Measuring climate change perception in China using mental images: A nationwide open-ended survey.

Current knowledge about public climate change perception mainly covers belief, concern, and attitudes. However, how this discourse is interpreted using individuals' own frame of reference remains largely unknown, particularly in many large emitters from non-Annex I countries such as China. This study, for the first time, performs a nationwide open-ended survey covering 4,037 respondents and collected 12,100 textual answers. Using a semiautomated coding method, we find seven mental images that exclusively represent the Chinese interpretation of the climate change issue, including global warming, distant icons, natural disasters, environmental degradation, cause, solution, and weather. Analysis of influencing factors shows that females, those with lower education levels, lower income, and older individuals tend to connect climate change with natural weather phenomena. Younger and well-educated residents in developed cities are more aware of various consequences and anthropogenic causes of climate change. People with stronger climate change beliefs, policy support, and personal experience of extreme weather are more likely to mention disastrous impacts, carbon emission as causes, and potential solutions. Employing the multilevel regression and post-stratification technique, we map the prevalence of mental images in China at the prefecture-city level. The results reveal significant geographical heterogeneity, with estimated national means ranging from a high of 55% (weather) to a low of 11% (solution). Our findings reveal diverse perspectives and a widespread misconception of climate change in China, suggesting the need for tailored clarification strategies to gain public consent.

A novel selenium analog of HDACi-based twin drug induces apoptosis and cell cycle arrest via CDC25A to improve prostate cancer therapy.

Cancer therapy has moved from single agents to more mechanism-based targeted approaches. In recent years, the combination of HDAC inhibitors and other anticancer chemicals has produced exciting progress in cancer treatment. Herein, we developed a novel prodrug via the ligation of dichloroacetate to selenium-containing potent HDAC inhibitors. The effect and mechanism of this compound in the treatment of prostate cancer were also studied. Methods: The concerned prodrug SeSA-DCA was designed and synthesized under mild conditions. This compound's preclinical studies, including the pharmacokinetics, cell toxicity, and anti-tumor effect on prostate cancer cell lines, were thoroughly investigated, and its possible synergistic mechanism was also explored and discussed. Results: SeSA-DCA showed good stability in physiological conditions and could be rapidly decomposed into DCA and selenium analog of SAHA (SeSAHA) in the tumor microenvironment. CCK-8 experiments identified that SeSA-DCA could effectively inhibit the proliferation of a variety of tumor cell lines, especially in prostate cancer. In further studies, we found that SeSA-DCA could also inhibit the metastasis of prostate cancer cell lines and promote cell apoptosis. At the animal level, oral administration of SeSA-DCA led to significant tumor regression without obvious toxicity. Moreover, as a bimolecular coupling compound, SeSA-DCA exhibited vastly superior efficacy than the mixture with equimolar SeSAHA and DCA both in vitro and in vivo. Our findings provide an important theoretical basis for clinical prostate cancer treatment. Conclusions: Our in vivo and in vitro results showed that SeSA-DCA is a highly effective anti-tumor compound for PCa. It can effectively induce cell cycle arrest and growth suppression and inhibit the migration and metastasis of PCa cell lines compared with monotherapy. SeSA-DCA's ability to decrease the growth of xenografts is a little better than that of docetaxel without any apparent signs of toxicity. Our findings provide an important theoretical basis for clinical prostate cancer treatment.

Cooperative Motion Optimization Based on Risk Degree under Automatic Driving Environment.

Appropriate traffic cooperation at intersections plays a crucial part in modern intelligent transportation systems. To enhance traffic efficiency at intersections, this paper establishes a cooperative motion optimization strategy that adjusts the trajectories of autonomous vehicles (AVs) based on risk degree. Initially, AVs are presumed to select any exit lanes, thereby optimizing spatial resources. Trajectories are generated for each possible lane. Subsequently, a motion optimization algorithm predicated on risk degree is introduced, which takes into account the trajectories and motion states of AVs. The risk degree serves to prevent collisions between conflicting AVs. A cooperative motion optimization strategy is then formulated, incorporating car-following behavior, traffic signals, and conflict resolution as constraints. Specifically, the movement of all vehicles at the intersection is modified to achieve safer and more efficient traffic flow. The strategy is validated through a simulation using SUMO. The results indicate a 20.51% and 11.59% improvement in traffic efficiency in two typical scenarios when compared to a First-Come-First-Serve approach. Moreover, numerical experiments reveal significant enhancements in the stability of optimized AV acceleration.

Natural Product Graveoline Modulates Kirsten Rat Sarcoma Viral Oncogene Homologue (KRAS) Membrane Association: Insights from Advanced Spectroscopic Studies.

The KRAS gene plays a pivotal role in numerous cancers by encoding a GTPase that upon association with the plasma membrane activates the MAPK pathway, promoting cellular proliferation. In our study, we investigated small molecules that disrupt KRAS's membrane interaction, hypothesizing that such disruption could in turn inhibit mutant RAS signaling. Native mass spectrometry screening of KRAS-FMe identified compounds with a preference for interacting with the hypervariable region (HVR), and surface plasmon resonance (SPR) further refined our selection to graveoline as a compound exhibiting preferential HVR binding. Subsequent nuclear magnetic resonance (NMR) analysis showed that graveoline's interaction with KRAS depends on C-terminal O-methylation. Moreover, our findings revealed multiple interaction sites, suggesting weak engagement with the KRAS G domain. Using nanodiscs as a membrane mimetic, further characterization through NMR and Förster resonance energy transfer (FRET) studies demonstrated graveoline's ability to perturb KRAS membrane interaction in a biochemical setting. Our biophysical approach sheds light on the intricate molecular mechanisms underlying KRAS-ligand interactions, providing valuable insights into understanding the KRAS-associated pathophysiology. These findings contribute to the translational aspect of our study, offering potential avenues for further research targeting KRAS membrane association with the potential to lead to a new class of RAS therapeutics.

Ratiometric Fluorescent Probe for Super-Resolution Imaging of Lysosome HClO in Ferroptosis Cells.

Ferroptosis is an iron-dependent programmed cell death that is characterized by the dysregulation of lipid reactive oxygen species (ROS) production, causing abnormal changes in hypochlorous acid (HClO) levels in lysosomes. Super-resolution imaging can observe the fine structure of the lysosome at the nanometer level; therefore, it can be used to detect lysosome HClO levels during ferroptosis at the suborganelle level. Herein, we utilize a ratiometric fluorescent probe, SRF-HClO, for super-resolution imaging of lysosome HClO. Structured-illumination microscopy (SIM) improves the accuracy of lysosome targeting and enables the probe SRF-HClO to be successfully applied to rapidly monitor the up-regulated lysosome HClO at the nanoscale during inflammation and ferroptosis. Importantly, the probe SRF-HClO can also detect HClO changes in inflammatory and ferroptosis mice and evaluate the inhibitory effect of ferroptosis on mice tumors.

Hippocampal Glutamate Levels and Their Correlation With Subregion Volume in School-Aged Children With MRI-Negative Epilepsy: A Preliminary Study.

BACKGROUND: Abnormal levels of glutamate constitute a key pathophysiologic mechanism in epilepsy. The use of glutamate chemical exchange saturation transfer (GluCEST) imaging to measure glutamate levels in pediatric epilepsy is rarely reported in research. PURPOSE: To investigate hippocampal glutamate level variations in pediatric epilepsy and the correlation between glutamate and hippocampal subregional volumes. STUDY TYPE: Cross-sectional, prospective. SUBJECTS: A total of 38 school-aged pediatric epilepsy patients with structurally normal MRI as determined by at least two independent radiologists (60% males; 8.7 ± 2.5 years; including 20 cases of focal pediatric epilepsy [FE] and 18 cases of generalized pediatric epilepsy [GE]) and 17 healthy controls (HC) (41% males; 9.0 ± 2.5 years). FIELD STRENGTH/SEQUENCE: 3.0 T; 3D magnetization prepared rapid gradient echo (MPRAGE) and 2D turbo spin echo GluCEST sequences. ASSESSMENT: The relative concentration of glutamate was calculated through pixel-wise magnetization transfer ratio asymmetry (MTRasym) analysis of the GluCEST data. Hippocampal subfield volumes were computed from MPRAGE data using FreeSurfer. STATISTICAL TESTS: This study used t tests, one-way analysis of variance, Kruskal-Wallis tests, and Pearson correlation analysis. P < 0.05 was considered statistically significant. RESULTS: The MTRasym values of both the left and right hippocampi were significantly elevated in GE (left: 2.51 ± 0.23 [GE] vs. 2.31 ± 0.12 [HCs], right: 2.50 ± 0.22 [GE] vs. 2.27 ± 0.22 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly elevated in FE (2.49 ± 0.28 [ipsilateral] vs. 2.29 ± 0.16 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly increased compared to the contralateral hippocampus in FE (2.49 ± 0.28 [ipsilateral] vs. 2.35 ± 0.34 [contralateral]). No significant differences in hippocampal volume were found between different groups (left hippocampus, P = 0.87; right hippocampus, P = 0.87). DATA CONCLUSION: GluCEST imaging have potential for the noninvasive measurement of glutamate levels in the brains of children with epilepsy. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Impact of chlorine disinfection on intracellular and extracellular antimicrobial resistance genes in wastewater treatment and water reclamation.

Wastewater treatment plants and water reclamation facilities are reservoirs of antimicrobial resistance genes (ARGs). These ARGs are not limited solely to intracellular DNA (inARGs) but include extracellular DNA (exARGs) present in wastewater. The release of exARGs from cells can be exacerbated by treatment processes, including chlorine disinfection, which disrupts bacterial cells. Given the potential for exARGs to drive horizontal gene transfer and contribute to the proliferation of antimicrobial resistance, it is imperative to recognize these fractions as emerging environmental pollutants. In this study, we conducted a comprehensive year-long assessment of both inARGs and exARGs, further differentiating between dissolved exARGs (Dis_exARGs) and exARGs adsorbed onto particulate matter (Ads_exARGs), within a full-scale wastewater treatment and water reclamation facility. The results revealed that Ads_exARGs comprised up to 30 % of the total ARGs in raw sewage with high biomass content. Generally, treatments at low and high doses of chlorine increased the abundance of Dis_exARGs and Ads_exARGs. The fate of ARG levels that varied depending on the type of ARGs suggested variations in the susceptibility of the host bacteria to chlorination. Moreover, co-occurrence of several potential opportunistic pathogenic bacteria and ARGs were observed. Therefore, we propose higher doses of chlorination as a prerequisite for the effective removal of inARGs and exARGs.

Colloidal Synthesis of Carbon Dot-ZnSe Nanoplatelet Van der Waals Heterostructures for Boosting Photocatalytic Generation of Methanol-Storable Hydrogen.

Methanol is not only a promising liquid hydrogen carrier but also an important feedstock chemical for chemical synthesis. Catalyst design is vital for enabling the reactions to occur under ambient conditions. This study reports a new class of van der Waals heterojunction photocatalyst, which is synthesized by hot-injection method, whereby carbon dots (CDs) are grown in situ on ZnSe nanoplatelets (NPLs), i.e., metal chalcogenide quantum wells. The resultant organic-inorganic hybrid nanoparticles, CD-NPLs, are able to perform methanol dehydrogenation through CH splitting. The heterostructure has enabled light-induced charge transfer from the CDs into the NPLs occurring on a sub-nanosecond timescale, with charges remaining separated across the CD-NPLs heterostructure for longer than 500 ns. This resulted in significantly heightened H2 production rate of 107 µmole·g-1·h-1 and enhanced photocurrent density up to 34 µA cm-2 at 1 V bias potential. EPR and NMR analyses confirmed the occurrence of α-CH splitting and CC coupling. The novel CD-based organic-inorganic semiconductor heterojunction is poised to enable the discovery of a host of new nano-hybrid photocatalysts with full tunability in the band structure, charge transfer, and divergent surface chemistry for guiding photoredox pathways and accelerating reaction rates.

Exploring the antibiofilm efficacy of cinnamaldehyde against Malassezia globosa associated pityriasis versicolor.

BACKGROUND: Malassezia globosa is a commensal basidiomycetous yeast occurring on the skin that causes pityriasis versicolor (PV) and seborrheic dermatitis, but that has also been implicated in other dermatoses. Cinnamaldehyde (CM) has antibacterial, antioxidant, and anti-inflammatory activities, but the effect of CM on M. globosa-infected PV has not been clarified. PURPOSE: The study aimed to investigate the possible antifungal and antibiofilm activities of CM against M. globosa-infected PV in vivo and in vitro. METHODS: The broth microdilution method was used to determine the minimum inhibitory concentration (MIC) of CM against M. globosa. The crystal violet staining assay and XTT assay were used to investigate the inhibition of CM on biofilm formation and the eradication of mature biofilms. The visualizations of the biofilm and cell distribution in the biofilm matrix were performed with a scanning electron microscope and confocal laser scanning microscope. The kits of antioxidant kinase were used to determine the activities of oxidative stress markers in M. globosa-stimulated HaCaT cells. Western blot assays were used to evaluate the role of TLR2/NF-κB in vitro. Furthermore, the protective effect of CM was assessed in M. globosa-associated PV mice. The expressions of inflammatory cytokines and apoptosis were screened using ELISA assays. The expressions of interleukin-6 and tumor necrosis factor-α were measured by an immunohistochemistry method in vivo. RESULTS: Our results showed that the MIC of CM against planktonic cells of M. globosa was 4 µg/ml and treatment with 20 × MIC CM eradicated mature biofilms of M. globosa. In vitro, after CM treatment the levels of oxidative stress indicators (i.e., superoxide dismutase, catalase, glutathione) significantly increased, while the levels of malondialdehyde decreased. In addition, the expression of TLR2/NF-κB in HaCaT cells was significantly reduced after CM treatment. On the other hand, an in vivo therapeutic effect of CM was assessed against M. globosa-infected mice. The fungal load on the skin decreased after treatment with CM compared to the M. globosa-infected group. In addition, the uninfected animals showed a normal skin structure, whereas, the M. globosa-infected mice showed extensive infiltration of neutrophils in skin tissues that improved after treatment with CM. Meanwhile, the levels of inflammatory and apoptotic factors improved after CM treatment. CONCLUSION: Our results showed that CM inhibits the biofilm formation of M. globosa and eradicates mature biofilms of M. globosa. Treatment with CM significantly decreased oxidative stress, apoptosis, and inflammatory markers in the skin tissue and HaCaT cells. Hence, this study suggests that CM is a good candidate therapeutic agent against M. globosa-induced PV infections because of its antifungal, antibiofilm, and anti-inflammatory properties.

Facet-selective growth of halide perovskite/2D semiconductor van der Waals heterostructures for improved optical gain and lasing.

The tunable properties of halide perovskite/two dimensional (2D) semiconductor mixed-dimensional van der Waals heterostructures offer high flexibility for innovating optoelectronic and photonic devices. However, the general and robust growth of high-quality monocrystalline halide perovskite/2D semiconductor heterostructures with attractive optical properties has remained challenging. Here, we demonstrate a universal van der Waals heteroepitaxy strategy to synthesize a library of facet-specific single-crystalline halide perovskite/2D semiconductor (multi)heterostructures. The obtained heterostructures can be broadly tailored by selecting the coupling layer of interest, and can include perovskites varying from all-inorganic to organic-inorganic hybrid counterparts, individual transition metal dichalcogenides or 2D heterojunctions. The CsPbI2Br/WSe2 heterostructures demonstrate ultrahigh optical gain coefficient, reduced gain threshold and prolonged gain lifetime, which are attributed to the reduced energetic disorder. Accordingly, the self-organized halide perovskite/2D semiconductor heterostructure lasers show highly reproducible single-mode lasing with largely reduced lasing threshold and improved stability. Our findings provide a high-quality and versatile material platform for probing unique optoelectronic and photonic physics and developing further electrically driven on-chip lasers, nanophotonic devices and electronic-photonic integrated systems.

Data-driven approaches linking wastewater and source estimation hazardous waste for environmental management.

Industrial enterprises are major sources of contaminants, making their regulation vital for sustainable development. Tracking contaminant generation at the firm-level is challenging due to enterprise heterogeneity and the lack of a universal estimation method. This study addresses the issue by focusing on hazardous waste (HW), which is difficult to monitor automatically. We developed a data-driven methodology to predict HW generation using wastewater big data which is grounded in the availability of this data with widespread application of automatic sensors and the logical assumption that a correlation exists between wastewater and HW generation. We created a generic framework that used representative variables from diverse sectors, exploited a data-balance algorithm to address long-tail data distribution, and incorporated causal discovery to screen features and improve computation efficiency. Our method was tested on 1024 enterprises across 10 sectors in Jiangsu, China, demonstrating high fidelity (R² = 0.87) in predicting HW generation with 4,260,593 daily wastewater data.

A Screening of 10,240 NatureBank Fractions Identifies Nematicidal Activity in Agelasine-Containing Extracts from Sponges.

Nematode infections affect a fifth of the human population, livestock, and crops worldwide, imposing a burden to global public health and economies, particularly in developing nations. Resistance to commercial anthelmintics has increased over the years in livestock infections and driven the pursuit for new drugs. We herein present a rapid, cost-effective, and automated assay for nematicide discovery using the free-living nematode Caenorhabditis elegans to screen a highly diverse natural product library enriched in bioactive molecules. Screening of 10,240 fractions obtained from extracts of various biological sources allowed the identification of 7 promising hit fractions, all from marine sponges. These fractions were further assayed for nematicidal activity against the sheep nematode parasite Haemonchus contortus and for innocuity in zebrafish. The most active extracts against parasites and innocuous toward vertebrates belong to two chemotypes. High-performance liquid chromatography (HPLC) coupled with nuclear magnetic resonance (NMR) revealed that the most abundant compound in one chemotype is halaminol A, an aminoalcohol previously identified in a small screen against H. contortus. Terpene-nucleotide hybrids known as agelasines predominate in the other chemotype. This study reinforces the power of C. elegans for nematicide discovery from large collections and the potential of the chemical diversity derived from marine invertebrate biota.

Water Scarcity Assessment of Hydropower Plants in China under Climate Change, Sectoral Competition, and Energy Expansion.

Hydropower plays a pivotal role in low-carbon electricity generation, yet many projects are situated in regions facing heightened water scarcity risks. This research devised a plant-level Hydropower Water Scarcity Index (HWSI), derived from the ratio of water demand for electricity generation to basin-scale available runoff water. We assessed the water scarcity of 1736 hydropower plants in China for the baseline year 2018 and projected into the future from 2025 to 2060. The results indicate a notable increase in hydropower generation facing moderate to severe water scarcity (HWSI >0.05), rising from 10% in 2018 to 24-34% of the national total (430-630 TWh), with a projected peak in the 2030s-2040s under the most pessimistic scenarios. Hotspots of risk are situated in the southwest and northern regions, primarily driven by decreased river basin runoff and intensified sectoral water use, rather than by hydropower demand expansion. Comparative analysis of four adaptation strategies revealed that sectoral water savings and enhancing power generation efficiency are the most effective, potentially mitigating a high of 16% of hydropower risks in China. This study provides insights for formulating region-specific adaptation strategies and assessing energy-water security in the face of evolving environmental and societal challenges.

Associated lifestyle factors of elevated plasma aldosterone concentration in community population, gender-stratified analysis of a cross-sectional survey.

BACKGROUND: Aldosterone plays important parts in development of cardio-metabolic diseases as end product of renin-angiotensin-aldosterone system. However, factors elevating circulating aldosterone are not clear, and lifestyle-related factors are suggested to be involved, whereas less studied. Therefore, we aimed to explore the association of lifestyle factors with plasma aldosterone concentration (PAC) in community population. METHODS: In this cross-sectional study, we recruited participants using multistage random sampling from Emin China in 2019, and collected data and fasting blood samples. The considered lifestyle factors included obesity parameters (neck circumference, abdominal circumference), alcohol consumption, blood pressure (BP), physical activity, sleep duration, sleep quality, mental state (depression and anxiety), fasting blood glucose (FBG), and lipid profiles (total cholesterol and triglyceride). PAC was measured using radioimmunoassay. We performed sex-stratified linear and logistic regressions to explore associated factors of PAC. Component analysis was further performed to identify the main factors affecting PAC. RESULTS: Twenty-seven thousand four hundred thirty-six participants with 47.1% men were included. Obesity parameters (neck circumference, abdominal circumference), glucose metabolism (FBG), psychological status (anxiety status in men and women, depression status in men), BP, liver function (in men), lipid metabolism (TC and TG in men), sleep parameters (sleep quality in women), and renal function (in women) are the main factors associated with elevated PAC. CONCLUSION: lower physical activity, alcohol consumption, higher BP, fat accumulation, dyslipidemia, higher fasting blood glucose, and presence of depression and anxiety were the main factors associated with eleveated PAC.

Gaps between current practice in perinatal depression screening and guideline recommendations: a systematic review.

OBJECTIVE: Screening for perinatal depression is recommended by many guidelines to reduce the disease burden, but current implementation practices require clarification. METHOD: Fifteen databases were searched for observational studies using a pre-tested search strategy. In addition, the websites of academic organizations were searched for guidelines, recommendations, and reports. Literature published between January 1, 2010, and December 19, 2021, in either English or Chinese, was included. The standard form of the Joanna Briggs Institute (JBI) was used to assess risk of bias of the included studies. RESULTS: The data analysis covered 103 studies, 21 guidelines, 11 recommendations, five position statements, three reports, two committee opinions, three consensuses, one consultation, and one policy statement. All but one guideline recommended that mothers be routinely screened for perinatal depression at least once during the perinatal period. In addition, 39 documents recommended that perinatal mothers at risk of perinatal depression be provided with or referred to counseling services. In original studies, however, only 8.7% of the original studies conducted routine screenings, and only one-third offered referral services after the screening process. The EPDS emerged as the most frequently used screening tool to measure perinatal depression. 32% (n = 33) of studies reported the technology used for screening. The most commonly used method was face-to-face interviews (n = 22). Screening personnel the agents conducting the screening comprised researchers (n = 26), nurses (n = 15), doctors (n = 11). CONCLUSIONS: A significant disparity was observed between the recommendations and implementation of perinatal depression screening, highlighting the need to integrate routine screening and referral processes into maternal care services.

Unveiling the role of APOM gene in liver cancer: Investigating the impact of hsa-miR-4489/MUC1-mediated ferroptosis on the advancement of hepatocellular carcinoma cells.

Primary liver cancer has consistently exhibited a high prevalence and fatality rate, necessitating the investigation of associated diagnostic markers and inhibition mechanisms to effectively mitigate its impact. The significance of apolipoprotein M (ApoM) in impeding the progression of neoplastic ailments is progressively gaining recognition. However, a comprehensive understanding of its underlying mechanism in liver cancer advancement remains to be elucidated. Recent evidence indicates a potential association between ApoM and polyunsaturated fatty acids (PUFAs), with the peroxidation of phospholipids (PLs) containing PUFAs being recognized as a crucial element in the occurrence of ferroptosis. This prompts us to investigate the impact of the APOM gene on the progression of liver cancer through the ferroptosis pathway and elucidate its underlying mechanisms. The findings of this study indicate that the liver cancer cell model, which was genetically modified to overexpress the APOM gene, demonstrated a heightened ferroptosis effect. Moreover, the observed inhibition of the GSH (Glutathione) - GPX4 (Glutathione Peroxidase 4) regulatory axis suggests that the role of this axis in inhibiting ferroptosis is weakened. Through intersection screening and validation, we found that Mucin 1,cell surface associated (MUC1) can inhibit ferroptosis and is regulated by the APOM gene. Bioinformatics analysis and screening identified miR-4489 as a mediator between the two. Experimental results using the dual luciferase reporter gene confirmed that has-miR-4489 targets MUC1's 3'-UTR and inhibits its expression. In conclusion, this study provides evidence that the APOM gene induces a down-regulation in the expression of the ferroptosis-inhibiting gene MUC1, mediated by miR-4489, thereby impeding the advancement of liver cancer cells through the facilitation of ferroptosis.

Balance between FeIV-NiIV synergy and Lattice Oxygen Contribution for Accelerating Water Oxidation.

Hydrogen obtained from electrochemical water splitting is the most promising clean energy carrier, which is hindered by the sluggish kinetics of the oxygen evolution reaction (OER). Thus, the development of an efficient OER electrocatalyst using nonprecious 3d transition elements is desirable. Multielement synergistic effect and lattice oxygen oxidation are two well-known mechanisms to enhance the OER activity of catalysts. The latter is generally related to the high valence state of 3d transition elements leading to structural destabilization under the OER condition. We have found that Al doping in nanosheet Ni-Fe hydroxide exhibits 2-fold advantage: (1) a strong enhanced OER activity from 277 mV to 238 mV at 10 mA cm-2 as the Ni valence state increases from Ni3.58+ to Ni3.79+ observed from in situ X-ray absorption spectra. (2) Operational stability is strengthened, while weakness is expected since the increased NiIV content with 3d8L2 (L denotes O 2p hole) would lead to structural instability. This contradiction is attributed to a reduced lattice oxygen contribution to the OER upon Al doping, as verified through in situ Raman spectroscopy, while the enhanced OER activity is interpreted as an enormous gain in exchange energy of FeIV-NiIV, facilitated by their intersite hopping. This study reveals a mechanism of Fe-Ni synergy effect to enhance OER activity and simultaneously to strengthen operational stability by suppressing the contribution of lattice oxygen.

Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms.

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

A nurse-led multidomain intervention to improve the management of chemotherapy-induced nausea and vomiting in patients with head and neck cancers: A randomized controlled trial.

PURPOSE: This study aimed to investigate the effect of a nurse-led multidomain intervention on chemotherapy induced nausea and vomiting (CINV) in patients with head and neck squamous cell carcinomas (HNSCC). METHODS: Ninety-two HNSCC patients who received cisplatin-based chemotherapy were divided into intervention group (n = 45) and control group (n = 47). The control group received usual care of CINV, which consisted of administration of antiemetics according to physicians' preference, education about CINV control and dietary recommendations provided by primary nurses. The intervention group received nurse-led, evidence-based multidomain management, including nurse-led CINV risk factors assessment, education on prevention and control of CINV, antiemetics following guidelines, dietary strategies, and relaxation therapy. The number of patients who experienced CINV was collected. The severity of CINV was graded according to the Common Terminology Criteria for Adverse Events v3.0. The influence of CINV on patient's quality of life was assessed by the Functional Living Index-Emesis (FLIE). RESULTS: The incidence and the severity of nausea and vomiting in the intervention group were significantly lower than those in the control group within 5 days after chemotherapy, and the scores of the dimension of nausea and vomiting in the intervention group were significantly higher than those in the control group [63.00 (50.00-63.00) vs 40.00(28.00-63.00), 63.00(63.00-63.00) vs 63.00 (43.00-63.00)], the differences were statistically significant (P < 0.05). CONCLUSIONS: Nurse-led multidomain intervention can reduce the incidence and the severity of CINV in patients with HNSCC who were treated with cisplatin-based chemotherapy, and thus reduced the influence of CINV on patients' quality of life. THE CLINICAL TRIAL REGISTRATION NUMBER: NCT05792228.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we propose an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.