Rat animal models are widely used owing to their relatively superior cognitive abilities and higher similarity compared with mouse models to human physiological characteristics. However, their use is limited because of difficulties in establishing embryonic stem cells and performing genetic modifications, and insufficient embryological research. In this study, we established optimal superovulation and fertilized–egg transfer conditions, including optimal hormone injection concentration (≥150 IU/kg of PMSG and hCG) and culture medium (mR1ECM), to obtain high-quality zygotes and establish in vitro fertilization conditions for rats. Next, sgRNA with optimal targeting activity was selected by performing PCR analysis and the T7E1 assay, and the CRISPR/Cas9 system was used to construct a rat model for muscular dystrophy by inducing a deficiency in the fukutin gene without any off-target effect detected. The production of fukutin knockout rats was phenotypically confirmed by observing a drop-in body weight to one-third of that of the control group. In summary, we succeeded in constructing the first muscular dystrophy disease rat model using the CRISPR/CAS9 system for increasing future prospects of producing various animal disease models and encouraging disease research using rats. Full article

Considering the high-speed and high power density technical specifications of new energy vehicle motors, there is a growing demand for rotor strength as motor peak speeds reach 20,000 r/min and beyond. The utilization of non-oriented silicon steel with a high yield strength in rotors has emerged as a promising approach to increase motor speed. However, the magnetic and mechanical properties of high-strength silicon steel under variable temperature conditions have not been fully explored, particularly in regards to their impact on motor torque, efficiency, and speed. This manuscript investigates the behavior of high-strength silicon steel before and after annealing and at different temperatures, analyzing its influence on high-speed motor performance. The validity and feasibility of this study are confirmed through prototype testing, providing a comprehensive reference for engineering design. Full article

Adipose tissue plays an important role in regulating body temperature and metabolism, with white adipocytes serving as storage units for energy. Recent research focused on the browning of white adipocytes (beige adipocytes), causing thermogenesis and lipolysis. The process of browning is linked to the activation of uncoupling protein (UCP) expression, which can be mediated by the β3 adrenergic receptor pathway. Transcriptional factors, such as peroxisome proliferator activated receptor γ (PPARγ) and PPARγ coactivator 1 alpha, play vital roles in cell fate determination for fat cells. Beige adipocytes have metabolic therapeutic potential to combat diseases such as obesity, diabetes mellitus, and dyslipidemia, owing to their significant impact on metabolic functions. However, the molecular mechanisms that cause the induction of browning are unclear. Therefore, research using animal models and primary culture is essential to provide an understanding of browning for further application in human metabolic studies. Pigs have physiological similarities to humans; hence, they are valuable models for research on adipose tissue. This study demonstrates the browning potential of pig white adipocytes through primary culture experiments. The results show that upregulation of UCP3 gene expression and fragmentation of lipid droplets into smaller particles occur due to isoproterenol stimulation, which activates beta-adrenergic receptor signaling. Furthermore, PPARγ and PGC-1α were found to activate the UCP3 promoter region, similar to that of UCP1. These findings suggest that pigs undergo metabolic changes that induce browning in white adipocytes, providing a promising approach for metabolic research with potential implications for human health. This study offers valuable insights into the mechanism of adipocyte browning using pig primary culture that can enhance our understanding of human metabolism, leading to cures for commonly occurring diseases. Full article

This paper examines the legacies of the emergence of the animal control and sheltering industry in the United States and their impact on contemporary public animal shelters. While decades of gradual reform have helped substantially reduce the number of animals entering shelters and being killed there, contemporary animal sheltering largely continues to follow the path set when animal sheltering developed in the late 1800s and early 1900s. Three key interrelated legacies of the pound model of early animal control and sheltering enduringly shape sheltering today: (1) the institutional culture of animal shelters grounded in the logics of caging and killing; (2) the lack of visibility and transparency, especially within government shelters; and (3) the economic logics of the pound model, including the disparities in sheltering resources across communities. Examining the origins of animal control and sheltering and identifying the specific legacies of this pound model within contemporary government-funded shelters improves understanding of why such shelters in the US have developed with a particular set of practices and ideologies, and thus provides an important footing for envisioning and enacting radical changes in animal sheltering. Full article

In this paper, a new automatic modulation recognition (AMR) method named CCLDNN (complex-valued convolution long short-term memory deep neural network) is proposed. It is designed to significantly improve the recognition accuracy of modulation modes in low signal-to-noise ratio (SNR) environments. The model integrates the advantages of existing mainstream neural networks. The phase and amplitude information of complex signals is effectively captured through a complex module in the input layer. The Squeeze-and-Excitation (SE) attention mechanism, Bi-LSTM layer, and deep convolutional layer are introduced in the feature extraction layer to gradually enhance feature expression. Among these, the introduction of LSTM enables the model to capture the sequence dependence of signals, and the application of the SE attention mechanism further improves the model’s ability to focus on key features. Tests using the RadioML2016.10a dataset show that the model performs well at multiple SNR levels, achieving an average recognition accuracy of more than 80% over an SNR range of 0 dB to 18 dB. However, under the condition of a low SNR from −20 dB to −2 dB, the model still maintains a high recognition ability. The advanced CCLDNN method shows great deep learning potential in solving practical communication problems. Full article

The emergence of the novel coronavirus in Wuhan, China since 2019, has put the world in an exotic state of emergency and affected millions of lives. It is five times more deadly than Influenza and causes significant morbidity and mortality. COVID-19 mainly affects the pulmonary system leading to respiratory disorders. However, earlier studies indicated that COVID-19 infection may cause cardiovascular diseases, which can be detected using an electrocardiogram (ECG). This work introduces an advanced deep learning architecture for the automatic detection of COVID-19 and heart diseases from ECG images. In particular, a hybrid combination of the EfficientNet-B0 CNN model and Vision Transformer is adopted in the proposed architecture. To our knowledge, this study is the first research endeavor to investigate the potential of the vision transformer model to identify COVID-19 in ECG data. We carry out two classification schemes, a binary classification to identify COVID-19 cases, and a multi-class classification, to differentiate COVID-19 cases from normal cases and other cardiovascular diseases. The proposed method surpasses existing state-of-the-art approaches, demonstrating an accuracy of 100% and 95.10% for binary and multiclass levels, respectively. These results prove that artificial intelligence can potentially be used to detect cardiovascular anomalies caused by COVID-19, which may help clinicians overcome the limitations of traditional diagnosis. Full article

Background: The risk of developing non-melanoma skin cancers (NMSCs) in patients with psoriasis is highly debated, and, to date, there is no unambiguous consensus opinion. Psoriasis is known to be related to an increased likelihood of other comorbidities such as psoriatic arthritis, obesity, metabolic syndrome, depression, and cardiovascular disease. Regarding cancer risk, previous studies have reported a greater tendency for the development of cutaneous T-lymphomas and colon, breast, kidney, and lung cancers. Furthermore, data from network meta-analyses have shown that patients with psoriasis have a higher risk of developing squamous cell carcinomas (SCCs) and/or basal cell carcinomas (BCCs). Multiple factors may contribute to the development of NMSCs in psoriatic patients, ranging from immunosuppression induced by biologic agents to previous phototherapy. However, the extent to which each factor may impact this risk has not been entirely assessed. The aim of this study was to evaluate the risk of developing NMSCs in patients with psoriasis observed for at least 5 years, by directly comparing patients only treated with phototherapy and patients treated with anti-tumor necrosis factor α (TNFα) agents, naive to other systemic treatments or phototherapy. Methods: We conducted a single-center retrospective study at Siena University Hospital, Italy, on 200 adult patients with psoriasis divided into two groups: (i) group 1, including 100 patients treated with narrow-band UVB phototherapy (nb-UVB), and (ii) group 2, including 100 patients treated with anti-TNFα. The patients included in group 2 had to be naive to cDMARDs and biologics and treated with anti-TNFα continuously for 5 years without loss of efficacy. All patients were observed for 5 years and underwent annual dermatologic examinations to assess for the occurrence of BCC or SCC. Results: A total of 34 out of 100 patients treated with phototherapy had one BCC or one SCC and 10 out of 34 developed two skin cancers. In particular, five had both types (one BCC and one SCC), and five had two BCCs. Conclusions: The results of our study highlight how the risk of developing NMSCs is greater in patients undergoing phototherapy compared to those treated with anti-TNFα. It also draws attention to the consideration that patients with scalp psoriasis might need closer follow-up as they could be more at risk of developing NMSCs. Full article

Human activity recognition (HAR) technology enables continuous behavior monitoring, which is particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these activities while under monitoring. Various machine learning algorithms, ranging from interpretable shallow models to state-of-the-art deep learning approaches designed for HAR (i.e., DeepConvLSTM and ConvTransformer), were employed for classification. The results demonstrate the ear sensor’s efficacy, with deep learning models achieving a 98% accuracy rate of classification. The obtained classification models are agnostic regarding which ear the sensor is worn and robust against moderate variations in sensor orientation (e.g., due to differences in auricle anatomy), meaning no initial calibration of the sensor orientation is required. The study underscores the ear’s efficacy as a suitable site for monitoring human daily activity and suggests its potential for combining HAR with in-ear vital sign monitoring. This approach offers a practical method for comprehensive health monitoring by integrating sensors in a single anatomical location. This integration facilitates individualized health assessments, with potential applications in tele-monitoring, personalized health insights, and optimizing athletic training regimes. Full article

Agriculture is facing several challenges related to its sustainability. In this regard, the need to reduce its environmental impact related to the use of synthetic inputs and its potential role in mitigating global warming and climate change call for a review of crop management. In this context, and in the framework of achieving sustainable development goals, the use of organic fertilizers and bio-waste represents a valuable contribution to the agricultural transition towards a bioeconomy model by reducing the negative impacts of waste disposal. Farmyard manure, composts, digestate from agrifood processes, and biochar are, among organic fertilizers, commonly used to manage soils and support crop growth. These fertilizers can provide essential nutrients, improve structure, and enhance microbial activity, thus increasing soil fertility and agriculture sustainability. While organic fertilizers offer the benefits of soil fertility and plant nutrition, their impact on greenhouse gas (GHG) emissions is complex and varies depending on factors such as fertilizer type, soil conditions, and management practices. Although organic fertilizers may initially increase GHG emissions, they often lead to carbon sequestration in soils highlighting a negative C balance. Additionally, organic fertilizers promote a reduction in fossil fuel consumption used for synthetic fertilizer production, further contributing to GHG emissions’ reduction. Therefore, while organic fertilizers pose challenges in managing GHG emissions, their various benefits warrant careful consideration and strategic implementation in agricultural systems. Full article

In this paper, we delve into the innovative application of large language models (LLMs) and their extension, large vision-language models (LVLMs), in the field of remote sensing (RS) image analysis. We particularly emphasize their multi-tasking potential with a focus on image captioning and visual question answering (VQA). In particular, we introduce an improved version of the Large Language and Vision Assistant Model (LLaVA), specifically adapted for RS imagery through a low-rank adaptation approach. To evaluate the model performance, we create the RS-instructions dataset, a comprehensive benchmark dataset that integrates four diverse single-task datasets related to captioning and VQA. The experimental results confirm the model’s effectiveness, marking a step forward toward the development of efficient multi-task models for RS image analysis. Full article

A labor companion of choice during childbirth is crucial for improving women’s birth experience and confidence to give birth. Labor companions provide various benefits, including enhanced communication, emotional support, non-pharmacological pain relief, and better healthcare. However, little is known about the supportive actions of labor companions with respect to women’s needs during labor and birth, as well as healthcare providers’ perceptions of labor companions. Therefore, this study was conducted to explore the perceptions of healthcare providers and women regarding labor companions. The study utilized an interpretative phenomenology research design. Data collection involved conducting semi-structured interviews with 14 participants. The sample consisted of mothers, physicians, and nurses, ensuring a diverse range of perspectives. An interpretative phenomenological analysis was conducted for data analysis. Five themes were identified: (a) impact of companionship, (b) benefits for healthcare providers, (c) companion roles, (d) loneliness and alienation of mothers, and (e) challenges of implementation. The findings indicated that the presence of a companion reduces the need for unnecessary medical interventions and eases the workload of healthcare providers. Without a companion, mothers often feel lonely and disconnected during the birthing process. The presence of companions is often hindered by space limitations in delivery rooms, the absence of clear policies, and lack of childbirth education programs for companions. Clear policies, education programs, and adequate space are essential for implementing and promoting labor companionship during childbirth. Full article

This Special Issue, titled “Sustainable Development Processes for Renewable Energy Technology II: An Overview”, presents a collection of papers in the field of sustainable development in the mineral resource sector, detailing the “seamless” process of transforming energy production into the use of renewable sources [...] Full article

Expansive soil underlying structures pose a significant risk to the integrity of superstructures. Chemical soil stabilization can be used to strengthen soils due to the cost and impracticality of mechanical approaches. Waste materials such as recycled gypsum and rice husk ash have been considered alternatives because of their sustainable and economic advantages. A combination of these additives was used to address the high absorption of gypsum and the lack of cohesion of the pozzolan. The study assessed the short-term and long-term performance of expansive soil treated with recycled gypsum and rice husk ash under normal and fluctuating moisture conditions. Direct shear tests indicated ductile and compressive soil behavior with improved shear strength. A good approximation of stress–strain response was made with a modified hyperbolic model for treated soils that exhibited strain hardening and compressive volumetric strain. Durability and water immersion tests were performed for samples after varying curing periods and cycles of capillary soaking to assess the behavior when exposed to varied environmental conditions. Samples under the modified durability test experienced significant strength loss, with decreasing compressive strength as curing durations increased. Specimens in the modified water immersion test experienced significant strength loss; however, it was determined that curing durations did not contribute to the change in the strength of the sample. Expansion index tests also determined that the treatment effectively mitigated expansivity and collapsibility in all samples. Despite improvement in shear strength and expansion potential, further investigation is needed to enhance the durability of soil treated with gypsum and rice husk ash. Full article

While RNA sequencing and multi-omic approaches have significantly advanced cancer diagnosis and treatment, their limitation in preserving critical spatial information has been a notable drawback. This spatial context is essential for understanding cellular interactions and tissue dynamics. Multiplex digital spatial profiling (MDSP) technologies overcome this limitation by enabling the simultaneous analysis of transcriptome and proteome data within the intact spatial architecture of tissues. In breast cancer research, MDSP has emerged as a promising tool, revealing complex biological questions related to disease evolution, identifying biomarkers, and discovering drug targets. This review highlights the potential of MDSP to revolutionize clinical applications, ranging from risk assessment and diagnostics to prognostics, patient monitoring, and the customization of treatment strategies, including clinical trial guidance. We discuss the major MDSP techniques, their applications in breast cancer research, and their integration in clinical practice, addressing both their potential and current limitations. Emphasizing the strategic use of MDSP in risk stratification for women with benign breast disease, we also highlight its transformative potential in reshaping the landscape of breast cancer research and treatment. Full article

Willow (Salix spp.) trees, found worldwide, contain secondary metabolites that are valuable as dietary supplements for animal feed and as antiparasitic compounds. We quantified secondary metabolites (phenolics, flavonoids, and salicylic acid) in ethanolic extracts from leaves and branches of three Salix acmophylla Boiss. genotypes and investigated their potential to inhibit Eimeria sp. sporulation, a major concern in ruminants. The total phenolic content of willow leaves and branches was similar in two of three different genotypes. The total flavonoid content of the branches was significantly higher than that of leaves of the same genotype; however, the salicylic acid content was significantly higher in leaves than in branches. Importantly, all extracts exhibited significant inhibition of Eimeria sporulation, where over 70% inhibition was obtained at concentrations as low as 750 mgL⁻¹. The sporulation inhibition by branch or leaf extracts exceeded 80% for leaves and 90% for branches at concentrations above 1250 mgL⁻¹. The study highlights the potential of using Salix extracts as bioactive compounds for biological control of coccidiosis in ruminants. We conclude that all parts and all investigated genotypes of S. acmophylla can provide secondary metabolites that act as a coccidiostat to treat Eimeria in goats. Full article

This study explored the association between renewable energy uptake and digitalization in the sector by reviewing relevant literature (published 2010–2022), with the aim of identifying the existing utilization of digital technologies within the sector, challenges to adoption, and future prospects. Different search engines (SCOPUS, Web of Science, and Google Scholar) were used to locate relevant papers and documents. The results revealed the high significance of digital technologies in supporting the renewable energy sector, with high costs and security risks representing the key challenges. Most papers reviewed had a positive outlook, but recommended further research and development for effective energy transition and resilient infrastructure. The current drivers of the integration of digital technologies to support the diffusion of renewable energy sources appear to extend beyond energy demand and involve many aspects of sustainability and sustainable development. Compared with previous reviews, this work has unique scope and novelty since it considers the bigger picture of the coupling between digitalization and the renewable energy sector, with a greater focus on critical areas in these two interconnected bodies that need to be addressed. The relatively small sample of relevant papers (69 from 836 hits) located in the literature review confirms the need for more research covering the subject in greater depth. Full article

Chronic migraine is a disease with a high burden on patients from both a working and quality of life point of view. The pathophysiology of this subtype of migraine is due to several factors, such as medication overuse. Nevertheless, the detrimental recurring of headache attacks with central and peripheral sensitization plays a central role and explains some additional symptoms complained about by these patients even in the interictal phase. OnabotulinumtoxinA is a therapy indicated for chronic migraine since it has proven to reduce peripheral sensitization, showing even efficacy on central symptoms. The aim of this narrative review is to present the current evidence regarding the effect of OnabotulinumtoxinA on sensitization and interictal symptoms. Full article

H19 is an essential imprinted gene that is expressed to govern normal embryonic development. During reprogramming, the parental pronuclei have asymmetric reprogramming capacities and the critical reprogramming factors predominantly reside in the male pronucleus. After inhibiting the expression of H19 and Gtl2, androgenetic haploid ESCs (AG-haESCs) can efficiently and stably support the generation of healthy SC pups at a rate of ~20%, and double-knockout parthenogenetic haESCs can also produce efficiently. Induced pluripotent stem (iPS) cell reprogramming is thought to have a characteristic epigenetic pattern that is the reverse of its developmental potential; however, it is unclear how H19 participates in iPS cell reprogramming. Here, we showed that the expression of H19 was transiently increased during iPSC reprogramming. H19 knockdown resulted in greater reprogramming efficiency. The genes associated with pluripotency showed enhanced expression during the early reprogramming process, and the Oct4 promoter was demethylated by bisulfite genomic sequencing analysis. Moreover, expression analysis revealed that the mesenchymal master regulators associated with epithelial-to-mesenchymal transition (EMT) were downregulated during reprogramming in H19 knockdown. These findings provide functional insight into the role of H19 as a barrier to the early reprogramming process. Full article

Background: Palliative care is a challenging specialty, especially when it comes to caring for children with serious life-limiting conditions and supporting their families. Workers face significant challenges and experience major impacts on their wellbeing. We conducted a qualitative study to understand the sources of stress in the palliative care team, their work expectations, and how they can cope with the demands. Methods: We used an online questionnaire about the causes of stress, the impact of the COVID-19 pandemic and the ways in which support is needed in the workplace. Results: Of the 56 palliative care professionals who participated in the survey, 57.1% considered the main causes of stress to be high workload, difficult emotional burdens (55.4%) affecting their outlook on life (61.2%), the death of patients (46.4%), and communication with patients’ families (26.8%). The COVID-19 pandemic increased stress levels for the majority of respondents (89.3%). The need for specialised training (53.6%), support groups, psychological counselling and adapted organisational policies was highlighted. Conclusions: The study demonstrates the importance of understanding the needs of both paediatric and adult palliative care staff in order to provide optimal care and support their balance in this demanding area of the healthcare system. Full article

Leaf movement is a manifestation of plant response to the changing internal and external environment, aiming to optimize plant growth and development. Leaf movement is usually driven by a specialized motor organ, the pulvinus, and this movement is associated with different changes in volume and expansion on the two sides of the pulvinus. Blue light, auxin, GA, H⁺-ATPase, K⁺, Cl⁻, Ca²⁺, actin, and aquaporin collectively influence the changes in water flux in the tissue of the extensor and flexor of the pulvinus to establish a turgor pressure difference, thereby controlling leaf movement. However, how these factors regulate the multicellular motility of the pulvinus tissues in a species remains obscure. In addition, model plants such as Medicago truncatula, Mimosa pudica, and Samanea saman have been used to study pulvinus-driven leaf movement, showing a similarity in their pulvinus movement mechanisms. In this review, we summarize past research findings from the three model plants, and using Medicago truncatula as an example, suggest that genes regulating pulvinus movement are also involved in regulating plant growth and development. We also propose a model in which the variation of ion flux and water flux are critical steps to pulvinus movement and highlight questions for future research. Full article

It is a challenging task to accurately segment damaged road markings from images, mainly due to their fragmented, dense, small-scale, and blurry nature. This study proposes a multi-scale spatial kernel selection net named M-SKSNet, a novel model that integrates a transformer and a multi-dilated large kernel convolutional neural network (MLKC) block to address these issues. Through integrating multiple scales of information, the model can extract high-quality and semantically rich features while generating damage-specific representations. This is achieved by leveraging both the local and global contexts, as well as self-attention mechanisms. The performance of M-SKSNet is evaluated both quantitatively and qualitatively, and the results show that M-SKSNet achieved the highest improvement in F1 by 3.77% and in IOU by 4.6%, when compared to existing models. Additionally, the effectiveness of M-SKSNet in accurately extracting damaged road markings from images in various complex scenarios (including city roads and highways) is demonstrated. Furthermore, M-SKSNet is found to outperform existing alternatives in terms of both robustness and accuracy. Full article

The ergogenic effects of simultaneous lower- and upper-body ischemic preconditioning (IPC) are a factor that has not been investigated exhaustively. Therefore, this study aimed to investigate the effects of IPC on 500 m rowing performance (time, relative peak [RPP] and mean [MPP] power output, time to peak power [TPP], and blood lactate concentration [BLa]), as well as heart rate (HR) among forty-three physically active male (n = 24) and female (n = 19) subjects. In this cross-over randomized trial, either the IPC (220 mmHg) or SHAM (20 mmHg) protocol was applied to the upper and lower limbs simultaneously for 5 min. Then, after 5 min of reperfusion, the participants performed an all-out 500 m rowing trial. During rowing, HR was recorded, and after the completion of the rowing, the BLa concentration was determined. Wilcoxon’s signed-rank test showed a significantly shorter TPP in the SHAM condition compared to under the IPC condition for females (Z = 2.415, p = 0.017), but not for males (Z = 1.914, p = 0.056). Moreover, a significant main effect of the group was reported for rowing time, BLa, RPP, and RMP (p < 0.001 for all dependent variables). No significant interactions nor a main effect of the condition were observed for rowing time, BLa, RPP, RMP, HR_WP, HR_MEAN, and HR_MAX (p > 0.05 for all dependent variables). Simultaneous lower- and upper-body IPC led to a significant decrease in the time to peak power during the 500 m ergometer rowing trial in females but not in males. Additionally, no significant effects on the time or other power output variables, HR, or BLa concentration were registered. Full article