Engineering the Mechanical Stability of a Therapeutic Affibody/PD-L1 Complex by Anchor Point Selection.

Protein-protein complexes can vary in mechanical stability depending on the direction from which force is applied. Here we investigated the anisotropic mechanical stability of a molecular complex between a therapeutic non-immunoglobulin scaffold called Affibody and the extracellular domain of the immune checkpoint protein PD-L1. We used a combination of single-molecule AFM force spectroscopy (AFM-SMFS) with bioorthogonal clickable peptide handles, shear stress bead adhesion assays, molecular modeling, and steered molecular dynamics (SMD) simulations to understand the pulling point dependency of mechanostability of the Affibody:(PD-L1) complex. We observed diverse mechanical responses depending on the anchor point. For example, pulling from residue #22 on Affibody generated an intermediate unfolding event attributed to partial unfolding of PD-L1, while pulling from Affibody's N-terminus generated force-activated catch bond behavior. We found that pulling from residue #22 or #47 on Affibody generated the highest rupture forces, with the complex breaking at up to ~ 190 pN under loading rates of ~104-105 pN/sec, representing a ~4-fold increase in mechanostability as compared with low force N-terminal pulling. SMD simulations provided consistent tendencies in rupture forces, and through visualization of force propagation networks provided mechanistic insights. These results demonstrate how mechanostability of therapeutic protein-protein interfaces can be controlled by informed selection of anchor points within molecules, with implications for optimal bioconjugation strategies in drug delivery vehicles.

Two-Dimensional Shear-Wave Elastography of the Thyroid in Clinically Healthy Dogs in Different Age Groups.

The thyroid of dogs has not been extensively studied in 2D shear-wave elastography, making it challenging to apply this technique in the diagnosis of thyroid diseases in a non-invasive manner. The aim of this study is to evaluate the thyroid glands of healthy dogs using 2D shear-wave elastography in order to establish qualitative and quantitative parameters of tissue stiffness in dogs in different age groups. A total of 31 dogs of various breeds, sexes, and sizes were evaluated. Animals with clinical signs or ultrasound findings indicative of endocrine disease or thyroid lesions were excluded from the study. The shear-wave velocity data in meters per second (m/s) and color elastograms were evaluated and calculated using QelaXto™ 2D software. A healthy thyroid exhibits a blue-color elastogram, indicative of low stiffness. The reference range for the shear-wave velocity of thyroid tissue assessed by 2D shear-wave elastography can be between 1.6 and 2.0 m/s, with a variation of ±0.889 in adult and senior dogs.

Effects of acute toxicity of the pesticide Chlorpyrifos and the metal Cadmium, both individually and in mixtures, on two species of native neotropical cladocerans.

The excessive use of pesticides in agriculture and the widespread use of metals in industrial activities and or technological applications has significantly increased the concentrations of these pollutants in both aquatic and terrestrial ecosystems worldwide, making aquatic biota increasingly vulnerable and putting many species at risk of extinction. Most aquatic habitats receive pollutants from various anthropogenic actions, leading to interactions between compounds that make them even more toxic. The aim of this study was to assess the effects of the compounds Chlorpyrifos (insecticide) and Cadmium (metal), both individually and in mixtures, on the cladocerans Ceriodaphnia rigaudi and Ceriodaphnia silvestrii. Acute toxicity tests were conducted for the compounds individually and in mixture, and an ecological risk assessment (ERA) was performed for both compounds. Acute toxicity tests with Cadmium resulted in EC50-48 h of 0.020 mg L-1 for C. rigaudi and 0.026 mg L-1 for C. silvestrii, while tests with Chlorpyrifos resulted in EC50-48 h of 0.047 µg L-1 and 0.062 µg L-1, respectively. The mixture test for C. rigaudi showed the occurrence of additive effects, while for C. silvestrii, antagonistic effects occurred depending on the dose level. The species sensitivity distribution curve for crustaceans, rotifers, amphibians, and fishes resulted in an HC5 of 3.13 and an HC50 of 124.7 mg L-1 for Cadmium; an HC5 of 9.96 and an HC50 of 5.71 µg L-1 for Chlorpyrifos. Regarding the ERA values, Cadmium represented a high risk, while Chlorpyrifos represented an insignificant to a high risk.

Achieving High-Temperature Stable Structural Color through Nanostructuring in Polymer-Derived Ceramics.

Structural colors offer a myriad of advantages over conventional pigment-based colors, which often rely on toxic chemical substances that are prone to UV degradation. To take advantage of these benefits in demanding environments, there is growing interest in producing structural colors from ceramics. Polymer-derived ceramics (PDCs) emerge as a compelling choice, presenting two distinct advantages: their enhanced shape ability in their polymeric state associated with impressive temperature resistance once converted to ceramics. This study pioneers the fabrication of noniridescent structural colors from silicon oxycarbide (SiOC) PDC, enabled by the nanostructuring of an inverse photonic glass within the PDC material. This design, a functionally graded material with an inverse photonic glass (FGM-PhG) structure, leverages the innate light-absorbing properties of SiOC, yielding a vivid structural color that maintains its saturation even in white surroundings. This study elucidates the process-structure-properties relationship for the obtained structural colors by investigating each layer of the functionally graded material (FGM) in a stepwise coating deposition process. To further emphasize the exceptional processing flexibility of PDCs, the three-step process is later transferred to an additive manufacturing approach. Finally, the FGM-PhG structural colors are demonstrated to have remarkable thermal stability up to 1000 °C for 100 h, possibly making them the most thermally stable ceramic structural colors to date.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions.

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

Ecological Implications on Aquatic Food Webs Due to Effects of Pesticides on Invertebrate Predators in a Neotropical Region.

Predation presents specific behavioral characteristics for each species, and the interaction between prey and predator influences the structuring of the food web. Concerning insects, predation can be affected in different ways, such as exposure to chemical stressors, e.g., pesticides. Therefore, analyses were carried out of the effects of exposure to insecticide fipronil and the herbicide 2,4-D on predation, parameters of food selectivity, and the swimming behavior of two neotropical predatory aquatic insects of the families Belostomatidae (giant water bugs) and larvae of Libellulidae (dragonfly). These predatory insects were exposed for 24 h to a commercial formulation of the chlorophenoxy herbicide, 2,4-D at nominal concentrations of 200, 300, 700, and 1400 µg L-1, and to a commercial formulation of the phenylpyrazole insecticide, fipronil at nominal concentrations of 10, 70, 140, and 250 µg L-1. In a control treatment, the insects were placed in clean, unspiked water. At the end of the exposure, the maximum swimming speed of the predators was evaluated. Afterward, the predators were placed in clean water in a shared environment for 24 h with several prey species, including the cladoceran Ceriodaphnia silvestrii, larvae of the insect Chironomus sancticaroli, the amphipod Hyalella meinerti, the ostracod Strandesia trispinosa, and the oligochaete Allonais inaequalis for 24 h. After this period, the consumed prey was counted. The results reveal that predators from both families changed prey consumption compared with organisms from the control treatment, marked by a decrease after exposure to fipronil and an increase in consumption caused by 2,4-D. In addition, there were changes in the food preferences of both predators, especially when exposed to the insecticide. Exposure to fipronil decreased the swimming speed of Belostomatidae individuals, possibly due to its neurotoxic effect. Exposure to the insecticide and the herbicide altered prey intake by predators, which could negatively influence the complex prey-predator relationship and the functioning of aquatic ecosystems in contaminated areas.

Use of New Ultrasonography Methods for Detecting Neoplasms in Dogs and Cats: A Review.

The aim of this literature review was to present the novel imaging modalities elastography and contrast-enhanced ultrasonography. We provided an overview of the concepts and applications of each technique for the investigation of neoplastic and metastatic tumors in dogs and cats. Studies on elastography are based on the elasticity and deformation of the evaluated tissue. The information obtained from the different types of elastography can aid in the detection and differentiation of malignant and benign structures. Descriptions of elastography studies in several organs and tissue in veterinary medicine reported that, in general, malignant tumors tend to be more rigid and, therefore, less deformable than benign lesions or in comparison to the healthy parenchyma. Contrast-enhanced ultrasonography is based on the intravenous injection of contrast media constituted by microbubbles. This imaging modality can be performed in nonsedated animals and provides information on the tissue perfusion, allowing the investigation of macro- and micro-circulation. Studies on different organs and tissues were performed in dogs and cats and revealed a tendency of malignant tumors to present faster transit of the contrast media (time to wash-in, peak and wash-out). These advanced techniques can be associated with other imaging modalities, aiding important information to the well-established exams of B-mode and Doppler ultrasonography. They can be used as screening tests, potentially representing an alternative to the invasive sampling methods required for cytological and histopathological analysis.

Effects of peppermint oil inhalation on vertical jump performance in elite young professional soccer players: A double-blinded randomized crossover study.

Aims: To evaluate peppermint essential oil (PEO) inhalation's effect on young soccer athletes' motor performance. Methods: A randomized crossover design was used to test the effect of the PEO. Eleven U-17 soccer players were evaluated into two conditions (PEO and Placebo - PLA). The players were tested in squat jump and countermovement jump and inhaled PEO or PLA and 10 min later performed the physical tests again. A mixed ANOVA was performed to test the hypotheses. Results: Main effects were found for the time in jumping height in the CMJ (p = 0.037). No main and interaction effects were found in the SJ variables. Conclusion: From the results, decrease CMJ performance acutely, both conditions presented decrease in JH, but based in effect size, PLA decrease is higher (more sample size for corroborate this) possibly due to improvements in the eccentric yielding sub-phase, where mentioned phase could be reflecting neural changes (required experimental verification). The PEO could be the interest in trainers for use before of match or in the half-time for minimize the decreased of physical performance by the rest.

Ecological risk assessment for metals in sediment and waters from the Brazilian Amazon region.

Pollution by metals is a matter of concern around the world. In recent decades, the high population growth in urban centers has significantly magnified the entry of these pollutants into aquatic ecosystems. The Amazon region, intense migratory flow, gold mining, and industrialization have been considered the main driving forces for increasing metal pollution. Thus, the main aim of this study is to conduct, for the first time, an Ecological Risk Assessment (ERA) based on metal concentrations measured in the sediment and water of several aquatic environments from the Amazon basin, based on the risk quotient values (RQ = measured environmental concentration - MEC/predicted no effect concentration - PNEC). In addition, the metal contamination factor (CF) was estimated. Although metal concentrations in water were generally low, these values were far above the limits established by current national legislation in many areas, showing higher concentrations for the metals Co, Pb, Cr, Cu, and Ni. Concentrations of Mn, Cu, Ba, Pb, Co, Ni, Cr, Zn, Cd, and As were especially high in the sediment for several evaluated environments. The ERA for the water compartment revealed that 56% of the studied areas presented high risk (RQ > 1) for aquatic biota. In the sediment, 66% of the sites presented a high risk and 40% medium risk (RQ = 0.1-1). The CF indicated that 49% of the sampling points had high contamination and only 24%, had low contamination. These results reveal that monitoring studies in the Amazon region, provides important information so that public policies for the preservation of water resources can be strengthened in the Amazon.

Deciphering molecular mechanisms stabilizing the reovirus-binding complex.

Mammalian orthoreoviruses (reoviruses) serve as potential triggers of celiac disease and have oncolytic properties, making these viruses potential cancer therapeutics. Primary attachment of reovirus to host cells is mainly mediated by the trimeric viral protein, σ1, which engages cell-surface glycans, followed by high-affinity binding to junctional adhesion molecule-A (JAM-A). This multistep process is thought to be accompanied by major conformational changes in σ1, but direct evidence is lacking. By combining biophysical, molecular, and simulation approaches, we define how viral capsid protein mechanics influence virus-binding capacity and infectivity. Single-virus force spectroscopy experiments corroborated by in silico simulations show that GM2 increases the affinity of σ1 for JAM-A by providing a more stable contact interface. We demonstrate that conformational changes in σ1 that lead to an extended rigid conformation also significantly increase avidity for JAM-A. Although its associated lower flexibility impairs multivalent cell attachment, our findings suggest that diminished σ1 flexibility enhances infectivity, indicating that fine-tuning of σ1 conformational changes is required to successfully initiate infection. Understanding properties underlying the nanomechanics of viral attachment proteins offers perspectives in the development of antiviral drugs and improved oncolytic vectors.

Characterization of Potent ABCG2 Inhibitor Derived from Chromone: From the Mechanism of Inhibition to Human Extracellular Vesicles for Drug Delivery.

Inhibition of ABC transporters is a promising approach to overcome multidrug resistance in cancer. Herein, we report the characterization of a potent ABCG2 inhibitor, namely, chromone 4a (C4a). Molecular docking and in vitro assays using ABCG2 and P-glycoprotein (P-gp) expressing membrane vesicles of insect cells revealed that C4a interacts with both transporters, while showing selectivity toward ABCG2 using cell-based transport assays. C4a inhibited the ABCG2-mediated efflux of different substrates and molecular dynamic simulations demonstrated that C4a binds in the Ko143-binding pocket. Liposomes and extracellular vesicles (EVs) of Giardia intestinalis and human blood were used to successfully bypass the poor water solubility and delivery of C4a as assessed by inhibition of the ABCG2 function. Human blood EVs also promoted delivery of the well-known P-gp inhibitor, elacridar. Here, for the first time, we demonstrated the potential use of plasma circulating EVs for drug delivery of hydrophobic drugs targeting membrane proteins.

Fabric-like Electrospun PVAc-Graphene Nanofiber Webs as Wearable and Degradable Piezocapacitive Sensors.

Flexible piezocapacitive sensors utilizing nanomaterial-polymer composite-based nanofibrous membranes offer an attractive alternative to more traditional piezoelectric and piezoresistive wearable sensors owing to their ultralow powered nature, fast response, low hysteresis, and insensitivity to temperature change. In this work, we propose a facile method of fabricating electrospun graphene-dispersed PVAc nanofibrous membrane-based piezocapacitive sensors for applications in IoT-enabled wearables and human physiological function monitoring. A series of electrical and material characterization experiments were conducted on both the pristine and graphene-dispersed PVAc nanofibers to understand the effect of graphene addition on nanofiber morphology, dielectric response, and pressure sensing performance. Dynamic uniaxial pressure sensing performance evaluation tests were conducted on the pristine and graphene-loaded PVAc nanofibrous membrane-based sensors for understanding the effect of two-dimensional (2D) nanofiller addition on pressure sensing performance. A marked increase in the dielectric constant and pressure sensing performance was observed for graphene-loaded spin coated membrane and nanofiber webs respectively, and subsequently the micro dipole formation model was invoked to explain the nanofiller-induced dielectric constant enhancement. The robustness and reliability of the sensor have been underscored by conducting accelerated lifetime assessment experiments entailing at least 3000 cycles of periodic tactile force loading. A series of tests involving human physiological parameter monitoring were conducted to underscore the applicability of the proposed sensor for IoT-enabled personalized health care, soft robotics, and next-generation prosthetic devices. Finally, the easy degradability of the sensing elements is demonstrated to emphasize their suitability for transient electronics applications.

Nanoencapsulation Boosts the Copper-Induced Defense Responses of a Susceptible Coffea arabica Cultivar against Hemileia vastatrix.

Due to the environmental risks of conventional Cu-based fungicides, Cu-loaded chitosan nanoparticles have been developed as nano-pesticides, aiming to protect plants against different diseases. In this sense, the objective was to verify the effects of chitosan nanoparticles containing Cu2+ ions on leaf discs of Coffea arabica cv. IPR 100 infected with Hemileia vastatrix. The treatments were water as a control (CONT), unloaded chitosan nanoparticles (NP), chitosan nanoparticles containing Cu2+ ions (NPCu), and free Cu2+ ions (Cu). Different concentrations of NP (0.25; 0.5; 1 g L-1) and Cu2+ ions (1.25; 2.5; 5 mmol L-1) were tested. The severity of the coffee rust was 42% in the CONT treatment, 22% in NP, and 2% in NPCu and Cu. The treatments protected coffee leaves; however, NPCu stood out for initial stress reduction, decreasing Cu phytotoxicity, promoting photosynthetic activity maintenance, and increasing antioxidant responses, conferring significant protection against coffee rust. At low concentrations (1.25 mmol L-1), NPCu showed higher bioactivity than Cu. These results suggest that Cu-loaded chitosan nanoparticles can induce a more significant plant defense response to the infection of Hemileia vastatrix than conventional Cu, avoiding the toxic effects of high Cu concentrations. Thus, this nanomaterial has great potential to be used as nano-pesticides for disease management.

May the force be with you: The role of hyper-mechanostability of the bone sialoprotein binding protein during early stages of Staphylococci infections.

The bone sialoprotein-binding protein (Bbp) is a mechanoactive MSCRAMM protein expressed on the surface of Staphylococcus aureus that mediates adherence of the bacterium to fibrinogen-α (Fgα), a component of the bone and dentine extracellular matrix of the host cell. Mechanoactive proteins like Bbp have key roles in several physiological and pathological processes. Particularly, the Bbp: Fgα interaction is important in the formation of biofilms, an important virulence factor of pathogenic bacteria. Here, we investigated the mechanostability of the Bbp: Fgα complex using in silico single-molecule force spectroscopy (SMFS), in an approach that combines results from all-atom and coarse-grained steered molecular dynamics (SMD) simulations. Our results show that Bbp is the most mechanostable MSCRAMM investigated thus far, reaching rupture forces beyond the 2 nN range in typical experimental SMFS pulling rates. Our results show that high force-loads, which are common during initial stages of bacterial infection, stabilize the interconnection between the protein's amino acids, making the protein more "rigid". Our data offer new insights that are crucial on the development of novel anti-adhesion strategies.

ChemFlow─From 2D Chemical Libraries to Protein-Ligand Binding Free Energies.

The accurate prediction of protein-ligand binding affinities is a fundamental problem for the rational design of new drug entities. Current computational approaches are either too expensive or inaccurate to be effectively used in virtual high-throughput screening campaigns. In addition, the most sophisticated methods, e.g., those based on configurational sampling by molecular dynamics, require significant pre- and postprocessing to provide a final ranking, which hinders straightforward applications by nonexpert users. We present a novel computational platform named ChemFlow to bridge the gap between 2D chemical libraries and estimated protein-ligand binding affinities. The software is designed to prepare a library of compounds provided in SMILES or SDF format, dock them into the protein binding site, and rescore the poses by simplified free energy calculations. Using a data set of 626 protein-ligand complexes and GPU computing, we demonstrate that ChemFlow provides relative binding free energies with an RMSE < 2 kcal/mol at a rate of 1000 ligands per day on a midsize computer cluster. The software is publicly available at https://github.com/IFMlab/ChemFlow.

Molecular Origins of Force-Dependent Protein Complex Stabilization during Bacterial Infections.

The unbinding pathway of a protein complex can vary significantly depending on biochemical and mechanical factors. Under mechanical stress, a complex may dissociate through a mechanism different from that used in simple thermal dissociation, leading to different dissociation rates under shear force and thermal dissociation. This is a well-known phenomenon studied in biomechanics whose molecular and atomic details are still elusive. A particularly interesting case is the complex formed by bacterial adhesins with their human peptide target. These protein interactions have a force resilience equivalent to those of covalent bonds, an order of magnitude stronger than the widely used streptavidin:biotin complex, while having an ordinary affinity, much lower than that of streptavidin:biotin. Here, in an in silico single-molecule force spectroscopy approach, we use molecular dynamics simulations to investigate the dissociation mechanism of adhesin/peptide complexes. We show how the Staphylococcus epidermidis adhesin SdrG uses a catch-bond mechanism to increase complex stability with increasing mechanical stress. While allowing for thermal dissociation in a low-force regime, an entirely different mechanical dissociation path emerges in a high-force regime, revealing an intricate mechanism that does not depend on the peptide's amino acid sequence. Using a dynamic network analysis approach, we identified key amino acid contacts that describe the mechanics of this complex, revealing differences in dynamics that hinder thermal dissociation and establish the mechanical dissociation path. We then validate the information content of the selected amino acid contacts using their dynamics to successfully predict the rupture forces for this complex through a machine learning model.

Enhancing satiety and aerobic performance with beer microparticles-based non-alcoholic drinks: exploring dose and duration effects.

Beer is an alcoholic beverage, rich in carbohydrates, amino acids, vitamins and polyphenols, consumed worldwide as a social drink. There is a large number of beer styles which depends on the ingredients and brewing process. The consumption of beer as a fluid replacement after sport practice is a current discussion in literature. A non-alcoholic pale-ale microparticles-based beverage (PABM) have been previously designed, however, its phenolic profile and ergogenic effect remain unknown. Thus, this study aims to verify the ergogenic potential (increase of running performance) of PAMB in male Wistar rats. Beer microparticles were obtained by spray drying and beverages with different concentrations were prepared in water. Wistar rats were subjected to a training protocol on a treadmill (5 times/week, 60 min/day) and daily intake of PABM (20 mg.kg-1 or 200 mg.kg-1) or water by gavage. Chlorogenic acid was found to be the main component in the phenolic profile (12.28 mg·g-1) of PABM analyzed with high-performance liquid chromatography and mass spectrometry. An increase in the aerobic performance was observed after 4 weeks in the 20 mg.kg-1 group, but the same dose after 8 weeks and a higher dose (200 mg.kg-1) blunted this effect. A higher dose was also related to decrease in food intake. These data suggest that PABM can improve satiety and aerobic performance, but its effect depends on the dose and time of consumption.

Soil Treatment with Nitric Oxide-Releasing Chitosan Nanoparticles Protects the Root System and Promotes the Growth of Soybean Plants under Copper Stress.

The nanoencapsulation of nitric oxide (NO) donors is an attractive technique to protect these molecules from rapid degradation, expanding, and enabling their use in agriculture. Here, we evaluated the effect of the soil application of chitosan nanoparticles containing S-nitroso-MSA (a S-nitrosothiol) on the protection of soybeans (Glycine max cv. BRS 257) against copper (Cu) stress. Soybeans were grown in a greenhouse in soil supplemented with 164 and 244 mg kg-1 Cu and treated with a free or nanoencapsulated NO donor at 1 mM, as well as with nanoparticles without NO. There were also soybean plants treated with distilled water and maintained in soil without Cu addition (control), and with Cu addition (water). The exogenous application of the nanoencapsulated and free S-nitroso-MSA improved the growth and promoted the maintenance of the photosynthetic activity in Cu-stressed plants. However, only the nanoencapsulated S-nitroso-MSA increased the bioavailability of NO in the roots, providing a more significant induction of the antioxidant activity, the attenuation of oxidative damage, and a greater capacity to mitigate the root nutritional imbalance triggered by Cu stress. The results suggest that the nanoencapsulation of the NO donors enables a more efficient delivery of NO for the protection of soybean plants under Cu stress.

Protein structure prediction in the era of AI: Challenges and limitations when applying to in silico force spectroscopy.

Mechanoactive proteins are essential for a myriad of physiological and pathological processes. Guided by the advances in single-molecule force spectroscopy (SMFS), we have reached a molecular-level understanding of how mechanoactive proteins sense and respond to mechanical forces. However, even SMFS has its limitations, including the lack of detailed structural information during force-loading experiments. That is where molecular dynamics (MD) methods shine, bringing atomistic details with femtosecond time-resolution. However, MD heavily relies on the availability of high-resolution structural data, which is not available for most proteins. For instance, the Protein Data Bank currently has 192K structures deposited, against 231M protein sequences available on Uniprot. But many are betting that this gap might become much smaller soon. Over the past year, the AI-based AlphaFold created a buzz on the structural biology field by being able to predict near-native protein folds from their sequences. For some, AlphaFold is causing the merge of structural biology with bioinformatics. Here, using an in silico SMFS approach pioneered by our group, we investigate how reliable AlphaFold structure predictions are to investigate mechanical properties of Staphylococcus bacteria adhesins proteins. Our results show that AlphaFold produce extremally reliable protein folds, but in many cases is unable to predict high-resolution protein complexes accurately. Nonetheless, the results show that AlphaFold can revolutionize the investigation of these proteins, particularly by allowing high-throughput scanning of protein structures. Meanwhile, we show that the AlphaFold results need to be validated and should not be employed blindly, with the risk of obtaining an erroneous protein mechanism.

Application of the RDoC Framework to Predict Alcohol Use and Suicidal Thoughts and Behaviors among Early Adolescents in the Adolescent Brain and Cognitive Development (ABCD) Study.

Alcohol use confers risk for suicidal thoughts and behaviors (ideation, attempt) in early adolescents. The Research Domain Criteria provides a framework for examination of multidimensional and modifiable risk factors. We examined distinct latent profiles based on patterns of positive valence (reward responsivity) and cognitive systems (neurocognition) from the ABCD Study (age 9−10, N = 10,414) at baseline enrollment. Longitudinal associations were determined between baseline positive valence and cognitive profiles and group classification (alcohol use, suicidal thoughts and behaviors, or their co-occurrence) two-years after initial assessment (ages 11−12). Three unique profiles of positive valence, cognition, alcohol use, and suicidal thoughts and behaviors were identified. Two baseline profiles predicted alcohol use and suicidal thoughts and behaviors, two-years after initial assessment. Low positive valence with high cognition (but low impulsivity) predicted alcohol use (OR = 1.414, p< 0.001), while high positive valence with low cognition (but high impulsivity) predicted suicidal thoughts and behaviors (OR = 1.25, p = 0.038), compared to average positive valence and cognition. Unique profiles of positive valence and cognitive systems among 9−12-year-olds may be predictive of alcohol use and suicidal thoughts and behaviors over a two-year period. Findings underscore the potential for trajectory research on positive valence and cognitive profiles to enhance prevention for early-adolescents.