Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low‐cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.     

Construction of a Model Culture System of Human Colonic Microbiota to Detect Decreased Lachnospiraceae Abundance and Butyrogenesis in the Feces of Ulcerative Colitis Patients

Compositional alteration of the gut microbiota is associated with ulcerative colitis (UC). Here, a model culture system is established for the in vitro human colonic microbiota of UC, which will be helpful for determining medical interventions. 16S ribosomal RNA sequencing confirms that UC models are successfully developed from fecal inoculum and retain the bacterial species biodiversity of UC feces. The UC models closely reproduce the microbial components and successfully preserve distinct clusters from the healthy subjects (HS), as observed in the feces. The relative abundance of bacteria belonging to the family Lachnospiraceae significantly decreases in the UC models compared to that in HS, as observed in the feces. The system detects significantly lower butyrogenesis in the UC models than that in HS, correlating with the decreased abundance of Lachnospiraceae. Interestingly, the relative abundance of Lachnospiraceae does not correlate with disease activity (defined as partial Mayo score), suggesting that Lachnospiraceae persists in UC patients at a decreased level, irrespective of the alteration in disease activity. Moreover, the system shows that administration of Clostridium butyricum MIYAIRI restores butyrogenesis in the UC model. Hence, the model detects deregulation in the intestinal environment in UC patients and may be useful for simulating the effect of probiotics.     

Data partitioning and correction for ascertainment bias reduce the uncertainty of placental mammal divergence times inferred from the morphological clock

Bayesian estimates of divergence times based on the molecular clock yield uncertainty of parameter estimates measured by the width of posterior distributions of node ages. For the relaxed molecular clock, previous works have reported that some of the uncertainty inherent to the variation of rates among lineages may be reduced by partitioning data. Here we test this effect for the purely morphological clock, using placental mammals as a case study. We applied the uncorrelated lognormal relaxed clock to morphological data of 40 extant mammalian taxa and 4,533 characters, taken from the largest published matrix of discrete phenotypic characters. The morphologically derived timescale was compared to divergence times inferred from molecular and combined data. We show that partitioning data into anatomical units significantly reduced the uncertainty of divergence time estimates for morphological data. For the first time, we demonstrate that ascertainment bias has an impact on the precision of morphological clock estimates. While analyses including molecular data suggested most divergences between placental orders occurred near the K‐Pg boundary, the partitioned morphological clock recovered older interordinal splits and some younger intraordinal ones, including significantly later dates for the radiation of bats and rodents, which accord to the short‐fuse hypothesis.     

A novel case of autogamy and cleistogamy in Dendrobium wangliangii: A rare orchid distributed in the dry‐hot valley

Dendrobium wangliangii is an epiphytic orchid distributed in the Jinshajiang dry‐hot valley in Luquan County, Yunnan Province, China. Most Dendrobium spp. typically have a low fruit set, but this orchid shows a higher fruit set under natural conditions despite the lack of effective pollinators. The pollination biology of the critically endangered D. wangliangii was investigated in this study. A fruit set rate of 33.33 ± 4.71% was observed after bagging treatment in 2017 and a high fruit set rate (65.72 ± 4.44% in 2011; 50.79 ± 5.44% in 2017) was observed under natural conditions, indicating that D. wangliangii is characterized by spontaneous self‐pollination. The anther cap blocked the growing pollinium; thus, the pollinium slid down and reached the stigmatic cavity, leading to autogamous self‐pollination. Specifically, 51.50% of 162 unopened flowers (total 257 flowers) of this Dendrobium species under extreme water‐deficit conditions developed into fruits, suggesting the presence of cleistogamy in D. wangliangii. Here, cleistogamy may represent the primary mode of pollination for this orchid. Spontaneous self‐pollination and specific cleistogamous autogamy could represent major adaptions to the drought and pollinator‐scarce habitat in the Jinshajiang dry‐hot valley.     

Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade‐off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be “poor” and 61% to show a degree of reliability split between “moderate” (30%), “good” (25%), and “excellent” (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold‐out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd‐sourcing further assessments by allowing web‐based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.     

Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition

The availability of suitable habitat is a key predictor of the changing status of biodiversity. Quantifying habitat availability over large spatial scales is, however, challenging. Although remote sensing techniques have high spatial coverage, there is uncertainty associated with these estimates due to errors in classification. Alternatively, the extent of habitats can be estimated from ground‐based field survey. Financial and logistical constraints mean that on‐the‐ground surveys have much lower coverage, but they can produce much higher quality estimates of habitat extent in the areas that are surveyed. Here, we demonstrate a new combined model which uses both types of data to produce unified national estimates of the extent of four key habitats across Great Britain based on Countryside Survey and Land Cover Map. This approach considers that the true proportion of habitat per km² (Z_i) is unobserved, but both ground survey and remote sensing can be used to estimate Z_i. The model allows the relationship between remote sensing data and Z_i to be spatially biased while ground survey is assumed to be unbiased. Taking a statistical model‐based approach to integrating field survey and remote sensing data allows for information on bias and precision to be captured and propagated such that estimates produced and parameters estimated are robust and interpretable. A simulation study shows that the combined model should perform best when error in the ground survey data is low. We use repeat surveys to parameterize the variance of ground survey data and demonstrate that error in this data source is small. The model produced revised national estimates of broadleaved woodland, arable land, bog, and fen, marsh and swamp extent across Britain in 2007.     

围产期干细胞库质量管理体系构建

围产期干细胞库质量管理体系（QMS）建设是保障干细胞产品和服务健康发展的基础工作。本文比较分析美国输血协会（AABB）、细胞疗法认证基金会（FACT）和ISO 9001的标准的架构、内容和侧重点,重点论述围产期干细胞库QMS构建的方法、步骤和参考模式。参照权威机构标准建立和运行QMS,能够保障我国围产期干细胞库标准化、规范化和科学化的建设和管理,提升我国干细胞库能力和信任水平。良好的QMS进一步促进干细胞与精准医疗战略性新兴产业升级,为建设健康中国提供动力。     

Decoupling the Roles of Cell Shape and Mechanical Stress in Orienting and Cueing Epithelial Mitosis

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