What are we to make of the concept of race?: Thoughts of a philosopher–scientist

Discussions about the biological bases (or lack thereof) of the concept of race in the human species seem to be never ending. One of the latest rounds is represented by a paper by Neven Sesardic, which attempts to build a strong scientific case for the existence of human races, based on genetic, morphometric and behavioral characteristics, as well as on a thorough critique of opposing positions. In this paper I show that Sesardic’s critique falls far short of the goal, and that his positive case is exceedingly thin. I do this through a combination of analysis of the actual scientific findings invoked by Sesardic and of some philosophical unpacking of his conceptual analysis, drawing on a dual professional background as an evolutionary biologist and a philosopher of science.     

Role of the apolipoprotein E and catechol-O-methyltransferase genes in prospective and retrospective memory traits

Human memory is a complex neurocognitive process. By combining psychological and molecular genetics expertise, we examined the APOE ε4 allele, a known risk factor for Alzheimer's disease, and the COMT Val 158 polymorphism, previously implicated in schizophrenia, for association with lowered memory functioning in healthy adults. To assess memory type we used a range of memory tests of both retrospective and prospective memory. Genotypes were determined using RFLP analysis and compared with mean memory scores using univariate ANOVAs. Despite a modest sample size (n=197), our study found a significant effect of the APOE ε4 polymorphism in prospective memory. Supporting our hypothesis, a significant difference was demonstrated between genotype groups for means of the Comprehensive Assessment of Prospective Memory total score (p=0.036; ε4 alleles=1.99; all other alleles=1.86). In addition, we demonstrate a significant interactive effect between the APOE ε4 and COMT polymorphisms in semantic memory. This is the first study to investigate both APOE and COMT genotypes in relation to memory in non-pathological adults and provides important information regarding the effect of genetic determinants on human memory.     

Novel mutation in the fukutin gene in an Egyptian family with Fukuyama congenital muscular dystrophy and microcephaly

Fukuyama-type congenital muscular dystrophy (FCMD, MIM#253800) is an autosomal recessive disorder characterized by severe muscular dystrophy associated with brain malformations. FCMD is the second most common form of muscular dystrophy after Duchenne muscular dystrophy and one of the most common autosomal recessive diseases among the Japanese population, and yet few patients outside of Japan had been reported with this disorder. We report the first known Egyptian patient with FCMD, established by clinical features of generalized weakness, pseudohypertrophy of calf muscles, progressive joint contractures, severe scoliosis, elevated serum creatine kinase level, myopathic electrodiagnostic changes, brain MRI with cobblestone complex, and mutation in the fukutin gene. In addition, our patient displayed primary microcephaly, not previously reported associated with fukutin mutations. Our results expand the geographic and clinical spectrum of fukutin mutations.     

Special Issue ofHuman evolution on intelligence and evolutionary biology

This is a Special Issue on intelligence and evolutionary biology, based on selected lectures at a NATO Advanced Study Institute on this topic. The proceedings of the ASI have been published in a separate volume. The papers presented here have been reviewed and updated to reflect information available in 1988.     

Current applications of deep-learning in neuro-oncological MRI

PurposeMagnetic Resonance Imaging (MRI) provides an essential contribution in the screening, detection, diagnosis, staging, treatment and follow-up in patients with a neurological neoplasm. Deep learning (DL), a subdomain of artificial intelligence has the potential to enhance the characterization, processing and interpretation of MRI images. The aim of this review paper is to give an overview of the current state-of-art usage of DL in MRI for neuro-oncology.MethodsWe reviewed the Pubmed database by applying a specific search strategy including the combination of MRI, DL, neuro-oncology and its corresponding search terminologies, by focussing on Medical Subject Headings (Mesh) or title/abstract appearance. The original research papers were classified based on its application, into three categories: technological innovation, diagnosis and follow-up.ResultsForty-one publications were eligible for review, all were published after the year 2016. The majority (N = 22) was assigned to technological innovation, twelve had a focus on diagnosis and seven were related to patient follow-up. Applications ranged from improving the acquisition, synthetic CT generation, auto-segmentation, tumor classification, outcome prediction and response assessment. The majority of publications made use of standard (T1w, cT1w, T2w and FLAIR imaging), with only a few exceptions using more advanced MRI technologies. The majority of studies used a variation on convolution neural network (CNN) architectures.ConclusionDeep learning in MRI for neuro-oncology is a novel field of research; it has potential in a broad range of applications. Remaining challenges include the accessibility of large imaging datasets, the applicability across institutes/vendors and the validation and implementation of these technologies in clinical practise.     

Prospects for the biology of human intelligence

Despite the ubiquitous nature of Spearman's g in mental test performance, the charge «intelligence is what intelligence tests test» has not been countered in a satisfactory way. It is proposed that there are two ways to answer this complaint. The first concerns the new hypothesis testing models in factor analysis. The second involves studying the ‘biology of intelligence’. The biology of intelligence has various meanings and four are discussed: biology as theory; biology as race and genetics; biology as neurobiology; and biology as basic psychological processes. The last of these is considered in some detail and it is found that reaction time, evoked potentials and inspection time offer bright prospects for further research on the biology of psychometric intelligence.     

计算机少儿智力测评软件的研究与开发

介绍一种用VB软件编写的数据库管理软件,用于《韦氏学龄儿童智力量表(WISC-R)和婴儿~初中学生社会生活能力量表(日本S-M社会生活能力检查修订版)》的计算机评价与统计。该软件操作简单,评价准确,携带方便,是一种专用的少儿智力测评软件。     

A long term trend in tooth size in the Eastern Mediterranean

Although estimates of brain weight are useless in prediction of individual intelligence in man, the available data (none of them entirely adequate) suggest that the real correlation may be as high as 0.3. Evaluation of causes suggests the participation of a direct effect. Natural selection on intelligence at a current estimated intensity suffices to explain the rapid rate of increase of brain size in human evolution. Selection on birth weight may also suffice for this. It does not seem overly difficult to estimate directly the relationships among brain weight, intelligence, and fitness.