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Oral diseases represent a major global health burden, underscoring the need for sensitive, accessible, and noninvasive diagnostic technologies. Electrochemical biosensing offers a powerful route for point-of-care oral health monitoring by translating biomolecular interactions in saliva, gingival crevicular fluid, and exhaled breath condensate into quantifiable electrical signals. This review systematically discusses electrochemical biosensing strategies for oral disease diagnosis, beginning with the structure and operating mechanisms of electrochemical sensors and then summarizing their applications in detecting disease-related nucleic acids, proteins, pathogens, and other molecules. We further examine feasible strategies for early diagnosis, including signal amplification methods based on nanomaterials, enzyme catalysis, nucleic acid amplification, chemical deposition, and cascade integration, as well as antifouling interfaces designed to maintain stable sensing performance in complex oral biofluids. Particular attention is given to advanced transistor architectures, especially organic electrochemical transistors (OECTs), which offer intrinsic signal amplification and high-gain readout for low-abundance biomarkers. Finally, we outline current challenges, future directions, and translational opportunities for electrochemical biosensing technologies, providing a roadmap toward precision dentistry and modern oral health management.

Uncontrolled hemorrhage, resulting from trauma or surgery, presents a critical challenge in medical care. This study introduces a novel eutectogel, a multifunctional material synthesized using choline chloride/phytic acid derived deep eutectic solvents (CP-DES)-mediated cellulose-MXene polyacrylamide, aimed at addressing hemostatic needs. The eutectogel combines photothermal and thermoelectric effects to accelerate hemorrhage control, significantly reducing blood loss and hemostasis time. Unlike existing hemostatic materials, our design leverages the synergistic effects of photothermal heating and thermoelectric current, enhancing coagulation and promoting tissue repair. The innovation lies in the integration of DES to stabilize MXene, optimizing its photothermal and thermoelectric properties, and enabling rapid gelation, self-healing, and anti-freezing capabilities. In vitro and in vivo tests demonstrate the material's superior performance in hemostasis compared to traditional gauze, highlighting its potential for trauma care and surgical applications. This approach sets a new paradigm in the development of advanced, multifunctional biomedical materials for hemostasis and beyond.

Despite advancements in therapeutic cancer vaccines, clinical translation has been hindered by limited efficacy, with Sipuleucel-T remaining the only FDA-approved therapeutic cancer vaccine to date. However, recent advances in personalized mRNA vaccines, such as Moderna's mRNA-4157 and BioNTech's autogene cevumeran, have demonstrated significant reductions in recurrence risk and improved survival across several cancer types, renewing optimism in the field. Personalized cancer vaccines leverage patient-specific tumor antigens to initiate potent and targeted immune responses. This review outlines various classes of personalized vaccines, including DNA-, mRNA-, peptide-, dendritic cell-, and whole-cell-based platforms, and examines the immunological challenges they face, such as tumor heterogeneity, immunosuppressive microenvironments, and inadequate immune memory. To address these limitations, both conventional and nanotechnology-enhanced delivery systems have been developed. Notably, nanovaccines constructed from lipid-polymer hybrids, biomimetic membranes, and stimulus-responsive materials enable codelivery of neoantigens and immunostimulatory agonists, promoting enhanced lymph node targeting, dendritic cell activation, and antigen cross-presentation. Furthermore, biomimetic formulations incorporating autologous tumor membranes preserve native antigenic diversity and allow dynamic adaptation to evolving tumors. When integrated with artificial intelligence for antigen selection and multiomics for patient stratification, these platforms accelerate vaccine design and improve precision. Combination regimens with immune checkpoint inhibitors or other agents further potentiate efficacy and promote durable antitumor immunity. Increasing clinical evidence, especially in melanoma and pancreatic cancer, underscores the potential of these strategies to induce long-term protection and reduce recurrence. Overall, next-generation personalized cancer vaccines are advancing the transition from reactive treatment to proactive, precision-controlled cancer immunotherapy.

Aspergillus niger is a renowned filamentous fungus with extensive industrial and biotechnological applications. A. niger is widely used to produce diverse organic acids, enzymes, and other value-added metabolites. Although strain-specific metabolic capabilities have been widely applied in industry, the genomic foundations of these capabilities have not yet been fully characterized. Here, we have described the isolation and provided the draft genome sequence of A. niger strain AN-L103_M1 to further study the genetic determinants of primary and secondary metabolism, given its metabolic versatility and great potential in biotechnology. This A. niger strain was developed through gamma radiation bombardment, and subsequently, all the mutants were screened through various steps for hyperproduction of citric acid. This genome sequence provided valuable information for further functional genomics and strain-improvement research. The A. niger strain was obtained through gamma radiation bombardment. After gamma radiation bombardment of the A. niger culture, it was subjected to various screening steps to achieve hyperproduction of citric acid. These experiments were performed in the Industrial Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan. The mycotoxin production potential of this mutant strain was assessed using LC-MS analysis, which detected no mycotoxins.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, driven largely by pronounced molecular heterogeneity and delayed clinical detection. Although high-throughput sequencing technologies have substantially advanced the understanding of CRC biology, their routine clinical implementation remains constrained by high costs, infrastructural requirements, and limited accessibility. This review addresses these translational barriers by systematically synthesizing circulating transcriptomic and proteomic biomarkers within a clinically scalable framework. Particular emphasis is placed on biomolecules detectable using reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA), two widely accessible platforms that underwent extensive global optimization during the COVID-19 pandemic and are readily adaptable to liquid biopsy workflows. Through a stage-resolved analysis, we identify 9 genomic and 7 proteomic biomarkers associated with early-stage (I-II) CRC, alongside 9 genomic and 4 proteomic biomarkers linked to advanced-stage (III-IV) disease progression. Beyond biomarker cataloging, these molecules are integrated with Cancer Hallmark pathways, clinical-stage associations, and available clinical trial evidence to evaluate their biological relevance and translational readiness. In addition, we summarize standardized operating procedure (SOP) considerations and multiplex detection strategies to improve assay reproducibility, scalability, and cross-border clinical implementation. Collectively, this review bridges molecular discovery with clinically deployable laboratory workflows and provides a translational roadmap for the development of affordable, liquid biopsy-based diagnostic strategies aimed at improving CRC detection, patient stratification, longitudinal monitoring, and early therapeutic intervention. Stage-resolved biomarker framework: Provides an integrated catalog of circulating transcriptomic and proteomic biomarkers stratified across CRC stages I–IV.Mechanistic and functional integration: Links circulating biomarkers with Cancer Hallmark pathways, highlighting biomolecules that function as both diagnostic indicators and molecular regulators of disease progression.Clinically scalable diagnostic focus: Prioritizes RT-PCR– and ELISA-based detection strategies to support affordable, high-throughput, and clinically accessible liquid biopsy applications.Translational readiness: Integrates clinical trial evidence, assay feasibility, and SOP considerations to strengthen the clinical applicability and reproducibility of candidate biomarkers.Multi-analyte precision diagnostics: Supports the development of combined transcriptomic–proteomic biomarker panels to improve diagnostic sensitivity, prognostic stratification, and disease monitoring.Global clinical applicability: Proposes a practical framework for biomarker implementation and validation across diverse healthcare systems, including resource-limited settings.

Chronological age remains widely used in perioperative decision-making but incompletely captures the biological heterogeneity that influences postoperative outcomes. Frailty has substantially advanced surgical risk assessment by shifting attention from age toward multidimensional vulnerability and diminished physiological reserve. Nevertheless, patients with similar frailty profiles often experience markedly different recovery trajectories, suggesting that baseline vulnerability alone may not fully explain postoperative adaptation. This narrative conceptual review was developed through a targeted search of PubMed/MEDLINE, Scopus, and Google Scholar, focusing on frailty, physiological reserve, physical resilience, intrinsic capacity, prehabilitation, and postoperative recovery. Peer-reviewed clinical studies, reviews, and conceptual frameworks from geroscience and perioperative medicine were synthesized to develop an integrated model of surgical resilience. Emerging evidence indicates that frailty and resilience represent related but distinct constructs. Frailty primarily identifies vulnerability before stress exposure, whereas resilience reflects the dynamic capacity to withstand, adapt to, and recover from physiological perturbation. Recent perioperative studies suggest that postoperative outcomes are influenced not only by baseline reserve but also by the interaction between reserve, surgical stress exposure, and recovery capacity. Within this framework, skeletal muscle function, nutritional status, cognition, inflammatory burden, and functional independence appear to contribute to an individual's adaptive potential. Surgery represents a uniquely informative human model through which stress-response biology and recovery trajectories can be studied longitudinally. We propose surgical physiological resilience as a dynamic stress-recovery phenotype emerging from the interaction among three interconnected domains: baseline reserve, surgical stress load, and recovery capacity. This framework extends current frailty-based approaches by incorporating longitudinal adaptation and recoverability after surgical stress. Reframing perioperative medicine around resilience may support trajectory-based risk stratification, targeted prehabilitation strategies, longitudinal functional monitoring, and the future development of a dynamic Surgical Resilience Index capable of capturing postoperative heterogeneity more accurately than chronological age or static vulnerability measures alone.

Efficient lignocellulosic biomass conversion under industrially relevant high temperatures is limited by the thermolability of commercial cellulases and a lack of synergistic, system-level thermostable cocktails. To address this gap, a thermostable cellulase cocktail comprising the endoglucanase TpEG, the cellobiohydrolase HmCel6A, and the β-glucosidase TnBglB was established, capable of synergistically hydrolyzing cellulose under high-temperature conditions. To further improve system performance, precise component optimization was performed using an advanced artificial intelligence framework. First, using the protein language model-guided enzyme mining pipeline VenusMine, EG5, an ultra-thermostable endoglucanase, was identified from a large sequence space and exhibited excellent thermostability at 90 °C. Concurrently, protein engineering of HmCel6A guided by the protein language model PRIME generated the variant S347P, yielding a 1.8-fold increase in catalytic activity. Both the wild-type (WT) and engineered cocktails showed excellent high-temperature hydrolytic activity. At 90 °C, DNS assay showed that the filter paper hydrolytic activity of the WT cocktail was approximately sevenfold higher than that of Cellic® CTec3 (Novonesis), while the engineered cocktail exhibited approximately 1.15-fold higher activity than the WT cocktail. HPLC analysis showed that the engineered cocktail released significantly more glucose from corn stover than both CTec3 and the WT cocktail. Furthermore, supplementation of CTec3 with these engineered enzymes led to increased reducing sugar release under the tested supplementation conditions. This study demonstrates the power of integrating artificial intelligence-driven enzyme discovery with protein engineering, expanding the design space for thermostable enzymes while delivering a high-performing cellulase cocktail for industrial-scale, high-temperature biomass saccharification.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive malignancies with limited diagnostic and prognostic markers. Neutrophil extracellular traps (NETs) have recently been implicated in cancer progression, but their clinical relevance in PDAC remains underexplored. In this preliminary study, we investigated NET levels in both peripheral blood and tumor tissues from PDAC patients (n = 30) and explored their associations with clinicopathological features. We quantified NETs using a multiparametric approach that included immunohistochemistry, immunofluorescence, qRT-PCR, ELISA, and flow cytometry. Plasma NET-associated DNA was measured using the Quant-iT PicoGreen assay. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic potential of NETs. We found NET levels were significantly elevated in both tumor tissue and the circulation of PDAC patients compared with healthy controls. The levels of NETs were strikingly higher in patients with advanced tumor stages and grades. Patients' NETs showed a typical morphology with enlarged nuclei, thread-like DNA fibres, and MPO-positive granules, which was confirmed by immunofluorescence analysis. The ROC analysis demonstrated that NETs displayed promising diagnostic performance (AUC = 0.852) compared to widely used conventional markers CEA and CA19-9 within the study cohort. In conclusion, our findings provide preliminary evidence that increased NETosis is associated with PDAC progression and highlight its potential as a diagnostic biomarker. Larger, independent studies are needed to validate these observations and to determine the clinical relevance of NET-associated markers in PDAC.

Large-scale interrogation of genome structure is crucial for understanding how genomic organization influences cellular function, yet existing methods are limited by the low density of achievable modifications or the toxicity of methods. Here we address this gap by presenting a versatile approach that combines gene editing and recombinase technologies. The protocol serves two critical purposes: (1) facilitating the introduction of hundreds to thousands of precise genomic edits per cell and (2) enabling the creation of a controlled platform to systematically investigate the effects of induced genomic rearrangements. Specifically, the method leverages prime editing to insert recombinase recognition sites (for example, loxP) into repetitive genomic regions, such as LINE-1 elements, thereby enabling extensive genetic modifications in human cells. This scale of genome editing has not previously been attainable and supports a wide range of studies, including genome-wide functional analyses and essentiality mapping. Inducing controlled rearrangements with recombinase and tracking cell survival under selective conditions allows direct mapping of genome architecture to cellular fitness, opening new opportunities for genome-wide functional screens and rational synthetic genome design. Unlike methods that rely on double-strand breaks or random transposon insertion, this Protocol supports a programmable installation of thousands of recombination sites at repeat elements, offering denser and more predictable substrates for controlled genome rearrangement. The full protocol takes ~12-18 weeks to complete and requires intermediate to advanced expertise in genome editing, mammalian cell culture and sequencing analysis.

Conventional hydrogel systems for biomedical applications face critical limitations in mechanical robustness, therapeutic functionality, and responsiveness to physiological stimuli, hindering their translation to precision medicine. The rational integration of engineered nanomaterials into injectable hydrogel matrices has emerged as a transformative strategy to overcome these constraints, enabling hierarchical, stimuli-responsive functionalities unattainable in traditional polymer networks. This review provides a mechanistic and translational analysis of injectable nanocomposite (NC) hydrogels, systematically examining how nanoparticle-polymer interfacial interactions govern gelation kinetics, mechanical properties, and controlled therapeutic release. Unlike previous reviews focused on material cataloguing, we critically evaluate the distinctive advantages of NC hydrogels over conventional dynamic hydrogels; including hierarchical drug release profiles, enhanced tumour penetration, and multiscale environmental responsiveness; whilst providing evidence-based assessment of clinical translation pathways. The strategic incorporation of metal-based nanostructures, carbon nanomaterials, lipid carriers, and black phosphorus nanosheets is analysed across four key biomedical domains: advanced drug delivery systems, tissue engineering scaffolds, chronic wound healing platforms, and biosensing technologies. We provide systematic coverage of injectability parameters, smart responsive behaviours, and patient-specific customisation strategies essential for minimally invasive delivery. Critically, this review addresses the gap between preclinical promise and clinical reality by examining actual clinical trial data, regulatory challenges, and manufacturing scalability barriers. Emerging artificial intelligence and machine learning tools for accelerated NC hydrogel design, predictive modelling, and real-time therapeutic monitoring are evaluated as enabling technologies for next-generation precision biomedicine. This comprehensive roadmap equips researchers and clinicians with mechanistic frameworks and practical guidance for translating injectable NC hydrogels from laboratory innovation to clinical impact.

Breast cancer (BC) is the second leading cause of cancer-related deaths worldwide and has a high recurrence rate. This study aimed to evaluate the expression levels of three biomarkers: DNA methyltransferase 1 (DNMT1), histone deacetylase 1 (HDAC1), and metallothionein 1E (MT1E) in BC patients. Peripheral blood and tissue samples from 95 female BC patients and 50 age-matched (&#xb1;5 years) healthy female controls were analyzed using an enzyme-linked immunosorbent assay (ELISA). Diagnostic potential was assessed through receiver operating characteristic (ROC) curve analysis. In silico analyses identified differentially expressed genes (DEGs), Gene Ontology (GO) terms, pathway enrichment, correlation analysis, miRNA-mRNA interactions, and drug-gene networks. Both experimental and computational results revealed significantly higher levels of DNMT1 and HDAC1 but lower levels of MT1E in BC patients compared to controls (p-value&#x2009;<&#x2009;0.0001). Furthermore, tumor expression of these genes correlated with molecular subtypes, showing distinct expression patterns in triple-negative BC (TNBC). Advanced-stage tumors also exhibited increased HDAC1 and DNMT1 expression. GO enrichment analysis indicated that these DEGs are involved in cell division, differentiation, and nuclear functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis linked DNMT1 to the p53 pathway, HDAC1 to mismatch repair, and MT1E to cytokine receptor interactions. The strongest gene correlations were DNMT1-ILF3, HDAC1-RBBP4, and MT1E-MT2A. Additionally, miRNA-mRNA interaction analysis revealed that DNMT1, HDAC1, and MT1E are targeted by multiple miRNAs, with the top interacting miRNAs being hsa-miR-103a-3p for DNMT1, hsa-miR-34a-5p for HDAC1, and hsa-miR-126-3p for MT1E. DNMT1 showed the highest number of miRNA interactions among the three genes. Moreover, 98 drugs were found to interact with these three genes. ROC analysis demonstrated promising diagnostic performance, with areas under the curve (AUC) of 0.916 for DNMT1, 0.792 for HDAC1, and 0.683 for MT1E (95% confidence interval [CI]). These findings suggest that DNMT1, HDAC1, and MT1E show potential as complementary biomarkers in BC diagnosis. However, further validation in larger cohorts and functional studies are warranted.

Brazil is the global leader in the production and export of tropical forage seeds. The livestock sector primarily relies on tropical grasses, including species of Urochloa and Megathirsus maximus, as well as other genera such as Paspalum, Cenchrus, and Setaria. The sustainability and competitiveness of this sector are increasingly threatened by climate change and biotic stresses. While conventional breeding has made progress, enhancing genetic gains requires advanced molecular tools due to the biological complexity of these grasses. Given the growing importance of forage genomics, this paper provides an up-to-date overview of genomic resources available for the main tropical forage species. We synthesized the state-of-the-art applications of genomics, transcriptomics, and functional genetics in forage research, consolidating findings from Brazilian and international institutions. In recent years, significant advances have been made, including the assembly of reference genomes, the development of comprehensive transcriptomic datasets, and the construction of high-density linkage maps. Despite the recent increase in genomic data, we identified significant bottlenecks, including the need for reference pangenomes, standardized phenotyping platforms, and robust functional validation pipelines for novel genes. This review serves as a critical roadmap, emphasizing that collaboration is vital to translate genomic data into resilient, nutritious, and climate-adapted tropical forage cultivars, securing the future of sustainable livestock production.

Spermatozoa undergo capacitation in the female reproductive tract to acquire competence to fertilize the oocyte. Studies describing the molecular pathways underlying successful fertilization indicate that the oviduct regulates the contact between sperm and oocyte. Among these pathways, heat shock proteins (HSPs) are recognized as critical regulators of sperm capacitation. This study synthesizes current understanding of the functional roles of HSPs in sperm capacitation, specifically examining their involvement in protein folding, chaperone activity, signal transduction, and the formation of critical protein complexes, thereby evaluating their potential as targets for future investigations into male infertility. Although, specific interactions of HSPs have been identified, further research is necessary to clarify the roles of these complexes in sperm function. This review presents current knowledge of how HSPs and other signaling molecules affect intracellular signaling pathways during sperm capacitation. Proteomics and metabolomics studies have shown that HSPs are differentially expressed in various male infertility disorders; however, further reviews and extensive clinical trials are necessary to corroborate these findings and confirm HSPs as reliable biomarkers for routine clinical application. Innovative technologies and research methodologies continue to emerge, including CRISPR/Cas9 gene editing, flow cytometry for dynamic processes, high-resolution protein interactions, and advanced proteomic analyses, which may improve our understanding of the impact of HSPs on male infertility. Understanding the specific mechanisms by which HSPs influence sperm capacitation may facilitate the development of new infertility treatments. Further inquiry into the role of HSPs in sperm motility holds significant promise to enhance understanding of male fertility and develop novel strategies for infertility therapy.

Plants are continuously exposed to a wide range of abiotic stresses, including drought, salinity, temperature extremes, nutrient deficiency, and heavy metal toxicity, which severely constrain growth and productivity. To cope with these challenges, plants have evolved sophisticated regulatory networks involving phytohormones and non-coding RNAs (ncRNAs). This review provides a comprehensive overview of the biogenesis and functional roles of major ncRNA classes' microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) and their dynamic interplay with phytohormonal signaling pathways under stress conditions. We highlight how ncRNAs modulate key hormonal pathways, including abscisic acid, auxin, jasmonic acid, ethylene, and gibberellins, to fine-tune stress-responsive gene expression and maintain cellular homeostasis. Special emphasis is placed on nutrient stress and heavy metal toxicity, where ncRNA-mediated regulation influences ion transport, autophagy, reactive oxygen species detoxification, and metabolic reprogramming. Emerging evidence on circRNAs as miRNA sponges further reveals an additional regulatory layer linking developmental processes with stress adaptation. The review also integrates recent advances in high-throughput sequencing, multi-omics approaches, and bioinformatics tools that have enabled large-scale identification and functional annotation of stress-responsive ncRNAs. Furthermore, the application of artificial intelligence and machine learning models in predicting ncRNA target interactions and regulatory networks is discussed as a transformative approach in plant stress biology. Collectively, this synthesis provides a systems-level understanding of ncRNA-phytohormone cross-talk and underscores its potential in developing climate-resilient crops through advanced molecular and computational strategies.

Sustainable production of biofuels and biochemicals from renewable biomass represents a promising alternative to fossil-based feedstocks, offering significant benefits for low-carbon economies and environmental protection. The biochemical 1,2,4-butanetriol (BT) is an important short-chain chiral triol, which is widely used as pharmaceuticals, industrial foam, anticorrosion additives, and plasticizers. Although biosynthesis of BT has been achieved in various engineered microbes, achieving cost-competitive production remains a significant challenge. This chapter focuses on research progress in metabolic engineering of BT production, which mainly includes (1) design of BT biosynthetic pathways for expression in bacterial and yeast cell factories, (2) current metabolic engineering and process optimization strategies to optimize BT production, and (3) utilizing lignocellulosic biomass as a sustainable feedstock for BT production. In addition, future prospects on enhancing BT production efficiency through advanced metabolic engineering and synthetic biology approaches integrating with artificial intelligence (AI)-based technologies are also presented.

Loss-of-function (LOF) alterations in PTCH1 are a hallmark of basal cell carcinoma (BCC) and drive activation of the Hedgehog (Hh) signaling pathway. Hh inhibitors are approved to treat advanced BCC, but little is known about the frequency, biology, and treatment of PTCH1 alterations in other cancers. We analyzed PTCH1 LOF alterations across diverse solid tumors and evaluated outcomes of patients with non-BCC tumors who received Hh inhibitors. Among 121,490 tumor samples, 2064 (1.7%) harbored PTCH1 LOF alterations. Among 13 patients with non-BCC tumors treated with an Hh inhibitor, the response rate was 31%, with responses seen in sebaceous adenocarcinoma, squamous cell lung cancer (SCC), cutaneous SCC and glioblastoma. Median progression-free survival was 4.1 months, and median overall survival was 9.8 months. PTCH1 LOF alterations may identify a tumor-agnostic subset of patients who could derive benefit from Hh inhibitors beyond BCC, supporting further prospective evaluation.

Cucumber is an economically important vegetable crop cultivated worldwide, but its productivity is severely affected by destructive foliar diseases particularly powdery mildew and downy mildew. These pathogens cause significant yield and quality losses and the continuous emergence of new races makes disease management increasingly challenging. Conventional approaches including cultural, biological and chemical control often provide limited and short-term effectiveness. Therefore, the development of host plant resistance remains the most sustainable and environmentally sound strategy for long-term disease control. Recent advances in cucumber genomics and molecular breeding have enabled the identification of resistance-associated loci through SNP genotyping, QTL mapping, genome-wide association studies and marker-assisted selection. Furthermore, multi-omics approaches such as transcriptomics, proteomics and metabolomics combined with innovative technologies like CRISPR/Cas-mediated genome editing, genomic selection and speed breeding are transforming resistance breeding. Therefore, by integrating advanced molecular tools with omics-driven insights, this review aims to accelerate genetic gains and facilitate the development of durable, broad-spectrum mildew-resistant cucumber cultivars for sustainable and resilient production systems.

Hybrids of taxonomically distant plant species have been important sources of genetic variation for introgression breeding in cereals and the generation of maternal haploid lines via paternal genome elimination followed by whole genome duplication. Despite a long history of crossing wheat and barley, the two most important temperate-zone cereals, efficient hybridization between the two species has not been achieved until recently. Here, we describe the crossing technique between suitable wheat and barley genotypes and demonstrate two procedures to confirm and characterize the resulting plants. First, multiplex PCR analysis allows the quick determination of chromosome composition in young plants. Further, advanced in situ hybridization tools such as FISH-GISH provide additional information about the fine structure of the hybrid chromosome complement.

The environment and food security are seriously threatened by the growing demand for food brought on by Pakistan's expanding population. Lab-grown meat has been proposed globally as a sustainable alternative because it offers reductions of up to 96% in water use, 99% in land use, 45% in energy use, and 96% in greenhouse gas emissions compared to conventional meat production. It also has the potential to address ethical and health issues. Although research on lab-grown meat has advanced globally, this is the first empirical study to look at consumer acceptance and awareness in Pakistan. The purpose of this study is to evaluate how consumer acceptance and rejection are influenced by awareness, perceived benefits and concerns, and socio-demographic characteristics. A cross-sectional online survey was used to collect data from 102 university personnel and students, and the data were analyzed in R. The results showed that acceptability levels are strongly influenced by eco-activism, food preferences, and gender. These findings provide the first empirical evidence on Pakistani consumer perceptions of lab-grown meat and offer insights for researchers, policymakers, climate activists, and meat-industry stakeholders to understand the knowledge gap and the factors driving adoption of lab-grown meat for a sustainable food system.