Systematic Analysis Research Articles

Transcriptome analysis of long non-coding RNA associated with embryonic muscle development in chickens.

1. Skeletal muscle is an important component of chicken carcass. In chickens, the number of muscle fibres is fixed during the embryonic period, and muscle development during the embryonic period determines the muscle development potential after hatching.2. Beijing-You (BY) and Cornish (CN) chickens show completely different growth rates and body types, and two breeds were used in this study to explore the role of lncRNAs in muscle development during different chicken embryonic periods. A systematic analysis of lncRNAs and mRNAs were conducted in the pectoral muscle tissues of BY and CN chickens at embryonic days 11 (ED11), 13 (ED13), 15 (ED15), 17 (ED17), and 1-day-old (D1) using RNA-seq. A total of 4,104 differentially expressed transcripts (DETs) were identified among the five stages, including 2,359 lncRNAs and 1,745 mRNAs.3. The number of DETs between the two breeds at ED17 (1,658 lncRNAs and 1,016 mRNAs) was much higher than the total number of DET at all the other stages (692 lncRNAs and 729 mRNAs), indicating that the two breeds show the largest difference in gene regulation at ED17.4. Correlation analysis was performed for all differentially expressed lncRNAs and mRNAs during the five periods. Forty-three, cis interaction pairs of lncRNA-mRNA related to chicken muscle development were predicted. The expression of four pairs was verified, and the results showed MSTRG.12395.2-FGFBP2 and MSTRG.18590.6-FMOD were significantly up-regulated in CN at ED11 compared to BY and might be important candidate genes for embryonic muscle development.

Анализ тревожности студентов первого и второго курсов (на примере Петрозаводского государственного университета)

The level of anxiety in modern stressful and foreign policy unfavorable conditions becomes one of the determining factors in the educational process, before the new reforms in the sphere of education there is a problem of organization of pedagogical process in students with high level of anxiety. In this article we study the actual indicators of personality and reactive anxiety in students of Petrozavodsk State University, we obtained data on statistically reliable differences in personality anxiety in students of different genders. We also conducted a systematic analysis of the literature on the platform elibrary.ru, which allowed us to obtain data on the average level of anxiety in students of different institutions of higher education from 2010 to 2022. The used indicators of the results were the values of the methodology ShRLT (Reactive (situational) and personality anxiety scale) C.D. Spielberger-J.L. Khanin.

Education policy and ‘free speech’ on race and faith equality at school

ABSTRACT Right-wing populists have recurrently created moral panics internationally about the supposed need to ‘protect free speech’ in higher education (HE), and ‘protect children’ from progressive speech in schools. This paper presents the first systematic analysis of how such dynamics function with respect to race and faith equality in a national school policy context. Drawing on a critical post-structural framework, we conceptualise the policy problematisation of speech as situated in a wider set of coercion-consent governing strategies used to manage contemporary authoritarian neoliberal contradictions, and to narrow the speakability of anti-racist and faith equality concerns. We present a two-stage thematic and discursive analysis of a corpus of primarily school-focused English policy texts from successive Conservative-led governments (2010–2022). The analysis outlines three main policy strategies which narrow speakability: the defining of ‘good’ schools and citizens with limited/oppositional reference to race equality, the problematising of ‘dangerous’ speech, and the indexing of school/HE subjects who are truly vulnerable to political speech. The paper offers an urgent case study of how possibilities for progressive race and faith-based expression are shaped beyond explicitly speech-focused policies, and argues that engagement of the complex governance of speakability offers nuanced possibilities for analysing bans on progressive education internationally.

Organosulfur Cathodes in Lithium Metal Batteries: Bridging the Gap between Fundamentals and Practical Applications

AbstractHigh‐specific energy sulfur‐based cathodes have attracted considerable interest in lithium batteries. Organosulfur cathodes offer inherent advantages of high element abundance and an extended cycling life, aligning with the evolving requirements of future energy storage devices. Over the past decade, research efforts have been devoted to optimizing electrochemical performance through the rich and tunable molecular structures of organosulfur compounds. To further advance the fundamental research and practical application of lithium‐organosulfur batteries, a systematical analysis of the correlation between the molecular structures and electrochemical mechanisms of organosulfur cathodes is imperative. This involves deriving the key parameters at the cell level and investigating the feasibility. In this review, the thermodynamics, reaction processes, and electrochemical kinetics of organosulfur cathodes, grounded in fundamental theories of electrochemistry and materials science are discussed. Expanding the insights, comparisons among elemental sulfur, organosulfur, and n‐type organic cathodes (e.g., carbonyl cathodes) are drawn. The gap between fundamentals and practical applications targeting 500 Wh kg−1 lithium organosulfur batteries is highlighted through energy density calculations and identification of key factors affecting pouch cells. Finally, potential strategies and prospects for the overall design of advanced lithium‐organosulfur batteries are proposed, considering both theoretical foundations and practical implementations.

COVID-19 and Family Visits: A Systematic Jurisdiction Analysis of Family Visitation and Safety Policies in Juvenile Correctional Facilities in the United States

When COVID-19 first hit the United States, juvenile correctional facilities across the country discontinued all in-person activities including family visits. Correctional facilities across the country were among the last institutions to reopen their doors for in-person activities given the heightened risk of rapid spread. Drawing on data gathered in February and March 2022, this study examined the state of family visitation policies and COVID-19 safety responses adopted by juvenile correctional facilities, as reported on websites, including information on the different types of contact allowed; COVID-19 safety protocols and practices; availability of information on COVID-19 infection and vaccination rates; and the overall timeliness, consistency, and comprehensiveness of the information available to families with incarcerated minor children. Our findings highlight just how untimely, inconsistent, and incomprehensive information and policies were across jurisdictions, sometimes with little to no stated explanation for their decision-making. We argue that juvenile correctional facilities should take a family-focused approach when developing and disseminating policies that impact the lives of incarcerated youth and their families, especially in times of global uncertainty.

Massively parallel dissection of RNA in RNA-protein interactions in vivo.

Many of the biological functions performed by RNA are mediated by RNA-binding proteins (RBPs), and understanding the molecular basis of these interactions is fundamental to biology. Here, we present massively parallel RNA assay combined with immunoprecipitation (MPRNA-IP) for in vivo high-throughput dissection of RNA-protein interactions and describe statistical models for identifying RNA domains and parsing the structural contributions of RNA. By using custom pools of tens of thousands of RNA sequences containing systematically designed truncations and mutations, MPRNA-IP is able to identify RNA domains, sequences, and secondary structures necessary and sufficient for protein binding in a single experiment. We show that this approach is successful for multiple RNAs of interest, including the long noncoding RNA NORAD, bacteriophage MS2 RNA, and human telomerase RNA, and we use it to interrogate the hitherto unknown sequence or structural RNA-binding preferences of the DNA-looping factor CTCF. By integrating systematic mutation analysis with crosslinking immunoprecipitation, MPRNA-IP provides a novel high-throughput way to elucidate RNA-based mechanisms behind RNA-protein interactions in vivo.

Systematic analysis of approaches used in cardiac arrest trials to inform relatives about trial enrolment of non-surviving patients

BackgroundThe recruitment of patients to emergency research studies without the requirement for prior informed consent has furthered the conduct of randomised studies in cardiac arrest. Frameworks enabling this vary around...

Speech, voice, and language outcomes following deep brain stimulation: A systematic review.

Deep brain stimulation (DBS) reliably ameliorates cardinal motor symptoms in Parkinson's disease (PD) and essential tremor (ET). However, the effects of DBS on speech, voice and language have been inconsistent and have not been examined comprehensively in a single study. We conducted a systematic analysis of literature by reviewing studies that examined the effects of DBS on speech, voice and language in PD and ET. A total of 675 publications were retrieved from PubMed, Embase, CINHAL, Web of Science, Cochrane Library and Scopus databases. Based on our selection criteria, 90 papers were included in our analysis. The selected publications were categorized into four subcategories: Fluency, Word production, Articulation and phonology and Voice quality. The results suggested a long-term decline in verbal fluency, with more studies reporting deficits in phonemic fluency than semantic fluency following DBS. Additionally, high frequency stimulation, left-sided and bilateral DBS were associated with worse verbal fluency outcomes. Naming improved in the short-term following DBS-ON compared to DBS-OFF, with no long-term differences between the two conditions. Bilateral and low-frequency DBS demonstrated a relative improvement for phonation and articulation. Nonetheless, long-term DBS exacerbated phonation and articulation deficits. The effect of DBS on voice was highly variable, with both improvements and deterioration in different measures of voice. This was the first study that aimed to combine the outcome of speech, voice, and language following DBS in a single systematic review. The findings revealed a heterogeneous pattern of results for speech, voice, and language across DBS studies, and provided directions for future studies.

Analyzing the Impact of Online Learning on Higher Education: A Text Analytics Approach

Amidst the relentless upheaval caused by the ongoing Covid-19 pandemic, the higher education landscape finds itself compelled to pivot towards internet-mediated learning modalities. This shift, while necessary for continuity, has engendered profound repercussions for students, educators, and administrative staff alike. Foremost among the concerns is the discernible impact on student learning outcomes and academic performance. Studies, such as those conducted by Brookings and The University of Chicago, underscore the alarming projections of learning loss and escalating failure rates within this context. Bloom, a prominent higher education institution grappling with the tumult of the pandemic, has witnessed a palpable decline in average grades since its onset. Recognizing the imperative to stem this tide and foster informed decision-making, Bloom endeavors to harness the power of text analytics. Through the systematic analysis of unstructured textual data sourced from diverse channels—ranging from social media platforms to educational websites—Bloom endeavors to unveil underlying patterns, discern actionable insights, and drive strategic interventions. This article presents a comprehensive framework delineating Bloom's foray into text analytics, elucidating the attendant challenges, proposed solutions, and anticipated implementation strategies. By delving into the nuances of managing unstructured textual data and navigating the complexities thereof, this endeavor seeks to empower Bloom with the tools and insights requisite for optimizing academic performance and mitigating the deleterious effects of the pandemic.

Pan-cancer analysis of LRRC59 with a focus on prognostic and immunological roles in hepatocellular carcinoma.

LRRC59 is a leucine-rich repeats-containing protein located in the endoplasmic reticulum (ER), it serves as a prognostic marker in several cancers. However, there has been no systematic analysis of its role in the tumor immune microenvironment, nor its predictive value of prognosis and immunotherapy response in different cancers. A comprehensive pan-cancer analysis of LRRC59 was conducted from various databases to elucidate the associations between its expression and the prognosis of cancer, genetic alterations, tumor metabolism, and tumor immunity. Additionally, further functional assays were performed in hepatocellular carcinoma (HCC) to study its biological role in regulating cell proliferation, migration, apoptosis, cell cycle arrest, and sensitivity to immunotherapy. The pan-cancer analysis reveals a significant upregulation of LRRC59 in pan-cancer, and its overexpression is correlated with unfavorable prognosis in cancer patients. LRRC59 is negatively correlated with immune cell infiltration, tumor purity estimation, and immune checkpoint genes. Finally, the validation in HCC demonstrates LRRC59 is significantly overexpressed in cancer tissue and cell lines, and its knockdown inhibits cell proliferation and migration, promotes cell apoptosis, induces cell cycle arrest, and enhances the sensitivity to immunotherapy in HCC cells. LRRC59 emerges as a novel potential prognostic biomarker across malignancies, offering promise for anti-cancer drugs and immunotherapy.

Application and Quality of Model-Based Meta-Analysis in Pharmaceutical Research: A Systematic Cross-Sectional Analysis and Practical Considerations.

Model-based meta-analysis (MBMA) can be used in assisting drug development and optimizing treatment in clinical practice, potentially reducing costs and accelerating drug approval. We aimed to assess the application and quality of MBMA studies. We searched multiple databases to identify MBMA in pharmaceutical research. Eligible MBMA should incorporate pharmacological concepts to construct mathematical models and quantitatively examine and/or predict drug effects. Relevant information was summarized to provide an overview of the application of MBMA. We used AMSTAR-2 and PRISMA 2020 checklists to evaluate the methodological and reporting quality of included MBMA, respectively. A total of 143 MBMA studies were identified. MBMA was increasingly used over time for one or more areas: drug discovery and translational research (n = 8, 5.6%), drug development decision making (n = 42, 29.4%), optimization of clinical trial design (n = 46, 32.2%), medication in special populations (n = 15, 10.5%), and rationality and safety of drug use (n = 71, 49.7%). The included MBMA covered 17 disease areas, with the top three being nervous system diseases (n = 19, 13.2%), endocrine/nutritional/metabolic diseases (n = 17, 11.8%), and neoplasms (n = 16, 11.1%). Of these MBMA studies, 138 (96.5%) were rated as very low quality. The average rate of compliance with PRISMA was only 51.4%. Our findings suggested that MBMA was mainly used to evaluate the efficacy and safety of drugs, with a focus on chronic diseases. The methodological and reporting quality of MBMA should be further improved. Given AMSTAR-2 and PRISMA checklists were not specifically designed for MBMA, adapted assessment checklists for MBMA should be warranted.

Prophylactic Antibiotics Delivered Via the Respiratory Tract to Reduce Ventilator-Associated Pneumonia: A Systematic Review, Network Meta-Analysis, and Trial Sequential Analysis of Randomized Controlled Trials

Objectives: To assess the effects of antibiotics delivered via the respiratory tract in preventing ventilator-associated pneumonia (VAP). Data Sources: We searched PubMed, Scopus, the Cochrane Library, and ClinicalTrials.gov for studies published in English up to October 25, 2023. Study Selection: Adult patients with mechanical ventilation of over 48 h and receiving inhaled or instilled antibiotics (with control group) to prevent VAP were included. Data Extraction: Two independent groups screened studies, extracted the data, and assessed the risk of bias. The Grading of Recommendations Assessment, Development, and Evaluation approach was used to assess the certainty/quality of the evidence. Results of a random-effects model were reported for overall and predefined subgroup meta-analyses. The analysis was primarily conducted on randomized controlled trials, and observational studies were used for sensitivity analyses. Data Synthesis: Seven RCTs with 1445 patients were included, of which six involving 1283 patients used nebulizers to deliver antibiotics. No obvious risk of bias was found among the included RCTs for the primary outcome. Compared with control group, prophylactic antibiotics delivery via the respiratory tract significantly reduced the risk of VAP (risk ratio [RR], 0.69 [95% CI, 0.53–0.89]), particularly in subgroups where aminoglycosides (RR, 0.67 [0.47–0.97]) or nebulization (RR, 0.64 [0.49–0.83]) were used as opposed to other antibiotics (ceftazidime and colistin) or intratracheal instillation. No significant differences were observed in mortality, mechanical ventilation duration, ICU and hospital length of stay, duration of systemic antibiotics, need for tracheostomy, and adverse events between the two groups. Results were confirmed in sensitivity analyses. Conclusions: In adult patients with mechanical ventilation for over 48 h, prophylactic antibiotics delivered via the respiratory tract reduced the risk of VAP, particularly for those treated with nebulized aminoglycosides.

Emergence of chambers in the Turkish history: the case of Dersaadet Chamber of Commerce (DCC) as a public-agent meta-organization, 1882–1929

Purpose Building on previous historical works, this study aims to develop a framework to represent chambers as meta-organizations and present the case of Dersaadet Chamber of Commerce (DCC), based on this framework, during its emergence and evolution in the late 19th and early 20th centuries. Design/methodology/approach In the study, a historical narrative was constructed from primary and secondary data. To complement data collected from the archives a systematic content analysis was used to explore the discourse of the chamber within its serial magazine. Findings It was found that the first chamber of the Ottoman Empire, DCC, was established according to the public law model as an extension of the economic context and the guild order, and it was observed that it increasingly conformed to this model between 1882 and 1929. Originality/value In this study, chamber models are examined for the first time according to the designated features of meta-organizational forms, built on the historical work on chambers. The case of DCC suggested that it adopted a public law model and displayed much continuity, even when significant transitions were observed during the modernization process from Ottoman Empire to Turkish Republic.

Blockchain for Organ Transplantation: A Survey

As blockchain becomes more widely used, a growing number of application fields are becoming interested in blockchain to benefit from its decentralised nature, invariability, security, transparency, quick transaction capabilities, and cost-effectiveness. Blockchain has a wide range of applications and uses in healthcare. Distributed ledger technology facilitates the secure transfer of patient medical records, manages the medicine supply chain, and creates an efficient, transparent, safe, and effective way of communicating data across global healthcare. The organ transplantation process (OTP) is one of the healthcare areas that benefit from the use of such technology to make its process more secure and transparent. In this article, we put forward a systematic literature review analysis on the application of blockchain to the OTP. Additionally, we address and highlight the barriers and challenges that arise while using blockchain technology for the OTP. We also offer some suggestions for future developments that would enhance blockchain’s implementation in the OTP domain.

Assessing the German Act on Corporate Due Diligence Obligations in Supply Chains: a perspective from the smallholder cocoa farmer

This research examines the potential outputs, outcomes, and impacts of the German Act on Corporate Due Diligence Obligations in Supply Chains (LkSG) on the smallholder cocoa farmers in West Africa. The study primarily relies on a literature review and an impact pathway to conduct a systematic analysis to identify the potential effects of the LkSG on smallholder cocoa farmers. The findings indicate that some, but not all of the risks addressed by the LkSG align with those faced by smallholder cocoa farmers and their families. Additionally, the research also reveals weaknesses, particularly in managing environmental risks, which the LkSG does not adequately cover. Our findings show that in the short- and medium-term, the LkSG has no potential effects on smallholder cocoa farmers. Furthermore, the potential positive impacts of the law on smallholder cocoa farmers will take a long time to realize, as the LkSG considers primarily tier-1 suppliers. Companies in Germany might reassess their supply chains to strive for an LkSG-risk-free supply chain, which could in the long term have sustained impacts on smallholder cocoa farmers. However, we recommend a comprehensive risk analysis of the cocoa supply chain to enhance the human rights of cocoa farmers.

M2WISH: An easy and efficient protocol for whole‐mount mRNAin situ hybridization that allows 3D cell resolution of gene expression in Arabidopsis thaliana

SUMMARYGene expression analysis is essential for understanding the mechanisms involved in plant development. Here, we developed M2WISH, a protocol based on MicroWave treatment for Wholemount mRNA In Situ Hybridization in Arabidopsis. By permeabilizing tissues without damaging cellular organization this protocol results in high and homogeneous hybridization yields that enable systematic analysis of gene expression dynamics. Moreover, when combined with cellular histochemical staining, M2WISH successfully provides a cellular resolution of gene expression. Thus, we demonstrate the robustness of M2WISH with 10 genes on roots, aerial meristems, leaves, and embryos in the seed. We applied M2WISH to study the spatial dynamics of WUSCHEL (WUS) and CLAVATA3 (CLV3) expression during in vitro meristematic conversion of roots into shoot apical meristems. Thus, we showed that shoot apical meristems could arise from two different types of root structures that differed by their CLV3 gene expression patterns. We constructed 3D cellular representations of WUS and CLV3 gene co‐expression pattern and stressed the variability inherent to meristem conversion. Thus, this protocol generates a large amount of data on the localization of gene expression, which can be used to model complex systems.

OPTIMIZATION OF ORGANIZATIONAL PROCESSES IN CIVIL ENGINEERING USING LOGISTICS MODELS

Purpose. In accordance with the analyzed problem, there is a need for a more detailed study and justification of the benefits of implementing logistics models to optimize organizational processes in civil engineering. Methodology. To achieve this goal, the article conducts a systematic analysis of organizational processes in civil engineering in terms of logistics approaches. Current trends in the industry, regulations and scientific developments are considered, risks and barriers that may arise when implementing logistics models in the construction industry are analyzed, practical examples of possible use of logistics concepts in civil engineering at different stages of work and when using specific building materials are offered, ways to overcome barriers and stimulate the implementation of logistics models are provided, and an integrated approach to optimizing organizational processes in civil engineering is proposed. Findings. The study has shown that the introduction of logistics models in civil engineering can lead to: significant efficiency improvements, shorter construction time, reduced costs for materials and transportation, improved quality of construction work, reduced environmental impact, rational use of resources, reduced construction waste, increased competitiveness, improved safety, and increased project profitability. Originality. The key principles of development and functioning of logistics models in the context of civil construction are identified: the principle of integration: combining all stages of the construction process into a single logistics system, the principle of resource optimization: minimizing the cost of materials, transport, labor, the principle of flexibility and adaptability: the ability to adapt the logistics model to changing construction conditions. Practical value. The results of the study indicate that the introduction of logistics models in civil engineering is a relevant and promising area for optimizing processes in this sector. The use of logistics can contribute to effective resource management, increase productivity and reduce costs, which is noted by the practical importance of this study.

Data quality analysis after hyperspectral LiDAR sequentially mapping trees

Abstract. Light detection and ranging (LiDAR), as an innovative remote sensing tool, not only captures target reflectance but also provides its morphological parameters. Traditional single/multi-band LiDAR and multispectral LiDAR (MSL) are presently employed in applications such as 3D modeling and plant biochemical parameter inversion albeit with effectiveness limited. Moreover, hyperspectral LiDAR (HSL) distinguished by its expanded array of spectral detection channels and enhanced spectral resolution, has proven more effective in meeting these requirements and also exhibits superior capabilities in both feature and land cover classification tasks. Nevertheless, point clouds acquired through HSL frequently exhibit quality deficiencies, including uneven density and excessive noise. Meanwhile, there exists a notable absence of technical specifications and operational standards governing the measurement protocols for HSL systems globally. To address this gap, this study constructed a systematic analysis framework of data quality in hyperspectral point clouds and endeavors to qualitatively analyse 30 tree point clouds continuously scanned with Finnish Geospatial Research Institute (FGI) 8-band hyperspectral laser scanner. Furthermore, this research validated the theoretical feasibility of employing the 8-band HSL system for inversion processes aimed at quantifying chlorophyll leaf content. Apart from detecting the time-varying patterns of reflectance within birch canopy point clouds, the results of this study also effectively pinpointed the band exhibiting heightened noise level of the HSL system, demonstrating the efficacy of our proposed quality analysis methodology. The endeavor presented in this study can serve as a cornerstone for advancing hyperspectral LiDAR across a diverse array of related remote sensing and earth observation applications.

Rescue and recovery: The COVID and post-COVID responses of apprenticeship systems

ABSTRACT Few changes have been so abruptly disruptive to apprenticeships worldwide as the global COVID outbreak from early 2020 onwards. Because apprenticeships involve experience in workplaces (normally via employment), as well as participation in education systems, the effects were especially serious. There was extra urgency to policy responses because apprenticeships are disproportionately, and in some countries, exclusively, undertaken by young people. There were no worldwide ‘answers’ as to what to do, as apprenticeship systems vary greatly among countries. The paper examines the development of apprenticeship-related measures in several countries worldwide, with a particular focus on Australia and England. The paper uses statistical data, government announcements, guidance from stakeholders and officials, and also a systematic analysis of presentations by leading country experts at an online international apprenticeship conference in May 2021. Reflecting on common concerns on apprenticeship system, the paper critiques and analyses the effects and potential effects of COVID and post-COVID measures on apprenticeship systems.

Well Selection for CO2 Huff-n-Puff in Unconventional Oil Reservoirs Based on Improved Fuzzy Method

The implementation of CO2 huff-n-puff in unconventional oil reservoirs represents a green development technology that integrates oil recovery and carbon storage, emphasizing both efficiency and environmental protection. A rational well selection method is crucial for the success of CO2 huff-n-puff development. This paper initially identifies eight parameters that influence the effectiveness of CO2 huff-n-puff development and conducts a systematic analysis of the impact of each factor on development effectiveness. A set of factors for well selection decisions is established with seven successful CO2 huff-n-puff cases. Subsequently, the influencing factors are classified into positive, inverse, and moderate indicators. By using an exponential formulation, a method for calculating membership degrees is calculated to accurately represent the nonlinearity of each parameter’s influence on development, resulting in a dimensionless fuzzy matrix. Furthermore, with the oil exchange ratio serving as a pivotal parameter reflecting development effectiveness, recalibration of weighting factors is performed in conjunction with the dimensionless fuzzy matrix. The hierarchical order of weighting factors, from primary to secondary, is as follows: porosity, reservoir temperature, water saturation, formation pressure, reservoir thickness, crude oil density, crude oil viscosity, and permeability. The comprehensive decision factor and oil exchange ratio exhibit a positive correlation, affirming the reliability of the weighting factors. Finally, utilizing parameters of the Ordos Basin as a case study, the comprehensive decision factor is calculated, with a value of 0.617, and the oil exchange ratio is predicted as 0.354 t/t, which falls between the Chattanooga and Eagle Ford reservoirs. This approach, which incorporates exponential membership degrees and recalibrated weighting factors derived from actual cases, breaks the limitations of linear membership calculation methods and human factors in expert scoring methods utilized in existing decision-making methodologies. It furnishes oilfield decision-makers with a swifter and more precise well selection method.