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Households’ over-indebtedness has various social and economic consequences. With an increasing number of over-indebted households and rising individual bankruptcies, especially in the post-COVID-19 pandemic era, the efficiency of the solutions available to target this issue is becoming questionable. The purpose of this study is to propose an innovative Shariah-compliant mechanism based on crowd-buying, aiming at alleviating households’ over-indebtedness. The present study adopts a qualitative research design based on an extensive review of the existing literature and a case study of the Real Estate Crowdbuying (REC) model. The study also presents a Shariah assessment of the REC model. The study found that the REC model has five contradictions with the guidelines of Shariah and proposes an enhanced version based on Shariah compliant contracts. As per the authors’ knowledge, this is the first study that provides a Shariah assessment to the REC model and proposes an enhanced Shariah-compliant version. The main limitation of this research is the limited focus on the Shariah compliance of the model. Further studies might explore the regulatory challenges of the application of this model in Malaysia and other Muslim countries. The proposition made by this paper contributes to broadening the range of Shariah-compliant instruments aiming at alleviating households’ over-indebtedness and curbing individual bankruptcy rates.

Abstract Background Lyme disease is one of the most commonly reported infectious diseases in the United States (US), accounting for more than $$90\%$$ 90 % of all vector-borne diseases in North America. Objective In this paper, self-reported tweets on Twitter were analyzed in order to predict potential Lyme disease cases and accurately assess incidence rates in the US. Methods The study was done in three stages: (1) Approximately 1.3 million tweets were collected and pre-processed to extract the most relevant Lyme disease tweets with geolocations. A subset of tweets were semi-automatically labelled as relevant or irrelevant to Lyme disease using a set of precise keywords, and the remaining portion were manually labelled, yielding a curated labelled dataset of 77, 500 tweets. (2) This labelled data set was used to train, validate, and test various combinations of NLP word embedding methods and prominent ML classification models, such as TF-IDF and logistic regression, Word2vec and XGboost, and BERTweet, among others, to identify potential Lyme disease tweets. (3) Lastly, the presence of spatio-temporal patterns in the US over a 10-year period were studied. Results Preliminary results showed that BERTweet outperformed all tested NLP classifiers for identifying Lyme disease tweets, achieving the highest classification accuracy and F1-score of $$90\%$$ 90 % . There was also a consistent pattern indicating that the West and Northeast regions of the US had a higher tweet rate over time. Conclusions We focused on the less-studied problem of using Twitter data as a surveillance tool for Lyme disease in the US. Several crucial findings have emerged from the study. First, there is a fairly strong correlation between classified tweet counts and Lyme disease counts, with both following similar trends. Second, in 2015 and early 2016, the social media network like Twitter was essential in raising popular awareness of Lyme disease. Third, counties with a high incidence rate were not necessarily related with a high tweet rate, and vice versa. Fourth, BERTweet can be used as a reliable NLP classifier for detecting relevant Lyme disease tweets.

Background: Ultrasonography (USG)-guided fine-needle aspiration cytology (FNAC) of the liver is a primary diagnostic procedure for primary and metastatic hepatic lesions. It is a minimally invasive and accurate technique and renders timely diagnosis for further management. Aims and Objectives: The purpose of the study was to evaluate the cytomorphological features of primary and metastatic hepatic lesions. Materials and Methods: This retrospective study was conducted in the Department of Pathology of a tertiary care hospital over a period of 2 years. 50 cases of clinically suspicious cases for hepatic malignancy were radiologically confirmed by USG and were subjected to FNAC under USG guidance with simultaneous cell block preparation in 35 cases. Relevant biochemical and serological data were retrieved from laboratory investigation archives. Results: The study was conducted on 50 cases of hepatic lesion. Majority of cases were male patients. All liver lesions were diagnosed on USG scan. Out of 50 cases diagnosed cytomorphologically, 8 cases (16%) were diagnosed as hepatocellular carcinoma. Among metastatic lesions, more prevalent lesions were adenocarcinoma 20 (40%). The rest of metastatic deposits included poorly differentiated carcinoma 12 (24%), mucinous carcinoma 4 (8%), malignant lymphoma 3 (6%), neuroendocrine tumor 2 (4%), and malignant melanoma 1 (2%). Primary site for metastatic lesions was diagnosed in 22 cases (52.4%) and unknown in 20 cases (47.6%). Conclusion: FNAC is a quick, feasible, and reliable procedure which enables the interpretation of cytological features of malignant hepatic masses.

BackgroundLyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals, and accurate laboratory testing and interpretation for clinical diagnosis validation. A lack of these can lead to delayed diagnosis and treatment, which can exacerbate the severity of Lyme disease symptoms. Therefore, there is a need to improve the monitoring of Lyme disease by using other data sources, such as web-based data. ObjectiveWe analyzed global Twitter data to understand its potential and limitations as a tool for Lyme disease surveillance. We propose a transformer-based classification system to identify potential Lyme disease cases using self-reported tweets. MethodsOur initial sample included 20,000 tweets collected worldwide from a database of over 1.3 million Lyme disease tweets. After preprocessing and geolocating tweets, tweets in a subset of the initial sample were manually labeled as potential Lyme disease cases or non-Lyme disease cases using carefully selected keywords. Emojis were converted to sentiment words, which were then replaced in the tweets. This labeled tweet set was used for the training, validation, and performance testing of DistilBERT (distilled version of BERT [Bidirectional Encoder Representations from Transformers]), ALBERT (A Lite BERT), and BERTweet (BERT for English Tweets) classifiers. ResultsThe empirical results showed that BERTweet was the best classifier among all evaluated models (average F1-score of 89.3%, classification accuracy of 90.0%, and precision of 97.1%). However, for recall, term frequency-inverse document frequency and k-nearest neighbors performed better (93.2% and 82.6%, respectively). On using emojis to enrich the tweet embeddings, BERTweet had an increased recall (8% increase), DistilBERT had an increased F1-score of 93.8% (4% increase) and classification accuracy of 94.1% (4% increase), and ALBERT had an increased F1-score of 93.1% (5% increase) and classification accuracy of 93.9% (5% increase). The general awareness of Lyme disease was high in the United States, the United Kingdom, Australia, and Canada, with self-reported potential cases of Lyme disease from these countries accounting for around 50% (9939/20,000) of the collected English-language tweets, whereas Lyme disease–related tweets were rare in countries from Africa and Asia. The most reported Lyme disease–related symptoms in the data were rash, fatigue, fever, and arthritis, while symptoms, such as lymphadenopathy, palpitations, swollen lymph nodes, neck stiffness, and arrythmia, were uncommon, in accordance with Lyme disease symptom frequency. ConclusionsThe study highlights the robustness of BERTweet and DistilBERT as classifiers for potential cases of Lyme disease from self-reported data. The results demonstrated that emojis are effective for enrichment, thereby improving the accuracy of tweet embeddings and the performance of classifiers. Specifically, emojis reflecting sadness, empathy, and encouragement can reduce false negatives.

The assessment of pesticide residues in agricultural soils is an essential prerogative in maintaining environmental health standards. Intensive vegetable cultivation is practiced in the Al-Kharj area of the eastern Najd region of Saudi Arabia, where excessive applications of agrochemicals are reported to pollute vegetable-growing soils, challenging the sustainable management of soils and groundwater resources. This study aimed to monitor the levels of thirty-two types of pesticide residues in the soils of vegetable fields and the estimated potential health risk for humans due to non-dietary exposure to pesticides in soils in the Al-Kharj region. Pesticide residues were evaluated at 0–10 cm and 10–20 cm depths at 20 sampling sites from Al-Kharj. Gas chromatograph-mass spectrometry, coupled with a quadrupole mass spectrometer with a GC column, was used in the analysis. The results indicated that agrochemical residues show prolonged soil pollution that may cause adverse impacts on human and environment. Herbicides Atrazine, Isoproturpon, and Linuron have been detected in the soils, and these pose many problematic environmental threats. Bromoxynil, Pendimetholin, and Diclofop-methyl could be used as per the recommendations to sustainably manage soil and water resources in the Al-Kharj area. Resmethrin, Methidathion, Ethoprophos, Tetramethrin, Bromophis-methyl, Bifenthion, Permethrin, Fenoxycarb, Cyfluthrin, Phosmet, and Azinophos-methyl can be used safely in the Al-Kharj agricultural area, maintaining sustainable soils and water resources. Applications of Carbaryl require sufficient care, while Endosulfan, Deltamethrin, Lindane, Chlorpyrifos, Chlorpyrifos-methly, Dimethoate, Heptachlor, and Mevinphos, which are detected in soils, require policy guidelines to limit the use to ensure sustainability. Policy interventions need to be formulated to increase the sustainability of soil management and groundwater resources in the Al-Kharj region to ensure the safety of people who are in direct contact with the agrochemicals used and to ensure the safety of agricultural products generated in this region.

The absence of calcium decreases the production of peanuts compared to any other element. To investigate the influence of calcium (Ca) applications on the production and seed quality of four diverse peanut cultivars from different regions—USA (NC-7), Egypt (Giza-6) and Nigeria (Samnut-23 and Samnut-24)—under clay soil conditions, two experiments were carried out at the Agricultural Experimental and Research Station, Cairo University, Egypt, during the two seasons of 2016 and 2017. The experimental design was a randomized complete block in a spilt-plot arrangement with three replications. The main plots were allocated to four peanut cultivars (Giza-6, Samnut-23, Samnut-24 and NC-7), and the sub-plots were devoted to calcium applications (soil application in the form of calcium sulfate dihydrate, foliar application in the form of calcium oxide and the control treatment of distilled water). Results indicated that all four peanut cultivars responded differently to the application of calcium fertilizers. The calcium application significantly enhanced peanut growth, yield components, biological, pod, seed, oil yields, seed oil, free fatty acids and seed calcium percentages in different cultivars. Soil calcium application significantly improved peanut production compared to foliar calcium application. NC-7 cultivar treated with the soil Ca application resulted in the maximum values of biological yield (92.9-ton ha−1), pod yield (6.8-ton ha−1), seed yield (4.4-ton ha−1), oil yield (2247.0 kg ha−1), pod index (203.2 g) and seed index (84.1 g). The interaction between the NC-7 cultivar and soil calcium applications is recommended to attain the best combination, leading to the highest yield and seed quality of peanuts.

Identifying important actors (or nodes) in a two-mode network is a crucial challenge in mining, analyzing, and interpreting real-world networks. While traditional bipartite centrality indices are often used to recognize key nodes that influence the network information flow, inaccurate results are frequently obtained in intricate situations such as massive networks with complex local structures or a lack of complete knowledge about the network topology and certain properties. In this paper, we introduce Bi-face (BF), a new bipartite centrality measurement for identifying important nodes in two-mode networks. Using the powerful mathematical formalism of Formal Concept Analysis, the BF measure exploits the faces of concept intents to detect nodes that have influential bicliques connectivity and are not located in irrelevant bridges. Unlike off-the shelf centrality indices, it quantifies how a node has a cohesive substructure influence on its neighbour nodes via bicliques while not being in network core-peripheral ones through its absence from non-influential bridges. In terms of identifying accurate node centrality, our experiments on a variety of real-world and synthetic networks show that BF outperforms several state-of-the art bipartite centrality measures, producing the most accurate Kendall coefficient. It provides unique node identification based on network topology. The findings also demonstrate that the presence of terminal nodes, influential bridges, and overlapping key bicliques impacts both the performance and behaviour of BF as well as its relationship with other traditional centrality measures. On the datasets tested, the computation of BF is at least twenty-three times faster than betweenness, eleven times faster than percolation, nine times faster than eigenvector, and ten times faster than closeness.

Abstract Background Multimodal perioperative analgesia including acetaminophen is recommended by current guidelines. The comparative efficacy of intravenous vs oral acetaminophen in sinus surgery is unknown. We aimed to determine whether intravenous or oral acetaminophen results in superior postoperative analgesia following sinus surgery. Methods This was a prospective randomized trial with blinded endpoint assessments conducted at a single large academic medical center. Subjects undergoing functional endoscopic sinus surgery were randomized to intravenous vs oral acetaminophen in addition to standard anesthetic and surgical care. The primary outcome was visual analogue scale pain score at 1 hour postoperatively. Results One hundred and ten adult patients were randomized; 9 were excluded from the data analysis. Fifty patients were assigned to intravenous acetaminophen and 51 to oral acetaminophen. Postoperative pain scores at 1 hour (primary endpoint) were not significantly different between the intravenous and oral acetaminophen groups. Similarly, there was no significant difference in pain scores at 24 hours postoperatively. Finally, there was no significant difference in postoperative opioid usage in the postanesthesia care unit or over the first 24 hours postoperatively. Conclusions This is the first comparative efficacy trial of oral vs intravenous acetaminophen in sinus surgery. There was no significant difference in pain scores at 1 or 24 hours postoperatively, and no difference in postoperative opioid use. Intravenous acetaminophen offers no apparent advantage over oral acetaminophen in patients undergoing sinus surgery. Level of Evidence 1b

Discovering influential nodes (or actors) in the network is often the key task of mining, analyzing, and understanding real-life networks. Centrality measures are commonly used to detect important nodes that control the information propagation in the network. While off-the-shelf centrality indices may provide effective node identification in several situations, they frequently produce inadequate results when confronted with massive networks, in the presence of complex local structures or the lack of certain characteristics. In this paper, we introduce Cross-face, a new scalable centrality measurement for the identification of key nodes in such networks. Inspired by the Formal Concept Analysis (FCA) framework, the conceptual idea of “Cross-face” is to leverage the faces of concepts to identify nodes that are located in “face bridges” and have an influential “cross clique” connectivity. Thus, it concurrently measures how the node influences its neighbour nodes through its cross cliques while linking the densely connected substructures of the network via its presence in bridges. Unlike traditional centrality measures, the cross-face of nodes can be computed using only a set of symmetrical concepts, which is often quite small compared to the set of nodes or edges in the network. Our experiments on several real-world networks show the efficiency of Cross-face over existing prominent centrality indices such as betweenness, closeness, eigenvector, and k-shell among others.

Abstract Background Sea cucumber populations in the Egyptian Red Sea have been exploited by uncontrolled fishery with no management takes place. The sea cucumber populations were surveyed at Abu Ghosoun area, Red Sea, during three period intervals in 2000, 2006, and 2016. Results In 2000 and 2006, the total number of recorded species was 13 species, which decreased to only 7 species in 2016. The population density of sea cucumber were greatly affected by overfishing and showed a uniform pattern of very low density in 2006 and 2016 after the high density recorded in 2000. Holothuria atra recorded the highest density that reached 128.1 ind./100 m2 in 2000 and decreased to 120.4 ind./100 m2 in 2006 and 87.4 ind./100 m2 in 2016. The dramatic decrease in densities was observed in other recorded species as in Thelenota ananas which decreased from 48.1 ind./100 m2 in 2000 to only 5.6 ind./100 m2 in 2006 and completely disappeared during 2016. The total abundance of all sea cucumber species recorded during 2000 was 13,880 individuals, which decreased to 7700 individuals in 2006, then to only 2420 individuals in 2016. The remaining individuals in 2016 comprise only 17.4% of the original population recorded in 2000, which means that 82.6% of the sea cucumber populations were lost during the 16 years. The study showed a difference in relative abundance between different species and years. In 2000, the relative abundance ranged between 3.03% for Actinopyga miliaris and 18.44 for Holothuria atra. In 2006, the relative abundance ranged between 2.08% for Stichopus horrens and 31.17% for Holothuria atra. While in 2016, the relative abundance ranged between 0% for several species and 71.9% for Holothuria atra. The total biomass recorded showed high decrease from 10,373.8 kg in 2000 to 5461 kg during 2006 and 1379.6 kg in 2016. Conclusion The study revealed that sea cucumber species diversity and density were much reduced from 2000 to 2016. It also revealed a difference in dispersion among the different years of investigation, indicating the high influence of overfishing on the sea cucumber populations.

Origanum majoranum L. is a Lamiaceae medicinal plant with culinary and ethnomedical applications. Its biological and phytochemical profiles have been extensively researched. Accordingly, this study aimed to investigate the chemical composition and the antibacterial and antioxidant properties of O. majoranum high features, as well as to search for techniques for activity optimization. A metabolomics study of the crude extract of O. majoranum using liquid chromatography-high-resolution electrospray ionization mass spectrometry (LC ± HR ± ESI ± MS) was conducted. Five fractions (petroleum ether, dichloromethane, ethyl acetate, n-butanol, and aqueous) were derived from the total extract of the aerial parts. Different chromatographic methods and NMR analysis were utilized to purify and identify the isolated phenolics (high features). Moreover, the antimicrobial, antibiofilm, and antioxidant activity of phenolics were performed. Results showed that metabolomic profiling of the crude extract of O. majoranum aerial parts revealed the presence of a variety of phytochemicals, predominantly phenolics, resulting in the isolation and identification of seven high-feature compounds comprising two phenolic acids, rosmarinic and caffeic acids, one phenolic diterpene, 7-methoxyepirosmanol, in addition to four flavonoids, quercetin, hesperitin, hesperidin, and luteolin. On the other hand, 7-methoxyepirosmanol (OM1) displayed the most antimicrobial and antioxidant potential. Such a phenolic principal activity improvement seems to be established after loading on gold nanoparticles.

Mentha is an aromatic plant used since antiquity for its pharmaceutical virtues. The climate of Saudi Arabia favors the growth of aromatic plants including Mentha suaveolens L. The aim of this study is to analyze the volatile oils of different parts of fresh and dried Mentha suaveolens L. grown in Saudi Arabia (Aljouf area) using Gas Chromatography/Mass Spectrometry (GC/MS) and Gas Chromatography Flame Ionization Detector (GC/FID) techniques, to recognize the effect of drying on chemical composition, then to evaluate the antioxidant and antifungal activities of different extracts. In total, 118 compounds were identified via GC/MS and GC/FID, in which carvone is the main volatile constituent (stems, leaves, whole plant 45–64%). This investigation deduces that Mentha belonged to the carvone chemotype. Then, the analysis of non-volatile constituents of fresh and dried Mentha was performed by HPLC. The main phenolic compound of fresh and dried Mentha for different parts was rosmarinic acid (ranging from 28,002.5 to 6558 µg/g). The ethanolic extract of fresh stem showed the highest antifungal activity (53% inhibition) compared with miconazole (60% inhibition) but the ethanoic extract of dry stem showed no activity. Additionally, all ethanolic extracts, whether for fresh or dry Mentha, have antioxidant activity more than 90% while the antioxidant activity of whole plant volatile oil is equal to 53.33%. This research shows that M. suaveolens L. could be applied to manufacture natural antioxidants, antifungal, and flavoring agents.

Background. Cardiovascular complications are the most serious threat to diabetic patients. Associated metabolic and microvascular changes are the main cause of cardiac function affection, and the earliest cardiac change is diastolic dysfunction. Assessment of LA function changes is a key to determine early heart damage of diabetic patients. Objectives. To evaluate the effect of diabetes mellitus on left atrial volumes and functions by using real-time 3-dimensional echocardiography in normotensive patients free from cardiovascular disease. Methods. The study included 110 individuals, 50 controls and 60 patients with diabetes mellitus, 30 patients with type 1 diabetes mellitus and 30 patients with type 2 diabetes mellitus. 2-dimensional echocardiography was used to assess the LA maximum volume and LA phasic volumes, and LA maximum volume indexed to body surface area were measured by 3D echocardiography. LA functions (LA total stroke volume, LA active stroke volume, and LA active emptying fraction) were obtained from RT3D volumetric analysis. Results. The results of the analysis revealed that type 2 diabetes mellitus showed enlarged Vmax, Vmin, and LAVi with an increased LA total stroke volume and decreased active emptying fraction, while type 1 diabetics showed only decreased in active emptying fraction. The LA maximum volume indexed to body surface area (LAVi) was significantly higher in type 2 diabetic patients as compared to normal controls which was 23.55±3.37 ml/m2 versus 20.30. Conclusion. Patients with type 2 diabetes mellitus have an increased LA volume with impaired compliance and contractility, while patients with type 1 diabetes mellitus have only impaired contractility compared to nondiabetic subjects.

This study was carried out at the experimental farm of Horticultural Department, Faculty of Agriculture., Al-Azhar University, Nasr City, Cairo, Egypt, during the two successive seasons of 2014/2015 and 2015/2016. The effect of ethephon at different the rate on Euphorbia pulcherrima var. 'Freedom Red' plants was studied to dwarf their height aiming to produce more compact potted plants. The maximum dwarfing was obtained with ethephon at 1000 ppm, which recorded average height of 22.95 and 23.95 cm/plants for November and December periods, respectively. Furthermore, applying plants with the same ethephon level gave the highest the number of branches, followed by 500 ppm ethephon compared to the other concentrations or the untreated plants (control). The maximum leaves the number was obtained with ethephon treatment of 500 ppm. All concentrations of ethephon delayed the first bract color timing, whereas ethephon treatments at 1000 ppm increased the number of days until the first bract coloring more than other treatments of 300 or 500 ppm and the control. The biggest bracts canopy was observed in the control plants, since it recorded 57.61 cm/canopy. On the other hand, the higher level of ethephon (1000 ppm) led to the lowest bracts canopy.

Abiotic stresses in sandy soil, which include saline water, saline soil, and lack of nutrients, affect the productivity and quality traits of peanuts (Arachis hypogaea L). Elemental calcium (Ca2+) is necessary for the proper development of peanut pods. This work aimed at comparing conventional Ca and nano-Ca form effects on peanut production and quality traits. Two randomized complete block field experiments were conducted in the 2015 and 2016 seasons. Treatments were control, gypsum plus calcium nitrate Ca(NO3)2, Ca(NO3)2, and chelated calcium, as well as 100, 75, 50, 25, and 12.5% of Ca(NO3)2 doses in a nano form. The results indicated that the treatment of gypsum plus conventional CaNO3 achieved the highest yield and best quality traits, followed by the Ca(NO3)2 and 100% nano Ca(NO3)2 treatments. The treatments of the control, gypsum, and 12.5% nano Ca(NO3)2 had the lowest effect on peanut performance. The conventional treatment of gypsum plus Ca(NO3)2 resulted in the greatest seed yield (1.6 ton ha−1), oil yield (700.3 kg ha−1), and protein yield (380.1 kg ha−1). Peanuts may benefit from Ca2+ better by using gypsum as the soil application and calcium nitrate as the foliar application to prevent disorders of Ca2+ deficiency under sandy soil conditions.

The commercial Nigerian peanut cultivars Ex-Dakar, Samnut-22 and Samnut-26, the Egyptian cultivar Ismailia-1 and the American cultivar NC-7 were genetically differentiated and the cultivars’ effects on growth and yield components, total lipid contents, including saturated and unsaturated fatty acids, and oil body size and number were investigated. Experiments were carried out at Cairo University Research Station, Giza, Egypt, during the summer seasons of 2016 and 2017. All cultivars had high contents of total unsaturated fatty acids and low contents of saturated fatty acids. Variations among tested cultivars in oil body size and number were documented and cultivars were ranked based on their oil bodies’ size as Ismailia-1 > Samnut-26 > NC-7 > Ex-Dakar ≥ Samnut-22. Oil body size and number were inversely related. This variation can be explained by the different amounts of acidic amino acids and the protein structure on the surface of the oil bodies of these cultivars. The distributions of protein bodies and oil bodies seemed to be negatively correlated. Cultivar effect was significant, and variation was found in seed production and quality in addition to the size and number of oil bodies, oil productivity, and oil quality among cultivars. Seasonal effects were not evident due to the stability of the climatic conditions during the two seasons of the study.

Heart failure is a costly and deadly disease, affecting over 23 million patients worldwide, half of which die within 5 years of diagnosis. The pathophysiological basis of heart failure is the inability of the adult heart to regenerate lost or damaged myocardium. Although limited myocyte turnover does occur in the adult heart, it is insufficient for restoration of contractile function1-6. In contrast to lower vertebrates which can regenerate their myocardium through cardiomyocyte proliferation,7-13, adult mammalian heart cardiomyogenesis very limited1-5. Studies in the late 90s elegantly demonstrated that mammalian cardiomyocytes continue to divide for a few days after birth 14-16, only to undergo permanent cell cycle arrest shortly thereafter. Recently, we demonstrated that resection of up to 15% of the apex of the left ventricle of postnatal day 1 (P1) mice results in complete regeneration within 21 days following injury, without significant fibrosis and cardiac dysfunction17. Moreover, we described a similar regenerative response following ischemic myocardial infarction 18. This response was well characterized by robust cardiomyocyte proliferation, with gradual restoration of normal cardiac morphology and function. In addition to the histological evidence of proliferating myocytes, genetic fate-mapping studies confirmed that the majority of newly formed cardiomyocytes are derived from proliferation of preexisting cardiomyocytes17. Intriguingly, this regenerative capacity is lost by P7, after which injury results in the cardiomyocyte hypertrophy and scar-formation, which coincides with binucleation and cell cycle exit of cardiomyocytes 14, 19. An important approach to understanding the loss of regenerative ability of the mammalian heart is to first consider why, and not only how, this happens. The regenerative ability of the early postnatal heart following resection or ischemic infarction involves regeneration of the lost myocardium and vasculature with restoration of normal myocardial thickness and architecture, and long-term functional recovery. Why would the heart permanently forego such a remarkable regenerative program shortly after birth? The answer may lie in within the fundamental principal of evolutionary tradeoff.

Background: Hyperimmunoglobulin E syndrome (HIES) is a rare primary immunodeficiency disorder characterize by elevated IgE level, eczema, recurrent staphylococcal skin abscesses, and pulmonary infections. Autosomal dominant and autosomal recessive forms of this disorder had been described. Most autosomal dominant HIES (AD-HIES) have been found to be due to mutations in STAT3 (Signal transducer and activator of transcription 3); whereas DOCK8 (dedicator of cytokinesis 8) mutations have been described in patients with autosomal recessive HIES (AR-HIES). Case report: We describe here non-consanguineous health Egyptian family with three affected siblings with hyper IgE syndrome (two females, 9 and 5.5 years, and one male 9-months), but the second girl died after diagnosis because of trauma at age of 1.8 years. The clinical presentations of all siblings are neonatal pustular rash, eczema, recurrent skin abscesses that need surgical drainage, lymphadenitis, recurrent oral and napkins severe fungal infections, recurrent chest infections with formation of pneumatoceles and complications with pneumothorax that required chest tube drainage and retention of primary teeth in the oldest girl. Regarding the laboratory tests high eosinophilia > 15 %, IgE level > 2500 IU/mL, normal other Igs, CD4 lymphopenia and coarse facial features. Their HIES scores were 65, 52 and 51, respectively. Conclusions: Our three patients had the typical features of HIES (neonatal pustular rash, eczema, recurrent skin abscesses, pulmonary manifestations, dental characteristics, skeletal and coarse facial features) although their parents are completely health with normal level of IgE.

The aim of this research is to evaluate arsenic distribution and associated hydrogeochemical parameters in 27 randomly selected boreholes representing aquifers in the Al-Kharj geothermal fields of Saudi Arabia. Arsenic was detected at all sites, with 92.5% of boreholes yielding concentrations above the WHO permissible limit of 10 μg/L. The maximum concentration recorded was 122 μg/L (SD = 29 μg/L skewness = 1.87). The groundwater types were mainly Ca+2-Mg+2-SO4-2-Cl− and Na+-Cl−-SO4-2, accounting for 67% of the total composition. Principal component analysis (PCA) showed that the main source of arsenic release was geothermal in nature and was linked to processes similar to those involved in the release of boron. The PCA yielded five components, which accounted for 44.1%, 17.0%, 10.1%, 08.4%, and 06.5% of the total variance. The first component had positive loadings for arsenic and boron along with other hydrogeochemical parameters, indicating the primary sources of As mobilization are derived from regional geothermal systems and weathering of minerals. The remaining principal components indicated reductive dissolution of iron oxyhydroxides as a possible mechanism. Spatial evaluation of the PCA results indicated that this secondary mechanism of arsenic mobilization may be active and correlates positively with total organic carbon. The aquifers were found to be contaminated to a high degree with organic carbon ranging from 0.57 mg/L to 21.42 mg/L and showed high concentrations of NO3- ranging from 8.05 mg/L to 248.2 mg/L.