Hasil untuk "Animal culture"

Xiaoqian Lv, Qiang Wei, Junjie Sun et al.

Chicken primordial germ cells (PGCs) hold significant value in avian gene-editing breeding and biomedical research. However, existing technologies are plagued by issues such as low transfection efficiency, high costs, and long screening and culture cycles, which have restricted their industrial application. In this study, an optimized electroporation knock-in system for chicken PGCs was established, comprising PGCs, a specific transfection vector (Z-NC_006127.4-200F-U6-TOP1-sgRNA-PGK-Puro-T2A-mCherry-Z-NC_006127.4-200R), Opti-MEM™ transfection buffer, and electroporation parameters (duration of Poring Pause: 10 ms, voltage of Poring Pause: 140 V, and cycles of poring pulses: 6). Additionally, a rapid enrichment method for positive cells based on limiting dilution and puromycin selection was developed. This system improved the transfection efficiency from < 5 % (using liposome transfection) to 54 %, reduced the cost per transfection by 90 %, and enabled the acquisition of positive cell lines with a purity of > 95 % within one month, while the cells retained their stem cell properties. This research provides an efficient and low-cost solution for the industrial application of avian gene-editing technology.

Yue Wang, Lawrence Amadi, Xiang Gao et al.

We present a zero-shot framework for transferring human facial expressions to 3D animal face meshes. Our method combines intrinsic geometric descriptors (HKS/WKS) with a mesh-agnostic latent embedding that disentangles facial identity and expression. The ID latent space captures species-independent facial structure, while the expression latent space encodes deformation patterns that generalize across humans and animals. Trained only with human expression pairs, the model learns the embeddings, decoupling, and recoupling of cross-identity expressions, enabling expression transfer without requiring animal expression data. To enforce geometric consistency, we employ Jacobian loss together with vertex-position and Laplacian losses. Experiments show that our approach achieves plausible cross-species expression transfer, effectively narrowing the geometric gap between human and animal facial shapes.

Yakup Yıldırım, Seval Bilge Dağalp, Gökhan Bozkurt et al.

ABSTRACT Background The orf virus (ORFV) is a viral pathogen that primarily causes contagious ecthyma in humans and different ruminants. The infection, which is common worldwide, causes large‐scale economic losses to animal breeders. Objective and Methods In this study, tissue samples collected from eight randomly selected goats with dermatological lesions on the teats were examined in different goat herds. B2L gene‐specific primer pairs (PP1, PP3 and PP4) were used to reveal the presence of ORFV by molecular methods and for phylogenetic analysis. Results Viral DNA was detected in four of eight tissues using the semi‐nested PCR method. In addition, the data obtained by performing sequence analyses of the amplicons with positive results were compared with the information of different ORFV isolates registered in the GenBank database. Based on the sequence analysis of the field isolates obtained in our study, it was found that the nucleotide similarities among these isolates and those from Asian countries were 100%. Furthermore, ORFV isolates collected from different species and produced in Türkiye over various periods exhibited homologous nucleotide sequences with similarities ranging from 98.1% to 98.8%. In the phylogenetic tree drawn based on the B2L genomic region, it was observed that our field isolates were classified in Group I together with other Turkish and Asian strains. Conclusion As a result, while other pathogenic agents are considered the cause of disease in goats with dermatological lesions on their mammary tissue, the ORFV should also be evaluated, and protection and control programs should be prepared accordingly.

Akshit R. Suthar, Alan R. Biggs, James T. Anderson

Despite increasing conservation efforts for shorebirds, there are widespread declines in many shorebird species in North America. Climate change is causing significant shorebird range shifts and population declines. This study investigates the relationship between meteorological variability and shorebird population dynamics over ten years (2014–2023) at Fish Haul Beach, Hilton Head Island, South Carolina, USA. Shorebirds, reliant on specific habitats for breeding and foraging, are increasingly vulnerable to climate-driven changes, including shifts in temperature, precipitation, and wind speed. Using Generalized Additive Models with Poisson distribution, we analyzed species-specific count data for 12 shorebird species in relation to annual meteorological variables. Additionally, the Mann–Kendall test and Sen’s slope were employed to assess decadal trends in population counts. The results reveal significant declines in Black-bellied Plover (<i>Pluvialis squatarola</i>), Marbled Godwit (<i>Limosa fedoa</i>), and Willet (<i>Tringa semipalmata</i>). In contrast, Semipalmated Plover (<i>Charadrius semipalmatus</i>) and Piping Plover (<i>Charadrius melodus</i>) showed increasing trends, indicating potential habitat benefits or conservation success. Temperature emerged as a key driver affecting the abundance of several species, while precipitation and wind speed also played crucial roles in shaping population dynamics. Our findings underscore the sensitivity of shorebird populations to weather fluctuations, emphasizing the need for integrating meteorological variability into management strategies to ensure shorebird conservation. This study provides critical insights into the impacts of meteorological variables on migratory shorebird populations along the Atlantic Flyway. It highlights the importance of maintaining healthy coastal ecosystems in South Carolina.

Farhan Farsi, Farnaz Aghababaloo, Shahriar Shariati Motlagh et al.

As large language models (LLMs) become increasingly embedded in our daily lives, evaluating their quality and reliability across diverse contexts has become essential. While comprehensive benchmarks exist for assessing LLM performance in English, there remains a significant gap in evaluation resources for other languages. Moreover, because most LLMs are trained primarily on data rooted in European and American cultures, they often lack familiarity with non-Western cultural contexts. To address this limitation, our study focuses on the Persian language and Iranian culture. We introduce 19 new evaluation datasets specifically designed to assess LLMs on topics such as Iranian law, Persian grammar, Persian idioms, and university entrance exams. Using these datasets, we benchmarked 41 prominent LLMs, aiming to bridge the existing cultural and linguistic evaluation gap in the field.

Saeed Almheiri, Rania Hossam, Mena Attia et al.

Large language models (LLMs) often reflect Western-centric biases, limiting their effectiveness in diverse cultural contexts. Although some work has explored cultural alignment, the potential for cross-cultural transfer, using alignment in one culture to improve performance in others, remains underexplored. This paper investigates cross-cultural transfer of commonsense reasoning in the Arab world, where linguistic and historical similarities coexist with local cultural differences. Using a culturally grounded commonsense reasoning dataset covering 13 Arab countries, we evaluate lightweight alignment methods such as in-context learning and demonstration-based reinforcement (DITTO), alongside baselines like supervised fine-tuning and direct preference optimization. Our results show that merely 12 culture-specific examples from one country can improve performance in others by 10\% on average, within multilingual models. In addition, we demonstrate that out-of-culture demonstrations from Indonesia and US contexts can match or surpass in-culture alignment for MCQ reasoning, highlighting cultural commonsense transferability beyond the Arab world. These findings demonstrate that efficient cross-cultural alignment is possible and offer a promising approach to adapt LLMs to low-resource cultural settings.

Spencer Dean Stewart

This paper presents a quantitative approach to studying linguistic and cultural change in China during the first half of the twentieth century, a period that remains understudied in computational humanities research. The dramatic changes in Chinese language and culture during this time call for greater reflection on the tools and methods used for text analysis. This preliminary study offers a framework for analyzing Chinese texts from the late nineteenth and twentieth centuries, demonstrating how established methods such as word counts and word embeddings can provide new historical insights into the complex negotiations between Western modernity and Chinese cultural discourse.

Jayanth Venkatarama Reddy, Nelson Ndahiro, Lateef Aliyu et al.

The majority of therapeutic monoclonal antibodies (mAbs) on the market are produced using Chinese Hamster Ovary (CHO) cells cultured at scale in chemically defined cell culture medium. Because of the high costs associated with mammalian cell cultures, obtaining high cell densities to produce high product titers is desired. These bioprocesses require high concentrations of nutrients in the basal media and periodically adding concentrated feed media to sustain cell growth and therapeutic protein productivity. Unfortunately, the desired or optimal nutrient concentrations of the feed media are often solubility limited due to precipitation of chemical complexes that form in the solution. Experimentally screening the various cell culture media configurations which contain 50 to 100 compounds can be expensive and laborious. This article lays the foundation for utilizing computational tools to understand precipitation of nutrients in cell culture media by studying the pairwise interactions between amino acids in thermodynamic models. Activity coefficient data for one amino acid in water and amino acid solubility data of two amino acids in water have been used to determine a single set of UNIFAC group interaction parameters to predict the thermodynamic behavior of the multi-component systems found in mammalian cell culture media. The data collected in this study is, to our knowledge, the largest set of ternary system amino acid solubility data reported to date. These amino acid precipitation predictions have been verified with experimentally measured ternary and quaternary amino acid solutions. Thus, we demonstrate the utility of our model as a digital twin to identify optimal cell culture media compositions by replacing empirical approaches for nutrient precipitation with computational predictions based on thermodynamics of individual media components in complex mixtures.

Zhong Ken Hew, Jia Xin Low, Sze Jue Yang et al.

Large Language Models (LLMs) often exhibit cultural biases due to training data dominated by high-resource languages like English and Chinese. This poses challenges for accurately representing and evaluating diverse cultural contexts, particularly in low-resource language settings. To address this, we introduce MyCulture, a benchmark designed to comprehensively evaluate LLMs on Malaysian culture across six pillars: arts, attire, customs, entertainment, food, and religion presented in Bahasa Melayu. Unlike conventional benchmarks, MyCulture employs a novel open-ended multiple-choice question format without predefined options, thereby reducing guessing and mitigating format bias. We provide a theoretical justification for the effectiveness of this open-ended structure in improving both fairness and discriminative power. Furthermore, we analyze structural bias by comparing model performance on structured versus free-form outputs, and assess language bias through multilingual prompt variations. Our evaluation across a range of regional and international LLMs reveals significant disparities in cultural comprehension, highlighting the urgent need for culturally grounded and linguistically inclusive benchmarks in the development and assessment of LLMs.

Arijit Maji, Raghvendra Kumar, Akash Ghosh et al.

We introduce DRISHTIKON, a first-of-its-kind multimodal and multilingual benchmark centered exclusively on Indian culture, designed to evaluate the cultural understanding of generative AI systems. Unlike existing benchmarks with a generic or global scope, DRISHTIKON offers deep, fine-grained coverage across India's diverse regions, spanning 15 languages, covering all states and union territories, and incorporating over 64,000 aligned text-image pairs. The dataset captures rich cultural themes including festivals, attire, cuisines, art forms, and historical heritage amongst many more. We evaluate a wide range of vision-language models (VLMs), including open-source small and large models, proprietary systems, reasoning-specialized VLMs, and Indic-focused models, across zero-shot and chain-of-thought settings. Our results expose key limitations in current models' ability to reason over culturally grounded, multimodal inputs, particularly for low-resource languages and less-documented traditions. DRISHTIKON fills a vital gap in inclusive AI research, offering a robust testbed to advance culturally aware, multimodally competent language technologies.

Zahra Bokaei, Walid Magdy, Bonnie Webber

Toxic language detection is crucial for creating safer online environments and limiting the spread of harmful content. While toxic language detection has been under-explored in Persian, the current work compares different methods for this task, including fine-tuning, data enrichment, zero-shot and few-shot learning, and cross-lingual transfer learning. What is especially compelling is the impact of cultural context on transfer learning for this task: We show that the language of a country with cultural similarities to Persian yields better results in transfer learning. Conversely, the improvement is lower when the language comes from a culturally distinct country. Warning: This paper contains examples of toxic language that may disturb some readers. These examples are included for the purpose of research on toxic detection.

Sina Malakouti, Boqing Gong, Adriana Kovashka

Text-to-image (T2I) diffusion models achieve impressive photorealism by training on large-scale web data, but models inherit cultural biases and fail to depict underrepresented regions faithfully. Existing cultural benchmarks focus mainly on object-centric categories (e.g., food, attire, and architecture), overlooking the social and daily activities that more clearly reflect cultural norms. Few metrics exist for measuring cultural faithfulness. We introduce CULTIVate, a benchmark for evaluating T2I models on cross-cultural activities (e.g., greetings, dining, games, traditional dances, and cultural celebrations). CULTIVate spans 16 countries with 576 prompts and more than 19,000 images, and provides an explainable descriptor-based evaluation framework across multiple cultural dimensions, including background, attire, objects, and interactions. We propose four metrics to measure cultural alignment, hallucination, exaggerated elements, and diversity. Our findings reveal systematic disparities: models perform better for global north countries than for the global south, with distinct failure modes across T2I systems. Human studies confirm that our metrics correlate more strongly with human judgments than existing text-image metrics.

Daeen Kabir, Minhajur Rahman Chowdhury Mahim, Sheikh Shafayat et al.

In this work, we introduce BLUCK, a new dataset designed to measure the performance of Large Language Models (LLMs) in Bengali linguistic understanding and cultural knowledge. Our dataset comprises 2366 multiple-choice questions (MCQs) carefully curated from compiled collections of several college and job level examinations and spans 23 categories covering knowledge on Bangladesh's culture and history and Bengali linguistics. We benchmarked BLUCK using 6 proprietary and 3 open-source LLMs - including GPT-4o, Claude-3.5-Sonnet, Gemini-1.5-Pro, Llama-3.3-70B-Instruct, and DeepSeekV3. Our results show that while these models perform reasonably well overall, they, however, struggles in some areas of Bengali phonetics. Although current LLMs' performance on Bengali cultural and linguistic contexts is still not comparable to that of mainstream languages like English, our results indicate Bengali's status as a mid-resource language. Importantly, BLUCK is also the first MCQ-based evaluation benchmark that is centered around native Bengali culture, history, and linguistics.

Mary Kate Hollifield, Ching-Yi Chen, Eric Psota et al.

Abstract Background With the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs. Behavior was recorded for 70 days after on-test at about 10 weeks of age and ended at off-test for 2008 female purebred pigs, totaling 119,812 day-wise records. Behavior traits included time spent eating, drinking, laterally lying, sternally lying, sitting, standing, and meters of distance traveled. A quality control procedure was created for algorithm training and adjustment, standardizing recording hours, removing culled animals, and filtering unrealistic records. Results Production traits included average daily gain (ADG), back fat thickness (BF), and loin depth (LD). Single-trait linear models were used to estimate heritabilities of the behavior traits and two-trait linear models were used to estimate genetic correlations between behavior and production traits. The results indicated that all behavior traits are heritable, with heritability estimates ranging from 0.19 to 0.57, and showed low-to-moderate phenotypic and genetic correlations with production traits. Two-trait linear models were also used to compare traits at different intervals of the recording period. To analyze the redundancies in behavior data during the recording period, the averages of various recording time intervals for the behavior and production traits were compared. Overall, the average of the 55- to 68-day recording interval had the strongest phenotypic and genetic correlation estimates with the production traits. Conclusions Digital phenotyping is a new and low-cost method to record behavior phenotypes, but thorough data cleaning procedures are needed. Evaluating behavioral traits at different time intervals offers a deeper insight into their changes throughout the growth periods and their relationship with production traits, which may be recorded at a less frequent basis.

Sekobane Daniel Kolobe, Tlou Grace Manyelo, Emmanuel Malematja et al.

Common food sources including meat, fish and vegetables are the main source of fats and fatty acids required by human body. Edible insects such as worms, locusts, termites, crickets and flies have also been identified as a potential source of essential fatty acids since they are highly documented to be rich in unsaturated fatty acids such as α-linolenic and linoleic acids which are vital for the normal functioning of the body. The approval of insects as edible food by the European Union has sparked research interest in their potential to form part of human and animal diets due to their abundant protein, amino acids, fats, and minerals. However, little attention has been given to the importance and health benefits of lipids and fatty acids present in edible insects consumed by human and animals. This article aims to review the biological significance of essential fatty acids found in edible insects. The accumulation of fats and essential fatty acids present in edible insects were identified and described based on recommended levels required in human diets. Furthermore, the health benefits associated with insect oils as well as different processing techniques that could influence the quality of fats and fatty acid in edible insects were discussed.

Andrew S. Hanzlicek, Kate S. KuKanich, Audrey K. Cook et al.

Abstract Background Culture can be used for diagnosis and antifungal susceptibility testing in animals with fungal infections. Limited information is available regarding the diagnostic performance of culture and the susceptibility patterns of Histoplasma spp. isolates. Hypothesis/Objectives Describe the clinical utility of culture and the susceptibility patterns of Histoplasma spp. isolates causing histoplasmosis in cats and dogs. Animals Seventy‐one client‐owned animals, including 33 cats and 19 dogs with proven or probable histoplasmosis. Methods Culture was attempted from tissue or fluid samples. Diagnostic performance of culture, cytopathology, and antigen detection were compared with final diagnosis. Susceptibility to antifungal agents was determined for a subset (11 from dogs, 9 from cats) of culture isolates. Results Culture had a diagnostic sensitivity of 17/33 (52%; 95% confidence interval [CI], 34%‐69%) and 15/19 (79%; 95% CI, 61%‐97%) and specificity of 6/6 (100%; 95% CI, 54%‐100%) and 10/10 (100%; 95% CI, 69%‐100%) in cats and dogs, respectively. Culture was not positive in any animal in which cytopathology and antigen testing were negative. Target drug exposure (area under the concentration curve [AUC]/minimum inhibitory concentration [MIC] >25) should be easily achieved for all isolates for itraconazole, voriconazole, or posaconazole. Five of 20 (25%) isolates had fluconazole MIC ≥32 μg/mL and achieving target drug exposure is unlikely. Conclusions and Clinical Importance Fungal culture did not improve diagnostic sensitivity when used with cytopathology and antigen detection. Susceptibility testing might help identify isolates for which fluconazole is less likely to be effective.

Nigini Oliveira, Jasmine Li, Koosha Khalvati et al.

Constructing a universal moral code for artificial intelligence (AI) is difficult or even impossible, given that different human cultures have different definitions of morality and different societal norms. We therefore argue that the value system of an AI should be culturally attuned: just as a child raised in a particular culture learns the specific values and norms of that culture, we propose that an AI agent operating in a particular human community should acquire that community's moral, ethical, and cultural codes. How AI systems might acquire such codes from human observation and interaction has remained an open question. Here, we propose using inverse reinforcement learning (IRL) as a method for AI agents to acquire a culturally-attuned value system implicitly. We test our approach using an experimental paradigm in which AI agents use IRL to learn different reward functions, which govern the agents' moral values, by observing the behavior of different cultural groups in an online virtual world requiring real-time decision making. We show that an AI agent learning from the average behavior of a particular cultural group can acquire altruistic characteristics reflective of that group's behavior, and this learned value system can generalize to new scenarios requiring altruistic judgments. Our results provide, to our knowledge, the first demonstration that AI agents could potentially be endowed with the ability to continually learn their values and norms from observing and interacting with humans, thereby becoming attuned to the culture they are operating in.

Anyou Wang

The mechanisms underlying lifespan evolution in organisms have long been mysterious. However, recent studies have demonstrated that organisms evolutionarily gain noncoding RNAs (ncRNAs) that carry endogenous profound functions in higher organisms, including lifespan. This study unveils ncRNAs as crucial drivers driving animal lifespan evolution. Species in the animal kingdom evolutionarily increase their ncRNA length in their genomes, coinciding with trimming mitochondrial genome length. This leads to lower energy consumption and ultimately lifespan extension. Notably, during lifespan extension, species exhibit a gradual acquisition of long-life ncRNA motifs while concurrently losing short-life motifs. These longevity-associated ncRNA motifs, such as GGTGCG, are particularly active in key tissues, including the endometrium, ovary, testis, and cerebral cortex. The activation of ncRNAs in the ovary and endometrium offers insights into why women generally exhibit longer lifespans than men. This groundbreaking discovery reveals the pivotal role of ncRNAs in driving lifespan evolution and provides a fundamental foundation for the study of longevity and aging.

Jeferson M. Lourenco, Taylor R. Krause, Christina B. Welch et al.

The ruminal microbiota of Angus cows and steers were characterized using 16s rRNA gene sequencing, and the expression of their metabolic pathways was predicted. Samples were collected on weaning day from the steers and the cows, and subsequently on three other occasions from the steers. Results showed that microbial richness, evenness, and diversity decreased (<i>p</i> < 0.001) in the rumen of the steers as they were weaned and transitioned to a high-concentrate feedlot diet. However, on the day of weaning, microbial evenness was similar to that observed in the rumen of cows (<i>p</i> = 0.12). The abundance of archaea was similar (<i>p</i> = 0.59) between the cows and steers at weaning, but it decreased (<i>p</i> = 0.04) in the rumen of steers after weaning, and remained stable (<i>p</i> ≥ 0.44) for the remainder of their lives. Likewise, no difference (<i>p</i> = 0.51) in the abundance of Bacteroidetes was detected between the cows and the calves on the day they were weaned, but the abundance of this phylum increased (<i>p</i> = 0.001) and remained stable after that. These results suggest that cows may have a strong influence on the composition, and help modulate the ruminal microbiota of young calves; however, following weaning, their ruminal microbiotas tend to differentiate from that state observed at earlier ages.

Zenon Zduńczyk, Dariusz Mikulski, Jan Jankowski et al.

This study investigated the effects of dietary replacement of soybean meal (SBM) with graded levels of pea seeds (PS) on the gastrointestinal function of turkeys. Seeds of 2 pea varieties, a colored-flowered variety and a white-flowered variety (CFP and WFP, respectively) were fed to 56-d-old birds for 8 wk. A total of 539 female Hybrid turkeys were allocated to 7 groups, each group consisted of 7 pens with 11 birds per pen. The experiment had a 2-factorial design, with 3 dietary inclusion levels of PS (100, 200 and 300 g/kg) and 2 pea varieties (CFP and WFP). The control group (diets without PS) was compared with CFP and WFP treatments by simple contrast analysis. In comparison with CFP seeds, WFP seeds contained 7-fold less tannins (0.67 vs. 4.66 g/kg) and less non-starch polysaccharides (NSP, 117.8 vs. 132.7 g/kg), but more trypsin inhibitors (1.34 vs. 0.98 g/kg) and starch (489 vs. 455 g/kg). A rise in the PS content of diets from 100 to 200 and 300 g/kg increased the weight of the small intestine (P = 0.031) and the dry matter (DM) content of intestinal digesta (P = 0.001), but it had no effect on the pH of digesta. Only the highest PS content differentiated the concentrations of short-chain fatty acids (SCFAs) in the small intestinal digesta (WFP > CFP, P = 0.008), whereas PS did not cause any changes in the morphological parameters of the small intestinal mucosa. The dietary inclusion of PS had no influence on the levels of acetate, butyrate, putrefactive SCFAs or total SCFAs in the cecal contents. Apart from increasing the activities of β-glucosidase (P = 0.017) and β-galactosidase (P = 0.025), pea varieties did not affect the activities of the analyzed cecal microbial enzymes. However, CFP seeds decreased the DM content (P = 0.041) and increased the pH of cecal digesta, compared with WFP seeds (P = 0.013). The results of this study, pointing to a few differences in the functional parameters of the small intestine and cecum, indicate that tannins are not a factor differentiating the suitability of CFP and WFP seeds in the nutrition of finisher turkeys. The inclusion of PS at 200 and 300 g/kg of the diet reduces the content of SBM and wheat in turkey diets, which has a positive effect on gastrointestinal function.