Distinction of papillary and adamantinomatous craniopharyngioma: Clinical features, surgical nuances and hypothalamic outcomes.

OBJECTIVE: Understanding the differences of suprasellar papillary and adamantinomatous craniopharyngiomas (PCPs/ACPs) is pivotal for target therapy, surgical strategy or postoperative management. Here, the clinical features, surgical nuances and postoperative hypothalamic outcomes of PCPs were systematically recapitulated. METHODS: 24 PCPs and 52 ACPs underwent initial surgery were retrospectively reviewed. Clinical data, quantified third ventricle (3rd V) occupation and optic chiasm distortion were compared, as well as intra-operative findings, operating notes and prognosis. Moreover, analysis of tumor/3rd V relationship and hypothalamic outcomes were also performed. RESULTS: Tumors were more likely to occupies the 3rd V cavity in PCPs. Chiasm distortion of "compressed forward" was the most common pattern (45.8 %) in PCPs, whereas "stretched forward" pattern accounted the highest (42.5 %) in ACPs. Besides, round-shaped with less calcification, duct-like recess, solid consistency, rare subdiaphragmatic invasion, visible lower stalk and improved postoperative visual outcome were more frequently observed in PCPs. The basal membranes of the tumor epithelium and the reactive gliosis were separated by a layer of collagen fibers in most PCPs, which differs from ACPs in the morphological examination of tumor/3rd V floor interface. In daytime sleepiness and memory difficulty, the PCPs showed significantly better outcomes than the ACPs groups, and PCPs suffered less postoperative weight gain (p < 0.05) than ACPs among adult-onset cases. CONCLUSION: PCPs are different from ACPs regards the clinical features, operative techniques and outcomes. If necessary, PCPs are suggested more amenable to total removal since its less invasiveness to the 3rd V floor and better hypothalamic outcomes.

Unlocking Bright and Switchable Dimeric Singlet Oxygen Electrochemiluminescence by Surface Engineering.

Visible electrochemiluminescence (ECL) of singlet oxygen (1O2) from the dimeric 1Δg state is a versatile and cost-efficient tool for sensing and imaging in various application fields such as biochemistry, pharmaceuticals, and material science. However, its implementation is hindered by weak emission and complex generation mechanisms. In this work, we enable a bright and switchable dimeric 1O2 ECL through facile yet effective surface engineering strategies on a screen-printed carbon electrode in aqueous media. Specifically, we complement a stepwise potential procedure with a pre-cathodic process to switch on the anodic 1O2 ECL and unravel how the in situ electrochemical pretreatments remarkably amplify the ECL intensity by modifying the surface oxygenates and promoting the 1O2-generating reactions. Additionally, ex situ oxygen plasma treatment on the electrode surface, which switches off the 1O2 ECL, further demonstrates the surface specificity of the 1O2 ECL from another perspective. Leveraging these surface strategies, we establish a sensing capability of the 1O2 ECL system with high sensitivity and selectivity toward tertiary amines. This work paves the way for translating a laboratory-scale 1O2-ECL system to portable and patternable sensing, imaging, and display applications.

Diversity and Activity of Soil N2O-Reducing Bacteria Shaped by Urbanization.

Nitrous oxide (N2O) is a potent greenhouse gas with various production pathways. N2O reductase (N2OR) is the primary N2O sink, but the distribution of its gene clades, typically nosZI and atypically nosZII, along urbanization gradients remains poorly understood. Here we sampled soils from forests, parks, and farmland across eight provinces in eastern China, using high-throughput sequencing to distinguish between two N2O-reducing bacteria clades. A deterministic process mainly determined assemblies of the nosZI communities. Homogeneous selection drove nosZI deterministic processes, and both homogeneous and heterogeneous selection influenced nosZII. This suggests nosZII is more sensitive to environmental changes than nosZI, with significant changes in community structure over time or space. Ecosystems with stronger anthropogenic disturbance, such as urban areas, provide diverse ecological niches for N2O-reducing bacteria (especially nosZII) to adapt to environmental fluctuations. Structural equation modeling (SEM) and correlation analyses revealed that pH significantly influences the community composition of both N2O-reducing bacteria clades. This study underscores urbanization's impact on N2O-reducing bacteria in urban soils, highlighting the importance of nosZII and survival strategies. It offers novel insights into the role of atypical denitrifiers among N2O-reducing bacteria, underscoring their potential ecological importance in mitigating N2O emissions from urban soils.

Clinical characteristics and outcomes of patients with antibody-related autoimmune encephalitis presenting with disorders of consciousness: A prospective cohort study.

OBJECTIVE: To explore the clinical characteristics, short- and long-term functional outcomes, and risk factors for antibody-related autoimmune encephalitis (AE) in patients with disorders of consciousness (DoC). METHODS: Clinical data were collected from AE patients admitted to Xuanwu Hospital of Capital Medical University from January 2012 to December 2021, and patients were followed up for up to 24 months after immunotherapy. RESULTS: A total of 312 patients with AE were included: 197 (63.1%) with anti-NMDAR encephalitis, 71 (22.8%) with anti-LGI1 encephalitis, 20 (6.4%) with anti-GABAbR encephalitis, 10 (3.2%) with anti-CASPR2 encephalitis, 10 (3.2%) with anti-GAD65 encephalitis, and 4 (1.3%) with anti-AMPAR2 encephalitis. Among these patients, 32.4% (101/312) presented with DoC, and the median (interquartile range, IQR) time to DoC was 16 (7.5, 32) days. DoC patients had higher rates of various clinical features of AE (p < .05). DoC was associated with elevated lumbar puncture cerebrospinal fluid (CSF) pressure, CSF leukocyte count, and specific antibody titer (p < .05). A high percentage of patients in the DoC group had a poor prognosis at discharge and at 6 months after immunotherapy (p < .001), but no significant difference in prognosis was noted between the DoC group and the non-DoC group at 12 and 24 months after immunotherapy. Dyskinesia (OR = 3.266, 95% CI: 1.550-6.925, p = .002), autonomic dysfunction (OR = 5.871, 95% CI: 2.574-14.096, and p < .001), increased CSF pressure (OR = 1.007, 95% CI: 1.001-1.014, p = .046), and modified Rankin scale (mRS) score ≥3 at the initiation of immunotherapy (OR = 7.457, 95% CI: 3.225-18.839, p < .001) were independent risk factors for DoC in AE patients. CONCLUSION: DoC is a relatively common clinical symptom in patients with AE, especially critically ill patients. Despite requiring longer hospitalization, DoC mostly improves with treatment of the primary disease and has a good long-term prognosis after aggressive life support and combination immunotherapy.

Prostate cancer progression modeling provides insight into dynamic molecular changes associated with progressive disease states.

Prostate cancer is a significant health concern and the most commonly diagnosed cancer in men worldwide. Understanding the complex process of prostate tumor evolution and progression is crucial for improved diagnosis, treatments, and patient outcomes. Previous studies have focused on unraveling the dynamics of prostate cancer evolution using phylogenetic or lineage analysis approaches. However, those approaches have limitations in capturing the complete disease process or incorporating genomic and transcriptomic variations comprehensively. In this study, we applied a novel computational approach to derive a prostate cancer progression model using multi-dimensional data from 497 prostate tumor samples and 52 tumor-adjacent normal samples obtained from the TCGA study. The model was validated using data from an independent cohort of 545 primary tumor samples. By integrating transcriptomic and genomic data, our model provides a comprehensive view of prostate tumor progression, identifies crucial signaling pathways and genetic events, and uncovers distinct transcription signatures associated with disease progression. Our findings have significant implications for cancer research and hold promise for guiding personalized treatment strategies in prostate cancer.

NJGCG: A node-based joint Gaussian copula graphical model for gene networks inference across multiple states.

Inferring the interactions between genes is essential for understanding the mechanisms underlying biological processes. Gene networks will change along with the change of environment and state. The accumulation of gene expression data from multiple states makes it possible to estimate the gene networks in various states based on computational methods. However, most existing gene network inference methods focus on estimating a gene network from a single state, ignoring the similarities between networks in different but related states. Moreover, in addition to individual edges, similarities and differences between different networks may also be driven by hub genes. But existing network inference methods rarely consider hub genes, which affects the accuracy of network estimation. In this paper, we propose a novel node-based joint Gaussian copula graphical (NJGCG) model to infer multiple gene networks from gene expression data containing heterogeneous samples jointly. Our model can handle various gene expression data with missing values. Furthermore, a tree-structured group lasso penalty is designed to identify the common and specific hub genes in different gene networks. Simulation studies show that our proposed method outperforms other compared methods in all cases. We also apply NJGCG to infer the gene networks for different stages of differentiation in mouse embryonic stem cells and different subtypes of breast cancer, and explore changes in gene networks across different stages of differentiation or different subtypes of breast cancer. The common and specific hub genes in the estimated gene networks are closely related to stem cell differentiation processes and heterogeneity within breast cancers.

Physiological Comparison of Airway Pressure Release Ventilation and Low Tidal Volume Ventilation in Acute Respiratory Distress Syndrome: A Randomized Controlled Trial.

BACKGROUND: The physiological effects of different ventilation strategies on patients with acute respiratory distress syndrome (ARDS) need to be better understood. RESEARCH QUESTION: In patients with ARDS under controlled mandatory ventilation, does airway pressure release ventilation (APRV) improve lung ventilation-perfusion matching and ventilation homogeneity compared to low tidal volume ventilation (LTV)? STUDY DESIGN AND METHODS: This study was a single-center randomized controlled trial. Patients with moderate-to-severe ARDS were randomly ventilated on APRV or LTV. Electrical impedance tomography (EIT) was utilized to assess lung ventilation and perfusion. EIT-based data and clinical variables related to respiratory and hemodynamic conditions were collected shortly before randomization (0h), and at 12 and 24 hours after randomization. RESULTS: A total of 40 subjects were included and randomized to the APRV or LTV group (20 per group). During the 24-hour trial period, patients on APRV exhibited significantly increased dorsal ventilation (difference value (24h-0h), median [25-75 percentiles]: 10.82% [2.62-13.74] vs 0.12% [-2.81-4.76], P = .017), decreased dorsal shunt (-4.67% [-6.83-0.59] vs 1.73% [-0.95-5.53], P = .008) and increased dorsal ventilation-perfusion matching (4.13% [-0.26-10.47] vs -3.29% [-5.05-2.81], P = .026) than those on LTV; no difference in ventral dead space was observed between study groups (P = .903). Additionally, two indicators of ventilation distribution heterogeneity: global inhomogeneity index significantly decreased, and center of ventilation significantly increased in the APRV group compared to the LTV group. Patients on APRV had significantly higher PaO2/FiO2, higher respiratory system static compliance (Crs) and lower PaCO2 than those on LTV at 24h. The cardiac output was comparable in both groups. INTERPRETATION: APRV, as compared to LTV, could recruit dorsal region, reduce dorsal shunt, increase dorsal ventilation-perfusion matching, and improve ventilation homogeneity of the lungs, leading to better gas exchange and Crs in patients with moderate-to-severe ARDS.

Integrated metabolomics and lipidomics investigation of the mechanism of Danggui Sini Decoction on improving lipid homeostasis in primary dysmenorrhea.

BACKGROUND: Danggui Sini Decoction (DGSND) is a classic prescription for treating primary dysmenorrhea (PD), while, the ameliorating effects of DGSND on PD and its mechanisms are not yet fully understood. PURPOSE: The present study is devoted to investigate the protective effect of DGSND against PD and the possible mechanism from the perspective of metabolomics as well as lipidomics. METHODS: DGSND was characterized by UPLC-Q-TOF/MS. The PD rat model was induced by estradiol benzoate and oxytocin, and traditional pharmacology, including writhing times, latency time, biochemical index, organ index, and histopathology were performed to evaluated the efficacy of DGSND on PD. Urine metabolomics strategy combined with functional analysis was adopted to delineate the therapeutic effect of DGSND on PD rats and anchor the crucial pathway, and lipidomics analysis was further performed with the uterine tissue as the research object to elucidate the protective mechanism of DGSND from the perspective of lipid homeostasis. Finally, western blot analysis was used to validate the expression of key metabolic enzymes in lipid metabolism. RESULTS: DGSND was effective in ameliorating writhing times, latency time, the value of prostaglandin F2α (PGF2α)/PGE2, uterus index, and morphological changes of PD rats. Metabolic signature of PD rats was primarily characterized by the disturbance of steroid hormone metabolism, amino acid metabolism, and lipid metabolism. Functional analysis revealed the urine biomarkers of PD were most related with lipid abnormality. Further lipidomics analysis indicated DGSND exerted anti-PD effects by remodeling lipid homeostasis, which might be due to the significant correlations between different kinds of lipids, especially the extremely high correlation of phosphatidylethanolamine, phosphatidylcholine, and fatty acids. Moreover, the key metabolic enzymes expression of CK, PLA2, LPCAT3, COX-2, and 5-LOX can be greatly downregulated by DGSND. CONCLUSION: Our findings demonstrated a novel protective mechanism of DGSND against PD by regulating lipid homeostasis.

OStr-DARTS: Differentiable Neural Architecture Search Based on Operation Strength.

Differentiable architecture search (DARTS) has emerged as a promising technique for effective neural architecture search, and it mainly contains two steps to find the high-performance architecture. First, the DARTS supernet that consists of mixed operations will be optimized via gradient descent. Second, the final architecture will be built by the selected operations that contribute the most to the supernet. Although DARTS improves the efficiency of neural architecture search (NAS), it suffers from the well-known degeneration issue which can lead to deteriorating architectures. Existing works mainly attribute the degeneration issue to the failure of its supernet optimization, while little attention has been paid to the selection method. In this article, we cease to apply the widely-used magnitude-based selection method and propose a novel criterion based on operation strength that estimates the importance of an operation by its effect on the final loss. We show that the degeneration issue can be effectively addressed by using the proposed criterion without any modification of supernet optimization, indicating that the magnitude-based selection method can be a critical reason for the instability of DARTS. The experiments on NAS-Bench-201 and DARTS search spaces show the effectiveness of our method.

Natural resourced polysaccharides: Preparation, purification, structural elucidation, structure-activity relationships and regulating intestinal flora, a system review.

Natural resourced polysaccharides (NRPs), as metabolites synthesized during activity of organisms, widely present in animal cell membranes or plant and microbial cell walls. NRPs have garnered extensive attention in the fields of medicine, foods, and farming owing to their distinct bioactivities and structural diversity. Despite the burgeoning growth in NRPs research, the available literature focuses primarily on a review of specific polysaccharides, necessitating an urgent need for a comprehensive summary of NRPs to offer readers a whole landscape of current advancements in NRPs research. Based on this, this article comprehensively reviews the latest research progress regarding preparation, purification, structure elucidation, structure-activity relationships and regulation of intestinal flora of NRPs in electronic databases, such as PubMed, Wiley, ScienceDirect and Web of Science from last 5 years. This review analyzes the effects of various extraction techniques on NRPs and also delves into the intrinsic correlation between the biological activity and structure of NRPs, highlighting that chemical modification can enhance their structural diversity and confer novel or improved biological functions. Moreover, this article extensively explores the application of NRP in promoting intestinal microecology balance, underscoring its significant potential as a probiotic initiator. This review lays a solid theoretical foundation for the future research and development of NRPs.