Advancing Open Science

Meta-analysis of proportions requires a rigorous transformation model due to the inherent mathematical constraints of proportional data (boundedness and non-constant variance). This study compared four proportions (Untransformed, Freeman–Tukey, Logit, and Arcsine) to determine the most reliable and numerically stable estimator for pooled prevalence. A rigorous comparative evaluation was performed using 35 empirical studies on Computer Vision Syndrome (CVS)-related musculoskeletal pain prevalence. The analysis employed frequentist methods, Monte Carlo simulations (10,000 iterations) to test CI coverage, and Bayesian sensitivity analysis. Key findings were validated using the Generalized Linear Mixed Model (GLMM), representing the one-step methodological standard. Pooled prevalence estimates were highly consistent (0.467 to 0.483). Extreme heterogeneity (I² ≈ 98–99%) persisted across all models, with τ² values exceeding 1.0 specifically in Logit and GLMM frameworks. Mixed-effects meta-regression confirmed that this heterogeneity was independent of study size (p = 0.692 to 0.755), with the moderator explaining virtually none of the variance (${\mathrm{R}}^2$) of 0% to 0.2%. This confirms that the high variance is an inherent feature of the dataset rather than a statistical artifact. Simulations revealed a critical trade-off: while the Untransformed model provided minimal bias, its CI coverage failed significantly in small-sample boundary scenarios (N = 50, p = 0.01, coverage: 39.36%). Under these conditions, the PFT transformation was most robust (98.51% coverage), while the Logit model also maintained high coverage accuracy (91.07%) despite its variance inflation. We conclude that model selection should be context-dependent: the Untransformed model is recommended for well-powered datasets, whereas the PFT transformation is essential for small samples to ensure valid inferential precision.

This study was conducted to investigate tick species that may harbour severe fever with thrombocytopenia syndrome virus (SFTSV) and Babesia microti in the provinces of Henan, Anhui, and Zhejiang, as well as in Shanghai in the central and eastern parts of China. Between March and September 2023, 721 pools of ticks were collected belonging to three genera and five species: Haemaphysalis longicornis (n = 612; 84.9%), Haemaphysalis fusca (n = 94; 13.0%), Rhipicephalus microplus (n = 10; 1.4%), Amblyomma testudinarium (n = 3; 0.4%), and Haemaphysalis wellingtoni (n = 2; 0.3%). The SFTSV-positive pool rate was 20.0%, 13.0%, 5.8%, and 4.1% in Xinyang, Henan; Songjiang, Shanghai; Lu’an, Anhui; and Zhoushan, Zhejiang, respectively. SFTSV was detected in all five tick species collected. Among the SFTSV-positive pools, H. longicornis constituted the highest proportion (83.9%, 78/93), whereas pools containing R. microplus and H. wellingtoni each represented the lowest proportion (1.1%, 1/93). Babesia microti was assayed only in these SFTSV-positive tick pools, and co-infection was found in both H. longicornis and H. wellingtoni, though it was most frequent in H. longicornis.

Neurodegenerative diseases, such as Parkinson’s and Alzheimer’s, are becoming an increasingly serious challenge for modern medicine because of the significant increase in incidence and the narrow range of effective therapeutic strategies. In recent years, the kynurenine pathway, which is one of the main pathways of tryptophan metabolism, responsible for the synthesis of products that act oppositely in the CNS including neurotoxic (quinolinic acid) and neuroprotective products, has gained increasing recognition as a potential therapeutic target. Abnormalities in the production of these metabolites, causing a disruption of homeostasis in the CNS, often lead to the development of inflammation, which can cause oxidative stress or neuronal death. This paper aims to discuss strategies useful in modulation of the kynurenine pathway, based on increasing the production of neuroprotective metabolites and reducing the synthesis of neurotoxic compounds, as well as to outline the progress in preclinical and clinical studies and the challenges encountered in these studies, among others, in the search for new KP inhibitors. The pharmacological (IDO and KMO inhibitors) and non-pharmacological (physical activity, diet) strategies are discussed, as well as new approaches from combination and targeted therapies. Together with the results of preclinical studies, they demonstrate the high utility of this target in the treatment of neurodegeneration. Despite its promising activity, further key studies are needed to fully understand the mechanisms involved in metabolism, which may translate into increased efficacy of developed therapies in the future.

To address surging and uncertain electricity customer demands, this paper proposes a data-driven electricity customer service scheduling (ECSS) optimization model to improve customer service quality and alleviate agent scheduling pressure. The method begins by building a demand analysis model based on customer feature extraction using the maximal information coefficient (MIC). An agent workforce sizing model is then developed by integrating the AHP–fuzzy comprehensive evaluation and Z-score standardization, accounting for call-volume proportion, hourly call-handling capacity, and time-period length. Furthermore, a demand–skill matching method is introduced between customer calls and agent skills. A particle swarm optimization (PSO)-based intelligent scheduling algorithm is established, with queuing time, skill level, and handling time as key objectives and constraints. Case-study validation shows that the model improves operational efficiency by approximately 26.28% and reduces annual labor costs by about 6.13%, thereby enhancing customer satisfaction, service center efficiency, and scheduling system economy.

The accurate estimation of the fundamental period is critical for seismic design using the Equivalent Lateral Force method. This study evaluates widely used empirical period formulae from international seismic codes and previous research by comparing them with detailed finite element method (FEM) analyses. A total of 93 reinforced concrete building models were assessed. The results show that most empirical formulae, notably the American Society of Civil Engineers Standard (ASCE 7-10), the Eurocode, the National Building Code of Canada (NBCC), and the Saudi Building Code (SBC 301), systematically underestimate the fundamental period in low- and mid-rise buildings often by more than 40% under cracked conditions, while discrepancies reduce under uncracked assumptions. Equations such as those proposed by the Building Standard Law of Japan (BSLJ) and Australian Standard (AS 11407.2) show comparatively closer agreements with FEM predictions, whereas formulae developed by Goel and Chopra and by Alguhane et al. have distinct differences, especially at greater heights. Statistical parameters, including the arithmetic mean difference and the standard deviation, were employed to enhance the comparison and assess the accuracy and dispersion of the estimated fundamental periods. The results indicate that empirical formulae, although beneficial in first-design stages, are likely to yield conservative results and suggest the use of advanced numerical computation or revised models and coefficients for RC high-rise and irregular buildings.

Common variable immunodeficiency (CVID) is the most prevalent symptomatic primary immunodeficiency or inborn error of immunity (IEI) encountered in clinical practice. Characterized by a remarkably broad clinical spectrum, CVID presents with phenotypes spanning from “infection only” to significant non-infectious complications. The frequent overlap between these classifications underscores that their distinction is more accurately viewed as a continuous spectrum, rather than a binary categorization. CVID-associated liver disease is a significant source of morbidity, yet often poses diagnostic challenges due to its insidious and clinically silent nature, typically becoming apparent only upon the development of complications. Manifestations range from abnormal liver tests to irreversible organ damage, with reports including granulomas, autoimmune hepatitis, fibrosis, and porto-sinusoidal vascular disorder (PSVD). Regenerative nodular hyperplasia (RNH), commonly associated with PSVD, is a frequent histopathological finding. Management requires a multidisciplinary approach, including cause-directed immunosuppression and supportive treatment for non-cirrhotic portal hypertension. Despite significant advances in comprehending CVID-associated liver involvement, substantial gaps persist concerning its pathogenesis, its optimal management, and the correlation between histological findings and clinical outcomes. A heightened awareness of CVID-associated liver disease is paramount for multidisciplinary teams across IEI centers. Furthermore, given its prevalence, its insidious clinical phenotype until advanced complications, and the significant diagnostic delay and underdiagnosis, such awareness is critical across a broader range of medical specialties. In this paper, we aim to consolidate current knowledge regarding CVID-related liver disease, examining its clinical presentation, recent genetic and pathogenetic advancements along with current diagnostic methodologies, and therapeutic strategies.

Drawing on a systematic review of both international and Chinese-language scholarship on counter-urbanization in China, this article proposes a comprehensive typology of counter-urbanization migrations—consisting of eight types of new migrants—based on the diverse motivations driving such migration. We build a bilingual corpus of 273 research papers published between the 1970s and 2025. Integrating bibliometric mapping and qualitative synthesis, we conduct a systematic review to trace the temporal evolution and thematic diversification of counter-urbanization research. The review reveals persistent conceptual ambiguity surrounding counter-urbanization in the Chinese context, which this study addresses by conceptually distinguishing counter-urbanization from suburban expansion, population decentralization, and return migration. Empirically, counter-urbanization in China is shown to involve heterogeneous demographic groups and multiple drivers. Our synthesis identifies a fundamental analytical divide between consumption-oriented and production-oriented engagements with rural space. Counter-urbanization in China therefore cannot be understood as a singular demographic reversal. Finally, contrary to the common view, it reveals that state intervention in China functions primarily as an enabling infrastructure rather than a direct driver of migration. Overall, this review advances a more nuanced theoretical framework for understanding urban-to-rural mobility in China and contributes to broader comparative debates on counter-urbanization beyond Western contexts.

The Tibetan Plateau is highly sensitive to global climate change and characterized by pronounced ecological fragility, making vegetation net primary productivity (NPP) a key indicator for assessing ecosystem functioning and regional ecological security. This study aims to characterize the spatiotemporal dynamics of NPP and to disentangle the multiple natural and land-use drivers shaping its variability across the Tibetan Plateau. MODIS-derived NPP data for the period 2001–2022 are integrated with multi-source datasets on climate, topography, normalized difference vegetation index (NDVI), and land use (CLCD), and analyzed using trend and correlation analyses, land-use transfer matrices, an optimal-parameter geographical detector, and partial least squares structural equation modeling (PLS-SEM). The results indicate that NPP exhibits a significant but fluctuating upward trend (0.52 gC·m⁻²·a⁻¹, p < 0.01), with higher values in the southeast and lower values in the northwest, the Yunnan Plateau evergreen broadleaf and pine forest region (VA5) and the southern Himalayan montane forest region (VA6) function as high-value centers, and regions such as the Kunlun high-cold desert region (HID1) represent low-value centers. The mutual conversion between forestland and grassland and bare land constitutes a key process driving regional NPP changes, with the net expansion of forestland making a substantial contribution to NPP increases (net gain of 2606.88 TgC). Geographic detector analysis indicates that NDVI (q = 0.741) and land use type (q = 0.741) are the primary factors governing the spatial differentiation of NPP, followed by precipitation, slope, and temperature. Moreover, interactions between any two factors enhance their explanatory power, with the interaction between aspect and land use type exhibiting the strongest effect (q approaching 1). PLS-SEM path analysis further quantifies the driving pathways, revealing that mean annual precipitation and land use type are the most direct drivers of NPP, while climatic and topographic factors influence NPP indirectly through their effects on vegetation cover and land use type. This study advances the understanding of the multifactorial driving mechanisms of ecosystem productivity on the Tibetan Plateau and provides a scientific basis for zoned and differentiated ecological restoration and climate adaptation strategies.