bluuebunny/crossref_metadata_2025 huggingface dataset:
SYSTEM VARIABLE REDUCTION AND GLOBAL SENSITIVITY ANALYSIS FOR A COMPLEX MODEL OF CANCER CELL DIFFERENTIATION
Authors: MARGARIT DAVID H. , PACCOSI GUSTAVO , PAGNANI ANDREA , REALE MARCELA V. , SCAGLIOTTI ARIEL F. , ROMANELLI LILIA M.
Published: October 2024

Model reduction aims to simplify complex models by decreasing the number of equations, variables, or parameters while preserving key characteristics. This approach enhances accessibility, comprehensibility, and computational efficiency, enabling a more focused analysis of relevant variables. In this study, we describe the reduction process of a population model that incorporates cancer cell differentiation and its interaction with the immune system, maintaining the fundamental dynamics and evolution of the original model. This led to a substantial reduction in variables and parameters, creating a more efficient model suitable for computational simulations, mathematical analysis, and quantitative understanding of population dynamics. Additionally, we performed a global sensitivity analysis of model parameters using the Sobol and eFast methods, revealing insights into differences and similarities in results from a biological perspective. Our findings emphasize the critical importance of understanding and controlling parameters related to the reproduction and death rates of differentiated cancer cells, as small variations in these parameters can have significant effects on model outcomes. This underscores the importance of thoroughly understanding these essential biological variables and processes in cancer treatment, as they have a significant impact on model outcomes and, consequently, on the development of more effective therapies.
ON A CLASS OF FRACTAL SETS WITH DIFFERENT UPPER AND LOWER BOX DIMENSIONS
Authors: REN QIANQIAN , LIANG YONGSHUN
Published: October 2024

This paper investigates a special Cantor set with different upper and lower box dimensions, and discusses its Hausdorff dimension. In addition, we extend the set and generate a class of sets with different upper and lower box dimensions, reaching a sufficiently large interval within the range of the box dimension.
REMARKS ON INEQUALITIES WITH PARAMETER BY CONFORMABLE FRACTIONAL INTEGRALS
Authors: HEZENCI FATIH , VIVAS-CORTEZ MIGUEL , BUDAK HÜSEYIN
Published: October 2024

We prove that an equation holds for differentiable convex functions, and this result has been derived using conformable integrals. With the help of this equality, several parameterized inequalities are established by using the conformable fractional integrals. Namely, we show that our main inequalities reduce to Ostrowski-, Hermite–Hadamard-, Simpson-, and Bullen-type inequalities which are proved in earlier published papers. More precisely, some inequalities are acquired by taking advantage of the convexity, the Hölder, and the power mean inequalities. Finally, examples are given to illustrate the investigated results.
Mentorship Lessons from Growing a Developing Country Journal
Authors: Machanick Philip
Published: October 2024

Experiences developing and using a quality open access journal to mentor emerging academics.
C
anton
MT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation
Authors: Yin Hong Kung , Han Lifeng , Batista-Navarro Riza , Nenadic Goran
Published: October 2024

This paper investigates the development and evaluation of machine translation models from Cantonese to English (and backward), where we propose a novel approach to tackle low-resource language translations. Despite recent improvements in Neural Machine Translation (NMT) models with Transformer-based architectures, Cantonese, a language with over 80 million native speakers, has below-par State-of-the-art commercial translation models due to a lack of resources. The main objectives of the study are to develop a model that can effectively translate Cantonese to English and evaluate it against state-of-the-art commercial models. To achieve this, a
new parallel corpus
has been created by combining different available corpora online with preprocessing and cleaning. In addition, a
monolingual Cantonese dataset
has been created through web scraping to aid the synthetic parallel corpus generation. Following the data collection process, several approaches, including
fine-tuning
models,
back-translation
, and
model switch
, have been used. The translation quality of models has been evaluated with multiple quality metrics, including lexicon-based metrics (SacreBLEU and hLEPOR) and embedding-space metrics (COMET and BERTscore). Based on the automatic metrics, the best model is selected and compared against the 2 best commercial translators using a
new human evaluation framework HOPES
. The best model proposed in this investigation (NLLB-mBART) with model switch mechanisms has reached comparable and even better automatic evaluation scores against State-of-the-art commercial models (Bing and Baidu Translators), with a SacreBLEU score of 16.8 on our test set. Furthermore, an open-source
web application
has been developed to allow users to translate between Cantonese and English, with the different trained models available for effective comparisons between models from this investigation and users.
CantonMT
is available at https://github.com/kenrickkung/CantoneseTranslation
Empowering Agrifood System with Artificial Intelligence: A Survey of the Progress, Challenges and Opportunities
Authors: Chen Tao , Lv Liang , Wang Di , Zhang Jing , Yang Yue , Zhao Zeyang , Wang Chen , Guo Xiaowei , Chen Hao , Wang Qingye , Xu Yufei , Zhang Qiming , Du Bo , Zhang Liangpei , Tao Dacheng
Published: October 2024

With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages. Recently, artificial intelligence (AI) techniques such as deep learning (DL) have demonstrated their strong abilities in various areas, including language, vision, remote sensing (RS), and agrifood systems applications. However, the overall impact of AI on agrifood systems remains unclear. In this article, we thoroughly review how AI techniques can transform agrifood systems and contribute to the modern agrifood industry. First, we summarize the data acquisition methods in agrifood systems, including acquisition, storage, and processing techniques. Second, we present a progress review of AI methods in agrifood systems, specifically in agriculture, animal husbandry, and fishery, covering topics such as agrifood classification, growth monitoring, yield prediction, and quality assessment. Furthermore, we highlight potential challenges and promising research opportunities for transforming modern agrifood systems with AI. We hope this survey can offer an overall picture to newcomers in the field and serve as a starting point for their further research. The project website is https://github.com/Frenkie14/Agrifood-Survey.
Knowledge Editing for Large Language Models: A Survey
Authors: Wang Song , Zhu Yaochen , Liu Haochen , Zheng Zaiyi , Chen Chen , Li Jundong
Published: October 2024

Large Language Models (LLMs) have recently transformed both the academic and industrial landscapes due to their remarkable capacity to understand, analyze, and generate texts based on their vast knowledge and reasoning ability. Nevertheless, one major drawback of LLMs is their substantial computational cost for pre-training due to their unprecedented amounts of parameters. The disadvantage is exacerbated when new knowledge frequently needs to be introduced into the pre-trained model. Therefore, it is imperative to develop effective and efficient techniques to update pre-trained LLMs. Traditional methods encode new knowledge in pre-trained LLMs through direct fine-tuning. However, naively re-training LLMs can be computationally intensive and risks degenerating valuable pre-trained knowledge irrelevant to the update in the model. Recently,Knowledge-based Model Editing(KME), also known asKnowledge EditingorModel Editing, has attracted increasing attention, which aims at precisely modifying the LLMs to incorporate specific knowledge, without negatively influencing other irrelevant knowledge. In this survey, we aim at providing a comprehensive and in-depth overview of recent advances in the field of KME. We first introduce a general formulation of KME to encompass different KME strategies. Afterward, we provide an innovative taxonomy of KME techniques based on how the new knowledge is introduced into pre-trained LLMs, and investigate existing KME strategies while analyzing key insights, advantages, and limitations of methods from each category. Moreover, representative metrics, datasets, and applications of KME are introduced accordingly. Finally, we provide an in-depth analysis regarding the practicality and remaining challenges of KME and suggest promising research directions for further advancement in this field.
Multi-Scale Feature Attention Fusion for Image Splicing Forgery Detection
Authors: Liang Enji , Zhang Kuiyuan , Hua Zhongyun , Jia Xiaohua
Published: October 2024

Image splicing is a widely occurrence image tampering technology. With the rapid development of digital image processing technology, detecting image splicing forgery has become significantly challenging. Although various methods have been devised to identify such tampered images, existing approaches have not achieved optimal performance due to limitations in effectively leveraging feature maps of different scales. To address this issue, we propose a novel method for image splicing forgery detection called multi-scale feature attention fusion network (MFAF-Net). We propose a multi-scale atrous feature attention (MAFA) module designed to capture rich contextual features for multi-scale high-level feature fusion. Additionally, we present the multi-branch attention mechanism (MBAM) module to fuse contextual information from various branches for low-level features. This integration enhances the capability of low-level features to produce more refined pixel-level attention. We employ the weighted binary cross-entropy loss and dice loss in the MFAF-Net to overcome the imbalance between positive and negative samples. Extensive experiments demonstrate that the proposed MFAF-Net outperforms state-of-the-art methods. Robustness experiments also show our model exhibits image splicing forgery detection robustness under common attacks.
Real-time Blood Pressure Prediction on Wearables with Edge-Based DNNs: A Co-Design Approach
Authors: Joseph Tresa , T.S Bindiya
Published: October 2024

This paper presents the hardware realization of a real-time blood pressure (BP) prediction model for wearable devices, utilizing long short-term memory (LSTM) deep neural networks (DNNs). The proposed system uses both electrocardiogram (ECG) and photoplethysmogram (PPG) signal values for BP prediction. It aims to address the limitations of traditional BP measurement methods, providing a low error, minimal computational overhead, and a more accurate and convenient alternative system for individuals with hypertension or those at risk for cardiovascular diseases. The utilization of a split matrix approach leads to a reduction in hardware complexity across the entire system. This technique involves breaking down the larger weight matrices used in the computations of DNNs into smaller matrices. This fragmentation results in a decrease in the complexity of the hardware responsible for performing matrix vector multiplications (MVMs) within LSTMs. The resultant architecture of the predictive model gains several advantages, including a lowered level of complexity in terms of the space occupied by individual cells, decreased processing delay, and reduced power consumption. Furthermore, this approach enables the achievement of a notably improved minimum achievable clock period of 2.972 ns. This prediction model can operate locally on wearable devices, reducing the reliance on cloud computing and improving privacy and security. The performance evaluations are carried out using both analytical and implementation results. The results indicate that the proposed model can be practically applied to real-world problems and can potentially enhance the accuracy of various machine-learning tasks.
Empirical and Experimental Insights into Data Mining Techniques for Crime Prediction: A Comprehensive Survey
Authors: Taha Kamal
Published: October 2024

This survey article presents a comprehensive analysis of crime prediction methodologies, exploring the various techniques and technologies utilized in this area. The article covers the statistical methods, machine learning algorithms, and deep learning techniques employed to analyze crime data, while also examining their effectiveness and limitations. We propose a methodological taxonomy that classifies crime prediction algorithms into specific techniques. This taxonomy is structured into four tiers, including methodology category, methodology sub-category, methodology techniques, and methodology sub-techniques. Empirical and experimental evaluations are provided to rank the different techniques. The empirical evaluation assesses the crime prediction techniques based on three criteria, while the experimental evaluation ranks the algorithms that employ the same sub-technique, the different sub-techniques that employ the same technique, the different techniques that employ the same methodology sub-category, the different methodology sub-categories within the same category, and the different methodology categories. The combination of methodological taxonomy, empirical evaluations, and experimental comparisons allows for a nuanced and comprehensive understanding of crime prediction algorithms, aiding researchers in making informed decisions. Finally, the article provides a glimpse into the future of crime prediction techniques, highlighting potential advancements and opportunities for further research in this field.
Exploring Automated Assertion Generation via Large Language Models
Authors: Zhang Quanjun , Sun Weifeng , Fang Chunrong , Yu Bowen , Li Hongyan , Yan Meng , Zhou Jianyi , Chen Zhenyu
Published: October 2024

Unit testing aims to validate the correctness of software system units and has become an essential practice in software development and maintenance. However, it is incredibly time-consuming and labor-intensive for testing experts to write unit test cases manually, including test inputs (i.e., prefixes) and test oracles (i.e., assertions). Very recently, some techniques have been proposed to apply Large Language Models (LLMs) to generate unit assertions and have proven the potential in reducing manual testing efforts. However, there has been no systematic comparison of the effectiveness of these LLMs, and their pros and cons remain unexplored.

To bridge this gap, we perform the first extensive study on applying various LLMs to automated assertion generation. The experimental results on two independent datasets show that studied LLMs outperform six state-of-the-art techniques with a prediction accuracy of 51.82%–58.71% and 38.72%–48.19%. The improvements achieve 29.60% and 12.47% on average. Besides, as a representative LLM, CodeT5 consistently outperforms all studied LLMs and all baselines on both datasets, with an average improvement of 13.85% and 26.64%, respectively. We also explore the performance of generated assertions in detecting real-world bugs, and find LLMs are able to detect 32 bugs from Defects4J on average, with an improvement of 52.38% against the most recent approach
EditAS
. Inspired by the findings, we construct a simplistic retrieval-and-repair-enhanced LLM-based approach by transforming the assertion generation problem into a program repair task for retrieved similar assertions. Surprisingly, such a simplistic approach can further improve the prediction accuracy of LLMs by 9.40% on average, leading to new records on both datasets. Besides, we provide additional discussions from different aspects (e.g., the impact of assertion types and test lengths) to illustrate the capacity and limitations of LLM-based approaches. Finally, we further pinpoint various practical guidelines (e.g., the improvement of multiple candidate assertions) for advanced LLM-based assertion generation in the near future. Overall, our work underscores the promising future of adopting off-the-shelf LLMs to generate accurate and meaningful assertions in real-world test cases and reduce the manual efforts of unit testing experts in practical scenarios.
Venoms of Lepidoptera: Evolution, Composition, and Molecular Modes of Action
Authors: Walker Andrew A.
Published: October 2024

Animal venoms are a focus of research due to the hazards they represent and to their relationship to evolution and ecology, pharmacology, biodiscovery, and biotechnology. Venoms have evolved multiple times in Lepidoptera, mostly as defensive adaptations that protect the larval life stages. While venoms are always produced in structures derived from cuticle and setae, they are diverse in their composition and bioactivity, reflecting their multiple evolutionary origins. The most common result of envenomation by lepidopterans is pain and inflammation, but envenomation by some species causes fatal hemorrhagic syndromes or chronic inflammatory conditions in humans or veterinary pathologies such as equine amnionitis and fetal loss. The handful of lepidopteran venom toxins that have been characterized includes coagulotoxins from Lonomia obliqua (Saturniidae) and pain-causing cecropin-like peptides from Doratifera vulnerans (Limacodidae). However, our knowledge of lepidopteran venoms remains comparatively poor, with further studies required to yield a clear picture of the evolution, composition, and function of venoms produced by Lepidoptera.
Effect of Heterojunction Dynamics on Electrochemical Properties of ZnS/MoS2 Type-II Nanocomposite for Photovoltaic Application
Authors: Shreya  , Phogat Peeyush , Jha Ranjana , Singh Sukhvir
Published: October 2024

In the present work, ZnS/MoS2 nanocomposite has been synthesized by hydrothermal route. X-ray diffraction analysis revealed ZnS and MoS2 phases, showing the crystallite size of 19.5 and 9.25 nm from W-H and S-S plots, respectively. The lattice parameters of MoS2 and ZnS were found to be a = b = 3.79 Å, c = 12.4 Å and a = b = 3.2 Å, and c = 9.5 Å, respectively. The dislocation density, stacking fault and strain from W-H and S-S plots were found to be 4.1 × 10−4, 2.4 × 10−3, −1.2 × 10-3 and −2.4 × 10−2, respectively. The absorbance peaks of the nanocomposite were observed at 209, 246 and 320 nm revealing a band gap of 3.3 eV with refractive index of 2.32. Scanning electron microscopy and transmission electron microscopy imaging demonstrated ZnS nanoparticles over MoS2 sheets with an average particle size of 45.9 and 23.8 nm, respectively. In cyclic voltammetry analysis, pure ZnS and nanocomposite showed maximum oxidation current of 0.25 and 0.51 mA, respectively. Electrochemical impedance spectroscopy analysis revealed the presence of Warburg diffusion with a high exchange current density of 2.5 mA along with electrolyte’s and working electrode’s resistance to be 1000 Ω and 100 Ω, respectively. Charge transfer resistance, Warburg impedance, electrical double layer capacitance and film’s capacitance was found to be 10 Ω, 1000 Ω·s−1/2, 100 μF and 1 μF, respectively.
Investigating a Spectrum of Machine Learning Methods for Leaf Disease Detection in Pepper, Potato, and Tomato
Authors: Bala Madhu , Bansal Sushil Kumar
Published: October 2024

An analysis of machine learning (ML) techniques such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF) and Naive Bayes (NB) was done to detect diseases among pepper, potato, and tomato crops to develop an algorithm to extract multiple features such as kurtosis, GLCM energy, skewness etc and to find region of interest (ROI). First, the sample images were resized and converted into greyscale. Then k-means clustering was used for segmentation. The cluster with the highest contrast or most significant visual features was chosen as the ROI and then passed to the machine learning models to predict the accuracy of finding the diseases. For experimentation purpose 20,639 leaf images of potato, tomato, and pepper plant is taken. From the dataset, 70% were used for training, while 30% of these images were used for testing. The data (biased and unbiased) was passed to these models in shuffled and un-shuffled orders, and it was found that Random Forest gave the highest accuracy i.e. 94.2% in the case of biased data and 89.90% with unbiased data. Hence, it is observed that the proposed algorithm works well for large number of images.
Sol-Gel Spin Coating Synthesis and Characterization of Cadmium Zinc Phosphate Thin Films: Structural, Optical, and Electrical Properties
Authors: El Nahrawy Amany M. , Abou Hammad Ali B. , Mansour A. M.
Published: October 2024

This study successfully implemented the sol-gel and spin coating technique to grow cadmium zinc phosphate cadmium zinc phosphate (CZP) thin films on a glass substrate and p-Si wafer. Structural and morphological analyses were conducted via X-ray diffraction (XRD) and field-emission scanning electron microscopy (SEM). Additionally, the films’ linear and nonlinear optical properties, encompassing absorbance performance, energy gap, refractive index, dielectric, conductivity, and electronegativity, were systematically studied through UV–vis spectroscopy. XRD analysis uncovers the zinc ions substitution by cadmium ions in zinc phosphate’s unit cell, generating oxygen vacancies crucial for maintaining charge neutrality. SEM images then showcase the intricate and organized nano CZP framework. Shifting to optical studies, CZP film analysis spanning 190–2500 nm reveals an indirect energy band gap of 2.92 eV. Transitioning to electrical characteristics, the CZP/p-Si junction undergoes dark mode I-V-T analysis, elucidating the ideality factor, series resistance, and barrier height.
Diabetes induces modifications in costameric proteins and increases cardiomyocyte stiffness
Authors: Romanelli Gerardo , Villarreal Lihuén , Espasandín Camila , Benech Juan Claudio
Published: October 2024

The structural organization of cardiomyocyte proteins is critical for their efficient functioning as a contractile unit in the heart. This work shows that diabetes mellitus induces significant changes in the spatial organization of costamere proteins, t tubules, and intercalated discs. We obtained the first elasticity map sections of living diabetic cardiomyocytes. The results show statistical differences in the map sections of diabetic and control cardiomyocytes, with diabetic cardiomyocytes being stiffer than normal ones.
Effects of age on human skeletal muscle: a systematic review and meta-analysis of myosin heavy chain isoform protein expression, fiber size, and distribution
Authors: Lee Christopher , Woods Philip C. , Paluch Amanda E. , Miller Mark S.
Published: October 2024

Human studies examining the cellular mechanisms behind sarcopenia, or age-related loss of skeletal muscle mass and function, have produced inconsistent results. A systematic review and meta-analysis were performed to determine the aging effects on protein expression, size, and distribution of fibers with various myosin heavy chain (MyHC) isoforms. Study eligibility included MyHC comparisons between young (18–49 yr) and older (≥60 yr) adults, with 27 studies identified. Relative protein expression was higher with age for the slow-contracting MyHC I fibers, with correspondingly lower fast-contracting MyHC II and IIA values. Fiber sizes were similar with age for MyHC I, but smaller for MyHC II and IIA. Fiber distributions were similar with age. When separated by sex, the few studies that examined females showed atrophy of MyHC II and IIA fibers with age, but no change in MyHC protein expression. Additional analyses by measurement technique, physical activity, and muscle biopsies provided important insights. In summary, age-related atrophy in fast-contracting fibers lead to more of the slow-contracting, lower force-producing isoform in older male muscles, which helps explain their age-related loss in whole muscle force, velocity, and power. Exercise or pharmacological interventions that shift MyHC expression toward faster isoforms and/or increase fast-contracting fiber size should decrease the prevalence of sarcopenia. Our findings also indicate that future studies need to include or focus solely on females, measure MyHC IIA and IIX isoforms separately, examine fiber type distribution, sample additional muscles to the vastus lateralis (VL), and incorporate an objective measurement of physical activity.
Exercise to combat cancer: focusing on the ends
Authors: Denham Joshua , Bliss Edward S. , Bryan Tracy M. , O’Brien Brendan J. , Mills Dean
Published: October 2024

Cancer remains a leading cause of death worldwide and although prognosis and survivorship after therapy have improved significantly, current cancer treatments have long-term health consequences. For decades telomerase-mediated telomere maintenance has been an attractive anti-cancer therapeutic target due to its abundance and role in telomere maintenance, pathogenesis, and growth in neoplasms. Telomere maintenance-specific cancer therapies, however, are marred by off-target side effects that must be addressed before they reach clinical practice. Regular exercise training is associated with telomerase-mediated telomere maintenance in normal cells, which is associated with healthy aging. A single bout of endurance exercise training dynamically, but temporarily, increases TERT mRNA and telomerase activity, as well as several molecules that control genomic stability and telomere length (i.e., shelterin and TERRA). Considering the epidemiological findings and accumulating research highlighting that exercise significantly reduces the risk of many types of cancers and the anti-carcinogenic effects of exercise on tumor growth in vitro, investigating the governing molecular mechanisms of telomerase control in context with exercise and cancer may provide important new insights to explain these findings. Specifically, the molecular mechanisms controlling telomerase in both healthy cells and tumors after exercise could reveal novel therapeutic targets for tumor-specific telomere maintenance and offer important evidence that may refine current physical activity and exercise guidelines for all stages of cancer care.
Factors Influencing Decision‐Making for Poststroke Paretic Upper Limb Treatment: A Survey of Japanese Physical and Occupational Therapists
Authors: Hirayama Koichiro , Takebayashi Takashi , Takahashi Kayoko
Published: October 2024

This study investigated the treatment methods used by physical and occupational therapists for poststroke paretic upper limbs and the factors influencing their decision‐making processes. For the treatment methods of poststroke paretic upper limbs, the respondents were asked to select the most clinically used treatment according to the severity of the patient’s condition. For the factors influencing their decision‐making processes, the respondents were asked to indicate each determinant using a 5‐point Likert scale (1 = no influence at all to 5 = very strong influence). Six hundred thirty‐eight therapists participated in this study. Exploratory factor analysis was used to assess the validity of the questionnaire. The findings indicated task‐specific training (N = 333, 52%) as the most popular for mild cases, followed by repetitive facilitative exercise (n = 143, 22.3%) for moderate cases and electrical stimulation (n = 246, 38.4%) for severe cases. This study revealed that evidence about treatment (very strong: n = 171 (27.0%), and strong: n = 287 (45.0%)) and patient preferences (very strong: n = 203 (31.8%), and strong: n = 251 (39.3%)) affected decision‐making significantly regarding treatment methods for the poststroke paretic upper limb.
Seaweed Fly Larvae Cultivated on Macroalgae Side Streams: A Novel Marine Protein and Omega‐3 Source for Rainbow Trout
Authors: Warwas Niklas , Berdan Emma L. , Xie Xintian , Jönsson Elisabeth , Roques Jonathan A. C. , Doyle Darragh , Langeland Markus , Hinchcliffe James , Pavia Henrik , Sundell Kristina
Published: October 2024

A nutritional bottleneck in salmonid aquaculture is the procurement of marine‐derived compounds, such as essential amino and fatty acids, including omega‐3 fatty acids, lysine, and methionine. Therefore, insects containing these compounds are highly promising as feed ingredients. The present study evaluates larvae of a “marine” insect (Coelopa frigida, the bristly‐legged seaweed fly larvae, SWFL) reared on brown algae side streams as a feed ingredient for rainbow trout (Oncorhynchus mykiss). SWFL contained, on a dry matter basis, 60% crude protein (CP), 3.5% lysine, and 1.5% methionine, as well as 17% lipids, including 4% eicosapentaenoic acid and docosahexaenoic acid. Four isoenergetic (ca. 23 MJ kg−1 gross energy) and isoproteic (ca. 45% CP) feeds were evaluated in a 10‐week feeding trial. The diets included a control containing 25% fish meal, a commercial reference, and two diets substituting 40% fish meal with either SWFL or partially defatted black soldier fly larvae (BSFL) meal (Hermetia illucens). SWFL‐fed fish displayed higher specific growth rates (SGR) compared to BSFL‐fed fish and similar SGR compared to control and reference diet‐fed fish. Feed intake in SWFL‐fed fish was higher than for the control and BSFL diets and similar to the reference diet. The feed conversion ratio of fish fed the BSFL and SWFL diets was higher compared to the control, suggesting lower bioavailability of both insect meals compared to fish meals. No difference in intestinal health parameters was noted between the insect diets and the control diet, indicating good intestinal health across all treatments. However, changes in electrogenic intestinal transport were observed between the SWFL and BSFL diets, illustrating the heterogeneous effect of different insect products. Overall, SWFL meal is a promising alternative marine feed ingredient, compatible with circular production systems, as it can be efficiently cultivated using marine side streams.
Dietary Bromelain From Pineapple Extracts Enhanced Growth Performance and Modulated Stomach Microbiota Which Provided Longer‐Term Protection to Penaeus vannamei Against Acute Hepatopancreatic Necrosis Disease (AHPND) Caused by Vibrio parahaemolyticus
Authors: Ng Wing-Keong , Mong Mei-Ling
Published: October 2024

The emergence of acute hepatopancreatic necrosis disease (AHPND) caused by pathogenic strains of Vibrio parahaemolyticus (VPAHPND) had economically impacted shrimp farmers. There is great interest in using phytogenics as antibiotic alternatives in mitigating bacterial diseases. A 28‐day feeding trial using quadruplicate groups of Penaeus vannamei was conducted to evaluate the efficacy of bromelain (BM), a pineapple extract, on growth, gut microbiota, and resistance to AHPND. Dietary 1% or 2% BM enhanced growth of shrimp, which was significantly (P  < 0.05) higher at 2% BM compared to control (0% BM). In the first AHPND challenge, shrimp survival (mean ± SE) fed 1% or 2% BM were 84.8% ± 3.8% and 78.3% ± 2.5%, respectively, and significantly higher compared to the positive control group (69.6% ± 1.8%). Surviving shrimp were then regrouped into triplicates and fed the control diet for 14 days. This wash‐out period was used to determine if prior dietary BM had a longer‐term effect on shrimp health. In the second AHPND challenge, shrimp survival previously fed 1% or 2% BM was 71.1% ± 9.7% and 73.3% ± 3.8%, respectively, and significantly higher compared to the control group (51.1% ± 2.2%). Hepatopancreas showed less damage and harbored significantly lower Vibrio counts in shrimp fed BM‐added diets. Dietary BM modulated the stomach bacterial community and imparted the highest alpha diversity. At the phylum level, Proteobacteria, Actinobacteria, and Bacteroidetes were the main groups across treatments but with varying relative abundance. Luteolibacter, Paracoccus, Planctomyces, and Demequina were identified as the main contributors for the diversity differences observed among treatment groups. The relative abundance of Luteolibacter was significantly enriched and Vibrio bacteria significantly lowered in the stomach of the BM‐added groups. It was concluded that dietary BM induced modulation of the stomach microbiota of shrimp, which potentially enhanced its resistance to AHPND‐causing VP.
Analysis of the Impact of Environmental Regulation Heterogeneity on the Eco‐Economic Efficiency of Mariculture Industry
Authors: Dong Jinli , Shen Manhong
Published: October 2024

Mariculture has not fundamentally reduced its dependence on resources and the environment; ecological and economic efficiency has become an important target of concern for the sustainable and healthy development of China’s mariculture industry. Environmental regulation (ER) is a core tool to realize the synergistic development of economic development and environmental resource protection in mariculture. In this paper, the provincial panel data of China’s coastal areas from 2007 to 2020 was selected, and the level of ecological and economic efficiency of mariculture in different provinces of China was measured by using the super slacks‐based measurement–data envelopment analysis model considering the undesirable output of mariculture, and the impact of different ERs on ecological and economic efficiency was explored. It was found that the impacts of different ER methods on the eco‐economic efficiency (EEF) of mariculture may be non‐linearized, and there is also regional heterogeneity in the optimal choice and combination of ER methods to improve the EEF of mariculture.
Temporal Heterogeneous in the Effectiveness of Inactivated CoronaVac and Sinopharm Vaccines Against SARS‐CoV‐2 Reinfections in China
Authors: Yang Shihong , Xin Hualei , Lang Xingying , Hua Jin , Cui Xiaoman , Li Lu , Ye Chuchu , Qin Ying , Li Yu , Cowling Ben , Lai Shengjie , Sun Ke , Li Zhongjie
Published: October 2024

We aimed to understand the temporal dynamics of SARS‐CoV‐2 reinfection risk and assess the impact of inactivated vaccination on the occurrence of reinfection. We investigated the reinfection risk of SARS‐CoV‐2 from November 1, 2022, to February 12, 2023, when China rapidly lifted the zero‐COVID policy. The study subjects were those who were first infected during the zero‐COVID period between January 1, 2020, and October 31, 2022, in Dalian city, China. Among the 1961 previous infections, 126 (6.4%, 95% CI: 5.4, 7.5) were reinfected. The risk of reinfection increased over time since initial infection. Compared with those who did not receive or received one dose of inactivated vaccine, receiving two or three doses was associated with additional protection against reinfection among individuals who were infected with pre‐Omicron more than a year earlier, with the OR ranged from 0.33 (95% CI: 0.03, 1.83) to 0.91 (95% CI: 0.22, 3.27). In contrast, no protective effect from two or three doses of vaccines against reinfection was observed among those who were first infected with Omicron variants within a year. Primary or booster vaccination contributed to limited protection against reinfection or symptomatic reinfection among individuals infected with Omicron SARS‐CoV‐2 within a year. However, a booster dose after 1 year of natural infection may provide additional protection against reinfection.
A Delphi Exploration of Toileting Activity Performance in Individuals With Cerebral Palsy Within the ICF‐CY Framework: Unveiling Influential Factors
Authors: Riyahi Azade , Akbarfahimi Malahat , Rassafiani Mehdi , Pournasiri Zahra , Ahmadi Maryam , Hassani Mehraban Afsoon
Published: October 2024

Introduction: Cerebral palsy (CP) is a common motor and postural developmental disability impacting daily activities like toileting. Despite its importance, toileting has often been undervalued in healthcare. This study is aimed at identifying and assessing the level of influence of various factors affecting toileting in individuals with CP using the International Classification of Functioning, Disability and Health for Children and Youth (ICF‐CY) framework.

Methods: The Delphi method was employed to reach a consensus on factors influencing toileting in individuals with CP. One hundred fifty‐eight professionals from 17 countries, each with at least 3 years’ experience in CP and/or toileting, participated in this two‐round study. Ethical approval (IR.IUMS.REC.1400.1111) and informed consent were obtained. The questionnaire, available in Farsi and English, used a Likert scale (5 = very high impact to 1 = no impact). Factors with 75% agreement and a mean above 3.75 were included in the final list, while those with 50%–75% agreement or a mean between 2.5 and 3.75 proceeded to the second round. Factors were initially identified through a literature review and research team consultation and categorized according to the ICF‐CY framework using the ICF 10 RULES. Validation and refinement were done through focus groups with caregivers and experienced professionals to ensure alignment with the framework and methodological rigor.

Results: The study highlighted significant factors influencing toileting activities in individuals with CP. Within the ICF‐CY framework, “neuromusculoskeletal and movement‐related functions” scored highest at 94.5% in “body functions and structures.” “Toilet environment” scored 90.5% in “environmental factors.” Support and relationship factors scored 82.3%. Attitudes toward “menstruation” ranked highest at 92.9%. Associated deficits with CP ranked top in personal factors at 93.7%.

Conclusion: The study identifies key factors influencing toileting activity performance in individuals with CP. “Main caregiver” emerges as a pivotal factor, followed by neuromusculoskeletal functions, personal factors, attitudes toward menstruation, the toilet environment, and support and relationships.
Supplementary Fig 1 from Steroid Ligands, the Forgotten Triggers of Nuclear Receptor Action; Implications for Acquired Resistance to Endocrine Therapy
Authors: Bleach Rachel , Madden Stephen F. , Hawley James , Charmsaz Sara , Selli Cigdem , Sheehan Katherine M. , Young Leonie S. , Sims Andrew H. , Souček Pavel , Hill Arnold D. , McIlroy Marie
Published: October 2024

KM survival data based on therapy
Supplementary materials from Darolutamide Potentiates the Antitumor Efficacy of a PSMA-targeted Thorium-227 Conjugate by a Dual Mode of Action in Prostate Cancer Models
Authors: Hammer Stefanie , Schlicker Andreas , Zitzmann-Kolbe Sabine , Baumgart Simon , Hagemann Urs B. , Scholz Arne , Haendler Bernard , Lejeune Pascale , Karlsson Jenny , Ellingsen Christine , Hennekes Hartwig , Nielsen Carsten H. , Juul Mark U. , Mumberg Dominik , Schatz Christoph A.
Published: October 2024

Supplementary methods (1), tables (1) and figures (8)
Supplementary Table from Identification of a Novel Inflamed Tumor Microenvironment Signature as a Predictive Biomarker of Bacillus Calmette-Guérin Immunotherapy in Non–Muscle-Invasive Bladder Cancer
Authors: Damrauer Jeffrey S. , Roell Kyle R. , Smith Markia A. , Sun Xuezheng , Kirk Erin L. , Hoadley Katherine A. , Benefield Halei C. , Iyer Gopakumar , Solit David B. , Milowsky Matthew I. , Kim William Y. , Nielsen Matthew E. , Wobker Sara E. , Dalbagni Guido , Al-Ahmadie Hikmat A. , Olshan Andrew F. , Bochner Bernard H. , Furberg Helena , Troester Melissa A. , Pietzak Eugene J.
Published: October 2024

Supplementary Table 1, 2, 3
Supplementary Figure 2 from Identification of a Novel Inflamed Tumor Microenvironment Signature as a Predictive Biomarker of Bacillus Calmette-Guérin Immunotherapy in Non–Muscle-Invasive Bladder Cancer
Authors: Damrauer Jeffrey S. , Roell Kyle R. , Smith Markia A. , Sun Xuezheng , Kirk Erin L. , Hoadley Katherine A. , Benefield Halei C. , Iyer Gopakumar , Solit David B. , Milowsky Matthew I. , Kim William Y. , Nielsen Matthew E. , Wobker Sara E. , Dalbagni Guido , Al-Ahmadie Hikmat A. , Olshan Andrew F. , Bochner Bernard H. , Furberg Helena , Troester Melissa A. , Pietzak Eugene J.
Published: October 2024

Supplemental Figure 2A shows FGFR3 Expression by UROMOL Subclasses in MSK and UNC cohorts and Supplemental Figure 2B demonstrates the Inverse Relationship between FGFR3 expression and mutation with Immune Signature Score.
Data from Darolutamide Potentiates the Antitumor Efficacy of a PSMA-targeted Thorium-227 Conjugate by a Dual Mode of Action in Prostate Cancer Models
Authors: Hammer Stefanie , Schlicker Andreas , Zitzmann-Kolbe Sabine , Baumgart Simon , Hagemann Urs B. , Scholz Arne , Haendler Bernard , Lejeune Pascale , Karlsson Jenny , Ellingsen Christine , Hennekes Hartwig , Nielsen Carsten H. , Juul Mark U. , Mumberg Dominik , Schatz Christoph A.
Published: October 2024

AbstractPurpose:
Androgen receptor (AR) inhibitors are well established in the treatment of castration-resistant prostate cancer and have recently shown efficacy also in castration-sensitive prostate cancer. Although most patients respond well to initial therapy, resistance eventually develops, and thus, more effective therapeutic approaches are needed. Prostate-specific membrane antigen (PSMA) is highly expressed in prostate cancer and presents an attractive target for radionuclide therapy. Here, we evaluated the efficacy and explored the mode of action of the PSMA-targeted thorium-227 conjugate (PSMA-TTC) BAY 2315497, an antibody-based targeted alpha-therapy, in combination with the AR inhibitor darolutamide.
Experimental Design:
The in vitro and in vivo antitumor efficacy and mode of action of the combination treatment were investigated in preclinical cell line–derived and patient-derived prostate cancer xenograft models with different levels of PSMA expression.
Results:
Darolutamide induced the expression of PSMA in androgen-sensitive VCaP and LNCaP cells in vitro, and the efficacy of darolutamide in combination with PSMA-TTC was synergistic in these cells. In vivo, the combination treatment showed synergistic antitumor efficacy in the low PSMA-expressing VCaP and in the high PSMA-expressing ST1273 prostate cancer models, and enhanced efficacy in the enzalutamide-resistant KUCaP-1 model. The treatments were well tolerated. Mode-of-action studies revealed that darolutamide induced PSMA expression, resulting in higher tumor uptake of PSMA-TTC, and consequently, higher antitumor efficacy, and impaired PSMA-TTC–mediated induction of DNA damage repair genes, potentially contributing to increased DNA damage.
Conclusions:
These results provide a strong rationale to investigate PSMA-TTC in combination with AR inhibitors in patients with prostate cancer.
Data from Inhibition of DNA-PK with AZD7648 Sensitizes Tumor Cells to Radiotherapy and Induces Type I IFN-Dependent Durable Tumor Control
Authors: Nakamura Kyoko , Karmokar Ankur , Farrington Paul M. , James Neil H. , Ramos-Montoya Antonio , Bickerton Susan J. , Hughes Gareth D. , Illidge Timothy M. , Cadogan Elaine B. , Davies Barry R. , Dovedi Simon J. , Valge-Archer Viia
Published: October 2024

AbstractPurpose:
Combining radiotherapy (RT) with DNA damage response inhibitors may lead to increased tumor cell death through radiosensitization. DNA-dependent protein kinase (DNA-PK) plays an important role in DNA double-strand break repair via the nonhomologous end joining (NHEJ) pathway. We hypothesized that in addition to a radiosensitizing effect from the combination of RT with AZD7648, a potent and specific inhibitor of DNA-PK, combination therapy may also lead to modulation of an anticancer immune response.
Experimental Design:
AZD7648 and RT efficacy, as monotherapy and in combination, was investigated in fully immunocompetent mice in MC38, CT26, and B16-F10 models. Immunologic consequences were analyzed by gene expression and flow-cytometric analysis.
Results:
AZD7648, when delivered in combination with RT, induced complete tumor regressions in a significant proportion of mice. The antitumor efficacy was dependent on the presence of CD8+ T cells but independent of NK cells. Analysis of the tumor microenvironment revealed a reduction in T-cell PD-1 expression, increased NK-cell granzyme B expression, and elevated type I IFN signaling in mice treated with the combination when compared with RT treatment alone. Blocking of the type I IFN receptor in vivo also demonstrated a critical role for type I IFN in tumor growth control following combined therapy. Finally, this combination was able to generate tumor antigen-specific immunologic memory capable of suppressing tumor growth following rechallenge.
Conclusions:
Blocking the NHEJ DNA repair pathway with AZD7648 in combination with RT leads to durable immune-mediated tumor control.
Data from Pharmacodynamic Biomarkers Predictive of Survival Benefit with Lenvatinib in Unresectable Hepatocellular Carcinoma: From the Phase III REFLECT Study
Authors: Finn Richard S. , Kudo Masatoshi , Cheng Ann-Lii , Wyrwicz Lucjan , Ngan Roger K.C. , Blanc Jean-Frederic , Baron Ari D. , Vogel Arndt , Ikeda Masafumi , Piscaglia Fabio , Han Kwang-Hyub , Qin Shukui , Minoshima Yukinori , Kanekiyo Michio , Ren Min , Dairiki Ryo , Tamai Toshiyuki , Dutcus Corina E. , Ikezawa Hiroki , Funahashi Yasuhiro , Evans Thomas R. Jeffry
Published: October 2024

AbstractPurpose:
In REFLECT, lenvatinib demonstrated an effect on overall survival (OS) by confirmation of noninferiority to sorafenib in unresectable hepatocellular carcinoma. This analysis assessed correlations between serum or tissue biomarkers and efficacy outcomes from REFLECT.
Experimental Design:
Serum biomarkers (VEGF, ANG2, FGF19, FGF21, and FGF23) were measured by ELISA. Gene expression in tumor tissues was measured by the nCounter PanCancer Pathways Panel. Pharmacodynamic changes in serum biomarker levels from baseline, and associations of clinical outcomes with baseline biomarker levels, were evaluated.
Results:
Four hundred and seven patients were included in the serum analysis set (lenvatinib n = 279, sorafenib n = 128); 58 patients were included in the gene-expression analysis set (lenvatinib n = 34, sorafenib n = 24). Both treatments were associated with increases in VEGF; only lenvatinib was associated with increases in FGF19 and FGF23 at all time points. Lenvatinib-treated responders had greater increases in FGF19 and FGF23 versus nonresponders at cycle 4, day 1 (FGF19: 55.2% vs. 18.3%, P = 0.014; FGF23: 48.4% vs. 16.4%, P = 0.0022, respectively). Higher baseline VEGF, ANG2, and FGF21 correlated with shorter OS in both treatment groups. OS was longer for lenvatinib than sorafenib [median, 10.9 vs. 6.8 months, respectively; HR, 0.53; 95% confidence interval (CI), 0.33–0.85; P-interaction = 0.0397] with higher baseline FGF21. In tumor tissue biomarker analysis, VEGF/FGF-enriched groups showed improved OS with lenvatinib versus the intermediate VEGF/FGF group (HR, 0.39; 95% CI, 0.16–0.91; P = 0.0253).
Conclusions:
Higher baseline levels of VEGF, FGF21, and ANG2 may be prognostic for shorter OS. Higher baseline FGF21 may be predictive for longer OS with lenvatinib compared with sorafenib, but this needs confirmation.