Correlation between Polycyclic Aromatic Hydrocarbons in Wharf Roach (Ligia spp.) and Environmental Components of the Intertidal and Supralittoral Zone along the Japanese Coast

Polycyclic aromatic hydrocarbon (PAH) concentrations in wharf roach (Ligia spp.), as an environmental indicator, and in environmental components of the intertidal and supralittoral zones were determined, and the PAH exposure pathways in wharf roach were estimated. Wharf roaches, mussels, and environmental media (water, soil and sand, and drifting seaweed) were collected from 12 sites in Japan along coastal areas of the Sea of Japan. PAH concentrations in wharf roaches were higher than those in mussels (median total of 15 PAHs: 48.5 and 39.9 ng/g-dry weight (dw), respectively) except for samples from Ishikawa (wharf roach: 47.9 ng/g-dw; mussel: 132 ng/g-dw). The highest total PAH concentration in wharf roach was from Akita (96.0 ng/g-dw), followed by a sample from Niigata (85.2 ng/g-dw). Diagnostic ratio analysis showed that nearly all PAHs in soil and sand were of petrogenic origin. Based on a correlation analysis of PAH concentrations between wharf roach and the environmental components, wharf roach exposure to three- and four-ring PAHs was likely from food (drifting seaweed) and from soil and sand, whereas exposure to four- and five-ring PAHs was from several environmental components. These findings suggest that the wharf roach can be used to monitor PAH pollution in the supralittoral zone and in the intertidal zone.

SARS-CoV-2 Detection on Bronchoalveolar Lavage: An Italian Multicenter experience

<b><i>Background:</i></b> Bronchoscopy with bronchoalveolar lavage (BAL) during the SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) pandemic should be reserved to a limited number of clinical indications. The yield of BAL for the diagnosis of suspected or confirmed pulmonary SARS-CoV-2 infection is still unknown. <b><i>Objectives:</i></b> We aimed to evaluate the diagnostic ratio of BAL in detecting SARS-CoV-2 pulmonary infection in patients undergoing bronchoscopy for different indications as well as describe the clinical, radiological, and endoscopic characteristics of patients with SARS-CoV-2 on BAL. <b><i>Method:</i></b> We conducted a multicenter retrospective study including all patients who underwent bronchoscopy for the detection of SARS-CoV-2 on BAL. Clinical, computed tomography (CT), endoscopic, and microbiologic data were gathered from March 16th to May 27th, 2020. <b><i>Results:</i></b> 131 patients were included. Bronchoscopy was performed for suspected SARS-CoV-2 infection (65.5%), alternative diagnosis (12.9%), suspected superinfections (19.8%), and lung atelectasis (1.5%). SARS-CoV-2 was isolated on BAL 43 times (32.8%) and the highest isolation rate was in patients with suspected SARS-CoV-2 infection (74.4%); 76% of positive patients had a double-negative nasopharyngeal swab. Peripheral, posterior and multilobar CT opacities were more frequent in SARS-CoV-2 patients, and the number of CT findings was higher in positive patients, particularly those with suspected SARS-CoV-2 infection. We recorded a progressive reduction of SARS-CoV-2 isolation during the observation period. <b><i>Conclusions:</i></b> In our centers, the rate of detection of SARS-CoV-2 on BAL in patients with suspected infection was 37.2%. The agreement of BAL with nasopharyngeal swabs was high; CT alterations could predict the pretest probability of SARS-CoV-2 infection, but suspicion of viral infection should be always considered.

Deep Learning Could Diagnose Diabetic Nephropathy with Renal Pathological Immunofluorescent Images

Artificial Intelligence (AI) imaging diagnosis is developing, making enormous steps forward in medical fields. Regarding diabetic nephropathy (DN), medical doctors diagnose them with clinical course, clinical laboratory data and renal pathology, mainly evaluate with light microscopy images rather than immunofluorescent images because there are no characteristic findings in immunofluorescent images for DN diagnosis. Here, we examined the possibility of whether AI could diagnose DN from immunofluorescent images. We collected renal immunofluorescent images from 885 renal biopsy patients in our hospital, and we created a dataset that contains six types of immunofluorescent images of IgG, IgA, IgM, C3, C1q and Fibrinogen for each patient. Using the dataset, 39 programs worked without errors (Area under the curve (AUC): 0.93). Five programs diagnosed DN completely with immunofluorescent images (AUC: 1.00). By analyzing with Local interpretable model-agnostic explanations (Lime), the AI focused on the peripheral lesion of DN glomeruli. On the other hand, the nephrologist diagnostic ratio (AUC: 0.75833) was slightly inferior to AI diagnosis. These findings suggest that DN could be diagnosed only by immunofluorescent images by deep learning. AI could diagnose DN and identify classified unknown parts with the immunofluorescent images that nephrologists usually do not use for DN diagnosis.

Geochemical Assessment of the Biodegradation Levels of Some Crude Oils from Bayelsa State, Nigeria

Coastal swamp crude oil samples obtained from Clough creek, Azuzuama and Tebidaba oil fields were analyzed to obtain their biodegradation rankings. The studied samples were fractionated by column chromatography into saturated and aromatic hydrocarbons. The saturated hydrocarbons were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). Some diagnostic ratios such as C 30 αβhopane/(Pr+Ph), (Pr+Ph)/(nC 17 +nC 18 ) and C 29 αβ 25 norhopane/C 30 αβhopane were used in assessing the biodegradation rankings. Though biodegradation was evident in the studied samples, their individual levels were compared based on these ratios. Assessment of the crude oil samples using C 29 αβ25norhopane/C 30 αβhopane ratio show that the oils from AZU ST and TEB12 are more degraded when compared to oils from WELL 2. Consequently, (Pr+Ph)/ (nC 17 +nC 18) ratios show that TEB 12 is the most degraded while WELL 2 is the least degraded. AZU ST was also shown as the most degraded oil using C 30 αβhopane/(Pr+Ph) diagnostic ratio.

Intelligent Ball Bearing Fault Diagnosis by using Fractional Lorenz Chaos Extension Detection Method with Acceleration Sensor

In this study we used a non-autonomous Chua&rsquo;s Circuit, and the fractional Lorenz chaos system together with a detection method from Extension theory to analyze the voltage signals. The measured bearing signals by acceleration sensor were introduced into the master and slave systems through a Chua&rsquo;s Circuit. In a chaotic system minor differences can cause significant changes that generate dynamic errors, and extension matter-element models can be used to judge the bearing conditions. Extension theory can be used to establish classical and sectional domains using the dynamic errors of the fault conditions. The results obtained were compared with those from Discrete Fourier Transform analysis, Wavelet analysis and an integer order chaos system. The diagnostic ratio showed the fractional order master and slave chaos system calculations. The results show that the method presented in this paper is very suitable for monitoring the operational state of ball bearing system to be superior to the other methods. The diagnosis ratio was better and there were other significant advantages such as low cost and few.

Levels of PAHs in shrimps, Penaeus monodon from Jones Creek southern Nigeria

Polycyclic aromatic hydrocarbons (PAHs) were measured in shrimp samples (Penaeus monodon) of Jones Creek southern Nigeria during the rainy and dry seasons and analysed for 16 priority PAHs. The ΣPAHs ranged from 0.073 to 0.800 mg/kg for shrimp samples collected for the 18 month duration of this study. Fluorene and anthracene were the most dominant PAH observed with concentrations of 0.084 ± 0.010 mg/kg and 0.059 ± 0.007 mg/kg respectively. Fluorene was also the most detected PAH comprising 21.91% of the 16 PAHs detected while benzo(g,h,i)perylene was the least with 0.02%. The source of contamination is closely related to human activities such as domestic and industrial discharges, refining activities and street runoff. High concentrations were recorded during the rainy season and during the first quarter of the year. The investigated samples were classified as minimally contaminated when compared with FDA levels of PAHs in shrimp samples. Distribution patterns showed that PAHs with 3 and 4 rings dominated confirming the pyrogenic source of the detected PAH. Diagnostic ratios such as phenanthrene/anthracene and benzo(a)anthracene/chrysene were achieved to evaluate the emission sources of PAHs. These ratios indicated a pyrolytic source of PAHs for sediments, as well as a pyrolytic or pyrogenic origin of the PAHs detected in the shrimp samples obtained within the study area.Key words: PAHs, sediment, shrimps, cancer risk, diagnostic ratio.