Essential contribution of caspase 3/CPP32 to apoptosis and its associated nuclear changes

Caspases are fundamental components of the mammalian apoptotic machinery, but the precise contribution of individual caspases is controversial. CPP32 (caspase 3) is a prototypical caspase that becomes activated during apoptosis. In this study, we took a comprehensive approach to examining the role of CPP32 in apoptosis using mice, embryonic stem (ES) cells, and mouse embryonic fibroblasts (MEFs) deficient for CPP32. CPP32(ex3-/-) mice have reduced viability and, consistent with an earlier report, display defective neuronal apoptosis and neurological defects. Inactivation of CPP32 dramatically reduces apoptosis in diverse settings, including activation-induced cell death (AICD) of peripheral T cells, as well as chemotherapy-induced apoptosis of oncogenically transformed CPP32(-/-) MEFs. As well, the requirement for CPP32 can be remarkably stimulus-dependent: In ES cells, CPP32 is necessary for efficient apoptosis following UV- but not gamma-irradiation. Conversely, the same stimulus can show a tissue-specific dependence on CPP32: Hence, TNFalpha treatment induces normal levels of apoptosis in CPP32 deficient thymocytes, but defective apoptosis in oncogenically transformed MEFs. Finally, in some settings, CPP32 is required for certain apoptotic events but not others: Select CPP32(ex3-/-) cell types undergoing cell death are incapable of chromatin condensation and DNA degradation, but display other hallmarks of apoptosis. Together, these results indicate that CPP32 is an essential component in apoptotic events that is remarkably system- and stimulus-dependent. Consequently, drugs that inhibit CPP32 may preferentially disrupt specific forms of cell death.     

Load balancing routing with queue overflow prediction for WSNs

The ease of deployment of Wireless Sensor Networks (WSNs) makes them very popular and useful for data collection applications. Nodes often use multihop communication to transmit data to a collector node. The next hop selection in order to reach the final destination is done following a routing policy based on a routing metric. The routing metric value is exchanged via control messages. Control messages transmission frequency can reduce the network bandwidth and affect data transmission. Some approaches like trickle algorithm have been proposed to optimize the network control messages transmission. In this paper, we propose a collaborative load balancing algorithm (CoLBA) with a prediction approach to reduce network overhead. CoLBA is a queuing delay based routing protocol that avoids packet queue overflow and uses a prediction approach to optimize control messages transmission. Simulation results on Cooja simulator show that CoLBA outperforms other existing protocols in terms of delivery ratio and queue overflow while maintaining a similar end-to-end delay.

     

Detection of methicillin-resistant coagulase-negative staphylococci and PVL/mecA genes in cefoxitin-susceptible Staphylococcus aureus (t044/ST80) from unpasteurized milk sold in stores in Djelfa,Algeria

This study was designed to determine antimicrobial resistance phenotypes and genotypes and virulence factors in Staphylococcus aureus and coagulase-negative staphylococci (CNS) in unpasteurized milk sold in Djelfa, Algeria. Eighty-two unpasteurized cow milk samples were randomly obtained from 82 retail stores in Djelfa and tested to detect staphylococci. Species were identified by biochemical tests and MALDI-TOF. Antimicrobial resistance phenotypes and genotypes were determined by disk diffusion test, PCR, and sequencing. The Staph. aureus isolates were subjected to spa typing, multilocus sequence typing, and detection of virulence genes and the scn gene by PCR and sequencing. Forty-five (54.9%) milk samples were contaminated by staphylococci and 45 isolates were recovered: 10 Staph. aureus (12.2% of total samples) and 35 CNS (42.7%). Resistance to penicillin (blaZ), tetracycline (tetL/tetK), and erythromycin (ermB/msrA/ermC) were the most common phenotypes (genotypes). Three CNS were methicillin-resistant and all were mecA-positive. The Staph. aureus isolates were ascribed to the following lineages [spa type/sequence type/associated clonal complex (number of isolates)]: t267/ST479/CC479 (n = 6), t1510/ST5651/CC45 (n = 1), t359/ST97/CC97/ (n = 1), t346/ST15/CC15 (n = 1), and t044/ST80 (n = 1). The mecA gene was detected in the cefoxitin-susceptible t044/ST80 isolate and co-harbored the lukF/lukS-PV and scn genes. The detection of mecA-PVL-positive Staph. aureus, methicillin-resistant CNS, and multidrug-resistant staphylococcal species indicates a potentially serious health issue and reveals that unpasteurized milk sold in Djelfa city could be a potential vehicle for pathogenic and antimicrobial-resistant staphylococci.     

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra‐low‐power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end‐to‐end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node‐to‐node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token‐passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS‐2 simulation process.     

Emergence of methicillin-resistant Staphylococcus aureus (MRSA) ST8 in raw milk and traditional dairy products in the Tizi Ouzou area of Algeria

Staphylococcus aureus is one of the leading causes of food-borne illness worldwide. Raw milk and dairy products are often contaminated with enterotoxigenic strains of this bacterium. Some of these strains carry antimicrobial resistance, leading to a potential risk for consumers. The aim of this study was to characterize S. aureus strains circulating in raw milk and traditional dairy products for carriage of staphylococcal enterotoxin (se) genes and antimicrobial resistance. Overall, 62 out of 270 samples (23%) were contaminated with S. aureus, and 69 S. aureus strains were identified. We studied the enterotoxin genes using 2 multiplex PCR targeting 11 se genes. Seventeen (24.6%) isolates carried one or more genes encoding for staphylococcal enterotoxins. The most commonly detected se genes were seb and sep, followed by seh, sea, and see. Using the disk diffusion method, we found that resistance to penicillin G and tetracycline was the most common. Eleven isolates of methicillin-resistant S. aureus (MRSA) carried the mecA gene. All MRSA isolates belonged to the same spa type (t024) and sequence type (ST8), and carried the seb and sep enterotoxin genes. However, none of them carried the Panton Valentine leukocidin gene (lukF/S-PV). The presence of enterotoxigenic S. aureus strains, including MRSA, in raw milk and dairy products, raises a serious public health concern, because these strains may cause food poisoning outbreaks, be disseminated to the population, or both.     

UHF Propagation Parameters to Support Wireless Sensor Networks for Onboard Trains

This paper reports numerical results for the characterization of the propagation channel in a train. Since the availability of a train to carry out measurements is not always easy, particularly when many changes must be done, a simulation tool provides a useful and reliable mean for the evaluation of the propagation characteristics of this complex and highly fluctuating channel. In order to benefit from previous results, the various existing softwares for complex electromagnetic fields environments simulations were fully searched and one that seems best suited has been retained for these computations. The results presented here are original, preliminaries and our approach provides a basis for study the propagation of waves in a very complex environment consisting of different electromagnetic fields like a train.