Biology and Life Sciences

Abstract: Proper identification and authentication of medicinal plants are vital for the quality and safety of herbal medications. Morphological and phytochemical-based traditional methods of identification may not suffice in discriminating close relatives, especially in dried, ground and processed herbs. DNA barcoding has emerged as a molecular identification technique that uses genomic loci in differentiating plant species as well as detecting botanical adulteration. This paper reviews the relative performance of three common DNA barcodes; nuclear ribosomal internal transcribed spacer 2 (ITS2) and chloroplast rbcL and matK genes. A structured narrative review was carried out on published literature on amplification and sequencing feasibility, ability of these three DNA barcodes to discriminate plant species, genetic variability, barcode gap properties and the use of the three barcodes in medicinal plant identification. According to published data, the ITS2 is more effective than the other two loci in providing high species discrimination, especially among medicinal plant species while rbcL provides successful amplification and sequencing but with low discrimination power. On the other hand, matK locus provides extra sequence variation with amplification efficiency being dependent on primer compatibility and taxonomy of plants. The findings in the study of medicinal plant species, such as Lamiaceae, provide additional proof that barcoding results can differ greatly depending on the quality of samples, taxonomic groups, database completeness, and identification process. Furthermore, the review stresses the importance of applying species-specific PCR amplification, quantitative PCR amplification, high-resolution melting analysis, and DNA metabarcoding in the detection of adulteration and misidentification in herbal products. However, the problems related to degraded DNA, hybridization, intragenomic polymorphism, primers' preference, and incompleteness of database cannot be overlooked either. Thus, the use of complementary DNA barcodes along with reference samples, validated sequence databases, and phytochemistry is the key.

Abstract: Background: Ranking genes as CAR-T cell targets is limited by the small number of validated positives (168 of 3,220 candidate genes). Antibody-drug conjugates (ADCs), bispecific antibodies and monoclonal antibodies pursue the same kind of surface antigen, so evidence that another modality already targets a gene may help prioritize it for CAR-T therapy. Results: We built an audited evidence table for 3,220 genes that combines single-cell tumor expression for five cancers, protein topology, normal-tissue expression and CAR-T labels from three trial registries, a CAR-construct library and a curated list, together with ADC, bispecific and monoclonal antibody labels. A model with four outputs, one per modality (CAR-T, ADC, bispecific, monoclonal antibody), was scored in an evidence regime and a biology-only regime under nested, gene-grouped cross-validation with fresh-split re-checks. A label-free count of other-modality evidence reached an end-to-end Matthews correlation coefficient (MCC) of 0.516, matching the best learners. Biology alone ranked curated targets well above chance (ROC-AUC 0.78; best MCC 0.283), with logistic regression and XGBoost ahead of a multilayer perceptron (0.207). A two-stage screen-then-classify design reduced class imbalance from 1:16 to between 1:3.8 and 1:8.4 and produced a tiered gene list; with evidence inputs it reached MCC 0.503 with 32 false positives, against 68 for single-stage XGBoost. Conclusions: Other-modality evidence is the strongest available signal for prioritizing CAR-T target genes, and compact, interpretable learners are sufficient with limited data. The audited evidence table and the two-regime design give a transparent basis for ranking candidate genes.

Abstract: Antimicrobial peptides (AMPs) are short, mostly cationic and amphipathic molecules that constitute an evolutionarily ancient arm of innate immunity in organisms ranging from bacteria to humans, and they have re-emerged as leading candidates against antimicrobial resistance (AMR). This review integrates the biosynthesis, structure–function relationships, molecular mechanisms, pharmacology and biomedical translation of AMPs. AMPs can be classified according their biosynthesis and structures: Ribosomally synthesized peptides—including classical host-defence peptides, ribosomally synthesized and post-translationally modified peptides (RiPPs), bacteriocins and non-ribosomal peptides assembled by modular megaenzymes (non-ribosomal peptide synthetases -NRPS. Activity is governed less by a fixed sequence than by a tunable balance of cationicity, hydrophobicity and amphipathicity that jointly determine potency and selectivity. Mechanistically, AMPs act through membrane permeabilization (barrel-stave, toroidal-pore and carpet models) and, as is increasingly recognized, through intracellular targets such as lipid II, nucleic acids, the ribosome and chaperones, as well as through host immunomodulation. The principal barrier to systemic use is due to unfavorable pharmacokinetics, proteolytic lability, rapid clearance and serum sequestration. Therefore, extensive peptide engineering (D-amino acids, cyclisation, lipidation, peptidomimetics) and most recently, machine learning and generative artificial intelligence (AI) to navigate an astronomically large sequence space toward multi-objective optima are used to develop new AMPs. Clinically validated AMPs (nisin, daptomycin, polymyxins, gramicidin, bacitracin) cluster where pharmacokinetic constraints are least binding, while antifungal, antiviral, antibiofilm, immunomodulatory, anticancer and antibiotic-resensitizing applications are advancing. With a comparatively high genetic barrier to resistance, AMPs are positioned as a complementary—not a replacement—class within the response to the AMR.

Abstract: Only about 10% of clinical programmes reach approval, yet drug mechanisms backed by human genetic evidence succeed 2.6 times as often, and plasma-protein evidence raised that to 4.7-fold in a preprint. Each molecular layer adds value only when integrated with the others, a step that automated analysis pipelines leave to human interpretation. Multi-agent artificial intelligence, in which specialist agents reason over individual omics layers under a shared orchestrator, promises to make that connection continuous. We assess how far the evidence supports it. Cross-omics agent systems that generate hypotheses from raw multiomics data exist, but to our knowledge none has been compared head-to-head with conventional pipelines and single-agent baselines. Performance metrics highlight the rapid evolution of multi-omics benchmarks: the best BixBench open-answer score was 17% at release, and a curated multiple-choice subset was answered at 84–98% a year later, yet research-study-scale tasks remain near 0.5. We compare six orchestration patterns, survey 2025–2026 systems and quantify fifteen obstacles, from inflated Type-I error and cascading failures to bias, security and oversight. We then propose eleven testable research directions, each with a validation metric and a rated primary risk, including an agent interoperability layer for biology, a provenance-and-confidence ledger, a living benchmark and trace-level failure diagnosis offered as a research agenda rather than as demonstrated results.

Abstract: The genetic characteristics and protective potential of the Nocardiopsis tropica strains SCPM-O-B-12605 (RCAM04882) and SCPM-O-B-12606 (RCAM04883), previously identified as N. umidischolae, have been studied. In this study, we aimed to conduct a comparative analysis of the functional genetic pool of N. tropica strains SCPM-O-B-12605 and SCPM-O-B-12606 and evaluate the effectiveness of their culture suspensions in a field experiment on the Azhur F1 tomato variety in terms of phytostimulatory, insectoacaricidal, and antiviral activity. Field trials were conducted in open ground in an arid zone of southern Russia. A high degree of genetic similarity was established among the studied strains: the average nucleotide identity of their genomes was 99.9978%. At the same time, differences in the composition of biosynthetic gene clusters were identified. SCPM-O-B-12605 contains clusters of non‑ribosomal peptide synthesis, type I polyketide synthases, and terpene precursor biosynthesis; SCPM-O-B-12606 contains clusters of class III and IV lantipeptides. The genomes also contain genes associated with resistance to heavy metals, drought, and osmotic stress, including systems for the synthesis and transport of compatible osmolytes. The results indicate the potential of the studied strains for the development of biopreparations aimed at increasing productivity and protecting tomatoes in arid conditions.

Abstract: We present a comprehensive, time-resolved dataset of Chinese Hamster Ovary (CHO) cultivation dynamics to support data-driven bioprocess engineering and process analytical technology development. The dataset includes 24 controlled bioreactor cultivations, representing 12 experiments performed in duplicate in a parallel bioreactor system with a working volume of 0.55 – 0.8 L and cultivation durations of 161.5 – 328.5 h. A total of 48 variables are provided, comprising 38 continuous inline variables and 10 offline variables sampled up to twice daily. In addition to standard process measurements, the dataset includes multimodal inline monitoring using turbidity, permittivity, and dissolved CO₂ sensors. The experiments systematically vary cultivation medium, agitation rate, aeration rate, and process mode (batch and fed-batch), providing diverse operating conditions for sensor evaluation, process modeling, and bioprocess analysis. Furthermore, the inoculation cell density, glutamine concentration, and impeller position were varied to further expand the range of investigated process conditions. The dataset preserves realistic measurement characteristics, including noise, and missing values, enabling robust benchmarking of data-driven methods for process monitoring, modeling, and control.

Abstract: Background/Objectives: Gastric cancer (GC) is one of the devastating cancers with frequent metastasis. The non-receptor tyrosine kinase Src may trigger oncogenic signaling, which is a critical target for preventing GC progression. Another potential GC target is the programmed death-1 ligand (PD-L1), which is one of the immune checkpoint molecule responsible for immunosuppression. Moreover, PD-L1 may directly influence cancer progression by regulating tumor-intrinsic events. Interestingly, Src has intimate relationship with tumor-intrinsic PD-L1 in terms of signal transduction. In this study, whether tumor-intrinsic PD-L1 interacts with Src to regulate GC progression was investigated. Methods: Western blot was used for analyzing expression of PD-L1 and activity of Src. Trans-well migration and invasion assays were for investigating whether PD-L1 and Src are required for GC progression in vitro. Lipid nanoparticles SNALPs carrying PD-L1 siRNA was for in vivo knockdown of PD-L1. Results: Experiments using Src inhibitors coupled with PD-L1 knockdown indicated PD-L1 and Src be both upstream and downstream of each other in conventional AGS and patient-derived SD110 GC cells. By scavenging reactive oxygen species (ROS) using an antioxidant dithiothreitol (DTT), both Src activity and PD-L1 expression were found to be ROS signaling-dependent. The ROS-mediated PD-L1/Src signaling was required for migration and invasion of AGS and SD110. Co-targeting Src and PD-L1 suppressed migration of AGS and SD110 more efficiently than single targeting. In the SCID mice, in vivo knockdown of PD-L1 reduced Src activity and metastasis of SD110 tumor from stomach to liver. Conclusions: co-targeting Src and tumor intrinsic PD-L1 might be a promising therapeutic approach in GC therapy.

Abstract: Background/Objectives: LINE-1 (L1) retrotransposons comprise approximately 17% of the human genome. Most are truncated, rearranged, or mutated molecular fossils, and only a small, variably estimated subset of L1 loci retains retrotransposition competence. L1 hypomethylation and retrotransposition have been associated with colorectal cancer (CRC), but comprehensive characterization of individual L1 insertions and their methylation remains challenging because of their repetitive sequence and length. In particular, conventional short-read sequencing provides limited resolution of individual L1 loci. Methods: We used Oxford Nanopore long-read whole-genome sequencing (WGS) to characterize L1 insertion-burden, insertion structure, and methylation in 21 CRC tissue samples, 22 normal adjacent tissue samples (NAT), 13 CRC-negative control tissues (NEG), and single samples of the CRC-derived cell lines SW480 and HT29. We focused on L1HS, the human-specific LINE-1 subfamily, and combined structural insertion detection with native DNA methylation profiling of individual full-length L1HS loci. Results: We identified 5,163 L1HS insertions meeting stringent predefined criteria, including 1,030 full-length insertions. L1HS insertion-burden showed a significant increase from NEG to NAT and CRC tissue groups (Jonckheere–Terpstra, P = 0.0338), while CRC tissues exhibited significantly lower mean L1HS methylation (Kruskal–Wallis \( P = 1.7 \times 10^{-5} \)) and substantial inter-sample and locus-level heterogeneity. Global mean L1HS methylation showed a weak but significant correlation with the number of full-length L1HS insertions, whereas the minimum methylation observed among L1HS loci within each sample showed a stronger correlation with L1HS insertion-burden. Conclusions: These findings demonstrate the utility of long-read sequencing for integrated structural and epigenetic characterization of individual L1HS loci in CRC and provide a framework for future investigation of LINE-1 features in larger, molecularly and clinically characterized cohorts.

Abstract: Microalgae are promising biological platforms for the sustainable production of biodegradable polymers, particularly polyhydroxybutyrate (PHB), a member of the polyhydroxyalkanoate (PHA) family. The environmental impacts of conventional plastics underscore the need for rapid, reliable screening methods to identify microalgal strains that accumulate PHB. Staining-based methods offer a cost-effective approach for the preliminary detection of intracellular polymer inclusions. This study, conducted in Yemen, compared three staining techniques—Nile Red, Nile Blue A, and Sudan Black B—for screening PHB accumulation in microalgal isolates. Nile Blue A was used to visualize putative PHB granules by fluorescence microscopy, Nile Red to detect intracellular hydrophobic inclusions, and Sudan Black B to provide a qualitative assessment by light microscopy. The findings indicate that the highest positive-reading rate was 100% for Nile Blue A dissolved in dimethyl sulfoxide (DMSO), followed by 98.20% for Nile Red in DMSO, 92.79% for Nile Blue A in acetone, and 88.29% for Nile Red in acetone. Sudan Black B in 70% ethanol yielded the lowest positive-reading rate (40.54%), with positive inclusions appearing blue-black. Negative reactions were characterized by pink or red cells or granules (Appendix A). Of the 37 samples examined in triplicate, 32 were classified as positive for intracellular biopolymer accumulation (86.49%). These samples may warrant further investigation for biotechnological applications. FTIR spectra of extracts from selected algal isolates showed absorption bands consistent with PHB, including an ester carbonyl (C=O) stretching band at approximately 1720–1724 cm⁻¹. These spectral features support the preliminary identification of PHB; additional confirmatory analyses are needed to establish polymer identity conclusively.

Abstract: Interpreting human disease-associated variants remains challenging because no single evidence type reliably establishes whether a sequence change disrupts a disease-relevant mechanism. Comparative genomics is widely used to address this problem, particularly through evolutionary conservation and constraint, yet the biological meaning and evidentiary value of comparative signals can vary substantially across genes, variants and disease mechanisms. This critical narrative review examines when evolutionary evidence genuinely improves human disease variant interpretation and when it can mislead. We evaluate conservation and constraint across coding and noncoding sequences in relation to evolutionary distance, orthology, alignment quality, population variation, gene-disease validity, phenotype, functional assays, transcriptomics and structural information. We argue that evolutionary evidence should be treated as a conditional evidence layer rather than a direct indicator of pathogenicity. We further identify evidentiary dependence as an underappreciated source of overconfidence, because conservation measures and computational predictors such as CADD, REVEL and AlphaMissense may draw on overlapping evolutionary data, annotations or clinical labels. To address these limitations, we propose a mechanism-first framework that begins by defining the relevant disease mechanism and transcript, then selects comparative evidence according to the biological claim being tested and evaluates whether additional evidence provides genuinely independent information. The framework also considers lineage-specific function, regulatory turnover, ancestry, reference bias, structural variation, pangenomes and emerging sequence-based models. We conclude that evolutionary evidence is most informative when it helps resolve a specific mechanistic question, identifies variants for functional investigation, or strengthens a coherent interpretation, rather than serving as a shortcut from sequence similarity to clinical causality.

Abstract: The article provides basic knowledge on how to calculate selectivity of ‘genetic zipper’ (‘GZ’) tech-nology-based oligonucleotide pesticides to provide safety for non-target organisms. Also here we rep-resent 500 oligonucleotide pesticides computationally predicted and generated in one day via the DNAInsector web tool (dnainsector.com). 11 nucleotides long pesticides targeting pests’ pre-rRNA and rRNA provide high species specificity and theoretical selectivity at the level of 1 in 4,194,304. None of the 500 computationally predicted oligonucleotide pesticides coincide with each other and this essentially shows that for any ecosystem, even if it consists of closely related species, it is possible to create selectively acting oligonucleotide pesticides. ‘GZ’ technology is a smart approach transfer-ring us to new possibilities of development of potent and selective oligonucleotide pesticides based on new principles prompted by nature.

Abstract: We present a comprehensive, time-resolved dataset of yeast cultivation dynamics to support data-driven bioprocess engineering and process analytical technology development. The dataset comprises 52 controlled bioreactor cultivations of two industrially relevant yeast species, Saccharomyces cerevisiae and Saccharomyces pastorianus, each conducted over 72 – 76 h at two scales (0.7 L and 10 L working volume) under systematic parameter variation. A total of 43 variables are provided, comprising 30 inline variables (30 s resolution) and 13 offline variables sampled up to three times per day, enabling multimodal characterization of cultivation dynamics. Importantly, the dataset preserves real experimental conditions, including measurement noise, outliers, and different types of missing data arising from sensor failures, transmission errors, and process interruptions. By retaining these non-ideal characteristics, the dataset enables realistic evaluation of modeling, monitoring, and control approaches. It provides a valuable resource for dynamic process analysis, system identification, soft sensor development, fault detection, and validation of advanced data-driven methods under practical operating conditions.

Abstract: The feeding of monogastric species of productive interest is a problem for many countries, especially underdeveloped ones; therefore, it is essential to study alternative systems that do not compete with human food, particularly through the revaluation of agri-food waste by fungal fermentation processes, an eco-friendly and efficient strategy. This research evaluated the pretreatment of sugarcane bagasse with the enzymatic crude from Curvularia kusanoi L7, whose laccase activity was the basis of the treatment, and its effect on the nutritional quality of bagasse and on in vivo digestibility in broiler chickens and rabbits. Fiber modifications were assessed by Fourier transform infrared spectroscopy (FTIR), and in vivo digestibility was analyzed using twenty 60-day-old male Cuban Brown rabbits and 30 broiler chickens (HEEB55). Both studies showed similar results: bagasse pretreated with the enzymatic crude presented higher in vivo digestibility than the control, and in poultry its digestibility did not differ from that of the corn-soybean control (87.46%). FTIR evidenced modification of the bagasse cell wall structure. It is concluded that pretreatment with the enzymatic crude rich in fungal laccases from C. kusanoi L7 increases the digestibility of sugarcane bagasse in diets for poultry and rabbits, representing a new option for developing fibrolytic products in modern livestock farming within the framework of fungal fermentation of fibrous sources for animal feed.

Abstract: Common variants in the tyrosinase gene (TYR) shape albinism risk when combined on one haplotype. Homozygosity for the haplotype formed by c.−301C, c.575A (p.Ser192Tyr) and c.1205A (p.Arg402Gln) carries an odds ratio above 82 for albinism, yet these estimates come from European cohorts and say nothing about penetrance or about other ancestries. Using public data, I reconstructed TYR haplotypes in 2,504 unrelated phased genomes from the 1000 Genomes Project, combined them with quality-filtered rare pathogenic variants in 18 albinism genes from gnomAD v4.1, estimated penetrance with Bayes’ rule from published genotype shares among patients, and traced the ancestral origin of each risk allele with gnomAD local-ancestry frequencies in admixed Americans. Homozygosity for a high-risk haplotype ([C;A;A] or [C;C;A]) occurred in about 1 in 4,700 Europeans, four times more often than albinism of any cause, implying a penetrance of 0.77% (95% CI 0.28–2.4%), whereas a high-risk haplotype in trans with a rare pathogenic TYR variant implied a penetrance of 6.4% (3.9–11.4%). The [C;A;A] haplotype was rare (0.8% of European chromosomes) because c.575A and c.1205A lie mainly on different haplotypes, the latter with the protective c.−301T allele. The high-risk haplotypes were absent from African and East Asian samples and, among Latin Americans, were found only in the most European-admixed populations. In admixed Americans, 98–99% of c.575A and c.1205A copies lay on European ancestry tracts, whereas the promoter risk allele c.−301C was more common on Indigenous American tracts. I also show that the rsID reported by Green et al. (2024) for the OCA2 partner variant, rs74653330, corresponds to a different variant (p.Ala481Thr), and identify the correct one as rs121918166. High-risk TYR albinism haplotypes are therefore common but rarely penetrant, and in Latin Americans their risk scales with European ancestry, so ancestry-aware interpretation is needed when these genotypes are reported in diagnostic testing.

Abstract: In 2018 a preprint reported 45 SNPs associated with self-reported “affinity to cannabis” in 26 openSNP participants, including an outlier in MYO16, and proposed a qPCR panel to predict individual cannabis response. The platform that hosted those data, openSNP, deleted its entire holdings in April 2025. We show that the cohort is nonetheless recoverable, and we use it to test the original claims. From Wayback Machine captures of openSNP phenotype 401, the 2017 Internet Archive data dump and the 2020 Zenodo data-freeze of 5,393 genomes, we reconstructed 78 respondents, classified 54 by verbatim self-description, and recovered genotypes for 45 (31 positive, 14 negative affinity) — a 73% larger analytic sample than the original. Genotype decoding was validated by three independent checks. In a genome-wide screen of 69,530 QC-passed SNPs under a 1,000-permutation max-statistic test, no variant was significant (best SNP rs6009352, z = −2.48, empirical p = 0.19; zero SNPs at permutation p ≤ 0.05 at either of two QC thresholds). The MYO16 region showed no signal, and principal component 1 did not separate the phenotype groups, contradicting the original figure. The only nominal signal was CNR1 rs1049353 (z = −2.21, uncorrected p ≈ 0.027; Firth p = 0.071), with the T allele enriched among negative responders — directionally concordant with independent 2025–2026 adverse-event studies. Simulation shows that at this sample size 80% power requires a per-allele odds ratio of about 3.8 even at a nominal threshold, whereas every replicated cannabis-use locus has an odds ratio between 1.03 and 1.2. We conclude that the original panel was statistical noise arising from uncorrected thresholds and a circular selection-then-visualisation procedure, that single-marker prediction of cannabis response is unattainable at consumer-genomics scale, and that the defensible successor programme is pharmacogene-informed safety screening. We provide a fully documented archival reconstruction protocol.

Abstract: Environmental xenobiotics are increasingly recognised as stressors that affect organisms across biological levels, yet researchers often study their consequences at the level of individual species, pollutant categories, or toxicological endpoints. This fragmentation limits understanding of how molecular responses to contamination may translate into organismal impairment, population change, and ecosystem disruption. This review provides a cross-species, metadata-based synthesis of the biological and ecological effects of major environmental xenobiotics, including microplastics, heavy metals, pesticides, pharmaceuticals, persistent organic pollutants, per- and polyfluoroalkyl substances, and other emerging contaminants. We systematically classify published evidence by pollutant type, environmental compartment, exposure route, taxonomic group, geographic region, study design, biological endpoint, and ecological outcome. We emphasise oxidative stress, genotoxicity, immune and endocrine disruption, metabolic and mitochondrial dysfunction, reproductive and developmental effects, behavioural alterations, and changes in organismal fitness. Cross-species comparisons identify conserved toxicological responses, species-specific vulnerabilities, and differences associated with exposure conditions and environmental context. The analysis further examines evidence linking molecular and organismal effects with population dynamics, trophic interactions, bioaccumulation, biomagnification, community structure, and ecosystem functions. By integrating toxicological and ecological evidence within a common metadata framework, this review identifies major geographic, taxonomic, methodological, and evidence-level gaps and highlights limitations in extrapolating molecular toxicity to ecosystem consequences. The proposed framework supports a One Health–One Environment perspective and provides a basis for more comparable, ecologically relevant, and cross-species assessment of environmental xenobiotic impacts.

Abstract: Gastric cancer is the fifth most commonly diagnosed malignancy and the fifth leading cause of cancer death worldwide, and it remains lethal chiefly because it is detected late. Endoscopic screening demonstrably works where it is deployed at scale, but endoscopy cannot be extended to the several hundred million people who would need it; a blood test that stratifies risk before endoscopy is therefore the only realistic route to population-level early detection. Aptamers-short, chemically synthesizable nucleic acid ligands-are attractive recognition elements for such a test, and more than a decade of work has produced hundreds of aptasensors that detect gastric cancer serum markers with impressive analytical sensitivity. Almost none has reached clinical use. Here we argue that this impasse is not a problem of affinity, nor of limit of detection, but of interface design. We resolve aptamer-based serum diagnostics into four coupled interfaces-molecular recognition, the serum matrix, signal transduction and clinical evidence-and show that each has been optimized locally while the constraints they impose jointly have been ignored. We then specify a reference architecture and a minimum evidence standard for a gastric cancer serum aptamer test, and identify the five measurements that would move the field from demonstration to deployment.

Abstract: Mirror biology is the creation of synthetic organisms composed entirely of mirror-image biomolecules, such as D-amino acids and L-sugars, in contrast to the natural use of L-amino acids and D-sugars. Though this novel field promises significant advances in medicine, biomanufacturing, and environmental applications due to the enhanced stability and immune evasion of mirror organisms, its features raise unprecedented biosecurity risks, particularly when combined with cybersecurity vulnerabilities in the digital infrastructures used to design, synthesise, and control mirror life. We mapped the mirror biology development pipeline, from genetic circuit design and cloud-based bioinformatics to automated laboratory systems, to examine the unprecedented biosecurity risks associated with mirror biology. We highlighted key cyber biosecurity vulnerabilities, including data manipulation, unauthorised access, and firmware tampering. Case studies illustrate specific risks such as tampering with genetic design tools and introducing harmful DNA sequences into supply chains. The paper reviews existing technological safeguards, including encryption, zero-trust architectures, AI-enabled anomaly detection, and governance mechanisms such as biosafety oversight and redline enforcement. It emphasises the need for inclusive governance, capacity building, and international collaboration to ensure that mirror biology is not pursued as a field of organism- level research.

Abstract: Acute kidney injury (AKI) is associated with mortality and chronic kidney disease, but conventional monitoring may detect it late. Drug-induced kidney injury (DIKI) is a potentially preventable cause of AKI and an important concern in people living with Human Immunodeficiency Virus (HIV) who receive potentially nephrotoxic medications. Serum creatinine and urine output describe functional changes, but do not directly measure tubular injury. Candidate biomarkers provide complementary information about injury, stress, inflammation, and filtration; their interpretation depends on the specimen, assay, timing, and clinical setting. This narrative review examines biomarker translation with a focus on point-of-care DIKI testing in resource-limited HIV/antiretroviral therapy (ART) services. It distinguishes analytical validity, clinical validity, clinical utility, and implementation, and proposes a staged evaluation roadmap. Priorities include reliable measurement under routine conditions, independent validation of decision thresholds, comparison with existing clinical assessments, and prospective evaluation of biomarker-guided care. Economic and equity assessments should accompany clinical studies. Earlier detection is valuable when a reliable result supports an effective clinical response; diagnostic accuracy alone does not establish patient benefit.

Abstract:

Plant essential oils (EOs) are promising sources of botanical biopesticides, and the genus Piper is particularly rich in bioactive constituents. This study investigated the chemical composition and biopesticidal potential of the EOs from seven Amazonian Piper species. The oils were characterized by GC–MS and evaluated for their phytotoxicity against Lolium perenne and Lactuca sativa, their antifeedant activity against Spodoptera littoralis, Myzus persicae and Rhopalosiphum padi, their antifungal activity against Aspergillus niger and Alternaria alternata, and their nematicidal activity against Meloidogyne javanica; composition–activity relationships were explored by multivariate analysis. The oils resolved into two chemotypes, one dominated by phenylpropanoids (mainly apiol) and the other by sesquiterpenes. Notably, all oils selectively inhibited the growth of the grass L. perenne while sparing or stimulating the dicot L. sativa. The apiol-rich oils of P. hispidum, P. stellipilum and P. demeraranum showed the strongest antifeedant effects on aphids, and all oils inhibited spore germination of both fungi. Principal component analysis associated apiol, but not dillapiol, with the phytotoxic and antifeedant activities, whereas antifungal activity was unrelated to the main compositional gradient. No nematicidal activity was observed. These results identify apiol-rich Amazonian Piper EOs as promising candidates for managing grass weeds, aphids and phytopathogenic fungi.