Cognitive functioning in substance abuse and dependence: a population-based study of young adults

Aims   To investigate whether substance use disorders (SUDs) are associated with verbal intellectual ability, psychomotor processing speed, verbal and visual working memory, executive function and verbal learning in young adults, and to study the associations of SUD characteristics with cognitive performance.
Participants   A population-based sample ( n  = 466) of young Finnish adults aged 21–35 years.
Measurements   Diagnostic assessment was based on all available information from a structured psychiatric interview (SCID-I) and in- and out-patient medical records. Established neuropsychological tests were used in the cognitive assessment. Confounding factors included in the analyses were comorbid psychiatric disorders and risk factors for SUDs, representing behavioural and affective factors, parental factors, early initiation of substance use and education-related factors.
Findings   Adjusted for age and gender, life-time DSM-IV SUD was associated with poorer verbal intellectual ability, as measured with the Wechsler Adult Intelligence Scale–Revised (WAIS-R) vocabulary subtest, and slower psychomotor processing, as measured with the WAIS-R digit symbol subtest. Poorer verbal intellectual ability was accounted for by parental and own low basic education, whereas the association with slower psychomotor processing remained after adjustment for SUD risk factors. Poorer verbal intellectual ability was related to substance abuse rather than dependence. Other SUD characteristics were not associated with cognition.
Conclusions   Poorer verbal intellectual ability and less efficient psychomotor processing are associated with life-time alcohol and other substance use disorders in young adulthood. Poorer verbal intellectual ability seems to be related to parental and own low basic education, whereas slower psychomotor processing is associated with SUD independently of risk factors.     

Nonparametric coalescent inference of mutation spectrum history and demography

As populations boom and bust, the accumulation of genetic diversity is modulated, encoding histories of living populations in present-day variation. Many methods exist to decode these histories, and all must make strong model assumptions. It is typical to assume that mutations accumulate uniformly across the genome at a constant rate that does not vary between closely related populations. However, recent work shows that mutational processes in human and great ape populations vary across genomic regions and evolve over time. This perturbs the mutation spectrum (relative mutation rates in different local nucleotide contexts). Here, we develop theoretical tools in the framework of Kingman’s coalescent to accommodate mutation spectrum dynamics. We present mutation spectrum history inference (mushi), a method to perform nonparametric inference of demographic and mutation spectrum histories from allele frequency data. We use mushi to reconstruct trajectories of effective population size and mutation spectrum divergence between human populations, identify mutation signatures and their dynamics in different human populations, and calibrate the timing of a previously reported mutational pulse in the ancestors of Europeans. We show that mutation spectrum histories can be placed in a well-studied theoretical setting and rigorously inferred from genomic variation data, like other features of evolutionary history.

Over the past decade, population geneticists have developed many sophisticated methods for inferring population demography and have consistently found that simple isolated populations of constant size are far from the norm (reviewed in refs. 1–3). Population expansions and founder events, as well as migration between species and geographic regions, have been inferred from virtually all high-resolution genetic datasets. We now recognize that inferring these nonequilibrium demographies is often essential for understanding the histories of adaptation and global migration. Population genetics has uncovered many features of human history that were once virtually unknowable by other means, revealing a complex series of migrations, population replacements, and admixture networks among human groups and extinct hominoids.Although demographic inference methods can model complex population histories, the germline mutation process that creates variation has long received a comparatively simple treatment. A single parameter, μ, is used to represent the mutation rate per generation at all loci, in all individuals, and at all times. In humans, μ is estimated from parent–child trio sequencing studies, and modest variation in μ can have major effects on the interpretation of inferred parameters, such as times of admixture and population divergence. In other organisms, for which trio sequence data are usually unavailable, μ is estimated from sequence divergence between species with a fossil-calibrated divergence time, and these estimates come with still higher uncertainty.A growing body of evidence indicates that simple, constant mutation rate models may not adequately describe how variation accumulates on either inter- or intraspecific timescales (4–7). Germline mutation rates appear to have evolved during the speciation of great apes and the divergence of modern human populations (reviewed in ref. 8). Much of this evolution might be caused by nearly neutral drift (9), but a contributing factor could be selection on traits, like life history and chromatin structure, that indirectly affect mutation accumulation. Because mutation is intimately tied to the basic housekeeping process of cell division, gamete production, and embryonic development, the accumulation of mutations is likely to be complexly coupled to other biological processes (10–12).It is difficult to disentangle past changes in mutation rate from past changes in effective population size, which modulate levels of polymorphism even when the mutation rate stays constant. However, evolution of the mutation process can be indirectly detected by measuring its effects on the mutation spectrum: the relative mutation rates among different local nucleotide contexts. Hwang and Green (13) modeled the triplet context dependence of the substitution process in a mammalian phylogeny, finding varying contributions from replication errors, cytosine deamination, and biased gene conversion and showing that the relative rates of these processes varied between different mammalian lineages. Many cancers also exhibit somatic hypermutability of certain triplet motifs due to different DNA damage agents and failure points in the DNA repair process (14, 15). Harris (6) and Harris and Pritchard (7) examined the variation of triplet spectra between closely related populations, counting single-nucleotide variants in each triplet mutation type as a proxy for mutational input. They found that human triplet spectra distinctly cluster by continental ancestry group and that historical pulses in mutation activity influence the distribution of allele frequencies in certain mutation types. The divergence of mutation spectra among human continental groups has been replicated in independently generated datasets (7, 16), and similar patterns have been observed in other species, including great apes (17), mice (18), and yeast (19). Some of the mutation spectrum divergence between mice and yeast lineages has been mapped to mutator alleles (19, 20).Emerging from the literature is a picture of a mutation process evolving within and between populations, anchored to genomic features and accented by spectra of local nucleotide context. If probabilistic models of population genetic processes are to keep pace with these empirical findings, mutation deserves a richer treatment in state-of-the-art inference tools. In this paper, we build on classical theoretical tools to introduce fast nonparametric inference of population-level mutation spectrum history (MuSH)—the relative mutation rate in different local nucleotide contexts across time—alongside inference of demographic history. Whereas previous work has uncovered mutation spectrum evolution using summary statistics of standing variation, we shift perspective to focus on inference of the MuSH, which we model on the same footing as demography.Demographic inference requires us to invert the map that takes population history to the patterns of genetic diversity observable today. This task is often simplified by first compressing these genetic diversity data into a summary statistic such as the sample frequency spectrum (SFS), the distribution of derived allele frequencies among sampled haplotypes. The SFS is a well-studied population genetic summary statistic that is sensitive to demographic history. Inverting the map from demographic history to SFS is a notoriously ill-posed problem, in that many different population histories can have identical expected SFS (21–25). One way to deal with the ill posedness of demographic inference is to specify a parametric model of population size change, usually piecewise linear or piecewise exponential. An alternative, which generalizes to other inverse problems, is to allow a more general space of solutions but to regularize by penalizing histories that contain biologically unrealistic features (e.g., high-frequency population size oscillations). Both approaches shrink the set of feasible solutions to the inverse problem so that it becomes well posed and can be thought of as leveraging prior knowledge. In particular, regularization constrains the population size from changing on arbitrarily small timescales since significant population size change usually takes at least a few generations.In this paper, we extend a coalescent framework for demographic inference to accommodate inference of the MuSH from an SFS that is resolved into different local k-mer nucleotide contexts. This is a richer summary statistic that we call the k-SFS where, for example, k=3 means triplet context. We show using coalescent theory that the k-SFS is related to the MuSH by a linear transformation while depending nonlinearly on the demographic history. We infer both demographic history and MuSH by optimizing a cost that balances a data-fitting term using the forward map from coalescent theory, along with regularization terms that favor solutions with low complexity. Our open-source software mushi (mutation spectrum history inference) is available in ref. 26 as a Python package with extensive documentation. Using default settings and modest hardware, mushi takes only a few seconds to infer histories from population-scale sample frequency data.The recovered MuSH is a rich object that illuminates dimensions of population history and addresses biological questions about the evolution of the mutation process. After validating with data simulated under known histories, we use mushi to independently infer histories for each of the 26 populations (from 5 superpopulations defined by continental ancestry) from the 1000 Genomes Project (1KG) Consortium (27) using recent high-coverage sequencing data (28). We demonstrate that mushi is a powerful tool for demographic inference that has several advantages over existing demographic inference methods and then go on to describe the illuminated features of human MuSH.We recover demographic features that are robust to regularization parameter choices, including the out-of-Africa event and the more recent bottleneck in the ancestors of modern Finns, and we find that effective population sizes converge ancestrally within each superpopulation, despite being inferred independently. Decomposing human MuSH into mutation signatures varying through time in each population, we see global divergence in the mutation process that impacts many mutation types and reflects population and superpopulation relatedness. Finally, we revisit the timing of a previously reported ancient pulse of elevated TCC → TTC mutation rate, active primarily in the ancestors of Europeans and absent in East Asians (6, 7, 29, 30). We find that the extent of the pulse into the ancient past is sensitive to the choice of demographic history model but that all demographic models that fit the k-SFS yield a pulse timing that is significantly older than previously thought, seemingly arising near the divergence time of East Asians and Europeans.With mushi, we can quickly reconstruct demographic history and MuSH without strong model specification requirements. This adds an approach to the toolbox for researchers interested only in demographic inference. For researchers studying the mutation spectrum, demographic history is necessary for time calibration of events in mutation history, so we expect that jointly modeling demography and MuSH will be important for studying mutational spectrum evolution in population genetics.     

Drug use patterns and infection with sexually transmissible agents among young adults in a high-risk neighbourhood in New York City

Aims To determine relationships between drug use ‘hardness’ (defined in increasing order of hardness as no drug use, marijuana use, non‐injected heroin or cocaine use, crack smoking and injection drug use) and prevalences of several sexually transmissible infections among young adults in a high‐risk neighbourhood. Drug users, particularly injection drug users and crack smokers, may be a core group for some sexually transmitted infections. Design Cross‐sectional survey and assays of young adults from (a) a household probability sample and (b) a targeted sample of youth who have used injected drugs, crack, other cocaine or heroin. Setting Bushwick, an impoverished New York City minority neighbourhood with major drug markets. Participants A total of 363 18–24‐year‐olds from a household probability sample; 165 Bushwick 18–24‐year‐olds who have used injected drugs, crack, other cocaine or heroin. Measurements Drug use by self‐report; serum‐ and urine‐based assays for HIV, hepatitis B and C, syphilis, gonorrhoea, chlamydia and herpes simplex (type 2). Findings Household‐sample prevalences: HIV, hepatitis C and syphilis, 1%; gonorrhoea 3%; chlamydia 5%; past or present hepatitis B infection 8%; herpes simplex (type 2) 18%. In combined household and targeted samples, hepatitis C and HIV were concentrated among drug injectors. Herpes simplex (type 2), syphilis and hepatitis B increased among women with ‘hardest drug ever used’. Conclusions Using ‘harder’ drugs is associated with some but not all of these infections. Prevention efforts should help youth avoid unsafe sex and higher‐risk drugs.     

钩藤天麻胶囊治疗缺血性中风急性期风火痰瘀互结证临床研究

目的：观察钩藤天麻胶囊治疗缺血性中风急性期风火痰瘀互结证的临床疗效。方法：将60例患者随机分为治疗组和对照组,每组各30例。对照组采用西药基础治疗,治疗组在对照组基础上加用钩藤天麻胶囊治疗。两组共治疗14 d,随访1个月。观察两组患者治疗前、治疗后及随访1个月后神经功能缺损程度评分、中医证候积分。结果：治疗14 d 后,两组患者神经功能缺损程度评分均较治疗前有不同程度下降（P ＜0．05）,两组患者组间比较无显著性差异（P ＞0．05）,两组患者中医证候积分比较,有显著性差异（P ＜0．05）。随访1个月后,两组患者神经功能缺损评分较治疗前有不同程度下降（P ＜0．05）,但治疗组改善更明显（P ＜0．05）;两组患者中医证候积分较治疗前有不同程度改善（P ＜0．05）,但治疗组改善更明显（P ＜0．05）。结论：钩藤天麻胶囊治疗缺血性中风急性期风火痰瘀互结证疗效显著,且无明显不良反应。     

肺硬化性血管瘤120例临床病理分析

目的探讨肺硬化性血管瘤(pulmonary sclerosing hemangioma,PSH)的临床病理特征及免疫表型。方法收集120例PSH的临床病理资料,探讨其临床特点、组织学特征及免疫表型。结果 PSH肿块与周围肺组织界限清楚,切面多为灰棕色,常伴出血灶。镜下可见两种肿瘤细胞、四种组织结构,多以混合形式存在(92/120,76.67%),并常发现泡沫样细胞灶性聚集及肥大细胞散在分布(83/120,69.17%)。免疫表型:表面立方细胞及间质多角形细胞TTF-1、EMA阳性,表面细胞SP-A、CK、Napsin A阳性,间质细胞vimentin阳性。结论 PSH大体表现及镜下典型的"两种细胞,四种结构"组织特点是诊断PSH的重要依据,泡沫样细胞灶性聚集及肥大细胞散在分布对PSH诊断及鉴别诊断有重要提示意义。     

Cost‐effective screening method for antinuclear antibody detection

Aim: To evaluate indirect immunoenzyme (IIE) technique, for detection of antinuclear antibodies (ANA) using serum and filter paper blood clots (FPBC) especially for screening. Methods: Antinuclear antibody processing from FPBC (prepared by expressing blood drops by finger pricking) was standardized in a pilot study. Paired samples (serum and corresponding FPBC) from 224 individuals [142 patients of systemic rheumatic diseases, chiefly lupus and rheumatoid arthritis (RA) and 82 healthy controls (HC)] were tested by the standard immunofluorescence (IIF) and IIE (using light microscope); samples were coded, blinded and randomly processed as per the protocol. End‐point titres were determined for positive serum samples only. Standard reagents (Immunoconcepts Incorporation, US) and controls (CDC, Atlanta, US) were used. All patients were identified in a rheumatology referral practice in an Indian metropolis. Results: The sensitivity of IIE and IIF for SLE, using serum and FPBC was ≈90%. The specificity of IIE and IIF for SLE, using serum and FPBC was in the range 66–73% and 58–63%, respectively. Good–perfect agreement (κ > 0.8) between the results was obtained by IIE and IIF for all groups except RA. Except the RA group, all other paired samples showed good concordance (72%) on testing for ANA patterns by both techniques. Conclusions: Indirect immunoenzyme technique is a robust technique and should be considered a viable option to IIF at least in countries like India; its further use on FPBC is a socioeconomically appealing proposition for carrying out population studies on lupus and related uncommon connective tissue disorders.     

Stepped‐wedge cluster randomised controlled trials: a generic framework including parallel and multiple‐level designs

Stepped‐wedge cluster randomised trials (SW‐CRTs) are being used with increasing frequency in health service evaluation. Conventionally, these studies are cross‐sectional in design with equally spaced steps, with an equal number of clusters randomised at each step and data collected at each and every step. Here we introduce several variations on this design and consider implications for power. One modification we consider is the incomplete cross‐sectional SW‐CRT, where the number of clusters varies at each step or where at some steps, for example, implementation or transition periods, data are not collected. We show that the parallel CRT with staggered but balanced randomisation can be considered a special case of the incomplete SW‐CRT. As too can the parallel CRT with baseline measures. And we extend these designs to allow for multiple layers of clustering, for example, wards within a hospital. Building on results for complete designs, power and detectable difference are derived using a Wald test and obtaining the variance–covariance matrix of the treatment effect assuming a generalised linear mixed model. These variations are illustrated by several real examples. We recommend that whilst the impact of transition periods on power is likely to be small, where they are a feature of the design they should be incorporated. We also show examples in which the power of a SW‐CRT increases as the intra‐cluster correlation (ICC) increases and demonstrate that the impact of the ICC is likely to be smaller in a SW‐CRT compared with a parallel CRT, especially where there are multiple levels of clustering. Finally, through this unified framework, the efficiency of the SW‐CRT and the parallel CRT can be compared. © 2014 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.     

Hypothesis testing for two‐stage designs with over or under enrollment

Simon's two‐stage designs are widely used in cancer phase II clinical trials for assessing the efficacy of a new treatment. However in practice, the actual sample size for the second stage is often different from the planned sample size, and the original inference procedure is no longer valid. Previous work on this problem has certain limitations in computation. In this paper, we attempt to maximize the unconditional power while controlling for the type I error for the modified second stage sample size. A normal approximation is used for computing the power, and the numerical results show that the approximation is accurate even under small sample sizes. The corresponding confidence intervals for the response rate are constructed by inverting the hypothesis test, and they have reasonable coverage while preserving the type I error. Copyright © 2015 John Wiley & Sons, Ltd.     

化痰活血中药治疗急性冠状动脉综合征

目的 探讨化痰活血中药治疗急性冠状动脉综合征临床效果.方法 从急诊科留观及住院患者中随机选择60例分为治疗组与对照组,各30例.对照组予西医常规治疗,治疗组在对照组治疗基础上予化痰活血中药治疗.结果 治疗后2组发作频率较治疗前均显著下降(P＜0.05),且治疗组优于对照组(P＜0.05);治疗组中医证候评分显著下降(P＜0.05);治疗后2组心肌酶相关指标水平均显著下降,P ＜0.05;且治疗组优于对照组(P＜0.05).2组均未发生不良反应.结论 西药联合化痰活血中药治疗急性冠状动脉综合征,能明显减少心绞痛发作频率,明显改善中医症状,提高患者生活质量.