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Abstract Background Drug combination treatments have proven to be a realistic technique for treating challenging diseases such as cancer by enhancing efficacy and mitigating side effects. To achieve the therapeutic goals of these combinations, it is essential to employ multi-targeted drug combinations, which maximize effectiveness and synergistic effects. Results This paper proposes ‘MultiComb’, a multi-task deep learning (MTDL) model designed to simultaneously predict the synergy and sensitivity of drug combinations. The model utilizes a graph convolution network to represent the Simplified Molecular-Input Line-Entry (SMILES) of two drugs, generating their respective features. Also, three fully connected subnetworks extract features of the cancer cell line. These drug and cell line features are then concatenated and processed through an attention mechanism, which outputs two optimized feature representations for the target tasks. The cross-stitch model learns the relationship between these tasks. At last, each learned task feature is fed into fully connected subnetworks to predict the synergy and sensitivity scores. The proposed model is validated using the O’Neil benchmark dataset, which includes 38 unique drugs combined to form 17,901 drug combination pairs and tested across 37 unique cancer cells. The model’s performance is tested using some metrics like mean square error ( $$MSE$$ MSE ), mean absolute error ( $$MAE$$ MAE ), coefficient of determination ( $${R}^{2}$$ R 2 ), Spearman, and Pearson scores. The mean synergy scores of the proposed model are 232.37, 9.59, 0.57, 0.76, and 0.73 for the previous metrics, respectively. Also, the values for mean sensitivity scores are 15.59, 2.74, 0.90, 0.95, and 0.95, respectively. Conclusion This paper proposes an MTDL model to predict synergy and sensitivity scores for drug combinations targeting specific cancer cell lines. The MTDL model demonstrates superior performance compared to existing approaches, providing better results.

Abstract This paper proposes a novel multi-view ensemble predictor model that is designed to address the challenge of determining synergistic drug combinations by predicting both the synergy score value values and synergy class label of drug combinations with cancer cell lines. The proposed methodology involves representing drug features through four distinct views: Simplified Molecular-Input Line-Entry System (SMILES) features, molecular graph features, fingerprint features, and drug-target features. On the other hand, cell line features are captured through four views: gene expression features, copy number features, mutation features, and proteomics features. To prevent overfitting of the model, two techniques are employed. First, each view feature of a drug is paired with each corresponding cell line view and input into a multi-task attention deep learning model. This multi-task model is trained to simultaneously predict both the synergy score value and synergy class label. This process results in sixteen input view features being fed into the multi-task model, producing sixteen prediction values. Subsequently, these prediction values are utilized as inputs for an ensemble model, which outputs the final prediction value. The ‘MVME’ model is assessed using the O’Neil dataset, which includes 38 distinct drugs combined across 39 distinct cancer cell lines to output 22,737 drug combination pairs. For the synergy score value, the proposed model scores a mean square error (MSE) of 206.57, a root mean square error (RMSE) of 14.30, and a Pearson score of 0.76. For the synergy class label, the model scores 0.90 for accuracy, 0.96 for precision, 0.57 for kappa, 0.96 for the area under the ROC curve (ROC-AUC), and 0.88 for the area under the precision-recall curve (PR-AUC).

Abstract This research investigates the application of the ordered ranked set sampling (ORSSA) procedure in constant-stress partially accelerated life-testing (CSPALTE). The study adopts the assumption that the lifespan of a specific item under operational stress follows a half-logistic probability distribution. Through Bayesian estimation methods, it concentrates on estimating the parameters, utilizing both asymmetric loss function and symmetric loss function. Estimations are conducted using ORSSAs and simple random samples, incorporating hybrid censoring of type-I. Real-world data sets are utilized to offer practical context and validate the theoretical discoveries, providing concrete insights into the research findings. Furthermore, a rigorous simulation study, supported by precise numerical calculations, is meticulously conducted to gauge the Bayesian estimation performance across the two distinct sampling methodologies. This research ultimately sheds light on the efficacy of Bayesian estimation techniques under varying sampling strategies, contributing to the broader understanding of reliability analysis in CSPALTE scenarios.

Abstract Polyvinyl chloride (PVC) is one of the most important commercial plastics but it is thermally unstable at processing temperatures. Therefore, heat stabilizers are widely used to safeguard by improving resistance of PVC products at high temperature. But most of them are a highly toxic that can cause severe health issues in humans and harmful to the environment. In the present study mixed of calcium/zinc stearate heat stabilizer and green Expandable graphite (EG) is prepared via hydrothermal treatment using additives of nontoxic, environmental protection. The characteristics of the thermal stability of poly vinyl chloride can be investigated by Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) will be used to examine structure of the heat stabilizers, A universal testing equipment will be used to determine the mechanical properties and thermal gravimetric analysis (TGA). From TGA results the weight loss was 43.49% at 342°C for sample with Ca/Zn‐ stearate, while wt loss is 55.87% at 260°C for sample with EG which increase thermal stability. Differential scanning calorimetry affirmed the enhancement of PVC's thermal stability, showing a shift in the glass transition temperature an increase of 67°C. Mechanical tests indicated that samples with EG exhibited higher tensile strength and elongation at break, emphasizing the positive impact on PVC's mechanical properties. The burning test highlighted thermal stability of EG‐containing samples, retaining color and structure even after exposure to 180°C heat. This innovative approach not only enhances thermal stability but also aligns with eco‐friendly principles, making it a promising solution for improving PVC properties. Highlights Ca/Zn‐ stearate, expandable graphite developed by a safe hydrothermal process. Comprehensive analysis indicates improved thermal stability. Safe stabilization of eco‐friendly calcium/zinc, expandable graphite. Effective solution: Eco‐friendly, improved PVC properties. Expandable graphite improved mechanical properties of PVC.

Abstract This paper proposes a multi-task deep learning model for determining drug combination synergistic by simultaneously output synergy scores and synergy class labels. Initially, the two drugs are represented using a Simplified Molecular-Input Line-Entry (SMILE) system. Chemical structural features of the drugs are extracted from the SMILE using the RedKit package. Additionally, an improved Multi-view representation is proposed to extract graph-based drug features. Furthermore, the cancer cell line is represented by gene expression. Then, a three fully connected layers are learned to extract cancer cell line features. To investigate the impact of drug interactions on cell lines, the drug interaction features are extracted from a pretrained drugs interaction network and fed into an attention mechanism along with the cancer cell line features, resulting in the output of affected cancer cell line features. Subsequently, the drug and cell line features are concatenated and fed into an attention mechanism, which produces a two-feature representation for the two predicted tasks. The relationship between the two tasks is learned using the cross-stitch algorithm. Finally, each task feature is inputted into a fully connected subnetwork to predict the synergy score and synergy label. The proposed model ‘MutliSyn’ is evaluated using the O'Neil cancer dataset, comprising 38 unique drugs combined to form 22,737 drug combination pairs, tested on 39 cancer cell lines. For the synergy score, the model achieves a mean square error (MSE) of 219.14, a root mean square error (RMSE) of 14.75, and a Pearson score of 0.76. Regarding the synergy class label, the model achieves an area under the ROC curve (ROC-AUC) of 0.95, an area under the precision-recall curve (PR-AUC) of 0.85, precision of 0.93, kappa of 0.61, and accuracy of 0.90.

Abstract Triple modular redundancy (TMR) is a robust technique utilized in safety-critical applications to enhance fault-tolerance and reliability. This article focuses on estimating the distribution parameters of a TMR system under step-stress partially accelerated life tests, where each component included in the system follows a Lomax distribution. The study aims to analyze the system’s reliability and mean residual lifetime based on the estimated parameters. Various estimation techniques, including maximum likelihood, percentile, least squares, and maximum product of spacings, are explored. Additionally, the optimal stress change time is determined using two criteria. An illustrative example supported by two actual data sets is presented to showcase the methodology’s application. By conducting Monte Carlo simulations, the assessment of the estimation methods’ effectiveness reveals that the maximum likelihood method outperforms the other three methods in terms of both accuracy and performance, as indicated by the numerical outcomes. This research contributes to the understanding and practical implementation of TMR systems in safety-critical industries, potentially saving lives and preventing catastrophic events.

In this article, we introduce and study the truncated inverse power Lindley distribution. The aim is to transpose the remarkable flexibility of the two-parameter inverse power Lindley distribution to the interval [0,1]. The corresponding probability density function has the potential to be unimodal, decreasing, right-skewed, and heavy-tailed. On the other hand, the hazard rate function can be increasing, N-shaped, or U-shaped. These shapes’ versatility enables accurate representation and analysis of proportional or percentage data across a wide range of applications, such as survival analysis, reliability, and uncertainty modeling. Several statistical features, such as the mode, quantiles, Bowley’s skewness, Moor’s kurtosis, MacGillivray’s skewness, moments, inverse moments, incomplete moments, and probability-weighted moments, are computed. In practice, for the estimation of the model parameters from truncated data under the progressively type-II censoring scheme, the maximum likelihood, maximum product spacing, and Bayesian approaches are used. The Tierney–Kadane approximation and Markov chain Monte Carlo techniques are employed to produce the Bayesian estimates under the squared error loss function. We present some simulation results to evaluate these approaches. Four applications based on real-world datasets—one of them is on times of infection, the second is on failure times, and the other two are on the rate of inflation in Asia and Africa—explain the significance of the new truncated model in comparison to some reputed comparable models, such as the inverse power Lindley, Kumaraswamy, truncated power Lomax, beta, truncated Weibull, unit-Weibull, Kumaraswamy Kumaraswamy, and exponentiated Kumaraswamy models.

Background and Aim: Given the rise in stray and imported dogs in Egypt over the past 5 years, it is surprising that no report of Brucella canis infection in dogs or humans has been documented in Egypt's published papers. This study aimed to detect the presence of antibodies against the rough (B. canis) and smooth Brucellae among dogs in Egypt and to characterize the Brucella species circulating in dogs. Materials and Methods: Blood samples (n = 449) were collected from owned and stray dogs in the Greater Cairo region (n = 309) and Damietta governorate (n = 140). The apparent, true, and total seroprevalence of canine brucellosis caused by B. canis infection were calculated using the 2-mercaptoethanol tube agglutination test (2-ME TAT) and rapid slide agglutination test (RSAT). We used the rose Bengal test (RBT) and the buffered acidified plate antigen test (BAPAT) to check the serum samples from dogs for the presence of antibodies against smooth Brucellae. Three polymerase chain reaction (PCR) assays - Bruce-ladder PCR, B. canis species-specific PCR (BcSS-PCR), and Abortus Melitensis Ovis Suis (AMOS)-PCR - were used to determine the Brucella species in the buffy coats of the serologically positive dogs. Results: The overall apparent and true prevalence of B. canis infection in dogs were estimated to be 3.8% and 13.2%. The estimated true prevalence in stray dogs (15%) was higher than in owned dogs (12.5%). The BAPAT and the RBT using smooth antigens revealed that 11 (2.4%) and 9 (2%) were positive. Bruce-ladder PCR targeting eryC, ABC, and Polysaccharide deacetylase genes was able to identify B. canis in nine out of 17 buffy coat samples. AMOS-PCR identified the eight undetermined Brucella species by Bruce-ladder PCR as Brucella abortus (n = 4) and Brucella melitensis (n = 4). To exclude the presence of Brucella suis, a one-step species-specific BcSS-PCR was performed and specifically amplified all B. canis DNA (n = 9) the same as did the Bruce-ladder PCR. Conclusion: To the best of our knowledge, this is the first report of B. canis detection in dogs in Egypt. Molecular identification of B. abortus and B. melitensis in the Egyptian canines highlights the role of stray dogs in brucellosis remerging in Brucellosis-free dairy farms. Brucella canis infection can be diagnosed specifically with the one-step BcSS-PCR. The obtained results set-an-alarm to the veterinary authorities to launch plans to control this disease in dogs.

Abstract The researchers, engineers, and physical experimenters may face difficulty to get a distribution that fits the failure data arising from certain systems. So, in this paper, a new distribution is introduced, named Poisson–logarithmic half-logistic distribution, based on a parallel–series system’s failure times. Specific statistical properties are investigated for the introduced distribution. Also, two real data sets are considered to compare the introduced distribution with some other distributions. The progressive-stress accelerated life test is applied using an increasing exponential function of time to units whose lifetimes are expected to follow the new distribution at normal stress conditions. Different estimation methods, such as maximum likelihood, percentile, least squares, and weighted least square methods, are considered on the basis of adaptive type-II progressive hybrid censoring. To assess the efficiency of the estimation methods, a simulation study is conducted, as well as numerical calculations.

Abstract Background Brucella suis is a zoonotic pathogen with a serious impact on public health and the pig industry worldwide. Information regarding B. suis in pigs in Egypt is scarce. This study aimed to investigate the prevalence of B. suis in slaughtered domestic pigs at El-Basatin abattoir in Cairo, Egypt. A total of 1,116 domestic pigs slaughtered in 2020 were sampled for Brucella isolation and identification. Identified Brucella isolates were molecularly confirmed at species, and biovar levels using Bruce ladder PCR and Suis ladder multiplex PCR. Additionally, high-risk practices of 16 abattoir workers (4 veterinarians, 10 butchering and evisceration workers, and 2 scalding workers) were investigated using a pre-piloted structured questionnaire. Results Brucella isolates were recovered from 1.3% of examined pigs (n = 14) at consistently low rates (1.1—2.9%) across the year of sampling from February to December 2020. All isolates were confirmed as B. suis biovar (bv) 2. Remarkably, 92.9% (13/14) of isolates showed atypical ability to produce H2S and hence were considered as B. suis bv2 atypical phenotype. The prevalence was higher in males (1.8%) than in females (0.9). However, this difference was not significant (Odds ratio = 1.9; CI 95% 0.7 – 5.7; P = 0.2). No detectable pathological lesions were associated with B. suis bv2 infection in examined pigs. All strains were isolated from cervical lymph nodes, highlighting a potential oral transmission. High-risk practices were recorded among swine abattoir workers in this study: 75% do not wear gloves or disinfect their knives daily, and 18.8% were willing to work with open wound injuries. Conclusions To the best of our knowledge, this is the first isolation of B. suis bv2 in Egypt. Detection of H2S producing B. suis bv2 atypical phenotype is alarming as it may result in misinterpretation of these isolates as highly human pathogenic B. suis bv1 in Egypt and possibly elsewhere. Further epidemiological tracing studies are crucial for the detection of the origin of this biovar. Including pigs in the national surveillance program of brucellosis, and an education program for swine abattoir workers about occupational risk of B. suis is a need in Egypt.

Pork production is a niche economy in Egypt, and pigs are typically raised as backyard animals with no sanitary control, potentially exposing them to various pathogens. Commercially available ELISAs were used to detect specific antibodies to the food-borne zoonotic parasites Toxoplasma gondii and Trichinella spp., as well as to Neospora caninum, in serum samples of pigs slaughtered at Egypt’s only licensed pig abattoir, the El-Bassatin abattoir in Cairo. Among the tested sera (n = 332), seroreactivity for T. gondii was 45.8% (95% confidence interval: 40.4–51.3), N. caninum was 28.0% (95% CI: 23.3–33.2), and Trichinella spp. was 1.2% (95% CI: 0.4–3.3). Mixed infection was only detected for T. gondii and N. caninum (18.7%; 95% CI: 14.7–23.4). The seroprevalence of T. gondii was significantly higher (p = 0.0003) in animals collected from southern Cairo (15 May city slum) than in eastern Cairo (Ezbet El Nakhl slum). Seroprevalence for N. caninum was higher in western (Manshiyat Naser slum; p = 0.0003) and southern Cairo (15 May city slum; p = 0.0003) than in that of eastern Cairo (Ezbet El Nakhl slum; p = 0.0003). Moreover, female pigs exhibited a higher rate of N. caninum antibodies than male ones (p < 0.0001). This study provides the first seroprevalence data for N. caninum in pigs in Egypt, and updates the prevalence of the zoonotic parasites Trichinella spp. and T. gondii.

It is of great importance for physicists and engineers to assess a lifetime distribution of a series-parallel system when its components' lifetimes are subject to a finite mixture of distributions. The present article addresses this problem by introducing a new distribution called "Poisson-geometric-Lomax distribution". Important properties of the proposed distribution are discussed. When the stress is an increasing nonlinear function of time, the progressive-stress model is considered and the inverse power-law model has suggested a relationship between the stress and the scale parameter of the proposed distribution. Based on the progressive type-II censoring with binomial removals, estimation of the included parameters is discussed using maximum likelihood and Bayes methods. An example, based on two real data sets, demonstrates the superiority of the proposed distribution over some other known distributions. To compare the performance of the implemented estimation methods, a simulation study is carried out. Finally, some concluding remarks followed by certain features and motivations to the proposed distribution are presented.

The objective of ranked set sampling is to gather observations from a population that is more likely to cover the population’s full range of values. In this paper, the ordered ranked set sample is obtained using the idea of order statistics from independent and nonidentically distributed random variables under progressive-stress accelerated life tests. The lifetime of the item tested under normal conditions is suggested to be subject to the Rayleigh distribution with a scale parameter satisfying the inverse power law such that the applied stress is a nonlinear increasing function of time. Considering the type-II censoring scheme, one-sample prediction for censored lifetimes is discussed. Numerous point predictors including the Bayes point predictor, conditional median predictor, and best unbiased predictor for future order statistics are discussed. Additionally, conditional prediction intervals for future order statistics are also studied. The theoretical findings reported in this work are shown by illustrative examples based on simulated data as well as real data sets. The effectiveness of the prediction methods is then evaluated by a Monte Carlo simulation study.

In this article, a new modified asymmetric Topp–Leone distribution is created and developed from a theoretical and inferential point of view. It has the feature of extending the remarkable flexibility of a special one-shape-parameter lifetime distribution, known as the inverse Topp–Leone distribution, to the bounded interval [0, 1]. The probability density function of the proposed truncated distribution has the potential to be unimodal and right-skewed, with different levels of asymmetry. On the other hand, its hazard rate function can be increasingly shaped. Some important statistical properties are examined, including several different measures. In practice, the estimation of the model parameters under progressive type-II censoring is considered. To achieve this aim, the maximum likelihood, maximum product of spacings, and Bayesian approaches are used. The Markov chain Monte Carlo approach is employed to produce the Bayesian estimates under the squared error and linear exponential loss functions. Some simulation studies to evaluate these approaches are discussed. Two applications based on real-world datasets—one on the times of infection, and the second dataset is on trading economics credit rating—are considered. Thanks to its flexible asymmetric features, the new model is preferable to some known comparable models.

Background and Aim: Different polymerase chain reaction (PCR) techniques have and are still being used for the direct detection of Brucella DNA in serum samples of different animal species and humans without being validated or properly validated, resulting in discrepancies. Thus, this study aimed to evaluate the diagnostic performance of the TaqMan Real- Time-PCR (RT-PCR) targeting the bcsp31 gene versus conventional PCR for the accurate diagnosis of brucellosis at the genus level in cattle sera. Materials and Methods: One hundred and eighty-four serum samples were collected from bacteriologically positive and negative cows with ages ranging from 1 to 5 years old at some infected private farms in the Nile Delta under quarantine measures as well as brucellosis free farms. These samples were classified into four groups after serological diagnosis and investigated by TaqMan RT-PCR and conventional PCR targeting the IS711 gene for Brucella DNA detection. The diagnostic performance characteristics of both PCR techniques were estimated considering the bacteriological results as a gold standard. Results: TaqMan RT-PCR revealed superiority over conventional PCR; it was able to detect Brucella DNA in 95% (67/70) and 89% (25/28) of the cattle sera samples belonging to Group 1 (serologically and bacteriologically positive) and Group 2 (serologically negative but bacteriologically positive), respectively. On evaluating the diagnostic performance, TaqMan RT-PCR showed superior diagnostic sensitivity (93.9%), diagnostic specificity (88.4%), performance index (182.3), almost perfect kappa agreement (0.825±0.042), strong positive correlation (r=0.826), high accuracy based on the receiver operating characteristic (ROC) curve, and area under the ROC curve (0.911) at p

Abstract In this study, Multiple Locus Variable Number Tandem Repeat Analysis (MLVA‐16) was performed on 18 Brucella isolates identified bacteriologically and molecularly (AMOS‐PCR) as Brucella abortus (n = 6) and Brucella melitensis (n = 12). This was aimed to study the genetic association among some Egyptian Brucella genotypes isolated during the period from 2002 to 2013 along with the global genotypes database. MLVA‐16 analysis for B. melitensis and B. abortus strains illustrates a total of 11, and 3 genotypes with 10 and 1 singleton genotypes, respectively. B. melitensis strains displayed greater markers diversity by VNTRs analysis of the 16 loci than B. abortus and this was attributed mainly to the diverging in panel 2B markers. B. melitensis genotype M4_Fayoum_Giza (3,5,3,13,1,1,3,3,8,21,8,7,5,9,5,3) was the only predominated genotype circulating between two different governorates. The most common B. abortus genotype, GT A3_Dakahlia (4,5,4,12,2,2,3,3,6,21,8,4,4,3,4,4), was present in three identical isolates. In phylogeny, Egyptian B. abortus bv1 genotypes were closely related to East Asian strain (for the first time), Western Mediterranean and Americas clonal lineages. B. melitensis local genotypes exhibit a genetic relatedness mostly to Western Mediterranean clonal lineage and one strain of Eastern Mediterranean clonal lineage. In conclusion, the geographic location is not the only factor stands behind the high genetic similarity of the Egyptian Brucella genotypes. These low variations may be a result of a stepwise mutational event of the most variable loci from a very limited number of ancestors especially during the transmission through non‐preference hosts. The authors encourage the authorities in charge to establish pre‐movement testing to reduce the risk of brucellosis spread.

Proline is water soluble amino acid extensively used in drug delivery systems. Compounds of cobalt (Co) transition metal have potent antimicrobial and anticancer activities. However, a drug delivery system combining proline cobalt is not reported yet. For the first time, new hybrid semi-organic single crystals of proline cobalt chloride (PCC) are prepared. The novelty of the article is also that single crystal proline cobalt chloride showed potent antimicrobial and antitumor activity. Doping of PCC by Ag0NPs significantly increased these biological activities. The anisotropic magnetic properties of single crystals can mitigate the cytotoxicity of Ag0NPs on normal cells. Silver nanoparticles (Ag0NPs) improved the crystal habits and physicochemical properties. Ag0NPs showed the best performance, paramagnetic materials n-type semiconductors due to delocalized excess electrons of Ag0NPs incorporated in the crystal lattice interstitially. Crystals have high absorptivity for UV-radiation electromagnetic radiation. Ag0NPs enhanced AC electrical conductivity up to 2.3 × 104 Ω cm−1 due to high electron density. Proline doped crystals are obtained in good purity as triclinic unit cell with having anisotropic magnetism. PCCAg0NPs crystal exhibited: high antimicrobial activities to various bacterial and fungal species, inhibition zone (mm): 21, 25, 24, 26, 30, 28, 12, and 46 for S. aureus, E. faecalis, S. typhi, E. coli, P. aerugino, K. pneumoniae, A. braselienses, and C. albicans, respectively, in comparison to ciprofloxacin antibiotic (23, 0, 26, 26, 25, 0, 0, 0) for the same tested species, respectively; higher cytotoxicity against breast cancer cells (IC50 22.1 μM) than the reference drug cisplatin (IC50 11.7 μM); and lower cytotoxicity to normal healthy lung cells MRC-5, (IC50 145.5 μM) than cisplatin (IC50 30.2 μM). Hence, this crystal is a candidate for chemotherapy of breast cancer.

Brucellosis is a highly contagious and incapacitating disease of humans, livestock and wildlife species globally. Treatment of brucellosis in animals is not recommended, and in humans, combinations of antibiotics recommended by the World Health Organization are used. However, sporadic antimicrobial-resistant (AMR) isolates and relapse cases have been reported from different endemic regions. In the current study, molecular characterization and antibiotic susceptibility testing using the microdilution method for 35 B. abortus and B. melitensis strains isolated from humans, milk and animal were carried out. Additionally, Next-Generation-Sequencing (NGS) technology was applied to confirm Brucella at the species level and investigate AMR and pathogenicity-associated determinants. MALDI-TOF seemed to be a rapid and reliable tool for routine identification of brucellae to the genus level; however, DNA-based identification is indispensable for accurate species identification. Brucella abortus strains were isolated from two human cases and a sheep. Such infections are uncommon in Egypt. Egyptian Brucella strains are still in-vitro susceptible to doxycycline, tetracyclines, gentamicin, ciprofloxacin, levofloxacin, chloramphenicol, streptomycin, trimethoprim/sulfamethoxazole and tigecycline. Probable (no CLSI/EUCAST breakpoints have been defined yet) in-vitro resistance to rifampicin and azithromycin was observed. WGS failed to determine classical AMR genes, and no difference in the distribution of virulence-associated genes in all isolates was found. Isolates of human and non-human origins were still susceptible to the majority of antibiotics used for treatment in humans. The absence of classical AMR genes in genomes of “resistant” Brucella strains may reflect a lack of information in databases, or resistance might not be encoded by single resistance genes. The One Health approach is necessary for tackling brucellosis. Continuous susceptibility testing, updating of breakpoints, assessing mutations that lead to resistance are needed.

Brucellosis is a zoonosis that has a devastating impact on the economy and public health, particularly in the Middle East, including Egypt. This study aimed to define risk factors associated with brucellosis in humans and in their cattle in Fayoum governorate - Upper Egypt. Also, molecular genotyping of recovered Brucella isolates from human cases and their cattle to assess the potential cross-species transmission in the study region. Data were obtained via double matched case–control studies for brucellosis in humans (106 cases and 160 controls) and in their cattle (78 cattle cases and 105 cattle controls). The results of multivariate regression analysis revealed that predictors of human brucellosis were animal-related occupations (OR 2.1, P 0.02), previous infection in other household members (OR 3.2, P 0.007), eating home-made soft cheese (OR 2.3, P 0.03), and exposure to cattle abortions (OR 6.9, P

The progressive-stress accelerated life test is discussed under the ordered ranked set sampling procedure. It is assumed that the lifetime of an item under use stress is exponentially distributed and the law of inverse power is considered as the relationship between the scale parameter and the applied stress. The involved parameters are estimated using the Bayesian technique, under symmetric and asymmetric loss functions, based on ordered ranked set samples and simple random samples subject to type-II censoring. Real and simulated data sets are used to illustrate the theoretical results presented in this paper. Finally, a simulation study followed by numerical calculations is performed to evaluate the Bayesian estimation performance based on the two sampling types.

Point and interval predictions of the s-th order statistic in a future sample are discussed. The informative sample is assumed to be drawn from a general class of distributions which includes, among others, Weibull, compound Weibull, Pareto, Gompertz and half-logistic distributions. The informative and future samples are progressively type-II censored, under competing risks model, and assumed to be obtained from the same population. A special attention is paid to the half-logistic distribution. Using six different progressive censoring schemes, numerical computations are carried out to illustrate the performance of the procedure. An illustrative example based on real data is also considered. The biases, mean squared prediction errors of the maximum likelihood predictors, coverage probabilities and average interval lengths of the Bayesian prediction intervals are computed via a simulation study.

Brucellosis, caused by the bacteria of the genus Brucella, is one of the most neglected common zoonotic diseases globally with a public health significance and a high economic loss among the livestock industry worldwide. Since little is known about the distribution of B. abortus in Egypt, a total of 46 B. abortus isolates recovered between 2012–2020, plus one animal isolate from 2006, were analyzed by examining the whole core genome single nucleotide polymorphism (cgSNP) in comparison to the in silico multilocus variable number of tandem repeat analysis (MLVA). Both cgSNP analysis and MLVA revealed three clusters and one isolate only was distantly related to the others. One cluster identified a rather widely distributed outbreak strain which is repeatedly occurring for at least 16 years with marginal deviations in cgSNP analysis. The other cluster of isolates represents a rather newly introduced outbreak strain. A separate cluster comprised RB51 vaccine related strains, isolated from aborted material. The comparison with MLVA data sets from public databases reveals one near relative from Argentina to the oldest outbreak strain and a related strain from Spain to a newly introduced outbreak strain in Egypt. The distantly related isolate matches with a strain from Portugal in the MLVA profile. Based on cgSNP analysis the oldest outbreak strain clusters with strains from the UK. Compared to the in silico analysis of MLVA, cgSNP analysis using WGS data provides a much higher resolution of genotypes and, when correlated to the associated epidemiological metadata, cgSNP analysis allows the differentiation of outbreaks by defining different outbreak strains. In this respect, MLVA data are error-prone and can lead to incorrect interpretations of outbreak events.

In this article, the tampered failure rate model is used in partially accelerated life testing. A non-decreasing time function, often called a ‘‘time transformation function", is proposed to tamper the failure rate under design conditions. Different types of the proposed function, which have sufficient conditions in order to be accelerating functions, are investigated. A baseline failure rate of the exponential distribution is considered. Some point estimation methods, as well as approximate confidence intervals, for the parameters involved are discussed based on generalized progressively hybrid censored data. The determination of the optimal stress change time is discussed under two different criteria of optimality. A real dataset is employed to explain the theoretical outcomes discussed in this article. Finally, a Monte Carlo simulation study is carried out to examine the performance of the estimation methods and the optimality criteria.

An expression for the stress-strength reliability R=P(X1

Motivated by the fact that the so-called Weibull generated exponentiated exponential distribution (WGEED) accommodates for non-monotone as well as monotone hazard rate functions (HRFs), we give some properties of this WGEED and explore its use in life testing by obtaining Bayes prediction intervals of future observables. The survival function (SF) of the WGEED is constructed by composing a Weibull cumulative distribution function (CDF) with –ln [exponentiated exponential] CDF. Some properties of the WGEED are given and prediction intervals of future observables, using the one- and two-sample schemes, are obtained. A comparison between the WGEE and the Weibull distributions, based on Kolmogorov-Smirnov goodness of fit test, shows that the former fits better than the latter. Real life data shows the possibility of using the WGEED in analyzing lifetime data. Numerical examples of one- and two- sample Bayes interval prediction are given to illustrate the procedure and a simulation study is made to compute the coverage probabilities and the average lengths of intervals.