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Species are fundamental units in biological research and can be defined on the basis of various operational criteria. There has been growing use of molecular approaches for species delimitation. Among the most widely used methods, the generalized mixed Yule-coalescent (GMYC) and Poisson tree processes (PTP) were designed for the analysis of single-locus data but are often applied to concatenations of multilocus data. In contrast, the Bayesian multispecies coalescent approach in the software Bayesian Phylogenetics and Phylogeography (BPP) explicitly models the evolution of multilocus data. In this study, we compare the performance of GMYC, PTP, and BPP using synthetic data generated by simulation under various speciation scenarios. We show that in the absence of gene flow, the main factor influencing the performance of these methods is the ratio of population size to divergence time, while number of loci and sample size per species have smaller effects. Given appropriate priors and correct guide trees, BPP shows lower rates of species overestimation and underestimation, and is generally robust to various potential confounding factors except high levels of gene flow. The single-threshold GMYC and the best strategy that we identified in PTP generally perform well for scenarios involving more than a single putative species when gene flow is absent, but PTP outperforms GMYC when fewer species are involved. Both methods are more sensitive than BPP to the effects of gene flow and potential confounding factors. Case studies of bears and bees further validate some of the findings from our simulation study, and reveal the importance of using an informed starting point for molecular species delimitation. Our results highlight the key factors affecting the performance of molecular species delimitation, with potential benefits for using these methods within an integrative taxonomic framework.

Diabetic nephropathy (DN) remains one of the severe complications associated with diabetes mellitus. It is worthwhile to uncover the underlying mechanisms of clinical benefits of human urine‐derived stem cells (hUSCs) in the treatment of DN. At present, the clinical benefits associated with hUSCs in the treatment of DN remains unclear. Hence, our study aims to investigate protective effect of hUSC exosome along with microRNA‐16‐5p (miR‐16‐5p) on podocytes in DN via vascular endothelial growth factor A (VEGFA). Initially, miR‐16‐5p was predicated to target VEGFA based on data retrieved from several bioinformatics databases. Notably, dual‐luciferase report gene assay provided further verification confirming the prediction. Moreover, our results demonstrated that high glucose (HG) stimulation could inhibit miR‐16‐5p and promote VEGFA in human podocytes (HPDCs). miR‐16‐5p in hUSCs was transferred through the exosome pathway to HG‐treated HPDCs. The viability and apoptosis rate of podocytes after HG treatment together with expression of the related factors were subsequently determined. The results indicated that miR‐16‐5p secreted by hUSCs could improve podocyte injury induced by HG. In addition, VEGA silencing could also ameliorate HG‐induced podocyte injury. Finally, hUSC exosomes containing overexpressed miR‐16‐5p were injected into diabetic rats via tail vein, followed by qualification of miR‐16‐5p and observation on the changes of podocytes, which revealed that overexpressed miR‐16‐5p in hUSCs conferred protective effects on HPDCs in diabetic rats. Taken together, the present study revealed that overexpressed miR‐16‐5p in hUSC exosomes could protect HPDCs induced by HG and suppress VEGFA expression and podocytic apoptosis, providing fresh insights for novel treatment of DN.

Background UCA1 is a long non-coding RNA which was found overexpressed in various human cancers including gastric cancer (GC). It is identified that UCA1 promotes GC cells proliferation, migration and invasion, however, the role of UCA1 during the processes of immune escape is still not unclear. Methods We collected 40 paired GC and non-tumor tissue samples. The level of UCA1 in GC and control tissue samples were determined by in situ hybridization and qRT-PCR. Cell viability was determined by MTT assay. GC cells’ migration capacities were examined by transwell assay. To understand the roles of UCA1 during immune escape, wildtype or UCA1 KO GC cells co-cultured with peripheral blood mononuclear cells or cytokine-induced killer cells in vitro. Mouse model was used to examine the function of UCA1 in vivo. Results UCA1 promoted GC cells proliferation and migration, and inhibit apoptosis. UCA1 repressed miR-26a/b, miR-193a and miR-214 expression through direct interaction and then up-regulated the expression of PDL1. UCA1-KO GC cells could induce a higher IFNγ expression when co-cultured with peripheral blood mononuclear cells (PBMCs), and have a lower survival rate when co-cultured with cytokine-induced killer (CIK) cells in vitro. UCA1-KO GC cells formed smaller tumors, had higher miR-26a, −26b, −193a and − 214 level, reduced cell proliferation and increased apoptosis in xenograft mouse model. Conclusions UCA1 overexpression protected PDL1 expression from the repression of miRNAs and contributed to the GC cells immune escape. UCA1 could serve as a potential novel therapeutic target for GC treatment.

Human-induced biodiversity change impairs ecosystem functions crucial to human well-being. However, the consequences of this change for ecosystem multifunctionality are poorly understood beyond effects of plant species loss, particularly in regions with high biodiversity across trophic levels. Here we adopt a multitrophic perspective to analyze how biodiversity affects multifunctionality in biodiverse subtropical forests. We consider 22 independent measurements of nine ecosystem functions central to energy and nutrient flow across trophic levels. We find that individual functions and multifunctionality are more strongly affected by the diversity of heterotrophs promoting decomposition and nutrient cycling, and by plant functional-trait diversity and composition, than by tree species richness. Moreover, cascading effects of higher trophic-level diversity on functions originating from lower trophic-level processes highlight that multitrophic biodiversity is key to understanding drivers of multifunctionality. A broader perspective on biodiversity-multifunctionality relationships is crucial for sustainable ecosystem management in light of non-random species loss and intensified biotic disturbances under future environmental change. Biodiversity change can impact ecosystem functioning, though this is primarily studied at lower trophic levels. Here, Schuldt et al. find that biodiversity components other than tree species richness are particularly important, and higher trophic level diversity plays a role in multifunctionality.

International agreements aim to conserve 17% of Earth's land area by 2020 but include no area‐based conservation targets within the working landscapes that support human needs through farming, ranching, and forestry. Through a review of country‐level legislation, we found that just 38% of countries have minimum area requirements for conserving native habitats within working landscapes. We argue for increasing native habitats to at least 20% of working landscape area where it is below this minimum. Such target has benefits for food security, nature's contributions to people, and the connectivity and effectiveness of protected area networks in biomes in which protected areas are underrepresented. We also argue for maintaining native habitat at higher levels where it currently exceeds the 20% minimum, and performed a literature review that shows that even more than 50% native habitat restoration is needed in particular landscapes. The post‐2020 Global Biodiversity Framework is an opportune moment to include a minimum habitat restoration target for working landscapes that contributes to, but does not compete with, initiatives for expanding protected areas, the UN Decade on Ecosystem Restoration (2021–2030) and the UN Sustainable Development Goals.

The ultimate goal of phototherapy based on nanoparticles, such as photothermal therapy (PTT) which generates heat and photodynamic therapy (PDT) which not only generates reactive oxygen species (ROS) but also induces a variety of anti-tumor immunity, is to kill tumors. In addition, due to strong efficacy in clinical treatment with minimal invasion and negligible side effects, it has received extensive attention and research in recent years. In this paper, the generations of nanomaterials in PTT and PDT are described separately. In clinical application, according to the different combination pathway of nanoparticles, it can be used to treat different diseases such as tumors, melanoma, rheumatoid and so on. In this paper, the mechanism of pathological treatment is described in detail in terms of inducing apoptosis of cancer cells by ROS produced by PDT, immunogenic cell death to provoke the maturation of dendritic cells, which in turn activate production of CD4+ T cells, CD8+T cells and memory T cells, as well as inhibiting heat shock protein (HSPs), STAT3 signal pathway and so on.

Recently, sleep has been recognized as a crucial factor for health and longevity. The daily sleep/wake cycle provides the basis of biorhythm, which controls whole-body homeostasis and homeodynamics. Sleep disturbances can contribute to several physical and psychological disorders, including cardiovascular disease, obesity, depression, and cognitive dysfunction. The clinical use of the N-methyl-D-aspartate (NMDA) receptor antagonist ketamine began in the 1970s. Over the years, physicians have used it as a short-acting anesthetic, analgesic, and antidepressant; however, in-depth research has revealed new possible applications for ketamine, such as for treating sleep disturbances and circadian rhythm disorders. The aim of this narrative review is to examine the literature on the mechanistic role of the antidepressant ketamine in affecting sleep disturbance. Additionally, we discuss the pharmacologic and pharmacokinetic mechanisms of ketamine as an antidepressant and the predictive biomarkers for ketamine’s effect on sleep and cognitive function.

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net.

In scenarios with constrained physical aperture sizes, aiming to enhance the resolution and accuracy of Direction of Arrival (DOA) estimation, this paper proposes a novel approach that integrates a moving synthetic virtual array with Sparse Bayesian Learning (SBL) for DOA estimation. Initially, a virtual array is constructed based on the motion characteristics of the target. Subsequently, the SBL method is employed to estimate the DOA of the target. Simulation experiments validate the effectiveness of this approach, demonstrating comparable DOA estimation performance to synthetic aperture methods with larger aperture sizes, even in situations with limited aperture expansion. Furthermore, under constant virtual aperture expansion, this method surpasses non‐SBL methods regarding DOA resolution. We explore the construction of a virtual array through the relative displacement induced by target motion. It further investigates the performance improvement of Direction of Arrival (DOA) estimation resolution using sparse Bayesian learning within the context of a virtual array.

Long non‐coding RNA (lncRNA) lnc‐ISG20 has been found aberrantly up‐regulated in the glomerular in the patients with diabetic nephropathy (DN). We aimed to elucidate the function and regulatory mechanism of lncRNA lnc‐ISG20 on DN‐induced renal fibrosis. Expression patterns of lnc‐ISG20 in kidney tissues of DN patients were determined by RT‐qPCR. Mouse models of DN were constructed, while MCs were cultured under normal glucose (NG)/high glucose (HG) conditions. The expression patterns of fibrosis marker proteins collagen IV, fibronectin and TGF‐β1 were measured with Western blot assay. In addition, the relationship among lnc‐ISG20, miR‐486‐5p, NFAT5 and AKT were analysed using dual‐luciferase reporter assay and RNA immunoprecipitation. The effect of lnc‐ISG20 and miR‐486/NFAT5/p‐AKT axis on DN‐associated renal fibrosis was also verified by means of rescue experiments. The expression levels of lnc‐ISG20 were increased in DN patients, DN mouse kidney tissues and HG‐treated MCs. Lnc‐ISG20 silencing alleviated HG‐induced fibrosis in MCs and delayed renal fibrosis in DN mice. Mechanistically, miR‐486‐5p was found to be a downstream miRNA of lnc‐ISG20, while miR‐486‐5p inhibited the expression of NFAT5 by binding to its 3'UTR. NFAT5 overexpression aggravated HG‐induced fibrosis by stimulating AKT phosphorylation. However, NFAT5 silencing reversed the promotion of in vitro and in vivo fibrosis caused by lnc‐ISG20 overexpression. Our collective findings indicate that lnc‐ISG20 promotes the renal fibrosis process in DN by activating AKT through the miR‐486‐5p/NFAT5 axis. High‐expression levels of lnc‐ISG20 may be a useful indicator for DN.