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Abstract The skeleton has been suggested to function as an endocrine organ controlling whole organism energy balance, however the mediators of this effect and their molecular links remain unclear. Here, utilizing Schnurri-3−/− (Shn3 −/− ) mice with augmented osteoblast activity, we show Shn3 −/− mice display resistance against diet-induced obesity and enhanced white adipose tissue (WAT) browning. Conditional deletion of Shn3 in osteoblasts but not adipocytes recapitulates lean phenotype of Shn3 −/− mice, indicating this phenotype is driven by skeleton. We further demonstrate osteoblasts lacking Shn3 can secrete cytokines to promote WAT browning. Among them, we identify a C-terminal fragment of SLIT2 (SLIT2-C), primarily secreted by osteoblasts, as a Shn3-regulated osteokine that mediates WAT browning. Lastly, AAV-mediated Shn3 silencing phenocopies the lean phenotype and augmented glucose metabolism. Altogether, our findings establish a novel bone-fat signaling axis via SHN3 regulated SLIT2-C production in osteoblasts, offering a potential therapeutic target to address both osteoporosis and metabolic syndrome.

Background: Recently, the osteogenic potential of Adiponectin-labeled adipogenic lineage progenitors (Adipoq-lineage progenitors) in bone marrow has been observed to support bone maintenance and repair. However, little is known about the function of Schnurri-3 (SHN3, also known as HIVEP3) in other mesenchymal lineage cells, apart from its negative regulation of bone formation on osteoblasts. Method: In this study, we used single-cell RNA sequencing (scRNA-seq) profiling to demonstrate that Adipoq-lineage progenitors express higher levels of Shn3 compared to other mesenchymal cell populations in mice and humans. To investigate the role of SHN3 in Adipoq-lineage progenitors, we generated a murine model specifically harboring a Shn3-deficient allele in Adipoq-expressing cells. Information of mice body weight was collected weekly to generate body weight curve. Bone phenotype was analyzed using micro-CT and histomorphometric studies. To eliminate the role of peripheral adipose tissue on bone, we collected adipose wet weight, performed intraperitoneal glucose tolerance tests and intraperitoneal insulin tolerance tests, and conducted a fat-transplantation study. Osteoblast and osteoclast functions were assessed through toluidine blue staining and TRAP staining, respectively. We further investigated the effect of Shn3 depletion on the differentiation of Adipoq-lineage progenitors through immunostaining and in vitro differentiation assays. Finally, we evaluated whether Shn3 deficiency in Adipoq-lineage progenitors affects the fracture healing process by generating bi-cortical femoral fracture models. Results: Depletion of Shn3 in Adipoq-lineage progenitors resulted in a significant increase in trabecular bone mass and bone formation in vivo, without disrupting whole-body energy metabolism and skeletal development. Consistent with these findings, both cell-lineage tracing and functional assays revealed that Shn3 ablation effectively shifted the cell fate of Adipoq-lineage progenitors towards an osteogenic phenotype in the bone marrow. Furthermore, in vivo studies demonstrated that the lack of Shn3 in Adipoq-lineage progenitors also enhanced bone fracture healing under pathological conditions. Conclusion: Overall, our findings provide a novel strategy for targeting the osteoanabolic potential of bone marrow Adipoq-lineage progenitors as a potential treatment for bone loss-related disorders. Translational potential of this article: We have identified a novel gene target that directs the cell fate of a previously identified non-osteogenic cell population under physiological conditions. This study not only expands the therapeutic value of Shn3 ablation in treating osteoporotic or traumatic bone diseases but also provides new insights into the contribution of bone marrow Adipoq-lineage progenitors to osteogenesis. Thus, this article further supports Shn3 silencing as a valuable approach to treat osteopenia and accelerate fracture healing (see graphical abstract)

Accurate mapping of irrigated croplands is crucial for a comprehensive understanding of agricultural practices and land management. Despite recent advancements, there remains room for further exploration of the effective fusion of temporal information from multitemporal remote sensing images, which is essential for capturing the dynamic nature of agricultural landscapes. Many existing irrigation mapping methods concatenate multitemporal images in a direct way and thus neglect the temporal relationships within the image time series, especially the sequence and interdependencies of the temporal dimension. To address this gap, a novel deep learning model, named the attention-enhanced spatial–temporal high-resolution network (AEST-HRNet), which incorporates parallel processing and a fusion mechanism of multiresolution information streams, three-dimensional (3D) spatial–temporal convolution, and temporal attention modules, was proposed. When applied to irrigated regions in Washington and California, USA, AEST-HRNet effectively extracted irrigated areas using multitemporal Sentinel-2 images obtained with the Google Earth Engine (GEE). To validate the results, 208 representative sample patches were selected, and the AEST-HRNet maps were compared against third-party ground reference data and statistics from the United States National Agricultural Statistics Survey (NASS). Quantitative assessment revealed an impressive F1-score of 0.956, an intersection over union (IoU) value of 0.867, and an overall accuracy (OA) value of 0.973 in Washington, outperforming publicly released maps. Comparative evaluations demonstrated that AEST-HRNet outperforms pixel-based classification using the random forest (RF) model and convolution-based semantic segmentation methods based on metrics such as F1-score, IoU, and Kappa. This study introduces a promising solution for precise irrigation mapping, offering increased accuracy and efficiency in producing reliable irrigation maps.

Canonical correlation analysis (CCA), Multivariate synchronization index (MSI), and their extended methods have been widely used for target recognition in Brain-computer interfaces (BCIs) based on Steady State Visual Evoked Potentials (SSVEP), and covariance calculation is an important process for these algorithms. Some studies have proved that embedding time-local information into the covariance can optimize the recognition effect of the above algorithms. However, the optimization effect can only be observed from the recognition results and the improvement principle of time-local information cannot be explained. Therefore, we propose a time-local weighted transformation (TT) recognition framework that directly embeds the time-local information into the electroencephalography signal through weighted transformation. The influence mechanism of time-local information on the SSVEP signal can then be observed in the frequency domain. Low-frequency noise is suppressed on the premise of sacrificing part of the SSVEP fundamental frequency energy, the harmonic energy of SSVEP is enhanced at the cost of introducing a small amount of high-frequency noise. The experimental results show that the TT recognition framework can significantly improve the recognition ability of the algorithms and the separability of extracted features. Its enhancement effect is significantly better than the traditional time-local covariance extraction method, which has enormous application potential.

Abstract Loss of refreshment in nucleus pulposus (NP) cellularity leads to intervertebral disc (IVD) degeneration. Nevertheless, the cellular sequence of NP cell differentiation remains unclear, although an increasing body of literature has identified markers of NP progenitor cells (NPPCs). Notably, due to their fragility, the physical enrichment of NP‐derived cells has limited conventional transcriptomic approaches in multiple studies. To overcome this limitation, a spatially resolved transcriptional atlas of the mouse IVD is generated via the 10x Genomics Visium platform dividing NP spots into two clusters. Based on this, most reported NPPC‐markers, including Cathepsin K (Ctsk), are rare and predominantly located within the NP‐outer subset. Cell lineage tracing further evidence that a small number of Ctsk‐expressing cells generate the entire adult NP tissue. In contrast, Tie2, which has long suggested labeling NPPCs, is actually neither expressed in NP subsets nor labels NPPCs and their descendants in mouse models; consistent with this, an in situ sequencing (ISS) analysis validated the absence of Tie2 in NP tissue. Similarly, no Tie2‐cre‐mediated labeling of NPPCs is observed in an IVD degenerative mouse model. Altogether, in this study, the first spatial transcriptomic map of the IVD is established, thereby providing a public resource for bone biology.

Abstract Understanding the interplay between immune cells and the bone marrow microenvironment is crucial for elucidating age‐related musculoskeletal changes. In this commentary manuscript, we summarized that studies have shown that proinflammatory immune cells in the bone marrow, such as macrophages and neutrophils, can inhibit bone formation by secreting grancalcin. Research on skeletal stem cells (SSCs) in aged mice reveals a shift towards pro‐inflammatory gene expression, affecting their osteogenic potential, while another study maps age‐related changes in cranial SSC niches, emphasizing the role of the CXCL12–CXCR4 axis in stem cell‐immune cell communication, Additionally, the immune system influences hematopoietic stem cells (HSCs); Niche ageing and accumulation of mutations with age lead to HSC exhaustion and a bias towards myeloid differentiation, with toll‐like receptors playing a key role in maintaining hematopoiesis and bone metabolism balance.

Abstract Dual atom catalysts, bridging single atom and metal/alloy nanoparticle catalysts, offer more opportunities to enhance the kinetics and multifunctional performance of oxygen reduction/evolution and hydrogen evolution reactions. However, the rational design of efficient multifunctional dual atom catalysts remains a blind area and is challenging. In this study, we achieved controllable regulation from Co nanoparticles to CoN4 single atoms to Co2N5 dual atoms using an atomization and sintering strategy via an N-stripping and thermal-migrating process. More importantly, this strategy could be extended to the fabrication of 22 distinct dual atom catalysts. In particular, the Co2N5 dual atom with tailored spin states could achieve ideally balanced adsorption/desorption of intermediates, thus realizing superior multifunctional activity. In addition, it endows Zn-air batteries with long-term stability for 800 h, allows water splitting to continuously operate for 1000 h, and can enable solar-powered water splitting systems with uninterrupted large-scale hydrogen production throughout day and night. This universal and scalable strategy provides opportunities for the controlled design of efficient multifunctional dual atom catalysts in energy conversion technologies.

Abstract Evidence from numerous studies has revealed the synchronous progression of aging in bone and muscle; however, little is known about the underlying mechanisms. To this end, human muscles and bones are harvested and the aging‐associated transcriptional dynamics of two tissues in parallel using single‐cell RNA sequencing are surveyed. A subset of lipid‐associated macrophages (triggering receptor expressed on myeloid cells 2, TREM2+ Macs) is identified in both aged muscle and bone. Genes responsible for muscle dystrophy and bone loss, such as secreted phosphoprotein 1 (SPP1), are also highly expressed in TREM2+ Macs, suggesting its conserved role in aging‐related features. A common transition toward pro‐inflammatory phenotypes in aged CD4+ T cells across tissues is also observed, activated by the nuclear factor kappa B subunit 1 (NFKB1). CD4+ T cells in aged muscle experience Th1‐like differentiation, whereas, in bone, a skewing toward Th17 cells is observed. Furthermore, these results highlight that degenerated myocytes produce BAG6‐containing exosomes that can communicate with Th17 cells in the bone through its receptor natural cytotoxicity triggering receptor 3 (NCR3). This communication upregulates CD6 expression in Th17 cells, which then interact with TREM2+ Macs through CD6‐ALCAM signaling, ultimately stimulating the transcription of SPP1 in TREM2+ Macs. The negative correlation between serum exosomal BCL2‐associated athanogene 6 (BAG6) levels and bone mineral density further supports its role in mediating muscle and bone synchronization with aging.

Abstract Background Women suffer from various distress and disturbances after menopause, including osteoporosis, a risk factor associated with multiple diseases. Altered gut microbiota has been implicated in postmenopausal osteoporosis. In this study, to understand gut microbiota signatures and fecal metabolite changes in postmenopausal women with osteoporosis, 108 postmenopausal women were recruited for intestinal microbiota and fecal metabolite detection. Among these participants, 98 patients, who met the inclusion criteria, were divided into postmenopausal osteoporosis (PMO) and non-postmenopausal osteoporosis (non-PMO) groups based on bone mineral density (BMD). The compositions of gut bacteria and fungi were examined by 16 S rRNA gene sequencing and ITS sequencing, respectively. Meanwhile, fecal metabolites were analyzed using liquid chromatography coupled with mass spectrometry (LC-MS). Results We found that bacterial α-diversity and β-diversity were significantly altered in PMO compared to non-PMO patients. Interestingly, fungi composition showed larger changes, and the differences in β-diversity were more significant between PMO and non-PMO patients. Metabolomics analysis revealed that fecal metabolites, such as levulinic acid, N-Acetylneuraminic acid, and the corresponding signaling pathways were also changed significantly, especially in the alpha-Linolenic acid metabolism and selenocompound metabolism. The screened differential bacteria, fungi, and metabolites closely correlated with clinical findings between these two groups, for example, the bacterial genus, Fusobacterium, the fungal genus, Devriesia, and the metabolite, L-pipecolic acid, were significantly associated with BMD. Conclusions Our findings indicated that there were remarkable changes in gut bacteria, fungi, and fecal metabolites in postmenopausal women, and such changes were notably correlated with patients’ BMD ​​and clinical findings. These correlations provide novel insights into the mechanism of PMO development, potential early diagnostic indicators, and new therapeutic approaches to improve bone health in postmenopausal women.

Abstract Ferroptosis is a type of regulated cell death characterized by iron-mediated lipid peroxidation, in contrast with apoptosis, autophagy, and necrosis. It can be triggered by many pathological processes, including cellular metabolism, tumors, neurodegenerative diseases, cardiovascular diseases, and ischemia–reperfusion injuries. In recent years, ferroptosis has been discovered to be associated with p53. P53 is a tumor suppressor protein with multiple and powerful functions in cell cycle arrest, senescence, cell death, repair of DNA damage, and mitophagy. Emerging evidence shows that ferroptosis plays a crucial role in tumor suppression by p53. P53 functions as a key bidirectional regulator of ferroptosis by adjusting metabolism of iron, lipids, glutathione peroxidase 4, reactive oxygen species, and amino acids via a canonical pathway. In addition, a noncanonical pathway of p53 that regulates ferroptosis has been discovered in recent years. The specific details require to be further clarified. These mechanisms provide new ideas for clinical applications, and translational studies of ferroptosis have been performed to treat various diseases.

High- and very high-resolution (HR, VHR) remote sensing (RS) images can provide comprehensive and intricate spatial information for land cover classification, which is particularly crucial when analyzing complex built-up environments. However, the application of HR and VHR images to large-scale and detailed land cover mapping is always constrained by the intricacy of land cover classification models, the exorbitant cost of collecting training samples, and geographical changes or acquisition conditions. To overcome this limitation, we propose an unsupervised domain adaptation (UDA) with contrastive learning-based discriminative feature augmentation (CLDFA) for RS image classification. In detail, our method first utilizes contrastive learning (CL) through a memory bank in order to memorize sample features and improve model performance, where the approach employs an end-to-end Siamese network and incorporates dynamic pseudo-label assignment and class-balancing strategies for adaptive domain joint learning. By transferring classification models trained on a source domain (SD) to an unlabeled target domain (TD), our proposed UDA method enables large-scale land cover mapping. We conducted experiments using a massive five billion-pixels dataset as the SD and tested the HR and VHR RS images of five typical Chinese cities as the TD and applied the method on the completely unlabeled world view 3 (WV3) image of Urumqi city. The experimental results demonstrate that our method excels in large-scale HR and VHR RS image classification tasks, highlighting the advantages of semantic segmentation based on end-to-end deep convolutional neural networks (DCNNs).

Retinoic acid receptor-related orphan receptor alpha (RORα), a candidate tumor suppressor, is prevalently downregulated or lost in malignant breast cancer cells. However, the mechanisms of how RORα expression is regulated in breast epithelial cells remain incompletely understood. Protein arginine N-methyltransferase 5 (PRMT5), a type II methyltransferase catalyzing the symmetric methylation of the amino acid arginine in target proteins, was reported to regulate protein stability. To study whether and how PRMT5 regulates RORα, we examined the direct interaction between RORα and PRMT5 by immunoprecipitation and GST pull-down assays. The results showed that PRMT5 directly bound to RORα, and PRMT5 mainly symmetrically dimethylated the DNA-binding domain (DBD) but not the ligand-binding domain (LBD) of RORα. To investigate whether RORα protein stability is regulated by PRMT5, we transfected HEK293FT cells with RORα and PRMT5-expressing or PRMT5-silencing (shPRMT5) vectors and then examined RORα protein stability by a cycloheximide chase assay. The results showed that PRMT5 increased RORα protein stability, while silencing PRMT5 accelerated RORα protein degradation. In PRMT5-silenced mammary epithelial cells, RORα protein expression was decreased, accompanied by an enhanced epithelial–mesenchymal transition morphology and cell invasion and migration abilities. In PRMT5-overexpressed mammary epithelial cells, RORα protein was accumulated, and cell invasion was suppressed. These findings revealed a novel mechanism by which PRMT5 regulates RORα protein stability.

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability is substantial. In response, we have integrated wave energy with offshore photovoltaic and wind power generation and propose a day-ahead and intra-day multi-time-scale rolling optimization scheduling strategy for the complementary dispatch of these three energy sources. Using real meteorological data from this maritime area, we employed a CNN-LSTM neural network to predict the power generation and load demand of the area on both day-ahead 24 h and intra-day 1 h time scales, with the DDPG algorithm applied for refined electricity management through rolling optimization scheduling of the forecast data. Simulation results demonstrate that the proposed strategy effectively meets load demands through complementary scheduling of wave power, wind power, and photovoltaic power generation based on the climatic characteristics of the Bohai and Yellow Sea regions, reducing the negative impacts of the seasonality and intra-day uncertainty of these three energy sources on the grid. Additionally, compared to the day-ahead scheduling strategy alone, the day-ahead and intra-day rolling optimization scheduling strategy achieved a reduction in system costs by 16.1% and 22% for a typical winter day and a typical summer day, respectively.

Objective： This study aimed to improve the yield and gelling property of lemon pectin. Methods: Oxalic acid was used to extract pectin from lemon residue. The factors of optimal ratio of solid-liquid, pH, extraction temperature and extraction time were optimized through single factor experiments and orthogonal experiments. The purity, degree of esterification and rheological properties of the extracted lemon pectin were analyzed. The differences of gelling property between the extracted lemon pectin and two kinds of commercial high methoxyl pectins (HMP-1, HMP-2) were compared. Results: The results showed that the yield of pectin extract was 22.83%, with total galacturonic acid of 76.06% and degree of esterification of 75.94%, when the ratio of solid-liquid was 1∶20 （g/mL）, extracting pectin at pH 2.2 and 95 ℃ for 75 min. The viscosity of the extracted lemon pectin was higher than HMP-1 and HMP-2. The calcium sensitivity was between HMP-1 and HMP-2, and the temperature sensitivity was similar to HMP-2. The sol-gel transformation of the extracted lemon pectin was found at 76.55 ℃ in the calcium ion environment. Conclusion: Lemon pectin extracted by oxalic acid has good rheological and gel properties, and can be potentially used as a stabilizer in acidic milk drinks.

IntroductionThe common spatial patterns (CSP) algorithm is the most popular technique for extracting electroencephalogram (EEG) features in motor imagery based brain-computer interface (BCI) systems. CSP algorithm embeds the dimensionality of multichannel EEG data to extract features of motor imagery tasks. Most previous studies focused on the optimization of the time domain and the spectrum domain of EEG signal to improve the effectiveness of CSP, whereas ignoring the constraint on the projected feature space.MethodsThis study proposed a variance characteristic preserving CSP (VPCSP) that is modified by a regularization item based on graph theory. Specifically, we calculated the loss of abnormalities of the projected data while preserving the variance characteristic locally. Then the loss could be rewritten as a matrix with the introduction of the Laplace matrix, which turned it into a generalized eigenvalue problem equivalent to CSP. This study evaluated the proposed method on two public EEG datasets from the BCI competition. The modified method could extract robust and distinguishable features that provided higher classification performance. Experimental results showed that the proposed regularization improved the effectiveness of CSP significantly and achieved superior performance compared with reported modified CSP algorithms significantly.ResultsThe classification accuracy of the proposed method achieved 87.88 %, 90.07 %, and 76.06 % on public dataset IV part I, III part IVa and the self-collected dataset, respectively. Comparative experiments are conducted on two public datasets and one self-collected dataset. Results showed that the proposed method outperformed the reported algorithm.DiscussionThe proposed method can extract robust features to increase the performance of BCI systems. And the proposal still has expandability. These results show that our proposal is a promising candidate for the performance improvement of MI-BCI.

The potential of marine natural products as effective drugs for osteoporosis treatment is an understudied area. In this study, we investigated the ability of lead compounds from deep-sea-derived Penicillium solitum MCCC 3A00215 to promote bone formation in vitro and in vivo. We found that penicopeptide A (PPA) promoted osteoblast mineralization among bone marrow mesenchymal stem cells (BMSCs) in a concentration-dependent manner, and thus, we selected this natural peptide for further testing. Our further experiments showed that PPA significantly promoted the osteogenic differentiation of BMSCs while inhibiting their adipogenic differentiation and not affecting their chondrogenic differentiation. Mechanistic studies showed that PPA binds directly to the AKT and GSK-3β and activates phosphorylation of AKT and GSK-3β, resulting in the accumulation of β-catenin. We also evaluated the therapeutic potential of PPA in a female mouse model of ovariectomy-induced systemic bone loss. In this model, PPA treatment prevented decreases in bone volume and trabecular thickness. In conclusion, our in vitro and in vivo results demonstrated that PPA could promote osteoblast-related bone formation via the AKT, GSK-3β, and β-catenin signaling pathways, indicating the clinical potential of PPA as a candidate compound for osteoporosis prevention.

Motor imagery-based brain-computer interfaces (MI-BCIs) features are generally extracted from a wide fixed frequency band and time window of EEG signal. The performance suffers from individual differences in corresponding time to MI tasks. In order to solve the problem, in this study, we propose a novel method named Riemannian sparse optimization and Dempster-Shafer fusion of multi-time-frequency patterns (RSODSF) to enhance the decoding efficiency. First, we effectively combine the Riemannian geometry of the spatial covariance matrix with sparse optimization to extract more robust and distinct features. Second, the Dempster-Shafer theory is introduced and used to fuse each time window after sparse optimization of Riemannian features. Besides, the probabilistic values of the support vector machine (SVM) are obtained and transformed to effectively fuse multiple classifiers to leverage potential soft information of multiple trained SVM. The open-access BCI Competition IV dataset IIa and Competition III dataset IIIa are employed to evaluate the performance of the proposed RSODSF. It achieves higher average accuracy (89.7% and 96.8%) than state-of-the-art methods. The improvement over the common spatial patterns (SFBCSP) are respectively 9.9% and 12.4% (p < 0.01, paired t-test). These results show that our proposed RSODSF method is a promising candidate for the performance improvement of MI-BCI.

Abstract The intervertebral disc (IVD) acts as a fibrocartilaginous joint to anchor adjacent vertebrae. Although several studies have demonstrated the cellular heterogeneity of adult mature IVDs, a single‐cell transcriptomic atlas mapping early IVD formation is still lacking. Here, the authors generate a spatiotemporal and single cell‐based transcriptomic atlas of human IVD formation at the embryonic stage and a comparative mouse transcript landscape. They identify two novel human notochord (NC)/nucleus pulposus (NP) clusters, SRY‐box transcription factor 10 (SOX10)+ and cathepsin K (CTSK)+, that are distributed in the early and late stages of IVD formation and they are validated by lineage tracing experiments in mice. Matrisome NC/NP clusters, T‐box transcription factor T (TBXT)+ and CTSK+, are responsible for the extracellular matrix homeostasis. The IVD atlas suggests that a subcluster of the vertebral chondrocyte subcluster might give rise to an inner annulus fibrosus of chondrogenic origin, while the fibroblastic outer annulus fibrosus preferentially expresseds transgelin and fibromodulin . Through analyzing intercellular crosstalk, the authors further find that notochordal secreted phosphoprotein 1 (SPP1) is a novel cue in the IVD microenvironment, and it is associated with IVD development and degeneration. In conclusion, the single‐cell transcriptomic atlas will be leveraged to develop preventative and regenerative strategies for IVD degeneration.

The progenitor cells that form articular cartilage express a gene for a protein called NFATc1, which stops articular chondrocytes from developing too early in the joint.

Three new polyketides (penidihydrocitrinins A–C, 1–3) and fourteen known compounds (4–17) were isolated from the deep-sea-derived Penicillium citrinum W17. Their structures were elucidated by comprehensive analyses of 1D and 2D NMR, HRESIMS, and ECD calculations. Compounds 1–17 were evaluated for their anti-inflammatory and anti-osteoporotic bioactivities. All isolates exhibited significant inhibitory effects on LPS-stimulated nitric oxide production in murine brain microglial BV-2 cells in a dose-response manner. Notably, compound 14 displayed the strongest effect with the IC50 value of 4.7 µM. Additionally, compounds 6, 7, and 8 significantly enhanced osteoblast mineralization, which was comparable to that of the positive control, purmorphamine. Furthermore, these three compounds also suppressed osteoclastogenesis in a dose-dependent manner under the concentrations of 2.5 μM, 5.0 μM, and 10 μM.

M-CSF is a critical growth factor for myeloid lineage cells, including monocytes, macrophages, and osteoclasts. Tissue-resident macrophages in most organs rely on local M-CSF. However, it is unclear what specific cells in the bone marrow produce M-CSF to maintain myeloid homeostasis. Here, we found that Adipoq-lineage progenitors but not mature adipocytes in bone marrow or in peripheral adipose tissue, are a major cellular source of M-CSF, with these Adipoq-lineage progenitors producing M-CSF at levels much higher than those produced by osteoblast lineage cells. The Adipoq-lineage progenitors with high CSF1 expression also exist in human bone marrow. Deficiency of M-CSF in bone marrow Adipoq-lineage progenitors drastically reduces the generation of bone marrow macrophages and osteoclasts, leading to severe osteopetrosis in mice. Furthermore, the osteoporosis in ovariectomized mice can be significantly alleviated by the absence of M-CSF in bone marrow Adipoq-lineage progenitors. Our findings identify bone marrow Adipoq-lineage progenitors as a major cellular source of M-CSF in bone marrow and reveal their crucial contribution to bone marrow macrophage development, osteoclastogenesis, bone homeostasis, and pathological bone loss.

A major complication of a joint replacement is prosthesis loosening caused by inflammatory osteolysis, leading to the revision of the operation. This is due to the abnormal activation of osteoclast differentiation and function caused by periprosthetic infection. Therefore, targeting abnormally activated osteoclasts is still effective for treating osteolytic inflammatory diseases. CDZ173 is a selective PI3K inhibitor widely used in autoimmune-related diseases and inflammatory diseases and is currently under clinical development. However, the role and mechanism of CDZ173 in osteoclast-related bone metabolism remain unclear. The possibility for treating aseptic prosthesis loosening brought on by inflammatory osteolysis illness can be assessed using an LPS-induced mouse cranial calcium osteolysis model. In this study, we report for the first time that CDZ173 has a protective effect on LPS-induced osteolysis. The data show that this protective effect is due to CDZ173 inhibiting the activation of osteoclasts in vivo. Meanwhile, our result demonstrated that CDZ173 had a significant inhibitory effect on RANKL-induced osteoclasts. Furthermore, using the hydroxyapatite resorption pit assay and podosol actin belt staining, respectively, the inhibitory impact of CDZ173 on bone resorption and osteoclast fusion of pre-OC was determined. In addition, staining with alkaline phosphatase (ALP) and alizarin red (AR) revealed that CDZ173 had no effect on osteoblast development in vitro. Lastly, CDZ173 inhibited the differentiation and function of osteoclasts by weakening the signal axis of PI3K-AKT/MAPK-NFATc1 in osteoclasts. In conclusion, our results highlight the potential pharmacological role of CDZ173 in preventing osteoclast-mediated inflammatory osteolysis and its potential clinical application.

It has been nearly 35 months since the COVID-19 outbreak. The pathogen SARS-CoV-2 has evolved into several variants. Among them, Omicron is the fifth variant of concern which have rapidly spread globally during the past 8 months. Omicron variant shows different characteristics from previous variants, which is highly infectious, highly transmissible, minimally pathogenic, vaccine and antibody tolerant; however, it is less likely to cause severe illness, resulting in fewer deaths. Omicron has evolved into five main lineages, including BA.1, BA.2, BA.3, BA.4, and BA.5. Before BA.5, Omicron BA.2 sublineage was the dominant strain all over the world for several months. The experience of prevention and treatment against BA.2 is worth studying and learning for overcoming other Omicron subvariants. Although the Omicron subvariant BA.2 is significantly less severe than that caused by ancestral strains, it is still far more dangerous than influenza, and its long-term sequelae are unknown. Effective treatments are currently limited; therefore, effective defense may be the key to controlling the epidemic today, rather than just “living with” the virus.

Hedgehog signaling is essential for bone formation. Here, the authors show that the transmembrane protein SLITRK5 is a negative regulator of hedgehog signaling in osteoblasts, suggesting it may be a potential therapeutic target to enhance bone formation.

ObjectiveClinical assessment of consciousness relies on behavioural assessments, which have several limitations. Hence, disorder of consciousness (DOC) patients are often misdiagnosed. In this work, we aimed to compare the repetitive assessment of consciousness performed with a clinical behavioural and a Brain-Computer Interface (BCI) approach.Materials and methodsFor 7 weeks, sixteen DOC patients participated in weekly evaluations using both the Coma Recovery Scale-Revised (CRS-R) and a vibrotactile P300 BCI paradigm. To use the BCI, patients had to perform an active mental task that required detecting specific stimuli while ignoring other stimuli. We analysed the reliability and the efficacy in the detection of command following resulting from the two methodologies.ResultsOver repetitive administrations, the BCI paradigm detected command following before the CRS-R in seven patients. Four clinically unresponsive patients consistently showed command following during the BCI assessments.ConclusionBrain-Computer Interface active paradigms might contribute to the evaluation of the level of consciousness, increasing the diagnostic precision of the clinical bedside approach.SignificanceThe integration of different diagnostic methods leads to a better knowledge and care for the DOC.

Emerging evidence supports that osteogenic differentiation of skeletal progenitors is a key determinant of overall bone formation and bone mass. Despite extensive studies showing the function of mitogen-activated protein kinases (MAPKs) in osteoblast differentiation, none of these studies show in vivo evidence of a role for MAPKs in osteoblast maturation subsequent to lineage commitment. Here, we describe how the extracellular signal-regulated kinase (ERK) pathway in osteoblasts controls bone formation by suppressing the mechanistic target of rapamycin (mTOR) pathway. We also show that, while ERK inhibition blocks the differentiation of osteogenic precursors when initiated at an early stage, ERK inhibition surprisingly promotes the later stages of osteoblast differentiation. Accordingly, inhibition of the ERK pathway using a small compound inhibitor or conditional deletion of the MAP2Ks Map2k1 (MEK1) and Map2k2 (MEK2), in mature osteoblasts and osteocytes, markedly increased bone formation due to augmented osteoblast differentiation. Mice with inducible deletion of the ERK pathway in mature osteoblasts also displayed similar phenotypes, demonstrating that this phenotype reflects continuous postnatal inhibition of late-stage osteoblast maturation. Mechanistically, ERK inhibition increases mitochondrial function and SGK1 phosphorylation via mTOR2 activation, which leads to osteoblast differentiation and production of angiogenic and osteogenic factors to promote bone formation. This phenotype was partially reversed by inhibiting mTOR. Our study uncovers a surprising dichotomy of ERK pathway functions in osteoblasts, whereby ERK activation promotes the early differentiation of osteoblast precursors, but inhibits the subsequent differentiation of committed osteoblasts via mTOR-mediated regulation of mitochondrial function and SGK1.

The P300-based brain–computer interfaces (BCIs) enable participants to communicate by decoding the electroencephalography (EEG) signal. Different regions of the brain correspond to various mental activities. Therefore, removing weak task-relevant and noisy channels through channel selection is necessary when decoding a specific type of activity from EEG. It can improve the recognition accuracy and reduce the training time of the subsequent models. This study proposes a novel block sparse Bayesian-based channel selection method for the P300 speller. In this method, we introduce block sparse Bayesian learning (BSBL) into the channel selection of P300 BCI for the first time and propose a regional smoothing BSBL (RSBSBL) by combining the spatial distribution properties of EEG. The RSBSBL can determine the number of channels adaptively. To ensure practicality, we design an automatic selection iteration strategy model to reduce the time cost caused by the inverse operation of the large-size matrix. We verified the proposed method on two public P300 datasets and on our collected datasets. The experimental results show that the proposed method can remove the inferior channels and work with the classifier to obtain high-classification accuracy. Hence, RSBSBL has tremendous potential for channel selection in P300 tasks.

Bone homeostasis only exists when the physical function of osteoblast and osteoclast stays in the balance between bone formation and resorption. Bone resorption occurs when the two processes are uncoupled, shifting the balance in favour of bone resorption. Excessive activation of osteoclasts leads to a range of osteolytic bone diseases including osteoporosis, aseptic prosthesis loosening, rheumatoid arthritis, and osteoarthritis. Receptor activator of nuclear factor kappa-B ligand (RANKL) and its downstream signaling pathways are recognized as key mediators that drive the formation and activation of osteoclastic function. Hence, osteoclast formation and/or its function remain as dominant targets for research and development of agents reaching the treatment towards osteolytic diseases. Chrysin (CHR) is a flavonoid with a wide range of anti-inflammatory and anti-tumor effects. However, its effect on osteoclasts remains unknown. In this study, we found the effects of CHR on inhibiting osteoclast differentiation which were assessed in terms of the number and size of TRAcP positive multinucleated osteoclasts (OCs). Further, the inhibitory effects of CHR on bone resorption and osteoclast fusion of pre-OC were assessed by hydroxyapatite resorption pit assay and F-actin belts staining; respectively. Western blotting analysis of RANKL-induced signaling pathways and immunofluorescence analysis for p65 nuclear translocation in response to RANKL-induced osteoclasts were used to analyze the mechanism of action of CHR affecting osteoclasts. Lastly, the murine calvarial osteolysis model revealed that CHR could protect against particle-induced bone destruction in vivo. Collectively, our data strongly suggested that CHR with its promising anti-tumor effects would also be a potential therapeutic agent for osteolytic diseases.

Osteoporosis is a serious public health problem that results in fragility fractures, especially in postmenopausal women. Because the current therapeutic strategy for osteoporosis has various side effects, a safer and more effective treatment is worth exploring. It is important to examine natural plant extracts during new drug design due to low toxicity. Mogrol is an aglycon of mogroside, which is the active component of Siraitia grosvenorii (Swingle) and exhibits anti-inflammatory, anticancer and neuroprotective effects. Here, we demonstrated that mogrol dose-dependently inhibited osteoclast formation and function. To confirm the mechanism, RNA sequencing (RNA-seq), real-time PCR (RT–PCR), immunofluorescence and Western blotting were performed. The RNA-seq data revealed that mogrol had an effect on genes involved in osteoclastogenesis. Furthermore, RT–PCR indicated that mogrol suppressed osteoclastogenesis-related gene expression, including CTSK, ACP5, MMP9 and DC-STAMP, in RANKL-induced bone marrow macrophages Western blotting demonstrated that mogrol suppressed osteoclast formation by blocking TNF receptor-associated factor 6 (TRAF6)-dependent activation of the mitogen-activated protein kinase nuclear factor-B (NF-κB) signaling pathway, which decreased two vital downstream transcription factors, the nuclear factor of activated T cells calcineurin-dependent 1 (NFATc1) and c-Fos proteins expression. Furthermore, mogrol dramatically reduced bone mass loss in postmenopausal mice. In conclusion, these data showed that mogrol may be a promising procedure for osteoporosis prevention or therapy.

Neurofibromatosis type I (NF1) is characterized by prominent skeletal abnormalities mediated in part by aberrant ERK pathway activation due to NF1 loss-of-function. Here, the authors report the MEKK2 is a key mediator of this aberrant ERK activation and that MEKK2 inhibitors, including ponatinib, ameliorate skeletal defects in a mouse model of NF1.

Runx2 is essential for tuning the generation of bone from skeletal stem cells (SSCs). Here, the authors demonstrate that the CK2/HAUSP pathway stabilizes RUNX2 protein thereby regulating the commitment of SSCs to osteoprogenitors as well as their subsequent maturation, and that inhibition of this pathway can block heterotopic ossification.

Adipose tissue, an energy storage and endocrine organ, is emerging as an essential player for ECM remodeling. Fibrosis is one of the hallmarks of obese adipose tissue, featuring excessive ECM deposition and enhanced collagen alignment. A variety of ECM components and ECM-related enzymes are produced by adipocytes and myofibroblasts in obese adipose tissue. Data from lineage-tracing models and a single-cell analysis indicate that adipocytes can transform or de-differentiate into myofibroblast/fibroblast-like cells. This de-differentiation process has been observed under normal tissue development and pathological conditions such as cutaneous fibrosis, wound healing, and cancer development. Accumulated evidence has demonstrated that adipocyte de-differentiation and myofibroblasts/fibroblasts play crucial roles in obesity-associated ECM remodeling and cancer progression. In this review, we summarize the recent progress in obesity-related ECM remodeling, the mechanism underlying adipocyte de-differentiation, and the function of obesity-associated ECM remodeling in cancer progression.

The shearer drum undertakes the main function of coal falling and loading, and picks distributed on it have a great impact on the performance of the drum. However, few studies have optimized the pick and drum at the same time. In this paper, parameters of pick and drum are considered as design variables, and the response functions of design variables are established based on the central composite experiment method. The optimal structural and working parameters of the pick and the drum of MG500/1130-WD shearer are obtained by using the multi-objective bat algorithm and multi-objective bat algorithm with grid, respectively. Comparing results of the two algorithms, the multi-objective bat algorithm with grid is more effective in improving the comprehensive performance of the drum. According to the optimized design variables, a coal mining test is carried out to verify the optimization effect of the algorithm. The result provides some theoretical references for the design and production of the drum and has some engineering application value.

Abstract Background Cardamonin, a chalcone isolated from Alpiniae katsumadai, has anti-inflammatory and anti-tumor activities. However, the molecular mechanism by which cardamonin inhibits breast cancer progression largely remains to be determined. Methods CCK-8 and Hoechst 33258 staining were used to detect cell growth and apoptosis, respectively. HIF-1α driven transcription was measured by luciferase reporter assay. Glucose uptake and lactate content were detected with 2-NBDG and L-Lactate Assay Kit. Cell metabolism assays were performed on Agilent’s Seahorse Bioscience XF96 Extracellular Flux Analyzer. Mitochondrial membrane potential was measured with JC-1 probe. DCFH-DA was used to measure ROS level. Protein expression was detected by western blotting assay. Immunohistochemistry was performed to measure the expression of HIF-1α, LDHA and CD31 in tumor tissues. Results Cardamonin inhibited growth of the triple negative breast cancer cell line MDA-MB-231 in vitro and in vivo by suppressing HIF-1α mediated cell metabolism. Cardamonin inhibited the expression of HIF-1α at mRNA and protein levels by repressing the mTOR/p70S6K pathway, and subsequently enhanced mitochondrial oxidative phosphorylation and induced reactive oxygen species (ROS) accumulation. We also found that cardamonin inhibited the Nrf2-dependent ROS scavenging system which further increased intracellular ROS levels. Eventually, accumulation of the intracellular ROS induced apoptosis in breast cancer cells. In addition, cardamonin treatment reduced glucose uptake as well as lactic acid production and efflux, suggesting its function in repressing the glycolysis process. Conclusions These results reveal novel function of cardamonin in modulating cancer cell metabolism and suppressing breast cancer progression, and suggest its potential for breast cancer treatment.

Abstract Background Increased collagen expression and deposition are associated with cancer progression and poor prognosis in breast cancer patients. However, function and regulation of membrane-associated collagen in breast cancer have not been determined. Collagen XIII is a type II transmembrane protein within the collagen superfamily. Experiments in tissue culture and knockout mouse models show that collagen XIII is involved in cell adhesion and differentiation of certain cell types. In the present study, we determined roles of collagen XIII in breast cancer progression and metastasis. Methods We analyzed the association of collagen XIII expression with breast cancer development and metastasis using published gene expression profiles generated from human breast cancer tissues. Utilizing gain- and loss- of function approaches and 3D culture assays, we investigated roles of collagen XIII in regulating invasive tumor growth. Using the tumorsphere/mammosphere formation assay and the detachment cell culture assay, we determined whether collagen XIII enhances cancer cell stemness and induces anoikis resistance. We also inhibited collagen XIII signaling with β1 integrin function-blocking antibody. Finally, using the lung colonization assay and the orthotopic mammary tumor model, we investigated roles of collagen XIII in regulating breast cancer colonization and metastasis. Cox proportional hazard (log-rank) test, two-sided Student’s t-test (two groups) and one-way ANOVA (three or more groups) analyses were used in this study. Results Collagen XIII expression is significantly higher in human breast cancer tissue compared with normal mammary gland. Increased collagen XIII mRNA levels in breast cancer tissue correlated with short distant recurrence free survival. We showed that collagen XIII expression promoted invasive tumor growth in 3D culture, enhanced cancer cell stemness, and induced anoikis resistance. Collagen XIII expression induced β1 integrin activation. Blocking β1 integrin activation significantly reduced collagen XIII-induced invasion and mammosphere formation. Importantly, silencing collagen XIII in MDA-MB-231 cells reduced lung colonization and metastasis. Conclusions Our results demonstrate a novel function of collagen XIII in promoting cancer metastasis, cell invasion, and anoikis resistance.

Osteoclasts mediate bone disruption in a number of degenerative bone diseases. Here, the authors show that miR-182 regulates osteoclastogenesis via PKR and IFN-beta signaling, is correlated with rheumatoid arthritis, and that its ablation or inhibition is protective against bone erosion in mouse models of osteoporosis or inflammatory arthritis.

Hyperactivation of HIF-1α is crucial in progression of triple-negative breast cancer, but how HIF-1α stability is maintained in a hypoxia-independent manner is unclear. Here, the authors show collagen prolyl-4-hydroylase 1 stabilises HIF-1α and is involved in chemoresistance in TNBC.

Considering that stress condition associated with osteoporosis, the hypothalamic-pituitary-adrenal (HPA) axis, which is essential for central stress response system, is implicated in regulating bone mass accrual. Melanocortin 2 receptor (MC2R), the receptor of adrenocorticotropic hormone is expressed in both adrenal gland cells and bone cells. To elucidate the role of HPA axis in bone metabolism, we assessed the skeletal phenotype of MC2R deficient mice (MC2R −/− mice). We first examined bone mineral density and cortical thickness of femur using dual x-ray absorptiometry and micro-computed tomography. We then conducted histomorphometric analysis to calculate the static and dynamic parameters of vertebrae in MC2R −/− mice. The levels of osteoblastic marker genes were examined by quantitative PCR in primary osteoblasts derived from MC2R −/− mice. Based on these observations, bone mineral density of femur in MC2R −/− mice was increasing relative to litter controls. Meanwhile, the thickness of cortical bone of femur in MC2R −/− mice was remarkably elevated. Moreover, serum osteocalcin level was drastically raised in MC2R −/− mice. However, bone histomorphometry revealed that static and dynamic parameters reflecting bone formation and resorption were unchanged in vertebrae of MC2R −/− mice compared to the control, indicating that MC2R function may be specific to appendicular bone than axis bone. Taken together, the HPA axis due to deletion of MC2R is involved in bone metabolism.

Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor and cognitive disabilities. Recent research has shown that non-invasive brain-computer interface (BCI) technology could help assess these patients’ cognitive functions and command following abilities. 20 DOC patients participated in the study and performed 10 vibro-tactile P300 BCI sessions over 10 days with 8–12 runs each day. Vibrotactile tactors were placed on the each patient’s left and right wrists and one foot. Patients were instructed, via earbuds, to concentrate and silently count vibrotactile pulses on either their left or right wrist that presented a target stimulus and to ignore the others. Changes of the BCI classification accuracy were investigated over the 10 days. In addition, the Coma Recovery Scale-Revised (CRS-R) score was measured before and after the 10 vibro-tactile P300 sessions. In the first run, 10 patients had a classification accuracy above chance level (>12.5%). In the best run, every patient reached an accuracy ≥60%. The grand average accuracy in the first session for all patients was 40%. In the best session, the grand average accuracy was 88% and the median accuracy across all sessions was 21%. The CRS-R scores compared before and after 10 VT3 sessions for all 20 patients, are showing significant improvement (p = 0.024). Twelve of the twenty patients showed an improvement of 1 to 7 points in the CRS-R score after the VT3 BCI sessions (mean: 2.6). Six patients did not show a change of the CRS-R and two patients showed a decline in the score by 1 point. Every patient achieved at least 60% accuracy at least once, which indicates successful command following. This shows the importance of repeated measures when DOC patients are assessed. The improvement of the CRS-R score after the 10 VT3 sessions is an important issue for future experiments to test the possible therapeutic applications of vibro-tactile and related BCIs with a larger patient group.

Downscaling considerably alleviates the drawbacks of regional climate simulation by general circulation models (GCMs). However, little information is available regarding the downscaling using machine learning methods, specifically at hydrological basin scale. This study developed multiple machine learning (ML) downscaling models, based on a Bayesian model average (BMA), to downscale the precipitation simulation of 8 Coupled Model Intercomparison Project Phase 5 (CMIP5) models using model output statistics (MOS) for the years 1961–2005 in the upper Han River basin. A series of statistical metrics, including Pearson’s correlation coefficient (PCC), root mean squared error (RMSE), and relative bias (Rbias), were used for evaluation and comparative analyses. Moreover, the BMA and the best ML downscaling model were used to downscale precipitation in the 21st century under Representative Concentration Pathway 4.5 (RCP4.5) and RCP8.5 scenarios. The results show the following: (1) The performance of the BMA ensemble simulation is clearly better than that of the individual models and the simple mean model ensemble (MME). The PCC reaches 0.74, and the RMSE is reduced by 28%–60% for all the GCMs and 33% compared to the MME. (2) The downscaled models greatly improved station simulation performance. Support vector machine for regression (SVR) was superior to multilayer perceptron (MLP) and random forest (RF). The downscaling results based on the BMA ensemble simulation and SVR models were regarded as the best performing overall (PCC, RMSE, and Rbias were 0.82, 35.07, mm and −5.45%, respectively). (3) Based on BMA and SVR models, the projected precipitations show a weak increasing trend on the whole under RCP4.5 and RCP8.5. Specifically, the average rainfall during the mid- (2040–2069) and late (2070–2099) 21st century increased by 3.23% and 1.02%, respectively, compared to the base year (1971–2000) under RCP4.5, while they increased by 4.25% and 8.30% under RCP8.5. Additionally, the magnitude of changes during winter and spring was higher than that during summer and autumn. Furthermore, future work is recommended to study the improvement of downscaling models and the effect of local climate.

Background. Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Method. Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were assessed by the Fugl-Meyer Assessment (FMA) of motor function. Results. The average improvement score of the BCI group was 3.5, which was higher than that of the control group (0.9). The active EEG patterns of the four patients in the BCI group whose FMA scores increased gradually became centralized and shifted to sensorimotor areas and premotor areas throughout the study. Conclusions. Study results showed evidence that patients in the BCI group achieved larger functional improvements than those in the control group and that the BCI-FES system is effective in restoring motor function to upper extremities in stroke patients. This study provides a more autonomous approach than traditional treatments used in stroke rehabilitation.

Breast cancer development is associated with macrophage infiltration and differentiation in the tumor microenvironment. Our previous study highlights the crucial function of reactive oxygen species (ROS) in enhancing macrophage infiltration during the disruption of mammary tissue polarity. However, the regulation of ROS and ROS-associated macrophage infiltration in breast cancer has not been fully determined. Previous studies identified retinoid orphan nuclear receptor alpha (RORα) as a potential tumor suppressor in human breast cancer. In the present study, we showed that retinoid orphan nuclear receptor alpha (RORα) significantly decreased ROS levels and inhibited ROS-mediated cytokine expression in breast cancer cells. RORα expression in mammary epithelial cells inhibited macrophage infiltration by repressing ROS generation in the co-culture assay. Using gene co-expression and chromatin immunoprecipitation (ChIP) analyses, we identified complex I subunits NDUFS6 and NDUFA11 as RORα targets that mediated its function in suppressing superoxide generation in mitochondria. Notably, the expression of RORα in 4T1 cells significantly inhibited cancer metastasis, reduced macrophage accumulation, and enhanced M1-like macrophage differentiation in tumor tissue. In addition, reduced RORα expression in breast cancer tissue was associated with an increased incidence of cancer metastasis. These results provide additional insights into cancer-associated inflammation, and identify RORα as a potential target to suppress ROS-induced mammary tumor progression.

The effects of cholesterol-lowering drugs, including those that reduce cholesterol synthesis (statins) and those that reduce cholesterol absorption (ezetimibe), on cholesterol absorption and synthesis are well understood. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors are a novel class of cholesterol-lowering drugs that robustly reduce LDL-cholesterol (LDL-C), but little is known about their effects on cholesterol absorption and synthesis. We evaluated how treatment with evolocumab, a fully human monoclonal IgG2 antibody to PCSK9, affects markers of cholesterol synthesis and absorption by measuring these markers in patients from an evolocumab clinical trial. At 2 weeks, changes in β-sitosterol/total cholesterol (TC) from baseline were 4% for placebo, 10% for evolocumab 140 mg (nonsignificant vs. placebo), and 26% for evolocumab 420 mg (P < 0.001 vs. placebo). Changes in campesterol/TC at week 2, relative to baseline between placebo and evolocumab, were all nonsignificant. Evolocumab had a modest effect on markers of cholesterol synthesis. At 2 weeks, changes in desmosterol/TC were 1% for placebo, 7% for evolocumab 140 mg (nonsignificant vs. placebo), and 15% for evolocumab 420 mg (P < 0.01 vs. placebo). Changes from baseline in lathosterol/TC at week 2 between placebo and evolocumab were nonsignificant. These results suggest that evolocumab has a modest effect on cholesterol synthesis and absorption despite significant LDL-C lowering.

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not show any sign of awareness of their environment, while minimally conscious state (MCS) patients show reproducible but fluctuating signs of awareness. Some patients, although with remaining cognitive abilities, are not able to exhibit overt voluntary responses at the bedside and may be misdiagnosed as UWS. Several studies investigated functional neuroimaging and neurophysiology as an additional tool to evaluate the level of consciousness and to detect covert command following in DOC. Most of these studies are based on auditory stimulation, neglecting patients suffering from decreased or absent hearing abilities. In the present study, we aim to assess the response to a P3-based paradigm in 40 patients with DOC and 12 healthy participants using auditory (AEP) and vibrotactile (VTP) stimulation. To this end, an EEG-based brain-computer interface was used at DOC patient’s bedside. We compared the significance of the P3 performance (i.e., the interpretation of significance of the evoked P3 response) as obtained by ‘direct processing’ (i.e., theoretical-based significance threshold) and ‘offline processing’ (i.e., permutation-based single subject level threshold). We evaluated whether the P3 performances were dependent on clinical variables such as diagnosis (UWS and MCS), aetiology and time since injury. Last we tested the dependency of AEP and VTP performances at the single subject level. Direct processing tends to overestimate P3 performance. We did not find any difference in the presence of a P3 performance according to the level of consciousness (UWS vs. MCS) or the aetiology (traumatic vs. non-traumatic brain injury). The performance achieved at the AEP paradigm was independent from what was achieved at the VTP paradigm, indicating that some patients performed better on the AEP task while others performed better on the VTP task. Our results support the importance of using multimodal approaches in the assessment of DOC patients in order to optimise the evaluation of patient’s abilities.

Collagen prolyl 4-hydroxylase 1 (C-P4H1) is an α-ketoglutarate (α-KG)-dependent dioxygenase that catalyzes 4-hydroxylation of proline on collagen. C-P4H1-induced prolyl hydroxylation is required for proper collagen deposition and cancer metastasis. Therefore, targeting C-P4H1 is considered a potential therapeutic strategy for collagen-related cancer progression and metastasis. However, no C-P4H1 inhibitors are available for clinical testing, and the high content assay is currently not available for C-P4H1 inhibitor screening. In the present study, we developed a high-throughput screening assay by quantifying succinate, a byproduct of C-P4H-catalyzed hydroxylation. C-P4H1 is the major isoform of collagen prolyl 4-hydroxylases (CP4Hs) that contributes the majority prolyl 4-hydroxylase activity. Using C-P4H1 tetramer purified from the eukaryotic expression system, we showed that the Succinate-GloTM Hydroxylase assay was more sensitive for measuring C-P4H1 activity compared with the hydroxyproline colorimetric assay. Next, we performed high-throughput screening with the FDA-approved drug library and identified several new C-P4H1 inhibitors, including Silodosin and Ticlopidine. Silodosin and Ticlopidine inhibited C-P4H1 activity in a dose-dependent manner and suppressed collagen secretion and tumor invasion in 3D tissue culture. These C-P4H1 inhibitors provide new agents to test clinical potential of targeting C-P4H1 in suppressing cancer progression and metastasis.