Seasonal Weather Changes Research Articles

Basic Aspects of Seasonal Cardiovascular Mortality

The review demonstrates the main aspects of seasonal cardiovascular mortality. Climatic factors, including seasonal weather changes, have a significant impact on the biosphere. People are also characterized by the seasonal dynamics of the activity of many organs and systems, biochemical parameters, and mortality. Cardiovascular mortality is also characterized by seasonal fluctuations: in winter it is maximum, in summer it is minimal. The same patterns are characteristic of mortality from cardiovascular diseases (myocardial infarction, stroke, cardiac arrhythmias, etc.). The article presents the basic patterns of seasonal cardiovascular mortality in various climatic zones, the cardiovascular mortality of countries located in the equatorial and subequatorial climatic region. In addition, the mortality displacement phenomenon, the paradox of winter mortality. The main trends in changes in cardiovascular mortality over a long period of time are demonstrated. The paper discusses some of the mechanisms that underlie the dynamics of cardiovascular mortality during the year: seasonal fluctuations in the level of vitamin D, lipids in the blood plasma, changes in hemodynamic parameters, the effects of microbial and viral infections in the cold season, etc. In addition, data on seasonal the dynamics of risk factors for cardiovascular diseases is considered: an increase in body weight, a physical activity decrease, a change in the nutrition structure in the winter, the seasonal dynamics of depression, anxiety, hostility, the relationship of seasonal cardiovascular mortality with socio-economic, demographic and other factors. In conclusion, the main ways of development and prevention of seasonal CV cardiovascular mortality M, taking into account modern technologies at the international level, for state health departments, for specific patients, are demonstrated.

Diversity, Co-Occurrence, and Nestedness Patterns of Sand Fly Species (Diptera: Psychodidae) in Two Rural Areas of Western Panamá.

Simple SummarySand flies are insects that can transmit the parasites causing leishmaniasis, a major neglected tropical disease. In the Americas, these insects are highly diverse, and unlike what is observed for other vector-borne diseases, many species co-occur in sites where this disease affects human populations. Here, we present results from a two-year-long study where we study how the number of species changes in two rural areas of Western Panamá with different land use cover and through the dry and wet seasons. We found that species number increased during the wet season and in plots with higher natural forest cover and that species number decreased in both areas in plots when the forest cover decreased, with some species changing through the seasons, and some species disappearing when comparing the sand fly faunas of the most forested with less forested plots. However, our results suggest that seasonality, or the change from a dry to rainy season, can be a more important driver of the number of species locally observed in the studied areas.Cutaneous Leishmaniasis transmission in the New World is observed in areas with rich sand fly species’ faunas. The diversity and composition of sand fly species can change in response to seasonal weather and land use changes. Here, we present results from a two-year-long study where we collected, using Centers for Disease Control (CDC) light traps, sand flies from two rural areas, Las Pavas (LP) and Trinidad de las Minas (T) in western Panamá. Over 710 trap-nights, we collected 16,156 sand flies from 15 genera and 35 species. We identified 34 species in T, and the most abundant species collected was Nyssomyia trapidoi (Fairchild and Hertig, 1952) (n = 2278, 37%), followed by Psychodopygus panamensis (Shannon, 1926) (n = 1112, 18%), and Trichopygomyia triramula (Fairchild and Hertig, 1952) (n = 1063, 17%). In LP, we identified 26 species, and the most abundant species collected were Ty. triramula (n = 4729, 48%), and Ps. panamensis (n = 3444, 35%). We estimated a higher species’ richness in T (Chao2 ± S.E.: 36.58 ± 3.84) than in LP (27.49 ± 2.28). In T, species’ richness was significantly higher in the rainy season, but no seasonal differences were observed in LP. Species’ assemblages were nested in the two areas. Phlebotomine sand fly species’ abundance increased at the two sites during the rainy season. Our data suggest that seasonality is more important than land use as a factor driving sand fly species’ diversity at the studied sites.

Variability of the food potential of the Kerch strait and the black sea pre-strait zone as a prospective area for the development of mollusks Mariculture

Based on the data of integrated observations, the variability of phytoplankton, the amount of suspended organic matter and zooplankton of the pelagic zone of the Kerch Strait and the pre-strait zone of the Black Sea is considered. The algal flora of the entire Black Sea, the Kerch Strait and the pre-strait is characterized by the predominance of diatoms over pyridineas (pyrrophytes or dinoflagellates). The study of the species range, number and biomass of the phytoplankton community during several periods of the year showed that its dynamics is largely dependent on seasonal weather changes (climate). In the process of phytoplankton development, several phases of autogenic succession were revealed. It is expressed in a sequential change in phytoplankton forms, changes in its abundance and biomass typical of the eastern shelf of the Black Sea. The zooplankton community of the Kerch Strait is represented by micro-, meso- and macro- zooplankton typical of the Black Sea. Microzooplankton is represented by zooflagellates and protozoa, as well as by early larval stages of planktonic crustaceans, apendicularia and mollusks. Its total biomass averages about 80 mg/m3.The above analysis of the collected material allows us to conclude that the distribution of suspended matter and larvae is related primarily to the peculiarities of water circulation in the strait. In the case of low concentrations of larvae, the dynamic factor can be decisive in the process of sedimentation intensity. The amounts of suspended matter can reach 20 mg/m3, which is 2-3 times higher than on average for the Black Sea. It further demonstrates the high productivity of waters and the prospects of the latter to be the area for commercial growing of mussels.

Targeting Vulnerability to Seasonal and Acute Weather Changes to Keep Australians With Cardiovascular Disease Out of Hospital - The RESILIENCE Trial

Australia is experiencing ever more frequent weather/environmental challenges, including extreme heatwaves and bushfires. There are no proven interventions to reduce seasonal challenges to the cardiovascular health of vulnerable individuals. The REsilience to Seasonal ILlness and Increased Emergency admissioNs CarE (RESILIENCE) Trial will test the hypothesis that an individually-tailored intervention program will reduce re-hospitalisation risk and mortality in vulnerable individuals.

Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network

This paper proposes a new class of extreme value distribution called compound generalized extreme value (CGEV) distribution for investigating the effects of monthly and seasonal variation on extreme travel delays in road networks. Since the frequency and severity of extreme events are highly correlated to the variation in weather conditions as an extrinsic cause of incidents and long delays, monthly and seasonal changes in weather contributes to extreme travel time variability. The change in driving behavior, which itself varies according to road/weather conditions, also contributes to the monthly and seasonal variation in observed extreme travel times. Therefore, it is critical to model the effect of monthly and seasonal changes on observed extreme travel delays on road networks. Based on the empirically revealed linear relationship between mean and standard deviation (SD) of extreme travel delays for both monthly and seasonal levels, two multiplicative error models are formulated. The CGEV distribution is then obtained by linking the two multiplicative error models and forming a compound distribution that characterizes the overall variation in extreme travel delay. The CGEV distribution parameters are calibrated and the underlying assumptions that are used to derive the CGEV distribution are validated using multi-year observed travel time data from the City of Calgary road network. The results indicate that accounting for the seasonality by identifying seasonal specific parameters provides a flexible and not too complex CGEV distribution that is shown to outperform the traditional GEV distribution. Finally, the application of the proposed CGEV distribution is evaluated in the context of road network vulnerability taking into account the observed probability of extreme event occurrences and the link importance. This derived data-driven vulnerability index incorporates a wealth of information related to both network topography in terms of connectivity and the dynamic interaction between travel demand and supply. This new data-driven vulnerability measure can thus be used as a decision support tool to inform decision-makers in prioritizing improvements to critical links to enhance overall network vulnerability, reliability, and resilience.

Threshold and stability results in a periodic model for malaria transmission with partial immunity in humans

We develop a periodic compartmental population model for the spread of malaria, dividing the human population into two classes: non-immune and semi-immune. The effect of seasonal changes in weather on the malaria transmission is considered by applying a non-autonomous model where mosquito birth, death and biting rates are time-dependent. We show that the global dynamics of the system is determined by the basic reproduction number, which we define as the spectral radius of a linear integral operator. For values of the basic reproduction number less than unity, the disease-free periodic solution is globally asymptotically stable, while if R0>1, then the disease remains endemic in the population. We show simulations in accordance with the analytic results. Finally, we show that the time-average reproduction rate gives an underestimation for malaria transmission risk.

Effect of Forest Management Types on Soil Carbon Stocks in Montane Forests: A Case Study of Eastern Mau Forest in Kenya

Mau Forest, a major forest reserve in Kenya, has experienced anthropogenic disturbances through encroachment and forest fires. This study aimed at comparing the soil carbon stocks in different forest management types as well as how seasonal climatic changes influence its dynamics. The study was undertaken in the Eastern Mau block (Sururu) which forms part of the greater Mau Forest Complex. The forest management interventions have been in place for over 15 years with disturbed (fire) natural forest experiencing fires in 2005, 2007, and 2014 while cypress plantations were established in 1994. A nested experimental design was used in data collection, where thirty-two sample plots were nested into four blocks each measuring 100 m2 delineated by forest management types (disturbed by fire, natural forest, undisturbed natural forest, plantation, and glades). In each plot, data on soil carbon stocks, soil bulk density, soil moisture, and temperature were collected for both dry and wet seasons. Data collection was carried out between November 2015 and December 2016. The results indicated that there were no significant differences in the carbon stocks among the forest management types (F4,16 = 0.61, P = 0.613 ). However, seasonal weather changes significantly affected the amount of carbon stocks among the forest management types (F4,16 = 0.61, P > 0.05 ). The undisturbed natural forest had the highest mean soil carbon stocks, while the plantation forest had the lowest as follows: undisturbed natural forest (135.17 ± 35.99.0 Mg·C−ha), disturbed natural forest by fire (134.52 ± 38.11 Mg·C−ha), glades (122.4 ± 64.9 Mg·C−ha), and plantation forest (116.51 ± 39.77 Mg·C−ha). Furthermore, the undisturbed natural forest management had the highest bulk density (0.66 g/cm3), while the disturbed (fire) natural forest had the lowest (0.59 g/cm3). These values were low compared to most normal mineral soils which have a bulk density of between 1.0 g/cm3 and 1.5 g/cm3. There was a significant ( P > 0.01 ) relationship between seasonal weather (temperature) changes and soil carbon stocks under different forest management types with the relationship being stronger in soils under glades (r2 = 0.62) and weak in the undisturbed natural forest (r2 = 0.26). In conclusion, forest disturbances have an impact on soil carbon stocks, and for effective management of forest towards climate stabilization, then disturbance should be minimized if not avoided.

Waiting for accelerations. Speculating on guar seeds in the Indian desert

ABSTRACT This article unfolds how an extreme acceleration in the price of a seed in 2012 changed farming in a rural area of India by reorienting the imagined sources of wealth in farming. The seed in question is guar which have been grown for centuries for cow fodder, but which is also used in fracking, and because of a growing international demand combined with a limited supply and wild speculation, the prices in 2012 grew exponentially with 1500% in a period of 3 months, after which it crashed at a similar rate. The article argues that this acceleration of prices caused an escalation that changed the perspective of change for farmers. it shifted the main focus from farming as a repetitive event tied to the seasonal weather changes, to one of future potentiality tied to sudden market movements. This shift in the scale of measuring change in farming moved farmers from producing seeds to also speculating in seeds, through methods of trading and stocking. The guar price acceleration opened up to imaginaries of new avenues of future income from farming that was not flowing in with the rain, but with the market.

Tunable infrared transmission for energy-efficient pneumatic building façades

Thermal regulation of buildings in climates with daily and seasonal weather changes can prove challenging and result in high building energy consumption. While adaptable façades with tunable infrared transmitting properties could modulate solar transmittance through the building envelope and, as such, increase energy efficiency, available technologies to meet these needs are often expensive, relatively complicated, and challenging to implement in a lightweight form factor.Motivated by these limitations, this report presents a novel tunable light-modulating technology for energy-efficient pneumatic façades in the form of polydimethylsiloxane (PDMS) film with a thin gold surface coating. Sequential stretching and relaxing of this film results in strain-induced microscale surface cracks that can significantly modulate both visible and near infrared light transmission, and consequently, the material’s solar heat gain coefficient (SHGC).The material’s tunability has shown a significant potential to reduce building energy use, as assessed with building simulation software. The technology offers additional advantages for light modulation in pneumatic façades including real-time operation, ease of implementation and control, and predictable performance. Façade design guidelines for the integration of the infrared-regulating film into ethylene tetrafluoroethylene (ETFE) building envelopes and climate suitability are described, and a critical evaluation of material durability, optical clarity, and material costs are provided.

Climatic Changes, Water Systems, and Adaptation Challenges in Shawi Communities in the Peruvian Amazon

Climate change impacts on water systems have consequences for Indigenous communities. We documented climatic changes on water systems observed by Indigenous Shawi and resultant impacts on health and livelihoods, and explored adaptation options and challenges in partnership with two Indigenous Shawi communities in the Peruvian Amazon. Qualitative data were collected via PhotoVoice, interviews, focus group discussions, and transect walks, and analyzed using a constant comparative method and thematic analysis. Quantitative data were collected via a household survey and analyzed descriptively. Households observed seasonal weather changes over time (n = 50; 78%), which had already impacted their family and community (n = 43; 86%), such as more intense rainfall resulting in flooding (n = 29; 58%). Interviewees also described deforestation impacts on the nearby river, which were exacerbated by climate-related changes, including increased water temperatures (warmer weather, exacerbated by fewer trees for shading) and increased erosion and turbidity (increased rainfall, exacerbated by riverbank instability due to deforestation). No households reported community-level response plans for extreme weather events, and most did not expect government assistance when such events occurred. This study documents how Indigenous peoples are experiencing climatic impacts on water systems, and highlights how non-climatic drivers, such as deforestation, exacerbate climate change impacts on water systems and community livelihoods in the Peruvian Amazon.

The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings

Several studies have indicated that Model Predictive Control (MPC) of space heating systems can utilize the thermal mass of residential buildings as short-term thermal storage for various demand response purposes. Realization of this potential relies heavily on the accuracy of the model used to represent the thermodynamics of the building. Such models, whether they are grey box or black box, are calibrated using relevant data obtained from initial measurements, and the performance of the calibrated model is validated using data from a subsequent period. However, many studies use validation periods with weather conditions similar to those of the calibration period. Only a few studies investigate whether the calibrated model performs satisfactory when subjected to significantly different conditions. This paper presents data from a simulation-based study on the effect of seasonal weather changes on the performance of a black-box model. The study was conducted using 11 years of Danish weather data (2008-2018). The results indicate that the performance of the black-box model deteriorate as the weather data conditions become increasingly different from those used in the initial model calibration. Further, the results show that calibration in heating season leads to satisfactory model performance through the heating season, but lower performance in transitional seasons (especially spring). Results also show that calibration in February led to highest model performance through heating season, while calibration in March led to satisfactory model performance in the whole heating and fall season.

Seasonal Weather Changes Affect the Yield and Quality of Recombinant Proteins Produced in Transgenic Tobacco Plants in a Greenhouse Setting.

Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.

Machine Learning Model for Imbalanced Cholera Dataset in Tanzania.

Cholera epidemic remains a public threat throughout history, affecting vulnerable population living with unreliable water and substandard sanitary conditions. Various studies have observed that the occurrence of cholera has strong linkage with environmental factors such as climate change and geographical location. Climate change has been strongly linked to the seasonal occurrence and widespread of cholera through the creation of weather patterns that favor the disease's transmission, infection, and the growth of Vibrio cholerae, which cause the disease. Over the past decades, there have been great achievements in developing epidemic models for the proper prediction of cholera. However, the integration of weather variables and use of machine learning techniques have not been explicitly deployed in modeling cholera epidemics in Tanzania due to the challenges that come with its datasets such as imbalanced data and missing information. This paper explores the use of machine learning techniques to model cholera epidemics with linkage to seasonal weather changes while overcoming the data imbalance problem. Adaptive Synthetic Sampling Approach (ADASYN) and Principal Component Analysis (PCA) were used to the restore sampling balance and dimensional of the dataset. In addition, sensitivity, specificity, and balanced-accuracy metrics were used to evaluate the performance of the seven models. Based on the results of the Wilcoxon sign-rank test and features of the models, XGBoost classifier was selected to be the best model for the study. Overall results improved our understanding of the significant roles of machine learning strategies in health-care data. However, the study could not be treated as a time series problem due to the data collection bias. The study recommends a review of health-care systems in order to facilitate quality data collection and deployment of machine learning techniques.

Variations in Gut Microbiota of Siberian Flying Squirrels Correspond to Seasonal Phenological Changes in Their Hokkaido Subarctic Forest Ecosystem.

Gut microbial communities of animals are influenced by diet and seasonal weather changes. Since foraging strategies of wild animals are affected by phenological changes, gut microbial communities would differ among seasons. However, interactions of plant-animal-microbiota with seasonal changes have not been well characterized. Here, we surveyed gut microbial diversity of Siberian flying squirrels (Pteromys volans orii) from a natural forest in Hokkaido during spring and summer of 2013 and 2014. Additionally, we compared microbial diversity to temperature changes and normalized difference vegetation index (NDVI). Changes in both seasonal temperature and phenology were significantly associated with alterations in gut microbiota. There were two clusters of OTUs, below and above 20°C that were significantly correlated with low and high temperatures, respectively. Low-temperature cluster OTUs belonged to various phyla, whereas the high-temperature cluster was only constituted by Firmicutes. In conclusion, gut microbiota of Siberian flying squirrels varied with environmental changes on an ecological scale.

Durability of adhesively bonded joints between pultruded GFRP adherends under hygrothermal and natural ageing

This paper presents an experimental and numerical study about the durability of adhesively bonded joints between pultruded glass fibre reinforced polymer (GFRP) adherends for civil engineering applications. Single lap joint (SLJ) specimens were manufactured using either epoxy (EP) or polyurethane (PUR) adhesives and exposed to the following hygrothermal and outdoor ageing conditions for up to 730 days: water and salt water immersion at 20 °C and 40 °C, continuous condensation at 40 °C, salt fog spray at 35 °C, and outdoor ageing in Lisbon, Portugal. At predetermined times, the mechanical behaviour of the SLJs was assessed through shear tests, after drying the specimens to constant mass. Results obtained show that hygrothermal ageing detrimentally affected the failure load and stiffness of the SLJs made with both adhesives, although this degradation was balanced to some extent by post-curing effects and the desorption period (recovery after drying). The magnitude of such degradation was not significantly influenced by the immersion media, but was largely affected by temperature. Outdoor ageing did not cause significant changes in terms of stiffness; for both adhesives, failure load presented a moderate increasing trend, with cyclic pattern, reflecting the effects of seasonal changes in weather. For both adhesives, failure always initiated in one of the GFRP adherends, regardless of the ageing process. However, ageing seemed to affect the portion of bond area with either (light) fibre-tear or adhesive failure: in EP-GFRP specimens, the area with adhesive failure (initially null) increased due to ageing, while in PUR-GFRP specimens (significant in unaged joints) it decreased. The final part of the paper presents linear finite element (FE) models of the SLJs exposed to the harsher ageing environment; these models were developed to numerically simulate the mechanical performance of the joints and to assess the evolution of the internal stresses developed in the SLJs due to the effects of hygrothermal ageing in the constituent materials.

Contribution of Home Gardens to Household Food Security in Sri Lanka: A Comparative Study on Wet Zone and Intermediate Zone

In Sri Lanka, home gardens ensure to some extent the stability of household food security at the village level. Home gardening, which is an age-old practice in various parts of the country, varies on the basis of plant growth influenced by the seasonal weather changes, the composition of the soil and the structure of the locality. This paper attempts to identify the contribution of home gardens to food security with a focus on species richness and the availability of annual food supplement for family nutrition, as identified in a study carried out in four Agro Ecological Zones: the Kariyamadiththa and the Dambethalawa GN in the Intermediate Low Country (ILC); the Kumbalgama and the Silogama GN in the Intermediate Mid Country (IMC); the Vidulipura North and the Vidulipura South GN in the Wet Zone Up Country (WZUP); and the Dammala and the Pannimula GN in the Wet Zone Low Country (WZLC). The sample consists of 200 village level home gardens. While the sampling was random, the data analysis was carried out by means of SPSS 17.0 and the Shannon Diversity Index. According to the sample, the highest number of fruit varieties was found in the WZLC while the highest number of vegetable types was found in the WZUC. Most of the home gardens were maintained for both family consumption and marketing in the ILC. Animal husbandry was practiced sparsely but mostly in the ILC. Shannon diversity index shows that there are large variation in diversity and evenness among home gardens. The survey revealed that most of the householders did not have a reasonable knowledge about the seasons in which crops were available in their home gardens. The study highlights the importance of giving continuous incentives and identification of the potentials of the home gardens for increasing production to minimize the household food insecurity.

The influence of seasonal factors on the content of keratoses, free internal lipids, and physical characteristics of sheep wool

Wool formation is a complex and multifaceted process, which depend on a lot of factors, namely genetic, alimentary, animal maintenance conditions, including seasonal factors’ impact. Seasonal weather changes or so-called photoperiodism, changing the retention and feeding regimes by periods of the year, highly correlate with the physiological state of the organism of the sheep and influence the growth and quality of the wool. Given this the purpose of our work was to investigate the impact of the season on the macrostructure, chemical composition and physical properties of wool. For the research wool of ewe breed precos was used, the samples of which were taken in different seasons, in particular winter, spring, summer and autumn periods of animal maintenance. In the wool there were determined the contents of keratoses and free internal lipids, as well as the strength of the fibers at the break. It was established that wool that grew in the winter and spring period contains the largest amount of protein macro- and microfiber, i.e. alpha keratosis. Instead, with the onset of summer and until autumn the amount of this fraction decreased by an average of 2%. A similar trend was observed on the part of beta keratosis, however, these changes were less significant and did not exceed one percent. It has been established that the content of gamma keratosis, i.e. matrix of fiber, is on the highest level in summer and spring periods, that is, the periods of the best alimentary provision of animals. In the pasture period in the sheep wool there is the biggest amount of free internal lipids (1.1%). In the autumn period, their number begins to decrease gradually and the lowest one is recorded in the winter-stool period (0.9%). The most distinct seasonal changes among these lipids are fixed by cholesterol factions. In particular, the largest number of unesterified cholesterol is contained in the wool of winter growth – 67.2%. With the onset of spring the amount of this fraction decreases up to 62.3% (Р < 0.01) and the trend continues in the summer (61.6%, Р < 0.001) and autumn (60.8%, Р < 0.01) periods. Regarding unesterified cholesterol, there is a diametrically opposite picture of changes. It was established that the strength of the wool of the summer-autumn growth period is bigger by 12%, in comparison with the wool that grew in the winter-stool period. It is shown that there is a positive correlation between the strength of fibers and the content of ceramides in them, which in the winter period was 0.923, in the spring one was 0.989, for summer it was 0.827, in autumn it was 0.786.

Spring poisons

The risks of exposure to some toxicological hazards varies with the season due to seasonal weather changes, people's behaviour or cultural festivals and celebrations.

Effects of the season on physiological and endocrine traits and on HSP70 in Saanen goats under Mediterranean climate conditions

This study was conducted to determine the impact of heat stress on some physiological and endocrine traits in Saanen goats raised under Mediterranean climate conditions. The effects of thermal stress on heart rate (HR), respiration rate (RR) and rectal temperature (RT) on plasma total trii-odothyronine (T3), thyroxine (T4), Cortisol (C), and HSP70 concentrations were evaluated on twenty two Saanen goats of different ages in the second week of April 2013, July 2013, October 2013 and January 2014. Climatic data such as temperature (°C) and relative humidity (%) were recorded from Spring 2013 to Winter 2014. Live body and BCS values were also recorded during this period. The physiological parameters above were measured twice on each experiment day (morning and afternoon) in all seasons. Blood samples were collected in each afternoon of the experiment day to analyze T3, T4 C, and HSP70. All data were analyzed. According to the values of rectal temperature (RT), it was estimated that the goats were under extreme heat stress only in the summer season. The heart rate (HR) values in the winter season for morning and noon periods were found statistically significant (p < 0.05). The average respiratory rate (RR) in the spring season was found significantly lower. On the other hand, the RR for the noon period in the summer was higher than in the fall and winter seasons (p < 0.05). There was a significant difference (p < 0.05) between summer and fall seasons for C values. The highest value (96.62 ng/ml) was obtained in spring, whereas the lowest (60.58 ng/ml) in the fall. T3 levels in the fall and winter were found to be statistically significant (p < 0.05). They were the highest in the winter and spring, and the lowest in fall. T4 and T4/T3 levels in the winter were found to be statistically higher than in other seasons (p < 0.05). The lowest value for T4 was found in the fall and for T4/T3 in summer. Mean HSP70 value in spring was found to be statistically low (p < 0.05). The changes in THI values in different seasons, particularly between mornings and afternoons, indicated that thermal stress was evident, and that the animals became resistant to it eventually. The fluctuations of the C, T3, T4 and HSP70 values were indicators of the animals’ reaction to thermal stress. The THI values in spring, which were between 16 and 18 THI, may be considered within the ideal comfort zone for goats. It was observed that Saanen goats were able to adapt to seasonal weather changes in the environmental conditions of the region....

Seasonal Variation and Weather Changes Related to the Occurrence and Severity of Acute Hematogenous Osteomyelitis in Children.

Acute hematogenous osteomyelitis (AHO) demonstrates regional variability in incidence and severity. In this study, we evaluated seasonal variations of AHO and assessed the effects of weather trends on the occurrence and severity of illness in affected children. National Weather Service data from the dates of symptom onset and of admission of children with AHO were gathered. Seasonal occurrence rates and the weather patterns were studied according to severity-of-illness category. Statistical analysis was performed with Pearson and Spearman correlations and analysis of variance. A total of 209 children with AHO were admitted within 21 days of symptom onset (average, 5.0 ± 3.8 days). Severity-of-illness scores ranged from 0 to 10 (average, 3.2 ± 3.2). Symptom onset occurred most commonly in summer (73 [34.9%]) or spring (54 [25.8%]). We found a significant correlation between severity of illness and minimum temperature at symptom onset during the summer season (P = .020). A significant change in average humidity (21.6%) occurred during the winter between the date of symptom onset and the date of admission for children with severe illness (P = .020). This study identified seasonal variation in the occurrence of AHO in children; summer was the most common season for occurrence. To our knowledge, this is the first detailed evaluation of weather parameters and trends in weather changes from symptom onset to admission with consideration of the effects of weather on the occurrence of infection and severity of illness.