Genetic Techniques Research Articles

New insights into the endothelial origin of hematopoietic system inspired by "TIF" approaches.

Hematopoietic stem progenitor cells (HSPCs) are derived from a specialized subset of endothelial cells named hemogenic endothelial cells (HECs) via a process of endothelial-to-hematopoietic transition during embryogenesis. Recently, with the usage of multiple single-cell technologies and advanced genetic lineage tracing techniques, namely, "TIF" approaches that combining transcriptome, immunophenotype and function/fate analyses, massive new insights have been achieved regarding the cellular and molecular evolution underlying the emergence of HSPCs from embryonic vascular beds. In this review, we focus on the most recent advances in the enrichment markers, functional characteristics, developmental paths, molecular controls, and the embryonic site-relevance of the key intermediate cell populations bridging embryonic vascular and hematopoietic systems, namely HECs and pre-hematopoietic stem cells, the immediate progenies of some HECs, in mouse and human embryos. Specifically, using expression analyses at both transcriptional and protein levels and especially efficient functional assays, we propose that the onset of Kit expression is at the HEC stage, which has previously been controversial.

Research on Fracture Parameter Optimization Method Based on Generative Adversarial Network in Small Sample Size

Abstract This study addresses the optimization of fracturing parameters in the fractured gas reservoirs of the Tarim Basin, especially under the challenge of small sample sizes and high data acquisition costs. It proposes an innovative method based on Generative Adversarial Networks (GAN). Traditional fracturing technology parameter optimization often leads to model overfitting and poor generalization due to limited data. This research adopts GAN for data augmentation to generate additional training samples, thereby improving the training effect of machine learning models. The combination of genetic algorithms and model fusion techniques further optimizes production capacity prediction and fracturing parameter adjustment. Application of this method to actual data from the Tarim Basin shows that it effectively enhances the accuracy of parameter optimization and the generalization ability of the model, providing significant guidance for gas reservoir development under similar complex geological conditions.

Consanguinity and Occurrence of Monogenic Diseases in a Single Tertiary Centre in Riyadh, Saudi Arabia: A 2 Years Cross-Sectional Study.

Consanguinity, or the practice of marrying close relatives, is a common cultural tradition in Saudi Arabia, with rates among the highest in the world. This practice has significant implications for the prevalence and distribution of major single genetic defects and chromosomal abnormalities within the Saudi population. Herein, using the BESTCare electronic medical record system (designed to streamline hospital operations, enhance patient care, and improve the overall efficiency of healthcare services; bestcare.ezcaretech.com) in a single tertiary centre, King Abdullah Specialized Children Hospital (KASCH) in Riyadh, Saudi Arabia, we performed a cross-sectional study for all patients referred to the hospital from the 1st January 2020 until 1st January 2022. The present study, which included 1100 individuals, found a high prevalence of consanguinity (64%) and a significant proportion of third-degree relatives (69%). The mean age of participants was 12.24 years, and the diagnostic rate using advanced molecular genetics techniques was 45%, with whole exome sequencing (WES) being the most common method (43%). The study also noted a significant delay in diagnosis for more than a year in 16% of cases, with a common neurodevelopmental phenotype (18%). In conclusion, we revealed the prevalence of consanguineous marriages in the KASCH hospital in Riyadh, Saudi Arabia. We also highlighted the most frequently referred phenotype. These findings are consistent with previous research on the prevalence and impact of consanguinity on rare genetic disorders.

Recombinant Influenza A Viruses Expressing Reporter Genes from the Viral NS Segment.

Studying influenza A viruses (IAVs) requires secondary experimental procedures to detect the presence of the virus in infected cells or animals. The ability to generate recombinant (r)IAV using reverse genetics techniques has allowed investigators to generate viruses expressing foreign genes, including fluorescent and luciferase proteins. These rIAVs expressing reporter genes have allowed for easily tracking viral infections in cultured cells and animal models of infection without the need for secondary approaches, representing an excellent option to study different aspects in the biology of IAV where expression of reporter genes can be used as a readout of viral replication and spread. Likewise, these reporter-expressing rIAVs provide an excellent opportunity for the rapid identification and characterization of prophylactic and/or therapeutic approaches. To date, rIAV expressing reporter genes from different viral segments have been described in the literature. Among those, rIAV expressing reporter genes from the viral NS segment have been shown to represent an excellent option to track IAV infection in vitro and in vivo, eliminating the need for secondary approaches to identify the presence of the virus. Here, we summarize the status on rIAV expressing traceable reporter genes from the viral NS segment and their applications for in vitro and in vivo influenza research.

Prediction model for hardness and tensile strength of graphene reinforced AZ 61 alloy based composite using Metaheuristic Algorithm

It is possible to produce improved material performance through the utilization of computational intelligence approaches such as genetic algorithms optimization technique which are discussed in this paper. The optimization of processes and the development of models that are driven by data are the key uses of these technologies. This article offers a comprehensive introduction of the topic of materials and discusses the ways in which computational intelligence techniques might be utilized to develop new materials. The present study envisages the development of data driven model that enables to derive desirable properties of the said composite; so, in order to secure the optimized subset of requirements (process parameters), a metaheuristic optimization tool is employed. We invoke the use of the Genetic Algorithm (GA) optimizing tool in association with linear regression, so as to achieve the best combination of hardness and tensile strength of AZ61 graphene nanoplate (GNP) composite.

Unusual familial cystic kidney disease: combining fine radiologic and genetic evaluation to solve the case

BackgroundAutosomal dominant polycystic kidney disease (ADPKD) is the most prevalent hereditary kidney disease, characterized by enlarged kidneys with numerous cysts, high blood pressure, and a variety of extrarenal complications. This disease is a significant cause of renal failure and requires accurate differentiation from other cystic kidney diseases, especially when family history does not clearly indicate ADPKD. This is crucial due to differences in prognosis, treatment, and familial implications. Advanced molecular genetics and imaging techniques are employed to diagnose and assess the prognosis of patients and their families.Case presentationThe case study revolves around three patients from the same family—two sisters and one daughter—referred to a nephrology department for ADPKD management. The initial proband, a 42-year-old woman, experienced abdominal discomfort leading to an ultrasound that suggested ADPKD. However, MRI findings indicated standard-sized kidneys with bilateral parapelvic cysts, and no genetic markers for ADPKD were found. Her sister, presenting with controlled hypertension and similar ultrasound findings, also had her initial ADPKD diagnosis refuted by MRI and genetic testing, which revealed no significant mutations. The daughter, however, exhibited a different scenario with enlarged kidneys and multiple cysts characteristic of early-stage ADPKD. Genetic testing confirmed a deleterious PKD1 mutation, suggesting a de novo mutation, as her father showed no signs of the disease.ConclusionThis study highlights the complexity and necessity of thorough diagnostic processes in suspected ADPKD cases to prevent misdiagnosis. The initial symptoms and imaging might misleadingly suggest ADPKD, as seen in the cases of the two older patients. Still, further detailed imaging and genetic analyses revealed no ADPKD, preventing inappropriate treatment and stress. In contrast, the younger patient's distinctive clinical and genetic profile confirmed ADPKD, illustrating the variability within even closely related individuals. Such detailed assessments are crucial in guiding correct treatment decisions and providing accurate familial counseling, emphasizing the importance of considering a broader spectrum of renal cystic disorders before confirming a diagnosis of ADPKD.

THE ARABIDOPSIS NHX1 GENE: OVEREXPRESSION AND ITS IMPACT ON SALT TOLERANCE IN TRANSGENIC PLANTS

Abiotic stresses, such as salinity, negatively impact crop growth, development and overall production. The discovery and operational confirmation of new genes will provide the framework for successful genetic engineering techniques to increase crop plants' resistance to salinity stress. The most effective method for maintaining ionic balance in plants under stress due to saltiness is provided by the membrane and vacuolar Na+/H+ counter transporter. The function of AtNHX1, the initially identified vacuolar antiporter from more advanced crops, was extensively researched. In this article, we will review the possible function of the Arabidopsis NHX1 gene that is responsible for salt tolerance and its transformation into Wheat, Barley, Poplar, Fescue, Petunia hybrid, Alfalfa & Soybean. Reason to engineer higher plants' genomes using Arabidopsis NHX1 genes to provide food sustainably in salinity-affected locations.

Bioinformatics Analysis of the Panax ginseng Cyclophilin Gene and Its Anti-Phytophthora cactorum Activity.

In this paper, Panax ginseng cyclophilin (PgCyP) was successfully obtained through a genetic engineering technique. A bioinformatics method was used to analyze the physicochemical properties and structure of PgCyP. The results showed that PgCyP belongs to the cyclophilin gene family. The protein encoded by the PgCyP gene contains the active site of PPIase (R62, F67, and H133) and a binding site for cyclosporine A (W128). The relative molecular weight of PgCyP is 187.11 bp; its theoretical isoelectric point is 7.67, and it encodes 174 amino acids. The promoter region of PgCyP mainly contains the low-temperature environmental stress response (LTR) element, abscisic acid-responsive cis-acting element (ABRE), and light-responsive cis-acting element (G-Box). PgCyP includes a total of nine phosphorylation sites, comprising four serine phosphorylation sites, three threonine phosphorylation sites, and two tyrosine phosphorylation sites. PgCyP was recombined and expressed in vitro, and its recombinant expression was investigated. Furthermore, it was found that the recombinant PgCyP protein could effectively inhibit the germination of Phytophthora cactorum spores and the normal growth of Phytophthora cactorum mycelia in vitro. Further experiments on the roots of susceptible Arabidopsis thaliana showed that the PgCyP protein could improve the resistance of arabidopsis to Phytophthora cactorum. The findings of this study provide a basis for the use of the PgCyP protein as a new type of green biopesticide.

Direct protein delivery into intact Arabidopsis cells for genome engineering

Intracellular delivery of biomolecules is a prerequisite for genetic techniques such as recombinant engineering and genome editing. Realizing the full potential of this technology requires the development of safe and effective methods for delivering protein tools into cells. In this study, we demonstrated the spontaneous internalization of exogenous proteins into intact cells and root tissue of whole plants of Arabidopsis thaliana. We termed this internalization phenomenon as protein Delivery Independent of Vehicles or Equipment (DIVE), which efficiently delivered genome engineering proteins including Cre recombinase and zinc-finger nucleases (ZFN) into plant cells. Using protein DIVE, we achieved less toxic protein delivery than electroporation with up to 94% efficiency in Arabidopsis cell culture and 19% genome modification in Arabidopsis plants that was maintained in regenerated tissue. This work illustrates the potential of protein DIVE for a wide range of applications, including genome engineering in plants.

Modeling of genetic algorithm tuned adaptive fuzzy fractional order PID speed control of permanent magnet synchronous motor for electric vehicle

This study presents a novel Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative (GA-AFFFOPID) controller for enhancing the speed control performance of permanent magnet synchronous motor (PMSM) drives in Electric Vehicles. The proposed GA-AFFFOPID controller, which combines the advantages of genetic algorithm optimization and adaptive fuzzy fractional-order PID control, represents a unique and innovative approach to address the control challenges associated with PMSM drives. Permanent magnet synchronous motor technology, known for its efficiency, compactness, reliability, and versatility in motion control applications, is increasingly adopted in electric vehicle drive systems. However, the inherent non-linearity, dynamics, and uncertainties of permanent magnet synchronous motors pose significant control challenges. The exceptional performance of the GA-AFFFOPID controller, demonstrated through its superior system dynamics, precise speed tracking, and robustness against parameter variations and sudden load disturbances, underscores the significant advancements enabled by the genetic algorithm optimization technique in improving the control performance of PMSM drives for electric vehicle applications. Comparative analysis with traditional control methods demonstrates the exceptional performance of the Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative controller. These findings highlight the significant performance improvements facilitated by the genetic algorithm optimization technique in enhancing the control performance of the adaptive fuzzy fractional order PID controller in PMSM drives for electric vehicle applications.

Prenatal diagnosis in fetal right aortic arch using chromosomal microarray analysis and whole exome sequencing: a Chinese single-center retrospective study

BackgroundRight aortic arch (RAA) is a common congenital aortic arch abnormality. Fetuses with RAA frequently have good outcomes after birth. However, chromosomal abnormalities and genetic syndromes suggest poor prognosis for these patients. So far the underlying genetic etiology is still not identified in most RAA patients based on traditional genetic techniques and a problem is still debated whether fetuses with isolated RAA should be referred for CMA. Our study aims to investigate the genetic etiology of fetuses with right aortic arch (RAA) by chromosomal microarray analysis (CMA) and whole exome sequencing (WES) and evaluate the efficacy of CMA in fetal isolated RAA.ResultsAmong these 153 fetuses, 99 (64.7%) with isolated RAA and 54 (35.3%) with non-isolated RAA; 25.5% (39/153) with additional intracardiac anomalies (ICA), and 19.0% (29/153) with extracardiac anomalies (ECA). Tetralogy of Fallot (n = 10) and persistent left superior vena cava (n = 11) are the most common ICA and ECA, respectively. CMA detected 15 clinically significant copy number variations (CNVs) in 14 cases (9.2%); microdeletion of 22q11.21 was the most common pathogenic CNVs (7.8%). The chromosomal abnormalities rate was higher in non-isolated RAA and RAA with ICA groups than in isolated RAA group (16.7% vs. 5.1%; 20% vs. 5.1%, both p < 0.05). From five cases further undergoing WES, a diagnostic variant in MTOR gene (c.7255G > A, de novo) was first reported in prenatal, extending the prenatal manifestation of Smith–Kingsmore syndrome (OMIM: 616638); a clinically relevant variant c.3407A > T in STAG2 was identified, being inherited from the healthy mother. Moreover, the premature birth and termination rates were higher in non-isolated RAA group than in isolated RAA group (11.1% vs. 1.0%; 37.0% vs. 2.0%, both p < 0.01).ConclusionsWe demonstrate that CMA and WES are useful diagnostic tools for fetal RAA, particularly non-isolated RAA, and all fetuses with RAA should be referred for CMA. The data probably aids in prenatal diagnosis and prenatal counseling of fetal RAA.

The 129 strain-derived passenger mutations in ACKR1-deficient mice alter the expression of PYHIN and Fc-gamma receptor genes.

A majority of genetically modified mice have been produced using 129 strain-derived embryonic stem cells (ESCs). Despite ample backcrosses with other strains, these may retain characteristic for 129 passenger mutations leading to confounding phenotypes unrelated to targeted genes. Here we show that widely used Ackr1-/-129ES mice have approximately 6Mb of the 129-derived genome retained adjacently to the Ackr1 locus on chromosome 1, including several characteristic polymorphisms. These most notably affect the expression of PYHIN and Fc-gamma receptor genes in myeloid cells resulting in the overproduction of IL-1β by activated macrophages and the loss of Fc-gamma receptors on myeloid progenitor cells. Therefore, caution is warranted when interpreting Ackr1-/-129ES mouse phenotypes as being solely due to the ACKR1 deficiency. Our findings call for a careful reevaluation of data from previous studies using Ackr1-/-129ES mice and underscore the limitations and pitfalls inherent to mouse models produced using traditional genetic engineering techniques involving 129 ESCs.

Unveiling the DHX15–G-patch interplay in retroviral RNA packaging

We explored how a simple retrovirus, Mason-Pfizer monkey virus (M-PMV) to facilitate its replication process, utilizes DHX15, a cellular RNA helicase, typically engaged in RNA processing. Through advanced genetic engineering techniques, we showed that M-PMV recruits DHX15 by mimicking cellular mechanisms, relocating it from the nucleus to the cytoplasm to aid in viral assembly. This interaction is essential for the correct packaging of the viral genome and critical for its infectivity. Our findings offer unique insights into the mechanisms of viral manipulation of host cellular processes, highlighting a sophisticated strategy that viruses employ to leverage cellular machinery for their replication. This study adds valuable knowledge to the understanding of viral-host interactions but also suggests a common evolutionary history between cellular processes and viral mechanisms. This finding opens a unique perspective on the export mechanism of intron-retaining mRNAs in the packaging of viral genetic information and potentially develop ways to stop it.

Glycogen synthase activity in Candida albicans is partly controlled by the functional ortholog of Saccharomyces cerevisiae Gac1p.

To adapt to various host microenvironments, the human fungal pathogen Candida albicans possesses the capacity to accumulate and store glycogen as an internal carbohydrate source. In the model yeast Saccharomyces cerevisiae, ScGlc7p and ScGac1p are the serine/threonine type 1 protein phosphatase catalytic and regulatory subunits that control glycogen synthesis by altering the phosphorylation state of the glycogen synthase Gsy2p. Despite recent delineation of the glycogen synthesis pathway in C. albicans, the molecular events driving synthase activation are currently undefined. In this study, using a combination of microbiologic and genetic techniques, we determined that the protein encoded by uncharacterized gene C1_01140C, and not the currently annotated C. albicans Gac1p, is the major regulatory subunit involved in glycogen synthesis. C1_01140Cp contains a conserved GVNK motif observed across multiple starch/glycogen-binding proteins in various species, and alanine substitution of each residue in this motif significantly impaired glycogen accumulation in C. albicans. Fluorescent protein tagging and microscopy indicated that C1_01140Cp-GFPy colocalized with CaGlc7p-tdTomato and CaGsy1p-tdTomato accordingly. Co-immunoprecipitation assays further confirmed that C1_01140Cp associates with CaGlc7p and CaGsy1p during glycogen synthesis. Lastly, c1_01140cΔ/Δ exhibited colonization defects in a murine model of vulvovaginal candidiasis. Collectively, our data indicate that uncharacterized C1_01140Cp is the functional ortholog of the PPP1R subunit ScGac1p in C. albicans.IMPORTANCEThe capacity to synthesize glycogen offers microbes metabolic flexibility, including the fungal pathogen Candida albicans. In Saccharomyces cerevisiae, dephosphorylation of glycogen synthase by the ScGlc7p-containing phosphatase is a critical rate-limiting step in glycogen synthesis. Subunits, including ScGac1p, target ScGlc7p to α-1,4-glucosyl primers for efficient ScGsy2p synthase activation. However, this process in C. albicans had not been delineated. Here, we show that the C. albicans genome encodes for two homologous phosphatase-binding subunits, annotated CaGac1p and uncharacterized C1_01140Cp, both containing a GVNK motif required for polysaccharide affinity. Surprisingly, loss of CaGac1p only moderately reduced glycogen accumulation, whereas loss of C1_01140Cp ablated it. Fluorescence microscopy and co-immunoprecipitation approaches revealed that C1_01140Cp associates with CaGlc7p and CaGsy1p during glycogen synthesis. Moreover, C1_01140Cp contributed to fungal fitness at the vaginal mucosa during murine vaginitis. Therefore, this work demonstrates that glycogen synthase regulation is conserved in C. albicans and C1_01140Cp is the functional ortholog of ScGac1p.

Traffic Classification in Software-Defined Networking Using Genetic Programming Tools

The classification of Software-Defined Networking (SDN) traffic is an essential tool for network management, network monitoring, traffic engineering, dynamic resource allocation planning, and applying Quality of Service (QoS) policies. The programmability nature of SDN, the holistic view of the network through SDN controllers, and the capability for dynamic adjustable and reconfigurable controllersare fertile ground for the development of new techniques for traffic classification. Although there are enough research works that have studied traffic classification methods in SDN environments, they have several shortcomings and gaps that need to be further investigated. In this study, we investigated traffic classification methods in SDN using publicly available SDN traffic trace datasets. We apply a series of classifiers, such as MLP (BFGS), FC2 (RBF), FC2 (MLP), Decision Tree, SVM, and GENCLASS, and evaluate their performance in terms of accuracy, detection rate, and precision. Of the methods used, GenClass appears to be more accurate in separating the categories of the problem than the rest, and this is reflected in both precision and recall. The key element of the GenClass method is that it can generate classification rules programmatically and detect the hidden associations that exist between the problem features and the desired classes. However, Genetic Programming-based techniques require significantly higher execution time compared to other machine learning techniques. This is most evident in the feature construction method where at each generation of the genetic algorithm, a set of learning models is required to be trained to evaluate the generated artificial features.

Update on Clinical Trial Endpoints in Gene Therapy Trials for Inherited Retinal Diseases.

Inherited retinal diseases (IRDs) encompass a wide spectrum of rare conditions characterized by diverse phenotypes associated with hundreds of genetic variations, often leading to progressive visual impairment and profound vision loss. Multiple natural history studies and clinical trials exploring gene therapy for various IRDs are ongoing. Outcomes for ophthalmic trials measure visual changes in three main categories-structural, functional, and patient-focused outcomes. Since IRDs may range from congenital with poor central vision from birth to affecting the peripheral retina initially and progressing insidiously with visual acuity affected late in the disease course, typical outcome measures such as central visual acuity and ocular coherence tomography (OCT) imaging of the macula may not provide adequate representation of therapeutic outcomes including alterations in disease course. Thus, alternative unique outcome measures are necessary to assess loss of peripheral vision, color vision, night vision, and contrast sensitivity in IRDs. These differences have complicated the assessment of clinical outcomes for IRD therapies, and the clinical trials for IRDs have had to design novel specialized endpoints to demonstrate treatment efficacy. As genetic engineering and gene therapy techniques continue to advance with growing investment from industry and accelerated approval tracks for orphan conditions, the clinical trials must continue to improve their assessments to demonstrate safety and efficacy of new gene therapies that aim to come to market. Here, we will provide an overview of the current gene therapy approaches, review various endpoints for measuring visual function, highlight those that are utilized in recent gene therapy trials, and provide an overview of stage 2 and 3 IRD trials through the second quarter of 2024.

Acceptance of emerging renal oncocytic neoplasms: a survey of urologic pathologists.

Oncocytic renal neoplasms are a major source of diagnostic challenge in genitourinary pathology; however, they are typically nonaggressive in general, raising the question of whether distinguishing different subtypes, including emerging entities, is necessary. Emerging entities recently described include eosinophilic solid and cystic renal cell carcinoma (ESC RCC), low-grade oncocytic tumor (LOT), eosinophilic vacuolated tumor (EVT), and papillary renal neoplasm with reverse polarity (PRNRP). A survey was shared among 65 urologic pathologists using SurveyMonkey.com (Survey Monkey, Santa Clara, CA, USA). De-identified and anonymized respondent data were analyzed. Sixty-three participants completed the survey and contributed to the study. Participants were from Asia (n = 21; 35%), North America (n = 31; 52%), Europe (n = 6; 10%), and Australia (n = 2; 3%). Half encounter oncocytic renal neoplasms that are difficult to classify monthly or more frequently. Most (70%) indicated that there is enough evidence to consider ESC RCC as a distinct entity now, whereas there was less certainty for LOT (27%), EVT (29%), and PRNRP (37%). However, when combining the responses for sufficient evidence currently and likely in the future, LOT and EVT yielded > 70% and > 60% for PRNRP. Most (60%) would not render an outright diagnosis of oncocytoma on needle core biopsy. There was a dichotomy in the routine use of immunohistochemistry (IHC) in the evaluation of oncocytoma (yes = 52%; no = 48%). The most utilized IHC markers included keratin 7 and 20, KIT, AMACR, PAX8, CA9, melan A, succinate dehydrogenase (SDH)B, and fumarate hydratase (FH). Genetic techniques used included TSC1/TSC2/MTOR (67%) or TFE3 (74%) genes and pathways; however, the majority reported using these very rarely. Only 40% have encountered low-grade oncocytic renal neoplasms that are deficient for FH. Increasing experience with the spectrum of oncocytic renal neoplasms will likely yield further insights into the most appropriate work-up, classification, and clinical management for these entities.

Genetic Algorithm-Based Data-Driven Process Selection System for Additive Manufacturing in Industry 4.0.

Additive manufacturing (AM) has impacted the manufacturing of complex three-dimensional objects in multiple materials for a wide array of applications. However, additive manufacturing, as an upcoming field, lacks automated and specific design rules for different AM processes. Moreover, the selection of specific AM processes for different geometries requires expert knowledge, which is difficult to replicate. An automated and data-driven system is needed that can capture the AM expert knowledge base and apply it to 3D-printed parts to avoid manufacturability issues. This research aims to develop a data-driven system for AM process selection within the design for additive manufacturing (DFAM) framework for Industry 4.0. A Genetic and Evolutionary Feature Weighting technique was optimized using 3D CAD data as an input to identify the optimal AM technique based on several requirements and constraints. A two-stage model was developed wherein the stage 1 model displayed average accuracies of 70% and the stage 2 model showed higher average accuracies of up to 97.33% based on quantitative feature labeling and augmentation of the datasets. The steady-state genetic algorithm (SSGA) was determined to be the most effective algorithm after benchmarking against estimation of distribution algorithm (EDA) and particle swarm optimization (PSO) algorithms, respectively. The output of this system leads to the identification of optimal AM processes for manufacturing 3D objects. This paper presents an automated design for an additive manufacturing system that is accurate and can be extended to other 3D-printing processes.

Molecular Genetics MDT, a new experience at Warith International Cancer Institute/Iraq

Introduction: The advances in molecular targeted therapies made huge differences in cancer care. Genome analysis become more frequent during practice; genomic test results need to be discussed interdisciplinary to reach the maximum treatment benefit. Methods: We established the first multidisciplinary cancer genetics meeting at Warith international cancer institute to discuss patients with different malignancies from a molecular perspective. Results: From May 2024 to September 2024, 15 cases were discussed in the molecular genetics MDT. In regard to many clinical scenarios like: patient centered care, limitation of treatment toxicity, preserving quality of life, tailoring cancer treatment plan and advanced genetic counselling techniques. Conclusion: This approach tends to be successful in discussing cancer cases by the involvement of different specialties to reach optimal cancer care. Although, it highlighted the significance of investment in cancer genomic infrastructure. Hence, improving patient’s outcome and personalize cancer care.

Microbial strategies for lead remediation in agricultural soils and wastewater: mechanisms, applications, and future directions.

High lead (Pb) levels in agricultural soil and wastewater threaten ecosystems and organism health. Microbial remediation is a cost-effective, efficient, and eco-friendly alternative to traditional physical or chemical methods for Pb remediation. Previous research indicates that micro-organisms employ various strategies to combat Pb pollution, including biosorption, bioprecipitation, biomineralization, and bioaccumulation. This study delves into recent advancements in Pb-remediation techniques utilizing bacteria, fungi, and microalgae, elucidating their detoxification pathways and the factors that influence Pb removal through specific case studies. It investigates how bacteria immobilize Pb by generating nanoparticles that convert dissolved lead (Pb-II) into less harmful forms to mitigate its adverse impacts. Furthermore, the current review explores the molecular-level mechanisms and genetic engineering techniques through which microbes develop resistance to Pb. We outline the challenges and potential avenues for research in microbial remediation of Pb-polluted habitats, exploring the interplay between Pb and micro-organisms and their potential in Pb removal.