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Background: This study investigated the association between vasoactive medication exposure and mortality risk in patients with sepsis using the norepinephrine equivalent (NEE) score and vasoactive-inotropic score (VIS). Methods: This retrospective cohort study included adult patients with sepsis requiring vasoactive agents. The data were extracted from the Medical Information Mart for Intensive Care IV database. The primary outcome was 28-day mortality. Multivariate Cox regression was used to elucidate the relationship between vasoactive medication exposure and 28-day mortality, as quantified by the VIS and NEE score. Hazard ratios with 95% confidence intervals (CI) for 28-day mortality were generated, and forest plots were constructed to present the results of univariate and multivariate analyses. The Kaplan-Meier method was used to analyze the cumulative incidence of 28-day mortality. A nomogram was constructed to predict the prognosis of patients with sepsis. Results: The present study encompassed 9,032 patients diagnosed with sepsis who received vasoactive therapy, of which 4,229 patients were further analyzed at the second hour after the onset of sepsis. Distinct variations in demographic data were observed between survivors (n = 3,265, 77.21%) and non-survivors (n = 964, 22.79%). Multivariate analysis indicated that several factors, including VIS >15.04 (p = 0.001), NEE >0.10 (p < 0.001), heart rate (p = 0.045), mean arterial pressure (p = 0.009), respiratory rate (p < 0.001), oxygen saturation (p < 0.001), blood urea nitrogen (BUN) (p = 0.001), and the Acute Physiology and Chronic Health Evaluation II (p < 0.001), were significantly associated with 28-day mortality in the patients with sepsis. The NEE score, respiratory rate, oxygen saturation, and BUN were incorporated into the nomogram model with a concordance index of 0.779 and an area under the curve of 0.802 (95% CI 0.787-0.818). Conclusion: We found that the VIS and NEE score had favorable values for predicting mortality risk in patients with sepsis in the intensive care units. The VIS and NEE score in the second hour after sepsis onset were independently associated with 28-day mortality in patients with sepsis.
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Overcoming immune-mediated resistance to PD-1 blockade remains a major clinical challenge. Enhanced efficacy has been demonstrated in melanoma patients with combined nivolumab (anti-PD-1) and relatlimab (anti-LAG-3) treatment, the first in its class to be FDA approved. However, how these two inhibitory receptors synergize to hinder anti-tumor immunity remains unknown. Here, we show that CD8+ T cells deficient in both PD-1 and LAG-3, in contrast to CD8+ T cells lacking either receptor, mediate enhanced tumor clearance and long-term survival in mouse models of melanoma. PD-1- and LAG-3-deficient CD8+ T cells were transcriptionally distinct, with broad TCR clonality and enrichment of effector-like and interferon-responsive genes, resulting in enhanced IFN-γ release indicative of functionality. LAG-3 and PD-1 combined to drive T cell exhaustion, playing a dominant role in modulating TOX expression. Mechanistically, autocrine, cell-intrinsic IFN-γ signaling was required for PD-1- and LAG-3-deficient CD8+ T cells to enhance anti-tumor immunity, providing insight into how combinatorial targeting of LAG-3 and PD-1 enhances efficacy.
Subject(s)
Antigens, CD , CD8-Positive T-Lymphocytes , Interferon-gamma , Lymphocyte Activation Gene 3 Protein , Mice, Inbred C57BL , Programmed Cell Death 1 Receptor , Programmed Cell Death 1 Receptor/metabolism , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , Animals , Interferon-gamma/metabolism , Mice , Antigens, CD/metabolism , Autocrine Communication , Humans , Melanoma/immunology , Melanoma/drug therapy , Female , Cell Line, Tumor , Melanoma, Experimental/immunology , T-Cell ExhaustionABSTRACT
BACKGROUND: Childhood trauma is closely tied to adult depression, but the neurobiological mechanisms remain unclear. Previous studies suggested associations between depression and large-scale brain networks such as the Ventral Attention Network (VAN) and Somatosensory Motor Network (SMN). This study hypothesized that functional connectivity (FC) within and between these networks mediates the link between childhood trauma and adult depression. METHODS: The Childhood Trauma Questionnaire (CTQ) assessed developmental experiences, and the Hamilton Rating Scale for Depression (HAMD-17) gauged depressive symptoms. Resting-state functional magnetic resonance imaging (fMRI) analyzed FC within and between the VAN and SMN. RESULTS: Depression group exhibited significantly higher HAMD and CTQ scores, as well as elevated FC within the VAN and between the VAN and SMN (P < 0.05). Positive correlations were found between HAMD total score and FC within the VAN (P < 0.05, r = 0.35) and between the VAN and SMN (P < 0.05, r = 0.34), as well as with CTQ total score (P < 0.05, r = 0.27). Positive correlations were also observed between CTQ total score and FC within the VAN (P < 0.05, r = 0.31) and between the VAN and SMN (P < 0.05, r = 0.29). In the mediation model, FC within and between the VAN and SMN significantly mediated childhood trauma and depression. LIMITATIONS: The cross-sectional design limits causal inference. The sample size for different trauma types is relatively small, urging caution in generalizing findings. CONCLUSIONS: The study underscores the association between depression severity, VAN dysfunction, abnormal VAN-SMN FC, and childhood trauma. These findings contribute to understanding the neurobiological mechanisms underlying childhood trauma and depression.
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Alien invasive aquatic-plant (AIA) species are severely threatening the aquatic ecosystems worldwide, especially biodiversity. Although plankton have been used to monitor and address biodiversity, some gaps remain in understanding of the relationships between plankton communities and AIA species. Here, the effects of two typical AIA species (Pistia stratiotes and Eichhornia crassipes) on plankton communities in freshwater with a native plant Vallisneria natans were investigated using a 50-d microcosm experiment. Results showed that AIA species significantly decreased water pH and dissolved oxygen while increased oxidation-reduction potential (p < 0.05). AIA species, especially P. stratiotes, significantly inhibited dry biomass accumulation in V. natans by an average rate of 39.0 %, decreased water pH by up to 14.62 %, and increased aboveground lengths and chlorophyll contents of V. natans by up to 36.2 % and 63.7 % (p < 0.05), respectively. These species further modified the growth strategy of V. natans from dry biomass accumulation to aboveground elongation. Although the AIA species did not alter plankton diversity (p > 0.05), but they changed their dominant species, functional communities (e.g., Groups D and TB), and co-occurrence networks. P. stratiotes decreased the average degree of the networks by 12.37-19.02 % and the graph density by 10.53-14.47 %, while E. crassipes decreased the modularity of the networks by 10.24 % compared with the control (without AIA species), respectively. Overall, AIA species inhibited the growth of V. natans and decreased the stability of plankton communities and their resistance to environmental disturbances. These findings enhance our understanding of how AIA species affect the growth of native plants and variations in plankton communities, thereby providing a theoretical basis for improving the ecological function and safety of freshwater.
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Approaches to reverse or limit regulatory T cell (Treg) insufficiency are of great interest for development of immunotherapeutic treatments for autoimmune patients, including type 1 diabetes. Treg insufficiency is heavily implicated in the progression of autoimmune diabetes in the NOD mouse model and is characterized by defects in Treg numbers, development, and/or function. Utilizing a Treg-centric screen, we show that intraislet Tregs have a uniquely dysfunctional phenotype, hallmarked by an almost complete lack of neuropilin-1 (Nrp1), a cell surface receptor required to maintain Treg stability. Intraislet Nrp1- Tregs exhibit hallmark features of fragility, including reduced suppressive capacity, decreased CD73 and Helios, and increased Rorγt and Tbet. Intraislet Nrp1- Tregs also exhibit decreased Foxp3 expression on a per cell basis, suggesting that Nrp1 may also be required for long-term Treg stability. Mechanistically, Treg-restricted augmentation of Nrp1 expression limited the onset of autoimmune diabetes in NOD mice suggesting that Nrp1 critically impacts intraislet Treg function. Transcriptional analysis showed that Nrp1 restoration led to an increase in markers and pathways of TCR signaling, survival, and suppression, and when Nrp1 protein expression is examined by cellular indexing of transcriptomes and epitopes by sequencing, significant differences were observed between Nrp1+ and Nrp1- Tregs in all tissues, particularly in markers of Treg fragility. This translated into substantive differences between Nrp1+ and Nrp1- Tregs that afforded the former with a competitive advantage in the islets. Taken together, these data suggest that maintenance of Nrp1 expression and signaling on Tregs limits diabetes onset and may serve as a strategy to combat Treg insufficiency in autoimmune disease.
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Pre-clinical models indicate that Amiloride (AMD) reduces baroreflex sensitivity and perturbs homeostatic blood pressure (BP) regulation. However, it remains unclear whether these findings translate to humans. This study investigated whether oral administration of AMD reduces spontaneous cardiac and sympathetic baroreflex sensitivity and perturbs BP regulation in healthy young humans. Heart rate (HR; electrocardiography), beat-to-beat BP (photoplethysmography), and muscle sympathetic activity (MSNA, microneurography) were continuously measured in 10 young subjects (4 females) during rest across two randomized experimental visits: (1) after 3 hours of oral administration of placebo (PLA - 10 mg of methylcellulose within a gelatin capsule) and (2) after 3 hours of oral administration of AMD (10 mg). Visits were separated for at least 48 hours. We calculated the standard deviation and other indices of BP variability. Spontaneous cardiac baroreflex was assessed via the sequence technique and cardiac autonomic modulation through time- and frequency-domain HR variability. The sensitivity (gain) of the sympathetic baroreflex was determined via weighted linear regression analysis between MSNA and diastolic BP. AMD did not affect HR, BP, and MSNA compared to PLA. Indexes of cardiac autonomic modulation (time- and frequency-domain HR variability) and BP variability were also unchanged after AMD ingestion. Likewise, AMD did not modify the gain of both spontaneous cardiac and sympathetic arterial baroreflex. A single oral dose of AMD does not affect spontaneous arterial baroreflex sensitivity and BP variability in healthy young adults.
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Residual normal plasma cells (NPCs), which compete with tumor plasma cells, play an important role in multiple myeloma. However, large-scale cohort studies investigating residual NPCs, especially at the minimal residual disease (MRD) phase, are currently lacking. In this study, we conducted a comprehensive investigation into the clinical significance of residual NPCs throughout the entire disease course in 1363 myeloma patients from the NICHE cohort (NCT04645199). Our results revealed that myeloma patients with high baseline NPCs ratio (≥5%) exhibited distinct indolent features, characterized by lower tumor burden, reduced frequencies of cytopenia, immunoparesis, and high-risk cytogenetics. Importantly, high residual NPCs ratio at diagnosis or relapse was independently associated with favorable survival. High absolute percentages of NPCs at undetectable MRD were related with superior clinical benefit and immune reconstitution. At MRD-positive phases, grouping based on NPCs ratio (<50%, 50-90%, ≥90%) demonstrated better risk stratification compared to residual tumor log levels. Based on the time-dependent NPCs ratio trend, we developed a dynamic MRD model that classifies patients into three groups with diverse longitudinal trends, leading to distinct prognoses. Collectively, residual NPCs serves not only as a valuable complementary biomarker for risk stratification but also provides valuable insights on reclassifications and kinetics of MRD.
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Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646.
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Mesenchymal stem cells (MSCs) are essential in regenerative medicine. However, conventional expansion and harvesting methods often fail to maintain the essential extracellular matrix (ECM) components, which are crucial for their functionality and efficacy in therapeutic applications. Here, we introduce a bone marrow-inspired macroporous hydrogel designed for the large-scale production of MSC-ECM spheroids. Through a soft-templating approach leveraging liquid-liquid phase separation, we engineer macroporous hydrogels with customizable features, including pore size, stiffness, bioactive ligand distribution, and enzyme-responsive degradability. These tailored environments are conducive to optimal MSC proliferation and ease of harvesting. We find that soft hydrogels enhance mechanotransduction in MSCs, establishing a standard for hydrogel-based 3D cell culture. Within these hydrogels, MSCs exist as both cohesive spheroids, preserving their innate vitality, and as migrating entities that actively secrete functional ECM proteins. Additionally, we also introduce a gentle, enzymatic harvesting method that breaks down the hydrogels, allowing MSCs and secreted ECM to naturally form MSC-ECM spheroids. These spheroids display heightened stemness and differentiation capacity, mirroring the benefits of a native ECM milieu. Our research underscores the significance of sophisticated materials design in nurturing distinct MSC subpopulations, facilitating the generation of MSC-ECM spheroids with enhanced therapeutic potential.
Subject(s)
Extracellular Matrix , Hydrogels , Mesenchymal Stem Cells , Spheroids, Cellular , Mesenchymal Stem Cells/cytology , Mesenchymal Stem Cells/metabolism , Hydrogels/chemistry , Extracellular Matrix/metabolism , Spheroids, Cellular/cytology , Spheroids, Cellular/metabolism , Humans , Cell Differentiation , Cell Culture Techniques/methods , Cell Proliferation , Porosity , Mechanotransduction, Cellular/physiology , Cells, CulturedABSTRACT
Engineered Living Materials (ELMs) are materials composed of or incorporating living cells as essential functional units. These materials can be created using bottom-up approaches, where engineered cells spontaneously form well-defined aggregates. Alternatively, top-down methods employ advanced materials science techniques to integrate cells with various kinds of materials, creating hybrids where cells and materials are intricately combined. ELMs blend synthetic biology with materials science, allowing for dynamic responses to environmental stimuli such as stress, pH, humidity, temperature, and light. These materials exhibit unique "living" properties, including self-healing, self-replication, and environmental adaptability, making them highly suitable for a wide range of applications in medicine, environmental conservation, and manufacturing. Their inherent biocompatibility and ability to undergo genetic modifications allow for customized functionalities and prolonged sustainability. This review highlights the transformative impact of ELMs over recent decades, particularly in healthcare and environmental protection. We discuss current preparation methods, including the use of endogenous and exogenous scaffolds, living assembly, 3D bioprinting, and electrospinning. Emphasis is placed on ongoing research and technological advancements necessary to enhance the safety, functionality, and practical applicability of ELMs in real-world contexts.
Subject(s)
Synthetic Biology , Synthetic Biology/methods , Bioprinting/methods , Tissue Engineering/methods , Biocompatible Materials/chemistry , Humans , Printing, Three-Dimensional , Tissue Scaffolds/chemistry , AnimalsABSTRACT
Weakly coupled mode-division multiplexing (MDM) transmission over legacy laid multimode fiber (MMF) has great economic efficiency and can enormously enhance the capacity of short-reach optical interconnections. In order to be compatible with cost-efficient intensity-modulation/direct-detection (IM/DD) transceivers, weakly coupled mode-group demultiplexers that can simultaneously receive each mode group of MMFs are highly desired. In this paper, we propose a scalable low-modal-crosstalk mode-group demultiplexer over MMF based on multiplane light conversion (MPLC). Multiple input Hermite-Gaussian (HG) modes of MMF are first converted to bridging modes that are composed of H G 00 modes distributed as a right-angle triangle in Cartesian coordinates, and then each H G 00 mode belonging to a degenerate mode group is mapped to different overlapped H G n0 modes with vertical orientation for simultaneous detection. With the help of bridging modes, the MPLC-based mode-group demultiplexer can efficiently demultiplex all mode groups in standard MMFs with less than 20 phase masks. A nine-mode-group demultiplexer is further designed for demonstration, and simulation results show that the MPLC-based demultiplexer achieves low modal crosstalk of lower than -22.3d B at 1550 nm and lower than -17.9d B over the C-band for all the nine mode groups with only 16 phase masks.
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We propose an all-fiber mode-selective power splitter (MSPS) for non-circular-symmetric LPlm (l = 1, 2, ) modes, which is suitable for multicasting and optical performance monitoring in mode-division multiplexing optical fiber networks. The MSPSs are asymmetric two-core few-mode directional couplers composed of a few-mode fiber and a two-mode fiber. We theoretically studied the three conditions required by the MSPSs. By carefully choosing the core-to-core distance and coupling length, the MSPS can achieve arbitrary splitting ratio regardless of the modal field orientation of the input non-circular-symmetric LP mode. By using an asymmetric structure, the MSPS can ensure the power splitting only happens on the target non-circular-symmetric LP mode when the phase matching condition is satisfied. In addition, we designed and numerically simulated LP31 MSPSs with four kinds of splitting ratios, among which the one with 90/10 splitting ratio was fabricated based on tapering and polishing method. The fabricated LP31 MSPS is characterized and the results show that its splitting ratio is much more stable than regular LP31 mode-selective coupler.
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BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)ï¼and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.
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Neuroinflammation is pivotal in the development of neuropathic pain (NeP). While mitochondrial deoxyribonucleic acid (mtDNA) and cyclic GMP-AMP synthase (cGAS) are recognized for inducing inflammation in various neurological disorders, their involvement in NeP remains ambiguous. In this study, we examined: (1) the changes in mtDNA and cGAS in mice with NeP induced by chronic constriction injury (CCI) of the sciatic nerve, whether mtDNA triggers inflammation via the cGAS signaling; (2) the effects of RU.521, a cGAS antagonist, on CCI-induced nociception (allodynia and hyperalgesia) and relative inflammatory protein expression; (3) the activation of microglia and the cGAS-IFN pathway mediated by mtDNA in BV2 cell; (4) the effect of RU.521 on mtDNA-induced inflammatory response in BV2 cells. Results revealed reduced mtDNA levels in the sciatic nerve but increased levels in the spinal cord of CCI mice, along with elevated cGAS expression and inflammatory factors. RU.521 alleviated nociceptive behaviors in CCI mice, possibly by normalizing cGAS levels and suppressing inflammation. Neuron-derived mtDNA provoked cellular activation and upregulated cGAS signaling in BV2 cells. Additionally, RU.521 and DNase I effectively inhibited cGAS-induced inflammation. These findings underscore the critical role of mtDNA accumulation and mtDNA-mediated cGAS signaling in NeP development after peripheral nerve injury.
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Objective: To investigate the effect of AngioJet thrombectomy combined with catheter-contact thrombolysis on the therapeutic effect and safety of patients with lower extremity deep vein thrombosis (LEDVT). Methods: 48 patients with LEDVT admitted to our hospital from February 2020 to January 2022 were selected as the study objects and were divided into a control group (n = 24) and research group (n = 24) by random number table method. The control group was treated with catheter-directed thrombolysis (CDT) while the research group was treated with a combination of CDT and AngioJet thrombectomy. The perioperative indicators, symptom improvement, thrombolytic indicators, coagulation function, and the incidence of complications were compared. Results: After treatment, the time of thrombectomy, the total dosage of urokinase, and the length of hospital stay in the research group were all lower than those in the control group (P < .05). After treatment, the peripheral diameter differences of large contralateral crus and calf of the two groups were lower than those before treatment; these peripheral diameter differences of the research group were significantly lower than those of the control group, and the differences were statistically significant (P < .05). After treatment, the venous patency rate, thrombus clearance rate, detumescence rate of the affected limb, and the proportion of grade III in the thrombolysis grade in the research group were all higher than those in the control group. The incidence of complications in the research group after treatment (8.33%) was significantly lower than in the control group (20.83%), with P < .05. Conclusion: AngioJet thrombectomy combined with catheter-contact thrombolysis in the treatment of patients with LEDVT can significantly improve the venous patency rate and thrombolysis rate, regulate the level of coagulation factors, and achieve good thrombolytic effect and safety.
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Purpose: Sleep structure is crucial in sleep research, characterized by its dynamic nature and temporal progression. Traditional 30-second epochs falter in capturing the intricate subtleties of various micro-sleep states. This paper introduces an innovative artificial neural network model to generate continuous sleep depth value (SDV), utilizing a novel multi-feature fusion approach with EEG data, seamlessly integrating temporal consistency. Methods: The study involved 50 normal and 100 obstructive sleep apnea-hypopnea syndrome (OSAHS) participants. After segmenting the sleep data into 3-second intervals, a diverse array of 38 feature values were meticulously extracted, including power, spectrum entropy, frequency band duration and so on. The ensemble random forest model calculated the timing fitness value for all the features, from which the top 7 time-correlated features were selected to create detailed sleep sample values ranging from 0 to 1. Subsequently, an artificial neural network (ANN) model was trained to delineate sleep continuity details, unravel concealed patterns, and far surpassed the traditional 5-stage categorization (W, N1, N2, N3, and REM). Results: The SDV changes from wakeful stage (mean 0.7021, standard deviation 0.2702) to stage N3 (mean 0.0396, standard deviation 0.0969). During the arousal epochs, the SDV increases from the range (0.1 to 0.3) to the range around 0.7, and decreases below 0.3. When in the deep sleep (≤0.1), the probability of arousal of normal individuals is less than 10%, while the average arousal probability of OSA patients is close to 30%. Conclusion: A sleep continuity model is proposed based on multi-feature fusion, which generates SDV ranging from 0 to 1 (representing deep sleep to wakefulness). It can capture the nuances of the traditional five stages and subtle differences in microstates of sleep, considered as a complement or even an alternative to traditional sleep analysis.
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Rivers are important reservoirs of antibiotic resistance genes (ARGs). However, most current studies have focused on the temporal and spatial distribution, and data on the differences in the species and abundance of ARGs between urban and rural rivers is still lacking for certain areas. In view of this, two rural rivers and three urban rivers were selected in Shijiazhuang City. In both December 2020 and April 2021, sediments were collected at 15 sampling sites. Metagenomic sequencing technology was used to compare the differences in temporal-spatial variation for ARGs in sediments. The results showed that:â 162 and 79 ARGs were detected in urban (4 776 ±4 452) and rural rivers (1 043 ±632), respectively. The abundance and species of ARGs in urban rivers were higher than those in rural rivers. â¡ The relative abundances of sulfonamide (SAs,27 %), aminoglycoside (AGs,26 %), and multidrug (MDs,15 %) ARGs had the highest abundance in urban rivers, whereas the relative abundance of MDs ARGs was highest in rural rivers (65 %). On the whole, the complexity of ARGs in urban rivers was higher than that in rural rivers. ⢠There was a significant positive correlation between SAs, AGs, MDs, tetracycline, phenicol, macrolides-lincosamids-streptogramins (MLS), ß-lactams, and diaminopyrimidine ARGs in urban rivers (P < 0.01); however, there was a significant negative correlation between glycopeptide ARGs and all types of ARGs (P < 0.05 and P < 0.01). There was a significant positive correlation between MDs and SAs ARGs in rural rivers (P < 0.05), but there was a significant negative correlation between amino aminocoumarin, peptide, rifamycin, and fosfomycin ARGs (P < 0.05 and P < 0.01). ⣠For the temporal variation in urban rivers, 162 ARGs (4 776 ±4 452) and 148 ARGs (5 673 ±5 626) were detected in December and April, respectively. For the temporal variation in rural rivers, 79 species (1 043 ±632) and 46 species (467 ±183) were detected in December and April, respectively. ⤠RDA analysis results showed that the spatial-temporal distributions of ARGs in urban and rural rivers were different. Correlation analysis showed that the ARGs in urban rivers were significantly correlated with the number of industrial enterprises, whereas the ARGs in rural rivers were significantly correlated with the output value of animal husbandry. In general, this study identified the main influencing factors for ARGs in different rivers and provided data support for ARGs risk management in different rivers.
Subject(s)
Cities , Drug Resistance, Microbial , Geologic Sediments , Rivers , Geologic Sediments/microbiology , China , Drug Resistance, Microbial/genetics , Environmental Monitoring , Genes, Bacterial , Spatio-Temporal Analysis , Anti-Bacterial Agents/analysisABSTRACT
In order to explore the evolution law and driving mechanism of aerobic denitrification bacteria in Baiyangdian Lake under different hydrological scenarios, based on water quality survey and high-throughput sequencing technology, this study conducted a water quality factor analysis and aerobic denitrification bacteria α-diversity analysis, species composition, and network analysis. The results showed that the water body of Baiyangdian Lake was weakly alkaline, with the highest T and the lowest DO in the rainy season and the lowest T and the highest DO in the freezing season. There were significant differences between NH4+-N, NO2--N, NO3--N, TN, permanganate index, Fe, and Mn in Baiyangdian water under different hydrological scenarios (P < 0.01), and there was no significant difference in TP under different hydrological scenarios (P > 0.05). The largest category in water bodies under different hydrological scenarios was Proteobacteria, and the genera with a higher relative abundance were Magnetospirillum, Aeromonas, Pseudomonas, Azospirillum, and Bradyrhizobium. In addition, within the aerobic denitrifying bacteria community, there were significant differences in α-diversity (P < 0.001), with the highest abundance of microbial communities occurring during the freezing period, and the highest diversity and evenness of microbial communities during the dry and freezing periods. According to the RDA and Mantel analyses, the water quality driving factors of flora were different under different hydrological scenarios. The water quality driving factors of flora in the dry season were pH, NO3--N, NO2--N, and permanganate index; the driving factors of flora in the rainy season were pH, T, DO, NO2--N, and TP; the driving factors of flora in the normal season were NO2--N, Fe, and permanganate index; and the driving factors of flora in the freezing season were NO3--N and NONO2--N. Network analysis showed that there were temporal differences in species related to water quality driving factors. The genera related to water quality driving factors during the dry season were Magnetospirillum, Aeromonas, and Azoarcus, whereas the genera related to the rainy season were Magnetospirillum, Pseudomonas, and Aeromonas. The genera related to the normal season were Magnetospirillum, Pseudomonas, and Limnohabitans, and the genera related to the freezing period were Magnetospirillum, Azoarcus, and Pseudomonas. The relationship between key water quality factors (mainly T, DO, NO3--N, and permanganate index) and aerobic denitrification flora in different hydrological scenarios was gradually changing with time. In conclusion, the study on the evolution characteristics of aerobic denitrification bacteria in Baiyangdian Lake under different hydrological scenarios and the driving mechanism of environmental factors could provide a basis for understanding the evolution mechanism of aerobic denitrification bacteria in the natural environment.
Subject(s)
Denitrification , Lakes , Water Quality , China , Lakes/microbiology , Hydrology , Bacteria, Aerobic/metabolism , Bacteria, Aerobic/isolation & purification , Environmental Monitoring , Proteobacteria/isolation & purification , Water Pollutants, Chemical/analysis , Water Pollutants, Chemical/metabolismABSTRACT
PURPOSE: In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA-sequencing (scRNA-seq) to paired diagnostic and post-treatment bone marrow (BM) samples. EXPERIMENTAL DESIGN: scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (MGUS) (n = 1), MM patients at diagnosis (n = 19), MM post-treatment (n = 17), and one healthy donor. The single-cell transcriptome data of malignant plasma cells and the surrounding immune microenvironment were analyzed. RESULTS: Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-), as well as clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift towards fatty acid oxidation in cycling-resistant plasma cells (PCs), while selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and non-genetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant plasma cells and the tumor microenvironment (TME). Selective PCs showed the most robust cellular interactions with the TME. CONCLUSIONS: These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in multiple myeloma.