Final Set Research Articles

Comparing the contents of outcome measures in upper-limb amputation using the International Classification of Functioning, Disability, and Health: A systematic review.

The International Classification of Functioning, Disability, and Health (ICF) provides a universal framework for assessing the functioning of any person. To facilitate the application of the ICF in practice, ICF core sets are being developed. This study is part of a project intended to develop an ICF core set for upper-limb amputation (ULA) and aims to identify relevant concepts included in the outcome measurements used in studies of ULA. Articles involving ULA aged 18 years or older from January 2011 to December 2021 were searched on Cumulative Index to Nursing and Allied Health Literature, SPORTdiscus, and Medical Literature Analysis and Retrieval System Online. We included studies with particular designs (randomized controlled trials, before/after studies, cross-sectional studies, and longitudinal observational studies) and published in English. Relevant concepts were extracted from measurements and linked to the ICF using linking rules, and a frequency analysis was conducted. Sixty-one of the 1272 identified publications were included, from which 86 measurements were extracted. Concepts extracted from measurements were linked to 129 ICF categories. Three hundred twenty-six (29.23%) of the 1115 concepts were related to body functions, 643 (57.66%) to activity and participation, 96 (8.60%) to environmental factors, 19 (1.70%) to body structures, and 6 (0.53%) to personal factors. Twenty-five (2.24%) were characterized as "nd-not definable." "Fifty-four" categories identified in at least 5% of the publications will be considered for inclusion in the final ICF core set for ULA during the consensus conference. This review provides information about the content of measures, and the identified ICF categories reveal the research perspective for developing an ICF core set for ULA.

Gene co-expression network and differential expression analyses reveal key genes for weaning weight in Simmental-Holstein crossbred cattle

Weaning weight is a key indicator of the early growth performance of cattle. An understanding of the genetic mechanisms underlying weaning weight will help increase the accuracy of selection of breeding animals. In order to identify candidate genes associated with weaning weight in Simmental-Holstein crossbred cattle, this study generated RNA-Sequencing (RNA-seq) data from 86 crossbred calves (37 males and 49 famales) and measured their weaning weight and body size traits (wither height, body length, chest girth, rump width, and rump length). Differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) were performed. A total of 498 differentially expressed genes (DEGs) were identified between the low weaning weight (LWW) group and the high weaning weight (HWW) group. Weaning weight was transcriptionally correlated (FDR < 0.05) with four of the eleven co-expression gene modules. By intersecting DEGs and hub genes of the four modules, we identified a final set of 37 candidate genes enriched in growth, development, or immune-related processes. In addition, one co-expression module was significantly correlated with all the five body size traits (P < 0.05), from which MX1 was identified as a key candidate gene through protein-protein interaction (PPI) analysis of hub genes. Further evidence from cattle transcriptome-wide association study analysis (TWAS) and human phenome-wide association study (PheWAS) validated significant associations of CACNA1S, SEMA7A, VCAN, CD101, CD19, and CSF2RB with growth and development traits (P < 0.05). Notably, CACNA1S and CD19 were also associated with typical immune traits such as B cell proliferation, differentiation, and activation. In conclusion, this study reveals new candidate genes significantly associated with weaning weight in Simmental-Holstein crossbred cattle, providing a basis for further exploration of the genetic mechanisms behind growth traits of cattle.

A multi-stage feature selection method to improve classification of potential super-agers and cognitive decliners using structural brain MRI data-a UK biobank study.

Cognitive aging is described as the age-related decline in areas such as memory, executive function, reasoning, and processing speed. Super-Agers, adults over 80 years old, have cognitive function performance comparable to middle-aged adults. To improve cognitive reserve and potentially decrease Alzheimer's disease (AD) risk, it is essential to contrast changes in regional brain volumes between "Positive-Agers" who have superior cognitive performance compared to their age peers but are not 80 years old yet and aging adults who show cognitive decline (i.e., "Cognitive Decliners"). Using longitudinal cognitive tests over 7-9 years in UK Biobank, principal component analysis (PCA) was first applied to four cognitive domains to create a general cognition (GC) composite score. The GC score was then used to identify latent cognitive groups. Given cognitive groups as the target variable and structural magnetic resonance imaging (sMRI) data and demographics as predictors, we developed a multi-stage feature selection algorithm to identify the most important features. We then trained a Random Forest (RF) classifier on the final set of 54 selected sMRI and covariate predictors to distinguish between Positive-Agers and Cognitive Decliners. The RF model achieved an AUC of 73%. The top 6 features were age, education, brain total surface area, the area of pars orbitalis, mean intensity of the thalamus, and superior frontal gyrus surface area. Prediction of cognitive trajectory types using sMRI may improve our understanding of successful cognitive aging.

A Cheminformatics Workflow to Select Representative TSCA Chemicals for New Approach Methodology (NAM) Screening.

The Toxic Substances Control Act (TSCA) requires the US EPA to evaluate the hazard and exposure of new and existing chemicals. New chemical notifications are typically data-poor and EPA has historically relied upon approaches including chemical categories to fill data gaps. As part of a multi-year Research Program, opportunities are being explored to leverage New Approach Methods (NAMs) in hazard and exposure assessments. Data from a battery of in vitro NAMs will be generated to form a case study for an adaptable approach to inform new chemical assessments. Herein, a cheminformatics workflow was developed to identify a set of ∼300 representative candidate chemicals for in vitro screening from the TSCA non-confidential active inventory. The freely available web application ClassyFire was used to categorize all discrete organic structures from the TSCA inventory into one of 68 primary structural categories. Large primary categories were subcategorized into smaller categories using hierarchical agglomerative clustering, ultimately yielding 180 structural terminal categories. The inventory was filtered to substances that lacked previous ToxCast bioactivity screening, were associated with physicochemical property predictions indicating non-volatile solids or liquids, and had a higher chance of procurement. Amenability predictions for liquid chromatography-mass spectrometry were also generated to provide an indication of which chemicals lent themselves to aqueous-based screening and analytical verification in solvated samples. Structures associated with transformation in solvent, potentially explosive or highly reactive, were excluded. Potential candidate substances were selected on the basis of being structurally representative of the terminal category and meeting other screenability conditions. A final set of 318 candidate chemicals were proposed to undergo analytical quality control and screening in a range of broad and targeted biological technologies for human health-relevant end points. Finally, in silico tools were applied to explore predicted hazard profiles of these candidate substances relative to the full inventory.

In vitro evaluation of the influence of ultrasonic activation on physicochemical properties of three endodontic repair materials.

The influence of ultrasonic activation (UA) on the physicochemical properties of setting time (n = 5), volumetric stability (n = 10), alkalizing activity/calcium ions release (pH/Ca2+) (n = 10) and calcium/phosphate-rich substance formation in simulated body fluid (Hank's balanced salt solution; HBSS) of three cements was evaluated: white MTA-Angelus (MTA), MTA Repair HP (MTAHP) and Biodentine (BIO). It was observed that UA influenced the setting times (min) distinctly, delaying the initial setting time of MTA (40.8/64.6) and accelerating that of BIO (35.6/22.4). The final setting time of MTAHP (154.4/114.6) and BIO (64.4/42.4) were also accelerated (p < 0.05). Volumetric reduction was observed in all groups, with MTA/UA being the most volumetrically stable (0.98%); UA did not influence volumetric stability (p > 0.05). All groups exhibited an alkaline pH, with a disadvantage for MTAHP and MTAHP/UA at 24 h, 72 h and 168 h (p < 0.05). All groups showed Ca2+ release. The tested cements exhibited a favourable Ca/P ratio on their surface after 28 days.

CNS-CLIP: Transforming a Neurosurgical Journal Into a Multimodal Medical Model.

Classical biomedical data science models are trained on a single modality and aimed at one specific task. However, the exponential increase in the size and capabilities of the foundation models inside and outside medicine shows a shift toward task-agnostic models using large-scale, often internet-based, data. Recent research into smaller foundation models trained on specific literature, such as programming textbooks, demonstrated that they can display capabilities similar to or superior to large generalist models, suggesting a potential middle ground between small task-specific and large foundation models. This study attempts to introduce a domain-specific multimodal model, Congress of Neurological Surgeons (CNS)-Contrastive Language-Image Pretraining (CLIP), developed for neurosurgical applications, leveraging data exclusively from Neurosurgery Publications. We constructed a multimodal data set of articles from Neurosurgery Publications through PDF data collection and figure-caption extraction using an artificial intelligence pipeline for quality control. Our final data set included 24 021 figure-caption pairs. We then developed a fine-tuning protocol for the OpenAI CLIP model. The model was evaluated on tasks including neurosurgical information retrieval, computed tomography imaging classification, and zero-shot ImageNet classification. CNS-CLIP demonstrated superior performance in neurosurgical information retrieval with a Top-1 accuracy of 24.56%, compared with 8.61% for the baseline. The average area under receiver operating characteristic across 6 neuroradiology tasks achieved by CNS-CLIP was 0.95, slightly superior to OpenAI's Contrastive Language-Image Pretraining at 0.94 and significantly outperforming a vanilla vision transformer at 0.62. In generalist classification, CNS-CLIP reached a Top-1 accuracy of 47.55%, a decrease from the baseline of 52.37%, demonstrating a catastrophic forgetting phenomenon. This study presents a pioneering effort in building a domain-specific multimodal model using data from a medical society publication. The results indicate that domain-specific models, while less globally versatile, can offer advantages in specialized contexts. This emphasizes the importance of using tailored data and domain-focused development in training foundation models in neurosurgery and general medicine.

Multisociety consensus recommendations on hepatitis delta virus infection.

Hepatitis D virus (HDV) prevalence data and country-specific HDV guidelines are not widely available in the Gulf Cooperation Council (GCC) states. We developed consensus recommendations to guide healthcare professionals, policymakers, and researchers in improving HDV management and patient health outcomes in three GCC states: Kuwait, Saudi Arabia, and the United Arab Emirates. A consensus panel comprising hepatology experts (n = 6) from the three GCC societies was formed. The panel identified two broader areas related to clinical practice (screening and diagnosis, and treatment and management), addressed critical questions, and developed draft recommendations in February 2024. The strength of the final set of recommendations was subjected to consensus voting in March 2024. A majority was defined a priori with a two-thirds vote (67%). The paper outlines those recommendations alongside showcasing the current epidemiology of HDV in the GCC states, emphasizing the variability in prevalence, demographic patterns, and region-specific risk factors. It also highlights the current state of screening and diagnosis practices, identifying key obstacles, such as access to advanced screening protocols and diagnostic tools. Furthermore, HDV treatment landscape and preventative strategies are outlined, focusing on vaccination, public health initiatives, and the crucial role of public awareness and education. Ethical and sociocultural considerations are discussed, underscoring the importance of culturally sensitive healthcare practices. These recommendations present a comprehensive overview of the challenges and strategies for managing HDV in these states. Policy recommendations are provided to support HDV management, including standardizing care protocols and promoting public health measures.

Metaphors of young-onset dementia in the illness narratives of those with the condition.

This study identified and analyzed metaphors related to the lived experience of young-onset dementia that were used in nine illness narratives written by people with the condition. A final set of 1111 MEs sorted into 30 source domain categories were grouped according to six target domain categories reflecting the biologic (the person with dementia's body/brain), psychologic (suffering with dementia, coping with dementia, dementia itself, the person with dementia), and social (the social experience of dementia) aspects of having dementia. Notably, many of the metaphors were similar to previously reported metaphors of illness, such as fight and journey, and other metaphors of embodiment, as well as disease as enemy, body as container, and body as machine. In addition, although negative conceptualizations were in the majority, almost one-third of the metaphoric expressions, belonging to the fight and journey source domain categories, reflected mainly positive images. The commonality of metaphor types with those of other illness experiences supports the notion of shared metaphors across illness contexts. Moreover, in contrast to the dehumanizing and stigmatizing terms that have previously been used to socially construct dementia, the positivity of metaphoric images identified here indicates the authors' proactive and affirming conceptualizations of their experience of dementia. Health care professionals can draw on this study's findings to help their own patients make sense of and cope with dementia.

A high-quality chromosome-level genome assembly of the traditional Chinese medicinal herb Zanthoxylum nitidum

Dried roots of Zanthoxylum nitidum (2n=2x=70, family Rutaceae) was referred as “Liang-Mian-Zhen” in Chinese, acting as a valuable species due to its notable pharmacological activities. Herein, we combined PacBio HiFi data together with Hi-C mapping technology to construct a chromosome-scale reference genome assembly for Z. nitidum. The assembly reached a length of 2.24 Gb, successfully anchoring 99.31% of sequences onto 35 pseudo-chromosomes. Among these, 26 chromosomes achieved telomere-to-telomere assembly, and 11 chromosomes were gap-free. The contigs N50 and scaffolds N50 reached 57.61 Mb and 78.00 Mb, respectively. Transposable elements comprised 81.44% of the Z. nitidum genome, and over 78% of them were long-terminal repeat retrotransposon elements. Furthermore, 32,737 protein-coding genes were identified and 99.38% of all were functionally annotated. The completeness of the genome assembly and final gene sets reached 97.83% and 96.47% based on Benchmarking Universal Single-Copy Orthologs (BUSCO), respectively. Taken together, our results provided a high-quality chromosome-level assembly of Z. nitidum genome and will be a valuable resource that will facilitate breeding varieties with higher alkaloids content.

Application of porous luffa fiber as a natural internal curing material in high-strength mortar

This study explores the potential of renewable plant fibers as internal curing (IC) materials, analyzing their potential in high-strength mortar (HSM) applications. Experiments involving the incorporation of different volumetric ratios of luffa fiber into concrete assessed impacts on autogenous shrinkage (AS), mechanical properties, and microstructure. The research found that the addition of luffa fibers extended both the setting times of the mixture, and after final setting, continued the hydration reaction by releasing internally stored water. Compared to the control group, luffa fibers significantly reduced AS by up to 56.87%, primarily due to their high-water absorption capacity (211%), which mitigates the internal capillary pressures during the cement hydration process. Moreover, the inclusion of luffa fibers significantly affected the concrete's mechanical properties: a 1% luffa addition enhanced the compressive strength at 28 days by 7.6% over the control; concrete with 2% luffa fiber exhibited the highest flexural strength at 28 days, showing a 9.4% increase over the control. Microstructural analysis revealed that luffa fiber not only promoted continued hydration but also increased the content of hydration products and enhanced the compactness of the cementitious matrix. Overall, luffa fibers effectively reduce HSM’s AS and enhance its mechanical properties and microstructure, showing potential to improve concrete performance.

Enhancing Solidification in One-Part Geopolymer Systems through Alkali-Thermal Activation of Bauxite residue and Silica fume Integration

This work describes the synthesis of geopolymers, a family of amorphous alumino-silicates, employing Silica fume and bauxite waste as precursor materials in an alkali-activated polycondensation reaction and the investigation of their properties. The purpose of the study is to determine the feasibility of producing one-part alkali-activated geopolymer for use in cast-in-place construction. Following calcination of the bauxite residue at 800 °C, different amounts of solid activator Na2O (10%, 15%, and 20%) were added. Furthermore, Silica fume content ranging between 10% and 40% was utilised at intervals of 10%, in lieu of alkali-thermally treated bauxite residue. The primary objective of the study is to evaluate the fresh properties throughout the first 28 days of geopolymer formation, including consistency, flowability, heat evolution, initial setting time (IST), and final setting time (FST). Scanning electron microscopy (SEM) images are used in conjunction with the 28-day average compressive strength to demonstrate the solidification of one-part geopolymers. Furthermore, these properties are affected by adding Silica fume at regular intervals between 10% and 40% as a replacement of the alkali-thermally treated Bauxite residue. The 28-day average compressive strength, with a maximum value of 19MPa indicating successful geopolymer formation, supports the solidification of one-part geopolymers.

In-depth investigation on macro-properties and micro-mechanism of sustainable alkali-activated slag/fly ash paste incorporating seawater

The impacts of seawater on the workability, hydration product features, and mechanical properties of alkali-activated fly ash (FA)/ground blast furnace slag (GBFS) binary system (AAFS) are investigated. The potential suitability of the AAFS for application in marine construction projects is discussed. The findings illustrate that seawater considerably enhances the dissolution of AAFS. The high pH of the seawater AAFS (SAAFS) pore solution accelerates the early hydration process. The presence of seawater leads to a relatively wide half-peak width and an increased average crystallite spacing in calcium (alumina) silicate hydration (C-(A)-S-H) gels. Moreover, seawater facilitates the transformation of silicate ions ([SiO4]4-) into highly polymerized state. The final setting time and fluidity of AAFS are reduced by the addition of seawater. Furthermore, the introduction of seawater contributes to higher contents of C-(A)-S-H gels, which densifies the SAAFS matrix and improves the compressive strength of SAAFS.

Impact of treated sewage water on early strength development of calcium sulfoaluminate cement paste: A comparative study

This study investigates the use of treated sewage water (TSW) as a substitute for fresh tap water (FTW) in concrete production using calcium sulfoaluminate (CSA) cement. The research addresses concerns about freshwater scarcity and emphasizes CSA cement's rapid setting properties, crucial for emergency constructions like military airfield recovery. The focus is on the early-age properties of CSA paste mixed with TSW, with assessments conducted at 4 hours, 1 day, and 3 days post-mixing. Key parameters, including slump, setting times, and hardened characteristics, were evaluated. TSW contained significant metal concentrations and a high pH, with total dissolved solids exceeding FTW by 67%, yet all parameters remained within acceptable limits. Analytical techniques identified ettringite (AFt) as a primary hydration product, while ye'elimite (C4A3Š) was present as a component of the unhydrated clinker in the CSA cement. Simulations showed improved stability in the TSW-CSA interface compared to FTW, although early hydration was slower, likely due to delayed C4A3Š hydration and increased AFt formation. Initially, CSA/TSW pastes presented a refined microstructure, which altered by 3 days. Despite a 14% faster final setting time, compressive strength was 21% lower at 4 hours. These findings highlight TSW's potential as a sustainable alternative in CSA cement mixing, necessitating further research for long-term performance evaluation.

2024 Standardization of Polysomnography Reports - A Consensus of the Brazilian Sleep Association.

Introduction The absence of standardized reporting for sleep medicine exams across different laboratories can lead to misinterpretation, diagnostic inconsistencies, and suboptimal treatment strategies. This document seeks to establish guidelines for the development of sleep study reports, covering recordings from studies of types 1 to 4, and represents the official position of Associação Brasileira do Sono (ABS; Brazilian Sleep Association) on the standardization of polysomnography (PSG) and cardiorespiratory polygraphies. Materials and Methods The recommendations for the items to be reported in PSG records were developed by means of a Delphi study, comprised of two voting rounds. In each round, participants had to vote regarding the appropriateness of items to be reported in type-1 to -4 sleep studies, rating them as recommended , optional , or not recommended . The consensus threshold was set at 66% in each voting round, or 75% for the combined responses of recommended and optional . Results The panel was comprised of 29 experts. After 2 voting rounds and subsequent deliberations by the steering committee, 352 items were included in the final set of recommendations. Consensus was achieved for 339 items (96.3%), of which 145 (41.2%) were classified as recommended , 154 as optional (43.8%), 35 as not recommended (9.9%), and 5 as not allowed (1.4%). No consensus was reached for 13 items (3.7%). The items recommended in this consensus are detailed in the main text. Conclusion These guidelines provide comprehensive recommendations for reporting diagnostic tests in sleep medicine.

Flexural Behavior of Innovative Glass Fiber-Reinforced Composite Beams Reinforced with Gypsum-Based Composites.

Glass Fiber-Reinforced Composite (GFRP) has found widespread use in engineering structures due to its lightweight construction, high strength, and design flexibility. However, pure GFRP beams exhibit weaknesses in terms of stiffness, stability, and local compressive strength, which compromise their bending properties. In addressing these limitations, this study introduces innovative square GFRP beams infused with gypsum-based composites (GBIGCs). Comprehensive experiments and theoretical analyses have been conducted to explore their manufacturing process and bending characteristics. Initially, four types of GBIGC-namely, hollow GFRP beams, pure gypsum, steel-reinforced gypsum, and fiber-mixed gypsum-infused beams-were designed and fabricated for comparative analysis. Material tests were conducted to assess the coagulation characteristics of gypsum and its mechanical performance influenced by polyvinyl acetate fibers (PVAs). Subsequently, eight GFRP square beams (length: 1.5 m, section size: 150 mm × 150 mm) infused with different gypsum-based composites underwent four-point bending tests to determine their ultimate bending capacity and deflection patterns. The findings revealed that a 0.12% dosage of protein retarder effectively extends the coagulation time of gypsum, making it suitable for specimen preparation, with initial and final setting times of 113 min and 135 min, respectively. The ultimate bending load of PVA-mixed gypsum-infused GFRP beams is 203.84% higher than that of hollow beams, followed by pure gypsum and steel-reinforced gypsum, with increased values of 136.97% and 186.91%, respectively. The ultimate load values from the theoretical and experimental results showed good agreement, with an error within 7.68%. These three types of GBIGCs with significantly enhanced flexural performance can be filled with different materials to meet specific load-bearing requirements for various scenarios. Their improved flexural strength and lightweight characteristics make GBIGCs well suited for applications such as repairing roof beams, light prefabricated frames, coastal and offshore buildings.

Effect of Traffic Vibration on Compressive Strength of High-Strength Concrete and Tensile Strength of New-to-Old Concrete Interfaces

Widening existing bridges is an important way to meet the surge in traffic demand, which is often carried out in a way that does not interrupt traffic. To investigate the effect of traffic vibration on the compressive strength of high-strength concrete and the splitting strength of new-to-old concrete interfaces, the initial to final set time of high-strength concrete C60 was first investigated in this article. Then, the traffic disturbance parameters were determined. Later, the compressive strength of C60 concrete at different stages under traffic disturbance parameters was carried out. Finally, the splitting tensile strength of new-to-old concrete specimens at different stages with different loading modes was tested. The test results indicated that the compressive strength of the specimens vibrated for 3 h and cured for 3, 7, and 28 days was increased by 4.3%, 5.7%, and 11.9%, respectively; those of the specimens vibrated for 7 h and cured for 3, 7, and 28 days was decreased by 13.7%, 20.4%, and 19.9%, respectively; the effect traffic vibration on the compressive strength of the specimens vibrated for 5 h was not obvious. When loaded along the old and new concrete joint, the specimens cracked along the joint; the splitting tensile strengths of the specimen at different disturbed stages were significantly decreased. When loaded perpendicular to the joint, the specimens cured for 3 and 7 days still cracked along the joint, and the splitting tensile strengths of the specimen at different disturbed stages were significantly decreased; while the specimens cured for 28 days cracked in the direction perpendicular to the joint, the tensile strengths of the specimens at different disturbed stages were significantly decreased. This study can promote the widening and improvement of existing concrete highways and bridges, which can save resources and improve land use.

Solar Energy Applications in Protected Agriculture: A Technical and Bibliometric Review of Greenhouse Systems and Solar Technologies

This study addresses solar energy applications in protected agriculture, focusing on greenhouses and related technologies. A bibliometric and technical analysis is developed, covering research published between 1976 and 2024, to identify the main trends and challenges in the use of solar energy in controlled environments. The methodology was based on the PRISMA approach, using the Scopus database to retrieve relevant documents. From an initial total of 221 documents, 216 were selected after a filtering and debugging process, ensuring the relevance of the final set. In the analytical phase, the results showed a moderate growth of 3.68% in the annual publication rate, highlighting the impact of research on solar energy’s application to air conditioning and energy efficiency in greenhouses. Most of the studies reviewed feature hybrid systems that combine solar energy with other resources, and we highlight both advances in climate control through artificial intelligence and the implementation of photovoltaic and thermal technologies to improve the energy efficiency of agricultural systems. The results also underline the importance of tomato cultivation in the selected studies, reflecting its global economic impact. The conclusions highlight the need for the further integration of energy storage and desalination technologies, especially in arid regions with high solar irradiation, to ensure the sustainability of greenhouses. It is proposed that future research should address the wider implementation of hybrid systems and advanced climate control technologies, optimizing both the use of energy resources and the performance of crops under cover. In addition, it is recommended that international collaboration be strengthened to address technical and climatic challenges in protected agriculture and to expand the adoption of innovative solutions in different geographical contexts.

Considerations for the Design of Pedagogical Tasks in Computer‐Based L2 Listening

Considerations for the Design of Pedagogical Tasks in Computer‐Based <scp>L2</scp> Listening

Development of a Knowledge Assessment Tool to Measure Farmers' Understanding of Improved Groundnut Cultivation Practices

This study focused on assessing farmers' knowledge of improved cultivation practices in groundnut farming. An initial pool of 40 knowledge-related items was developed, drawing from various sources such as literature, input from field extension personnel, insights from relevant specialists, and the researchers' own expertise. After applying statistical procedures to ensure the reliability and validity of the knowledge test, the final set was refined to 21 items. This standardized knowledge test serves as a tool for evaluating the extent of farmers' understanding of advanced groundnut cultivation practices.

Large language models in neurosurgery: a systematic review and meta-analysis.

Large Language Models (LLMs) have garnered increasing attention in neurosurgery and possess significant potential to improve the field. However, the breadth and performance of LLMs across diverse neurosurgical tasks have not been systematically examined, and LLMs come with their own challenges and unique terminology. We seek to identify key models, establish reporting guidelines for replicability, and highlight progress in key application areas of LLM use in the neurosurgical literature. We searched PubMed and Google Scholar using terms related to LLMs and neurosurgery ("large language model" OR "LLM" OR "ChatGPT" OR "GPT-3" OR "GPT3" OR "GPT-3.5" OR "GPT3.5" OR "GPT-4" OR "GPT4" OR "LLAMA" OR "MISTRAL" OR "BARD") AND "neurosurgery". The final set of articles was reviewed for publication year, application area, specific LLM(s) used, control/comparison groups used to evaluate LLM performance, whether the article reported specific LLM prompts, prompting strategy types used, whether the LLM query could be reproduced in its entirety (including both the prompt used and any adjoining data), measures of hallucination, and reported performance measures. Fifty-one articles met inclusion criteria, and were categorized into six application areas, with the most common being Generation of Text for Direct Clinical Use (n = 14, 27.5%), Answering Standardized Exam Questions (n = 12, 23.5%), and Clinical Judgement and Decision-Making Support (n = 11, 21.6%). The most frequently used LLMs were GPT-3.5 (n = 30, 58.8%), GPT-4 (n = 20, 39.2%), Bard (n = 9, 17.6%), and Bing (n = 6, 11.8%). Most studies (n = 43, 84.3%) used LLMs directly out-of-the-box, while 8 studies (15.7%) conducted advanced pre-training or fine-tuning. Large language models show advanced capabilities in complex tasks and hold potential to transform neurosurgery. However, research typically addresses basic applications and overlooks enhancing LLM performance, facing reproducibility issues. Standardizing detailed reporting, considering LLM stochasticity, and using advanced methods beyond basic validation are essential for progress.