Irinotecan dosing and pharmacogenomics: a comprehensive exploration based on UGT1A1 variants and emerging insights.

Irinotecan is a critical anticancer drug used to treat metastatic colorectal cancer and advanced pancreatic ductal adenocarcinoma by obstructing topoisomerase 1; however, it can cause minor-to-severe and life-threatening adverse effects. UDP glucuronosyltransferase family 1 member A1 (UGT1A1) polymorphisms increase the risk of irinotecan-induced neutropenia and diarrhea. Hence, screening for UGT1A1 polymorphisms before irinotecan-based chemotherapy is recommended to minimize toxicity, whereas liposomes offer the potential to deliver irinotecan with fewer side effects in patients with pancreatic ductal adenocarcinoma. This review presents a comprehensive overview of the effects of genotype-guided dosing of irinotecan on UGT1A1*28 and UGT1A1*6 variants, incorporating pharmacogenomic research, optimal regimens for metastatic colorectal and pancreatic cancer treatment using irinotecan, guidelines for toxicity reduction, and an evaluation of the cost-effectiveness of UGT1A1 genotype testing.

Assessment and Exposure Analysis of Trace Metals in Different Age Groups of the Male Population in Southern Punjab, Pakistan.

In developing countries, like Pakistan, the pursuit of urbanization and economic development disrupts the delicate ecosystem, resulting in additional biogeochemical emissions of heavy metals into the human habitat and posing significant health risks. The levels of these trace elements in humans remain unknown in areas at higher risk of pollution in Pakistan. In this investigation, selected trace metals including Copper (Cu), Chromium (Cr), Lead (Pb) Cadmium (Cd), Cobalt (Co), Nickel (Ni), and Arsenic (As) were examined in human hair, urine, and nail samples of different age groups from three major cities (Muzaffargarh, Multan, and Vehari) in Punjab province, Pakistan. The results revealed that the mean concentrations (ppm) of Cr (1.1) and Cu (9.1) in hair was highest in Muzaffargarh. In urine samples, the mean concentrations (µg/L) of Co (93), As (79), Cu (69), Cr (56), Ni (49), Cd (45), and Pb (35) were highest in the Multan region, while As (34) and Cr (26) were highest in Vehari. The mean concentrations (ppm) of Ni (9.2), Cr (5.6), and Pb (2.8), in nail samples were highest in Vehari; however, Multan had the highest Cu (28) concentration (ppm). In urine samples, the concentrations of all the studied metals were within permissible limits except for As (34 µg/L) and Cr (26 µg/L) in Vehari. However, in nail samples, the concentrations of Ni in Multan (8.1 ppm), Muzaffargarh (9 ppm), Vehari (9.2 ppm), and Cd (3.69 ppm) in Muzaffargarh exceeded permissible limits. Overall, the concentrations of metals in urine, nail, and hair samples were higher in adults (39-45 age group). Cr, Cu, and Ni revealed significantly higher concentrations of metals in hair and water in Multan, whereas As in water was significantly (p < 0.001) correlated with urinary As in Multan, indicating that the exposure source was region-specific.

Industrial wastewater irrigation increased higher heavy metals uptake and expansins, metacaspases, and cystatin genes expression in Parthenium and maize.

Industrial wastewater irrigation of agricultural crops can cause a lot of environmental and health problems in developing countries due to heavy metals deposition in agricultural soils as well as edible plant consumption by human beings. Therefore, this study was conducted to find out the heavy metals concentration in industrial wastewater and soil irrigated with that wastewater. In addition, the aim was to determine the impact of industrial wastewater irrigation on Parthenium hysterophorus and Zea mays genes involved in growth improvement and inhibition. For this purpose, plant samples from agriculture fields irrigated with wastewater from Hattar Industrial Estate (HIE) of Haripur, Pakistan, and control plants from non-contaminated soil irrigated with tape water were collected after 15 and 45 days of germination. Heavy metals concentration in the collected plant samples, wastewater, and soil was determined. The results revealed that the soil of the sample collection site was predominantly contaminated with Cr, Pb, Ni, Cu, Co, Zn, and Cd up to the concentrations of 38.98, 21.14, 46.01, 155.73, 12.50, 68.50, and 7.01 mg/kg, respectively. The concentrations of these heavy metals were found to surpass the permissible limit in normal agricultural soil. Expansins, cystatins (plant growth enhancers), and metacaspases (plant growth inhibitor) gene expression were studied through reverse transcription polymerase chain reaction. The results showed that the expression of these genes was higher in samples collected from wastewater-irrigated soils as compared to control. The expression of these genes was observed in 45 days old samples, 15 days old samples, and control. Taken together, this study suggests the use of Parthenium and maize for phytoremediation and that they should not be used for eating purposes if irrigated with industrial wastewater.

Targeting Melanoma with a phytochemical pool: Tailing Makisterone C.

BACKGROUND AND OBJECTIVE: According to World Health Organization, melanoma claims the lives of about 48000 people worldwide each year. The purpose of this study was to identify potential phytochemical pool from Diplazium esculentum against proteins that contribute to melanoma development. METHODS: The research was carried to locate potentially bioactive molecules and conduct a theoretical analysis of active ingredients from DE to impact melanoma. Network pharmacology, pharmacokinetics, protein network interaction, gene enrichment, survival, and infiltration analysis were conducted. Furthermore, molecular docking and molecular dynamics simulation was carried out for makisterone C-MAPK1, MAPK3, and AKT1 complexes. RESULTS: The potential phytochemical pool were identified (stigmast-5-en-3-ol, esculentic acid, rutin, and makisterone C) and based on network pharmacology and molecular docking studies, makisterone-C was proposed to be the most promising ingredient. Furthermore, the investigation revealed 14 genes as critical "hubs" involved in combating melanoma that are manipulated by the above-mentioned 4 active ingredients and modulate multiple signaling in melanoma development. CONCLUSION: This study insights into the potential anti-melanoma effects of phytochemical pool from Diplazium esculentum using network pharmacology analysis, molecular docking, and simulation tailing makisterone C as a lead moiety and suggests the need for makisterone C further evaluation in intervening melanoma progression.

mAb therapy controls CNS-resident lyssavirus infection via a CD4 T cell-dependent mechanism.

Infections with rabies virus (RABV) and related lyssaviruses are uniformly fatal once virus accesses the central nervous system (CNS) and causes disease signs. Current immunotherapies are thus focused on the early, pre-symptomatic stage of disease, with the goal of peripheral neutralization of virus to prevent CNS infection. Here, we evaluated the therapeutic efficacy of F11, an anti-lyssavirus human monoclonal antibody (mAb), on established lyssavirus infections. We show that a single dose of F11 limits viral load in the brain and reverses disease signs following infection with a lethal dose of lyssavirus, even when administered after initiation of robust virus replication in the CNS. Importantly, we found that F11-dependent neutralization is not sufficient to protect animals from mortality, and a CD4 T cell-dependent adaptive immune response is required for successful control of infection. F11 significantly changes the spectrum of leukocyte populations in the brain, and the FcRγ-binding function of F11 contributes to therapeutic efficacy. Thus, mAb therapy can drive potent neutralization-independent T cell-mediated effects, even against an established CNS infection by a lethal neurotropic virus.

Internet addiction and its relationship with attention deficit hyperactivity disorder (ADHD) symptoms, anxiety and stress among university students in Malaysia.

BACKGROUND AND AIMS: There is growing evidence on the contribution of psychological factors to internet addiction; yet it remains inconsistent and deserves further exploration. The aim of this study was to determine the relationship between the psychological symptoms (Attention Deficit Hyperactivity Disorder (ADHD) symptoms, stress, depression, anxiety and loneliness) and internet addiction (IA) among the university students in Malaysia. MATERIALS AND METHODS: A total of 480 students from different faculties in a Malaysian public university participated in this study. They were selected by simple random sampling method. They completed self-administered questionnaires including the Malay Version of Internet Addiction Test (MVIAT)) to measure internet addiction and Adult Self-Report Scale (ASRS) Symptom Checklist, Depression Anxiety Stress Scales (DASS) and UCLA Loneliness Scale (Version 3) to assess for ADHD symptoms, depression, anxiety, stress, and loneliness respectively. RESULTS: The prevalence of IA among university students was 33.33% (n = 160). The respondents' mean age was 21.01 ± 1.29 years old and they were predominantly females (73.1%) and Malays (59.4%). Binary logistic regression showed that gender (p = 0.002; OR = 0.463, CI = 0.284-0.754), ADHD inattention (p = 0.003; OR = 2.063, CI = 1.273-3.345), ADHD hyperactivity (p<0.0001; OR = 2.427, CI = 1.495-3.939), stress (p = 0.048; OR = 1.795, CI = 1.004-3.210) and loneliness (p = 0.022; OR = 1.741, CI = 1.084-2.794) were significantly associated with IA. CONCLUSION: A third of university students had IA. In addition, we found that those who were at risk of IA were males, with ADHD symptoms of inattention and hyperactivity, who reported stress and loneliness. Preventive strategy to curb internet addiction and its negative sequelae may consider these factors in its development and implementation.

Gender Differences Associated with Hyper-Inflammatory Conditions in COVID-19 Patients.

COVID-19 has been associated with various hyper-inflammatory conditions (HICs) such as macrophage activation, hematological dysfunction, cytokinaemia, coagulopathy, and liver inflammation. However, it is not clear if the differences in the disease severity and mortality shown by male and female COVID-19 patients are associated with these HICs. Here, we review the literature and present supporting laboratory data on the gender differences associated with various HICs in COVID-19 patients. We measured plasma/serum levels of various HIC specific clinical markers in severe male (N=132) and severe female (N=78) COVID-19 patients. The result revealed that all clinical markers were highly elevated above the normal in both male and female COVID-19 patients. However, a comparison of AUROC (area under the receiving operative characteristics) of specific clinical markers revealed that elevation in serum ferritin (marker for macrophage activation), and neutrophil to lymphocyte (N/L) ration (marker for hematological dysfunction) was much higher in male compared to the female COVD-19 patients. Further, univariate regression analyses revealed that male COVID-19 patients had two times higher risks than female patients for developing macrophage activation (OR 2.36, P=0.004)), hematological dysfunctions (OR 2.23, P=0.01), coagulopathy (OR 2.10, P=0.01), and cytokinaemia (OR 2.31, P=0.01). Similar results were obtained in bivariate analyses. Survival curve analysis showed that male COVID-19 patients had relatively short survival duration than female COVID-19 patients (hazard ratio 2.0, 95% CI 1.3-3.7, P=0.01). The above findings suggest that the high mortality rate in male COVID-19 patients compared to the female could be due to higher prevalence and severity of various HICs.

Correlation of FGF-23 With Biochemical Markers and Bone Density in Chronic Kidney Disease-Bone Mineral Density Disorder.

Aim The purpose of this study was to determine the relationship between biochemical markers such as serum calcium (Ca), phosphorus (P), intact parathyroid hormone (iPTH), 25(OH) vitamin D, and fibroblast growth factor 23 (FGF23) in our study group, as well as to correlate dual-energy X-ray absorptiometry (DEXA) findings with these biochemical markers. Methodology  An eligible group of 50 chronic hemodialysis (HD) patients, age 18 and older, who have undergone HD two times a week for at least six months participated in this retrospective cross-sectional study. We compared serum FGF23, intact parathyroid hormone (iPTH), 25(OH) vitamin D, calcium, phosphorus, and dual-energy X-ray absorptiometry scan showing bone mineral density disorder (BMD) around the femoral neck, distal radius, and lumbar spine. Human FGF23 Enzyme Linked Immuno Sorbent Assay (ELISA) Kit PicoKine® (Catalog # EK0759; Boster Biological Technology, Pleasanton, CA) was used in the optimum moisture content (OMC) lab to measure FGF23 levels. For the analysis of associations with various studied variables, the levels of FGF23 were split into two groups, which were high (group 1, FGF23 50 to 500 pg/ml), that is, up to 10 times the normal levels and extremely high (group 2, FGF23 > 500 pg/ml) FGF23 levels. All the tests were conducted for routine examination where the data obtained was analyzed in this research project.  Results The mean age of patients was 39.18 ±12.84 years, of whom 35 (70%) were males and 15 (30%) were females. For the entire cohort, serum PTH levels were consistently high, and vitamin D levels were low. FGF23 levels were high in the whole cohort. The average iPTH concentration was 304.20 ± 113.18 pg/ml, while the average 25(OH) vitamin D concentration was 19.68±7.49 ng/ml. The mean FGF23 levels were 1877.36±1378.67 pg./ml. The mean calcium value was 8.23±1.05 mg /dl and the mean phosphate of 6.56±2.28 mg /dl. In the whole cohort, FGF23 showed a negative correlation with vitamin D and a positive correlation with PTH, but not statistically significant. Extremely high FGF23 levels were associated with lower bone density compared to high FGF23 values. Considering that in the whole cohort of patients, only nine had high FGF-23 and the rest of 41 patients had extremely high FGF23, we could not ascertain differences in PTH, calcium, phosphorus, and 25(OH) vitamin D levels between the two groups. The average length of time on dialysis was eight months, and there was no link between FGF-23 levels and the length of time on dialysis. Conclusion Bone demineralization and biochemical abnormalities are a hallmark in chronic kidney disease (CKD) patients. Abnormalities in serum phosphate, parathyroid hormone, calcium, and 25(OH) vitamin D play critical roles in the development of BMD in CKD patients. With the discovery of FGF-23 as a biomarker that is increased early in CKD patients, new questions arise about the effects and actions of FGF-23 in controlling bone demineralization and other biochemical markers. Our study found no statistically significant correlation to suggest an effect of FGF-23 on these parameters. But the findings need to be looked at more in prospective, controlled research, especially to find out if therapies that successfully target FGF-23 can make a big difference in how people with CKD feel about their health.

Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models.

Antibiotic-resistant bacteria and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that seriously threaten public health and ecosystems. Machine learning (ML) prediction models have been applied to predict ARGs in beach waters. However, the existing studies were conducted at a single location and had low prediction performance. Moreover, ML models are "black boxes" that do not reveal their predictions' internal nuances and mechanisms. This lack of transparency and trust can result in serious consequences when using these models in high-stakes decisions. In this study, we developed a gradient boosted regression tree based (GBRT) ML model and then described its behavior using six explainable artificial intelligence (XAI) model-agnostic explanation methods. We used hydro-meteorological and qPCR data from the beaches in South Korea and Pakistan and developed ML prediction models for aac (6'-lb-cr), sul1, and tetX with 10-fold time-blocked cross-validation performances of 4.9, 2.06 and 4.4 root mean squared logarithmic error, respectively. We then analyzed the local and global behavior of the developed ML model using four interpretation methods. The developed ML models showed that water temperature, precipitation and tide are the most important predictors for prediction of ARGs at recreational beaches. We show that the model-agnostic interpretation methods not only explain the behavior of the ML model but also provide insights into the behavior of the ML model under new unseen conditions. Moreover, these post-processing techniques can be a debugging tool for ML-based modeling.

Impact of the COVID-19 pandemic on a respiratory physiology department and the patient's perception of rapid service change.

BACKGROUND: Originating as a cluster of unexplained cases of pneumonia in Wuhan, China, a novel coronavirus disease, officially named as COVID-19 by WHO, has now reached a pandemic level. In the wake of this global health crisis, stringent public health measures were implemented to curtail the spread of COVID-19. At a local level, the University Hospitals of North Midlands National Health Service Trust suspended all elective and outpatient activity, primarily to address the current potential implications of the COVID-19 outbreak. Within respiratory physiology, all but urgent and emergency work was suspended. METHODS: In June 2020, the service commenced its restoration/recovery plan, which was based on national and international guidelines to ensure safe practice for patients and staff alike. The plan was a roadmap developed to upscale the respiratory physiology service to deliver urgent and routine care and to assist the service to undertake the essential task of managing the patient backlog as a consequence of the interruption of service. Patient concerns and anxieties due to the pandemic was a key aspect of the restoration/recovery plan. The service developed numerous initiatives along with a questionnaire to assess patient experience following attendance for investigations or assessment. RESULTS: The questionnaire confirmed that the initiatives put in place as part of the restoration/recovery plan achieve high levels of satisfaction in terms of communication, interaction within the service, professionalism and importantly patient safety. CONCLUSION: COVID-19 had a significant impact on routine clinical care and out-patient activity. This brought about significant change in service delivery that required a strict regimen to ensure COVID-19 free status and minimise cross-contamination of service users. The systems and processes introduced demonstrated positive responses and confirmed the objective of patient safety, which translated to the service users.

A Deterministic Model for Determining Degree of Friendship Based on Mutual Likings and Recommendations on OTT Platforms.

In recent years, the application of various recommendation algorithms on over-the-top (OTT) platforms such as Amazon Prime and Netflix has been explored, but the existing recommendation systems are less effective because either they fail to take an advantage of exploiting the inherent user relationship or they are not capable of precisely defining the user relationship. On such platforms, users generally express their preferences for movies and TV shows and also give ratings to them. For a recommendation system to be effective, it is important to establish an accurate and precise relationship between the users. Hence, there is a scope of research for effective recommendation systems that can define a relationship between users and then use the relationship to enhance the user experiences. In this research article, we have presented a hybrid recommendation system that determines the degree of friendship among the viewers based on mutual liking and recommendations on OTT platforms. The proposed enhanced model is an effective recommendation model for determining the degree of friendship among viewers with improved user experience.

A Novel Memory and Time-Efficient ALPR System Based on YOLOv5.

With the rapid development of deep learning techniques, new innovative license plate recognition systems have gained considerable attention from researchers all over the world. These systems have numerous applications, such as law enforcement, parking lot management, toll terminals, traffic regulation, etc. At present, most of these systems rely heavily on high-end computing resources. This paper proposes a novel memory and time-efficient automatic license plate recognition (ALPR) system developed using YOLOv5. This approach is ideal for IoT devices that usually have less memory and processing power. Our approach incorporates two stages, i.e., using a custom transfer learned model for license plate detection and an LSTM-based OCR engine for recognition. The dataset that we used for this research was our dataset consisting of images from the Google open images dataset and the Indian License plate dataset. Along with training YOLOv5 models, we also trained YOLOv4 models on the same dataset to illustrate the size and performance-wise comparison. Our proposed ALPR system results in a 14 megabytes model with a mean average precision of 87.2% and 4.8 ms testing time on still images using Nvidia T4 GPU. The complete system with detection and recognition on the other hand takes about 85 milliseconds.

Mercury fractionation, bioavailability, and the major factors predicting its transfer and accumulation in soil-wheat systems.

Soil mercury (Hg) and its bioaccumulation in food crops have attracted widespread concerns globally due to its harmful effects on biota. However, soil mercury fractionation, bioavailability, and the major factors predicting its transfer and accumulation in soil-wheat-systems have not been thoroughly explored. Twenty-one (21) soil samples collected throughout China with a wide spectrum of physico-chemical characteristics were contaminated with HgCl2 and winter wheat (Triticum aestivum L.) was grown on the soils in a greenhouse pot-culture experiment for 180 days. A four-step sequential extraction was used segregating soil Hg into water-soluble (F1, 0.21 %), exchangeable (F2, 0.07 %), organically bound (F3, 16.40 %), and residual fractions (F4, 83.32 %). Step-wise multiple linear regression (SMLR) and path analysis (PA) were used to develop a prediction model and identify the major controlling factors of soil-wheat Hg transference. The SMLR results revealed that wheat Hg in leaves, husk, and grain was positively correlated with soil total and available Hg, and crystalline manganese (Cryst-Mn), while negatively correlated with soil pH, amorphous manganese (Amor-Mn) and crystalline aluminium (Cryst-Al). Bioconcentration factor (BCF) values were significantly higher in acidic soils (highest 0.05), with phytotoxic effects in some soils, as compared to alkaline soils (lowest 0.006). Furthermore, wheat grain Hg was significantly correlated with total (R2 = 0.25), water-soluble (R2 = 0.54) and NH4Ac-extractable Hg (R2 = 0.43) while also had a good correlation with soil pH (R2 = -0.20). In conclusion, the soil total and available Hg (water-soluble + exchangeable fraction), pH, organic matter, and Amor-Mn are the most important soil variables that support Hg uptake in the wheat plants, which benefit managing Hg-enriched agricultural soils for safe wheat production.

Carvacrol protects against carbonyl osmolyte-induced structural modifications and aggregation to serum albumin: Insights from physicochemical and molecular interaction studies.

The robust use of osmolytes (i.e., polyols and sugars) in the key therapeutic regimens/formulations has questioned their impact beyond the stability of therapeutic proteins as these osmolytes trigger structural alterations into proteins including misfolding and subsequent aggregation into amyloid fibrils. Therefore, the current study is the first to delineate the inhibitory effect of carvacrol (CRV) on the carbonyl osmolyte-induced aggregation as well as structural alterations to the bovine serum albumin (BSA) via a set of physicochemical as well as artificial intelligence (AI)-based molecular docking studies. Our initial findings from physicochemical investigations revealed that CRV exhibits substantial protection to BSA under carbonyl osmolyte stress as evident by the compromised hyperchromicity, Schiff's bases, carbonyl and hydroxymethyl furfural content, reduced fluorescent signals, low Rayleigh scattering and prevention of covalent modifications at Lys and Arg residues. The protection against aggregate formation by CRV was further confirmed through the reduced amyloid-specific congo red absorbance as well as fluorescent signals recorded after adding the fibril-specific extrinsic fluorophore probes (i.e., ThT and ANS). The AI-based molecular docking analysis further revealed that CRV (ΔG: -4.96 kcal/mol) competes with d-fructose (ΔG: -4.40 kcal/mol) to mask the Lys and Arg residues to restrict the osmolyte-mediated protein modifications. In conclusion, CRV exhibits substantial protective impact against carbonyl osmolyte-induced structural alterations and protein misfolding and aggregation.

Retesting the EKC hypothesis through transmission of the ARMEY curve model: an alternative composite model approach with theory and policy implications for NAFTA countries.

We investigate the validity of the environmental Kuznets curve (EKC) hypothesis for the NAFTA countries. In this investigation, we approach this hypothesis from a different methodology and propose employing the ARMEY curve hypothesis since the mathematical-functional propositions of both hypotheses were constructed on the same inverted U-shaped relationships. Thus, for the first time, it can be interpreted that the EKC hypothesis is empirically tested through a transmission mechanism of the ARMEY curve hypothesis in a single composite model. Therefore, this approach makes our study different from all empirical studies in the relevant literature. We apply the Augmented Mean Group (AMG) estimator to this aim. Empirical findings indicate that the ARMEY curve hypothesis was verified only for the USA. However, this new approach proposed in this study cannot test the EKC hypothesis through the ARMEY curve model for any NAFTA country since this approach requires verification of the ARMEY curve hypothesis and a significant composite model for the same NAFTA country. If our composite model was significant, it might make it possible to numerically determine a maximum real GDP per capita level that would minimize or maximize CO2 emission levels for the USA. Therefore, this study introduces-proposes this new methodology as an alternative way of testing the EKC hypothesis in the relevant literature for future empirical studies.

Phytoavailability and transfer of mercury in soil-pepper system: Influencing factors, fate, and predictive approach for effective management of metal-impacted spiked soils.

Mercury (Hg) contamination and accumulation in food crops is a global threat posing potential health risk to humans. However, Hg phytoavailability in soil-pepper system and its influencing factors largely remain unknown. In this study, a greenhouse pot experiment was conducted to grow peppers using 21 Chinese agricultural soils with varied soil properties and aged Hg levels. Mercury concentration in pepper leaves and fruits ranged from 0.021 to 0.057 mg kg-1 and 0.005-0.022 mg kg-1 respectively, while fruit Hg content in three soils (Anhui, Hubei, Beijing) exceeded the safety limit. Fruit Hg concentration was better positively correlated with soil Mg(NO3)2-extractable Hg content (r = 0.7, P < 0.0001) than soil total Hg content (r = 0.45, P < 0.0001). Highest bioconcentration factor (BCF, ratio of Hg plant to Hg soil) yielded in acidic soils, while the lowest BCF occurred in alkaline soils. Path analysis indicated available-Hg (R2 = 0.40) and total-Hg (R2 = 0.40) had direct positive effects on the pepper fruit Hg concentration, while direct negative effects including pH (R2 = -0.86), organic matter (R2 = -0.7), crystalline-Fe (R2 = -0.68). Those agreed with the stepwise multiple linear regression analysis which yielded a regression predictive model (R2 = 0.73, P < 0.0001). Soil available-Hg, total-Hg, pH, organic matter and crystalline-Fe & Mn were the most influencing factors of Hg phytoavailability. These results provide new insights into the phytoavailability of Hg in soil-pepper system, thus facilitating the management of pepper cultivation in Hg-enriched soils.

Using an asymmetrical technique to assess the impacts of CO2 emissions on agricultural fruits in Pakistan.

Human activities such as deforestation and cultivation contribute to the accumulation of carbon dioxide in the environment. Methane is emitted by energy exploration, coal mining, natural gas spills, waste, and waste dumps. Methane generated by such greenhouse gases has significantly contributed to the climate change and global warming. However, the most significant contributor to climate change and global warming is the use of fossil fuels. These fuels contribute to ozone depletion and global warming by emitting greenhouse gases into the atmosphere. The current study key objective was to determine the CO2 emission effect to key fruit production in Pakistan by taking time series annual data varies from 1970 to 2019. A non-linear autoregressive distributed lag model (NARDL) was employed to check the variables linkages. The consequences of short- and long-run estimates expose that the positive and adverse shocks of citrus fruit create expressively to upsurge the CO2 emission. Similarly, the positive and negative shocks of mango fruit expose an adverse interaction to CO2 emission. The positive shock of apple fruit has constructive but negative shock expose and adverse linkage to CO2 emission. Further, banana fruit also exposes a negative but constructive via positive shock linkage to CO2 emission. Moving towards the apricot fruit production that exposed a constructive linkage via positive and negative shocks to CO2 emission. The almond fruit productivity via positive and negative shocks exposed an adverse relation to carbon dioxide emission. Grape fruit via positive shock shows a construct, but negative shock exposed an adverse association to carbon emission in Pakistan. Finally the guava fruit production exposed a construct linkage to CO2 emission via positive and negative shocks. Since agricultural activities and CO2 emissions are essential to resolving the pollution problem, a series of practicable steps must be taken by the Pakistani authorities to tackle this issue.

Soil conditioners improve rhizodegradation of aged petroleum hydrocarbons and enhance the growth of Lolium multiflorum.

Bioremediation and phytoremediation have demonstrated potential for decontamination of petroleum hydrocarbon-impacted soils. The total petroleum hydrocarbons (TPHs) are known to induce phytotoxicity, reduce water retention in soil, associate hydrophobic nature and contaminants' in situ heterogeneous distribution, limit soil nutrient release and reduce soil aeration and compaction. The ageing of TPHs in contaminated soils further hinders the degradation process. Soil amendments can promote plant growth and enhance the TPH removal from contaminated aged soil. In the present experiment, remediation of TPH-contaminated aged soil was performed by Italian ryegrass, with compost (COM, 5%), biochar (BC, 5%) and immobilized microorganisms' technique (IMT). Results revealed that significantly highest hydrocarbon removal (40%) was noted in mixed amendments (MAA) which contained BC + COM + IMT, followed by COM (36%), compared to vegetative control and other treatments. The higher TPH removal in aged soil corresponds with the stimulated rhizospheric effects, as evidenced by higher root biomass (85-159% increase), and bacterial count compared to NA control. Phyto-stimulants actions of biochar and IMT improved seed germination of Italian ryegrass. The compost co-amendment with other treatments showed improvement in plant physiological status. These results suggested that plant growth and TPH removal from aged, contaminated soils using BC, COM and IMT can improve bioremediation efficiency.

Exploring the dynamic interaction of CO2 emission on population growth, foreign investment, and renewable energy by employing ARDL bounds testing approach.

Greenhouse gases are considered an immense threat for the environment and humanity on the planet, and also cause the climatic change. The present analysis key aim was to explore the effect of CO2 emission on foreign investment, renewable energy utilization, and population growth in Pakistan. The ARDL bounds testing technique was applied to investigate the variables' interaction via short- and long-run analysis. Furthermore, pairwise Granger causality method was also utilized to check the causal relation amid the study variables. Outcomes expose that CO2 emission has an adverse interaction with renewable energy with probability value (0.5497), while the variable foreign investment and population growth exposed a constructive association with carbon dioxide emission with probability values (0.3548) and (0.4217) consistently. Similarly, the results through long-run analysis expose that CO2 emission has an adverse influence to renewable energy usage with P-value (0.4646). Moreover, the results also uncovered that foreign investment and population growth has positive interaction with CO2 emission and having probability values (0.3577) and (0.5715). Solid steps are required from the Pakistani government regarding the demonization of CO2 emission in order to upsurge the economic progress.

NF-κB-induced R-loop accumulation and DNA damage select for nucleotide excision repair deficiencies in adult T cell leukemia.

Constitutive NF-κB activation (NF-κBCA) confers survival and proliferation advantages to cancer cells and frequently occurs in T/B cell malignancies including adult T cell leukemia (ATL) caused by human T-cell leukemia virus type 1 (HTLV-1). Counterintuitively, NF-κBCA by the HTLV-1 transactivator/oncoprotein Tax induces a senescence response, and HTLV-1 infections in culture mostly result in senescence or cell-cycle arrest due to NF-κBCA How NF-κBCA induces senescence, and how ATL cells maintain NF-κBCA and avert senescence, remain unclear. Here we report that NF-κBCA by Tax increases R-loop accumulation and DNA double-strand breaks, leading to senescence. R-loop reduction via RNase H1 overexpression, and short hairpin RNA silencing of two transcription-coupled nucleotide excision repair (TC-NER) endonucleases that are critical for R-loop excision-Xeroderma pigmentosum F (XPF) and XPG-attenuate Tax senescence, enabling HTLV-1-infected cells to proliferate. Our data indicate that ATL cells are often deficient in XPF, XPG, or both and are hypersensitive to ultraviolet irradiation. This TC-NER deficiency is found in all ATL types. Finally, ATL cells accumulate R-loops in abundance. Thus, TC-NER deficits are positively selected during HTLV-1 infection because they facilitate the outgrowth of infected cells initially and aid the proliferation of ATL cells with NF-κBCA later. We suggest that TC-NER deficits and excess R-loop accumulation represent specific vulnerabilities that may be targeted for ATL treatment.