Facet-Dependent Surface Restructuring on Nickel (Oxy)hydroxides: A Self-Activation Process for Enhanced Oxygen Evolution Reaction.

Unraveling the catalyst surface structure and behavior during reactions is essential for both mechanistic understanding and performance optimization. Here we report a phenomenon of facet-dependent surface restructuring intrinsic to ß-Ni(OH)2 catalysts during oxygen evolution reaction (OER), discovered by the correlative ex situ and operando characterization. The ex situ study after OER reveals ß-Ni(OH)2 restructuring at the edge facets to form nanoporous Ni1-xO, which is Ni deficient containing Ni3+ species. Operando liquid transmission electron microscopy (TEM) and Raman spectroscopy further identify the active role of the intermediate ß-NiOOH phase in both the OER catalysis and Ni1-xO formation, pinpointing the complete surface restructuring pathway. Such surface restructuring is shown to effectively increase the exposed active sites, accelerate Ni oxidation kinetics, and optimize *OH intermediate bonding energy toward fast OER kinetics, which leads to an extraordinary activity enhancement of ∼16-fold. Facilitated by such a self-activation process, the specially prepared ß-Ni(OH)2 with larger edge facets exhibits a 470-fold current enhancement than that of the benchmark IrO2, demonstrating a promising way to optimize metal-(oxy)hydroxide-based catalysts.

Uncertainty-aware refinement framework for ovarian tumor segmentation in CECT volume.

BACKGROUND: Ovarian cancer is a highly lethal gynecological disease. Accurate and automated segmentation of ovarian tumors in contrast-enhanced computed tomography (CECT) images is crucial in the radiotherapy treatment of ovarian cancer, enabling radiologists to evaluate cancer progression and develop timely therapeutic plans. However, automatic ovarian tumor segmentation is challenging due to factors such as inhomogeneous background, ambiguous tumor boundaries, and imbalanced foreground-background, all of which contribute to high predictive uncertainty for a segmentation model. PURPOSE: To tackle these challenges, we propose an uncertainty-aware refinement framework that aims to estimate and refine regions with high predictive uncertainty for accurate ovarian tumor segmentation in CECT images. METHODS: To this end, we first employ an approximate Bayesian network to detect coarse regions of interest (ROIs) of both ovarian tumors and uncertain regions. These ROIs allow a subsequent segmentation network to narrow down the search area for tumors and prioritize uncertain regions, resulting in precise segmentation of ovarian tumors. Meanwhile, the framework integrates two guidance modules that learn two implicit functions capable of mapping query features sampled according to their uncertainty to organ or boundary manifolds, guiding the segmentation network to facilitate information encoding of uncertain regions. RESULTS: Firstly, 367 CECT images are collected from the same hospital for experiments. Dice score, Jaccard, Recall, Positive predictive value (PPV), 95% Hausdorff distance (HD95) and Average symmetric surface distance (ASSD) for the testing group of 77 cases are 86.31%, 73.93%, 83.95%, 86.03%, 15.17  mm and 2.57  mm, all of which are significantly better than that of the other state-of-the-art models. And results of visual comparison shows that the compared methods have more mis-segmentation than our method. Furthermore, our method achieves a Dice score that is at least 20% higher than the Dice scores of other compared methods when tumor volumes are less than 20 cm 3 $^3$ , indicating better recognition ability to small regions by our method. And then, 38 CECT images are collected from another hospital to form an external testing group. Our approach consistently outperform the compared methods significantly, with the external testing group exhibiting substantial improvements across key evaluation metrics: Dice score (83.74%), Jaccard (69.55%), Recall (82.12%), PPV (81.61%), HD95 (12.31 mm), and ASSD (2.32 mm), robustly establishing its superior performance. CONCLUSIONS: Experimental results demonstrate that the framework significantly outperforms the compared state-of-the-art methods, with decreased under- or over-segmentation and better small tumor identification. It has the potential for clinical application.

Decreased FoxO1 expression contributes to facet joint osteoarthritis pathogenesis by impairing chondrocyte migration and extracellular matrix synthesis.

Facet joint osteoarthritis (FJOA), a condition commonly observed in individuals of middle to old age, has been relatively under-researched compared to other subtypes of osteoarthritis (OA). This study investigated the role of transcription factor FoxO1 in FJOA using a Col2a1-creERT knock-in mouse model. It was found that FoxO1 deletion led to severe osteoarthritic changes, indicating that FoxO1 played a critical role in cartilage homeostasis. Transcriptome sequencing was performed on degenerated cartilage from FoxO1-deleted mice. This process identified differentially expressed genes (DEGs), offering insights into the molecular mechanisms underlying FJOA. Bioinformatics analysis, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and protein-protein interaction (PPI) network analysis, identified Itgb3, Itga1, Itga6, Itga7, Itga8, Itga10, Col1a1, and Il6, as potential key contributors to FJOA after FoxO1 deletion. Importantly, overexpression of Itgb3 and inhibition of Il6 counteracted FoxO1 knockdown-induced impairments in chondrocyte migration and extracellular matrix synthesis, respectively. This study discovered FoxO1 as a key regulator of the pathogenesis of FJOA, helped unravel the complex molecular mechanisms underlying FJOA, and contributed to the development of promising therapeutic avenues toward FJOA.

Breast Fibroglandular Tissue Segmentation for Automated BPE Quantification With Iterative Cycle-Consistent Semi-Supervised Learning.

Background Parenchymal Enhancement (BPE) quantification in Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast cancer diagnosis and prognosis. However, the emerging deep learning-based breast fibroglandular tissue segmentation, a crucial step in automated BPE quantification, often suffers from limited training samples with accurate annotations. To address this challenge, we propose a novel iterative cycle-consistent semi-supervised framework to leverage segmentation performance by using a large amount of paired pre-/post-contrast images without annotations. Specifically, we design the reconstruction network, cascaded with the segmentation network, to learn a mapping from the pre-contrast images and segmentation predictions to the post-contrast images. Thus, we can implicitly use the reconstruction task to explore the inter-relationship between these two-phase images, which in return guides the segmentation task. Moreover, the reconstructed post-contrast images across multiple auto-context modeling-based iterations can be viewed as new augmentations, facilitating cycle-consistent constraints across each segmentation output. Extensive experiments on two datasets with various data distributions show great segmentation and BPE quantification accuracy compared with other state-of-the-art semi-supervised methods. Importantly, our method achieves 11.80 times of quantification accuracy improvement along with 10 times faster, compared with clinical physicians, demonstrating its potential for automated BPE quantification. The code is available at https://github.com/ZhangJD-ong/Iterative-Cycle-consistent-Semi-supervised-Learning-for-fibroglandular-tissue-segmentation.

A robust and efficient AI assistant for breast tumor segmentation from DCE-MRI via a spatial-temporal framework.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows screening, follow up, and diagnosis for breast tumor with high sensitivity. Accurate tumor segmentation from DCE-MRI can provide crucial information of tumor location and shape, which significantly influences the downstream clinical decisions. In this paper, we aim to develop an artificial intelligence (AI) assistant to automatically segment breast tumors by capturing dynamic changes in multi-phase DCE-MRI with a spatial-temporal framework. The main advantages of our AI assistant include (1) robustness, i.e., our model can handle MR data with different phase numbers and imaging intervals, as demonstrated on a large-scale dataset from seven medical centers, and (2) efficiency, i.e., our AI assistant significantly reduces the time required for manual annotation by a factor of 20, while maintaining accuracy comparable to that of physicians. More importantly, as the fundamental step to build an AI-assisted breast cancer diagnosis system, our AI assistant will promote the application of AI in more clinical diagnostic practices regarding breast cancer.

TS-DSANN: Texture and shape focused dual-stream attention neural network for benign-malignant diagnosis of thyroid nodules in ultrasound images.

Recently, accurate diagnosis of thyroid nodules has played a critical role in precision medicine and healthcare system management. Due to complicated changes in ultrasound features of texture, and similar visual appearance of benign-malignant nodules, the identification of cancerous thyroid lesions from a given ultrasound image still faces challenges for even experienced radiologists. Learning-based computer-aided diagnosis (CAD) systems have accordingly attracted more and more attention recently. However, little research is committed to developing a deep learning-based CAD system that has greater conformity with radiologists' diagnostic decision-making. In this study, we devise a texture and shape focused dual-stream attention neural network, dubbed TS-DSANN. Specifically, in the texture focused stream, we utilize the ImageNet pre-trained ResNet34 to guide the network to recognize texture-related nodule attributes. Meanwhile, in the shape focused stream, in addition to using ResNet34 backbone, jointly learning from scratch with the contour obtained by contour detection module to enhance the extraction of shape features. Afterward, we employ a concatenation operation to aggregate the abovementioned two stream networks for capturing richer and more representative features. Finally, we further utilize an online class activation mapping mechanism to assist the dual-stream network in generating a localization heatmap to obtain more visualization attention to the nodule from the whole image, and supervise classifier's attention in decision-making. Experimental results conducted on the two-center thyroid nodule ultrasound datasets verify that our proposed method has improved the classification performance, superior to the state-of-the-art methods.

Positioning and design by computed tomography imaging in neuroendoscopic surgery of patients with chronic subdural hematoma.

BACKGROUND: Neuroendoscopy is a very useful technique to Chronic Subdural Hematoma (CSH). But how to achieve the goal of treatment more minimally invasive? AIM: To develop a simple, fast and accurate preoperative planning method in our way for endoscopic surgery of patients with CSH. METHODS: From June 2018 to May 2020, forty-two patients with CSH, admitted to our hospital, were performed endoscopic minimally invasive surgery; computed tomography (CT) imaging was employed to locate the intracerebral hematoma and select the appropriate endoscopic approach before the endoscopic surgery. The clinical data and treatment efficacy were analyzed. RESULTS: According to the learning of CT scanning images, the surgeon can accurately design the best minimally invasive neuroendoscopic surgical approach and realize the precise positioning and design of the drilling site of the skull and the size of the bone window, so as to provide the most effective operation space with the smallest bone window. In this group, the average operation time was only about 1 h, and the clearance rate of hematoma was about 95%. CONCLUSION: Patients with CSH can achieve good therapeutic effect by using our way to positioning and design to assist the operation of CSH according to CT scan and image, and our way is very useful and necessary.

Semi-Supervised Standard-Dose PET Image Generation via Region-Adaptive Normalization and Structural Consistency Constraint.

Positron Emission Tomography (PET) is an important nuclear medical imaging technique, and has been widely used in clinical applications, e.g., tumor detection and brain disease diagnosis. As PET imaging could put patients at risk of radiation, the acquisition of high-quality PET images with standard-dose tracers should be cautious. However, if dose is reduced in PET acquisition, the imaging quality could become worse and thus may not meet clinical requirement. To safely reduce the tracer dose and also maintain high quality of PET imaging, we propose a novel and effective approach to estimate high-quality Standard-dose PET (SPET) images from Low-dose PET (LPET) images. Specifically, to fully utilize both the rare paired and the abundant unpaired LPET and SPET images, we propose a semi-supervised framework for network training. Meanwhile, based on this framework, we further design a Region-adaptive Normalization (RN) and a structural consistency constraint to track the task-specific challenges. RN performs region-specific normalization in different regions of each PET image to suppress negative impact of large intensity variation across different regions, while the structural consistency constraint maintains structural details during the generation of SPET images from LPET images. Experiments on real human chest-abdomen PET images demonstrate that our proposed approach achieves state-of-the-art performance quantitatively and qualitatively.

A novel role of lactate: Promotion of Akt-dependent elongation of microglial process.

As a key component of the innate immune system, over-activation of microglia that occurs in nervous system diseases is usually accompanied by retraction of their branched processes. Reversal of microglial process retraction is a potential strategy to prevent neuroinflammation. In our previous studies, we reported some molecules that can promote the elongation of microglial processes under in vitro and in vivo conditions, such as butyrate, ß-hydroxybutyrate, sulforaphane, diallyl disulfide, compound C, and KRIBB11. Here, we found that lactate, a molecule that mimics endogenous lactic acid and has been shown to suppress neuroinflammation, reversibly triggered significant elongations of processes in microglia under cultured and in vivo conditions. Pretreatment with lactate also prevented lipopolysaccharide (LPS)-induced shortening of microglial processes under cultured and in vivo conditions, pro-inflammatory responses in primary cultured microglia and prefrontal cortex, and depression-like behaviors in mice. Mechanistic studies revealed that incubation with lactate increased phospho-Akt levels in primary cultured microglia and inhibition of Akt blocked the pro-elongation effect of lactate on the microglial process under cultured and in vivo conditions, suggesting that the regulatory effect of lactate on the microglial process is dependent on activation of Akt. Inhibition of Akt also abolished the preventive effect of lactate on LPS-induced inflammatory responses in primary cultured microglia and prefrontal cortex and on LPS-induced depression-like behaviors in mice. Overall, these results demonstrate that lactate can induce Akt-mediated elongation of the microglial process, which appropriately contributes to the inhibition of microglia-mediated neuroinflammation.

BowelNet: Joint Semantic-Geometric Ensemble Learning for Bowel Segmentation From Both Partially and Fully Labeled CT Images.

Accurate bowel segmentation is essential for diagnosis and treatment of bowel cancers. Unfortunately, segmenting the entire bowel in CT images is quite challenging due to unclear boundary, large shape, size, and appearance variations, as well as diverse filling status within the bowel. In this paper, we present a novel two-stage framework, named BowelNet, to handle the challenging task of bowel segmentation in CT images, with two stages of 1) jointly localizing all types of the bowel, and 2) finely segmenting each type of the bowel. Specifically, in the first stage, we learn a unified localization network from both partially- and fully-labeled CT images to robustly detect all types of the bowel. To better capture unclear bowel boundary and learn complex bowel shapes, in the second stage, we propose to jointly learn semantic information (i.e., bowel segmentation mask) and geometric representations (i.e., bowel boundary and bowel skeleton) for fine bowel segmentation in a multi-task learning scheme. Moreover, we further propose to learn a meta segmentation network via pseudo labels to improve segmentation accuracy. By evaluating on a large abdominal CT dataset, our proposed BowelNet method can achieve Dice scores of 0.764, 0.848, 0.835, 0.774, and 0.824 in segmenting the duodenum, jejunum-ileum, colon, sigmoid, and rectum, respectively. These results demonstrate the effectiveness of our proposed BowelNet framework in segmenting the entire bowel from CT images.

Percutaneous vertebral-disc plasty for thoracolumbar very severe osteoporotic vertebral compression fractures: A randomized controlled study.

Purpose: To compare the clinical outcomes and radiological parameters of patients undergoing percutaneous vertebroplasty (PVP) versus those undergoing percutaneous vertebral-disc plasty (PVDP) for back pain, segmental instability, and kyphosis due to thoracolumbar very severe osteoporotic vertebral compression fractures (vsOVCFs). Methods: This prospective randomized controlled study included elderly patients with thoracolumbar vsOVCFs. All the patients were randomly allocated into the PVP group (who underwent conventional PVP) and the PVDP group (who underwent PVP combined percutaneous cement discoplasty). The visual analogue scale (VAS), Oswestry Disability Index (ODI), local kyphosis angle, and disc height were recorded preoperatively and postoperatively. Results: Significant postoperative improvements in the VAS, ODI, and the local kyphosis angle (LKA) were shown, compared with the preoperative values in both groups (p < 0.05). The average VAS, ODI, and LKA for patients in the PVP group were increased compared to those in the PVDP group observed at the last follow-up (p < 0.05). The DHA, DHP, and LKA were seen to be maintained in the PVDP group at the last follow-up (p > 0.05). The change was significantly lower in the PVDP group at the last follow-up in those parameters (p < 0.05). Conclusion: PVDP may be a feasible and effective technique for the treatment of very severe OVCFs, that can restore intervertebral height, provide segmental stabilizing and relieve back pain in the short term.

Potential therapeutic effects and pharmacological evidence of sinomenine in central nervous system disorders.

Sinomenine is a natural compound extracted from the medicinal plant Sinomenium acutum. Its supplementation has been shown to present benefits in a variety of animal models of central nervous system (CNS) disorders, such as cerebral ischemia, intracerebral hemorrhage, traumatic brain injury (TBI), Alzheimer's disease (AD), Parkinson's disease (PD), epilepsy, depression, multiple sclerosis, morphine tolerance, and glioma. Therefore, sinomenine is now considered a potential agent for the prevention and/or treatment of CNS disorders. Mechanistic studies have shown that inhibition of oxidative stress, microglia- or astrocyte-mediated neuroinflammation, and neuronal apoptosis are common mechanisms for the neuroprotective effects of sinomenine. Other mechanisms, including activation of nuclear factor E2-related factor 2 (Nrf2), induction of autophagy in response to inhibition of protein kinase B (Akt)-mammalian target of rapamycin (mTOR), and activation of cyclic adenosine monophosphate-response element-binding protein (CREB) and brain-derived neurotrophic factor (BDNF), may also mediate the anti-glioma and neuroprotective effects of sinomenine. Sinomenine treatment has also been shown to enhance dopamine receptor D2 (DRD2)-mediated nuclear translocation of αB-crystallin (CRYAB) in astrocytes, thereby suppressing neuroinflammation via inhibition of Signal Transducer and Activator of Transcription 3 (STAT3). In addition, sinomenine supplementation can suppress N-methyl-D-aspartate (NMDA) receptor-mediated Ca2+ influx and induce γ-aminobutyric acid type A (GABAA) receptor-mediated Cl- influx, each of which contributes to the improvement of morphine dependence and sleep disturbance. In this review, we outline the pharmacological effects and possible mechanisms of sinomenine in CNS disorders to advance the development of sinomenine as a new drug for the treatment of CNS disorders.

Comprehensive insights into the function and molecular and pharmacological regulation of neuron-derived orphan receptor 1, an orphan receptor.

Neuron-derived orphan receptor 1 (NOR1), also called nuclear receptor subfamily 4 group A member 3 (NR4A3), is a nuclear receptor belonging to the NR4A family. Since no endogenous ligand has been identified to date, NOR1 is also referred to as an orphan receptor. NOR1 is expressed in a variety of cells and tissues, including neurons, vascular smooth muscle cells, T lymphocytes, dendritic cells, tumor cells, heart, liver, and pancreas. Because NOR1 was first identified in apoptotic neurons, it is functionally associated with the regulation of cell migration and the growth of neuronal synapses. In-depth studies have shown that NOR1 can be edited by the immediate early gene and functions as a transcription factor. NOR1 has been shown to be rapidly induced by a number of stimulants including growth factors, fatty acids, and neurotransmitters. Elevated NOR1 levels may be involved in a number of pathophysiological processes. These include regulation of cellular apoptosis and regeneration, neuron formation, contextual fearing memory, inflammation, vascular smooth muscle proliferation, insulin secretion, and tumor development, whereby NOR1 mediates the pathogenesis of numerous diseases such as cerebral ischemia, depression, post-traumatic stress disorder, atherosclerosis, abdominal aortic aneurysm, cardiac hypertrophy, diabetes, osteoarthritis, rheumatoid arthritis, and cancer. However, to date, comprehensive insights into the function of NOR1 are not available in sources published online. In this review, we provide a brief overview of the function and molecular and pharmacological regulation of NOR1 in various pathological or physiological conditions to advance the development of NOR1 as a novel target for disease treatment.

A review for the pharmacological effects of paeoniflorin in the nervous system.

Paeoniflorin, a terpenoid glycoside compound extracted from Paeonia lactiflora Pall, shows preventive and therapeutic effects in various types of nervous system disorders. However, to date, no comprehensive knowledge on the pharmacological effects of paeoniflorin on the nervous system is available online. Clarification of this issue may be useful for the development of paeoniflorin as a new drug for the treatment of nervous system disorders. To this end, the authors summarize the pharmacological aspects of paeoniflorin and its possible mechanisms, such as restoration of mitochondrial function; inhibition of neuroinflammation, oxidative stress, and cellular apoptosis; activation of adenosine A1 receptor, cAMP response element-binding protein (CREB) and extracellular signal-regulated kinase 1/2 (ERK1/2); or enhancement of brain-derived neurotrophic factor and serotonin function, in the prevention of disorders such as cerebral ischemia, subarachnoid hemorrhage, vascular dementia, Alzheimer's disease, Parkinson's disease, depression, post-traumatic syndrome disorder, and epilepsy, by reviewing the previously published literature.

Identification of hub genes in the subacute spinal cord injury in rats.

BACKGROUND: Spinal cord injury (SCI) is a common trauma in clinical practices. Subacute SCI is mainly characterized by neuronal apoptosis, axonal demyelination, Wallerian degeneration, axonal remodeling, and glial scar formation. It has been discovered in recent years that inflammatory responses are particularly important in subacute SCI. However, the mechanisms mediating inflammation are not completely clear. METHODS: The gene expression profiles of GSE20907, GSE45006, and GSE45550 were downloaded from the GEO database. The models of the three gene expression profiles were all for SCI to the thoracic segment of the rat. The differentially expressed genes (DEGs) and weighted correlation network analysis (WGCNA) were performed using R software, and functional enrichment analysis and protein-protein interaction (PPI) network were performed using Metascape. Module analysis was performed using Cytoscape. Finally, the relative mRNA expression level of central genes was verified by RT-PCR. RESULTS: A total of 206 candidate genes were identified, including 164 up-regulated genes and 42 down-regulated genes. The PPI network was evaluated, and the candidate genes enrichment results were mainly related to the production of tumor necrosis factors and innate immune regulatory response. Twelve core genes were identified, including 10 up-regulated genes and 2 down-regulated genes. Finally, seven hub genes with statistical significance in both the RT-PCR results and expression matrix were identified, namely Itgb1, Ptprc, Cd63, Lgals3, Vav1, Shc1, and Casp4. They are all related to the activation process of microglia. CONCLUSION: In this study, we identified the hub genes and signaling pathways involved in subacute SCI using bioinformatics methods, which may provide a molecular basis for the future treatment of SCI.

Codon-optimized FAM132b gene therapy prevents dietary obesity by blockading adrenergic response and insulin action.

BACKGROUND: FAM132b (myonectin) has been identified as a muscle-derived myokine with exercise and has hormone activity in circulation to regulate iron homeostasis and lipid metabolism via unknown receptors. Here, we aim to explore the potential of adeno-associated virus to deliver FAM132b in vivo to develop a gene therapy against obesity. METHODS: Adeno-associated virus AAV9 were engineered to induce overexpression of FAM132b with two mutations, A136T and P159A. Then, AAV9 was delivered into high-fat diet mice through tail vein, and glucose homeostasis and obesity development of mice were observed. Methods of structural biology were used to predict the action site or receptor of the FAM132b mutant. RESULTS: Treatment of high-fat diet-fed mice with AAV9 improved glucose intolerance and insulin resistance, and resulted in reductions in body weight, fat depot, and adipocyte size. Codon-optimized FAM132b (coFAM132b) reduced the glycemic response to epinephrine (EPI) in the whole body and increased the lipolytic response to EPI in adipose tissues. However, FAM132b knockdown by shRNA significantly increased the glycemic response to EPI in vivo and reduced adipocyte response to EPI and adipose tissue browning. Structural analysis predicted that the FAM132b mutant with A136T and P159A may form a weak bond with ß2 adrenergic receptor (ADRB2) and may have more affinity for insulin and insulin-receptor complexes. CONCLUSIONS: Our study underscores the potential of FAM132b gene therapy with codon optimization to treat obesity by modulating the adrenergic response and insulin action. Both structural biological analysis and in vivo experiments suggest that the adrenergic response and insulin action are most likely blockaded by FAM132b mutants.

Gene expression profile associated with Asmt knockout-induced depression-like behaviors and exercise effects in mouse hypothalamus.

Sleep disorder caused by abnormal circadian rhythm is one of the main symptoms and risk factors of depression. As a known hormone regulating circadian rhythms, melatonin (MT) is also namely N-acetyl-5-methoxytryptamine. N-acetylserotonin methyltransferase (Asmt) is the key rate-limiting enzyme of MT synthesis and has been reportedly associated with depression. Although 50-90% of patients with depression have sleep disorders, there are no effective treatment ways in the clinic. Exercise can regulate circadian rhythm and play an important role in depression treatment. In the present study, we showed that Asmt knockout induced depression-like behaviors, which were ameliorated by swimming exercise. Moreover, swimming exercise increased serum levels of MT and 5-hydroxytryptamine (5-HT) in Asmt knockout mice. In addition, the microarray data identified 10 differentially expressed genes (DEGs) in KO mice compared with WT mice and 29 DEGs in KO mice after swimming exercise. Among the DEGs, the direction and magnitude of change in epidermal growth factor receptor pathway substrate 8-like 1 (Eps8l1) and phospholipase C-ß 2 (Plcb2) were confirmed by qRT-PCR partly. Subsequent bioinformatic analysis showed that these DEGs were enriched significantly in the p53 signaling pathway, long-term depression and estrogen signaling pathway. In the protein-protein interaction (PPI) networks, membrane palmitoylated protein 1 (Mpp1) and p53-induced death domain protein 1 (Pidd1) were hub genes to participate in the pathological mechanisms of depression and exercise intervention. These findings may provide new targets for the treatment of depression.

Simplified Chinese Version of the Spinal Instability Neoplastic Score in Evaluating Patients with Metastatic Spinal Tumor: A Cross-Cultural Adaptation and Validation.

OBJECTIVE: To translate the original English version of the Spinal Instability Neoplastic Score (SINS) into simplified Chinese, adapt it cross-culturally, validate its psychometric properties in measuring spinal instability in patients with metastatic spinal tumors in the Chinese mainland, examine the reliability and validity to demonstrate its accuracy and applicability in clinical practice. METHODS: Patients diagnosed with metastatic spinal disease between January 2016 and January 2020 were recruited. The number of participants was advised to be at least 50 for appropriate analysis of reliability, construct validity, as well as ceiling or floor effects, and recruitment of 100 patients was advised for internal consistency analysis. The study was conducted in two phases: first, the SINS was translated into simplified Chinese; second, the factor structure, internal consistency, test-retest reliability, validity, and floor and ceiling effects of the SC-SINS were assessed. The internationally recognized cross-cultural adaptation guidelines were followed. Internal consistency was evaluated with Cronbach's alpha. Test-retest reliability was examined among the patients with a 4-week interval. The validity of the Chinese version of SINS (SC-SINS) was assessed by examining its relationship with Kostuik classification. Principal component analysis was conducted to confirm the factor structure of each subscale. RESULTS: A total of 160 participants (88 males and 72 females) were enrolled. No major difficulties occurred in the forward and backward translations of SINS. The internal consistency of SC-SINS was excellent (Cronbach's α =0.857, ranging from 0.68 to 0.85). Test-retest reliability was also excellent with a value of 0.89, ranging from 0.86 to 0.95. Validity analyses indicated that the SC-SINS was positively and significantly correlated with Kostuik classification. The correlation between "Posterolateral Involvement of Spinal Elements" and "1-2 Partial Damage" was the highest with a correlation value of 0.792. The correlation between "Pain" and "1-2 Partial Damage" was the lowest with a value of 0.341. All items showed principal component coefficients greater than 0.4. The values of Factor 1 ranged from 0.523 to 0.681; Factor 2 ranged from 0.591 to 0.731; Factor 3 ranged from 0.613 to 0.754; Factor 4 ranged from 0.461 to 0.711; Factor 5 ranged from 0.513 to 0.701; and Factor 6 ranged from 0.501 to 0.668. In addition, neither floor nor ceiling effects were seen in the SC-SINS. CONCLUSION: The SC-SINS demonstrated high internal consistency and test-retest reliability, which has been proven valid and reliable to measure spinal stability in patients from the Chinese mainland with metastatic spinal tumor.

Upregulation of P2Y12 inhibits chondrocyte apoptosis in lumbar osteoarthritis through the PI3K/AKT signaling pathway.

Lumbar facet osteoarthritis (FJOA) is a major cause of severe lower back pain and disability worldwide. However, the mechanism underlying cartilage degeneration in FJOA remains unclear. The purpose of this study was to investigate the regulation and mechanism of P2Y12 on chondrocyte apoptosis in FJOA. The experimental rats were randomly divided into non-operation (n = 20) and operation groups (n = 20). In the operation group, Sodium iodoacetate (MIA, Sigma, 200 mg/mL) was injected into the right L4/5 facet process using a blunt nanoneedle 26 (WPI, Sarasota, FL, USA) under the control of an injection pump. The final injection volume was 5µL and the injection rate was 2µL/min. The facet joint was removed four weeks after surgery. After the operation, samples were stored at -80 °C until further use, whereby the right facet joints in each group were tested. Hematoxylin and eosin (HE) and iron-red solid green staining were used to observe the degeneration of articular chondrocytes in rats. Immunohistochemistry and western blotting were used to observe the expressions of P2Y12, Matrix metalloproteinase 13 (MMP13), Collagen II (COL2), and other cartilage degeneration and apoptosis-related genes. Co-localization of P2Y12-cleaved caspase-3 in the apoptosis model was detected by dual-standard immunofluorescence staining. Apoptosis was also detected by flow cytometry and TUNEL assay.P2Y12 is highly expressed in OA cartilage tissue, and inhibits IL-1ß -induced chondrocyte apoptosis through PI3K/AKT signaling pathway, thus playing a certain protective role on cartilage.