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Group discussions improve reliability and validity of rated categories based on qualitative data from systematic review

The number of literature reviews in the fields of ecology and conservation has increased dramatically in recent years. Scientists conduct systematic literature reviews with the aim of drawing conclusions based on the content of a representative sample of publications. This requires subjective judgments on qualitative content, including interpretations and deductions. However, subjective judgments can differ substantially even between highly trained experts that are faced with the same evidence. Because classification of content into codes by one individual rater is prone to subjectivity and error, general guidelines recommend checking the produced data for consistency and reliability. Metrics on agreement between multiple people exist to assess the rate of agreement (consistency). These metrics do not account for mistakes or allow for their correction, while group discussions about codes that have been derived from classification of qualitative data have shown to improve reliability and accuracy. Here, we describe a pragmatic approach to reliability testing that gives insights into the error rate of multiple raters. Five independent raters rated and discussed categories for 23 variables within 21 peer-reviewed publications on conservation management plans. Mistakes, including overlooking information in the text, were the most common source of disagreement, followed by differences in interpretation and ambiguity around categories. Discussions could resolve most differences in ratings. We recommend our approach as a significant improvement on current review and synthesis approaches that lack assessment of misclassification.

Concise Syntheses of Lycojapomine Alkaloids Enabled by Radical Dearomatization of a Pyrrole

Dynamic CYP2E1 expression and metabolic activity changes in male rats during immune liver injury and sex differences in alcohol metabolism

Previous studies conducted by our team have demonstrated that CYP2E1 expression is downregulated during Bacillus Calmette-Guérin (BCG)-induced immune liver injury (hepatitis). However, the dynamic changes in CYP2E1 metabolic activity during the acute, chronic, and recovery phases of hepatitis remain unclear. This study developed a non-invasive approach using a breath alcohol analyzer to assess CYP2E1 metabolic activity through alcohol metabolism and examined sex-based differences in alcohol metabolism in rats. Using a BCG-induced male rat hepatitis model, we investigated the dynamic changes in CYP2E1 metabolic activity at different stages of hepatitis and explored the underlying mechanisms. The results indicated that the breath alcohol analysis method exhibited high precision, linearity, and reproducibility in assessing CYP2E1 metabolic activity. CYP2E1 metabolic activity and protein expression displayed an induction trend with increased alcohol intake (P < 0.05). Female rats exhibited significantly higher CYP2E1 metabolic activity compared to males (P < 0.05), indicating significant sexual dimorphism. On day 6 post-BCG stimulation, CYP2E1 metabolic activity was most severely impaired (P < 0.05). Notably, alterations in metabolic activity were detected earlier and were more pronounced than changes in protein expression. Similar dynamic changes were observed in the hepatic NF-κB inflammatory pathway and the MAPK oxidative stress pathway. In conclusion, the breath alcohol analysis method is an effective tool for assessing CYP2E1 metabolic activity in rats. CYP2E1 can be significantly induced following a single high dose of alcohol, with female rates exhibiting greater metabolic activity compared to males. CYP2E1 metabolic activity showed the most notable impairment on day 6 post-BCG, with gradual recovery observed at days 10 and 14, and parallel changes observed in inflammatory and MAPK pathways. The recovery of CYP2E1 protein expression occurred after 14 days, which was later than that of the metabolic activity.

The use of ultrasonography in the diagnosis and management of Acute Kidney Injury and other forms renal dysfunction in the paediatric population: Systematic review protocol

Background Acute kidney injury remains one of the most prevalent complications in hospitalised patients, with an especially high incidence in the paediatric population. Its diverse pathophysiological aetiologies present significant challenges in its clinical diagnosis. Relying solely on serum creatinine levels and urine output measurements for diagnosis has been shown to be inadequate, particularly for early detection of the disease. The wide range of disease manifestations highlights the importance of exploring diagnostic techniques that can identify patients at risk before disease progression occurs, thereby allowing for the implementation of timely corrective measures. Point-of-care ultrasound is a valuable technique with the potential to aid in the early identification of at-risk patients. Objective To describe ultrasound parameters associated with the development of acute kidney injury or renal dysfunction in the hospitalised paediatric patient, and to examine their association with its development. This will include an analysis of the specific ultrasound features that may predict or be associated with the occurrence of acute kidney injury, as well as their potential role in identifying at-risk paediatric patients, facilitating timely interventions to mitigate further kidney damage. Methods A systematic review of existing literature will be performed to assess ultrasound modalities currently associated with the diagnosis of acute kidney injury in the paediatric population. The protocol for this review has been registered with PROSPERO (CDR42024547614) and was developed in accordance with the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA). A comprehensive search of scientific literature will be conducted across PubMed, Scopus, Cochrane Library, and CINAHL databases. The data search will be performed independently by the primary researchers (GL and NA), with any disagreements resolved by the third and fourth researchers (MK, PMC). The COVIDENCE Systematic Review Software® 2024 will be utilised for article exportation, review, and data extraction. The QUADAS-2 tool will be applied to assess the risk of bias in the diagnostic accuracy of the studies included in the review. Conclusion This protocol outlines a systematic review designed to evaluate the application of ultrasonography in identifying paediatric patients at risk of developing acute kidney injury and other forms of renal dysfunction. The review will critically assess the effectiveness of ultrasound techniques, including point-of-care ultrasound, in identifying acute kidney injury in children, with a particular emphasis on early detection. The findings from this review will contribute to a deeper understanding of the role of ultrasonography in clinical practice, with the potential to improve patient outcomes through earlier intervention. The ultrasound techniques identified, including Doppler imaging and flow measurements, will be employed in a subsequent prospective study within the paediatric population to evaluate their role, sensitivity, and accuracy.

Photoinduced Copper-Catalyzed Enantioselective Allylic C(<i>sp</i>³)–H Oxygenation of Acyclic Terminal Olefins Enabled by SphenBOX

Improving the performance of the coffee supply chain using integrating fuzzy MCDM and simulation methods

Coffee is one of the drinks that are consumed worldwide. The global coffee beans industry is currently facing several challenges, including The COVID19 pandemic’s long-term effects on their supply chains (SCs), adverse weather conditions affecting major coffee-producing regions, escalating price dynamics, and the increased in transportation costs. Jordan significantly relies on coffee imports, a critical agricultural product that constitutes an important part of local trade. Due to the lack of previous studies, the research aims to evaluate the current SC and improve Jordan’s coffee SC performance by reducing lead time and shipping cost. The research first uses the combined Fuzzy Analytic Hierarchy Process (FAHP) and The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the supplier and choose the best suppliers based on established criteria. Then, the research proposes an analysis with the goal of enhancing the efficiency of Jordan’s coffee SC by applying Discrete Event Simulation (DES). Real company data is utilized to study, apply and evaluate the methodology used. The decision-making process employ decision makers and expert opinion input, providing a comprehensive and balanced evaluation of suppliers. Different scenarios are evaluated and compared based on the integrations of the FMCDM results in the simulation model. The findings identify the best and least favorable suppliers, highlighting Ethiopia’s leadership in several indicators. The outcomes suggest reducing lead time and shipping costs, investing in technology, and establishing a culture of continuous improvement to improve efficiency, stability, and adapt to market conditions. The research provides a comprehensive analysis of the current state of the coffee SC and suggests opportunities for development. Finally, recommendations to improve the current coffee SC in Jordan and directions for future research are discussed.

Retraction: Selective inhibition of carbonic anhydrase IX over carbonic anhydrase XII in breast cancer cells using benzene sulfonamides: Disconnect between activity and growth inhibition

Topochemical Synthesis, <i>micro</i>-Electron Diffraction (3D ED), and Electron Beam-Initiated Topotactic Dimer Splitting of cis,syn-Thymine Dimer Crystals

Accuracy of bedside ultrasound for predicting resting energy expenditure in critically ill patients: A feasibility study

Objectives This study aimed to assess the accuracy of bedside ultrasound in predicting resting energy expenditure (REE) in critically ill patients. Methods We studied critically ill patients admitted to our hospital’s ICU between November 2021 and March 2023 who underwent REE, cardiac ultrasound, and muscle ultrasound evaluations. General demographic information and ultrasound data (including cardiac output, biceps brachii and quadriceps femoris thickness) were collected to estimate REE (REE-US). Simultaneously, REE was measured using indirect calorimetry (REE-IC). Correlations between REE-US and established equations (Harris-Benedict, Penn State University (PSU), Mifflin, ASPEN standard) as well as REE-IC were evaluated. Additionally, the feasibility and application of ultrasound for REE prediction across different disease conditions in critically ill patients were analysed. Results Ninety-seven critically ill patients with 124 ultrasound measurements were included. The Penn State University formula showed the highest correlation with REE-IC (r = 0.779, p &lt; 0.001), followed by ultrasound estimation (r = 0.668, p &lt; 0.001). Correlation between the PSU formula and REE-IC remained robust across subgroups. However, REE-US correlation was weaker in patients with low BMI (BMI &lt; 20 kg/m2) (r = 0.521, p = 0.009) but comparable to the PSU formula in normal and high BMI groups (BMI 20–30 kg/m2: r = 0.682 vs. r = 0.714, p = 0.5743; BMI &gt; 30 kg/m2: r = 0.712 vs. r = 0.882, p = 0.1294). In subgroup analysis, REE-US performed similarly to the PSU formula in the sepsis subgroup (r = 0.612 vs r = 0.661, p = 0.6852) and ICU patients in the late period of the acute phase (r = 0.675 vs r = 0.751, p = 0.2762). Conclusions The Penn State University formula demonstrated the strongest correlation with REE-IC in critically ill patients. Ultrasound may replace the PSU formula in non-mechanically ventilated patients with unavailable gas measurement parameters. However, ultrasound-derived REE is less predictive in patients with low BMI or during the early acute phase of critical illness. Further research is warranted to refine ultrasound application in these populations.

Light-Driven Lithium Extraction from Mixtures of Alkali Cations Using an Azobipyridine Ligand

Digital study and correlation analysis of sagittal balance parameters in adolescents with idiopathic scoliosis: A comparative study with healthy adolescents

Purpose This study aimed to compare sagittal spinal parameters between healthy adolescents and those with adolescent idiopathic scoliosis (AIS), identify factors influencing disease progression, and provide insights for optimizing preoperative assessments. Methods Sagittal full-spine radiographs from 40 healthy adolescents and 41 AIS patients (aged 10–18 years) were analyzed using Mimics 21.0 software. Fifteen parameters, including spinopelvic angle (SPA), thoracic kyphosis (TK), lumbar lordosis (LL), and pelvic tilt (PT), were measured. Statistical analyses included logistic regression to identify predictors of AIS and sex-based subgroup comparisons. Results SPA was significantly higher in AIS patients compared to controls (median: 176.48° vs. 169.64°, P = 0.008) and emerged as the sole predictor of AIS (odds ratio = 1.568, 95% CI = 1.129–2.177, P = 0.007). Sex differences revealed higher spinal tilt (ST) in female AIS patients (P = 0.034), while males exhibited elevated TK (P = 0.006) and SPA (P = 0.002). Correlations among parameters highlighted strong associations between LL and pelvic incidence (PI, r = 0.682) and between SPA and pelvic tilt (PT, r=−0.537). Conclusion Increased SPA is a critical indicator of AIS, necessitating preoperative evaluation of sagittal spinopelvic alignment. Female patients require heightened attention to spinal tilt. Future studies should expand sample sizes and integrate multi-planar analyses to refine clinical strategies.

Efficient Aminations of Aryl Halides by a Cu(II) Catalyst

Research on road surface damage detection based on SEA-YOLO v8

Road damage detection is of great significance to traffic safety and road maintenance. However, the existing target detection technology still has shortcomings in accuracy, real-time and adaptability. In order to meet this challenge, this study constructed SEA-YOLO v8 model for road damage detection. Firstly, the SBS module is constructed to optimize the computational complexity, achieve real-time target detection under limited hardware resources, successfully reduce the model parameters, and make the model more lightweight; Secondly, we integrate the EMA attention mechanism module into the neck component, enabling the model to utilize feature information from different layers, enabling the model to selectively focus on key areas and improve feature representation; Then, an adaptive attention feature pyramid structure is proposed to enhance the feature fusion capability of the network; Finally, lightweight shared convolutional detection head (LSCD-Head) is introduced to improve feature representation and reduce the number of parameters. The experimental results on the RDD2022 dataset show that the SEA-YOLO v8 model has achieved 63.2% mAP50. The performance is better than yolov8 model and mainstream target detection model. This shows that in complex urban traffic scenarios, the model has high detection accuracy and adaptability, can accurately locate and detect road damage, save manpower and material resources, provide guidance for road damage assessment and maintenance, and promote the sustainable development of urban roads.

The Binding Affinities of Serum Proteins to Nanoparticles

Microbiota and Postmenopause: The resilience of intestinal bacteria in the face of female hormonal aging

Background Female aging is characterized by a decline in ovarian function until the establishment of the post-menopausal state. Other research lines seek to understand how the gut microbiota contributes to these diseases at all stages of life, including post-menopause, and its potential to be used as an ally to promote healthy aging and as a biomarker that can be associated with the pre-and post-menopausal period. Methods Post-menopausal women (n = 44) aged between 45 and 60, divided into Group A n = 34 (up to 10 years postmenopause) and Group B n = 10 (more than 10 years postmenopause) had fecal samples analyzed by metabarcoding using the 16S rRNA gene, and bacterial composition and diversity were compared between the two groups. Results Both groups showed high diversity in microbiota according to Shannon’s index but with no difference. Simpson’s index indicated that post-menopausal women over 10 had a more diverse microbiota with lower species dominance (p-value 0.04). The predominant organisms were Phyla Firmicutes, Bacteroidota, Proteobacteria, and Actinobacteria; Families Lachnospiraceae, Bacteroidaceae, Ruminococcaceae, Prevotellaceae; Genera Bacteroides, Prevotella, Faecalibacterium, Agathobacter and Dialister. There were no differences between the groups. Conclusion Women who had been post-menopausal for ten years or more had microbiota with greater diversity and less dominance of taxa. There was no difference between the ten most enriched taxa in each group. Our results indicated that the fecal Microbiota of these women showed a uniform and equitable distribution of the organisms inferred for the groups, regardless of the time elapsed since postmenopause.

Band Gap Engineering and Metastable Phase Discovery in Cu₂BaSnS_4–<i>x</i>Se_<i>x</i> Nanocrystals via Topotactic Anion Exchange

Cost-effectiveness analysis of two inhaled antibiotics for stable Bronchiectasis with Pseudomonas aeruginosa infections in China

Objective To evaluate the cost-effectiveness of two available options for inhaled antibiotic treatment for patients with Bronchiectasis (BE) with Pseudomonas aeruginosa (PA) infections from the perspective of China’s healthcare system. Methods A four-state Markov model was developed over a one-year horizon to simulate the cost-effectiveness of two inhaled antibiotic strategies: Tobramycin inhalation solution (TIS) versus nebulized colistimethate sodium (CMS). The inputs for the model were derived from phase III clinical trials and published literature, with cost data were sourced from public and real-world databases, etc. The incremental cost-effectiveness ratio (ICER) was assessed, setting the willingness-to-pay threshold at one times the per capita GDP of China. Scenario and sensitivity analyses were performed to explore the impact of uncertainties in input parameters. Results Over a one-year period, TIS was found to dominate CMS, resulting in a cost saving of CNY 41,109.53 (USD 5,689.27) and an increase of 0.0048 quality-adjusted life years (QALYs) per patient. Sensitivity analyses confirmed the robustness of these findings, which remained consistent under various scenarios. Conclusions TIS reduces healthcare costs and improves clinical outcomes compared to CMS in managing BE with PA infections in China. This study supports the inclusion of TIS in clinical guidelines for managing BE with PA infections, considering both economic benefits and health outcomes.

Post-harvest treatment of wild-simulated ginseng under climate-smart environmental conditions

Wild-simulated ginseng (WSG; Panax ginseng C.A. Meyer) is prized for its unique ginsenoside profile and medicinal properties; however, traditional cultivation faces challenges, such as declining survival rates and prolonged growth periods. We aimed to develop an enhanced post-harvest treatment using climate-smart conditions to improve survival rates, boost root mass, and preserve the characteristic ginsenoside profile of WSG. Three-year-old WSG roots were transplanted and cultivated in a controlled smart facility in regulated light and irrigation conditions for five months using premium ginseng soil, a certified organic ginseng soil medium. Growth performance was monitored and ginsenoside profiles were analysed via ultra-performance liquid chromatography. Post-treatment, WSG exhibited a 2.5-fold increase in root weight and an overall survival rate of 97%. Total ginsenoside content reached 10.458 mg/g dried ginseng, with notably high levels of Re (7.716 mg/g) and the presence of rare compounds, such as Compound K and Rg3. The root-to-shoot ratio exceeded 1.23, indicating efficient resource allocation. These results demonstrate that climate-smart post-harvest treatment effectively enhances root development and maintains the medicinal quality of WSG, offering a promising strategy to overcome the limitations of conventional cultivation and improve its commercial viability.

Near-Infrared Light-Driven Condensation Using Branched Two-Photon-Absorbing Organic Photocatalysts with Viscosity-Dependent Properties

DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome

As one of the most critical post-replication modifications, N6-methylation (6mA) at adenine residue plays an important role in a variety of biological functions. Existing computational methods for identifying 6mA sites across large genomic regions tend to fall short in either accuracy or computational efficiency. To address this, we introduce DeepRice6mA, a sophisticated comprehensive predictive tool for identifying rice 6mA sites, using a deep learning approach that incorporates ensemble strategies from one-hot encoding and 3-kmer feature embedding. The proposed model, labeled DeepRice6mA, reaches state-of-the-art results compared to current approaches, with 10-fold cross-validation scores of 98% for accuracy, 98% for sensitivity, 98% for specificity, a Matthew’s correlation coefficient (MCC) of 0.96, and an area under the receiver operating characteristic curve (AUC) of 0.99. We anticipate that DeepRice6mA will significantly enhance our understanding of DNA methylation and its implications for biological processes and disease states.