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Kalanchoe pinnata (Lam.) Pers. is an ethnomedicinal plant known for its antioxidant, antibacterial, and therapeutic potential. The current study was an effort to explore the impact of extraction technique on the phytochemical, antioxidant, and antibacterial profile of the plant extracts. K. pinnata leaf extracts were prepared using conventional solvent extraction (100% methanol; 50% methanol: 50% water; 100% water), microwave-assisted extraction at 700-W power (3 min; 6 min; 9 min), and supercritical fluid extraction (SFE) (3500 psi; 4500 psi; 5500 psi). Best results were attained from SFE in terms of total phenolic content (240 ± 3 mg GAE/g), total flavonoid content (165.2 ± 0.4 mg QE/g), 2,2-diphenyl-1-picrylhydrazyl radical scavenging potential (91.9 ± 0.4%), 2,2′-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid assay value (8.04 ± 0.03 mMol TE/g) and ferric reducing antioxidant power assay value (471.7 ± 0.8 µg/mL). K. pinnata leaf extracts have been found to be most effective against Yersinia pseudotuberculosis (22.20 ± 0.95 mm) and least effective againstProteus vulgaris (0 ± 0 mm). High-performance liquid chromatography analysis of K. pinnata extract showed that it contains flavanol quercetin (2.0 ± 0.1 mg/g). It is evident from the findings of current study that K. pinnata extract can effectively treat bacterial infections and can cure metabolic disorders by reducing oxidative stress. Application of advance extraction techniques enhances the biological activity of plant extracts.

The yield and composition of pyrolysis products depend on the characteristics of feed stock and process operating parameters. Effect of particle size, reaction temperature and carrier gas flow rate on the yield of bio-oil from fast pyrolysis of Pakistani maize stalk was investigated. Pyrolysis experiments were performed at temperature range of 360-540°C, feed particle size of 1-2 mm and carrier gas fl ow rate of 7.0-13.0 m3/h (0.61.1 m/s superficial velocity). Bio-oil yield increased with the increase of temperature followed by a decreasing trend. The maximum yield of bio-oil obtained was 42 wt% at a temperature of 490°C with the particle size of around 1.0 mm and carrier gas flow rate of 11.0 m3/h (0.9 m/s superficial velocity). High temperatures resulted in the higher ratios of char and non-condensable gas.

Working in a toxic environment makes it harder to be productive. This study examines the direct impact of Machiavellianism and professional envy on research productivity (individual and group) with the moderating role of knowledge-hiding behaviors. For this purpose, through convenience sampling, an online survey through Google Docs was conducted, and 221 permanent faculty members from private sector higher education institutions participated. The impact of moderating variables between predictors and criterion variables was tested through PROCESS-macro. The findings of this study revealed that Machiavellianism and professional envy have a significant negative influence on individuals and as well group-based research productivity. In contrast, knowledge hiding behaviors of faculty members moderate the relationships between Machiavellianism, professional envy, and individual and group-based research productivity.

Nowadays, waste discharge and contaminants in drinking water have emerged as a significant global problem. Therefore, it is necessary to remove these pollutants from the water and photocatalysis is the best technique for this purpose. The co-precipitation technique was employed to produce NiMn2O4 and ZnMn2O4 and a photocatalyst containing NiMn2O4/ZnMn2O4 heterostructure nanocomposite. Various analytical techniques have been ascribed to examine the physical, morphological and optical features of the fabricated catalysts. XRD diffraction peak patterns were utilized to confirm the presence of cubic NiMn2O4, tetragonal ZnMn2O4 and NiMn2O4/ZnMn2O4 phases in a nanocomposite. In photodegradation tests, the nanocomposite catalyst outperformed the individual catalysts. After 60 minutes of visible light exposure, this nanocomposite catalyst eliminated the methylene blue (MB) dye, attaining substantially higher degradation rates than pure NiMn2O4 (66%) and ZnMn2O4 (77%). The nanocomposite catalyst was highly effective against methylene blue (MB) dye with a degradation efficiency of 92%.

Stevia rebaudiana is zero-calorie bio-sweetener and furnishes the best nutrition out of it. The study was conducted to characterize the extracts from water, ethanol, methanol, and supercritical fluid for Steviosides/SGs. The compounds found in appreciable quantities were Stevioside (665.34 ± 27.27 to 1107.95 ± 50.96 mg/kg), Rebaudioside A (383.38 ± 17.25 to 792.15 ± 38.02 mg/kg) and Steviol (357.26 ± 14.64 to 485.25 ± 22.32 mg/kg). Stevia cookies were prepared by replacing sucrose with Stevia powder (10%), water extract (1%), and supercritical extract (3%). Bio-efficacy rats modeling trials were done to check their impact against hyperglycemia and hypercholesterolemia. Blood glucose level was reduced from 4.54 to 7.00%, insulin level was increased by 4.27 to 6.13% due to diets enriched with stevia powder and extracts as compared to the control. In hypercholesterolemic rats, up surged cholesterol level was reported to reduce as a function of Stevia powder and extracts from 1.28 to 5.47%. Substantial increment in HDL, and reduction in LDL and triglycerides was recorded in Stevia leaves powder and extracts treatments by 2.79–6.66%, 2.68–4.16%, and 3.12–5.36, respectively. Stevia cookies administration in rats showed non-significant impact on the liver, renal, and hepatological parameters, while the safety of cookies was improved. Therefore, it can be concluded from the outcomes that in addition to sweetness, Stevia health health-beneficial effects make it suitable to be included in cookies.

Introduction: To derive the reference intervals of serum soluble FMS like tyrosine kinase -1/Placental growth factor ratio in pregnant and non-pregnant females. Aims & Objectives: To derive the reference intervals of serum soluble FMS like tyrosine kinase -1/Placental growth factor ratio in pregnant and non-pregnant females. Place and Duration of Study: A comparative Cross-sectional study conducted in department of Chemical Pathology and Immunology, Chughtai Institute of Pathology, Lahore from February 2024 till May 2024 Material & Method: Blood samples from 120 pregnant and 120 non-pregnant females from 14±1 to 27±1 weeks were taken. All participants were of reproductive age group, disease free, non-hypertensive, non-diabetic, without any inherited or autoimmune disorders and not any significant drug history. Levels of placental growth factor (PGF) and soluble FMS like tyrosine kinase -1(sFlt-1) were estimated by Elecsys cobas e601. Data was analysed by SPSS 21. Shapiro-Wilk test and Kolmogorov Smirnov test were applied. p value

Cooperative communication through energy harvested relays in Cognitive Internet of Things (CIoT) has been envisioned as a promising solution to support massive connectivity of Cognitive Radio (CR) based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems. In this work, a cooperative CIoT system is contemplated, in which a source acts as a satellite, communicating with multiple CIoT devices over numerous relays. Unmanned Aerial Vehicles (UAVs) are used as relays, which are equipped with onboard Energy Harvesting (EH) facility. We adopted a Power Splitting (PS) method for EH at relays, which are harvested from the Radio frequency (RF) signals. In conjunction with this, the Decode and Forward (DF) relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices. We developed a Multi-Objective Optimization (MOO) framework for joint optimization of source power allocation, CIoT device selection, UAV relay assignment, and PS ratio determination. We formulated three objectives: maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission. The MOO formulation is a Mixed-Integer Non-Linear Programming (MINLP) problem, which is challenging to solve. To address the joint optimization problem for an epsilon optimal solution, an Outer Approximation Algorithm (OAA) is proposed with reduced complexity. The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search (NOMAD) algorithm.

Background and aimFecal incontinence (FI) is defined as the unintended loss of solid or liquid stool. FI adversely affects the patient’s quality of life. However, due to stigma, lack of awareness, and underdiagnosis, there is a notable gap in the knowledge regarding its prevalence. This study aimed to conduct a systematic review and meta-analysis of published literature reporting on FI prevalence and estimate the number of people afflicted by FI.MethodsA systematic review was conducted following the PRISMA 2020 guidelines, using the Embase, MEDLINE, CINHAL, and PubMed databases to identify relevant publications in the English language. Two reviewers independently screened the articles and extracted data. The reference sections and content of the review papers were also evaluated. Thirty-two articles were selected and included. A meta-analysis of proportions was performed using RStudio software. A sub-analysis was conducted to account for the variation between sample population age groups to minimize heterogeneity. The pooled prevalence was extrapolated to the Canadian population and a sample of ten densely populated countries to estimate the number of people affected by FI.ResultsThe Mean pooled FI prevalence in men and women was 7% (95% CI: 6-9%) and 10% (95% CI: 8-12%), respectively. The sub-analysis mean pooled prevalence of FI in men and women was 8% (95% CI: 6-10%) and 10% (95% CI: 8-12%), respectively. The authors estimate that between 1 and 1.5 million Canadians and 320 to 500 million people in the ten most populous countries suffer from FI.ConclusionFecal incontinence is a prevalent underdiagnosed condition requiring appropriate and timely treatment to improve a patient’s quality of life.

Pakistan is facing the worst level of energy and economic crisis of its history. The underlying reason of the economic crisis is basically due to the energy crisis. Various approaches have been adopted to tackle the energy crises which the country is facing for over 2 decades. Demand-side management (DSM) is the most potent and cost-effective option to redress the energy crisis, which, unfortunately, has been the most neglected strategy in Pakistan. DSM has the potential to save up to 10.0%–15.0% of primary energy to ensure the country’s future energy security. Laws and codes do exist, but ironically, the most vital element of DSM’s policy framework and implementation mechanism is missing. Hence, the main objective of this research is to develop a DSM model for Pakistan and analyze the reference and DSM scenarios. Low-emission analysis platform (LEAP) is used to develop Pakistan’s DSM model for the study period 2021–2050. The three alternative DSM scenarios developed include energy efficiency (EEF), energy conservation (EC), and load management (LOM), and they are all analyzed. The model results estimate the electricity demand forecast of 1009.8 TWh under the reference scenario in 2050, whereas DSM tends to result in a 26.38% decreased electricity demand compared to the reference scenario. The alternative DSM scenarios also outperform the reference scenario. In 2050, the EC scenario reduces consumption by 178.0 TWh and GHG emissions by 19.20 million metric tons, the EEF scenario reduces consumption by 110.30 TWh and GHG emissions by 10.04 million metric tons, and the LOM scenario suggests reduced consumption by 101.0 TWh and GHG emissions by 6.20 million metric tons. This study concluded that the DSM must be institutionalized in Pakistan by building a robust regulatory framework and execution mechanism at the government and utility levels.

We present the case of a 36-year-old female who visited the OPD of a local hospital in Lahore, Pakistan, with history of chest pain, shortness of breath and palpitations. Echocardiogram and transesophageal echocardiography revealed right ventricular outflow tract mass, dilated coronary sinus and atrial septal defect. Surgery was advised, and successful excision of the mass was done and the specimen later sent to Chughtai Institute of Pathology for histopathological evaluation and diagnosis. The results revealed benign thyroid tissue with no evidence of malignancy. The patient was symptom-free on follow up after 6 months.

Pakistan is facing energy crises due to localized shortages, market manipulation, infrastructure disruption, rising demand, governance issues, climate and geopolitical events. In this situation Demand Side Management (DSM) is a promising solution to overcome the problem of energy crises. DSM strategy helps to manage consumer demand through energy conservation rather than to addition of new power capacity. In this study, Low Emissions Analysis Platform (LEAP) develops an energy model for Pakistan for the period 2022–2050. Three scenarios has been to constructed namely Baseline (BAS), Green Energy Policy (GEP), and Energy Efficiency (ENE) to predict the future energy demand, production, carbon emissions and the investment cost which covers capital, operational and maintenance costs. The model results suggest that DSM targets should be achieved through the implementation of ENE scenario. Predicted energy production and consumption under the ENE scenario are substantially less than those under the BAS scenario. The country can meet its 635.83,000 GWh energy demand with its 747.15,000 GWh energy production. Non-renewable sources produce 171.27,000 GWh, whilst renewable sources produce 575.88,000 GWh. According to this scenario, by 2050, CO2 emissions will be produced around 93.16 million metric tons, requiring an investment cost of $46.80 billion for building new power capacity. The study provides a roadmap with a suggestive optimal balance between energy saving with DSM approach and utilizing renewable energy production to meet energy demand for different sectors of the economy.

Abstract Background and Aims Several studies imply that influenza and other respiratory illnesses could lead to acute myocardial infarction (AMI), but data from low‐income countries are scarce. We investigated the prevalence of recent respiratory illnesses and confirmed influenza in AMI patients, while also exploring their relationship with infarction severity as defined by ST‐elevation MI (STEMI) or high troponin levels. Methods This cross‐sectional study, held at a Dhaka tertiary hospital from May 2017 to October 2018, involved AMI inpatients. The study examined self‐reported clinical respiratory illnesses (CRI) in the week before AMI onset and confirmed influenza using baseline real‐time reverse transcription polymerase chain reaction (qRT‐PCR). Results Of 744 patients, 11.3% reported a recent CRI, most prominently during the 2017 influenza season (35.7%). qRT‐PCR testing found evidence of influenza in 1.5% of 546 patients, with all positives among STEMI cases. Frequencies of CRI were higher in patients with STEMI and in those with high troponin levels, although these relationships were not statistically significant after adjusting for other variables. The risk of STEMI was significantly greater during influenza seasons in the unadjusted analysis (relative risk: 1.09, 95% confidence interval [CI]: 1.02–1.18), however, this relationship was not significant in the adjusted analysis (adjusted relative risk: 1.03, 95% CI: 0.91–1.16). Conclusion In Bangladesh, many AMI patients had a recent respiratory illness history, with some showing evidence of influenza. However, these illnesses showed no significant relationship to AMI severity. Further research is needed to understand these relationships better and to investigate the potential benefits of infection control measures and influenza vaccinations in reducing AMI incidence.

The Intelligent Transportation System (ITS) has the potential to significantly improve communication reliability, efficiency, and manageability in transportation systems. Vehicular ad hoc networks (VANETs) are particularly valuable for sustaining ITS features in dynamic, high-density environments. Integrating the Internet of Things (IoT) into modern transportation systems can further enhance ITS capabilities by providing real-time data and connectivity. Challenges like insufficient spectrum utilization and increased end-to-end latency in single-radio data transmission systems have led to the development of advanced techniques such as dual-radio multi-channel systems. However, these approaches often compromise network performance due to interference. To address these limitations, this paper proposes drone-assisted cooperative routing (DACR), incorporating IoT elements for improved connectivity and data exchange. Performance evaluation, based on comparative analysis with existing state-of-the-art schemes, indicates that the proposed DACR outperforms in packet delivery ratio, end-to-end delay, and control message overhead. DACR demonstrates a 22% and 52% reduction in control message overhead compared to U2RV and CRRA, a 23% improvement in ETE delay over U2RV, a 33% improvement over CRRA, and a 14.5% and 44% increase in PDR, respectively.

Abstract Background To summarize current evidence to report a comparative systematic review and meta-analysis of prostatic artery embolization (PAE) with transurethral resection of the prostate (TURP) and open simple prostatectomy (OSP) for the treatment of benign prostatic hyperplasia (BPH). Methods A systematic literature search was performed to identify studies published from inception until August 2021. The search terms used were (prostate embolization OR prostatic embolization) AND (prostatic hyperplasia OR prostatic obstruction) as well as the abbreviations of PAE and BPH. Risk of bias was assessed using the Cochrane Risk of Bias tool for randomized controlled trials (RCTs) and the Risk of Bias in Non-randomized Studies—of Interventions (ROBINS-I) tool for observational studies. Random-effects meta-analysis was performed using Revman 5.4. Results Seven studies were included with 810 patients: five RCTs and one observational study compared PAE with TURP, and one observational study compared PAE with OSP. The included studies had considerable risk of bias concerns. TURP and OSP were associated with more statistically significant improvements in urodynamic measures and BPH symptoms compared to PAE. However, PAE seems to significantly improve erectile dysfunction compared to OSP and improve other outcome measures compared to TURP, although not significantly. PAE appeared to reduce adverse events and report more minor complications compared with TURP and OSP, but it is unclear whether PAE is more effective in the long-term. Conclusion PAE is an emerging treatment option for patients with symptomatic BPH who cannot undergo surgery or have undergone failed medical therapy. Overall, PAE groups reported fewer adverse events. Future ongoing and longer-term studies are needed to provide better insight into the benefit of PAE compared to other treatment options.

Introduction: Phenytoin is one of the commonly used anti-seizure medications in nontraumatic seizures. However, its utility and safety in young patients with traumatic brain injury (TBI) for the prevention of early-onset seizures (EOS) are debatable. We sought to explore the use of phenytoin as a seizure prophylaxis following TBI. We hypothesized that administering phenytoin is not effective in preventing EOS after TBI. Methods: This was a retrospective observational study conducted on adult TBI patients. EOS was defined as a witnessed seizure within a week postinjury. Data were compared as phenytoin versus no-phenytoin use, EOS versus no-EOS, and among TBI severity groups. Results: During 1 year, 639 TBI patients were included with a mean age of 32 years; of them, 183 received phenytoin as seizure prophylaxis, and 453 received no prophylaxis medication. EOS was documented in 13 (2.0%) patients who received phenytoin, and none had EOS among the nonphenytoin group. The phenytoin group was more likely to have a higher Marshall Score (P = 0.001), lower Glasgow Coma Scale (GCS) (P = 0.001), EOS (P = 0.001), and higher mortality (P = 0.001). Phenytoin was administrated for 15.2%, 43.2%, and 64.5% of mild, moderate, and severe TBI patients, respectively. EOS and no-EOS groups were comparable for age, gender, mechanism of injury, GCS, Marshall Score, serum phenytoin levels, liver function levels, hospital stay, and mortality. Multivariable logistic regression analysis showed that low serum albumin (odds ratio [OR] 0.81; 95% confidence interval [CI] 0.676–0.962) and toxic phenytoin level (OR 43; 95% CI 2.420–780.7) were independent predictors of EOS. Conclusions: In this study, the prophylactic use of phenytoin in TBI was ineffective in preventing EOS. Large-scale matched studies and well-defined hospital protocols are needed for the proper utility of phenytoin post-TBI.

With the increasing prevalence of multi-user, multi-service, and heterogeneous multi-device environments, there is a need to address the imperative for efficient resource allocation in contemporary wireless networks, such as those involving unmanned aerial vehicles (UAVs) or drones. In this regard, this work addresses the challenges within a five-dimensional heterogeneous wireless network model, focusing on diverse services such as Big Data Analytics, Video Rendering, and Computer-Aided Design, and the allocation of resources among heterogeneous devices, including UAVs, tethered balloons, and multi-rotors. The resource allocation is facilitated through multiple interfaces like LTE, Wifi, LoRa, and Sigfox, catering to the diverse needs of users operating in aerial Networks. Additionally, this work introduces a novel Intelligent Relaxation using the Penalty Function (IRPF) approach for resource allocation, treating it as an integer programming problem to balance user needs while ensuring affordability. A comparative analysis is conducted between the proposed approach and the traditional branch-and-bound algorithm. In scenarios requiring resource allocation for numerous services based on user demand and device capabilities, the proposed work presents a penalty-based integrality gap solution adept at managing fractional values. The resulting optimization framework is meticulously designed to minimize activation and operating costs while optimizing utility. Additionally, the computing efficiency of the proposed approach is demonstrated by extensive simulations that prove its superiority over the traditional algorithm. Consequently, this research emphasizes the essential role of the proposed model in navigating the intricate challenges of resource allocation in modern drone-centric wireless networks.

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality. Precise diagnosis of CRC plays a crucial role in increasing patient survival rates and formulating effective treatment strategies. Deep learning algorithms have demonstrated remarkable proficiency in the precise categorization of histopathology images. In this article, we introduce a novel deep learning model, termed DeepCon which incorporates the divide-and-conquer principle into the classification task. DeepCon has been methodically conceived to scrutinize the influence of acquired composition on the learning process, with a specific application to the classification of histology images related to CRC. Our model harnesses pre-trained networks to extract features from both the source and target domains, employing a two-stage transfer learning approach encompassing multiple loss functions. Our transfer learning strategy exploits a learned composition of decomposed images to enhance the transferability of extracted features. The efficacy of the proposed model was assessed using a clinically valid dataset of 5000 CRC images. The experimental results reveal that DeepCon when coupled with the Xception network as the backbone model and subjected to extensive fine-tuning, achieved a remarkable accuracy rate of 98.4% and an F1 score of 98.4%.

Abstract In 2021, the International Diabetes Federation (IDF) reported that the prevalence of diabetes in Pakistan was 9.6%, higher than the global average. However, adherence to treatment guidelines, e.g., American Diabetes Association and Pakistan Endocrine Society and prescription patterns for Oral anti-diabetes (OAD), is poorly understood in Pakistan. Therefore, this study aimed to examine the prescribing practices of anti-diabetic medications, an association of lifestyle modification with drugs prescribed, and their effectiveness in preserving ideal glycemic levels in diabetic patients undergoing treatment in tertiary care teaching hospitals in rural and urban Pakistan. In this cross-sectional study, data were collected from prescriptions of outpatient diabetic patients from different rural and urban tertiary care hospitals between October 2021 and February 2022. 388 participants were enrolled in the study for a detailed interview on prescription evaluation and glycemic control. The coinvestigators conducted an interview with the patient and used a pre-validated questionnaire to collect the data. The relationship between following treatment guidelines and clinical and demographic factors was found using chi-square tests for bivariate analyses. The study reported that out of 388, the mean ages of the patients were 48 ± 12.4, and the majority were female. It was observed that 60.1% and 66.5% have uncontrolled fasting and random blood glucose, respectively. The education level of the study participants was also below par to have a complete understanding of the medical condition and self-management therapy. Even though they were taking the right medications—an average prescription regimen included 5.08 medications—52.1% of the studied people had glycated haemoglobin (HbA1c) levels higher than the therapeutic threshold set by the International Diabetes Federation. In this modern era, it was observed that the prescribing trend was still focused on traditional therapeutic options Biguanides, sulfonylureas, and dipeptidyl peptidase-4 inhibitors were prescribed in 64.6% of the patients. A significant association was found between glycemic control and body mass index, adherence to lifestyle modifications, and the number of medications prescribed (p-value

The study attempts to highlight a major cause of learners' detachment and low performance in ESL classrooms at graduation levels in Bahawalpur City, Punjab, Pakistan. In this connection, this study tries to focus on the role of teachers' feedback remarks as a major cause of either instilling or accelerating sense of alienation among ESL learners. This study underpinned exploratory sequential mixed method research design to prove its hypotheses. The qualitative data shows that ESL learners receive evaluative remarks from their teachers in the form of 'face-threatening acts' more than 'face-saving acts' during classroom activities. Resultantly, they experience a sense of alienation from the language-related tasks and try to avoid the classroom situation feeling it a threat. The quantitative analysis shows the average range of sense of alienation experienced by learners which are highest in oral activities, lower in written tasks and lowest in comprehension-based activities. ESL teachers' evaluative feedback either instils or accelerates the sense of alienation among learners during various classroom activities. The type of alienation experienced more was an accelerated sense of alienation. This is why the majority of learners avoid getting engaged in the activities in which they find chances of losing self-image. Keeping the results in view, training sessions on 'Face Wants, Politeness theory, and Speech Acts' are recommended for ESL teachers to enhance their follow-up remarking practices. Moreover, there is a need to develop an anxiety-free classroom atmosphere to strengthen learners' autonomy and linguistic self-concept.

Abstract Dalbergia sissoo Roxb. (Shisham) is a timber-producing species of economic, cultural, and medicinal importance in the Indian subcontinent. In the past few decades, Shisham's dieback disease caused by the fungus Botryodiplodia theobromae has become an evolving issue in the subcontinent endangering its survival. To gain insights into this issue, a standard transcriptome assembly was deployed to assess the response of D. sissoo at the transcriptomic level under the stress of B. theobromae infection. For RNA isolation, the control and infected leaf tissue samples were taken from 1-year-old greenhouse-grown D. sissoo plants after 20 days of stem-base spore inoculation. cDNA synthesis was performed from these freshly isolated RNA samples that were then sent for sequencing. About 18.14 Gb (Giga base) of data was generated using the BGISEQ-500 sequencing platform. In terms of Unigenes, 513,821 were identified after a combined assembly of all samples and then filtering the abundance. The total length of Unigenes, their average length, N50, and GC-content were 310,523,693 bp, 604 bp, 1,101 bp, and 39.95% respectively. The Unigenes were annotated using 7 functional databases i.e., 200,355 (NR: 38.99%), 164,973 (NT: 32.11%), 123,733 (Swissprot: 24.08%), 142,580 (KOG: 27.75%), 139,588 (KEGG: 27.17%), 99,752 (GO: 19.41%), and 137,281 (InterPro: 26.72%). Furthermore, the Transdecoder detected 115,762 CDS. In terms of SSR (Simple Sequence Repeat) markers, 62,863 of them were distributed on 51,508 Unigenes and on the predicted 4673 TF (Transcription Factor) coding Unigenes. A total of 16,018 up- and 19,530 down-regulated Differentially Expressed Genes (DEGs) were also identified. Moreover, the Plant Resistance Genes (PRGs) had a count of 9230. We are hopeful that in the future, these identified Unigenes, SSR markers, DEGs and PRGs will provide the prerequisites for managing Shisham dieback disease, its breeding, and in tree improvement programs.

Abstract Background The impact of wildfire smoke is a growing public health issue, especially for those living with preexisting respiratory conditions. Understanding perceptions and behaviors relevant to the use of individual protective strategies, and how these affect the adoption of these strategies, is critical for the development of future communication and support interventions. This study focused on the use of masks by people living in the Australian community with asthma or chronic obstructive pulmonary disease (COPD). Methods Semi-structured phone interviews were undertaken with people living in the community aged 18 years and over. Participants lived in a bushfire-prone area and reported having been diagnosed with asthma or COPD. Results Twenty interviews were undertaken between July and September 2021. We found that, during wildfire episodes, there was an overwhelming reliance on closing windows and staying inside as a means of mitigating exposure to smoke. There was limited use of masks for this purpose. Even among those who had worn a mask, there was little consideration given to the type of mask or respirator used. Reliance on sensory experiences with smoke was a common prompt to adopting an avoidance behavior. Participants lacked confidence in the information available from air-quality apps and websites, however they were receptive to the idea of using masks in the future. Conclusions Whilst COVID-19 has changed the nature of community mask use over the last couple of years, there is no guarantee that this event will influence an individual’s mask behavior during other events like bushfires. Instead, we must create social support processes for early and appropriate mask use, including the use of air quality monitoring.