Factors influencing the relationship between coaches and athletes with disabilities: a systematic review.

Introduction: The relationship between coaches and athletes with disabilities is critical for enhancing athletes' performance and psychosocial well-being. This study aims to provide evidence-based recommendations for coaches, sports organizations, and policymakers dedicated to supporting athletes with disabilities. Methods: A comprehensive analysis of existing literature was conducted. Five databases were searched, including PubMed, Web of Science, SPORTDiscus, Google Scholar, and China National Knowledge Infrastructure. A total of 22 studies were included for thematic analysis. Results: This systematic review identifies key factors influencing the coach-athlete relationship in disabled sports. These factors are categorized into three main domains: professional, interpersonal, and intrapersonal. In the professional domain, effective coaching requires sport-specific skills and adaptive techniques tailored to the unique needs of athletes with disabilities. Coaches must understand the technical and tactical aspects of each parasport and adapt training plans to optimize performance and foster independence. The interpersonal domain emphasizes communication strategies and team-building practices. Effective communication involves understanding athletes' needs and adapting approaches to maximize strengths. Building rapport, managing conflict, and fostering a supportive team environment are crucial for maintaining a positive coach-athlete relationship. The intrapersonal domain highlights the importance of self-reflection and continuous learning. Coaches who engage in self-reflection and professional development better understand their behaviors and biases, enabling them to tailor coaching strategies to the specific needs of athletes with disabilities. Continuous learning is essential for remaining responsive to the evolving needs of these athletes. Discussion: This review underscores the importance of a holistic approach that integrates professional expertise, interpersonal skills, and intrapersonal awareness. By addressing these factors, it provides a foundation for developing more effective coaching strategies and supports for athletes with disabilities, ultimately enhancing their performance and well-being. Future research should explore cultural differences, the specific coaching needs of athletes with intellectual disabilities, and the impact of policies and structural barriers on the coach-athlete relationship in disabled sports.

Age-associated changes in innate and adaptive immunity: role of the gut microbiota.

Aging is generally regarded as an irreversible process, and its intricate relationship with the immune system has garnered significant attention due to its profound implications for the health and well-being of the aging population. As people age, a multitude of alterations occur within the immune system, affecting both innate and adaptive immunity. In the realm of innate immunity, aging brings about changes in the number and function of various immune cells, including neutrophils, monocytes, and macrophages. Additionally, certain immune pathways, like the cGAS-STING, become activated. These alterations can potentially result in telomere damage, the disruption of cytokine signaling, and impaired recognition of pathogens. The adaptive immune system, too, undergoes a myriad of changes as age advances. These include shifts in the number, frequency, subtype, and function of T cells and B cells. Furthermore, the human gut microbiota undergoes dynamic changes as a part of the aging process. Notably, the interplay between immune changes and gut microbiota highlights the gut's role in modulating immune responses and maintaining immune homeostasis. The gut microbiota of centenarians exhibits characteristics akin to those found in young individuals, setting it apart from the microbiota observed in typical elderly individuals. This review delves into the current understanding of how aging impacts the immune system and suggests potential strategies for reversing aging through interventions in immune factors.

ADP-based online compensation hierarchical sliding-mode control for partially unknown switched nonlinear systems with actuator failures.

This article investigates an adaptive dynamic programming-based online compensation hierarchical sliding-mode control problem for a class of partially unknown switched nonlinear systems with actuator failures and uncertain perturbations under an identifier-critic neural networks architecture. Firstly, by introducing a cost function related to hierarchical sliding-mode surfaces for the nominal system, the original control problem is equivalently converted into an optimal control problem. To obtain this optimal control policy, the Hamilton-Jacobi-Bellman equation is solved through an adaptive dynamic programming method. Compared with conventional adaptive dynamic programming methods, the identifier-critic network architecture not only overcomes the limitation on the unknown internal dynamic but also eliminates the approximation error arising from the actor network. The weights in the critic network are tuned via the gradient descent approach and the experience replay technology, such that the persistence of excitation condition can be relaxed. Then, a compensation term containing hierarchical sliding-mode surfaces is used to offset uncertain actuator failures without the fault detection and isolation unit. Based on the Lyapunov stability theory, all states of the closed-loop nonlinear system are stable in the sense of uniformly ultimately boundedness. Finally, numerical and practical examples are given to demonstrate the effectiveness of our presented online compensation control strategy.

Adaptive critic design for safety-optimal FTC of unknown nonlinear systems with asymmetric constrained-input.

Safe fault tolerant control is one of the key technologies to improve the reliability of dynamic complex nonlinear systems with limited inputs, which is hard to solve and definitely a great challenge to tackle. Thus the paper presents a novel safety-optimal FTC (Fault Tolerant Control) approach for a category of completely unknown nonlinear systems incorporating actuator fault and asymmetric constrained-input, which can guarantee the system's operation within a safe range while showcasing optimal performance. Firstly, a CBF (Control Barrier Function) is incorporated into the cost function to penalize unsafe behaviors, and then we translate the intractable safety-optimal FTC problem into a differential ZSG (Zero-Sum Game) problem by defining the control input and the actuator fault as two opposing sides. Secondly, a neural-network-based identifier is employed to reconstruct system dynamics using system data, and the resolution of handling asymmetric constrained-input with the introduced non-quadratic cost function is achieved through the design of an adaptive critic scheme, aiming to reduce computational expenses accordingly. Finally, through the theoretical stability analysis, it is demonstrated that all signals in the closed-loop system are consistently UUB (Uniformly Ultimately Bounded). Furthermore, the proposed method's effectiveness is also verified in the simulation experiments conducted on a model of a single-link robotic arm system with actuator failure. The result shows that the algorithm can fulfill the safety-optimal demand of fault tolerant control in fault system with asymmetric constrained-input.

Online Adaptive Proton Therapy Facilitated by Artificial Intelligence-based Auto Segmentation in Pencil Beam Scanning Proton Therapy: Prostate oAPT in PBSPT.

PURPOSE: Online adaptive proton therapy (oAPT) is essential to address interfractional anatomical changes in patients receiving pencil beam scanning proton therapy (PBSPT). Artificial intelligence (AI)-based auto-segmentation can increase the efficiency and accuracy. Linear energy transfer (LET)-based biological effect evaluation can potentially mitigate possible adverse events caused by high LET. New spot arrangement based on the verification CT (vCT) can further improve the re-plan quality. We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. METHODS AND MATERIALS: AI-based auto-segmentation tool AccuContourTM (Manteia, Xiamen, China) was seamlessly integrated into oAPT. Initial spot arrangement tool on the vCT for re-optimization was implemented using raytracing. An LET-based biological effect evaluation tool was developed to assess the overlap region of high dose and high LET in selected OARs. Eleven prostate cancer patients were retrospectively selected to verify the efficacy and efficiency of the proposed oAPT workflow. The time cost of each component in the workflow was recorded for analysis. RESULTS: The verification plan showed significant degradation of the CTV coverage and rectum and bladder sparing due to the interfractional anatomical changes. Re-optimization on the vCT resulted in great improvement of the plan quality. No overlap regions of high dose and high LET distributions were observed in bladder or rectum in re-plans. 3D Gamma analyses in PSQA confirmed the accuracy of the re-plan doses before delivery (Gamma passing rate = 99.57 ± 0.46%), and after delivery (98.59 ± 1.29%). The robustness of the re-plans passed all clinical requirements. The average time for the complete execution of the workflow was 9.12 ± 0.85 minutes, excluding manual intervention time. CONCLUSION: The AI-facilitated oAPT workflow was demonstrated to be both efficient and effective by generating a re-plan that significantly improved the plan quality in prostate cancer treated with PBSPT.

Advance Care Planning Bundle: Using Technical and Adaptive Solutions to Promote Goal Concordant Care.

BACKGROUND: Advance Care Planning (ACP) is critical to achieve goal-aligned care for patients. However, optimal implementation requires complex coordination and alignment across a healthcare system. MEASURES: A survey of rapid response providers assessed usefulness of the ACP quality improvement bundle and perceptions of use and adherence. INTERVENTION: We implemented a bundle of advance care planning tools and interventions using the technical-adaptive framework. These included orders, documentation templates and processes, and standard education. OUTCOMES: Ninety-three rapid response providers completed the survey. 80.5% reported that overall, these quality improvement efforts have been very helpful or somewhat helpful in improving their ability to provide care consistent with the patient's goals. CONCLUSIONS/LESSONS LEARNED: Implementation of technical and adaptive tools as a bundle for Advance Care Planning shows promise to improve and sustain goal-aligned care. Quality Improvement in ACP is a complex, iterative process involving both structural change and behavioral adaptation.

The 2024 roadmap for understanding marine species' resilience in a changing ocean.

Written to serve as a guideline for future research in this field, this roadmap provides some perspectives on the main developments and remaining challenges in the field of marine animal acclimatisation, adaptive potential and resilience to climate change. There has been extensive research conducted on the impact of climate change stress on marine animals, with studies recognising the potential for cross- and multi- generational impacts. Parents can potentially pass on resilience to offspring. The response of marine animals to climate change stressors is complex where utilising marginal and extreme systems as natural laboratories can help to address key research gaps and provide an understanding of the plastic and adaptive changes necessary for survival under stress.

Every problem is embedded in a greater whole.

Peter Drucker pointed out an important distinction between 'doing things right' and 'doing the right thing', which recognised that all problems are embedded in a context and thus can only be understood within their unique contextual setting. Contemporary research practices in clinical medicine often regards contextual factors as potential confounders that will bias effect estimates and thus must be avoided. However rigorous, research devoid of context ultimately deprives users of understanding of the support factors that make research transferable to policy decisions or managing care of individual patients-it stands in the way of 'doing the right thing' in 'real life' settings. Appreciating that all problems are embedded in a greater context means that one should not ignore their interconnected and interdependent systemic nature, that is, every variable is simultaneously dependent and independent. This is the reason for the cascading effects and feedback loops witnessed in disease progression and policy efforts. We discuss the need for researchers to a-priori consider the context of their research question as well as the structural relationships of the variables under investigation, which in turn provides the basis for choosing the most appropriate research design. We have a moral imperative to first 'do the right thing'-ask questions that address the contextual needs of our patients, and then to 'do it right'-choose the best research method to answer this contextually framed need. Only then will our research efforts have meaningful and lasting impacts on patient care.

Adaptive Deep Brain Stimulation in Parkinson's Disease: A Delphi Consensus Study.

Importance: If history teaches, as cardiac pacing moved from fixed-rate to on-demand delivery in in 80s of the last century, there are high probabilities that closed-loop and adaptive approaches will become, in the next decade, the natural evolution of conventional Deep Brain Stimulation (cDBS). However, while devices for aDBS are already available for clinical use, few data on their clinical application and technological limitations are available so far. In such scenario, gathering the opinion and expertise of leading investigators worldwide would boost and guide practice and research, thus grounding the clinical development of aDBS. Observations: We identified clinical and academically experienced DBS clinicians (n=21) to discuss the challenges related to aDBS. A 5-point Likert scale questionnaire along with a Delphi method was employed. 42 questions were submitted to the panel, half of them being related to technical aspects while the other half to clinical aspects of aDBS. Experts agreed that aDBS will become clinical practice in 10 years. In the present scenario, although the panel agreed that aDBS applications require skilled clinicians and that algorithms need to be further optimized to manage complex PD symptoms, consensus was reached on aDBS safety and its ability to provide a faster and more stable treatment response than cDBS, also for tremor-dominant Parkinson's disease patients and for those with motor fluctuations and dyskinesias. Conclusions and Relevance: Despite the need of further research, the panel concluded that aDBS is safe, promises to be maximally effective in PD patients with motor fluctuation and dyskinesias and therefore will enter into the clinical practice in the next years, with further research focused on algorithms and markers for complex symptoms.

MR-linac based radiation therapy in gastrointestinal cancers: a narrative review.

Background and Objective: Magnetic resonance guided radiotherapy (MRgRT) is an emerging technological innovation with more and more institutions gaining clinical experience in this new field of radiation oncology. The ability to better visualize both tumors and healthy tissues due to excellent soft tissue contrast combined with new possibilities regarding motion management and the capability of online adaptive radiotherapy might increase tumor control rates while potentially reducing the risk of radiation-induced toxicities. As conventional computed tomography (CT)-based image guidance methods are insufficient for adaptive workflows in abdominal tumors, MRgRT appears to be an optimal method for this tumor site. The aim of this narrative review is to outline the opportunities and challenges in magnetic resonance guided radiation therapy in gastrointestinal cancers. Methods: We searched for studies, reviews and conceptual articles, including the general technique of MRgRT and the specific utilization in gastrointestinal cancers, focusing on pancreatic cancer, liver metastases and primary liver cancer, rectal cancer and esophageal cancer. Key Content and Findings: This review is highlighting the innovative approach of MRgRT in gastrointestinal cancer and gives an overview of the currently available literature with regard to clinical experiences and theoretical background. Conclusions: MRgRT is a promising new tool in radiation oncology, which can play off several of its beneficial features in the specific field of gastrointestinal cancers. However, clinical data is still scarce. Nevertheless, the available literature points out large potential for improvements regarding dose coverage and escalation as well as the reduction of dose exposure to critical organs at risk (OAR). Further prospective studies are needed to demonstrate the role of this innovative technology in gastrointestinal cancer management, in particular trials that randomly compare MRgRT with conventional CT-based image-guided radiotherapy (IGRT) would be of high value.

An enhanced Garter Snake Optimization-assisted deep learning model for lung cancer segmentation and classification using CT images.

An early detection of lung tumors is critical for better treatment results, and CT scans can reveal lumps in the lungs which are too small to be picked up by conventional X-rays. CT imaging has advantages, but it also exposes a person to radiation from ions, which raises the possibility of malignancy, particularly when the imaging procedure is done. Access to expensive-quality CT scans and the related sophisticated analytic tools might be restricted in environments with fewer resources due to their high cost and limited availability. It will need an array of creative technological innovations to overcome such weaknesses. This paper aims to design a heuristic and deep learning-aided lung cancer classification using CT images. The collected images are undergone for segmentation, which is performed by Shuffling Atrous Convolutional (SAC) based ResUnet++ (SACRUnet++). Finally, the lung cancer classification is performed by the Adaptive Residual Attention Network (ARAN) by inputting the segmented images. Here the parameters of ARAN are optimally tuned using the Improved Garter Snake Optimization Algorithm (IGSOA). The developed lung cancer classification performance is compared to conventional lung cancer classification models and it showed high accuracy.

The irtQ R package: a user-friendly tool for item response theory-based test data analysis and calibration.

Computerized adaptive testing (CAT) has become a widely adopted test design for high-stakes licensing and certification exams, particularly in the health professions in the United States, due to its ability to tailor test difficulty in real time, reducing testing time while providing precise ability estimates. A key component of CAT is item response theory (IRT), which facilitates the dynamic selection of items based on examinees' ability levels during a test. Accurate estimation of item and ability parameters is essential for successful CAT implementation, necessitating convenient and reliable software to ensure precise parameter estimation. This paper introduces the irtQ R package, which simplifies IRT-based analysis and item calibration under unidimensional IRT models. While it does not directly simulate CAT, it provides essential tools to support CAT development, including parameter estimation using marginal maximum likelihood estimation via the expectation-maximization algorithm, pretest item calibration through fixed item parameter calibration and fixed ability parameter calibration methods, and examinee ability estimation. The package also enables users to compute item and test characteristic curves and information functions necessary for evaluating the psychometric properties of a test. This paper illustrates the key features of the irtQ package through examples using simulated datasets, demonstrating its utility in IRT applications such as test data analysis and ability scoring. By providing a user-friendly environment for IRT analysis, irtQ significantly enhances the capacity for efficient adaptive testing research and operations. Finally, the paper highlights additional core functionalities of irtQ, emphasizing its broader applicability to the development and operation of IRT-based assessments.

Latest Developments in "Adaptive Enrichment" Clinical Trial Designs in Oncology.

As cancer has become better understood on the molecular level with the evolution of gene sequencing techniques, considerations for individualized therapy using predictive biomarkers (those associated with a treatment's effect) have shifted to a new level. In the last decade or so, randomized "adaptive enrichment" clinical trials have become increasingly utilized to strike a balance between enrolling all patients with a given tumor type, versus enrolling only a subpopulation whose tumors are defined by a potential predictive biomarker related to the mechanism of action of the experimental therapy. In this review article, we review recent innovative design extensions and adaptations to adaptive enrichment designs proposed during the last few years in the clinical trial methodology literature, both from Bayesian and frequentist perspectives.

Photografting of Surface-assembled Hydrogel Prepolymers to Elastomeric Substrates for Production of Stimuli-Responsive Microlens Arrays.

Hydrogels have emerged as prototypical stimuli-responsive materials with potential applications in soft robotics, microfluidics, tissue engineering, and adaptive optics. To leverage the full potential of these materials, fabrication techniques capable of simultaneous control of microstructure, device architecture, and interfacial stability, i.e., adhesion of hydrogel components to support substrates, are needed. A universal strategy for the microfabrication of hydrogel-based devices with robust substrate adhesion amenable to use in liquid environments would enable numerous applications. This manuscript reports a general approach for the facile production of covalently attached, ordered arrays of microscale hydrogels (microgels) on silicone supports. Specifically, silicone-based templates were used to: i) drive mechanical assembly of prepolymer droplets into well-defined geometries and morphologies, and ii) present appropriate conjugation moieties to fix gels in place during photoinitiated crosslinking via a "graft from" polymerization scheme. Automated processing enabled rapid microgel array production for characterization, testing, and application. Furthermore, the stimuli-responsive microlensing properties of these arrays, via contractile modulated refractive index, were demonstrated. This process is directly applicable to the fabrication of adaptive optofluidic systems and can be further applied to advanced functional systems such as soft actuators and robotics and 3D cell culture technologies.

Prior-image-based low-dose CT reconstruction for adaptive radiation therapy.

OBJECTIVE: The study aims to reduce the imaging radiation dose in Adaptive Radiotherapy (ART) while maintaining high-quality CT images, critical for effective treatment planning and monitoring. APPROACH: We developed the Prior-aware Learned Primal-Dual Network (pLPD-UNet), which uses prior CT images to enhance reconstructions from low-dose scans. The network was separately trained on thorax and abdomen datasets to accommodate the unique imaging requirements of each anatomical region. MAIN RESULTS: The pLPD-UNet demonstrated improved reconstruction accuracy and robustness in handling sparse data compared to traditional methods. It effectively maintained image quality essential for precise organ delineation and dose calculation, while achieving a significant reduction in radiation exposure. SIGNIFICANCE: This method offers a significant advancement in the practice of ART by integrating prior imaging data, potentially setting a new standard for balancing radiation safety with the need for high-resolution imaging in cancer treatment planning.

Opioid-specific harm reduction in the emergency department: how staff provide harm reduction and contextual factors that impact their capacity to engage in harm reduction practice.

BACKGROUND: Emergency Departments (ED) staff, including nurses and physicians, are most directly involved in the care of people who use unregulated substances, and are ideally positioned to provide harm reduction interventions. Conceptualizing the ED as a complex adaptive system, this paper examines how ED staff experience opioid-specific harm reduction provision and engage in harm reduction practice, including potential facilitators and barriers to engagement. METHODS: Using a mixed methods approach, ED nurses and physicians completed a self-administered staff survey (n = 99) and one-on-one semi-structured interviews (n = 15). Five additional interviews were completed with clinical leaders. Survey data were analyzed to generate descriptive statistics and to compute scale scores. De-identified interview data were analyzed using a reflexive thematic analysis approach, which was informed by the theory of complex adaptive systems, as well as understandings of harm reduction as both a technical solution and a contextualized social practice. The final analysis involved mixed analysis through integrating both quantitative and qualitative data to generate overarching analytical themes. RESULTS: Study findings illustrated that, within the context of the ED as a complex adaptive system, three interrelated contextual factors shape the capacity of staff to engage in harm reduction practice, and to implement the full range of opioid-specific harm reduction interventions available. These factors include opportunities to leverage benefits afforded by working collaboratively with colleagues, adequate preparation through receiving the necessary education and training, and support in helping patients establish connections for ongoing care. CONCLUSIONS: There is a need for harm reduction provision across all health and social care settings where people who use unregulated opioids access public sector services. In the context of the ED, attention to contextual factors including teamwork, preparedness, and connections is warranted to support that ED staff engage in harm reduction practice.

Associations of Early Prolonged Secondary Amenorrhea in Women With and Without HIV.

Background: The menstrual cycle is a critical indicator of women's health. Early prolonged secondary amenorrhea increases risks for morbidity and mortality. Menstrual cycle research in women with HIV is inconsistent and often lacks an adequate comparison sample. We aimed to determine whether women with HIV have a higher lifetime prevalence of amenorrhea and whether this is independently associated with HIV and/or other biopsychosocial variables. Methods: With data from 2 established HIV cohorts, participants assigned female at birth were eligible if aged ≥16 years, not pregnant/lactating, and without anorexia/bulimia nervosa history. Amenorrhea was defined by self-reported history of (1) no menstrual flow for ≥12 months postmenarche not due to pregnancy/lactation, medications, or surgery or (2) early menopause or premature ovarian insufficiency. Multivariable logistic regression models explored biopsychosocial covariates of amenorrhea. Results: Overall, 317 women with HIV (median age, 47.5 years [IQR, 39.2-56.4]) and 420 women without HIV (46.2 [32.6-57.2]) were included. Lifetime amenorrhea was significantly more prevalent among women with HIV than women without HIV (24.0% vs 13.3%). In the multivariable analysis, independent covariates of amenorrhea included HIV (adjusted odds ratio, 1.70 [95% CI, 1.10-2.64]), older age (1.01 [1.00-1.04]), White ethnicity (1.92 [1.24-3.03]), substance use history (6.41 [3.75-11.1]), and current food insecurity (2.03 [1.13-3.61]). Conclusions: Nearly one-quarter of women with HIV have experienced amenorrhea, and this is associated with modifiable risk factors, including substance use and food insecurity. Care providers should regularly assess women's menstrual health and advocate for actionable sociostructural change to mitigate risks.

CT-Guided Online Adaptive Hypofractionated Radiotherapy for Primary Bladder Cancer: A Report of Two Cases.

Trimodality treatment for bladder cancer, consisting of maximal transurethral resection of the tumor followed by concurrent chemoradiotherapy, is an attractive management option with curative and organ-sparing intent. However, such treatment can be associated with acute toxicities related to the large treatment margins required due to daily variation in bladder filling, with resultant bladder, bowel, and rectal toxicity. Adaptive radiation, which accounts for inter-fraction variations in bladder size, allows the confident delivery of radiation to bladder cancer with smaller margins, with the potential to reduce toxicities without the associated risk of compromising the target coverage. Herein, we present a case series of two patients with primary bladder cancer who were treated with computed tomography (CT)-based online adaptive hypofractionated radiotherapy using the Ethos system (Varian Medical Systems, Palo Alto, CA, USA). The first is an 83-year-old male with a remote history of prostate cancer treated with radiotherapy, who received adaptive radiotherapy as a means of decreasing the required margin size and optimizing planning based on adjacent bowel to reduce the risk of re-irradiation. The second patient is a 78-year-old male with node-positive bladder cancer, which necessitated whole pelvis radiotherapy, who underwent adaptive treatment (25 fractions) as a means of sparing cumulative dose to the bowel while ensuring suitable target coverage. In both cases, the clinical target volume consisted of the entire bladder (± nodes) with a planning target volume expansion of 7 mm. During treatment, daily cone-beam CT scans were acquired and used to generate adapted plans. These plans were compared to the original plans, with attention to target coverage and dose to organs at risk. For all 45 fractions, the adaptive plan was selected, primarily as a means of improving target coverage. This case series demonstrates that the adaptive Ethos system effectively delivers treatment for primary bladder cancer. Further data are needed for clinical toxicity outcomes and the efficacy of this approach.

Application of neural network adaptive filter method to simultaneous detection of polymetallic ions based on ultraviolet-visible spectroscopy.

A novel neural network adaptive filter algorithm is proposed to address the challenge of weak spectral signals and low accuracy in micro-spectrometer detection. This algorithm bases on error backpropagation (BP) and least mean square (LMS), introduces an innovative BP neural network model incorporating instantaneous error function and error factor to optimize the learning process. It establishes a network relationship through the input signal, output signal, error and step factor of the adaptive filter, and defines a training optimization learning method for this relationship. To validate the effectiveness of the algorithm, experiments were conducted on simulated noisy signals and actual spectral signals. Results show that the algorithm effectively denoises signals, reduces noise interference, and enhances signal quality, the SNR of the proposed algorithm is 3-4 dB higher than that of the traditional algorithm. The experimental spectral results showed that the proposed neural network adaptive filter algorithm combined with partial least squares regression is suitable for simultaneous detection of copper and cobalt based on ultraviolet-visible spectroscopy, and has broad application prospects.

Latitudinal trends in an invasive plant: genetic differentiation, phenotypic plasticity, and the effects of heavy metals and herbivores on growth, defence, and reproductive characteristics.

BACKGROUND AND AIMS: Invasive species usually demonstrate remarkable adaptability across diverse environments, successfully inhabiting a wide variety of regions. This adaptability often links to genetic differentiation and phenotypic plasticity, leading to latitudinal trends in phenotypic traits. In this study, we collected seeds of invasive plant Phytolacca americana from different latitudes and planted them in homogeneous gardens to investigate the latitudinal variation of P. americana phenotypic traits and to evaluate the effects of herbivory and heavy metals on plant growth, defence, and reproductive characteristics. METHODS: P. americana seeds from different latitudes were planted in a homogeneous garden. For the experimental treatment, the seeds were divided into four groups: a heavy metal treatment group and its corresponding control group, and a cover treatment group with its corresponding control group. After the fruits matured, their growth, reproduction, and defence indicators were measured. KEY RESULTS: Significant latitudinal trends were observed in P. americana's growth and defence characteristics, including changes in branch number, underground biomass, total biomass, and leaf tannin content. Compared to previous field surveys on P. americana, our study found that the latitude trends in growth structure and defence traits were consistent. But the latitudinal trend of reproductive structure is different. Moreover, heavy metals and herbivory substantially influenced the plant's growth, reproduction, and defence mechanisms, further shaping its latitudinal patterns. CONCLUSIONS: The observed phenotypic variations in P. americana across latitudes can be largely attributed to the synergistic effects of phenotypic plasticity and genetic variation. At a broader geographical scale, adaptations to heavy metal stress and herbivory pressure among different P. americana populations involve distinct trade-offs related to growth, reproduction, and defence strategies.