Binding of SARS-CoV-2 Nonstructural Protein 1 to 40S Ribosome Inhibits mRNA Translation.

Experimental evidence has established that SARS-CoV-2 NSP1 acts as a factor that restricts cellular gene expression and impedes mRNA translation within the ribosome's 40S subunit. However, the precise molecular mechanisms underlying this phenomenon have remained elusive. To elucidate this issue, we employed a combination of all-atom steered molecular dynamics and coarse-grained alchemical simulations to explore the binding affinity of mRNA to the 40S ribosome, both in the presence and absence of SARS-CoV-2 NSP1. Our investigations revealed that the binding of SARS-CoV-2 NSP1 to the 40S ribosome leads to a significant enhancement in the binding affinity of mRNA. This observation, which aligns with experimental findings, strongly suggests that SARS-CoV-2 NSP1 has the capability to inhibit mRNA translation. Furthermore, we identified electrostatic interactions between mRNA and the 40S ribosome as the primary driving force behind mRNA translation. Notably, water molecules were found to play a pivotal role in stabilizing the mRNA-40S ribosome complex, underscoring their significance in this process. We successfully pinpointed the specific SARS-CoV-2 NSP1 residues that play a critical role in triggering the translation arrest.

Effects of thinning and understory removal on soil phosphorus fractions in subtropical pine plantations.

Forest management changes the physical environments and nutrient dynamics and then regulates the forest productivity. Soil phosphorus (P) availability is critical for productivity in tropical and subtropical forests. However, it was still poorly understood how soil P content and fraction respond to various forest management practices in these regions. Here, we measured the soil total P, available P, and Hedley's P fractions, including inorganic and organic P (Pi and Po), in subtropical pine plantations treated with understory removal (UR), non-dominant species thinning (NDST) and dominant species thinning (DST) after nine years. Compared to plantations without management (CK), treatments such as UR, NDST, and DST decreased soil total P at 0-10 cm and soil available P at 0-10 cm and 10-20 cm. Increases in resin-Pi, NaOH-Pi, and C.HCl-Pi resulted in a higher total Pi in 0-10 cm (p < 0.05) in treated plots (UR, NDST, and DST) than in CK plots. UR, NDST, and DST treatments increased NaHCO3-Po and NaOH-Po (p < 0.05) but decreased C.HCl-Po at a depth of 0-10 cm. Regardless of management treatments, soil total P, available P, and P fractions in 0-10 cm showed higher contents than those in 10-20 cm. There were positive relationships between total P and total Po (p < 0.01) and between available P and total Pi. There were also positive relationships between total P, available P, NaHCO3-Pi, and NaOH-Pi (p < 0.05). In conclusion, forest management such as UR, NDST, and DST decreased soil total P and available P, and transforming soil P fractions to available P will meet the P demand following management in the pine plantations of subtropical China.

Neuropilin-1 Protein May Serve as a Receptor for SARS-CoV-2 Infection: Evidence from Molecular Dynamics Simulations.

The binding of the virus to host cells is the first step in viral infection. Human cell angiotensin converting enzyme 2 (ACE2) is the most popular receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while other receptors have recently been observed in experiments. Neuropilin-1 protein (NRP1) is one of them, but the mechanism of its binding to the wild type (WT) and different variants of the virus remain unclear at the atomic level. In this work, all-atom umbrella sampling simulations were performed to clarify the binding mechanism of NRP1 to the spike protein fragments 679-685 of the WT, Delta, and Omicron BA.1 variants. We found that the Delta variant binds most strongly to NRP1, while the affinity for Omicron BA.1 slightly decreases for NRP1 compared to that of WT, and the van der Waals interaction plays a key role in stabilizing the studied complexes. The change in the protonation state of the His amino acid results in different binding free energies between variants. Consistent with the experiment, decreasing the pH was shown to increase the binding affinity of the virus to NRP1. Our results indicate that Delta and Omicron mutations not only affect fusogenicity but also affect NRP1 binding. In addition, we argue that viral evolution does not further improve NRP1 binding affinity which remains in the µM range but may increase immune evasion.

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta.

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-ß (Aß42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the ß-content of Aß42; however, it increases the tendency of the monomeric Aß42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aß42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aß42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Exploring Structural Insights of Aß42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations.

Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-ß 42 (Aß42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aß42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aß42 dimer. The binding of α-Syn to Aß42 reduces the propensity of Aß42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aß42 significantly increases the ß-content of α-Syn, consistent with the experiments showing that Aß42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aß42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aß42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.

Contrasting water-use strategies to climate warming in white birch and larch in a boreal permafrost region.

The effects of rising atmospheric CO2 concentrations (Ca) with climate warming on intrinsic water-use efficiency and radial growth in boreal forests are still poorly understood. We measured tree-ring cellulose δ13C, δ18O, and tree-ring width in Larix dahurica (larch) and Betula platyphylla (white birch), and analyzed their relationships with climate variables in a boreal permafrost region of northeast China over past 68 years covering a pre-warming period (1951-1984; base period) and a warm period (1985-2018; warm period). We found that white birch but not larch significantly increased their radial growth over the warm period. The increased intrinsic water-use efficiency in both species was mainly driven by elevated Ca but not climate warming. White birch but not larch showed significantly positive correlations between tree-ring δ13C, δ18O and summer maximum temperature as well as vapor pressure deficit in the warm period, suggesting a strong stomatal response in the broad-leaved birch to temperature changes. The climate warming-induced radial growth enhancement in white birch is primarily associated with a conservative water-use strategy. In contrast, larch exhibits a profligate water-use strategy. It implies an advantage for white birch over larch in the warming permafrost regions.

Serotonin Promotes Vesicular Association and Fusion by Modifying Lipid Bilayers.

The primary event in chemical neurotransmission involves the fusion of a membrane-limited vesicle at the plasma membrane and the subsequent release of its chemical neurotransmitter cargo. The cargo itself is not known to have any effect on the fusion event. However, amphiphilic monoamine neurotransmitters (e.g., serotonin and dopamine) are known to strongly interact with lipid bilayers and to affect their mechanical properties, which can in principle impact membrane-mediated processes. Here, we probe whether serotonin can enhance the association and fusion of artificial lipid vesicles in vitro. We employ fluorescence correlation spectroscopy and total internal reflection fluorescence microscopy to measure the attachment and fusion of vesicles whose lipid compositions mimic the major lipid components of synaptic vesicles. We find that the association between vesicles and supported lipid bilayers is strongly enhanced in a serotonin dose-dependent manner, and this drives an increase in the rate of spontaneous fusion. Molecular dynamics simulations and fluorescence spectroscopy data show that serotonin insertion increases the water content of the hydrophobic part of the bilayer. This suggests that the enhanced membrane association is likely driven by an energetically favorable drying transition. Other monoamines, such as dopamine and norepinephrine, but not other related species, such as tryptophan, show similar effects on membrane association. Our results reveal a lipid bilayer-mediated mechanism by which monoamines can themselves modulate vesicle fusion, potentially adding to the control toolbox for the tightly regulated process of neurotransmission in vivo.

The Diversity and Composition of Soil Microbial Communities Differ in Three Land Use Types of the Sanjiang Plain, Northeastern China.

In recent years, the Sanjiang Plain has experienced drastic human activities, which have dramatically changed its ecological environment. Soil microorganisms can sensitively respond to changes in soil quality as well as ecosystem function. In this study, we investigated the changes in soil microbial community diversity and composition of three typical land use types (forest, wetland and cropland) in the Sanjiang Plain using phospholipid fatty acid analysis (PLFA) technology, and 114 different PLFA compounds were identified. The results showed that the soil physicochemical properties changed significantly (p < 0.05) among the different land use types; the microbial diversity and abundance in cropland soil were lower than those of the other two land use types. Soil pH, soil water content, total organic carbon and available nitrogen were the main soil physico-chemical properties driving the composition of the soil microbial community. Our results indicate that the soil microbial community response to the three different habitats is complex, and provide ideas for the mechanism by which land use changes in the Sanjiang Plain affect the structure of soil microbial communities, as well as a theoretical basis for the future management and sustainable use of the Sanjiang plain, in the northeast of China.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study.

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Treadmill training impacts the skeletal muscle molecular clock after ischemia stroke in rats.

Objective: Stroke is frequently associated with muscle mass loss. Treadmill training is considered the most effective treatment for sarcopenia. Circadian rhythms are closely related to exercise and have been extensively studied. The skeletal muscle has its molecular clock genes. Exercise may regulate skeletal muscle clock genes. This study evaluated the effects of early treadmill training on the skeletal muscle molecular clock machinery in rats with stroke and determined the relationship of these changes with exercise-induced improvements in skeletal muscle health. Materials and methods: Overall, 168 Sprague-Dawley rats were included in this study. We established an ischemic stroke rat model of sarcopenia. Finally, 144 rats were randomly allocated to four groups (36 per group): normal, sham, middle cerebral artery occlusion, and training. Neurological scores, rotating rod test, body weight, muscle circumference, wet weight, and hematoxylin-eosin staining were assessed. Twenty-four rats were used for transcriptome sequencing. Gene and protein expressions of skeletal muscles, such as brain muscle arnt-like 1, period 1, and period 2, were measured by quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assays. Results: Neurological function scores and rotating rod test results improved after treadmill training. Nine differentially expressed genes were identified by comparing the sham group with the hemiplegic side of the model group. Seventeen differentially expressed genes were identified between the hemiplegic and non-hemiplegic sides. BMAL1, PER1, and PER2 mRNA levels increased on both sides after treadmill training. BMAL1 expression increased, and PER1 expression decreased on both sides, whereas PER2 expression decreased on the hemiplegic side but increased on the non-hemiplegic side. Conclusion: Treadmill training can mitigate muscle loss and regulate skeletal muscle clock gene expression following ischemic stroke. Exercise affects the hemiplegic side and has a positive regulatory effect on the non-hemiplegic side.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2.

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.

Synonymous Mutations Can Alter Protein Dimerization Through Localized Interface Misfolding Involving Self-entanglements.

Synonymous mutations in messenger RNAs (mRNAs) can reduce protein-protein binding substantially without changing the protein's amino acid sequence. Here, we use coarse-grain simulations of protein synthesis, post-translational dynamics, and dimerization to understand how synonymous mutations can influence the dimerization of two E. coli homodimers, oligoribonuclease and ribonuclease T. We synthesize each protein from its wildtype, fastest- and slowest-translating synonymous mRNAs in silico and calculate the ensemble-averaged interaction energy between the resulting dimers. We find synonymous mutations alter oligoribonuclease's dimer properties. Relative to wildtype, the dimer interaction energy becomes 4% and 10% stronger, respectively, when translated from its fastest- and slowest-translating mRNAs. Ribonuclease T dimerization, however, is insensitive to synonymous mutations. The structural and kinetic origin of these changes are misfolded states containing non-covalent lasso-entanglements, many of which structurally perturb the dimer interface, and whose probability of occurrence depends on translation speed. These entangled states are kinetic traps that persist for long time scales. Entanglements cause altered dimerization energies for oligoribonuclease, as there is a large association (odds ratio: 52) between the co-occurrence of non-native self-entanglements and weak-binding dimer conformations. Simulated at all-atom resolution, these entangled structures persist for long timescales, indicating the conclusions are independent of model resolution. Finally, we show that regions of the protein we predict to have changes in entanglement are also structurally perturbed during refolding, as detected by limited-proteolysis mass spectrometry. Thus, non-native changes in entanglement at dimer interfaces is a mechanism through which oligomer structure and stability can be altered.

Nutritional changes in trees during drought-induced mortality: A comprehensive meta-analysis and a field study.

Both macronutrients and micronutrients are essential for tree growth and development through participating in various ecophysiological processes. However, the impact of the nutritional status of trees on their ability to withstand drought-induced mortality remains inconclusive. We thus conducted a comprehensive meta-analysis, compiling data on 11 essential nutrients from 44 publications (493 independent observations). Additionally, a field study was conducted on Pinus sylvestris L. trees with varying drought-induced vitality loss in the "Visp" forest in southern Switzerland. No consistent decline in tree nutritional status was observed during tree mortality. The meta-analysis revealed significantly lower leaf potassium (K), iron (Fe), and copper (Cu) concentrations with tree mortality. However, the field study showed no causal relationships between nutritional levels and the vitality status of trees. This discrepancy is mainly attributed to the intrinsic differences in the two types of experimental designs and the ontogenetic stages of target trees. Nutrient reductions preceding tree mortality were predominantly observed in non-field conditions, where the study was conducted on seedlings and saplings with underdeveloped root systems. It limits the nutrient uptake capacity of these young trees during drought. Furthermore, tree nutritional responses are also influenced by many variables. Specifically, (a) leaf nutrients are more susceptible to drought stress than other organs; (b) reduced tree nutrient concentrations are more prevalent in evergreen species during drought-induced mortality; (c) of all biomes, Mediterranean forests are most vulnerable to drought-induced nutrient deficiencies; (d) soil types affect the direction and extent of tree nutritional responses. We identified factors that influence the relationship between tree nutritional status and drought survival, and proposed potential early-warning indicators of impending tree mortality, for example, decreased K concentrations with declining vitality. These findings contribute to our understanding of tree responses to drought and provide practical implications for forest management strategies in the context of global change.

Application of machine learning in predicting survival outcomes involving real-world data: a scoping review.

BACKGROUND: Despite the interest in machine learning (ML) algorithms for analyzing real-world data (RWD) in healthcare, the use of ML in predicting time-to-event data, a common scenario in clinical practice, is less explored. ML models are capable of algorithmically learning from large, complex datasets and can offer advantages in predicting time-to-event data. We reviewed the recent applications of ML for survival analysis using RWD in healthcare. METHODS: PUBMED and EMBASE were searched from database inception through March 2023 to identify peer-reviewed English-language studies of ML models for predicting time-to-event outcomes using the RWD. Two reviewers extracted information on the data source, patient population, survival outcome, ML algorithms, and the Area Under the Curve (AUC). RESULTS: Of 257 citations, 28 publications were included. Random survival forests (N = 16, 57%) and neural networks (N = 11, 39%) were the most popular ML algorithms. There was variability across AUC for these ML models (median 0.789, range 0.6-0.950). ML algorithms were predominately considered for predicting overall survival in oncology (N = 12, 43%). ML survival models were often used to predict disease prognosis or clinical events (N = 27, 96%) in the oncology, while less were used for treatment outcomes (N = 1, 4%). CONCLUSIONS: The ML algorithms, random survival forests and neural networks, are mainly used for RWD to predict survival outcomes such as disease prognosis or clinical events in the oncology. This review shows that more opportunities remain to apply these ML algorithms to inform treatment decision-making in clinical practice. More methodological work is also needed to ensure the utility and applicability of ML models in survival outcomes.

Identification of potential anti-hyperglycemic compounds in Cordyceps militaris ethyl acetate extract: in vitro and in silico studies.

Cordyceps militaris has been long known for valuable health benefits by folk experience and was recently reported with diabetes-tackling evidences, thus deserving extending efforts on screening for component-activity relationship. In this study, experiments were carried out to find the evidence, justification, and input for computations on the potential against diabetes-related protein structures: PDB-4W93, PDB-3W37, and PDB-4A3A. Liquid chromatography identified 14 bioactive compounds in the ethyl acetate extract (1-14) and quantified the contents of cordycepin (0.11%) and adenosine (0.01%). Bioassays revealed the overall potential of the extract against α-amylase (IC50 = 6.443 ± 0.364 mg.mL-1) and α-glucosidase (IC50 = 2.580 ± 0.194 mg.mL-1). A combination of different computational platforms was used to select the most promising candidates for applications as anti-diabetic bio-inhibitors, i.e. 1 (ground state: -888.49715 a.u.; dipole moment 3.779 Debye; DS¯ -12.3 kcal.mol-1; polarizability 34.7 Å3; logP - 1.30), 10 (ground state: -688.52406 a.u.; dipole moment 5.487 Debye; DS¯ -12.6 kcal.mol-1; polarizability 24.9 Å3; logP - 3.39), and 12 (ground state: -1460.07276 a.u.; dipole moment 3.976 Debye; DS¯ -12.5 kcal.mol-1; polarizability 52.4 Å3; logP - 4.39). The results encourage further experimental tests on cordycepin (1), mannitol (10), and adenosylribose (12) to validate their in-practice diabetes-related activities, thus conducive to hypoglycemic applications.Communicated by Ramaswamy H. Sarma.

Recent Advances and Challenges in Ti-Based Oxide Anodes for Superior Potassium Storage.

Developing high-performance anodes is one of the most effective ways to improve the energy storage performances of potassium-ion batteries (PIBs). Among them, Ti-based oxides, including TiO2, K2Ti6O13, K2Ti4O9, K2Ti8O17, Li4Ti5O12, etc., as the intrinsic structural advantages, are of great interest for applications in PIBs. Despite numerous merits of Ti-based oxide anodes, such as fantastic chemical and thermal stability, a rich reserve of raw materials, non-toxic and environmentally friendly properties, etc., their poor electrical conductivity limits the energy storage applications in PIBs, which is the key challenge for these anodes. Although various modification projects are effectively used to improve their energy storage performances, there are still some related issues and problems that need to be addressed and solved. This review provides a comprehensive summary on the latest research progress of Ti-based oxide anodes for the application in PIBs. Besides the major impactful work and various performance improvement strategies, such as structural regulation, carbon modification, element doping, etc., some promising research directions, including effects of electrolytes and binders, MXene-derived TiO2-based anodes and application as a modifier, are outlined in this review. In addition, noteworthy research perspectives and future development challenges for Ti-based oxide anodes in PIBs are also proposed.

Amyloid-ß Tetramers and Divalent Cations at the Membrane/Water Interface: Simple Models Support a Functional Role.

Charge polarization at the membrane interface is a fundamental process in biology. Despite the lower concentration compared to the abundant monovalent ions, the relative abundance of divalent cations (Ca2+, Mg2+, Zn2+, Fe2+, Cu2+) in particular spaces, such as the neuron synapse, raised many questions on the possible effects of free multivalent ions and of the required protection of membranes by the eventual defects caused by the free forms of the cations. In this work, we first applied a recent realistic model of divalent cations to a well-investigated model of a polar lipid bilayer, di-myristoyl phosphatidyl choline (DMPC). The full atomistic model allows a fairly good description of changes in the hydration of charged and polar groups upon the association of cations to lipid atoms. The lipid-bound configurations were analyzed in detail. In parallel, amyloid-ß 1-42 (Aß42) peptides assembled into tetramers were modeled at the surface of the same bilayer. Two of the protein tetramers' models were loaded with four Cu2+ ions, the latter bound as in DMPC-free Aß42 oligomers. The two Cu-bound models differ in the binding topology: one with each Cu ion binding each of the monomers in the tetramer; one with pairs of Cu ions linking two monomers into dimers, forming tetramers as dimers of dimers. The models here described provide hints on the possible role of Cu ions in synaptic plasticity and of Aß42 oligomers in storing the same ions away from lipids. The release of structurally disordered peptides in the synapse can be a mechanism to recover ion homeostasis and lipid membranes from changes in the divalent cation concentration.

Tomato Maturity Detection and Counting Model Based on MHSA-YOLOv8.

The online automated maturity grading and counting of tomato fruits has a certain promoting effect on digital supervision of fruit growth status and unmanned precision operations during the planting process. The traditional grading and counting of tomato fruit maturity is mostly done manually, which is time-consuming and laborious work, and its precision depends on the accuracy of human eye observation. The combination of artificial intelligence and machine vision has to some extent solved this problem. In this work, firstly, a digital camera is used to obtain tomato fruit image datasets, taking into account factors such as occlusion and external light interference. Secondly, based on the tomato maturity grading task requirements, the MHSA attention mechanism is adopted to improve YOLOv8's backbone to enhance the network's ability to extract diverse features. The Precision, Recall, F1-score, and mAP50 of the tomato fruit maturity grading model constructed based on MHSA-YOLOv8 were 0.806, 0.807, 0.806, and 0.864, respectively, which improved the performance of the model with a slight increase in model size. Finally, thanks to the excellent performance of MHSA-YOLOv8, the Precision, Recall, F1-score, and mAP50 of the constructed counting models were 0.990, 0.960, 0.975, and 0.916, respectively. The tomato maturity grading and counting model constructed in this study is not only suitable for online detection but also for offline detection, which greatly helps to improve the harvesting and grading efficiency of tomato growers. The main innovations of this study are summarized as follows: (1) a tomato maturity grading and counting dataset collected from actual production scenarios was constructed; (2) considering the complexity of the environment, this study proposes a new object detection method, MHSA-YOLOv8, and constructs tomato maturity grading models and counting models, respectively; (3) the models constructed in this study are not only suitable for online grading and counting but also for offline grading and counting.

Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.

How soluble misfolded proteins bypass chaperones at the molecular level.

Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so. Thus, some misfolded subpopulations commonly bypass chaperones. Using multi-scale simulation models we observe that the misfolded structures that bypass various chaperones can do so because their structures are highly native like, leading to a situation where chaperones do not distinguish between the folded and near-native-misfolded states. More broadly, these results provide a mechanism by which long-time scale changes in protein structure and function can persist in cells because some misfolded states can bypass components of the proteostasis machinery.