Search Results (72)

Reporting delays are a common challenge in actuarial reserving and infectious disease surveillance, where incomplete development information can distort real-time estimation and decision-making. Classical reserving methods, such as the chain ladder method, assume stable development patterns across event periods, which may be unrealistic when reporting behavior evolves over time. This paper develops a Hoerl-type state-space framework, in which development dynamics evolve as latent stochastic processes within a linear Gaussian state-space model. Estimation is conducted using the Kalman filter and Rauch-Tung-Striebel smoother, allowing recursive estimation under incomplete run-off triangles. The paper further establishes consistency and asymptotic normality for estimators of latent states, ultimate quantities, and the effective reproduction number. Simulation and empirical applications show that the proposed method performs comparably to Mack’s model under stable development patterns while providing substantially more accurate estimates of effective reproduction numbers when reporting behavior varies over time or delays remain unresolved near the boundary of the observation window. These results suggest that the proposed approach provides a flexible and theoretically grounded extension of classical actuarial reserving methods. Full article

Background/Objectives: Endometrial B-cell lymphoma 6 (BCL6) overexpression has been proposed as a marker of progesterone resistance, occult endometriosis, and endometrial dysfunction in infertile women. Its possible association with reproductive outcomes and its potential role in guiding management before embryo transfer have attracted increasing interest. However, the prognostic and clinical significance of BCL6 across infertility settings remains incompletely defined. We systematically reviewed the literature on endometrial BCL6 expression and reproductive outcomes in infertile women. Methods: This systematic review was conducted according to a prospectively registered PROSPERO protocol. Studies evaluating endometrial BCL6 expression on biopsy in infertile women were eligible if they reported reproductive outcomes or clinically relevant comparative data. Two prespecified questions were addressed: whether high or abnormal BCL6 expression is associated with poorer reproductive outcomes than low or normal expression, and whether treatment before embryo transfer improves outcomes in BCL6-positive women. Thirteen studies were included in the review. Because the included studies differed substantially in infertility phenotype, embryo context, hormonal preparation, biopsy timing, and outcome reporting, findings were synthesized narratively. Results: The available evidence suggests that abnormal or elevated endometrial BCL6 expression may be associated with poorer reproductive outcomes in some infertility populations, particularly in women with unexplained infertility undergoing IVF, although this pattern was less evident in selected euploid embryo transfer cohorts. Treatment-oriented studies suggested a possible benefit of pre-transfer medical suppression or surgical management in some BCL6-positive women, but findings were variable across studies. Supportive non-comparative and mechanistic studies further indicated that interpretation of BCL6 is influenced by hormonal preparation, endometrial context, and whether BCL6 is considered in isolation or within a broader biological or multimarker framework. Interpretation of the available evidence was constrained by the limited number of comparative studies, observational study designs, variability in clinical populations, and incomplete standardization of reproductive outcome reporting. Conclusions: Endometrial BCL6 appears biologically and clinically relevant as a marker of endometrial dysfunction in selected infertility settings, but current evidence is insufficient to support routine stand-alone clinical use or strong treatment recommendations. Its apparent prognostic and clinical utility varies across patient populations and reproductive settings. Larger prospective comparative studies with harmonized biopsy protocols, standardized outcome reporting, and independent external validation are needed to clarify the role of BCL6 in reproductive medicine. Full article

Background: Scarlet fever has seen a sharp increase in its reported incidence in China since 2011, and this study focuses on Shanghai as a representative setting to systematically investigate its transmission dynamics by analyzing age structure. It further identifies high-risk age groups and provides a theoretical foundation for prevention and non-pharmaceutical intervention strategies. Methods: We developed an SIR model that incorporates age structure and seasonality of transmission rate. In parameter estimation, the methodology of the partially observed Markov process framework is employed to derive results based on monthly data. The time-varying reproduction number $R_0\left(t\right)$ is derived monthly from the next-generation matrix. Age-specific forces of infection are estimated to identify high-risk groups and quantify how school-term-driven contact patterns modulate transmissibility. Results: The force of infection peaked in children aged 7–9 years, whereas the force of infection was highest among adults aged 35–39 years. The seasonal amplitude for transmission among school-aged groups was 39% (95% CI: 37–41%). The estimated $R_0\left(t\right)$ varied seasonally between 3.02 and 8.83. Conclusions: The transmission rate in Shanghai shows strong age heterogeneity and school-driven seasonality. Children aged 7–9 years are the highest-risk group, and interventions should target them during periods of high $R_0\left(t\right)$. Full article

Virtual acoustics enables the creation and simulation of realistic and ecologically valid indoor environments vital for hearing research and audiology. For real-time applications, room acoustics simulation requires simplifications. However, the acoustic level of detail (ALOD) necessary to capture all perceptually relevant effects remains unclear. This study examines the impact of varying ALOD in simulations of three real environments: a living room with a coupled kitchen, a pub, and an underground station. ALOD was varied by generating different numbers of image sources for early reflections, or by excluding geometrical room details specific for each environment. Simulations were perceptually evaluated using headphones in comparison to measured, real binaural room impulse responses, or by using loudspeakers. The perceived overall difference, spatial audio quality differences, plausibility, speech intelligibility, and externalization were assessed. A transient pulse, an electric bass, and a speech token were used as stimuli. The results demonstrate that considerable reductions in acoustic level of detail are perceptually acceptable for communication-oriented scenarios. Speech intelligibility was robust across ALOD levels, whereas broadband transient stimuli revealed increased sensitivity to simplifications. High-ALOD simulations yielded plausibility and externalization ratings comparable to real-room recordings under both headphone and loudspeaker reproduction. Full article

Background/Objectives: This ecological study aimed to investigate changes in the time-varying reproduction number (Rt) of SARS-CoV-2 across six regions of Massachusetts from 2020 to 2022 and to evaluate the impact of various nonpharmaceutical interventions (NPIs) implemented in 2020 by examining associated changes in the Rt. Methods: COVID-19 incident case data from the Johns Hopkins University database were adjusted for reporting delays using deconvolution and for underreporting via a Poisson-distributed multiplier of 4. Negative and zero counts were corrected using imputation. Rt was estimated using R package EpiEstim (Version 2.2-4) with a 7-day sliding window from 2020 to 2022 and with non-overlapping time windows between policy changes in 2020. Results: From 2020 to 2022, Massachusetts experienced five COVID-19 surges, linked to the wild-type strain and emerging variants, with Rt exceeding 1 during each wave and stabilizing at or dropping below 1 during low-incidence phases. School closure and gathering restrictions, the first major intervention, were associated with a 14.7% statewide reduction in Rt (95% credible interval (CrI): −23.6%, −5.6%), with greater reductions in high-density areas such as Boston (−16.9%; 95% CrI: −26.9%, −7.5%). No statistically significant changes in Rt were found to be associated with other NPIs in 2020, including the mask mandate, reopening phases, travel restrictions and quarantine requirements, and curfews. Conclusions: Our findings highlight the different NPIs’ varying impacts on COVID-19 transmission dynamics across regions in Massachusetts in 2020 and underscore the importance of early interventions for future pandemic preparedness. Full article

We present a comprehensive mathematical analysis of a within-host dual-target HIV dynamics model, which explicitly incorporates the virus’s interactions with its two primary cellular targets: CD4⁺ T cells and macrophages. The model is formulated as a system of five nonlinear delay differential equations, integrating three distinct discrete time delays to account for critical intracellular processes such as the development of productively infected cells and the maturation of new virions. We first establish the model’s biological well-posedness by proving the non-negativity and boundedness of solutions, ensuring all trajectories remain within a feasible region. The basic reproduction number, ${\mathcal{R}}_0^d$, is derived using the next-generation matrix method and serves as a sharp threshold for disease dynamics. Analytical results demonstrate that the infection-free equilibrium is globally asymptotically stable (GAS) when ${\mathcal{R}}_0^d\le 1$, guaranteeing viral eradication from any initial state. Conversely, when ${\mathcal{R}}_0^d>1$, a unique endemic equilibrium emerges and is proven to be GAS, representing a state of chronic infection. These global stability properties are rigorously established for both the non-delayed and delayed systems using carefully constructed Lyapunov functions and functionals, coupled with LaSalle’s invariance principle. A sensitivity analysis identifies viral production rates ($p_1,p_2$) and infection rates (${\beta }_1,{\beta }_2$) as the most influential parameters on ${\mathcal{R}}_0^d$, while the viral clearance rate (m) and maturation delay (${\tau }_3$) have a suppressive effect. The model is extended to evaluate antiretroviral therapy (ART), revealing a critical treatment efficacy threshold ${ϵ}^{cr}$ required to suppress the virus. Numerical simulations validate all theoretical findings and further investigate the dynamics under varying treatment efficacies and maturation delays, highlighting how these factors can shift the system from persistence to clearance. This study provides a rigorous mathematical framework for understanding HIV dynamics, with actionable insights for designing targeted treatment protocols aimed at achieving viral suppression. Full article

The literature for brown lemming (Lemmus trimucronatus) and collared lemming (Dicrostonyx groenlandicus) population cycles was revisited from Barrow, Alaska. This review covered observations and research primarily from 1946 to 1974. Much of what we know about brown lemming cycles from North America was derived from these early studies. The data for collared lemming, however, are far less extensive and only a minor part of the historical research at Barrow. Nonetheless, important information was discovered. Collectively, the historical literature is confusing and sometimes contradictory. The time intervals, amplitude, and density of lemming populations from Barrow varied greatly from year to year. For example, in most papers, 1956 was considered a lemming population high, but in a major research paper in 1993, the 1956 data was sometimes included and sometimes deleted because it did not meet an arbitrary mathematical definition of a population high. Qualitative explanations were often used to support the lemming population cycle concept when it was apparently in flux or did not exist. Other investigations suggested synchronous lemming population fluctuations over wide geographic areas did not occur, but rather were localized most of the time. Even within a specific local area, lemming densities varied with habitat. Presumably, higher densities were in higher quality habitats, but this could vary somewhat with season. It is unlikely that lemming migrations occurred; however, local movements of large numbers of lemmings were witnessed. Although many studies suggested a specific event influenced lemming population fluctuations, overall, the data suggest multiple factors acting synergistically drove the x-fold increases and x-fold decreases in lemming populations at Barrow. Other qualitative observations, and quantitative studies suggest lemming population fluctuations affect and have an effect on the survival and reproduction of other species of birds and mammals at Barrow. Brown lemmings should be considered an indicator of the health of the Arctic environment at Barrow. Clearly, population fluctuations of lemmings at Barrow existed with an average interval for peak populations of about 3.8 years, ranging from 2 to 6 years, depending on what data was included and how it was analyzed. The conundrum, however, is defining a peak. Furthermore, one must ask if an average interval between peak lemming populations is really a cycle. The data support population fluctuations; however, the four annual phases of the cycle (e.g., increase, peak, decline, low) did not repeat themselves in sequence. Overall, perhaps cycles did not exist in the strictest definition of the word at Barrow. Perhaps it is time to redefine Barrow lemming “cycles” as annual population fluctuations that exhibit patterns over time. Full article

The study aimed to evaluate regional variation in SARS-CoV-2 transmission and assess associations between public health interventions and the time-varying reproduction number (Rt) across Maine from January 2020 to February 2023. Daily confirmed COVID-19 case counts were adjusted for reporting anomalies and delays using deconvolution. Infection counts were estimated by applying a Poisson-distributed multiplier of 4 to account for underreporting. Rt was estimated using EpiEstim with a 7-day sliding window from January 2020 through February 2023. The analysis of associations between Rt and public health interventions was limited to 2020, concluding just before COVID-19 vaccines became available in Maine in December 2020. EpiEstim was parameterized with an Omicron-specific serial interval distribution (main analysis) and an early-pandemic serial interval distribution (sensitivity analysis). Maine experienced four major COVID-19 waves. Rt values fluctuated but remained close to 1 at both the statewide and district levels. No statistically significant changes in Rt were observed in association with any interventions implemented in 2020. Our findings underscore the challenges of quantifying intervention impacts in rural settings, where low incidence and sparse data can obscure the effects of interventions. This highlights the need for enhanced surveillance tools tailored to the unique constraints of rural public health contexts. Full article

This study explores the viral dynamics of SARS-CoV-2 infection within host cells by incorporating the pharmacological effects of andrographolide—a bioactive compound extracted from Andrographis paniculata, renowned for its antiviral, anti-inflammatory, and immunomodulatory properties. Through the application of mathematical modeling, the interactions among the virus, host cells, and immune responses are simulated to provide a comprehensive analysis of viral behavior over time. Two distinct models were employed to assess the impact of varying andrographolide dosages on viral load, target cell populations, and immune responses. One model revealed a clear dose–response relationship, whereas the other indicated that additional biological or pharmacological factors may modulate drug efficacy. Both models demonstrated stability, with basic reproductive numbers (R₀) suggesting the potential for viral propagation in the absence of effective therapeutic interventions. This study emphasizes the significance of understanding the pharmacokinetics (PK) and pharmacodynamics (PD) of andrographolide to optimize its therapeutic potential. The findings also underscore the necessity for further investigation into the compound’s absorption, distribution, metabolism, and excretion (ADME) characteristics, as well as its prospective applications in the treatment of not only COVID-19 but also other viral infections. Overall, the results lay a foundational framework for future experimental research and clinical trials aimed at refining andrographolide dosing regimens and improving patient outcomes. Full article

This study develops a high-dimensional impulsive differential equation model to analyze Huanglongbing (HLB) transmission dynamics, incorporating seasonal fluctuations in vector psyllid populations and multi-pronged control measures: (1) periodic removal of infected/dead citrus trees to eliminate pathogen reservoirs and (2) non-uniform pesticide applications timed to disrupt psyllid life cycles. The model analytically derives the basic reproduction number ($R_0$) and proves the existence of a unique disease-free periodic solution. Theoretical analysis reveals a threshold-dependent stability: when $R_0<1$, the disease-free solution is globally asymptotically stable, ensuring pathogen extinction; when $R_0>1$, the system becomes uniformly persistent, indicating endemic HLB. Numerical simulations validate these findings and demonstrate that integrated interventions, combining psyllid population control and removal of infected plants, can significantly suppress HLB spread. The results provide a mathematical framework for optimizing intervention timing and intensity, offering actionable strategies for citrus growers. Full article

Domestic geese are typically seasonal breeders, and the timing and number of eggs they lay vary depending on the region and breed. Previous studies evaluated the Zi goose, which is currently the domestic goose breed with the highest egg production. This research divided the reproductive cycle into four periods and compared the ovarian RNA-seq and DNA methylation data of Zi geese across these time points to identify the key genes that increase egg production. By integrating differentially expressed genes and differentially methylated genes, we identified 525 candidate genes that presented upregulated expression and hypomethylated regions (the hypo-up group). Ultimately, we found that the thyrotropin-releasing hormone degrading enzyme (TRHDE) and thyroid-stimulating hormone receptor (TSHR) genes play a crucial role in regulating the reproductive cycle of Zi geese. We also generated a proposed model of the relationship between the TRHDE and TSHR genes in Zi geese. This study provides theoretical references for the development of egg-laying goose breeds and raises additional scientific questions for further discussion among researchers. Full article

This paper introduces a novel fractional Susceptible-Infected-Recovered ($\mathbb{SIR}$) model that incorporates a power Caputo fractional derivative (PCFD) and a density-dependent recovery rate. This enhances the model’s ability to capture memory effects and represent realistic healthcare system dynamics in epidemic modeling. The model’s utility and flexibility are demonstrated through an application using parameters representative of the COVID-19 pandemic. Unlike existing fractional $\mathbb{SIR}$ models often limited in representing diverse memory effects adequately, the proposed PCFD framework encompasses and extends well-known cases, such as those using Caputo–Fabrizio and Atangana–Baleanu derivatives. We prove that our model yields bounded and positive solutions, ensuring biological plausibility. A rigorous analysis is conducted to determine the model’s local stability, including the derivation of the basic reproduction number (${\mathbf{R}}_0$) and sensitivity analysis quantifying the impact of parameters on ${\mathbf{R}}_0$. The uniqueness and existence of solutions are guaranteed via a recursive sequence approach and the Banach fixed-point theorem. Numerical simulations, facilitated by a novel numerical scheme and applied to the COVID-19 parameter set, demonstrate that varying the fractional order significantly alters predicted epidemic peak timing and severity. Comparisons across different fractional approaches highlight the crucial role of memory effects and healthcare capacity in shaping epidemic trajectories. These findings underscore the potential of the generalized PCFD approach to provide more nuanced and potentially accurate predictions for disease outbreaks like COVID-19, thereby informing more effective public health interventions. Full article

Herbivores can negatively impact plant reproduction by altering floral traits, pollination, and fruit production. To counteract this, plants developed defense mechanisms, such as the biotic defense resulting from associations with ants. The aim of this study was to investigate whether leaf herbivory at different intensities influences reproductive success and extrafloral nectar secretion patterns in a savanna plant, Banisteriopsis malifolia (Malpighiaceae). Plants were subjected to simulated leaf herbivory and divided into three groups: Control (damage < 5%), T15 (15% leaf area removed), and T50 (50% leaf area removed). Assessments continued until fruiting. The findings indicate an increase in extrafloral nectar sugar concentration after simulated herbivory. Increasing foliar damage significantly delayed the time to bloom, decreased the number of inflorescences per plant, and reduced the size of buds and flowers. Foliar damage significantly decreased fruit size. Furthermore, ant foraging was influenced by herbivory, with a predominance of aggressive ants on plants with high levels of damage. Our study shows that varying levels of leaf damage affect extrafloral nectar secretion, ant foraging behavior, and plant reproductive structures. These findings highlight how insect herbivores and the level of damage they cause influence plant fitness and consequently community structure. Full article

Meloidogyne incognita, a widely distributed plant parasite that is considered one of the most devastating species for various crops, has traditionally been controlled through the use of synthetic products. However, the risks associated with these products for human health and the environment have prompted a search for more sustainable alternatives. In this context, plant extracts rich in secondary metabolites, such as those of Tagetes zypaquirensis and Dysphania ambrosioides, have shown potential for nematode management, although their efficacy varies. This study aimed to evaluate the effect of extracts of T. zypaquirensis, Lonchocarpus urucu, D. ambrosioides, Urera laciniata, and Ricinus communis on the population of M. incognita in Selenicereus megalanthus under controlled greenhouse conditions. A completely randomized block experimental design was used with three replicates per treatment and six yellow pitahaya (or dragon fruit) plants per experimental unit. A total of 10 g of extract per plant was applied at two application times: 7 days before nematode inoculation and 7 days after. In addition, two controls were included: an absolute control, with no extract application and no nematode inoculation, and an inoculated control, consisting of plants exposed only to nematodes. The results showed that the preventive application of T. zypaquirensis and D. ambrosioides extracts 7 days before nematode inoculation significantly reduced M. incognita populations compared to the inoculated control. At 60 days, both extracts were able to reduce nematode populations and the number of nodules on roots, with reproductive factors close to 1 (1.47 and 1.50), indicating efficient control. Moreover, plants treated with these extracts showed superior growth compared to the other treatments and the inoculated control. In conclusion, the preventive application of T. zypaquirensis and D. ambrosioides extracts had a positive influence on the control of M. incognita and caused an improvement in plant growth variables. These results suggest that these botanical extracts could be adopted within integrated nematode management strategies in agriculture, contributing to sustainability and a reduction in the use of chemicals. Full article

Background: Polycystic ovary syndrome (PCOS) is the most prevalent endocrinopathy in women of reproductive age, characterized by a broad spectrum of clinical, metabolic, and ultrasound findings. Over time, ultrasound has evolved into a cornerstone for diagnosing polycystic ovarian morphology (PCOM), thanks to advances in probe technology, 3D imaging, and novel stromal markers. The recent incorporation of artificial intelligence (AI) further enhances diagnostic precision by reducing operator-related variability. Methods: We conducted a narrative review of English-language articles in PubMed and Embase using the keywords “PCOS”, “polycystic ovary syndrome”, “ultrasound”, “3D ultrasound”, and “ovarian stroma”. Studies on diagnostic criteria, imaging modalities, stromal assessment, and machine-learning algorithms were prioritized. Additional references were identified via citation screening. Results: Conventional 2D ultrasound remains essential in clinical practice, with follicle number per ovary (FNPO) and ovarian volume (OV) functioning as primary diagnostic criteria. However, sensitivity and specificity values vary significantly depending on probe frequency, cut-off thresholds (≥12, ≥20, or ≥25 follicles), and patient characteristics (e.g., adolescence, obesity). Three-dimensional (3D) ultrasound and Doppler techniques refine PCOS diagnosis by enabling automated follicle measurements, stromal/ovarian area ratio assessments, and evaluation of vascular indices correlating strongly with hyperandrogenism. Meanwhile, AI-driven ultrasound analysis has emerged as a promising tool for minimizing observer bias and validating advanced metrics (e.g., SA/OA ratio) that may overcome traditional limitations of stroma-based criteria. Conclusions: The continual evolution of ultrasound, encompassing higher probe frequencies, 3D enhancements, and now AI-assisted algorithms, has expanded our ability to characterize PCOM accurately. Nevertheless, challenges such as operator dependency and inter-observer variability persist despite standardized protocols; the integration of AI holds promise in further enhancing diagnostic accuracy. Future directions should focus on robust AI training datasets, multicenter validation, and age-/BMI-specific cut-offs to optimize the balance between sensitivity and specificity, ultimately facilitating earlier and more precise PCOS diagnoses. Full article