Preliminary assessment of microfibres amount in textile wastewater

Textile wastewater is a complex mixture of inorganic compounds, polymers, organic products, dyes, and microfibers (MFs), including microplastics (MPs) and natural fibers. The treatment of textile wastewater, which contains a significant share of MFs, is of great importance to prevent the release of MPs in the environment. MPs analysis requires multiple phases of pretreatment (to eliminate the organic compounds), separation of the MFs from the water, and identification of the MPs among the MFs.This work presents the preliminary results of a research aimed at exploring two issues. Firstly, the pretreatment (through Fenton, H2O2, HCl, KOH and NaOH, applied at 25 °C for 5 days and 60 °C for 6 hours) of artificial textile wastewater, evaluating the effect of the different conditions on the MFs and the MPs. Secondly, the separation of MFs from a real textile wastewater sample through different processes (centrifugation, sink-float & filtration, filtration). The results of the pretreatment tests revealed Fenton, HCl, and H2O2 at 25 °C for 5 days as the best performing chemicals and conditions. Considering the results of the separation tests, filtration gave back the best removal of the MFs from wastewater compared to centrifugation and sink-float and filtration, which left some MFs in the supernatant/float and in the sediment/sink. In conclusion, these preliminary results may be useful to further explore the detection of MFs and MPs in textile wastewater

Constraining recent lead pollution sources in the North Pacific using ice core stable lead isotopes

Trends and sources of lead (Pb) aerosol pollution in the North Pacific rim of North America from 1850 to 2001 are investigated using a high-resolution (subannual to annual) ice core record recovered from Eclipse Icefield (3017 masl; St. Elias Mountains, Canada). Beginning in the early 1940s, increasing Pb concentration at Eclipse Icefield occurs coevally with anthropogenic Pb deposition in central Greenland, suggesting that North American Pb pollution may have been in part or wholly responsible in both regions. Isotopic ratios (208Pb/207Pb and 206Pb/207Pb) from 1970 to 2001 confirm that a portion of the Pb deposited at Eclipse Icefield is anthropogenic, and that it represents a variable mixture of East Asian (Chinese and Japanese) emissions transported eastward across the Pacific Ocean and a North American component resulting from transient meridional atmospheric flow. Based on comparison with source material Pb isotope ratios, Chinese and North American coal combustion have likely been the primary sources of Eclipse Icefield Pb over the 1970–2001 time period. The Eclipse Icefield Pb isotope composition also implies that the North Pacific mid-troposphere is not directly impacted by transpolar atmospheric flow from Europe. Annually averaged Pb concentrations in the Eclipse Icefield ice core record show no long-term trend during 1970–2001; however, increasing 208Pb/207Pb and decreasing 206Pb/207Pb ratios reflect the progressive East Asian industrialization and increase in Asian pollutant outflow. The post-1970 decrease in North American Pb emissions is likely necessary to explain the Eclipse Icefield Pb concentration time series. When compared with low (lichen) and high (Mt. Logan ice core) elevation Pb data, the Eclipse ice core record suggests a gradual increase in pollutant deposition and stronger trans-Pacific Asian contribution with rising elevation in the mountains of the North Pacific rim

Highly sensitive and label-free digital detection of whole cell E. coli with interferometric reflectance imaging

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in identifying the bacterial contaminations and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards development of new biosensors. Biosensors offering label free, whole bacteria detection are highly desirable over those relying on label based or pathogenic molecular components detection. The major advantage is eliminating the additional time and cost required for labeling or extracting the desired bacterial components. Here, we demonstrate rapid, sensitive and label free E. coli detection utilizing interferometric reflectance imaging enhancement allowing for visualizing individual pathogens captured on the surface. Enabled by our ability to count individual bacteria on a large sensor surface, we demonstrate a limit of detection of 2.2 CFU/ml from a buffer solution with no sample preparation. To the best of our knowledge, this high level of sensitivity for whole E. coli detection is unprecedented in label free biosensing. The specificity of our biosensor is validated by comparing the response to target bacteria E. coli and non target bacteria S. aureus, K. pneumonia and P. aeruginosa. The biosensor performance in tap water also proves that its detection capability is unaffected by the sample complexity. Furthermore, our sensor platform provides high optical magnification imaging and thus validation of recorded detection events as the target bacteria based on morphological characterization. Therefore, our sensitive and label free detection method offers new perspectives for direct bacterial detection in real matrices and clinical samples.First author draf

Bisphenol A sulfonation is impaired in metabolic and liver disease

Background: Bisphenol A (BPA) is a widely used industrial chemical and suspected endocrine disruptor to which humans are ubiquitously exposed. The liver metabolizes and facilitates BPA excretion through glucuronidation and sulfonation. The sulfotransferase enzymes contributing to BPA sulfonation (detected in human and rodents) is poorly understood. Objectives: To determine the impact of metabolic and liver disease on BPA sulfonation in human and mouse livers. Methods: The capacity for BPA sulfonation was determined in human liver samples that were categorized into different stages of metabolic and liver disease (including obesity, diabetes, steatosis, and cirrhosis) and in livers from ob/ob mice. Results: In human liver tissues, BPA sulfonation was substantially lower in livers from subjects with steatosis (23%), diabetes cirrhosis (16%), and cirrhosis (18%), relative to healthy individuals with non-fatty livers (100%). In livers of obese mice (ob/ob), BPA sulfonation was lower (23%) than in livers from lean wild-type controls (100%). In addition to BPA sulfonation activity, Sult1a1 protein expression decreased by 97% in obese mouse livers. Conclusion: Taken together these findings establish a profoundly reduced capacity of BPA elimination via sulfonation in obese or diabetic individuals and in those with fatty or cirrhotic livers versus individuals with healthy livers

ROCK MASS DISCONTINUITY DETERMINATION WITH TRANSFER LEARNING

Rock mass discontinuity and orientation are among the important rock mass features. They are conventionally determined with scan-line surveys by engineering geologists in field, which can be difficult or impossible depending on site accessibility. Photogrammetry and computer vision techniques can aid to automatically perform these measurements, although variations in size, shape and appearance of rock masses make the task challenging. Here we propose an automated approach for the detection of rock mass discontinuities using deep learning and photogrammetric image processing methods. Two deep convolutional neural network (DCNNs) were implemented for this purpose and applied to basalts in Kizilcahamam Guvem Geosite near Ankara, Türkiye. Red-green-blue (RGB) band images of the site were taken from an off-the-shelf camera with 1.7 mm resolution and a 3D digital surface model and orthophotos were produced by using photogrammetric software. The discontinuities were delineated manually on the orthophoto and converted to masks. The first DCNN model was based on the open-source crack dataset consisting of a total of 11,298 road and pavement images, which were used to train the Resnet-18 model (Model-1). The second model (Model-2) was based on fine-tuning of Model-1 using the study data from Kizilcahamam. After fine-tuning, Model-2 was able to achieve high performance with a Jaccard Score of 88% on the test data. The results show high potential of the methodology for transfer learning with fine-tuning of a small amount of data that can be applied to other sites and rock mass types as well

Identification of tissue-specific microRNAs from mouse

MicroRNAs (miRNAs) are a new class of noncoding RNAs, which are encoded as short inverted repeats in the genomes of invertebrates and vertebrates [1, 2]. It is believed that miRNAs are modulators of target mRNA translation and stability, although most target mRNAs remain to be identified. Here we describe the identification of 34 novel miRNAs by tissue- specific cloning of approximately 21-nucleotide RNAs from mouse. Almost all identified miRNAs are conserved in the human genome and are also frequently found in nonmammalian vertebrate genomes, such as pufferfish. In heart, liver, or brain, it is found that a single, tissue-specifically expressed miRNA dominates the population of expressed miRNAs and suggests a role for these miRNAs in tissue specification or cell lineage decisions. Finally, a miRNA was identified that appears to be the fruitfly and mammalian ortholog of C. elegans lin-4 stRNA

Daily antibiotic cost of nosocomial infections in a Turkish university hospital

BACKGROUND: Many studies associated nosocomial infections with increased hospital costs due to extra days in hospital, staff time, extra investigations and drug treatment. The cost of antibiotic treatment for these infections represents a significant part of hospital expenditure. This prospective observational study was designed to determine the daily antibiotic cost of nosocomial infections per infected adult patient in Akdeniz University Hospital. METHODS: All adult patients admitted to the ICUs between January 1, 2000, and June 30, 2003 who had only one nosocomial infection during their stay were included in the study. Infection sites and pathogens, antimicrobial treatment of patient and it's cost were recorded. Daily antibiotic costs were calculated per infected patient. RESULTS: Among the 8460 study patients, 817 (16.6%) developed 1407 episodes of nosocomial infection. Two hundred thirty three (2.7%) presented with only one nosocomial infection. Mean daily antibiotic cost was $89.64. Daily antibiotic cost was$99.02 for pneumonia, $94.32 for bloodstream infection,$94.31 for surgical site infection, $52.37 for urinary tract infection, and$162.35 for the other infections per patient. The treatment of Pseudomonas aeruginosa infections was the most expensive infection treated. Piperacillin-tazobactam and amikacin were the most prescribed antibiotics, and meropenem was the most expensive drug for treatment of the nosocomial infections in the ICU. CONCLUSIONS: Daily antibiotic cost of nosocomial infections is an important part of extra costs that should be reduced providing rational antibiotic usage in hospitals

Antibody profiling and predictive modeling discriminate between Kaposi sarcoma and asymptomatic KSHV infection

Protein-level immunodominance patterns against Kaposi sarcoma-associated herpesvirus (KSHV), the aetiologic agent of Kaposi sarcoma (KS), have been revealed from serological probing of whole protein arrays, however, the epitopes that underlie these patterns have not been defined. We recently demonstrated the utility of phage display in high-resolution linear epitope mapping of the KSHV latency-associated nuclear antigen (LANA/ORF73). Here, a VirScan phage immunoprecipitation and sequencing approach, employing a library of 1,988 KSHV proteome-derived peptides, was used to quantify the breadth and magnitude of responses of 59 sub-Saharan African KS patients and 22 KSHV-infected asymptomatic individuals (ASY), and ultimately to support an application of machine-learning-based predictive modeling using the peptide-level responses. Comparing anti-KSHV antibody repertoire revealed that magnitude, not breadth, increased in KS. The most targeted epitopes in both KS and ASY were in the immunodominant proteins, notably, K8.129−56 and ORF65140-168, in addition to LANA. Finally, using unbiased machine-learning-based predictive models, reactivity to a subset of 25 discriminative peptides was demonstrated to successfully classify KS patients from asymptomatic individuals. Our study provides the highest resolution mapping of antigenicity across the entire KSHV proteome to date, which is vital to discern mechanisms of viral pathogenesis, to define prognostic biomarkers, and to design effective vaccine and therapeutic strategies. Future studies will investigate the diagnostic, prognostic, and therapeutic potential of the 25 discriminative peptides

Common variable immunodeficiency syndrome with right aortic arch: a case report

BACKGROUND: Common variable immunodificiency syndrome predominantly affects adults. It is characterized by low production of all the major classes of immunoglobulins. We report a case of common variable immunodeficiency syndrome with right aortic arch. An association of right-sided arch and common variable immunodificiency syndrome has not been previously reported. CASE PRESENTATION: A 41-year-old female patient presented with a history of recurrent pneumonia, sinusitis, otitis media, diarrhoea, cystitis since childhood. Biochemical and immunocytochemical analysis revealed common variable immunodeficiency syndrome and radiological evaluation confirmed right aortic arch and aberrant left subclavian artery. CONCLUSION: Common variable immunodeficiency syndrome syndrome is a clinical entity that should be kept in mind in patients with recurrent infections of different sites