Spermatozoa and seminal plasma small extracellular vesicles miRNAs as biomarkers of boar semen cryotolerance.

Freeze boar semen is still the biggest challenge for the swine industry due to the high cold shock sensitivity of boar sperm cells and the variance of post-thaw results among individuals and ejaculates from the same boar. To solve this problem, we investigate if miRNAs present in sperm cells and small extracellular vesicles (EVs) from seminal plasma of raw boar ejaculates can predict high-quality ejaculates after underwent the freeze-thaw process. For this, we obtained miRNAs samples of sperm cells and EVs from raw seminal plasma from 27 ejaculates before the cryopreservation process. Two groups with different freezability considering the analysis post-thaw of structure and sperm functionality were formed: High freezability (HF; n = 04) and low freezability (LF; n = 04). That done, we investigated the miRNAs profile of sperm cells and EVs from seminal plasma in both groups. Three miRNAs were differently abundant in LF ejaculates, being the ssc-miR-503 found in higher levels in sperm cells (P < 0.10). The ssc-miR-130a and ssc-miR-9 most abundant in EVs from seminal plasma (P < 0.10), in LF ejaculates. Through enrichment analysis, it was possible to verify that these miRNAs could be performing modifications in the development of male germ cells and in the production of energy to spermatozoa to maintain their viability and functionality. Therefore, we can demonstrate that ssc-miR-503, ssc-miR-130a, and ssc-miR-9 are related to low sperm cryotolerance in boars semen. So those miRNAs can be used as a biomarker to predict their low ability to tolerate the cryopreservation process.

Climate teleconnections and recent patterns of human and animal disease outbreaks.

BACKGROUND: Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. METHODS AND FINDINGS: We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. CONCLUSIONS/SIGNIFICANCE: Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks.

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program's ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

The changing carbon cycle at Mauna Loa Observatory.

The amplitude of the CO(2) seasonal cycle at the Mauna Loa Observatory (MLO) increased from the early 1970s to the early 1990s but decreased thereafter despite continued warming over northern continents. Because of its location relative to the large-scale atmospheric circulation, the MLO receives mainly Eurasian air masses in the northern hemisphere (NH) winter but relatively more North American air masses in NH summer. Consistent with this seasonal footprint, our findings indicate that the MLO amplitude registers North American net carbon uptake during the warm season and Eurasian net carbon release as well as anomalies in atmospheric circulation during the cold season. From the early 1970s to the early 1990s, our analysis was consistent with that of Keeling et al. [Keeling CD, Chin JFS, Whorf TP (1996) Nature 382:146-149], suggesting that the increase in the MLO CO(2) amplitude is dominated by enhanced photosynthetic drawdown in North America and enhanced respiration in Eurasia. In contrast, the recent decline in the CO(2) amplitude is attributed to reductions in carbon sequestration over North America associated with severe droughts from 1998 to 2003 and changes in atmospheric circulation leading to decreased influence of Eurasian air masses. With the return of rains to the U.S. in 2004, both the normalized difference vegetation index and the MLO amplitude sharply increased, suggesting a return of the North American carbon sink to more normal levels. These findings indicate that atmospheric CO(2) measurements at remote sites can continue to play an important role in documenting changes in land carbon flux, including those related to widespread drought, which may continue to worsen as a result of global warming.

Trigger events: enviroclimatic coupling of Ebola hemorrhagic fever outbreaks.

We use spatially continuous satellite data as a correlate of precipitation within tropical Africa and show that the majority of documented Ebola hemorrhagic fever outbreaks were closely associated with sharply drier conditions at the end of the rainy season. We propose that these trigger events may enhance transmission of Ebola virus from its cryptic reservoir to humans. These findings suggest specific directions to help understand the sylvatic cycle of the virus and may provide early warning tools to detect possible future outbreaks of this enigmatic disease.