Craniometric variation in the Aleutians: integrating morphological, molecular, spatial, and temporal data

Several hypotheses have been put forward about the origins and evolution of the inhabitants of the Aleutian Islands. Both Hrdli?ka [The Aleutian and Commander Islands and Their Inhabitants (Philadelphia: Wistar Institute of Anatomy and Biology, 1945)] and Laughlin ["The Alaska gateway viewed from the Aleutian Islands," in Papers on the Physical Anthropology of the American Indian, W. S. Laughlin, ed. (New York: Viking Fund, 1951), 98-126] analyzed cranial morphology and came to somewhat different conclusions using a typological approach and limited analytical methods. Subsequent investigations using morphological data have not significantly improved our understanding of Aleut prehistory. More recently, radiocarbon dating and mitochondrial DNA analyses have shed light on Aleut genetic variation and changes over time, but better morphological methods using multivariate statistical analysis have not yet been used. We analyzed craniometric data using multivariate procedures and found that Aleuts demonstrate significant changes in cranial morphology over time, and these changes correspond to Hrdli?ka's observations but may not necessarily reflect in-migration. The morphological changes were concentrated in the very aspects of morphology that are easily observable and that Hrdli?ka most often measured, namely, cranial length, breadth, and height, but they were obscured when craniometric variation as a whole was analyzed. Also, we found that the morphological changes over time were not related to the changes in haplogroup frequencies over time, suggesting that migration into the Aleutians did not play a significant role in producing the morphological changes. However, craniometric variability apparently increases over time, suggesting in-migration, localized selection, and/or greater environmental heterogeneity. Our results contradict Laughlin's observations but may be more in line with his hypothesis of in situ evolutionary changes absent gene flow. In addition to selection, gene flow, and gene drift, however, sociocultural changes must also be considered as a factor in why morphology changed over time.     

Prediction of drug combinations by integrating molecular and pharmacological data

Combinatorial therapy is a promising strategy for combating complex disorders due to improved efficacy and reduced side effects. However, screening new drug combinations exhaustively is impractical considering all possible combinations between drugs. Here, we present a novel computational approach to predict drug combinations by integrating molecular and pharmacological data. Specifically, drugs are represented by a set of their properties, such as their targets or indications. By integrating several of these features, we show that feature patterns enriched in approved drug combinations are not only predictive for new drug combinations but also provide insights into mechanisms underlying combinatorial therapy. Further analysis confirmed that among our top ranked predictions of effective combinations, 69% are supported by literature, while the others represent novel potential drug combinations. We believe that our proposed approach can help to limit the search space of drug combinations and provide a new way to effectively utilize existing drugs for new purposes.     

Systematic revision of Entomobryidae (Collembola) by integrating molecular and new morphological evidence

Entomobryidae, the largest collembolan family, is traditionally classified at suprageneric level using a limited set of morphological structures, such as scales, antennal segmentation. Most tribal and subfamilial delimitations appear, however, disputable in the light of recent works. Integrating molecular and morphological evidence, we propose here a revision of the systematics of the family. In addition to traditional taxonomic characters, tergal specialized chaetae (S‐chaetae) are newly introduced, and their patterns are shown to be diversified at all levels from species to subfamilies. S‐chaetotaxic pattern on phylogenetic tree shows that evolution of S‐chaetae is not parallel between the different terga and that their patterns coincide well with the known molecular phylogeny, providing a powerful tool for the systematics of Entomobryidae. Orchesellinae sensu Soto‐Adames et al. (Annals of the Entomological Society of America, 101, 2008, 501); is divided into three subfamilies: Orchesellinae s. s., Bessoniellinae and Heteromurinae, the latter two upgraded from the original tribal level. Entomobryinae sensu Szeptycki (Morpho‐Systematic Studies on Collembola. IV. Chaetotaxy of the Entomobryidae and its Phylogenetical Significance, 1979), is no longer divided into scaled and unscaled tribes, and Lepidosira‐group is transferred from Seirinae to Entomobryinae. A key to subfamilies and tribes and a comparison with previous classifications of the Entomobryidae are provided. This study greatly improves the understanding of primary and secondary characters and erects the fundamental framework for the taxonomy of Entomobryidae.     

结合分子相似性、药效团和分子对接筛选新的HIV-1蛋白酶抑制剂

结合分子相似性、药效团和分子对接建立兼顾计算效率和预测准确度的HIV-1蛋白酶抑制剂筛选方法。首先通过对现有HIV-1蛋白酶抑制剂分子进行相似性分析,选取代表性的HIV-1蛋白酶抑制剂作为模板分子,构建和优化药效团模型,并从1万个化合物中优先筛选出500个化合物。而后采用分子对接方法进一步考察化合物与HIV-1蛋白酶结合情况,得到4个新的活性候选化合物,并进行其结合自由能计算和抗突变性分析。结果表明新候选化合物ST025723和HIV-1蛋白酶表现出较好的相互作用和抗突变性,具有深入研究的价值,同时也证明分子相似性、药效团和分子对接相结合能够快速有效地发现新颖活性候选化合物。     

New insight into the systematics of Tomoceridae (Hexapoda,Collembola) by integrating molecular and morphological evidence

Tomoceridae is common but among the most problematic groups of Collembola. Its position within Collembola and the relationships within the family remain obscure. This also extends to the generic division of the subfamily Tomocerinae that remains controversial. This study examines these issues by integrating both molecular and morphological evidence. Our molecular phylogeny based on rDNA sequences supports the monophyly of Tomoceridae and the sister relationship between Tomocerinae and Lepidophorellinae. Reconstructions and tree topology tests constraining monophyly did not resolve the relationships between Tomoceridae and other collembolan groups. We also examined the morphology of the first instar (primary) larvae, which has significant phylogenetic value among higher Collembola. Mapping primary chaetotaxy onto our molecular phylogeny provided further evidence for the unique position of Tomoceridae within Entomobryomorpha and Collembola. The monophyly and subfamilial classification within Tomoceridae were validated here, whereas its position among Collembola will need further studies in a broader consideration across the major collembolan orders. Within Tomocerinae, the monophyly of Pogonognathellus was demonstrated, but the status of Tomocerus and Tomocerina is still to be resolved.     

A conceptual framework for the spatial analysis of landscape genetic data

Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.     

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.     

Concordance of molecular and morphological data: The example of the Acoela

Morphological features of the Acoela appear to be quite plastic, including those of the copulatory organs, which provide the principle characteristics used for the systematics of this group. Consequently, classification schemes of the Acoela comprise numerous polyphyletic groupings. In this review, we detail recent revisions of acoel systematics using molecular sequence data and new and reevaluated morphological characteristics. Gene trees are discordant with traditional systematic schemes but strongly concordant with new morphological characteristics obtained through the use of transmission electron microscopy and confocal laser scanning microscopy, namely, characteristics of body-wall and copulatory organ musculature, sperm, sperm ducts, sagittocysts, and immunocytochemistry of the nervous system. This merger of molecular and morphological data has led to significant changes in acoel classification, including a major emendation of the largest family of the Acoela, the Convolutidae, whereby half of its members were transferred to a newly created family, the Isodiametridae.     

A new genus of African Karniellina (Orthoptera,Tettigoniidae, Conocephalinae,Conocephalini): integrating morphological,molecular and bioacoustical data

Melanoscirtes gen.n. is established within Karniellina. The members of this subtribe are small conocephaline bush crickets, confined to Africa. Melanoscirtes is erected on Phlesirtes kibonotensis, a species restricted to forest clearings and forest edge in the submontane and montane zones of Mt. Kilimanjaro. A subspecies, M. kibonotensis uguenoensis, is described from the North Pare mountains, a mountain range of the Eastern Arc adjacent to Mt. Kilimanjaro. Further species of Melanoscirtes occur on other mountain ranges of the northern branch of the Eastern Arc mountains of northern Tanzania and southern Kenya. The South Pare mountains harbour M. shengenae; the West Usambaras, M. usambarensis, and the Taita Hills, M. taitensis. All species and subspecies of Melanoscirtes exhibit a similar morphology and occupy analogous habitats on the respective mountains. The song patterns for all species found within this genus are very similar, and this, together with evidence from molecular data, suggests that allopatric speciation is the reason for the biogeographic pattern found in this genus. A key for the subspecies and species of Melanoscirtes is provided.     

不同空间尺度景观特征对南流江水质的影响差异

流域景观特征决定了非点源污染物来源与地表景观削减消纳能力,但尚缺乏全流域不同空间尺度对二者关联性的认识。以广西北部湾南流江为例,分别在子流域、河岸缓冲带以及监测点圆形缓冲区三种尺度上,基于2020年Landsat 8 OLI遥感影像解译的土地利用类型特征,结合水质监测数据,运用数理统计和GIS空间分析方法,探讨了流域景观特征在不同空间尺度上对河流水质的影响。结果表明：(1)在子流域尺度,土地利用类型以林地为主,而在河岸缓冲带与监测点圆形缓冲区均以耕地为主;(2)水质指标高锰酸盐指数、生化需氧量与景观特征相关性最为显著,耕地、建设用地、其他用地和园地与其呈正相关,是南流江水质污染负荷的重要来源区;景观格局指数中,斑块密度、蔓延度指数、多样性指数、均匀度指数是引起河流水质指标变化的主要景观因子;(3)受流域内或不同子流域间景观特征差异,景观组成面积占比和景观格局指数均在河岸缓冲带尺度对水质状况影响最大,分别可解释57.0%和64.7%的水质指标变化;子流域尺度次之,圆形缓冲区尺度最小,且景观格局指数对水质状况的影响大于景观组成面积占比。建议在河岸带50 m范围内严格控制耕地面积,建设河岸缓...     

Object-based classification of land cover and tree species by integrating airborne LiDAR and high spatial resolution imagery data

We evaluated the effectiveness of integrating discrete return light detection and ranging (LiDAR) data with high spatial resolution near-infrared digital imagery for object-based classification of land cover types and dominant tree species. In particular we adopted LiDAR ratio features based on pulse attributes that have not been used in past studies. Object-based classifications were performed first on land cover types, and subsequently on dominant tree species within the area classified as trees. In each classification stage, two different data combinations were examined: LiDAR data integrated with digital imagery or digital imagery only. We created basic image objects and calculated a number of spectral, textural, and LiDAR-based features for each image object. Decision tree analysis was performed and important features were investigated in each classification. In the land cover classification, the overall accuracy was improved to 0.975 when using the object-based method and integrating LiDAR data. The mean height value derived from the LiDAR data was effective in separating “trees” and “lawn” objects having different height. As for the tree species classification, the overall accuracy was also improved by object-based classification with LiDAR data although it remained up to 0.484 because spectral and textural signatures were similar among tree species. We revealed that the LiDAR ratio features associated with laser penetration proportion were important in the object-based classification as they can distinguish tree species having different canopy density. We concluded that integrating LiDAR data was effective in the object-based classifications of land cover and dominant tree species.     

Discovery of novel human breast cancer microRNAs from deep sequencing data by analysis of pri-microRNA secondary structures

MicroRNAs (miRNAs) are key regulators of gene expression and contribute to a variety of biological processes. Abnormal miRNA expression has been reported in various diseases including pathophysiology of breast cancer, where they regulate protumorigenic processes including vascular invasiveness, estrogen receptor status, chemotherapy resistance, invasion and metastasis. The miRBase sequence database, a public repository for newly discovered miRNAs, has grown rapidly with approximately >10,000 entries to date. Despite this rapid growth, many miRNAs have not yet been validated, and several others are yet to be identified. A lack of a full complement of miRNAs has imposed limitations on recognizing their important roles in cancer, including breast cancer. Using deep sequencing technology, we have identified 189 candidate novel microRNAs in human breast cancer cell lines with diverse tumorigenic potential. We further show that analysis of 500-nucleotide pri-microRNA secondary structure constitutes a reliable method to predict bona fide miRNAs as judged by experimental validation. Candidate novel breast cancer miRNAs with stem lengths of greater than 30 bp resulted in the generation of precursor and mature sequences in vivo. On the other hand, candidates with stem length less than 30 bp were less efficient in producing mature miRNA. This approach may be used to predict which candidate novel miRNA would qualify as bona fide miRNAs from deep sequencing data with approximately 90% accuracy.     

Deciphering the functional landscape of phosphosites with deep neural network

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