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The intensity of human activity, habitat loss and habitat degradation have significant impacts on biodiversity. Habitat quality plays an important role in spatial dynamics when evaluating fragmented landscapes and the effectiveness of biodiversity conservation. This study aimed to evaluate the status and characteristic variation in habitat quality to analyze the underlying factors affecting habitat quality in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Here, we applied Kendall’s rank correlation method to calculate the sensitivity of habitat types to threat factors for the Integrated Valuation of Ecosystem Services and Tradeoffs habitat quality (InVEST-HQ) model. The spatiotemporal variation in habitat quality of the GBA in the period 1995–2015 was estimated based on the InVEST-HQ model. We analyzed the characteristic habitat quality using different ecosystem classifications and at different elevation gradients. Fractional vegetation cover, the proportion of impervious surface, population distribution and gross domestic product were included as the effect factors for habitat quality. The correlation between the effect factors and habitat quality was analyzed using Pearson’s correlation tests. The results showed that the spatial pattern of habitat quality decreased from fringe areas to central areas in the GBA, that the forest ecosystem had the highest value of habitat quality, and that habitat quality increased with elevation. In the period from 1995 to 2015, habitat quality declined markedly and this could be related to vegetation loss, land use change and intensity of human activity. Built-up land expansion and forest land fragmentation were clear markers of land use change. This study has great significance as an operational approach to mitigating the tradeoff between natural environment conservation and rapid economic development.

Although chiral allene preparation via formal S N 2’ nucleophilic substitutions of enantioenriched propargylic derivatives or metal-catalyzed reactions of racemic propargylic derivatives has attracted considerable attention and found applications in many areas of research, direct use of propargylic alcohols instead of propargylic derivatives for catalytic asymmetric allene synthesis is unknown. Here, we show that a highly enantioselective synthesis of tetrasubstituted allenes from racemic propargylic alcohols has been realized by organocatalysis with good efficiency (up to 96% yield and 97% ee). The intermolecular C–C and C–S bond formation was achieved efficiently with simultaneous stereocontrol over the axial chirality. Furthermore, an adjacent quaternary stereocenter could also be constructed. Mechanistically, the reaction may involve efficient stereocontrol on the propargylic cation by its chiral counter anion or 1,8-conjugate addition of para -quinone methides. In sharp contrast to previous central chirality construction, this process employs quinone methides for axial chirality construction. Axially chiral allenes that are normally present in natural products, bioactive molecules, organocatalysts, and functional materials are usually produced from propargylic derivatives. Here, the authors show direct use of propargylic alcohols for catalytic asymmetric allene synthesis.

What are the main findings? A framework for constructing spatial networks of multiple ecosystem services was proposed. The framework is implemented by the InVEST model, the minimum cumulative resistance model and a multiresolution segmentation method. What are the implications of the main findings? The proposed framework is feasible for capturing the spatial connectivity of multiple ecosystem services. Different ecosystem service networks exhibited conspicuous spatial heterogeneity but generally maintained relatively high connectivity. Exploring the interaction relationship among multiple ecosystem services is vital for maintaining ecosystem function. However, traditional approaches are limited in their ability to: (i) characterize complex interactions and (ii) visualize the spatial connectivity of various ecosystem services delivered by social–ecological systems. To address these challenges, a framework for constructing spatial networks of multiple ecosystem services was proposed. The framework is implemented by: (i) estimating the spatial distribution of multiple ecosystem services using the InVEST model, and (ii) generating network nodes and edges with geographical attributes based on the minimum cumulative resistance model and a multiresolution segmentation method. We conducted a case study in the Guangdong–Hong Kong–Macao Greater Bay Area and examined the topological features of the spatial networks using complex network indicators. For each network, winding and multiple edges connected adjacent nodes and formed continuous linkages across the entire study area, indicating that the proposed framework is feasible for capturing the spatial connectivity of multiple ecosystem services. The different ecosystem service networks exhibited conspicuous spatial heterogeneity and generally maintained relatively high connectivity, as evidenced by their tree-like structure with winding pathways and the distribution of multi-edge nodes, indicating that each ES was predominantly connected with multiple other ecosystem services. Meanwhile, nodes with high values of degree centrality and clustering coefficient were mainly concentrated in coastal and mountainous regions. This study advances the representation of complex interactions among multiple ecosystem services from a spatial perspective, thereby facilitating a deeper understanding of the interaction mechanisms underlying ecosystem functioning.

Background Adolescent depression is becoming one of the major public health concerns, because of its increased prevalence and risk of significant functional impairment and suicidality. Clinical depression commonly emerges in adolescence; therefore, the prevention and intervention of depression at this stage is crucial. Recent evidence supports the importance of the gut microbiota (GM) in the modulation of multiple functions associated with depression through the gut-brain axis (GBA). However, the underlying mechanisms remain poorly understood. Therefore, in the current study, we aimed to screen the microbiota out from healthy and depressive adolescents, delineate the association of the targeted microbiota and the adolescent depression, address the salutary effects of the targeted microbiota on anti-depressive behaviors in mice involving the metabolism of the tryptophan (Trp)-derived neurotransmitters along the GBA. Results Here, we found the gut microbiota from healthy adolescent volunteers, first diagnosis patients of adolescent depression, and sertraline interveners after first diagnosis displayed significant difference, the relative abundance of Faecalibacterium , Roseburia , Collinsella , Blautia , Phascolarctobacterium , Lachnospiraceae-unclassified decreased in adolescent depressive patients, while restored after sertraline treatment. Of note, the Roseburia abundance exhibited a high efficiency in predicting adolescent depression. Intriguingly, transplantation of the fecal microbiota from healthy adolescent volunteers to the chronic restraint stress (CRS)-induced adolescent depressed mice significantly ameliorated mouse depressive behaviors, in which the Roseburia exerted critical roles, since its effective colonization in the mouse colon resulted in remarkably increased 5-HT level and reciprocally decreased kynurenine (Kyn) toxic metabolites quinolinic acid (Quin) and 3-hydroxykynurenine (3-HK) levels in both the mouse brain and colon. The specific roles of the Roseburia were further validated by the target bacteria transplantation mouse model, Roseburia intestinalis ( Ri .) was gavaged to mice and importantly, it dramatically ameliorated CRS-induced mouse depressive behaviors, increased 5-HT levels in the brain and colon via promoting tryptophan hydroxylase-2 (TPH2) or -1 (TPH1) expression. Reciprocally, Ri. markedly restrained the limit-step enzyme responsible for kynurenine (indoleamine2,3-dioxygenase 1, IDO1) and quinolinic acid (3-hydroxyanthranilic acid 3,4-dioxygenase, 3HAO) generation, thereby decreased Kyn and Quin levels. Additionally, Ri . administration exerted a pivotal role in the protection of CRS-induced synaptic loss, microglial activation, and astrocyte maintenance. Conclusions This study is the first to delineate the beneficial effects of Ri . on adolescent depression by balancing Trp-derived neurotransmitter metabolism and improving synaptogenesis and glial maintenance, which may yield novel insights into the microbial markers and therapeutic strategies of GBA in adolescent depression. 5cVo2w5j9eyh76CmRyRzSQ Video Abstract

Exosomes are extracellular vesicles with diameters of about 100 nm that are naturally secreted by cells into body fluids. They are derived from endosomes and are wrapped in lipid membranes. Exosomes are involved in intracellular metabolism and intercellular communication. They contain nucleic acids, proteins, lipids, and metabolites from the cell microenvironment and cytoplasm. The contents of exosomes can reflect their cells’ origin and allow the observation of tissue changes and cell states under disease conditions. Naturally derived exosomes have specific biomolecules that act as the “fingerprint” of the parent cells, and the contents changed under pathological conditions can be used as biomarkers for disease diagnosis. Exosomes have low immunogenicity, are small in size, and can cross the blood–brain barrier. These characteristics make exosomes unique as engineering carriers. They can incorporate therapeutic drugs and achieve targeted drug delivery. Exosomes as carriers for targeted disease therapy are still in their infancy, but exosome engineering provides a new perspective for cell‐free disease therapy. This review discussed exosomes and their relationship with the occurrence and treatment of some neuropsychiatric diseases. In addition, future applications of exosomes in the diagnosis and treatment of neuropsychiatric disorders were evaluated in this review. Exosomes from neural cells can cross the blood–brain barrier, which can be used for diagnosis. Meanwhile, exosomes can be modified and engineered by loading specific nucleic acids, proteins, and drugs, which can be peripherally injected and play a therapeutic role to restore the health of the brain.

This study examined to evaluate the predictive value of a nomogram with Ki-67 in overall and disease-free survival in glioma patients, a total of 76 patients diagnosed with glioma by pathology in Tengzhou Central People’s Hospital were enrolled. The baseline data and follow ups were retrospectively collected from medical records. The associations between Ki-67 and survival status were examined using log-rank test, univariate and multivariate Cox proportional hazard regression models. Calibrations were performed to validate the established nomograms. Ki-67 negative group showed of a longer OS survival time and a longer PFS survival time with log-rank test (x 2  = 16.101, P < 0.001 and x 2  = 16.961, P < 0.001). Age older than 50 years (HR = 2.074, 95% CI 1.097–3.923), abnormal treatment (HR = 2.932, 95% CI 1.343–6.403) and Ki-67 positive (HR = 2.722, 95% CI 1.097–6.755) were the independent predictive factors of death. High grade pathology (HR = 2.453, 95% CI 1.010–5.956) and Ki-67 positive (HR = 2.200, 95% CI 1.043–4.639) were the independent predictive factors of recurrence. The C-index for the nomogram of OS and PFS were 0.745 and 0.723, respectively. The calibration results showed that the nomogram could predict the overall and disease-free 1-year survival of glioma patients. In conclusion, the nomograms with Ki-67 as independent risk factor for OS and PFS could provide clinical consultation in the treatment and follow-up of malignant glioma.

Background Limited data are available on the effectiveness of inactivated and Ad5-nCoV COVID-19 vaccines in real-world use—especially against Omicron variants in SARS-CoV-2 infection-naïve population. Methods A matched case-control study was conducted among people aged ≥ 3 years between 2 December 2021 and 13 May 2022. Cases were SARS-CoV-2-infected individuals, individuals with severe/critical COVID-19, or COVID-19-related deaths. Controls were selected from consecutively test-negative individuals at the same time as cases were diagnosed and were exact-matched on year-of-age, gender, birthplace, illness onset date, and residential district in ratios of 1:1 with infected individuals and 4:1 with severe/critical COVID-19 and COVID-19-related death. Additionally, two subsets were constructed to analyze separate vaccine effectiveness (VE) of inactivated vaccines (subset 1) and Ad5-vectored vaccine (subset 2) against each of the three outcomes. Results Our study included 612,597 documented SARS-CoV-2 infections, among which 1485 progressed to severe or critical illness and 568 died. Administering COVID-19 vaccines provided limited protection against SARS-CoV-2 infection across all age groups (overall VE: 16.0%, 95% CI: 15.1–17.0%) but high protection against severe/critical illness (88.6%, 85.8–90.8%) and COVID-19-related death (91.6%, 86.8–94.6%). In subset 1, inactivated vaccine showed 16.3% (15.4–17.2%) effective against infection, 88.6% (85.8–90.9%) effective against severe/critical COVIID-19, and 91.7% (86.9–94.7%) against COVID-19 death. Booster vaccination with inactivated vaccines enhanced protection against severe COVID-19 (92.7%, 90.1–94.6%) and COVID-19 death (95.9%, 91.4–98.1%). Inactivated VE against infection began to wane 12 weeks after the last dose, but two and three doses sustained high protection levels (> 80%) against severe/critical illness and death, while subset 2 showed Ad5-vectored vaccine was 13.2% (10.9–15.5%) effective against infection and 77.9% (15.6–94.2%) effective against severe/critical COVIID-19. Conclusions Our real-world study found high and durable two- and three-dose inactivated VE against Omicron-associated severe/critical illness and death across all age groups, but lower effectiveness against Omicron infection, which reinforces the critical importance of full-series vaccination and timely booster dose administration for all eligible individuals.

Semantic segmentation is an important and challenging task in the aerial image community since it can extract the target level information for understanding the aerial image. As a practical application of aerial image semantic segmentation, building extraction always attracts researchers’ attention as the building is the specific land cover in the aerial images. There are two key points for building extraction from aerial images. One is learning the global and local features to fully describe the buildings with diverse shapes. The other one is mining the multi-scale information to discover the buildings with different resolutions. Taking these two key points into account, we propose a new method named global multi-scale encoder-decoder network (GMEDN) in this paper. Based on the encoder-decoder framework, GMEDN is developed with a local and global encoder and a distilling decoder. The local and global encoder aims at learning the representative features from the aerial images for describing the buildings, while the distilling decoder focuses on exploring the multi-scale information for the final segmentation masks. Combining them together, the building extraction is accomplished in an end-to-end manner. The effectiveness of our method is validated by the experiments counted on two public aerial image datasets. Compared with some existing methods, our model can achieve better performance.

Palygorskite (Pal) shows great potential for physical, chemical and biological uses due to its colloidal, catalytic and adsorption properties. Pal mines, however, are facing the challenge of low-grade materials (5-15%), making it difficult to use Pal in emerging fields such as new materials, environmental protection and health. Therefore, there is an urgent need to develop an efficient method for separating and purifying Pal to obtain high purity levels. Hence, we have developed a dispersant-assisted rotating liquid film reactor separation strategy based on sodium hexametaphosphate as the dispersant. This strategy utilizes the double electron layer of Pal and the density difference between impurities to achieve effective disaggregation and purification of Pal bundles through the promotion of repulsive driving effects. Under optimal conditions, the purity of Pal can be increased from less than 10% to over 80%. This research presents a novel approach to the efficient refining of low-grade Pal. The crudely purified Pal's adsorption capacity for methylene blue increased from 84.2 to 256.4 mg g-1.

Flavonoids are major active small-molecule compounds in bamboo leaves, which can be easily obtained from the bamboo leaves extraction residues (BLER) after the polysaccharides extraction. Six macroporous resins with different properties were screened to prepare and enrich isoorientin (IOR), orientin (OR), vitexin (VI), and isovitexin (IVI) from BLER, and the XAD-7HP resin with the best adsorption and desorption performance was selected for further evaluation. Based on the static adsorption experiments, the experimental results showed that the adsorption isotherm fitted well with the Langmuir isotherm model, and the adsorption process was better explained by the pseudo-second-order kinetic model. After the dynamic trial of resin column chromatography, 20 bed volume (BV) of upload sample and 60% ethanol as eluting solvent was used in a lab scale-up separation, and the results demonstrated that the content of four flavonoids could be increased by 4.5-fold, with recoveries between 72.86 and 88.21%. In addition, chlorogenic acid (CA) with purity of 95.1% was obtained in water-eluted parts during dynamic resin separation and further purified by high-speed countercurrent chromatography (HSCCC). In conclusion, this rapid and efficient method can provide a reference to utilize BLER to produce high-value-added food and pharmaceutical products.