bluuebunny/crossref_metadata_2025_split huggingface dataset:
In silico guided pre‐treatment of sugarcane juice with natural inhibitors of polyphenol oxidase (PPO) is a new and effective strategy for development of spray‐dried formulation
Authors: Kanagaraj Jaya Chendrayan , Jana Shilpa B. , Marathe Sandesh J. , Singhal Rekha S. 
Published: February 2024

AbstractSugarcane juice is a popular beverage and is also processed to produce sugar. The polyphenol oxidase (PPO) in sugarcane juice causes enzymatic browning and makes the process of sugar production complex and cumbersome. Storage of sugarcane juice is also hampered by the high sugar content and rapid microbial fermentation. The present research assessed the potential of lemon juice (LJ) and ginger extract (GE) as natural inhibitors of PPO. Enzyme kinetics and the mechanism of inhibition of LJ and GE were studied. Primary investigation was carried out using molecular docking approach to assess the inhibitory potential of LJ and GE and to determine the nature of interaction between the enzyme and inhibitors. Extracts were used as inhibitors and studies revealed that both reduced the PPO activity. Subsequently, pure bioactive inhibitors such as ascorbic acid, citric acid, and 6‐shogaol present in these natural extracts were used to study the mode of inhibition of PPO. Citric acid decreased PPO activity by lowering pH, while ascorbic acid was found to be a competitive inhibitor of PPO with a Ki of 75.69 µM. The proportion of LJ and GE required in sugarcane juice was optimized on the basis of browning index and sensory acceptance. Further, the sugarcane cane juice after inhibition of PPO under optimized conditions was spray dried and evaluated for reconstitution properties. The product formulated in the present study is a new and effective approach to address quality‐compromising issues associated with long‐term storage of cane juice.
Novel Lactobacillaceae strains and consortia to produce propionate‐containing fermentates as biopreservatives
Authors: Buljubašić Ena , Bambace Maria Florencia , Christensen Mie Henriette Løve , Ng Ker‐Sin , Huertas‐Díaz Lucía , Sundekilde Ulrik , Marietou Angeliki , Schwab Clarissa 
Published: February 2024

AbstractBiopreservation refers to the use of natural or controlled microbial single strains or consortia, and/or their metabolites such as short‐chain carboxylic acids (SCCA), to improve the shelf‐life of foods. This study aimed at establishing a novel Lactobacillaceae‐driven bioprocess that led to the production of the SCCA propionate through the cross‐feeding on 1,2‐propanediol (1,2‐PD) derived from the deoxyhexoses rhamnose or fucose. When grown as single cultures in Hungate tubes, strains of Lacticaseibacillus rhamnosus preferred fucose over rhamnose and produced 1,2‐PD in addition to lactate, acetate, and formate, while Limosilactobacillus reuteri metabolized 1,2‐PD into propionate, propanol and propanal. Loigolactobacillus coryniformis used fucose to produce 1,2‐PD and only formed propionate when supplied with 1,2‐PD. Fermentates collected from batch fermentations in bioreactor using two‐strain consortia (L. rhamnosus and L. reuteri) or fed‐batch fermentations of single strain cultures of L. coryniformis with rhamnose contained mixtures of SCCA consisting of mainly lactate and acetate and also propionate. Synthetic mixtures that contained SCCA at concentrations present in the fermentates were more antimicrobial against Salmonella enterica if propionate was present. Together, this study (i) demonstrates the potential of single strains and two‐strain consortia to produce propionate in the presence of deoxyhexoses extending the fermentation metabolite profile of Lactobacillaceae, and (ii) emphasizes the potential of applying propionate‐containing fermentates as biopreservatives.
Exploring deep learning techniques for wild animal behaviour classification using animal‐borne accelerometers
Authors: Otsuka Ryoma , Yoshimura Naoya , Tanigaki Kei , Koyama Shiho , Mizutani Yuichi , Yoda Ken , Maekawa Takuya 
Published: February 2024

Abstract

Machine learning‐based behaviour classification using acceleration data is a powerful tool in bio‐logging research. Deep learning architectures such as convolutional neural networks (CNN), long short‐term memory (LSTM) and self‐attention mechanism as well as related training techniques have been extensively studied in human activity recognition. However, they have rarely been used in wild animal studies. The main challenges of acceleration‐based wild animal behaviour classification include data shortages, class imbalance problems, various types of noise in data due to differences in individual behaviour and where the loggers were attached and complexity in data due to complex animal‐specific behaviours, which may have limited the application of deep learning techniques in this area.

To overcome these challenges, we explored the effectiveness of techniques for efficient model training: data augmentation, manifold mixup and pre‐training of deep learning models with unlabelled data, using datasets from two species of wild seabirds and state‐of‐the‐art deep learning model architectures.

Data augmentation improved the overall model performance when one of the various techniques (none, scaling, jittering, permutation, time‐warping and rotation) was randomly applied to each data during mini‐batch training. Manifold mixup also improved model performance, but not as much as random data augmentation. Pre‐training with unlabelled data did not improve model performance. The state‐of‐the‐art deep learning models, including a model consisting of four CNN layers, an LSTM layer and a multi‐head attention layer, as well as its modified version with shortcut connection, showed better performance among other comparative models. Using only raw acceleration data as inputs, these models outperformed classic machine learning approaches that used 119 handcrafted features.

Our experiments showed that deep learning techniques are promising for acceleration‐based behaviour classification of wild animals and highlighted some challenges (e.g. effective use of unlabelled data). There is scope for greater exploration of deep learning techniques in wild animal studies (e.g. advanced data augmentation, multimodal sensor data use, transfer learning and self‐supervised learning). We hope that this study will stimulate the development of deep learning techniques for wild animal behaviour classification using time‐series sensor data.
METTL14 affects UVB‐induced human dermal fibroblasts photoaging via miR‐100‐3p biogenesis in an m6A‐dependent manner
Authors: Chen Lihao , Hu Yu , Zhang Min , Liu Lihao , Ma Jing , Xu Zhuohong , Zhang Jiaan , Gu Heng , Chen Kun 
Published: February 2024

AbstractExposure to ultraviolet radiation can lead to skin photoaging, which increases the risk of skin tumors. This study aims to investigate how microRNA m6A modification contributes to skin photoaging. This study found that skin fibroblasts exposed to a single UVB dose of 30 mJ/cm2 exhibited characteristics of photoaging. The m6A level of total RNA decreased in photoaged cells with a down‐regulated level of METTL14, and overexpression of METTL14 displayed a photoprotective function. Moreover, miR‐100‐3p was a downstream target of METTL14. And METTL14 could affect pri‐miR‐100 processing to mature miR‐100‐3p in an m6A‐dependent manner via DGCR8. Furthermore, miR‐100‐3p targeted at 3′ end untranslated region of ERRFI1 mRNA with an inhibitory effect on translation. Additionally, photoprotective effects of overexpression of METTL14 were reversed by miR‐100‐3p inhibitor or overexpression of ERRFI1. In UVB‐induced photoaging of human skin fibroblasts, METTL14‐dependent m6A can regulate miR‐100‐3p maturation via DGCR8 and affect skin fibroblasts photoaging through miR‐100‐3p/ERRFI1 axis.
Double mutualism involving Melocactus (Cactaceae) and lizards in the Brazilian Caatinga: Another isolated case or is it an established interaction?
Authors: Bezerra‐Silva Alexsandro , Gomes Vanessa Gabrielle Nóbrega , Albuquerque‐Lima Sinzinando , Nadia Tarcila Lima , Machado Isabel Cristina , Silveira Funch Ligia 
Published: February 2024

AbstractThis work discusses a fascinating ecological relationship, in which the lizard Tropidurus cocorobensis and the cactus Melocactus violaceus engage in a double mutualism. In this interaction, observed in a Caatinga, a dry tropical forest in Northeastern Brazil, T. cocorobensis feed on the nectar and pollen of M. violaceus, transferring the grains to the stigmas of another flower, acting as a potential pollinator. Additionally, the lizards consume fruits of M. violaceus, helping to disperse the seeds. The concentrated nectar of M. violaceus attracts lizards, and the morphological compatibility between the small pink flowers and the size of T. cocorobensis is important to this double mutualism. The findings mentioned here highlight the importance of Tropidurus lizards in the reproductive success of Melocactus species and provide insights into the coevolution of these species in a seasonal and resource‐scarce environment, like the Caatinga.
Recruitment failure of keystone trees in Phytophthora infested forest
Authors: Mansfield Thomas , Hardy Giles , Fleming Patricia , Standish Rachel 
Published: February 2024

AbstractInvasive plant pathogens cause considerable forest loss worldwide. However, little is known about how tree populations recover post‐invasion. In Western Australia, Phytophthora cinnamomi ‘dieback’ affects jarrah (Eucalyptus marginata), with historical records of mass deaths in this keystone tree species due to infestation, resulting in permanent loss of standing forest. Historical observations of marri (Corymbia calophylla), a co‐dominant keystone jarrah forest tree, suggest it is resistant to P. cinnamomi. Impacts of P. cinnamomi on the population dynamics of jarrah and marri are unknown. We recorded densities and stem diameters of jarrah and marri in a peri‐urban forest to examine their population demographics in >60‐year‐old P. cinnamomi infestations compared with adjacent non‐infested forest. While seedling (<0.5 cm stem diameter, ~ 2 –15 cm tall) densities were not significantly different, total tree densities were 43% (jarrah) and 48% (marri) lower for infested sites. Densities of jarrah 0.5–9 and 20–29 cm stem diameters were lower within infestations. Survival probabilities of jarrah seedlings were significantly greater in P. cinnamomi infestations, but those of mature jarrah were not different. While average marri stem density was 49% greater within infestations, densities of small marri (<20 cm stem diameter) were lower within infestations. Survival probabilities for marri seedlings were significantly decreased in infestations, while there was greater survival probability for mature marri within P. cinnamomi infestations. Our data suggest recruitment of jarrah and marri has likely reduced since P. cinnamomi invasion. This is the first documented impact on marri, which indicates that we have been overlooking the risk of decline due to P. cinnamomi for this species. We stress the need for continued management and highlight the necessity of planting seedlings ~6 months old, and assisting their survival with phosphite and fertilizers, to bolster local tree populations.
Phenotypic correlations of carpal gland diverticular number with production traits and its genome‐wide association analysis in multiple pig populations
Authors: Cui Dengshuai , Li Longyun , Yu Naibiao , Xiong Sanya , Xiao Shijun , Zheng Hao , Huang Zhiyong , Guo Yuanmei , Huang Lusheng 
Published: February 2024

AbstractPig carpal glands play crucial roles in territorial recognition, reproductive behavior, and information exchange; however, their effects on production traits and underlying genetic mechanisms remain unclear. In this study, 1028 pigs from six populations were counted for the carpal gland diverticular numbers (CGDNs) on the left (CGDNL) and right (CGDNR) legs, and their carcass and meat quality traits were assessed. The CGDNs were significantly different among the populations, and Licha Black pigs had a lower CGDN than the Bama Xiang breed. It was also significantly different between sexes, with males having more diverticula than females (p ≤ 0.0391). Moreover, the number was asymmetric, with CGDNR being significantly higher than CGDNL. Notably, CGDNs was significantly correlated with each other in phenotype and genetics and with 24‐h pH, 24‐h meat color score, 24‐h marbling score, fat content, moisture content, sodium salt content, and saturated fatty acid content in phenotype. Furthermore, genome‐wide association analyses identified seven SNPs in association with CGDNs at a 5% genome‐wide significance level, all of which were located in a 1.78‐Mb (35.347–37.129 Mb) region on chromosome 1. CNC10010837 and CNC10010840 were the top SNPs: both had an additive effect of 0.789 ± 0.120 on CGDNR with p = 8.31E‐10. These findings provide important insights into the functions and underlying genetic mechanisms of swine carpal glands.
Unified robust estimation
Authors: Wang Zhu 
Published: February 2024

SummaryRobust estimation is primarily concerned with providing reliable parameter estimates in the presence of outliers. Numerous robust loss functions have been proposed in regression and classification, along with various computing algorithms. In modern penalised generalised linear models (GLMs), however, there is limited research on robust estimation that can provide weights to determine the outlier status of the observations. This article proposes a unified framework based on a large family of loss functions, a composite of concave and convex functions (CC‐family). Properties of the CC‐family are investigated, and CC‐estimation is innovatively conducted via the iteratively reweighted convex optimisation (IRCO), which is a generalisation of the iteratively reweighted least squares in robust linear regression. For robust GLM, the IRCO becomes the iteratively reweighted GLM. The unified framework contains penalised estimation and robust support vector machine (SVM) and is demonstrated with a variety of data applications.
Effects of starch content of calf starter on rumen properties and blood concentrations of metabolites and hormones in dairy calves under a high plane of milk feeding
Authors: Satoh Hitomi , Fukumori Rika , Kumano Ren , Kamata Maho , Shimada Kensuke , Izumi Kenichi , Oikawa Shin 
Published: February 2024

AbstractThe objective of this study was to investigate the effects of calf starters with different starch content on rumen and blood properties in calves fed under a high plane of nutrition program. Twenty‐seven Holstein calves (14 female, 13 male) were assigned to one of three starter treatment groups in a randomized block design: high‐starch (41.8%) (n = 9), H; medium‐starch (31.9%) (n = 9), M; low‐starch (22.0%) (n = 9), L. Milk replacer on powder basis was fed up to 1.2 kg/day as fed, gradually reduced from 6 weeks of age; calves were weaned at 8 weeks of age. Each starter (up to 3.5 kg/day as fed) and chopped hay were provided ad libitum from 5 days of age. Blood was collected from 4 to 13 weeks of age. Rumen fluid was collected at 6, 8, 10, and 13 weeks of age. Serum urea nitrogen concentration after weaning was the lowest in H. Plasma IGF‐1 concentrations were higher in H than in L. Ruminal pH was not different, but the molar proportion of ruminal propionate was higher in H than in L throughout the study period. In summary, a high‐starch starter may increase propionate production and microbial protein synthesis in the rumen, inducing higher plasma IGF‐1 concentrations.
Holotoxin A1 from Apostichopus japonicus inhibited oropharyngeal and intra‐abdominal candidiasis by inducing oxidative damage in Candida albicans
Authors: Liao Min , Xia Xuekui , Meng Qingzhou , Zhu Chengguang , Liao Binyou , Wang Jiannan , Gou Lichen , Zhou Xuedong , Yuan Wenpeng , Cheng Lei , Ren Biao 
Published: February 2024

AbstractBackground and PurposeThe holotoxin A1, isolated from Apostichopus japonicus, exhibits potent antifungal activities, but the mechanism and efficacy against candidiasis are unclear. In this study we have studied the antifungal effects and mechanism of holotoxin A1 against Candida albicans and in murine oropharyngeal and intra‐abdominal candidiasis.Experimental ApproachThe antifungal effect of holotoxin A1 against C. albicans was tested in vitro. To explore the antifungal mechanism of holotoxin A1, the transcriptome, ROS levels, and mitochondrial function of C. albicans was evaluated. Effectiveness and systematic toxicity of holotoxin A1 in vivo was assessed in the oropharyngeal and intra‐abdominal candidiasis models in mice.Key ResultsHolotoxin A1 was a potent fungicide against C. albicans SC5314, clinical strains and drug‐resistant strains. Holotoxin A1 inhibited oxidative phosphorylation and induced oxidative damage by increasing intracellular accumulation of ROS in C. albicans. Holotoxin A1 induced dysfunction of mitochondria by depolarizing the mitochondrial membrane potential and reducing the production of ATP. Holotoxin A1 directly inhibited the enzymatic activity of mitochondrial complex I and antagonized with the rotenone, an inhibitor of complex I, against C. albicans. Meanwhile, the complex I subunit NDH51 null mutants showed a decreased susceptibility to holotoxin A1. Furthermore, holotoxin A1 significantly reduced fungal burden and infections with no significant systemic toxicity in oropharyngeal and intra‐abdominal candidiasis in murine models.Conclusion and ImplicationsHolotoxin A1 is a promising candidate for the development of novel antifungal agents against both oropharyngeal and intra‐abdominal candidiasis, especially when caused by drug‐resistant strains.
Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy
Authors: Minegishi Yuriko , Haga Yoshimi , Ueda Koji 
Published: February 2024

AbstractWith significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor‐specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the “dark matter” of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine‐learning‐supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.
Enhancing scene‐text visual question answering with relational reasoning, attention and dynamic vocabulary integration
Authors: Agrawal Mayank , Jalal Anand Singh , Sharma Himanshu 
Published: February 2024

AbstractVisual question answering (VQA) is a challenging task in computer vision. Recently, there has been a growing interest in text‐based VQA tasks, emphasizing the important role of textual information for better understanding of images. Effectively utilizing text information within the image is crucial for achieving success in this task. However, existing approaches often overlook the contextual information and neglect to utilize the relationships between scene‐text tokens and image objects. They simply incorporate the scene‐text tokens mined from the image into the VQA model without considering these important factors. In this paper, the proposed model initially analyzes the image to extract text and identify scene objects. It then comprehends the question and mines relationships among the question, OCRed text, and scene objects, ultimately generating an answer through relational reasoning by conducting semantic and positional attention. Our decoder with attention map loss enables prediction of complex answers and handles dynamic vocabularies, reducing decoding space. It outperforms softmax‐based cross entropy loss in accuracy and efficiency by accommodating varying vocabulary sizes. We evaluated our model's performance on the TextVQA dataset and achieved an accuracy of 53.91% on the validation set and 53.98% on the test set. Moreover, on the ST‐VQA dataset, our model obtained ANLS scores of 0.699 on the validation set and 0.692 on the test set.
Mapping social conflicts to enhance the integrated management of white‐tailed deer (Odocoileus virginianus)
Authors: Stinchcomb Taylor R. , Ma Zhao , Swihart Robert K. , Caudell Joe N. , Nyssa Zoe , Sponarski Carly C. 
Published: February 2024

AbstractUnderstanding the social feasibility of wildlife conservation approaches is essential to reducing social conflicts over wildlife and public backlash toward wildlife agencies and organizations. The Potential for Conflict Index2 (PCI2) and geospatial analyses of conflict can help wildlife practitioners strategically engage their publics, but these two tools have yet to be combined. Using data from a 2021 survey about white‐tailed deer in Indiana (n = 1806), we analyzed conflict levels among stakeholder self‐identities and political ideologies regarding the acceptability of six possible management methods, three lethal and three nonlethal. We then conducted a hotspot analysis of gridded PCI2 values to map areas of high and low social conflicts across the state. Conflict potentials showed more consistent covariation with political ideologies than with stakeholder self‐identities, aligning with urban–rural divides in wildlife experiences. Data on political leanings and residency may thus be more reliable than stakeholder categories to predict social conflicts over wildlife management. Hotspots of conflict over lethal methods clustered around urban areas, indicating that agencies should focus on engaging urban residents about deer management. Our conflict hotspots can be combined with other spatial data to create social units of analysis, which can help practitioners develop targeted and socially accepted strategies for wildlife conservation and management.