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Generation of a genetically engineered porcine melanoma model featuring oncogenic control through conditional Cre recombination

AbstractMelanoma is a serious type of skin cancer that originates from melanocytes. Rodent melanoma models have provided valuable insights into melanoma pathology; however, they often lack applicability to humans owing to genetic, anatomical, physiological, and metabolic differences. Herein, we developed a transgenic porcine melanoma model that closely resembles humans via somatic cell nuclear transfer (SCNT). Our model features the conditional oncogenes cassettes, TP53R167H and human BRAFV600E, controlled by melanocyte-specific CreER recombinase. After SCNT, transgenic embryos developed normally, with the capacity to develop porcine embryonic stem cells. Seven transgenic piglets with oncogene cassettes were born through embryo transfer. We demonstrated that Cre recombination-mediated oncogene activation remarkably triggered the mitogen-activated protein kinase pathway in vitro. Notably, intradermal injection of 4-hydroxytamoxifen activated oncogene cassettes in vivo, resulting in melanocytic lesions resembling hyperpigmented nevi with increased proliferative properties similar to early human melanomas. This melanoma-inducing system, heritably transmitted to offspring, supports large-scale studies. The novel porcine model provides a valuable tool for elucidating melanoma development and metastasis mechanism, advancing translational medicine, and facilitating preclinical evaluation of new anticancer drugs.

Characteristics of successful expansion of tumor-infiltrating lymphocytes from colorectal cancer liver metastasis

Subsurface warming associated with Pacific Summer Water transport toward the Chukchi Borderland in the Arctic Ocean

Design of an improved model using federated learning and LSTM autoencoders for secure and transparent blockchain network transactions

Smartphone based non invasive real time white blood cell counter leveraging blue light and static magnetic field

High-throughput sequencing revealed the symptomatic common bean (Phaseolus vulgaris L.) virome in Iran

Epigenetic drug screening identifies enzyme inhibitors A-196 and TMP-269 as novel regulators of sprouting angiogenesis

Role of Arg1+ ILC2s and ILCregs in gestational diabetes progression

Unusual free trisaccharides in caprine colostrum discovered by logically derived sequence tandem mass spectrometry

Associations between environmental glyphosate exposure and glucose homeostasis indices in US general adults: a national population-based cross-sectional study

Emerging biofilm formation and disinfectant susceptibility of ESBL-producing Klebsiella pneumoniae

AbstractKlebsiella pneumoniae is an opportunistic pathogen responsible for various infections in humans and animals. It is known for its resistance to multiple antibiotics, particularly through the production of Extended-Spectrum Beta-Lactamases (ESBLs), and its ability to form biofilms that further complicate treatment. This study aimed to isolate and identify K. pneumoniae from animal and environmental samples and assess commercial disinfectants’ effectiveness against K. pneumoniae isolates exhibiting ESBL-mediated resistance and biofilm-forming ability in poultry and equine farms in Giza Governorate, Egypt. A total of 320 samples, including nasal swabs from equine (n = 60) and broiler chickens (n = 90), environmental samples (n = 140), and human hand swabs (n = 30), were collected. K. pneumoniae was isolated using lactose broth enrichment and MacConkey agar, with molecular confirmation via PCR targeting the gyrA and magA genes. PCR also identified ESBL genes (blaTEM, blaSHV, blaCTX-M, blaOXA-1) and biofilm genes (luxS, Uge, mrkD). Antimicrobial susceptibility was assessed, and the efficacy of five commercial disinfectants was evaluated by measuring inhibition zones. Klebsiella pneumoniae was isolated from poultry (13.3%), equine (8.3%), wild birds (15%), water (10%), feed (2%), and human hand swabs (6.6%). ESBL and biofilm genes were detected in the majority of the isolates, with significant phenotypic resistance to multiple antibiotics. The disinfectants containing peracetic acid and hydrogen peroxide were the most effective, producing the largest inhibition zones, while disinfectants based on sodium hypochlorite and isopropanol showed lower efficacy. Statistical analysis revealed significant differences in the effectiveness of disinfectants against K. pneumoniae isolates across various sample origins (P < 0.05). The presence of K. pneumoniae in animal and environmental sources, along with the high prevalence of ESBL-mediated resistance and biofilm-associated virulence genes, underscores the zoonotic potential of this pathogen. The study demonstrated that disinfectants containing peracetic acid and hydrogen peroxide are highly effective against ESBL-producing K. pneumoniae. Implementing appropriate biosecurity measures, including the use of effective disinfectants, is essential for controlling the spread of resistant pathogens in farm environments.

Does fact-checking work? What the science says

Daily briefing: Earth breaches 1.5 °C climate limit for the first time

Mind matters: investigating academia’s ‘mental health crisis’

Rising stars in AI use robotics and automation to accelerate their work

How breakthroughs happen: Unearthing the boundary conditions of eco-friendly deliberate practice and eco-innovation performance

Surprisingly innovation process based on deliberate practice has rarely been unearthed that might explore the boundary conditions of the eco-friendly deliberate practice and eco-innovation performance relationship. Anchored on the organizational support theory and the social cognitive, the current study seeks to investigate the impacts of perceived organizational support (POS) and developmental leadership (DL) on eco-innovation performance (EP) through the mediating role of eco-friendly deliberate practice (EDP). In addition, the study explores the boundary effects of employee resilience (ER) on the relationship between EDP and EP. The study collects time-lagged (i.e., “three-wave”) and multisource (i.e., “self-rated and supervisor-rated”) data from 383 respondents working in the service sector organizations in Pakistan. The authors processed data in SmartPLS (v 4.0) to assess the measurement model and the structural model. The study finds that POS and DL have significant positive relationships with EDP. Further, EDP partially mediates the links between POS, DL, and EP. Moreover, ER intervenes the association between EDP and EP such that at high levels of ER, the relationship is stronger and vice versa. Despite growing interest in deliberate practice, the boundary conditions of EDP in the work context are rarely investigated. This is the first study that explores the contextual and individual factors that can underpin the influence of EDP on EP.

Investigations on segmentation-based fractal texture for texture classification in the presence of Gaussian noise

Texture is a significant component used for several applications in content-based image retrieval. Any texture classification method aims to map an anonymously textured input image to one of the existing texture classes. Extensive ranges of methods for labeling image texture were proposed earlier. However, computing the performance of these methods in the presence of various degradations is always an open area of discussion. Image noise is always a dominant factor among various image degradation factors, affecting the performance of these methods and making texture classification challenging. Therefore, it is essential to investigate the interpretation of these methods in the presence of prominent degradation factors such as noise. Applications for Segmentation-Based Fractal Texture Features (SFTF) include image classification, texture generation, and medical image analysis. They are beneficial for examining textures with intricate, erratic patterns that are difficult to characterize using conventional statistical techniques accurately. This paper assesses two texture feature extraction methods based on SFTF and statistical moment-based texture features in the presence and absence of Gaussian noise. The SFTF and statistical moments-based handcrafted features are passed to a multilayer feed-forward neural network for classification. These models are evaluated on natural textures from Kylberg Texture Dataset 1.0. The results show the superiority of segmentation-based fractal analysis over other approaches. The average accuracy rates using the SFTF are 99% and 97% in the absence and presence of Gaussian noise, respectively.

Being honest won’t pay. Seven- but not 5-year-olds begin to predict that others will lie for reputational reasons

Children begin to manage their reputation around school-age, but it remains unclear when they start to explicitly reason about reputational strategies such as lying from a third-person perspective. The current study investigated whether 5- and 7-year-old children would explicitly predict reputational lying in the context of a third party interaction. Participants were told hypothetical stories and asked to predict whether a protagonist would lie to a peer character about a selfish resource allocation. Results revealed that about half of the 7-year-olds and neglectable few of the 5-year-olds began to predict that the protagonist would lie to his peer out of reputational concern and whitewash the selfishly distributed amount. The prediction of reputational lying did not differ for ingroup or outgroup third parties. Seven-year-olds justified their prediction of a lie with reference to how the protagonist would look to others. While reputational lying has been shown in 5-year-olds in comparable interactive scenarios with peers, a more abstract, explicit understanding of reputational lying seems to be a more complex cognitive ability, emerging around the age of 7 years.

Genome-wide association mapping of bruchid resistance loci in soybean

Soybean is a globally important industrial, food, and cash crop. Despite its importance in present and future economies, its production is severely hampered by bruchids ( Callosobruchus chinensis ), a destructive storage insect pest, causing considerable yield losses. Therefore, the identification of genomic regions and candidate genes associated with bruchid resistance in soybean is crucial as it helps breeders to develop new soybean varieties with improved resistance and quality. In this study, 6 multi-locus methods of the mrMLM model for genome-wide association study were used to dissect the genetic architecture of bruchid resistance on 4traits: percentage adult bruchid emergence (PBE), percentage weight loss (PWL), median development period (MDP), and Dobie susceptibility index (DSI) on 100 diverse soybean genotypes, genotyped with 14,469 single-nucleotide polymorphism (SNP) markers. Using the best linear unbiased predictors (BLUPs), 13 quantitative trait nucleotides (QTNs) were identified by the mrMLM model, of which rs16_14976250 was associated with more than 1 bruchid resistance traits. As a result, the identified QTNs linked with resistance traits can be employed in marker-assisted breeding for the accurate and rapid screening of soybean genotypes for resistance to bruchids. Moreover, a gene search on the Phytozome soybean reference genome identified 27 potential candidate genes located within a window of 478.45 kb upstream and downstream of the most reliable QTNs. These candidate genes exhibit molecular and biological functionalities associated with various soybean resistance mechanisms and, therefore, could be incorporated into the farmers’ preferred soybean varieties that are susceptible to bruchids.

Effectiveness of oral health promotion in children and adolescents through behaviour change interventions: A scoping review

Objective To explore the interventions for change in oral health behaviour that are effective in improving oral health behaviours in 8 to 18-year-old children during oral health promotion. Methods The Joanna Briggs Institute framework of evidence synthesis for conducting a scoping review was implemented for the methodology. Included studies related to the objective, measured clinical or non-clinical outcomes, were in English, 2011–2023, and were experimental, observational or reviews. PUBMED, Science-Direct, Scopus and Sabinet were systematically searched with predetermined search strings. Studies were selected by appraisal of the title, abstract and full text. Data were extracted using a standardised template and the key questions were addressed via a qualitative analysis. Results Searches yielded 407 articles from electronic databases. Of these, 290 articles were excluded, and 47 full-text studies were assessed for eligibility, with 23 studies and two systematic reviews finalised for inclusion. In addition, a PEARL search was conducted from the reference lists of other studies. Most studies (91.3%) focused on educating children directly; 8.7% indirectly influenced parents, guardians, and teachers. Interventions focused largely on traditional oral health education presented in diverse forms and via different platforms. Studies differentiated clinical outcomes (indices) from non-clinical outcomes (knowledge, behaviour). All included RCTs were of different quality regarding selection, performance and detection bias. But all studies indicated a low risk of bias in attrition and Reporting bias. Seventeen of the 25 studies (68%) were not based on any behaviour change theory. Conclusions Oral health interventions based on motivational interviewing and the social cognitive theory have been shown to be to be effective. Interventions could also include practical tooth brushing activities, gamification, audio-visual components, as well as reinforcement and repetition in the longer term. Future oral health promotion in children should be designed to include these elements. There is a need for higher quality studies in this field, with future research being urged to provide detailed intervention descriptions and incorporate longer follow-up periods.