Futuristic Biotechnology

Synthesis and Biological Applications of Roasted Foxnut-Mediated Silver Nanoparticles

Tue, 30 Jun 2026 00:00:00 +0000

Nanotechnology is developing into a fast-expanding discipline with extensive use in medicine, pharmaceuticals, and environmental sciences. AgNPs have been of particular interest because of their potent antimicrobial and antioxidant effects. Objectives: To synthesize silver nanoparticles using roasted foxnut (Euryale ferox) extract, which was utilized as an eco-friendly and cost-effective green method. Methods: A green method involving the synthesis of silver nanoparticles using roasted foxnut (Euryale ferox) extract was utilized in the current study as an eco-friendly and cost-effective green method. The roasted foxnut extract acted as a natural reducing and stabilizing agent. Silver nanoparticles were prepared by combining foxnut extract with silver nitrate solution, and the formation of silver nanoparticles was observed by a change in color of the light-yellow solution to brown. To ascertain the formation of nanoparticles, also the functional groups involved in their formation, UV-Visible spectroscopy and FTIR assisted in characterizing the nanoparticles. To determine the biological potential of the nanoparticles synthesized, antioxidant and antibacterial assays were conducted. Results: The antioxidant activity of nanoparticles was tested at 500 ppm and 1000 ppm with the assistance of the DPPH free radical scavenging assay. For statistical analysis, one-way ANOVA was used, and SPSS version 22.0 was used. The results were statistically significant (p˂0.05) with higher scavenging efficiency observed at 1000 ppm. The agar well diffusion method was used to test the antibacterial activity against Escherichia coli and Staphylococcus aureus. Conclusions: Roasted foxnut extract-derived silver nanoparticles used in biomedical and pharmaceutical fields should be emphasized owing to significant antioxidant and antibacterial properties.

Comprehensive in-Silico Characterization of Deleterious IDH2 Variants and Their Structural and Functional Implications in Acute Myeloid Leukemia

Afia Muhammad Akram, Huma Nosheen, Hafsa Zaheer, Shanza Chaudhary, Zafar Iqbal — Tue, 30 Jun 2026 00:00:00 +0000

Mutations in the isocitrate dehydrogenase 2 (IDH2) gene are frequently implicated in the pathogenesis of acute myeloid leukemia (AML). Objectives: To comprehensively evaluate the structural and functional consequences of deleterious single nucleotide polymorphisms (SNPs) in the IDH2 gene using an integrative in silico approach. Methods: SNP data were retrieved from public databases, and multiple bioinformatics tools were employed to predict pathogenic variants, Structural stability, conformational changes, Conservation analysis, RNA folding alterations, and protein-protein interactions. Results: A total of 10 high-confidence deleterious SNPs were identified, predominantly located in evolutionarily conserved regions. These variants significantly affected protein stability, increased hydrophobicity, disrupted structural conformation, and reduced protein-protein interaction affinity. RNA folding analysis further suggested altered transcript stability. Conclusions: Collectively, these findings highlight the potential of IDH2 variants as molecular markers in AML and provide insights into their structural and functional implications. This study underscores the importance of integrative computational approaches in prioritizing clinically relevant mutations and may facilitate future experimental and therapeutic investigations.

Statistical Characterization of Plant Biosensor Data: Distributional Properties and Inter-Variable Relationships

Maham Riaz — Tue, 30 Jun 2026 00:00:00 +0000

Precision agriculture is now increasingly being monitored with continuous biosensors. But many datasets are analyzed for predictive modeling without any basic statistical properties of the data being characterized, which is required to be able to determine whether it is appropriate for downstream use. Objectives: To characterize the distributional properties of the key environmental and soil biosensor variables, to assess the linear relations among variables, and to determine if the biosensor readings vary systematically across individual plants of a biosensor-monitored dataset. Methods: A de-identified dataset of plant biosensor readings was used, consisting of 120 readings per plant from 10 plants spanning an approximate 6-hour time interval. The soil moisture, ambient temperature, soil temperature, humidity, light intensity, soil pH, nitrogen level, and phosphorus level were analyzed. Descriptive statistics were conducted, normality was tested, and ANOVA was used. Results: All variables showed very peaked and leptokurtic distribution shapes (skewness and excess kurtosis values close to zero). The patterns here are not a formal goodness-of-fit test against a uniform distribution, so they are not definitive statements of uniformity, but rather hypotheses that should be considered. Conclusions: The distributional patterns of the biosensor variables were very symmetrical and flattened (indicating uniformity) and had very low inter-variable correlation. The statistical characteristics in these readings indicate that single-timepoint readings alone might not be suitable for predicting an outcome in a meaningful way without extra labeled outcome data and engineered temporal properties. The results provide a baseline of statistics to be used in subsequent research with this data.

Sodium Bicarbonate and Hydrogen Peroxide Irrigation Improves (Ex Vitro) Survival of Agrobacterium-Transformed Wheat. Plantlets: A Comparative Assessment of Post-Regeneration Interventions

Muhammad Tahir Arshad — Tue, 30 Jun 2026 00:00:00 +0000

Low ex vitro survival rates of transgenic wheat plantlets following transfer from tissue culture to soil represent a major constraint limiting the efficiency of genetic transformation pipelines, with losses often exceeding 70-90%. Objectives: To compare the effectiveness of four simple, low-cost post-regeneration interventions PPM supplementation, photo-acclimatization, modified root-transfer technique, and irrigation with sodium bicarbonate Na₂CO₃ + H₂O₂ in improving the ex-vitro survival of Agrobacterium-transformed Borlaug-16 wheat plantlets, and to identify the most practical protocol modification for routine transformation workflows. Methods: Fifty putative transgenic wheat plantlets (Triticum aestivum L. cv. Borlaug-16), generated via Agrobacterium tumefaciens (strain AGL1)-mediated transformation of immature embryo-derived calli with a Bar gene selection cassette, were allocated to four treatment groups (n=10 each) and one untreated control (n=10). Genomic DNA was extracted using the cetyltrimethylammonium bromide (CTAB) method, and PCR analysis targeting the ubiquitin promoter–Bar gene junction confirmed transgene integration in all surviving plantlets. Results: The Na₂CO₃ + H₂O₂ irrigation treatment achieved the highest survival rate at 30%, representing a 20-percentage-point improvement over the untreated control (10%). In contrast, PPM supplementation showed no improvement (10%), while both photo-acclimatization and modified root-transfer resulted in 0% survival. PCR analysis confirmed the presence of the expected ~1 kb ubiquitin–Bar amplicon in all surviving plantlets. Conclusions: Supplementing irrigation water with Na₂CO₃ and H₂O₂ provides an inexpensive and effective strategy for ex-vitro survival of transgenic wheat plantlets, whereas PPM, photo-acclimatization, and tissue-wrapped root transfer offered no advantage under the conditions tested.

Bioactive Phytochemicals and Future Biotechnological Strategies in Obesity Management

Farhat Bano — Tue, 30 Jun 2026 00:00:00 +0000

According to the World Health Organization (WHO), more than one billion people were living with obesity in 2022. This chronic metabolic disorder is associated with increased morbidity and mortality worldwide. The increasing frequency of obesity has contributed to the development of cardiovascular diseases, type 2 diabetes mellitus, hypertension, stroke, sleep apnea, fatty liver disease, osteoarthritis, and certain types of cancer. Obesity develops when calorie intake exceeds calorie expenditure; its pathogenesis is highly complex and involves genetic, environmental, hormonal, neurochemical, and sedentary lifestyle factors (1). Numerous traditional herbs, including cinnamon, Nigella sativa, fenugreek, bitter melon, ginger, turmeric, and green tea, have been investigated for their potential benefits for metabolic health. These herbs may influence lipid metabolism, glucose homeostasis, and appetite-regulating pathways, generating considerable interest in identifying the bioactive phytochemicals responsible for their therapeutic effects (2). Biotechnology has transformed natural-product research from traditional empirical observations into a systematic scientific approach. Advanced biotechnological tools enable the rapid screening of medicinal plants for biologically active compounds with potential therapeutic applications. High-throughput screening, molecular characterization, and pathway-based investigations facilitate the identification of bioactive phytochemicals and their molecular targets. These approaches not only improve our understanding of the mechanisms underlying herbal therapies but also accelerate the development of novel therapeutic agents for obesity and related metabolic disorders (3). The growing interest in herbal medicine has highlighted the importance of identifying and isolating bioactive phytochemicals responsible for therapeutic effects. Biotechnology plays a key role in explaining the mode of action of anti-obesity herbs. Advanced analytical and molecular approaches allow researchers to identify bioactive chemical compounds produced by herbs. Modern biotechnology has provided powerful tools to investigate potent bioactive photochemicals present in medicinal plants rather than relying solely on crude herbal preparations. Advanced techniques such as chromatography, mass spectrometry, metabolomics, and molecular profiling enable researchers to isolate, characterize, and evaluate phytochemicals responsible for biological activity. Studying these compounds separately may provide valuable insights into their mechanisms of action, molecular targets, efficacy, and safety. Such an approach may facilitate the development of novel anti-obesity drugs derived from natural products with improved therapeutic properties and reduced adverse effects (3- 5). Recent advances in biotechnology have further accelerated natural-product-based drug discovery. Genomics, proteomics, metabolomics, and bioinformatics are increasingly being used to identify molecular pathways involved in obesity and to evaluate the therapeutic potential of bioactive compounds. Artificial intelligence (AI) and computational drug discovery have emerged as powerful tools capable of analyzing large biological datasets, predicting molecular interactions, and identifying promising therapeutic candidates [6]. These technologies may significantly reduce the time and cost required for drug development while improving the efficiency of identifying compounds with desirable pharmacological properties [7].

The integration of knowledge with modern biotechnology represents a promising strategy for future anti-obesity drug development. Identification of bioactive phytochemicals and characterization of their molecular targets may provide valuable information regarding appetite regulation, energy balance, neurochemical, and metabolic control. As obesity continues to affect an increasing proportion of the global population, biotechnology-driven approaches combined with natural product research may pave the way for safer, more effective, and personalized therapeutic strategies for obesity management.

Approaches for Pandemic Preparedness and Response: Lessons from the SARS-CoV-2 Pandemic — A Global Narrative Review

Nida Shabbir, Urooj Irshad, Muhammad Naveed Anjum — Tue, 30 Jun 2026 00:00:00 +0000

SARS-CoV-2 emerged in December 2019 and rapidly spread globally, catalyzing an unprecedented acceleration of biotechnology innovation. The pandemic served as a real-world proving ground for mRNA and nucleic-acid vaccine platforms. To synthesize current evidence on futuristic biotechnology platforms developed or matured during the SARS-CoV-2 pandemic, to evaluate their translational readiness and limitations, and to outline how their convergence could reshape preparedness for future biological threats, framed against the epidemiological and risk-factor lessons of COVID-19. A narrative literature review was conducted following standard review guidance. A systematic search was performed in PubMed, Scopus, and Web of Science for articles published between December 2019 and July 2026, combining the keywords SARS-CoV-2, epidemiology, mRNA vaccine, CRISPR diagnostics, artificial intelligence, nanotechnology, and wearable biosensor. Peer-reviewed, English-language articles reporting original data, technology-validation studies, or authoritative surveillance reports were eligible; conference abstracts, non-peer-reviewed preprints, and articles without full text were excluded. Two reviewers independently screened titles and abstracts and assessed full texts for eligibility; disagreements were resolved by discussion. As of July 2026, the World Health Organization has reported over 7 million deaths globally. Lipid-nanoparticle-encapsulated mRNA vaccines demonstrated that nucleic-acid platforms can be designed, manufactured, and deployed within months rather than years, and next-generation bivalent and pan-sarbecovirus candidates are now in development. CRISPR-Cas12/Cas13-based diagnostics achieved RT-qPCR-comparable sensitivity at a fraction of the cost and turnaround time. The SARS-CoV-2 pandemic has catalyzed future biotechnology, validating nucleic acid vaccine platforms, CRISPR diagnostics, AI-driven drug discovery, nanomedicine, and digital/genomic surveillance as complementary, convergent tools.

AI-Designed Synthetic CRISPR Enzymes: Evolving Molecular Scissors Beyond Natural Constraints

Shaista Khalid — Tue, 30 Jun 2026 00:00:00 +0000

Therapeutic gene editing has historically relied on naturally evolved bacterial nucleases (SpCas9, Cas12a), imposing constraints: rigid protospacer-adjacent motif (PAM) requirements, protein sizes challenging adeno-associated virus packaging, and pre-existing human immunity. This narrative review assesses the paradigm shift from natural-product discovery toward generative artificial intelligence (AI) for engineering non-natural CRISPR-Cas nucleases with user-defined properties. This study synthesizes the design–build–test–learn pipeline encompassing protein language models (ESM3), diffusion-based structure generators (RFdiffusion, ProteinMPNN), and property-specific architectures (Protein2PAM). High-throughput platforms like Sequence Display generate >10 million sequence–activity data points per experiment for closed-loop validation. AI-generated OpenCRISPR-1 (>400 mutations from SpCas9) matches natural on-target efficiency while achieving sub-1% median off-target indels and up to 95% reduction at specific sites. Protein2PAM-evolved Nme1Cas9 variants show broadened PAM tolerance and up to 50-fold increased activity without iterative evolution. Generative AI addresses PAM restriction, packaging, and immunogenicity simultaneously. However, in vivo validation, long-term genotoxicity data, and biosecurity governance gaps remain unresolved.