Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

An intelligent system for estimating frog community calling activity and species richness

Over the past decade, dramatic declines in frog populations have been noticed worldwide. To examine this decline, monitoring frogs is becoming increasingly important. Compared to traditional field survey methods, recent advances in acoustic sensor technology have greatly extended spatial and temporal scales for monitoring animal populations. In this paper, we examine the problem of monitoring frog populations by analysing acoustic sensor data, where the population is reflected by community calling activity and species richness. Specifically, a novel acoustic event detection (AED) algorithm is first proposed to filter out those recordings without frog calls. Then, multi-label learning is used to classify each individual recording with six acoustic features: linear predictive coding coefficients, Mel-frequency cepstral coefficients, linear-frequency cepstral coefficients, acoustic complexity index, acoustic diversity index, and acoustic evenness index. Next, frog community calling activity and species richness are estimated by accumulating the results of AED and multi-label learning, respectively. Finally, ordinary least squares regression (OLS) is conducted to reveal the relationship between frog populations (frog calling activity and species richness) and weather variables (maximum temperature and rainfall). Experimental results demonstrate that our proposed intelligent system can significantly facilitate the effort to estimate frog community calling activity and species richness with comparable accuracies. The statistical results of OLS indicate that rainfall pattern has a lagged impact on frog community calling activity (significant in the first day after rainy day) and species richness (significant in the fourth day after rainy day). Temperature is shown to affect species richness but is less likely to change calling activity.     

城市景观生态风险评估框架与实践——以北京天坛地区为例

当前，城市景观生态风险研究缺少科学合理、方便实用的评估框架。作者基于景观生态风险评估基本范式，明确了城市景观生态服务价值的测算方法，分析了引起生态损害的自然因素和人类活动因素，形成了城市景观生态风险评估的技术框架和参数体系；继而以北京天坛地区为研究区，开展了典型城市景观生态风险的定量评估。结果表明：（1）天坛地区景观生态价值总量约为2.41亿元。区域的历史文化价值最高，教育和美学景观价值紧随其后。（2）城市景观生态受损概率呈现"北高南低"的空间分布格局。生态受损概率的高值区面积占整个区域总面积的22.2%，主要分布在珠市口、磁器口和崇文门附近区域。（3）城市景观生态风险呈现"北低南高"的空间分布格局。高风险区主要分布在天坛公园内的文物建筑周边。本研究提供了一个可参考的城市景观生态风险评估应用框架，对生态风险评估中的不确定性进行了讨论，研究针对天坛案例区的具体结论有助于城市管理者避免潜在的风险。     

Measurement of 7-dehydrocholesterol and cholesterol in hair can be used in the diagnosis of Smith-Lemli-Opitz syndrome

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50–4000 ng/mg and 30–6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.     

Isolation and PCR detection of <Emphasis Type="Italic">Enterobacter sakazakii</Emphasis> in South African food products,specifically infant formula milks

Enterobacter sakazakii has recently been identified as an opportunistic pathogen. The current culture-dependent detection methods for these bacteria are time-consuming and in this study a PCR method for the detection of E. sakazakii in South African food products, including an internal amplification control (IAC) was developed. DNA was isolated and amplified from the products and they were plated on selective growth media after pre-enrichment and enrichment in Enterobacteriaceae enrichment broth. Four of the 22 products tested positive for the presence of E. sakazakii, confirmed by PCR detection and growth on selective media. The PCR method proved effective in detecting E. sakazakii in South African products after three days and could serve as an alternative for traditional microbiological techniques.     

The importance of chemical environmental cues for juvenile Lethrinus nebulosus Forsskål (Lethrinidae, Teleostei) when settling into their first benthic habitat

A commercially important coral-reef fish, the spangled emperor Lethrinus nebulosus, settles into seagrass beds at the end of its pelagic larval phase, but the mechanism for locating these beds is unknown. To investigate this mechanism we first used a wide-choice, ex situ setup to examine the ability of captivity-reared naïve L. nebulosus settlers to select their first benthic habitat by reference to chemical cues. Second, we examined the morphology and ultrastructure of the nasal olfactory organ in settling L. nebulosus juveniles. We obtained the first evidence of a tropical seagrass-settling coral reef fish that can use chemical environmental cues in selecting its first benthic habitat at ranges up to at least 2 m. The L. nebulosus settlers exhibited a well developed pair of nasal olfactory organs, positioned in nares on the dorsal side of the head. These organs were elliptical radial rosettes, one in each of the olfactory chambers, and each comprised 12 lamellae, six on each side of a midline raphe, which were totally covered with sensory and non-sensory cilia, except for the margins. This type of cilia distribution is thought to indicate an acute sense of smell. The olfactory epithelium contained mature and immature ciliated receptor neurons bearing three to five cilia, and a second type of receptor neuron bearing six to eight microvilli.     

Simple and efficient cell disruption of extremely small quantities of mycelium of phytopathogenic mycotoxin-producing moulds for quantitative extraction of genomic DNA

DNA was efficiently and quantitatively isolated from extremely small quantities of mycelia (0.1–10 mg) of different phytopathogenic moulds by grinding freeze-dried mycelia with glass beads and then using a commercial DNA extraction kit. The efficiency of disruption of the mycelia and the quantitative DNA extraction was proved by microscopy and the quantification of isolated DNA by real time PCR. Presented at the 27^th Mykotoxin-Workshop, Dortmund, Germany, June 13–15, 2005 Financial support: German Research Foundation (DFG grant Pr 708/2). J.M. thanks the Cusanuswerk for a doctoral scholarship     

Biosensors based on peptide exposure show single molecule conformations in live cells

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Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.