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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.

The feasibility of delivering mitochondria intranasally so as to bypass the blood–brain barrier in treating Parkinson's disease (PD), was evaluated in unilaterally 6-OHDA-lesioned rats. Intranasal infusion of allogeneic mitochondria conjugated with Pep-1 (P-Mito) or unconjugated (Mito) was performed once a week on the ipsilateral sides of lesioned brains for three months. A significant improvement of rotational and locomotor behaviors in PD rats was observed in both mitochondrial groups, compared to sham or Pep-1-only groups. Dopaminergic (DA) neuron survival and recovery > 60% occurred in lesions of the substantia nigra (SN) and striatum in Mito and P-Mito rats. The treatment effect was stronger in the P-Mito group than the Mito group, but the difference was insignificant. This recovery was associated with restoration of mitochondrial function and attenuation of oxidative damage in lesioned SN. Notably, P-Mito suppressed plasma levels of inflammatory cytokines. Mitochondria penetrated the accessory olfactory bulb and doublecortin-positive neurons of the rostral migratory stream (RMS) on the ipsilateral sides of lesions and were expressed in striatal, but not SN DA neurons, of both cerebral hemispheres, evidently via commissural fibers. This study shows promise for intranasal delivery of mitochondria, confirming mitochondrial internalization and migration via RMS neurons in the olfactory bulb for PD therapy.

Tea seed oil is a high quality edible oil, yet lacking sufficient scientific evidences to support the nutritional and medical purposes. We identified major and minor components in Camellia tenuifolia seed oil and investigated the antioxidative activity and its underlying mechanisms in Caenorhabditis elegans. The results showed that the major constitutes in C. tenuifolia seed oil were unsaturated fatty acids (~78.4%). Moreover, two minor compounds, β-amyrin and β-sitosterol, were identified and their antioxidative activity was examined. We found that oleic acid was the major constitute in C. tenuifolia seed oil and plays a key role in the antioxidative activity of C. tenuifolia seed oil in C. elegans. This study found evidences that the transcription factor DAF-16/FOXO was involved in both oleic acid- and C. tenuifolia seed oil-mediated oxidative stress resistance in C. elegans. This study suggests the potential of C. tenuifolia seed oil as nutrient or functional foods.

Solar-cell panels use sunlight as a source of energy to generate electricity. However, the performances of solar panels decline when they degrade, owing to defects. Some common defects in solar-cell panels include hot spots, cracking, and dust. Hence, it is important to efficiently detect defects in solar-cell panels and repair them. In this study, we propose a lightweight inception residual convolutional network (LIRNet) to detect defects in solar-cell panels. LIRNet is a neural network model that utilizes deep learning techniques. To achieve high model performance on solar panels, including high fault detection accuracy and processing speed, LIRNet draws on hierarchical learning, which is a two-phase solar-panel-defect classification method. The first phase is the data-preprocessing stage. We use the K-means clustering algorithm to refine the dataset. The second phase is the training of the model. We designed a powerful and lightweight neural network model to enhance accuracy and speed up the training time. In the experiment, LIRNet improved the accuracy by approximately 8% and performed ten times faster than EfficientNet.

In the context of increasing competition, the phenomenon of individuals experiencing guilt or anxiety at rest has become more pronounced, particularly among Chinese university students. While previous research has primarily explained this phenomenon from the perspective of collectivist cultures, this study posits that vertical individualism may offer a more compelling explanation. A sample of 550 Chinese university students was surveyed to collect data on vertical/horizontal individualism-collectivism, status anxiety, and rest intolerance. A partial correlation network analysis, controlling for demographic covariates, was conducted to explore the psychological structure of these constructs. The results identified Vertical Individualism (VI) and Status Anxiety (SA) as the core bridge nodes connecting the community of cultural values to the dimensions of rest intolerance. Subsequent mediation analyses confirmed that SA partially mediated the relationship between VI and overall rest intolerance. This indirect effect was particularly pronounced for the affective and social-comparative components of the phenomenon. These findings challenge traditional collectivist frameworks and reveal a nuanced psychological mechanism: competitive cultural values exacerbate rest intolerance through the pathway of status anxiety. This provides novel theoretical insights for psychological interventions and cultural adaptation education in higher education settings.

In recent years, skin spectral information has been gradually applied in various fields, such as the cosmetics industry and clinical medicine. However, the high price and the huge size of the skin spectrum measurement device make the related applications of the skin spectrum unable to be widely used in practical applications. We used convolutional neural network (CNN) to achieve a satisfying accuracy of the Fitzpatrick skin-type classification by using a simple self-developed device in 2018. Leveraging on the hardware, firmware, and software app-developing experience, a low-cost miniature skin spectrum measurement system (LMSSMS) using deep neural network (DNN) technology was further studied, and the feasibility of the system is verified in this paper. The developed LMSSMS is divided into three parts: (1) miniature skin spectrum measurement device (MSSMD), (2) DNN model, and (3) mobile app. The MSSMD was developed with innovative low-cost MSSC, 3D printing, and a simple LED light source. The DNN model is designed to enhance measurement accuracy. Finally, the mobile app is used to control and show the measurement results. The developed app also includes a variety of skin-spectrum-related applications, such as erythema index and melanin index (EI/MI) measurement, Fitzpatrick skin-type classification, Pantone SkinTone classification, sun-exposure estimation, and body-fat measurement. In order to verify the feasibility of LMSSMS, we used the standard instrumentation device as a reference. The results show that the accuracy of the LMSSMS can reach 94.7%, which also confirms that this development idea has much potential for further development.

Long-read DNA sequencing has propelled medicinal plant genomics forward, with over 400 genomes from 203 plants sequenced by February 2025. However, many genomes still have assembly and annotation flaws, with only 11 gapless telomere-to-telomere assemblies. The core challenge remains identifying genes linked to secondary metabolite biosynthesis, regulation and evolution. High-quality complete genomes are essential for characterizing biosynthetic gene clusters and for enabling robust functional genomics and synthetic biology applications. We propose to focus on achieving more complete genome assemblies in diverse varieties on the basis of refining the currently available ones, leverage lessons from crop genomics research, and apply the cutting-edge genomics technologies in research of medicinal plant genomics. Genomics resources are crucial for discovering and producing phytochemicals with pharmacological activities. Here, the authors summarize current advancements and limitations in medicinal plant genomics and provide outlooks to move the field forward.

Sanitation in neighbourhood and household domains can provide primary protection against diarrhea morbidity, yet their distinct health benefits have not been succinctly distinguished and reviewed. We present here the first systematic review and meta-analysis of the distinct effect of neighbourhood and household sanitation conditions on diarrhea morbidity. We identified studies reporting the effect of neighbourhood-level exposure to wastewater or household sanitation facilities on diarrhea, by performing comprehensive search on five databases, namely the Cochrane library, PubMed, Embase, Scopus and Web of Science, from the earliest date available to February 2015. Twenty-one non-randomized studies and one randomized controlled trial met the pre-determined inclusion criteria, consisting of six datasets on neighbourhood sanitation conditions (total 8271 subjects) and 20 datasets on household sanitation (total 20021 subjects). We calculated the pooled effect estimates of neighbourhood and household sanitation conditions on diarrhea morbidity using the inverse variance random-effects model. The pooled effect estimates showed that both neighbourhood sanitation conditions (odds ratio = 0.56, 95%CI: 0.40-0.79) and household sanitation (odds ratio = 0.64, 95%CI: 0.55-0.75) are associated with reduced diarrheal illness, and that the magnitudes of the associations are comparable. Evidence of risk of bias and heterogeneity were found in the included studies. Our findings confirm that both neighbourhood sanitation conditions and household sanitation are associated with considerable reduction in diarrhea morbidity, in spite of a number of methodological shortcomings in the included studies. Furthermore, we find evidence that neighbourhood sanitation conditions is associated with similar magnitude of reduction in diarrhea morbidity as household sanitation. The findings suggest that, in addition to household sanitation provision, dual emphasis on neighbourhood sanitation through public sanitation infrastructure provision and community-wide sanitation adoption is advisable for effective reduction of diarrheal disease burden.

Purpose: Detrusor sphincter dyssynergia (DSD), a common lower urinary tract condition in patients with suprasacral spinal cord injury (SCI), can lead to urological complications and reduced quality of life. Urethral sphincter botulinum toxin A (BoNT-A) injection has been used to promote spontaneous voiding, albeit with limited success. This study aimed to identify predictive factors for treatment success. Methods: This retrospective analysis included 207 patients (157 males and 50 females) with chronic SCI and varying DSD grades treated with urethral sphincter BoNT-A injection. Each received 100 U of onabotulinumtoxinA via transurethral sphincter injection. The primary outcome was voiding efficiency (VE) and symptom improvement, assessed via global response evaluation 3 months post-treatment. Baseline videourodynamic parameters were used to predict success. Results: Successful outcomes were observed in 33.8% of patients. These patients were older and had higher voiding pressure, maximum flow rate (Qmax), voided volume, bladder contractility index, and VE, as well as lower post-void residual (PVR) volume and bladder outlet obstruction index. Patients with SCI and DSD grade 1 had the highest success rate (65.7%) compared to those with DSD grade 2 (14.3%) or 3 (7.1%). Patients with DSD grade 3 had the highest failure rate (55.8%). Multivariate analysis showed that higher Qmax and lower PVR significantly predicted success, consistent with lower DSD grades. Conclusion: Grade 1 DSD, higher Qmax, and lower PVR were associated with higher success after urethral BoNT-A injection, whereas grade 3 DSD predicted failure. Thus, careful patient selection is essential for effective DSD treatment with urethral BoNT-A injection.

The pathogenesis of Parkinson’s disease (PD) remains to be elucidated. Metabolomic analysis has the potential to identify biochemical pathways and metabolic profiles that are involved in PD pathogenesis. Here, we performed a targeted metabolomics to quantify the plasma levels of 184 metabolites in a discovery cohort including 82 PD patients and 82 normal controls (NCs) and found two up-regulated (dopamine, putrescine/ornithine ratio) and four down-regulated (octadecadienylcarnitine C18:2, asymmetric dimethylarginine, tryptophan, and kynurenine (KYN)) metabolites in the plasma of PD patients. We then measured the plasma levels of a panel of metabolic products of KYN pathway in an independent validation cohort including 118 PD patients, 22 Huntington’s disease (HD) patients, and 37 NCs. Lower kynurenic acid (KA)/KYN ratio, higher quinolinic acid (QA) level, and QA/KA ratio were observed in PD patients compared to HD patients and NCs. PD patients at advanced stage (Hoehn-Yahr stage > 2) showed lower KA and KA/KYN ratio, as well as higher QA and QA/KA ratio compared to PD patients at early stage (Hoehn-Yahr stage ≤ 2) and NCs. Levels of KA and QA, as well as the ratios of KA/KYN and QA/KA between PD patients with and without psychiatric symptoms, dementia, or levodopa-induced dyskinesia in the advanced PD were similar. This metabolomic analyses demonstrate a number of plasma biomarker candidates for PD, suggesting a shift toward neurotoxic QA synthesis and away from neuroprotective KA production in KYN pathway.