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\"From celebrated genetic anthropologist Jennifer Raff comes the untold story-and fascinating mystery-of how humans migrated to the Americas\"-- Provided by publisher.

A growing number of population pharmacokinetic analyses of therapeutic monoclonal antibodies (mAbs) have been published in the scientific literature. The aims of this article are to summarize the findings from these studies and to relate the findings to the general pharmacokinetic and structural characteristics of therapeutic mAbs. A two-compartment model was used in the majority of the population analyses to describe the disposition of the mAb. Population estimates of the volumes of distribution in the central (V 1 ) and peripheral (V 2 ) compartments were typically small, with median (range) values of 3.1 (2.4–5.5) L and 2.8 (1.3–6.8) L, respectively. The estimated between-subject variability in the V 1 was usually moderate, with a median (range) coefficient of variation (CV) of 26% (12–84%). Between-subject variability in other distribution-related parameters such as the V 2 and intercompartmental clearance were often not estimated. Although the pharmacokinetic models used most frequently in the population analyses were models with linear clearance, other models with nonlinear, or parallel linear and nonlinear clearance pathways were also applied, as many therapeutic mAbs are eliminated via saturable target-mediated mechanisms. Population estimates of the maximum elimination rate (V max ) and the mAb concentration at which elimination was at half maximum for Michaelis-Menten-type elimination pathways varied considerably among the different therapeutic mAbs. However, estimates of the total clearance (CL) of mAbs with linear clearance characteristics and of the clearance of mAbs via the linear clearance pathway (CL L ) with parallel linear and nonlinear clearance were quite similar for the different mAbs and typically ranged from 0.2 to 0.5 L/day, which is relatively close to the estimated clearance of endogenous IgG of 0.21 L/day. The between-subject variability in the V max , CL and CL L was moderate to high, with estimated CVs ranging from 15% to 65%. Measures of body size were the covariates most commonly identified as influencing the pharmacokinetics of therapeutic mAbs. In summary, many features of the population pharmacokinetics of currently used therapeutic mAbs are similar, despite differences in their pharmacological targets and studied patient populations.

\"Technological innovations now allow scientists to extract and analyze ancient DNA as never before, and it has become clear--in part from David Reich's own contributions to the field--that genomics is as important a means of understanding the human past as archeology, linguistics, and the written word. Now, in [this book], Reich describes ... just how the human genome provides not only all the information that a fertilized human egg needs to develop but also contains within it the history of our species\"-- Provided by publisher.

Background Rapid and accurate detection of antibiotic heteroresistance (HR) causing clinical bacterial infections is essential for prompt and effective treatment. However, current detection methods vary across laboratories. This study aimed to evaluate a Simplified Agar-based Population Analysis Profiling (SA-PAP) method as a practical alternative to the reference Population Analysis Profiling (PAP) for HR detection, and to describe the screening performance of a modified E-test. Methods We collected 56 carbapenem-resistant Escherichia coli (CREC) and 305 methicillin-resistant Staphylococcus aureus (MRSA) clinical isolates. HR to tigecycline (in CREC), vancomycin, and teicoplanin (in MRSA) was assessed using the modified E-test, SA-PAP, and PAP (reference method). The screening performance of the modified E-test was evaluated descriptively, while the diagnostic agreement of SA-PAP with PAP was assessed using Cohen’s kappa. Results By PAP, HR prevalence was 37.5% (21/56) to tigecycline in CREC, and 34.1% (104/305) and 53.8% (163/305) to vancomycin and teicoplanin in MRSA, respectively. Compared to PAP, the modified E-test showed variable and lower sensitivities (66.7% for CREC/tigecycline, 70.2% for MRSA/vancomycin, and 48.8% for MRSA/teicoplanin), indicating a substantial risk of false-negative results. In contrast, SA-PAP demonstrated excellent agreement (Cohen’s kappa > 0.90 for all combinations) with sensitivities of 100%, 100%, and 99.4%, and specificities of 97.1%, 95.0%, and 97.9%, respectively. Conclusions Heteroresistance is highly prevalent among clinical CREC and MRSA isolates, underscoring the need for its detection. SA-PAP offers a reliable, simpler, and more economical alternative to the reference PAP method for HR confirmation. The modified E-test may serve as a rapid initial screen but has significant limitations due to its suboptimal sensitivity. Laboratories should consider adopting SA-PAP for accurate HR identification.

The oleaginous yeast Yarrowia lipolytica has the ability to use oils and fats as carbon source, making it a promising cell factory for the design of alternative bioprocesses based on renewable substrates. However, such a multiphasic bioreactor design is rather complex and leads to several constraints when considering emulsification of the oil-in-water mixture, foaming and cell growth/physiology on hydrophobic substrate. This study aims to shed light on the effect of pH changes on the physico-chemical properties of the cultivation medium and on cell physiology. It was indeed observed that at a pH value of 6, cell growth rate and intracellular lipid accumulation were optimized. Additionally, foaming was significantly reduced. In order to avoid over foaming in bioreactor, without impairing cell physiology, the use of alternative processes that can only act on the physical structure of culture medium, seems to be an effective alternative to usual chemical anti-foam agents.

Potassium‐competitive acid blockers (PCABs) are emerging alternatives to proton pump inhibitors for the treatment of acid‐related diseases. However, due to the complex, nonlinear interaction between drug exposure, food intake, and physiological rhythms, optimizing dosing strategies remains challenging. A multi‐leveled population analysis was conducted using published pharmacokinetic and pharmacodynamic data on four representative PCABs: tegoprazan, YH4808, fexuprazan, and vonoprazan. A semi‐mechanistic population PK/PD model was developed to account for food effects, circadian pH rhythms, and pH‐dependent drug absorption. A multi‐level nonlinear mixed‐effects modeling framework was implemented to capture both inter‐drug and inter‐study variability. The model successfully described the time course of plasma concentration and intragastric pH for all four PCABs under various conditions. The model identified differences in pharmacokinetics and pharmacodynamic potency between drugs (with the relative in vitro potency ranked as vonoprazan > fexuprazan > YH4808 > tegoprazan), and simulations demonstrated that both pre‐ and post‐meal administration enhanced pH control in early time period via potentially distinct mechanisms: the pre‐meal effect may arise from temporally separated contributions of food‐ and drug‐induced pH elevation, whereas the post‐meal effect is likely driven by temporally overlapping, additive actions, particularly under low‐dose or non‐steady‐state conditions. Predicted pH profiles and holding times above pH 4 closely matched reported clinical outcomes. The study demonstrates the application of a mechanistic, multi‐level population approach for cross‐drug PK/PD evaluation of PCABs. The findings support drug‐specific dose optimization and highlight the clinical relevance of food–drug interactions. The modeling approach provides a model platform for pharmacotherapy or model‐informed drug development (MIDD). Study Highlights What is the current knowledge on the topic? ○Potassium‐competitive acid blockers (PCABs) are increasingly used as alternatives to proton pump inhibitors due to their rapid onset and stable acid suppression. However, existing pharmacometric models often fail to fully integrate the complex bidirectional relationship between drug exposure and intragastric pH, particularly under variable food intake and circadian conditions. Prior models are drug‐specific and typically lack scalability across the class of PCABs. What question did this study address? ○This study aimed to determine whether a unified, mechanistic population PK/PD model—developed through a multi‐level population approach—could simultaneously describe and compare the pharmacokinetic and pharmacodynamic behavior of multiple PCABs under various clinical conditions, including food intake timing and dosing regimens. What does this study add to our knowledge? ○The study introduces a novel multi‐level population PK/PD model that incorporates circadian rhythms, food effects, and pH‐dependent absorption within a single framework. By capturing both inter‐drug and inter‐study variability, the model enables quantitative comparison of PCABs and provides mechanistic insight into drug–pH interactions. Simulation results replicate clinical pH profiles and highlight drug‐specific differences in optimal dosing strategies, particularly in the early treatment phase. How might this change drug discovery, development, and/or therapeutics? ○This integrative model offers a scalable platform for model‐informed drug development (MIDD) of current and next‐generation PCABs. It facilitates rational dose optimization by accounting for both physiological and pharmacological contributors to acid suppression. The framework may also inform trial design, improve predictability of food–drug interactions, and enable mechanistic reinterpretation of complex clinical outcomes in gastroenterology. Schematic overview of a mechanism‐based, multi‐level population model for potassium‐competitive acid blockers.

Plant traits play an important role in determining plant density and final grain yield. In this study, two related RIL populations developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for 13 plant traits under four environments. QTL were detected within population and in joint-population analysis, and compared with the result obtained in the two F 2:3 generations. Our main objective was to find identical QTL and key genetic regions valuable in further research. Totally, 318 single-population QTL, 142 pairs of digenic epistasis and 412 joint-population QTL were detected. Joint-population analysis could detect much more QTL and increase the accuracy of QTL localization. Consistent QTL across generations, environments and analysis methods were observed for five traits at four bins. QTL for plant height and ear height at bin 3.05, and for leaf area at bin 6.03–6.04 had the highest consistency across most situations. These QTL with high consistency were worthy to be put into marker-assisted selection in trait improvement and to construct near isogenic lines in further research. Maize breeding could be improved by integrating marker assisted selection and phenotypic selection.

This paper summarizes new scientific evidence supporting the hypothesis that among the many factors contributing to international development, the combination of education and health stands out as a root cause on which other dimensions of development depend. Much of this recent analysis is based on new reconstructions and projections of populations by age, sex and four levels of educational attainment for more than 120 countries using the demographic method of multi-state population dynamics. It also refers to a series of systems analytical population-development-environment case studies that comprehensively assess the role of population and education factors relative to other factors in the struggle for sustainable development. The paper also claims that most concerns about the consequences of population trends are in fact concerns about human capital, and that only by adding the 'quality' dimension of education to the traditionally narrow focus on size and age structure can some of the long-standing population controversies be resolved.

Second primary cancer (SPC) is one of the most life‐threatening late effects of childhood cancers. We investigated the incidence and survival outcomes of SPC in childhood cancer patients in Japan. Data were obtained from the population‐based Osaka Cancer Registry. Individuals diagnosed with cancer at age 0–14 years during 1975–2014 and survived 2 months or longer were followed through December 2015. The risk of developing SPC was assessed with standardized incidence ratio (SIR), excess absolute risk (EAR, per 100,000 person‐years), and cumulative incidence. Multivariable Poisson regression analysis was carried out to assess relative risks of SPC by treatment method. Survival analysis was undertaken using the Kaplan–Meier method. Of 7229 childhood cancer survivors, 101 (1.4%) developed SPC after a median of 11.6 years. Overall SIR was 5.0, which corresponded with 84.3 EAR. The cumulative incidence was 0.9%, 2.1%, and 3.4% at 10, 20, and 30 years, respectively. Among all SPCs, the type that contributed most to the overall burden was cancers in the central nervous system (EAR = 28.0) followed by digestive system (EAR = 15.1), thyroid (EAR = 8.3), and bones and joints (EAR = 7.8); median latency ranged from 2.0 years (lymphomas) to 26.6 years (skin cancers). Patients treated with radiotherapy alone were at a 2.58‐fold increased risk of developing SPC compared to those who received neither chemotherapy nor radiotherapy. Among patients who developed SPCs, 5‐year and 10‐year survival probabilities after SPC diagnosis were 61.7% and 52.0%, respectively. Risk‐based long‐term follow‐up planning is essential to inform survivorship care and help reduce the burden of SPCs in childhood cancer survivors. We investigated the incidence and survival outcomes of SPC in childhood cancer patients in Japan using the population‐based Osaka Cancer Registry. During 1975‐2015, childhood cancer patients who survived ≥2 months were at a five‐fold increased risk of developing a new cancer relative to the general population of Osaka with a median of 11.6 years of latency. Risk‐based long‐term follow‐up planning is essential to inform survivorship care and help reduce the burden of SPCs in childhood cancer survivors.

The viability of populations can be quantified with several measures, such as the probability of extinction, the mean time to extinction, or the population size. While conservation management decisions can be based on these measures, it has not yet been explored systematically if different viability measures rank species and scenarios similarly and if one viability measure can be converted into another to compare studies. To address this challenge, we conducted a quantitative comparison of eight viability measures based on the simulated population dynamics of more than 4500 virtual species. We compared (a) the ranking of scenarios based on different viability measures, (b) assessed direct correlations between the measures, and (c) explored if parameters in the simulation models can alter the relationship between pairs of viability measures. We found that viability measures ranked species similarly. Despite this, direct correlations between the different measures were often weak and could not be generalized. This can be explained by the loss of information due to the aggregation of raw data into a single number, the effect of model parameters on the relationship between viability measures, and because distributions, such as the probability of extinction over time, cannot be ranked objectively. Similar scenario rankings by different viability measures show that the choice of the viability metric does in many cases not alter which population is regarded more viable or which management option is the best. However, the more two scenarios or populations differ, the more likely it becomes that different measures produce different rankings. We thus recommend that PVA studies publish raw simulation data, which not only describes all risks and opportunities to the reader but also facilitates meta‐analyses of PVA studies. Population viability was ranked similarly in a quantitative comparison of eight measures of population viability derived from simulated population dynamics of more than 4500 virtual species. However, direct correlations between measures were weak and could not be generalized. We thus recommend that population‐viability analyses publish raw simulation data to support robust comparisons of population viabilities.