A supervised multiclass framework for mineral classification of Iberian beads.

Research on personal adornments depends on the reliable characterisation of materials to trace provenance and model complex social networks. However, many analytical techniques require the transfer of materials from the museum to the laboratory, involving high insurance costs and limiting the number of items that can be analysed, making the process of empirical data collection a complicated, expensive and time-consuming routine. In this study, we compiled the largest geochemical dataset of Iberian personal adornments (n = 1243 samples) by coupling X-ray fluorescence compositional data with their respective X-ray diffraction mineral labels. This allowed us to develop a machine learning-based framework for the prediction of bead-forming minerals by training and benchmarking 13 of the most widely used supervised algorithms. As a proof of concept, we developed a multiclass model and evaluated its performance on two assemblages from different Portuguese sites with current mineralogical characterisation: Cova das Lapas (n = 15 samples) and Gruta da Marmota (n = 10 samples). Our results showed that decisión-tres based classifiers outperformed other classification logics given the discriminative importance of some chemical elements in determining the mineral phase, which fits particularly well with the decision-making process of this type of model. The comparison of results between the different validation sets and the proof-of-concept has highlighted the risk of using synthetic data to handle imbalance and the main limitation of the framework: its restrictive class system. We conclude that the presented approach can successfully assist in the mineral classification workflow when specific analyses are not available, saving time and allowing a transparent and straightforward assessment of model predictions. Furthermore, we propose a workflow for the interpretation of predictions using the model outputs as compound responses enabling an uncertainty reduction approach currently used by our team. The Python-based framework is packaged in a public repository and includes all the necessary resources for its reusability without the need for any installation.

A prospective evaluation of the prostate microbiome in malignant and benign tissue using transperineal biopsy.

BACKGROUND: The link between the prostate microbiome and prostate cancer remains unclear. Few studies have analyzed the microbiota of prostate tissue, and these have been limited by potential contamination by transrectal biopsy. Transperineal prostate biopsy offers an alternative and avoids fecal cross-contamination. We aim to characterize the prostate microbiome using transperineal biopsy. METHODS: Patients with clinical suspicion for prostate cancer who were to undergo transperineal prostate biopsy with magnetic resonance imaging (MRI) fusion guidance were prospectively enrolled from 2022 to 2023. Patients were excluded if they had Prostate Imaging Reporting and Data System lesions with scores ≤ 3, a history of prostate biopsy within 1 year, a history of prostate cancer, or antibiotic use within 30 days of biopsy. Tissue was collected from the MRI target lesions and nonneoplastic transitional zone. Bacteria were identified using 16S ribosomal RNA gene sequencing. RESULTS: Across the 42 patients, 76% were found to have prostate cancer. Beta diversity indices differed significantly between the perineum, voided urine, and prostate tissue. There were no beta diversity differences between cancerous or benign tissue, or between pre- and postbiopsy urines. There appear to be unique genera more abundant in cancerous versus benign tissue. There were no differences in alpha diversity indices relative to clinical findings including cancer status, grade, and risk group. CONCLUSIONS: We demonstrate a rigorous method to better characterize the prostate microbiome using transperineal biopsy and to limit contamination. These findings provide a framework for future large-scale studies of the microbiome of prostate cancer.

Engineered reversible inhibition of SpyCatcher reactivity enables rapid generation of bispecific antibodies.

The precise regulation of protein function is essential in biological systems and a key goal in chemical biology and protein engineering. Here, we describe a straightforward method to engineer functional control into the isopeptide bond-forming SpyTag/SpyCatcher protein ligation system. First, we perform a cysteine scan of the structured region of SpyCatcher. Except for two known reactive and catalytic residues, none of these mutations abolish reactivity. In a second screening step, we modify the cysteines with disulfide bond-forming small molecules. Here we identify 8 positions at which modifications strongly inhibit reactivity. This inhibition can be reversed by reducing agents. We call such a reversibly inhibitable SpyCatcher "SpyLock". Using "BiLockCatcher", a genetic fusion of wild-type SpyCatcher and SpyLock, and SpyTagged antibody fragments, we generate bispecific antibodies in a single, scalable format, facilitating the screening of a large number of antibody combinations. We demonstrate this approach by screening anti-PD-1/anti-PD-L1 bispecific antibodies using a cellular reporter assay.

Holographic Gaussian Boson Sampling with Matrix Product States on 3D cQED Processors.

We introduce quantum circuits for simulations of multimode state vectors on 3D circuit quantum electrodynamics (cQED) processors using matrix product state representations. The circuits are demonstrated as applied to simulations of molecular docking based on holographic Gaussian boson sampling (GBS), as illustrated for the binding of a thiol-containing aryl sulfonamide ligand to the tumor necrosis factor-α converting enzyme receptor. We show that cQED devices with a modest number of modes could be employed to simulate multimode systems by repurposing working modes through measurement and reinitialization. We anticipate that a wide range of GBS applications could be implemented on compact 3D cQED processors analogously using the holographic approach. Simulations on qubit-based quantum computers could be implemented analogously using circuits that represent continuous variables in terms of truncated expansions of Fock states.

Spatiotemporal variability of lake surface water temperature and water quality parameters and its interrelationship with water hyacinth biomass in Lake Tana, Ethiopia.

Urbanization, agriculture, and climate change affect water quality and water hyacinth growth in lakes. This study examines the spatiotemporal variability of lake surface water temperature, turbidity, and chlorophyll-a (Chl-a) and their association with water hyacinth biomass in Lake Tana. MODIS Land/ Lake surface water temperature (LSWT), Sentinel 2 MSI Imagery, and in-situ water quality data were used. Validation results revealed strong positive correlations between MODIS LSWT and on-site measured water temperature (R = 0.90), in-situ turbidity and normalized difference turbidity index (NDTI) (R = 0.92), and in-situ Chl-a and normalized difference chlorophyll index (NDCI) (R = 0.84). LSWT trends varied across the lake, with increasing trends in the northeastern, northwestern, and southwestern regions and decreasing trends in the western, southern, and central areas (2001-2022). The spatial average LSWT trend decreased significantly in pre-rainy (0.01 ℃/year), rainy (0.02 ℃/year), and post-rainy seasons (0.01℃/year) but increased non-significantly in the dry season (0.00 ℃/year) (2001-2022, P < 0.05). Spatial average turbidity decreased significantly in all seasons, except in the pre-rainy season (2016-2022). Likewise, spatial average Chl-a decreased significantly in pre-rainy and rainy seasons, whereas it showed a non-significant increasing trend in the dry and post-rainy seasons (2016-2022). Water hyacinth biomass was positively correlated with LSWT (R = 0.18) but negatively with turbidity (R = -0.33) and Chl-a (R = -0.35). High spatiotemporal variability was observed in LSWT, turbidity, and Chl-a, along with overall decreasing trends. The findings suggest integrated management strategies to balance water hyacinth eradication and its role in water purification. The results will be vital in decision support systems and preparing strategic plans for sustainable water resource management, environmental protection, and pollution prevention.

Benchmarking various nonadiabatic semiclassical mapping dynamics methods with tensor-train thermo-field dynamics.

Accurate quantum dynamics simulations of nonadiabatic processes are important for studies of electron transfer, energy transfer, and photochemical reactions in complex systems. In this comparative study, we benchmark various approximate nonadiabatic dynamics methods with mapping variables against numerically exact calculations based on the tensor-train (TT) representation of high-dimensional arrays, including TT-KSL for zero-temperature dynamics and TT-thermofield dynamics for finite-temperature dynamics. The approximate nonadiabatic dynamics methods investigated include mixed quantum-classical Ehrenfest mean-field and fewest-switches surface hopping, linearized semiclassical mapping dynamics, symmetrized quasiclassical dynamics, the spin-mapping method, and extended classical mapping models. Different model systems were evaluated, including the spin-boson model for nonadiabatic dynamics in the condensed phase, the linear vibronic coupling model for electronic transition through conical intersections, the photoisomerization model of retinal, and Tully's one-dimensional scattering models. Our calculations show that the optimal choice of approximate dynamical method is system-specific, and the accuracy is sensitively dependent on the zero-point-energy parameter and the initial sampling strategy for the mapping variables.

Mutation-induced shift of the photosystem II active site reveals insight into conserved water channels.

Photosystem II (PSII) is the water-plastoquinone photo-oxidoreductase central to oxygenic photosynthesis. PSII has been extensively studied for its ability to catalyze light-driven water oxidation at a Mn4CaO5 cluster called the oxygen-evolving complex (OEC). Despite these efforts, the complete reaction mechanism for water oxidation by PSII is still heavily debated. Previous mutagenesis studies have investigated the roles of conserved amino acids, but these studies have lacked a direct structural basis that would allow for a more meaningful interpretation. Here, we report a 2.14-Å resolution cryo-EM structure of a PSII complex containing the substitution Asp170Glu on the D1 subunit. This mutation directly perturbs a bridging carboxylate ligand of the OEC, which alters the spectroscopic properties of the OEC without fully abolishing water oxidation. The structure reveals that the mutation shifts the position of the OEC within the active site without markedly distorting the Mn4CaO5 cluster metal-metal geometry, instead shifting the OEC as a rigid body. This shift disturbs the hydrogen-bonding network of structured waters near the OEC, causing disorder in the conserved water channels. This mutation-induced disorder appears consistent with previous FTIR spectroscopic data. We further show using quantum mechanics/molecular mechanics methods that the mutation-induced structural changes can affect the magnetic properties of the OEC by altering the axes of the Jahn-Teller distortion of the Mn(III) ion coordinated to D1-170. These results offer new perspectives on the conserved water channels, the rigid body property of the OEC, and the role of D1-Asp170 in the enzymatic water oxidation mechanism.

Untangling the complex food webs of tropical rainforest streams.

Food webs depict the tangled web of trophic interactions associated with the functioning of an ecosystem. Understanding the mechanisms providing stability to these food webs is therefore vital for conservation efforts and the management of natural systems. Here, we first characterised a tropical stream meta-food web and five individual food webs using a Bayesian Hierarchical approach unifying three sources of information (gut content analysis, literature compilation and stable isotope data). With data on population-level biomass and individually measured body mass, we applied a bioenergetic model and assessed food web stability using a Lotka-Volterra system of equations. We then assessed the resilience of the system to individual species extinctions using simulations and investigated the network patterns associated with systems with higher stability. The model resulted in a stable meta-food web with 307 links among the 61 components. At the regional scale, 70% of the total energy flow occurred through a set of 10 taxa with large variation in body masses. The remaining 30% of total energy flow relied on 48 different taxa, supporting a significant dependency on a diverse community. The meta-food web was stable against individual species extinctions, with a higher resilience in food webs harbouring omnivorous fish species able to connect multiple food web compartments via weak, non-specialised interactions. Moreover, these fish species contributed largely to the spatial variation among individual food webs, suggesting that these species could operate as mobile predators connecting different streams and stabilising variability at the regional scale. Our results outline two key mechanisms of food web stability operating in tropical streams: (i) the diversity of species and body masses buffering against random and size-dependent disturbances and (ii) high regional diversity and weak omnivorous interactions of predators buffering against local stochastic variation in species composition. These mechanisms rely on high local and regional biodiversity in tropical streams, which is known to be strongly affected by human impacts. Therefore, an urgent challenge is to understand how the ongoing systematic loss of diversity jeopardises the stability of stream food webs in human-impacted landscapes.

As teias alimentares representam um emaranhado de interações tróficas associadas ao funcionamento de um ecossistema. Compreender os mecanismos que proporcionam estabilidade a estas teias alimentares é, portanto, vital para os esforços de conservação e gestão dos sistemas naturais. Aqui, primeiro caracterizamos uma meta teia alimentar de riachos tropicais e cinco teias alimentares individuais usando uma abordagem hierárquica Bayesiana unificando três fontes de informação (análise de conteúdo estomacal, compilação de literatura, dados de isótopos estáveis). Com dados sobre biomassa em nível populacional e massa corporal medida individualmente, aplicamos um modelo bioenergético e avaliamos a estabilidade da cadeia alimentar usando um sistema de equações Lotka­Volterra. Em seguida, avaliamos a resiliência do sistema às extinções de espécies individuais usando simulações e investigamos os padrões de rede associados a sistemas com maior estabilidade. O modelo resultou em uma meta teia alimentar estável com 307 ligações entre os 61 componentes. Na escala regional, 70% do fluxo total de energia ocorreu através de um conjunto de dez taxa com grande variação nas massas corporais. Os restantes 30% do fluxo total de energia dependiam de 47 taxa diferentes, apoiando uma dependência significativa de uma comunidade diversificada. A meta teia alimentar foi estável contra extinções de espécies individuais, com uma maior resiliência em teias alimentares que abrigam espécies de peixes onívoros capazes de conectar múltiplos compartimentos da teia alimentar através de interações fracas e não especializadas. Além disso, estas espécies de peixes contribuíram amplamente para a variação espacial entre as cadeias alimentares individuais, sugerindo que estas espécies poderiam operar como predadores móveis conectando diferentes riachos e estabilizando a variabilidade à escala regional. Nossos resultados descrevem dois mecanismos principais de estabilidade da cadeia alimentar operando em riachos tropicais: (i) a diversidade de espécies e massas corporais que protegem contra distúrbios aleatórios e dependentes do tamanho (ii) alta diversidade regional e fracas interações onívoras de predadores que protegem contra a variação estocástica local na composição de espécies. Estes mecanismos dependem de uma elevada biodiversidade local e regional em riachos tropicais, que são conhecidos por serem fortemente afetados pelos impactos humanos. Portanto, um desafio urgente é compreender como a contínua perda sistemática de diversidade põe em risco a estabilidade das teias alimentares em paisagens impactadas pelo homem.

Water Ligands Regulate the Redox Leveling Mechanism of the Oxygen-Evolving Complex of the Photosystem II.

Understanding how water ligands regulate the conformational changes and functionality of the oxygen-evolving complex (OEC) in photosystem II (PSII) throughout the catalytic cycle of oxygen evolution remains a highly intriguing and unresolved challenge. In this study, we investigate the effect of water insertion (WI) on the redox state of the OEC by using the molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) hybrid methods. We find that water binding significantly reduces the free energy change for proton-coupled electron transfer (PCET) from Mn to YZ•, underscoring the important regulatory role of water binding, which is essential for enabling the OEC redox-leveling mechanism along the catalytic cycle. We propose a water binding mechanism in which WI is thermodynamically favored by the closed-cubane form of the OEC, with water delivery mediated by Ca2+ ligand exchange. Isomerization from the closed- to open-cubane conformation at three post-WI states highlights the importance of the location of the MnIII center in the OEC and the orientation of its Jahn-Teller axis to conformational changes of the OEC, which might be critical for the formation of the O-O bond. These findings reveal a complex interplay between conformational changes in the OEC and the ligand environment during the activation of the OEC by YZ•. Analogous regulatory effects due to water ligand binding are expected to be important for a wide range of catalysts activated by redox state transitions in aqueous environments.

A Pragmatic Review on Spinal Cord Stimulation Therapy for Parkinson's Disease Gait Related Disorders: Gaps and Controversies.

BACKGROUND: Parkinson's Disease (PD) is a progressive neurological disorder that results in potentially debilitating mobility deficits. Recently, spinal cord stimulation (SCS) has been proposed as a novel therapy for PD gait disorders. The highest levels of evidence remain limited for SCS. OBJECTIVES: In this systematic review and narrative synthesis, the literature was searched using combinations of key phrases indicating spinal cord stimulation and PD. METHODS: We included pre-clinical studies and all published clinical trials, case reports, conference abstracts as well as protocols for ongoing clinical trials. Additionally, we included trials of SCS applied to atypical parkinsonism. RESULTS: A total of 45 human studies and trials met the inclusion criteria. Based on the narrative synthesis, a number of knowledge gaps and future avenues of potential research were identified. This review demonstrated that evidence for SCS is currently not sufficient to recommend it as an evidence-based therapy for PD related gait disorders. There remain challenges and significant barriers to widespread implementation, including issues regarding patient selection, effective outcome selection, stimulation location and mode, and in programming parameter optimization. Results of early randomized controlled trials are currently pending. SCS is prone to placebo, lessebo and nocebo as well as blinding effects which may impact interpretation of outcomes, particularly when studies are underpowered. CONCLUSION: Therapies such as SCS may build on current evidence and be shown to improve specific gait features in PD. Early negative trials should be interpreted with caution, as more evidence will be required to develop effective methodologies in order to drive clinical outcomes.

Genome sequencing reanalysis increases the diagnostic yield in dystonia.

PURPOSE: We investigated the contribution of genomic data reanalysis to the diagnostic yield of dystonia patients who remained undiagnosed after prior genome sequencing. METHODS: Probands with heterogeneous dystonia phenotypes who underwent initial genome sequencing (GS) analysis in 2019 were included in the reanalysis, which was performed through gene-specific discovery collaborations and systematic genomic data reanalysis. RESULTS: Initial GS analysis in 2019 (n = 111) identified a molecular diagnosis in 11.7 % (13/111) of cases. Reanalysis between 2020 and 2023 increased the diagnostic yield by 7.2 % (8/111); 3.6 % (4/111) through focused gene-specific clinical correlation collaborative efforts [VPS16 (two probands), AOPEP and POLG], and 3.6 % (4/111) by systematic reanalysis completed in 2023 [NUS1 (two probands) and DDX3X variants, and a microdeletion encompassing VPS16]. Seven of these patients had a high phenotype-based dystonia score ≥3. Notable unverified findings in four additional cases included suspicious variants of uncertain significance in FBXL4 and EIF2AK2, and potential phenotypic expansion associated with SLC2A1 and TREX1 variants. CONCLUSION: GS data reanalysis increased the diagnostic yield from 11.7 % to 18.9 %, with potential extension up to 22.5 %. While optimal timing for diagnostic reanalysis remains to be determined, this study demonstrates that periodic re-interrogation of dystonia GS datasets can provide additional genetic diagnoses, which may have significant implications for patients and their families.

Mechanism of Action of KL-50, a Candidate Imidazotetrazine for the Treatment of Drug-Resistant Brain Cancers.

Aberrant DNA repair is a hallmark of cancer, and many tumors display reduced DNA repair capacities that sensitize them to genotoxins. Here, we demonstrate that the differential DNA repair capacities of healthy and transformed tissue may be exploited to obtain highly selective chemotherapies. We show that the novel N3-(2-fluoroethyl)imidazotetrazine "KL-50" is a selective toxin toward tumors that lack the DNA repair protein O6-methylguanine-DNA-methyltransferase (MGMT), which reverses the formation of O6-alkylguanine lesions. We establish that KL-50 generates DNA interstrand cross-links (ICLs) by a multistep process comprising DNA alkylation to generate an O6-(2-fluoroethyl)guanine (O6FEtG) lesion, slow unimolecular displacement of fluoride to form an N1,O6-ethanoguanine (N1,O6EtG) intermediate, and ring-opening by the adjacent cytidine. The slow rate of N1,O6EtG formation allows healthy cells expressing MGMT to reverse the initial O6FEtG lesion before it evolves to N1,O6EtG, thereby suppressing the formation of toxic DNA-MGMT cross-links and reducing the amount of DNA ICLs generated in healthy cells. In contrast, O6-(2-chloroethyl)guanine lesions produced by agents such as lomustine and the N3-(2-chloroethyl)imidazotetrazine mitozolomide rapidly evolve to N1,O6EtG, resulting in the formation of DNA-MGMT cross-links and DNA ICLs in healthy tissue. These studies suggest that careful consideration of the rates of chemical DNA modification and biochemical DNA repair may lead to the identification of other tumor-specific genotoxic agents.

Insertion sequence IS6770 modulates potassium symporter kup transcription in Enterococcus faecalis JH2-2 under low pH conditions.

Enterococcus faecalis is a phylogenetically and industrially relevant microorganism associated with Lactic Acid Bacteria. Some strains of this bacterium are employed as probiotics in commercial applications, while others serve as the principal component in starter cultures for artisanal regional cheese production. However, over the last decade, this species has emerged as an opportunistic multiresistant pathogen, raising concerns about its impact on human health. Recently, we identified multiple potassium transporter systems in E. faecalis, including the Ktr systems (KtrAB and KtrAD), Kup, KimA and Kdp complex (KdpFABC). Nevertheless, the physiological significance of these proteins remains not fully understood. In this study, we observed that the kup gene promoter region in the JH2-2 strain was modified due to the insertion of a complete copy of the IS6770 insertion sequence. Consequently, we investigated the influence of IS6770 on the expression of the kup gene. To achieve this, we conducted a mapping of the promoter region of this gene in the E. faecalis JH2-2 strain, employing fluorescence gene reporters. In addition, a transcriptional analysis of the kup gene was executed in a strain derived from E. faecalis V583 that lacks the IS30-related insertion element, facilitating the identification of the transcriptional start site. Next, the expression of the kup gene was evaluated via RT-qPCR under different pH stressful conditions. A strong upregulation of the kup gene was observed at an initial pH of 5.0 in the strain derived from E. faecalis V583. However, the activation of transcription was not observed in the E. faecalis JH2-2 strain due to the hindrance caused by the presence of IS6770. Besides that, our computational analysis of E. faecalis genomes elucidates a plausible association between transposition and the regulation of the kup gene. Remarkably, the ubiquitous presence of IS6770 throughout the phylogenetic tree implies its ancient existence within E. faecalis. Moreover, the recurrent co-occurrence of IS6770 with the kup gene, observed in 30 % of IS6770-positive strains, alludes to the potential involvement of this genomic arrangement in the adaptive strategies of E. faecalis across diverse niches.

Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction.

Toxicity is a roadblock that prevents an inordinate number of drugs from being used in potentially life-saving applications. Deep learning provides a promising solution to finding ideal drug candidates; however, the vastness of chemical space coupled with the underlying O(n3) matrix multiplication means these efforts quickly become computationally demanding. To remedy this, we present a hybrid quantum-classical neural network for predicting drug toxicity utilizing a quantum circuit design that mimics classical neural behavior by explicitly calculating matrix products with complexity O(n2). Leveraging the Hadamard test for efficient inner product estimation rather than the conventionally used swap test, we reduce the number of qubits by half and remove the need for quantum phase estimation. Directly computing matrix products quantum mechanically allows for learnable weights to be transferred from a quantum to a classical device for further training. We apply our framework to the Tox21 data set and show that it achieves commensurate predictive accuracy to the model's fully classical O(n3) analogue. Additionally, we demonstrate that the model continues to learn, without disruption, once transferred to a fully classical architecture. We believe that combining the quantum advantage of reduced complexity and the classical advantage of noise-free calculation will pave the way for more scalable machine learning models.

Early and long-term outcomes following cardiac surgery for patients with heterotaxy syndrome.

Objective: Heterotaxy syndrome is a complex multisystem abnormality historically associated with high morbidity and mortality. We sought to evaluate the early and long-term outcomes after cardiac surgery in heterotaxy syndrome. Methods: This is a single-center retrospective review of patients with heterotaxy syndrome undergoing single-ventricle palliation or primary or staged biventricular repair from 1998 to 2018. Patients were stratified by single ventricle versus biventricular physiology, and the severity of atrioventricular valve regurgitation. Demographics, anatomic characteristics, and early and late outcomes, including the length of stay, mortality, and surgical or catheter reinterventions, were analyzed. Results: Among 250 patients, 150 (60%) underwent biventricular repair. In-hospital mortality was 7.6% (n = 19). Median follow-up was 5.2 (range, 0-16) years. Among survivors to discharge, mortality was 19% (n = 44) and reintervention was 52% (n = 120). Patients with moderate/severe atrioventricular valve regurgitation were older (32 vs 16 months, P = .02), were more likely to experience adverse events during their index surgical admission (72% vs 46%, P < .001), and had longer in-hospital length of stay (20 vs 12 days, P = .009). Among patients with moderate to severe atrioventricular valve regurgitation, single-ventricle palliation is associated with a greater risk of unplanned reintervention compared with patients undergoing biventricular repair (hazard ratio, 2.13; CI, 1.10-4.12; P = .025). Conclusions: There was no significant difference in early or late outcomes in single-ventricle versus biventricular repair strategies in heterotaxy. In the subgroup of patients with moderate/severe atrioventricular valve regurgitation, patients who underwent single-ventricle palliation were 2.5 times more likely to need a late reintervention compared with those undergoing biventricular repair.

Non-destructive SPE-UPLC-based Quantification of Aflatoxins and Stilbenoid Phytoalexins in Single Peanut (Arachis spp.) Seeds.

Aflatoxins are highly carcinogenic secondary metabolites of some fungal species, particularly Aspergillus flavus. Aflatoxins often contaminate economically important agricultural commodities, including peanuts, posing a high risk to human and animal health. Due to the narrow genetic base, peanut cultivars demonstrate limited resistance to fungal pathogens. Therefore, numerous wild peanut species with tolerance to Aspergillus have received substantial consideration by scientists as sources of disease resistance. Exploring plant germplasm for resistance to aflatoxins is difficult since aflatoxin accumulation does not follow a normal distribution, which dictates the need for the analyses of thousands of single peanut seeds. Sufficiently hydrated peanut (Arachis spp.) seeds, when infected by Aspergillus species, are capable of producing biologically active stilbenes (stilbenoids) that are considered defensive phytoalexins. Peanut stilbenes inhibit fungal development and aflatoxin production. Therefore, it is crucial to analyze the same seeds for peanut stilbenoids to explain the nature of seed resistance/susceptibility to the Aspergillus invasion. None of the published methods offer single-seed analyses for aflatoxins and/or stilbene phytoalexins. We attempted to fulfill the demand for such a method that is environment-friendly, uses inexpensive consumables, and is sensitive and selective. In addition, the method is non-destructive since it uses only half of the seed and leaves the other half containing the embryonic axis intact. Such a technique allows germination and growth of the peanut plant to full maturity from the same seed used for the aflatoxin and stilbenoid analysis. The integrated part of this method, the manual challenging of the seeds with Aspergillus, is a limiting step that requires more time and labor compared to other steps in the method. The method has been used for the exploration of wild Arachis germplasm to identify species resistant to Aspergillus and to determine and characterize novel sources of genetic resistance to this fungal pathogen.

Deep Learning for Cell Migration in Nonwoven Materials and Evaluating Gene Transfer Effects following AAV6-ND4 Transduction.

Studying cell settlement in the three-dimensional structure of synthetic biomaterials over time is of great interest in research and clinical translation for the development of artificial tissues and organs. Tracking cells as physical objects improves our understanding of the processes of migration, homing, and cell division during colonisation of the artificial environment. In this study, the 3D environment had a direct effect on the behaviour of biological objects. Recently, deep learning-based algorithms have shown significant benefits for cell segmentation tasks and, furthermore, for biomaterial design optimisation. We analysed the primary LHON fibroblasts in an artificial 3D environment after adeno-associated virus transduction. Application of these tools to model cell homing in biomaterials and to monitor cell morphology, migration and proliferation indirectly demonstrated restoration of the normal cell phenotype after gene manipulation by AAV transduction. Following the 3Rs principles of reducing the use of living organisms in research, modeling the formation of tissues and organs by reconstructing the behaviour of different cell types on artificial materials facilitates drug testing, the study of inherited and inflammatory diseases, and wound healing. These studies on the composition and algorithms for creating biomaterials to model the formation of cell layers were inspired by the principles of biomimicry.

Persistent GDNF Expression 45 Months after Putaminal Infusion of AAV2-GDNF in a Patient with Parkinson's Disease.

OBJECTIVE: Gene therapy by convection-enhanced delivery of type 2 adeno-associated virus-glial cell derived neurotrophic factor (AAV2-GDNF) to the bilateral putamina seeks to increase GDNF gene expression and treat Parkinson's disease (PD). METHODS: A 63-year-old man with advanced PD received AAV2-GDNF in a clinical trial. He died from pneumonia after anterior cervical discectomy and fusion 45 months later. An autopsy included brain examination for GDNF transgene expression. Putaminal catecholamine concentrations were compared to in vivo 18F-Fluorodopa (18F-FDOPA) positron emission tomography (PET) scanning results before and 18 months after AAV2-GDNF infusion. RESULTS: Parkinsonian progression stabilized clinically. Postmortem neuropathology confirmed PD. Bilateral putaminal regions previously infused with AAV2-GDNF expressed the GDNF gene. Total putaminal dopamine was 1% of control, confirming the striatal dopaminergic deficiency suggested by baseline 18F-DOPA-PET scanning. Putaminal regions responded as expected to AAV2-GDNF. CONCLUSION: After AAV2-GDNF infusion, infused putaminal regions showed increased GDNF gene expression, tyrosine hydroxylase immunoreactive sprouting, catechol levels, and 18F-FDOPA-PET signal, suggesting the regenerative potential of AAV2-GDNF in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.