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PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Wildlife forensic DNA evidence links a suspected vehicle to a fatal lowland tapir (Tapirus terrestris) collision in Misiones, Argentina.

Vehicle collisions are recognized as a major driver of biodiversity loss, particularly in road-dense landscapes, exceeding the impact of invasive species and wildlife trafficking. For large-bodied, slow-reproducing, and low-abundance species, such as the lowland tapir (Tapirus terrestris), this threat can have major impacts. Here, we present a wildlife forensic investigation in Misiones, Argentina, involving a tapir, a species afforded the highest level of legal protection as a Provincial Natural Monument. The fatal hit-by-vehicle (HBV) incident occurred in northern Misiones on 31 March 2019 along Provincial Route 19, in a portion that bisects Parque Provincial Urugua-í, with the driver involved in the collision leaving the scene. The suspect was later located and claimed that the damage to the vehicle resulted from a collision with a horse (Equus caballus) rather than a tapir. To legally resolve the incident, DNA (hair and blood) recovered from the suspected vehicle's bumper (evidence) was compared with tissue samples from the tapir carcass (reference). Genetic confirmation of species identity used a 110-bp region of the mitochondrial cytochrome b gene, and individual identity was assessed using 12 species-specific microsatellite loci. These analyses confirmed that all evidence matched the tapir carcass at both species and individual levels, strongly supporting the association between the suspected vehicle and the HBV tapir, and refuting the alternative explanation proposed by the driver. This case demonstrates the value of using wildlife forensic genetics to reconstruct wildlife-vehicle collisions, supporting environmental law enforcement, and strengthening conservation efforts in the Atlantic Forest of Misiones, Argentina.

Animals↗

PubMed2026

Effectiveness of STK Spray® for semen stain localization on solid surfaces: A specificity and sensitivity study.

Semen identification is a crucial step in sexual assault cases. The aim of this study was to assess STK Spray®, a presumptive test for semen, under controlled conditions including, simulated crime scene stains detection. Easy to use, it can be sprayed directly onto different surfaces and visualized under UV light. Several tests were performed on five different substrates (ceramic tile, drywall, metal, wood, and faux leather). The spray was able to enhance semen fluorescence, especially in diluted samples, with characteristic "globular" spots. Although it showed good specificity, false positives could be obtained with 10% bleach. The fluorescence signals were quantified using ImageJ™ and showed a statistically significant substrate-dependent variability. Mixture analysis indicated that saliva did not interfere with detection of semen, while urine partially suppressed the signal and blood markedly affected its interpretation. Simulation tests with UV lamp comparisons confirmed the importance of choosing the right detection method and the utility of this presumptive test in combination with additional immunochromatographic tests. A preliminary signal retention test showed stable fluorescence for up to two years when stains were stored appropriately. Finally, complete DNA profiles (100% of alleles) were obtained from all samples (n = 24) after exposure to the reagent and UV light. Because of its ability to enhance semen signal, especially on specific surfaces, and its rapidity of use and detection, STK Spray® may represent a useful aid in the preliminary screening phase.

Humans↗

PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗

PubMed2026

Comparative evaluation of molecular technologies for the identification of prevalent non-tuberculous mycobacteria in pulmonary infections: a systematic review and meta-analysis.

BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.

Humans↗

PubMed2026

Pictographs: feasibility and acceptability of a novel method of newborn identification to reduce wrong-patient errors in the NICU.

Wrong-patient errors cause serious harm in newborns. These errors involve ordering and administering tests, procedures, medications, and breast milk to an unintended patient. Newborns receiving care in neonatal intensive care units (NICUs) are at particularly high risk. Although more distinct newborn naming conventions as recommended by the Joint Commission significantly reduce wrong-patient orders, name similarities among multiple-birth infants and truncation of differentiating information in some electronic health record (EHR) systems contribute to this persistent increased risk. Accordingly, novel newborn identifiers are urgently needed. We propose Pictographs - images that are appealing, recognizable, and appropriate - to serve as visual identifiers for newborns in NICUs. Pictographs are selected by caregivers, uploaded into the EHR, and displayed at bedside. As part of a multicenter randomized controlled trial assessing effectiveness of Pictographs to prevent wrong-patient order errors, we initially evaluated feasibility and acceptability of Pictographs at two study sites. Pictographs as novel visual identifiers for newborns in the NICU were generally well received by caregivers and clinicians, and the vast majority of caregivers selected a Pictograph for their infant(s), which was posted at the bedside and uploaded into the EHR. Ordering clinicians - the primary target of the intervention to prevent wrong-patient errors - recognized the potential for Pictographs to provide a visual cue when placing orders, particularly for multiple-birth infants. Here, we describe the rationale, implementation, framework, feasibility, usefulness, and acceptability of Pictographs among key stakeholders. If found effective for preventing wrong-patient errors, Pictographs could be adopted as a patient safety solution in hospitals worldwide.

Female↗

PubMed2026

Identification Matters: How Data Sharing Affects Pupil Honesty and Engagement in Universal School Well-Being Assessments.

PURPOSE: Universal well-being assessments in schools may support early identification of pupils needing mental health support. However, little is known about how privacy and confidentiality concerns influence pupils' acceptability of assessments and willingness to engage authentically. This study examined how hypothetical identification, where responses are linked to pupils and shared with key stakeholders, affects pupils' anticipated honesty and engagement, and whether known help-seeking barriers predict negative responses. METHODS: Cross-sectional data were collected from 12,377 primary (ages 8-10) and secondary pupils (ages 11-17) across 55 schools in England. Pupils reported whether their responses would change if identifiable and shared with school staff, parents/guardians, or external professionals. Responses indicating reduced honesty or likelihood of disengagement were coded as negative. Predictors were examined using mixed-effects logistic regression models, including demographics, school connectedness, and mental well-being. RESULTS: Identification and data sharing influenced pupils' anticipated engagement, particularly in secondary schools. Identification by school staff elicited the highest proportion of negative responses in both phases, whereas external professionals elicited the fewest. Most primary pupils reported they would respond authentically, while a larger proportion of secondary pupils indicated they would respond less honestly or disengage when responses were identifiable and shared. Across primary and secondary samples, low well-being, low school connectedness, and being female were associated with greater likelihood of negative response. DISCUSSION: Pupils' anticipated engagement with well-being assessments is shaped by who accesses their data, with marked developmental differences. Strengthening trust, privacy, and connectedness, and supporting pupils' autonomy, may improve the acceptability and response accuracy.

Humans↗

PubMed2026

The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

Meta-analysis of source identification and apportionment in soil: A systematic review of analytical procedures, receptor modeling, and environmental applications.

Soil pollution poses significant risks to ecosystems and human health, necessitating accurate source identification and apportionment to guide mitigation strategies. This systematic review evaluates the application of Positive Matrix Factorization (PMF) and other receptor models in soil pollution studies, focusing on analytical procedures, tracer indicators, and environmental applications. This review aims to provide a comprehensive framework for conducting soil source apportionment studies, aiding policymakers in designing effective, region-specific environmental management strategies by compiling global trends and methodological insights. The study addresses sampling protocols, emphasizing representativeness and quality control. Data from 500 peer-reviewed publications highlight the dominance of research in China, Eastern Europe, and South Asia, with agricultural soils being the most frequently studied. Key findings reveal that traffic emissions (20.8 %) and industrial activities (19.4 %) are the primary global contributors to soil contamination, with regional variations such as coal combustion in cold climates and agricultural inputs in developing regions. Policy recommendations include stricter industrial regulations, sustainable agricultural practices, and targeted remediation efforts based on source-specific risks.

Soil Pollutants↗

PubMed2026

Chemical and sensory profiling of fermented, washed, and artificially flavored coffee beans: Insights into flavour quality, authenticity, and food safety implications.

This study establishes an integrated framework combining chemical profiling, sensory analysis, and molecular mechanism evaluation to compare flavour quality and authenticity among fermented, washed, and artificially flavored coffees. GC × GC-TOF-MS and UHPLC-HRMS showed that fermented samples had markedly higher ester and aromatic alcohol levels (total esters 74.5 ± 7.8 mg kg-1; phenylethanol 27.5 ± 3.2 mg kg-1, p < 0.01), enhancing fruity-floral notes. Washed coffees contained the highest organic acid concentrations (45.2 ± 3.8 mg kg-1, p < 0.01), supporting brightness and umami. Artificially flavored coffees exhibited elevated exogenous aromatics (vanillin 21.5 ± 3.1 mg kg-1) but significantly fewer Maillard products (p < 0.05) and reduced flavour retention (55% after 14 days). Molecular docking revealed higher theoretical binding affinities for naturally generated compounds, suggesting a potential molecular basis for their greater sensory persistence. The framework supports constructing coffee quality fingerprints and verifying flavour authenticity.

Flavoring Agents↗

PubMed2026

Identification and characterization of G protein-coupled receptors in the nocturnal halictid bee Megalopta genalis.

G protein-coupled receptors (GPCRs) are one of the largest families of membrane proteins in insects, regulating vision, neural signal transduction, and various physiological behaviors. Megalopta genalis exhibits a unique facultatively eusocial lifestyle and possesses adaptations for nocturnal activity; however, its GPCR family has not yet been systematically characterized. In this study, we performed genome-wide identification, phylogenetic analysis, and expression profiling of GPCRs in M. genalis by integrating genomic annotation and transcriptomic analysis. The results showed that a total of 99 GPCRs were identified in the genome of M. genalis, which were classified into four major families. Here, we show that M. genalis has undergone lineage-specific GPCR repertoire remodeling, marked by the expansion of novel orphan receptors and the systematic loss of multiple receptor subtypes, such as the neuropeptide receptors MIP-R and NPFR. Moreover, opsins have formed a diverse array of combinations and non-GPCR odorant receptors have undergone significant expansion via tandem duplication. Together, these features may represent part of the molecular repertoire associated with the adaptation of M. genalis to a nocturnal lifestyle. Furthermore, transcriptomic analysis revealed distinct spatiotemporal expression divergence within each of the Mth/Mthl and Fz GPCR families, suggesting functional specialization across development and adult tissues. This study provides the first systematic identification and initial functional characterization of GPCRs in M. genalis, revealing an evolutionary pattern characterized by the coexistence of contraction and expansion within the GPCR family. These findings lay a foundation for further studies aimed at elucidating the roles of these GPCRs in regulating M. genalis physiology and behavior.

Animals↗

PubMed2026

Deciphering S-nitrosylation-regulated metabolic networks in postmortem beef based on label-free modificomics: Identification of ferroptosis as a novel quality-related pathway.

This study elucidated the molecular mechanisms of S-nitrosylation on postmortem beef metabolism and quality based on the label-free modificomics. Varying degrees of S-nitrosylation were exogenously induced in beef semimembranosus (SM) muscle. Results indicated that a high S-nitrosylation level significantly increased beef pH and Warner-Bratzler shear force (WBSF) while reducing centrifugal loss (P < 0.05). A total of 828 S-nitrosylated proteins and 1458 modification sites were identified, of which 114 sites on 81 proteins (DSNPs) exhibited differential modification abundance, representing an increase of 125% compared with previous proteomics studies. DSNPs were mainly involved in glycolysis, the tricarboxylic acid cycle, oxidative phosphorylation, calcium signaling, cell structure, and ferroptosis. Notably, this study provides the first evidence in postmortem muscle that S-nitrosylation regulates key ferroptosis-related proteins, including ACSL, CP, and TF, offering new insights into the link between S-nitrosylation and the ferroptosis pathway in meat. Correlation analysis demonstrated that TF was significantly negatively correlated with pH and WBSF, but positively correlated with centrifugal loss (P < 0.05). Collectively, protein S-nitrosylation critically modulates postmortem beef quality through the coordinated regulation of multiple metabolic processes. More importantly, the identification of ferroptosis as a S-nitrosylation-sensitive pathway provides a new perspective for regulating meat quality through protein post-translational modifications.

Animals↗

PubMed2026

Genome-wide identification and characterization of ABC transporters and their expression in response to saline-alkaline stress and WSSV infection in Fenneropenaeus chinensis.

ATP-binding cassette (ABC) transporters play crucial roles in stress responses across organisms, yet their functions in Fenneropenaeus chinensis remain largely unknown. In this study, we identified 42 FcABC genes (FcABCs) in the F. chinensis genome and analyzed their phylogenetic relationships, gene structures, and chromosomal distributions. Phylogenetic analysis grouped the FcABCs into eight subfamilies (ABCA-ABCH), with conserved motif and domain compositions within each subfamily. Expression analysis showed that several FcABC genes, including FcABCG5, FcABCA1, and FcABCC3, were significantly induced under saline-alkaline stress in gill and hepatopancreas tissues. In contrast, most FcABCs were downregulated after WSSV challenge, though a subset (e.g., FcABCB1, FcABCC1) exhibited early upregulation. Functional validation via RNA interference demonstrated that knockdown of FcABCG5 increased shrimp mortality under saline-alkaline stress. Cis-regulatory element analysis revealed an enrichment of stress- and immune-related elements in FcABC promoters. Protein-protein interaction network predictions indicated potential roles for FcABCs in cholesterol metabolism and organic anion transport. Our findings provide insights into the roles of FcABC genes in stress adaptation and immune defense, offering candidate genes for the breeding of stress-resistant shrimp varieties.

Animals↗

PubMed2026

Identification of aquaporin (AQP) genes in the noble scallop Chlamys nobilis and characterization of their expression under low-temperature stress.

Aquaporins (AQPs) are transmembrane channel proteins essential for water homeostasis and cellular stress responses. In marine bivalves, their roles in cold tolerance remain poorly understood despite frequent winter mortality events in aquaculture. Here, we identified nine AQP genes in the genome of the economically important noble scallop Chlamys nobilis. Phylogenetic analysis revealed strong conservation with other bivalve AQPs, and structural features, including conserved NPA motifs and ar/R selectivity filters, support their canonical water/glycerol transport functions. Tissue-specific expression profiling showed predominant enrichment in osmoregulatory tissues (gills, intestine) and gonads. Under both chronic and acute low-temperature stress from 23 °C to 9 °C, most CnAQP genes exhibited transient upregulation followed by suppression. Notably, CnAQP4 displayed sustained upregulation, implicating it as a key mediator of long-term cold adaptation. Promoter analysis further revealed abundant cis-elements linked to growth and development as well as immune regulation. Our findings provide the first comprehensive characterization of the AQP family in C. nobilis, highlighting its critical role in maintaining cellular integrity during cold stress and offering molecular targets for selective breeding of cold-tolerant scallop strains.

Animals↗

PubMed2026

Genome-wide identification of the HSP70 superfamily in tropical sea cucumber Stichopus monotuberculatus and their expression analysis under low-salinity stress.

Heat shock proteins (HSPs) are a group of evolutionarily conserved molecular chaperones that serve as indispensable core regulators in preserving cellular homeostasis and orchestrating organismal stress responses. The tropical sea cucumber Stichopus monotuberculatus, a high-value aquaculture species, is sensitive to fluctuations in environmental salinity-a challenge that has emerged as a critical bottleneck limiting its large-scale commercial cultivation. However, no systematic investigation has been conducted to characterize the HSP70 superfamily in S. monotuberculatus and elucidate its functional roles in salinity adaptation. In the present study, we performed a comprehensive genome-wide scan and identified 19 HSP70 superfamily genes in the S. monotuberculatus genome, with the HSP70IV subfamily showing remarkable gene expansion, containing 8 distinct copies. Phylogenetic analysis, conserved motif identification, and gene structure characterization demonstrated high evolutionary conservation within each HSP subfamily. These genes were unevenly distributed across the chromosomes of S. monotuberculatus, and prediction of cis-acting elements revealed that their upstream regulatory regions were enriched with numerous functional elements associated with stress response and immune regulation. Salinity stress experiments revealed that under severe low-salinity conditions (18‰), the expression levels of SmHSPA14L and multiple HSP70IV subfamily members were significantly elevated, while SmHYOU1D was significantly downregulated; in contrast, only subtle changes were detected in the expression of most HSP70 genes under moderate low-salinity stress (24‰). These findings strongly suggest that HSP70 genes, particularly the expanded HSP70IV subfamily, may act as key modulators in the low-salinity stress response. This work provides valuable insight into the molecular mechanisms underlying salinity adaptation in tropical sea cucumbers.

Animals↗