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This is an article in the field of metallurgical engineering. Mangane-zinc spinel ferrite has been widely used in various fields due to its advantages of high permeability， high frequency and low loss. In order to make full use of Fe, Zn, Mn and other elements in electric arc furnace dust (EAFD)， Mn-Zn spinel ferrite was prepared by solid phase sintering method with alkali leaching zinc-containing EAFD as raw materials and MnSO4·H2O added. The effects of temperature， mass ratio (RZ/M) and pretreatment on the synthesis and magnetic properties of Mn-Zn ferrite were investigated by XRD, SEM-EDS and VSM. The results show that with the increase of reaction temperature，the speed of inter-grain merging in the Mn-Zn ferrite increases， the magnetic saturation induction and crystal grain size increase， and the coercivity decreases. When RZ/M changes to 1∶1.0，the magnetic saturation induction， coercivity and grain size increase. After pretreatment，the content of SiO2 in the EAFD decreases，and the magnetic saturation strength of the synthesized manganese-zinc ferrite increases. Therefore, after pretreatment with 2 mol/L alkali solution， the performance of manganzn-spinel ferrite synthesized at the condition of mass ratio 1∶1.0 and calcination temperature 1 100 ℃ is the best. Its saturation magnetic induction intensity (Ms) is 17.902 emu/g, and coercivity (Hc) is 3.21 kA/m.

Abstract Background The limited regenerative capacity of damaged neurons in adult mammals severely restricts neural repair. Although stem cell transplantation is promising, its clinical application remains challenging. Direct reprogramming, which utilizes cell plasticity to regenerate neurons, is an emerging alternative approach. Methods We utilized primary postnatal cortical astrocytes for reprogramming induced neurons (iNs) through the viral-mediated overexpression of the transcription factors Ngn2 and Pax6 (NP). Fluorescence-activated cell sorting (FACS) was used to enrich successfully transfected cells, followed by single-cell RNA sequencing (scRNA-seq) using the 10 × Genomics platform for comprehensive transcriptomic analysis. Results The scRNA-seq revealed that NP overexpression led to the differentiation of astrocytes into iNs, with percentages of 36% and 39.3% on days 4 and 7 posttransduction, respectively. CytoTRACE predicted the developmental sequence, identifying astrocytes as the reprogramming starting point. Trajectory analysis depicted the dynamic changes in gene expression during the astrocyte-to-iN transition. Conclusions This study elucidates the molecular dynamics underlying astrocyte reprogramming into iNs, revealing key genes and pathways involved in this process. Our research contributes novel insights into the molecular mechanisms of NP-mediated reprogramming, suggesting avenues for optimizing the efficiency of the reprogramming process.

Objective: Ischemic stroke (IS) is a significant health concern with high disability and fatality rates despite available treatments. Immune cells and cuproptosis are associated with the onset and progression of IS. Investigating the interaction between cuproptosis-related genes (CURGs) and immune cells in IS can provide a theoretical basis for IS treatment. Methods: We obtained IS datasets from the Gene Expression Omnibus (GEO) and employed machine learning to identify CURGs. The diagnostic efficiency of the CURGs was evaluated using receiver operating characteristic (ROC) curves. KEGG and gene set enrichment analysis (GSEA) were also conducted to identify biologically relevant pathways associated with CURGs in IS patients. Single-cell analysis was used to confirm the expression of 19 CURGs, and pathway activity calculations were performed using the AUCell package. Additionally, a risk prediction model for IS patients was developed, and core modules and hub genes related to IS were identified using weighted gene coexpression network analysis (WGCNA). We classified IS patients using a method of consensus clustering. Results: We established a precise diagnostic model for IS. Enrichment analysis revealed major pathways, including oxidative phosphorylation, the NF-kappa B signaling pathway, the apoptosis pathway, and the Wnt signaling pathway. At the single-cell level, compared to those in non-IS samples, 19 CURGs were primarily overexpressed in the immune cells of IS samples and exhibited high activity in natural killer cell-mediated cytotoxicity, steroid hormone biosynthesis, and oxidative phosphorylation. Two clusters were obtained through consensus clustering. Notably, immune cell types including B cells, plasma cells, and resting NK cells, varied between the two clusters. Furthermore, the red module and hub genes associated with IS were uncovered. The expression patterns of CURGs varied over time. Conclusion: This study developed a precise diagnostic model for IS by identifying CURGs and evaluating their interaction with immune cells. Enrichment analyses revealed key pathways involved in IS, and single-cell analysis confirmed CURG overexpression in immune cells. A risk prediction model and core modules associated with IS were also identified.

As a growth asset, many listed companies have distinct characteristics of their respective industries. The listed companies in the same industry have a link effect, which can provide a wealth of information for stock operations. In this paper, a complete automated quantitative investment model is developed based on statistical models that use industry information to select stocks and time the market, thereby bringing out the synergistic effect of the system and ensuring maximum returns on investment. Risk control is taken into consideration in our model, a risk control factor is designed by measuring volatility of stock prices to determine the buying volume and the timing of stop loss, effectively safeguarding capital security. The latest industry classification results published by the China Securities Regulatory Commission are used as the basis for the industry classification. After data preprocessing, there are 70 sub-categories in 18 major categories of industry. We take the stock price of the 70 sub-categories from January 1, 2012 to January 1, 2022 as our research data. The back testing results show that positive returns are obtained in all industries except for six in our model. The average annualized rate of return is 11.10 %, which is higher than the stock indexes of the same period and far higher than the investment model of bank savings. Additionally, in accordance with a real trading system, the experiment simulates the inclusion of all transaction fees in the trading process, demonstrating the practical application value of our expert system.

Abstract Background Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and lethal hepatobiliary tumor with few therapeutic strategies. The metabolic reprogramming of tumor cells plays an essential role in the development of tumors, while the metabolic molecular classification of iCCA is largely unknown. Here, we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients, hoping to provide a novel perspective to understand and treat iCCA. Methods We performed integrated multiomics analysis in 116 iCCA samples, including whole‐exome sequencing, bulk RNA‐sequencing and proteome analysis. Based on the non‐negative matrix factorization method and the protein abundance of metabolic genes in human genome‐scale metabolic models, the metabolic subtype of iCCA was determined. Survival and prognostic gene analyses were used to compare overall survival (OS) differences between metabolic subtypes. Cell proliferation analysis, 5‐ethynyl‐2'‐deoxyuridine (EdU) assay, colony formation assay, RNA‐sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinase α (DGKA) in iCCA cells. Results Three metabolic subtypes (S1‐S3) with subtype‐specific biomarkers of iCCA were identified. These metabolic subtypes presented with distinct prognoses, metabolic features, immune microenvironments, and genetic alterations. The S2 subtype with the worst survival showed the activation of some special metabolic processes, immune‐suppressed microenvironment and Kirsten rat sarcoma viral oncogene homolog (KRAS)/AT‐rich interactive domain 1A (ARID1A) mutations. Among the S2 subtype‐specific upregulated proteins, DGKA was further identified as a potential drug target for iCCA, which promoted cell proliferation by enhancing phosphatidic acid (PA) metabolism and activating mitogen‐activated protein kinase (MAPK) signaling. Conclusion Via multiomics analyses, we identified three metabolic subtypes of iCCA, revealing that the S2 subtype exhibited the poorest survival outcomes. We further identified DGKA as a potential target for the S2 subtype.

Abstract This study used a Mendelian randomization (MR) approach to investigate the causal relationship between genetically predicted endometriosis (EMS) and breast cancer risk. A total of 122,977 cases and 105,974 controls were included in the analysis, with gene-level summary data obtained from the Breast Cancer Association Consortium (BCAC). An inverse variance-weighting approach was applied to assess the causal relationship between EMS and breast cancer risk, and weighted median and MR-Egger regression methods were used to evaluate pleiotropy. Results showed a causal relationship between EMS and a decreased risk of overall breast cancer (odds ratio [OR] 0.95; 95% CI 0.90–0.99, p = 0.02). Furthermore, EMS was associated with a lower risk for estrogen receptor (ER)-positive breast cancer in a subgroup analysis based on immunohistochemistry type (OR 0.91; 95% CI 0.86–0.97, p = 0.005). However, there was no causal association between ER-negative breast cancer and survival (OR 1.00; 95% CI 0.94–1.06, p = 0.89). Pleiotropy was not observed. These findings provide evidence of a relationship between EMS and reduced breast cancer risk in invasive breast cancer overall and specific tissue types, and support the results of a previous observational study. Further research is needed to elucidate the mechanisms underlying this association.

The enhancement of bioactivity in materials has become an important focus within the field of bone tissue engineering. Four-dimensional intelligent osteogenic module, an innovative fusion of 3D printing with the time axis, shows immense potential in augmenting the bioactivity of these materials, thereby facilitating autologous bone regeneration efficiently. This study focuses on novel bone repair materials, particularly bioactive scaffolds with a developmental osteogenic microenvironment prepared through 3D bioprinting technology. This research mainly creates a developmental osteogenic microenvironment named “DOME”. This is primed by the application of a small amount of the small molecule drug SB216763, which activates canonical Wnt signaling in osteocytes, promoting osteogenesis and mineralization nodule formation in bone marrow stromal cells and inhibiting the formation of adipocytes. Moreover, DOME enhances endothelial cell migration and angiogenesis, which is integral to bone repair. More importantly, the DOME-PCI3D system, a 4D intelligent osteogenic module constructed through 3D bioprinting, stably supports cell growth (91.2% survival rate after 7 days) and significantly increases the expression of osteogenic transcription factors in bone marrow stromal cells and induces osteogenic differentiation and mineralization for 28 days. This study presents a novel approach for bone repair, employing 3D bioprinting to create a multifunctional 4D intelligent osteogenic module. This innovative method not only resolves challenges related to shape-matching and biological activity but also demonstrates the vast potential for applications in bone repair.

Abstract Background SQSTM1/p62 is a selective autophagy receptor that regulates multiple signaling pathways participating in the initiation and progression of tumors. Metastasis is still the main cause for intrahepatic cholangiocarcinoma (ICC)‐associated mortality. Hence, this study aimed to explore the mechanism of p62 promoting the progression of ICC. Methods Western blotting and immunohistochemical analyses were conducted to detect the expression level of protein p62 in ICC tissues and its correlation with prognosis. Subsequently, the loss‐of‐function experiments in vitro and in vivo were performed to define the role of p62 in ICC cell proliferation, invasion, and metastasis. Then, the effect of p62 knockdown on mitochondrial function and mitophagy was evaluated by measuring the oxygen consumption rate, and using immunofluorescence and western blotting analyses. Results The expression of p62 was significantly upregulated in ICC specimens compared with normal tissues. We further illustrated that p62 expression positively correlated with lymph node metastasis and poor prognosis. The loss‐of‐function assays revealed that p62 not only promoted ICC cell proliferation, migration, and invasive capacities in vitro, but also induced lung metastasis in the xenograft mouse model. Mechanistically, high expression of p62‐induced epithelial–mesenchymal transition (EMT) with the upregulation of Snail, vimentin, N‐cadherin, and downregulation of E‐cadherin. Moreover, the autophagy‐dependent function of p62 might play a vital role in maintaining the mitochondrial function of ICC by mitophagy which might further promote EMT. Conclusion These data provided new evidence for the mechanism by which abundant p62 expression promoted ICC progression, suggesting a promising therapeutic target for antimetastatic strategies in patients with ICC.

Rhizomes from Polygonatum spp. have multi-functions of both medicine and foods. Three major species are Polygonatum sibiricum Red., Polygonatum kingianum Coll. et Hemsl and Polygonatum cyrtonema Hua. As the key component, the polysaccharides from Polygonatum spp. have various biological activities. The astringency of fresh rhizomes of Polygonatum spp. can cause throat irritation. Thus, the rhizomes of Polygonatum spp. must be processed before consumption as foods or medicine to reduce toxicity and enhance efficacy. However, both of traditional and modern processing methods lead to significant reduction in polysaccharide content, which also change its structure and biological value. Thus, based on literature research, this article summarizes common processing methods of Polygonatum spp., including steaming, stewing, with wine, and shining. In addition, effects of processing methods on polysaccharide content, its structural properties (including monosaccharide composition, molecular weight, etc.), and its physiological activities (including antioxidant activity, regulation of glucose and lipid metabolism, immune-enhancing activity, anti-fatigue activity, antibacterial activity, etc.) are reviewed. It is meaningful to provide references for efficiently industrial use and accurate control during processing of Polygonatum spp..

BackgroundVarious immune cell types in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC) have been identified as important parameters associated with prognosis and responsiveness to immunotherapy. However, how various factors influence immune cell infiltration remains incompletely understood. Hence, we investigated the single cell multi-omics landscape of immune infiltration in HCC, particularly key gene and cell subsets that influence immune infiltration, thus potentially linking the immunotherapy response and immune cell infiltration.MethodsWe grouped patients with HCC according to immune cell infiltration scores calculated by single sample gene set enrichment analysis (ssGSEA). Differential expression analysis, functional enrichment, clinical trait association, gene mutation analysis, tumor immune dysfunction and exclusion (TIDE) and prognostic model construction were used to investigate the immune infiltration landscape through multi-omics. Stepwise regression was further used to identify key genes regulating immune infiltration. Single cell analysis was performed to explore expression patterns of candidate genes and investigate associated cellular populations. Correlation analysis, ROC analysis, Immunotherapy cohorts were used to explore and confirm the role of key gene and cellular population in predicting immune infiltration state and immunotherapy response. Immunohistochemistry and multiplexed fluorescence staining were used to further validated our results.ResultsPatients with HCC were clustered into high and low immune infiltration groups. Mutations of CTNNB1 and TTN were significantly associated with immune infiltration and altered enrichment of cell populations in the TME. TIDE analysis demonstrated that T cell dysfunction and the T cell exclusion score were elevated in the high and low infiltration groups, respectively. Six risk genes and five risk immune cell types were identified and used to construct risk scores and a nomogram model. CXCR6 and LTA, identified by stepwise regression, were highly associated with immune infiltration. Single cell analysis revealed that LTA was expressed primarily in tumor infiltrating T lymphocytes and partial B lymphocytes, whereas CXCR6 was enriched predominantly in T and NK cells. Notably, CXCR6+ CD8 T cells were characterized as tumor enriched cells that may be potential predictors of high immune infiltration and the immune-checkpoint blockade response, and may serve as therapeutic targets.ConclusionWe constructed a comprehensive single cell and multi-omics landscape of immune infiltration in HCC, and delineated key genes and cellular populations regulating immune infiltration and immunotherapy response, thus providing insights into the mechanisms of immune infiltration and future therapeutic control.

Recently, mental health has received increasing attention, particularly preoperative anxiety, which constitutes a bad emotional experience for surgical patients. Many experts have studied preoperative anxiety in terms of its related risk factors, interventions, and postoperative effects; however, there has been no systematic analysis of published articles. This paper presents a bibliometric review of documents related to preoperative anxiety published between 2001 and 2021. A detailed data analysis of 1,596 publications was conducted using CiteSpace and VOSviewer. Since the 20th century, the field of preoperative anxiety has gradually developed; research began around 2000 and has made a huge leap forward since 2016. Developed countries, led by the United States, were the first to conduct research, but preoperative anxiety research in developing countries like Turkey and China has gradually increased and led to an irreplaceable contribution. Intervention has remained the main topic of preoperative anxiety research, and measures have developed from premedication to the provision of education and information. Moreover, the use of advanced equipment such as virtual reality has emerged with great popularity. Based on previous research, the application of virtual reality combined with pediatric patients will become a new research direction.

IntroductionBreast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA.MethodsThe clinical data and transcriptome data of patients with BRCA were acquired from the Cancer Genome Atlas database (TCGA), and autophagy-related genes were obtained from the human autophagy database (HADb). ARlncRNAs were identified by conducting co‑expression analysis. Univariate and multivariate Cox regression analysis were performed to construct an ARlncRNA prognostic model. The prognostic model was evaluated by Kaplan–Meier survival analysis, plotting risk curve, Independent prognostic analysis, clinical correlation analysis and plotting ROC curves. Finally, the tumor immune microenvironment of the prognostic model was studied.Results10 ARlncRNAs(AC090912.1, LINC01871, AL358472.3, AL122010.1, SEMA3B-AS1, BAIAP2-DT, MAPT-AS1, DNAH10OS, AC015819.1, AC090198.1) were included in the model. Kaplan–Meier survival analysis of the prognostic model showed that the overall survival(OS) of the low-risk group was significantly better than that of the high-risk group (p< 0.001). Multivariate Cox regression analyses suggested that the prognostic model was an independent prognostic factor for BRCA (HR = 1.788, CI = 1.534–2.084, p < 0.001). ROCs of 1-, 3- and 5-year survival revealed that the AUC values of the prognostic model were all > 0.7, with values of 0.779, 0.746, and 0.731, respectively. In addition, Gene Set Enrichment Analysis (GSEA) suggested that several tumor-related pathways were enriched in the high-risk group, while several immune‑related pathways were enriched in the low-risk group. Patients in the low-risk group had higher immune scores and their immune cells and immune pathways were more active. Patients in the low-risk group had higher PD-1 and CTLA-4 levels and received more benefits from immune checkpoint inhibitors (ICIs) therapy.DiscussionThe ARlncRNA prognostic model showed good performance in predicting the prognosis of patients with BRCA and is of great significance to guide the individualized treatment of these patients.

Abstract Due to the impedance characteristic of conductor, the ground potential rise is different within grounding grid when impulse current is injected. When staff touches objects with different GPR at the same time, the GPD will be applied to human body, leading to potential personal safety problem. The impact of GPD on human body needs to be evaluated. The method of moment was used to calculate the ground potential rise of grounding grid under impulse current. By regarding the human body as a resistance, the current flowing through it because of ground potential difference was obtained. Methods based on current amplitude and electrical charge was used to evaluate personal safety. The effects of injecting current waveform, injecting position, soil resistivity, grounding conductor and grounding grid structure on ground potential difference and safe current threshold were studied. Results show the ground potential difference near injecting point may pose a threat to personal safety. The evaluation method based on electrical charge was recommended. In field test, the injecting point of grounding grid should be far away from corners, and staff should be kept away from the injecting point, so as to mitigate the risk of ground potential difference on personal safety.

Nervous system diseases present significant challenges to the neuroscience community due to ethical and practical constraints that limit access to appropriate research materials. Somatic cell reprogramming has been proposed as a novel way to obtain neurons. Various emerging techniques have been used to reprogram mature and differentiated cells into neurons. This review provides an overview of somatic cell reprogramming for neurological research and therapy, focusing on neural reprogramming and generating different neural cell types. We examine the mechanisms involved in reprogramming and the challenges that arise. We herein summarize cell reprogramming strategies to generate neurons, including transcription factors, small molecules, and microRNAs, with a focus on different types of cells.. While reprogramming somatic cells into neurons holds the potential for understanding neurological diseases and developing therapeutic applications, its limitations and risks must be carefully considered. Here, we highlight the potential benefits of somatic cell reprogramming for neurological disease research and therapy. This review contributes to the field by providing a comprehensive overview of the various techniques used to generate neurons by cellular reprogramming and discussing their potential applications.

BackgroundVirtual reality (VR) training is a promising intervention strategy that has been utilized in health care fields like stroke rehabilitation and psychotherapy. Current studies suggest that VR training is effective in improving the locomotor ability of stroke patients. ObjectiveThis is the first meta-meta-analysis of the effects of VR on motor function in stroke patients. This study aimed to systematically summarize and quantify the present meta-analyses results of VR training and produce high-quality meta-meta-analysis results to obtain a more accurate prediction. MethodsWe searched 4 online databases (Web of Science, Scopus, PubMed, and Chinese National Knowledge Infrastructure) for meta-analysis studies. After accounting for overlap, 10 studies (accounting for almost 550 stroke patients) were obtained. Based on the meta-meta-analysis of these patients, this study quantified the impact of VR training on stroke patients’ motor performance, mainly including upper limb function, balance, and walking ability. We combined the effects under the random effect model and pooled the estimates as standardized mean differences (SMD). ResultsThe results of the meta-meta-analysis showed that VR training effectively improves upper limb function (SMD 4.606, 95% CI 2.733-6.479, P

Abstract Background Heat stroke (HS) is a critical illness that can cause multiple organ dysfunction, including damage to the central nervous system (CNS), which can be life-threatening in severe cases. Brain lesions in patients with HS who present with CNS damage have been rarely reported before, and they usually vary in different cases, hence, patients with such lesions may present a clinical challenge in terms of diagnosis and management. Cerebral venous thrombosis (CVT) is a rare cause of stroke that mostly affects young individuals and children. The pathogenesis of brain damage caused by HS is complex, and CVT may be involved in the pathogenesis of HS with CNS damage. In this manuscript, we have reported a case of a patient with HS having CVT with symmetrical lesions in the bilateral putamen, posterior limb of the internal capsule, external capsule, insular lobe, and subcortical white matter in the brain. Case presentation We encountered a 48-year-old man who presented with HS in the summer season. During admission, he had a high body temperature and was in coma and shock. Then, he developed rhabdomyolysis syndrome, acute kidney and liver damage, electrolyte imbalance, and acid–base balance disorders, and his D-dimer level was elevated. After several days of anti-shock treatment, the patient’s level of consciousness improved. However, he experienced a decline in vision. Cerebral magnetic resonance imaging (MRI) showed symmetrical lesions in the bilateral posterior limb of the internal capsule, putamen, external capsule, insula, and subcortical white matter, and cerebral magnetic resonance venography (MRV) showed the development of CVT. Therefore, anti-coagulation treatment was provided. After timely clinical intervention, the symptoms of the patient gradually improved. Conclusions This case showed that HS can cause CVT. Therefore, cerebral MRI findings in HS must be assessed; in addition, early MRV can help in the diagnosis of the disease, which can effectively improve prognosis.

Background: In November 2017, the American College of Cardiology/American Heart Association (ACC/AHA) updated their definition of hypertension from 140/90 mm Hg to 130/80 mm Hg. Objectives: We sought to assess the situation of hypertension and the impact of applying the new threshold to a geographically and ethnically diverse population. Methods: We analyzed selected data on 237,142 participants aged ≥40 who had blood pressure taken for the 2014 China National Stroke Screening and Prevention Project. Choropleth maps and logistic regression analyses were performed to estimate the prevalence, geographical distribution and risk factors of hypertension using both 2017 ACC/AHA guidelines and 2014 evidence-based guidelines. Results: The present cross-sectional study showed the age- and sex-standardized prevalence of hypertension was 37.08% and 58.52%, respectively, according to 2014 evidence-based guidelines and 2017 ACC/AHA guidelines. The distribution of hypertension and risk factors changed little between guidelines, with data showing a high prevalence of hypertension around Bohai Gulf and in south central coastal areas using either definition. The age- and sex-standardized prevalence of newly labeled as hypertensive was 21.44%. Interestingly, the high prevalence region of newly labeled as hypertensive was found in the north China. Conclusion: The prevalence of hypertension increased significantly on 2017 ACC/AHA guidelines compared to the prevalence when using 2014 evidence-based guidelines, with high prevalence areas of newly labeled as hypertensive now seen mainly in north China. There need to be correspondingly robust efforts to improve health education, health management, and behavioral and lifestyle interventions in the north.

Immunoglobulin G4 (IgG4)-related disease is a systemic disease characterized by sclerosing lesions and an increased serum IgG4 level. This condition can involve any organ, but IgG4-related spinal pachymeningitis is relatively rare. In the current study, we report a case of spinal cord compression caused by IgG4-related spinal pachymeningitis. A 39-year-old man presented to us with a 15-day history of back pain and a 3-day history of dysuresia, exacerbated by weakness in the lower extremities for 2 days. Cervical magnetic resonance imaging (MRI) showed strip-shaped abnormal signals along the anterior and posterior borders of the spinal cord at the C5–T4 levels. The IgG level in cerebrospinal fluid was 718.0 mg/L. Thoracic MRI revealed strip-shaped abnormal signals with remarkable enhancement along the anterior and posterior borders of the dural sac at the T1–T6 levels. Histopathological examination confirmed IgG4-related spinal pachymeningitis. The symptoms worsened rapidly, and surgical resection of the space-occupying lesion in the vertebral canal was performed for spinal decompression. Corticosteroid therapy was administered, and the patient's motor functions were mildly improved. IgG4-related disease can manifest as spinal pachymeningitis and cause spinal cord compression. Clinicians should be aware of this rare condition, and early diagnosis, timely surgical decompression, and appropriate corticosteroid therapy should be highlighted.

Combined inhibition of programmed death-ligand 1 (PD-L1) and transforming growth factor-β (TGF-β) displayed additive anti-tumor response in a subgroup of cancer patients, highlighting the importance of understanding the multifaceted roles of TGF-β in immunity and fibrosis. In the present research, we show that TGF-β signaling pathway, controlled by miR-20a-5p and transforming growth factor-β receptor 2 (TGFBR2), alters the inflammation and fibrosis processes in liver. We performed integrated analysis of differently expressed miRNA (DEM) associated with liver fibrosis and screened miR-20a-5p out as a key regulator in inflammation-driven liver fibrosis. We subsequently conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the genes targeted by miR-20a-5p. And the result showed that 12 target genes were significantly enriched in TGF-β signaling pathway. Further study showed that miR-20a-5p was down-regulated and involved in inflammation during liver fibrosis in human and mouse samples, indicating that miR-20a-5p and inflammation are functionally linked during liver fibrosis progression. To uncover the underlying pro-inflammatory mechanism of miR-20a-5p in liver fibrosis, we selected and verified TGFBR2, which is a key functional receptor in TGF-β signaling pathway, as a direct target gene of miR-20a-5p. The downregulation of miR-20a-5p in liver fibrosis resulted in TGFBR2-activated TGF-β signaling pathway, followed by the activation of macrophage and extracellular matrix (ECM) production by hepatic stellate cell (HSC). Our results identify the miR-20a-5p/TGFBR2 axis as a key regulator of TGF-β signaling, and highlight the critical role of miR-20a-5p in the development of liver fibrosis.

Massive loss of neurons following brain injury or disease is the primary cause of central nervous system dysfunction. Recently, much research has been conducted on how to compensate for neuronal loss in damaged parts of the nervous system and thus restore functional connectivity among neurons. Direct somatic cell differentiation into neurons using pro-neural transcription factors, small molecules, or microRNAs, individually or in association, is the most promising form of neural cell replacement therapy available. This method provides a potential remedy for cell loss in a variety of neurodegenerative illnesses, and the development of reprogramming technology has made this method feasible. This article provides a comprehensive review of reprogramming, including the selection and methods of reprogramming starting cell populations as well as the signaling methods involved in this process. Additionally, we thoroughly examine how reprogramming astrocytes into neurons can be applied to treat stroke and other neurodegenerative diseases. Finally, we discuss the challenges of neuronal reprogramming and offer insights about the field. [ABSTRACT FROM AUTHOR]

Background: Various immune cell types in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC) have been identified as important parameters associated with prognosis and responsiveness to immunotherapy. However, how various factors influence immune cell infiltration remains incompletely understood. Hence, we investigated the single cell multi-omics landscape of immune infiltration in HCC, particularly key gene and cell subsets that influence immune infiltration, thus potentially linking the immunotherapy response and immune cell infiltration. Methods: We grouped patients with HCC according to immune cell infiltration scores calculated by single sample gene set enrichment analysis (ssGSEA). Differential expression analysis, functional enrichment, clinical trait association, gene mutation analysis, tumor immune dysfunction and exclusion (TIDE) and prognostic model construction were used to investigate the immune infiltration landscape through multi-omics. Stepwise regression was further used to identify key genes regulating immune infiltration. Single cell analysis was performed to explore expression patterns of candidate genes and investigate associated cellular populations. Correlation analysis, ROC analysis, Immunotherapy cohorts were used to explore and confirm the role of key gene and cellular population in predicting immune infiltration state and immunotherapy response. Immunohistochemistry and multiplexed fluorescence staining were used to further validated our results. Results: Patients with HCC were clustered into high and low immune infiltration groups. Mutations of CTNNB1 and TTN were significantly associated with immune infiltration and altered enrichment of cell populations in the TME. TIDE analysis demonstrated that T cell dysfunction and the T cell exclusion score were elevated in the high and low infiltration groups, respectively. Six risk genes and five risk immune cell types were identified and used to construct risk scores and a nomogram model. CXCR6 and LTA, identified by stepwise regression, were highly associated with immune infiltration. Single cell analysis revealed that LTA was expressed primarily in tumor infiltrating T lymphocytes and partial B lymphocytes, whereas CXCR6 was enriched predominantly in T and NK cells. Notably, CXCR6+ CD8 T cells were characterized as tumor enriched cells that may be potential predictors of high immune infiltration and the immunecheckpoint blockade response, and may serve as therapeutic targets. Conclusion: We constructed a comprehensive single cell and multi-omics landscape of immune infiltration in HCC, and delineated key genes and cellular populations regulating immune infiltration and immunotherapy response, thus providing insights into the mechanisms of immune infiltration and future therapeutic control. [ABSTRACT FROM AUTHOR]

This paper notes a simple connection between synthetic control and online learning. Specifically, we recognize synthetic control as an instance of Follow-The-Leader (FTL). Standard results in online convex optimization then imply that, even when outcomes are chosen by an adversary, synthetic control predictions of counterfactual outcomes for the treated unit perform almost as well as an oracle weighted average of control units' outcomes. Synthetic control on differenced data performs almost as well as oracle weighted difference-in-differences, potentially making it an attractive choice in practice. We argue that this observation further supports the use of synthetic control estimators in comparative case studies. [ABSTRACT FROM AUTHOR]

Introduction: Breast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA. Methods: The clinical data and transcriptome data of patients with BRCA were acquired from the Cancer Genome Atlas database (TCGA), and autophagyrelated genes were obtained from the human autophagy database (HADb). ARlncRNAs were identified by conducting co‑expression analysis. Univariate and multivariate Cox regression analysis were performed to construct an ARlncRNA prognostic model. The prognostic model was evaluated by Kaplan–Meier survival analysis, plotting risk curve, Independent prognostic analysis, clinical correlation analysis and plotting ROC curves. Finally, the tumor immune microenvironment of the prognostic model was studied. Results: 10 ARlncRNAs(AC090912.1, LINC01871, AL358472.3, AL122010.1, SEMA3B-AS1, BAIAP2-DT, MAPT-AS1, DNAH10OS, AC015819.1, AC090198.1) were included in the model. Kaplan–Meier survival analysis of the prognostic model showed that the overall survival(OS) of the low-risk group was significantly better than that of the high-risk group (p< 0.001). Multivariate Cox regression analyses suggested that the prognostic model was an independent prognostic factor for BRCA (HR = 1.788, CI = 1.534–2.084, p < 0.001). ROCs of 1-, 3- and 5-year survival revealed that the AUC values of the prognostic model were all > 0.7, with values of 0.779, 0.746, and 0.731, respectively. In addition, Gene Set Enrichment Analysis (GSEA) suggested that several tumor-related pathways were enriched in the high-risk group, while several immune‑related pathways were enriched in the low-risk group. Patients in the low-risk group had higher immune scores and their immune cells and immune pathways were more active. Patients in the low-risk group had higher PD-1 and CTLA-4 levels and received more benefits from immune checkpoint inhibitors (ICIs) therapy. Discussion: The ARlncRNA prognostic model showed good performance in predicting the prognosis of patients with BRCA and is of great significance to guide the individualized treatment of these patients. [ABSTRACT FROM AUTHOR]