Search Results (5,144)

Displaying representations or actual individuals of the same or similar species can have a congregating or deterring effect on animals. An effigy, an animal or animal representation in a moribund state, is a tool aimed at deterring target animals in wildlife management settings. Despite being used as a deterrent for decades, neither a synthesis of effigies nor an exploration of the behavioral drivers tied to effigy effectiveness has occurred. We reviewed the effigy literature in terms of both efficacy as a deterrent and behavioral driver(s). We examined research on effigies encompassing 13 social avian species. Nine of seventeen (53%) investigations included experimentation and statistical validation, and of those, six of nine (66%) found effigies to be effective at deterring the focal species, though the temporal scale and spatial extents of the investigations were highly variable. We argue that central to an effigy’s effectiveness is the elicitation of fear in the target animal(s) and propose and discuss several potential drivers of fear derived from an effigy, namely antipredator behavior, neophobia, and disgust. Only a single study discussed behavioral drivers of effigy response. We conclude that effigies show promise as a wildlife deterrent for social avian species and have potential for uninvestigated species, and greater efforts should be made to incorporate robust study designs capable of strong inference and elucidation of behavioral drivers of an animal’s response to an effigy. Full article

Background/Objective: Sacubitril/Valsartan are a combination drug approved for heart failure treatment, known to enhance natriuretic peptide activity and inhibit the renin–angiotensin–aldosterone system (RAAS). While its clinical efficacy is well-established, its broader impact on human metabolism remains insufficiently characterized. This study aimed to explore the time-resolved metabolic changes induced by Sacubitril/Valsartan in healthy individuals using an untargeted metabolomics approach. Methods: Fourteen healthy male volunteers received a single oral dose of Sacubitril/Valsartan (200 mg; 97.2 mg Sacubitril and 102.8 mg Valsartan) across two phases separated by a two-week washout period. Plasma samples were collected at eight individualized time points based on pharmacokinetic profiles. Metabolites were extracted and analyzed using high-resolution liquid chromatography–mass spectrometry (LC-QToF HRMS). Data processing included peak alignment, annotation via HMDB and METLIN, and statistical modeling through multivariate (PLS-DA, OPLS-DA) and univariate (ANOVA with FDR correction) analyses. Results: Out of 20,472 detected features, 13,840 were retained after quality filtering. A total of 315 metabolites were significantly dysregulated (FDR p < 0.05), of which 31 were confidently annotated as endogenous human metabolites. Among these, key changes were observed in the pyrimidine metabolism pathway, particularly elevated levels of uridine triphosphate (UTP) associated with cellular proliferation and metabolic remodeling. OPLS-DA models demonstrated clear separation between pre-dose and Cmax samples (R²Y = 0.993, Q² = 0.768), supporting the robustness of the time-dependent effects. Conclusions: This is the first study to characterize the dynamic metabolomic signature of Sacubitril/Valsartan in healthy humans. The findings reveal a distinctive perturbation in pyrimidine metabolism, suggesting possible links to drug mechanisms relevant to cardiac cell cycle regulation. These results underscore the utility of untargeted pharmacometabolomics in uncovering systemic drug effects and highlight potential biomarkers for monitoring therapeutic response or guiding precision treatment strategies in heart failure. Full article

Age-related physiological and cognitive changes significantly affect older adults’ participation in day-to-day functioning. This interview study aimed to uncover and illuminate the intricate dynamics between individuals’ responses to aging restrictions and day-to-day functioning, and how they relate to successful aging. We used a qualitative research design to explore the various responses to aging decline and their implications for daily functioning among older adults. Eighteen in-depth interviews were conducted with older adults, focusing on their occupational characteristics, needs, and responses to aging constraints. The transcripts were analyzed using principles of constructivist grounded theory. Three main categories were identified regarding older adults’ responses to the decline in abilities that come with age: (a) acceptance, reflecting the individual’s ability to adapt to the age-related changes and constraints; (b) personal resources, including a positive mindset and self-efficacy; and (c) coping strategies, including meaningful roles and occupational adaptation. This study’s findings indicate three types of responses to aging restrictions that may contribute to greater engagement in daily life and, consequently, be a key to successful aging. Developing individually tailored interventions that focus on occupational adaptations according to individual needs and preferences is vital in helping older adults maintain their daily functioning and quality of life. Full article

The evolving paradigm of precision medicine is redefining the landscape of orthobiologic therapies by moving beyond traditional diagnosis-driven approaches toward biologically tailored interventions. This review synthesizes current evidence supporting precision orthobiologics, emphasizing the significance of individualized treatment strategies in musculoskeletal regenerative medicine. This narrative review synthesized literature from PubMed, Embase, and Web of Science databases (January 2015–December 2024) using search terms, including ‘precision medicine,’ ‘orthobiologics,’ ‘regenerative medicine,’ ‘biomarkers,’ and ‘artificial intelligence’. Biological heterogeneity among patients with ostensibly similar clinical diagnoses—reflected in diverse inflammatory states, genetic backgrounds, and tissue degeneration patterns—necessitates patient stratification informed by molecular, genetic, and multi-omics biomarkers. These biomarkers not only enhance diagnostic accuracy but also improve prognostication and monitoring of therapeutic responses. Advanced imaging modalities such as T2 mapping, DTI, DCE-MRI, and molecular PET offer non-invasive quantification of tissue health and regenerative dynamics, further refining patient selection and treatment evaluation. Simultaneously, bioengineered delivery systems, including hydrogels, nanoparticles, and scaffolds, enable precise and sustained release of orthobiologic agents, optimizing therapeutic efficacy. Artificial intelligence and machine learning approaches are increasingly employed to integrate high-dimensional clinical, imaging, and omics datasets, facilitating predictive modeling and personalized treatment planning. Despite these advances, significant challenges persist—ranging from assay variability and lack of standardization to regulatory and economic barriers. Future progress requires large-scale multicenter validation studies, harmonization of protocols, and cross-disciplinary collaboration. By addressing these limitations, precision orthobiologics has the potential to deliver safer, more effective, and individualized care. This shift from generalized to patient-specific interventions holds promise for improving outcomes in degenerative and traumatic musculoskeletal disorders through a truly integrative, data-informed therapeutic framework. Full article

Orthodontic tooth movement (OTM) is accompanied by sterile inflammation, a necessary biological process that facilitates tooth displacement but also contributes to adverse effects, including hyalinization and orthodontically induced external apical root resorption (OEARR). Despite advancements in orthodontic therapies, the inflammatory response—regulated by dynamic interactions between tissue-specific cells and their molecular mediators—remains a critical factor influencing treatment outcomes. This review summarizes the current understanding of the cellular and molecular mechanisms underlying OTM, with a focus on how these insights can support the development of targeted therapeutic strategies. These include cell- and molecule-based therapies, biomaterial-mediated delivery systems, and applications of artificial intelligence (AI). Notably, AI offers promising opportunities for modeling and simulating biological responses, enabling the optimization of individualized treatment planning. We further discuss current clinical practices and highlight emerging experimental findings, with an emphasis on unresolved research questions pivotal to improving therapeutic efficacy and reducing complications such as OEARR. This comprehensive overview aims to inform future directions in orthodontics by integrating mechanistic knowledge with technological innovation. Full article

Metastatic cancer, characterized by poor survival outcomes and grim prognosis, represents the final stage of malignancy. The current evidence regarding the prophylactic effects of glucagon-like peptide-1 (GLP-1) receptor agonists and sodium–glucose cotransporter 2 (SGLT2) inhibitors on metastatic cancer remains largely unexamined. With a confirmatory approach based on the Cochrane recommendation, we conducted a frequentist-based network meta-analysis (NMA) of randomized controlled trials (RCTs) evaluating such medications. The primary outcome was the incidence of metastatic cancer, while secondary outcomes included safety profiles assessed through dropout rates. The findings were reaffirmed by sensitivity analysis with a Bayesian-based NMA. This NMA of 207,606 participants from 67 RCTs revealed that only efpeglenatide demonstrated a statistically significant reduction in metastatic cancer events compared to controls (odds ratio = 0.26, 95% confidence intervals = 0.09 to 0.70, p = 0.010, number needed to treat = 188.4). Efpeglenatide’s efficacy was not confined to specific cancer types. Safety profiles were comparable across all treatments. These findings indicate that efpeglenatide may possess a broad, systemic preventive effect against metastatic cancers, potentially operating through mechanisms that are not restricted to individual organ systems. Further research is warranted to elucidate the molecular pathways underlying its anti-metastatic properties and to explore its role in preventive oncology. Full article

Strongyloidosis is a parasitic disease caused by Strongyloides stercoralis, a nematode with a complex life cycle that facilitates long-term persistence within the host. The infection affects millions of people in tropical and subtropical regions and poses a particular challenge in immunocompromised individuals. Although conventional treatments, such as ivermectin and albendazole, are generally effective, emerging concerns regarding drug resistance and adverse effects have prompted the search for alternative therapeutic options. In this context, natural products—including plant extracts, bioactive phytochemicals, and nanoparticle-based formulations derived from natural sources—are emerging as promising anti-Strongyloides potential. This review summarizes recent studies on natural products with anthelmintic activity against strongyloidiasis, with emphasis on their mechanisms of action, efficacy, and future perspectives. A systematic search of the literature was conducted using terms related to Strongyloides, plant species, extracts, and bioactive compounds with nematocidal activity. Eligible studies included those reporting the activity of plants, plant extracts, and their purified metabolites against Strongyloides spp. Data were compiled into a comprehensive table including year of publication, author, plant species, active principle, application conditions, and target nematode species. The pharmacological treatment of this parasite varies according to its life cycle stage. Various biomolecules, phytoactive compounds, and novel plant-based formulations have demonstrated promising activity and may be considered both for treatment and for inclusion in control programs for strongyloidiasis. This review highlights medicinal plants and phytochemicals with ethnopharmacological background and experimentally validated activity against Strongyloides spp., integrating evidence from in vitro, in vivo, and experimental models, as well as clinical trials. Full article

Letrozole, a third-generation aromatase inhibitor initially developed for breast cancer, has become the preferred first-line agent for ovulation induction (OI), particularly in women with polycystic ovary syndrome (PCOS). This narrative review critically evaluates the efficacy, safety, and clinical applications of letrozole across diverse infertility contexts. Compared to clomiphene citrate, letrozole is associated with higher ovulation and live birth rates, a lower risk of multiple gestation, and a more favorable endometrial environment. Its pharmacokinetics—marked by transient estrogen suppression and a short half-life—limit embryonic exposure, supporting its favorable safety profile. Emerging data from large, randomized trials and meta-analyses demonstrate no increase in congenital anomalies, miscarriage, or adverse perinatal outcomes in letrozole-conceived pregnancies. Moreover, maternal side effects are generally mild, and the risk of ovarian hyperstimulation syndrome is low. Letrozole has also shown utility in mild stimulation protocols, fertility preservation for estrogen-sensitive malignancies, and clomiphene-resistant PCOS. Key clinical strategies—such as early-cycle initiation, lowest effective dosing, and individualized monitoring—optimize therapeutic outcomes while minimizing potential risks. While long-term offspring data remain limited and mechanistic concerns persist, current evidence robustly supports letrozole as a safe and effective option for OI, balancing reproductive success with maternal–fetal safety across a range of infertility indications. Full article

Background/Objectives: Nipple trauma is a common challenge during the early postpartum period, often undermining maternal confidence and breastfeeding success. Although deep-learning-based image analysis offers the potential for objective and remote assessments, its feasibility in clinical practice has not been well examined. This study aimed to evaluate the feasibility and acceptability of a deep-learning-based nipple trauma assessment system and explore maternal perceptions of the intervention. Methods: A quasi-experimental study was conducted at a maternity hospital in Japan. Participants were assigned to intervention or control groups based on their delivery month. Mothers in the intervention group used a dedicated offline smartphone to photograph their nipples during hospitalization. Images were analyzed using a pretrained deep-learning model, and individualized feedback was delivered via a secure messaging platform. Self-administered questionnaires were collected at three points: late pregnancy, during hospitalization, and one month postpartum. Maternal experiences and satisfaction with breastfeeding were also assessed. Results: A total of 23 participants (intervention = 8 and control = 15) completed the study. The system functioned without technical errors, and no adverse events were reported. Most participants found the AI results useful, with 75% receiving high-confidence outputs (predicted class probability ≥ 60%). Participants expressed interest in real-time feedback and post-discharge use. Breastfeeding self-efficacy scores (BSES-SF) improved more in the intervention group (+9.8) than in the control group (+7.8). Conclusions: This study confirmed the feasibility and acceptability of a deep-learning-based nipple trauma assessment system during postpartum hospitalization. The system operated safely and was well received by participants. Future developments should prioritize real-time, remote functionality to support diverse maternal needs. Full article

Traumatic brain injury (TBI) is a major cause of long-term neurological impairment, with aging amplifying vulnerability and worsening recovery. Older individuals face greater cognitive and motor deficits post-TBI and respond less effectively to treatments, as both aging and TBI independently elevate neuroinflammation and cognitive decline. This study evaluated the therapeutic effects of human adipose-derived stem cell small extracellular vesicles (hASC-sEVs) on neurological recovery and neuroinflammation in a mouse model of TBI. Male C57BL/6 mice (3, 15, and 20 months old) underwent controlled cortical impact (CCI) and received intranasal hASC-sEVs 48 h post-injury; control groups received PBS. A dose–response study at 7 days post injury (dpi) identified 20 µg as the optimal therapeutic dose, improving motor function, reducing neuroinflammation, and enhancing neurogenesis. This was followed by a 30-dpi study assessing cognitive function, neuroinflammation, neurogenesis, and proteomic changes in microglia and astrocytes via mass spectrometry. hASC-sEV treatment significantly improved behavioral outcomes and reduced neuroinflammatory markers (GFAP, IBA-1, and MHC-II), with reduced efficacy observed in older mice. Proteomics revealed that hASC-sEVs reduce inflammatory proteins (TNF-α, IL-1β, IFNG, CCL2) and modulated mitochondrial dysfunction and reactive oxygen species. These results highlight hASC-sEVs as a promising cell-free therapy for improving TBI outcomes, especially in aging populations. Full article

Background. Parkinson’s Disease (PD) is a neurological condition that can severely impair gait, often through changes to gait parameters including stride length, velocity, and variability. Therapeutic interventions such as Rhythmic Auditory Stimulation (RAS^®) target gait dysfunction in PD by using the regular beat of music or metronome clips to cue normalized walking patterns. Previous research has suggested that auditory cue properties (e.g., familiarity and groove) and individual factors (e.g., beat perception ability and susceptibility to dual-task interference) influence auditory cueing treatment efficacy in healthy young and older adults; however, optimization of rhythmic cueing across individuals with PD remains understudied. Methods. To address this, we explored the effects of familiarity, groove, beat perception ability, and synchronization instructions on gait in patients with PD during accelerated auditory cues. Individuals with idiopathic PD were randomized to walk freely or synchronized to music and metronome cues played 10% faster than their baseline walking cadence. Musical stimuli varied in self-reported familiarity and perceived groove and beat perception ability was assessed to classify participants as good or poor beat perceivers. Results. Overall, high-groove music and synchronized walking elicited faster gait patterns compared to low-groove music and free walking, respectively, as demonstrated by increased gait velocity and cadence. Familiarity and beat perception ability did not significantly affect gait in individuals with PD. Discussion. Altogether, our results indicate that high-groove music and synchronized walking lead to the greatest gait improvements during cueing, regardless of beat perception ability. Conclusion. Future studies and clinical interventions should consider stimulus type and synchronization instructions when implementing cueing therapies for gait dysfunction in PD in order to optimize treatment responses. Full article

To enhance the convergence efficiency and solution precision of the Red-billed Blue Magpie Optimizer (RBMO), this study proposes a Multi-Strategy Enhanced Red-billed Blue Magpie Optimizer (MRBMO). The principal methodological innovations encompass three aspects: (1) Development of a novel dynamic boundary constraint handling mechanism that strengthens algorithmic exploration capabilities through adaptive regression strategy adjustment for boundary-transgressing particles; (2) Incorporation of an elite guidance strategy during the predation phase, establishing a guided search framework that integrates historical individual optimal information while employing a Lévy Flight strategy to modulate search step sizes, thereby achieving effective balance between global exploration and local exploitation capabilities; (3) Comprehensive experimental evaluations conducted on the CEC2017 and CEC2022 benchmark test suites demonstrate that MRBMO significantly outperforms classical enhanced algorithms and exhibits competitive performance against state-of-the-art optimizers across 41 standardized test functions. The practical efficacy of the algorithm is further validated through successful applications to four classical engineering design problems, confirming its robust problem-solving capabilities. Full article

Objective: Dinutuximab beta (DB) and naxitamab (NAXI) with GM-CSF are used for maintenance treatment of relapsed/refractory neuroblastoma. The objective of this study was to systematically assess comparative efficacy of the two therapies within their designated indications in accordance with established clinical guidelines. Methods: Relevant evidence was identified in systematic literature review. Individual patient data (IPD) from prospective clinical trials of DB were assessed and data on patients with disease in bone or bone marrow, as assessed in MRI, CT, mIBG or biopsy, with incomplete response to previous therapy were included. Patients with complete response, progressive disease and/or soft tissue disease were excluded. DB population was adjusted for sex, MYCN amplification, disease type (relapsed, refractory), and disease site (bone marrow and/or bone) to balance aggregated characteristics of NAXI population. More characteristics were included in sensitivity analyses, including DB treatment without interleukin-2, as currently recommended. Overall response rate (ORR) was assessed as best response. Results: Aggregated data for NAXI from Study 201 (n = 52) and Study 230 (n = 38) and IPD from DB studies (APN311-202, APN311-304, c = 77) met the inclusion criteria. Compared to NAXI, DB significantly extended progression-free survival (PFS): hazard ratio, DB vs. NAXI of 0.47 (95% CI: 0.26 to 0.87, p = 0.015). ORR was 60.1% (95% CI: 48.5% to 71.6%) for DB vs. 43.3% (33.1% to 53.6%) for NAXI (ORR odds ratio, DB vs. NAXI was 1.97, 95% CI: 1.02 to 3.80, p = 0.044). Sensitivity analyses and unadjusted comparisons supported the results. Conclusion: In the indirect comparison, dinutuximab beta significantly extended PFS and increased ORR compared to naxitamab. Full article

Background: Antimicrobial resistance is a growing global health concern that requires multiple strategies to be tackled effectively. While the discovery of new antimicrobial molecules is essential, the repurposing of existing compounds also plays a significant role. Standard methods to evaluate antimicrobial efficacy, regulated by the Committee on Antimicrobial Susceptibility Testing (EUCAST) and the Clinical and Laboratory Standards Institute (CLSI), such as the determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), are available. However, several potential antimicrobics show interference with these standard methods, resulting in underestimated activity and their premature dismissal from further studies. This work compares reference methods in evaluating different compounds with unique physico-chemical characteristics. We aim to demonstrate that combining different susceptibility tests is mandatory for a successful preclinical screening of antimicrobial compounds. Methods: A selection of substances including natural extracts, both free and in the form of nanocomposites with fumed silica, ionic liquids, ozonated oils, commercial and pure antibiotics, was tested using broth microdilution, disk diffusion, and agar dilution. These methods were chosen following EUCAST and CLSI guidelines, and comparisons were made to evaluate their applicability and limitations for non-conventional substances. Results: The study highlighted significant variability in the outcomes depending on the method used, especially for substances with intrinsic properties such as high viscosity, poor solubility, or specific interactions with the testing medium. In several cases, the use of a single standard method failed to accurately reflect the real antimicrobial activity, leading to potential misinterpretation of effectiveness. Conclusions: A combined methodological approach is recommended to overcome the limitations of individual techniques. The integration of multiple reference methods offers a more accurate screening strategy for identifying and characterizing new and repurposed antimicrobials. Full article

Schizophrenia is a complex disorder that affects mental organization and cognitive functions, including concentration and memory. One notable manifestation of cognitive changes in schizophrenia is a diminished ability to scan and perform tasks related to visual inspection. From the three evaluable aspects of the ocular movements (saccadic, smooth pursuit, and fixation) in particular, smooth pursuit eye movement (SPEM) involves the tracking of slow moving objects and is closely related to attention, visual memory, and processing speed. However, evaluating smooth pursuit in clinical settings is challenging due to the technical complexities of detecting these movements, resulting in limited research and clinical application. This pilot study investigates whether the quantitative metrics derived from eye-tracking data can distinguish between patients with schizophrenia under treatment and healthy controls. The study included nine healthy participants and nine individuals receiving treatment for schizophrenia. Gaze trajectories were recorded using an eye tracker during a controlled visual tracking task performed during a clinical visit. Spatiotemporal analysis of gaze trajectories was performed by evaluating three different features: polygonal area, colocalities, and direction difference. Subsequently, a support vector machine (SVM) was used to assess the separability between healthy individuals and those with schizophrenia based on the identified gaze trajectory features. The results show statistically significant differences between the control and subjects with schizophrenia for all the computed indexes (p < 0.05) and a high separability achieving around 90% of accuracy, sensitivity, and specificity. The results suggest the potential development of a valuable clinical tool for the evaluation of SPEM, offering utility in clinics to assess the efficacy of therapeutic interventions in individuals with schizophrenia. Full article