Subsistence and Food Sharing in Northern Siberia: Social and Nutritional Ecology of the Dolgan and the Nganasan

Traditional foraging activities and extensive food sharing are critical to the contemporary nutritional well-being of Dolgan and Nganasan people in the Taimyr Region, Russia. Despite recent economic transformations geared toward free-market capitalism in the post-socialist era, since 1991, a native communal resource-management regime has developed. This article outlines the social and nutritional significance of subsistence and food sharing within a remote indigenous community in Arctic Siberia. Empirical data on procurement processes and relationships, along with data on food distributions and rationales, are discussed. These data are relevant to questions about food sharing and its significance in hunting-and-gathering economies and the evolution of human sociality.     

责任亲情交互护理模式对初产妇产后泌乳功能、负性情绪及应对方式的影响

目的：观察责任亲情交互护理模式对初产妇产后泌乳功能、负性情绪及应对方式的影响。方法：回顾性分析2018年1月至2021年2月于该院生产的60名初产妇的临床资料,按照护理方法不同分为观察组与对照组各30名。对照组采用常规护理,观察组采用责任亲情交互护理,比较两组初乳始动时间、产后48 h的泌乳功能、焦虑自评量表（SAS）评分、抑郁自评量表（SDS）评分和医学应对方式量表（MCMQ）评分。结果：观察组初乳始动时间短于对照组,产后48 h泌乳功能优于对照组,差异有统计学意义（P<0.05）;出院时,两组SAS、SDS评分均低于护理前,且观察组低于对照组,差异有统计学意义（P<0.05）;出院时,两组MCMQ面对评分高于护理前,且观察组高于对照组,两组MCMQ回避、屈服评分低于护理前,且观察组低于对照组,差异有统计学意义（P<0.05）。结论：责任亲情交互护理可提高初产妇产后泌乳功能,降低其SAS、SDS评分,改善其应对方式,效果优于常规护理。     

EARLY DAYS AT THE TAVISTOCK INSTITUTE

The paper describes a developing sociological and psychoanalytic approach to the study of 20 London families in the early 1950s.     

Development and evaluation of a novel panel containing 188 microhaplotypes for 2nd-degree kinship testing in the Hebei Han population

Distant kinship identification is one of the critical problems in forensic genetics. As a new type of genetic marker defined and discussed in the last decade, the microhaplotype (MH) has drawn much attention in such identification owing to its specific advantages to traditional short tandem repeat (STR) or single nucleotide polymorphism (SNP) markers. In this study, MH markers were screened step by step from the 1000 Genomes Project database, and a novel multiplex panel containing 188 MHs (in which 181 are reported the first time, while 1 was reported in a previous study and the other 6 have partial overlaps with known markers) was constructed for application in 2nd- and 3rd-degree kinship identification. Along with the construction, a novel MH nomenclature was proposed, in which the SNP position information they contained was taken into account to eliminate the possibility that the same locus was named differently interlaboratory. After a series of evaluations, the panel was shown to have good sequencing accuracy, high sensitivity, species specificity, and resistance to anti-PCR inhibitors or degradation. Population data of the 188 MHs were calculated based on the genetic information of 221 unrelated Hebei Han individuals, and the effective number of alleles (Ae) ranged from 2.0925 to 8.2634 (with an average of 2.9267). For the whole system, the cumulative matching probability (CMP), the cumulative power of exclusion in paternity testing of duos (CPEduo) and that of trios (CPEtrio) reached 2.8422 × 10⁻¹³⁷, 1–1.3109 × 10⁻²¹, and 1–2.8975 × 10⁻³⁹, respectively, indicating that this panel was satisfactory for individual identification and paternity testing. Then, the efficiency of the 188 MHs in 2nd- and 3rd-degree kinship testing was studied based on 30 extended families consisting of 179 2nd-degree and 121 3rd-degree relatives, as well as simulations of 0.5 million pairs of those two kinships. The results showed that clear opinions would be given in 83.36% of 2nd-degree identifications with a false rate less than 10⁻⁵, when the confirming and excluding thresholds of cumulative likelihood ratio (CLR) were set as 10⁴ and 10⁻⁴, respectively. This panel is still not sufficient to solve the problem of 3rd-degree kinship identification alone, and approximately 300 or 870 MH loci would be needed in 2nd- or 3rd-degree kinship identification, respectively, to achieve a system efficiency not less than 0.99 with such a threshold set; such necessary numbers would be used only as a reference in further research.     

A fast linkage method for population GWAS cohorts with related individuals

Linkage analysis, a class of methods for detecting co-segregation of genomic segments and traits in families, was used to map disease-causing genes for decades before genotyping arrays and dense SNP genotyping enabled genome-wide association studies in population samples. Population samples often contain related individuals, but the segregation of alleles within families is rarely used because traditional linkage methods are computationally inefficient for larger datasets. Here, we describe Population Linkage, a novel application of Haseman–Elston regression as a method of moments estimator of variance components and their standard errors. We achieve additional computational efficiency by using modern methods for detection of IBD segments and variance component estimation, efficient preprocessing of input data, and minimizing redundant numerical calculations. We also refined variance component models to account for the biases in population-scale methods for IBD segment detection. We ran Population Linkage on four blood lipid traits in over 70,000 individuals from the HUNT and SardiNIA studies, successfully detecting 25 known genetic signals. One notable linkage signal that appeared in both was for low-density lipoprotein (LDL) cholesterol levels in the region near the gene APOE (LOD = 29.3, variance explained = 4.1%). This is the region where the missense variants rs7412 and rs429358, which together make up the ε2, ε3, and ε4 alleles each account for 2.4% and 0.8% of variation in circulating LDL cholesterol. Our results show the potential for linkage analysis and other large-scale applications of method of moments variance components estimation.     

Effects of DNA degradation and genotype imputation on high-density SNP microarray in pairwise kinship analysis

High-density single nucleotide polymorphisms (SNPs) can detect distant relatives even in the context of pairwise kinship analysis. Although DNA microarrays conveniently generate genome-wide SNP data, they require large quantities of high-quality DNA. Genotyping data obtained from low-quantity and low-quality samples are likely unreliable owing to the incidence of no-called or mistyped SNPs. In this study, we examined the effects of insufficient sample densities and sample degradation on the efficacy of kinship analysis. While low DNA amounts had a minor effect, DNA degradation led to a significant increase in no-call rates and error rates. Posterior probabilities of kinship determination, calculated using the index of chromosomal sharing, were markedly lower in proportion to the no-call rates and error rates. We also investigated the effect of genotype imputation to complement the no-called genome data utilizing SNPs reference panels. We found that the posterior probability of the relative-assumed person increased with genotype complementation in case of mild degradation, even with mistyped genotypes. Therefore, DNA microarray with imputation is a promising method for analyzing forensic DNA samples taken from situations where DNA quantity and quality may be compromised, such as disaster victim identification using pairwise kinship analysis.