bluuebunny/crossref_metadata_2025_split huggingface dataset:
PLGA nanoparticle loaded with antioxidants and photosensitizer for ROS shock mediated phototherapy of triple negative breast cancer
Authors: Buddhiraju Hima Sree , Balaraman Jayalakshmi , Dehariya Dheeraj , Pebam Monika , Eswar Kalyani , Rengan Aravind Kumar 
Published: August 2023

Abstract
The potential use of antioxidants for photodynamic therapy (PDT) is investigated in this study. PDT causes reactive oxygen species (ROS)-mediated cell death; on the contrary, antioxidants scavenge ROS. The use of a photosensitizer along with an antioxidant photosensitizer compensates for the loss of ROS due to the use of antioxidant, eventually leading to cell death. In this work, for PDT and photothermal therapy (PTT), we have combined the photosensitizer IR 792 perchlorate dye with the antioxidants alpha-tocopherol (A) and p-coumaric acid (C) encapsulated in a polymeric nanocarrier (AC IR NPs). We have reported the synthesis of AC IR NPs using poly lactic-co-glycolic acid (PLGA) by nanoprecipitation method. The size of the polymeric nanoparticles was found to be 80.4 ± 15.6 nm, with a spherical morphology observed by scanning electron microscopy and transmission electron microscopy. The synthesized AC IR NPs demonstrated good biocompatibility in fibroblast cell lines (L929). Furthermore, the efficacy assessment of the as prepared nanosystem in vitro on breast cancer cell lines (4T1) revealed a significant cell death of nearly 80%. This could be attributed to the ROS generation leading to oxidative stress and inhibition of metastasis. This study provides evidence that the combination of antioxidant drugs along with photosensitizers have the potential to be an effective therapy for treating triple negative breast cancer.
Water clubs: a new model for managing freshwater in small catchments
*
Authors: Talbot-Jones Julia , Sağlam Yiğit 
Published: August 2023

Abstract
Over the past 30 years market-based mechanisms have been upheld as the gold-standard of water governance approaches. However, while some water markets have been successful, many struggle to meet the strict institutional preconditions for efficiency and effectiveness, which has implications for social welfare and public good provision. As pressures on water resources increase, there is a growing need to consider alternative market designs that foster more cooperation between water users. Drawing on club theory and game theory, this paper investigates the economic and environmental benefits of (re)designing water markets as clubs. It finds that in small catchments, the introduction of group-level trading can increase provision of the public good, improve social welfare, and reduce free-riding when compared with a regulatory status quo. It also finds that the club model performs best when the number of active traders is low—a result that challenges the common assumption regarding group size and effective market performance. In local contexts, the group-level trading may also help characterise the optimal group size by weighing the benefits from more trading opportunities against the losses from free-riding.
Changes in vegetation greenness and its response to precipitation seasonality in Central Asia from 1982 to 2022
Authors: Su Yanan , Chen Shengqian , Li Xin , Ma Shuai , Xie Tingting , Wang Jianbang , Yan Dezhao , Chen Jianhui , Feng Min , Chen Fahu 
Published: August 2023

Abstract
Central Asia is the world’s largest azonal arid region, with strong seasonal precipitation patterns. Vegetation in this region is relatively sparse and extremely sensitive to climatic changes. However, long-term trends in vegetation in Central Asia are still unclear or even controversially recognized, hindering the assessment of climate change’s impact on regional sustainability. Here, we present the longest time series of vegetation index in Central Asia and investigated its response to precipitation seasonality from 1982 to 2022 by integrating normalized difference vegetation index data from the Global Inventory Monitoring and Modeling Studies and the Moderate Resolution Imaging Spectroradiometer. The results indicate a greening trend during 1982–2000 and a browning trend during 2000–2008. In contrast to previous studies, we detected a rapid greening trend during 2008–2022, largely resulted from a continuous warm-wet trend in Central Asia. In addition, strong spatial variation in vegetation is uncovered within the region, suggesting spatial differences in vegetation responding to contrasting precipitation seasonality. Under CMIP6 climate scenarios, spring wetting and summer drying are projected to prompt Central Asian vegetation change to a simultaneous greening south and browning north.
The association between exposure to PM2.5 components from coal combustion and mortality in female breast cancer patients
Authors: Su Mintao , Sun Huimin , Qiao Liying , Lin Hai , Zhang Yunjing , Qi Meng , Yan Ying , Kang Weiwei , Xu Lu , Liu Guozhen , Wang Mingyuan , Zhu Dawei , Liang Baosheng , Lv Xiaozhen , Meng Ruogu , Xi Yunfeng , Wang Shengfeng , Li Jing , Zhang Zhenyu 
Published: August 2023

Abstract
PM2.5 components may promote the development of breast cancer and increase the risk of mortality. This study aims to investigate the associations between long-term exposure to PM2.5 components and multiple causes of mortality among women with breast cancer living in Inner Mongolia, China. We constructed an Inner Mongolia cohort of 33 952 breast cancer patients from 2012 to 2021 using data from the Inner Mongolia Regional Health Information Platform. We assessed each patient’s exposure to PM2.5 components using the Tracking Air Pollution in China database. Cox regression models were used to estimate adjusted hazard ratios and 95% confidence intervals (95% CIs). A total of 3295 deaths were identified. For each interquartile increase in concentration in the 5 years before diagnosis, the all-cause mortality increased significantly by 5% (HR: 1.05, 95%CI: 1.00–1.10) for black carbon and by 4% (HR: 1.04, 95%CI: 1.00–1.09) for sulfate (SO4
2−), and decreased by 7% (HR: 0.93, 95%CI: 0.88–0.98) for nitrate (NO3
−). An association between organic matter and an increased all-cause mortality was also observed. Similar results were found for associations with risk of death from breast cancer-specific causes, cardio-cerebrovascular disease (CCVD) causes, and respiratory causes. Stronger associations were observed in older age groups and in Han Chinese patients. Our results showed that long-term exposure to black carbon, organic matter, and SO4
2− were more responsible for the increased risk of death from all causes, breast cancer-specific causes, CCVD causes, and respiratory causes. This suggests that more effective measures to control coal combustion emissions in Inner Mongolia are urgently needed. The elderly and Han Chinese populations may be at high risk.
Machine learning models to predict the relationship between printing parameters and tensile strength of 3D Poly (lactic acid) scaffolds for tissue engineering applications
Authors: Ege Duygu , Sertturk Seda , Acarkan Berk , Ademoglu Ahmet 
Published: August 2023

Abstract
3D printing is an effective method to prepare 3D scaffolds for tissue engineering applications. However, optimization of printing conditions to obtain suitable mechanical properties for various tissue engineering applications is costly and time consuming. To address this problem, in this study, scikit-learn Python machine learning library was used to apply four machine learning-based approaches which are ordinary least squares (OLS) linear regression, random forest (RF), light gradient Boost (LGBM), extreme gradient boosting (XGB) and artificial neural network models to understand the relationship between 3D printing parameters and tensile strength of poly(lactic acid) (PLA). 68 combinations of process parameters for nozzle temperature, printing speed, layer height and tensile strength were used from investigated research papers. Then, datasets were divided as training (80%) and test (20%). After building the OLS linear regression, RF, LGBM, XGB and artificial neural network models, the correlation heatmap and feature importance of each printing parameter for tensile strength values were determined, respectively. Then, the tensile strength was predicted for real datasets to evaluate the performance of the models. The results demonstrate that XGB model was the most successful in predicting tensile strength among the studied models with an R
2 value of 0.98 and 0.94 for train and test values, respectively. A close R
2 value for the train and test also indicated that there was no overfitting of the data to the model. Finally, SHAP analysis shows significance of each feature on prediction of tensile strength. This study can be extended for independent variables including nozzle pressure, strut size and molecular weight of PLA and dependent variables such as elongation and elastic modulus of PLA which may be a powerful tool to predict the mechanical properties of scaffolds for tissue engineering applications.
Enhanced synaptic characteristics of H
x
WO3-based neuromorphic devices, achieved by current pulse control, for artificial neural networks
Authors: Nishioka Daiki , Tsuchiya Takashi , Higuchi Tohru , Terabe Kazuya 
Published: August 2023

Abstract
Artificial synapses capable of mimicking the fundamental functionalities of biological synapses are critical to the building of efficient neuromorphic systems. We have developed a H
x
WO3-based artificial synapse that replicates such synaptic functionalities via an all-solid-state redox transistor mechanism. The subject synaptic-H
x
WO3 transistor, which operates by current pulse control, exhibits excellent synaptic properties including good linearity, low update variation and conductance modulation characteristics. We investigated the performance of the device under various operating conditions, and the impact of the characteristics of the device on artificial neural network computing. Although the subject synaptic-H
x
WO3 transistor showed an insufficient recognition accuracy of 66% for a handwritten digit recognition task with voltage pulse control, it achieved an excellent accuracy of 88% with current pulse control, which is approaching the 93% accuracy of an ideal synaptic device. This result suggests that the performance of any redox-transistor-type artificial synapse can be dramatically improved by current pulse control, which in turn paves the way for further exploration and the evolution of advanced neuromorphic systems, with the potential to revolutionize the artificial intelligence domain. It further marks a significant stride towards the realization of high-performance, low-power consumption computing devices.
InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data
Authors: Yang Hai , Liu Yawen , Yang Yijing , Li Dongdong , Wang Zhe 
Published: August 2023

Abstract
Cancer driver genes are critical in driving tumor cell growth, and precisely identifying these genes is crucial in advancing our understanding of cancer pathogenesis and developing targeted cancer drugs. Despite the current methods for discovering cancer driver genes that mainly rely on integrating multi-omics data, many existing models are overly complex, and it is difficult to interpret the results accurately. This study aims to address this issue by introducing InDEP, an interpretable machine learning framework based on cascade forests. InDEP is designed with easy-to-interpret features, cascade forests based on decision trees and a KernelSHAP module that enables fine-grained post-hoc interpretation. Integrating multi-omics data, InDEP can identify essential features of classified driver genes at both the gene and cancer-type levels. The framework accurately identifies driver genes, discovers new patterns that make genes as driver genes and refines the cancer driver gene catalog. In comparison with state-of-the-art methods, InDEP proved to be more accurate on the test set and identified reliable candidate driver genes. Mutational features were the primary drivers for InDEP’s identifying driver genes, with other omics features also contributing. At the gene level, the framework concluded that substitution-type mutations were the main reason most genes were identified as driver genes. InDEP’s ability to identify reliable candidate driver genes opens up new avenues for precision oncology and discovering new biomedical knowledge. This framework can help advance cancer research by providing an interpretable method for identifying cancer driver genes and their contribution to cancer pathogenesis, facilitating the development of targeted cancer drugs.
Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection
Authors: Le Nguyen Quoc Khanh , Li Wanru , Cao Yanshuang 
Published: August 2023

Abstract
Protein crystallization is crucial for biology, but the steps involved are complex and demanding in terms of external factors and internal structure. To save on experimental costs and time, the tendency of proteins to crystallize can be initially determined and screened by modeling. As a result, this study created a new pipeline aimed at using protein sequence to predict protein crystallization propensity in the protein material production stage, purification stage and production of crystal stage. The newly created pipeline proposed a new feature selection method, which involves combining Chi-square (${\chi }^{2}$) and recursive feature elimination together with the 12 selected features, followed by a linear discriminant analysisfor dimensionality reduction and finally, a support vector machine algorithm with hyperparameter tuning and 10-fold cross-validation is used to train the model and test the results. This new pipeline has been tested on three different datasets, and the accuracy rates are higher than the existing pipelines. In conclusion, our model provides a new solution to predict multistage protein crystallization propensity which is a big challenge in computational biology.
Maternal blood transcriptome as a sensor of fetal organ maturation at the end of organogenesis in cattle
Authors: Rabaglino Maria Belen , Sánchez José María , McDonald Michael , O’Callaghan Elena , Lonergan Pat 
Published: August 2023

Abstract
Harnessing information from the maternal blood to predict fetal growth is attractive yet scarcely explored in livestock. The objectives were to determine the transcriptomic modifications in maternal blood and fetal liver, gonads, and heart according to fetal weight and to model a molecular signature based on the fetal organs allowing the prediction of fetal weight from the maternal blood transcriptome in cattle. In addition to a contemporaneous maternal blood sample, organ samples were collected from 10 male fetuses at 42 days of gestation for RNA-sequencing. Fetal weight ranged from 1.25 to 1.69 g (mean = 1.44 ± 0.15 g). Clustering data analysis revealed clusters of co-expressed genes positively correlated with fetal weight and enriching ontological terms biologically relevant for the organ. For the heart, the 1346 co-expressed genes were involved in energy generation and protein synthesis. For the gonads, the 1042 co-expressed genes enriched seminiferous tubule development. The 459 co-expressed genes identified in the liver were associated with lipid synthesis and metabolism. Finally, the cluster of 571 co-expressed genes determined in maternal blood enriched oxidative phosphorylation and thermogenesis. Next, data from the fetal organs were used to train a regression model of fetal weight, which was predicted with the maternal blood data. The best prediction was achieved when the model was trained with 35 co-expressed genes overlapping between heart and maternal blood (root-mean-square error = 0.04, R2 = 0.93). In conclusion, linking transcriptomic information from maternal blood with that from the fetal heart unveiled maternal blood as a predictor of fetal development.
Children’s growth and motor development following a severe burn: a systematic review
Authors: Cuijpers Maxime D , Baartmans Martin G A , van Zuijlen Paul P M , Ket Johannes C F , Pijpe Anouk 
Published: August 2023

Abstract

Background
The epidemiological data on post-burn growth, body composition and motor development is ambiguous and scattered. The aim of this systematic review was therefore to summarize the current body of evidence on post-burn growth, body composition and motor development in children.

Methods
A literature search was conducted in PubMed, EMBASE and Web of Science up to March 2021. We considered observational studies that reported (1) metrics on weight, height, body composition, bone mineral content, bone mineral density or motor development, in (2) paediatric burn patients and (3) published in a peer-reviewed journal.

Results
A total of 16 studies were included. Each of the included studies used quantitative methods, but with differing methodology: prospective cohort studies (n = 8), retrospective chart reviews (n = 3), case–control studies (n = 2), cross sectional studies (n = 2) and a retrospective cohort study (n = 1). When combined, the included studies represented 2022 paediatric burn patients, with a mean age of 7.7 (±3.2) years. The average burn size was 52.8% (±12.7) of the total body surface area. Identified outcome measures included weight (n = 12), height (n = 7), muscular strength (n = 4), bone mineral content (n = 5), bone mineral density (n = 5), body mass index (n = 3), fat mass (n = 5), lean body mass (n = 7) and fine and gross motor development (n = 1).

Conclusions
Following an initial decline, patients’ growth and motor development started to recover during the first or second year post-burn. Nonetheless, burns may have a profound and prolonged effect on the paediatric burn patients’ muscular strength, bone mineral content and lean body mass. It should be noted that the vast majority of studies included only patients with burns covering ≥30% total body surface area. The evidence presented in this review may thus not be representative of the whole paediatric burn population.
Effect of elevated embryonic incubation temperature on the temperature preference of juvenile lake (Coregonus clupeaformis) and round whitefish (Prosopium cylindraceum)
Authors: Harman Adam , Mahoney Hannah , Thompson William Andrew , Fuzzen Meghan L M , Aggarwal Bhuvan , Laframboise Lisa , Boreham Douglas R , Manzon Richard G , Somers Christopher M , Wilson Joanna Y 
Published: August 2023

Abstract
Anthropogenic impacts can lead to increased temperatures in freshwater environments through thermal effluent and climate change. Thermal preference of aquatic organisms can be modulated by abiotic and biotic factors including environmental temperature. Whether increased temperature during embryogenesis can lead to long-term alterations in thermal preference has not been explicitly tested in native freshwater species. Lake (Coregonus clupeaformis) and round (Prosopium cylindraceum) whitefish were incubated at natural and elevated temperatures until hatching, following which, all groups were moved to common garden conditions (15°C) during the post-hatching stage. Temperature preference was determined at 8 months (Lake whitefish only) and 12 months of age (both species) using a shuttle box system. Round whitefish preferred a cooler temperature when incubated at 2 and 6°C compared with 0.5°C. Lake whitefish had similar temperature preferences regardless of age, weight and incubation temperature. These results reveal that temperature preference in freshwater fish can be programmed during early development, and that round whitefish may be more sensitive to incubation temperature. This study highlights the effects that small increases in temperature caused by anthropogenic impacts may have on cold-adapted freshwater fish.
27. OPLAH PROTEIN EXPRESSION STRATIFIES THE PROGNOSIS OF PATIENTS WITH SQUAMOUS CELL CARCINOMA OF THE ESOPHAGUS
Authors: Shimizu Dai , Kanda Mitsuro , Nakanishi Koki , Kurimoto Keisuke , Umeda Shinichi , Takami Hideki , Inokawa Yoshikuni , Hattori Norifumi , Hayashi Masamichi , Sato Yusuke , Tanaka Chie , Nakayama Goro , Fujiwara Michitaka , Kodera Yasuhiro 
Published: August 2023

Abstract

Background
Squamous cell carcinoma (SCC) is one of the major subtypes of esophageal carcinoma, and accounts for up to 90% of esophageal carcinoma cases in eastern Asia and eastern and southern Africa and 50% in Western countries. The 5-year overall survival rate of ESCC patients who undergo curative treatment remains below 40%. The elucidation of molecular biomarkers could be of clinical importance both as prognostic factors besides the established clinical staging and as potential targets for treatment. We aimed to detect and validate the prognosticators of esophageal squamous cell carcinoma in patients who underwent radical esophagectomy.

Methods
We identified OPLAH as one of the differentially expressed genes between esophageal squamous cell carcinoma (ESCC) tissue and normal esophageal mucosa whose expression changes were significantly associated with a patient prognosis using The Cancer Genome Atlas data. The OPLAH protein expression in ESCC tissue and serum OPLAH protein concentrations were evaluated and analyzed for their association with clinicopathological factors.

Results
OPLAH mRNA was significantly overexpressed in ESCC tissue compared to normal esophageal mucosa, and patients with high OPLAH mRNA expression had a significantly poorer prognosis according to The Cancer Genome Atlas data. The high staining intensity of OPLAH protein in ESCC tissue clearly stratified patient prognosis. According to the multivariable analysis, high OPLAH protein expression was an independent prognostic factor for survival after surgery. Pre-neoadjuvant chemotherapy serum OPLAH protein concentrations were significantly associated with clinical tumor depth and node positivity and, consequently, with advanced clinical stage. The serum OPLAH protein concentration was significantly decreased by neoadjuvant chemotherapy.

Conclusions
OPLAH may serve as a useful prognosticator for ESCC patients.
46. THORACOSCOPIC REPAIR OF IATROGENIC INJURY TO THE THORACIC AORTA DURING MINIMALLY INVASIVE ESOPHAGECTOMY
Authors: Tan Jeremy , Chan Weng Hoong , Lee Zhen Jin , Lim Eugene , Chng Jack Kian 
Published: August 2023

Abstract

Description of video:

Background
We present the case of a 75-year-old male patient with locally advanced Siewert Type 2 gastroesophageal adenocarcinoma post neoadjuvant chemotherapy. Inadvertent through-and-through piercing of the lower thoracic aorta with the tip of an energy device just above the diaphragm was sustained during the thoracoscopic esophageal dissection phase of the three-field minimally-invasive McKeown approach.

Methods
The procedure proceed thoracoscopically. The lower thoracic aorta was dissected and mobilized proximally and distally, and clamped on both ends with the introduction of Debakey clamps directly through separate small incisions in the chest wall. Primary repair of both anterior and posterior defects was then performed with monofilament non-absorbable sutures. Total clamp time was 30 minutes (in 15-minute intervals).

Results
Post-repair, perfusion status to the distal viscera and lower limbs were verified and intact. The rest of the operation then proceeded uneventfully. A Computed Tomography scan of the thoracic aorta on postoperative day 14 showed a patent thoracic aorta with no intraluminal narrowing or thrombosis.

Conclusion
Thoracoscopic repair of aortic injury sustained during the thoracoscopic dissection phase of a minimally invasive esophagectomy can be performed safely in well-selected, haemodynamically stable patients.
Drpbox link to video: https://www.dropbox.com/s/xbwt6ge23iywr3m/aorta3mus1.mp4?dl&#x003D;0.