Multiomics analyses provide insights into the genomic basis of differentiation among four sweet osmanthus groups.

Sweet osmanthus (Osmanthus fragrans) is famous in China for its flowers and contains four groups: Albus, Luteus, Aurantiacus, and Asiaticus. Understanding the relationships among these groups and the genetic mechanisms of flower color and aroma biosynthesis are of tremendous interest. In this study, we sequenced representative varieties from two of the four sweet osmanthus groups. Multiomics and phylogenetic analyses of varieties from each of the four groups showed that Asiaticus split first within the species, followed by Aurantiacus and the sister groups Albus and Luteus. We show that the difference in flower color between Aurantiacus and the other three groups was caused by a 4-bp deletion in the promoter region of carotenoid cleavage dioxygenase 4 (OfCCD4) that leads to expression decrease. In addition, we identified 44 gene pairs exhibiting significant structural differences between the multiseasonal flowering variety "Rixianggui" in the Asiaticus group and other autumn-flowering varieties. Through correlation analysis between intermediate products of aromatic components and gene expression, we identified eight genes associated with the linalool and α- and ß-ionone biosynthesis pathways. Overall, our study offers valuable genetic resources for sweet osmanthus, while also providing genetic clues for improving the flower color and multiseasonal flowering of osmanthus and other flowers.

Differential mRNA profiles reveal the potential roles of genes involved in lactate stimulation in mouse macrophages.

Lactate is a glycolysis end product, and its levels are markedly associated with disease severity, morbidity, and mortality in sepsis. It modulates key functions of immune cells, including macrophages. In this investigation, transcriptomic analysis was performed using lactic acid, sodium lactate, and hydrochloric acid-stimulated mouse bone marrow-derived macrophages (iBMDM), respectively, to identify lactate-associated signaling pathways. After 24 h of stimulation, 896 differentially expressed genes (DEG) indicated were up-regulation, whereas 792 were down-regulated in the lactic acid group, in the sodium lactate group, 128 DEG were up-regulated, and 41 were down-regulated, and in the hydrochloric acid group, 499 DEG were up-regulated, and 285 were down-regulated. Subsequently, clinical samples were used to further verify the eight genes with significant differences, among which Tssk6, Ypel4, Elovl3, Trp53inp1, and Cfp were differentially expressed in patients with high lactic acid, indicating their possible involvement in lactic acid-induced inflammation and various physiological diseases caused by sepsis. However, elongation of very long chain fatty acids protein 3 (Elovl3) was negatively correlated with lactic acid content in patients. The results of this study provide a necessary reference for better understanding the transcriptomic changes caused by lactic acid and explain the potential role of high lactic acid in the regulation of macrophages in sepsis.

Time-Resolved Ultraviolet Photodissociation Mass Spectrometry Probes the Mutation-Induced Alterations in Protein Stability and Unfolding Dynamics.

How mutations impact protein stability and structure dynamics is crucial for understanding the pathological process and rational drug design. Herein, we establish a time-resolved native mass spectrometry (TR-nMS) platform via a rapid-mixing capillary apparatus for monitoring the acid-initiated protein unfolding process. The molecular details in protein structure unfolding are further profiled by a 193 nm ultraviolet photodissociation (UVPD) analysis of the structure-informative photofragments. Compared with the wild-type dihydrofolate reductase (WT-DHFR), the M42T/H114R mutant (MT-DHFR) exhibits a significant stability decrease in TR-nMS characterization. UVPD comparisons of the unfolding intermediates and original DHFR forms indicate the special stabilization effect of cofactor NADPH on DHFR structure, and the M42T/H114R mutations lead to a significant decrease in NADPH-DHFR interactions, thus promoting the structure unfolding. Our study paves the way for probing the mutation-induced subtle changes in the stability and structure dynamics of drug targets.

Panda-UV Unlocks Deeper Protein Characterization with Internal Fragments in Ultraviolet Photodissociation Mass Spectrometry.

Ultraviolet photodissociation (UVPD) mass spectrometry unlocks insights into the protein structure and sequence through fragmentation patterns. While N- and C-terminal fragments are traditionally relied upon, this work highlights the critical role of internal fragments in achieving near-complete sequencing of protein. Previous limitations of internal fragment utilization, owing to their abundance and potential for random matching, are addressed here with the development of Panda-UV, a novel software tool combining spectral calibration, and Pearson correlation coefficient scoring for confident fragment assignment. Panda-UV showcases its power through comprehensive benchmarks on three model proteins. The inclusion of internal fragments boosts identified fragment numbers by 26% and enhances average protein sequence coverage to a remarkable 93% for intact proteins, unlocking the hidden region of the largest protein carbonic anhydrase II in model proteins. Notably, an average of 65% of internal fragments can be identified in multiple replicates, demonstrating the high confidence of the fragments Panda-UV provided. Finally, the sequence coverages of mAb subunits can be increased up to 86% and the complementary determining regions (CDRs) are nearly completely sequenced in a single experiment. The source codes of Panda-UV are available at https://github.com/PHOENIXcenter/Panda-UV.

Mediation of White Matter Alterations in the Association Between Ventricular Dilation and Cognitive Decline in Hydrocephalus Patients: An MRI Study.

BACKGROUND: Cognitive impairment is commonly observed in hydrocephalus patients. Ventricular enlargement compresses brain parenchyma, especially the white matter (WM). PURPOSE: To investigate whether the relationship between ventricular dilation and cognitive decline in hydrocephalus patients is mediated by WM alterations. STUDY TYPE: Retrospective. POPULATION: 51 communicating hydrocephalus patients (median age, 54 years), 50 obstructive hydrocephalus patients (median age, 49 years), and 53 control subjects (median age, 50 years). FIELD STRENGTH/SEQUENCE: Diffusion tensors imaging, 3D T1 BRAVO, 3D FIESTA, CUBE T2, and FLAIR sequences at 3T. ASSESSMENT: DTI parameters (skeletonized fractional anisotropy (FA), skeletonized mean diffusivity (MD), and peak width of skeletonized mean diffusivity p(PSMD)) were extracted using FSL software. Global, periventricular, and deep white matter hyperintensity (WMH) volumes, degree of ventricular enlargement (Evans index), and other conventional imaging markers (number of lacunes and perivascular spaces, intracranial and brain volume) were extracted using united imaging intelligence. Cognitive tests included Montreal cognitive assessment (MoCA), clock drawing test (CDT), and vocabulary fluency test (VFT). STATISTICAL TESTS: Multivariable linear regression analysis, mediation analyses, and dominance analysis. P-value <0.05 was considered significant. RESULTS: The degree of ventricular dilation, DTI parameters, and cognitive function scores were interrelated. The skeletonized FA values (ß = -0.0917, 95% confidence interval (CI): -0.205, -0.024) and normalized global WMH volume (ß = -0.0635, 95% CI: -0.13, -0.0005) together mediated 37.2% of the association between Evans index and MoCA. A comparable causal pathway was found for periventricular WMHs but not for deep WMHs. Dominance analysis indicated skeletonized FA values had a greater impact on cognition than WMH volume. The skeletonized FA values also mediated the association between Evans index and CDT (ß = -0.0897, 95% CI: -0.165, -0.026) and VFT (ß = -0.1589, 95% CI: -0.27, -0.083). CONCLUSION: WM alterations were causal mediators between ventricular dilation and cognitive decline in hydrocephalus patients. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 3.

Evaluation of pancreatic iodine uptake and related influential factors in multiphase dual-energy CT.

OBJECTIVES: To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT). MATERIALS AND METHODS: This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s-40 s, 60 s-70 s, and 150 s-180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses. RESULTS: A total of 562 participants (median age 58 years [interquartile range: 47-67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (ß = 0.362, p < 0.001), smoking (ß = -0.240, p = 0.001), and type-II diabetes (ß = -0.449, p < 0.001); NICPP by VFA (ß = -0.301, p = 0.017) and smoking (ß = -0.291, p < 0.001); and NICEP by smoking (ß = -0.154, p = 0.10) and alcohol consumption (ß = -0.350, p < 0.001) with statistical power values over 0.81. CONCLUSION: NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake. CLINICAL RELEVANCE STATEMENT: This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker. KEY POINTS: Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies. Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake. Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.

MicroRNAs regulate the vicious cycle of vascular calcification-osteoporosis in postmenopausal women.

Menopause is a normal physiological process accompanied by changes in various physiological states. The incidence of vascular calcification (VC) increases each year after menopause and is closely related to osteoporosis (OP). Although many studies have investigated the links between VC and OP, the interaction mechanism of the two under conditions of estrogen loss remains unclear. MicroRNAs (miRNAs), which are involved in epigenetic modification, play a critical role in estrogen-mediated mineralization. In the past several decades, miRNAs have been identified as biomarkers or therapeutic targets in diseases. Thus, we hypothesize that these small molecules can provide new diagnostic and therapeutic approaches. In this review, we summarize the close interactions between VC and OP and the role of miRNAs in their interplay.

Remote ischemic conditioning reduces adverse events in patients with acute ischemic stroke complicating acute myocardial infarction: a randomized controlled trial.

BACKGROUND: Acute ischemic stroke (AIS) complicating an acute myocardial infarction (AMI) is not uncommon, but can severely worsen the clinical prognosis. This study aimed to investigate whether remote ischemic conditioning (RIC) could provide clinical benefits to patients with AIS complicating AMI. METHODS: Subjects with AIS complicating AMI were recruited in this double-blind, randomized, controlled trial; assigned to the RIC and sham groups; and respectively underwent twice daily RIC and sham RIC for 2 weeks. All subjects received standard medical therapy. The primary endpoint was the rate of major adverse cardiac and cerebrovascular events (MACCEs) within 3 months after enrollment. MACCEs comprise of death from all causes, unstable anginas, AMI, acute ischemic strokes, and transient ischemic attacks. RESULTS: Eighty subjects were randomly assigned; 37 patients in the RIC group and 40 patients in the sham-RIC group completed the 3-month follow-up and were included in the final analysis. Both RIC and sham RIC procedures were well tolerated. At 3-month follow-up, 11 subjects (29.7%) in the RIC group experienced MACCEs compared to 21 (52.5%) in the sham group (hazard ratio [HR], 0.396; 95% confidence interval, 0.187-0.838; adjusted p < 0.05). Six subjects (16.2%) in the RIC group had died at the 3-month follow up, significantly lower than the 15 (37.5%) deaths in the sham group (adjusted HR 0.333; 95% CI 0.126-0.881; p = 0.027). Seventeen subjects (45.9%) in the RIC group and 6 subjects (15.0%) in the sham group achieved functional independence (mRS score ≤ 2) at 3-month follow-up (adjusted OR 12.75; 95% CI 2.104-77.21; p = 0.006). CONCLUSIONS: Among patients with acute ischemic stroke complicating acute myocardial infarction, treatment with remote ischemic conditioning decreased the major adverse cardiac and cerebrovascular events and improved functional outcomes at 90 days. TRIAL REGISTRATION: URL: www. CLINICALTRIALS: gov . Unique identifier: NCT03868007. Registered 8 March 2019.

Deep Mind 21 functional does not extrapolate to transition metal chemistry.

The development of density functional approximations stands at a crossroads: while machine-learned functionals show potential to surpass their human-designed counterparts, their extrapolation to unseen chemistry lags behind. Here we assess how well the recent Deep Mind 21 (DM21) machine-learned functional [Science, 2021, 374, 1385-1389], trained on main-group chemistry, extrapolates to transition metal chemistry (TMC). We show that DM21 demonstrates comparable or occasionally superior accuracy to B3LYP for TMC, but consistently struggles with achieving self-consistent field convergence for TMC molecules. We also compare main-group and TMC machine-learning DM21 features to shed light on DM21's challenges in TMC. We finally propose strategies to overcome limitations in the extrapolative capabilities of machine-learned functionals in TMC.

Association analysis of the sorting nexin 29 (SNX29) gene copy number variations with growth traits in Diannan small-ear (DSE) pigs.

SNX29 is a potential functional gene associated with meat production traits. Previous studies have shown that SNX29 copy number variation (CNV) could be implicated with phenotype in goats. However, in Diannan small-ear (DSE) pigs, the genetic impact of SNX29 CNV on growth traits remains unclear. Therefore, this study investigated the associations between SNX29 CNVs (CNV10810 and CNV10811) and growth traits in 415 DSE pigs. The results revealed that the CNV10810 mutation was significantly associated with backfat thickness in DSE pigs at 12 and 15 months old (P < 0.05), while the CNV10811 mutation had significant effects on various growth traits at 6 and 12 months old, particularly for body weight, body height, back height and backfat thickness (P < 0.05 or P < 0.001). In conclusion, our results confirm that SNX29 CNV plays a role in regulating growth and development in pigs, thus suggesting its potential application for pig breeding programmes.

Distributed Vibration Monitoring System for 10 kV-400 kVA 3D Wound Core Transformer under Progressive Short-Circuit Impulses.

As large-scale, high-proportion, and efficient distribution transformers surge into the grids, anti-short circuit capability testing of transformer windings in efficient distribution seems necessary and prominent. To deeply explore the influence of progressively short-circuit shock impulses on the core winding deformation of efficient power transformers, a finite element theoretical model was built by referring to a three-phase three-winding 3D wound core transformer with a model of S20-MRL-400/10-NX2. The distributions of internal equivalent force and total deformation of the 3D wound core transformer along different paths under progressively short-circuit shock impulses varying from 60% to 120% were investigated. Results show that the equivalent stress and total deformation change rate reach their maximum as the short-circuit current increases from 60% to 80%, and the maximum and average variation rate for the equivalent stress reach 177.75% and 177.43%, while the maximum and average variation rate for the total deformation corresponds to 178.30% and 177.45%, respectively. Meanwhile, the maximum equivalent stress and maximum total deformation reach 29.81 MPa and 38.70 µm, respectively, as the applied short-circuit current increased to 120%. In light of the above observations, the optimization and deployment of wireless sensor nodes was suggested. Therefore, a distributed monitoring system was developed for acquiring the vibration status of the windings in a 3D wound core transformer, which is a beneficial supplement to the traditional short-circuit reactance detection methods for an efficient grid access spot-check of distribution transformers.

An Improved Nested U-Net Network for Fluorescence In Situ Hybridization Cell Image Segmentation.

Fluorescence in situ hybridization (FISH) is a powerful cytogenetic method used to precisely detect and localize nucleic acid sequences. This technique is proving to be an invaluable tool in medical diagnostics and has made significant contributions to biology and the life sciences. However, the number of cells is large and the nucleic acid sequences are disorganized in the FISH images taken using the microscope. Processing and analyzing images is a time-consuming and laborious task for researchers, as it can easily tire the human eyes and lead to errors in judgment. In recent years, deep learning has made significant progress in the field of medical imaging, especially the successful application of introducing the attention mechanism. The attention mechanism, as a key component of deep learning, improves the understanding and interpretation of medical images by giving different weights to different regions of the image, enabling the model to focus more on important features. To address the challenges in FISH image analysis, we combined medical imaging with deep learning to develop the SEAM-Unet++ automated cell contour segmentation algorithm with integrated attention mechanism. The significant advantage of this algorithm is that it improves the accuracy of cell contours in FISH images. Experiments have demonstrated that by introducing the attention mechanism, our method is able to segment cells that are adherent to each other more efficiently.

The Dynamic Evolution Model of the Chemical and Carbon Isotopic Composition of C1-3 during the Hydrocarbon Generation Process.

A new approach is presented in this paper for the dynamic modeling of the chemical and isotopic evolution of C1-3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for the pyrolysis of various hydrocarbon sources (type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, and asphalt, etc.), the empirical evolution framework of the chemical and isotopic composition of C1-3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting a large amount of pyrolysis data, the chemical and isotopic composition of C1-3 derived from the pyrolysis experiments all follow evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed), δ13Cmixed = X×niA×δ13CiA+Y×niB×δ13CiBX×niA+Y×niB, it can be derived that the cumulative isotopic composition of alkane generated in a certain maturity interval can be expressed by the integral of the product of the instantaneous isotopic composition and instantaneous yield at a certain maturity point, and then divided by the cumulative yield of alkane generated in the corresponding maturity interval. Thus, the cumulative isotopic composition (A(X)), cumulative yield (B(X)), instantaneous isotope (C(X)), and instantaneous yield (D(x)) in the dynamic model, comply with the following formula during the maturity interval of (X0~X). A(X) = ∫X0XCX×DXdxB(X), where A(X) and B(X) can be obtained by the fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of the cumulative yield, instantaneous yield, cumulative isotope, and instantaneous isotope of C1-3 with increasing maturity. The dynamic model can quantify the yield of methane, ethane, and propane, as well as δ13C1, δ13C2, and δ13C3, respectively, during the hydrocarbon generation process. This model is of great significance for evaluating the natural gas resources of hydrocarbon source rock of different maturities and for identifying the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of the isotope series of C1-3 (including reversed isotopic series), which is promising for revealing the mechanism responsible for isotopic reversal when combined with post-generation studies.

The Effect of "Offline-to-Online" Trust Transfer on the Utilization of Online Medical Consultation Among Chinese Rural Residents: Experimental Study.

BACKGROUND: Online medical consultation can serve as a valuable means for rural residents to access high-quality health care resources, thereby mitigating the geographic and economic disadvantages prevalent in rural areas. Nevertheless, due to lower cognitive abilities, rural residents often face challenges in trusting and making effective use of online medical consultations. More likely, adopting a bounded rational decision-making model that facilitates the "offline-to-online" trust transfer could prove to be a potentially effective approach. This strategy aims to encourage less technologically experienced rural residents to trust and make use of online medical consultations. OBJECTIVE: This study aims to characterize the status of "offline-to-online" trust transfer among rural residents in the context of internet health care, and analyze its direct impact on facilitating the utilization of online medical consultation. Additionally, we investigate the family spillover effect of "offline-to-online" trust transfer in promoting the use of online medical consultation among rural family members, considering its distributional effect across various education levels of the population. METHODS: A multistage stratified random sampling method was used to survey participants in rural areas of China from July to September 2021, encompassing a total of 2597 rural residents from 960 rural households. Propensity score values were estimated using logit regression, and the propensity score matching method, using the K-nearest neighbor matching, radius matching, and kernel matching methods, was applied to create matched treatment and control samples of rural residents based on their experience of "offline-to-online" trust transfer. Subsequently, we calculated average treatment effect scores to compare the differences in utilizing online medical consultation between the treatment and control rural samples. RESULTS: As many as 551/960 (57.4%) rural residents experienced an "offline-to-online" trust transfer, with a higher likelihood observed in the older population with lower levels of education and higher satisfaction with local health care services. Furthermore, rural residents who underwent "offline-to-online" trust transfer were 37%-40% more likely to utilize online medical consultation compared with those who did not experience this trust transfer. Additionally, family members of householders who underwent "offline-to-online" trust transfer were 25%-28% more likely to utilize online medical consultation than those whose householders did not experience this trust transfer. Notably, when compared with populations with high-level education, the "offline-to-online" trust transfer had more significant direct and spillover effects on the utilization of online medical consultation services among rural residents with low-level education. CONCLUSIONS: To enhance the "offline-to-online" trust transfer among rural residents and its facilitation in their utilization of online medical consultation, as well as other mobile health (mHealth) and ubiquitous health (uHealth) services, we recommend that online health care providers adopt a "patient-oriented" service model. This approach aims to elevate rural residents' satisfaction with local health care services and harness the trust-building functions inherent in physician-patient relationships and among family members.

A Review of Research Progress in Microfluidic Bioseparation and Bioassay.

With the rapid development of biotechnology, the importance of microfluidic bioseparation and bioassay in biomedicine, clinical diagnosis, and other fields has become increasingly prominent. Microfluidic technology, with its significant advantages of high throughput, automated operation, and low sample consumption, has brought new breakthroughs in the field of biological separation and bioassay. In this paper, the latest research progress in microfluidic technology in the field of bioseparation and bioassay is reviewed. Then, we focus on the methods of bioseparation including active separation, passive separation, and hybrid separation. At the same time, the latest research results of our group in particle separation are introduced. Finally, some application examples or methods for bioassay after particle separation are listed, and the current challenges and future prospects of bioseparation and bioassay are discussed.

Immunological Landscape of Retinal Ischemia-Reperfusion Injury: Insights into Resident and Peripheral Immune Cell Responses.

Retinal ischemia-reperfusion injury (RIRI) is a complex condition characterized by immune cell-mediated inflammation and consequent neuronal damage. This review delves into the immune response mechanisms in RIRI, particularly emphasizing the roles played by resident and peripheral immune cells. It highlights the pivotal role of microglia, the primary resident immune cells, in exacerbating neuroinflammation and neuronal damage through their activation and subsequent release of pro-inflammatory mediators. Additionally, the review explores the contributions of other glial cell types, such as astrocytes and Müller cells, in modulating the immune response within the retinal environment. The dual role of the complement system in RIRI is also examined, revealing its complex functions in both safeguarding and impairing retinal health. Inflammasomes, triggered by various danger signals, are discussed as crucial contributors to the inflammatory pathways in RIRI, with an emphasis on the involvement of different NOD-like receptor family proteins. The review further analyzes the infiltration and impact of peripheral immune cells like neutrophils, macrophages, and T cells, which migrate to the retina following ischemic injury. Critical to this discussion is the interplay between resident and peripheral immune cells and its implications for RIRI pathophysiology. Finally, the review outlines future research directions, focusing on basic research and the potential for clinical translation to enhance understanding and treatment of RIRI.

High-throughput screening carbon and nitrogen sources to promote growth and sporulation in Rhizopus arrhizus.

Rhizopus arrhizus is a saprotrophic, sometimes clinically- and industrially-relevant mold (Mucorales) and distributed worldwide, suggesting it can assimilate a broad spectrum of substrates. Here, 69 strains of R. arrhizus were investigated by using the Biolog FF MicroPlate for the profiles of utilizing 95 carbon and nitrogen substrates. The study showed that most R. arrhizus strains were similar in average well color development (AWCD) and substrate richness (SR). Nevertheless, 13 strains were unique in principal component analyses, heatmap, AWCD, and SR analyses, which may imply a niche differentiation within R. arrhizus. The species R. arrhizus was able to utilize all the 95 carbon and nitrogen substrates, consistent with the hypothesis of a great metabolic diversity. It possessed a substrate preference of alcohols, and seven substrates were most frequently utilized, with N-acetyl-D-galactosamine and L-phenylalanine ranking at the top of the list. Eight substrates, especially L-arabinose and xylitol, were capable of promoting sporulation and being applied for rejuvenating degenerated strains. By phenotyping R. arrhizus strains in carbon and nitrogen assimilation capacity, this study revealed the extent of intra-specific variability and laid a foundation for estimating optimum substrates that may be useful for industrial applications.

Characterizing the impact of reservoir storage and discharge on nitrogen dynamics in an upstream wetland using a δ15N and δ18O dual-isotope approach.

The identification of nitrate sources in reservoir water is important for watershed-scale surface pollution management. Significant fluctuations in river water levels arising from reservoir storage and discharge influence nitrate sources and transport processes. The Sanmenxia Reservoir, in the middle reaches of the Yellow River in China, undergoes significant water level changes (290-316 m), altering the composition of the nitrogen sources. This study employed a δ15N and δ18O dual-isotope method and MixSIAR modeling to quantify the contributions of nitrate sources. This reveals the impact of reservoir water impoundment and discharge on nitrogen dynamics in the upstream region of the wetland and the model sensitivity for each nitrate source. The results showed that the average concentrations of nitrate­nitrogen (NO- 3-N) were elevated during the impoundment period compared to the discharge period. Nitrogen sources exhibited varying proportions in surface water, groundwater, and soil water during both the impoundment and discharge periods. The predominant sources include manure and sewage (MS), with a maximum proportion of 57.4 % in surface water. Soil nitrogen (SN) accounted for 25.8 % of groundwater nitrogen and 32.1 % of soil water nitrogen during the impoundment period, whereas, during the discharge period, soil nitrogen made up 41.4 % of surface water nitrogen, manure and sewage contributed 44.8 % of groundwater nitrogen, and manure and sewage dominated with 56.7 % of soil water nitrogen. Sensitivity analysis of the MixSIAR model revealed that the isotopic composition of the manure and sewage primary source most significantly influenced the apportionment results of the riverine nitrate source. Reservoir discharge facilitates the dissimilatory nitrate reduction to ammonium (DNRA). The migration of NO- 3 from surface water to soil water and groundwater occurred from the impoundment period to the discharge period.

Floating Photothermal Hydrogen Production.

Solar-to-hydrogen (STH) is emerging as a promising approach for energy storage and conversion to contribute to carbon neutrality. The lack of efficient catalysts and sustainable reaction systems is stimulating the fast development of photothermal hydrogen production based on floating carriers to achieve unprecedented STH efficiency. This technology involves three major components: floating carriers with hierarchically porous structures, photothermal materials for solar-to-heat conversion and photocatalysts for hydrogen production. Under solar irradiation, the floating photothermal system realizes steam generation which quickly diffuses to the active site for sustainable hydrogen generation with the assistance of a hierarchically porous structure. Additionally, this technology is endowed with advantages in the high utilization of solar energy and catalyst retention, making it suitable for various scenarios, including domestic water supply, wastewater treatment, and desalination. A comprehensive overview of the photothermal hydrogen production system is present due to the economic feasibility for industrial application. The in-depth mechanism of a floating photothermal system, including the solar-to-heat effect, steam diffusion, and triple-phase interaction are highlighted by elucidating the logical relationship among buoyant carriers, photothermal materials, and catalysts for hydrogen production. Finally, the challenges and new opportunities facing current photothermal catalytic hydrogen production systems are analyzed.

Zebularine potentiates anti-tumor immunity by inducing tumor immunogenicity and improving antigen processing through cGAS-STING pathway.

DNA methylation is an important epigenetic mechanism involved in the anti-tumor immune response, and DNA methyltransferase inhibitors (DNMTi) have achieved impressive therapeutic outcomes in patients with certain cancer types. However, it is unclear how inhibition of DNA methylation bridges the innate and adaptive immune responses to inhibit tumor growth. Here, we report that DNMTi zebularine reconstructs tumor immunogenicity, in turn promote dendritic cell maturation, antigen-presenting cell activity, tumor cell phagocytosis by APCs, and efficient T cell priming. Further in vivo and in vitro analyses reveal that zebularine stimulates cGAS-STING-NF-κB/IFNß signaling to enhance tumor cell immunogenicity and upregulate antigen processing and presentation machinery (AgPPM), which promotes effective CD4+ and CD8+ T cell-mediated killing of tumor cells. These findings support the use of combination regimens that include DNMTi and immunotherapy for cancer treatment.