On Heterogeneous Neighbor Discovery in Wireless Sensor Networks

Neighbor discovery plays a crucial role in the formation of wireless sensor networks and mobile networks where the power of sensors (or mobile devices) is constrained. Due to the difficulty of clock synchronization, many asynchronous protocols based on wake-up scheduling have been developed over the years in order to enable timely neighbor discovery between neighboring sensors while saving energy. However, existing protocols are not fine-grained enough to support all heterogeneous battery duty cycles, which can lead to a more rapid deterioration of long-term battery health for those without support. Existing research can be broadly divided into two categories according to their neighbor-discovery techniques---the quorum based protocols and the co-primality based protocols.In this paper, we propose two neighbor discovery protocols, called Hedis and Todis, that optimize the duty cycle granularity of quorum and co-primality based protocols respectively, by enabling the finest-grained control of heterogeneous duty cycles. We compare the two optimal protocols via analytical and simulation results, which show that although the optimal co-primality based protocol (Todis) is simpler in its design, the optimal quorum based protocol (Hedis) has a better performance since it has a lower relative error rate and smaller discovery delay, while still allowing the sensor nodes to wake up at a more infrequent rate.Comment: Accepted by IEEE INFOCOM 201

XRCC3 Thr241Met polymorphism and ovarian cancer risk: a meta-analysis

Genetic polymorphism of X-ray repair crosscomplementing group 3 (XRCC3) Thr241Met has been implicated to alter the risk of ovarian cancer, but the results are controversial. In order to get a more precise result, a meta-analysis was performed. All eligible studies were identified through an extensive search in PubMed, Excerpta Medica Database (Embase), Chinese National Knowledge Infrastructure database, and Chinese Biomedical Literature Database before August 2013. The association between the XRCC3 Thr241Met polymorphism and ovarian cancer risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CIs). Finally, a total of four publications including seven studies with 3,635 cases and 5,473 controls were included in our meta-analysis. Overall, there was no association between XRCC3 Thr241Met polymorphism and risk of ovarian cancer under all five genetic models in overall population (T vs. C: OR = 0.99, 95 % CI = 0.960–1.03, P = 0.752; TT vs. CC: OR = 1.00, 95 % CI = 0.91–1.10, P = 0.943; TC vs. TT: OR = 0.97, 95 % CI = 0.92–1.04, P = 0.396, Fig. 1; TT vs. TC/CC: OR = 1.00, 95 % CI = 0.91–1.12, P = 0.874; TT/TC vs. CC: OR = 0.98, 95 % CI = 0.94–1.03, P = 0.486). In the subgroup analysis according to ethnicity, the results suggested that XRCC3 Thr241Met polymorphism was not associated with the risk of ovarian cancer in Caucasians population. No significant association was found between the XRCC3 Thr241 Met polymorphism and the risk of ovarian cancer. Given the limited sample size and ethnicities included in the meta-analysis, further large scaled and well-designed studies are needed to confirm our results

Current evidences on XPC polymorphisms and gastric cancer susceptibility: a meta-analysis

BACKGROUND: Reduced DNA repair capacities due to inherited polymorphisms may increase the susceptibility to cancers including gastric cancer. Previous studies investigating the association between Xeroderma Pigmentosum group C (XPC) gene polymorphisms and gastric cancer risk reported inconsistent results. We performed a meta-analysis to summarize the possible association. METHODS: All studies published up to January 2014 on the association between XPC polymorphisms and gastric cancer risk were identified by searching electronic databases PubMed, EMBASE, Cochrane library, and Chinese Biomedical Literature database (CBM). The association between XPC polymorphisms and gastric cancer risk was assessed by odds ratios (ORs) together with their 95% confidence intervals (CIs). RESULTS: Six studies with 1,355 gastric cancer cases and 2,573 controls were finally included in the meta-analysis. With respect to Lys939Gln polymorphism, we did not observe a significant association when all studies were pooled into the meta-analysis. When stratified by ethnicity, source of control, and study quality, statistical significant association was not detected in all subgroups. With respect to Ala499Val and PAT−/+polymorphisms, we also did not observe any significant association with gastric cancer risk in the pooled analysis. CONCLUSIONS: This meta-analysis based on current evidences suggested that the XPC polymorphisms (Lys939Gln, Val499Arg, and PAT−/+) did not contribute to gastric cancer risk. Considering the limited sample size and ethnicity included in the meta-analysis, further larger scaled and well-designed studies are needed to confirm our results. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/148588031255506

Association of MDR1 G2677T polymorphism and leukemia risk: evidence from a meta-analysis

In the light of the relationship between the MDR1 G2677T polymorphism and the risk of leukemia remains inclusive or controversial. For better understanding of the effect of MDR1 G2677T polymorphism on leukemia risk, we performed a meta-analysis. Eligible studies were identified through a search of electronic databases such as PubMed, Excerpta Medica Database (Embase), Cochrane Library, and Chinese Biomedical Literature Database (CBM). The association between the MDR1 G2677T polymorphism and leukemia risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CI). A total of seven publications including eight studies with 1,229 cases and 1,097 controls were included in the meta-analysis. There was no association between MDR1 G2677T polymorphism and leukemia risk in all of five models in overall populations (T vs. G: OR = 1.00, 95 % CI = 0.88–1.12, P = 0.914; TT vs. GG: OR = 0.97, 95 % CI = 0.75–1.26, P = 0.812; TG vs. GG: OR = 1.00, 95 % CI = 0.92–1.08, P = 0.939; TT vs. TG/GG: OR = 0.98, 95 % CI = 0.67–1.43, P = 0.906; TT/TG vs. GG: OR = 1.00, 95 % CI = 0.95–1.06, P = 0.994). However, the significant association was found in others (Table 2) under the homozygote model (TT vs. GG: OR = 0.68, 95 % CI = 0.48–0.94, P = 0.020) and recessive model (TT vs. TG/GG: OR = 0.63, 95 % CI = 0.43–0.92, P = 0.016). In the subgroup analysis, according to the type of leukemia, significant association was found between MDR1 G2677T polymorphism and myeloid leukemia but not lymphoblastic leukemia (TT vs. GG: OR = 0.66, 95 % CI = 0.46–0.95, P = 0.026; TT vs. TG/GG: OR = 0.56, 95 % CI = 0.38–0.84, P = 0.005). The results suggested that there was no association between MDR1 G2677T polymorphism and leukemia risk in overall populations, but significant association was found in others populations (Asians and Africans), and myeloid leukemia indicated that G2677T polymorphism might be a protective factor in the susceptibility of myeloid leukemia and in Asians and Africans

Epidemiological studies of gut microbiome in metabolic and musculoskeletal outcomes

Due to global aging and the increasing prevalence of sedentary lifestyles, the incidence of metabolic-related chronic diseases—such as obesity, cardiometabolic disorders, osteoporosis, and sarcopenia—is rapidly rising. ,The etiology of these complex conditions remains incompletely understood. Recent studies suggest that genetic factors account for only a small portion of the risk of developing noncommunicable diseases, highlighting the important role of environmental influences. Among these, the gut microbiome—a dynamic and modifiable reflection of environmental exposures—has emerged as a crucial player. Its role in the onset and progression of diseases is increasingly recognized, but the identification of specific gut microbiome biomarkers relevant to disease etiology remains an important area for future research.<br/

Epidemiological studies of gut microbiome in metabolic and musculoskeletal outcomes

Due to global aging and the increasing prevalence of sedentary lifestyles, the incidence of metabolic-related chronic diseases—such as obesity, cardiometabolic disorders, osteoporosis, and sarcopenia—is rapidly rising. ,The etiology of these complex conditions remains incompletely understood. Recent studies suggest that genetic factors account for only a small portion of the risk of developing noncommunicable diseases, highlighting the important role of environmental influences. Among these, the gut microbiome—a dynamic and modifiable reflection of environmental exposures—has emerged as a crucial player. Its role in the onset and progression of diseases is increasingly recognized, but the identification of specific gut microbiome biomarkers relevant to disease etiology remains an important area for future research.<br/