bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neoadjuvant chemotherapy with or without camrelizumab in resectable esophageal squamous cell carcinoma: the randomized phase 3 ESCORT-NEO/NCCES01 trial
Authors: Qin Jianjun , Xue Liyan , Hao Anlin , Guo Xiaofeng , Jiang Tao , Ni Yunfeng , Liu Shuoyan , Chen Yujie , Jiang Hongjing , Zhang Chen , Kang Mingqiang , Lin Jihong , Li Hecheng , Li Chengqiang , Tian Hui , Li Lin , Fu Junke , Zhang Yong , Ma Jianqun , Wang Xiaoyuan , Fu Maoyong , Yang Hao , Yang Zhaoyang , Han Yongtao , Chen Longqi , Tan Lijie , Dai Tianyang , Liao Yongde , Zhang Weiguo , Li Bin , Chen Qixun , Guo Shiping , Qi Yu , Wei Li , Li Zhigang , Tian Ziqiang , Kang Xiaozheng , Zhang Ruixiang , Li Yong , Wang Zhen , Chen Xiankai , Hou Zhiguo , Zheng Rongrong , Zhu Wenqing , He Jie , Li Yin 
Published: July 2024

AbstractRecent single-arm studies involving neoadjuvant camrelizumab, a PD-1 inhibitor, plus chemotherapy for resectable locally advanced esophageal squamous cell carcinoma (LA-ESCC) have shown promising results. This multicenter, randomized, open-label phase 3 trial aimed to further assess the efficacy and safety of neoadjuvant camrelizumab plus chemotherapy followed by adjuvant camrelizumab, compared to neoadjuvant chemotherapy alone. A total of 391 patients with resectable thoracic LA-ESCC (T1b-3N1-3M0 or T3N0M0) were stratified by clinical stage (I/II, III or IVA) and randomized in a 1:1:1 ratio to undergo two cycles of neoadjuvant therapy. Treatments included camrelizumab, albumin-bound paclitaxel and cisplatin (Cam+nab-TP group; n = 132); camrelizumab, paclitaxel and cisplatin (Cam+TP group; n = 130); and paclitaxel with cisplatin (TP group; n = 129), followed by surgical resection. Both the Cam+nab-TP and Cam+TP groups also received adjuvant camrelizumab. The dual primary endpoints were the rate of pathological complete response (pCR), as evaluated by a blind independent review committee, and event-free survival (EFS), as assessed by investigators. This study reports the final analysis of pCR rates. In the intention-to-treat population, the Cam+nab-TP and Cam+TP groups exhibited significantly higher pCR rates of 28.0% and 15.4%, respectively, compared to 4.7% in the TP group (Cam+nab-TP versus TP: difference 23.5%, 95% confidence interval (CI) 15.1–32.0, P < 0.0001; Cam+TP versus TP: difference 10.9%, 95% CI 3.7–18.1, P = 0.0034). The study met its primary endpoint of pCR; however, EFS is not yet mature. The incidence of grade ≥3 treatment-related adverse events during neoadjuvant treatment was 34.1% for the Cam+nab-TP group, 29.2% for the Cam+TP group and 28.8% for the TP group; the postoperative complication rates were 34.2%, 38.8% and 32.0%, respectively. Neoadjuvant camrelizumab plus chemotherapy demonstrated superior pCR rates compared to chemotherapy alone for LA-ESCC, with a tolerable safety profile. Chinese Clinical Trial Registry identifier: ChiCTR2000040034.
Chromosome-level genome assembly of Helwingia omeiensis: the first genome in the family Helwingiaceae
Authors: Chen Yanyu , Feng Landi , Lin Hao , Liu Jianquan , Hu Quanjun 
Published: July 2024

AbstractHelwingia, a shrub of the monotypic cosmopolitan family Helwingiaceae, is distinguished by its inflorescence, in which flowers are borne on the midrib of the leaf—a trait not commonly observed in related plant families. Previous studies have investigated the development of this unusual structure using comparative anatomical methods. However, the scarcity of genomic data has hindered our understanding of the origins and evolutionary history of this uncommon trait at the molecular level. Here, we report the first high-quality genome of the family Helwingiaceae. Assembled using HiFi sequencing and Hi-C technologies, the genome of H. omeiensis is anchored to 19 chromosomes, with a total length of 2.75 Gb and a contig N50 length of 6.78 Mb. The BUSCO completeness score of the assembled genome was 98.2%. 53,951 genes were identified, of which 99.7% were annotated in at least one protein database. The high-quality reference genome of H. omeiensis provides an essential genetic resource and sheds light on the phylogeny and evolution of specific traits in the family Helwingiaceae.
1 Million Segmented Red Blood Cells With 240 K Classified in 9 Shapes and 47 K Patches of 25 Manual Blood Smears
Authors: Elsafty Ahmed , Soliman Ahmed , Ahmed Yomna 
Published: July 2024

AbstractAround 20% of complete blood count samples necessitate visual review using light microscopes or digital pathology scanners. There is currently no technological alternative to the visual examination of red blood cells (RBCs) morphology/shapes. True/non-artifact teardrop-shaped RBCs and schistocytes/fragmented RBCs are commonly associated with serious medical conditions that could be fatal, increased ovalocytes are associated with almost all types of anemias. 25 distinct blood smears, each from a different patient, were manually prepared, stained, and then sorted into four groups. Each group underwent imaging using different cameras integrated into light microscopes with 40X microscopic lenses resulting in total 47 K + field images/patches. Two hematologists processed cell-by-cell to provide one million + segmented RBCs with their XYWH coordinates and classified 240 K + RBCs into nine shapes. This dataset (Elsafty_RBCs_for_AI) enables the development/testing of deep learning-based (DL) automation of RBCs morphology/shapes examination, including specific normalization of blood smear stains (different from histopathology stains), detection/counting, segmentation, and classification. Two codes are provided (Elsafty_Codes_for_AI), one for semi-automated image processing and another for training/testing of a DL-based image classifier.
A comprehensive phenotypic and genotypic evaluation of Spanish groundnuts from diverse crosses to identify superior and stable donors for fresh seed dormancy
Authors: Rani Kirti , Gangadhara K. , Ajay B. C. , Kona Praveen , Kumar Narendra , Bera S. K. 
Published: July 2024

AbstractBreeding high yielding groundnut cultivars with 2–3 weeks of fresh seed dormancy, particularly in Spanish-type cultivars, enhances the sustainability of agriculture in groundnuts. In this context, we conducted a comprehensive phenotypic and genotypic evaluation of advanced breeding lines developed in the genetic background of Spanish types. By employing multi-phenotyping and marker data, we identified PBS 15044, 16004, 16013, 16015, 16016, 16017, 16020, 16021, 16026, 16031, 16035, 16037, 16038, 16039, 16041, and 16042 with 2–3 weeks dormancy (> 90%).The various parametric and non-parametric estimates identified the stable fresh dormant genotypes with one or more superior economic trait. PBS 16021, 15044, 16038, and 16039 identified with high hundred pod weight (HPW) were also reported having high intensity of dormancy (> 90% for up to 3 weeks); PBS 15044, 16016, PBS 16038 and PBS 16039 with high hundred kernel weight (HKW) also reported with up to 3 weeks fresh seed dormancy; and PBS 16013, 16031, and 16038 with up to 3 weeks fresh seed dormancy had high shelling percentage (SP). They can be used to develop lines with the desired level of dormancy, and high yields, by designing appropriate breeding strategies.
Modeling and optimization of dyeing process of polyamide 6 and woolen fabrics with plum-tree leaves using artificial intelligence
Authors: Shahmoradi Ghaheh Fatemeh , Razbin Milad , Tehrani Majid , Zolfipour Aghdam Vayghan Leila , Sadrjahani Mehdi 
Published: July 2024

Abstract
The dyeing process of textile materials is inherently intricate, influenced by a myriad of factors, including dye concentration, dyeing time, pH level, temperature, type of dye, fiber composition, mechanical agitation, salt concentration, mordants, fixatives, water quality, dyeing method, and pre-treatment processes. The intricacy of achieving optimal settings during dyeing poses a significant challenge. In response, this study introduces a novel algorithmic approach that integrates response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA) techniques for the precise fine-tuning of concentration, time, pH, and temperature. The primary focus is on quantifying color strength, represented as K/S, as the response variable in the dyeing process of polyamide 6 and woolen fabric, utilizing plum-tree leaves as a sustainable dye source. Results indicate that ANN (R2 ~ 1) performs much better than RSM (R2 > 0.92). The optimization results, employing ANN-GA integration, indicate that a concentration of 100 wt.%, time of 86.06 min, pH level of 8.28, and a temperature of 100 °C yield a K/S value of 10.21 for polyamide 6 fabric. Similarly, a concentration of 55.85 wt.%, time of 120 min, pH level of 5, and temperature of 100 °C yield a K/S value of 7.65 for woolen fabric. This proposed methodology not only paves the way for sustainable textile dyeing but also facilitates the optimization of diverse dyeing processes for textile materials.
Biophysical and structural studies of fibulin-2
Authors: Sohail Anil A. , Koski M. Kristian , Ruddock Lloyd W. 
Published: July 2024

AbstractFibulin-2 is a multidomain, disulfide-rich, homodimeric protein which belongs to a broader extracellular matrix family. It plays an important role in the development of elastic fiber structures. Malfunction of fibulin due to mutation or poor expression can result in a variety of diseases including synpolydactyly, limb abnormalities, eye disorders leading to blindness, cardiovascular diseases and cancer. Traditionally, fibulins have either been produced in mammalian cell systems or were isolated from the extracellular matrix, a procedure that results in poor availability for structural and functional studies. Here, we produced seven fibulin-2 constructs covering 62% of the mature protein (749 out of 1195 residues) using a prokaryotic expression system. Biophysical studies confirm that the purified constructs are folded and that the presence of disulfide bonds within the constructs makes them extremely thermostable. In addition, we solved the first crystal structure for any fibulin isoform, a structure corresponding to the previously suggested three motifs related to anaphylatoxin. The structure reveals that the three anaphylatoxins moieties form a single-domain structure.
Factors influencing psychological distress among breast cancer survivors using machine learning techniques
Authors: Park Jin-Hee , Chun Misun , Bae Sun Hyoung , Woo Jeonghee , Chon Eunae , Kim Hee Jun 
Published: July 2024

AbstractBreast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients experience significant distress relating to their diagnosis and treatment. Managing this distress is critical for improving the lifespan and quality of life of breast cancer survivors. This study aimed to assess the level of distress in breast cancer survivors and analyze the variables that significantly affect distress using machine learning techniques. A survey was conducted with 641 adult breast cancer patients using the National Comprehensive Cancer Network Distress Thermometer tool. Participants identified various factors that caused distress. Five machine learning models were used to predict the classification of patients into mild and severe distress groups. The survey results indicated that 57.7% of the participants experienced severe distress. The top-three best-performing models indicated that depression, dealing with a partner, housing, work/school, and fatigue are the primary indicators. Among the emotional problems, depression, fear, worry, loss of interest in regular activities, and nervousness were determined as significant predictive factors. Therefore, machine learning models can be effectively applied to determine various factors influencing distress in breast cancer patients who have completed primary treatment, thereby identifying breast cancer patients who are vulnerable to distress in clinical settings.
Phylogenomic analysis and dynamic evolution of chloroplast genomes of Clematis nannophylla
Authors: Qin Jinping , Ma Yushou , Liu Ying , Wang Yanlong 
Published: July 2024

AbstractClematis nannophylla is a perennial shrub of Clematis with ecological, ornamental, and medicinal value, distributed in the arid and semi-arid areas of northwest China. This study successfully determined the chloroplast (cp) genome of C. nannophylla, reconstructing a phylogenetic tree of Clematis. This cp genome is 159,801 bp in length and has a typical tetrad structure, including a large single-copy, a small single-copy, and a pair of reverse repeats (IRa and IRb). It contains 133 unique genes, including 89 protein-coding, 36 tRNA, and 8 rRNA genes. Additionally, 66 simple repeat sequences, 50 dispersed repeats, and 24 tandem repeats were found; many of the dispersed and tandem repeats were between 20–30 bp and 10–20 bp, respectively, and the abundant repeats were located in the large single copy region. The cp genome was relatively conserved, especially in the IR region, where no inversion or rearrangement was observed, further revealing that the coding regions were more conserved than the noncoding regions. Phylogenetic analysis showed that C. nannophylla is more closely related to C. fruticosa and C. songorica. Our analysis provides reference data for molecular marker development, phylogenetic analysis, population studies, and cp genome processes to better utilise C. nannophylla.
Reduction of organic contaminants from industrial effluent using the advanced oxidation process, chemical coagulation, and green nanotechnology
Authors: Naguib Amany M. , Abdel-Gawad Soha A. , Mahmoud Ahmed S. 
Published: July 2024

AbstractMunicipal wastewater treatment systems use the chemical oxygen demand test (COD) to identify organic contaminants in industrial effluents that impede treatment due to their high concentration. This study reduced the COD levels in tannery wastewater using a multistage treatment process that included Fenton oxidation, chemical coagulation, and nanotechnology based on a synthetic soluble COD standard solution. At an acidic pH of 5, Fenton oxidation reduces the COD concentration by approximately 79%. It achieves this by combining 10 mL/L of H2O2 and 0.1 g/L of FeCl2. Furthermore, the author selected the FeCl3 coagulant for the coagulation process based on the best results of comparisons between different coagulants. At pH 8.5, the coagulation dose of 0.15 g/L achieved the maximum COD removal efficiency of approximately 56.7%. Finally, nano bimetallic Fe/Cu was used to complete the degradation and adsorption of the remaining organic pollutants. The XRD, SEM, and EDX analyses proved the formation of Fe/Cu nanoparticles. A dose of 0.09 g/L Fe/Cu NPs, 30 min of contact time, and a stirring rate of 200 rpm achieve a maximum removal efficiency of about 93% of COD at pH 7.5. The kinetics studies were analyzed using pseudo-first-order P.F.O., pseudo-second-order P.S.O., and intraparticle diffusion models. The P.S.O. showed the best fit among the kinetic models, with an R2 of 0.998. Finally, the authors recommended that technique for highly contaminated industrial effluents treatment for agriculture or industrial purposes.
Impact of Bariatric Surgery on metabolic health in a Uruguayan cohort and the emerging predictive role of FSTL1
Authors: Santos Leonardo , Patrone Mariana , Prieto-Echagüe Victoria , Lapi Silvana , Perdomo Mauro , Vaucher Andrea , Rodriguez Gustavo , Valsangiacomo Pablo , Naya Hugo , Escande Carlos , Badano Jose L. , Spangenberg Lucia , Bruno Gustavo 
Published: July 2024

AbstractObesity poses significant challenges, necessitating comprehensive strategies for effective intervention. Bariatric Surgery (BS) has emerged as a crucial therapeutic approach, demonstrating success in weight loss and comorbidity improvement. This study aimed to evaluate the outcomes of BS in a cohort of 48 Uruguayan patients and investigate the interplay between BS and clinical and metabolic features, with a specific focus on FSTL1, an emerging biomarker associated with obesity and inflammation. We quantitatively analyzed BS outcomes and constructed linear models to identify variables impacting BS success. The study revealed the effectiveness of BS in improving metabolic and clinical parameters. Importantly, variables correlating with BS success were identified, with higher pre-surgical FSTL1 levels associated with an increased effect of BS on BMI reduction. FSTL1 levels were measured from patient plasma using an ELISA kit pre-surgery and six months after. This research, despite limitations of a small sample size and limited follow-up time, contributes valuable insights into understanding and predicting the success of BS, highlighting the potential role of FSTL1 as a useful biomarker in obesity.
Enhancing deep neural network training efficiency and performance through linear prediction
Authors: Ying Hejie , Song Mengmeng , Tang Yaohong , Xiao Shungen , Xiao Zimin 
Published: July 2024

AbstractDeep neural networks have achieved remarkable success in various fields. However, training an effective deep neural network still poses challenges. This paper aims to propose a method to optimize the training effectiveness of deep neural networks, with the goal of improving their performance. Firstly, based on the observation that parameters (weights and bias) of deep neural network change in certain rules during training process, the potential of parameters prediction for improving training efficiency is discovered. Secondly, the potential of parameters prediction to improve the performance of deep neural network by noise injection introduced by prediction errors is revealed. And then, considering the limitations comprehensively, a deep neural network Parameters Linear Prediction method is exploit. Finally, performance and hyperparameter sensitivity validations are carried out on some representative backbones. Experimental results show that by employing proposed Parameters Linear Prediction method, as opposed to SGD, has led to an approximate 1% increase in accuracy for optimal model, along with a reduction of about 0.01 in top-1/top-5 error. Moreover, it also exhibits stable performance under various hyperparameter settings, shown the effectiveness of the proposed method and validated its capacity in enhancing network’s training efficiency and performance.
Indoor environmental quality in WELL-certified and LEED-certified buildings
Authors: Kent Michael G. , Parkinson Thomas , Schiavon Stefano 
Published: July 2024

AbstractInternational building certification systems, such as the WELL and Leadership in Energy and Environmental Design (LEED) standards, play a pivotal role in the design of healthy and sustainable buildings. While LEED adopts a holistic approach to designing healthy and sustainable buildings, the WELL standard has a strong emphasis on human health, comfort, and well-being. Although prior research has revealed inconsistent results for occupant satisfaction in office buildings with WELL certification compared to buildings without WELL certification, or are certified using another certification system (e.g., LEED), most of these comparisons tend to lack methodological rigor. This study used a statistical procedure to match and compare 1634 occupant surveys from LEED-certified buildings to 1634 surveys from WELL-certified buildings. Six important architectural and experiential parameters were matched, masking their influence on the outcome. Overall building and workspace satisfaction was high in both WELL-certified buildings (94% and 87%) and LEED-certified (73% and 71%). We found that there is a 39% higher probability of finding occupants who are more satisfied in WELL-certified buildings compared to LEED-certified buildings, indicating occupant satisfaction is higher in buildings with WELL certification. Although we were unable to pinpoint the reason for higher occupant satisfaction in WELL-certified buildings, the results consistently showed that perceived indoor environmental quality was enhanced across all parameters except for the amount of space.
Selection of renewable energy development path for sustainable development using a fuzzy MCDM based on cumulative prospect theory: the case of Malaysia
Authors: Li Taikun , Wang Hong , Lin Yonghui 
Published: July 2024

AbstractMalaysia's excessive energy consumption has led to the depletion of traditional energy reserves such as oil and natural gas. Although Malaysia has implemented multiple policies to achieve sustainable national energy development, the current results are unsatisfactory. As of 2022, only 2% of the country's electricity supply comes from renewable energy, which accounts for less than 30% of the energy structure. Malaysia must ensure energy security and diversified energy supply while ensuring sustainable energy development. This article uses the fuzzy multi-criteria decision-making(MCDM) method based on cumulative prospect theory to help decision-makers choose the most suitable renewable energy for sustainable development in Malaysia from four dimensions of technology, economy, society, and environment. The results show that solar power is the most suitable renewable energy for sustainable development, followed by biomass, wind, and hydropower, but the optimal alternative is sensitive to the prospect parameters. Finally, it was analyzed that efficiency, payback period, employment creation, and carbon dioxide (CO2) emissions are the most critical factors affecting the development of renewable energy in Malaysia under the four dimensions. Reasonable suggestions are proposed from policy review, green finance, public awareness, engineering education, and future energy. This research provides insightful information that can help Malaysian decision-makers scientifically formulate Sustainable development paths for renewable energy, analyze the problems encountered in the current stage of renewable energy development, and provide recommendations for Malaysia's future renewable energy transition and sustainable development.
An age-period-cohort analysis of hysterectomy incidence trends in Germany from 2005 to 2019
Authors: Baffour Awuah Gifty , Schauberger Gunther , Klug Stefanie J. , Tanaka Luana Fiengo 
Published: July 2024

AbstractRecent studies show declining trends in hysterectomy rates in several countries. The objective of this study was to analyse hysterectomy time trends in Germany over a fifteen-year period using an age-period-cohort approach. Using an ecological study design, inpatient data from Diagnoses Related Group on hysterectomies by subtype performed in Germany from 2005 to 2019 were retrieved from the German Statistical Office. Descriptive time trends and age-period-cohort analyses were then performed. A total of 1,974,836 hysterectomies were performed over the study period. The absolute number of hysterectomies reduced progressively from 155,680 (365 procedures/100,000 women) in 2005 to 101,046 (257 procedures/100,000 women) in 2019. Total and radical hysterectomy decreased by 49.7% and 44.2%, respectively, whilst subtotal hysterectomy increased five-fold. The age-period-cohort analysis revealed highest hysterectomy rates in women aged 45–49 for total and subtotal hysterectomy with 608.63 procedures/100,000 women (95% CI 565.70, 654.82) and 151.30 procedures/100,000 women (95% CI 138.38, 165.44) respectively. Radical hysterectomy peaked later at 65–69 years with a rate of 40.63 procedures/100,000 women (95% CI 38.84, 42.52). The risk of undergoing total or radical hysterectomy decreased over the study period but increased for subtotal hysterectomy. Although, overall hysterectomy rates have declined, subtotal hysterectomy rates have increased; reflecting changes in clinical practice largely influenced by the availability of uterus-sparing options, evolving guidelines and introduction of newer surgical approaches.