This study aims to elucidate the dynamic patterns of mosquito species composition and density across seasons and habitats in Yandu District, Yancheng City, from 2016 to 2023 and quantitatively assess the impact of key meteorological factors on population variations, thereby providing a basis for precise risk forecasting of mosquito-borne diseases. Mosquito surveillance was conducted monthly from 2016 to 2023 across 13 sampling sites in urban, rural, and wetland areas of Jiangsu Province using light traps (12 trap-hours per session). Daily meteorological data, including temperature, rainfall, and wind speed, were obtained from local weather stations. Statistical analyses were performed using SAS 9.1 and GraphPad Prism 10. Spearman’s correlation and the Mann-Kendall test were applied to assess relationships and trends. A Generalized Additive Model via Penalized Likelihood (GAMPL) was employed to capture nonlinear effects of meteorological factors on mosquito density, while a Generalized Linear Model (GENMOD) was used to evaluate linear associations. All analyses used a significance level of α = 0.05. From 2016 to 2023, a total of 103,901 mosquitoes were captured via light trapping, with an overall density of 15.04 individuals/(lamp·h). These mosquitoes belonged to 8 species, 4 genera, and 2 subfamilies. The dominant species were Culex pipiens pallens (65.66%), Culex tritaeniorhunchus(18.90%), and Anopheles sinensis (10.29%), accounting for 94.85% of the total captures. Monthly mosquito density showed a unimodal distribution, peaking at 29.11 individuals/(lamp·h) in July. Spatially, the annual average mosquito density in wetland parks (45.78 individuals/(lamp·h)) was significantly higher than that in urban environments (P < .01). Spearman correlation analysis revealed significant correlations between mosquito density and mean temperature, maximum temperature, minimum temperature, and mean precipitation (PRCP) (all P < .001). Generalized linear regression indicated that when temperature exceeded 20°C, each 1°Cincrease was associated with an absolute increase of 1.64 individuals/(lamp·h) in mosquito density (β = 1.64). GAMPL analysis demonstrated a significant nonlinear effect of PRCP on mosquito density, with a smoothed component plot showing an inverted “U” shape. Based on these observational findings, mosquito management strategies may benefit from prioritizing wetland and rural zones during July. Furthermore, temperature-precipitation data could potentially inform early warning systems to guide localized control efforts.

Determining how the thermal tolerances of species are related to climatic conditions at multiple spatial scales can improve our understanding of species distributions and their vulnerability to climate change. We compare the warming tolerances-a metric of warming vulnerability-of arboreal and ground-dwelling ants from savanna and adjacent semideciduous forest in Brazil's Cerrado. Warming tolerance was estimated using the difference between an ant's upper thermal limit and a thermal index of its habitat and stratum. We also evaluated if differences in the upper and lower thermal limits of Cerrado ant assemblages conform to the thermal adaptation (TAH) and the niche asymmetry (NAH) hypotheses. We found that the mean critical thermal maximum (CTmax) and range (CTrange) were higher for ants in savanna than in forest, a pattern that is consistent with the TAH as savanna had higher maximum and more variable air temperatures. However, arboreal ants had lower CTmin than those on the ground despite the similarities in minimum temperatures between the two strata. CTmax was lower for ground than for arboreal ants even though in the savanna (but not in the forest) average maximum air temperatures on the ground were 2°C higher than in trees. Further, the greater heat tolerance of savanna ants was less than the ~7°C difference at the ground stratum in mean maximum temperatures between savanna and forest. A moderate phylogenetic signal was found for CTmax, CTmin, and CTrange. However, accounting for phylogeny did not change our results. Our key finding is that vulnerability to global warming cannot be adequately predicted based on heat tolerance alone-species having a similar CTmax can have very different vulnerability to global warming because of differences in exposure to direct insolation of their preferred habitat or stratum. In our study system, savanna ground ants are more vulnerable to global warming compared to ants living on the forest floor or to arboreal ants more generally. This may have important implications for conservation of the Brazilian savanna ant fauna since most Cerrado species, including several endemics, nest and forage on the ground.

Superheating of the Collecting System during Renal Microwave Ablations; Experimental Study Using an Ex Vivo Perfused Kidney Model.

Comparison of osseodensification and conventional drilling in terms of primary stability and thermal changes under non-irrigated conditions: An ex vivo study.

ABSTRACTThe influence of climate change on emergence phenology of hibernating mammals in northern latitudes is receiving increased attention, yet for freshwater semi‐aquatic mammals such as beavers, which do not hibernate and therefore maintain an obligatory dependence on freshwater habitats throughout the year, little is known about factors influencing their spring emergence above the ice. Given documented effects of increased warming on patterns of ice formation and ice duration on boreal lakes and ponds, we recorded the date of beaver emergence from their winter lodge onto the ice from 2008 to 2025 (18 years) to examine the possible role of temperature, precipitation, and ice phenology on timing of beaver emergence in the spring. On average, ice‐on to emergence lasted 144 days (min 124.0, max 173.0) with a mean emergence date of April 1st. Increased length of the ice‐free period prior to winter, total precipitation and average temperature from spring ice‐off to the next year's emergence were the best predictors of beaver emergence in spring. Temperature was the best predictor of variation in ice duration, while total precipitation from spring ice‐off to ice‐on and average maximum summer temperature appeared to influence the ice‐on date. Trend analyses revealed increasing annual maximum mean temperatures, with increasing summer temperatures being most apparent. With longer ice‐free periods, beavers can forage longer and store more food for winter access; however, longer periods of open water also increase the period that their activities expose them to increased conflict with humans. Understanding the influence of climate change on the ecology of non‐hibernating, yet ice‐bound mammals provides greater insights into future management of these species.

The Tibetan Plateau (TP) is a sensitive area for climate change, with its temperature affected by global warming. However, the variation in the diurnal temperature range (DTR) remains unclear. Therefore, using observational data from 115 stations and ERA5 reanalysis data for TP and the surrounding regions from 1980 to 2022, this study explores the change in DTR and its causes. It also examines temperature simulations of TP in 2000-2021. The results show that: (1) From 1980 to 2022, both the annual mean maximum temperature (Tmax) and minimum temperature (Tmin) in TP show an upward trend, increasing by 0.33°C/10a and 0.47°C/10a respectively. The annual mean DTR exhibits a downward trend, decreasing by -0.14°C/10a. Moreover, the rates of change for Tmax and Tmin are highest during winter, at 0.47°C/10a and 0.59°C/10a, respectively. The DTR declines most rapidly in summer, at -0.17°C/10a. The current temperature trend in TP is expected to persist. (2) During 1980-2022, TCC, SMOIS and Rnl values in TP are higher in the east than in the west, with a significant increase in the western region. The rates of increase surpass 0.005/10a for TCC, 0.005 m3·m-3/10a for SMOIS, and 0.5 W·m-2/10a for Rnl. Rns is higher in the west and lower in the east, with significant increases in the east, reaching up to 2.5 W·m-2/10a. In summer, the rates of change for all four factors in the western part of TP pass the significance test of α = 95%. (3) Simulations based on the QTP-HRAD data are generally lower than observed values. Simulation results indicate that the annual mean Tmax and Tmin in TP are warming at rates over 0.6°C/10a. The DTR is decreasing at rates below -0.6°C/10a in the eastern regions of TP. During autumn, Tmax and Tmin exhibit the most pronounced changes with increases exceeding 1.6°C/10a, while DTR drops most sharply in summer, with decreases below -1.6°C/10a. (4) Analysis of observational and ERA5 reanalysis data from 1980 to 2022 reveals that the three temperature variables in TP are negatively correlated with TCC, SMOIS, and Rnl, and positively correlated with Rns. Validation using QTP-HRAD data from 2000 to 2021 shows that SMOIS negatively correlates with Tmax in the northern region and positively with Tmin in the southern region, and negatively with DTR. Rnl and Rns exhibit negative correlations with all three temperature variables and positive correlations respectively. This study enhances understanding of the impacts of climate change on TP and the surrounding areas.

After substantial progress in malaria control, Ethiopia's Amhara Region experienced a marked resurgence since 2018. The relative contributions of climate variability, environmental context, intervention coverage, and unmeasured factors to this resurgence remain inadequately quantified. This study used a Bayesian spatiotemporal framework to estimate factor associations with malaria incidence, decompose spatial versus temporal climate effects, and identify persistent hotspots. We conducted an ecological district-level panel analysis of 13,944 district-month observations from 166 districts (January 2018-December 2024). Monthly confirmed malaria counts (total,Plasmodium falciparum,P. vivax) were modelled using Bayesian hierarchical negative binomial regression with BYM2 spatial and AR(1) temporal random effects, fitted with integrated nested Laplace approximation. Covariates included lagged rainfall, temperature, NDVI, elevation, and programmatic indicators (ITN ownership, IRS protection, and larval source management [LSM] intensity). Climate covariates were decomposed into between-district (spatial) means and within-district (temporal) deviations. Sensitivity analyses included alternative IRS protection windows and district fixed-effects models. A total of 5,746,571 confirmed cases were reported (64.3%P. falciparum, 35.7%P. vivax). Mean monthly incidence increased 5.5-fold from 1.19 per 1,000 (2018) to 6.53 per 1,000 (2024), while regional mean maximum temperature showed a small declining trend over the period. In fully adjusted models, higher lagged maximum temperature and rainfall were associated with higher incidence, and elevation was protective. IRS protection, higher ITN ownership, and higher LSM intensity were each associated with lower incidence; effect directions were consistent in within-district sensitivity analyses, although residual confounding and measurement error cannot be excluded. Climate-incidence associations were predominantly spatial (between-district) rather than temporal (within-district), suggesting that geographic ecological suitability explains much of the spatial patterning, rather than temporal warming trends explaining the resurgence. Districts with persistently elevated residual spatial risk (exceedance probability of residual RR > 1.25) clustered in low-elevation western border areas. Malaria resurgence in Amhara (2018-2024) occurred alongside strong spatial climatic and elevational gradients and was not consistent with a temporal warming-driven explanation at the regional scale. Remaining unexplained spatiotemporal variation highlights the likely importance of unmeasured drivers (e.g., conflict-related service disruption, vector/insecticide resistance dynamics, and population mobility). Climate-informed, spatially targeted intervention packages prioritizing districts with persistently high residual risk are warranted.

Equine encephalosis (EE) is caused by an Orbivirus from the family Sedoreoviridae and is thus similar to African horse sickness (AHS) and Bluetongue viruses (BTV). These viruses are transmitted by Culicoides midges. Equine encephalosis can infect horses, donkeys and zebras sub-clinically while only horses develop clinical disease. The vector's distribution is climate-dependent with evidence for circulation in Southern Africa, the Middle East and India. Global warming could facilitate the expansion of this distribution and consequently the potential spread into Europe should not be overlooked. To describe clinical signs, clinicopathological abnormalities, and outcomes in horses naturally infected with EE. A retrospective, descriptive, observational study. Data were obtained from the Onderstepoort Veterinary Academic Hospital's clinical database to identify cases with EE from 2013 to 2023. Data including the history, clinical signs and clinicopathology were analysed. Equine encephalosis cases predominantly occurred from February to April. Twenty-five horses were included. Throughout the disease, 25 (100.0%) horses had pyrexia (mean maximum temperature 39.3°C; SD 0.86°C), 16 (64.0%) horses had tachycardia (median maximum heart rate 52/min; range 36-100/min), 19 (76.0%) horses had tachypnoea (median maximum respiratory rate 24/min; range 12-60/min). Within 24 h of presentation, horses predominantly displayed lymphopenia (median 1.17 × 109 cells/L; range 0.15-9.21 × 109 cells/L), thrombocytopenia (median 67.5 × 109 cells/L; range 3-303 × 109 cells/L), and leukopenia (median 5.44 × 109 cells/L; range 2.08-18.07 × 109 cells/L). Retrospective study design with a small number of cases and many of these evaluated at differing times after infection. Pyrexia, tachycardia and tachypnoea are the most common clinical signs associated with EE. Haematological evaluation appears valuable in EE cases, with leukopenia, lymphopenia, and thrombocytopenia commonly observed. Equine encephalosis is a relevant differential diagnosis for other infectious diseases in horses in geographical regions where EEV and Culicoides vectors are potentially present.

This study examines the trends and impacts of heat waves (HWs) and cold waves (CWs) in Eastern Uttar Pradesh, India, from 1961 to 2020, utilizing gridded daily maximum and minimum temperature data from the Indian Meteorological Department. This study analyzes the decadal totals of days, maximum continuous duration days, and mean maximum and minimum temperatures of HWs and CWs across nine meteorological stations. The findings reveal a significant increase in HW occurrences, particularly in stations like Fatehpur and Varanasi, while a decline in CW events is noted across the region. The Excess Heat Factor (EHF) index indicates a rising trend in heat stress events, and this study suggests that the intensity of HWs is increasing due to changes in temperature variability rather than mean warming alone.

Introduction Climate change significantly influences tree radial growth, particularly in high-elevation forests. As a typical plateau lake in the Hengduan Mountains, Lugu Lake lacks sufficient dendrochronological research, hindering the understanding of regional conifers’ responses to climate change. Methods Using dendrochronological methods, we constructed residual chronologies from tree-ring width data of Larix potaninii Batalin. (Chinese larch), Picea likiangensis Franch. (Lijiang spruce) and Pinus yunnanensis Franch. (Yunnan pine) collected around Lugu Lake. We used Response Function Analysis (RFA) and Redundancy Analysis (RDA) to quantify growth–climate relationships. We further identified the key climatic drivers of radial growth for the three conifers. Results and discussion The radial growth of L. potaninii , P. likiangensis , and P. yunnanensis around Lugu Lake was jointly influenced by temperature and precipitation. Specifically, the mean minimum temperature ( T min ) of previous September, current January precipitation, the mean temperature ( T mean ) of current May, and the mean maximum temperature ( T max ) of current September were common factors influencing the radial growth of three conifers. L. potaninii was more influenced by temperature in the early growing season (April–May) and moisture conditions in the post growing season (September–October). Elevated growing-season temperatures were detrimental to the growth of P. likiangensis . P. yunnanensis was more affected by spring drought stress and summer precipitation. Under projected warming with slightly reduced precipitation, the observed climate sensitivities suggest that growth of L. potaninii and P. likiangensis may respond differently, whereas the response of P. yunnanensis is likely more complex. RFA and RDA demonstrated consistency and could effectively complement each other in dendroclimatological studies. This study provides new tree-ring evidence from northwestern Yunnan and insights into potential future growth responses in the region under climate change.

Studies have shown that temperature is closely related to human metabolism, but only a few studies have focused on the effect of abmient temperature on gestational diabetes mellitus (GDM). Evidence from temperate regions is particularly lacking. Our study aimed to explore the association between ambient temperature during pregnancy and the risk of GDM, and further analyze the critical window. This study used data from the Shandong Multi-Center Healthcare Big Data Platform (SMCHBDP). Generalized additive model (GAM) and logistic regression were used to analyze the association between ambient temperature and the risk of GDM. Distributed lag non-linear models (DLNMs) were applied to assess the critical window. Among 3052 subjects, 382 pregnant women were diagnosed with GDM (12.52%). GAM and logistic regression showed that high mean temperature (> 25.18℃) during the 2nd trimester was the risk factor for GDM, and the aOR (95%CI) was 1.67 (1.15-2.45). Extreme high temperature during 13th-18th weeks of gestation was associated with an increased risk of GDM. The effect was greatest at the 16th week of gestation, and the ORs for maximum temperature, minimum temperature and mean temperature were 2.15 (1.19-3.89), 2.25 (1.27-4.01) and 2.71 (1.43-5.13), respectively. An increased risk of GDM was observed for each IQR (2.2°C) increase in diurnal temperature range (DTR) at 17th-21st weeks of gestation. Therefore, extreme high temperature and DTR affect GDM mainly in the 2nd trimester. These findings highlight the need for targeted protective measures for pregnant women during these periods, especially amid global warming, to mitigate temperature-related GDM risk.

Abstract Climate change and variability have significantly impacted smallholder and subsistence farmers in Ethiopia. The effectiveness of adaptation measures largely depends on how farmers perceive climate change and variability. Hence, understanding their perception and comparing it with long-term trends is crucial for designing appropriate responses. Thus, this study examined climate parameters and smallholder farmers’ awareness of climate change in the Jemma sub-basin. A total of 366 households were randomly selected from highland, midland, and lowland kebeles. Quantitative and qualitative data were collected through household surveys, focus group discussions, and key informant interviews. Grided monthly precipitation and temperature data were obtained from the Ethiopian Meteorology Institute. The Mann–Kendall test and Sen’s slope estimator were employed to examine the time series trends of rainfall and temperature. The MK trend test results revealed that yearly and summer season rainfall exhibit a non-significant increasing trend, while spring season rainfall shows a decreasing trend. The coefficient of variance shows that the monthly and spring season rainfall shows the highest variability (CV&gt;30 %), while the annual rainfall shows less variability. Similarly, the mean annual, maximum, and minimum temperatures show an increasing trend. Consequently, about 83.47 % of highland, 91.54 % of midland, and 100 % of lowland respondents feel the temperature rise, and 44.62 %, 66.2 %, and 100 % of highland, midland, and lowland respondents recognized the decreasing rainfall trend, respectively. The analysis result reveals that age, gender, access to climate information, education, farming experience, and market access significantly influence perceptions of temperature and rainfall trends. Therefore, farmers’ perceptions should be integrated into meteorological data analysis, and policymakers should consider these disparities when developing climate adaptation strategies.

Prescribed burning (PB) has been used on UK heathlands for centuries, which has not been without controversy concerning the potential to heat organic-rich soils. In recent years accredited training has been available to UK land managers providing them with improved skills with which to burn safely. Aims We assessed the levels of soil heating beneath PBs undertaken by these teams that have recently been upskilled and provide a broad assessment of a range of burns using the same methodology at each burn. Methods In-field measurements of soil (3 cm depth), above-ground temperatures and fire severity assessments were taken during eight PBs across the UK, conducted under mild weather conditions and complying with PB guidance. Key results Both organic-rich peaty soils and mineral soils received little heating during the PBs tested, with mean maximum temperatures of &amp;lt;43.4°C, and surface mean maximum temperatures of 784.5°C. Fire severity assessments indicated no below-ground organic matter loss. Conclusions When following new accredited training and according to Department for Environment, Food and Rural Affairs current guidance, underlying soils were not subjected to high temperatures that could directly damage long-term carbon stores. Implications Our results provide valuable insights into soil temperatures reached during PBs, highlighting that well-planned fire can be used safely in respect to burning vegetation particularly over organic-rich peaty soils.

Climate change is a hot topic these days in all countries around the world. Although Romania has taken important steps to combat climate change, continued efforts are needed to implement existing policies for monitoring and forecasting climate parameters, as well as to raise population awareness. In this paper, several climatic parameters are analyzed, such as mean annual air temperature, average minimum and maximum temperatures per month, mean temperature during the vegetation season, annual amount of precipitation, amount of precipitation per month and amount of precipitation during the vegetation season. Climatic parameters were studied over four periods: 1901-1930, 1931-1960, 1961-1990 and 1991-2023. Temperatures were also estimated until the year 2100. Projected future temperatures were estimated by combining data found in the current databases and Representative Concentration Pathways (RCP) projection data. Some ecoclimatic indices were calculated, such as De Martonne aridity index and the Lang rainfall index. To achieve the objectives of this study, the following databases were used: World Bank Climate Knowledge Portal, European Environment Agency (EEA), Our World in Data, European Drought Observatory (EDO), European Climate Assessment &amp; Dataset.

Temperature is increasing highly day by day and its influence on climate change is unfavourable. Many researchers have studied several characteristics of temperature all over the world in various frame of data usually in yearly based data or season wise data. This paper is concerned with the comparison of accuracy percentage of statistical model of temperature in two dimensions, one is monthly mean minimum temperature and another one is monthly mean maximum temperature based on yearly data and season wise data for the period of 1985-2022 in various zones of Assam (Guwahati, Dibrugarh, Silchar, Tezpur). The analysis clearly showed that accuracy percentage of statistical model of temperature season wise is more than that of yearly based data. The study shows that there is an increasing trend in case of monthly mean maximum temperature and in case of monthly mean minimum temperature, there is both increasing and decreasing trend in accordance to months for the period 1985-2018 in Guwahati, the capital of Assam.

A warming climate poses significant threats to seagrass species worldwide, resulting in ecosystem impacts such as reduced foreshore stabilisation, decreased fisheries habitat, and diminished carbon sequestration. The recovery of seagrass is often inconsistent, taking weeks to years, and in severe cases, recovery may not occur. Recovery is facilitated through both asexual and sexual reproduction, with smaller or short-term disturbances typically favoring asexual reproduction, while large-scale disturbances rely on a persistent seed bank. This study investigated reproductive metrics of Zostera muelleri in persistent thermal plumes, measuring reproductive shoot density, spathe counts, and seed bank density and viability. An estuary affected by thermal effluent, Lake Macquarie, NSW, Australia, was used as a proxy for future climate scenarios and compared with two other east coast Australian estuaries. Seed banks in all three systems were relatively small (averaging 16 seeds m-2), suggesting that these populations may not rely strongly on seed banks for recovery. Mean reproductive shoot densities ranged from 4 to 8 shoots m-2, while spathe counts averaged between 10 and 20 per reproductive shoot, with peak reproductive metrics observed in November and January. Importantly, no significant differences in reproductive shoot densities, spathe counts, or seed bank viability were found between thermally affected (mean maximum temperatures ~2°C higher) and ambient conditions, indicating that Zostera muelleri reproduction on the east coast of Australia may have the capacity to acclimate to temperatures expected by the end of the 21st century.

Sri Lanka is a tropical island in the Indian Ocean, which has a diverse climate shaped by monsoonal variations and seasonal fluctuations that have a significant impact on temperature trends, underscoring the need for accurate forecasting models. This study focuses on Trincomalee District, one of the hottest regions in Sri Lanka, where the highest recorded temperature from 1949 to April 2024 was 39.5C. The research aims to model and forecast the monthly mean maximum and minimum temperature series using Periodic Autoregressive (PAR) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. Monthly data from January 2008 to October 2024 was analyzed to assess model performance in capturing seasonal and periodic trends. The SARIMA (1, 0, 0) (2, 1, 1) model best fits the maximum temperature series, with a low RMSE (0.7830) and MAPE (1.7628%). Meanwhile, the minimum temperature series shows significant periodicity, with the PAR(1) model offering better precision (RMSE 0.4391, MAPE 1.4071%). These findings support to improvement of climate forecasting and agricultural planning in Sri Lanka’s dry zone.

ABSTRACT The Murray Mallee (MM) and Upper Eyre Peninsula (UEP) are two important regions to the South Australian agricultural economy. The UEP is dominated by agricultural land use with a semi‐arid Mediterranean‐type climate, with low, variable annual rainfall. The climate is similar, with significant farming production around the Murray Mallee, adjacent to the Murray River. When investigating rainfall trends in the UEP region, annual rainfall has decreased considerably in the last 73 years, from 1950 to 2023, at all rain monitoring stations. From the 15 stations in the MM, most of the locations' rainfall is decreasing, but three stations, including Callington, Murray Bridge, and Mannum, show an increasing trend in annual rainfall. Monarto Safari Park station had only recent rainfall records; however, it also shows an increasing trend. The records for MM, particularly for gauges where rainfall has seen an increasing trend, seem to correspond with a revegetation program on the Monarto Plateau during the 1970s, and this may have been significant enough to increase rainfall in the surrounding regions, including Callington and Murray Bridge. Each station's annual rainfall, mean minimum temperature, and mean maximum temperature data are analyzed separately using trend analysis with exponential smoothing and three robust change‐point analysis methods in the MM and UEP regions. The significant change points observed in annual rainfall and temperature in each location and the overall reduction in rainfall may be attributed to industrial expansion, climate change, and shifts in land use patterns driven by urbanization, which have likely impacted water resources. This study investigated the relationship between land use and climate change that may impact South Australian rainfall patterns and increases in temperature over the last few decades.

ABSTRACT Heat stress severely impairs wheat yields and poses significant challenges to food security. In the present investigation, 72 diverse bread wheat genotypes were evaluated in the completely randomised block design with two replicates at four locations under normal and heat stress conditions during Rabi , 2022–23. The mean maximum temperature was above congenial (&gt; 25°C) at 27.9°C, 28.8°C, 33.4°C and 33.3°C at Karnal, Hisar, Niphad and Pune locations, which imposed adverse effects at the heading and grain filling stages. Under heat stress, the pooled mean grain yield varied from 294.8 g (DHTW60) to 660.2 g/plot (RWP2017‐21). The genotype DBW173 showed an 8.07% yield reduction under heat stress, followed by DBW187 (9.51%), PBW826 (10.25%), 29 th SAWYT‐303 (10.36%), Raj3765 (11.41%), and RWP2017‐21 (11.54%). The 1000 grain weight (TKW) reduction was also low for these genotypes, except for 29 th SAWYT‐303 (19.80%). Here, the yield stability index (YSI) and heat susceptibility index (HSI) ranged from 0.56 to 1.02 and −0.09 to 1.95, respectively. In contrast, the relative heat index (RHI) and percent yield reduction (PYR) varied from 0.73 to 1.31 and −1.99 to 43.63, respectively. The low HSI values (&lt; 0.60) were recorded for NIAW1342, HI1605, DBW173, DBW187, PBW826, 29 th SAWYT‐303, 20 th HTWYT‐2, Raj3765, RWP2017‐21, K7903 and K9465. PCA clustered 13 heat stress indices into three clusters, where TOL, HSPI, HSI and PYR were grouped into a single segment. The genotypes DBW173, DBW187, HI1531, HI1605, NIAW1342, PBW826, Raj3765, RWP2017‐21, 20 th HTWYT‐2, 20 th HTWYT‐13, 20 th HTWYT‐41, 29 th SAWYT‐303 and WAP96 appeared as heat tolerant. The higher TKW, grains/spike, coupled with higher NDVI values, can be used as selection criteria under heat stress breeding. The indices HSI, PYR, HRI, YI and YSI can be employed effectively in future studies.

Introduction: Skull density ratio (SDR) is an important criterion for predicting efficacy of high-intensity focused ultrasound (HIFU) thalamotomy for essential tremor and tremor-dependent Parkinson’s disease. Bisphosphonates are known to increase bone density and are postulated to raise SDR and improve HIFU energy transmission efficiency. However, the impact of bisphosphonate pre-treatment on HIFU outcomes has not been investigated. Methods: A retrospective analysis was conducted on the sonication parameters of patients with SDR <0.45 who were pre-treated off-label with bisphosphonates prior to HIFU. For comparison, the sonication parameters were also collected for patients with SDR <0.45 not pre-treated with bisphosphonates, patients with mid-range SDR (0.45–0.49), and patients with high SDR (0.5–0.55). All patients underwent HIFU thalamotomy between March 2022 and December 2024. Results: The bisphosphonate pre-treatment group (28 patients) and the low-SDR untreated group (29 patients) both had mean SDRs of 0.41. Respectively, the bisphosphonate-treated and low-SDR untreated group had mean final sonication energy of 23 kJ versus 26 kJ, final sonication duration of 27.1 versus 28.6 s, mean maximum temperature of 52.8°C versus 53.2°C, and average of 5.6 versus 4.9 sonications per treatment (p > 0.05 for each comparison). No significant differences between the two low-SDR groups were found for the thermal efficiency of sonication. Compared to the bisphosphonate-treated low-SDR group, the mid- and high-SDR groups exhibited significantly decreased sonication energy (p < 0.0001), final sonication duration (p < 0.0001), and higher final sonication max temperature (p < 0.01). Across all patients, a negative correlation was observed between SDR and final sonication energy (p < 0.0001, r = −0.48) and a positive correlation was observed between SDR and last sonication temperature (p < 0.005, r = 0.27), although in the low-SDR cohort, a correlation was not observed. No clinically significant differences were found in demographics, self-reported tremor improvement, or incidence of side effects. Conclusion: No significant differences were found in sonication response parameters between the bisphosphonate-treated and untreated low-SDR groups, whereas mid- and high-SDR groups had significantly reduced sonication energy and time to produce greater heat. These findings show that while bisphosphonates are an established way of raising bone density in osteoporosis, pre-treatment with bisphosphonates does not shift the sonication response from that of a low SDR to a mid-range SDR. Additionally, other factors besides just skull density likely determine the thermal response to sonication.