Little is known about how stigma is perceived within psychiatric genetics, a field increasingly central to public discussions about heredity, neurodiversity, and psychiatric risk. Understanding how stigma is perceived and experienced by psychiatric geneticists is important for guiding responsible communication and future stigma-reduction efforts. The International Society of Psychiatric Genetics (ISPG) Stigma Reduction Special Interest Group surveyed members' experiences and perceptions of mental health-related stigma (122 responses; response rate = 11.3%). Two-thirds believed that psychiatric genetics research reduces stigma, and there was a general consensus that researchers should consider stigma-related impacts when communicating research findings. Almost half of respondents perceived public stigma toward the field, and one-third reported avoiding certain research projects due to stigma-related concerns. Among respondents with a mental health diagnosis, 51% described selective disclosure at work shaped by fears of judgment or career impact. Respondents reported the persistence of stigmatizing attitudes within workplaces, despite reporting perceptions of meaningful cultural improvements in recent years. This first empirical assessment of stigma among psychiatric genetics professionals provides several key action points for the field: (1) developing stigma-sensitive research communication guidelines, (2) explicitly include individuals with lived experience, (3) reconsidering mentoring and hiring practices, and (4) evaluating organizational stigma-reducing efforts.
Auricular anomalies, including microtia and preauricular tags (PATs), are frequently overlooked findings on prenatal ultrasound, yet they may represent the earliest and sometimes the only clue to a wide spectrum of craniofacial and multisystem disorders. Distinguishing isolated anomalies from syndromic conditions remains a major diagnostic challenge in fetal medicine. In this illustrated, state of the art case-based review, we propose a practical, imaging-driven diagnostic framework for the prenatal evaluation of auricular anomalies. Drawing on a decade of clinical experience and a curated series of representative cases, we integrate high-resolution ultrasound features with a structured anatomical approach and current advances in molecular genetics. Syndromes associated with microtia and PATs are organized into 3 clinically relevant groups: branchial arch disorders, overlapping syndromic entities, and conditions in which auricular findings are non-specific. Our approach is based on systematic assessment of 3 key craniofacial regions: the auricle and pretragal area, the mandible, and the zygomatic-mandibular complex, combined with evaluation of craniofacial symmetry and targeted screening of extra craniofacial structures. This strategy enables pattern recognition that refines differential diagnosis and guides the appropriate use of genetic testing. Although molecular analyses contribute to etiologic characterization, their diagnostic yield remains limited in certain conditions, particularly craniofacial microsomia, reinforcing the pivotal role of detailed morphological assessment. This integrated imaging-genomic approach provides a clinically applicable framework for improving diagnostic orientation, prenatal counseling, and perinatal management, and highlights the central role of ultrasound in navigating the complexity of auricular anomalies.
Major depressive disorder (MDD) is a widespread, recurrent, and severely disabling psychiatric disorder that imposes a heavy global health burden. Although genetic factors contribute to disease risk, growing evidence highlights gene-environment interaction as the core driver of MDD pathogenesis. Epigenetic regulation acts as a precisely molecular interface that translates environmental stressors into stable changes in gene expression and long-term behavioral phenotypes. In this review, we provide a comprehensive and up-to-date overview of epigenetic dysregulation in MDD, covering five major regulatory layers: DNA methylation, histone post-translational modifications, non-coding RNA networks, RNA chemical modifications, and ATP-dependent chromatin remodeling. We emphasize the spatiotemporal specificity, brain regional selectivity, and cell-type. dependency of these epigenetic events, and their roles in disrupting neuroplasticity, hypothalamic-pituitary-adrenal (HPA) axis function, neurotransmitter homeostasis, and neuroinflammation. We further evaluate the translational value of peripheral epigenetic markers for early diagnosis, severity monitoring, and prediction of antidepressant treatment responses. We also discuss emerging epigenetic-targeted therapeutic strategies, including small-molecule inhibitors, RNA-based modulators, and brain-targeted delivery systems. Finally, we address key obstacles to clinical translation, such as tissue heterogeneity, unclear causality, limited reproducibility, and lack of standardized protocols. We propose future directions centered on single-cell multi-omics, longitudinal clinical validation, and sex-and ethnicity-stratified research. This review aims to establish an integrated framework for understanding MDD epigenetics and accelerating the development of precision diagnostic and therapeutic approaches.
Rupert Riedl did not use the term evolvability, but his writings and teachings in the 1970s and 1980s were important precursors and influences on the research that became associated with the term when it appeared in the 1990s. Riedl served as a motivator for many researchers that later took up questions related to evolvability, and also had an indirect influence in that Riedl-inspired researchers created a research program to combine the systems thinking that Riedl championed with the theoretical population genetics of the modern synthesis. Notably, this was despite a near-total absence of population perspectives in Riedl's personal research. In this essay I review some of Riedl's perspectives on evolvability, speculate on his influence on later evolvability research, and review what we have later learned about the questions and perspectives initiated by him.
Type VIII 3-methylglutaconic aciduria (MGCA8) is a neurodegenerative disorder which involves biallelic pathogenic variants of HTRA2. This gene encodes a mitochondrial serine protease responsible for apoptosis regulation and mitochondrial proteins' quality. Clinical manifestations include dysfunctional muscle tone, movement disorder, severe encephalopathy, epileptic seizures, dysautonomia, feeding difficulty, intermittent neutropenia, bradycardia, and recurrent apneas, often progressing into respiratory failure. We describe a newborn presenting with abnormal muscle tone, progressive dystonic movements, recurrent apneas, feeding difficulties, and epileptic seizures. Biochemical analysis revealed a markedly elevated urinary 3-methylglutaconic acid, and genetic test identified biallelic pathogenic variant in HTRA2. Brain MRI revealed progressive brain atrophy, thalamic hypoplasia, and ventriculomegaly. EEG recordings found organizational abnormalities that turned into epileptic spasms. Despite intensive care, the patient suffered rapid neurological decline and died following a prolonged apnea episode. Thereafter the family had another infant diagnosed with the same biallelic pathogenic variant in HTRA2, that died a few days after birth due to respiratory failure. MGCA8 is a lethal condition characterized by loss-of-function biallelic mutations in HTRA2, which lead to mitochondrial dysfunction and altered apoptosis regulation, especially in the brain. High levels of 3-methylglutaconic acid in urine are one important early diagnostic marker, when associated with a consistent clinical phenotype. Our report contributes to the limited existing case series and provides a detailed characterization of the EEG findings associated with this rare condition.
Somatic cell nuclear transfer (SCNT, or cloning) in wild animal species is considered a potential tool in biodiversity conservation to restore genetic diversity in animal populations and overcome the detrimental effects of inbreeding, climate change, or diseases in rare and endangered animal populations. In January 2026, the Committee for Companion Animals, Non-Domestic and Endangered Species (CANDES) of the International Embryo Technology Society (IETS) organized a round table discussion on future directions in wildlife cloning. This paper reflects the content of discussions among experts in assisted reproductive technologies (ARTs) and specialists in wild animal conservation. After reviewing the advantages and limitations of SCNT, several research priorities were identified. Importantly, strengthening open communication and data exchange among experts was highly recommended to ensure that progress in the field is effective. It was also emphasized that regulatory and ethical frameworks are still required to better integrate this technology into animal conservation efforts. Overall, SCNT remains a highly specialized technology with a distinct, yet currently limited, role in biodiversity conservation. Its true value does not lie in immediate population recovery, but in its capacity to preserve genetic material, generate critical scientific insight, and inspire new collaborations across different disciplines.
Protein nanoparticles offer an innovative approach to next-generation subunit vaccine development by displaying antigenic sequences on the nanoparticle surface. Compared to traditional subunit vaccines, protein nanoparticle vaccines often show improved interaction with the immune system due to their particulate size and repetitive epitope display. Ferritin from Helicobacter pylori assembles into a spherical shape composed of 24 subunits that can display foreign peptides on its surface for use in vaccine development. Surface display can be achieved via genetic fusion of sequences encoding antigenic peptides to the N-terminus of the protein. Ferritin-based vaccine candidates have been increasingly explored through recombinant production in bacteria, insect cells, and mammalian cells; however, this protein had not been produced in plants before. We expressed ferritin from H. pylori in Nicotiana benthamiana and targeted it to the secretory pathway. We also modified ferritin to prevent glycosylation. We found this ferritin variant accumulates to over 0.2 mg/g fresh weight in plant leaves, and genetic fusion of a viral glyco-epitope to this protein significantly increases accumulation. We determined that the epitope is efficiently glycosylated and the protein fusion assembles into characteristic nanoparticles. We found that this fusion protein shows similar iron mineralization to the unmodified ferritin, and introducing a two amino acid substitution decreased this function. This study provides the groundwork for further exploration of plant-produced ferritin as a scaffold for vaccine development.
Genome stability is shaped by DNA sequence and chromatin context, but their relative contributions to double-strand break (DSB) sensitivity remain unclear. We show that the DNA language model, GROVER, can infer DSB location based on sequence. DSB hotspots tend to contain GC-rich sequences that belong to promoters, genes and short interspersed nuclear elements (SINEs). Additionally, we identified several specific short sequences (tokens) that are associated with modulating DSB sensitivity. Another model using chromatin and genome regulatory features outperforms the sequence-only model, highlighting complementary and cell-type specific information. Integrating sequence and genome biological features yields the best performance, demonstrating their synergy. Analyzing this model revealed that, dependent on the sample, genome stability information encoded in H3K36me3 and DNase-seq can be learned from the sequence, but not H3K27ac or H3K9me3. Embedding chromatin data directly into the GROVER architecture enabled cell-type specific modeling with performance matching the full chromatin feature model. Our results suggest that while chromatin and regulatory context provides important information, such as cell-type specificity, much of the information shaping DSB patterns is already encoded in the DNA sequence itself. Our integrative modeling approach not only reveals DSB patterns but also provides a generalizable strategy for tracing predictions in genomic data. Data, models, and a tutorial are available on Zenodo. doi:10.5281/zenodo.16375950. doi:10.5281/zenodo.21131569. Supplementary data are available at Bioinformatics online.
Migraine frequently co-occurs with psychiatric disorders, yet the immunogenetic mechanisms linking these conditions remain largely unexplored. Using cis-eQTL data from 28 immune cell subtypes (1,925 donors) and GWAS summary statistics for migraine and five psychiatric disorders, we performed single-cell transcriptome-wide Mendelian randomization, Bayesian colocalization, genetic correlation, and cross-disease pleiotropy analyses. Independent replication was performed using external datasets. Migraine and its subtypes showed significant positive genetic correlations with all five psychiatric disorders (rg = 0.39-0.73). We identified 83 immune cell gene targets for migraine, 13 for migraine with aura, and 19 for migraine without aura. Among these, 6 targets showed shared associations with anxiety and 1 with depression. Three prioritized genes-HLA-A, CDK2AP1, and TTC24-demonstrated cross-disease pleiotropic effects. Notably, HLA-A in cDC1 exhibited discordant pleiotropy (protective for migraine with aura, risk for depression), with known drug-gene interactions involving antiepileptics and tricyclic antidepressants. These findings suggest that immune cell-specific genes, particularly HLA-A, CDK2AP1, and TTC24, may bridge migraine and psychiatric disorders, offering potential candidates for further investigation into shared immunogenetic mechanisms. Not applicable.
To map how sleep has been assessed in osteoarthritis (OA) and/or inflammatory arthritis (IA), and to synthesise the evidence on the prevalence, characteristics, and relationships between sleep disturbances and these conditions. We conducted a scoping review following the JBI guidelines and reported it following the PRISMA extension guidelines for scoping reviews (PRISMA-ScR). Medline (PubMed), EMBASE, CINAHL, Cochrane Central, PsycINFO, grey literature sources, and ClinicalTrials.gov were searched. Using the RU-SATED framework, we categorised and narratively synthesised sleep dimensions and assessment methods, and tracked the clinical impact of sleep disturbances in OA and IA. 283 records (265 published studies; 18 registered trials) were included. They comprised 171 studies on IA, 77 on OA, and 17 on mixed populations, which were considered separately where appropriate. Sleep assessment methods varied across studies, favouring subjective over objective measurements. Studies primarily focused on sleep satisfaction, duration, efficiency, and sleepiness, overlooking regularity and timing. Global sleep disturbances were observed in ∼40-90% of OA and IA participants, with prevalence estimates varying substantially according to definitions, assessment methods, and study populations. A consistent pattern of discrepancies between subjective and objective sleep metrics was identified. Sleep disturbance is a prevalent and clinically significant feature of both OA and IA, yet it remains underrepresented in research and routine care. This review highlights substantial heterogeneity in sleep assessment and consistent discrepancies between subjective and objective measures. These findings support the need for standardised, multimethod approaches and for integrating sleep evaluation into rheumatology research and clinical guidelines.
Spatial transcriptomics has transformed plant biology by restoring the spatial context lost in bulk and dissociation-based transcriptomic approaches. This review synthesizes recent progress across diverse plant species and tissues, showing that gene expression is not only cell-type specific but also tightly organized by position within organs and developmental niches. Studies of meristems, vascular tissues, and floral organs reveal spatially segregated developmental programs underlying growth and differentiation; seed and grain analyses uncover compartmentalized programs controlling nutrient transport, dormancy, and embryogenesis; plant-microbe and emerging plant-parasite studies show that symbiosis, immunity, and feeding-site development depend on sharply localized host responses; and work on photosynthesis, drought adaptation, and regeneration demonstrates that metabolic and stress-related processes are likewise spatially patterned. Together, these findings establish spatial gene expression as a fundamental organizing principle of plant development and physiology. At the same time, the plant spatial transcriptomics community faces important limitations, including restricted spatial resolution in standard array-based platforms, reliance on computational deconvolution, uneven taxonomic coverage, limited temporal resolution, and a persistent gap between correlation and causal validation. The next stage of plant spatial transcriptomics will require true single-cell spatial resolution, standardized computational pipelines, spatial multi-omics integration, improved benchmarking across platforms, and functional perturbation of spatially defined regulators. By connecting transcriptomic position to biological function, spatial transcriptomics is poised to move plant science from descriptive atlas-building toward mechanistic and predictive understanding with major implications for crop improvement and resilience.
Disorders of intracellular cobalamin metabolism are rare but treatable conditions that mimic bone marrow failure syndromes. An eight-month-old male presented with macrocytic anemia, reticulocytopenia, neutropenia, infections, failure to thrive, and developmental delay. Bone marrow examination showed hypocellularity with paucity of myeloid precursors, dysplastic megakaryocytes, fibrosis, and cytoplasmic vacuolization of hematopoietic precursors. Whole-exome-sequencing identified a homozygous LMBRD1 variant (c.907C > A; p.Pro303Thr), confirmed by parental segregation. Treatment with parenteral hydroxocobalamin resulted in partial improvement. LMBRD1-related cblF deficiency is an exceptionally rare but treatable mimic of inherited bone marrow failure. Early recognition enables targeted therapy.
Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world. El cambio climático y la pérdida de hábitat están impulsando respuestas evolutivas rápidas en poblaciones de todo el mundo, lo que crea una necesidad urgente de realizar predicciones evolutivas en conservación y agricultura. Los enfoques de predicción pueden agruparse en tres escalas temporales: modelos basados en rasgos, que utilizan ecuaciones multivariadas de genética cuantitativa para proyectar respuestas fenotípicas correlacionadas hasta aproximadamente 20 generaciones; análisis basados en alelos, que modelan la dinámica de las frecuencias alélicas hasta 100 generaciones; y puntuaciones compuestas de adaptación, que integran numerosos efectos de pequeña magnitud para generar predicciones a plazos más largos. Sin embargo, estos enfoques han permanecido en gran medida desconectados. Aquí presentamos un marco bayesiano que integra estos tres enfoques complementarios de predicción evolutiva. Nuestro marco combina datos genómicos, fenotípicos y ambientales para generar predicciones probabilísticas que representan explícitamente la incertidumbre. Mostramos cómo estas predicciones pueden validarse mediante evolución experimental, experimentos de campo, ejemplares históricos y trasplantes recíprocos. Una vez validadas, pueden contribuir a los programas de conservación y agricultura al ayudar a predecir qué poblaciones corren riesgo de extinguirse en el futuro, optimizar los programas de mejoramiento genético para las condiciones climáticas futuras y planificar la gestión de los ecosistemas frente al cambio ambiental. Al favorecer una transición hacia enfoques más predictivos en biología evolutiva, este marco podría mejorar nuestra capacidad para gestionar la biodiversidad y salvaguardar la seguridad alimentaria en un mundo cambiante. 气候变化和生境丧失正在推动世界各地的种群产生快速的进化响应，因此，保护生物学和农业领域迫切需要开展进化预测。这类预测可按时间尺度分为三类:基于性状的模型利用多变量数量遗传学方程，预测最多约20代内相互关联的表型响应；基于等位基因的分析模拟最多100代内等位基因频率的动态变化；复合适应评分则汇总许多小效应，以对更长时间尺度作出预测。然而，这些方法迄今仍大多彼此割裂。本文提出一个贝叶斯框架，将这三类互补的进化预测方法整合起来。该框架结合基因组、表型和环境数据，产生明确呈现不确定性的概率预测。我们说明了如何通过实验进化、野外实验、历史标本和互惠移植实验来验证这些进化预测。经验证的预测可推动保护和农业项目，帮助预测哪些种群未来面临灭绝风险，优化面向未来气候条件的育种计划，并规划环境变化背景下的生态系统管理。通过推动进化生物学转向更具预测性的方法，该框架或可提高我们在不断变化的世界中管理生物多样性并维护粮食安全的能力。. As mudanças climáticas e a perda de habitat estão impulsionando respostas evolutivas rápidas em populações de todo o mundo, o que cria uma necessidade urgente de previsões evolutivas em conservação e agricultura. Essas previsões podem ser agrupadas em três escalas temporais: modelos baseados em caracteres, que utilizam equações multivariadas de genética quantitativa para projetar respostas fenotípicas correlacionadas por até cerca de 20 gerações; análises baseadas em alelos, que modelam a dinâmica das frequências alélicas por até 100 gerações; e escores compostos de adaptação, que integram numerosos efeitos de pequena magnitude para gerar previsões em horizontes temporais mais longos. No entanto, essas abordagens permaneceram, em grande parte, desconectadas. Apresentamos aqui um arcabouço bayesiano que integra essas três abordagens complementares de previsão evolutiva. Nosso arcabouço combina dados genômicos, fenotípicos e ambientais para gerar previsões probabilísticas que representam explicitamente a incerteza. Mostramos como essas previsões podem ser validadas por meio de evolução experimental, experimentos de campo, espécimes históricos e transplantes recíprocos. Uma vez validadas, elas podem contribuir para programas de conservação e programas agrícolas ao ajudar a prever quais populações correm risco de extinção no futuro, otimizar programas de melhoramento genético para condições climáticas futuras e planejar o manejo de ecossistemas diante das mudanças ambientais. Ao favorecer uma transição para abordagens mais preditivas na biologia evolutiva, esse arcabouço pode melhorar nossa capacidade de gerir a biodiversidade e salvaguardar a segurança alimentar em um mundo em transformação.
暂无摘要（点击查看详情）
Deubiquitylases modulate cellular processes by removing monoubiquitin or cleaving polyubiquitin chains. The ARISC-RAP80 complex partners with BRCA1-BARD1 to form the BRCA1-A supercomplex, which recognises K63-linked ubiquitin chains at DNA damage sites. ARISC-RAP80 contains multiple ubiquitin-binding sites, yet how these influence recognition and cleavage of K63-polyubiquitylated substrates remains unknown. We discover that a composite three-subunit interface allows ARISC-RAP80 to position K63-linked polyubiquitin chains in its catalytic site. Substrate recognition is further supported by RAP80 and non-catalytic ubiquitin-binding sites that impose a compact conformation on K63-polyubiquitylated substrates. This mechanism exploits the inherent flexibility of long ubiquitin chains and differs considerably from other deubiquitylases. Structure-guided mutageneses validate ubiquitin chain interactions, and cell-based assays demonstrate a functional role of the observed interfaces in chromatin recruitment. Our findings define mechanisms of polyubiquitin chain decoding and cleavage by ARISC-RAP80, linking ubiquitin reading and erasing functions to BRCA1-A mediated DNA damage responses.
Learning requires adaptive changes in neuronal circuits, but how neurons encode learning content in their activity patterns to construct memories remains poorly understood. Using longitudinal multi-site recordings in freely moving male mice performing a sensory discrimination task, we discover the emergence of burst-coding neurons (BCNs) across cortical, thalamic, and extrathalamic regions. BCNs encoded task rules through the presence or absence of bursts, with their proportion increasing as learning progressed. Decoding analyses reveal that BCNs act as the principal carriers of rule information within the thalamocortical system. BCN burst rates scaled with stimulus valence, collapsed when contingencies were degraded, and inverted after repeated rule reversals, demonstrating that bursts dynamically track associative context during learning. Indeed, pharmacological and focal genetic suppression of thalamocortical bursting disrupted learning and task performance, establishing neuronal bursts as context-sensitive drivers of associative learning. These findings identify a burst-based neural code for stimulus-outcome associations in the thalamocortical system and provide causal evidence linking cellular firing dynamics to reward contingency learning.
Long COVID is characterized by persistent, far-reaching effects in convalescent individuals, with pulmonary diffusion impairment emerging as a clinically impactful sequela affecting more than one-third of this population. The salivary microbiome and metabolome, reflecting the oral-lung axis, offer a window into the mechanisms underlying this condition. However, systematic longitudinal evidence on their long-term dynamics after infection and their predictive value for persistent pulmonary diffusion impairment remains scarce. In this prospective cohort, we profiled the salivary bacterial microbiome (16S rRNA sequencing) and metabolome (untargeted LC-MS/MS) in 424 COVID-19 convalescents at 2 (T1) and 3 (T2) years post-discharge, alongside 106 demographically matched healthy controls. To explore whether 2-year salivary multiomics signatures were associated with 3-year pulmonary diffusion status, microbial and metabolic features were ranked using random forest mean decrease in accuracy and used to train 10 machine-learning classifiers after stratified training/internal validation splitting. Because this modeling strategy was exploratory, we further performed a repeated stability-selection analysis across 100 stratified resampling iterations to identify reproducibly selected salivary multiomics features. COVID-19 convalescents exhibited sustained, interrelated salivary microbiome dysbiosis and metabolic reprogramming at 3 years post-infection. The microbial perturbations were characterized by reduced alpha diversity, a shift in phylogenetic dominance from Bacteroidota to Actinobacteriota, and a marked expansion of Proteobacteria at the 2-year follow-up. The microbial co-occurrence networks also became sparser, suggesting diminished stability. Metabolomic profiling revealed upregulation of the TCA cycle, purine/pyrimidine metabolism, arginine biosynthesis, and other pathways at the 2-year follow-up, with a discernible trend toward recovery by year 3. Notably, 36.6% of patients presented with persistent pulmonary diffusion dysfunction at the 3-year follow-up. Leveraging 2-year salivary multiomics signatures, we developed an exploratory proof-of-concept model for predicting 3-year pulmonary diffusion dysfunction. The CatBoost classifier achieved the best overall performance, achieving an area under the curve of 0.808 in the internal validation set; key predictive features included genera Catonella and Actinomyces, and metabolites adenosine 3',5'-diphosphate, triiodothyronine sulfate and betaine. In an exploratory stability-selected analysis, a conservatively tuned CatBoost model based on repeatedly selected features achieved an internal validation AUC of 0.798. This research provides the first longitudinal characterization of the salivary bacterial microbiome and metabolome in COVID-19 convalescents up to 3 years post infection. Furthermore, we developed a novel predictive model for post-SARS-CoV-2 pulmonary diffusion impairment based on salivary multiomics features, which may represent a promising screening tool for identifying high-risk individuals.
Pharmacogenomics has the potential to improve medication responses for the public; however, its adoption in clinical practice has been slow. Consumer representation and engagement are crucial for pharmacogenomics implementation, since it is their data that is central to testing. This study investigated the Australian public's awareness, knowledge, and perceptions of pharmacogenomics via a mixed-methods approach. Firstly, a cross-sectional survey with a nationally representative sample of 772 members of the Australian general public assessed the frequency of pharmacogenomics awareness, knowledge, perceived benefit and concern. Subsequent semi-structured interviews with 21 members of the Australian public provided deeper insights into perceptions through thematic analysis. Over three-quarters (76.3%) of participants were unaware of pharmacogenomics, while 6.2% categorized themselves as aware and knowledgeable about the topic. Interviews found five major themes: (1) Knowledge and Understanding, (2) Trust, (3) Personalized and Holistic Care, (4) Clinical Utility, and (5) Accessibility. Overall, participants highlighted several key steps for pharmacogenomics integration into clinical practice and to increase awareness. These include the importance of simplifying the terminology, providing education and transparency to overcome apprehension, addressing cost concerns, communicating the value clearly and increasing community engagement.
To report the clinical outcomes of photodynamic therapy (PDT), alone and in combination with electrochemotherapy (ECT), in the conservative treatment of bilateral palpebral squamous cell carcinoma (SCC) in a cat, involving the right and left eyelids, with functional preservation and local tumor control. A domestic shorthair cat with histologically confirmed squamous cell carcinoma affecting both eyelid margins underwent different therapeutic protocols. The left eye received a single PDT session with topical a lipophilic methyl ester derivative of 5-aminolevulinic acid (160 mg/g) and red LED light, while the right eye received two sessions, followed by adjuvant ECT with intravenous bleomycin. The lesion in the left eye presented with pallor associated with mild inflammation after the PDT session, with complete resolution in the following days and recovery of its normal clinical appearance. In the right eye, the first two PDT sessions resulted in significant regression of the neoplastic lesions. However, a lesion in the medial canthus showed partial response, requiring adjuvant treatment with ECT, which led to complete clinical resolution, despite the presence of mild eyelid deformity. In this single case report, PDT was associated with clinical regression of superficial lesions, while adjuvant ECT was followed by complete clinical resolution of the residual lesion. The combination of these modalities represents a viable conservative alternative to extensive surgical excision, enabling the tumor remission while preserving the aesthetic appearance and functional integrity of the eyelid.
Subterranean estuaries (STEs) are key bioreactors regulating the quantity and chemical composition of groundwater-derived nitrogen (N) reaching coastal ecosystems. Yet, the microbial controls on N-cycling within these groundwater-seawater mixing zones remain poorly understood. We investigated the spatio-temporal variations in microbial communities and their N-cycling potential within an alluvial Mediterranean STE with high N concentration. We explored changes in microbial abundance, heterotrophic activity, taxonomic composition, and the abundance of N-cycling genes across groundwater samples collected at several depths and distances from the shoreline in winter and summer. Microbial abundance, activity, and diversity varied strongly across hydrochemical zones according to physicochemistry and aquifer depth but showed limited seasonality. Functional predictions suggested a complex, spatially structured suite of N pathways encoded by diverse taxa occupying different STE zones, and quantitative-PCR revealed niche partitioning between ammonia-oxidizing archaea, prevalent in fresh-groundwater, and bacterial denitrifiers enriched in deep-saline layers. Multiple linear model predictions showed a stronger fit for NO2 - and NH4 + concentrations when using microbial properties than when using environmental variables, highlighting their importance for understanding N cycling in STEs. Our results suggest that the functional potential of the STE microbiome is complex and spatially structured across hydrochemical zones, explaining spatial variations in STE N-cycling.