The stomatal response to vapor pressure deficit drives the apparent temperature response of photosynthesis in tropical forests.

As temperature rises, net carbon uptake in tropical forests decreases, but the underlying mechanisms are not well understood. High temperatures can limit photosynthesis directly, for example by reducing biochemical capacity, or indirectly through rising vapor pressure deficit (VPD) causing stomatal closure. To explore the independent effects of temperature and VPD on photosynthesis we analyzed photosynthesis data from the upper canopies of two tropical forests in Panama with Generalized Additive Models. Stomatal conductance and photosynthesis consistently decreased with increasing VPD, and statistically accounting for VPD increased the optimum temperature of photosynthesis (Topt) of trees from a VPD-confounded apparent Topt of c. 30-31°C to a VPD-independent Topt of c. 33-36°C, while for lianas no VPD-independent Topt was reached within the measured temperature range. Trees and lianas exhibited similar temperature and VPD responses in both forests, despite 1500 mm difference in mean annual rainfall. Over ecologically relevant temperature ranges, photosynthesis in tropical forests is largely limited by indirect effects of warming, through changes in VPD, not by direct warming effects of photosynthetic biochemistry. Failing to account for VPD when determining Topt misattributes the underlying causal mechanism and thereby hinders the advancement of mechanistic understanding of global warming effects on tropical forest carbon dynamics.

A medida que aumenta la temperatura, disminuye la absorción neta de carbono en los bosques tropicales, sin embargo, aún no se conocen bien los mecanismos que la subyacen. Las altas temperaturas pueden limitar la fotosíntesis directamente, por ejemplo, reduciendo la eficiencia de los procesos bioquímicos, pero también de forma indirecta a través del aumento del déficit de presión de vapor (DPV) que resulta en el cierre estomático. Para explorar los efectos independientes de la temperatura y el DPV en la fotosíntesis, analizamos datos de la absorción neta de carbono del dosel de dos bosques tropicales en Panamá utilizando modelos aditivos generalizados. La conductancia estomática y la fotosíntesis disminuyó consistentemente con el aumento de DPV, y considerando el DPV en modelas estadísticas, la temperatura óptima de la fotosíntesis (Topt) aumentó, de un Topt aparente influida por la DVP de c. 30­31°C a un Topt independiente del DPV de c. 33­36°C. Los árboles y las lianas mostraron respuestas similares a la temperatura y a la DVP en ambos bosques, a pesar de la diferencia de 1500 mm en la precipitación media anual. La fotosíntesis en los bosques tropicales está limitada en gran medida por los efectos indirectos del aumento de la temperatura, a través de cambios en el DPV y no por los efectos directos en los procesos bioquímicos. Si no se tiene en cuenta el DPV al determinar el Topt, se atribuye erróneamente el mecanismo causal subyacente y, por lo tanto, se obstaculiza el avance en la comprensión de los efectos del calentamiento global en la dinámica del carbono.

Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change.

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

Pervious Concrete Made with Recycled Coarse Aggregate and Reinforced with Date Palm Leaves Fibers.

This study considers 12 pervious concrete mixes incorporating 100% recycled coarse aggregate from old concrete demolition waste and containing various amounts of natural fine aggregate and date palm leaves fibers. First, the properties of the recycled aggregate in terms of their particle size distribution, abrasion resistance, crushing values, specific gravity and water absorption are obtained. Next, the pervious concrete density, compressive strength, tensile strength, permeability and porosity are determined by experimental testing following the relevant standards. The results are analyzed and compared to determine the influence of using recycled coarse aggregate in the mixtures and the impact of the amount of natural sand and volume fraction of the fibers on the mechanical properties, permeability and porosity of the concrete. Findings of the study showed that the use of recycled coarse aggregate in pervious concrete without fine aggregate reduced the compressive strength by 36% and tensile strength by 57%. Replacing 11.7% of the recycled coarse aggregate with natural sand and adding date palm leaves fibers in an amount equivalent to 0.64% volumetric content to such concrete helped increase the compressive strength by 16.2% and tensile strength by 3.2% above the corresponding strengths of the control mix. There is a clear relationship between permeability and porosity due to their correlation with the density of pervious concrete, and the effect of porosity on tensile strength is more influential than it is on the compressive strength. An equation that can predict the tensile strength of pervious concrete from the compressive strength is proposed, as a function of the natural fine aggregate fraction of the coarse aggregate and volumetric content of natural fibers. Results of the research confirm the feasibility of using recycled aggregate in pervious concrete mixes and the positive impact of natural fibers on the mechanical properties.

Action needed to make carbon offsets from forest conservation work for climate change mitigation.

Carbon offsets from voluntary avoided-deforestation projects are generated on the basis of performance in relation to ex ante deforestation baselines. We examined the effects of 26 such project sites in six countries on three continents using synthetic control methods for causal inference. We found that most projects have not significantly reduced deforestation. For projects that did, reductions were substantially lower than claimed. This reflects differences between the project ex ante baselines and ex post counterfactuals according to observed deforestation in control areas. Methodologies used to construct deforestation baselines for carbon offset interventions need urgent revisions to correctly attribute reduced deforestation to the projects, thus maintaining both incentives for forest conservation and the integrity of global carbon accounting.

Effect of proton pump inhibitors on Magnesium levels in Type II diabetic patients: a single centre study from Saudi Arabia.

OBJECTIVE: In recent years, increasing evidence suggests an association between low Magnesium levels and type 2 diabetes mellitus. It has also been reported that the use of proton pump inhibitors may induce hypomagnesemia. Although some case reports have described patients with Proton Pump Inhibitor-induced hypomagnesemia, the impact of Proton Pump Inhibitor use on hypomagnesemia has not been fully clarified in comparative studies. The objective of the study was to determine the Magnesium levels in patients with diabetes who are taking proton pump inhibitors and also to correlate the Magnesium levels in diabetic patients who take proton pump inhibitors with those not taking proton pump inhibitors. PATIENTS AND METHODS: A cross-sectional study was carried out in the study population comprising adult patients attending internal medicine clinics in King Khalid Hospital, Majmaah, KSA. A total of 200 patients who gave informed consent were recruited into the study over one year. RESULTS: Overall prevalence of hypomagnesemia was observed among 128 patients out of 200 (64%) diabetic patients. Relatively more patients with hypomagnesemia were found in group 2 (without PPI use) (38.5%) compared to group 1 (with PPI use) (25.5%). A statistically significant difference was not observed in group 1 using proton pump inhibitors and group 2 not using proton pump inhibitors (p-value = 0.473). CONCLUSIONS: Hypomagnesemia is seen in diabetic patients and patients who take proton pump inhibitors. There was no statistically significant difference in Magnesium levels in diabetic patients, irrespective of proton pump inhibitor use.

Seeing the unforeseen: an insight into kingdom-wide psychological impact of COVID-19 pandemic.

OBJECTIVE: The aim of the manuscript was to measure the levels of psychological stress, both acute and post-traumatic in the Saudi Arabian population during the situation resulting from the COVID-19 outbreak. MATERIALS AND METHODS: A cross-sectional survey was carried out among people of Saudi Arabia (SA) to measure levels of psychological stress, both acute and post-traumatic during the COVID-19 outbreak. Data were collected from five regions in SA using validated questionnaires including Kessler Psychological Distress Scale (K10) and Impact of Events Scale (IES) through social media channels from March 2021 to January 2022. RESULTS: The total number of participants was 1,560. Most of participants (60.2%) were females. Around 53.6% of the sample were aged between 16-24 years old. The majority of participants (87.3%) was Saudi national. About 82% of participants was from Eastern (40.1%) and Western (42.2%) regions, followed by those from Central, Northern, and Southern. More than 60% of them had a college degree or above. The mean K 10 score was 28.33 for the sample which was above the cut-off of 25, implying significant levels of acute stress in the sample. IES values showed a mean of 28.19, well above the cut-off of significant Post Traumatic Stress Disorder (PTSD) symptoms (24). K-10 and IES scores revealed that about 76.7% of the participants suffered from significant acute stress and 59.1% suffered from symptoms of PTSD during the COVID-19 era. CONCLUSIONS: The nationwide study emphasizes the fact that the Saudi population was found to be extremely stressed and traumatized during the COVID-19 pandemic era and calls for effective.

Tropical tree mortality has increased with rising atmospheric water stress.

Evidence exists that tree mortality is accelerating in some regions of the tropics1,2, with profound consequences for the future of the tropical carbon sink and the global anthropogenic carbon budget left to limit peak global warming below 2 °C. However, the mechanisms that may be driving such mortality changes and whether particular species are especially vulnerable remain unclear3-8. Here we analyse a 49-year record of tree dynamics from 24 old-growth forest plots encompassing a broad climatic gradient across the Australian moist tropics and find that annual tree mortality risk has, on average, doubled across all plots and species over the last 35 years, indicating a potential halving in life expectancy and carbon residence time. Associated losses in biomass were not offset by gains from growth and recruitment. Plots in less moist local climates presented higher average mortality risk, but local mean climate did not predict the pace of temporal increase in mortality risk. Species varied in the trajectories of their mortality risk, with the highest average risk found nearer to the upper end of the atmospheric vapour pressure deficit niches of species. A long-term increase in vapour pressure deficit was evident across the region, suggesting that thresholds involving atmospheric water stress, driven by global warming, may be a primary cause of increasing tree mortality in moist tropical forests.

Prediction of COVID-19 severity from clinical and biochemical markers: a single-center study from Saudi Arabia.

OBJECTIVE: It is known that the severity of COVID-19 is linked to the prognosis of patients; therefore, an early identification is required for patients who are likely to develop severe or critical COVID-19 disease. The purpose of this study is to propose a statistical method for identifying the severity of COVID-19 disease by using clinical and biochemical laboratory markers. PATIENTS AND METHODS: A total of 48 clinically and laboratory-confirmed cases of COVID-19 were obtained from King Fahad Hospital, Medina (KFHM) between 27th April 2020 to 25th May 2020. The patients' demographics and severity of COVID-19 disease were assessed using 39 clinical and biochemical features. After excluding the demographics, 35 predicting features were included in the analysis (diabetes, chronic disease, viral and bacterial co-infections, PCR cycle number, ICU admission, clot formation, cardiac enzymes elevation, hematology profile, sugar levels in the blood, as well as liver and kidney tests, etc.). Logistic regression, stepwise logistic regression, L-2 logistic regression, L-2 stepwise logistic regression, and L-2 best subset logistic regression were applied to model the features. The consistency index was used with kernel Support-Vector Machines (SVM) for the identification of associated markers. RESULTS: L-2 best subset logistic regression technique outperformed all other fitted models for modeling COVID-19 disease severity by achieving an accuracy of 88% over the test data. Consistency index over L-2 best subset logistic regression identified 14 associated markers that can best predict the COVID-19 severity among COVID-19 patients. CONCLUSIONS: By combining a variety of laboratory markers with L-2 best subset logistic regression, the current study has proposed a highly accurate and clinically interpretable model of predicting COVID-19 severity.

Towards species-level forecasts of drought-induced tree mortality risk.

Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344-1424 mm yr-1 ). We conducted three experiments: applying CABLE to the 2017-2019 drought; a 20% drier drought; and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO2 ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within-species' ranges, but we also pinpointed resilience in species found in predominantly semiarid areas. The importance of the role of CO2 in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Tropical tree growth sensitivity to climate is driven by species intrinsic growth rate and leaf traits.

A better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) drive spatial variations in species' baseline growth rates, whereas deviations from these averages over time (anomalies) can create growth variation around the local baseline. However, the rarity of long-term tree census data spanning climatic gradients has so far limited our understanding of their respective role, especially in tropical systems. Furthermore, tree growth sensitivity to climate is likely to vary widely among species, and the ecological strategies underlying these differences remain poorly understood. Here, we utilize an exceptional dataset of 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how multiannual tree growth responds to both climate means and anomalies, and how species' functional traits mediate these growth responses to climate. We show that anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both climate means and anomalies. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests and that species traits can provide insights into understanding these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

Shoulder Function Assessment After Head And Neck Reconstruction With Pedicled Supraclavicular Flap.

The supraclavicular artery flap is used for reconstruction of defects of the head and neck. One of the major implications of this procedure is injury to the nerve roots of C3 and C4 of the superficial cervical plexus, which provides sensation over the clavicle, shoulder and proximal chest, thereby causing problems in overall shoulder function. The objective of this study was to assess shoulder function, range of motion, pain, daily activities and overall satisfaction of the patient after using this flap. This study was conducted at the Department of Plastic & Reconstructive Surgery, Dow University of Health Sciences & Dr. Ruth KM Pfau Civil Hospital Karachi, Pakistan, from May 2015 to November 2018. Supraclavicular flap was used in 35 patients who underwent soft tissue reconstruction of defect of the neck after release of post burn contracture. Penn Shoulder Score and Constant Murley Score were used as assessment tools. Assessment by Penn Shoulder Score resulted in 25 (71.4%) patients within the upper quartile and 10 (18.6%) patients within the lower quartile. Constant Murley Score showed 19 (54.2%) of patients had 161°-180° shoulder abduction and lateral elevation. Forward flexion of 161°-180° was seen in 17 (48.5%) patients, 17 (48.5%) had internal rotation till the inter scapular region, 15 (42.8%) had no impairment of external rotation, 19 (54.2%) patients had no impairment of work/recreation, 25 (71.4%) had felt no change in their sleep and 22 (62.8%) were able to position their arm above their head. Overall parameters indicate better function, good range of motion, less pain, resumption of daily activities, and overall satisfaction.

Le lambeau pédiculé supraclaviculaire est utilisé pour la reconstruction cervico- faciale. Sa complication principale est la lésion des racines C3 et C4 du plexus cervical superficiel, responsables de la sensibilité de la région claviculaire, de l'épaule et de la partie haute du thorax entraînant des troubles de la fonction de l'épaule. Cette étude avait pour but d'évaluer la fonction motrice de l'épaule, la douleur, les activités quotidiennes et la satisfaction des patients après ce type de chirurgie. Elle a été réalisée dans le service chirurgie plastique et reconstructrice de l'hôpital civil de Karachi entre mai 2015 et novembre 2018, auprès de 35 patients ayant bénéficié d'une reconstruction cervico- faciale par lambeau supraclaviculaire pour bride post- brûlure. Le score d'épaule de Penn et celui de Constant- Murley ont été utilisés. Vingt- cinq (71,4%) des patients étaient classés dans le quart supérieur du score de Penn, et 10 (18,6%) dans le quart inférieur. Dix- neuf (54,2%) patients avaient une élévation latérale et une abduction entre 161 et 180°, 17 (48,5%) une flexion antérieure entre 161 et 180° ou une rotation interne jusqu'à la région interscapulaire. Quinze (42,8%) patients avaient une rotation externe normale, 19 (54,2%) n'avaient aucune gêne dans la vie courante, 25 (71,4%) avaient un sommeil normal et 22 (62,8%) pouvaient positionner leur bras au- dessus de la tête. Globalement, la fonction est améliorée, les amplitudes sont bonnes, la douleur est diminuée, les activités quotidiennes sont restituées et les patients sont satisfaits.

Fine root dynamics across pantropical rainforest ecosystems.

Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.

Photosynthetic plasticity of a tropical tree species, Tabebuia rosea, in response to elevated temperature and [CO2 ].

Atmospheric and climate change will expose tropical forests to conditions they have not experienced in millions of years. To better understand the consequences of this change, we studied photosynthetic acclimation of the neotropical tree species Tabebuia rosea to combined 4°C warming and twice-ambient (800 ppm) CO2 . We measured temperature responses of the maximum rates of ribulose 1,5-bisphosphate carboxylation (VCMax ), photosynthetic electron transport (JMax ), net photosynthesis (PNet ), and stomatal conductance (gs ), and fitted the data using a probabilistic Bayesian approach. To evaluate short-term acclimation plants were then switched between treatment and control conditions and re-measured after 1-2 weeks. Consistent with acclimation, the optimum temperatures (TOpt ) for VCMax , JMax and PNet were 1-5°C higher in treatment than in control plants, while photosynthetic capacity (VCMax , JMax , and PNet at TOpt ) was 8-25% lower. Likewise, moving control plants to treatment conditions moderately increased temperature optima and decreased photosynthetic capacity. Stomatal density and sensitivity to leaf-to-air vapour pressure deficit were not affected by growth conditions, and treatment plants did not exhibit stronger stomatal limitations. Collectively, these results illustrate the strong photosynthetic plasticity of this tropical tree species as even fully developed leaves of saplings transferred to extreme conditions partially acclimated.

Automated detection of diabetic retinopathy using machine learning classifiers.

OBJECTIVE: Diabetic Retinopathy (DR) is a highly threatening microvascular complication of diabetes mellitus. Diabetic patients must be screened annually for DR; however, it is practically not viable due to the high volume of patients, lack of resources, economic burden, and cost of the screening procedure. The use of machine learning (ML) classifiers in medical science is an emerging frontier and can help in assisted diagnosis. The few available proposed models perform best when used in similar population cohorts and their external validation has been questioned. Therefore, the purpose of our research is to classify the DR using different ML methods on Saudi diabetic data, propose the best method based on accuracy and identify the most discriminative interpretable features using the socio-demographic and clinical information. PATIENTS AND METHODS: This cross-sectional study was conducted among 327 diabetic patients in Almajmaah, Saudi Arabia. Socio-demographic and clinical data were collected using a systematic random sampling technique. For DR classification, ML algorithm including, linear discriminant analysis, support vector machine, K nearest neighbor, random forest and its variate ranger random forest classifiers were used through cross-validation resampling procedure. RESULTS: In classifying DR, ranger random forest outperforms the other methods by accurately classifying 86% of the DR patients on the test data. HbA1c (p<0.001) and duration of diabetes (p<0.001) were the most influential risk factor that best discriminated the DR patients. Other influential risk factors were the body mass index (p<0.001), age-onset (p<0.001), age (p<0.001), systolic blood pressure (p<0.05), and the use of medication (p<0.05) that significantly discriminated the DR patients. CONCLUSIONS: Based on the present study findings, integrating ophthalmology and ML can transform diagnosing the disease pattern that can help generate a compelling clinical effect. ML can be used as an added tool for clinical decision-making and must not be the sole substitute for a clinician. We will work to examine the classification performance of multi-class data using more sophisticated ML methods.

Primary Hyperhidrosis: Prevalence, Severity, and Impact on Quality of Life among Jordanian Patients.

BACKGROUND: Primary hyperhidrosis (PHH) is characterized by idiopathic, focal, bilateral, and symmetrical excessive and exaggerated sweating with a major impact on the quality of life (QoL). To date, there are no studies about the prevalence of PHH in Jordan and in the Arab region. AIM: To assess the prevalence, severity, and characteristics of PHH in the Jordanian population as well as its impact on QoL. MATERIAL AND METHODS: This study was conducted in five hospitals in Jordan and included 4,500 attendants of outpatient clinics who were evaluated for the presence of PHH. To assess the severity of hyperhidrosis (HH), we used the Hyperhidrosis Disease Severity Scale (HDSS). To evaluate the impact of HH on QoL, the Dermatology Life Quality Index (DLQI) questionnaire was answered by our patients, either digitally or on paper. RESULTS: The overall prevalence of PHH in the Jordanian population was 3.2% (n = 144). The most common site was the axillae (63%), either isolated or in association with other sites. Both sexes were affected equally. The overall mean age of onset was 14.7 years. Positive family history was found in 35% of the patients. Nearly two-thirds of the patients presented with HDSS of 3 or 4. The impact on QoL was substantial with a mean DLQI of 12.8. CONCLUSION: PHH prevalence in the Jordanian population is 3.2%, which has a major impact on QoL. This raises the need for addressing this disease to reduce its burden on patient lives.

Impact of weather conditions on incidence and mortality of COVID-19 pandemic in Africa.

OBJECTIVE: The weather-related conditions change the ecosystem and pose a threat to social, economic and environmental development. It creates unprecedented or unanticipated human health problems in various places or times of the year. Africa is the world's second largest and most populous continent and has relatively changeable weather conditions. The present study aims to investigate the impact of weather conditions, heat and humidity on the incidence and mortality of COVID-19 pandemic in various regions of Africa. MATERIALS AND METHODS: In this study, 16 highly populated countries from North, South, East, West, and Central African regions were selected. The data on COVID-19 pandemic including daily new cases and new deaths were recorded from World Health Organization. The daily temperature and humidity figures were obtained from the weather web "Time and Date". The daily cases, deaths, temperature and humidity were recorded from the date of appearance of first case of "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)" in the African region, from Feb 14 to August 2, 2020. RESULTS: In African countries, the daily basis mean temperature from Feb 14, 2020 to August 2, 2020 was 26.16±0.12°C, and humidity was 57.41±0.38%. The overall results revealed a significant inverse correlation between humidity and the number of cases (r= -0.192, p<0.001) and deaths (r= -0.213, p<0.001). Similarly, a significant inverse correlation was found between temperature and the number of cases (r= -0.25, p<0.001) and deaths (r=-0.18, p<0.001). Furthermore, the regression results showed that with 1% increase in humidity the number of cases and deaths was significantly reduced by 3.6% and 3.7% respectively. Congruently, with 1°C increase in temperature, the number of cases and deaths was also significantly reduced by 15.1% and 10.5%, respectively. CONCLUSIONS: Increase in relative humidity and temperature was associated with a decrease in the number of daily cases and deaths due to COVID-19 pandemic in various African countries. The study findings on weather events and COVID-19 pandemic have an impact at African regional levels to project the incidence and mortality trends with regional weather events which will enhance public health readiness and assist in planning to fight against this pandemic.

Effect of heat and humidity on the incidence and mortality due to COVID-19 pandemic in European countries.

OBJECTIVE: The weather allied conditions have an impact on air, water, soil, food, ecosystem, feelings, behaviors, and pattern of health and disease. The present study aims to investigate the impact of heat and humidity on the daily basis incidence and mortality due to COVID-19 pandemic in European countries. MATERIALS AND METHODS: We selected 10 European countries, Russia, United Kingdom, Spain, Italy, Germany, Turkey, France, Belgium, Netherlands and Belarus. This region has a relatively low temperature and high humidity, and has homogenous European ethnicity with almost similar socioeconomic culture and health care system. The data on COVID-19 pandemic including daily new cases and new deaths were recorded from World Health Organization (WHO). The information on daily temperature and humidity was obtained from world climate web "Time and Date". The daily cases, deaths, temperature and humidity were recorded from the date of appearance of first case of "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)" in the European region, from Jan 27, 2020 to July 17, 2020. RESULTS: In 10 European countries, (Russia, United Kingdom, Spain, Italy, Germany, Turkey, France, Belgium, Netherlands and Belarus), the daily basis mean temperature from Jan 27, 2020 to July 17, 2020 was 17.07±0.18°C, and humidity was 54.78±0.47%. The overall results revealed a significant inverse correlation between humidity and the number of cases (r= -0.134, p<0.001) and deaths (r= -0.126, p<0.001). Moreover, an increase in temperature was linked with an increase in the number of cases (r=0.062, p=0.013) and deaths (r=0.118, p<0.001). The regression analysis results further revealed that with an increase of 1% humidity the number of cases (ß = -15.90, p<0.001) and deaths (ß=-1.56, p<0.001) reduced significantly. Whereas, with an increase of 1°C in temperature the number of cases (ß = 20.65, p<0.001) and deaths (ß = 3.71, p<0.001) increased significantly. CONCLUSIONS: Increase in relative humidity was associated with a decrease in the number of daily cases and deaths, however, a rise in temperature was allied with an upsurge in the number of daily cases and daily deaths due to COVID-19 pandemic in European countries. The study findings on weather events and COVID-19 pandemic have an impact at European regional levels to project the incidence and mortality trends with regional weather events to enhance public health readiness and assist in planning to fight against this pandemic situation.

Identifying areas at risk of drought-induced tree mortality across South-Eastern Australia.

South-East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000-2009 and Big Dry, 2017-2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to assess the vulnerability of Australian trees to drought. Here we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterized the drought response behaviour of five broad vegetation types, based on a common garden dry-down experiment with species originating across a rainfall gradient (188-1,125 mm/year) across South-East Australia. The new hydraulics model significantly improved (~35%-45% reduction in root mean square error) CABLE's previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape-scale predictions of the greatest percentage loss of hydraulic conductivity (PLC) of about 40%-60%, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South-East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional-scale predictions of potential drought-induced hydraulic failure.