山西省农田生境复杂程度对小型啮齿动物多样性的影响

目的探索山西省不同地区农田小型啮齿动物的多样性与环境因子的关系,为制定山西省农田小型啮齿动物区域性综合治理措施提供主要依据。方法在山西省南部的临汾市隰县、中部的太原市娄烦县和北部的忻州市五台县设立研究区,在3-11月采用夹日法调查各研究区农田小型啮齿动物的多样性,以调查期内7月中旬的植被异质性指数来判定研究区的生境复杂程度,探讨山西省农田的生境复杂程度对小型啮齿动物多样性的影响。结果山西省农田小型啮齿动物的丰富度与其多样性指数和植被异质性指数的相关系数为0．998,呈显著的正相关;物种优势度指数与植被异质性指数的相关系数达-1．000,呈极显著负相关关系;而捕获率及均匀度指数和植被异质性指数只有0．404和0．994,其相关性并不显著。结论栖息环境的复杂程度是影响小型啮齿动物群落丰富度和多样性的关键因子,而农田中各植被类型盖度的均匀程度可能与小型啮齿动物群落的均匀度指数有关。     

Kellann综合征遗传学研究进展

卡尔曼综合征（Kallmann syndrome,KS）是一种先天性促性腺功能低下和嗅觉缺失联合出现的疾病。该病具有高度的临床异质性和遗传异质性,目前对该病的研究发现有18个相关致病基因,分别为 KAL1、FGFR1、PROKR2、PROK2、CHD7、FGF8、WDR11、NELF、HS6ST1、SEMA3A、HESX1、SOX10、IL17RD、FGF17、SPRY4、DUSP6、FLRT3和AXL,然而这些基因中研究相对透彻的前6种基因（KAL1、FGFR1、PROKR2、PROK2、CHD7、FGF8）仅约占其致病因素的30%,仍有约70%的致病因素和机制未知。综述KS的临床评估、发病机制、相关致病基因研究新进展以及该病的部分可逆性和早期诊断等。     

Effects of differential habitat warming on complex communities

Food webs unfold across a mosaic of micro and macro habitats, with each habitat coupled by mobile consumers that behave in response to local environmental conditions. Despite this fundamental characteristic of nature, research on how climate change will affect whole ecosystems has overlooked (i) that climate warming will generally affect habitats differently and (ii) that mobile consumers may respond to this differential change in a manner that may fundamentally alter the energy pathways that sustain ecosystems. This reasoning suggests a powerful, but largely unexplored, avenue for studying the impacts of climate change on ecosystem functioning. Here, we use lake ecosystems to show that predictable behavioral adjustments to local temperature differentials govern a fundamental structural shift across 54 food webs. Data show that the trophic pathways from basal resources to a cold-adapted predator shift toward greater reliance on a cold-water refuge habitat, and food chain length increases, as air temperatures rise. Notably, cold-adapted predator behavior may substantially drive this decoupling effect across the climatic range in our study independent of warmer-adapted species responses (for example, changes in near-shore species abundance and predator absence). Such modifications reflect a flexible food web architecture that requires more attention from climate change research. The trophic pathway restructuring documented here is expected to alter biomass accumulation, through the regulation of energy fluxes to predators, and thus potentially threatens ecosystem sustainability in times of rapid environmental change.Natural systems are inherently complex entities, wherein organisms act as agents of material and biomass transport (1) weaving food webs through a mosaic thermal environment. Direct temperature effects on trophic interactions arise through thermal regulation of an organism’s physiology and behavior (2–5). For ecotherms (that is, organisms whose body temperature is aligned with ambient temperature), several biological rates show unimodal responses to temperature (2, 3, 6), and correspondingly, studies have shown that consumption rates initially rise with warming to a peak rate and then fall rapidly approaching a critical temperature (6). Understanding the ways that these organism responses alter food webs, and how these food web responses affect ecosystem function, are key requirements to predicting climate change impacts on ecosystems (7–11).A simple way to think about temperature’s effects on any single trophic interaction is through the general linear consumption function:Consumption(per?capita) = a?t_s?R, [1]where a is the attack rate, t_s is the time searching, and R is the resource biomass density. The direct effects of temperature on an organism’s ability to encounter and capture resources in a given habitat may largely depend on a, and t_s (with potential indirect effects relative to the consumer through temperature influences on R). The argument for the temperature dependence of attack rate (a) is relatively straightforward. Temperature mediates foraging velocity (3), and considering all else equal, velocity determines encounter rates and prey capture success. The influence of temperature on time searching is a little more complex, but the general expectation is that its influence will be shaped by the requirement that the organism allocate its feeding time in different patches or habitats to increase its fitness (5). Such thermal limitation of search time would lead to reductions of interaction strength in warming habitats—in effect, temperature would mediate prey availability (e.g., when temperature exceeds physiological limits). What remains to complete the consumption equation above is the effect of temperature on R, both the direct effects (for example, the impact of warming on R’s productivity) and indirect effects (for example, impact of warming on the number and consumption capabilities of consumers competing for R) (12, 13). Note that the numerical response (i.e., biomass accumulation) of the consumer may depend on additional vital rates (e.g., conversion efficiency). The conversion of prey biomass to predator biomass (often denoted e) may not change with temperature (2, 3), although recent research suggests that e may be temperature dependent if consumers switch among resources with different elemental composition to balance changing metabolic and somatic demands (14). Nevertheless, we focus on consumption (a, t_s, R) as a means to build an argument for temperature’s influence on trophic structure.Here, we extend the logic that underlies this simple representation of temperature-dependent consumption to develop hypotheses that link temperature differentials, through direct and indirect means, to spatial food web structure. Spatially simple laboratory studies of food webs suggest that larger-bodied, higher trophic level organisms are likely to have high extinction risk with ambient warming (15). In natural systems, these higher-order predators provide a spatially unifying component to food webs: their high mobility enables them to forage among different habitats, coupling food chains with unique basal resource groups (16–18). This coupling structure can be an important part of sustaining higher-order consumers with consequences for food chain length, trophic control, and ecosystem stability (16, 19–21). For example, theory argues that reduced access to a novel resource compartment may decrease a consumer’s biomass (19, 20), thereby increasing the chance of local extinction from a random event. When accessibility is limited, reduced coupling may alter food chain length if habitats contain prey that differ in trophic position (22) or if higher level prey increase, with reduced trophic control, and consequently predators become less omnivorous (19, 21). Given that temperature change can drive asymmetric responses in species that differ in thermal tolerance, the influence of spatially structuring elements on the response of a food web to warming will depend not only on the direct responses of consumers to temperature (2, 3, 5) but also those responses of other interacting community members (i.e., resources and competing predators) (12, 13, 23). We test notions of the structuring effects of differential temperature on spatially coupled food webs (thermal-accessibility hypothesis), using boreal lakes as a natural study system (Fig. 1). To make this test, we assembled one of the largest comparative food web datasets on record: 54 ecosystems, characterized using >3,000 isotope (N and C) samples.Open in a separate windowFig. 1.Simple schematic showing expected effects of differential warming on habitat coupling (horizontal axis) and habitat use (vertical axis) by lake trout in cold (Upper) and warm (Lower) lakes. A thermal accessibility argument predicts that lake trout couple into the thermally exposed near-shore resource channel less and should use (proportionally) that habitat less under warmer conditions (indicated by lake trout position). The arrow direction and thickness indicate coupling direction and strength. The letters in the upper diagram identify trophic groups used in both cold (Upper) and warm (Lower) lake depictions: lake trout (a), pelagic forage fish (b), pelagic invertebrates (c), pelagic phytoplankton (d), littoral fish (e), littoral invertebrates (f), and benthic algae (g). To the right in the diagram, we show thermal profile data contrasting temperature at depth from Victoria Lake [cold; summer air temperature, 15.5 °C; latitude (lat), 49.62306; longitude (long), −91.54889] and Charleston Lake (warm; summer air temperature, 19.7 °C; lat, 44.53611; long, −76.01194) taken at the time of sampling. Temperature is visually highlighted with darker blue (cold) and darker red (warm) hues. These lakes experience temperatures near the cold and warm endpoints for our dataset and are of the same order of magnitude in size, and both had thermal profiles recorded to 30 m.Freshwater lakes are particularly sensitive to climate change as lake habitats are structured by climate-driven water temperature and many biota are vulnerable to ambient temperature change (24). A key habitat feature of boreal lakes is thermal stratification, an effect of antagonistic physical forces of mixing by wind energy and resistance to mixing by solar heating that separates cold, more dense water (hypolimnion) from warmer, less dense surface water (epilimnion) (25). The stratification process creates a potential for temperature differentials between deeper offshore and shallower near-shore subhabitats within a lake, as temperatures remain relatively constant in deep habitats, whereas shallower near-shore temperatures are strongly influenced by air temperatures (26). Monitoring in the boreal region (27, 28) has shown that rising air temperature warms surface waters, accelerates the stratification process, and extends the duration of stratification; thus, air temperature is a primary determinant of lake thermal heterogeneity.Most aquatic organisms (e.g., invertebrates, amphibians, fish) are ectotherms; therefore, the demands of the thermal environment arguably form the most influential set of abiotic factors aquatic organisms must satisfy (29, 30) (including increased oxygen requirements in warmer water). Thermal differentiation in lakes typically corresponds with the species differences that characterize offshore and near-shore habitats. Conveniently, biomass flow from these habitats through a food web can be traced using stable carbon and nitrogen isotope ratios due to isotope differences at the base of the food web between phytoplankton (offshore) and benthic algae (near-shore) (18, 22, 31, 32).We focus our study on the trophic pathways that flow from basal resources to lake trout (Salvelinus namaycush), a vulnerable, cold-adapted (10–12 °C preference) apex predator (33) estimated to reside in 66,500 Canadian lakes (34) (Fig. 1). Previous studies show that lake trout play a keystone structural role in integrating resource pools in offshore and near-shore habitats (18, 21, 22, 31). In what follows, we test the direct and indirect effects of differential warming on this natural system (lake trout food web) across a summer mean temperature gradient ranging 15–20 °C. At the warmer end of this range, surface water temperatures will often exceed the physiological tolerance of lake trout and should restrict accessibility into the near-shore habitat (Fig. 1, Lower). Given this thermal mechanism, we predict that lake trout in warmer climates may change their habitat use to deeper waters and this spatial behavior may shift the degree that near-shore resource pools are coupled by this predator relative to cooler climates (Fig. 1). We further consider whether spatial responses are associated with a shift in the length of the apex predator’s food chain. This thermal-accessibility–mediated restructuring of fundamental food web structure is considered along with complementary notions of warm-tolerant competitor effects and relative prey abundance changes with climate.     

CT signal heterogeneity of abdominal aortic aneurysm as a possible predictive biomarker for expansion

Objective

There is a need for prognostic biomarkers for risk assessment of small abdominal aortic aneurysm (AAA). Since CT textural analysis of tissue is a recognized feature of adverse biology and patient outcome in other diseases, we investigated it as a possible biomarker in small AAA.

Methods

Fifty consecutive patients (46-men, 4-woman, median-age 75y, range 56–85) with small AAA (3–5.5 cm) under surveillance undergoing serial ultrasound were prospectively recruited and assessed at baseline with CT texture analysis (CTTA) and ¹⁸F-Fluorodeoxyglucose positron emission tomography (¹⁸F-FDG-PET). We followed forty patients (36-men, 4-woman, median-age = 74 y, range 60–85, participation rate = 80% for 1 year. For each axial image, CTTA using the filtration-histogram technique was carried out using a software algorithm that selectively extracts texture features of different coarseness (fine, medium and coarse) and intensity variation. Standard-deviation (SD) and kurtosis (K) at each feature-scale were measured. The maximum standardized uptake value (SUV_max) of ¹⁸F-FDG in each axial image of the AAA was also measured with corrections for blood pool ¹⁸F-FDG activity to assess AAA metabolic activity. Specificity, sensitivity, and c-statistics were calculated with 95% confidence intervals for prediction of significant AAA expansion (≥2 mm) by CTTA measures before and after adjusting for clinical variables.

Results

The median aneurysm expansion at 12 months was 2.0 mm, (IQR 0.0–4.0). Coarse texture SD correlated inversely with AAA SUV_max (r_s = −0.456, P = 0.003). Medium coarse texture K correlated significantly with future AAA expansion adjusted for baseline size (r_s = 0.343, P = 0.030). AAA SUV_max correlated inversely with AAA expansion corrected for baseline size (r_s = −0.383, P = 0.015). Medium texture K was a strong predictor of significant AAA expansion (area under the Receiver-operating-characteristic (ROC) curve was 0.813) after adjusting for clinical variables.

Conclusion

We have shown evidence that CT signal heterogeneity measurements in small aortic aneurysm may be considered as a risk stratification tool in future prospective studies to identify aneurysms at risk of significant expansion. CT textural data appears to reflect AAA metabolism measured by PET.     

MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

Glioblastomas (GBMs) diffusely infiltrate the brain, making complete removal by surgical resection impossible. The mixture of neoplastic and nonneoplastic cells that remain after surgery form the biological context for adjuvant therapeutic intervention and recurrence. We performed RNA-sequencing (RNA-seq) and histological analysis on radiographically guided biopsies taken from different regions of GBM and showed that the tissue contained within the contrast-enhancing (CE) core of tumors have different cellular and molecular compositions compared with tissue from the nonenhancing (NE) margins of tumors. Comparisons with the The Cancer Genome Atlas dataset showed that the samples from CE regions resembled the proneural, classical, or mesenchymal subtypes of GBM, whereas the samples from the NE regions predominantly resembled the neural subtype. Computational deconvolution of the RNA-seq data revealed that contributions from nonneoplastic brain cells significantly influence the expression pattern in the NE samples. Gene ontology analysis showed that the cell type-specific expression patterns were functionally distinct and highly enriched in genes associated with the corresponding cell phenotypes. Comparing the RNA-seq data from the GBM samples to that of nonneoplastic brain revealed that the differentially expressed genes are distributed across multiple cell types. Notably, the patterns of cell type-specific alterations varied between the different GBM subtypes: the NE regions of proneural tumors were enriched in oligodendrocyte progenitor genes, whereas the NE regions of mesenchymal GBM were enriched in astrocytic and microglial genes. These subtype-specific patterns provide new insights into molecular and cellular composition of the infiltrative margins of GBM.Glioma cells diffusely infiltrate the brain and intermingle with neural cells in the surrounding brain tissue, resulting in a complex mixture that includes variable proportions of glioma cells, neurons, and various lineages of reactive or recruited glia. At the infiltrative margins of glioblastoma (GBM), the nonneoplastic brain cells can far outnumber the glioma cells and, therefore, will have a significant effect on the molecular features of the tissue. Expression profiling and whole genome sequencing from hundreds of GBM specimens by The Cancer Genome Atlas (TCGA) has revealed a broad spectrum of genetic alterations and discrete expression signatures or subtypes that stratify the majority of patients (1, 2). These studies analyzed tumor samples that were removed during surgery, but were not radiographically localized and, therefore, do not address the question of how the molecular signature may vary across different regions of a tumor. Recent studies have sampled multiple regions within a GBM and shown that more than one molecular subtype can coexist within a single tumor (3). However, the effect of varying cellular composition on GBM subtype, particularly the contribution of nonneoplastic cells, has not been addressed.GBM typically appears as a contrast-enhancing mass, which represents the highly cellular core of the tumor with vascular proliferation and blood–brain barrier breakdown. This contrast-enhancing (CE) region is typically surrounded by a diffuse, nonenhancing (NE) region of abnormal T2/FLAIR signal, which represents edematous brain tissue with varying numbers of infiltrating glioma cells. The primary treatment of GBM is surgical resection, during which the surgeon removes as much of the CE mass as possible. Thus, molecular and genetic profiling of GBM, including the TCGA effort, has predominantly used samples from the CE regions of tumor. However, it is the NE regions of glioma that are left behind after surgery, which neurooncologists must treat and which inevitably give rise to recurrence. Thus, there is immense prognostic and therapeutic significance to understanding the cellular and molecular features of the NE regions of tumor, yet often these areas are not resected and, therefore, have not been directly studied.There are two major obstacles to this goal. The first is the surgical challenge of radiographically localized sampling of the NE tumor margins. The second is the issue of the complex cellular composition that characterizes these regions of diffuse infiltration. In this study, we have addressed both challenges, and associated distinct molecular and cellular features of the NE regions of GBM with the molecular subtype, as defined by the resected CE regions of the tumor.