Enhance the physicochemical properties of the citronella oil -SLNPs to improve the insecticidal activity against Spodoptera littoralis (Boisd) (Lep. Nactuidae).

The Nano-formulation of citronella essential oil (Cymbopogon nardus (L.) and their mixtures of three adjuvants (Provecta®, Top film®, and PEG600-dioleate) were studied to enhance physico-chemical properties of the Nano-formulation and improve the insecticidal effect against Spodoptera littoralis (Boisd). Characterisation of physicochemical properties of Nano-formulation was studied by calculating droplet size, polydispersity index (PDI), and Zeta-potential parameters. The results showed that the Solid Lipid Nanoparticles (SLNs) mixtures of three adjuvant mixtures had more toxic activity and stability than the Nano-formulation alone. Before storage the acidity, alkalinity (pH), and viscosity exhibited an acidic pH value in the range (4.11-5.34), whereas after three months of storage was recorded high pH, a shift in the pH on storage can indicate the instability of active substances or product under semi field-laboratory conditions. Nano-formulation of the citronella oil mixed with the three adjuvants increased the mortality percentage of S. littoralis larvae.

Optimal controller design for reactor core power stabilization in a pressurized water reactor: Applications of gold rush algorithm.

Nuclear energy (NE) is seen as a reliable choice for ensuring the security of the world's energy supply, and it has only lately begun to be advocated as a strategy for reducing climate change in order to meet low-carbon energy transition goals. To achieve flexible operation across a wide operating range when it participates in peak regulation in the power systems, the pressurised water reactor (PWR) NE systems must overcome the nonlinearity problem induced by the substantial variation. In light of this viewpoint, the objective of this work is to evaluate the reactor core (main component) of the NE system via different recent optimization techniques. The PWR, which is the most common form, is the reactor under investigation. For controlling the movement of control rods that correspond with reactivity for power regulation the PWR, PID controller is employed. This study presents a dynamic model of the PWR, which includes the reactor core, the upper and lower plenums, and the piping that connects the reactor core to the steam alternator is analyzed and investigated. The PWR dynamic model is controlled by a PID controller optimized by the gold rush optimizer (GRO) built on the integration of the time-weighted square error performance indicator. Additionally, to exhibit the efficacy of the presented GRO, the dragonfly approach, Arithmetic algorithm, and planet optimization algorithm are used to adjust the PID controller parameters. Furthermore, a comparison among the optimized PID gains with the applied algorithms shows great accuracy, efficacy, and effectiveness of the proposed GRO. MATLAB\ Simulink program is used to model and simulate the system components and the applied algorithms. The simulation findings demonstrate that the suggested optimized PID control strategy has superior efficiency and resilience in terms of less overshoot and settling time.

Phenolics from Nigella sativa L. straw: Characterization and insecticidal activity against Agrotis ipsilon (Hüfnagel).

The excessive production of food and agro-waste has become a significant problem for society, the economy, and the environment. To meet the growing demand for food free from harmful synthetic insecticides, a recent study has investigated the potential use of an ethanolic extract obtained from the straw of Nigella sativa L., a byproduct of seed collection, as a bioinsecticide. The study also evaluated its in-vitro and in-silico acetylcholinesterase (AChE) inhibitory potential against the Agrotis ipsilon (Hufnagel) moth species, which is known to cause damage to various crops and ornamental plants. The high-performance liquid chromatography examination revealed that the ethanolic N. sativa straw extract contained 18 phenolics, including 3 simple phenols, 8 phenolic acids, and 7 flavonoids. Catechol (330.14 µg/ml), chlorogenic (169.23 µg/ml), and gallic (110.93 µg/ml) acids were the predominant phenolics. On the other hand, catechin (94.07 µg/ml), naringenin (91.99 µg/ml), and rutin (78.16 µg/ml) were the major flavonoids identified in the extract. The insecticidal activity of the extract against the 4th larval instar of A. ipsilon was evaluated using four concentrations (1.25-10 %). The study found that higher extract concentrations led to increased mortality in the larvae. Specifically, the concentration of 10 % resulted in the highest mortality rate of 96.67 %. Lower concentrations of 5 %, 2.5 %, and 1.25 % resulted in mortality rates of 51.11 %, 18.89 %, and 9.17 %, respectively. The extract also showed higher activity against AChE in larval tissue, with an inhibition percentage of 65.2 % after 24 h of treatment. Docking experiments confirmed that ellagic acid and apigenin had higher binding affinity than the control (lanate). These results demonstrate the potential of utilizing agricultural waste like N. sativa straw to create innovative and sustainable bioinsecticides.

FMDNet: An Efficient System for Face Mask Detection Based on Lightweight Model during COVID-19 Pandemic in Public Areas.

A new artificial intelligence-based approach is proposed by developing a deep learning (DL) model for identifying the people who violate the face mask protocol in public places. To achieve this goal, a private dataset was created, including different face images with and without masks. The proposed model was trained to detect face masks from real-time surveillance videos. The proposed face mask detection (FMDNet) model achieved a promising detection of 99.0% in terms of accuracy for identifying violations (no face mask) in public places. The model presented a better detection capability compared to other recent DL models such as FSA-Net, MobileNet V2, and ResNet by 24.03%, 5.0%, and 24.10%, respectively. Meanwhile, the model is lightweight and had a confidence score of 99.0% in a resource-constrained environment. The model can perform the detection task in real-time environments at 41.72 frames per second (FPS). Thus, the developed model can be applicable and useful for governments to maintain the rules of the SOP protocol.

Cardiovascular and Thyroid Late Effects in Pediatric Patients With Hodgkin Lymphoma Treated With ABVD Protocol.

BACKGROUND: Hodgkin lymphoma (HL) survivors are at risk of developing a range of therapy-related complications. The goal of this study is to investigate therapy-related late-effects in HL survivors. MATERIALS AND METHODS: We performed a cross-sectional study on 208 HL survivors who were treated at the National Cancer Institute or at the Children Cancer Hospital Egypt with doxorubicin, bleomycin, vinblastine, and dacarbazine chemotherapy. RESULTS: Age at diagnosis ranged from 2.5 to 17.5 with a median of 8.7 years. The cumulative incidence of cardiac toxicity at 5 and 9 years were 18.7%±2.7% and 43.3%±4.4%, respectively. Preexisting cardiac abnormalities, cumulative anthracycline dose, and end of treatment cardiac status are strong predictors of late cardiotoxicity. Hypertension was observed in ~31% of patients. Young age and obesity at the time of treatment are important risk factors for hypertension. Thyroid abnormalities developed with a 5-year cumulative incidence of 2%±1%, whereas at 9 years the cumulative incidence was 27.9%±4.5%. Thyroid dysfunction was observed in 21.2% and thyroid tumors in 1.6% of cases. Subclinical hypothyroidism was the most common thyroid abnormality. CONCLUSIONS: Cardiotoxicity, hypertension, and thyroid dysfunction are frequent late effects after doxorubicin, bleomycin, vinblastine, and dacarbazine regimen, especially if combined with radiation therapy.

Multiple Site Dissimilarities of Herbaceous Species Due to Coal Fly Ash Dumping Based Soil Heavy Metal Toxication.

The present study analyzes the determinants and patterns of the regional, local, and differential plant diversity of two different sites with similar climatic but varied edaphic factors. This research was undertaken to study the plant diversity and population structure as a consequence of variation in the soil quality between two biotopes: Guru Ghasidas Vishwavidyalaya in Koni (site-I) and National Thermal Power Corporation in Sipat (site-II). The soil of site-I was found to be fertile and showed rich vegetation. On the other hand, the soil of site II was found to be contaminated with heavy metals, which impacts the flora of the region. The ecology of both sites was studied, and their quantitative and qualitative aspects were compared and contrasted. The abundance, density, and richness of the plants in site II were fairly lower than in site-I, which was confirmed by utilizing Simpson's and Shannon's diversity indices. Many of the species collected from site II were heavy metal accumulators and could also serve as indicators of heavy metal toxicity.

African Swine Fever and Its Control Measures in Wild Boar: A "De Iure Condito" Analysis in the European Union.

Recently, the African swine fever (ASF) epizootic has been reported in domestic pigs and wild boars in several European Union Member States (EU MS) and epidemiological evidence has accumulated which indicates that wild boar play a key role in maintaining and spreading the disease. Thanks to the experience gained when managing ASF outbreaks in Sardinia (Italy) and Eastern Europe, Directive 2002/60 CE was issued. This directive represented an important step forward in controlling the disease, particularly the risk of spreading the virus to wild animals. Since 2021, according to Regulation (EU) 2016/429, which is also called "Animal Health Law-AHL", when the MS competent authority suspects or confirms ASF (a cat. A listed disease) in wild animals, it is mandatory to conduct surveillance in the wild boar population and implement the necessary control measures. Within AHL, Regulations (EU) 2020/687 and 2023/594 established special ASF control measures in kept and wild porcine animals, and their products and by-products, focusing on and underlying old and new responsibilities that vets (both public and private ones) have to accomplish under the new regulations. The new change in the legal framework deals with specific measures to be applied in the wild and represents a great challenge for MS veterinary services. Some of these measures have been well established in the last two decades, particularly those related to application in the farming system, while other measures are still new to veterinary health management and require a holistic approach in terms of intensity, considering all geographical, ecological, productive, cultural and social features of the involved EU MS. In this contribution, the authors intend to focus on specific measures which have been issued in order to limit or stop the spread of ASF in a wild, "boundless" ecosystem. These measures expand the field of competence of the official veterinary service to wild areas in addition to farm activity.

Conditional Most-Correlated Distribution-Based Load-Balancing Scheme for Hybrid LiFi/WiGig Network.

A hybrid network has recently been proposed as a framework for a high-speed wireless communication network. Basically, it integrates light fidelity (LiFi) with radio frequency wireless gigabit alliance (WiGig) networks that operate, simultaneously, in a completely different frequency band. To assign the best access point (AP) and provide enough resources for each user, an effective load-balancing (LB) strategy is needed. However, the traditional LB strategies involve sophisticated iterative computing procedures whenever the user distribution changes. Hence, the first contribution of this work is to offer a more adaptable, two-step, conditional, and most-correlated distribution (CMCD) algorithm. Thus, the low-complexity most-correlated distribution (MCD) LB scheme is applied, and the average data rates for all users are then calculated. If the results achieve the predefined performance threshold (PDT), the decisions will be confirmed; otherwise, the proposed scheme automatically switches to the more accurate, but more complex, consecutive assign WiGig first separate optimization algorithms (CAWFS) algorithm. The suggested algorithm provides a clear performance-complexity trade-off, which could be simply controlled by choosing the suitable performance tolerance factor. The second contribution of this paper is the correlation-weighted majority voting (CWMV) method, which attempts to benefit from as many prior decision votes as possible, instead of relying just on one vote. In the CWMV technique, the weight of each vote is calculated based on the correlation between the history distribution vectors and the new user distribution vector. A significant increase in the system performance is evident from the simulation results.

Preliminary Study on the Host Response to Bivalent and Monovalent Autogenous Vaccines against Mycoplasma agalactiae in Dairy Sheep.

In Italy, dairy sheep farming represents a vital agro-industry sector, but it is still challenged by contagious agalactia (CA), which is endemic there, and vaccination is the most economical and sustainable tool for control. This study aimed to evaluate the combined Mycoplasma agalactiae (Ma)-Staphylococcus aureus (Sa) vaccine (Ma-Sa) against the Ma monovalent vaccine in ewes. Twelve primiparous Ma-free ewes were randomly grouped into three equal groups: first, the control group injected with placebo, second, the group vaccinated with the Ma monovalent vaccine, and third, the group vaccinated with Ma-Sa combined vaccine, with two S/C doses at 45-day intervals. The animals were examined for serological, hematological, and somatic cell count (SCC) changes for 17 successive weeks. A significant increase in anti-Ma antibody mean titers, leukocytes, and platelets was observed in the vaccinated animals, with the highest values in those who received the combined vaccine. Neutrophils were high only in the animals who received the combined vaccine. SCC was lower in the vaccinated animals during the first six weeks. This study concludes that the combined Ma-Sa vaccines enhance immune response and potentiate its efficacy against Ma. This improvement might be attributed to the sensitization/activation effect of S. aureus on platelets, which are recoded to act as a key regulator for the coordination of all components of the innate immune system. Even though this study included a small number of animals, its findings about the potentialities of this inactivated vaccine in the control of CA are strongly encouraging. Further confirmation might be needed through additional replicates and a challenge study is needed before proceeding with widespread use.

COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization.

The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a result, it has disastrous consequences for people's lives, public health, and the global economy. Clinical studies have revealed a link between the severity of COVID-19 cases and the amount of virus present in infected people's lungs. Imaging techniques such as computed tomography (CT) and chest x-rays can detect COVID-19 (CXR). Manual inspection of these images is a difficult process, so computerized techniques are widely used. Deep convolutional neural networks (DCNNs) are a type of machine learning that is frequently used in computer vision applications, particularly in medical imaging, to detect and classify infected regions. These techniques can assist medical personnel in the detection of patients with COVID-19. In this article, a Bayesian optimized DCNN and explainable AI-based framework is proposed for the classification of COVID-19 from the chest X-ray images. The proposed method starts with a multi-filter contrast enhancement technique that increases the visibility of the infected part. Two pre-trained deep models, namely, EfficientNet-B0 and MobileNet-V2, are fine-tuned according to the target classes and then trained by employing Bayesian optimization (BO). Through BO, hyperparameters have been selected instead of static initialization. Features are extracted from the trained model and fused using a slicing-based serial fusion approach. The fused features are classified using machine learning classifiers for the final classification. Moreover, visualization is performed using a Grad-CAM that highlights the infected part in the image. Three publically available COVID-19 datasets are used for the experimental process to obtain improved accuracies of 98.8, 97.9, and 99.4%, respectively.

COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization.

Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the lives of millions of people worldwide in the last 2 years. Because of the disease's rapid spread, it is critical to diagnose it at an early stage in order to reduce the rate of spread. The images of the lungs are used to diagnose this infection. In the last 2 years, many studies have been introduced to help with the diagnosis of COVID-19 from chest X-Ray images. Because all researchers are looking for a quick method to diagnose this virus, deep learning-based computer controlled techniques are more suitable as a second opinion for radiologists. In this article, we look at the issue of multisource fusion and redundant features. We proposed a CNN-LSTM and improved max value features optimization framework for COVID-19 classification to address these issues. The original images are acquired and the contrast is increased using a combination of filtering algorithms in the proposed architecture. The dataset is then augmented to increase its size, which is then used to train two deep learning networks called Modified EfficientNet B0 and CNN-LSTM. Both networks are built from scratch and extract information from the deep layers. Following the extraction of features, the serial based maximum value fusion technique is proposed to combine the best information of both deep models. However, a few redundant information is also noted; therefore, an improved max value based moth flame optimization algorithm is proposed. Through this algorithm, the best features are selected and finally classified through machine learning classifiers. The experimental process was conducted on three publically available datasets and achieved improved accuracy than the existing techniques. Moreover, the classifiers based comparison is also conducted and the cubic support vector machine gives better accuracy.

BrainNet: Optimal Deep Learning Feature Fusion for Brain Tumor Classification.

Early detection of brain tumors can save precious human life. This work presents a fully automated design to classify brain tumors. The proposed scheme employs optimal deep learning features for the classification of FLAIR, T1, T2, and T1CE tumors. Initially, we normalized the dataset to pass them to the ResNet101 pretrained model to perform transfer learning for our dataset. This approach results in fine-tuning the ResNet101 model for brain tumor classification. The problem with this approach is the generation of redundant features. These redundant features degrade accuracy and cause computational overhead. To tackle this problem, we find optimal features by utilizing differential evaluation and particle swarm optimization algorithms. The obtained optimal feature vectors are then serially fused to get a single-fused feature vector. PCA is applied to this fused vector to get the final optimized feature vector. This optimized feature vector is fed as input to various classifiers to classify tumors. Performance is analyzed at various stages. Performance results show that the proposed technique achieved a speedup of 25.5x in prediction time on the medium neural network with an accuracy of 94.4%. These results show significant improvement over the state-of-the-art techniques in terms of computational overhead by maintaining approximately the same accuracy.

The Valorization of Spent Coffee Ground Extract as a Prospective Insecticidal Agent against Some Main Key Pests of Phaseolus vulgaris in the Laboratory and Field.

The exploitation of massive amounts of food and agro-waste represents a severe social, economic, and environmental issue. Under the growing demand for food products that are free of toxic synthetic insecticides, a methanolic extract of spent coffee grounds (SCGs), which represent the main byproduct of coffee production, was applied in the current study as a bioinsecticide against the main pests of the green bean: Spodoptera littoralis, Agrotis ipsilon, Bemisia tabaci, Empoasca fabae, and Aphis craccivora. A deterrent assay, contact bioassay, and lethal concentration analysis were performed to reveal the repellent, antifeedant, and oviposition deterrent effects. Parallel to the above-mentioned bioassays, the phytochemical composition of the methanolic SCG extract was investigated via a high-performance liquid chromatography (HPLC) analysis. Fourteen phenolic acids and five flavonoids, in addition to caffeine (alkaloid), were identified in the extract. Cinnamic, rosmarinic, and gallic acids were the predominant phenolics, while apigenin-7-glucoside was the main flavonoid, followed by naringin, catechin, and epicatechin. The extract of SCGs showed an insecticidal effect, with a mortality between 27.5 and 76% compared to the control (7.4%) and based on the concentration of the extract used. In the same trend, the oviposition efficiency revealed different batches of laid eggs (0.67, 2.33, 7.33, and 8.67 batches/jar) for 100, 50, and 25% of the SCG extract and the control. Finally, the major components of the SCG extract were docked into the insecticide acetylcholinesterase enzyme to explore their potential for inhibition, where apigenin-7-glucoside showed a higher binding affinity, followed by catechin, compared to the control (lannate). The obtained findings could be a starting point for developing novel bioinsecticides from SCGs.

Impact of sustained virologic response in regression of portal hypertension in Egyptian patients with hepatitis C virus-associated cirrhosis and portal hypertension.

Background: Portal hypertension (PH) is a common consequence in hepatitis C virus cirrhotic patients. With interferon alpha-based therapy, SVR was linked to improved PH and fibrosis regression. SVR to oral antiviral regimens is linked to reduced portal pressure in patients with clinically significant portal hypertension (CSPH) at baseline. However, CSPH continues in most of the patients. This study aims to assess the reversibility and/or improvement of PH in Egyptian patients with HCV-related cirrhosis and CSPH after achieving SVR with DAAs. The second aim is to evaluate performance of the noninvasive markers of fibrosis in prediction of the presence and/or reversibility of the CSPH in correlation to radiological and endoscopic parameters. Subjects and methods: We evaluated noninvasive parameters, radiological and endoscopic signs of PH at baseline, and/or SVR 24 and SVR 48 post-DAA therapy in 40 patients with cirrhosis and CSPH (group A) and another 40 patients with cirrhosis only (group B). Results: In group A, the spleen diameter decreased from baseline (15.74 ± 1.53 cm), and SVR 24 (15.48 ± 1.51), to SVR 48 (15.35 ± 1.49 cm). No ascites detected at SVR 48 in 62.5%. Portal vein diameter and portal vein blood velocity reduced to 13.53 ± 1.07 mm and 14.14 ± 2.2 cm/s at SVR 48, with reversibility of hepatic vein waveform towards the triphasic pattern. Medium to large esophageal varices regressed from 52.5% to 2.5%, and up to 70% of patients showed no EVs at SVR 48. In group A, 24 patients showed complete reversibility of CSPH, and 16 patients showed improvement of CSPH. Child-Pugh score, FIB-4 index, King's score, and Lok index revealed higher significance for detection of the presence of PH. Child-Pugh score, PC/SD ratio, and Lok index revealed higher significance for detection of reversibility of PH. Conclusion: We concluded that CSPH improved after SVR with DAAs and completely regressed in some patients. Upon predicting the presence of PH, Child-Pugh score, FIB-4 index, King's score, and Lok index were the most significant noninvasive scores. While for predicting the reversibility of PH, Child-Pugh score, PC/SD ratio, and Lok index were the most significant scores.

First Molecular Survey to Detect Mycoplasma gallisepticum and Mycoplasma synoviae in Poultry Farms in a Strategic Production District of Sicily (South-Italy).

Mycoplasmas are recognized as avian pathogens, which may cause both respiratory disease and synovial infections in poultry, resulting in severe economic losses. Our study aims to determine the occurrence of Mycoplasma gallisepticum (MG) and Mycoplasma synoviae (MS) among commercial and rural laying hens located in Ragusa province (South Italy), using a duplex real time PCR. Four hundred tracheal swabs were collected from seven commercial (200 swabs) and 25 rural (200 swabs) farms without any clinical disease history. Out of 400 swabs collected, 50 (12.5%) and 93 (23.25%) were positive for MG and MS, respectively. In particular, 9 (18%) and 22 (23.65%) positive swabs for MG and MS, respectively, originated from commercial farms, compared to 41 (82%) and 71 (76.34%) obtained from rural farms. Data obtained show a lower prevalence of MG than MS in the studied farms. Moreover, both pathogens were spread in rural and commercial farms. PCR could be concluded as a rapid and sensitive method for the identification of MG and MS in areas where commercial farms that are declared Mycoplasma-free and rural flocks coexist. These data highlight the importance of surveillance also in rural poultry to monitoring the occurrence of mycoplasmas strains in strategic productive districts.

Diagnostic Findings in a Confirmed Outbreak of Brucella ovis Infection in a Traditional Sheep Farm in Sicily (South-Italy).

Aim of this study is to report a laboratory investigation performed following the isolation of Brucella ovis, causing ovine epididymitis, in a traditional sheep farm in Sicily (South Italy). This disease represents a newly emerging risk for Italian livestock and is listed among diseases of EU priority (EU Reg 2016/429). Blood samples from 56 rams and 143 ewes were analyzed by both Enzyme-Linked Immunosorbent Assay (ELISA) and Complement Fixation Test (CFT). Genital swabs from all rams and 15 lactating ewes were collected to perform real-time PCR. Eighteen serologically positive rams were slaughtered and postmortem-inspected. Samples of testicle, epididymis, lymph nodes, and urine were also collected in order to perform microbiological, molecular, and histopathological analysis. Twelve slaughtered rams showed anatomo-pathological lesions. Real-time PCR for B. ovis BOV_A0504 gene was positive for 13 testicles and epididymis and 11 urine while B. ovis was isolated from epididymis and testicles of 7 slaughtered rams. This is the first exhaustive laboratory report of a microbiological, molecular, and serological pattern of the disease in sheep in Italy. Despite the impact on health and animal welfare, the epidemiology of B. ovis infection is still unknown, particularly in our country where the disease is considered endemic.

Prevalence of non-alcoholic fatty liver disease among patients with non-diabetic chronic kidney disease detected by transient elastography.

PURPOSE: Non-alcoholic fatty liver disease (NAFLD) shares a close relationship with cardiovascular morbidity and mortality. The purpose of this study is to evaluate the frequency of NAFLD in the patients with non-diabetic chronic kidney disease (CKD). METHODS: This cross-sectional study included 80 patients with non-diabetic CKD, of which, 50 patients were on hemodialysis (HD) and 30 patients had CKD stage G3-5 not on dialysis. These patients were randomly selected from Ain Shams University Hospitals, Cairo, Egypt. Patients with diabetes mellitus, obesity, alcohol intake, viral hepatitis, or drug-induced liver steatosis were excluded from this study. Importantly, the controlled attenuation parameter (CAP) (dB/m) of liver steatosis (S0-S3) and liver stiffness/fibrosis measurement (F0-F4) were measured using transient elastography (Fibroscan®). Other evaluations included complete blood count, routine blood chemistry, and C-reactive protein (CRP) titer. RESULTS: In total, 45 (56.25%) (30 males, 15 females) out of total 80 studied patients were reported to have NAFLD. There were 29 patients with end-stage renal disease who were on regular HD and 16 patients with pre-dialysis CKD G3-5. The mean CAP values of hepatic steatosis in the patients with CKD on dialysis and patients with pre-dialysis CKD were 265.41 ± 52.73 and 259 ± 44.8 dB/m, respectively. A significant association between the severity of hepatic steatosis degree with decreased glomerular filtration rate and increased CKD stage was observed in this study. The degree of liver stiffness was significantly related to an increased hepatic steatosis grade. A significant positive correlation was found between the degree of NAFLD and serum levels of alanine aminotransferase, aspartate transaminase, total cholesterol, triglycerides, low-density lipoprotein, and CRP titer (P < 0.05). Importantly, NAFLD was significantly associated with an evident history of cardiovascular disease (CVD) among the studied patients. CONCLUSION: A high frequency of NAFLD (56%) was observed among the patients with non-diabetic CKD on hemodialysis and patients with pre-dialysis CKD. NAFLD may be associated with an increased liver stiffness grade and CVD among those patients.

Faecal calprotectin levels after rifaximin treatment in patients with irritable bowel syndrome with diarrhoea: A single-center prospective study.

BACKGROUND AND STUDY AIMS: Although unclear, the pathophysiology of irritable bowel syndrome (IBS) is considered to be multifactorial. Recent studies have suggested that IBS is a low-grade inflammatory bowel disease (IBD) with high faecal calprotectin (FC) levels. Rifaximin is a potential therapeutic agent for IBS with diarrhoea (IBS-D) due to its ability to decrease FC levels. This study evaluated the role of FC as a follow-up marker of IBS-D after short-course rifaximin treatment. PATIENTS AND METHODS: Ninety-six patients with chronic diarrhoea who fulfilled the Rome IV criteria for IBS-D were enrolled in this study from outpatient clinics. After excluding 18 patients who did not complete the study due to treatment noncompliance or missing follow-up visits, 78 patients (mean age, 39.2 ± 6.9 years) with IBS-D and elevated baseline FC levels were included. An FC level of <50 µg/g was considered normal. Abdominal symptoms were assessed using a Likert scale. All patients received oral rifaximin (550 mg three times daily) for 2 weeks, followed by assessment for abdominal symptoms and FC levels; the treatment was extended to 4 weeks if FC levels remained elevated after 2 weeks of treatment. RESULTS: FC levels normalised in 66 (84.6%) patients, including 60 and 6 patients treated for 2 and 4 weeks, respectively. The remaining 12 (15.4%) patients with persistently elevated FC levels despite 4 weeks of treatment also showed a significant decline in their final FC levels compared with the baseline, accompanied with a significant improvement in abdominal symptoms (p = 0.001). A cutoff baseline FC value of 148.5 µg/g could predict non-responders with 100% sensitivity and 50% specificity. CONCLUSION: Short-course oral rifaximin treatment results in FC normalisation in IBS-D patients with high baseline FC values. Therefore, FC should be considered as a biomarker of follow-up after rifaximin treatment for IBS-D.

Novel Biomarkers of Mastitis in Goat Milk Revealed by MALDI-TOF-MS-Based Peptide Profiling.

Mastitis is the most common infection of dairy goats impairing milk production and quality, which is usually recognized by mammary gland visual inspection and palpation. Subclinical forms of the disease are also widely represented, which lack the typical signs of the clinical ones but are still associated with reduced production and safety for human consumption of milk, generally presenting a high bacterial count. In order to obtain novel analytical tools for rapid and non-invasive diagnosis of mastitis in goats, we analyzed milk samples from healthy, subclinical and clinical mastitic animals with a MALDI-TOF-MS-based peptidomic platform, generating disease group-specific spectral profiles whose signal intensity and mass values were analyzed by statistics. Peculiar spectral signatures of mastitis with respect to the control were identified, while no significant spectral differences were observed between clinical and subclinical milk samples. Discriminant signals were assigned to specific peptides through nanoLC-ESI-Q-Orbitrap-MS/MS experiments. Some of these molecules were predicted to have an antimicrobial activity based on their strong similarity with homolog bioactive compounds from other mammals. Through the definition of a panel of peptide biomarkers, this study provides a very rapid and low-cost method to routinely detect mastitic milk samples even though no evident clinical signs in the mammary gland are observed.