Relative Population Research Articles

Population Power Curves in ASCA With Permutation Testing

ABSTRACTIn this paper, we revisit the power curves in ANOVA simultaneous component analysis (ASCA) based on permutation testing and introduce the population curves derived from population parameters describing the relative effect among factors and interactions. The relative effect has important practical implications: The statistical power of a given factor depends on the design of other factors in the experiment and not only of the sample size. Thus, understanding the relative power in a specific experimental design can be extremely useful to maximize our capability of success when planning the experiment. In the paper, we derive relative and absolute population curves, where the former represent statistical power in terms of the normalized effect size between structure and noise, and the latter in terms of the sample size. Both types of population curves allow us to make decisions regarding the number and nature (fixed/random) of factors, their relationships (crossed/nested), and the number of levels and replicates, among others, in an multivariate experimental design (e.g., an omics study) during the planning phase of the experiment. We illustrate both types of curves through simulation.

Abietane diterpenoid salvipisone: Structure elucidation, conformational analysis, and antimicrobial activity

Salvipisone, an abietane diterpenoid, was isolated from the roots of Salvia aethiopis L. using a combination of chromatographic separation techniques. Its structure was elucidated employing a variety of spectroscopic methods, including ultraviolet (UV), infrared (IR), 1D and 2D nuclear magnetic resonance (NMR), and mass spectrometry. A comprehensive analysis of experimental 1D and 2D NMR data, incorporating 1H iterative full spin analysis and higher-order multiplet simulation, revealed discrepancies with previously reported NMR data for this compound. Detailed examination of the 1H NMR spectrum's spin-spin coupling structure provided insights into the relative populations of the three staggered conformers around the C12–C13 bond at room temperature. The conformer populations were determined using the relationship between the experimental values for vicinal coupling constants and the estimated ones for the preferred staggered conformers, yielding a ratio of approx. 80:4:16 for anti, gauche, and gauche′-conformers, respectively. Possible reasons for the observed unevenly populated staggered conformers were also discussed. The antimicrobial activity of salvipisone was evaluated using in vitro and in silico methods. In vitro antimicrobial assays demonstrated that salvipisone exhibited the highest inhibitory effect against Staphylococcus aureus ATCC and Enterococcus faecalis ATCC (MIC = 3.125 μg/mL), followed by Bacillus subtilis ATCC (MIC = 6.25 μg/mL). In contrast, concentrations above 100 μg/mL were necessary to inhibit Escherichia coli ATCC and Klebsiella pneumoniae ATCC. In silico studies suggested that salvipisone, particularly its keto form, has significant potential for inhibiting the enzyme gyrase, highlighting its mechanism of antimicrobial action. Our findings highlight the promising antimicrobial and inhibitory properties of salvipisone, particularly against Gram-positive bacteria such as S. aureus.

A novel method for cell deconvolution using DNA methylation in PCA space

BackgroundIn this study, we present a novel method for reference-based cell deconvolution using data from DNA methylation arrays. Different from existing methods like IDOL-Ext, which operate on probe-level data, our approach represents features in the principal component analysis (PCA) space for cell type deconvolution.ResultsOur method’s accuracy in estimating cell compositions is validated across various public datasets, including blood samples from glioma patients. It demonstrates precision comparable to IDOL-Ext, with R2 values ranging from 0.73 to 0.99 for most cell types, while offering improved discrimination between similar cell types, particularly T cell subtypes in glioma patient samples (R2 0.42–0.75 vs. 0.36–0.66 for IDOL-Ext). However, both methods showed lower accuracy for certain cell types, such as memory CD8 T cells in glioma patients (R2 0.42 vs. 0.36 for IDOL-Ext), highlighting the challenges in distinguishing closely related cell populations. We have made this method available as an R package “BloodCellDecon” on GitHub.ConclusionsOur study confirms the efficacy of cell type deconvolution in PCA space. The results indicate wide-ranging applicability and potential for adaptation to other forms of genomic data.

Weak Ergodicity in G-NHMS

In the present we provide the definition of the new concept of the General Non-Homogeneous Markov System (G-NHMS) and establish the expected population structure of a NHMS in the various states. These results will be the basis to build on the new concepts and the basic theorems of what follows.We then establish the set of all possible expected relative distributions of the initial number of memberships at time t and all possible expected relative distributions of the expansion memberships at time t. We call this set the general expected relative population structure in the states of a G-NHMS. We then proceed by providing the new definitions of weak ergodicity in a G-NHMS and weak ergodicity with a geometrical rate of convergence. We then prove the Theorem 4 which is a new building block in the theory of G-NHMS. We also prove a similar theorem under the assumption that relative expansion of the population vanishes at infinity.We then provide a generalization of the coupling theorem for populations. We proceed then to study the asymptotic behavior of a G-NHMS when the input policy consists of independent non-homogeneous Poisson variates for each time interval t-1,t\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( t-1,t\\right] $$\\end{document}. It is founded in Theorem 7 that it displays a kind of weak ergodicity behavior, that is, it converges at each step to the row of a stable matrix. This row is independent of the initial distribution and of the asymptotic input policy unlike the results in previous works. Hence it generalizes the result in that works. Finally we illustrate our results numerically for a manpower system with three states.

Energetics and spectroscopic studies of clusters and the temperature dependencies of the isomers: An approach based on a combined recipe of parallel tempering and quantum chemical methods.

A system associated with several number of weak interactions supports numerous number of stable structures within a narrow range of energy. Often, a deterministic search method fails to locate the global minimum geometry as well as important local minimum isomers for such systems. Therefore, in this work, the stochastic search technique, namely parallel tempering, has been executed on the quantum chemical surface of the system for -8 to generate global minimum as well as several number of local minimum isomers. IR spectrum can act as the fingerprint property for such system to be identified. Thus, IR spectroscopic features have also been included in this work. Vertical detachment energy has also been calculated to obtain clear information about number of water molecules in several spheres around the central anion. In addition, in a real experimental scenario, not only the global but also the local minimum isomers play an important role in determining the average value of a particular physically observable property. Therefore, the relative conformational populations have been determined for all the evaluated structures for the temperature range between 20K and 400K. Further to understand the phase change behavior, the configurational heat capacities have also been calculated for different sizes.

Exploring Uncharted Territory: Spectroscopic Evidence on a Novel Tetrel Bond with -C≡C- Triple Bond.

This study presents an investigation of the 2-butynyl alcohol···CO2 adduct, combining pulsed jet Fourier transform microwave spectroscopy with quantum chemical calculations. Two distinct isomers have been observed in the pulsed jet with a relative population ratio of 3/2. It marks the first instance of microwave spectroscopic evidence, to the best of our knowledge, suggesting the existence of a CCO2···π-C≡C- tetrel bond (π-C≡C-···π*CO2 interaction) in both observed isomers. This study highlights the importance of noncovalent interactions involving CO2 in reactant complexes, paving the way for more efficient applications of CO2 by understanding the physical basis of these noncovalent bonds.

Incorporating density‐dependent regulation into impact assessments for seabirds

Abstract Many industries are required to perform population viability analysis (PVA) during the consenting process for new developments to establish potential impacts on protected populations. However, these assessments rarely account for density‐dependent regulation of demographic rates. Excluding density‐dependent regulation from PVA‐based impact assessments is often assumed to provide a maximum estimate of impact and therefore offer a precautionary approach to assessment. However, there is also concern that this practice may unnecessarily impede the development of important industries, such as offshore renewable energy. In this study, we assess density‐dependent regulation of breeding success in 31 populations of seabird. We then quantify the strength and form of this regulation using eight different formulations. Finally, we use PVA to examine how each formulation influences the recreation of observed dynamics (i.e. model validation), as well as the predicted absolute and relative population response to an extrinsic threat (i.e. model projection). We found evidence of both negative (n = 3) and positive (n = 5) regulation of seabird breeding success. In populations exhibiting negative regulation, excluding density‐dependent regulation from PVA‐based impact assessment allowed uncontrolled population growth, such that model outcomes became biologically implausible. By contrast, in populations exhibiting positive regulation, excluding density‐dependent regulation provided an appropriate reconstruction of observed dynamics, but population decline was underestimated in some populations. We find that multiple formulations of density dependence perform comparably at the detection, validation and projection stages of analysis. However, we tentatively recommend using a log‐linear or Weibull distribution to describe density‐dependent regulation of seabird breeding success in impact assessments to balance accuracy with caution. Finally, we show that relative PVA metrics of impact assessment cannot necessarily be used to overcome PVA misspecification by assuming density independence in positively regulated populations. Synthesis and applications: We suggest that a density‐dependent approach when performing PVA‐based assessments for seabird populations will prevent biologically unrealistic, unconstrained population growth and therefore ensure meaningful PVA metrics in populations experiencing negative regulation. It will also maintain a precautionary approach for populations experiencing positive regulation, crucial when estimating impacts for these more vulnerable populations. These conclusions have immediate international application within the consenting processes for marine industries.

Variable Craniofacial Shape and Development among Multiple Cave-Adapted Populations of Astyanax mexicanus.

Astyanax mexicanus is a freshwater fish species with blind cave morphs and sighted surface morphs. Like other troglodytic species, independently evolved cave-dwelling A. mexicanus populations share several stereotypic phenotypes, including the expansion of certain sensory systems, as well as the loss of eyes and pigmentation. Here, we assess the extent to which there is also parallelism in craniofacial development across cave populations. Since multiple forces may be acting upon variation in the A. mexicanus system, including phylogenetic history, selection, and developmental constraint, several outcomes are possible. For example, eye regression may have triggered a conserved series of compensatory developmental events, in which case we would expect to observe highly similar craniofacial phenotypes across cave populations. Selection for cave-specific foraging may also lead to the evolution of a conserved craniofacial phenotype, especially in regions of the head directly associated with feeding. Alternatively, in the absence of a common axis of selection or strong developmental constraints, craniofacial shape may evolve under neutral processes such as gene flow, drift, and bottlenecking, in which case patterns of variation should reflect the evolutionary history of A. mexicanus. Our results found that cave-adapted populations do share certain anatomical features; however, they generally did not support the hypothesis of a conserved craniofacial phenotype across caves, as nearly every pairwise comparison was statistically significant, with greater effect sizes noted between more distantly related cave populations with little gene flow. A similar pattern was observed for developmental trajectories. We also found that morphological disparity was lower among all three cave populations versus surface fish, suggesting eye loss is not associated with increased variation, which would be consistent with a release of developmental constraint. Instead, this pattern reflects the relatively low genetic diversity within cave populations. Finally, magnitudes of craniofacial integration were found to be similar among all groups, meaning that coordinated development among anatomical units is robust to eye loss in A. mexicanus. We conclude that, in contrast to many conserved phenotypes across cave populations, global craniofacial shape is more variable, and patterns of shape variation are more in line with population structure than developmental architecture or selection.

Measurement of the fluorescence decay rate of 2 PJ3 positronium

The fluorescence decay rate of 2 PJ3 positronium (Ps) atoms [Γfl] has been experimentally determined using a Stark-mixing technique. Ground-state Ps atoms were optically excited in an electric field to states containing both 2 PJ3 and 23S1 components. The relative state populations were controlled via an applied mixing electric field, and a larger, pulsed, electric field was used to induce rapid quenching of the system after a fixed time delay. The dependence of the quenching signal on the mixing field strength was used to determine the relative and populations of the mixed states, whose decay rates are determined by the intrinsic self-annihilation and fluorescence decay rates. The measurements were compared to a trajectory simulation and Stark-mixing model, using the fluorescence decay rate as a free parameter. By finding the best agreement between the data and simulations we obtain Γfl=299±25µs−1, which is consistent with the mean theoretical value of 313.343±0.003µs−1. Published by the American Physical Society 2024

Computational Analysis of Ion Clustering Statistics in Liquid Battery Electrolytes

The transport properties of liquid battery electrolytes critically depend on molecular-level solvation structures of ions. In contrast to the dilute regime where the majority of counterions are sufficiently separated spatially, in global or localized high-concentrated electrolytes (HCEs) counterions tend to form superstructures such as contact-ion pairs (CIPs) or aggregates (AGGs). The presence and relative population of such superstructures can drastically change the ionic transport behavior in liquid electrolytes. We have developed a computer program [1] that can efficiently perform analysis of ion clustering statistics from molecular dynamics simulations, complementary to experimental measurements. We have successfully applied our method to various systems, including (1) a prototypical concentrated liquid electrolyte (Li:EC:DEC) [2], and (2) a series of newly developed high-entropy liquid electrolytes [3]. In both cases, we find consistent agreements between our prediction and experimentally measured nanostructures and solvation strengths. We envision that our method would be widely applicable to generic structurally disordered systems.[1] Cohen et al., Journal of Open Source Software 8, 84 (2023)[2] Xie and Wang et al., Science Advances 9, eadc9721 (2023)[3] Kim and Wang et al. Nature Energy 8, 814–826 (2023)

An Epidemiological Assessment of SARS-CoV-2 in the Sewage System of a Higher Education Institution.

Background: The World Health Organization declared the end of the COVID-19 pandemic in May 2023, three years after the adoption of global emergency measures. Monitoring of SARS-CoV-2 in sewage underscores its importance due to its effectiveness and cost-effectiveness, highlighting the need to prioritize research on water resources and sanitation. Objectives: The aim of this study was to conduct an epidemiological assessment of SARS-CoV-2 in the sewage system of a higher education institution located in Vitória Espírito Santo State, Maruípe campus. Methods: Over a period of 66 days, from February 6 to April 12, 2023, 15 samples were collected. Each sample consisted of 1 L, collected in 1 hour, with 250 mL collected every 15 minutes. The samples were characterized by assessing their appearance, and pH was measured using a Horiba U-50 multiparameter probe. The extracted RNA was subjected to RT-qPCR using the Allplex™ 2019-nCovAssay Seegene kit. Results: The samples exhibited a cloudy appearance with impurities, and the pH ranged from 6.35 to 8.17. Among the evaluated samples, SARS-CoV-2 RNA was detected in two, and, by comparing this with the epidemiological bulletin issued by the State Health Department, an increase in cases in the state was observed during the collection period of these samples. Conclusions: Sewage monitoring proved to be an important tool in this post-pandemic period, serving as an alert and prevention mechanism for the population in relation to new outbreaks. Furthermore, it represents a low-cost mapping strategy and extensive testing of a population, aligning with the studies presented at the beginning of the pandemic. We recommend specific adjustments considering distinct populations.

Machine Learning and Statistical Shape Modelling Methodologies to Assess Vascular Morphology before and after Aortic Valve Replacement.

Introduction: Statistical shape modelling (SSM) is used to analyse morphology, discover qualitatively and quantitatively unique shape features within a population, and generate mean shapes and shape modes that show morphological variability. Hierarchical agglomerative clustering is a machine learning analysis used to identify subgroups within a given population in relation to shape features. We tested the application of both methods in the clinically relevant scenario of patients undergoing aortic valve repair (AVR). Every year, around 5000 patients undergo surgical AVR in the UK. Aims: Evaluate aortic morphology and identify subgroups amongst patients who had undergone AVR, including Ozaki, Ross, and valve-sparing procedures using SSM and unsupervised hierarchical clustering analysis. This methodological framework can evaluate both pre- and post-surgical variability across subgroups undergoing different surgeries. Methods: Pre- (n = 47) and post- (n = 35) operative three-dimensional (3D) aortic models were reconstructed from computed tomography (CT) and cardiac magnetic resonance (CMR) images. Computational analyses for SSM and hierarchical clustering were run separately for the two subgroups, assessing (a) ascending aorta only and (b) the whole aorta. This allows for exploring possible variations in morphological classification related to the input shape. Results: Most patients in the Ross procedure subgroup exhibited differences in aortic morphology from other subgroups, including an elongated ascending and wide aortic arch pre-operatively, and an elongated ascending aorta with a slightly enlarged sinus post-operatively. In hierarchical clustering, the Ross aortas also appeared to cluster together compared to the other surgical procedures, both pre-operatively and post-operatively. There were significant differences between clusters in terms of clustering distance in the pre-operative analyses (p = 0.003 for ascending aortas, p = 0.016 for whole aortas). There were no significant differences between the clusters in post-operative analyses (p = 0.47 for ascending, p = 0.19 for whole aorta). Conclusions: We demonstrated the feasibility of evaluating aortic morphology before and after different aortic valve surgeries using SSM and hierarchical clustering. This framework could be used to further explore shape features associated with surgical decision-making pre-operatively and, importantly, to identify subgroups whose morphology is associated with poorer clinical outcomes post-operatively. Statistical shape modelling (SSM) and unsupervised hierarchical clustering are two statistical methods that can be used to assess morphology, show morphological variations, with the latter being able to identify subgroups within a population. These methods have been applied to the population of aortic valve replacement (AVR) patients since there are different surgical procedures (traditional AVR, Ozaki, Ross, and valve-sparing). The aim is to evaluate aortic morphology and identify subgroups within this population before and after surgery. Computed tomography and cardiac magnetic resonance images were reconstructed into 3D models of the ascending aorta and whole aorta, which were then input into SSM and hierarchical clustering. The results show that the Ross aortic morphology is quite different from the other aortas. The clustering did not classify the aortas based on the surgical procedures; however, most of the Ross group did cluster together, indicating low variability within this surgical group.

Revisiting the IR Spectra of H2S in an Argon Matrix: Identification of (H2S)n (n ≤ 4) Clusters via the Spectral Assignment of νS-H Transitions.

Small-molecular clusters of H2S up to tetramer have been experimentally identified in a cold and solid argon matrix by the spectral assignment of νS-H fundamental transitions for different H2S:argon mixing ratios. Normal-mode frequency calculations at the MP2-CP/aug-cc-pV(Q + d)Z level have been used to support the spectral assignments. In addition, modulations in relative populations of different clusters due to the annealing of the deposited matrix and the preheating of the H2S-argon gas mixture before deposition reinforced the spectral assignments. Variations in mixing ratio, annealing of the matrix, and preheating of the gas mixture have also been used, in a combined manner, to unambiguously identify the ν1 and ν3 bands of the H2S monomer, which has been a matter of dispute for a long period. The two bands have been identified at 2634.4 and 2648.0 cm-1, respectively, while three bands at 2581.5, 2568.4, and 2547.6 cm-1 have been assigned to H-bonded dimers, cyclic trimers, and cyclic tetramers, respectively. Multiple bands within 2550-2580 cm-1 have been assigned to caged tetramers. The cooperative strengthening of S-H···S H bonds in cyclic H2S clusters was evident from the linear increment in νS-H spectral shifts with cluster size.

Growth and biomass of Wolffia arrhiza with different sources of organic fertilizer

Wolffia arrhiza has a growth rate and biomass as well as a good nutritional content for the growth of cultivated fish, especially herbivorous fish. Due to the high protein content (up to 45% of the dry weight), Wolffia is an excellent plant for the production of various biologically active substances, especially proteins. These plants can double every 1-6 days, similar to algae or mushrooms, and the number of leaves doubles every 2-3 days. This study aims to determine the effect of different fertilizer sources on doubling time, relative growth rate, population density and biomass of Wolffia arrhiza and water quality. The method used in this research is experimental. The research design used a completely randomized design (CRD) consisting of 4 treatments and 3 replications. The treatments were as follows: treatment A: chicken manure, B: cow manure, C: buffalo manure and D: goat manure with each dose of 200 grams. Parameters observed included doubling time, relative growth rate, population density, biomass and water quality parameters. The results showed that treatment B (cow manure) gave the highest value for doubling time, 1.59 days, relative growth rate 0.392 g/day, population density 209.75 ind/cm2, biomass 94.97. Keyword: Biomass; Fertilizer; Growth; Wolffia

Reverse engineering control of the relative phase and populations of two-level quantum systems

Reverse engineering control of the relative phase and populations of two-level quantum systems

Experimental and Theoretical Study of the Reaction of F2 with Thiirane.

The kinetics of the F2 reaction with thiirane (C2H4S) was studied for the first time in a flow reactor combined with mass spectrometry at a total helium pressure of 2 Torr and in the temperature range of 220 to 800 K. The rate constant of the title reaction was determined under pseudo-first-order conditions, either monitoring the kinetics of F2 or C2H4S consumption in excess of thiirane or of F2, respectively: k1 = (5.79 ± 0.17) × 10-12 exp(-(16 ± 10)/T) cm3 molecule-1 s-1 (the uncertainties represent precision of the fit at the 2σ level, with the total 2σ relative uncertainty, including statistical and systematic errors on the rate constant being 15% at all temperatures). HF and CH2CHSF were identified as primary products of the title reaction. The yield of HF was measured to be 100% (with an accuracy of 10%) across the entire temperature range of the study. Quantum computations revealed reaction enthalpies ranging from -409.9 to -509.1 kJ mol-1 for all the isomers/conformers of the products, indicating a strong exothermicity. Boltzmann relative populations were then established for different temperatures.

Effects of seasonal temperature fluctuations and social factors on the transmission of malaria

AIM: To conduct a retrospective analysis of the incidence of malaria episodes in the Astrakhan region from 2002 to 2022 in relation to climatic and social factors in order to provide the evidence for development of effective preventive measures. MATERIAL AND METHODS: An observational study. We performed correlation analysis to study associations between the spread of malaria and climatic and social factors in 2002–2022 in the Astrakhan region. The analysis was based on the data obtained from reporting forms of the Center for Hygiene and Epidemiology in the Astrakhan Region and Rospotrebnadzor in the Astrakhan region. Statistical processing of the data was carried out using Microsoft Office Excel tables (Microsoft, USA) and BioStat Professional 5.8.4. RESULTS: A decrease in the number of malaria cases in the Astrakhan region over the study period was a positive trend, which indicates the importance and effectiveness of measures to combat this serious disease. CONCLUSIONS: It is necessary to continue working in this direction in order to ensure the safety and well-being of the population in relation to the reported imported cases of malaria in the region.

Accumulation of Per- and Polyfluoroalkyl Substances (PFAS) in Coastal Sharks from Contrasting Marine Environments: The New York Bight and The Bahamas.

Per- and polyfluoroalkyl substances (PFAS) enter the marine food web, accumulate in organisms, and potentially have adverse effects on predators and consumers of seafood. However, evaluations of PFAS in meso-to-apex predators, like sharks, are scarce. This study investigated PFAS occurrence in five shark species from two marine ecosystems with contrasting relative human population densities, the New York Bight (NYB) and the coastal waters of The Bahamas archipelago. The total detected PFAS (∑PFAS) concentrations in muscle tissue ranged from 1.10 to 58.5 ng g-1 wet weight, and perfluorocarboxylic acids (PFCAs) were dominant. Fewer PFAS were detected in Caribbean reef sharks (Carcharhinus perezi) from The Bahamas, and concentrations of those detected were, on average, ∼79% lower than in the NYB sharks. In the NYB, ∑PFAS concentrations followed: common thresher (Alopias vulpinus) > shortfin mako (Isurus oxyrinchus) > sandbar (Carcharhinus plumbeus) > smooth dogfish (Mustelus canis). PFAS precursors/intermediates, such as 2H,2H,3H,3H-perfluorodecanoic acid and perfluorooctanesulfonamide, were only detected in the NYB sharks, suggesting higher ambient concentrations and diversity of PFAS sources in this region. Ultralong-chain PFAS (C ≥ 10) were positively correlated with nitrogen isotope values (δ15N) and total mercury in some species. Our results provide some of the first baseline information on PFAS concentrations in shark species from the northwest Atlantic Ocean, and correlations between PFAS, stable isotopes, and mercury further contextualize the drivers of PFAS occurrence.

Incidence of and risk factors for small vulnerable newborns in north India: a secondary analysis of a prospective pregnancy cohort

Globally, recent estimates have shown there have been 3·6 million stillbirths and neonatal deaths in 2022, with nearly 60% occurring in low-income and middle-income countries. The Small Vulnerable Newborn Consortium has proposed a framework combining preterm birth (<37 weeks of gestation), small for gestational age (SGA) by INTERGROWTH-21st standard, and low birthweight (<2500 g) under the category small vulnerable newborns (SVN). Reliable data on SVN from sub-Saharan Africa, central Asia, and south Asia are sparse. We aimed to estimate the incidence of SVN and its types, and quantify risk factors, both overall and trimester-specific, from a pregnancy cohort in north India. In the GARBH-Ini (Interdisciplinary Group for Advanced Research on Birth Outcomes-DBT India Initiative) pregnancy cohort, 8000 participants were enrolled with less than 20 weeks' gestation between May 11, 2015, and Aug 8, 2020, at a secondary-care hospital in north India. The cohort was followed up across the antenatal period for a detailed study on preterm birth. We conducted a secondary analysis of cohort data for the outcome of SVN, classified into its types: preterm-SGA, preterm-nonSGA, and term-SGA. We estimated the relative risk and population attributable fraction of candidate risk factors for SVN (modified Poisson regression) and its types (multinomial regression). 7183 (89·9%) of 7990 participants completed the study. Among 6206 newborns included for analysis, the incidence of SVN was 48·4% (35·1% term-SGA newborns [n=2179], 9·7% preterm-nonSGA newborns [n=605], and 3·6% preterm-SGA newborns [n=222]). Compared with term-nonSGA newborns, proportions of stillbirths and neonatal deaths within 72 h of birth among SVN were three times and 2·5 times higher, respectively. Preterm-SGA newborns had the highest incidence of stillbirth (15 [6·8%] of 222) and neonatal deaths (six [4·2%] of 142). Low body-mass index (BMI <18·5 kg/m2) of participants at the start of pregnancy was associated with higher risk for preterm-SGA (adjusted relative risk [RR] 1·61 [95% CI 1·17-2·22]), preterm-nonSGA (1·35 [1·09-1·68]), and term-SGA (1·44 [1·27- 1·64]), with population attributable fraction ranging from 8·7% to 13·8%. Pre-eclampsia (adjusted RR 1·48 [95% CI 1·30-1·71]), short cervical length (1·15 [1·04-1·26]), and bacterial vaginosis (1·13 [0·88-1·45]) were other important antenatal risk factors. In a comprehensive analysis of SVN and its types from north India, we identified risk factors to guide prioritisation of interventions. Complemented with risk-stratification tools, this focused approach will enhance antenatal care, and accelerate achievement of Sustainable Development Goals-namely, to end preventable deaths of newborns and children younger than 5 years by 2030 (target 3·2). Department of Biotechnology, Government of India and Grand Challenges India-Biotechnology Industry Research Assistance Council, Government of India. For the Hindi translation of the abstract see Supplementary Materials section.

Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA.

Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches-firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes-and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.