Genome editing for improvement of biotic and abiotic stress tolerance in cereals.

Global agricultural production must quadruple by 2050 to fulfil the needs of a growing global population, but climate change exacerbates the difficulty. Cereals are a very important source of food for the world population. Improved cultivars are needed, with better resistance to abiotic stresses like drought, salt, and increasing temperatures, and resilience to biotic stressors like bacterial and fungal infections, and pest infestation. A popular, versatile, and helpful method for functional genomics and crop improvement is genome editing. Rapidly developing genome editing techniques including clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) are very important. This review focuses on how CRISPR/Cas9 genome editing might enhance cereals' agronomic qualities in the face of climate change, providing important insights for future applications. Genome editing efforts should focus on improving characteristics that confer tolerance to conditions exacerbated by climate change (e.g. drought, salt, rising temperatures). Improved water usage efficiency, salt tolerance, and heat stress resilience are all desirable characteristics. Cultivars that are more resilient to insect infestations and a wide range of biotic stressors, such as bacterial and fungal diseases, should be created. Genome editing can precisely target genes linked to disease resistance pathways to strengthen cereals' natural defensive systems.

Remote sensing analysis of spatiotemporal impacts of anthropogenic influence on mountain landscape ecology in Pir Chinasi national park.

Mountain landscapes can be fragmented due to various human activities such as tourism, road construction, urbanization, and agriculture. It can also be due to natural factors such as flash floods, glacial lake outbursts, land sliding, and climate change such as rising temperatures, heavy rains, or drought.The study's objective was to analyze the mountain landscape ecology of Pir Chinasi National Park under anthropogenic influence and investigate the impact of anthropogenic activities on the vegetation. This study observed spatiotemporal changes in vegetation due to human activities and associated climate change for the past 25 years (1995-2020) around Pir Chinasi National Park, Muzaffrabad, Pakistan. A structured questionnaire was distributed to 200 residents to evaluate their perceptions of land use and its effects on local vegetation. The findings reveal that 60% of respondents perceived spatiotemporal pressure on the park. On the other hand, the Landsat-oriented Normalized Difference Vegetation Index (NDVI) was utilized for the less than 10% cloud-covered images of Landsat 5, 7, and 8 to investigate the vegetation degradation trends of the study area. During the entire study period, the mean maximum NDVI was approximately 0.28 in 1995, whereas the mean minimum NDVI was - 2.8 in 2010. QGIS 3.8.2 was used for the data presentation. The impact of temperature on vegetation was also investigated for the study period and increasing temperature trends were observed. The study found that 10.81% (1469.08 km2) of the area experienced substantial deterioration, while 23.57% (3202.39 km2) experienced minor degradation. The total area of degraded lands was 34.38% (or 4671.47 km2). A marginal improvement in plant cover was observed in 24.88% of the regions, while 9.69% of the regions experienced a major improvement. According to the NDVI-Rainfall relationships, the area was found to be significantly impacted by human pressures and activities (r ≤ 0.50) driving vegetation changes covering 24.67% of the total area (3352.03 km2). The area under the influence of climatic variability and change (r ≥ 0.50 ≥ 0.90) accounted for 55.84% (7587.26 km2), and the area under both climatic and human stressors (r ≥ 0.50 < 0.70) was 64%. Sustainable land management practices of conservation tillage, integrated pest management, and agroforestry help preserve soil health, water quality, and biodiversity while reducing erosion, pollution, and the degradation of natural resources. landscape restoration projects of reforestation, wetland restoration, soil erosion control, and the removal of invasive species are essential to achieve land degradation neutrality at the watershed scale.

Assessing the diagnostic accuracy of postnatal clinical scoring methods and foot length measurement for estimating gestational age and birthweight of newborns in low- and middle-income countries: a systematic review and meta-analysis.

BACKGROUND: This study aimed to update systematic reviews and meta-analyses on the diagnostic accuracy of postnatal clinical scoring (PCS) methods and foot length (FL) measurement for assessing gestational age (GA) and birth weight in low-income and middle-income countries (LMICs). In addition, the quality of reference standards, including antenatal ultrasound (A-US), last menstrual period (LMP), PCS and newborn weighing scales, was also evaluated. METHODS: Studies from LMICs published between January 2000 and February 2024 were searched, using databases such as PubMed, Web of Science, Cochrane Library, CINAHL and Scopus. Studies that compared PCS and/or FL with LMP and/or A-US to estimate GA or used calibrated newborn weighing scales for birthweight estimation were included. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-II tool and evaluated the quality of the reference standards. When sufficient data were available, pooled estimates were calculated using random-effects models. RESULTS: A total of 50 studies were included. A-US was a reasonable tool for GA assessment if conducted by physicians using fetal biometry and the Hadlock method for GA estimation. LMP was reasonable when women had regular cycles, knew their LMP, were not using contraceptives and LMP data were collected by healthcare providers. When A-US was used as the reference standard, PCS methods estimated GA with a precision of ±2.8 to ±3.2 weeks. FL measurement <7.5 cm showed a pooled sensitivity of 76.2% and specificity of 36.6% for identifying preterm birth. FL measurement ≤7.6 cm had a pooled sensitivity of 78.6% and specificity of 65.7% for identifying low birth weight (LBW). High heterogeneity across studies was observed. CONCLUSION: This systematic review and meta-analysis highlights significant variability and methodological inconsistencies in using PCS methods and FL measurement for estimating GA and LBW in LMICs. The observed high heterogeneity across studies suggests a cautious interpretation of the results. PROSPERO REGISTRATION NUMBER: CRD42020209455.

Factor Xa inhibitors versus low-molecular-weight heparin for preventing coagulopathy following COVID-19: a systematic review and meta-analysis of randomized controlled trials.

Background: Hospitalized patients with COVID-19 have shown a significant occurrence of thromboembolism and a heightened risk of death. It remains unclear whether factor Xa inhibitors are superior to enoxaparin in this context. Hence, there is a need for a direct comparison to assess the preventive effects and safety of factor Xa inhibitors versus enoxaparin in hospitalized COVID-19 patients. Methods: MEDLINE, Embase, and Cochrane Central databases were searched for randomized controlled trials (RCTs) or retrospective studies that compared the effectiveness or safety of factor Xa inhibitors and enoxaparin in preventing thromboembolism in hospitalized patients with COVID-19. Embolic incidence, incidence of bleeding, and all-cause mortality were among the outcomes of interest. Mantel-Haenszel weighted random-effects model was used to calculate relative risks (RRs) with 95 percent CIs. Results: The analysis included six RCTs and two retrospective studies containing 4048 patients. Meta-analysis showed a statistically significant reduction among patients on factor Xa inhibitors compared with low-molecular-weight heparin (LMWH) in the embolic incidence [risk ratio (RR) 0.64 (95%, CI 0.42, 0.98); P=0.04, I2=12%]. Upon subgroup analysis by type of study design, no significant reductions were noted in patients on factor Xa inhibitors in RCTs (RR: 0.62; 95% CI: 0.33-1.17; P=0.14) or observational studies (RR: 0.53; 95% CI: 0.23-1.26; P=0.15) when compared with enoxaparin Factor Xa inhibitors were not significantly associated with incidence of bleeding [RR 0.76 (95% CI 0.36, 1.61); P=0.47, I2=0%] or all-cause mortality (RR: 0.81; 95% CI: 0.48-1.36; P=0.43). Consistent results were obtained upon subgroup analysis by the type of study design. Conclusion: Factor Xa inhibitors are more effective than enoxaparin in preventing thromboembolism among patients with COVID-19 who are not acutely ill and are hospitalized. Additional rigorous RCTs comparing factor Xa inhibitors with enoxaparin are warranted.

The potential impact of renin-angiotensin system inhibitors on cancer survival and recurrence: A systemic review and meta-analysis.

Renin-angiotensin-system inhibitors (RASi), specifically angiotensin-converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARBs), are widely used anti-hypertensives. Their impact on the prognostic outcomes among cancer patients has been subject to scrutiny and debate. The aim of this study is to evaluate the effect of RASi on survival in cancer patients. We systematically searched PubMed, Web of Science, Embase and Cochrane Library for relevant studies published until April 1st, 2022. All the studies, interventional or observational, which examined effects of ARBs and ACEi on cancer prognosis compared to a control group and reported the survival outcomes and Hazards Ratios were included in the analysis. From each study, pooled hazard ratios (HR) with corresponding 95% confidence intervals (95% CI) were identified and collected. Subgroup analysis was conducted to investigate heterogeneity. Sixty-one studies were included in this meta-analysis. Data of 343,283 participants were used in the study. It was found that RASi improved overall survival (OS) (HR=0.88; 95% CI: 0.82-0.93; P<0.0001), progression free survival (PFS) (HR=0.72; 95% CI: 0.65-0.79; P<0.00001), disease specific survival (DSS) (HR=0.86; 95% CI: 0.71-1.04; P=0.03), and recurrence free survival (RFS) (HR=0.74; 95% CI: 0.58-0.93; P=0.01) in cancer patients. The effect of RASi on OS varied depending on the type of cancer or type of RASi (ACEi or ARBs), according to subgroup analysis. The usage of RAS inhibitors has a positive impact on survival outcomes and recurrence among cancer patients.

Malnutrition and Its Influence on Sepsis Outcomes in Elderly Patients.

BACKGROUND: Malnutrition is common among the elderly and has significant implications for hospitalization outcomes. This is particularly true for severe illnesses such as sepsis, given age-related physiological changes and comorbidities. OBJECTIVE: This study examined how malnutrition affected hospitalization outcomes in older adults admitted for sepsis. MATERIALS & METHODS:  A prospective cohort study was conducted at Lady Reading Hospital in Peshawar, Pakistan, from January to December 2023, focusing on 390 sepsis patients aged 55 years and older. Data on clinical history, length of stay, mortality rates, comorbidities, and nutritional assessments were collected using standardized forms. After controlling for confounding variables, statistical analysis using SPSS version 23 (IBM Corp., Armonk, NY) examined the relationship between hospitalization outcomes and nutritional status. RESULTS: The research included 390 elderly sepsis patients and showed significant variations in the demographics, comorbidities, and severity of disease between the well-nourished and malnourished groups. Malnourished patients had higher rates of ICU admission (52.82% vs. 29.23%), mechanical ventilation (45.13% vs. 16.41%), mortality (27.18% vs. 14.87%), and 30-day readmission (28.21% vs. 12.82%) as compared to the well-nourished group. They also had longer hospital stays (18.1 days vs. 12.6 days). Malnutrition significantly influenced outcomes, with multivariate analysis indicating it as a predictor of longer stays (ß = 2.8, p < 0.001) and increased mortality risk (OR = 3.2, 95% CI: 1.9-5.4, p < 0.001). CONCLUSION: Malnutrition significantly worsens outcomes for elderly sepsis patients, increasing ICU admissions, ventilation needs, mortality rates, and readmissions, emphasizing the need for proactive nutritional interventions.

Innovative road distress detection (IR-DD): an efficient and scalable deep learning approach.

In the rapidly evolving landscape of transportation infrastructure, the quality and condition of road networks play a pivotal role in societal progress and economic growth. In the realm of road distress detection, traditional methods have long grappled with manual intervention and high costs, requiring trained observers for time-consuming and expensive data collection processes. The limitations of these approaches are compounded by challenges in adapting to diverse road surfaces and handling low-resolution data, particularly in early automated distress survey technologies. This article addresses the critical need for efficient road distress detection, a key component of ensuring safe and reliable transportation systems. Effectively addressing these challenges is crucial for enhancing the efficiency, accuracy, and safety of road distress detection systems. Leveraging advancements in object detection, we introduce the Innovative Road Distress Detection (IR-DD), a novel framework that integrates the YOLOv8 algorithm to enhance the accuracy and real-time capabilities of road distress detection, catering to applications such as smart cities and autonomous vehicles. Our approach incorporates bidirectional feature pyramid network (BiFPN) recursive feature fusion and bidirectional connections to optimize the utilization of multi-scale features, addressing challenges related to information loss and gradients encountered in traditional methods. Comprehensive experimental analysis demonstrates the superior performance, efficiency, and robustness of our integrated approach, positioning it as a cost-effective and compelling alternative to conventional road distress detection methods. Our findings demonstrate the superior performance of our approach compared to other state-of-the-art methods across various evaluation metrics, including precision, recall, F1 score, and mean average precision (mAP) at different intersection over union (IoU) thresholds. Specifically, our method achieves notable results with a precision of 0.666, F1 score of 0.630, mAP@0.5 of 0.650, all while operating at a speed of 86 frames per second (FPS). These outcomes underscore the effectiveness of our approach in real-time road distress detection. This article contributes to the ongoing innovation in object detection techniques, emphasizing the practicality and effectiveness of our proposed solution in advancing the field of road distress detection.

An updated model of shoot apical meristem regulation by ERECTA family and CLAVATA3 signaling pathways in Arabidopsis.

The shoot apical meristem (SAM) gives rise to the aboveground organs of plants. The size of the SAM is relatively constant due to the balance between stem cell replenishment and cell recruitment into new organs. In angiosperms, the transcription factor WUSCHEL (WUS) promotes stem cell proliferation in the central zone of the SAM. WUS forms a negative feedback loop with a signaling pathway activated by CLAVATA3 (CLV3). In the periphery of the SAM, the ERECTA family receptors (ERfs) constrain WUS and CLV3 expression. Here, we show that four ligands of ERfs redundantly inhibit the expression of these two genes. Transcriptome analysis confirmed that WUS and CLV3 are the main targets of ERf signaling and uncovered new ones. Analysis of promoter reporters indicated that the WUS expression domain mostly overlaps with the CLV3 domain and does not shift along the apical-basal axis in clv3 mutants. Our three-dimensional mathematical model captured gene expression distributions at the single-cell level under various perturbed conditions. Based on our findings, CLV3 regulates cellular levels of WUS mostly through autocrine signaling, and ERfs regulate the spatial expression of WUS, preventing its encroachment into the peripheral zone.

Numerical Approximation of a Nonequilibrium Model of Gradient Elution Chromatography Considering Different Functional Relationships between Model Parameters and Solvent Composition.

In this paper, a rigorous theoretical study is conducted to analyze the influence of varying solvent compositions on the retention characteristics of elution profiles within a fixed-bed liquid chromatographic column. In gradient chromatography, the propagation speed of elution profiles is manipulated through a progressive variation in the mobile-phase composition. Consequently, enhanced separation of the mixture components can be achieved together with a reduction in the requisite recycling times for subsequent injections. In other words, both the efficiency and the selectivity of the column can be enhanced. The lumped kinetic model coupled with the convection-diffusion equation for the volume fraction of the solvent is applied to simulate the process. The resulting nonlinear model equations are numerically solved by applying a semidiscrete second-order finite-volume method. The numerical solutions are utilized to quantify the effects of gradient starting and ending times, solvent composition, solvent strength parameters, and gradient slope on the concentration profiles. Additionally, temporal numerical moments are plotted versus the starting and ending times of the gradient, and standard performance criteria are presented for evaluating the process performance. The outcomes of this investigation will contribute to further enhancements in gradient elution chromatography.

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters.

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi2, σ2i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on  paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on 'mean verses stability analysis of GGE biplot', 'Which-won-where' GGE Biplot, 'discriminativeness vs. representativeness' pattern of stability, 'IPCA and WAASB/GY' ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha-1. Discriminativeness vs. representativeness' pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Ductal carcinoma in situ and invasive carcinoma originating in a Fibroadenoma with concurrent benign phyllodes tumor: A case report.

INTRODUCTION AND IMPORTANCE: This case report presents a rare occurrence of multiple bilateral breast fibroadenomas, one evolving into ductal carcinoma in situ (DCIS) and invasive carcinoma, occurring simultaneously with a benign phyllodes tumor in the same breast. The importance of this case lies in emphasizing the crucial need for surveillance in patients with a long history of fibroadenomas and the necessity to investigate any rapid change in the size of fibroadenoma. CASE PRESENTATION: A 35-year-old multiparous female with a 17 year history of bilateral multiple breast lumps presented with recent onset of right breast pain and yellowish nipple discharge. Two lumps in her right breast had demonstrated an increase in size. Examination revealed a significant mass in the retroareolar region of the right breast and another at the 2 o'clock position. Histopathological examination of the biopsy specimens revealed fibroadenoma and benign phyllodes tumor. The patient underwent a bilateral breast lumpectomy. Further histopathological examination revealed ductal carcinoma in situ and invasive carcinoma within a complex fibroadenoma in the right breast and benign phyllodes tumor. Sentinel lymph node biopsy was negative. She had adjuvant radiations and trastuzumab. Regular follow-ups show no recurrence. CLINICAL DISCUSSION: Fibroadenomas are usually benign but rarely undergo malignant change. Quick response to size changes and early detection greatly enhance patient results. CONCLUSION: Ductal carcinoma in situ and invasive breast cancer, a rare malignancy found within a fibroadenoma, necessitates histopathological specimens and immunohistochemical results for accurate diagnosis. Survival rates are significantly enhanced through a multidisciplinary approach.

Unlocking the potential of biochar in the remediation of soils contaminated with heavy metals for sustainable agriculture.

Agricultural soils contaminated with heavy metals (HMs) impose a threat to the environmental and to human health. Amendment with biochar could be an eco-friendly and cost-effective option to decrease HMs in contaminated soil. This paper reviews the application of biochar as a soil amendment to immobilise HMs in contaminated soil. We discuss the technologies of its preparation, their specific properties, and effect on the bioavailability of HMs. Biochar stabilises HMs in contaminated soil, enhance the overall quality of the contaminated soil, and significantly reduce HM uptake by plants, making it an option in soil remediation for HM contamination. Biochar enhances the physical (e.g. bulk density, soil structure, water holding capacity), chemical (e.g. cation exchange capacity, pH, nutrient availability, ion exchange, complexes), and biological properties (e.g. microbial abundance, enzymatic activities) of contaminated soil. Biochar also enhances soil fertility, improves plant growth, and reduces the plant availability of HMs. Various field studies have shown that biochar application reduces the bioavailability of HMs from contaminated soil while increasing crop yield. The review highlights the positive effects of biochar by reducing HM bioavailability in contaminated soils. Future work is recommended to ensure that biochars offer a safe and sustainable solution to remediate soils contaminated with HMs.

Phylogenomic curation of Ovate Family Proteins (OFPs) in the U's Triangle of Brassica L. indicates stress-induced growth modulation.

The Ovate Family Proteins (OFPs) gene family houses a class of proteins that are involved in regulating plant growth and development. To date, there is no report of the simultaneous functional characterization of this gene family in all members of U's Triangle of Brassica. Here, we retrieved a combined total of 256 OFP protein sequences and analyzed their chromosomal localization, gene structure, conserved protein motif domains, and the pattern of cis-acting regulatory elements. The abundance of light-responsive elements like G-box, MRE, and GT1 motif suggests that OFPs are sensitive to the stimuli of light. The protein-protein interaction network analysis revealed that OFP05 and its orthologous genes were involved in regulating the process of transcriptional repression through their interaction with homeodomain transcription factors like KNAT and BLH. The presence of domains like DNA binding 2 and its superfamily speculated the involvement of OFPs in regulating gene expression. The biotic and abiotic stress, and the tissue-specific expression analysis of the RNA-seq datasets revealed that some of the genes such as BjuOFP30, and BnaOFP27, BolOFP11, and BolOFP10 were highly upregulated in seed coat at the mature stage and roots under various chemical stress conditions respectively which suggests their crucial role in plant growth and development processes. Experimental validation of prominent BnaOFPs such as BnaOFP27 confirmed their involvement in regulating gene expression under salinity, heavy metal, drought, heat, and cold stress. The GO and KEGG pathway enrichment analysis also sheds light on the involvement of OFPs in regulating plant growth and development. These findings have the potential to serve as a forerunner for future studies in terms of functionally diverse analysis of the OFP gene family in Brassica and other plant species.

DDoS attack detection in smart grid network using reconstructive machine learning models.

Network attacks pose a significant challenge for smart grid networks, mainly due to the existence of several multi-directional communication devices coupling consumers to the grid. One of the network attacks that can affect the smart grid is the distributed denial of service (DDoS), where numerous compromised communication devices/nodes of the grid flood the smart grid network with false data and requests, leading to disruptions in smart meters, data servers, and the state estimator, ultimately effecting the services for end-users. Machine learning-based strategies show distinctive benefits in resolving the challenge of securing the network from DDoS attacks. Regardless, a notable hindrance in deploying machine learning-based techniques is the requirement of model retraining whenever new attack classes arise. Practically, disrupting the normal operations of smart grid is really discouraged. To handle this challenge effectively and detect DDoS attacks without major disruptions, we propose the deployment of reconstructive deep learning techniques. A primary benefit of our proposed technique is the minimum disruption during the introduction of a new attack class, even after complete deployment. We trained several deep and shallow reconstructive models to get representations for each attack type separately, and we performed attack detection by class-specific reconstruction error-based classification. Our technique experienced rigid evaluation via multiple experiments using two well-acknowledged standard databases exclusively for DDoS attacks, including their subsets. Later, we performed a comparative estimation of our outcomes against six methods prevalent within the same domain. Our outcomes reveal that our technique attained higher accuracy, and notably eliminates the requirement of a complete model retraining in the event of the introduction of new attack classes. This method will not only boost the security of smart grid networks but also ensure the stability and reliability of normal operations, protecting the critical infrastructure from ever-evolving network attacks. As smart grid is advancing rapidly, our approach proposes a robust and adaptive way to overcome the continuous challenges posed by network attacks.

Genetic variants rs2910164, rs4636297 and rs895819 may contribute to the onset of acute myocardial infarction in Pakistani population.

The most serious type of coronary artery disease (CAD), acute myocardial infarction (AMI), is a major global cause of death. The development of AMI is accompanied by several risk factors. AMI may be caused by variations in the microRNA (miRNA) genes, which have a negative impact on miRNA-mediated regulation of gene expression. The target mRNAs are dysregulated because of these genetic changes in the miRNA genes, which interfere with the vital biological processes that result in AMI. Using allele-specific PCR, the aim of the study is to examine the association of the variants (rs2910164, rs4636297, and rs895819) in MIR146A, MIR126, and MIR27A with AMI susceptibility. A difference in genotype distribution among the patients and control for variation rs2910164 was identified by co-dominant [χ2 = 68.34,2; P value<0.0001], dominant (G/G vs G/C + C/C) [OR = 4.167 (2.860-6.049); P value<0.0001], recessive (C/C vs G/C + G/G) [OR = 0.2584 (0.1798-0.3731); P value<0.0001], and additive models [OR = 3.847 (2.985-4.959); P value<0.0001]. Whereas the association of rs4636297 was investigated by co-dominant [χ2 = 6.882,2; P value = 0.0320], dominant (G/G vs G/A + A/A) [OR = 0.6914 (0.4849-0.9948); P value = 0.0489], recessive (A/A vs A/G + G/G) [OR = 2.434 (0.9849-5.616830); P value = 0.0595], and additive models [OR = 0.7716 (0.6000-0.9918); P value = 0.0433]. Similarly, association of rs895819 was determined by co-dominant [χ2 = 5.277, 2; P value = 0.0715], dominant (G/G vs G/A + A/A) [OR = 1.654(0.9819-2.801); P value = 0.06440], recessive (A/A vs A/G + G/G) [OR = 0.7227 (0.5132-1.022); P value = 0.0748], and additive models [OR = 1.3337 (1.041-1.719); P value = 0.0233]. The results of this study found a significant association of rs2910164 and rs4636297 with AMI and are considered as the risk factor for AMI in the Pakistani population. We observed no significant association of the variant MIR27A (rs895819) with AMI incidence.

Evaluation of functional kompetitive allele-specific PCR (KASP) markers for selection of drought-tolerant wheat (Triticum aestivum) genotypes.

Wheat (Triticum aestivum ) is a major crop around the globe and different techniques are being used for its productivity enhancement. Germplasm evaluation to improve crop productivity mainly depends on accurate phenotyping and selection of genotypes with a high frequency of superior alleles related to the trait of interest. Therefore, applying functional kompetitive allele-specific PCR (KASP) markers for drought-related genes is essential to characterise the genotypes for developing future climate-resilient wheat crop. In this study, eight functional KASP markers and nine morphological traits were employed to evaluate the 40 wheat genotypes for drought tolerance. Morphological traits showed significant variation (P ≤0.05) among the genotypes, except tiller count (TC), fresh root weight (FRW) and dry root weight (DRW). PCA biplot showed that 63.3% phenotypic variation was explained by the first two PCs under control treatment, while 70.8% variation was explained under drought treatment. It also indicated that root length (RL) and primary root (PR) have considerable variations among the genotypes under both treatments and are positively associated with each other. Hence, the findings of this study suggested that both these traits could be used as a selection criterion to classify the drought-tolerant wheat genotypes. KASP genotyping accompanied by morphological data revealed that genotypes Markaz, Bhakar Star, China 2, Aas and Chakwal-50 performed better under drought stress. These outperforming genotypes could be used as parents in developing drought-tolerant wheat genotypes. Hence, KASP genotyping assay for functional genes or significant haplotypes and phenotypic evaluation are prerequisites for a modern breeding program.

The miRNA variants MIR196A2 (rs11614913) and MIR423 (rs6505162) contribute to an increase in the risk of myocardial infarction.

INTRODUCTION: MicroRNAs (miRNAs) are small, single-stranded RNA molecules that negatively regulate gene expression and play a key role in the pathogenesis of human diseases. Recent studies have suggested that miRNAs contribute to cardiovascular diseases (CVDs). However, the association between single-nucleotide polymorphisms (SNPs) in miRNAs and myocardial infarction (MI) remains in infancy. AIM: The current study was designed to find out the association of SNPs in MIR196A2 and MIR423 (rs11614913 and rs6505162, respectively). METHODS: Using Tetra-Primer Amplification Refractory Mutation System-Polymerase Chain Reaction (T-ARMS PCR) in 400 cases (MI patients) and 336 healthy controls. Using different inheritance models (co-dominant, homozygous dominant, homozygous recessive, and additive models), the association of these SNPs was genotyped with MI risk. RESULTS: For variant rs11614913, significant distribution of the genotypes among the cases and controls was determined by co-dominant [χ2 = 29.19, 2; p value < 0.0001], dominant (C/C vs. C/T + T/T) [OR = 0.45 (0.34 to 0.61); p < 0.0001], recessive (T/T vs. C/T + C/C) [OR = 1.009 (0.63 to 1.63); p-value p value > 0.999], and additive models [OR = 0.65 (0.52 to 0.80); p value = 0.0001]. Similarly, a significant association of rs6505162 was determined by co-dominant [χ2 = 24.29, 2; p value < 0.0001], dominant (C/C vs. A/C+ A/A) [OR = 0.44 (0.32 to 0.61); p value < 0.0001], recessive (A/A vs. A/C + C/C) [OR = 1.29 (0.85 to 1.98); p value = 0.28], and additive models [OR = 0.65 (0.52 to 0.81); p value = 0.0001]. CONCLUSION: Therefore, the current study showed that both variants rs11614913 and rs6505162 are significantly associated with MI in the Pakistani population.

Efficacy of Atezolizumab Plus Bevacizumab Versus Lenvatinib in Patients with Unresectable Hepatocellular Carcinoma: a Meta-analysis.

INTRODUCTION: Hepatocellular carcinoma is a lethal disease and there has been a debate regarding the first-line treatment of its advanced and unresectable form. Observational studies have explored atezolizumab plus bevacizumab versus lenvatinib, yielding mixed results. This systematic review and meta-analysis aim to compare efficacy and safety of both treatment arms. METHODS: A systematic literature review was conducted in accordance with PRISMA guidelines. Randomized control trials, cohort studies, or case-control that included patients above age 60 with unresectable hepatocellular carcinoma confirmed by radiological imaging were included. At least one of the outcomes: overall survival (OS), progression-free survival (PFS), objective response rate (ORR), duration of response, or adverse events was included in the selected studies. RESULTS: Ten cohorts were included in the analysis with a total of 6493 patients. Nine of the included studies had patients with advanced HCC (BCLC-C) or intermediate HCC (BCLC-B) and 1 study included patients with all three stages (BCLC-A, BCLC-B, and BCLC-C). Of these patients, 2524 patients received atezolizumab plus bevacizumab (A + B) combination while 3969 received lenvatinib. The overall survival was better statistically in the A + B group then the lenvatinib group (MD: - 5.06; 95% CI: - 7.79 to - 2.33; p = 0.0003, I2 = 0%). The progression-free survival was significantly improved in A + B arm as well group (MD: - 4.96; 95% CI: - 7.67 to - 2.26; I2 = 0%, p = 0. 0003). There was no significant difference in objective response rate, disease control rate, and frequency of adverse events in either of the group. CONCLUSION: Our study concluded that combination therapy with atezolizumab plus bevacizumab could increase the survival duration without affecting the disease course. Moreover, while the severity of adverse events was greater in the A + B group, their frequency was comparable to the lenvatinib group.

The comparative transcriptome analysis of two green super rice genotypes with varying tolerance to salt stress.

BACKGROUND: Salinity is one of the main abiotic factors that restrict plant growth, physiology, and crop productivity is salt stress. About 33% of the total irrigated land suffers from severe salinity because of intensive underground water extraction and irrigation with brackish water. Thus, it is important to understand the genetic mechanism and identify the novel genes involved in salt tolerance for the development of climate-resilient rice cultivars. METHODS AND RESULTS: In this study, two rice genotypes with varying tolerance to salt stress were used to investigate the differential expressed genes and molecular pathways to adapt under saline soil by comparative RNA sequencing at 42 days of the seedling stage. Salt-susceptible (S3) and -tolerant (S13) genotypes revealed 3982 and 3463 differentially expressed genes in S3 and S13 genotypes. The up-regulated genes in both genotypes were substantially enriched in different metabolic processes and binding activities. Biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, and plant signal transduction mechanisms were highly enriched. Salt-susceptible and -tolerant genotypes shared the same salt adaptability mechanism with no significant quantitative differences at the transcriptome level. Moreover, bHLH, ERF, NAC, WRKY, and MYB transcription factors were substantially up-regulated under salt stress. 391 out of 1806 identified novel genes involved in signal transduction mechanisms. Expression profiling of six novel genes further validated the findings from RNA-seq data. CONCLUSION: These findings suggest that the differentially expressed genes and molecular mechanisms involved in salt stress adaptation are conserved in both salt-susceptible and salt-tolerant rice genotypes. Further molecular characterization of novel genes will help to understand the genetic mechanism underlying salt tolerance in rice.

Bacopa monnieri: A promising herbal approach for neurodegenerative disease treatment supported by in silico and in vitro research.

Neurodegenerative disorders, caused by progressive neuron loss, are a global health issue. Among the various factors implicated in their pathogenesis, dysregulation of acetylcholinesterase activity has been recognized as a key contributor. Acetylcholinesterase breaks down the neurotransmitter acetylcholine, important for neural transmission. Evaluating phyto-compounds from Bacopa monnieri Linn. through in vitro and in silico analysis may expand their role as alternative therapeutic agents by modulating the function of acetylcholinesterase and complementing existing treatments. To accomplish this objective, chemical structures of phyto-compounds were retrieved from PubChem database and subjected to in silico and in vitro approaches. Virtual screening was performed through molecular docking and molecular dynamic simulation resulting in four top hit compounds including quercetin, apigenin, wogonin, and bacopaside X (novel lead compound for acetylcholinesterase inhibitor) with least binding score. Further, dose dependent acetylcholinesterase inhibition biochemical assay depicted that bacopaside X, apigenin, quercetin, and wogonin exhibited strong potential against acetylcholinesterase with IC50 values of 12.78 µM, 13.83 µM, 12.73 µM and 15.48 µM respectively, in comparison with the donepezil (IC50: 0.0204 µM). The in silico and in vitro research suggests that B. monnieri phyto-compounds have the potential to modulate molecular targets associated with neurodegenerative diseases and have a role in neuroprotection.