MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks

The chemical properties of metal complexes are strongly dependent on the number and geometrical arrangement of ligands coordinated to the metal center. Existing methods for determining either coordination number or geometry rely on a trade-off between accuracy and computational costs, which hinders their application to the study of large structure data sets. Here, we propose MetalHawk (https://github.com/vrettasm/MetalHawk), a machine learning-based approach to perform simultaneous classification of metal site coordination number and geometry through artificial neural networks (ANNs), which were trained using the Cambridge Structural Database (CSD) and Metal Protein Data Bank (MetalPDB). We demonstrate that the CSD-trained model can be used to classify sites belonging to the most common coordination numbers and geometry classes with balanced accuracy equal to 96.51% for CSD-deposited metal sites. The CSD-trained model was also found to be capable of classifying bioinorganic metal sites from the MetalPDB database, with balanced accuracy equal to 84.29% on the whole PDB data set and to 91.66% on manually reviewed sites in the PDB validation set. Moreover, we report evidence that the output vectors of the CSD-trained model can be considered as a proxy indicator of metal-site distortions, showing that these can be interpreted as a low-dimensional representation of subtle geometrical features present in metal site structures.

Novel rat model of gaming disorder: assessment of social reward and sex differences in behavior and c-Fos brain activity

RATIONALE

In 2018, the International Classification of Diseases (ICD-11) classified Gaming Disorder (GD) as a mental disorder. GD mainly occurs among adolescents, who, after developing addiction, show psychopathological traits, such as social anxiety, depression, social isolation, and attention deficit. However, the different studies conducted in humans so far show several limitations, such as the lack of demographic heterogeneity and equal representation of age, differences in the type of game and in the follow-up period. Furthermore, at present, no animal models specific to GD are available.

OBJECTIVES

To address the lack of an experimental model for GD, in the present work, we proposed a new GD rat model to investigate some peculiar tracts of the disorder.

METHODS

Two-month-old Wistar Kyoto rats, both males and females, were subject to a five-week training with a new innovative touch-screen platform. After five weeks of training, rats were assessed for: (a) their attachment to the play under several conditions, (b) their hyperactivity during gaming, and (c) the maintenance of these conditions after a period of game pause and reward interruption. After sacrifice, using immunohistochemistry techniques, the immunoreactivity of c-Fos (a marker of neuronal activity) was analyzed to study different neural areas.

RESULTS

After the training, the rats subjected to GD protocol developed GD-related traits (e.g., hyperactivity, loss control), and the behavioral phenotype was maintained consistently over time. These aspects were completely absent in the control groups. Lastly, the analysis of c-Fos immunoreactivity in prelimbic cortex (PrL), orbitofrontal cortex (OFC), nucleus Accumbens, amygdala and bed nucleus of stria terminalis (BNST) highlighted significant alterations in the GD groups compared to controls, suggesting modifications in neural activity related to the development of the GD phenotype.

CONCLUSIONS

The proposal of a new GD rat model could represent an innovative tool to investigate, in both sexes, the behavioral and neurobiological features of this disorder, the possible role of external factors in the predisposition and susceptibility and the development of new pharmacological therapies.

Point-Of-Care Ultra-Portable Single-Molecule Bioassays for One-Health

Screening asymptomatic organisms (humans, animals, plants) with a high-diagnostic accuracy using point-of-care-testing (POCT) technologies, though still visionary holds great potential. Convenient surveillance requires easy-to-use, cost-effective, ultra-portable but highly reliable, in-vitro-diagnostic devices that are ready for use wherever they are needed. Currently, there are not yet such devices available on the market, but there are a couple more promising technologies developed at readiness-level 5: the Clustered-Regularly-Interspaced-Short-Palindromic-Repeats (CRISPR) lateral-flow-strip tests and the Single-Molecule-with-a-large-Transistor (SiMoT) bioelectronic palmar devices. They both hold key features delineated by the World-Health-Organization for POCT systems and an occurrence of false-positive and false-negative errors <1-5% resulting in diagnostic-selectivity and sensitivity >95-99%, while limit-of-detections are of few markers. CRISPR-strip is a molecular assay that, can detect down to few copies of DNA/RNA markers in blood while SiMoT immunometric and molecular test can detect down to a single oligonucleotide, protein marker, or pathogens in 0.1mL of blood, saliva, and olive-sap. These technologies can prospectively enable the systematic and reliable surveillance of asymptomatic ones prior to worsening/proliferation of illnesses allowing for timely diagnosis and swift prognosis. This could establish a proactive healthcare ecosystem that results in effective treatments for all living organisms generating diffuse and well-being at efficient costs.

Theoretical prediction of nanosizing effects and role of additives in the decomposition of Mg(BH4)2

The energetic transition towards renewable resources is one of the biggest challenges of this century. In this context, the role of H2 is of paramount importance as a key source of energy that could substitute traditional fossil fuels. This technology, even if available in several manufactures, still needs to be optimized at all levels (production, storage and distribution) to be integrated on a larger scale. Among materials suitable to store H2, Mg(BH4)2 is particularly interesting due to its high content of H2 in terms of gravimetric density. Nanosizing effects and role of additives in the decomposition of Mg(BH4)2 were studied by density functional theory (DFT) modelling. Both effects were analyzed because of their contribution in promoting the decomposition of the material. In particular, to have a quantitative idea of nanosizing effects, we used thin film 2D models corresponding to different crystallographic surfaces and referred to the following reaction: Mg(BH4)2 → MgB2 + 4H2. When moving from bulk to nanoscale (2D models), a remarkable decrease in the decomposition energy (10-20 kJ mol-1) was predicted depending on the surface and the thin film thickness considered. As regards the role of additives (Ni and Cu), we based our analysis on their effect in perturbing neighboring borohydride groups. We found a clear elongation of some B-H bonds, in particular with the NiF2 additive (about 0.1 Å). We interpreted this behavior as an indicator of the propensity of borohydride towards dissociation. On the basis of this evidence, we also explored a possible reaction pathway of NiF2 and CuF2 on Mg(BH4)2 up to H2 release and pointed out the major catalytic effect of Ni compared to Cu.

Shining Light on Inverted Singlet-Triplet Emitters

The inversion of the lowest singlet and triplet excited states, observed in several triangle-shaped organic molecules containing conjugated carbon and nitrogen atoms, is an astonishing result that implies the breakdown of Hund's rule. The phenomenon attracted interest for its potential toward triplet harvesting in organic LEDs. On a more fundamental vein, the singlet-triplet (ST) inversion sheds new light on the role of electron correlations in the excited-state landscape of π-conjugated molecules. Relying on the celebrated Pariser-Parr-Pople model, the simplest model for correlated electrons in π-conjugated systems, we demonstrate that the ST inversion does not require triangle-shaped molecules nor any specific molecular symmetry. Indeed, the ST inversion does not require strictly non-overlapping HOMO and LUMO orbitals but rather a small gap and a small exchange integral between the frontier orbitals.

Stability and Formation of the Li3PS4/Li, Li3PS4/Li2S, and Li2S/Li Interfaces: A Theoretical Study

Solid electrolytes have shown superior behavior and many advantages over liquid electrolytes, including simplicity in battery design. However, some chemical and structural instability problems arise when solid electrolytes form a direct interface with the negative Li-metal electrode. In particular, it was recognized that the interface between the β-Li3PS4 crystal and lithium anode is quite unstable and tends to promote structural defects that inhibit the correct functioning of the device. As a possible way out of this problem, we propose a material, Li2S, as a passivating coating for the Li/β-Li3PS4 interface. We investigated the mutual affinity between Li/Li2S and Li2S/β-Li3PS4 interfaces by DFT methods and investigated the structural stability through the adhesion energy and mechanical stress. Furthermore, a topological analysis of the electron density identified preferential paths for the migration of Li ions.

Emotional reactivity and prosocial behaviour in response to witnessing social exclusion in adolescents with eating disorders and healthy controls

BACKGROUND

Prosocial behaviour can promote positive social interactions and it is a key skill in adolescence. People with emotional problems or psychiatric disorders, such as people with eating disorders might have impairments in prosocial behaviour, due to broader documented difficulties in underlying processes (e.g., mentalizing).

METHODS

The aim of this study was to examine prosocial behaviour in adolescents with eating disorders compared to healthy controls, using a computerised behavioural task. Adolescents (N = 123) including patients with eating disorders (n = 61) and healthy adolescents (n = 62) played a four-player computerised Prosocial Cyberball Game with three pre-programmed avatar players. During the task, participants witnessed the exclusion of one of the players, and subsequently had the opportunity to compensate for this by throwing the ball more often to the excluded player. Throughout the game, participants rated the level of negative emotion in themselves and in the excluded player.

RESULTS

Patients made significantly fewer ball tosses towards the excluded player during the compensation round compared to healthy controls (large effect size). Patients reported a significantly smaller increase in negative emotion after witnessing the exclusion and a significantly smaller decrease in negative emotion following the compensation round (large effect sizes). Patients also estimated a smaller decrease in negative emotion in the excluded player following the compensation round (medium effect size). There were no significant associations between these outcomes and eating disorder psychopathology in patients.

CONCLUSIONS

Compared to healthy adolescents, adolescent patients with eating disorders demonstrated less prosocial compensatory behaviour towards a computerised victim of social exclusion. In addition, they reported flatter negative emotion in themselves in response to witnessing and compensating for exclusion, and in the excluded player following compensation. If these findings are replicated, interventions to target these difficulties might contribute to improvements in social functioning in this patient group.

Secondary Prevention and Extreme Cardiovascular Risk Evaluation (SEVERE-1), Focus on Prevalence and Associated Risk Factors: The Study Protocol

INTRODUCTION

Despite significant improvement in secondary CardioVascular (CV) preventive strategies, some acute and chronic coronary syndrome (ACS and CCS) patients will suffer recurrent events (also called "extreme CV risk"). Recently new biochemical markers, such as uric acid (UA), lipoprotein A [Lp(a)] and several markers of inflammation, have been described to be associated with CV events recurrence. The SEcondary preVention and Extreme cardiovascular Risk Evaluation (SEVERE-1) study will accurately characterize extreme CV risk patients enrolled in cardiac rehabilitation (CR) programs.

AIM

 Our aims will be to describe the prevalence of extreme CV risk and its association with newly described biochemical CV risk factors.

AIM

Our aims will be to describe the prevalence of extreme CV risk and its association with newly described biochemical CV risk factors.

METHODS

We will prospectively enrol 730 ACS/CCS patients at the beginning of a CR program. Extreme CV risk will be retrospectively defined as the presence of a previous (within 2 years) CV events in the patients' clinical history. UA, Lp(a) and inflammatory markers (interleukin-6 and -18, tumor necrosis factor alpha, C-reactive protein, calprotectin and osteoprotegerin) will be assessed in ACS/CCS patients with extreme CV risk and compared with those without extreme CV risk but also with two control groups: 1180 hypertensives and 765 healthy subjects. The association between these biomarkers and extreme CV risk will be assessed with a multivariable model and two scoring systems will be created for an accurate identification of extreme CV risk patients. The first one will use only clinical variables while the second one will introduce the biochemical markers. Finally, by exome sequencing we will both evaluate polygenic risk score ability to predict recurrent events and perform mendellian randomization analysis on CV biomarkers.

CONCLUSIONS

Our study proposal was granted by the European Union PNRR M6/C2 call. With this study we will give definitive data on extreme CV risk prevalence rising attention on this condition and leading cardiologist to do a better diagnosis and to carry out a more intensive treatment optimization that will finally leads to a reduction of future ACS recurrence. This will be even more important for cardiologists working in CR that is a very important place for CV risk definition and therapies refinement.

Thermoplasmonic In Situ Fabrication of Nanohybrid Electrocatalysts over Gas Diffusion Electrodes for Enhanced H2O2 Electrosynthesis

Large-scale development of electrochemical cells is currently hindered by the lack of Earth-abundant electrocatalysts with high catalytic activity, product selectivity, and interfacial mass transfer. Herein, we developed an electrocatalyst fabrication approach which responds to these requirements by irradiating plasmonic titanium nitride (TiN) nanocubes self-assembled on a carbon gas diffusion layer in the presence of polymeric binders. The localized heating produced upon illumination creates unique conditions for the formation of TiN/F-doped carbon hybrids that show up to nearly 20 times the activity of the pristine electrodes. In alkaline conditions, they exhibit enhanced stability, a maximum H2O2 selectivity of 90%, and achieve a H2O2 productivity of 207 mmol gTiN-1 h-1 at 0.2 V vs RHE. A detailed electrochemical investigation with different electrode arrangements demonstrated the key role of nanocomposite formation to achieve high currents. In particular, an increased TiOxNy surface content promoted a higher H2O2 selectivity, and fluorinated nanocarbons imparted good stability to the electrodes due to their superhydrophobic properties.

Automated detection of cerebral microbleeds on MR images using knowledge distillation framework

Introduction

Cerebral microbleeds (CMBs) are associated with white matter damage, and various neurodegenerative and cerebrovascular diseases. CMBs occur as small, circular hypointense lesions on T2*-weighted gradient recalled echo (GRE) and susceptibility-weighted imaging (SWI) images, and hyperintense on quantitative susceptibility mapping (QSM) images due to their paramagnetic nature. Accurate automated detection of CMBs would help to determine quantitative imaging biomarkers (e.g., CMB count) on large datasets. In this work, we propose a fully automated, deep learning-based, 3-step algorithm, using structural and anatomical properties of CMBs from any single input image modality (e.g., GRE/SWI/QSM) for their accurate detections.

Methods

In our method, the first step consists of an initial candidate detection step that detects CMBs with high sensitivity. In the second step, candidate discrimination step is performed using a knowledge distillation framework, with a multi-tasking teacher network that guides the student network to classify CMB and non-CMB instances in an offline manner. Finally, a morphological clean-up step further reduces false positives using anatomical constraints. We used four datasets consisting of different modalities specified above, acquired using various protocols and with a variety of pathological and demographic characteristics.

Results

On cross-validation within datasets, our method achieved a cluster-wise true positive rate (TPR) of over 90% with an average of <2 false positives per subject. The knowledge distillation framework improves the cluster-wise TPR of the student model by 15%. Our method is flexible in terms of the input modality and provides comparable cluster-wise TPR and better cluster-wise precision compared to existing state-of-the-art methods. When evaluating across different datasets, our method showed good generalizability with a cluster-wise TPR >80 % with different modalities. The python implementation of the proposed method is openly available.

A fluorescent sensor to detect lead leakage from perovskite solar cells

Hybrid perovskites have been considered a hot material in the semiconductor industry; included as an active layer in advanced devices, from light emitting applications to solar cells, where they lead as a new strategic solution, they promise to be the next generation high impact class of materials. However, the presence - in most cases - of lead in their matrix, or lead byproducts as a consequence of material degradation, such as PbI₂, is currently hindering their massive deployment. Here, we develop a fluorescent organic sensor (FS) based on the Pb-selective BODIPY fluorophore that emits when the analyte - lead in this case - is detected. We carried out a fluorimetric analysis to quantify the trace concentration of Pb²⁺ released from lead-based perovskite solar cells, exploring different material compositions. In particular, we immersed the devices in rainwater, to simulate the behavior of the devices under atmospheric conditions when the sealing is damaged. The sensor is studied in a phosphate buffer solution (PBS) at pH 4.5 to simulate the pH of acidic rain, and the results obtained are compared with ICP-OES measurements. We found that with fluorometric analysis, lead concentration could be calculated with a detection limit as low as 5 μg l^-1, in agreement with ICP-OES analysis. In addition, we investigated the possibility of using the sensor on a solid substrate for direct visualization to determine the presence of Pb. This can constitute the base for the development of a Pb-based label that can switch on if lead is detected, alerting any possible leakage.

Effects of perinatal exposure to bisphenol A or S in EAE model of multiple sclerosis

Epidemiological studies support the idea that multiple sclerosis (MS) is a multifactorial disease, overlapping genetic, epigenetic, and environmental factors. A better definition of environmental risks is critical to understand both etiology and the sex-related differences of MS. Exposure to endocrine-disrupting compounds (EDCs) fully represents one of these risks. EDCs are natural or synthetic exogenous substances (or mixtures) that alter the functions of the endocrine system. Among synthetic EDCs, exposure to bisphenol A (BPA) has been implicated in the etiology of MS, but to date, controversial data has emerged. Furthermore, nothing is known about bisphenol S (BPS), one of the most widely used substitutes for BPA. As exposure to bisphenols will not disappear soon, it is necessary to clarify their role also in this pathological condition defining their role in disease onset and course in both sexes. In this study, we examined, in both sexes, the effects of perinatal exposure to BPA and BPS in one of the most widely used mouse models of MS, experimental autoimmune encephalomyelitis (EAE). Exposure to bisphenols seemed to be particularly deleterious in males. In fact, both BPA- and BPS-treated males showed anticipation of the disease onset and an increased motoneuron loss in the spinal cord. Overall, BPA-treated males also displayed an exacerbation of EAE course and an increase in inflammation markers in the spinal cord. Analyzing the consequences of bisphenol exposure on EAE will help to better understand the role of both xenoestrogens and endogenous estrogens on the sexually dimorphic characteristics of MS.

A Comprehensive Approach to Exciton Delocalization and Energy Transfer

Electrostatic intermolecular interactions lie at the heart of both the Förster model for resonance energy transfer (RET) and the exciton model for energy delocalization. In the Förster theory of RET, the excitation energy incoherently flows from the energy donor to a weakly coupled energy acceptor. The exciton model describes instead the energy delocalization in aggregates of identical (or nearly so) molecules. Here, we introduce a model that brings together molecular aggregates and RET. We will consider a couple of molecules, each described in terms of two diabatic electronic states, coupled to an effective molecular vibration. Electrostatic intermolecular interactions drive energy fluxes between the molecules, that, depending on model parameters, can be described as RET or energy delocalization. At variance with the standard Förster model for RET and of the exciton model for aggregates, our approach applies both in the weak and in the strong coupling regimes and fully accounts for the quantum nature of molecular vibrations in a nonadiabatic approach. Coupling the system to a thermal bath, we follow RET and energy delocalization in real time and simulate time-resolved emission spectra.

Boys Do Cry: Age and Gender Differences in Psycho-Physiological Distress during the COVID-19 Pandemic in Italy

This article contributes to the quality of life literature by investigating gender and age gaps in psycho-physiological distress during the COVID-19 pandemic in Italy. Specifically, we investigate whether women experienced higher levels of distress than men, and if such gap can be explained by a greater negative reaction of women in the experience of a negative COVID-19 related event, such as the illness or death of a relative. Moreover, we explore whether age moderated or amplified the effect of a negative event on distress among women and men. To do so we rely on an ad hoc survey carried out between April 2020 and June 2021 in Italy, the first European country to be hit by the pandemic. Our results indicate that subjects who experienced the hospitalization or, more so, the death of a family member during the pandemic were more exposed to psycho-psychological distress compared to subjects who were not directly touched by COVID-19. Moreover, our results show that while women were on average more likely to express feelings of distress than men in absence of evident stressors, this gap disappeared among subjects who experience the death of a relative. Furthermore, our results indicate that experiencing a negative COVID-19 related event led to an increase in distress among all respondents except older men, who appeared to be the most resilient to the manifestation of any sign of distress. These results speak to important age and gender differences in the feelings and externalization of grief in the Italian context.

Unveiling the Role of PEO-Capped TiO2 Nanofiller in Stabilizing the Anode Interface in Lithium Metal Batteries

Lithium metal batteries (LMBs) will be a breakthrough in automotive applications, but they require the development of next-generation solid-state electrolytes (SSEs) to stabilize the anode interface. Polymer-in-ceramic PEO/TiO₂ nanocomposite SSEs show outstanding properties, allowing unprecedented LMBs durability and self-healing capabilities. However, the mechanism underlying the inhibition/delay of dendrite growth is not well understood. In fact, the inorganic phase could act as both a chemical and a mechanical barrier to dendrite propagation. Combining advanced in situ and ex situ experimental techniques, we demonstrate that oligo(ethylene oxide)-capped TiO₂, although chemically inert toward lithium metal, imparts SSE with mechanical and dynamical properties particularly favorable for application. The self-healing characteristics are due to the interplay between mechanical robustness and high local polymer mobility which promotes the disruption of the electric continuity of the lithium dendrites (razor effect).

Laser Ablation Nanoarchitectonics of Au-Cu Alloys Deposited on TiO2 Photocatalyst Films for Switchable Hydrogen Evolution from Formic Acid Dehydrogenation

The regulation of H₂ evolution from formic acid dehydrogenation using recyclable photocatalyst films is an essential approach for on-demand H₂ production. We have successfully generated Au-Cu nanoalloys using a laser ablation method and deposited them on TiO₂ photocatalyst films (Au _x Cu_100-x /TiO₂). The Au-Cu/TiO₂ films were employed as photocatalysts for H₂ production from formic acid dehydrogenation under light-emitting diode (LED) irradiation (365 nm). The highest H₂ evolution rate for Au₂₀Cu₈₀/TiO₂ is archived to 62,500 μmol h^-1 g^-1 per photocatalyst weight. The remarkable performance of Au₂₀Cu₈₀/TiO₂ may account for the formation of Au-rich surfaces and the effect of Au alloying that enables Cu to sustain the metallic form on its surface. The metallic Au-Cu surface on TiO₂ is vital to supply the photoexcited electrons of TiO₂ to its surface for H₂ evolution. The rate-determining step (RDS) is identified as the reaction of a surface-active species with protons. The results establish a practical preparation of metal alloy deposited on photocatalyst films using laser ablation to develop efficient photocatalysts.

Haralick's texture analysis to predict cellular proliferation on randomly oriented electrospun nanomaterials

Using a computer vision approach we have extracted the Haralick's texture features of randomly oriented electrospun nanomaterials in order to predict the proliferative behavior of cells which were subsequently seeded onto the nanosurfaces.

A Waste-Minimized Approach to Cassar-Heck Reaction Based on POLITAG-Pd0 Heterogeneous Catalyst and Recoverable Acetonitrile Azeotrope

Three different Pd0 -based heterogeneous catalysts were developed and tested in the Cassar-Heck reaction (i. e., copper-free Sonogashira reaction) aiming at the definition of a waste minimized protocol. The cross-linked polymeric supports used in this investigation were designed to be adequate for different reaction media and were decorated with different pincer-type ionic ligands having the role of stabilizing the formation and dimension of palladium nanoparticles. Among the ionic tags tested, bis-imidazolium showed the best performances in terms of efficiency and durability of the metal catalytic system. Eventually, aqueous acetonitrile azeotrope was selected as the reaction medium as it allowed the best catalytic efficiency combined with easy recovery and reuse. Finally, the synergy between the selected catalyst and reaction medium allowed to obtain highly satisfactory isolated yields of a variety of substrates while using a low amount of metal catalyst. The high performance of the designed POLymeric Ionic TAG (POLITAG)-Pd0 , along with its good selectivity achieved in a copper-free process, also led to a simplified purification procedure allowing the minimization of the waste generated as also proven by the very low E-factor values (1.4-5) associated.

WO3/BiVO4 Photoanodes: Facets Matching at the Heterojunction and BiVO4 Layer Thickness Effects

Photoelectrochemical solar energy conversion offers a way to directly store light into energy-rich chemicals. Photoanodes based on the WO₃/BiVO₄ heterojunction are most effective mainly thanks to the efficient separation of photogenerated charges. The WO₃/BiVO₄ interfacial space region in the heterojunction is investigated here with the increasing thickness of the BiVO₄ layer over a WO₃ scaffold. On the basis of X-ray diffraction analysis results, density functional theory simulations show a BiVO₄ growth over the WO₃ layer along the BiVO₄ {010} face, driven by the formation of a stable interface with new covalent bonds, with a favorable band alignment and band bending between the two oxides. This crystal facet phase matching allows a smooth transition between the electronic states of the two oxides and may be a key factor ensuring the high efficiency attained with this heterojunction. The photoelectrochemical activity of the WO₃/BiVO₄ photoanodes depends on both the irradiation wavelength and the thickness of the visible-light-absorbing BiVO₄ layer, a 75 nm thick BiVO₄ layer on WO₃ being best performing.

Combining Culture-Dependent and Culture-Independent Methods: New Methodology Insight on the Vibrio Community of Ruditapes philippinarum

Vibrios represent a natural contaminant of seafood products. V. alginolyticus, V. cholerae, V. parahaemolyticus and V. vulnificus are the most hazardous species to human health. Given the worldwide consumption of mollusc products, reliable detection of Vibrio species is recommended to prevent human vibriosis. In this study, culture-dependent and -independent methods were compared and integrated to implement knowledge of the Manila clam Vibrio community composition. Here, 16S and recA-pyrH metabarcoding were applied to compare the microbial communities of homogenate clam samples (culture-independent method) and their culture-derived samples plated on three different media (culture-dependent method). In addition, a subset of plated clam samples was investigated using shotgun metagenomics. Homogenate metabarcoding characterized the most abundant taxa (16S) and Vibrio species (recA-pyrH). Culture-dependent metabarcoding detected the cultivable taxa, including rare species. Moreover, marine agar medium was found to be a useful substrate for the recovery of several Vibrio species, including the main human pathogenic ones. The culture-dependent shotgun metagenomics detected all the main human pathogenic Vibrio species and a higher number of vibrios with respect to the recA-pyrH metabarcoding. The study revealed that integration of culture-dependent and culture-independent methods might be a valid approach for the characterization of Vibrio biodiversity.