Integrated metagenomic and metabolomic analysis reveals distinctive stage-specific gut-microbiome-derived metabolites in intracranial aneurysms.

OBJECTIVE: Our study aimed to explore the influence of gut microbiota and their metabolites on intracranial aneurysms (IA) progression and pinpoint-related metabolic biomarkers derived from the gut microbiome. DESIGN: We recruited 358 patients with unruptured IA (UIA) and 161 with ruptured IA (RIA) from two distinct geographical regions for conducting an integrated analysis of plasma metabolomics and faecal metagenomics. Machine learning algorithms were employed to develop a classifier model, subsequently validated in an independent cohort. Mouse models of IA were established to verify the potential role of the specific metabolite identified. RESULTS: Distinct shifts in taxonomic and functional profiles of gut microbiota and their related metabolites were observed in different IA stages. Notably, tryptophan metabolites, particularly indoxyl sulfate (IS), were significantly higher in plasma of RIA. Meanwhile, upregulated tryptophanase expression and indole-producing microbiota were observed in gut microbiome of RIA. A model harnessing gut-microbiome-derived tryptophan metabolites demonstrated remarkable efficacy in distinguishing RIA from UIA patients in the validation cohort (AUC=0.97). Gut microbiota depletion by antibiotics decreased plasma IS concentration, reduced IA formation and rupture in mice, and downregulated matrix metalloproteinase-9 expression in aneurysmal walls with elastin degradation reduction. Supplement of IS reversed the effect of gut microbiota depletion. CONCLUSION: Our investigation highlights the potential of gut-microbiome-derived tryptophan metabolites as biomarkers for distinguishing RIA from UIA patients. The findings suggest a novel pathogenic role for gut-microbiome-derived IS in elastin degradation in the IA wall leading to the rupture of IA.

Photoinduced Ordered Growth of Copper-Doped Polyaniline Nanotubes: A Method to Improve the Catalytic Activity for C-N Coupling Reactions.

Polyaniline-supported metal nanoparticles (M@PANIs) have been widely employed as catalysts for organic reactions. Traditionally, the catalytic activities of the materials can be improved by introducing functional groups onto the aniline monomers, but it may enhance the catalyst cost and reduce the production yield of the material. This work reports a new strategy for improving the catalytic activity of M@PANIs. It was found that induced by visible light in the presence of a polymeric carbon nitride catalyst and copper dopant, the oxidative polymerization of simple aniline occurred slowly and orderly to produce the copper-doped polyaniline nanotubes. The unique tubular structure protected the catalytically active Cu(I) inside and endowed even more sufficient contact of the catalytic sites with reactants so that the material exhibited excellent catalytic performances in C-N coupling reactions.

Tunable single emitter-cavity coupling strength through waveguide-assisted energy quantum transfer.

The emitter-cavity strong coupling manifests crucial significance for exploiting quantum technology, especially in the scale of individual emitters. However, due to the small light-matter interaction cross-section, the single emitter-cavity strong coupling has been limited by its harsh requirement on the quality factor of the cavity and the local density of optical states. Herein, we present a strategy termed waveguide-assisted energy quantum transfer (WEQT) to improve the single emitter-cavity coupling strength by extending the interaction cross-section. Multiple ancillary emitters are optically linked by a waveguide, providing an indirect coupling channel to transfer the energy quantum between target emitter and cavity. An enhancement factor of coupling strength g ̃ / g > 10 can be easily achieved, which dramatically release the rigorous design of cavity. As an extension of concept, we further show that the ancillae can be used as controlling bits for a photon gate, opening up new degrees of freedom in quantum manipulation.

Gut commensal metabolite rhamnose promotes macrophages phagocytosis by activating SLC12A4 and protects against sepsis in mice.

Sepsis progression is significantly associated with the disruption of gut eubiosis. However, the modulatory mechanisms of gut microbiota operating during sepsis are still unclear. Herein, we investigated how gut commensals impact sepsis development in a pre-clinical model. Cecal ligation and puncture (CLP) surgery was used to establish polymicrobial sepsis in mice. Mice depleted of gut microbiota by an antibiotic cocktail (ABX) exhibited a significantly higher level of mortality than controls. As determined by metabolomics analysis, ABX treatment has depleted many metabolites, and subsequent supplementation with l-rhamnose (rhamnose, Rha), a bacterial carbohydrate metabolite, exerted profound immunomodulatory properties with a significant enhancement in macrophage phagocytosis, which in turn improved organ damage and mortality. Mechanistically, rhamnose binds directly to and activates the solute carrier family 12 (potassium-chloride symporter), member 4 (SLC12A4) in macrophages and promotes phagocytosis by activating the small G-proteins, Ras-related C3 botulinum toxin substrate1 (Rac1) and cell division control protein 42 homolog (Cdc42). Interestingly, rhamnose has enhanced the phagocytosis capacity of macrophages from sepsis patients. In conclusion, by identifying SLC12A4 as the host interacting protein, we disclosed that the gut commensal metabolite rhamnose is a functional molecular that could promote the phagocytosis capacity of macrophages and protect the host against sepsis.

The nasal microbiota is a potential diagnostic biomarker for sepsis in critical care units.

This study aimed to characterize the composition of intestinal and nasal microbiota in septic patients and identify potential microbial biomarkers for diagnosis. A total of 157 subjects, including 89 with sepsis, were enrolled from the affiliated hospital. Nasal swabs and fecal specimens were collected from septic and non-septic patients in the intensive care unit (ICU) and Department of Respiratory and Critical Care Medicine. DNA was extracted, and the V4 region of the 16S rRNA gene was amplified and sequenced using Illumina technology. Bioinformatics analysis, statistical processing, and machine learning techniques were employed to differentiate between septic and non-septic patients. The nasal microbiota of septic patients exhibited significantly lower community richness (P = 0.002) and distinct compositions (P = 0.001) compared to non-septic patients. Corynebacterium, Staphylococcus, Acinetobacter, and Pseudomonas were identified as enriched genera in the nasal microbiota of septic patients. The constructed machine learning model achieved an area under the curve (AUC) of 89.08, indicating its efficacy in differentiating septic and non-septic patients. Importantly, model validation demonstrated the effectiveness of the nasal microecological diagnosis prediction model with an AUC of 84.79, while the gut microecological diagnosis prediction model had poor predictive performance (AUC = 49.24). The nasal microbiota of ICU patients effectively distinguishes sepsis from non-septic cases and outperforms the gut microbiota. These findings have implications for the development of diagnostic strategies and advancements in critical care medicine.IMPORTANCEThe important clinical significance of this study is that it compared the intestinal and nasal microbiota of sepsis with non-sepsis patients and determined that the nasal microbiota is more effective than the intestinal microbiota in distinguishing patients with sepsis from those without sepsis, based on the difference in the lines of nasal specimens collected.

Clinical characteristics of post-stroke basal ganglia aphasia and the study of language-related white matter tracts based on diffusion spectrum imaging.

BACKGROUND: Stroke often damages the basal ganglia, leading to atypical and transient aphasia, indicating that post-stroke basal ganglia aphasia (PSBGA) may be related to different anatomical structural damage and functional remodeling rehabilitation mechanisms. The basal ganglia contain dense white matter tracts (WMTs). Hence, damage to the functional tract may be an essential anatomical structural basis for the development of PSBGA. METHODS: We first analyzed the clinical characteristics of PSBGA in 28 patients and 15 healthy controls (HCs) using the Western Aphasia Battery and neuropsychological test batteries. Moreover, we investigated white matter injury during the acute stage using diffusion magnetic resonance imaging scans for differential tractography. Finally, we used multiple regression models in correlation tractography to analyze the relationship between various language functions and quantitative anisotropy (QA) of WMTs. RESULTS: Compared with HCs, patients with PSBGA showed lower scores for fluency, comprehension (auditory word recognition and sequential commands), naming (object naming and word fluency), reading comprehension of sentences, Mini-Mental State Examination, and Montreal Cognitive Assessment, along with increased scores in Hamilton Anxiety Scale-17 and Hamilton Depression Scale-17 within 7 days after stroke onset (P < 0.05). Differential tractography revealed that patients with PSBGA had damaged fibers, including in the body fibers of the corpus callosum, left cingulum bundles, left parietal aslant tracts, bilateral superior longitudinal fasciculus II, bilateral thalamic radiation tracts, left fornix, corpus callosum tapetum, and forceps major, compared with HCs (FDR < 0.02). Correlation tractography highlighted that better comprehension was correlated with a higher QA of the left inferior fronto-occipital fasciculus (IFOF), corpus callosum forceps minor, and left extreme capsule (FDR < 0.0083). Naming was positively associated with the QA of the left IFOF, forceps minor, left arcuate fasciculus, and uncinate fasciculus (UF) (FDR < 0.0083). Word fluency of naming was also positively associated with the QA of the forceps minor, left IFOF, and thalamic radiation tracts (FDR < 0.0083). Furthermore, reading was positively correlated with the QA of the forceps minor, left IFOF, and UF (FDR < 0.0083). CONCLUSION: PSBGA is primarily characterized by significantly impaired word fluency of naming and preserved repetition abilities, as well as emotional and cognitive dysfunction. Damaged limbic pathways, dorsally located tracts in the left hemisphere, and left basal ganglia pathways are involved in PSBGA pathogenesis. The results of connectometry analysis further refine the current functional localization model of higher-order neural networks associated with language functions.

Combined analysis of the effects of hypoxia and oxidative stress on DNA methylation and the transcriptome in HTR-8/SVneo trophoblast cells.

The alterations in DNA methylation and transcriptome in trophoblast cells under conditions of low oxygen and oxidative stress have major implications for pregnancy-related disorders. However, the exact mechanism is still not fully understood. In this study, we established models of hypoxia (H group) and oxidative stress (HR group) using HTR-8/SVneo trophoblast cells and performed combined analysis of genome-wide DNA methylation changes using reduced representation bisulphite sequencing and transcriptome expression changes using RNA sequencing. Our findings revealed that the H group exhibited a higher number of differentially methylated genes and differentially expressed genes than the HR group. In the H group, only 0.90% of all differentially expressed genes displayed simultaneous changes in DNA methylation and transcriptome expression. After the threshold was expanded, this number increased to 6.29% in the HR group. Notably, both the H group and HR group exhibited concurrent alterations in DNA methylation and transcriptome expression within Axon guidance and MAPK signalling pathway. Among the top 25 differentially methylated KEGG pathways in the promoter region, 11 pathways were commonly enriched in H group and HR group, accounting for 44.00%. Among the top 25 KEGG pathways in transcriptome with significant differences between the H group and HR group, 10 pathways were consistent, accounting for 40.00%. By integrating our previous data on DNA methylation from preeclamptic placental tissues, we identified that the ANKRD37 and PFKFB3 genes may contribute to the pathogenesis of preeclampsia through DNA methylation-mediated transcriptome expression under hypoxic conditions.

Identification of Curcumin Targets in the Brain of Epileptic Mice Using DARTS.

Curcumin, a compound derived from turmeric, is traditionally utilized in East Asian medicine for treating various health conditions, including epilepsy. Despite its involvement in numerous cellular signaling pathways, the specific mechanisms and targets of curcumin in epilepsy treatment have remained unclear. Our study focused on identifying the primary targets and functional pathways of curcumin in the brains of epileptic mice. Using drug affinity responsive target stabilization (DARTS) and affinity chromatography, we identified key targets in the mouse brain, revealing 232 and 70 potential curcumin targets, respectively. Bioinformatics analysis revealed a strong association of these proteins with focal adhesions and cytoskeletal components. Further experiments using DARTS, along with immunofluorescence staining and cell migration assays, confirmed curcumin's ability to regulate the dynamics of focal adhesions and influence cell migration. This study not only advances our understanding of curcumin's role in epilepsy treatment but also serves as a model for identifying therapeutic targets in neurological disorders.

Quantification of gut microbiome metabolites using chemical isotope derivatization strategy combined with LC-MS/MS: Application in neonatal hypoxic-ischemic encephalopathy rat model.

The gut microbiome plays pivotal roles in various physiological and pathological processes, with key metabolites including short chain fatty acids (SCFAs), bile acids (BAs), and tryptophan (TRP) derivatives gaining significant attention for their diverse physiological roles. However, quantifying these metabolites presents challenges due to structural similarity, low abundance, and inherent technical limitations in traditional detection methods. In this study, we developed a precise and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method utilizing a chemical isotope derivatization technique employing 4-(aminomethyl)-N,N-dimethylaniline-d0/d6 (4-AND-d0/d6) reagents to quantify 37 typical gut microbiome-derived metabolites. This method achieved an impressive 1500-fold enhancement in sensitivity for detecting metabolites, compared to methods using non-derivatized, intact molecules. Moreover, the quantitative accuracy of our chemical isotope derivatization strategy proved comparable to the stable isotope labeled internal standards (SIL-IS) method. Subsequently, we successfully applied this newly developed method to quantify target metabolites in plasma, brain, and fecal samples obtained from a neonatal hypoxic-ischemic encephalopathy (HIE) rat model. The aim was to identify crucial metabolites associated with the progression of HIE. Overall, our sensitive and reliable quantification method holds promise in elucidating the role of gut microbiome metabolites in the pathogenesis of various diseases.

High intestinal carriage of Clostridium perfringens in healthy individuals and ICU patients in Hangzhou, China.

Clostridium perfringens has emerged as a growing public health concern due to its ability to cause various infections and its increasing resistance to antibiotics. To assess its current epidemiology in clinical settings, we conducted a survey involving 426 healthy individuals and 273 ICU inpatients at a provincial hospital in China. Our findings revealed a high prevalence of C. perfringens in healthy individuals (45.77%, 95% CI: 41.0%-50.6%) and ICU patients (12.82%, 95% CI: 9.1%-17.4%). The identified 220 C. perfringens isolates displayed substantial resistance to erythromycin (57.9%), clindamycin (50.7%), and tetracycline (32.0%), primarily attributed to the presence of erm(Q) (54.4%), lnu(P) (13.8%), tetB(P) (83.6%), and tetA(P) (66.7%). Notably, C. perfringens isolates from this particular hospital demonstrated a high degree of sequence type diversity and phylogenic variation, suggesting that the potential risk of infection primarily arises from the bacteria's gut colonization rather than clonal transmissions within the clinical environment. This study provides an updated analysis of the current epidemiology of C. perfringens in healthy individuals and ICU patients in China and emphasizes the need to optimize intervention strategies against its public health threat. IMPORTANCE: Clostridium perfringens is a bacterium of growing public health concern due to its ability to cause infections and its increasing resistance to antibiotics. Understanding its epidemiology in clinical settings is essential for intervention strategies. This study surveyed healthy individuals and ICU inpatients in a provincial hospital in China. It found a high prevalence of C. perfringens, indicating infection risk. The isolates also showed significant antibiotic resistance. Importantly, the study revealed diverse sequence types and phylogenetic variation, suggesting infection risk from intestinal colonization rather than clonal transmission in hospitals. This analysis emphasizes the need to optimize intervention strategies against this public health threat.

Dynamic behaviors of protein and water associated with fresh noodle quality during processing based on different HMW-GSs at Glu-D1.

In this study, dynamic behaviors of proteins and water during fresh noodles processing associated with the quality of fresh noodles were systematically investigated by using wheat near-isogenic lines carrying high-molecular-weight glutenin subunits (HMW-GS) 2 + 12, 3 + 12 or 5 + 10 at the Glu-D1 locus. The results showed that subunits 5 + 10 tend to form a complex gluten network and had a poorly hydrated ability, that prevent the intrusion of external water during cooking; subunits 3 + 12 formed a moderate strength gluten network that generated a medium ability to resist the hydrated and mechanical treatment, which explained the highest water absorption and less cooking loss of cooked noodles; while subunits 2 + 12 formed fragile protein aggregates that had a poor ability to resist mechanical. The findings demonstrated that subunits 3 + 12 provided a suitable gluten network which was crucial for intrusion and hydration of external water thus formed a uniform gluten network and excellent fresh noodle quality.

Blood-brain barrier disruption and hemorrhagic transformation in acute stroke before endovascular reperfusion therapy.

Background and purpose: Early blood-brain barrier (BBB) disruption in patients with acute ischemic stroke (AIS) can be detected on perfusion computed tomography (PCT) images before undergoing reperfusion therapy. In this study, we aimed to determine whether early disruption of the BBB predicts intracranial hemorrhage transformation (HT) in patients with AIS undergoing endovascular therapy and further identify factors influencing BBB disruption. Methods: We retrospectively analyzed general clinical and imaging data derived from 159 consecutive patients with acute anterior circulation stroke who were admitted to the Department of Neurology of the First Hospital of Jilin University, and who underwent endovascular treatment between January 1, 2021, and March 31, 2023. We evaluated the relationship between BBB destruction and intracranial HT before endovascular reperfusion therapy and examined the risk factors for early BBB destruction. Results: A total of 159 patients with assessable BBB leakage were included. The median (interquartile range, IQR) age was 63 (54-70) years, 108 (67.9%) patients were male, and the median baseline National Institutes of Health Stroke Scale (NHISS) score was 12 (10-15). Follow-up non-contrast computed tomography (NCCT) detected HT in 63 patients. After logistic regression modeling adjustment, we found that BBB leakage in the true leakage area was slightly more than 2-fold risk of HT (odds ratio [OR], 2.01; 95% confidence interval [CI] 1.02-3.92). Heart rate was also associated with HT (OR, 1.03, 95% CI, 1.00-1.05). High Blood-brain barrier permeability (BBBP) in the true leakage area was positively correlated with infarct core volume (OR, 1.03; 95% CI, 1.01-1.05). Conclusion: Early BBB destruction before endovascular reperfusion therapy was associated with HT, whereas high BBBP correlated positively with infarct core volume.

National genomic epidemiology investigation revealed the spread of carbapenem-resistant Escherichia coli in healthy populations and the impact on public health.

BACKGROUND: Carbapenem-resistant Escherichia coli (CREC) has been considered as WHO priority pathogens, causing a great public health concern globally. While CREC from patients has been thoroughly investigated, the prevalence and underlying risks of CREC in healthy populations have been overlooked. Systematic research on the prevalence of CREC in healthy individuals was conducted here. We aimed to characterize CREC collected from healthy populations in China between 2020 and 2022 and to compare the genomes of CREC isolates isolated from healthy individuals and clinical patients. METHODS: We present a nationwide investigation of CREC isolates among healthy populations in China, employing robust molecular and genomic analyses. Antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatics were utilized to analyze a cohort of CREC isolates (n = 113) obtained from fecal samples of 5 064 healthy individuals. Representative plasmids were extracted for third-generation nanopore sequencing. We previously collected 113 non-duplicate CREC isolates (59 in 2018, 54 in 2020) collected from ICU patients in 15 provinces and municipalities in China, and these clinical isolates were used to compare with the isolates in this study. Furthermore, we employ comparative genomics approaches to elucidate molecular variations and potential correlations between clinical and non-clinical CREC isolates. RESULTS: A total of 147 CREC isolates were identified from 5 064 samples collected across 11 provinces in China. These isolates were classified into 64 known sequence types (STs), but no dominant STs were observed. In total, seven carbapenemase genes were detected with blaNDM-5 (n = 116) being the most prevalent one. Genetic environments and plasmid backbones of blaNDM were conserved in CREC isolated from healthy individuals. Furthermore, we compared clinical and healthy human-originated CRECs, revealing noteworthy distinctions in 23 resistance genes, including blaNDM-1, blaNDM-5, and blaKPC (χ2 test, p < 0.05). Clinical isolates contained more virulence factors associated with iron uptake, adhesion, and invasion than those obtained from healthy individuals. Notably, CREC isolates generally found healthy people are detected in hospitalized patients. CONCLUSIONS: Our findings underscore the significance of healthy populations-derived CRECs as a crucial reservoir of antibiotic resistance genes (ARGs). This highlights the need for ongoing monitoring of CREC isolates in healthy populations to accurately assess the potential risks posed by clinical CREC isolates.

The role of language-related functional brain regions and white matter tracts in network plasticity of post-stroke aphasia.

The neural mechanisms underlying language recovery after a stroke remain controversial. This review aimed to summarize the plasticity and reorganization mechanisms of the language network through neuroimaging studies. Initially, we discussed the involvement of right language homologues, perilesional tissue, and domain-general networks. Subsequently, we summarized the white matter functional mapping and remodeling mechanisms associated with language subskills. Finally, we explored how non-invasive brain stimulation (NIBS) promoted language recovery by inducing neural network plasticity. It was observed that the recruitment of right hemisphere language area homologues played a pivotal role in the early stages of frontal post-stroke aphasia (PSA), particularly in patients with larger lesions. Perilesional plasticity correlated with improved speech performance and prognosis. The domain-general networks could respond to increased "effort" in a task-dependent manner from the top-down when the downstream language network was impaired. Fluency, repetition, comprehension, naming, and reading skills exhibited overlapping and unique dual-pathway functional mapping models. In the acute phase, the structural remodeling of white matter tracts became challenging, with recovery predominantly dependent on cortical activation. Similar to the pattern of cortical activation, during the subacute and chronic phases, improvements in language functions depended, respectively, on the remodeling of right white matter tracts and the restoration of left-lateralized language structural network patterns. Moreover, the midline superior frontal gyrus/dorsal anterior cingulate cortex emerged as a promising target for NIBS. These findings offered theoretical insights for the early personalized treatment of aphasia after stroke.

Association of air temperature exposure during pregnancy with risk of preeclampsia in Guangzhou, China.

Environmental exposures during pregnancy have been associated with adverse obstetric outcomes. However, limited and inconsistent evidence exists regarding the association between air temperature exposure and the risk of preeclampsia (PE). This study aimed to evaluate the correlation between ambient temperature exposure during pregnancy and PE risk, as well as identify the specific time window of temperature exposure that increases PE risk. A population-based cohort study was conducted from January 2012 to April 2022 in Guangzhou, China. Pregnant women were recruited in early pregnancy and followed until delivery. A total of 3,314 PE patients and 114,201 normal pregnancies were included. Ambient temperature exposures at different gestational weeks were recorded for each participant. Logistic regression models were used to evaluate the correlation between ambient temperature exposure and PE risk. Stratified analyses were conducted based on maternal age and pre-pregnancy BMI. Distributed lag models were employed to identify the time window of temperature exposure related to PE. Exposure to extreme high temperature (aOR = 1.24, 95 % CI 1.12-1.38) and moderate high temperature (aOR = 1.22, 95 % CI 1.10-1.35) during early pregnancy was associated with an increased risk of PE. Furthermore, women with higher pre-pregnancy BMI had a higher risk of developing PE when exposed to high temperature during early pregnancy compared to normal-weight women. The time window of temperature exposure related to PE was identified as pregnancy weeks 1 to 8. This study provides evidence for the association of high temperature exposure during early pregnancy with the risk of PE, as well as identifies the specific time window of temperature exposure related to PE. These findings have implications for developing potential strategies to protect pregnant women, particularly those with higher pre-pregnancy BMI, from the adverse effects of extreme temperatures during early pregnancy.

metaProbiotics: a tool for mining probiotic from metagenomic binning data based on a language model.

Beneficial bacteria remain largely unexplored. Lacking systematic methods, understanding probiotic community traits becomes challenging, leading to various conclusions about their probiotic effects among different publications. We developed language model-based metaProbiotics to rapidly detect probiotic bins from metagenomes, demonstrating superior performance in simulated benchmark datasets. Testing on gut metagenomes from probiotic-treated individuals, it revealed the probioticity of intervention strains-derived bins and other probiotic-associated bins beyond the training data, such as a plasmid-like bin. Analyses of these bins revealed various probiotic mechanisms and bai operon as probiotic Ruminococcaceae's potential marker. In different health-disease cohorts, these bins were more common in healthy individuals, signifying their probiotic role, but relevant health predictions based on the abundance profiles of these bins faced cross-disease challenges. To better understand the heterogeneous nature of probiotics, we used metaProbiotics to construct a comprehensive probiotic genome set from global gut metagenomic data. Module analysis of this set shows that diseased individuals often lack certain probiotic gene modules, with significant variation of the missing modules across different diseases. Additionally, different gene modules on the same probiotic have heterogeneous effects on various diseases. We thus believe that gene function integrity of the probiotic community is more crucial in maintaining gut homeostasis than merely increasing specific gene abundance, and adding probiotics indiscriminately might not boost health. We expect that the innovative language model-based metaProbiotics tool will promote novel probiotic discovery using large-scale metagenomic data and facilitate systematic research on bacterial probiotic effects. The metaProbiotics program can be freely downloaded at https://github.com/zhenchengfang/metaProbiotics.

Copper Vacancy and LSPR-Activated MXene Synergistically Enabling Selective Photoreduction CO2 to Acetate.

Photocatalytic CO2 conversion towards C2+ fuels is a promising technology for simultaneously achieving carbon neutrality and alleviating the energy crisis. However, this strategy is inefficient due to the difficulty of both multi-electron transfer and C-C coupling during C2+ formation. In this work, CuInS2/MXene heterostructure with Cu vacancy is rationally designed by in situ hydrothermal synthesis. The VCu-CuInS2/MXene heterostructure has a suitable band structure and tight interface contact. Catalytic performances under different testing conditions, in situ spectroscopy, and COMSOL simulation reveal that LSPR-activated MXene promotes the formation of crucial intermediate CH2* and triggers the C-C coupling process under near-infrared light, as the key to acetate. Moreover, in situ XPS analysis, DFT calculations, and photoelectrochemical characterizations unveil that copper vacancy can promote charge transfer from CuInS2 to MXene and boost local electron aggregation on the MXene, further enhancing the photocatalytic efficiency and selectivity of C2 products. Contributing to the synergistic effect of copper vacancy and plasmonic MXene, VCu-CuInS2/MXene achieved excellent CO2RR activity with an acetate evolution rate of 250.0 µmol/h/g and a selectivity of 97.5 % under the full spectrum irradiation, which is 38.8 and 3.3 times higher than that of VCu-CuInS2 and CuInS2/MXene, respectively.

One-Pot Reaction Sequence: N-Acylation/Pictet-Spengler Reaction/Intramolecular [4 + 2] Cycloaddition/Aromatization in the Synthesis of ß-Carboline Alkaloid Analogues.

One-pot synthesis of tetrahydro-ß-carbolines, fused with an isoindole core, was proposed starting from maleic anhydride and azomethines easily available from tryptamines and 3-(hetaryl)acroleins. This sequence includes four key steps: an acylation of the aldimine with maleic anhydride, a Pictet-Spengler cyclization, an intramolecular Diels-Alder reaction, and a concluding [1,3]-H shift. As a result, six- or seven-nuclear alkaloid-like heterocyclic systems, containing a benzo[1,2]indolizino[8,7-b]indole fragment annulated with furan, thiophene, or pyrrole, are formed in a diastereoselective manner.

The Control of the Expansion or Compression of Colloidal Crystals Lattice with Salt Solution.

Tuning the lattice spacing or stop bands holds great significance in the design and application of materials with colloidal crystals. Typically, particle surface modifications or the application of external physical fields are needed. In this study, we demonstrated the ability to expand or compress the lattice of colloidal crystals simply by utilizing a salt solution, without the need for any special treatments to the colloidal particles. We found that by only considering the diffusiophoresis effect we cannot explain the reversion of lattice expansion to lattice compression with the increase in the salt concentration and that the diffusioosmotic flow originating from the container wall must be taken into account. Further analysis revealed that variations in the salt concentration altered the relative amplitudes between diffusiophoresis and diffusioosmosis through changing the zeta potentials of the particles and the wall, and the competition between the particle diffusiophoresis and wall diffusioosmosis lay at the center of the underlying mechanism.

Automatic detection of standing dead trees based on improved YOLOv7 from airborne remote sensing imagery.

Detecting and localizing standing dead trees (SDTs) is crucial for effective forest management and conservation. Due to challenges posed by mountainous terrain and road conditions, conducting a swift and comprehensive survey of SDTs through traditional manual inventory methods is considerably difficult. In recent years, advancements in deep learning and remote sensing technology have facilitated real-time and efficient detection of dead trees. Nevertheless, challenges persist in identifying individual dead trees in airborne remote sensing images, attributed to factors such as small target size, mutual occlusion and complex backgrounds. These aspects collectively contribute to the increased difficulty of detecting dead trees at a single-tree scale. To address this issue, the paper introduces an improved You Only Look Once version 7 (YOLOv7) model that incorporates the Simple Parameter-Free Attention Module (SimAM), an unparameterized attention mechanism. This improvement aims to enhance the network's feature extraction capabilities and increase the model's sensitivity to small target dead trees. To validate the superiority of SimAM_YOLOv7, we compared it with four widely adopted attention mechanisms. Additionally, a method to enhance model robustness is presented, involving the replacement of the Complete Intersection over Union (CIoU) loss in the original YOLOv7 model with the Wise-IoU (WIoU) loss function. Following these, we evaluated detection accuracy using a self-developed dataset of SDTs in forests. The results indicate that the improved YOLOv7 model can effectively identify dead trees in airborne remote sensing images, achieving precision, recall and mAP@0.5 values of 94.31%, 93.13% and 98.03%, respectively. These values are 3.67%, 2.28% and 1.56% higher than those of the original YOLOv7 model. This improvement model provides a convenient solution for forest management.