Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts

We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Detection of a putative hemolysin operon, hhdBA, of Haemophilus parasuis from pigs with Glasser disease

The aim of the current study was to investigate whether polymerase chain reaction amplification of 16S ribosomal (r)RNA and a putative hemolysin gene operon, hhdBA, can be used to monitor live pigs for the presence of Haemophilus parasuis and predict the virulence of the strains present. Nasal cavity swabs were taken from 30 live, healthy, 1- to 8-week-old pigs on a weekly cycle from a commercial Thai nursery pig herd. A total of 27 of these pigs (90%) tested positive for H. parasuis as early as week 1 of age. None of the H. parasuis-positive samples from healthy pigs was positive for the hhdBA genes. At the same pig nursery, swab samples from nasal cavity, tonsil, trachea, and lung, and exudate samples from pleural/peritoneal cavity were taken from 30 dead pigs displaying typical pathological lesions consistent with Glasser disease. Twenty-two of 140 samples (15.7%) taken from 30 diseased pigs yielded a positive result for H. parasuis. Samples from the exudate (27%) yielded the most positive results, followed by lung, tracheal swab, tonsil, and nasal swab, respectively. Out of 22 positive samples, 12 samples (54.5%) harbored hhdA and/or hhdB genes. Detection rates of hhdA were higher than hhdB. None of the H. parasuis-positive samples taken from nasal cavity of diseased pigs tested positive for hhdBA genes. More work is required to determine if the detection of hhdBA genes is useful for identifying the virulence potential of H. parasuis field isolates.

Infrared thermal imaging for automated detection of diabetic foot complications

Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis

Early identification of diabetic foot complications and their precursors is essential in preventing their devastating consequences, such as foot infection and amputation. Frequent, automatic risk assessment by an intelligent telemedicine system might be feasible and cost effective. Infrared thermography is a promising modality for such a system. The temperature differences between corresponding areas on contralateral feet are the clinically significant parameters. This asymmetric analysis is hindered by (1) foot segmentation errors, especially when the foot temperature and the ambient temperature are comparable, and by (2) different shapes and sizes between contralateral feet due to deformities or minor amputations. To circumvent the first problem, we used a color image and a thermal image acquired synchronously. Foot regions, detected in the color image, were rigidly registered to the thermal image. This resulted in 97.8% ± 1.1% sensitivity and 98.4% ± 0.5% specificity over 76 high-risk diabetic patients with manual annotation as a reference. Nonrigid landmark-based registration with Bsplines solved the second problem. Corresponding points in the two feet could be found regardless of the shapes and sizes of the feet. With that, the temperature difference of the left and right feet could be obtained.

Rhizoctonia -Scots pine interactions: detection, impact on seedling performance and host defence gene response

Rhizoctonia spp. are ubiquitous soil inhabiting fungi that enter into pathogenic or symbiotic associations with plants. In general Rhizoctonia spp. are regarded as plant pathogenic fungi and many cause root rot and other plant diseases which results in considerable economic losses both in agriculture and forestry. Many Rhizoctonia strains enter into symbiotic mycorrhizal associations with orchids and some hypovirulent strains are promising biocontrol candidates in preventing host plant infection by pathogenic Rhizoctonia strains. This work focuses on uni- and binucleate Rhizoctonia (respectively UNR and BNR) strains belonging to the teleomorphic genus Ceratobasidium, but multinucleate Rhizoctonia (MNR) belonging to teleomorphic genus Thanatephorus and ectomycorrhizal fungal species, such as Suillus bovinus, were also included in DNA probe development work. Strain specific probes were developed to target rDNA ITS (internal transcribed spacer) sequences (ITS1, 5.8S and ITS2) and applied in Southern dot blot and liquid hybridization assays. Liquid hybridization was more sensitive and the size of the hybridized PCR products could be detected simultaneously, but the advantage in Southern hybridization was that sample DNA could be used without additional PCR amplification. The impacts of four Finnish BNR Ceratorhiza sp. strains 251, 266, 268 and 269 were investigated on Scot pine (Pinus sylvestris) seedling growth, and the infection biology and infection levels were microscopically examined following tryphan blue staining of infected roots. All BNR strains enhanced early seedling growth and affected the root architecture, while the infection levels remained low. The fungal infection was restricted to the outer cortical regions of long roots and typical monilioid cells detected with strain 268. The interactions of pathogenic UNR Ceratobasidium bicorne strain 1983-111/1N, and endophytic BNR Ceratorhiza sp. strain 268 were studied in single or dual inoculated Scots pine roots. The fungal infection levels and host defence-gene activity of nine transcripts [phenylalanine ammonia lyase (pal1), silbene synthase (STS), chalcone synthase (CHS), short-root specific peroxidase (Psyp1), antimicrobial peptide gene (Sp-AMP), rapidly elicited defence-related gene (PsACRE), germin-like protein (PsGER1), CuZn- superoxide dismutase (SOD), and dehydrin-like protein (dhy-like)] were measured from differentially treated and un-treated control roots by quantitative real time PCR (qRT-PCR). The infection level of pathogenic UNR was restricted in BNR- pre-inoculated Scots pine roots, while UNR was more competitive in simultaneous dual infection. The STS transcript was highly up-regulated in all treated roots, while CHS, pal1, and Psyp1 transcripts were more moderately activated. No significant activity of Sp-AMP, PsACRE, PsGER1, SOD, or dhy-like transcripts were detected compared to control roots. The integrated experiments presented, provide tools to assist in the future detection of these fungi in the environment and to understand the host infection biology and defence, and relationships between these interacting fungi in roots and soils. This study further confirms the complexity of the Rhizoctonia group both phylogenetically and in their infection biology and plant host specificity. The knowledge obtained could be applied in integrated forestry nursery management programmes.

Microbial diversity in the municipal composting process and development of detection methods

Composting refers to aerobic degradation of organic material and is one of the main waste treatment methods used in Finland for treating separated organic waste. The composting process allows converting organic waste to a humus-like end product which can be used to increase the organic matter in agricultural soils, in gardening, or in landscaping. Microbes play a key role as degraders during the composting-process, and the microbiology of composting has been studied for decades, but there are still open questions regarding the microbiota in industrial composting processes. It is known that with the traditional, culturing-based methods only a small fraction, below 1%, of the species in a sample is normally detected. In recent years an immense diversity of bacteria, fungi and archaea has been found to occupy many different environments. Therefore the methods of characterising microbes constantly need to be developed further. In this thesis the presence of fungi and bacteria in full-scale and pilot-scale composting processes was characterised with cloning and sequencing. Several clone libraries were constructed and altogether nearly 6000 clones were sequenced. The microbial communities detected in this study were found to differ from the compost microbes observed in previous research with cultivation based methods or with molecular methods from processes of smaller scale, although there were similarities as well. The bacterial diversity was high. Based on the non-parametric coverage estimations, the number of bacterial operational taxonomic units (OTU) in certain stages of composting was over 500. Sequences similar to Lactobacillus and Acetobacteria were frequently detected in the early stages of drum composting. In tunnel stages of composting the bacterial community comprised of Bacillus, Thermoactinomyces, Actinobacteria and Lactobacillus. The fungal diversity was found to be high and phylotypes similar to yeasts were abundantly found in the full-scale drum and tunnel processes. In addition to phylotypes similar to Candida, Pichia and Geotrichum moulds from genus Thermomyces and Penicillium were observed in tunnel stages of composting. Zygomycetes were detected in the pilot-scale composting processes and in the compost piles. In some of the samples there were a few abundant phylotypes present in the clone libraries that masked the rare ones. The rare phylotypes were of interest and a method for collecting them from clone libraries for sequencing was developed. With negative selection of the abundant phylotyps the rare ones were picked from the clone libraries. Thus 41% of the clones in the studied clone libraries were sequenced. Since microbes play a central role in composting and in many other biotechnological processes, rapid methods for characterization of microbial diversity would be of value, both scientifically and commercially. Current methods, however, lack sensitivity and specificity and are therefore under development. Microarrays have been used in microbial ecology for a decade to study the presence or absence of certain microbes of interest in a multiplex manner. The sequence database collected in this thesis was used as basis for probe design and microarray development. The enzyme assisted detection method, ligation-detection-reaction (LDR) based microarray, was adapted for species-level detection of microbes characteristic of each stage of the composting process. With the use of a specially designed control probe it was established that a species specific probe can detect target DNA representing as little as 0.04% of total DNA in a sample. The developed microarray can be used to monitor composting processes or the hygienisation of the compost end product. A large compost microbe sequence dataset was collected and analysed in this thesis. The results provide valuable information on microbial community composition during industrial scale composting processes. The microarray method was developed based on the sequence database collected in this study. The method can be utilised in following the fate of interesting microbes during composting process in an extremely sensitive and specific manner. The platform for the microarray is universal and the method can easily be adapted for studying microbes from environments other than compost.

Early diagnosis of breast cancer

The greatest effect on reducing mortality in breast cancer comes from the detection and treatment of invasive cancer when it is as small as possible. Although mammography screening is known to be effective, observer errors are frequent and false-negative cancers can be found in retrospective studies of prior mammograms. In the year 2001, 67 women with 69 surgically proven cancers detected at screening in the Mammography Centre of Helsinki University Hospital had previous mammograms as well. These mammograms were analyzed by an experienced screening radiologist, who found that 36 lesions were already visible in previous screening rounds. CAD (Second Look v. 4.01) detected 23 of these missed lesions. Eight readers with different kinds of experience with mammography screening read the films of 200 women with and without CAD. These films included 35 of those missed lesions and 16 screen-detected cancers. CAD sensitivity was 70.6% and specificity 15.8%. Use of CAD lengthened the mean time spent for readings but did not significantly affect readers sensitivities or specificities. Therefore the use of applied version of CAD (Second Look v. 4.01) is questionable. Because none of those eight readers found exactly same cancers, two reading methods were compared: summarized independent reading (at least a single cancer-positive opinion within the group considered decisive) and conference consensus reading (the cancer-positive opinion of the reader majority was considered decisive). The greatest sensitivity of 74.5% was achieved when the independent readings of 4 best-performing readers were summarized. Overall the summarized independent readings were more sensitive than conference consensus readings (64.7% vs. 43.1%) while there was far less difference in mean specificities (92.4% vs. 97.7%). After detecting suspicious lesion, the radiologist has to decide what is the most accurate, fast, and cost-effective means of further work-up. The feasibility of FNAC and CNB in the diagnosis of breast lesions was compared in non-randomised, retrospective study of 580 (503 malignant) breast lesions of 572 patients. The absolute sensitivity for CNB was better than for FNAC, 96% (206/214) vs. 67% (194/289) (p < 0.0001). An additional needle biopsy or surgical biopsy was performed for 93 and 62 patients with FNAC, but for only 2 and 33 patients with CNB. The frequent need of supplement biopsies and unnecessary axillary operations due to false-positive findings made FNAC (294 ) more expensive than CNB (223 ), and because the advantage of quick analysis vanishes during the overall diagnostic and referral process, it is recommendable to use CNB as initial biopsy method.

Mass spectrometry and n-in-one analytics in early drug discovery: Combinatorial chemistry libraries, lipophilicity and absorption screening

This thesis describes current and past n-in-one methods and presents three early experimental studies using mass spectrometry and the triple quadrupole instrument on the application of n-in-one in drug discovery. N-in-one strategy pools and mix samples in drug discovery prior to measurement or analysis. This allows the most promising compounds to be rapidly identified and then analysed. Nowadays properties of drugs are characterised earlier and in parallel with pharmacological efficacy. Studies presented here use in vitro methods as caco-2 cells and immobilized artificial membrane chromatography for drug absorption and lipophilicity measurements. The high sensitivity and selectivity of liquid chromatography mass spectrometry are especially important for new analytical methods using n-in-one. In the first study, the fragmentation patterns of ten nitrophenoxy benzoate compounds, serial homology, were characterised and the presence of the compounds was determined in a combinatorial library. The influence of one or two nitro substituents and the alkyl chain length of methyl to pentyl on collision-induced fragmentation was studied, and interesting structurefragmentation relationships were detected. Two nitro group compounds increased fragmentation compared to one nitro group, whereas less fragmentation was noted in molecules with a longer alkyl chain. The most abundant product ions were nitrophenoxy ions, which were also tested in the precursor ion screening of the combinatorial library. In the second study, the immobilized artificial membrane chromatographic method was transferred from ultraviolet detection to mass spectrometric analysis and a new method was developed. Mass spectra were scanned and the chromatographic retention of compounds was analysed using extract ion chromatograms. When changing detectors and buffers and including n-in-one in the method, the results showed good correlation. Finally, the results demonstrated that mass spectrometric detection with gradient elution can provide a rapid and convenient n-in-one method for ranking the lipophilic properties of several structurally diverse compounds simultaneously. In the final study, a new method was developed for caco-2 samples. Compounds were separated by liquid chromatography and quantified by selected reaction monitoring using mass spectrometry. This method was used for caco-2 samples, where absorption of ten chemically and physiologically different compounds was screened using both single and nin- one approaches. These three studies used mass spectrometry for compound identification, method transfer and quantitation in the area of mixture analysis. Different mass spectrometric scanning modes for the triple quadrupole instrument were used in each method. Early drug discovery with n-in-one is area where mass spectrometric analysis, its possibilities and proper use, is especially important.

Identification of immuno-dominant antigens of Trypanosoma evansi for detection of chronic trypanosomosis using experimentally infected equines

Trypanosoma evansi is the most extensively distributed trypanosome responsible for disease called surra in livestock in many countries including frequent outbreaks in India. The prevalence of this disease is most commonly reported by standard parasitological detection methods (SPDM); however, antibody ELISA is being in practice by locally produced whole cell lysate (WCL) antigens in many countries. In the present investigation, we attempted to identify and purify immuno dominant, infection specific trypanosome antigens from T. evansi proteome using experimentally infected equine serum by immuno blot. Three immuno dominant clusters of proteins i.e. 62-66 kDa, 52-55 kDa and 41-43 kDa were identified based on their consistent reactivity with donkey sequential serum experimentally infected T. evansi up to 280 days post infection (dpi). The protein cluster of 62-66 kDa was purified in bulk in native form and comparatively evaluated with whole cell lysate antigen (WCL). ELISA and immuno blot showed that polypeptide of this cluster is 100% sensitive in detection of early and chronic infection. Further, this protein cluster was also found immuno reactive against hyper immune serum raised against predominantly 66 kDa exo antigen, revealed that this is a common immunodominant moieties in proteome and secretome of T. evansi.

Detection of Atomic Scale Changes in the Free Volume Void Size of Three-Dimensional Colorectal Cancer Cell Culture Using Positron Annihilation Lifetime Spectroscopy

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Detection of particles with a cloud chamber

Cloud chambers were essential devices in early nuclear and particle physics research. Superseded by more modern detectors in actual research, they still remain very interesting pedagogical apparatus. This thesis attempts to give a global view on this topic. To do so, a review of the physical foundations of the diffusion cloud chamber, in which an alcohol is supersaturated by cooling it with a thermal reservoir, is carried out. Its main results are then applied to analyse the working conditions inside the chamber. The analysis remarks the importance of using an appropriate alcohol, such as isopropanol, as well as a strong cooling system, which for isopropanol needs to reach −40ºC. That theoretical study is complemented with experimental tests that were performed with what is the usual design of a home-made cloud chamber. An effective setup is established, which highlights details such as a grazing illumination, a direct contact with the cooling reservoir through a wide metal plate, or the importance of avoiding vapour removal. Apart from that, video results of different phenomena that cloud chamber allow to observe are also presented. Overall, it is aimed to present a physical insight that pedagogical papers usually lack.

HPV infection, a described cause for human cancer: HPV detection and molecular mechanisms of HPV carcinogenesis (Review).

[en]Human papillomavirus (HPV) belongs to the Papillomaviridae virus family and it is one of the most common sexual transmission infections. HPV genome is composed of eight genes, including two early genes and six late genes. Among these late genes, E6 and E7 code for proteins that trigger cell-cycle re-entry in infected cells, which can lead to cervical cancer development. The IARC (International Agency for Research Cancer) proposed a guideline based on Hill’s criteria to determine whether the relation between HPV infection and cervical cancer is causal or not. Epidemiological studies have demonstrated that HPV infection is a necessary but non-sufficient cause for cervical cancer. Furthermore, HPV infection is considered the first necessary cause described of a human cancer, being HPV16 and 18 carcinogenic to humans and the most studied types. Cervical cancer is the second leading cause of cancer death among women worldwide. Different screening programs are carried out with the aim of preventing cervical cancer; such as cytologies and HPV tests. There are two main methods which are equally usable to detect HPV: the real-time PCR assays and the array assays. Regarding the molecular mechanisms of HPV mediated malignancies, E2, E6 and E7 proteins of HPV16 lead to immune response evasion, inducing IL-10 and TGF-β1 gene expression. Besides, E6 and E7 proteins allow cell-cycle reentry, phosphorylating RB and ubiquitinating p53 respectively. HPV genome integration in host genome leads to the alteration of host and viral genes expression, including oncogenes and tumor suppressor genes. However, the differences of E6 and E7 oncoproteins in different HPV types is poorly known due to the fact that almost the most studied HPV type has been HPV16.

On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection

Mammographic mass detection is an important task for the early diagnosis of breast cancer. However, it is difficult to distinguish masses from normal regions because of their abundant morphological characteristics and ambiguous margins. To improve the mass detection performance, it is essential to effectively preprocess mammogram to preserve both the intensity distribution and morphological characteristics of regions. In this paper, morphological component analysis is first introduced to decompose a mammogram into a piecewise-smooth component and a texture component. The former is utilized in our detection scheme as it effectively suppresses both structural noises and effects of blood vessels. Then, we propose two novel concentric layer criteria to detect different types of suspicious regions in a mammogram. The combination is evaluated based on the Digital Database for Screening Mammography, where 100 malignant cases and 50 benign cases are utilized. The sensitivity of the proposed scheme is 99% in malignant, 88% in benign, and 95.3% in all types of cases. The results show that the proposed detection scheme achieves satisfactory detection performance and preferable compromises between sensitivity and false positive rates.

Study on early-stage development of conchospore in Porphyra yezoensis Ueda

Porphyra yezoensis Ueda (Rhodophyta) is a seaweed of economic importance with a typical dimorphic life cycle consisting of a leafy gametophyte and a filamentous sporophyte. Recently, it has been recognized as a model system for fundamental and applied studies in marine biological sciences. Conchospore, a major spore linking the two distinct multicellular phases in the life cycle, is most widely used in the breeding of P. yezoensis. In this paper, the early-stage development of conchospore, including the attachment and the cell wall formation, was studied with fluorescent reagents staining and Scanning Electron Microscopy detection. Results displayed: (I) the cell wall began to be generated after culturing for 4 h in the attached conchospores; (2) the initially released conchospores were plastids with some filmy, amorphous substance on the surface, and they attached to the fibers firmly via the actively secreted mucilaginous substances after their touch to the fibers; (3) cellulase and pectolase prohibited the attachment of conchospores in the different ways; and (4) only attached conchospores generated cell walls and developed normally, while the suspending ones could not. It indicated that the cellulose played crucial roles in the permanent attachment as the pectin did in the initial attachment. The conchospore attachment seemed to trigger the cell wall formation and the further development. Affects of light on the development of conchospores were also discussed. The results showed that high intensity (200 mu mol.m(-2).s(-1)) and long-wave (>= 580 nm) light facilitated the division rate of conchospores. (C) 2008 Elsevier B.V. All rights reserved.