advanced Himawari Imager (AHI) AODs as the target variable, and ② sunphotometer AODs from 89 ground-based stations are used to fine-tune the DNN parameters. Out-of-station validation shows that the retrieved AOD attains high accuracy, characterized by a coefficient of determination (R2) of 0.70, a mean bias error (MBE) of 0.03, and a percentage of data within the expected error (EE) of 70.7%. A sensitivity study reveals that the top-of-atmosphere reflectance at 650 and 470 nm, as well as the surface reflectance at 650 nm, are the two largest sources of uncertainty impacting the retrieval. In a case study of monitoring an extreme aerosol event, the AGRI AOD is found to be able to capture the detailed temporal evolution of the event. This work demonstrates the superiority of the transfer-learning technique in satellite AOD retrievals and the applicability of the retrieved AGRI AOD in monitoring extreme pollution events.

ABSTRACT Objective: To compare effectiveness of Dynesys and hybrid system in treating patients with multi-segmental lumbar degenerative disease (LDD). Methods: Patients involved in this retrospective study were divided into Dynesys (n = 22) and Hybrid (n = 13) groups. Clinical outcomes were evaluated using Oswestry Disability Index (ODI), and Visual Analogue Scale (VAS). Radiologic evaluations included X-ray, MRI, and CT. Furthermore, different complications were analyzed. Results: At the last follow-up, ODI and VAS of each group were improved (p < 0.05), and the range of motion (ROM) of operating segments decreased. However, Dynesys group preserved a larger extent of ROM at the final follow-up (p < 0.05). ROM of the upper adjacent segment was increased in both groups (p < 0.05), while the disc heights were decreased at the final follow-up (p < 0.05). Besides, Dynesys group had a more obvious decrease in the disc height of dynamic segments (p < 0.05). No significant difference existed in complications between both groups (p > 0. 05). Conclusion: In our study, similar satisfactory results were obtained in both groups. Both surgical procedures can be employed as effective treatments for middle-aged and physically active patients with multi-segmental LDD. Level of Evidence III; Retrospective Comparative Study.

Osteoporosis (OP) is a systemic skeletal disease that primarily affects the elderly population, which greatly increases the risk of fractures. Here we report that Kindlin-2 expression in adipose tissue increases during aging and high-fat diet fed and is accompanied by decreased bone mass. Kindlin-2 specific deletion (K2KO) controlled by Adipoq-Cre mice or adipose tissue-targeting AAV (AAV-Rec2-CasRx-sgK2) significantly increases bone mass. Mechanistically, Kindlin-2 promotes peroxisome proliferator-activated receptor gamma (PPARγ) activation and downstream fatty acid binding protein 4 (FABP4) expression through stabilizing fatty acid synthase (FAS), and increased FABP4 inhibits insulin expression and decreases bone mass. Kindlin-2 inhibition results in accelerated FAS degradation, decreased PPARγ activation and FABP4 expression, and therefore increased insulin expression and bone mass. Interestingly, we find that FABP4 is increased while insulin is decreased in serum of OP patients. Increased FABP4 expression through PPARγ activation by rosiglitazone reverses the high bone mass phenotype of K2KO mice. Inhibition of FAS by C75 phenocopies the high bone mass phenotype of K2KO mice. Collectively, our study establishes a novel Kindlin-2/FAS/PPARγ/FABP4/insulin axis in adipose tissue modulating bone mass and strongly indicates that FAS and Kindlin-2 are new potential targets and C75 or AAV-Rec2-CasRx-sgK2 treatment are potential strategies for OP treatment.

Abstract Insufficient pancreatic β-cell mass and reduced insulin expression are key events in the pathogenesis of diabetes mellitus (DM). Here we demonstrate the high expression of Talin-1 in β-cells and that deficiency of Talin-1 reduces β-cell proliferation, which leads to reduced β-cell mass and insulin expression, thus causing glucose intolerance without affecting peripheral insulin sensitivity in mice. High-fat diet fed exerbates these phenotypes. Mechanistically, Talin-1 interacts with the E3 ligase smad ubiquitination regulatory factor 1 (Smurf1), which prohibits ubiquitination of the signal transducer and activator of transcription 3 (Stat3) mediated by Smurf1, and ablation of Talin-1 enhances Smurf1-mediated ubiquitination of Stat3, leading to decreased β-cell proliferation and mass. Furthermore, haploinsufficiency of Talin-1 and Stat3 genes, but not that of either gene, in β-cell in mice significantly impairs glucose tolerance and insulin expression, indicating that both factors indeed function in the same genetic pathway. Finally, inducible deletion Talin-1 in β-cell causes glucose intolerance in adult mice. Collectively, our findings reveal that Talin-1 functions as a crucial regulator of β-cell mass, and highlight its potential as a therapeutic target for DM patients.

Abstract In recent years, the conservation and protection of ancient cultural heritage have received increasing attention, and non-destructive testing (NDT), which can minimize the damage done to the test subject, plays an integral role therein. For instance, NDT through active infrared thermal imaging can be applied to ancient polyptychs, which can realize accurate detection of damage and defects existing on the surface and interior of the polyptychs. In this study, infrared thermography is used for non-invasive investigation and evaluation of two polyptych samples with different pigments and artificial defects, but both reproduced based on a painting by Pietro Lorenzetti (1280/85–1348) using the typical tempera technique of the century. It is noted that, to avoid as far as possible secondary damages done to the ancient cultural heritages, repeated damage-detection experiments are rarely carried out on the test subjects. To that end, numerical simulation is used to reveal the heat transfer properties and temperature distributions, as to perform procedural verification and reduce the number of experiments that need to be conducted on actual samples. Technique-wise, to improve the observability of the experimental results, a total variation regularized low-rank tensor decomposition algorithm is implemented to reduce the background noise and improve the contrast of the images. Furthermore, the efficacy of image processing is quantified through the structural-similarity evaluation.

Abstract Objective To construct a clinical prediction nomogram model using the 1-min IOF osteoporosis risk test as an evaluation tool for male osteoporosis. Methods The 1-min test results and the incidence of osteoporosis were collected from 354 patients in the osteoporotic clinic of our hospital. LASSO regression model and multi-factor logistic regression were used to analyze the risk factors of osteoporosis in patients, and the risk prediction model of osteoporosis was established. Verify with an additional 140 objects. Results We used logistic regression to construct a nomogram model. According to the model, the AUC value of the training set was 0.760 (0.704–0.817). The validation set has an AUC value of 0.806 (0.733–0.879). The test set AUC value is 0.714 (0.609–0.818). The calibration curve shows that its advantage is that the deviation correction curve of the nomogram model can maintain a good consistency with the ideal curve. In terms of clinical applicability, compared with the "total intervention" and "no intervention" schemes, the clinical net return rate of the nomogram model showed certain advantages. Conclusion Using the 1-min osteoporosis risk test provided by IOF, we built a male osteoporosis risk prediction model with good prediction effect, which can provide greater reference and help for clinicians.

Gridded global horizontal irradiance (GHI) databases are fundamental for analysing solar energy applications' technical and economic aspects, particularly photovoltaic applications. Today, there exist numerous gridded GHI databases whose quality has been thoroughly validated against ground-based irradiance measurements. Nonetheless, databases that generate data at latitudes above 65˚ are few, and those available gridded irradiance products, which are either reanalysis or based on polar orbiters, such as ERA5, COSMO-REA6, or CM SAF CLARA-A2, generally have lower quality or a coarser time resolution than those gridded irradiance products based on geostationary satellites. Amongst the high-latitude gridded GHI databases, the STRÅNG model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is likely the most accurate one, providing data across Sweden. To further enhance the product quality, the calibration technique called ''site adaptation'' is herein used to improve the STRÅNG dataset, which seeks to adjust a long period of low-quality gridded irradiance estimates based on a short period of high-quality irradiance measurements. This study introduces a novel approach for site adaptation of solar irradiance based on machine learning techniques, which differs from the conventional statistical methods used in previous studies. Seven machine-learning algorithms have been analysed and compared with conventional statistical approaches to identify Sweden's most accurate algorithms for site adaptation. Solar irradiance data gathered from three weather stations of SMHI is used for training and validation. The results show that machine learning can substantially improve the STRÅNG model's accuracy. However, due to the spatiotemporal heterogeneity in model performance, no universal machine learning model can be identified, which suggests that site adaptation is a location-dependant procedure.

Ensemble modeling is a chief strategy for probabilistic forecasting. In weather forecasting, analog ensemble, which operates under the principle that weather patterns often repeat, and dynamical ensemble, which generates equally likely trajectories of future weather by perturbing the initial and boundary conditions, constitute the two most common approaches to making ensembles. That said, in the field of solar forecasting, nor is there any head-to-head comparison made thus far in regard to understanding the relative performance of these two competing approaches; this work seeks to fill the gap. Four years (2017–2020) of operational forecasts, at seven locations, from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used, and both the raw and post-processed versions of the ensemble irradiance forecasts are verified in a fair and thorough fashion. Three classical post-processing methods, namely, Bayesian model averaging, nonhomogeneous Gaussian regression, and quantile regression, are applied to both the analog ensemble forecasts derived from ECMWF’s high-resolution control forecasts and dynamical ensemble forecasts from ECMWF’s Ensemble Prediction System. It is found that analog ensemble before post-processing possesses some advantage in terms of calibration over dynamical ensemble; their average reliability values are 0.6 W/m2 and 8.2 W/m2, respectively. However, dynamical ensemble after post-processing becomes generally more attractive, obtaining an average continuous ranked probability score of 49.0 W/m2, against 51.7 W/m2 for AnEn.

Background: Cell culture studies demonstrate the importance of β3 integrin in osteocyte mechanotransduction. However, the in vivo roles of osteocyte β3 integrin in the regulation of bone homeostasis and mechanotransduction are poorly defined. Materials and methods: To study the in vivo role of osteocyte β3 integrin in bone, we utilized the 10-kb Dmp1 (dentin matrix acidic phosphoprotein 1)-Cre to delete β3 integrin expression in osteocyte in mice. Micro-computerized tomography (μCT), bone histomorphometry and in vitro cell culture experiments were performed to determine the effects of osteocyte β3 integrin loss on bone mass accrual and biomechanical properties. In addition, in vivo tibial loading model was applied to study the possible involvement of osteocyte β3 integrin in the mediation of bone mechanotransduction. Results: Deletion of β3 integrin in osteocytes resulted in a low bone mass and impaired biomechanical properties in load-bearing long bones in adult mice. The loss of β3 integrin led to abnormal cell morphology with reduced number and length of dentritic processes in osteocytes. Furthermore, osteocyte β3 integrin loss did not impact the osteoclast formation, but significantly reduced the osteoblast-mediated bone formation rate and reduced the osteogenic differentiation of the bone marrow stromal cells in the bone microenvironment. In addition, mechanical loading failed to accelerate the anabolic bone formation in mutant mice. Conclusions: Our studies demonstrate the essential roles of osteocyte β3 integrin in regulating bone mass and mechanotransduction.

Abstract Accurately retrieving precipitable water vapor (PWV) over wide‐area land surface remains challenging. Unlike passive infrared remote sensing, passive microwave (PMW) remote sensing provides almost all‐weather PWV retrievals. This study develops a PMW‐based land PWV retrieval algorithm using automated Machine learning (ML) (AutoML). Data from the Advanced Microwave Scanning Radiometer 2 serve as the main predictor variables and high‐quality Global Positioning System (GPS) PWV data as the target variable. Unprecedentedly large GPS training samples (over 50 million) from more than 12,000 stations worldwide are used to train the AutoML model. New predictors with clear physical mechanisms enable PWV retrieval over almost any land surface type, including snow cover and near open water. Validation shows good agreement between PWV retrievals and ground observations, with a root mean square error of 3.1 mm. This encouraging outcome highlights the potential of the algorithm for application with other PMW radiometers with similar wavelengths.

Micro short circuit (MSC) fault diagnosis is thought functional in preventing thermal runaway of lithium-ion battery packs. Inconsistencies in the initial state-of-charge and aging state inevitably exist among cells of a battery pack. The existing method for MSC diagnosis disregards the symptoms originating from cell-to-cell inconsistency, which may lead to misdiagnosing inconsistent cells as MSC cells and vice versa. This work presents a method for detecting and quantitatively diagnosing MSC faults in lithium-ion battery packs, while taking cell inconsistency into consideration. Initially, the median incremental capacity (IC), derived based on ranking the terminal voltages of cells, is used as a benchmark representing the state of normal cells. Subsequently, the correlation coefficients between the ICs of individual cells and their median IC are calculated in both the time and frequency domains, as to distinguish the normal, inconsistent, and MSC cells. After detecting the MSC cell, an algorithm, which is based on a recursive least squares algorithm with forgetting factor and an adaptive H∞ Kalman filtering, is designed to calculate the short-circuit resistance online. The experimental results demonstrate that the short-circuit resistance estimated by the proposed algorithm exhibits rapid convergence to the actual values, thereby confirming the utility of the proposed algorithm in real-life contexts.

A novel sprayable adhesive is established (ZnMet-PF127) by the combination of a thermosensitive hydrogel (Pluronic F127, PF127) and a coordination complex of zinc and metformin (ZnMet). Here we demonstrate that ZnMet-PF127 potently promotes the healing of traumatic skin defect and burn skin injury by promoting cell proliferation, angiogenesis, collagen formation. Furthermore, we find that ZnMet could inhibit reactive oxygen species (ROS) production through activation of autophagy, thereby protecting cell from oxidative stress induced damage and promoting healing of skin wound. ZnMet complex exerts better effects on promoting skin wound healing than ZnCl2 or metformin alone. ZnMet complex also displays excellent antibacterial activity against Staphylococcus aureus or Escherichia coli, which could reduce the incidence of skin wound infections. Collectively, we demonstrate that sprayable PF127 could be used as a new drug delivery system for treatment of skin injury. The advantages of this sprayable system are obvious: (1) It is convenient to use; (2) The hydrogel can cover irregular skin defect sites evenly in a liquid state. In combination with this system, we establish a novel sprayable adhesive (ZnMet-PF127) and demonstrate that it is a potential clinical treatment for traumatic skin defect and burn skin injury.

Background: The key focal adhesion protein β1 integrin plays an essential role in early skeletal development. However, roles of β1 integrin expression in osteocytes during the regulation of bone homeostasis and mechanotransduction are incompletely understood. Materials and methods: To study the in vivo function of osteocyte β1 integrin in bone, we utilized the 10-kb Dmp1 (Dentin matrix acidic phosphoprotein 1)-Cre to generate mice with β1 integrin deletion in this cell type. Micro-computerized tomography, bone histomorphometry and immunohistochemistry were performed to determine the effects of osteocyte β1 integrin loss on bone mass accrual and biomechanical properties. In vivo tibial loading model was applied to study the possible involvement of osteocyte β1 integrin in bone mechanotransduction. Results: Loss of β1 integrin expression in osteocytes resulted in a severe low bone mass and impaired biomechanical properties in load-bearing long bones and spines, but not in non-weight-bearing calvariae, in mice. The loss of β1 integrin led to enlarged size of lacunar-canalicular system, abnormal cell morphology, and disorientated nuclei in osteocytes. Furthermore, β1 integrin loss caused shortening and disorientated collagen I fibers in long bones. Osteocyte β1 integrin loss did not impact the osteoclast activities, but significantly reduced the osteoblast bone formation rate and, in the meantime, enhanced the adipogenic differentiation of the bone marrow stromal cells in the bone microenvironment. In addition, tibial loading failed to accelerate the anabolic bone formation and improve collagen I fiber integrity in mutant mice. Conclusions: Our studies demonstrate an essential role of osteocyte β1 integrin in regulating bone homeostasis and mechanotransduction.The transnational potential of this article: This study reveals the regulatory roles of osteocyte β1 integrin in vivo for the maintenance of bone mass accrual, biomechanical properties, extracellular matrix integrity as well as bone mechanobiology, which defines β1 integrin a potential therapeutic target for skeletal diseases, such as osteoporosis.

Abstract Background Skeletal muscle atrophy is a common clinical manifestation of various neurotrauma and neurological diseases. In addition to the treatment of primary neuropathies, it is a clinical condition that should be investigated. FoxO3 activation is an indispensable mechanism in denervation‐induced muscle atrophy; however, upstream factors that control FoxO3 expression and activity have not been fully elucidated. N6‐methyladenosine (m6A) methylation is a novel mode of epitranscriptional gene regulation that affects several cellular processes. However, the biological significance of m6A modification in FoxO3‐dependent atrophy is unknown. Methods We performed gain‐of‐function and loss‐of‐function experiments and used denervation‐induced muscle atrophy mouse model to evaluate the effects of m6A modification on muscle mass control and FoxO3 activation. m6A‐sequencing and mass spectrometry analyses were used to establish whether histone deacetylase 4 (HDAC4) is a mediator of m6A demethylase ALKBH5 regulation of FoxO3. A series of cellular and molecular biological experiments (western blot, immunoprecipitation, half‐life assay, m6A‐MeRIP‐qPCR, and luciferase reporter assays among others) were performed to investigate regulatory relationships among ALKBH5, HDAC4, and FoxO3. Results In skeletal muscles, denervation was associated with a 20.7–31.9% decrease in m6A levels (P

Abstract Postmenopausal osteoporosis is a common bone metabolic disorder characterized by deterioration of the bone microarchitecture, leading to an increased risk of fractures. Recently, circular RNAs (circRNAs) have been demonstrated to play pivotal roles in regulating bone metabolism. However, the underlying functions of circRNAs in bone metabolism in postmenopausal osteoporosis remain obscure. Here, we report that circStag1 is a critical osteoporosis-related circRNA that shows significantly downregulated expression in osteoporotic bone marrow mesenchymal stem cells (BMSCs) and clinical bone tissue samples from patients with osteoporosis. Overexpression of circStag1 significantly promoted the osteogenic capability of BMSCs. Mechanistically, we found that circStag1 interacts with human antigen R (HuR), an RNA-binding protein, and promotes the translocation of HuR into the cytoplasm. A high cytoplasmic level of HuR led to the activation of the Wnt signaling pathway by stabilizing and enhancing low-density lipoprotein receptor-related protein 5/6 (Lrp5/6) and β-catenin expression, thereby stimulating the osteogenic differentiation of BMSCs. Furthermore, overexpression of circStag1 in vivo by circStag1-loaded adeno-associated virus (circStag1-AAV) promoted new bone formation, thereby preventing bone loss in ovariectomized rats. Collectively, we show that circStag1 plays a pivotal role in promoting the regeneration of bone tissue via HuR/Wnt signaling, which may provide new strategies to prevent bone metabolic disorders such as postmenopausal osteoporosis.

Parathyroid hormone (PTH) plays a role in maintaining calcium and phosphorus homeostasis, and in secondary hyperparathyroidism excess PTH secretion contributes to bone loss. Here the authors report an optogenetic approach to inhibit PTH secretion in human hyperplastic parathyroid cells, and prevented hyperplastic parathyroid tissue-induced bone loss in mice.

Abstract Bone injury caused changes to surrounding tissues, leading to a large number of osteoclasts appeared to clear the damaged bone tissue before bone regeneration. However, overactive osteoclasts will inhibit bone formation. In this study, we prepared methacrylylated gelatin (GelMA)‐based hydrogel to co‐crosslink with OP3‐4 peptide, a receptor activator of NF‐κB ligand (RANKL) binding agent, to achieve the slow release of OP3‐4 peptide to inhibit the activation of osteoclasts, thus preventing the long‐term existence of osteoclasts from affecting bone regeneration, and promoting osteogenic differentiation. Moreover, CXCL9 secreted by osteoblasts will bind to endogenous VEGF and inhibit vascularization, finally hinder bone formation. Thus, anti‐CXCL9 antibodies (A‐CXCL9) were also loaded in the hydrogel to neutralize excess CXCL9. The hydrogel slow released of OP3‐4 cyclic peptide and A‐CXCL9 to simultaneously inhibiting osteoclast activation and promoting vascularization, thereby accelerating the healing of femur defect. Further analysis of osteogenic protein expression and signal pathways showed that the hydrogel may be through activating the AKT‐RUNX2‐ALP pathway and ultimately promote osteogenic differentiation. This dual‐acting hydrogel can effectively prevent nonunion caused by low vascularization and provide long‐term support for the treatment of bone injury.

Abstract Mechanotransduction is a fundamental ability that allows living organisms to receive and respond to physical signals from both the external and internal environments. The mechanotransduction process requires a range of special proteins termed mechanotransducers to convert mechanical forces into biochemical signals in cells. The Piezo proteins are mechanically activated nonselective cation channels and the largest plasma membrane ion channels reported thus far. The regulation of two family members, Piezo1 and Piezo2, has been reported to have essential functions in mechanosensation and transduction in different organs and tissues. Recently, the predominant contributions of the Piezo family were reported to occur in the skeletal system, especially in bone development and mechano-stimulated bone homeostasis. Here we review current studies focused on the tissue-specific functions of Piezo1 and Piezo2 in various backgrounds with special highlights on their importance in regulating skeletal cell mechanotransduction. In this review, we emphasize the diverse functions of Piezo1 and Piezo2 and related signaling pathways in osteoblast lineage cells and chondrocytes. We also summarize our current understanding of Piezo channel structures and the key findings about PIEZO gene mutations in human diseases.

Accurate evaluation of the health status of lithium-ion batteries must be deemed as of great significance, insofar as the utility and safety of batteries are of concern. Lithium plating, in particular, is notoriously known to be a chemical reaction that can cause deterioration in, or even fatal hazards to, the health of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS), which has distinct advantages such as being fast and non-destructive over its competitors, suffices in detecting lithium plating and thus has been attracting increasing attention in the field of battery management, but its ability of assessing quantitatively the degree of lithium plating remains largely unexplored hitherto. On this point, this work seeks to narrow that gap by proposing an EIS-based method that can quantify the degree of lithium plating. The core conception is to eventually circumvent the reliance on state-of-health measurement, and use instead the impedance spectrum to acquire an estimate on battery capacity loss. To do so, the effects of solid electrolyte interphase formation and lithium plating on battery capacity must be first decoupled, so that the mass of lithium plating can be quantified. Then, based on an impedance spectrum measurement, the parameters of the fractional equivalent circuit model (ECM) of the battery can be identified. These fractional ECM parameters are received as inputs by an artificial neural network, which is tasked with establishing a correspondence between the model parameters and the mass of lithium plating. The empirical part of the work revolves around the data collected from an aging experiment, and the validity of the proposed method is truthfully attested by dismantling the batteries, which is otherwise not needed during the actual uptake of the method.

The establishment of scientific and reasonable ecological function regionalization (EFR) plays an important role in giving full play to regional advantages and realizing the benign development of resource exploitation, ecological construction, and environmental protection. However, the existing EFR lacks the identification ability for the leading functions among various ecological functions, and it is difficult to determine the regional ecological advantages, which may hinder the practical application of EFR in ecological environment zoning management. In view of this, we propose a new leading ecological function (LEF) index and the corresponding calculation method to describe the main regional ecosystem services and functions; its application in EFR could enhance the regional spatial guidance effect. We took the Core Area of the Beijing-Hangzhou Grand Canal (CA-BHGC) in China as the study area and used the maximum value composite (MVC) method to identify the LEFs of acquired grid pixels. Furthermore, the LEFs of grid pixels were applied to county-level administrative regions to complete the EFR process. Based on the results, in the CA-BHGC, although the spatial distribution of ecological function values was extremely uneven, the contribution rate of the LEF of grid pixels to the comprehensive ecological function value was usually more than 50%, reliably representing the advantageous ecological functions of grid pixels. The LEFs of the CA-BHGC included biodiversity maintenance, food production, and water retention, with grid proportions of 51.64%, 41.04%, and 6.93%, respectively, highlighting the global ecological resource advantages. The functional areas designated based on LEFs showed a good spatial correlation with the natural geographical environment. The seven biodiversity maintenance areas were mostly located at the river confluence; the two water retention areas were in the south of the Qinling-Huaihe River Line, and the six food production areas were in the central plain. In addition, the EFR process comprehensively considered the LEFs, river reaches, and provincial divisions, and it might be easier to coordinate various conflicts of interest, including economic development and ecological protection, cross-administrative regions, and adjacent functional areas.

BackgroundThe aim of the study was to compare the clinical characteristics of diabetic carpal tunnel syndrome between patients with neuropathic pain (NeuP) and non-NeuP.MethodsWe enrolled 276 patients with diabetic carpal tunnel syndrome. Pain symptoms were evaluated using a visual analog scale. Douleur Neuropathique 4, the Neuropathic Pain Symptoms Inventory questionnaire, and the body map were used to assess neuropathic symptoms. Baseline information, clinical manifestations, electrophysiological test results, and psychological status were compared between the neuropathic pain (NeuP) and non-NeuP to identify the risk factor for NeuP occurrence.ResultsResults showed that the degree of pain was more severe in NeuP patients than in nociceptive pain patients (p = 0.025). The frequencies of light touch and pinprick were more pronounced in the NeuP group than in the non-NeuP group (light touch: p = 0.001; pinprick: p = 0.004). There were 48 and 27 NeuP patients with extramedian and proximal spread, respectively, whereas in the non-NeuP group, there were 11 and 9 patients, respectively (p = 0.03). Electrophysiological results showed that patients in the NeuP group exhibited greater sensory nerve conduction velocity impairment compared with the non-NeuP group (p = 0.033). Pain Catastrophizing Scale total scores of the NeuP group were significantly higher than those of the non-NeuP group (p = 0.006).ConclusionOf the 276 diabetic carpal tunnel syndrome patients studied, the majority had NeuP. Furthermore, light touch, electrophysiological test results, and psychological factors were found to be related to NeuP occurrence in patients with diabetic carpal tunnel syndrome.

Studies have shown that the circulating tumor cell (CTC) is a necessary condition for the invasion and distant metastasis of renal cell carcimona (RCC). However, few CTCs-related gene mutations have been developed which could promote the metastasis and implantation of RCC. The objective of this study is to explore the potential driver gene mutations that promote RCC metastasis and implantation based on CTCs culture. Fifteen patients with primary mRCC and three healthy subjects were included, and peripheral blood was obtained. After the preparation of synthetic biological scaffolds, peripheral blood CTCs were cultured. Successful cultured CTCs were applied to construct CTCs-derived xenograft (CDX) models, followed by DNA extraction, whole exome sequencing (WES) and bioinformatics analysis. Synthetic biological scaffolds were constructed based on previously applied techniques, and peripheral blood CTCs culture was successfully performed. We then constructed CDX models and performed WES, and explored the potential driver gene mutations that may promote RCC metastasis and implantation. Bioinformatics analysis showed that KAZN and POU6F2 may be closely related to the prognosis of RCC. We successfully performed the culture of peripheral blood CTCs and, on this basis we initially explored the potential driver mutations for the metastasis and implantation of RCC.

Land desertification profoundly affects economic and social development, thus necessitating a collective response. Regional land control planning needs to assess the land sensitivity to desertification across different regions. In this study, we selected 12 factors from soil, vegetation, climate, and terrain aspects to calculate and evaluate Xinjiang’s land sensitivity to desertification, from 2001 to 2020, and analyzed its trends and drivers. The results indicated that the region is highly (22.93%) to extremely sensitive (34.63%) to desertification. Of these, deserts, Gobi lands, oasis–desert transitional zones, and the downstream of rivers are highly and extremely sensitive areas. Mountainous areas, oases, and along rivers are non- and mildly sensitive areas. Over the past two decades, most areas have experienced stability (45.07%) and a slight improvement of desertification (26.18%), while the Junggar Basin and Central Taklamakan Desert have seen slight and severe intensification trends, respectively. Climate-related indicators, such as surface temperature and potential evapotranspiration (PET), were identified as the most important drivers of changes in land sensitivity to desertification. Having an integrated water resource allocation and establishing the long-term monitoring of land sensitivity to desertification would have positive implications for desertification control.

Land use change has significant impacts on the regional and global environment; thus, in-depth research on the associated ecological risks is necessary for promoting ecological restoration and sustainable development. Xinjiang, China, is characterized by a fragile ecological environment, and this study aimed to predict the land use change in the region in 2030 under different scenarios, including natural development, ecological conservation, and urban development, by using the PLUS model based on land use data from 2000, 2010, and 2020. Based on the landscape structure of regional ecosystems, we developed a comprehensive ecological risk assessment framework by utilizing a combination of landscape disturbance index, vulnerability index, and loss index. This framework allowed us to evaluate the spatiotemporal patterns and variations of landscape ecological risks under different scenarios in 2030. The study results indicate the following: (1) During the period from 2000 to 2020, the primary landscape type in Xinjiang was unused land. However, significant changes were observed in the area of cultivated land, mainly due to the conversion of grassland and construction land. The expansion of construction land during the urbanization process resulted in a decline in ecological landscapes, such as grassland, thereby weakening the ecosystem’s stability. (2) Under different simulation scenarios, the urban development scenario primarily led to the conversion of unused land into construction land, which is beneficial for economic development. On the other hand, the ecological conservation scenario resulted in a modest increase in construction land and a transformation of unused land into forest and grassland, which aligns with the principles of sustainable development. (3) Different scenarios in 2030 result in varying degrees of changes in each landscape type in Xinjiang, with the spatial distribution characteristics of landscape ecological risks remaining similar to those observed in 2020. Notably, under the urban development scenario, the area of lowest and medium risk areas decreases significantly while the area of higher and highest risk areas increases substantially. Conversely, under the ecological conservation scenario, the area of the lowest risk areas experiences a more significant increase. (4) Overall, the spatial differences in the ecological risk of Xinjiang’s landscape are significant, with HH and LL clustering types predominating and presenting a polarization pattern. The distribution pattern is low in the north and high in the central and southern parts of the study area.

ObjectiveThe efficacy of hybrid (Dynesys and fusion) surgery and the traditional transforaminal lumbar interbody fusion surgery was compared in patients with multi-segmental lumbar spinal stenosis.MethodsA total of 68 patients with multi-segmental lumbar spinal stenosis subjected to surgery were recruited between January 2013 and October 2020 in the First Affiliated Hospital of Southern University of Science and Technology. The patients were divided into a hybrid group (N = 33) and a TLIF group (N = 35) by surgery. After surgery, follow-up was conducted for 12 months. Between the two groups, the following parameters were compared: general conditions, clinical symptom scores, imaging parameters, and early complications.ResultsA statistically significant difference in the duration of surgery was noted between the two groups. After 12 months of follow-up, the range of motion disappeared in the TLIF group, while 63.53% was preserved in the hybrid group with statistically significant differences. A statistically significant difference was identified in the Oswestry Disability Index one week after surgery. Nonetheless, no statistically significant differences were observed at the 12-month post-surgical follow-up. Pfirrmann grade showed a 3.03% upper adjacent segment degeneration rate in the hybrid group (1/33) at 12-month follow-up and 2.86% (1/35) in the TLIF group. Notably, no early complications (screw loosening and wound infection) were identified in the two groups.ConclusionThe Dynesys hybrid surgery combined the advantages of two systems of dynamic stabilization and rigid fusion. Besides, hybrid surgery is potentially a novel approach for the treatment of multi-segmental lumbar spinal stenosis.

Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This article offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing high-quality research papers; and offers an outlook into the future of energy forecasting.

As an important second messenger in adipocytes, calcium ions (Ca2+) are essential in regulating various intracellular signalling pathways that control critical cellular functions. Calcium channels show selective permeability to Ca2+ and facilitate Ca2+ entry into the cytoplasm, which are normally located in the plasmatic and intracellular membranes. The increase of cytosolic Ca2+ modulates a variety of signalling pathways and results in the transcription of target genes that contribute to adipogenesis, a key cellular event includes proliferation and differentiation of adipocyte. In the past decades, the involvement of some Ca2+-permeable ion channels, such as Ca2+ release-activated Ca2+ channels, transient receptor potential channels, voltage-gated calcium channels and others, in adipogenesis has been extensively explored. In the present review, we provided a summary of the expression and contributions of these Ca2+-permeable channels in mediating Ca2+ influxes that drive adipogenesis. Moreover, we discussed their potentials as future therapeutic targets.

Musculoskeletal diseases, such as osteoporosis and sarcopenia, are tremendous and growing public health concerns. Considering the intimate functional relationship between muscle and bone throughout development, growth, and aging, muscle provides the primary source of skeletal loading through contraction force. However, significant gaps exist in our knowledge regarding the role of muscle in bone homeostasis and little is known regarding the mechanism through which the central nervous system responds and regulates unloading-induced bone loss. Here, we showed that the basolateral amygdala (BLA) and medial part of the central nucleus (CeM) are anatomically connected with the musculoskeletal system. Unloading-induced bone loss is accompanied by a decrease in serum semaphorin 3A (Sema3A) levels as well as sensory denervation. In vivo fiber photometry recordings indicated that the mechanical signal is integrated by the BLA and CeM within 24 h and subsequently regulates bone remodeling. Moreover, chemogenetic activation of BLACaMKII neurons mitigates severe bone loss caused by mechanical unloading via increased serum levels of Sema3A and sensory innervation. These results indicate that the BLA integrates the mechanosensory signals rapidly and mediates the systemic hormonal secretion of Sema3A to maintain bone homeostasis.

The aim of this study was to prepare a promising biomaterial for bone tissue repair and regeneration. The Strontium – calcium sulfate hemihydrate (Sr-α-CaS) scaffold incorporating gelatin microspheres (GMs) encapsulated with Ginsenoside Rg1 (Rg1) was designed. The scaffolds of Rg1/GMs/Sr-α-CaS showed sustained release of Rg1, good biocompatibility and ability of promoting osteogenic differentiation and angiogenesis in vitro. The scaffolds were implanted into animal model of cranial bone defect to characterize bone tissue repair and regeneration in vivo. From the images of Micro-CT, it was obvious that the most bone tissue was formed in Rg1/GMs/Sr-α-CaS group in 12 weeks. New bone structure, collagen and mineralization were analyzed with staining of HE, Masson and Safranin O-Fast green and showed good distribution. The expression of osteocalcin of Rg1/GMs/Sr-α-CaS indicated new bone formation in defect site. The results revealed that synergy of Rg1 and Sr showed the best effect of bone repair and regeneration, which provided a new candidate for bone defect repair in clinic.

Osteoporotic vertebral compression fracture (OVCF) is a common cause of pain and disability and is steadily increasing due to the growth of the elderly population. To date, percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP) are almost universally accepted as appropriate vertebral augmentation procedures for OVCFs. There are many advantages of vertebral augmentation, such as short surgical time, performance under local anaesthesia, and rapid pain relief. However, there are certain issues regarding the utilization of these vertebral augmentations, such as loss of vertebral height, cement leakage, and adjacent vertebral refracture. Hence, the treatment for OVCF has changed in recent years. Satisfactory clinical results have been obtained worldwide after application of the OsseoFix System, the SpineJack System, radiofrequency kyphoplasty of the vertebral body, and the Kiva VCF treatment system. The following review discusses the development of the current techniques used for vertebral augmentation.

Developing countries account for about 86.5% of the world’s population and are experiencing rapid urbanization. Globally, the increase in the urban population is generally accompanied by the expansion of the latter and construction lands, as well as the reduction in the rural population and rural construction lands. However, with the rapid development of urbanization in China, the rural population has decreased, while the proportion of rural construction lands has increased, resulting in a significant waste of land resources. In order to quantitatively characterize the degree of deviation between the permanent rural population and rural construction lands based on the 2009–2016 demographic data and land survey data in China, we comprehensively used the decoupling model and the coordination degree model to analyze the temporal change characteristics, spatial distribution law, and the degree of deviation of rural construction land areas and the number of rural permanent residents. Firstly, according to the decoupling model, the type of decoupling between the area of rural construction lands and the number of rural permanent residents at the national scale was strongly negative. Secondly, according to the coordination degree model, the coordination type between rural construction land areas and the rural resident population was uncoordinated; at the provincial scale, the coordination system involved one city and one district (Beijing and the Tibet Autonomous Region) and the basic coordination of two cities (Tianjin and Shanghai). Xinjiang and Qinghai belonged to the reconcilable type, and the other 25 provinces belonged to the uncoordinated type. Finally, according to the comprehensive measurement model, the number of rural permanent residents and rural construction lands showed two types of decoupling: highly strong negative decoupling incoordination and moderately and weakly strong negative decoupling incoordination.

Traffic development can promote the flow of goods and people, which has long been widely considered to have a poverty reduction effect but, in fact, is not unbreakable. The development of traffic is similar to economic and social development, with internal and external characteristics, but few studies have explored the differences between the effects of their poverty reduction. Taking the land traffic of the Chengdu-Chongqing Economic Zone (CCEZ) as an example, this paper represents traffic accessibility at a county level by relying on the average internal and external travel times. Rural poverty was identified by the pentagon of livelihoods to measure the Multidimensional Development Index (MDI). Furthermore, a Geographically Weighted Regression (GWR) model was used to explore the relationship and spatial differentiation characteristics between county traffic accessibility and poverty. The results show that the traffic accessibility of the counties in the CCEZ was quite different. The average internal travel time was between 0.16 and 7 h, and the average external travel time was between 4.2 and 10.6 h. The radiation gradient structure centered on Chengdu municipal districts and the Chongqing main urban area, and the accessibility level needed to be improved. Furthermore, the MDI values of each county in the CCEZ showed the structural characteristics of “large bottom and small top”; additionally, the higher the high-value group of MDI, the stronger the spatial aggregation and the more obvious the characteristics of regional differentiation. Finally, the relationship between traffic accessibility and poverty in counties cannot be generalized. The improvement of external traffic accessibility obviously helped to improve the poverty situation in the CCEZ; the improvement of internal traffic accessibility had a multidimensional impact, but it was mainly due to the occupation or spillover of livelihood capital in rural areas; counties accounting for 82.74% would even reduce the MDI and, thus, aggravate poverty.

BMP promotes bone formation but its efficacy is limited in some patients. Here, the authors show that osteoporosis patients with a poor response to BMP have increased expression of Smurf1, which targets BMP effectors for degradation, and demonstrate that its chemical inhibition enhances BMP-mediated bone formation in mice.

There has been a limited amount of research that has attempted to determine teaching strategies using adaptive learning systems. Most studies have attempted to measure success of the use of these technologies based on improvements in students' test scores but have lacked to provide any information regarding the pedagogy implemented while using the tool or teachers' perceptions of it. A basic qualitative study was conducted where five Chicagoland high school mathematics teachers, who used the Assessment and Learning in Knowledge Spaces (ALEKS) system, were interviewed three times during one academic school year. This study asked participants to share first-hand experiences and perceptions of using ALEKS as the main learning tool. Teachers used ALEKS for assessing student understanding through its quizzes and assignments, analyzing student progress, and allowing students to practice and receive feedback on mathematical concepts. The findings of this study indicate that teachers found ALEKS to be easy to use and useful in their teaching. Specifically, teachers cited the assessment tools, built-in feedback, ability to personalize learning, and the accessibility of learning tools for students as useful in their teaching.

Abstract Background Teaching online is a different experience from that of teaching in a face-to-face setting. Knowledge and skills developed for teaching face-to-face classes are not adequate preparation for teaching online. It is even more challenging to teach science, technology, engineering and math (STEM) courses completely online because these courses usually require more hands-on activities and live demonstrations. Although the demand for online STEM courses has never been higher, little has been done to develop effective instructional and online course design strategies for teaching STEM courses online. This paper reports the effectiveness of the instructional strategies adopted and the online course design features in a fully online statistics course from the students’ perspectives. The online statistics course was an introductory, quantitative research course that covered common statistical concepts and focused on the application of educational research concepts for graduate students in educational technology. In terms of the statistics concepts covered, the course was similar to an introductory statistics class for students majoring in science, technology, math and engineering (STEM). The participants were mostly K-20 (meaning from kindergarten to college) instructors who had knowledge of instructional strategies. Results Data collected from participants’ reflections and course evaluations revealed that a range of instructional strategies and course design features were effective and helped students learn statistics in an online environment. Specifically, case studies, video demonstrations, instructor’s notes, mini projects, and an online discussion forum were most effective. For online course design features, consistent structure, various resources and learning activities, and the application focused course content were found to be effective. Conclusions The implications of this study include effective instructional strategies and online course design for application-oriented STEM courses such as physics and engineering. The study results can be used to guide online teaching and learning as well as online course design for instructors, course designers, and students in STEM fields.

Allograft inflammatory factor-1 (AIF1) is a cytoplasmic scaffold protein shown to influence immune responses in macrophages and microglial cells. The protein contains Ca2+ binding EF-hand and PDZ interaction domains important for mediating intracellular signaling complexes. This study now reports that AIF1 is expressed in CD11c+ dendritic cells (DC) and silencing of expression restrains induction of antigen-specific CD4+ T cell effector responses. AIF1 knockdown in murine DC resulted in impaired T cell proliferation and skewed polarization away from T helper type 1 and 17 fates. In turn, there was a parallel expansion of IL-10-producing and CD25+Foxp3+ T regulatory subsets. These studies are the first to demonstrate that AIF1 expression in DC serves as a potent governor of cognate T cell responses and presents a novel target for engineering tolerogenic DC-based immunotherapies.

This article empirically demonstrates the impacts of truthfully sharing forecast information and using forecast combinations in a fast-moving-consumer-goods (FMCG) supply chain. Although it is known a priori that sharing information improves the overall efficiency of a supply chain, information such as pricing or promotional strategy is often kept proprietary for competitive reasons. In this regard, it is herein shown that simply sharing the retail-level forecasts—this does not reveal the exact business strategy, due to the effect of omni-channel sales—yields nearly all the benefits of sharing all pertinent information that influences FMCG demand. In addition, various forecast combination methods are used to further stabilize the forecasts, in situations where multiple forecasting models are used during operation. In other words, it is shown that combining forecasts is less risky than “betting” on any component model.

The intent of this study was to learn about students’ perceived barriers and the impact of those barriers on the quality of online discussions between two distinct cultural groups in Eastern and Northern Siberia (Russia). A mixed-methods approach utilizing surveys and interviews was used to investigate (1) the types of barriers the students perceived participating in an asynchronous online course across the two cultural groups, and (2) the impact of those barriers on the quality of students’ postings. Findings indicate that cultural influences can add potential barriers to online learning aside from those widely reported in the literature. The study has implications for instructors and designers in creating online learning environments, especially as it relates to asynchronous communication across multiple locations and cultural backgrounds.