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Oases are receiving particular attention for their capacity to provide different ecosystem services, and as examples of adaptation and resilience in the context of climate change. A 2025 study focusing on the global distribution of oases has been published by Hernández-Agüero et al. (DOI 10.7717/peerj.18884) reporting quantitative and spatial data about the global distribution of oases. An in-depth review of this global oases mapping found significantly inconsistent data with the risk of misinforming the scientific community and other relevant stakeholders about the global distribution of oases. The main critical issues are related to: (i) the oasis definition, (ii) not distinguishing between traditional and modern oases, (iii) methodological inconsistencies in the performed spatial analysis, and inadequate spatial resolution. While most common definitions of oases agree regarding the key role of (traditional) agricultural activities and practices for the oases' origin, shaping, and preservation, the Hernández-Agüero et al. global oases mapping includes among the oases large portions of areas only characterized by natural vegetation of different types in arid areas. In addition, the global oases mapping includes intensive and, in the long term, unsustainable cultivations, and even urban areas. Traditional oases should be considered separately from intensive cultivation systems in arid areas, as only traditional oases are strictly related to high levels of agrobiodiversity, cultural values, traditional ecological knowledge, cultural landscapes, and sustainability. Oases, especially traditional ones, are characterized by different and complex characteristics with local high variability in terms of cultivated varieties, vertical and horizontal structure, and complexity of the landscape mosaic structure. An inaccurate mapping, together with the absence of a differentiation between modern and traditional oases, can lead to a misallocation of conservation resources or to misguided policy strategies. More research and training of automatic classification at a local/national level are needed due to the local/regional pattern variability, while the development of a shared oasis definition is essential for studies related to their mapping and knowledge, as well as for an effective strategy for the protection of these agroecosystems with important ecological and cultural values.

In this study, we propose a new biometric methodology for annelids, based on the number of chaetiger segments as an indicator of growth (independent variable), relating to other structures, such as the number of paragnaths and parapodia, using the commercial species Hediste diversicolor (Müller, 1776) as a model. This species belongs to the family Nereididae, found in estuarine environments along the European Atlantic coast (DOI 10.11646/zootaxa.5696.1.2). This species has several appendages with sensory functions along the body that help the animal navigate in its environment. It also has specialised feeding structures in the peristomium that are essential for taxonomic identification, called paragnaths. The parapodium has distinct chaetal arrangements that distinguish it from other species in the same genus. Due to the importance of economic activities such as fishing and aquaculture, this ragworm is a typical protagonist for studies in multiple areas, with a well-documented life cycle. However, knowledge is lacking on the growth and evolution of individual structures and appendages of the body in this species during its life cycle. Our findings revealed a significant positive correlation between the number of chaetiger segments and most of the morphological structures analysed, evidencing a proportional growth of most of these features, related directly to the chaetigers segments. Simple chaetae, a specific type of chaeta only present in the genus Hediste, were only found in individuals with more than 25 chaetiger segments, possibly indicating a functional change as the worm matures. Simple chaetae tend to be found earlier along the body axis, closer to the median chaetiger as the organism matures. The results illustrate how H. diversicolor develops over time, highlighting the developmental processes and representing the first biometric study of nereidid polychaetes, based on chaetiger count as a proxy for biometric growth, to define new possible life cycle stages, for supporting aquaculture purposes and other research fields.

Background: In the 28S rRNA molecule of many invertebrates, a hidden break splits this large subunit into two noncovalently associated fragments (28Sa and 28Sb), masking 28S in electrophoretic profiles and biasing the standard measurements of RNA quality in extracted tissue samples. Pancrustacean diversity in RNA hidden breaks remains incompletely surveyed, particularly for Oligostraca.

Methods: We sampled 12 species spanning Branchiopoda, Malacostraca, and Oligostraca around Valencia (Spain). RNA was stabilized with DNA/RNA Shield, extracted with Quick-RNA MagBead, and profiled on an Agilent 5200 Fragment Analyzer. Peaks were assigned to 18S and 28S fragments using BLAST-inferred gene lengths from reference genomes and annotated rDNA. We analyzed 28S secondary-structure domains (D-regions) using RNAfold and focusing on D3 and D7a.

Results: Oligostracans and most branchiopods analyzed showed the canonical single-peak profile consistent with 18S, 28Sa, and 28Sb of similar size. Malacostracans exhibited greater profile diversity, including multiple distinct peaks attributable to expansions that alter the relative sizes of 28Sa and b, including expansions near D7a. Comparative analyses indicate conserved D3/D7a architecture across Oligostraca/Branchiopoda and higher variability with frequent expansions in Malacostraca.

Conclusions: Our data extend RNA profile diversity to Oligostraca, refine fragment-size estimates with higher-resolution capillary electrophoresis, and link malacostracan profile heterogeneity to D7a and other expansions. We recommend rRNA-aware quality control for arthropod samples and targeted sequencing of poorly sampled lineages (e.g., Mystacocarida, Cephalocarida, Remipedia) to resolve mechanisms and the phylogenetic distribution of the hidden break.

Objective: This study aimed to evaluate the impact of GLP-1 receptor agonists (GLP-1 RAs) on metabolic inflammatory markers in patients with type 2 diabetes mellitus (T2DM), providing evidence-based insights for their potential application in anti-inflammatory therapy.

Methods: Research questions were developed using the PICOS framework, and the study strictly adhered to PRISMA guidelines. Comprehensive literature searches were conducted across PubMed, EBSCO, Embase, Web of Science, and the Cochrane Library. Data synthesis and subgroup analyses (focusing on GLP-1 RA subtypes, treatment duration, and administration frequency) were performed using RevMan 5.4 software.

Results: Out of 1,347 articles retrieved, 25 studies were ultimately included, comprising a total sample of 1,878 participants (879 in the experimental groups and 999 in the control groups). Quality assessment indicated that most studies exhibited a low risk of bias, with only one study rated as high risk and three studies showing some concerns. Meta-analysis results demonstrated that 18 studies reported a significant reduction in CRP levels in T2DM patients treated with GLP-1 RAs (SMD = -0.39, 95% CI [-0.72 to -0.06], P = 0.02, I² = 88%). Although the results from 13 studies indicated a decreasing trend in IL-6 levels (SMD = -0.52), this change was not statistically significant (95% CI [-1.34 to 0.29], P = 0.21, I² = 96%). Additionally, 14 studies showed that GLP-1 RAs significantly reduced TNF-α levels (SMD = -0.51, 95% CI [-0.81 to -0.20], P = 0.001, I² = 81%). Subgroup analyses revealed that both the type of GLP-1 RA and a longer treatment duration (≥36 weeks) were associated with more pronounced improvements in inflammatory markers.

Conclusion: GLP-1 RAs exhibit a certain degree of anti-inflammatory effect in patients with T2DM, effectively reducing CRP and TNF-α levels. The anti-inflammatory efficacy appears to be influenced by both the type of drug used and the duration of treatment, with more pronounced effects observed for specific drug classes and with longer treatment periods. These findings provide further evidence supporting the use of GLP-1 RAs in the anti-inflammatory management of T2DM.

Background: Repetitive transcranial magnetic stimulation (rTMS) is an effective tool for motor function recovery in patients with ischemic stroke (IS). Dysfunction of the glymphatic system is implicated in the pathological process of IS. However, it is still unclear whether the recovery of upper limb motor function in IS is affected by rTMS-driven modulation of glymphatic system function. This study aimed to investigate the potential utility of diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) in assessing the impact of rTMS on IS recovery.

Methods: This prospective study recruited IS participants with upper limb motor disorders. A total of 35 participants were randomly assigned to receive either low-frequency rTMS (LF-rTMS) or high-frequency rTMS (HF-rTMS) for two weeks. HF-rTMS was conducted on the infarcted hemisphere M1 and the LF-rTMS was conducted on the non-infarcted hemisphere M1. The information collected from each patient included clinical characteristics, upper limb motor function score, and bilateral hemisphere DTI-ALPS index. Paired t-tests were used to evaluate longitudinal changes of the DTI-ALPS index in LF-rTMS and HF-rTMS groups. The DTI-ALPS index change rates were calculated, and their differences were compared between groups. Spearman's correlation analyses were performed to assess the relationships between DTI-ALPS index changes and changes in upper limb motor function score.

Results: At baseline, no significant differences were observed in the DTI-ALPS index between the HF-rTMS and LF-rTMS groups. After two weeks of rTMS treatment, the DTI-ALPS index of the non-stimulated hemisphere in the HF-rTMS group significantly decreased (t = 2.42, P = 0.028), and the change rate of the DTI-ALPS index was negatively correlated with the recovery of upper limb motor function (r =  - 0.42, P = 0.011). In the LF-rTMS group, longitudinal analysis showed improvement in upper limb motor function scores, but there was no significant change in the DTI-ALPS index.

Conclusion: Both HF-rTMS and LF-rTMS are beneficial for the rehabilitation of upper limb motor function in patients with IS, but the different changes in DTI-ALPS index may indicate differential effects of HF-rTMS and LF-rTMS on the glymphatic system. However, more research is needed to confirm the underlying mechanisms of this interaction.

Background: The incidence of cesarean section (CS) is increasing each year and may be associated with an increased risk of postpartum depression (PPD). Although studies have examined the association between cesarean delivery and postpartum depression, the associated risk factors have not been fully investigated. This study aims to identify key risk factors for planned and emergency cesarean delivery through meta-analysis to help develop clinical prevention strategies.

Methods: We searched multiple databases, including CNKI, Wan Fang, VIP, PubMed, Embase, Scopus, Google Scholar, CINAHL, Cochrane Library, and Web of Science, for studies published from the inception of these databases through January 8, 2025. The quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS), and standardized mean difference (SMD) and ratio of ratios (OR) were used to assess the strength of association between different risk factors and postpartum depression, when I² > 50%, a random effects model was used for data analysis; when I² < 50%, a fixed effects model was chosen for analysis.

Result: Nine articles (n = 3,338) were included in this study, meta-analysis results suggest that younger women (SMD = -0.16, 95% CI [-0.29 to -0.04], I² = 0%), higher antenatal depression scores (SMD = 0.28, 95% CI [0.13-0.44], I² = 15.1%), higher antenatal anxiety scores (SMD = 0.56, 95% CI [0.40-0.72], I² = 35.6%) are more likely to experience postpartum depression, nulliparous (OR = 1.9, 95% CI [1.39-2.60], I² = 0%) and elementary education level (OR = 1.34, 95% CI [1.05-1.72], I² = 44.3%) were risk factor for postpartum depression after caesarean section.

Conclusion: In summary, age, first-time pregnancy status, education level, and antenatal depression and anxiety scores are important risk factors for postpartum depression following cesarean delivery. Identifying and addressing these factors could provide valuable insights for the prevention and management of postpartum depression.

Objective: This study aims to evaluate whether Positron Emission Tomography-Computed Tomography (PET-CT) imaging features of primary tumors and lymph nodes, combined with clinical and pathological data, can accurately predict mediastinal lymph node metastasis (MLNM) in resectable non-small cell lung cancer (NSCLC) using machine learning models.

Methods: A retrospective study was conducted on 390 NSCLC patients who underwent tumor resection and lymph node dissection between January 2017 and December 2023. All patients received 18F-fluorodeoxyglucose (18F-FDG) PET-CT scans within two weeks before surgery. Data from 390 primary tumors and 1,026 lymph node stations were analyzed. Clinical and PET-CT imaging features were extracted, and feature selection was performed using a random forest algorithm. Eight machine learning models were evaluated, including Logistic Regression, classification and regression tree (CART), support vector machine (SVM), gradient boosting decision tree (GBDT), Random Forest, multi-layer perceptron (MLP), extreme gradient boosting tree (XGBoost) and k-nearest neighbor algorithm (KNN).

Three models were developed: Tumor-Pathology-Clinical (TPC), Lymph-Pathology-Clinical (LPC), and Tumor-Lymph-Pathology-Clinical (TLPC). Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and confusion matrices.

Results: The TLPC model, based on the XGBoost algorithm, showed the best performance, with an Area Under the Curve (AUC) of 0.90 (95% CI [0.883-0.957]), specificity of 0.84, and sensitivity of 0.96 (P = 0.0069; significant at P < 0.05). In comparison, the TPC model achieved an AUC of 0.67 (95% CI [0.647-0.703]), specificity of 0.46, and sensitivity of 0.56 (P = 0.7037; not significant). The LPC model showed intermediate performance, with an AUC of 0.78 (95% CI [0.713-0.751]), specificity of 0.73, and sensitivity of 0.84 (P = 0.0269; significant at P < 0.05). All P-values were derived from DeLong's test comparing AUCs between models, with statistical significance defined as P < 0.05. Of the 1,026 lymph node stations analyzed, 204 showed metastasis, while 822 did not. XGBoost consistently outperformed other models in predicting MLNM.

Conclusion: Combining PET-CT imaging features of primary tumors and lymph nodes with clinical and pathological data shows promise for accurately predicting MLNM in NSCLC. The TLPC model offers a non-invasive method for identifying lymph node metastasis, supporting personalized treatment strategies. However, since PET-CT was performed selectively rather than routinely acquired, external validation across diverse clinical settings is warranted to confirm model generalizability.

Objective: This study investigated the relationships between physical literacy (PL), physical activity levels (PALs), and physical fitness among Chinese university students, with a particular focus on the mediating role of PALs and the consistency of findings across various analytical methods.

Methods: Participants included 115 first-year students (79 males, 36 females) from Nanjing, China. PL was assessed using the Perceived Physical Literacy Instrument (PPLI-SC), PALs were measured using the Physical Activity Questionnaire for Adolescents (PAQ-A), and physical fitness was assessed through four indicators: body mass index (BMI), 50-m sprint, sit-and-reach, and 800/1,000-m run. Descriptive statistics, correlation, and regression analyses were conducted in SPSS 26.0. Mediation was tested using the PROCESS macro (Model 4, 5,000 bootstrap samples), and structural equation modeling (SEM) was applied using AMOS 26.0 for validation.

Results: Males outperformed females in the 50-m sprint, while females exhibited superior flexibility and cardiorespiratory endurance; BMI was significantly higher in males (p < 0.01). PL was positively correlated with PALs (r = 0.584, p < 0.01), and both were significantly associated with all fitness indicators except BMI. Mediation analyses indicated that PALs fully mediated the associations between PL and sprint performance, flexibility, and cardiorespiratory endurance. For BMI, the PROCESS macro suggested a weak indirect effect, whereas SEM results were nonsignificant, highlighting the sensitivity of the results to the analytical method used.

Conclusion: PL is strongly linked to physical fitness in Chinese university students, with PALs acting as a critical mediator. The inconsistent BMI findings underscore its complex determinants, which extend beyond physical activity. Promoting PL and PALs through university physical education programs may improve fitness outcomes. Future research should validate these findings using larger samples, longitudinal designs, and broader body composition indicators (e.g., body fat percentage, muscle mass).

Rice, a global food staple, primary food source for half of the world's population, is highly vulnerable to abiotic stresses such as drought, salinity, heat, and heavy metal toxicity. Silicon nanoparticles (SiNPs) have emerged as promising nano-interventions to enhance stress resilience by improving antioxidant defenses, photosynthesis, and ion homeostasis. Recent studies demonstrate that SiNPs modulate the expression of key transporter genes (OsHMA3, OsLsi1, OsABCC1) and activate transcription factors (DREB, NAC, WRKY) that regulate stress tolerance pathways. They also promote the accumulation of compatible solutes and phenolic compounds, reducing oxidative damage and metal toxicity. Omics-based research reveals that SiNPs influence redox signaling, hormonal balance, and epigenetic regulation, providing a clear understanding of their protective mechanisms at the physiological level. These effects are linked to enhanced structural integrity, reactive oxygen species (ROS) scavenging, and better nutrient uptake. However, rice-specific datasets remain limited, and field-scale validations are still scarce. SiNPs show strong potential as smart nanocarriers for nutrient delivery and gene modulation, integrating effectively with precision and sustainable agriculture practices. However, uncertainties regarding dosage, soil persistence, and food safety require careful evaluation before large-scale use. This review synthesizes physiological, molecular, and omics-based insights into SiNP-mediated abiotic stress tolerance in rice, emphasizing advances in understanding underlying resilience mechanisms. It also highlights environmental and regulatory challenges, identifies critical research gaps, and proposes future directions for safe and scalable applications of SiNPs in rice systems.