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Sugarcane mechanized harvesting generates large volumes of data that are used to monitor harvesters’ functionalities. The dynamic interaction of the machine-onboard instrumentation–crop system introduces discrepant and noisy values into the data, requiring outlier detectors to support this complex and empirical decision. This study proposes an automatic filtering technique for sugarcane harvesting data to automate the process. A three-step automated filtering algorithm based on a sliding window was developed and further evaluated with four configurations of the maximum variation factor f and six SW sizes. The performance of the proposed method was assessed by using artificial outliers in the datasets with an outlier magnitude (OM) of ±0.01 to ±1.00. Three case studies with real crop data were presented to demonstrate the effectiveness of the proposed filter in detecting outliers of different magnitudes, compared to filtering by another method in the literature. In each dataset, the proposed filter detected nearly 100% of larger (OM = ±1.00 and ±0.80) and medium (OM = ±0.50) magnitudes’ outliers, and approximately 26% of smaller outliers (OM = ±0.10, ±0.05, and ±0.01). The proposed algorithm preserved wider ranges of data compared to the comparative method and presented equivalent results in the identification of regions with different productive potentials of sugarcane in the field. Therefore, the proposed method retained data that reflect sugarcane yield variability at the row level and it can be used in practical application scenarios to deal with large datasets obtained from sugarcane harvesters.

Alternative options have been studied to mitigate the negative impact of fossil fuel sources, mainly especially when it comes to alternative energy sources. In this work, cannabis residues have been considered as a potential biomass residues for energy recovery due to their energy content, and the increase in the cannabis market in Canada has created an opportunity niche for treating and valorizing these residues as energy. This study thus aims to investigate the potential of energy recovery from cannabis residue pellets via combustion and the impact of steam explosion on the pellets’ properties as well as combustion behavior. Two batches of pellets were produced namely with and without the steam explosion pretreatment. The properties of the pellets were then compared to those of the CANplus certification. Cannabis pellets were then combusted at 290 °C in a fixed-bed reactor using three different air coefficients (α) ranging from 1 to 1.3 (α = 1.0, α = 1.15, and α = 1.3). Flue gas quantification was performed using gas chromatography combined with a NOx detector. Results showed that the properties of this biomass is comparable to other sources of lignocellulosic biofuels. The steam explosion pretreatment enhanced pellet properties, including higher heating value (HHV), ash content, durability, and fines allowing the product to reach the CANplus requirements. The air coefficients influenced the emission levels, with an optimal value at α = 1.15, that indicated an improved combustion quality. However, steam explosion negatively affected combustion efficiency, resulting in incomplete combustion. Overall, cannabis residues show a strong potential for energy recovery and could offer a sustainable option for bioenergy applications.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, disabling disorder of unknown etiology, poor prognosis, and limited therapeutic options. Previously, 3′5-dimaleamylbenzoic acid (3′5-DMBA) was shown to exert resolving effects in IPF, offering a promising alternative for treating this disease; however, the molecular mechanisms associated with this effect have not been explored. Objetive: We evaluated the potential antifibrotic mechanisms of 3′5-DMBA by network pharmacology (NP) and molecular docking (MD). Methods: 3′5-DMBA-associated targets were identified by screening in SwissTargetPrediction. IPF-associated targets were identified using lung tissue meta-analysis and public databases. Common targets were identified, and a protein–protein interaction (PPI) network was constructed; we ranked the proteins in the PPI network by topological analysis. MD validated the binding of 3′5-DMBA to the main therapeutic targets. Results: A total of 57 common targets were identified between 3′5-DMBA and IPF; caspase 8, 9, 3, and 7; myeloid leukemia-induced cell differentiation protein Mcl-1; and poly [ADP-ribose] polymerase 1 are primary targets regulating PPI networks. Functional analysis revealed that the common targets are involved in the pathological features of tissue fibrosis and primarily in the apoptotic process. MD revealed favorable interaction energies among the three main targets regulating PPI networks. Conclusions: NP results suggest that the antifibrotic effect of 3′5-DMBA is due to its regulation of the pathological features of IPF, mainly by modulating signaling pathways leading to apoptosis, suggesting its therapeutic potential to treat this disease.

Workers’ attitudes towards people with disabilities can influence labor inclusion. Despite the relevance of learning about these attitudes, in Chile, there are no reliable and validated instruments to measure them in workers. An instrumental study was carried out to adapt and psychometrically analyze the Spanish version of the Scale of Attitudes towards People with Disabilities (EAPCD) in the Chilean population. By means of a non-probabilistic convenience sampling, 310 people between 19 and 76 years of age (M = 39.4; SD = 11.2) from different regions of Chile participated in the study. The linguistic adaptation included the change in Spanish idioms and expressions to the Chilean context, whose relevance was validated with cognitive interviews. Descriptive analysis, internal consistency analysis, and CFA (confirmatory factor analysis) were performed. The CFA indicated an adequate fit to the three-factor model proposed in the original scale (χ2(431) = 808.070, p < 0.01; RMSEA = 0.053; CFI = 0.93; TLI = 0.93). The Social Relations and Normalization dimensions were reliable; however, it is recommended that the items of the Intervention Programs dimension be revised or eliminated, since they could be confusing in the local context. It is concluded that the scale is reliable and valid to evaluate attitudes towards the inclusion of people with disabilities in Chile in the work context.

In the field of computational chemistry, computer models are quickly and cheaply constructed to predict toxicology hazards and results, with no need for test material or animals as these computational predictions are often based on physicochemical properties of chemical structures. Multiple methodologies are employed to support in silico assessments based on machine learning (ML) and deep learning (DL). This review introduces the development of computational toxicology, focusing on ML and DL and emphasizing their importance in the field of toxicology. A fine balance between target potency, selectivity, absorption, distribution, metabolism, excretion, toxicity (ADMET) and clinical safety properties should be achieved to discover a potential new drug. It is advantageous to perform virtual predictions as early as possible in drug development processes, even before a molecule is synthesized. Currently, there are numerous commercially available and free web-based programs for toxicity prediction, which can be used to construct various predictive models. The key features of the QSAR method are also outlined, and the selection of appropriate physicochemical descriptors is a prerequisite for robust predictions. In addition, examples of open-source tools applied to toxicity prediction are included, as well as examples of the application of different computational methods for the prediction of toxicity in drug design and environmental toxicology.

In captive environments, mammals are frequently exposed to various parasitic protozoa and other vector-borne pathogens that can impact both animal health and public health. Monitoring these pathogens is essential for animal welfare and zoonotic disease control. This study aimed to investigate the prevalence of parasitic protozoa and other vector-borne pathogens in captive mammals through molecular detection methods at the Belo Horizonte Zoo, Brazil. Between November 2021 and March 2023, whole blood samples were collected from 40 mammals. Molecular analyses identified piroplasms, Leishmania spp., granulocytic/platelet Anaplasma/Ehrlichia spp., monocytic Ehrlichia spp., Bartonella spp. and hemotropic Mycoplasma spp. with a 72.5% positivity rate. Piroplasms were found in 22.5% (two Pantanal cats, two gorillas, one white rhinoceros, one spider monkey, one jaguar, one tufted capuchin and one hippo) and Leishmania spp. in 12.9% (four maned wolves). Granulocytic/platelet Anaplasma/Ehrlichia spp. were found in 12.5% of the samples (one gorilla and four maned wolves), Ehrlichia canis in 2.5% of the animals (one maned wolf), Bartonella spp. in 42.5% (six howler monkeys, two maned wolves, one gorilla, one white rhino, one southern tamandua, one common woolly monkey, one tufted capuchin, one brown brocket deer, one agouti, one cougar and one hippo), hemotropic Mycoplasma spp. in 17.5% (one gorilla, one maned wolf, one white rhino, one howler monkey, two common woolly monkeys and one European fallow deer). Five Artiodactyla members tested negative for A. marginale. Coinfections occurred in 34.5% of the positive samples. Sequencing revealed that Theileria spp. and Cytauxzoon spp. are closely related to Theileria bicornis and Cytauxzoon felis; Ehrlichia canis and Bartonella spp. are closely related to B. clarridgeiae and B. henselae; and hemotropic Mycoplasma spp. are closely related to Candidatus Mycoplasma haemominutum. Our results showed a high occurrence of vector-borne pathogens in captive animals, including zoonotic species, which may pose a risk to animal and human public health.

Education 4.0 arises to provide citizens with the technical/digital competencies and cognitive/interpersonal skills demanded by Industry 4.0. New technologies drive this change, though time-independent learning remains a challenge, because students might face a lack of support, advice and surveillance when teachers are unavailable. This study proposes complementing presential lessons with online learning driven by ChatGPT, applied as an educational tool able to mentor K-12 students learning science at home. First, ChatGPT’s performance in the field of K-12 science is evaluated, scoring A (9.3/10 in 2023, and 9.7/10 in 2024) and providing detailed, analytic, meaningful, and human-like answers. Then, an empirical interventional study is performed to assess the impact of using ChatGPT as a virtual mentor on real K-12 students. After the intervention, the grades of students in the experimental group improved by 30%, and 70% of students stated a positive perception of the AI, suggesting a positive impact of the proposed educational approach. After discussion, the study concludes ChatGPT might be a useful educational tool able to provide K-12 students learning science with the functional and social/emotional support they might require, democratizing a higher level of knowledge acquisition and promoting students’ autonomy, security and self-efficacy. The results probe ChatGPT’s remarkable capacity (and immense potential) to assist teachers in their mentoring tasks, laying the foundations of virtual mentoring and paving the way for future research aimed at extending the study to other areas and levels, obtaining a more realistic view of AI’s impact on education.

Background: The inflammation associated with overweight and obesity seems to alter iron metabolism, but there are few studies evaluating those conditions in children. Thus, we aimed to evaluate the leukometric, immunological, and hematimetric parameters of overweight and obese schoolchildren. Methods: This is a cross-sectional study in which 39 children living in Chonim de Cima (Brazil) underwent anthropometric, hematological, and immunological assessments. The evaluated parameters were compared between the study group (overweight/obesity, n = 15) and the control group (n = 24). Unpaired t-test, Mann–Whitney test, and linear regression were used for statistical tests, and the panoramic profile was used to illustrate differences between groups. Results: The study group had lower mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) and higher TNF levels compared to the control group. Positive correlations were observed between BMI-for-age percentile and total leukocytes (r = 0.1493; p = 0.0151) or neutrophils (r = 0.1395; p = 0.0192). Negative correlations between the BMI-for-age percentile and MCV (r = 0.1464; p = 0.0162) and MCH (r = 0.1460; p = 0.0164) were found. Furthermore, through the panoramic profile, it was noted that the study group had a higher frequency of individuals with high levels of TNF and lower frequencies of individuals with increased hemoglobin and serum iron. Conclusions: Our data suggest that overweight and obesity contribute to a pro-inflammatory context (leukocytes, neutrophils, and TNF) and MCV and MCH reduction in schoolchildren.

Frequency-Selective Surfaces (FSSs) are structures that act as frequency-dependent electromagnetic filters, enabling innovative designs for energy-efficient building envelopes. This paper explores their potential for energy harvesting and integration into construction materials, offering insights into design strategies, performance analysis, and potential applications of FSS sin future architectural projects. A range of FSS designs are presented and systematically classified based on their performance and adaptability for building integration. This includes their use as part of traditional construction elements or as independent components of building walls. Critical issues such as the limitations, challenges, and durability of FSSs in real-world applications are also examined to provide a comprehensive view of their practical feasibility. Additionally, incorporating the electromagnetic properties of these materials into Building Information Modelling (BIM) systems is recommended. Doing so will enable architects and engineers to better utilize the novel opportunities that FSSs offer, fostering more innovative, energy-efficient building envelopes. Overall, this paper provides valuable insights into how FSSs can transform the future of sustainable architecture and energy management in buildings.

Bats and rodents serve as reservoirs for numerous zoonotic pathogens, including species of Trypanosoma and Leishmania. Domestic rats host the flea-transmitted Trypanosoma (Herpetosoma) lewisi, which can be associated with humans, particularly young or immunocompromised individuals. Using Fluorescent Fragment Length Barcoding (FFLB) and phylogenetic analyses based on SSU rRNA sequences, we identified two Herpetosoma species, T. lewisi-like and T. musculi-like species, in bats of different families inhabiting rooftops and peridomestic structures in Brazil (44%, 107 bats examined) and Venezuela (50%, 52 bats examined). These species are typically associated with Rattus spp. (domestic rats) and Mus musculus (house mice), respectively. Furthermore, bats were co-infected with up to five other species, including Trypanosoma dionisii, Trypanosoma cruzi marinkellei, and isolates from the Trypanosoma Neobat clade, all strongly associated with bats, and Trypanosoma cruzi and Trypanosoma rangeli, known to infect various mammals, including humans. Therefore, our findings expand the known host range of Herpetosoma to bats, marking the first report of potential spillover of Herpetosoma trypanosomes from rodents to bats and underscoring the potential for the cross-species transmission of flea-borne trypanosomes. These results highlight the need for a One Health approach to assess infection risks associated with trypanosome spillover from synanthropic rodents and bats to humans.

The combination of multispectral data and machine learning provides effective and flexible monitoring of the soil nutrient content, which consequently positively impacts plant productivity and food security, and ultimately promotes sustainable agricultural development overall. The aim of this study was to investigate the associations between spectral variables and soil physicochemical attributes, as well as to predict these attributes using spectral variables as inputs in machine learning models. One thousand soil samples were selected from agricultural areas 0–20 cm deep and collected from Northeast Mato Grosso do Sul state of Brazil. A total of 20 g of the dried and homogenized soil sample was added to the Petri dish to perform spectral measurements. Reflectance spectra were obtained by CROP CIRCLE ACS-470 using three spectral bands: green (532–550 nm), red (670–700 nm), and red-edge (730–760 nm). The models were developed with the aid of the Weka environment to predict the soil chemical attributes via the obtained dataset. The models tested were linear regression, random forest (RF), reptree M5P, multilayer preference neural network, and decision tree algorithms, with the correlation coefficient (r) and mean absolute error (MAE) used as accuracy parameters. According to our findings, sulfur exhibited a correlation greater than 0.6 and a reduced mean absolute error, with better performance for the M5P and RF algorithms. On the other hand, the macronutrients S, Ca, Mg, and K presented modest r values (approximately 0.3), indicating a moderate correlation with actual observations, which are not recommended for use in soil analysis. This soil analysis technique requires more refined correlation models for accurate prediction.

The application of hyperspectral data in machine learning models can contribute to the rapid and accurate determination of caffeine content in coffee beans. This study aimed to identify the machine learning algorithm with the best performance for predicting caffeine content and to find input data for these models that can improve the accuracy of these algorithms. The coffee beans were harvested one year after the seedlings were planted. The fresh beans were taken to the spectroscopy laboratory (Laspec) at the Federal University of Mato Grosso do Sul, Chapadão do Sul campus, for spectral evaluation using a spectroradiometer. For the analysis, the dried coffee beans were ground and sieved for the quantification of caffeine, which was carried out using a liquid chromatograph on the Waters Acquity 1100 series UPLC system, with an automatic sample injector. The spectral data of the beans, as well as the spectral data of the roasted and ground coffee, were analyzed using machine learning (ML) algorithms to predict caffeine content. Four databases were used as input: the spectral information of the bean (CG), the spectral information of the bean with additional clone information (CG+C), the spectral information of the bean after roasting and grinding (CGRG) and the spectral information of the bean after roasting and grinding with additional clone information (CGRG+C). The caffeine content was used as an output to be predicted. Each database was subjected to different machine learning models: artificial neural networks (ANNs), decision tree (DT), linear regression (LR), M5P, and random forest (RF) algorithms. Pearson’s correlation coefficient, mean absolute error, and root mean square error were tested as model accuracy metrics. The support vector machine algorithm showed the best accuracy in predicting caffeine content when using hyperspectral data from roasted and ground coffee beans. This performance was significantly improved when clone information was included, allowing for an even more accurate analysis.

Background: The Internet of Things (IoT) has improved many aspects that have impacted the industry and the people’s daily lives. To begin with, the IoT allows communication to be made across a wide range of devices, from household appliances to industrial machinery. This connectivity allows for a better integration of the pervasive computing, making devices “smart” and capable of interacting with each other and with the corresponding users in a sublime way. However, the widespread adoption of IoT devices has introduced some security challenges, because these devices usually run in environments that have limited resources. As IoT technology becomes more integrated into critical infrastructure and daily life, the need for stronger security measures will increase. These devices are exposed to a variety of cyber-attacks. This literature review synthesizes the current research of artificial intelligence (AI) technologies to improve IoT security. This review addresses key research questions, including: (1) What are the primary challenges and threats that IoT devices face?; (2) How can AI be used to improve IoT security?; (3) What AI techniques are currently being used for this purpose?; and (4) How does applying AI to IoT security differ from traditional methods? Methods: We included a total of 33 peer-reviewed studies published between 2020 and 2024, specifically in journal and conference papers written in English. Studies irrelevant to the use of AI for IoT security, duplicate studies, and articles without full-text access were excluded. The literature search was conducted using scientific databases, including MDPI, ScienceDirect, IEEE Xplore, and SpringerLink. Results were synthesized through a narrative synthesis approach, with the help of the Parsifal tool to organize and visualize key themes and trends. Results: We focus on the use of machine learning, deep learning, and federated learning, which are used for anomaly detection to identify and mitigate the security threats inherent to these devices. AI-driven technologies offer promising solutions for attack detection and predictive analysis, reducing the need for human intervention more significantly. This review acknowledges limitations such as the rapidly evolving nature of IoT technologies, the early-stage development or proprietary nature of many AI techniques, the variable performance of AI models in real-world applications, and potential biases in the search and selection of articles. The risk of bias in this systematic review is moderate. While the study selection and data collection processes are robust, the reliance on narrative synthesis and the limited exploration of potential biases in the selection process introduce some risk. Transparency in funding and conflict of interest reporting reduces bias in those areas. Discussion: The effectiveness of these AI-based approaches can vary depending on the performance of the model and the computational efficiency. In this article, we provide a comprehensive overview of existing AI models applied to IoT security, including machine learning (ML), deep learning (DL), and hybrid approaches. We also examine their role in enhancing the detection accuracy. Despite all the advances, challenges still remain in terms of data privacy and the scalability of AI solutions in IoT security. Conclusion: This review provides a comprehensive overview of ML applications to enhance IoT security. We also discuss and outline future directions, emphasizing the need for collaboration between interested parties and ongoing innovation to address the evolving threat landscape in IoT security.

Background: Puerto Rico (PR) has experienced significant demographic changes, characterized primarily by an aging population and an unprecedented exodus of medical doctors. Ophthalmologists are of particular concern as they commonly serve older populations, and the island has high rates of some age-related eye diseases in the United States (US). Our research aims to investigate the factors driving ophthalmologists in PR to emigrate to the mainland US. Methods: This is a cross-sectional study among ophthalmologists in PR, using survey data collected from May to June 2023. This study recruited a convenient sample of all ophthalmologists practicing in PR via outreach in person and online communities. The survey covered various types of challenges faced by ophthalmologists, their demographics, and practice details. STATA/BE 18 statistical software was used for data analysis. Statistical tests, such as chi-square and proportion tests, were performed, stratifying results by age, gender, subspecialty, geographic health districts, experience, and practice type. Results: Among 130 of the estimated 218 ophthalmologists in PR, insurance/billing issues were identified as the primary challenge to practicing in PR and the primary reason to leave PR. The challenges that were identified included required authorizations for patient care, unjustified claim rejections, and threats of contract cancellation. We found that new ophthalmologists (≤15 years of practice) faced more specific challenges than experienced ophthalmologists (>15 years of practice), such as difficulty in obtaining insurance contracts. Conclusions: Insurance/billing issues are a pervasive concern for ophthalmologists in PR. New ophthalmologists are disproportionately affected by these challenges, potentially leading some to find employment outside of PR. There is a need for targeted policies—regulation of insurance contracting and increased reimbursement from private insurance plans—to reduce insurance contracting barriers for keeping a sustainable physician workforce in PR.

Background/Objectives: Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by cutaneous and visceral fibrosis, vascular alterations, and a persistent inflammatory response. Despite advances in understanding the pathogenic mechanisms underlying SSc, current therapeutic options remain limited. Chlorogenic acid (CGA) is a polyphenol widely distributed in plants and has shown antioxidant, anti-inflammatory, and antifibrotic properties. However, its therapeutic potential in SSc has not been investigated yet. Methods: A model of SSc was established by administering bleomycin (BLM) at 100 U/kg to CD1 mice via an osmotic minipump. After fourteen days of BLM administration, CGA (60 mg/kg) was intragastric administered on consecutive days until day 20. On day 21, all mice were sacrificed. The effect of CGA was histologically evaluated by hematoxylin and eosin and Masson’s trichrome staining. Results: CGA treatment significantly attenuated dermal fibrosis in the BLM-induced mice model of SSc by reducing histopathological damage, including increased dermal thickness, inflammation, collagen deposition, and SSc-associated pulmonary fibrosis. Conclusions: The evidence shows that CGA attenuates BLM-induced SSc in a mice model and strongly suggests that CGA may be a promising compound for the treatment of SSc.

Background. Peptidergic GPCR systems are broadly distributed in the human body and regulate numerous physiological processes by activating complex networks of intracellular biochemical events responsible for cell regulation and survival. Excessive stimulation, ill-function, or blockade of GPCRs produces cell disturbances that may cause disease should compensatory mechanisms not suffice. Methods and Results. Revision of updated experimental research provided an evident relationship associating peptidergic GPCR malfunction with tumor formation and maintenance resulting from uncontrolled cell proliferation and migration, colonization, inhibition of apoptosis or altered metabolism, and increased angiogenesis in tumoral tissues. Conclusion. Determination of the implication of GPCR peptide signaling in specific neoplasia is crucial to designing tailored pharmacological treatments to counteract or dismantle the origin of the signaling circuitry causing cellular disruption. In some cases, particular ligands for these receptors may serve as concomitant treatments to aid other pharmacological or physical approaches to eradicate neoplasias.

Background: Plantar warts, caused by human papillomavirus (HPV), are a common condition that can be painful and resistant to treatment. There are various therapeutic options for managing them, but it is not always clear which are the most effective and tolerated by patients. Among the most commonly used treatments are a zinc and nitric complex (nitrizinc complex), cantharidin, and bleomycin, each with different mechanisms of action and profiles in terms of pain and patient satisfaction. Objectives: We aimed to evaluate and compare the clinical efficacy, post-treatment pain, and patient satisfaction among three common treatments (zinc and nitric complex, cantharidin, and bleomycin) in subjects with plantar warts, as well as identify the most effective and best-tolerated treatment. Materials and Methods: This is a retrospective case series study analyzing 60 records of subjects aged 18 to 40 years diagnosed with plantar warts without systemic diseases or allergies and without any prior treatment. Complete records from 2020 to 2023 were selected. Subjects were divided into three groups according to the treatment received (zinc and nitric complex, cantharidin, bleomycin), and demographic variables, post-treatment pain (measured using the visual analog scale), the number of sessions required, and satisfaction after discharge (evaluated with the Likert scale) were analyzed. Results: Of the 60 subjects included, the group treated with bleomycin experienced higher levels of pain after the first session (mean of 7.1 points on the VAS) compared to the cantharidin group (2.7 points) and the zinc and nitric complex group (1.1 points). However, the bleomycin group required fewer sessions for complete healing (an average of 1.8 sessions), while the nitric acid group needed more (3.4 sessions), with cantharidin falling in between (2.5 sessions). Regarding post-discharge satisfaction, all groups showed comparable scores (between 7.9 and 8.5 points), although cantharidin demonstrated slightly higher satisfaction. A statistical analysis showed significant differences in the number of sessions and post-treatment pain between treatments (p < 0.05) but not in final satisfaction. Conclusions: Although bleomycin treatment is more painful, it is the most effective in terms of reducing the number of sessions required for complete healing. Cantharidin offers a good balance between efficacy and patient satisfaction, while a zinc and nitric complex, although less painful, requires more sessions for complete treatment. Each treatment has specific advantages, suggesting that therapeutic choices should be personalized according to the patient’s needs and preferences.

The liver is a common site for metastatic disease. In select patients with isolated liver metastases, surgical resection improves survival and may be potentially curative in patients with favorable “tumor biology”. However, when surgical resection is not feasible, liver-directed therapies (LDTs) can also improve outcomes, including survival, in the appropriate clinical situations. LDTs, including hepatic artery infusion, radioembolization, radiation, and ablation techniques, such as thermal ablation and histotripsy, offer local control and potential systemic effects, including the abscopal effect. The abscopal effect occurs when nontargeted, nontreated tumors regress following localized therapy to other tumors. Preclinical and clinical studies suggest that antigen-induced upregulation of key immune regulators plays a central role in this process. Unfortunately, clinical reports of the abscopal effect following LDT are exceedingly rare. However, histotripsy, a noninvasive, nonionizing, and nonthermal ablation technique, may induce an abscopal effect more frequently and robustly than other LDTs. Histotripsy enhances tumor immunogenicity through precise acoustic cavitation that better preserves the local tissue architecture while increasing antigen release, resulting in a robust local and systemic immune response. Ongoing trials are investigating these immunogenic mechanisms and the ability to generate an abscopal effect more reliably with adjuncts such as checkpoint inhibitors. This work has significant implications regarding the management of patients with liver metastasis.

Initial studies indicate that structured polymer surfaces can support the attachment and biofilm formation of bacteria and thereby provide enhanced positive effects of beneficial bacteria, for instance in biocontrol in aquacultures. In this study, we demonstrate a test platform to further explore the surface topography for bacterial attachment and biofilm growth. It is based on a cyclic olefin copolymer (COC) materials platform, and nanoimprint technology was used for the replication of microstructures. The use of nanoimprint technology ensures precise micropattern transfer, enabling easy prototyping. Further, the process parameters of the mold preparation and nanoimprinting are discussed, with the purpose of optimizing the polymer pattern profile. This study has the potential to identify promising surfaces for biofilm growth of beneficial bacteria.

Background: Pediatric illnesses not only impose physical challenges on affected children, but also profoundly impact their emotional well-being. Understanding how parents respond to their children’s psychological distress during medical experiences is crucial for enhancing the overall support provided to these families. Aim: This study evaluated the internal structure of the Parental Response Styles Questionnaire (PRSQ), designed to differentiate parental responses to psychological distress in children with pediatric illnesses. Methods: A sample of 701 parents of children with medical issues responded to the PRSQ, reporting their different emotional expressions and responses to their children’s expressions of distress during the medical experience. Results: Factor analysis confirmed, in three of the five subsamples, an internal scale structure consisting of four factors: apathy and dysphoria, irritability and rejection, overprotectiveness, and perceived maladjustment. The invariance analyses revealed that congenital heart disease and neurological disorders are more similar in function to each other than pediatric cancer. Parents of children with neurological disorders exhibited a notably insecure pattern of parental responsiveness. Conclusions: In pediatric contexts, parental responses to their children’s emotional distress are significant factors in the process of adaptation. These responses can be measured, differentiated, and, ideally, managed by nurses and other healthcare professionals. The Parental Response Styles Questionnaire (PRSQ) is a promising tool for assessing parental reactions during their children’s treatment, and its structure appears to be particularly robust across diagnoses such as pediatric cancer, congenital heart disease, and neurological disorders.

Background: Nursing students face unique challenges during their university education, making them vulnerable to mental health problems. Psychological resilience has been identified as a protective factor against these issues. However, previous reviews have identified gaps in the literature on resilience and mental health among nursing students. Objectives: This scoping review aims to identify and map studies on psychological resilience and mental health in undergraduate nursing students, synthesize current evidence on their relationship, identify interventions for enhancing resilience, and highlight gaps in the existing literature. Eligibility criteria: Studies published between January 2019 and April 2024 in English, Portuguese, and Spanish addressing resilience and mental health in undergraduate nursing students will be included. Primary studies, secondary studies, clinical guidelines, and grey literature will be considered. Sources of evidence: Searches will be conducted in multiple databases including EMBASE, ERIC, PubMed, Science Direct, Web of Science, DOAJ, ELSEVIER, EMERALD, and WILEY ONLINE LIBRARY. Grey literature sources will also be searched. Charting methods: Data will be extracted using a standardized form and synthesized narratively. Thematic analysis will be conducted using MAXQDA software ((Verbi GmbH, 24 version, 2023). Quantitative summaries, visual mapping, subgroup analyses, and trend analyses will be performed where appropriate. Results: As this is a protocol, results are not yet available. The review will present a comprehensive map of the current literature on psychological resilience and mental health in nursing students, including identified interventions and research gaps. Conclusions: This scoping review will provide valuable insights to guide curriculum development, support services, and policy-making in nursing education. The findings may support actions to strengthen resilience and prevent mental health problems among future nursing professionals.

Background: The care of dependent people is eminently family-oriented, and often, there is a high level of dedication to this family care. Constant and continuous care leads to a series of negative psychological consequences. Social support has been related to improved mental health in family caregivers. We found heterogeneous results regarding the relationship between the types of social support received and the perceived level of support. In addition, to our knowledge, no reviews analyse this relationship among family caregivers. Objectives: Therefore, we objective to systematically synthesise the relationships between perceived and received social support in informal caregivers. Methodology: We have carried out a quantitative systematic review with a meta-analysis, registered in PROSPERO (id: CRD42023470047); the systematic search was carried out in the following databases: PubMed, CINAHL, PsycINFO, and Scopus, until November 2023. After the selection and review of the results, twelve studies were obtained, two of which were eliminated due to a high risk of classification bias. Results: Regarding the results, a medium-size positive statistical association was found (r = 0.43). The results were consistent, accurate, and robust. The Trim and Fill test showed a variation of 7%. Subgroup analysis indicated no differences in the age group of the people cared for (adults or children), selection bias, and confounding bias. Conclusions: In conclusions, perceived social support is related to more social support received by family caregivers.

We investigate the dynamic excitation of surface plasmon polaritons (SPPs) using vector Laguerre–Gauss (LG) beams, which offer unique properties for manipulating the polarization and spatial distribution of light. Our study demonstrates the efficient coupling of SPPs with LG beams, characterized by their azimuthal and radial indices (m,p), as well as polarization distribution type. Numerical simulations reveal that the vector nature of LG beams enables selective excitation of SPPs, depending on the polarization type of the beam. Experimental verification of our simulations is achieved using a gold circular Bragg grating and a spatial light modulator that generates vector LG beams. Leakage radiation imaging demonstrates the potential of vector LG beams for dynamic SPP excitation and manipulation. This study opens novel ways for the control of SPPs in plasmonic devices, such as modulators, and nanophotonic circuits.

Aims: this study aims to investigate the impact of simulated skin color and the use of fiducial markers on the accuracy of 3D facial scans, comparing two types of structured light scanners under constant ambient lighting conditions. Materials and Methods: Three mannequins with different skin colors—black, white, and pink—were scanned using two light based hand-held scanners (infrared light and blue-light). Each mannequin was scanned with and without fiducial markers placed on defined anatomical landmarks. A total of one hundred thirty-two scans were performed and converted into standard tessellation language (STL) files. STL files from each scanner were compared to their respective control scans using point cloud comparison software. Accuracy was evaluated based on root mean square (RMS) values. Descriptive statistics summarized the data, and a t-test was performed to assess differences in RMS values between scans with and without fiducial markers for each scanner type. Results: The infrared light scanner showed the highest accuracy for the white mannequin, as evidenced by lower RMS values compared to the pink and black mannequins. Adding fiducial markers significantly enhanced scan accuracy for the pink and black mannequins. The blue-light scanner achieved accuracy for the white and pink mannequins comparable to that of the infrared scanner. However, it was unable to scan the black mannequin, even with the use of markers. Conclusions: Within the limitations of this study, simulated skin color significantly affects the accuracy of facial 3D scans. Scans of lighter (white) tones demonstrate higher accuracy compared to darker tones. Fiducial markers enhance the accuracy for an infrared scanner; however, a blue-light scanner is unable to capture dark simulated skin, even with the addition of fiducial markers.

Biochar, produced through the pyrolysis of biomass and green waste, offers significant potential as a soil amendment to enhance soil health and sustainability in agriculture. However, the current Measurement, Reporting, and Verification (MRV) systems for biochar predominantly focus on carbon credits/offsets, neglecting crucial aspects related to its usability and suitability as a soil amendment on agricultural fields. Through an examination of recent findings, this perspective explores the integration of geochemical tracers, functional group (hydroxyl, carboxyl, phenolic, lactonic, etc.) analysis, and nutrient dynamics into MRV procedures/systems to create a more comprehensive framework. By examining the applicability of these indicators, this paper identifies key gaps and proposes a more robust MRV approach. Such a system would not only facilitate better assessment of biochar’s agronomic benefits but also guide its optimal use in various soil types and agricultural practices.

European sea bass (Dicentrarchus labrax) is one of the most significant species farmed in the Mediterranean, yet a very perishable product. Its quality deteriorates rapidly as a result of three mechanisms: microbial activity, chemical oxidation, and enzymatic degradation. Microbial spoilage is the mechanism that contributes most to the quality deterioration of fresh and non-processed fish. To this end, our study aims to identify for the first time the combined effect of aquatic environment and harvest method on the composition and trajectory at storage at 0 °C of the European sea bass skin microbiome. Sampling was performed in two commercial fish farms in Western (WG) and Central Greece (CG) where fish were harvested using different methods: direct immersion in ice water or a mixture of slurry ice; application of electro-stunning prior to immersion in ice water. Samples were collected on harvest day and one week post-harvest. To profile the bacterial communities in the fish skin, 16S ribosomal RNA gene sequencing was used. The results and the following analyses indicated that the aquatic environment shaped the original composition of the skin microbiome, with 815 ASVs identified in the WG farm as opposed to 362 ASVs in the CG farm. Moreover, Pseudomonas and Pseudoalteromonas dominated the skin microbiome in the WG farm, unlike the CG farm where Shewanella and Psychrobacter were the dominant genera. All these genera contain species such as Shewanella putrefaciens, Pseudomonas aeruginosa, Pseudoalteromonas spp., and Psychrobacter sp., all of which have been implicated in the deterioration and spoilage of the final product. The different harvest methods drove variations in the microbiome already shaped by the aquatic environment, with electro-stunning favoring more diversity in the skin microbiome. The aquatic environment in combination with the harvest method appeared to determine the skin microbiome trajectory at storage at 0 °C. Although Shewanella had dominated the skin microbiome in all samples one week post-harvest, the diversity and the relative abundance of genera were strongly influenced by the aquatic environment and the harvest method. This study sheds light on the hierarchy of the factors shaping the fish skin microbiome and their importance for controlling post-harvest quality of fresh fish.

Emerging pollutants, like phytoestrogens, are gaining attention in the scientific community for their impact on aquatic organisms. Nevertheless, there is a paucity of studies examining their effects on tropical aquatic species. In this context, the objective of this study was to (i) conduct chronic ecotoxicological assays with the sea urchin Echinometra lucunter with two phytoestrogens, namely genistein and daidzein (both derived from soy plant), and compare the results to the synthetic estrogen ‘estradiol valerate’; (ii) predict the potential risks of these phytoestrogens through an ecological risk assessment; and (iii) create a prioritization list of the most hazardous phytoestrogens using environmental persistence, bioaccumulation, and toxicity (PBT criteria). The results of chronic exposure demonstrated the following order of toxicity: daidzein (IC50 = 2.60 mg/L); genistein (IC50 = 3.37 mg/L); and estradiol valerate (IC50 = 28.40 mg/L). The results classify genistein and daidzein as “toxic” and estradiol valerate as “harmful” to the sea urchin. The final ranking of the PBT approach in coastal waters was as follows: biochanin A (the highest priority), followed by formononetin, genistein, enterolactone, daidzein, estradiol valerate, coumestrol, and 8-prenylnaringenin. The dataset highlights the importance of environmental monitoring to track phytoestrogens in Latin American coastal areas, particularly in developing countries.

In this research work, the feasibility of using fusel oil, a by-product of the sugar–alcohol industry, as an LVLC solvent in blends with straight vegetable oils (SVOs) and diesel was investigated. Concretely, diesel/fusel oil/sunflower oil (D/FO/SO) and diesel/fusel oil/castor oil (D/FO/CO) triple blends were prepared and characterized by measuring the most important physicochemical properties, i.e., viscosity, density, cold flow properties, flash point and cetane number. An appreciable improvement in cold flow values has been achieved with triple blends, without compromising properties such as calorific value and cetane number. Likewise, the triple blends meet the viscosity and density requirements specified by the European quality standard EN 14214 and the American standard ASTM D6751. After characterization, the triple blends were used on a diesel engine, evaluating different parameters such as power output, opacity, exhaust emissions (CO and NOx) and consumption at different engine loads. The results indicate that as the biofuel content in the blend increases, engine power decreases while fuel consumption rises. Nevertheless, the values obtained with D/FO/CO are better than those for D/FO/SO and are also very similar to those of fossil diesel. Regarding opacity values and NOx emissions obtained with the utilization of the triple blends, they are lower than those produced by diesel. However, in the case of CO emissions, it depends on the type of oil used, with the samples prepared with castor oil exhibiting the best results.

The rapid urbanization process in recent decades has altered the carbon cycle and exacerbated the impact of climate change, prompting many cities to develop tree planting and green area preservation as mitigation and adaptation measures. While numerous studies have estimated the carbon stocks of urban trees in temperate and subtropical cities, data from tropical regions, including tropical botanic gardens, are scarce. This study aimed to quantify the aboveground biomass and carbon (AGB and AGC, respectively) stocks in trees at the Rio de Janeiro Botanical Garden arboretum, Rio de Janeiro, Brazil. Our survey included 6793 stems with a diameter at breast height (DBH) ≥ 10 cm. The total AGB was 8047 ± 402 Mg, representing 4024 ± 201 Mg of AGC. The AGB density was 207 ± 10 Mg·ha−1 (AGC = 104 ± 5 Mg·ha−1), which is slightly lower than the density stored in Brazil’s main forest complexes, the Atlantic and Amazon forests, but much higher than in many cities worldwide. Our results suggest that, in addition to their global importance for plant conservation, tropical botanic gardens could function as significant carbon sinks within the urban matrix.

The aim of this study was to assess the mental health situation of children and adolescents during a period of less strict COVID-19-pandemic-related measures after the first pandemic wave. This cross-sectional study was conducted in July 2021 by carrying out an online survey among children and adolescents (aged 10–18 years) from Halle (Saale), Germany (n = 233). The questionnaire measured important aspects of mental health among young people, namely health-related quality of life (HRQoL, using the self-report version of the KIDSCREEN-10), mental health problems in general (using the SDQ), depressive symptoms (using the CES-DC), and psychosomatic complaints (using the HBSC symptom checklist). In addition, other important health issues such as sleep behavior and related difficulties, disordered eating, and any positive consequences of the pandemic were addressed. The results were analyzed using descriptive statistics. A total of 223 children participated in the survey. About 69.7% of the participating children and adolescents had a high HRQoL, while 10.5% displayed abnormal results on the SDQ. There were indications of emotional problems in 16.5% of the participants based on the SDQ subscales. Almost 44% of the participants were screened as positive for depressive symptoms on the CES-DC, with girls and older adolescents being more likely to be affected. This also applied for psychosomatic complaints. Here, irritability was experienced at least once a week or more frequently by 58.9% of the children and adolescents. Although we had a small sample size, this study showed a high prevalence of mental health problems regarding the SDQ and HRQoL. However, our study population showed a better mental health than comparable studies conducted earlier in the pandemic. Depressive symptoms were still substantially higher than those in pre-pandemic data. We hypothesize that this might reflect the fact that there were a few COVID-19-related restrictions at the time when our survey took place. Based on these findings, we assume that the mental health of children and adolescents differed between different phases in the pandemic.

Drylands in Brazil have been exploring sisal (Agave sisalana) as an essential source of income. However, the solid residues generated because of this activity still need suitable destinations; therefore, research has been carried out to transform them into added-value products. Therefore, the present study evaluated the potential of sisal or agave solid residue as a precursor feedstock for second-generation ethanol production. Acid and acid–alkaline pretreatments were carried out on sisal residues to enrich the biomass with cellulose and maximize enzymatic digestibility. Second-generation ethanol production was carried out using Semi-simultaneous saccharification and fermentation (SSSF). Regardless of catalyst dosage and incubation time, oxalic acid pretreatments generated samples with a similar chemical composition to those pretreated with sulfuric acid. However, samples pretreated with oxalic acid showed lower enzymatic digestibility. Samples pretreated with oxalic acid and sodium hydroxide obtained 14.28 g/L of glucose and cellulose conversion of 79.1% (at 5% solids), while 21.49 g/L glucose and 91.2% of cellulose conversion were obtained in the hydrolysis of pretreated samples with sulfuric acid and sodium hydroxide combined pretreatments. The pretreatment sequence efficiently reduced cellulase dosage from 20 to 10 FPU/g without compromising sugar release. SSSF achieved maximum production of 40 g/L ethanol and 43% ethanol conversion using 30% solids and gradually adding biomass and cellulases.

Background/Objectives: Physiotherapists face significant challenges in managing chronic pain; a complex condition best addressed through a biopsychosocial (BPS) approach. Although substantial evidence exists globally, research specific to Spain remains limited. This study explores the experiences and challenges Spanish physiotherapists encounter in integrating BPS elements across public and private healthcare settings. Methods: Semi-structured interviews with 12 experienced physiotherapists were conducted, using a qualitative approach with purposive sampling and reflexive thematic analysis. The analysis, grounded in a constructivist/interpretivist framework, allowed themes to emerge naturally from the data, supported by relevant quotes. Results: Three primary themes were identified: (1) challenges in implementing the BPS approach, including patient resistance and limited training; (2) facilitators for adopting the BPS model, such as multidisciplinary support and positive patient outcomes; and (3) emotional and psychological aspects of the physiotherapists. The findings highlight the complexities of chronic pain management in physiotherapy, emphasizing the need for enhanced psychological training, integrated multidisciplinary care, early diagnosis, and effective family involvement. These insights are critical for improving both patient care and physiotherapist well-being. Conclusions: This study provides valuable guidance for future strategies, focusing on educational enhancements, multidisciplinary collaboration, healthcare policy reform, and emotional support for physiotherapists within the Spanish healthcare context.

The main objectives of this study were to adapt the AUTODDIS scale to the cultural and social dimensions of Chile and to analyze its reliability and validity. The reliability and validity were assessed through a pilot study conducted with a population of students with intellectual disabilities (ID). The linguistic adaptation was executed according to expert judgments of each indicator: adequacy, coherence, relevance, and clarity. After the scale adaptation, a scale pilot was conducted to explore its technical properties. It was performed in a public school for students with ID. The validity coefficient result was 0.998, while the complete reliability result was α = 0.978. For the reliability subscales, the results were the following: autonomy α = 0.941, self-initiation α = 0.925, self-direction α = 0.970, self-regulation α = 0.804, and self-concept α = 0.935. The results confirm the AUTODDIS scale as a valid and reliable instrument to evaluate self-determination. However, it is necessary to apply this scale to a larger number of students with ID to generalize these results.

Medial gastrocnemius silent contractures (MGSCs) are prevalent, notably impacting functional status and increasing the risk of foot and ankle disorders, especially among aging populations. Although traditionally managed by podiatrists and physiotherapists, the role of rehabilitation nursing in addressing MGSCs is gaining recognition. This paper elucidates the contributions of rehabilitation nursing to the functional rehabilitation of MGSC patients and underscores its vital role within the multidisciplinary team. Initially, the paper defines the clinical and physiological characteristics of MGSCs and their implications in foot and ankle disorders. It then meticulously explores rehabilitation nursing interventions—including personalized stretching regimens, vibration therapy, balance exercises, and judicious footwear selection—emphasizing their efficacy in enhancing muscle flexibility, joint mobility, and postural stability. The emphasis is on patient-centered approaches and education to foster treatment adherence and positive rehabilitation outcomes. The significance of interdisciplinary collaboration is highlighted, focusing on how rehabilitation nursing optimizes patient care and mitigates complications. The paper advocates for recognizing and integrating rehabilitation nursing in managing MGSC-related disorders, emphasizing its importance in achieving successful functional outcomes.

Varronia curassavica Jacq. is an aromatic species appertaining to the Boraginaceae family and has been mentioned for its numerous traditional uses and pharmacological properties, especially its antimicrobial and anti-inflammatory effects. The aim of the present study was to investigate the phytochemical profile and antifungal activities of the essential oils of V. curassavica, in addition to analyzing the ADMET properties of the majority components. The GC-MS analysis of V. curassavica essential oil (EOVC) comprised 97.36% of total composition, with α-pinene, β-caryophyllene, and bicyclogermacrene (44.46%, 22.87%, and 13.05%, respectively) as the main constituents among other minor/trace constituents. The antifungal activity of EOVC was evaluated against three Candida species and was observed with IC50 > 200 μg/mL. Remarkably, the combination of EOVC with fluconazole significantly reduced the IC50 required for the drug to inhibit C. tropicalis (0.003 μg/mL), C. albicans (0.7996 μg/mL), and C. krusei (17.73 μg/mL). In addition, ADME/Tox studies using α-pinene revealed that the compound poses no toxicity threats but requires caution due to its high permeability to the blood–brain barrier (BBB). Overall, the obtained results suggest that Varronia curassavica essential oil is a potentially good antifungal agent for combating fungal resistance.

Many anuran survival strategies involve hydric regulation, and reproduction is not different. The aquaporin (AQP) family plays an important role in water transport and regulation in many tissues, including the male gonad. The testes undergo various stages of change during the reproductive cycle, and water balance is an important factor for ensuring reproductive success. Considering the relevance of water control in testicular development in anurans and the lack of research regarding the tissue localization of AQP in the male gonad, the present study investigated the expression of three AQPs (1, 2, and 9) in the testis of the neotropical anuran species Leptodactylus podicipinus during two different periods of the reproductive cycle (reproductive and non-reproductive). AQP1 and 2 immunoreactions were found in early germ cells, spermatozoa, Leydig cells, and Sertoli cells, which were more frequently expressed within the reproductive period. AQP1 was also found in the testicular blood vessels. AQP9 was identified predominantly in the epithelium of the intratesticular ducts of reproductive-period individuals. This study presents, for the first time, the localization of AQP1, AQP2, and AQP9 in the testes of an anuran species and the differences in their location during two distinct periods of the reproductive cycle.

Thyroid gland carcinoma (TGC), though only 1% of all carcinomas, is the most common endocrine neoplasm with an increasing incidence since the 1990s. Of the TGC types, papillary thyroid carcinoma (PTC) is the most common and has the best overall prognosis. Although primarily studied in various neural spectrum disorders, monoamine oxidase A (MAOA) may also contribute to cancer occurrence. This case control study assessed the prevalence of MAOA uVNTR polymorphism in PTC patients, compared its frequency with a healthy control, and assessed the variant’s impact on clinical features. The research participants consisted of 30 PTC patients (20 female, 10 male) over 18 years old who underwent thyroidectomy and radioiodine therapy at a Federal District private clinic and 30 paired and unrelated healthy volunteers (18 female, 12 male). The most frequent MAOA uVNTR alleles were 3R and 4R. Although no significant difference was detected in the genotypic distribution nor the PTC patients’ thyroglobulin, thyroid-stimulating hormone, and antithyroglobulin levels; body mass indexes; administered radiopharmaceutical (131I) doses; or biological sex, the presence of at least one 3R allele was associated with a larger tumor size (T3 + T4 staging). Thus, the 3R allele seems to be associated with PTC pathogenesis severity.

Background: The use of complementary therapies in the general population is increasing, so it is necessary to understand the training that health professionals receive in this type of therapy in their training plans, as they are often the primary source of information for patients. Our aim was to investigate Spanish universities that offer subjects on complementary therapies in their nursing degree programs. Methods: This study is an observational, descriptive, cross-sectional study. For this purpose, we used a document published on the website of the Ministry of Universities as the working document. Additionally, a literature search was conducted up to September 2023 in the PubMed database, along with reverse searches. Results: Out of a total of 62 universities, only 16 (29%) offer a subject related to this type of therapy, 27.5% (11) are public universities and 22.7% (5) are private universities, most of them being optional subjects. Conclusions: The training content on complementary care in nursing degree programs in Spanish universities is scarce, highlighting the potential benefit of expanding and promoting it, in line with the recommendations of the World Health Organization.

This study investigates the temporal trends and correlations between Saharan dust mass concentration densities (DMCD) and Sargassum concentrations (SCT) in the tropical North Atlantic. Average DMCD data for June, July, and August from 1980 to 2022, alongside SCT data for the same months from 2012 to 2022, were analyzed using Mann–Kendall tests for trends and lagged regression models to assess whether higher Saharan dust levels correlate with Sargassum outbreaks in the region. A comprehensive analysis reveals a significant upward trend in Saharan dust quantities over the study period, with the summer months of June, July, and August exhibiting consistent increases. Notably, 2018 and 2020 recorded the highest mean DMCD levels, with June showing the most significant increasing trend, peaking in 2019. These findings are consistent with previous studies indicating a continuous elevation in Saharan dust concentrations in the tropical atmosphere of the North Atlantic. Simultaneously, Sargassum concentrations also show a notable increasing trend, particularly in 2018, which experienced both peak SCT and elevated DMCD levels. Mann–Kendall tests confirm statistically significant upward trends in both Saharan dust and Sargassum concentrations. Simple linear regression and lagged regression analyses reveal positive correlations between DMCD and SCT, highlighting a temporal component with stronger associations observed in July and the overall June–July–August (JJA) period. These results underscore the potential contribution of elevated Saharan dust concentrations to the recent surge in Sargassum outbreaks in the tropical North Atlantic. Furthermore, the results from forward stepwise regression (FSR) models indicate that DMCD and chlorophyll (CHLO) are the most critical predictors of SCT for the summer months, while sea surface temperature (SST) was not a significant predictor. These findings emphasize the importance of monitoring Saharan dust and chlorophyll trends in the Eastern Caribbean, as both factors are essential for improving Sargassum modeling and prediction in the region. This study provides valuable insights into the climatic factors influencing marine ecosystems and highlights the need for integrated environmental monitoring to manage the impacts on coastal economies.

Introduction: Advancements in oncology have revolutionized cancer treatment, with new drugs being approved at different rates worldwide. Our objective was to evaluate the approval of new oncological drugs for solid tumors by the Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Brazilian Health Regulatory Agency (ANVISA) since 2008. Methods: Data were collected from public and online databases by searching for the date of submission, the date of the procedure, the date of approval, clinical indication, and drug characteristics. The distribution was tested using the Shapiro–Wilk, test and comparisons were made using the Mann–Whitney U test; the data are reported using median days and interquartile range (IQR1–IQR3). Results: In total, 104 new oncologic drugs for the treatment of solid tumors were approved by the three agencies: 98 by the FDA, 90 by the EMA, and 68 by ANVISA. The cancer types with the highest number of first indications were lung cancer (n = 24), breast cancer (n = 15), and melanoma (n = 15). Most approvals were for oral medications (n = 63) and tyrosine–kinase inhibitors or other small-molecule inhibitors (n = 54). Time to approval after submission was as follows: the FDA—224 days (167–285); the EMA—364 days (330–418); and ANVISA—403 days (276–636) (p < 0.00001 for the FDA to the EMA and the FDA to ANVISA). The difference between submission dates among the agencies was as follows: EMA–FDA: 24 days (0–85); ANVISA–FDA: 255 (114–632); and ANVISA–EMA: 260 (109–645). The difference in approval dates between the agencies was as follows: EMA–FDA: 185 days (59–319); ANVISA–FDA: 558 (278–957); and ANVISA–EMA: 435 days (158–918). Conclusions: New oncologic drugs are submitted to the FDA and EMA for approval on similar dates; however, the longer appraisal period by the EMA pushes the approval date for Europe to approximately 6 months later. The same steps at ANVISA delay the approval by 1.5 years. Such procedures cause a significant difference in available medications between these regions.

Endangered sharks and rays usually often lack basic information specific to conservation, such as population size. Previous studies have reconstructed shark and ray catch statistics between 1950 and 2019 for the southeast = south of Brazil, but lacking detail at the species level, because the catches were grouped by family, genus or even common name (e.g., skates and rays, Dasyatidae, Rhinobatos, Sphyrnidae, Squatinidae). In this study, we used proportions between species from scientific observer fishing trips and Dirichlet regression modelling to reclassify these categories. This model is a multivariate extension of beta regression and enables the modeling of asymmetric and heteroscedastic compositional data, allowing multinomial data to be obtained in a more informative way. The reconstruction of catches for unclassified data showed a massive dominance of the Squatinidae family until the late 1970s, when catches showed signs of decline. At the same time, the rays of the “emplastro” family showed a progressive increase from 2006 onwards. However, this scenario changed after the reclassification. The category Squatinidae was maintained almost exclusively by S. guggenheim, while 16 categories of species were observed within “emplastro” rays, many of which fall into “endangered”, “vulnerable” and “critically endangered” criteria. These reconstructed series provide a more reliable scenario of the catches of thirty elasmobranch species in the southeast and south of Brazil and serve as baseline information for understanding the conservation status of these species.

The rate of six-month-old infants exclusively breastfed in Spain remains below the recommended rate. This study aimed to explore in detail the evolution of feeding during the first six months of life of a group of newborns, as well as to identify the reasons reported by the mothers for feeding change. A secondary analysis of two prospective longitudinal observational studies was conducted. In both studies, women participants, during the clinical puerperium, opted for exclusive breastfeeding for their newborns. The participants were followed up during the infants’ first six months. A sample size of 314 participants was obtained, of which 77.1% (n = 232) were of Spanish origin, and 51% (n = 160) were primiparous. The prevalence of exclusive breastfeeding at six months was 55.4% (n = 174). During the first four months of life, the main reason for early abandonment of breastfeeding was the perception of insufficient milk production. After the fourth month, the predominant reason was starting work. Statistically significant differences were observed between the reasons for giving up and the total weeks of exclusive breastfeeding (p < 0.001) and total weeks of breastfeeding (p = 0.002). Early weaning from breastfeeding is a multifactorial phenomenon. However, depending on the moment cessation occurs, some reasons predominate over others and, in many cases, can be prevented. These results indicate the need to continue investing efforts to promote and protect breastfeeding in Spain.

In this study, the environmental impacts associated with the intensive production of Persian lemons are assessed, including the agricultural and packing phases of the fresh fruit. A life-cycle assessment (LCA) tool was used in accordance with the ISO 14040 and 14044 standards and implemented in SimaPro PhD (9.2) software. The life-cycle inventory database was primarily composed of data collected during field visits to local lemon orchards and the main packing company in the region. The functional unit was defined as 1 kg of packed fresh Persian lemons. The selected impact categories were the carbon footprint, water footprint, and energy footprint, and the results obtained for the defined functional unit were 405.8 g CO2 eq, 40.3 L of water, and 5.9 MJ, respectively. The industrial packing phase of the fruits had a greater impact on the carbon and energy footprints, mostly due to the manufacturing of packaging materials and cardboard boxes, followed by the transportation of supplies. Regarding the water footprint, the agricultural phase was identified as the most significant contributor to water consumption, primarily attributed to maintenance operations and the application of agrochemicals.

SARS-CoV-2 is an obligatory intracellular pathogen that requires a lipid bilayer membrane for its transport to build its nucleocapsid envelope and fuse with the host cell. The biological membranes are constituted by phospholipids (PLs), and vitamin E (Vit E) protects them from oxidative stress (OS). The aim of this study was to demonstrate if treatment with Vit E restores the modified profile of the FA in PLs in serum from patients with coronavirus disease-19 (COVID-19). We evaluated Vit E, total fatty acids (TFAs), fatty acids of the phospholipids (FAPLs), total phospholipids (TPLs), 8-isoprostane, thromboxane B2 (TXB2), prostaglandins (PGE2 and 6-keto-PGF1α), interleukin-6 (IL-6), and C-reactive protein (CRP) in serum from 22 COVID-19 patients before and after treatment with Vit E and compared the values with those from 23 healthy subjects (HSs). COVID-19 patients showed a decrease in Vit E, TPLs, FAPLs, and TFAs in serum in comparison to HSs (p ≤ 0.01), and Vit E treatment restored their levels (p ≤ 0.04). Likewise, there was an increase in IL-6 and CRP in COVID-19 patients in comparison with HSs (p ≤ 0.001), and treatment with Vit E decreased their levels (p ≤ 0.001). Treatment with Vit E as monotherapy can contribute to restoring the modified FA profile of the PLs in the SARS-CoV-2 infection, and this leads to a decrease in lipid peroxidation, OS, and the inflammatory process.

Lipoatrophia semicircularis is a benign pathology characterized by subcutaneous tissue atrophy that affects the skin and related structures. Its etiology remains unclear; however, in the recent few years, it has been proposed that electrostatic charges could be a potential factor. Based on this hypothesis, the aim of this work is to study the cause–effect relation between electrostatic energy and LS, providing insights into the molecular mechanisms. For this purpose, an experimental murine model was created using obese mice. One group served as a control and the other groups involved charging clothes with varying connections to the ground: through the skin, through the clothes or not connected to the ground). Skin biopsies showed that the most significant lesions, including lipophagic granulomas with inflammatory infiltrate, were found in the first group (connected to the ground through the skin). Lipophagic reactions without an inflammatory infiltrate were observed in the other groups subjected to electrical discharges. In the control mice, no histological changes were observed. Oxidative processes were also measured in lower limbs tissue. Malondialdehyde levels significantly increased in the lower limbs after electrostatic discharges. However, the presence of ground through a wire attached to highly conductive clothes around the thigh significantly reduced the effect of electrostatic charges on lipid peroxidation. To our knowledge, this is the first study in which an experimental model has been used to reproduce LS induced by electrostatic energy, suggesting a cause–effect relationship between electrostatic charge and discharge with fat tissue lesion.

Background: Complete dentures should withstand occlusal forces and wear. However, over time, dentures can suffer fatigue and develop cracks, chipping, and fractures. Conventional methods for the fabrication of complete dentures involve injection molding, thermal curing, and the use of microwaves with polymethyl methacrylate (PMMA)-based materials. These methods have served well for many years. More recently, the incorporation of computer-aided design and computer-aided manufacturing (CAD/CAM) to fabricate complete dentures has been shown to enhance the dentures’ mechanical properties, including resistance to wear and impact strength. This study aims to investigate the mechanical properties and fracture types of CAD/CAM denture base materials (both milled and printed) as compared to a novel proprietary method that embeds a 3D-printed framework within PMMA-milled blocks. The null hypothesis is that incorporating a 3D-printed framework does not affect the mechanical properties of milled PMMA blocks. Methods: Three groups of bars were fabricated using CAD/CAM methods: printed (P), milled (M), and milled with a 3D-printed metallic framework reinforcement (M + F). A three-point bending test evaluated deformation, followed by an impact fracture test for fracture toughness. A descriptive fractographic analysis assessed the fracture characteristics. A statistical analysis using a paired t-test compared the differences between the groups. Results: The P group showed more elastic deformation than the M and M + F groups (p < 0.05). The M + F group achieved a higher fracture toughness as compared to the M and P groups (p < 0.05). Conclusions: Within the limitations of this experimental study, the null hypothesis can be rejected. Milled samples with an embedded 3D-printed titanium framework possess higher resistance to impact than milled samples without frameworks, and printed samples and milled samples with embedded 3d-printed titanium frameworks present increased flexural strength and lower elastic deformation as compared to milled samples without frameworks and printed samples.

Objectives: The purpose of this study was to evaluate and compare the noise levels in current incubator models and a prototype designed to improve acoustic comfort in neonatal incubators. Methods: Tests were carried out on three different models of incubators and a prototype called Neonatal Incubator Acoustic Comfort Class (NICA). The tests measured both internal and external sound pressure levels under laboratory conditions. The noise index has been taken as the A-weighted equivalent continuous sound pressure level (LAeq,T) for a time interval of 1 min. Results: The results obtained show variations between the different models of incubators, although, overall, they are high values (around 56/60 dBA). The results prove that premature newborns under normal conditions of using these incubators are exposed to noise levels above international recommendations. The new incubator design minimizes noise generation and generates noise levels lower than international recommendations. Conclusions: The results obtained from the prototype (NICA+) show the effectiveness of the proposed design in improving acoustic comfort in neonatal incubators. The data show that the noise levels generated by the prototype under normal operating conditions are significantly lower than international recommendations.

Agricultural tractors are an essential agricultural power source. Therefore, the scientific literature tests have described agricultural tractors’ evolution over time and determined future trends. This paper uses bibliometric tools to assess the agricultural evolution of tractor testing from 1969 to 2022 to ascertain the publication’s scientific perspective on operational, ergonomic, and energy performance. We searched for relevant research in the Scopus and Web of Science (WOS) databases. The data were processed in RStudio software version 4.4.1, and we used elaborated bibliometric maps to research evolution, major journals, studies, countries, and keywords. The first research mainly concerned the development of new wheelsets, more efficient engines, and fuel consumption prediction models. After the 2000s, environmental protocols contributed to increasing publications on biofuels and renewable energies. Recently, an intense process of robotization in autonomous vehicles has improved to allow the replacement of combustion engines. Ergonomics and safety have been less recurrent topics in recent years, indicating a stable level in the actual research. New machine control models involving artificial intelligence are currently applied to obtain test results without using the machine in the field. These virtual models reduce costs and optimize resources. The most common terms were “tractor” and “agricultural machinery”. The terms “Electric tractor”, “agricultural robots”, and “Matlab” indicate solid trends for future research.

Coffee production has become increasingly technified in order to optimize the use of inputs and the sustainable use of natural resources. In this context, one way that farmers are investing in their coffee plantations is in the use of precision agriculture techniques, termed precision coffee farming. Over the last few years, research has been conducted to facilitate the application of this technology, and sampling grids with two points per hectare have been recommended by several studies. These georeferenced demarcations in a plot are generally shaped as equidistant squares or rectangles, and the sampling points are located at the centers of these areas. Coffee farmers typically plant their crops following the level line, which greatly hinders the navigation of equidistant points within the field. Thus, the objective of this study was to develop an optimized walking route method to reduce the distance for sampling soil, leaf, and yield attributes. The experimental plots were established in 2000 at Samambaia Farm, located in Santo Antônio do Amparo, Minas Gerais, Brazil, with coffee the cultivar Acaia IAC 479-19, totaling 56.65 ha. The 111 sampling points were distributed in the land following the new method proposed in this study, and, after walking simulations using Farm Works Mapping Software, the new method was compared with the conventional method using the mean displacement between points. The new optimized walking routes method reduced the mean distance traveled to sample the points by 50.1%.

Sulfated polysaccharides (SPs), especially those with immunostimulant effects on shrimp and fish, are bioactive compounds with potential use in aquaculture. In this study, Pacific white shrimp (Penaeus vannamei) were fed diets containing 0%, 0.5%, 1.0%, 1.5%, or 2.0% crude extracts from the microalga Porphyridium cruentum for 30 days. After dietary supplementation, the shrimp were exposed to Vibrio alginolyticus, allowing the assessment of phenoloxidase activity (PO) and total hemocyte count (THC) pre- and post-challenge, as well as shrimp survival rates. Shrimp that received the 1.0% treatment had greater survival (90%) at 48 h post-challenge, while the 0% and 2.0% treatments had survival rates close to 63% in the same period. Furthermore, at 48 h post-challenge, THC was significantly greater (p < 0.05) in the shrimp that received crude extract supplementation compared to that in shrimp of the control group (0%). PO showed a proportional increase according to crude extract inclusion levels. Such dose-dependency in response to PO increases became significantly greater (p < 0.05) in the 2.0% treatment group compared to that in the 0% treatment group in the pre-challenge period and that in the 0% and 0.5% treatment groups in the post-challenge period. These results showed that crude extracts from P. cruentum could be considered immunostimulants by increasing the resistance of P. vannamei exposed to V. alginolyticus, potentially representing a major breakthrough for marine shrimp farming.