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"Xie, Feng"
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Single-cell RNA sequencing analysis of mouse follicular somatic cells
Within the development of ovarian follicle, in addition to cell proliferation and differentiation, sophisticated cell–cell cross talks are established among follicular somatic cells such as granulosa cells (GCs) and theca cells. To systematically reveal the cell differentiation and signal transductions in follicular somatic cells, we collected the mouse follicular somatic cells from secondary to ovulatory stage, and analyzed the single cell transcriptomes. Having data filtered and screened, we found 6883 high variable genes in 4888 single cells. Then follicular somatic cells were clustered into 26 cell clusters, including 18 GC clusters, 4 theca endocrine cell (TEC) clusters, and 4 other somatic cell clusters, which include immune cells and Acta2 positive theca externa cells. From our data, we found there was metabolic reprogramming happened during GC differentiation. We also found both Cyp19a1 and Cyp11a1 could be expressed in TECs. We analyzed the expression patterns of genes associated with cell–cell interactions such as steroid hormone receptor genes, insulin signaling genes, and cytokine/transformation growth factor beta associated genes in all cell clusters. Lastly, we clustered the highly variable genes into 300 gene clusters, which could be used to search new genes involved in follicle development. These transcriptomes of follicular somatic cells provide us potential clues to reveal how mammals regulating follicle development and could help us find targets to improve oocyte quality for women with low fertility. Summary sentence In total, 6883 high variable genes are found in 4888 ovarian follicular somatic cells.
Journal Article
Electricity markets and power system economics
\"With the theories and rules of electricity markets developing rapidly, it's difficult for beginners to start learning and difficult for those in the field to keep up. Bringing together information previously scattered among various journals and scholarly articles, this book provides a comprehensive overview of the current state of development in the electricity market. It introduces the fundamental principles of power system operation so that even those with a basic understanding can benefit from the book. It includes a series of consistent mathematical models of market operation of power systems, original cases, and MATLAB programming examples with solutions\"-- Provided by publisher.
Book
Cruciform DNA in mouse growing oocytes: Its dynamics and its relationship with DNA transcription
Cruciform DNA is a causing factor of genome instability and chromosomal translocation, however, most studies about cruciform DNA in mammalian cells were based on palindromic sequences containing plasmids and reports about endogenous cruciform DNA are rare. In this study we observed the dynamics of endogenous cruciform DNA in mouse growing oocytes using immunofluorescence labeling method. We found cruciform DNA foci exist in transcription active growing oocytes but not in transcription inactive fully grown oocytes and colocalized with Parp1 but not with DNA damage marker γH2A.X. By analyzing the Genotype-Tissue Expression data, we found cruciform DNA-mediated chromosomal translocation in human spermatocytes is associated with the specific DNA transcription in testis. When inhibiting the transcription with α-amanitin in mouse oocytes, we found oocyte cruciform DNA foci decreased significantly. In summary, we observed the endogenous cruciform DNA in growing oocytes and our results showed that the cruciform DNA formation is transcription-dependent.
Journal Article
Neuronal dynamics direct cerebrospinal fluid perfusion and brain clearance
The accumulation of metabolic waste is a leading cause of numerous neurological disorders, yet we still have only limited knowledge of how the brain performs self-cleansing. Here we demonstrate that neural networks synchronize individual action potentials to create large-amplitude, rhythmic and self-perpetuating ionic waves in the interstitial fluid of the brain. These waves are a plausible mechanism to explain the correlated potentiation of the glymphatic flow
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through the brain parenchyma. Chemogenetic flattening of these high-energy ionic waves largely impeded cerebrospinal fluid infiltration into and clearance of molecules from the brain parenchyma. Notably, synthesized waves generated through transcranial optogenetic stimulation substantially potentiated cerebrospinal fluid-to-interstitial fluid perfusion. Our study demonstrates that neurons serve as master organizers for brain clearance. This fundamental principle introduces a new theoretical framework for the functioning of macroscopic brain waves.
Rhythmic neural activity drives cerebrospinal fluid perfusion through brain parenchyma to enhance brain cleansing.
Journal Article
Role of pyroptosis in inflammation and cancer
Pyroptosis is a form of programmed cell death mediated by gasdermin and is a product of continuous cell expansion until the cytomembrane ruptures, resulting in the release of cellular contents that can activate strong inflammatory and immune responses. Pyroptosis, an innate immune response, can be triggered by the activation of inflammasomes by various influencing factors. Activation of these inflammasomes can induce the maturation of caspase-1 or caspase-4/5/11, both of which cleave gasdermin D to release its N-terminal domain, which can bind membrane lipids and perforate the cell membrane. Here, we review the latest advancements in research on the mechanisms of pyroptosis, newly discovered influencing factors, antitumoral properties, and applications in various diseases. Moreover, this review also provides updates on potential targeted therapies for inflammation and cancers, methods for clinical prevention, and finally challenges and future directions in the field.
Journal Article
Nav1.8 and Chronic Pain: From Laboratory Animals to Clinical Patients
As a subtype of voltage-gated sodium channel and predominantly expressed in the sensory neurons located in the dorsal root ganglion (DRG), the Nav1.8 channel encoded by the SCN10A gene is found to have different variants in patients suffering chronic pain or insensitivity to pain due to the gain-of-function or loss-of-function of Nav1.8 channels. In animal models of chronic pain, Nav1.8 is also verified to be involved, suggesting that Nav1.8 may be a potential target for treatment of chronic pain. Another voltage-gated sodium channel, Nav1.7, is also proposed to be a target for chronic pain, supported by clinical findings in patients and laboratory animal models; however, there is no Nav1.7-specific drug that has passed clinical trials, although they demonstrated satisfactory effects in laboratory animals. This discrepancy between clinical and preclinical studies may be related to the differences between humans and laboratory animals or due to the degeneracy in different sodium channels governing the DRG neuronal excitability, which is thought of as the underlying machinery of chronic pain and mostly studied. This review summarizes recent findings of Nav1.8 in chronic pain from clinics and laboratories and discusses the difference, which may be helpful for future investigation of Nav1.8 in chronic pain, considering the dilemma of the Nav1.7 channel in chronic pain.
Journal Article
A predictive model for postoperative adverse outcomes following surgical treatment of acute type A aortic dissection based on machine learning
Acute type A aortic dissection (AAAD) has a high probability of postoperative adverse outcomes (PAO) after emergency surgery, so exploring the risk factors for PAO during hospitalization is key to reducing postoperative mortality and improving prognosis. An artificial intelligence approach was used to build a predictive model of PAO by clinical data‐driven machine learning to predict the incidence of PAO after total arch repair for AAAD. This study included 380 patients with AAAD. The clinical features that are associated with PAO were selected using the LASSO regression analysis. Six different machine learning algorithms were tried for modeling, and the performance of each model was analyzed comprehensively using receiver operating characteristic curves, calibration curve, precision recall curve, and decision analysis curves. Explain the optimal model through Shapley Additive Explanation (SHAP) and perform an individualized risk assessment. After comprehensive analysis, the authors believe that the extreme gradient boosting (XGBoost) model is the optimal model, with better performance than other models. The authors successfully built a prediction model for PAO in AAAD patients based on the XGBoost algorithm and interpreted the model with the SHAP method, which helps to identify high‐risk AAAD patients at an early stage and to adjust individual patient‐related clinical treatment plans in a timely manner.
Journal Article
Nondestructive halide exchange via SN2-like mechanism for efficient blue perovskite light-emitting diodes
Blue perovskite light-emitting diodes (PeLEDs) still remain poorly developed due to the big challenge of achieving high-quality mixed-halide perovskites with wide optical bandgaps. Halide exchange is an effective scheme to tune the emission color of PeLEDs, while making perovskites susceptible to high defect density due to solvent erosion. Herein, we propose a versatile strategy for nondestructive in-situ halide exchange to obtain high-quality blue perovskites with low trap density and tunable bandgaps through long alkyl chain chloride incorporated chloroform post-treatment. In comparison with conventional halide exchange method, the ionic exchange mechanism of the present strategy is similar to a bimolecular nucleophilic substitution process, which simultaneously modulates perovskite bandgaps and inhibits new halogen vacancy generation. Consequently, efficient PeLEDs across blue spectral regions are obtained, exhibiting external quantum efficiencies of 23.6% (sky-blue emission at 488 nm), 20.9% (pure-blue emission at 478 nm), and 15.0% (deep-blue emission at 468 nm), respectively.
Zhang et al. report non-destructive halide exchange by employing butylammonium halide incorporated post-treatment to achieve perovskite with low trap density and tuneable bandgap for blue LEDs, with external quantum efficiencies of 23.6%, 20.9%, and 15.5% for emission peaks at 488, 478, and 468 nm, respectively.
Journal Article
Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
Magnetocardiography (MCG) offers a noninvasive method for early screening and precise localization of cardiovascular diseases by measuring picotesla-level weak magnetic fields induced by cardiac electrical activity. However, in unshielded magnetic environments, geomagnetic disturbances, power-frequency electromagnetic interference, and physiological/motion artifacts can significantly overwhelm effective magnetocardiographic components. To address this challenge, this paper systematically constructs an integrated denoising framework, termed “AOA-VMD-WT”. In this approach, the Arithmetic Optimization Algorithm (AOA) adaptively optimizes the key parameters (decomposition level K and penalty factor α) of Variational Mode Decomposition (VMD). The decomposed components are then regularized based on their modal center frequencies: components with frequencies ≥50 Hz are directly suppressed; those with frequencies <50 Hz undergo wavelet threshold (WT) denoising; and those with frequencies <0.5 Hz undergo baseline correction. The purified signal is subsequently reconstructed. For quantitative evaluation, we designed performance indicators including QRS amplitude retention rate, high/low frequency suppression amount, and spectral entropy. Further comparisons are made with baseline methods such as FIR and wavelet soft/hard thresholds. Experimental results on multiple sets of measured MCG data demonstrate that the proposed method achieves an average improvement of approximately 8–15 dB in high-frequency suppression, 2–8 dB in low-frequency suppression, and a decrease in spectral entropy ranging from 0.1 to 0.6 without compromising QRS amplitude. Additionally, the parameter optimization exhibits high stability. These findings suggest that the proposed framework provides engineerable algorithmic support for stable MCG measurement in ordinary clinic scenarios.
Journal Article