An Improved TESLA Protocol Based on Queuing Theory and Benaloh-Leichter SSS in WSNs

Broadcast authentication is a fundamental security technology in wireless sensor networks (ab. WSNs). As an authentication protocol, the most widely used in WSN, TESLA protocol, its publication of key is based on a fixed time interval, which may lead to unsatisfactory performance under the unstable network traffic environment. Furthermore, the frequent network communication will cause the delay authentication for some broadcast packets while the infrequent one will increase the overhead of key computation. To solve these problems, this paper improves the traditional TESLA by determining the publication of broadcast key based on the network data flow rather than the fixed time interval. Meanwhile, aiming at the finite length of hash chain and the problem of exhaustion, a self-renewal hash chain based on Benaloh-Leichter secret sharing scheme (SRHC-BL SSS) is designed, which can prolong the lifetime of network. Moreover, by introducing the queue theory model, we demonstrate that our scheme has much lower key consumption than TESLA through simulation evaluations. Finally, we analyze and prove the security and efficiency of the proposed self-renewal hash chain, comparing with other typical schemes

Sestrin2 protects against hypoxic nerve injury by regulating mitophagy through SESN2/AMPK pathway

Hypoxia induced by high altitude can lead to severe neurological dysfunction. Mitophagy is known to play a crucial role in hypoxic nerve injury. However, the regulatory mechanism of mitophagy during this injury remains unclear. Recent studies have highlighted the role of Sestrin2 (SESN2), an evolutionarily conserved stress-inducible protein against acute hypoxia. Our study demonstrated that hypoxia treatment increased SESN2 expression and activated mitophagy in PC12 cells. Furthermore, the knock-out of Sesn2 gene led to a significant increase in mitochondrial membrane potential and ATP concentrations, which protected the PC12 cells from hypoxic injury. Although the AMPK/mTOR pathway was significantly altered under hypoxia, it does not seem to participate in mitophagy regulation. Instead, our data suggest that the mitophagy receptor FUNDC1 plays a vital role in hypoxia-induced mitophagy. Moreover, SESN2 may function through synergistic regulation with other pathways, such as SESN2/AMPK, to mediate cellular adaptation to hypoxia, including the regulation of mitophagy in neuron cells. Therefore, SESN2 plays a critical role in regulating neural cell response to hypoxia. These findings offer valuable insights into the underlying molecular mechanisms governing the regulation of mitophagy under hypoxia and further highlight the potential of SESN2 as a promising therapeutic target for hypoxic nerve injury

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07–0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits

A Glimpse of Streptococcal Toxic Shock Syndrome from Comparative Genomics of S. suis 2 Chinese Isolates

BACKGROUND: Streptococcus suis serotype 2 (SS2) is an important zoonotic pathogen, causing more than 200 cases of severe human infection worldwide, with the hallmarks of meningitis, septicemia, arthritis, etc. Very recently, SS2 has been recognized as an etiological agent for streptococcal toxic shock syndrome (STSS), which was originally associated with Streptococcus pyogenes (GAS) in Streptococci. However, the molecular mechanisms underlying STSS are poorly understood. METHODS AND FINDINGS: To elucidate the genetic determinants of STSS caused by SS2, whole genome sequencing of 3 different Chinese SS2 strains was undertaken. Comparative genomics accompanied by several lines of experiments, including experimental animal infection, PCR assay, and expression analysis, were utilized to further dissect a candidate pathogenicity island (PAI). Here we show, for the first time, a novel molecular insight into Chinese isolates of highly invasive SS2, which caused two large-scale human STSS outbreaks in China. A candidate PAI of ∼89 kb in length, which is designated 89K and specific for Chinese SS2 virulent isolates, was investigated at the genomic level. It shares the universal properties of PAIs such as distinct GC content, consistent with its pivotal role in STSS and high virulence. CONCLUSIONS: To our knowledge, this is the first PAI candidate from S. suis worldwide. Our finding thus sheds light on STSS triggered by SS2 at the genomic level, facilitates further understanding of its pathogenesis and points to directions of development on some effective strategies to combat highly pathogenic SS2 infections

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly

An Improved μTESLA Protocol Based on Queuing Theory and Benaloh-Leichter SSS in WSNs

Broadcast authentication is a fundamental security technology in wireless sensor networks (ab. WSNs). As an authentication protocol, the most widely used in WSN, μTESLA protocol, its publication of key is based on a fixed time interval, which may lead to unsatisfactory performance under the unstable network traffic environment. Furthermore, the frequent network communication will cause the delay authentication for some broadcast packets while the infrequent one will increase the overhead of key computation. To solve these problems, this paper improves the traditional μTESLA by determining the publication of broadcast key based on the network data flow rather than the fixed time interval. Meanwhile, aiming at the finite length of hash chain and the problem of exhaustion, a self-renewal hash chain based on Benaloh-Leichter secret sharing scheme (SRHC-BL SSS) is designed, which can prolong the lifetime of network. Moreover, by introducing the queue theory model, we demonstrate that our scheme has much lower key consumption than μTESLA through simulation evaluations. Finally, we analyze and prove the security and efficiency of the proposed self-renewal hash chain, comparing with other typical schemes

An Improved μTESLA Protocol Based on Queuing Theory and Benaloh-Leichter SSS in WSNs

Broadcast authentication is a fundamental security technology in wireless sensor networks (ab. WSNs). As an authentication protocol, the most widely used in WSN, μTESLA protocol, its publication of key is based on a fixed time interval, which may lead to unsatisfactory performance under the unstable network traffic environment. Furthermore, the frequent network communication will cause the delay authentication for some broadcast packets while the infrequent one will increase the overhead of key computation. To solve these problems, this paper improves the traditional μTESLA by determining the publication of broadcast key based on the network data flow rather than the fixed time interval. Meanwhile, aiming at the finite length of hash chain and the problem of exhaustion, a self-renewal hash chain based on Benaloh-Leichter secret sharing scheme (SRHC-BL SSS) is designed, which can prolong the lifetime of network. Moreover, by introducing the queue theory model, we demonstrate that our scheme has much lower key consumption than μTESLA through simulation evaluations. Finally, we analyze and prove the security and efficiency of the proposed self-renewal hash chain, comparing with other typical schemes