Path planning is one of the most essential parts of autonomous navigation. Most existing works are based on the strategy of adjusting angles for planning. However, drones are susceptible to collisions in environments with densely distributed and high-speed obstacles, which poses a serious threat to flight safety. To handle this challenge, we propose a new method based on Multiple Strategies for Avoiding Obstacles with High Speed and High Density (MSAO2H). Firstly, we propose to extend the obstacle avoidance decisions of drones into angle adjustment, speed adjustment, and obstacle clearance. Hybrid action space is adopted to model each decision. Secondly, the state space of the obstacle environment is constructed to provide effective features for learning decision parameters. The instant reward and the ultimate reward are designed to balance the learning efficiency of decision parameters and the ability to explore optimal solutions. Finally, we innovatively introduced the interferometric fluid dynamics system into the parameterized deep Q-network to guide the learning of angle parameters. Compared with other algorithms, the proposed model has high success rates and generates high-quality planned paths. It can meet the requirements for autonomously planning high-quality paths in densely dynamic obstacle environments. Full article

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously, there has been an increased use of uncrewed aerial systems (UASs) in remote sensing, as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UASs and the attention on agroecosystems, there is an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UASs to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and assembled accuracy assessments for each classification. The average overall accuracy (53.9%), though relatively low, was expected for such a diverse landscape with fine-resolution data. To bolster our understanding of the classifications, we interviewed farmers to understand their thoughts on how these maps may be best used to support their land management. After sharing imagery and land cover classifications with farmers, we found that while the prints were often a point of pride or curiosity for farmers, integrating the maps into farm management was perceived as impractical. These findings highlight that while researchers and government agencies can increasingly apply remote sensing to estimate land cover classes and ecosystem services in diverse agroecosystems, further work is needed to make these products relevant to diversified smallholder farmers. Full article

To explore the radial variation in wood properties of slash pine (Pinus elliottii Engelm.) during its growth process and to achieve the early prediction of these properties, our study was carried out in three slash pine harvest-age plantations in Ganzhou, Jian, and Jingdezhen, Jiangxi province of South China. Wood core samples were collected from 360 sample trees from the three plantations. SilviScan technology was utilized to acquire wood property parameters, such as tangential fiber widths (TFWs), radial fiber widths (RFWs), fiber wall thickness (FWT), fiber coarseness (FC), microfibril angle (MFA), modulus of elasticity (MOE), wood density (WD) and ring width (RD). Subsequent systematic analysis focused on the phenotypic and radial variation patterns of wood properties, aiming to establish a clear boundary between juvenile and mature wood. Based on determining the boundary between juvenile and mature wood, a regression equation was used to establish the relationship between the properties of juvenile wood and the ring ages. This relationship was then extended to the mature wood section to predict the properties of mature wood. Our results indicated significant differences in wood properties across different locations. The coefficients of variation for RD and MOE were higher than other properties, suggesting a significant potential for selective breeding. Distinct radial variation patterns in wood properties from the pith to the bark were observed. The boundary between juvenile and mature wood was reached at the age of 22. The prediction models developed for each wood property showed high accuracy, with determination coefficients exceeding 0.87. Additionally, the relative and standard errors between the measured and predicted values were kept below 10.15%, indicating robust predictability. Mature wood exhibited greater strength compared to juvenile wood. The approach of using juvenile wood properties to predict those of mature wood is validated. This method provides a feasible avenue for the early prediction of wood properties in slash pine. Full article

Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces a novel WL measurement method that combines Task Demand Load (TDL) and Subject Load Capacity (SLC) to quantitatively assess operator workload. This method was validated through experiments with 45 subjects using the Environmental Control and Atmospheric Regeneration (ECAR) system. The statistical results showed that as the designed WL levels increased, the Average Workload (AWL), the NASA-TLX score, and the work time percentage increased significantly, while the task accuracy and the fixation duration decreased significantly. These results also revealed the impact of WL levels on human responses (such as subjective feeling, work performance, and eye movement). In addition, very strong correlations were found between AWL measurements and NASA-TLX scores (r = 0.75, p < 0.01), task accuracy (r = −0.73, p < 0.01), and work time percentage (r = 0.97, p < 0.01). Overall, these results proved the effectiveness of the proposed method for measuring WL. On this basis, this study defined WL thresholds by integrating task accuracy with AWL calculations, providing a framework for the dynamic management of task allocation between humans and machines to maintain operators within optimal WL ranges. Full article

This systematic review and meta-analysis examined the impact of evidence-based practice (EBP) education programs on undergraduate nursing students, focusing on enhancing EBP competency, critical thinking, and problem-solving ability. Methods: The search, conducted through PubMed, Cochrane Library, EMBASE, CINAHL, and Web of Science up to December 2023, included studies published in English and Korean and adhered to PRISMA guidelines. Qualitative appraisal of the studies was conducted using the revised ROB II for randomized trials and the ROBINS-I for non-randomized trials. For the meta-analysis, the effect size of the intervention was calculated as a standardized mean difference. Results: In our study, 11 studies met our inclusion criteria, and 8 studies of those were included in the meta-analysis. The effect sizes for EBP competency, critical thinking, and problem-solving ability were 1.55, 1.29, and 0.65, respectively. The meta-regression analysis indicated that tailored education programs of 4–7 weeks and being in the 4th grade significantly enhanced EBP competency. Conclusion: These findings support the development of a customizable and applied EBP education actively for students, preparing nursing students to effectively implement EBP in clinical settings after graduation. Despite the significant effect size of the outcome variables, the high heterogeneity suggests the need for further investigation to validate the EBP educational outcomes for nursing students. Full article

We consider an operator ${\left\{S\left(t\right)\right\}}_{t\ge 0}$ on a Banach space X with generator A, characterized by being an $\alpha$-times-integrated C-regularized semigroup. The adjoint family $S^{*}\left(t\right):X^{*}\to X^{*}$ is introduced for analysis. ${\left\{S^{*}\left(t\right)\right\}}_{t\ge 0}$ maintains the characteristics of an $\alpha$-times-integrated C-regularized semigroup, though with strong continuity and Bochner integrals being substituted by weak${}^{*}$ continuity and weak${}^{*}$ integrals, respectively. Our investigation focuses on the closed subspace $X^{\odot }$, where ${\left\{S^{*}\left(t\right)\right\}}_{t\ge 0}$ exhibits strong continuity. Additionally, a comparison between the adjoint $A^{*}$ of A and the generator of the adjoint family is conducted. Full article

A subsurface investigation was conducted to assess the suitability of a site for potential tunnel construction, focusing on the determination of shear wave velocities (Vs) in subsurface materials. This study employed three distinct methods to analyze Vs in weathered soft rock: drilling mechanism, multichannel analysis of surface waves (MASW), and microtremor array measurement (MAM). Through the utilization of MASW and MAM, empirical relationships were established, enabling the determination of Vs based solely on soil type and depth, offering a practical alternative to the limitations of SPT N-Value, particularly when exceeding 50 blows. The comparison of Vs values obtained from these methods revealed a close alignment between empirical techniques and MASW/MAM, which proved to be cost-effective and an efficient alternative to drilling for comprehensive underground structure assessments. The reliability of MASW was further underscored through its comparison with existing empirical methods. Moreover, the empirical approach demonstrated its efficacy in predicting velocities in weathered soft rock within the Central Himalayan region of Nepal, thus enhancing the feasibility study of underground structures. Lastly, this study proposed a Vs-Depth correlation specifically tailored for highly weathered meta-sandstone bedrock resulting in clay and sandy soils. Full article

Novel psychoactive substances (NPSs) are compounds plotted to modify the chemical structures of prohibited substances, offering alternatives for consumption and evading legislation. The prompt emergence of these substances presents challenges in health concerns and forensic assessment because of the lack of analytical standards. A viable alternative for establishing these standards involves leveraging in silico methods to acquire spectroscopic data. This study assesses the efficacy of utilizing infrared spectroscopy (IRS) data derived from density functional theory (DFT) for analyzing NPSs. Various functionals were employed to generate infrared spectra for five distinct NPS categories including the following: amphetamines, benzodiazepines, synthetic cannabinoids, cathinones, and fentanyls. PRISMA software was conceived to rationalize data management. Unsupervised learning techniques, including Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE), were utilized to refine the assessment process. Our findings reveal no significant disparities among the different functionals used to generate infrared spectra data. Additionally, the application of unsupervised learning demonstrated adequate segregation of NPSs within their respective groups. In conclusion, integrating theoretical data and dimension reduction techniques proves to be a powerful strategy for evaluating the spectroscopic characteristics of NPSs. This underscores the potential of this combined methodology as a diagnostic tool for distinguishing IR spectra across various NPS groups, facilitating the evaluation of newly unknown compounds. Full article

Background: In an era of dramatic technological progress, the consequent economic transformations, and an increasing need for an adaptable workforce, the importance of education has risen to the forefront of the social discourse. The concurrent increase in the awareness of issues pertaining to social justice and the debate over what this justice entails and how it ought to be effected, feed into the education policy more than ever before. From the nexus of the aforementioned considerations, concern about the so-called education gap has emerged, with worldwide efforts to close it. Methods: I analyze the premises behind such efforts and demonstrate that they are founded upon fundamentally flawed ideas. Results: I show that in a society in which education is delivered equitably, education gaps emerge naturally as a consequence of differentiation due to talents, the tendency for matched mate selection, and the heritability of intellectual traits. Conclusion: I issue a call for a redirection of efforts away from the ill-founded idea of closing the education gap to the understanding of the magnitude of its unfair contributions, as well as to those social aspects that can modulate it in accordance with what a society deems fair according to its values. Full article

Corynebacterium rouxii is one of the recently described species of the Corynebacterium diphtheriae complex. As this species can potentially infect different hosts and harbor the tox gene, producing diphtheria toxin, we present its first pangenomic analysis in this work. A total of fifteen genomes deposited in online databases were included. After confirming the taxonomic position of the isolates by genomic taxonomy, the genomes were submitted to genomic plasticity, gene synteny, and pangenome prediction analyses. In addition, virulence and antimicrobial resistance genes were investigated. Finally, epidemiological data were obtained through molecular typing, clustering, and phylogenetic analysis. Our data demonstrated genetic diversity within the species with low synteny. However, the gene content is extensively conserved, and the pangenome is composed of 2606 gene families, of which 1916 are in the core genome and 80 are related to unique genes. Prophages, insertion sequences, and genomic islands were found. A type I-E CRISPR-Cas system was also detected. Besides the tox gene, determinants involved in adhesion and iron acquisition and two putative antimicrobial resistance genes were predicted. These findings provide valuable insight about this species’ pathogenicity, evolution, and diversity. In the future, our data can contribute to different areas, including vaccinology and epidemiology. Full article

Endophytic fungus is crucial for maintaining plant health and defense mechanisms, acting as protective barriers against pathogens, and producing medicinally beneficial bioactive compounds. Genome sequencing and metagenomics have significantly enhanced the understanding of fungal diversity and metabolic capabilities, enabling the identification of new genes and substances. Traditional culture-dependent methods have been complemented by culture-independent techniques, offering a more comprehensive view of fungal diversity. Using both culture-dependent and culture-independent techniques, the present research investigation explored the diversity of endophytic fungi encountered in the foliage of Hardwickia binata. The study examined the topographical characteristics and nutritional content of soil samples collected from the locality of the selected plant sample, H. binata, to better comprehend the effects on the plant’s growth. The balanced nutrient constituted approximately a pH of 7.2, which suggested an alkaline nature and promoted plant development. The ratio of nitrogen, phosphorous, and potassium remained 3:1:1. A total of 25 fungal isolates, categorized into 17 morphotypes, were obtained using the culture-dependent approach; Curvularia and Nigrospora emerged as the most common genera. Furthermore, the prediction of the ITS2 secondary structure supports the identification of species, highlighting a wide variety of fungal species present in H. binata. The culture-independent approach generated 69,570 high-quality sequences, identifying 269 Operational Taxonomic Units (OTUs). The dominant Ascomycota phylum, along with various genera, indicated a rich fungal community associated with H. binata. This study advances the understanding of the endophytic fungus communities that are associated with H. binata and the nature of soil ecology. The findings emphasize the significance of holistic techniques in the study of microbial dynamics within plant systems as well as their implications for ecosystem management and plant health. Full article

Infective pleural effusions are mainly represented by parapneumonic effusions and empyema. These conditions are a spectrum of pleural diseases that are commonly encountered and carry significant mortality and morbidity rates reaching upwards of 50%. The causative etiology is usually an underlying bacterial pneumonia with the subsequent seeding of the infectious culprit and inflammatory agents to the pleural space leading to an inflammatory response and fibrin deposition. Radiographical evaluation through a CT scan or ultrasound yields high specificity and sensitivity, with features such as septations or pleural thickening indicating worse outcomes. Although microbiological yields from pleural studies are around 56% only, fluid analysis assists in both diagnosis and prognosis by evaluating pH, glucose, and other biomarkers such as lactate dehydrogenase. Management centers around antibiotic therapy for 2–6 weeks and the drainage of the infected pleural space when the effusion is complicated through tube thoracostomies or surgical intervention. Intrapleural enzymatic therapy, used to increase drainage, significantly decreases treatment failure rates, length of hospital stay, and surgical referrals but carries a risk of pleural hemorrhage. This comprehensive review article aims to define and delineate the progression of parapneumonic effusions and empyema as well as discuss pathophysiology, diagnostic, and treatment modalities with aims of broadening the generalist’s understanding of such complex disease by reviewing the most recent and relevant high-quality evidence. Full article

Introduction: Necrotizing fasciitis (NF) is a critical disease with high morbidity and mortality rates that poses significant challenges in diagnosis and treatment. Prognostic factors for the clinical course of NF remain unclear and are currently under research. This study aims to identify such factors in a large cohort of patients which represents a major comprehensive investigation of prognostic factors for NF. Methods: Retrospective analysis was conducted on necrotizing fasciitis cases from 2003 to 2023 at two German hospitals. Data included demographics, comorbidities, laboratory findings, infection site, causative microorganisms and outcomes. Statistical analysis involved t-tests, chi-square tests, and ROC analysis. Results: A total of 209 patients were included, with a mortality rate of 18%. Patients were categorized into survivors (n = 171) and non-survivors (n = 38). Non-survivors were significantly older (68.9 ± 13.9 years vs. 55.9 ± 14.3 years; p < 0.01) and exhibited a higher prevalence of peripheral vascular diseases, cancer, and heart, liver, or renal insufficiency. Laboratory findings and scoring results also varied significantly between the two groups. The ROC curve analysis identified age as a predictor of mortality, with an optimal cut-off value of 68.5 years (sensitivity: 60.5%, specificity: 81.9%). Higher age was associated with increased mortality risk. Conclusions: The patient’s age stands out as the primary predictive element for mortality in necrotizing fasciitis. Additionally, we advocate for employing the Laboratory and Anamnestic Risk Indicator for Necrotizing Fasciitis (LARINF—score), which holds substantial prognostic significance and is straightforward to calculate. Considering our findings, crafting a clinical algorithm or scoring mechanism to forecast mortality in NF would be a promising target for future research. Full article

Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). The current solutions for its management, such as oral rehydration salts (ORS), inhibitors of gut motility, antibiotics, and living probiotics, only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. The potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22^® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signalling assays, the gut barrier formation assay, and the rotavirus gene expression assay were performed. ABB C22^® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22^® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments. Full article

This study presents an innovative lateral flow microfluidic paper-based analytical device (μPAD) designed for conducting quantitative paper-based enzyme-linked immunosorbent assays (p-ELISA), seamlessly executing conventional ELISA steps in a paper-based format. The p-ELISA device utilizes a passive fluidic circuit with functional elements such as a multi-bi-material cantilever (B-MaC) assembly, delay channels, and a buffer zone, all enclosed within housing for autonomous, sequential loading of critical reagents onto the detection zone. This novel approach not only demonstrates a rapid assay completion time of under 30 min, but also boasts reduced reagent requirements, minimal equipment needs, and broad applicability across clinical diagnostics and environmental surveillance. Through detailed descriptions of the design, materials, and fabrication methods for the multi-directional flow assay (MDFA), this manuscript highlights the device’s potential for complex biochemical analyses in a user-friendly and versatile format. Analytical performance evaluation, including a limit of detection (LOD) of 8.4 pM for Rabbit IgG, benchmarks the device’s efficacy compared to existing p-ELISA methodologies. This pioneering work lays the groundwork for future advancements in autonomous diagnostics, aiming to enhance global health outcomes through accessible and reliable testing solutions. Full article

The purpose of this mixed-method study was to (1) examine the effect of an adapted physical activity program, Fitness Access McGill (FAM), on leisure-time physical activity (LTPA), autonomous and controlled motivation, and the basic psychological needs of self-determination theory among university students/staff with a physical disability and/or chronic conditions, and (2) explore participants’ experiences after completing FAM. Nineteen participants completed validated questionnaires for all study outcomes pre- and post-FAM. Nine participants partook in a 30–60 min semi-structured interview conducted within three months of completing FAM. Quantitative data were analyzed using repeated measures effect size calculations. Qualitative data were analyzed using directed content analysis. Participants reported an increase in total LTPA (dRMpooled = 0.58), with the greatest positive change on strenuous intensity (dRMpooled = 0.81). Large effects were found for changes in autonomous motivation (dRMpooled = 0.52), autonomy (dRMpooled = 0.79), competence (dRMpooled = 0.79), and relatedness (dRMpooled = 0.89). Participants reported FAM being supportive towards their psychological needs, the development of a LTPA routine, and enhanced overall well-being. Future research can be built upon this study to develop a robust understanding as to how need-supportive, adapted LTPA programs could be implemented within community settings or out-patient rehabilitation to support exercise engagement, physical health and overall well-being among adults with disabilities. Full article

The hepatobiliary system is vital for the biotransformation and disposition of endogenous molecules. Any impairment in the normal functioning of the hepatobiliary system leads to a spectrum of hepatobiliary diseases (HBDs), such as liver cirrhosis, fatty liver, biliary dyskinesia, gallbladder cancer, etc. Especially in pregnancy, HBD may result in increased maternal and fetal morbidity and mortality. Maternal HBD is a burden to the fetus’s growth, complicates fetal development, and risks the mother’s life. In fetal programming, the maternal mechanism is significantly disturbed by multiple factors (especially diet) that influence the development of the fetus and increase the frequency of metabolic diseases later in life. Additionally, maternal under-nutrition or over-nutrition (especially in high-fat, high-carbohydrate, or protein-rich diets) lead to dysregulation in gut hormones (CCK, GLP-1, etc.), microbiota metabolite production (SCFA, LPS, TMA, etc.), neurotransmitters (POMC, NPY, etc.), and hepatobiliary signaling (insulin resistance, TNF-a, SREBPs, etc.), which significantly impact fetal programming. Recently, biotherapeutics have provided a new horizon for treating HBD during fetal programming to save the lives of the mother and fetus. This review focuses on how maternal impaired hepatobiliary metabolic signaling leads to disease transmission to the fetus mediated through the gut–brain axis. Full article

(1) Background: Although Physaloptera retusa is one of the most widespread species infecting reptiles in the Americas, numerous taxonomic problems and little genetic data are associated with it. To clarify the taxonomy of this species, we used an integrative approach. (2) Methods: Physaloptera retusa-infecting Erythrolamprus typhlus (snake) from the Pantanal wetlands, Brazil, was morphologically and genetically characterised (18S and 28S rDNA; COI mtDNA) and compared with conspecific sequences available in GenBank, from parasites of Tupinambis teguixin (lizard), using species delimitation methods. Type specimens of P. liophis were re-evaluated given its morphological similarities with P. retusa. (3) Results: The morphology of the present specimens was equal to that of P. retusa, in which the only difference from P. liophis was the relative position of the vulva. Species delimitation methods were more accurate for the COI dataset; all of them (except ABGD) indicated interspecificity among P. retusa sequences. However, a lack of morphological data or voucher material, associated with the deposited sequences, prevented more assertive conclusions. (4) Conclusions: The present results highlight the importance of a clear association between genetic data and morphology of the isolation source, or at least its adequate vouchering. Moreover, P. retusa may represent a species complex in cryptic speciation, since it is widespread and has low hosts specificity. Full article

In the process of collecting evidence of activities and events in network devices, there are problems with content and storage, and we aim to solve the problems faced by network devices in network forensics. In this paper, we propose a simple method for solving the problems with content and storage in acquiring communication logs on end hosts, implement a sniffing tool that captures raw packets with communication event control, compare it with existing tools, and conduct experiments and considerations. Through these experiments and considerations, we confirmed that the proposed communication log acquisition method can be implemented on the end host, and that the problem can be solved by using a tool that implements the proposed method. Also, we confirmed that it can be applied to real-world communication log collection scenarios, and that it can coexist with existing systems and tools that collect communication logs. Full article

(1) Background: MGMT (O-6-methylguanine-DNA methyltransferase) promoter methylation remains an important predictive biomarker in high-grade gliomas (HGGs). The influence of necrosis on the fidelity of MGMT promoter (MGMTp) hypermethylation testing is currently unknown. Therefore, our study aims to evaluate the effect of varying degrees of necrosis on MGMTp status, as determined by pyrosequencing, in a series of primary and recurrent HGGs; (2) Methods: Within each case, the most viable blocks (assigned as ‘true’ MGMTp status) and the most necrotic block were determined by histopathology review. MGMTp status was determined by pyrosequencing. Comparisons of MGMTp status were made between the most viable and most necrotic blocks. (3) Results: 163 samples from 64 patients with HGGs were analyzed. MGMTp status was maintained in 84.6% of primary and 78.3% of recurrent HGGs between the most viable and necrotic blocks. A threshold of ≥60% tumor cellularity was established at which MGMTp status was unaltered, irrespective of the degree of necrosis. (4) Conclusions: MGMTp methylation status, as determined by pyrosequencing, does not appear to be influenced by necrosis in the majority of cases at a cellularity of at least 60%. Further investigation into the role of intratumoral heterogeneity on MGMTp status will increase our understanding of this predictive marker. Full article

Background: Rare diseases, predominantly caused by genetic factors and often presenting neurological manifestations, are significantly underrepresented in research. This review addresses the urgent need for advanced research in rare neurological diseases (RNDs), which suffer from a data scarcity and diagnostic challenges. Bridging the gap in RND research is the integration of machine learning (ML) and omics technologies, offering potential insights into the genetic and molecular complexities of these conditions. Methods: We employed a structured search strategy, using a combination of machine learning and omics-related keywords, alongside the names and synonyms of 1840 RNDs as identified by Orphanet. Our inclusion criteria were limited to English language articles that utilized specific ML algorithms in the analysis of omics data related to RNDs. We excluded reviews and animal studies, focusing solely on studies with the clear application of ML in omics data to ensure the relevance and specificity of our research corpus. Results: The structured search revealed the growing use of machine learning algorithms for the discovery of biomarkers and diagnosis of rare neurological diseases (RNDs), with a primary focus on genomics and radiomics because genetic factors and imaging techniques play a crucial role in determining the severity of these diseases. With AI, we can improve diagnosis and mutation detection and develop personalized treatment plans. There are, however, several challenges, including small sample sizes, data heterogeneity, model interpretability, and the need for external validation studies. Conclusions: The sparse knowledge of valid biomarkers, disease pathogenesis, and treatments for rare diseases presents a significant challenge for RND research. The integration of omics and machine learning technologies, coupled with collaboration among stakeholders, is essential to develop personalized treatment plans and improve patient outcomes in this critical medical domain. Full article

The surveillance and treatment of parasites are important features of preventative healthcare plans in zoological institutes. The parasite control strategies employed in temperate regions often involve prophylactic anthelmintic treatments during seasons where the burden of gastrointestinal parasites in fecal testing is high. These strategies are, however, not applicable in the tropics, where temperatures remain high throughout the year, allowing continuous parasitic development. A risk-based parasite management strategy was adopted by a tropical zoological institute. For parasite surveillance, routine fecal direct smears and magnesium sulfate flotations were performed to determine parasitic prevalence. The frequency of fecal checks for the year was determined by the frequency at which clinically relevant parasitism (fecal tests that resulted in the animal being treated) was detected during routine fecal checks in the previous year. A yearly anthelmintic drug-class rotation schedule was also implemented. The total number of fecal tests performed per year and the number of animals with clinically significant parasitic disease decreased by 30.0% (637/2126) and 46.9% (207/451), respectively, over the four-year period of the study. Anthelmintic class rotation also improved the efficacy of fenbendazole in treating Strongyloides spp. infecting the group of orangutans. This parasite control strategy is a targeted approach to managing preventative healthcare, reducing the work required to perform routine surveillance tests whilst maintaining the health of the collection of animals. Full article