The application of demographic characteristics of Ectropis grisescens (Lepidoptera: Geometridae) in pest risk assessment of IPM.

Ectropis grisescens Warren is one of the most important pests of tea plants. In this study, data on the development, survival, and fecundity of E. grisescens were collected at 15, 22, and 32 °C and analyzed by using the age-stage, two-sex life table. At 15 °C, the duration of the preadult period of E. grisescens was significantly prolonged (81.06 days), with high mortality (69.0%), and the proportion of emerged female adults was extremely low (7.0%). At 32 °C, the preadult period was significantly shortened (29.12 days), with high preadult mortality (74.0%), and a low proportion of emerged female adults (15.0%). At 22 °C, with low preadult mortality (24.0%), and a high proportion of emerged female adults (26.0%). The overall effects of the shorter preadult duration, higher preadult survival rate, higher proportion of emerged female adults, higher fecundity (F = 350.88 eggs/♀), and higher net reproductive rate (R0 = 91.23 offspring/individual) at 22 °C resulted in the highest values of the intrinsic rate of increase (r = 0.1054 days-1) and finite rate of increase (λ = 1.1112 days-1). Computer simulation showed that E. grisescens populations can increase much faster at 22 °C than at 15 and 32 °C. The weighted population size and cumulative weighted insect-days provided the dynamics necessary for estimating the damage potential of E. grisescens in devising economical pest management programs. Our results demonstrate that populations of E. grisescens were able to develop at a broad range of temperatures and adapt to the high temperatures. These finding can be utilized to improve the management of E. grisescens.

Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma.

Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the approximate Bayesian computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended fourier amplitude sensitivity test. Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

Omega-3 polyunsaturated fatty acids and the psychiatric post-acute sequelae of COVID-19: A one-year retrospective cohort analysis of 33,908 patients.

BACKGROUND: Early prevention and management of psychiatric symptoms in long COVID (or post-COVID-19 conditions) are crucial for reducing long-term disability. Existing clinical guidelines recommend the use of omega-3 polyunsaturated fatty acids (PUFAs) as a promising therapeutic approach for various common psychiatric disorders due to their anti-inflammatory and neuroprotective characteristics. This study aims to investigate the potential efficacy of omega-3 PUFAs in alleviating the psychiatric sequelae following COVID-19. METHODS: This 1-year retrospective cohort study used the TriNetX electronic health records network to examine the effects of omega-3 PUFAs supplements on psychiatric sequelae in adults diagnosed with COVID-19. Using propensity-score matching, the study compared those who used omega-3 PUFAs supplements with those who did not, assessing outcomes including depression, anxiety disorders, insomnia, and other somatic conditions up to a year after COVID-19 diagnosis. RESULTS: In 16,962 patients who received omega-3 PUFAs supplements and 2,248,803 who did not, omega-3 supplementation significantly reduced the risk of developing psychiatric sequelae post-COVID-19 diagnosis (HR, 0.804; 95% CI, 0.729 to 0.888). Specifically, the risks for depression (HR, 0.828; 95% CI, 0.714 to 0.960), anxiety disorders (HR, 0.833; 95% CI, 0.743 to 0.933), and insomnia (HR, 0.679; 95% CI, 0.531 to 0.869) were reduced in the omega-3 group. This effect was consistent across sex, race, 18-59 age group, and patients with less than two doses of the COVID-19 vaccine. The omega-3 group also had a lower risk of cough and myalgia, but no significant difference was noted for other symptoms like chest pain, abnormal breathing, abdominal issues, fatigue, headache, and cognitive symptoms. CONCLUSION: Omega-3 PUFAs may require re-evaluation as a preventive strategy against adverse mental health outcomes post-COVID-19 in placebo-controlled clinical trials.

Coptisine Inhibits Influenza Virus Replication by Upregulating p21.

The activation of innate antiviral immunity is a promising approach for combatting viral infections. In this study, we screened Chinese herbs that activated human immunity and identified coptisine as a potent inhibitor of the influenza virus with an EC50 of 10.7 µM in MDCK cells. The time of an addition assay revealed that pre-treatment with coptisine was more effective at reducing viral replication than co-treatment or post-treatment. Our bulk RNA-sequencing data showed that coptisine upregulated the p21 signaling pathway in MDCK cells, which was responsible for its antiviral effects. Specifically, coptisine increased the expression of p21 and FOXO1 in a dose-dependent manner while leaving the MELK expression unchanged. Docking analysis revealed that coptisine likely inhibited MELK activity directly by forming hydrogen bonds with ASP-150 and GLU-87 in the catalytic pocket. These findings suggest that coptisine may be a promising antiviral agent that regulates the p21 signaling pathway to inhibit viral replication.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks.

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma.

Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the Approximate Bayesian Computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended Fourier Amplitude Sensitivity Test (eFAST). Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

Prolonged viral shedding from noninfectious individuals confounds wastewater-based epidemiology.

Wastewater surveillance has been widely used to track and estimate SARS-CoV-2 incidence. While both infectious and recovered individuals shed virus into wastewater, epidemiological inferences using wastewater often only consider the viral contribution from the former group. Yet, the persistent shedding in the latter group could confound wastewater-based epidemiological inference, especially during the late stage of an outbreak when the recovered population outnumbers the infectious population. To determine the impact of recovered individuals' viral shedding on the utility of wastewater surveillance, we develop a quantitative framework that incorporates population-level viral shedding dynamics, measured viral RNA in wastewater, and an epidemic dynamic model. We find that the viral shedding from the recovered population can become higher than the infectious population after the transmission peak, which leads to a decrease in the correlation between wastewater viral RNA and case report data. Furthermore, the inclusion of recovered individuals' viral shedding into the model predicts earlier transmission dynamics and slower decreasing trends in wastewater viral RNA. The prolonged viral shedding also induces a potential delay in the detection of new variants due to the time needed to generate enough new cases for a significant viral signal in an environment dominated by virus shed by the recovered population. This effect is most prominent toward the end of an outbreak and is greatly affected by both the recovered individuals' shedding rate and shedding duration. Our results suggest that the inclusion of viral shedding from non-infectious recovered individuals into wastewater surveillance research is important for precision epidemiology.

Reaction-Diffusion Modeling of E. coli Colony Growth Based on Nutrient Distribution and Agar Dehydration.

The bacterial colony is a powerful experimental platform for broad biological research, and reaction-diffusion models are widely used to study the mechanisms of its formation process. However, there are still some crucial factors that drastically affect the colony growth but are not considered in the current models, such as the non-homogeneously distributed nutrient within the colony and the substantially decreasing expansion rate caused by agar dehydration. In our study, we propose two plausible reaction-diffusion models (the VN and MVN models) based on the above two factors and validate them against experimental data. Both models provide a plausible description of the non-homogeneously distributed nutrient within the colony and outperform the classical Fisher-Kolmogorov equation and its variation in better describing experimental data. Moreover, by accounting for agar dehydration, the MVN model captures how a colony's expansion slows down and the change of a colony's height profile over time. Furthermore, we demonstrate the existence of a traveling wave solution for the VN model.

Divergent total synthesis of the revised structures of marine anti-cancer meroterpenoids (+)-dysiherbols A-E.

We report here a concise and divergent enantioselective total synthesis of the revised structures of marine anti-cancer sesquiterpene hydroquinone meroterpenoids (+)-dysiherbols A-E (6-10) using dimethyl predysiherbol 14 as a key common intermediate. Two different improved syntheses of dimethyl predysiherbol 14 were elaborated, one starting from Wieland-Miescher ketone derivative 21, which is regio- and diastereoselectively α-benzylated prior to establishing the 6/6/5/6-fused tetracyclic core structure through intramolecular Heck reaction. The second approach exploits an enantioselective 1,4-addition and a Au-catalyzed double cyclization to build-up the core ring system. (+)-Dysiherbol A (6) was prepared from dimethyl predysiherbol 14via direct cyclization, while (+)-dysiherbol E (10) was synthesized through allylic oxidation and subsequent cyclization of 14. Epoxidation of 14 afforded allylic alcohol 45 or unexpectedly rearranged homoallylic alcohol 44. By inverting the configuration of the hydroxy groups, exploiting a reversible 1,2-methyl shift and selectively trapping one of the intermediate carbenium ions through oxy-cyclization, we succeeded to complete the total synthesis of (+)-dysiherbols B-D (7-9). The total synthesis of (+)-dysiherbols A-E (6-10) was accomplished in a divergent manner starting from dimethyl predysiherbol 14, which led to the revision of their originally proposed structures.

The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19.

We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.

Traveling wave speed and profile of a "go or grow" glioblastoma multiforme model.

Glioblastoma multiforme (GBM) is a fast-growing and deadly brain tumor due to its ability to aggressively invade the nearby brain tissue. A host of mathematical models in the form of reaction-diffusion equations have been formulated and studied in order to assist clinical assessment of GBM growth and its treatment prediction. To better understand the speed of GBM growth and form, we propose a two population reaction-diffusion GBM model based on the 'go or grow' hypothesis. Our model is validated by in vitro data and assumes that tumor cells are more likely to leave and search for better locations when resources are more limited at their current positions. Our findings indicate that the tumor progresses slower than the simpler Fisher model, which is known to overestimate GBM progression. Moreover, we obtain accurate estimations of the traveling wave solution profiles under several plausible GBM cell switching scenarios by applying the approximation method introduced by Canosa.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Which Severe Mental Illnesses Most Increase the Risk of Developing Dementia? Comparing the Risk of Dementia in Patients with Schizophrenia, Major Depressive Disorder and Bipolar Disorder

Objective@#Previous studies have shown that certain severe mental illnesses (SMIs) increase the risk of dementia, but those that increase the risk to a greater degree in comparison with other SMIs are unknown. Furthermore, physical illnesses may alter the risk of developing dementia, but these cannot be well-controlled. @*Methods@#Using the Taiwan National Health Insurance Research Database, patients with schizophrenia, bipolar disorder and major depressive disorder (MDD) were recruited. We also recruited normal healthy subjects as the control group.All subjects were aged over 60 years, and the duration of follow-up was from 2008 to 2015. Multiple confounders were adjusted, including physical illnesses and other variables. Use of medications, especially benzodiazepines, was analyzed in a sensitivity analysis. @*Results@#36,029 subjects (MDD: 23,371, bipolar disorder: 4,883, schizophrenia: 7,775) and 108,084 control subjects were recruited after matching according to age and sex. The results showed that bipolar disorder had the highest hazard ratio (HR) (HR: 2.14, 95% confidence interval [CI]: 1.99−2.30), followed by schizophrenia (HR: 2.06, 95% CI: 1.93−2.19) and MDD (HR: 1.60, 95% CI: 1.51−1.69). The results remained robust after adjusting for covariates, and sensitivity analysis showed similar results. Anxiolytics use did not increase the risk of dementia in any of the three groups of SMI patients. @*Conclusion@#SMIs increase the risk of dementia, and among them, bipolar disorder confers the greatest risk of developing dementia. Anxiolytics may not increase the risk of developing dementia in patients with an SMI, but still need to be used with caution in clinical practices.

Treatment Retention Rates of 3-monthly Paliperidone Palmitate and Risk Factors Associated with Discontinuation: A Population-based Cohort Study

Objective@#Limited evidence exists regarding real-world 3-monthly paliperidone palmitate (PP3M) treatment retention and associated factors. @*Methods@#We conducted a retrospective, nationwide cohort study using the Taiwan National Health Insurance Research Database between October 2017 and December 2019. Adult patients with schizophrenia initiated on PP3M were enrolled. The primary outcomes were time to PP3M discontinuation, time to psychiatric hospitalization, and the proportions of patients receiving the next PP3M dose within 120 days among first-, second-, and third-dose completers. Key covariates included prior PP1M duration and adequate PP3M initiation. @*Results@#The PP3M treatment retention rates were 79.7%, 66.3%, and 52.5% after 6, 12, and 24 months, respectively, with 86.4%, 90.6%, and 90.0% of respective first-, second-, and third-dose completers receiving the next PP3M dose. Adequate PP3M initiation and prior PP1M treatment duration ＞ 180 days were associated with favorable PP3M treatment retention. In multivariate analyses, PP1M durations of 180−360 days (adjusted relative risk [aRR], 1.76) or ＜ 180 days (aRR, 2.79) were associated with PP3M discontinuation at the second dose. Inadequate PP3M initiation was associated with discontinuation at the third dose (aRR, 2.18). Patients fully adherent to PP3M treatment in the first year had a higher probability of being free from psychiatric hospitalization (86.7% at 2 years), compared with those partially adherent or non-adherent to PP3M in the first year. @*Conclusion@#Prior PP1M duration and adequate PP3M initiation are major factors affecting PP3M treatment retention. Higher PP3M treatment retention is associated with a lower risk of psychiatric hospitalization.

Harm Avoidance is Correlated with the Reward System in Adult Patients with Attention Deficit Hyperactivity Disorder: A Functional Magnetic Resonance Imaging Study

Objective@#Hypoactivity in the reward system among patients with attention deficit hyperactivity disorder (ADHD) is a well-known phenomenon. Whether the activity in the reward pathway is related to harm avoidance, such as in sensitivity to punishment, is unclear. Evidence regarding the potential difference between ADHD patients and controls in terms of this association is scarce. @*Methods@#Event-related functional magnetic resonance imaging was conducted on subjects performing the Iowa gambling test. Fourteen adults with ADHD and 14 controls were enrolled in the study. @*Results@#Harm avoidance was found to be positively correlated with the activities of the bilateral orbitofrontal cortex and right insula in individuals with ADHD. A group difference was also confirmed. @*Conclusion@#Understanding the roles of harm avoidance and brain activation during risk tasks is important.

Chemically mediated rheotaxis of endangered tri-spine horseshoe crab: potential dispersing mechanism to vegetated nursery habitats along the coast.

Background: An enhanced understanding of larval ecology is fundamental to improve the management of locally depleted horseshoe crab populations in Asia. Recent studies in the northern Beibu Gulf, China demonstrated that nesting sites of Asian horseshoe crabs are typically close to their nursery beaches with high-density juveniles distributed around mangrove, seagrass and other structured habitats. Methods: A laboratory Y-maze chamber was used to test whether the dispersal of early-stage juvenile tri-spine horseshoe crab Tachypleus tridentatus is facilitated by chemical cues to approach suitable nursery habitats. The juvenile orientation to either side of the chamber containing controlled seawater or another with various vegetation cues, as well as their movement time, the largest distance and displacement were recorded. Results: The juveniles preferred to orient toward seagrass Halophila beccarii cues when the concentration reached 0.5 g l-1, but ceased at 2 g l-1. The results can be interpreted as a shelter-seeking process to get closer to the preferred settlement habitats. However, the juveniles exhibited avoidance behaviors in the presence of mangrove Avicennia marina and invasive saltmarsh cordgrass Spartina alterniflora at 2 g l-1. The juveniles also spent less time moving in the presence of the A. marina cue, as well as reduced displacement in water containing the S. alterniflora cue at 1 and 2 g l-1. These results may explain the absence of juvenile T. tridentatus within densely vegetated areas, which have generally higher organic matter and hydrogen sulfide. Conclusion: Early-stage juvenile T. tridentatus are capable of detecting and responding to habitat chemical cues, which can help guide them to high-quality settlement habitats. Preserving and restoring seagrass beds in the intertidal areas should be prioritized when formulating habitat conservation and management initiatives for the declining horseshoe crab populations.

Glycyrrhizin Inhibits SARS-CoV-2 Entry into Cells by Targeting ACE2.

Coronavirus Disease 2019 (COVID-19) is a highly infectious and pathogenic disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early in this epidemic, the herbal formulas used in traditional Chinese medicine (TCM) were widely used for the treatment of COVID-19 in China. According to Venn diagram analysis, we found that Glycyrrhizae Radix et Rhizoma is a frequent herb in TCM formulas against COVID-19. The extract of Glycyrrhizae Radix et Rhizoma exhibits an anti-SARS-CoV-2 replication activity in vitro, but its pharmacological mechanism remains unclear. We here demonstrate that glycyrrhizin, the main active ingredient of Glycyrrhizae Radix et Rhizoma, prevents the coronavirus from entering cells by targeting angiotensin-converting enzyme 2 (ACE2). Glycyrrhizin inhibited the binding of the spike protein of the SARS-CoV-2 to ACE2 in our Western blot-based assay. The following bulk RNA-seq analysis showed that glycyrrhizin down-regulated ACE2 expression in vitro which was further confirmed by Western blot and quantitative PCR. Together, we believe that glycyrrhizin inhibits SARS-CoV-2 entry into cells by targeting ACE2.

Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth.

The growth rate hypothesis (GRH) posits that variation in organismal stoichiometry (C:P and N:P ratios) is driven by growth-dependent allocation of P to ribosomal RNA. The GRH has found broad but not uniform support in studies across diverse biota and habitats. We synthesise information on how and why the tripartite growth-RNA-P relationship predicted by the GRH may be uncoupled and outline paths for both theoretical and empirical work needed to broaden the working domain of the GRH. We found strong support for growth to RNA (r2  = 0.59) and RNA-P to P (r2  = 0.63) relationships across taxa, but growth to P relationships were relatively weaker (r2  = 0.09). Together, the GRH was supported in ~50% of studies. Mechanisms behind GRH uncoupling were diverse but could generally be attributed to physiological (P accumulation in non-RNA pools, inactive ribosomes, translation elongation rates and protein turnover rates), ecological (limitation by resources other than P), and evolutionary (adaptation to different nutrient supply regimes) causes. These factors should be accounted for in empirical tests of the GRH and formalised mathematically to facilitate a predictive understanding of growth.

High Accuracy Indicators of Androgen Suppression Therapy Failure for Prostate Cancer-A Modeling Study.

Prostate cancer is a serious public health concern in the United States. The primary obstacle to effective long-term management for prostate cancer patients is the eventual development of treatment resistance. Due to the uniquely chaotic nature of the neoplastic genome, it is difficult to determine the evolution of tumor composition over the course of treatment. Hence, a drug is often applied continuously past the point of effectiveness, thereby losing any potential treatment combination with that drug permanently to resistance. If a clinician is aware of the timing of resistance to a particular drug, then they may have a crucial opportunity to adjust the treatment to retain the drug's usefulness in a potential treatment combination or strategy. In this study, we investigate new methods of predicting treatment failure due to treatment resistance using a novel mechanistic model built on an evolutionary interpretation of Droop cell quota theory. We analyze our proposed methods using patient PSA and androgen data from a clinical trial of intermittent treatment with androgen deprivation therapy. Our results produce two indicators of treatment failure. The first indicator, proposed from the evolutionary nature of the cancer population, is calculated using our mathematical model with a predictive accuracy of 87.3% (sensitivity: 96.1%, specificity: 65%). The second indicator, conjectured from the implication of the first indicator, is calculated directly from serum androgen and PSA data with a predictive accuracy of 88.7% (sensitivity: 90.2%, specificity: 85%). Our results demonstrate the potential and feasibility of using an evolutionary tumor dynamics model in combination with the appropriate data to aid in the adaptive management of prostate cancer.

[Health economic evaluation of four prenatal screening strategies for Down syndrome in Changsha, China].

OBJECTIVE: To compare the clinical application and health economic values of non-invasive prenatal testing (NIPT) and second trimester serum screening (STSS). METHODS: A retrospective analysis was carried out on 54 026 singleton pregnant women undergoing NIPT and STSS from March 1, 2018 to December 31, 2019 in Changsha Maternal and Child Health Care Hospital. For pregnant women with high-risk results of NIPT, prenatal diagnosis and follow-up of pregnancy outcomes were conducted. The data was grouped to 4 screening models, and their cost-benefit was analyzed. RESULTS: The sensitivity, specificity and positive predictive value of NIPT were all higher than STSS. Screening models 1 to 4 have prevented the birth of 71, 29, 52 and 54 patients with Down syndrome, respectively. The safety index of screening models 1 to 4 were 0.0036, 0.3944, 02215 and 0.1281, respectively. When the price of NIPT was decreased to 600 RMB, the cost-benefit of the screening models 1 to 4 was 0.46, 0.65, 0.44 and 0.40 million RMB, respectively. CONCLUSION: NIPT has a better detection performance than STSS. When the price of NIPT is 600 RMB, screening model 1 has the best screening effect and the highest accuracy, safety index and health economical value.