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A demonstration-scale outdoor constructed wetland (CW) wastewater treatment system was evaluated for about two years for its effectiveness in treating septic system effluents. The system included three treatment cells: an anaerobic cell, an aerated cell, and a basic oxygen furnace slag (BOFS)-based phosphorus (P) treatment cell. High removal efficiencies were achieved, with reductions of >99% for PO4-P, >83% for NH3-N, >99% for cBOD5, and >76% for COD, with influent concentrations averaging 6, 48, 63, and 143 mg L−1, respectively. Additionally, pathogens removal were high, with an over 99% decrease in E. coli and total coliform levels. The BOFS cell was critical, elevating effluent pH to 10.9 ± 1.5, which effectively inactivated pathogens. Environmental safety before discharge was ensured by CO2(g) sparging to adjust the pH and a zero-valent iron layer in the BOFS cell to control dissolved metal concentrations. Analytical techniques (FESEM-EDX, FTIR, and XANES) confirmed the formation of Ca carbonate and Ca phosphate on spent BOFS, highlighting their role in the treatment process. This study highlights the potential of integrating complementary technologies in constructed wetlands for sustainable and efficient wastewater management.

The occurrence of pharmaceutically active compounds (PhACs), nutrients, and an artificial sweetener acesulfame in wastewater, and subsequent removal in an engineered system comprising aerobic wetland, anaerobic wetland, and steel slag cells, were investigated. The PhACs evaluated in this study covered a range of octanol–water partition coefficients (log Kow = 0.07–2.45) and acid dissociation constants (pKa = 1.7–13.9) and included carbamazepine, caffeine, sulfamethoxazole, ibuprofen, and naproxen. The mean flow rate in the system was 0.89 m3 day−1 (0.02 to 4.27 m3 day−1), representing a hydraulic retention time of 5 days. The removal efficiencies of PO4-P, NH3-N, and cBOD5 in the treatment system were >99, 82, and 98%. The removal efficiencies for the PhACs and acesulfame were classified into four groups, including those that were (a) efficiently removed (caffeine by >75%); (b) moderately removed (ibuprofen by 50–75%); (c) poorly removed (sulfamethoxazole and naproxen by 25–50%); and (d) recalcitrant (carbamazepine and acesulfame by

Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each functional domain separately by applying different behavioral tasks whereby the tests reflect the conceptual structure of cognition. Such an approach has limitations that are described in the article.Objective: Our aim was to improve the diagnosis of early cognitive decline. We estimated the onset of cognitive decline in a healthy population, using behavioral tests, and predicted the age group of an individual. The comparison between the predicted (“cognitive”) and chronological age will contribute to the early diagnosis of accelerated aging.Materials and Methods: We used publicly available datasets (POBA, SSCT) and Pearson correlation coefficients to assess the relationship between age and tests results, Kruskal-Wallis test to compare distribution, clustering methods to find an onset of cognitive decline, feature selection to enhance performance of the clustering algorithms, and classification methods to predict an age group from cognitive tests results.Results: The major results of the psychophysiological tests followed a U-shape function across the lifespan, which reflected the known inverted function of white matter volume changes. Optimal values were observed in those aged over 35 years, with a period of stability and accelerated decline after 55–60 years of age. The shape of the age-related variance of the performance of major cognitive tests was linear, which followed the trend of lifespan gray matter volume changes starting from adolescence. There was no significant sex difference in lifelong dynamics of major tests estimates. The performance of the classification model for identifying subject age groups was high.Conclusions: ML models can be designed and utilized as computer-aided detectors of neurocognitive decline. Our study demonstrated great promise for the utility of classification models to predict age-related changes. These findings encourage further explorations combining several tests from the cognitive and psychophysiological test battery to derive the most reliable set of tests toward the development of a highly-accurate ML model.

Summary: We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled interventions to a networked system while estimating how the algorithmic information content is affected. We demonstrate the method by reconstructing the phase space and their generative rules of some discrete dynamical systems (cellular automata) serving as controlled case studies. Next, the model-based interventional or causal calculus is evaluated and validated using (1) a huge large set of small graphs, (2) a number of larger networks with different topologies, and finally (3) biological networks derived from a widely studied and validated genetic network (E. coli) as well as on a significant number of differentiating (Th17) and differentiated human cells from a curated biological network data. : Gene Network; Systems Biology; Complex Systems; Computer Science; Algorithms Subject Areas: Gene Network, Systems Biology, Complex Systems, Computer Science, Algorithms

Objectives:. Coronavirus disease 2019 continues to spread worldwide with high levels of morbidity and mortality. We performed anticoronavirus immunoglobulin G profiling of critically ill coronavirus disease 2019 patients to better define their underlying humoral response. Design:. Blood was collected at predetermined ICU days to measure immunoglobulin G with a research multiplex assay against four severe acute respiratory syndrome coronavirus 2 proteins/subunits and against all six additionally known human coronaviruses. Setting:. Tertiary care ICU and academic laboratory. Subjects:. ICU patients suspected of being infected with severe acute respiratory syndrome coronavirus 2 had blood collected until either polymerase chain reaction testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until death or discharge if the patient tested polymerase chain reaction positive (coronavirus disease 2019 positive). Interventions:. None MEASUREMENTS AND MAIN RESULTS:. Age- and sex-matched healthy controls and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients had greater body mass indexes, presented with bilateral pneumonias more frequently, and suffered lower Pao2:Fio2 ratios, when compared with coronavirus disease 2019 negative patients (p < 0.05). Mortality rate for coronavirus disease 2019 positive patients was 50%. On ICU days 1–3, anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G was significantly elevated in coronavirus disease 2019 positive patients, as compared to both healthy control subjects and coronavirus disease 2019 negative patients (p < 0.001). Weak severe acute respiratory syndrome coronavirus immunoglobulin G serologic responses were also detected, but not other coronavirus subtypes. The four anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G were maximal by ICU day 3, with all four anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G providing excellent diagnostic potential (severe acute respiratory syndrome coronavirus 2 Spike 1 protein immunoglobulin G, area under the curve 1.0, p < 0.0005; severe acute respiratory syndrome coronavirus receptor binding domain immunoglobulin G, area under the curve, 0.93–1.0; p ≤ 0.0001; severe acute respiratory syndrome coronavirus 2 Spike proteins immunoglobulin G, area under the curve, 1.0; p < 0.0001; severe acute respiratory syndrome coronavirus 2 Nucleocapsid protein immunoglobulin G area under the curve, 0.90–0.95; p ≤ 0.0003). Anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G increased and/or plateaued over 10 ICU days. Conclusions:. Critically ill coronavirus disease 2019 patients exhibited anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G, whereas serologic responses to non–severe acute respiratory syndrome coronavirus 2 antigens were weak or absent. Detection of human coronavirus immunoglobulin G against the different immunogenic structural proteins/subunits with multiplex assays may be useful for pathogen identification, patient cohorting, and guiding convalescent plasma therapy.

Objectives:. Coronavirus disease 2019 continues to spread rapidly with high mortality. We performed metabolomics profiling of critically ill coronavirus disease 2019 patients to understand better the underlying pathologic processes and pathways, and to identify potential diagnostic/prognostic biomarkers. Design:. Blood was collected at predetermined ICU days to measure the plasma concentrations of 162 metabolites using both direct injection-liquid chromatography-tandem mass spectrometry and proton nuclear magnetic resonance. Setting:. Tertiary-care ICU and academic laboratory. Subjects:. Patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient tested positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top-performing metabolites for identifying coronavirus disease 2019 positive patients from healthy control subjects and was dominated by increased kynurenine and decreased arginine, sarcosine, and lysophosphatidylcholines. Arginine/kynurenine ratio alone provided 100% classification accuracy between coronavirus disease 2019 positive patients and healthy control subjects (p = 0.0002). When comparing the metabolomes between coronavirus disease 2019 positive and coronavirus disease 2019 negative patients, kynurenine was the dominant metabolite and the arginine/kynurenine ratio provided 98% classification accuracy (p = 0.005). Feature selection identified creatinine as the top metabolite for predicting coronavirus disease 2019-associated mortality on both ICU days 1 and 3, and both creatinine and creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death with 100% accuracy (p = 0.01). Conclusions:. Metabolomics profiling with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 negative patients from coronavirus disease 2019 positive patients. Arginine/kynurenine ratio accurately identified coronavirus disease 2019 status, whereas creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death. Administration of tryptophan (kynurenine precursor), arginine, sarcosine, and/or lysophosphatidylcholines may be considered as potential adjunctive therapies.

Objectives:. Coronavirus disease 2019 patients admitted to the ICU have high mortality. The host response to coronavirus disease 2019 has only been partially elucidated, and prognostic biomarkers have not been identified. We performed targeted proteomics on critically ill coronavirus disease 2019 patients to better understand their pathophysiologic mediators and to identify potential outcome markers. Design:. Blood was collected at predetermined ICU days for proximity extension assays to determine the plasma concentrations of 1,161 proteins. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy control subjects and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top performing proteins for identifying coronavirus disease 2019 positive ICU patients from both healthy control subjects and coronavirus disease 2019 negative ICU patients (classification accuracies 100%). The coronavirus disease 2019 proteome was dominated by interleukins and chemokines, as well as several membrane receptors linked to lymphocyte-associated microparticles and/or cell debris. Mortality was predicted for coronavirus disease 2019 positive patients based on plasma proteome profiling on both ICU day 1 (accuracy 92%) and ICU day 3 (accuracy 83%). Promising prognostic proteins were then narrowed down to six, each of which provided excellent classification performance for mortality when measured on ICU day 1 CMRF-35-like molecule, interleukin receptor-12 subunit B1, cluster of differentiation 83 [CD83], family with sequence similarity 3, insulin-like growth factor 1 receptor and opticin; area-under-the-curve =1.0; p = 0.007). Conclusions:. Targeted proteomics with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 tested negative ICU patients from coronavirus disease 2019 tested positive ICU patients. Multiple proteins were identified that accurately predicted coronavirus disease 2019 tested positive patient mortality.

Objectives:. Coronavirus disease 2019 is caused by the novel severe acute respiratory syndrome coronavirus 2 virus. Patients admitted to the ICU suffer from microvascular thrombosis, which may contribute to mortality. Our aim was to profile plasma thrombotic factors and endothelial injury markers in critically ill coronavirus disease 2019 ICU patients to help understand their thrombotic mechanisms. Design:. Daily blood coagulation and thrombotic factor profiling with immunoassays and in vitro experiments on human pulmonary microvascular endothelial cells. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had daily blood samples collected until testing was confirmed coronavirus disease 2019 negative on either ICU day 3 or ICU day 7 if the patient was coronavirus disease 2019 positive. Interventions:. None. Measurement and Main Results:. Age- and sex-matched healthy control subjects and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Compared with healthy control subjects, coronavirus disease 2019 positive patients had higher plasma von Willebrand factor (p < 0.001) and glycocalyx-degradation products (chondroitin sulfate and syndecan-1; p < 0.01). When compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had persistently higher soluble P-selectin, hyaluronic acid, and syndecan-1 (p < 0.05), particularly on ICU day 3 and thereafter. Thrombosis profiling on ICU days 1–3 predicted coronavirus disease 2019 status with 85% accuracy and patient mortality with 86% accuracy. Surface hyaluronic acid removal from human pulmonary microvascular endothelial cells with hyaluronidase treatment resulted in depressed nitric oxide, an instigating mechanism for platelet adhesion to the microvascular endothelium. Conclusions:. Thrombosis profiling identified endothelial activation and glycocalyx degradation in coronavirus disease 2019 positive patients. Our data suggest that medications to protect and/or restore the endothelial glycocalyx, as well as platelet inhibitors, should be considered for further study.

Objectives:. Coronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019. Design:. Daily blood inflammation profiling with immunoassays. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1–3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2–7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality. Conclusions:. While many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.

Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed progress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies—data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded in the course of the Innovative Medicines Initiative (IMI); which is a public-private partnership of the European Federation of Pharmaceutical Industry Associations (EFPIA) and the European Commission (EC).

The Balkans is currently going through its most profound period of change since Slobodan Milošević's overthrow in October 2000. Montenegro has declared its independence from the state union of Serbia and Montenegro; the Kosovo future status talks are in their final stages and by all indications will suggest some form of independence for the Serbian province; new governments are in place in Bosnia-Herzegovina and Macedonia; while the results of Serbia’s January 2007 elections suggest that Serbian politics will be unstable for the foreseeable future. All of this is occurring at a time when two of the pillars promoting stability in the Balkans - a substantial U.S. military presence and the foreseeable prospect of EU accession for the countries of the region - are being withdrawn. Meanwhile, anew variable is being introduced into the strategic equation in The region - the return of Russia as a serious player. As a result of all of these new developments without a more serious commitment to the region from both Washington and Brussels over the next few years, there is a serious likelihood that the democratic and economic transitions in the region will suffer serious setbacks or delays.

Background: Patients facing a cutaneous lymphoma diagnosis frequently turn to the internet for information but finding patient-accessible education may be a challenge. Objective: To investigate accessibility and readability of patient-oriented online education on cutaneous lymphomas, including cutaneous T-cell and B-cell lymphoma subtypes. Methods: This study queried a search engine for 11 cutaneous lymphoma terms, resulting in 1083 webpages. Webpages were screened using defined inclusion/exclusion criteria; literature directed to physicians and scientists was excluded. Webpages were stratified by academic/nonacademic and dermatology/nondermatology hosts and assessed by order of appearance. Readability, including text complexity, was analyzed for grade level understanding using 5 established calculators. Overall readability was assessed by Flesch–Kincaid Reading Ease. Results: Academic webpages had earlier order of appearance. There was a dearth in dermatology-hosted webpages. Rarer cutaneous lymphomas yielded fewer patient-accessible results. Search term readability significantly exceeded the American Medical Association–recommended sixth grade level (P

A common defect encountered in the spermatozoa of male infertility patients is an idiopathic failure of sperm-egg recognition. In order to resolve the molecular basis of this condition we have compared the proteomic profiles of spermatozoa exhibiting an impaired capacity for sperm-egg recognition with normal cells using label free mass spectrometry (MS)-based quantification. This analysis indicated that impaired sperm-zona binding was associated with reduced expression of the molecular chaperone, heat shock 70 kDa protein 2 (HSPA2), from the sperm proteome. Western blot analysis confirmed this observation in independent patients and demonstrated that the defect did not extend to other members of the HSP70 family. HSPA2 was present in the acrosomal domain of human spermatozoa as a major component of 5 large molecular mass complexes, the most dominant of which was found to contain HSPA2 in close association with just two other proteins, sperm adhesion molecule 1 (SPAM1) and arylsulfatase A (ARSA), both of which that have previously been implicated in sperm-egg interaction. The interaction between SPAM1, ARSA and HSPA2 in a multimeric complex mediating sperm-egg interaction, coupled with the complete failure of this process when HSPA2 is depleted in infertile patients, provides new insights into the mechanisms by which sperm function is impaired in cases of male infertility.

The causes of dolphin and whale stranding can often be difficult to determine. Because toothed whales rely on echolocation for orientation and feeding, hearing deficits could lead to stranding. We report on the results of auditory evoked potential measurements from eight species of odontocete cetaceans that were found stranded or severely entangled in fishing gear during the period 2004 through 2009. Approximately 57% of the bottlenose dolphins and 36% of the rough-toothed dolphins had significant hearing deficits with a reduction in sensitivity equivalent to severe (70-90 dB) or profound (>90 dB) hearing loss in humans. The only stranded short-finned pilot whale examined had profound hearing loss. No impairments were detected in seven Risso's dolphins from three different stranding events, two pygmy killer whales, one Atlantic spotted dolphin, one spinner dolphin, or a juvenile Gervais' beaked whale. Hearing impairment could play a significant role in some cetacean stranding events, and the hearing of all cetaceans in rehabilitation should be tested.

The number and function of human natural killer (NK) cells are generally assessed to monitor the baseline of immune function, the effect of treatment, the progress of malignancy or metastases and diseases. NK cells recognise and kill target cells in the absence of prior sensitisation and are able to defend the host from infection or prevent the progression of a disease. Human NK cells express CD16 and CD56 which are (massively) being used as a major hallmark for the NK cell. The purpose of this study was to identify the unique subsets of peripheral blood mononuclear cells (PBMC) (%CD3-CD56+ cells) by flow cytometry and to determine whether there is any correlation with functionally mature progeny of (NKp) precursor after five days of culture. The correlation was analysed using samples obtained from 120 Caucasian patients. 20-30ml of whole blood was collected in sterile tube containing preservative free sodium heparin and a similar sample was obtained after five days. Maturation of NKp required the continuous presence of recombinant interleukin 2 (rIL-2), or interleukin 15 (rIL-15) and functional maturity of NK cells was determined by their ability to lyse target cells from the K562 cell line. The NK precursor frequency was measured by limiting dilution analysis (LDA), which The NKpf assay was set up with a range of cell dilutions from 40,000 to 625 per 100l/well in 96 well culture plates. At the end of the culture period the K562 cell line labelled with Europium (Eu-K562) was added and Eu release measured in culture supernatants using time-resolved fluorometry. The PBMC were set up in parallel cultures under various conditions .On day five cells were collected from culture plates and adjusted to 1x10 cells/ml and then mixed. The mixture was incubated and anti CD3 and anti CD56 were added. NK cells were enumerated in 120 patients by double staining with a combination of anti-CD3- and anti-CD56+. The results of these Immunophenotyping studies by flow cytometry showed no correlation between the NKpf (natural killer precursor frequency) and the percent of CD3-CD56+ cells expressed after five days confirming that CD56 was inadequate as a unique marker for functional NK cells.