920 resultados para NIRS. Bactérias. PCA. SIMCA. PLS-DA


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Two key quality traits in milling wheat are flour yield (FY) and water absorption (WA). Ideally, breeders would prefer to use markers to select promising lines rather than time consuming rheology tests. In this study, we measured FY and WA on a wheat mapping population (Lang/QT8766) of 162 individuals grown in two replicated field experiments at three locations over 2 years. We also carried out near infrared reflectance spectroscopy (NIRS) predictions on the grain for these traits to see if NIRS phenotypic data could provide useful mapping results when compared to the reference phenotypic data. Several common QTLs were identified for FY and WA by both sets of data. The QTL on chromosome 4D was a consistently recurring QTL region for both traits. The QTL on chromosome 2A was positively linked to protein content which was supported by genetic correlation data. The results also indicated it was possible to obtain useful phenotypic data for mapping FY and WA using NIRS data. This would save time and costs as NIRS is quicker and cheaper than current rheology methods.

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BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

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Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

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Reliable age information is vital for effective fisheries management, yet age determinations are absent for many deepwater sharks as they cannot be aged using traditional methods of growth bands counts. An alternative approach to ageing using near infrared spectroscopy (NIRS) was investigated using dorsal fin spines, vertebrae and fin clips of three species of deepwater sharks. Ages were successfully estimated for the two dogfish, Squalus megalops and Squalus montalbani, and NIRS spectra were correlated with body size in the catshark, Asymbolus pallidus. Correlations between estimated-ages of the dogfish dorsal fin spines and their NIRS spectra were good, with S. megalops R2=0.82 and S. montalbani R2=0.73. NIRS spectra from S. megalops vertebrae and fin clips that have no visible growth bands were correlated with estimated-ages, with R2=0.89 and 0.76, respectively. NIRS has the capacity to non-lethally estimate ages from fin spines and fin clips, and thus could significantly reduce the numbers of sharks that need to be lethally sampled for ageing studies. The detection of ageing materials by NIRS in poorly calcified deepwater shark vertebrae could potentially enable ageing of this group of sharks that are vulnerable to exploitation.

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Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

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Historical sediment nutrient concentrations and heavy-metal distributions were studied in five embayments in the Gulf of Finland and an adjacent lake. The main objective of the study was to examine the response of these water bodies to temporal changes in human activities. Sediment cores were collected from the sites and dated using 210Pb and 137Cs. The cores were analyzed for total carbon (TC), total nitrogen (TN), total phosphorus (TP), organic phosphorus (OP), inorganic phosphorus (IP), biogenic silica (BSi), loss on ignition (LOI), grain size, Cu, Zn, Al, Fe, Mn, K, Ca, Mg and Na. Principal component analysis (PCA) was used to summarize the trends in the geochemical variables and to compare trends between the different sites. The links between the catchment land use and sediment geochemical data were studied using a multivariate technique of redundancy analysis (RDA). Human activities produce marked geochemical variations in coastal sediments. These variations and signals are often challenging to interpret due to various sedimentological and post-depositional factors affecting the sediment profiles. In general, the sites studied here show significant upcore increases in sedimentation rates, TP and TN concentrations. Also Cu, which is considered to be a good indicator of anthropogenic influence, showed clear increases from 1850 towards the top part of the cores. Based on the RDA-analysis, in the least disturbed embayments with high forest cover, the sediments are dominated by lithogenic indicators Fe, K, Al and Mg. In embayments close to urban settlement, the sediments have high Cu concentrations and a high sediment Fe/Mn ratio. This study suggests that sediment accumulation rates vary significantly from site to site and that the overall sedimentation can be linked to the geomorphology and basin bathymetry, which appear to be the major factors governing sedimentation rates; i.e. a high sediment accumulation rate is not characteristic either to urban or to rural sites. The geochemical trends are strongly site specific and depend on the local geochemical background, basin characteristics and anthropogenic metal and nutrient loading. Of the studied geochemical indicators, OP shows the least monotonic trends in all studied sites. When compared to other available data, OP seems to be the most reliable geochemical indicator describing the trophic development of the study sites, whereas Cu and Zn appear to be good indicators for anthropogenic influence. As sedimentation environments, estuarine and marine sites are more complex than lacustrine basins with multiple sources of sediment input and more energetic conditions in the former. The crucial differences between lacustrine and estuarine/coastal sedimentation environments are mostly related to Fe. P sedimentation is largely governed by Fe redox-reactions in estuarine environments. In freshwaters, presence of Fe is clearly linked to the sedimentation of other lithogenic metals, and therefore P sedimentation and preservation has a more direct linkage to organic matter sedimentation.

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Soil biogeochemical cycles are largely mediated by microorganisms, while fire significantly modifies biogeochemical cycles mainly via altering microbial community and substrate availability. Majority of studies on fire effects have focused on the surface soil; therefore, our understanding of the vertical distribution of microbial communities and the impacts of fire on nitrogen (N) dynamics in the soil profile is limited. Here, we examined the changes of soil denitrification capacity (DNC) and denitrifying communities with depth under different burning regimes, and their interaction with environmental gradients along the soil profile. Results showed that soil depth had a more pronounced impact than the burning treatment on the bacterial community size. The abundance of 16S rRNA and denitrification genes (narG, nirK, and nirS) declined exponentially with soil depth. Surprisingly, the nosZ-harboring denitrifiers were enriched in the deeper soil layers, which was likely to indicate that the nosZ-harboring denitrifiers could better adapt to the stress conditions (i.e., oxygen deficiency, nutrient limitation, etc.) than other denitrifiers. Soil nutrients, including dissolved organic carbon (DOC), total soluble N (TSN), ammonium (NH4 +), and nitrate (NO3 −), declined significantly with soil depth, which probably contributed to the vertical distribution of denitrifying communities. Soil DNC decreased significantly with soil depth, which was negligible in the depths below 20 cm. These findings have provided new insights into niche separation of the N-cycling functional guilds along the soil profile, under a varied fire disturbance regime.

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The project aimed to evaluate the innovative application of NIRS as a reliable, repeatable, and cost-effective method of ageing fish, using otoliths of Barramundi and Snapper as study species. Specific research questions included assessing how geographic and seasonal variation in otoliths affects NIRS predictive models of fish age, as well as how the NIR spectra of otoliths change in the short-term (i.e., <12 months) and long-term (i.e., historical otolith collections) and what effect this has on the predictive ability of NIRS models. The cost-effectiveness of using NIRS to supplement standard fish ageing methods was also evaluated using a hypothetical case study of Barramundi.

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Mechanical stress is an important external factor effecting the development and maintenance of articular cartilage. The metabolite profile of diseased cartilage has been well studied but there is limited information about the variation in metabolite profile of healthy cartilage. With the importance of load in maintaining healthy cartilage, regional differences in metabolite profile associated with differences in load may provide information on how load contributes to the maintenance of healthy cartilage. HR-MAS NMR spectroscopy allows the assessment of tissue samples without modification and was used for assessing the difference in metabolic profile between the load bearing and non-load bearing regions of the bovine articular cartilage. In this preliminary study, we examined cartilage from tibia and femur of four knee joints. Sixteen pairs of 1D-NOESY spectra were acquired. Principle component analysis (PCA) identified chemical shifts responsible for variance. SBASE (AMIX) and the Human Metabolome Database were used in conjunction with previous reported cartilage data for identifying metabolites associated with the PCA results. The major contributors to load-related differences in metabolite profile were N-acetyl groups, lactate and phosphocholine peaks. Integrals of these regions were further analysed using a Student's t-test. In load bearing cartilage regions. N-acetyl groups and phosphocholine were found at significantly higher concentration (p < 0.05 and p < 0.005, respectively) in both femur and tibia, while lactate was reduced in load bearing cartilage (p < 0.005). The results of this pilot HR-MAS NMR study demonstrate its ability to provide useful metabolite information for healthy cartilage.

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Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

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To obtain data on phytoplankton dynamics with improved spatial and temporal resolution, and at reduced cost, traditional phytoplankton monitoring methods have been supplemented with optical approaches. In this thesis, I have explored various fluorescence-based techniques for detection of phytoplankton abundance, taxonomy and physiology in the Baltic Sea. In algal cultures used in this thesis, the availability of nitrogen and light conditions caused changes in pigmentation, and consequently in light absorption and fluorescence properties of cells. In the Baltic Sea, physical environmental factors (e.g. mixing depth, irradiance and temperature) and related seasonal succession in the phytoplankton community explained a large part of the seasonal variability in the magnitude and shape of Chlorophyll a (Chla)-specific absorption. The variability in Chla-specific fluorescence was related to the abundance of cyanobacteria, the size structure of the phytoplankton community, and absorption characteristics of phytoplankton. Cyanobacteria show very low Chla-specific fluorescence. In the presence of eukaryotic species, Chla fluorescence describes poorly cyanobacteria. During cyanobacterial bloom in the Baltic Sea, phycocyanin fluorescence explained large part of the variability in Chla concentrations. Thus, both Chla and phycocyanin fluorescence were required to predict Chla concentration. Phycobilins are major light harvesting pigments for cyanobacteria. In the open Baltic Sea, small picoplanktonic cyanobacteria were the main source of phycoerythrin fluorescence and absorption signal. Large filamentous cyanobacteria, forming harmful blooms, were the main source of the phycocyanin fluorescence signal and typically their biomass and phycocyanin fluorescence were linearly related. Using phycocyanin fluorescence, dynamics of cyanobacterial blooms can be detected at high spatial and seasonal resolution not possible with other methods. Various taxonomic phytoplankton pigment groups can be separated by spectral fluorescence. I compared multivariate calibration methods for the retrieval of phytoplankton biomass in different taxonomic groups. Partial least squares regression method gave the closest predictions for all taxonomic groups, and the accuracy was adequate for phytoplankton bloom detection. Variable fluorescence has been proposed as a tool to study the physiological state of phytoplankton. My results from the Baltic Sea emphasize that variable fluorescence alone cannot be used to detect nutrient limitation of phytoplankton. However, when combined with experiments with active nutrient manipulation, and other nutrient limitation indices, variable fluorescence provided valuable information on the physiological responses of the phytoplankton community. This thesis found a severe limitation of a commercial fast repetition rate fluorometer, which couldn t detect the variable fluorescence of phycoerythrin-lacking cyanobacteria. For these species, the Photosystem II absorption of blue light is very low, and fluorometer excitation light did not saturate Photosystem II during a measurement. This thesis encourages the use of various in vivo fluorescence methods for the detection of bulk phytoplankton biomass, biomass of cyanobacteria, chemotaxonomy of phytoplankton community, and phytoplankton physiology. Fluorescence methods can support traditional phytoplankton monitoring by providing continuous measurements of phytoplankton, and thereby strengthen the understanding of the links between biological, chemical and physical processes in aquatic ecosystems.

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The accretion disk around a compact object is a nonlinear general relativistic system involving magnetohydrodynamics. Naturally, the question arises whether such a system is chaotic (deterministic) or stochastic (random) which might be related to the associated transport properties whose origin is still not confirmed. Earlier, the black hole system GRS 1915+105 was shown to be low-dimensional chaos in certain temporal classes. However, so far such nonlinear phenomena have not been studied fairly well for neutron stars which are unique for their magnetosphere and kHz quasi-periodic oscillation (QPO). On the other hand, it was argued that the QPO is a result of nonlinear magnetohydrodynamic effects in accretion disks. If a neutron star exhibits chaotic signature, then what is the chaotic/correlation dimension? We analyze RXTE/PCA data of neutron stars Sco X-1 and Cyg X-2, along with the black hole Cyg X-1 and the unknown source Cyg X-3, and show that while Sco X-1 and Cyg X-2 are low dimensional chaotic systems, Cyg X-1 and Cyg X-3 are stochastic sources. Based on our analysis, we argue that Cyg X-3 may be a black hole.

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Venous thromboembolism (VTE) is the greatest single cause of maternal mortality in pregnant women in developed countries. Pregnancy is a hypercoagulable state and brings about an enhanced risk of deep venous thrombosis (DVT) in otherwise healthy women. Traditionally, unfractionated heparin (UFH) has been used for treatment of DVT during pregnancy. We showed in our observational study that low molecular weight heparin (LMWH) is as effective and safe as UFH in the treatment of DVT during pregnancy. Although DVT during pregnancy is often massive, increasing the risk of developing long-term consequences, namely post-thrombotic syndrome (PTS), only 11% of all patients had confirmed PTS 3 4 years after DVT. In our studies the prevalence of PTS was not dependent on treatment (UFH vs LMWH). Low molecular weight heparin is more easily administered, few laboratory controls are required and the hospital stay is shorter, factors that lower the costs of treatment. Cervical insufficiency is defined as repeated very preterm delivery during the second or early third trimester. Infection is a well-known risk factor of preterm delivery. We found overpresentation of thrombophilic mutations (FV Leiden, prothrombin G20210A)among 42 patients with cervical insufficiency compared with controls (OR 6.7, CI 2.7 18.4). Thus, thrombophilia might be a risk factor of cervical insufficiency possibly explained by interaction of coagulation and inflammation processes. The presence of antiphospholipid (aPL) antibodies increases the risk for recurrent miscarriage (RM). Annexins are proteins which all bind to anionic phospholipids (PLs) preventing clotting on vascular phospholipid surfaces. Plasma concentrations of circulating annexin IV and V were investigated in 77 pregnancies at the beginning of pregnancy among women with a history of RM, and in connection to their aPL antibody status. Control group consisted unselected pregnant patients (n=25) without history of adverse pregnancy outcome. Plasma levels of annexin V were significantly higher at the beginning (≤5th week) of pregnancy in women with aPL antibodies compared with those without aPL antibodies (P=0.03). Levels of circulating annexin V were also higher at the 6th (P= 0.01) and 8th week of pregnancy in subjects with aPL antibodies (P=0.01). Results support the hypothesis that aPL could displace annexin from anionic phospholipid surfaces of syncytiotrophoblasts (STBs) and may exert procoagulant activities on the surfaces of STBs Recurrent miscarriage (RM) has been suggested to be caused by mutations in genes coding for various coagulation factors resulting in thrombophilia. In the last study of my thesis were investigated the prevalence of thrombomodulin (TM) and endothelial protein C receptor polymorphism EPCR among 40 couples and six women suffering RM. This study showed that mutations in the TM or EPCR genes are not a major cause of RM in Finnish patients.

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Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

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Prostate cancer (PCa) is the most commonly diagnosed non-skin cancer and second leading cause of cancer-related death of men in developed countries. Measurement of prostate specific antigen (PSA) is a very sensitive method for diagnosing and monitoring of prostate cancer (PCa), but the specificity needs improvement. Measurements of different molecular forms of PSA have been shown to improve differentiation between PCa and benign prostatic diseases. However, accurate measurement of some isoforms has not been achieved in previous assays. The aim of the present study was to develop new assays that reliably measure enzymatically active PSA, PSA-α1-chymotryposin (PSA-ACT) and PSA-α1-protease inhibitor (PSA-API), and to evaluate their diagnostic value. Double-label immunofluorometric assays using a novel monoclonal antibody (MAb) and another antibody to either free PSA (fPSA) or total PSA (tPSA) were developed and used to measure PSA-ACT and fPSA or tPSA at the same time. These assays provide enough sensitivity for measurement of PSA-ACT in sera with low PSA levels. The results obtained confirmed that proportion of PSA-ACT to tPSA (%PSA-ACT) was as useful as proportion of fPSA to tPSA (%fPSA) for discrimination between PCa and benign prostatic hyperplasia (BPH). We developed an immunoassay for detection of PSA-API based on proximity ligation, which improved assay sensitivity 10-fold compared with conventional assays. Our results confirmed previous findings that the PSA-API level is somewhat lower in men with than without PCa, and the combination of %fPSA and proportion of PSA-API to tPSA (%PSA-API) provides diagnostic improvement compared with either method alone. Assays based on this principle should be applicable to other immunoassays in which the nonspecific background is a problem. An immunopeptidometric sandwich assay (IPMA) was developed to measure the enzymatically active PSA. This assay showed high specificity, but sensitivity was not good enough for measurement of PSA concentrations in the gray zone, 2-10 µg/L, in which tPSA does not efficiently differentiate between PCa and BPH. We further developed a solid-phase proximity ligation immunoassay, which provided a 10-fold improvement in sensitivity. This proof of concept study shows that peptides reacting with proteins are potentially useful for sensitive and specific measurement of protein variants for which specific MAbs cannot be obtained.