Slaughterhouse wastewater (SWW) contains a significant volume of highly polluted organic wastes. These include blood, fat, soluble proteins, colloidal particles, suspended materials, meat particles, and intestinal undigested food that consists of higher concentrations of organics such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), nitrogen and phosphorus hence an efficient treatment is required before discharging into the water bodies. The effluent concentrations and performance of simultaneous sequential batch biofilm reactor (SBBR) with recycled plastic carrier media support are better than the local single-stage sequential batch reactor (SBR), which is lacking in the literature in terms of COD, NH3, NO3, and PO4 treatment efficiency. In the present study, we report a novel strategy to remove the above-mentioned contaminants using an intermittently aerated SBBR with recycled plastic carrier media support along with simultaneous nitrification and denitrification. The central composite design was evaluated to optimize the treatment performance of seven different process variables including; different alternating conditions (Oxic/anoxic) for aeration cycles (3/2 h in a 6 h cycle, 6/5 h in a 12 h cycle, and 9/8 h in an 18 h cycle) and hydraulic retention time (6, 12 and 18 h). The average removal efficiencies are 94.5% for NH3, 93% for NO3 and 90.1% for PO4, and 99% for COD. The study reveals that the denitrification in the post-anoxic phase was more efficient than the pre-anoxic phase for pollutant removal and maintaining higher quality effluent. The effluent concentrations and performance of simultaneous SBBR with recycled polyethylene carrier support media were better than local SBR system in terms of COD, NH3, NO3 and PO4 treatment efficiency. Results stipulated the suitability of SBBR for wastewater treatment and reusability as a sustainable approach for wastewater management under optimum conditions.

Since the outbreak of the COVID-19 pandemic, it has been obvious that virus infection poses a serious threat to human health on a global scale. Certain plants, particularly those rich in polyphenols, have been found to be effective antiviral agents. The effectiveness of Alchemilla viridiflora Rothm. (Rosaceae) methanol extract to prevent contact between virus spike (S)-glycoprotein and angiotensin-converting enzyme 2 (ACE2) and neuropilin-1 (NRP1) receptors was investigated. In vitro results revealed that the tested samples inhibited 50% of virus-receptor binding interactions in doses of 0.18 and 0.22 mg/mL for NRP1 and ACE2, respectively. Molecular docking studies revealed that the compounds from A. viridiflora ellagitannins class had a higher affinity for binding with S-glycoprotein whilst flavonoid compounds more significantly interacted with the NRP1 receptor. Quercetin 3-(6″-ferulylglucoside) and pentagalloylglucose were two compounds with the highest exhibited interfering potential for selected target receptors, with binding energies of −8.035 (S-glycoprotein) and −7.685 kcal/mol (NRP1), respectively. Furthermore, computational studies on other SARS-CoV-2 strains resulting from mutations in the original wild strain (V483A, N501Y-K417N-E484K, N501Y, N439K, L452R-T478K, K417N, G476S, F456L, E484K) revealed that virus internalization activity was maintained, but with different single compound contributions.

Aim To analyse biochemical markers as possible predictors of death before discharge in cooled newborns following perinatal asphyxia. Methods A total of 91 infants that underwent therapeutic hypothermia after perinatal asphyxia were included. Inclusion criteria for therapeutic hypothermia were Sarnat stage 2 or 3. Data were collected from medical histories regarding gender, gestational age, birth weight, Apgar and Sarnat score; additionally, gas analyses, liver and cardiac enzymes before, and in the first 12 hours after starting therapeutic hypothermia, were evaluated. The patients' characteristics were compared between two groups, survivors and non-survivors. Results Statistical difference was not found between groups regarding gender, gestational age, birth weight, delivery type, 1st and 5th minute Apgar score, seizures, alanine aminotransferase (ALT), creatine kinase (CK), troponin and fibrinogen level. Groups were significantly different regarding acid-base balance (p=0.012), base excess (BE) (p=0.025), lactate (p=0.002), aspartate aminotransferaze (AST), (p=0.011), lactate dehydrogenase (LDH) (p=0.006), activated partial thromboplastin clotting time (aPTT) (p=0.001) and international normalized ratio (INR) (p=0.001). Conclusion Acid-base balance, BE, lactate, AST, LDH, aPTT and INR were significantly higher in the group of cooled newborns after perinatal asphyxia (non-survivors), and can serve as predictors of death before discharge. Combining diagnostic modalities raises a chance for accurate prediction of outcomes of asphyxiated infants.

Background

Background Attention-deficit/hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD) are associated but it is unclear if this is a causal relationship or confounding. We used genetic analyses and sibling comparisons to clarify the direction this relationship. Methods Linkage Disequilibrium Score Regression and two-sample Mendelian randomization (MR) were used to test for genetic correlation (rg) and bidirectional causal effects using European ancestry genome-wide association studies of ADHD (20,183 cases and 35,191 controls) and six PTSD definitions (up to 320,369 individuals). Several additional variables were included in the analysis to verify the independence of the ADHD-PTSD relationship. In a population-based sibling comparison (N=2,082,118 individuals), Cox regression models were fitted to account for time at risk, a range of sociodemographic factors, and unmeasured familial confounders (via sibling comparisons). Results ADHD and PTSD had consistent rg (rg range, 0.43–0.52; P < .001). ADHD genetic liability was causally linked with increased risk for PTSD (Beta=0.367, 95% confidence interval (CI), 0.186-0.552, P=7.68x10−5). This result was not affected by heterogeneity, horizontal pleiotropy (MR Egger intercept=4.34x10−4, P=0.961), or other phenotypes, and was consistent across PTSD datasets. However, we found no consistent associations between PTSD genetic liability and ADHD risk. Individuals diagnosed with ADHD were at a higher risk for developing PTSD than their undiagnosed sibling (hazard ratio=2.37, 95% CI 1.98-3.53). Conclusions Our findings add novel evidence supporting the need for early and effective treatment of ADHD as patients with this diagnosis are at significantly higher risk to develop PTSD later in life.

Caused by the new SARS-CoV-2 coronavirus, COVID-19 (coronavirus disease 2019) evolves with clinical symptoms that vary widely in severity, from mild symptoms to critical conditions, which can even result in the patient's death. A critical aspect related to an individual response to SARS-CoV-2 infection is the competence of the immune system, and it is well known that several trace elements are essential for an adequate immune response and have anti-inflammatory and antioxidant properties that are of particular importance in fighting infection. Thus, it is widely accepted that adequate trace element status can reduce the risk of SARS-CoV-2 infection and disease severity. In this study, we evaluated the serum levels of Cu, Zn, Se, Fe, I and Mg in patients (n = 210) with clinical conditions of different severity (“mild”, “moderate”, “severe” and “exitus letalis”, i.e., patients who eventually died). The results showed significant differences between the four groups for Cu, Zn, Se and Fe, in particular a significant trend of Zn and Se serum levels to be decreased and Cu to be increased with the severity of symptoms. For Mg and I, no differences were observed, but I levels were shown to be increased in all groups.

Aim To evaluate clinical and epidemiological characteristics and outcome of patients with COVID-19, and impact of vaccine against COVID-19 on them. Methods This retrospective study included 225 patients treated from COVID-19 in the period from 1 to 30 September 2021 at the Clinic for Infectious Diseases, University Clinical Centre Tuzla (UCC Tuzla). For the diagnosis confirmation of Covid-19, RTPCR was used. Patients were divided in two groups: fully vaccinated with two doses of vaccine, and non-vaccinated or partially vaccinated. Results Of 225 patients, 120 (53.3%) were females, and 105 (46.7%) males. Mean age was 65.6 years. There were 26 (11.6%) fully vaccinated patients. Most common symptoms in unvaccinated patients were fatigue (70.9%), cough (70.4%) and fever (69.8%), and in vaccinated fever (76.9%), fatigue (69.2%) and cough (46.2%). Cough was more common in unvaccinated patients (p=0.013). Fatal outcome happened in 84 (37.3%) patients. Transfer to the Intensive Care Unit (ICU) and older age had a higher risk of death (p<0.001). Older age patients were more likely to have comorbidities like atrial fibrillation (p=0.017), hypertension (p<001) and diabetes mellitus (p=0.002). Atrial fibrillation (p<0.001), hypertension (p<0.001), diabetes mellitus (p=0.009) and history of stroke (p=0.026), were related to fatal outcome in unvaccinated patients, also did a shorter duration of illness prior to hospitalization (p<0.001) and shorter length of hospitalization (p=0.002). Conclusion Older patients with comorbidities, as well as those who were not vaccinated against COVID-19, were at higher risk for severe form of the disease and poor outcome.

Background: Despite many advances in the prevention, of sternal wound infection, especially deep ones, cardiac surgery with median sternotomy, still presents a significant postoperative complication. Numerous operative and non-operative procedures should be used in treatment, there is a prolonged hospital stay and increased hospital costs treating this postoperative complication. Objective: The present study was conducted aiming to determine the incidences, and risk factors, identify microbiology findings, and antibiotic therapy among patients with DSWI who underwent cardiac surgery with median sternotomy at our Clinic and VAC treatment. Methods: This retrospective observational study was conducted in Clinic for Cardiovascular Surgery at University Clinical Center Sarajevo from November 2015 to November 2020. The data were obtained from 15 patients with deep sternal wound infection (DSWI) following open-heart surgery. The inclusion criteria were DSWI after cardiac operation via median sternotomy, and complete results of microbiological findings obtained by sternal swab. The exclusion criteria were patients with incomplete clinical data. Results: We found that 9 (60%) patients were males and 6 (40%) were females. Coronary artery bypass grafting (CABG) operation had 11 (73,3%) patients, CABG with aortic valve replacement 2 (13,3%), valve replacement surgery operations (13,3%). The average age was 66 years. All patients were elective surgery patients. STS score in the Non-VAC group was 22.6, in the VAC group 16.6, and the average was 14.9. The number of patients with DSWI represents 1% of all sternotomy patients in the observed period. Two risk factors for DSWI had 37% of patients, 25% of them were diabetic, and 3 (9%) were overweight. Enterococcus faecalis was isolated predominantly in 6 (27%) patients, followed by Klebsiella pneumonia 3 (13%), Proteus mirabilis 2 (9%), and Serratia Maecenas 2 (9%). The mortality rate was 33.3% (5 of 15). Conclusion: The results of our study present our experience with DSWI treatment after open-heart surgery. What comes from our experience so far, is that is very important to determine patients who are at risk of developing DSWI after cardiac surgeries to lower its incidence.

Highlights • qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque.• MWF and MTsat exhibited the highest sensitivity to NAWM pathology.• qT1 appeared to be the most sensitive measure to NAGM pathology.• All myelin-sensitive qMRI measures exhibited high intra-scanner reproducibility.

This work aims to synthesize polygalacturonate-based magnetic iron oxide nanoparticles (INP-polyGalA). The synthesis consists of the diffusion of both Fe2+ and Fe3+ at a molar ratio of 1:2 through polyGalA solution followed by the addition of an alkaline solution. To form individual nanoparticle materials, the polyGalA concentration needs to be below its overlapping concentration (C*). The synthesized materials (INP-polyGalA) contain about 45 % of organic compound (polyGalA), and they have an average particle size ranging from 10 to 50 nm as estimated by several techniques (DLS, TEM and AFM) and their surfaces are negatively charged in pH range 2 to 7. The synthesized NPs showed magnetic characteristics, thanks to the formation of magnetite (Fe3O4) as confirmed by X-ray diffractions (XRD). Moreover, AFM combined with Infra-red mapping allowed us to conclude that polyGalA is located in the core of the nanoparticles but also on their surfaces. More specially, both carboxylate (COO-) and carboxylic (COOH) groups of polyGalA are observed on the NPs surfaces. The presence of such functional groups allowed the synthesized material to (i) bind through the electrostatic interactions methylene blue (MB) which may have a great potential for r pollution control or (ii) to form hydrogel beads (ionotropic gelation) by using calcium as a crosslinking agent which can be used to encapsulate active molecules and target their release by using an external stimulus (magnetic field).

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Manual segmentation is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Over the last decades, the active development in the field of deep learning, especially convolutional neural networks (CNNs), and the associated performance improvements have increased the demand for the application of CNN-based methods to provide consistent measurements and quantitative analyses. In this paper, we present an efficient deep learning approach for the segmentation of brain tissue. More specifically, we address the problem of segmentation of the posterior limb of the internal capsule (PLIC) in preterm neonates. To this end, we propose a CNN-based pipeline comprised of slice-selection modules and a multi-view segmentation model, which exploits the 3D information contained in the MRI volumes to improve segmentation performance. One special feature of the proposed method is its ability to identify one desired slice out of the whole image volume, which is relevant for pediatricians in terms of prognosis. To increase computational efficiency, we apply a strategy that automatically reduces the information contained in the MRI volumes to its relevant parts. Finally, we conduct an expert rating alongside standard evaluation metrics, such as dice score, to evaluate the performance of the proposed framework. We demonstrate the benefit of the multi-view technique by comparing it with its single-view counterparts, which reveals that the proposed method strikes a good balance between exploiting the available image information and reducing the required computing power compared to 3D segmentation networks. Standard evaluation metrics as, well as expert-based assessment, confirm the good performance of the proposed framework, with the latter being more relevant in terms of clinical applicability. We demonstrate that the proposed deep learning pipeline can compete with the experts in terms of accuracy. To prove the generalisability of the proposed method, we additionally assess our deep learning pipeline to data from the Developing Human Connectome Project (dHCP).

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.