Common Limitations Research Articles

Enhancement of systemic and lung-localized CD4<sup>+</sup> T-cell immune responses by truncation of NS1 protein of a seasonal live influenza vaccine strain

Introduction. There is a large variety of licensed influenza vaccines worldwide, but their common limitation is rather narrow specificity and inability to protect against antigenic-drift variants of influenza virus. Therefore, optimization of immunogenic and cross-protective properties of licensed influenza vaccines is an urgent priority of public health agenda. One such approach is to modulate the immunogenic properties of live attenuated influenza vaccine (LAIV) by truncating the open reading frame of influenza virus non-structural protein 1 (NS1). The main objective of this study is to evaluate the immunogenic properties of the H1N1 seasonal LAIV strain by truncation of the NS1 protein to 126 amino acides. Materials and methods. Using reverse genetics technique, two H1N1 LAIV strains with full-length and truncated NS1 protein with three consecutive stop codons added after the 126th amino acid residue were obtained.C57BL/6J mice were immunized intranasally with the vaccine candidates, twice at a three-week interval. Seven days after the second immunization, cells were isolated from spleen and lung tissues and stimulated with whole wild-type H1N1 influenza virus. Levels of systemic and tissue-resident cytokine-producing CD4+ and CD8+ memory T cells were assessed by intracellular cytokine staining assay with flow cytometry. Replication of engineered vaccine strains in in vitro and in vivo systems was also evaluated. Results. Truncation of NS1 protein of the LAIV strain significantly increased the levels of virus-specific CD4+ effector memory T cells in spleens and the levels of CD4+ tissue-resident memory T cells in lungs of mice after two-dose immunization, indicating a higher potential for protection against influenza infection of the LAIV NS126 vaccine strain compared to the classical variant of LAIV. Importantly, the LAIV NS126 strain also had a more pronounced attenuated phenotype in mice than its classical counterpart.

Abstract 4141461: Zonal Coating Application System for Left Atrial Appendage Occlusion Devices: A Novel Approach to Reduce Peri-Device Leakage and Device Related Thrombus.

Introduction: Left atrial appendage occlusion (LAAO) is an effective method of stroke prevention in patients with atrial fibrillation (AF). However, peri-device leakage (PDL) and device related thrombus (DRT) are common limitations of LAAO. Notably, PDL is associated with an increased risk of thromboembolic events. In order to minimize DRT, the Watchman FLX Pro is coated with PVDF-HFP. We aim to minimize both DRT and PDL with our novel zonal coating application system (ZCAS). ZCAS integrates a two-part thromboresistant and endothelialization promoting coating onto LAAO devices (Figure 1). In order to determine the optimal coating for the endothelialization promoting zone of ZCAS, we validated coating candidates in an in vitro model of LAAO device endothelialization (Figure 2). Hypothesis: We hypothesized that polyethylene terephthalate (PET) mesh coated with collagen type IV, fibronectin + VEGF, or poly-L-lysine would improve endothelial cell viability and proliferation. Methods: Human umbilical vein endothelial cells (HUVEC) were cultured in DMEM/F12 supplemented with ATCC’s Endothelial Cell Growth Kit and antibiotics. For the cell viability and proliferation assay, HUVEC cells were cultured in DMEM/F12 supplemented with 2% FBS, 10 mM L-glutamine, and antibiotics. A 96 well plate with PET inserts was coated with three coating candidates. Each coating was applied in three concentrations ([1x], [10x], and [100x]) with triplicates for each concentration. The coatings included collagen type IV ([1x]: 1 ug/cm2), fibronectin ([1x]: 1 ug/cm2) + VEGF ([1x]: 10 ng/cm2), and poly-L-lysine ([1x]: 4 ug/cm2). An MTS assay was performed at 48 hours after plating to assess cell viability and proliferation. Results: MTS absorbance relative to the uncoated control (MTS absorbance coated well/MTS absorbance uncoated well) for collagen type IV at [1x], [10x], and [100x] was 0.81, 1.29, and 0.84 respectively (Table 1). Fibronectin + VEGF at [1x], [10x], and [100x] was 1.31, 1.62, and 0.96. Finally, poly-L-lysine at [1x], [10x], and [100x] was 0.69, 0.90, and 0.91 respectively. Conclusion(s): Among the coating candidates, fibronectin (1 ug/cm2) + VEGF (100 ng/cm2) had the greatest increase in cell viability and proliferation compared to the uncoated PET control. The significance of this finding lies in the potential for ZCAS to improve the endothelial seal between the LAAO device and LAA orifice, which may significantly reduce PDL post-implantation.

Early Warning Systems for Acute Respiratory Infections: Scoping Review of Global Evidence.

Early warning systems (EWSs) are tools that integrate clinical observations to identify patterns indicating increased risks of clinical deterioration, thus facilitating timely and appropriate interventions. EWSs can mitigate the impact of global infectious diseases by enhancing information exchange, monitoring, and early detection. We aimed to evaluate the effectiveness of EWSs in acute respiratory infections (ARIs) through a scoping review of EWSs developed, described, and implemented for detecting novel, exotic, and re-emerging ARIs. We searched Ovid MEDLINE ALL, Embase, Cochrane Library (Wiley), and CINAHL (Ebsco). The search was conducted on October 03, 2023. Studies that implemented EWSs for the detection of acute respiratory illnesses were included. Covidence was used for citation management, and a modified Critical Appraisal Skills Programme (CASP) checklist was used for quality assessment. From 5838 initial articles, 29 met the inclusion criteria for this review. Twelve studies evaluated the use of EWSs within community settings, ranging from rural community reporting networks to urban online participatory surveillance platforms. Five studies focused on EWSs that used data from hospitalization and emergency department visits. These systems leveraged clinical and admission data to effectively detect and manage local outbreaks of respiratory infections. Two studies focused on the effectiveness of existing surveillance systems, assessing their adaptability and responsiveness to emerging threats and how they could be improved based on past performance. Four studies highlighted the integration of machine learning models to improve the predictive accuracy of EWSs. Three studies explored the applications of national EWSs in different health care settings and emphasized their potential in predicting clinical deterioration and facilitating early intervention. Lastly, 3 studies addressed the use of surveillance systems in aged-care facilities, highlighting the unique challenges and needs of monitoring and responding to health threats in environments housing vulnerable populations. The CASP tool revealed that most studies were relevant, reliable, and of high value (score 6: 11/29, 38%; score 5: 9/29, 31%). The common limitations included result generalizability, selection bias, and small sample size for model validation. This scoping review confirms the critical role of EWSs in enhancing public health responses to respiratory infections. Although the effectiveness of these systems is evident, challenges related to generalizability and varying methodologies suggest a need for continued innovation and standardization in EWS development.

Silyl Ethers as Latent Pronucleophiles in Enantioselective Lewis Base Catalyzed Synthesis of Allylic Ethers from Allylic Fluorides

AbstractAllylic ethers are a common occurrence in natural products, and are often used as intermediates in target-oriented synthesis. Their synthesis often relies on the use of transition-metal catalysts. Here, we report an organocatalytic method for the allylation of O-centered nucleophiles, the Lewis base catalyzed allylation of silyl ethers with allylic fluorides. The method relies on the concept of latent pronucleophiles in Lewis base catalysis to overcome common limitations in substrate scope, even permitting the allylation of sterically congested O-pronucleophiles. When chiral Lewis base catalysts are used, the allyl ethers are produced in an enantioenriched form through kinetic resolution of fluorides, where the stereoselectivity is determined by the chiral catalyst.

Two Monotonicity Results for Beta Distribution Functions.

Write pbeta(·,α,β) for the distribution function of the Beta distribution with parameters α and β. We show that α↦pbeta(α/(α+β),α,β) is decreasing and α↦pbeta(α/(α+β),α+1,β) is increasing over the positive reals, with the common limit for α→∞ expressible in terms of the Gamma distribution functions, and discuss implications for the distribution functions of the Gamma, Poisson and Binomial distributions.

Compact convolutional transformer for subject-independent motor imagery EEG-based BCIs

Motor imagery electroencephalography (EEG) analysis is crucial for the development of effective brain-computer interfaces (BCIs), yet it presents considerable challenges due to the complexity of the data and inter-subject variability. This paper introduces EEGCCT, an application of compact convolutional transformers designed specifically to improve the analysis of motor imagery tasks in EEG. Unlike traditional approaches, EEGCCT model significantly enhances generalization from limited data, effectively addressing a common limitation in EEG datasets. We validate and test our models using the open-source BCI Competition IV datasets 2a and 2b, employing a Leave-One-Subject-Out (LOSO) strategy to ensure subject-independent performance. Our findings demonstrate that EEGCCT not only outperforms conventional models like EEGNet in standard evaluations but also achieves better performance compared to other advanced models such as Conformer, Hybrid s-CViT, and Hybrid t-CViT, while utilizing fewer parameters and achieving an accuracy of 70.12%. Additionally, the paper presents a comprehensive ablation study that includes targeted data augmentation, hyperparameter optimization, and architectural improvements.

FSH3D: 3D Representation via Fibonacci Spherical Harmonics

AbstractSpherical harmonics are a favorable technique for 3D representation, employing a frequency‐based approach through the spherical harmonic transform (SHT). Typically, SHT is performed using equiangular sampling grids. However, these grids are non‐uniform on spherical surfaces and exhibit local anisotropy, a common limitation in existing spherical harmonic decomposition methods. This paper proposes a 3D representation method using Fibonacci Spherical Harmonics (FSH3D). We introduce a spherical Fibonacci grid (SFG), which is more uniform than equiangular grids for SHT in the frequency domain. Our method employs analytical weights for SHT on SFG, effectively assigning sampling errors to spherical harmonic degrees higher than the recovered band‐limited function. This provides a novel solution for spherical harmonic transformation on non‐equiangular grids. The key advantages of our FSH3D method include: 1) With the same number of sampling points, SFG captures more features without bias compared to equiangular grids; 2) The root mean square error of 32‐degree spherical harmonic coefficients is reduced by approximately 34.6% for SFG compared to equiangular grids; and 3) FSH3D offers more stable frequency domain representations, especially for rotating functions. FSH3D enhances the stability of frequency domain representations under rotational transformations. Its application in 3D shape reconstruction and 3D shape classification results in more accurate and robust representations. Our code is publicly available at https://github.com/Miraclelzk/Fibonacci-Spherical-Harmonics.

Test-and-FE-based method for obtaining complete stress-strain curves of structural steels including fracture

Ductile fracture is a common limit state of frameworks of steel structures and can be predicted by incorporating models for fracture initiation and propagation in finite element (FE) analyses. However, accurate prediction of fracture relies on unique fracture parameters for a given material, requiring precise predictions of fracture strain and stress states obtained through coupon tests and accompanying FE data analysis. In recent decades, various methods have been proposed to predict ductile fracture initiation, including various design geometries of coupons, test setups and FE analyses, which may lead to inconsistent fracture strains and stress states. Hence, there is a need for proposing a standard procedure for the design, test and accompanying FE-based calibration of fracture parameters, as pursued in this paper. Given that ductile fracture initiates under significant plastic strain, a constitutive model for the full strain range is required, as also proposed in this paper. Moreover, to reduce the experimental and data analytical efforts, an empirical method is proposed that uses only a small number of coupon tests to calibrate the fracture parameters. The method encompasses three levels wherein one, two, or three coupon tests are required. All in all, the paper presents a methodology for determining the full-range true stress-strain curve and the initiation of fracture, including a new post-necking constitutive model and methods for determining the free parameters of the post-necking and fracture initiation models. While applied to steel in this paper, the proposed methodology is potentially also applicable to other metals.

Tailored 3D Agarose-Well Integrated with Human Skin Equivalents for Enhanced Skin Penetration Assessment.

We developed a tailored 3D Agarose-well system integrated with reconstructed human skin equivalents to enhance skin penetration assessments. This system addresses common limitations in traditional trans-well reconstructions, such as dermal layer contraction and limited lateral diffusion, by entangling collagen fibrils within the Agarose-well. We evaluated the penetration behavior of three peptides, with and without skin-penetrating peptide (SPP) sequences, alongside adenosine, a known anti-wrinkle agent. Despite a SPP having a molecular weight approximately four times greater than that of adenosine, its kinetic constant was similar, with values of about 39 and 34, respectively. Moreover, this living skin equivalent system not only allowed for the evaluation of adenosine penetration, but also demonstrated its biological effects, with adenosine significantly enhancing procollagen synthesis by approximately 23% compared to the control. Overall, this novel strategy holds the potential for tailoring 3D Agarose-wells and advancing high-performance gel development, making it a promising approach for applications in tissue engineering, medical science, regenerative medicine, and cosmetics.

Maximizing desalination performance in pyramid distiller: Integration of vertical wick still and enhanced phase change material by nanoparticle and emerging fins

The growing global water crisis, driven by population growth and dwindling freshwater resources, demands innovative solutions for sustainable desalination. While traditional solar still designs have been explored, their efficiency remains limited. This study introduces an advanced approach to solar distillation by integrating a modified pyramid solar still (MPSS) with two key innovations: a vertically positioned wick still (VWSS) and phase change material (PCM) enhanced with silver nanomaterials (PCM-Ag Nano). In addition, the design features two absorber plate configurations—flat and finned—coupled with emerging fins (EF) within the PCM unit to improve heat conductivity, addressing a common limitation in solar distillation systems. By incorporating PCM-Ag Nano and finned absorbers, the MPSS achieved significant improvements in desalination performance. The combined system of MPSS-FA-PCM-Ag-EF and VWSS produced a total distillate volume of 12,870 ml, representing a 154 % increase over a conventional pyramid solar still (PSS). Specifically, daily outputs of 9,270 ml, 5,050 ml, and 3,600 ml were recorded for MPSS, PSS, and VWSS, respectively. Furthermore, the enhanced MPSS configuration attained the highest thermal efficiency at 60.5 %, and the desalination cost was reduced to $0.0142/L, compared to $0.019/L for the PSS. These results underscore the potential of this novel MPSS design, which combines PCM-Ag Nano and VWSS, to deliver substantial improvements in freshwater production, thermal efficiency, and cost-effectiveness. This innovative system offers a promising alternative to traditional desalination techniques, contributing to the global effort to mitigate water scarcity.

CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models

Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of large language models (LLMs) by incorporating external knowledge sources. This method addresses common LLM limitations, including outdated information and the tendency to produce inaccurate “hallucinated” content. However, evaluating RAG systems is a challenge. Most benchmarks focus primarily on question answering applications, neglecting other potential scenarios where RAG could be beneficial. Accordingly, in the experiments, these benchmarks often assess only the LLM components of the RAG pipeline or the retriever in knowledge-intensive scenarios, overlooking the impact of external knowledge base construction and the retrieval component on the entire RAG pipeline in non-knowledge-intensive scenarios. To address these issues, this paper constructs a large-scale and more comprehensive benchmark, and evaluates all the components of RAG systems in various RAG application scenarios. Specifically, we refer to the CRUD actions that describe interactions between users and knowledge bases, and also categorize the range of RAG applications into four distinct types–Create, Read, Update, and Delete (CRUD). “Create” refers to scenarios requiring the generation of original, varied content. “Read” involves responding to intricate questions in knowledge-intensive situations. “Update” focuses on revising and rectifying inaccuracies or inconsistencies in pre-existing texts. “Delete” pertains to the task of summarizing extensive texts into more concise forms. For each of these CRUD categories, we have developed different datasets to evaluate the performance of RAG systems. We also analyze the effects of various components of the RAG system, such as the retriever, context length, knowledge base construction, and LLM. Finally, we provide useful insights for optimizing the RAG technology for different scenarios 1 .

Quantitative Analysis about the Spatial Heterogeneity of Water Conservation Services Function Using a Space–Time Cube Constructed Based on Ecosystem and Soil Types

Precisely delineating the spatiotemporal heterogeneity of water conservation services function (WCF) holds paramount importance for watershed management. However, the existing assessment techniques exhibit common limitations, such as utilizing only multi-year average values for spatial changes and relying solely on the spatial average values for temporal changes. Moreover, traditional research does not encompass all WCF values at each time step and spatial grid, hindering quantitative analysis of spatial heterogeneity in WCF. This study addresses these limitations by utilizing an improved water balance model based on ecosystem type and soil type (ESM-WBM) and employing the EFAST and Sobol’ method for parameter sensitivity analysis. Furthermore, a space–time cube of WCF, constructed using remote-sensing data, is further explored by Emerging Hot Spot Analysis for the expression of WCF spatial heterogeneity. Additionally, this study investigates the impact of two core parameters: neighborhood distance and spatial relationship conceptualization type. The results reveal that (1) the ESM-WBM model demonstrates high sensitivity toward ecosystem types and soil data, facilitating the accurate assessment of the impacts of ecosystem and soil pattern alterations on WCF; (2) the EHSA categorizes WCF into 17 patterns, which in turn allows for adjustments to ecological compensation policies in related areas based on each pattern; and (3) neighborhood distance and the type of spatial relationships conceptualization significantly impacts the results of EHSA. In conclusion, this study offers references for analyzing the spatial heterogeneity of WCF, providing a theoretical foundation for regional water resource management and ecological restoration policies with tailored strategies.

Carbon Dots Infused 3D Printed Cephalopod Mimetic Bactericidal and Antioxidant Hydrogel for Uniaxial Mechano-Fluorescent Tactile Sensor.

Cephalopods use stretchy skin and dynamic color-tuning organs for visual communication and camouflage. Inspired by these natural mechanisms, a fluorescent biomaterial for deformation-induced illumination and optical communication is proposed. This is the first report of 3D printed soft biomaterials infused with carbon dots hydrothermally derived from chitosan and benzalkonium chloride. These biomaterials exhibit a comprehensive array of properties, including significant uniaxial stretching, near-instantaneous response to tactile stimuli and pH, UV resistance, antibacterial, antioxidant, noncytotoxicity, and highlighting their potential as mechano-optical materials for biomedical applications. The hydrogel's durability is evaluated by cyclic stretching, folding, rolling, and twisting tests to ensure its integrity and good signal-to-noise ratio. The diffusion mechanism is determined by water imbibition kinetics, network parameters, and time-dependent breathing. Overcoming the common limitations of short lifespans and complex manufacturing processes in existing soft hybrids, this work demonstrates a straightforward method to produce durable, energy-independent, mechano-optical hydrogel. Combined with investigations, molecular dynamic modeling is used to understand the interactions of hydrogel components.

Contemporary Rationales for Cemented Implant Restorations in the Esthetic Zone.

This article explores the ongoing relevance of cement-retained implant restorations, focusing on their contemporary rationales for their successful use. Comprehensive considerations include esthetic, positional, and occlusal factors alongside recent technological advancements designed to mitigate previous known challenges. In certain clinical scenarios, cement-retained implant restorations offer distinct advantages such as eliminating access holes for improved esthetics, particularly for malpositioned implants. Modern advancements in materials and techniques have enhanced their predictability, safety, and overall outcomes while minimizing biological risks. When performed within appropriate protocols, cement-retained implant restorations can effectively address diverse clinical challenges. Recent technical advancements further bolster their utility, supporting esthetic, technical, biomechanical, and biological outcomes in implant rehabilitation of the partially edentulous esthetic zone. Understanding the justifications and guidelines for cement-retained implant restorations, along with recent technological advancements, enables clinicians to optimize treatment outcomes with greater flexibility while minimizing common limitations in practice.

Comparison of experimental and simulated separation performance in capillary tube-in-manifold devices

A metal tube-in-manifold packed bed capillary column device, designed to overcome common limitations associated with capillary LC separations, is described. Experimental results of initial packing tests with sub-3 μm core-shell particles demonstrated efficiencies greater than 47,000 plates/m for a separation performed using the column device. Computational fluid dynamics (CFD) modeling of the multicomponent separation used for this work was validated against experimental LC results and the optimized model was able to effectively predict component peak retention times. However, the accuracy of predicted efficiencies requires further refinement. The tube-in-manifold design demonstrates that packed capillary columns with cylindrical cross-sectional channel geometry and ultrahigh pressure, low dead volume fluidic connections are achievable.

Evaluation of aerial thermography for measuring the thermal transmittance (U-value) of a building façade

In efforts to mitigate greenhouse gas emissions in the construction sector, policies promoting energy efficiency improvements in existing buildings are being implemented. Accurately assessing the impact of energy retrofit strategies requires precise determination of thermal envelope performance through energy audits. Aerial thermography, employing unmanned aerial vehicles (UAVs) equipped with infrared thermal cameras (IRT), is an underused method overcoming limitations in energy audits of large buildings or complexes. This approach offers an elevated perspective, providing an overview of the building’s thermal patterns, aiding in the identification of thermal envelope defects. By measuring temperature distribution, even in inaccessible envelope areas, the severity of identified defects can be estimated. Beyond detecting thermal bridges, air leaks, and moisture, aerial thermography is valid for estimating thermal transmittance (U-value) of enclosures. The aim of this research is to evaluate this method to calculate the U-value of the façade of an university building located in a Subtropical Mediterranean climate, during a typical full day in different seasons of the year. Concurrently with aerial thermography, the thermometric method (THM) was applied to compare results and refine the operational conditions during U-value measurement using different statistical indices and uncertainty analysis. The results demonstrated the validation of airborne thermography as a method for U-value calculation under specific meteorological and operational conditions, overcoming the common physical limitations of traditional building audit methods.

Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images

Identification of retinal diseases in automated screening methods, such as those used in clinical settings or computer-aided diagnosis, usually depends on the localization and segmentation of the Optic Disc (OD) and fovea. However, this task is difficult since these anatomical features have irregular spatial, texture, and shape characteristics, limited sample sizes, and domain shifts due to different data distributions across datasets. This study proposes a novel Multiresolution Cascaded Attention U-Net (MCAU-Net) model that addresses these problems by optimally balancing receptive field size and computational efficiency. The MCAU-Net utilizes two skip connections to accurately localize and segment the OD and fovea in fundus images. We incorporated a Multiresolution Wavelet Pooling Module (MWPM) into the CNN at each stage of U-Net input to compensate for spatial information loss. Additionally, we integrated a cascaded connection of the spatial and channel attentions as a skip connection in MCAU-Net to concentrate precisely on the target object and improve model convergence for segmenting and localizing OD and fovea centers. The proposed model has a low parameter count of 0.8 million, improving computational efficiency and reducing the risk of overfitting. For OD segmentation, the MCAU-Net achieves high IoU values of 0.9771, 0.945, and 0.946 for the DRISHTI-GS, DRIONS-DB, and IDRiD datasets, respectively, outperforming previous results for all three datasets. For the IDRiD dataset, the MCAU-Net locates the OD center with an Euclidean Distance (ED) of 16.90 pixels and the fovea center with an ED of 33.45 pixels, demonstrating its effectiveness in overcoming the common limitations of state-of-the-art methods.

Modeling building energy self-sufficiency of using rooftop photovoltaics on an urban scale

The significant contribution of buildings to global energy-related CO2 emissions and climate change has led to projections of a carbon–neutral building stock by 2050. This study evaluates the potential contribution of rooftop photovoltaics to urban energy self-sufficiency by developing an enhanced CityBEM framework, our in-house urban building energy model (UBEM). This methodology enables city-scale, simultaneous simulations of building energy use and rooftop photovoltaic retrofitting with low computational time. CityBEM’s robustness and high spatiotemporal resolution facilitate transient simulations of individual buildings with diverse usage types across large urban areas, addressing common computational constraints and input data limitations in UBEM applications. The rooftop photovoltaic model in CityBEM utilizes a comprehensive approach with physics-based modeling of crystalline PVs, model validation, and a proper design of array networks to manage self-shading effects. More than 57,000 buildings with a combined footprint of 32.37 million square meters are located in the simulation test case covering downtown Montreal (Quebec, Canada) and the surrounding areas. Results indicate that rooftop PV adoption in these buildings could potentially generate 5.9 TWh of electricity annually, reduce energy demand by 27.3%, and achieve an average annual energy saving of 40%. This local generation could also reduce operational CO2 equivalent emissions by over 0.2 megatons. Overall, this study highlights the significant potential of rooftop photovoltaics for a cleaner, more energy self-sufficient urban future.

Challenges and limitations in meta-analyses of complications in neurosurgery: Systematic review with proposed approach and checklist to mitigate errors and improve the assessment of the real-world experience.

Meta-analyses are highly valued in medical science, yet accurately reporting complications in neurosurgical studies remains challenging. Examples include inconsistencies in defining and classifying complications and variations in reporting methods. This lack of reproducibility and comparability, along with other issues related to biases, hinders the ability of meta-analyses to yield significant advancements. This systematic review investigated the challenges and limitations inherent in meta-analyses of complications in neurosurgery. Based on the identified challenges and our group's experience, we developed a practical checklist to mitigate and avoid common errors in meta-analyses of complications in neurosurgery.We searched PubMed, Embase, and Web of Science for studies addressing challenges in assessing complications in neurosurgery. The main findings were qualitatively synthesized to identify common challenges and limitations. The proposed checklist was developed using a modified Delphi technique. Eleven studies were included, uncovering heterogeneity and a lack of standardization regarding the classification of complications in neurosurgery across various authors and institutions. They suggested solutions such as implementing a more uniform classification system. Additionally, the NeuroComp Meta-Analysis Checklist was developed, comprising 23 items divided into 5 domains, with a practical approach and suggestions on how to deal with the challenges when meta-analyzing.We identified numerous challenges and concerns when assessing complications in the neurosurgical field. The NeuroComp Meta-Analysis Checklist incorporated methodologies and approaches we utilized in several previously published meta-analyses. While we acknowledge that the proposal cannot solve all the issues involved in comparing and meta-analyzing complications in neurosurgery, it has the potential to enhance the informativeness of future meta-analyses and help authors mitigate common errors. Ultimately, this tool has the potential to contribute to the advancement of accumulating real-world evidence in neurosurgical science.

Comparison and Optimization of Light Use Efficiency-Based Gross Primary Productivity Models in an Agroforestry Orchard

The light-use efficiency-based gross primary productivity (LUE-GPP) model is widely utilized for simulating terrestrial ecosystem carbon exchanges owing to its perceived simplicity and reliability. Variations in cloud cover and aerosol concentrations can affect ecosystem LUE, thereby influencing the performance of the LUE-GPP model, particularly in humid regions. In this study, the performance of six big-leaf LUE-GPP models and one two-leaf LUE-GPP model were evaluated in a humid agroforestry ecosystem from 2018–2020. All big-leaf LUE-GPP models yielded GPP values consistent with that derived from the eddy covariance system (GPPEC), with R2 ranging from 0.66–0.73 and RMSE ranging from 1.81–3.04 g C m−2 d−1. Differences in model performance were attributed to the differences in the quantification of temperature (Ts) and moisture constraints (Ws) and their combination forms in the models. The Ts and Ws algorithms in the eddy covariance-light-use efficiency (EF-LUE) model well characterized the environmental constraints on LUE. Simulation accuracy under the common limitation of Ts and Ws (Ts × Ws) was higher than the maximum limitation of Ts or Ws (Min (Ts, Ws)), and the combination of the Ts algorithm in the Carnegie–Ames–Stanford Approach (CASA) and the Ws algorithm in the EF-LUE model was optimized in combination forms, thereby constraining LUE for GPP estimates (GPPBLO, R2 = 0.76). Various big-leaf LUE-GPP models overestimated or underestimated GPP on sunny or cloudy days, respectively, while the two-leaf LUE-GPP model, which considered the transmission of diffuse radiation and the difference in photosynthetic capacity of canopy leaves, performed well (R2 = 0.72, p < 0.01). Nevertheless, the underestimation/overestimation for shaded/sunlit leaves remained under different weather conditions. Then, the clearness index (Kt) was introduced to calculate the dynamic LUE in the big-leaf and two-leaf LUE-GPP models in the form of exponential or power functions, resulting in consistent performance even in different weather conditions and an overall higher simulation accuracy. This study confirmed the potential applicability of different LUE-GPP models and emphasized the importance of dynamic LUE on model performance.