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Several studies have investigated the gut bacterial composition of wild ungulates in the Qinghai-Xizang Plateau. However, the relationship between their gut microbiome dendrograms and their phylogenetic tree remains unclear. In this study, we analyzed 45 amplicons (V3-V4 region of the 16S rRNA gene) from five wild ungulates-Pseudois nayaur, Pantholops hodgsonii, Gazella subgutturosa, Bos grunniens, and Equus kiang-from the Qinghai-Xizang Plateau to clarify the relationship between their phylogenies and gut microbiome dendrograms. The unweighted pair group method with arithmetic mean analysis and hierarchical clustering analysis indicated that G. subgutturosa is closely related to P. nayaur; however, these results were inconsistent with their phylogenetic trees. Additionally, the indicator genera in the microbiome of each wild ungulate showed strong associations with the diets and habitats of their host. Thus, diet and space niche differentiation may primarily account for the differences between the gut microbiome characteristics of these wild ungulates and their phylogeny. In summary, our research provides insights into the evolutionary factors influencing the gut microbiome of wild ungulates in the Qinghai-Xizang Plateau.

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Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among patients with epilepsy, causing a global public health burden. The underlying mechanisms of SUDEP remain elusive, and effective prevention or treatment strategies require further investigation. A major challenge in current SUDEP research is the lack of an ideal model that maximally mimics the human condition. Animal models are important for revealing the potential pathogenesis of SUDEP and preventing its occurrence; however, they have potential limitations due to species differences that prevent them from precisely replicating the intricate physiological and pathological processes of human disease. This Review provides a comprehensive overview of several available SUDEP animal models, highlighting their pros and cons. More importantly, we further propose the establishment of an ideal model based on brain-computer interfaces and artificial intelligence, hoping to offer new insights into potential advancements in SUDEP research. In doing so, we hope to provide valuable information for SUDEP researchers, offer new insights into the pathogenesis of SUDEP and open new avenues for the development of strategies to prevent SUDEP.

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The evolutionary patterns of the mitochondrial genome are influenced by both adaptive and nonadaptive forces, with their contributions varying among taxa. There appears to be a correlation linking mutagenesis and latitude, which could be due to differences in metabolic rates. These discrepancies in metabolic rates exhibit a positive connection with mutation pressure. On this basis, we hypothesise that nonadaptive forces play a role in the differences in mutation rates observed along latitudinal gradients. In this study, we selected widely distributed carnivores as representatives of mammals to test our hypothesis. We examined the correlations between the dN/dS ratio (ω), as well as the substitution rates (dS and dN), of 13 PCGs in the mtDNA of 122 carnivores, and the latitude and climatic factors. We found that taxa distributed in higher latitudes tend to have higher substitution rates, but not ω values indicating selective pressure. Notably, dN shows a strong positive correlation with dS, although dS is primarily influenced by mutation pressure, while dN is also influenced by effective population size (N e ). Phylogenetic generalised least squares (PGLS) regression analyses showed that both substitution rates were correlated with climatic factors representing the temperature, precipitation and variability of climate. Based on our findings, we propose that the mutations are primarily influenced by nonadaptive forces (mutation pressure). This forms the fundamental premise for natural selection and speciation. Moreover, the correlation between substitution rates and latitudinal distribution and climate, which are outcomes of nonadaptive factors, can aid in comprehending the global distribution of species diversity.

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Per- and polyfluoroalkyl substances (PFASs) are prevalently present in oceans, posing potential health risks to organisms and humans. However, information of PFAS distribution in remote open oceans is limited. In the Kuroshio Extension region of Northwest Pacific Ocean (6 stations), samples of 84 seawater (0-5800 m), 9 sediments, and 9 organisms were taken, and 25, 10, and 15 out of 29 PFASs were identified, respectively, with perfluorooctanoic acid (PFOA) and perfluorooctane sulfonates (PFOS) as the most dominant PFASs. In seawater, ΣPFASs concentration decreased from the Kuroshio region (4.47 ng/L) to the Oyashio region (3.15 ng/L), and decreased with increasing seawater depth under the function of biological and physical pumps. Additionally, 12 precursors and emerging PFASs, including perfluorooctane sulfonamide (FOSA, 0.20 ng/L), were detected. In sediment, PFASs (5.92-12.97 pg/g) were identified at depths exceeding 5000 m, including 3 precursors (e.g., FOSA, 0.82 pg/g). ΣPFASs contents were 27.12, 31.47 and 36.97 ng/g (dry weight) in brown algae (Phaeophyceae), barnacles (Balanus), and lanternfish (Myctophiformes), respectively, in which two precursors (e.g., FOSA, 0.09-0.12 ng/g) were also identified. A correlation with the trophic position was found for PFOA bioaccumulation. These findings provide useful information on PFAS distribution in the global open ocean environments.

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Kuroshio Extension (KE) is the most active region of oceanic change in the North Pacific Ocean, which provides an essential place for the survival of marine microorganisms. However, Vertical changes in microbial communities in the Kuroshio Extension and the mechanisms by which environmental factors drive vertical changes in community structure remain unclear. In this work, microbial diversity, abundance, and community structure of 12 water layers (from surface to bottom) at five stations were uncovered by 16S rRNA gene high-throughput sequencing. Microbial diversity and richness decreased with increasing seawater depth. Microorganisms in the euphotic zone can be well separated from other zones based on NMDS analysis. Proteobacteria (65.20%), Bacteroidota (8.48%), Actinobacteriota (5.76%), and Crenarchaeota (4.49%) accounted for a relatively large proportion and their distribution is similar in four zones. Most of microorganisms were significantly (Spearman test, p < 0.05) correlated with salinity, density, pressure, and temperature. This work enhances our understanding of vertical microbial diversity and provides insights into the pelagic microbial community structure.

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BACKGROUND AND PURPOSE: To evaluate the radiomics-based model performance for differentiation between glioblastoma (GB) and brain metastases (BM) using magnetization prepared rapid gradient echo (MPRAGE) and volumetric interpolated breath-hold examination (VIBE) T1-contrast enhanced sequences. MATERIALS AND METHODS: T1-CE MPRAGE and VIBE sequences acquired in 108 patients (31 GBs and 77 BM) during the same MRI session were retrospectively evaluated. Post standardized image pre-processing and segmentation, radiomics features were extracted from necrotic and enhancing tumor components. Pearson correlation analysis of radiomics features from tumor subcomponents was also performed. A total of 90 machine learning (ML) pipelines were evaluated using a five-fold cross validation. Performance was measured by mean AUC-ROC, Log-loss and Brier scores. RESULTS: A feature-wise comparison showed that the radiomic features between sequences were strongly correlated, with the highest correlation for shape-based features. The mean AUC across the top-ten pipelines ranged between 0.851-0.890 with T1-CE MPRAGE and between 0.869-0.907 with T1-CE VIBE sequence. Top performing models for the MPRAGE sequence commonly used support vector machines, while those for VIBE sequence used either support vector machines or random forest. Common feature reduction methods for top-performing models included linear combination filter and least absolute shrinkage and selection operator (LASSO) for both sequences. For the same ML-feature reduction pipeline, model performances were comparable (AUC-ROC difference range: [-0.078, 0.046]). CONCLUSIONS: Radiomic features derived from T1-CE MPRAGE and VIBE sequences are strongly correlated and may have similar overall classification performance for differentiating GB from BM. ABBREVIATIONS: BM: Brain metastases, GB: glioblastoma, T1-CE: T1 contrast enhanced sequence, MPRAGE: magnetization prepared rapid gradient echo, ML: machine learning, RF: random forest, VIBE: volumetric interpolated breath-hold examination.

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Recently, the introduction of fluorosulfonyl (-SO2F) groups have attracted considerable research interests, as this moiety could often afford enhanced activities and new functions in the context of chemical biology and drug discovery. Herein, we report the design and synthesis of 1-fluorosulfamoyl-pyridinium (FSAP) salts, which could serve as an effective photoredox-active precursor to fluorosulfamoyl radicals and enable the direct radical C-H fluorosulfonamidation of a variety of (hetero)arenes. This method features mild conditions, visible light, broad substrate scope, good group tolerance, etc., and a metal-free protocol is also viable by using organic photocatalysts. Further, FSAP can also be applied to the radical functionalization of alkenes via 1,2-difunctionalization, radical distal migration, tandem radical-polar crossover reactions, etc. In addition, a formal C-H methylamination of (hetero)arenes by combining this radical C-H fluorosulfonamidation with subsequent hydrolysis as well as product derivatization are also demonstrated.

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Accurate segmentation of retinal layers in optical coherence tomography (OCT) images is critical for assessing diseases that affect the optic nerve, but existing automated algorithms often fail when pathology causes irregular layer topology, such as extreme thinning of the ganglion cell-inner plexiform layer (GCIPL). Deep LOGISMOS, a hybrid approach that combines the strengths of deep learning and 3D graph search to overcome their limitations, was developed to improve the accuracy, robustness and generalizability of retinal layer segmentation. The method was trained on 124 OCT volumes from both eyes of 31 non-arteritic anterior ischemic optic neuropathy (NAION) patients and tested on three cross-sectional datasets with available reference tracings: Test-NAION (40 volumes from both eyes of 20 NAION subjects), Test-G (29 volumes from 29 glaucoma subjects/eyes), and Test-JHU (35 volumes from 21 multiple sclerosis and 14 control subjects/eyes) and one longitudinal dataset without reference tracings: Test-G-L (155 volumes from 15 glaucoma patients/eyes). In the three test datasets with reference tracings (Test-NAION, Test-G, and Test-JHU), Deep LOGISMOS achieved very high Dice similarity coefficients (%) on GCIPL: 89.97±3.59, 90.63±2.56, and 94.06±1.76, respectively. In the same context, Deep LOGISMOS outperformed the Iowa reference algorithms by improving the Dice score by 17.5, 5.4, and 7.5, and also surpassed the deep learning framework nnU-Net with improvements of 4.4, 3.7, and 1.0. For the 15 severe glaucoma eyes with marked GCIPL thinning (Test-G-L), it demonstrated reliable regional GCIPL thickness measurement over five years. The proposed Deep LOGISMOS approach has potential to enhance precise quantification of retinal structures, aiding diagnosis and treatment management of optic nerve diseases.

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The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

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Locomotor preferences and habitat types may drive animal evolution. In this study, we speculated that locomotor preference and habitat type may have diverse influences on Bovidae mitochondrial genes. We used selection pressure and statistical analysis to explore the evolution of mitochondrial DNA (mtDNA) protein-coding genes (PCGs) from diverse locomotor preferences and habitat types. Our study demonstrates that locomotor preference (energy demand) drives the evolution of Bovidae in mtDNA PCGs. The habitat types had no significant effect on the rate of evolution in Bovidae mitochondrial genes. Our study provides deep insight into the adaptation of Bovidae.

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The sorption behavior of phosphorus on marine sediments in the presence of black carbon derived from fly ash (FC) was studied. For both the FC and sediment samples, the kinetic curves could be described by a two-compartment first order equation, and the isotherms fit the Freundlich and Langmuir models well. The high specific surface area with abundant acidic functional groups of FC promoted the sorption and make this process more irreversible. The effects were more significant with higher amount of FC added. After sorption, more significant increase in Ex-P, Fe/Al-P and CaP was found in the sediment with FC added, while the organic groups in FC rarely react with phosphorus to form OP. The pH of medium influenced the sorption character, and FC promoted the process significantly at pH < pHPZNPC. The sorption was endothermic with an increase in randomness. The presence of FC had little effects on the thermodynamic parameters.

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Autotrophic microorganisms play a crucial role in soil CO2 assimilation. Although microplastic pollution is recognized as a significant global concern, its precise impact on carbon sequestration by autotrophic microorganisms in agroecosystem soil remains poorly understood. This study conducted microcosm experiments to explore how conventional polystyrene (PS) and biodegradable poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) microplastics affect carbon fixation rates (CFRs) and the community characteristics of soil autotrophic microorganisms in paddy agroecosystems. The results showed that compared with the control groups, 0.5 % and 1 % microplastic treatments significantly reduced soil CFRs by 11.8 - 24.5 % and 18.7 - 32.3 %, respectively. PS microplastics exerted a stronger inhibition effect on CFRs than PHBV microplastics in bulk soil. However, no significant difference was observed in the inhibition of CFRs by both types of microplastics in rhizosphere soils. Additionally, PS and PHBV microplastics altered the structure of autotrophic microbial communities, resulting in more stochastically dominated assembly and looser, more fragile coexistence networks compared to control groups. Moreover, microplastics drove the changes in autotrophic microbial carbon fixation primarily through their direct interference and the indirect effect by increasing soil organic carbon levels. Our findings enhance the understanding and predictive capabilities regarding the impacts of microplastic pollution on carbon sinks in agricultural soils.

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Body size may drive the molecular evolution of mitochondrial genes in response to changes in energy requirements across species of different sizes. In this study, we perform selection pressure analysis and phylogenetic independent contrasts (PIC) to investigate the association between molecular evolution of mitochondrial genome protein-coding genes (mtDNA PCGs) and body size in terrestrial Cetartiodactyla. Employing selection pressure analysis, we observe that the average non-synonymous/synonymous substitution rate ratio (ω) of mtDNA PCGs is significantly reduced in small-bodied species relative to their medium and large counterparts. PIC analysis further confirms that ω values are positively correlated with body size (R2 = 0.162, p = 0.0016). Our results suggest that mtDNA PCGs of small-bodied species experience much stronger purifying selection as they need to maintain a heightened metabolic rate. On the other hand, larger-bodied species may face less stringent selective pressures on their mtDNA PCGs, potentially due to reduced relative energy expenditure per unit mass. Furthermore, we identify several genes that undergo positive selection, possibly linked to species adaptation to specific environments. Therefore, despite purifying selection being the predominant force in the evolution of mtDNA PCGs, positive selection can also occur during the process of adaptive evolution.

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The two existing clades of Galloanseres, orders Galliformes (landfowl) and Anseriformes (waterfowl), exhibit dramatically different evolutionary trends. Mitochondria serve as primary sites for energy production in organisms, and numerous studies have revealed their role in biological evolution and ecological adaptation. We assembled the complete mitogenome sequences of two species of the genus Aythya within Anseriformes: Aythya baeri and Aythya marila. A phylogenetic tree was constructed for 142 species within Galloanseres, and their divergence times were inferred. The divergence between Galliformes and Anseriformes occurred ~79.62 million years ago (Mya), followed by rapid evolution and diversification after the Middle Miocene (~13.82 Mya). The analysis of selective pressure indicated that the mitochondrial protein-coding genes (PCGs) of Galloanseres species have predominantly undergone purifying selection. The free-ratio model revealed that the evolutionary rates of COX1 and COX3 were lower than those of the other PCGs, whereas ND2 and ND6 had faster evolutionary rates. The CmC model also indicated that most PCGs in Anseriformes exhibited stronger selective constraints. Our study suggests that the distinct evolutionary trends and energy requirements of Galliformes and Anseriformes drive different evolutionary patterns in the mitogenome.

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Introduction: To analyze the risk factors affecting recurrence in early-stage hepatocellular carcinoma (HCC) patients treated with ablation and then establish a nomogram to provide a clear and accessible representation of the patients' recurrence risk. Methods: Collect demographic and clinical data of 898 early-stage HCC patients who underwent ablation treatment at Beijing You'an Hospital, affiliated with Capital Medical University from January 2014 to December 2022. Patients admitted from 2014 to 2018 were included in the training cohort, while 2019 to 2022 were in the validation cohort. Lasso and Cox regression was used to screen independent risk factors for HCC patients recurrence, and a nomogram was then constructed based on the screened factors. Results: Age, gender, Barcelona Clinic Liver Cancer (BCLC) stage, tumor size, globulin (Glob) and γ-glutamyl transpeptidase (γ-GT) were finally incorporated in the nomogram for predicting the recurrence-free survival (RFS) of patients. We further confirmed that the nomogram has optimal discrimination, consistency and clinical utility by the C-index, Receiver Operating Characteristic Curve (ROC), calibration curve and Decision Curve Analysis (DCA). Moreover, we divided the patients into different risk groups and found that the nomogram can effectively identify the high recurrence risk patients by the Kaplan-Meier curves. Conclusion: This study developed a nomogram using Lasso-Cox regression to predict RFS in early-stage HCC patients following ablation, aiding clinicians in identifying high-risk groups for personalized follow-up treatments.

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Marine microorganisms are primary drivers of the elemental cycling. The interaction between heterotrophic prokaryotes and biomarker (n-alkane) in Kuroshio Extension (KE) remains unclear. Here, we categorize KE into three characteristic areas based on ocean temperatures and nutrient conditions: Cold Water Area (CWA), Mixed Area (MA), and Warm Water Area (WWA). A total of 49 samples were collected during two-year voyage to identify the source of n-alkane and associated degrading microorganisms. Total n-alkane concentrations (Σn-Alk) in surface water (SW) spanned from 1,308 ng L-1 to 1,890 ng L-1, it was significantly higher (Tukey-Kramer test, p < 0.05) in MA than CWA and WWA. The Σn-Alk in surface sediments (SS) gradually increased from north to south, ranging from 5,982 ng g-1 to 37,857 ng g-1. Bacteria and algae were the primary sources of n-alkane in both SW and SS. Proteobacteria was the most widely distributed among three areas. The presence of Rhodobacteraceae with alkB was the primary reason affecting n-alkane concentrations in SW. The Gammaproteobacteria with alkB and alkR chiefly affected n-alkane concentrations in SS. In summary, n-alkane s serve as an energy source for particular microorganisms, shaping the unique oceanographic patterns.

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A convenient method for the synthesis of perdeuterated alkyl amides/amines is disclosed. Perdeuterated acetyl amides can be achieved by a hydrogen-deuterium (H/D) exchange protocol with Pt/C as a catalyst and D2O as a deuterium source under mild conditions. After removal or reduction of the acetyl group, this protocol can provide perdeuterated primary, secondary, and tertiary amines, which are difficult to achieve via other methods.

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Microorganisms are a crucial component of lake ecosystems and significant contributors to biogeochemical cycles. However, the understanding of how primary microorganism groups (e.g., bacteria and fungi) are distributed and constructed within different lake habitats is lacking. We investigated the bacterial and fungal communities of Hulun Lake using high-throughput sequencing techniques targeting 16S rRNA and Internal Transcribed Spacer 2 genes, including a range of ecological and statistical methodologies. Our findings reveal that environmental factors have high spatial and temporal variability. The composition and community structures vary significantly depending on differences in habitats. Variance partitioning analysis showed that environmental and geographical factors accounted for <20% of the community variation. Canonical correlation analysis showed that among the environmental factors, temperature, pH, and dissolved oxygen had strong control over microbial communities. However, the microbial communities (bacterial and fungal) were primarily controlled by the dispersal limitations of stochastic processes. This study offers fresh perspectives regarding the maintenance mechanism of bacterial and fungal biodiversity in lake ecosystems, especially regarding the responses of microbial communities under identical environmental stress.IMPORTANCELake ecosystems are an important part of the freshwater ecosystem. Lake microorganisms play an important role in material circulation and energy flow owing to their unique enzymatic and metabolic capacity. In this study, we observed that bacterial and fungal communities varied widely in the water and sediments of Hulun Lake. The primary factor affecting their formation was identified as dispersal limitation during stochastic processes. Environmental and geographical factors accounted for <20% of the variation in bacterial and fungal communities, with pH, temperature, and dissolved oxygen being important environmental factors. Our findings provide new insights into the responses of bacteria and fungi to the environment, shed light on the ecological processes of community building, and deepen our understanding of lake ecosystems. The results of this study provide a reference for lake management and conservation, particularly with respect to monitoring and understanding microbial communities in response to environmental changes.

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The intrinsic ferromagnetism of two-dimensional transition metal carbide Co2C is remarkable. However, its practical application in spintronic devices is encumbered by a low Curie temperature (TC). To surmount this constraint, double transition-metal carbide CoMC (M = Ti, V, Cr, Mn, Fe, Ni) monolayers are constructed with the aim of improving the magnetic properties and Curie temperature of Co2C. The magnetic properties of CoMC monolayers are comprehensively investigated by first-principles calculations and the effects of hole doping and biaxial strain on the magnetic properties of CoMC (M = V, Cr, Mn) monolayers are also studied. The ground states of CoTiC, CoMnC and CoNiC monolayers all favor ferromagnetic ordering, whereas the CoVC and CoCrC monolayers favor antiferromagnetic ordering and the CoFeC monolayer is non-magnetic. Excitedly, the CoMnC monolayer displays a high total magnetic moment of 4.024µB and a TC of 1366 K. Moreover, the control of hole doping can effectively improve the TC of CoVC, CoCrC, and CoMnC monolayers to 680, 1317, 3044 K, respectively. Finally, applying the in-plain biaxial strain, the CoVC monolayer can be transformed into a ferromagnetic semiconductor under a tensile strain of 6%. The TC values of CoVC, CoCrC, and CoMnC monolayers are tuned by biaxial strain to 440, 1334 and 2390 K, respectively. Their TC above room temperature demonstrates that these monolayers have potential applications in spintronic devices. These theoretical investigations provide valuable insights into guiding experimental synthesis endeavors.

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Purpose: Although alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) have a certain predictive ability for the prognosis of hepatocellular carcinoma (HCC), there are still some cases of aggressive recurrence among patients with AFP and DCP double-negative HCC (DNHC) after local ablation. However, prediction models to forecast the prognosis of DNHC patients are still lacking. Thus, this retrospective study aims to explore the prognostic factors in DNHC patients and develop a nomogram to predict recurrence. Patients and methods: 493 DNHC patients who underwent the local ablation at Beijing You'an Hospital between January 1, 2014, and December 31, 2022, were enrolled. A part that was admitted from January 1, 2014, to December 31, 2018, was designated to the training cohort (n = 307); others from January 1, 2019, to December 31, 2022, were allocated to the validation cohort (n = 186). Lasso regression and Cox regression were employed with the aim of screening risk factors and developing the nomogram. The nomogram outcome was assessed by discrimination, calibration, and decision curve analysis (DCA). Results: Independent prognostic factors selected by Lasso-Cox analysis included age, tumor size, tumor number, and gamma-glutamyl transferase. The area under the receiver operating characteristic (ROC) curves (AUCs) of the training and validation groups (0.738, 0.742, 0.836, and 0.758, 0.821) exhibited the excellent predicted outcome of the nomogram. Calibration plots and DCA plots suggest desirable calibration performance and clinical utility. Patients were stratified into three risk groups by means of the nomogram: low-risk, intermediate-risk, and high-risk, respectively. There exists an obvious distinction in recurrence-free survival (RFS) among three groups (p<0.0001). Conclusion: In conclusion, we established and validated a nomogram for DNHC patients who received local ablation. The nomogram showed excellent predictive power for the recurrence of HCC and could contribute to guiding clinical decisions.