Naturally-associated bacteria modulate Orsay virus infection of Caenorhabditis elegans.

Microbes associated with an organism can significantly modulate its susceptibility to viral infections, but our understanding of the influence of individual microbes remains limited. The nematode Caenorhabditis elegans is a model organism that in nature inhabits environments rich in bacteria. Here, we examine the impact of 71 naturally associated bacteria on C. elegans susceptibility to its only known natural virus, the Orsay virus. Our findings reveal that viral infection of C. elegans is significantly influenced by monobacterial environments. Compared to an Escherichia coli environmental reference, the majority of tested bacteria reduced C. elegans susceptibility to viral infection. This reduction is not caused by virion degradation or poor animal nutrition by the bacteria. The repression of viral infection by the bacterial strains Chryseobacterium JUb44 and Sphingobacterium BIGb0172 does not require the RIG-I homolog DRH-1, which is known to activate antiviral responses such as RNA interference and transcriptional regulation. Our research highlights the necessity of considering natural biotic environments in viral infection studies and opens the way future research on host-microbe-virus interactions.

Entropic control of the free-energy landscape of an archetypal biomolecular machine.

Biomolecular machines are complex macromolecular assemblies that utilize thermal and chemical energy to perform essential, multistep, cellular processes. Despite possessing different architectures and functions, an essential feature of the mechanisms of action of all such machines is that they require dynamic rearrangements of structural components. Surprisingly, biomolecular machines generally possess only a limited set of such motions, suggesting that these dynamics must be repurposed to drive different mechanistic steps. Although ligands that interact with these machines are known to drive such repurposing, the physical and structural mechanisms through which ligands achieve this remain unknown. Using temperature-dependent, single-molecule measurements analyzed with a time-resolution-enhancing algorithm, here, we dissect the free-energy landscape of an archetypal biomolecular machine, the bacterial ribosome, to reveal how its dynamics are repurposed to drive distinct steps during ribosome-catalyzed protein synthesis. Specifically, we show that the free-energy landscape of the ribosome encompasses a network of allosterically coupled structural elements that coordinates the motions of these elements. Moreover, we reveal that ribosomal ligands which participate in disparate steps of the protein synthesis pathway repurpose this network by differentially modulating the structural flexibility of the ribosomal complex (i.e., the entropic component of the free-energy landscape). We propose that such ligand-dependent entropic control of free-energy landscapes has evolved as a general strategy through which ligands may regulate the functions of all biomolecular machines. Such entropic control is therefore an important driver in the evolution of naturally occurring biomolecular machines and a critical consideration for the design of synthetic molecular machines.

Structure and dynamics of a processive Brownian motor: the translating ribosome.

There is mounting evidence indicating that protein synthesis is driven and regulated by mechanisms that direct stochastic, large-scale conformational fluctuations of the translational apparatus. This mechanistic paradigm implies that a free-energy landscape governs the conformational states that are accessible to and sampled by the translating ribosome. This scenario presents interdependent opportunities and challenges for structural and dynamic studies of protein synthesis. Indeed, the synergism between cryogenic electron microscopic and X-ray crystallographic structural studies, on the one hand, and single-molecule fluorescence resonance energy transfer (smFRET) dynamic studies, on the other, is emerging as a powerful means for investigating the complex free-energy landscape of the translating ribosome and uncovering the mechanisms that direct the stochastic conformational fluctuations of the translational machinery. In this review, we highlight the principal insights obtained from cryogenic electron microscopic, X-ray crystallographic, and smFRET studies of the elongation stage of protein synthesis and outline the emerging themes, questions, and challenges that lie ahead in mechanistic studies of translation.

Late steps in bacterial translation initiation visualized using time-resolved cryo-EM.

The initiation of bacterial translation involves the tightly regulated joining of the 50S ribosomal subunit to an initiator transfer RNA (fMet-tRNAfMet)-containing 30S ribosomal initiation complex to form a 70S initiation complex, which subsequently matures into a 70S elongation-competent complex. Rapid and accurate formation of the 70S initiation complex is promoted by initiation factors, which must dissociate from the 30S initiation complex before the resulting 70S elongation-competent complex can begin the elongation of translation1. Although comparisons of the structures of the 30S2-5 and 70S4,6-8 initiation complexes have revealed that the ribosome, initiation factors and fMet-tRNAfMet can acquire different conformations in these complexes, the timing of conformational changes during formation of the 70S initiation complex, the structures of any intermediates formed during these rearrangements, and the contributions that these dynamics might make to the mechanism and regulation of initiation remain unknown. Moreover, the absence of a structure of the 70S elongation-competent complex formed via an initiation-factor-catalysed reaction has precluded an understanding of the rearrangements to the ribosome, initiation factors and fMet-tRNAfMet that occur during maturation of a 70S initiation complex into a 70S elongation-competent complex. Here, using time-resolved cryogenic electron microscopy9, we report the near-atomic-resolution view of how a time-ordered series of conformational changes drive and regulate subunit joining, initiation factor dissociation and fMet-tRNAfMet positioning during formation of the 70S elongation-competent complex. Our results demonstrate the power of time-resolved cryogenic electron microscopy to determine how a time-ordered series of conformational changes contribute to the mechanism and regulation of one of the most fundamental processes in biology.

Ratchet, swivel, tilt and roll: a complete description of subunit rotation in the ribosome.

Protein synthesis by the ribosome requires large-scale rearrangements of the 'small' subunit (SSU; ∼1 MDa), including inter- and intra-subunit rotational motions. However, with nearly 2000 structures of ribosomes and ribosomal subunits now publicly available, it is exceedingly difficult to design experiments based on analysis of all known rotation states. To overcome this, we developed an approach where the orientation of each SSU head and body is described in terms of three angular coordinates (rotation, tilt and tilt direction) and a single translation. By considering the entire RCSB PDB database, we describe 1208 fully-assembled ribosome complexes and 334 isolated small subunits, which span >50 species. This reveals aspects of subunit rearrangements that are universal, and others that are organism/domain-specific. For example, we show that tilt-like rearrangements of the SSU body (i.e. 'rolling') are pervasive in both prokaryotic and eukaryotic (cytosolic and mitochondrial) ribosomes. As another example, domain orientations associated with frameshifting in bacteria are similar to those found in eukaryotic ribosomes. Together, this study establishes a common foundation with which structural, simulation, single-molecule and biochemical efforts can more precisely interrogate the dynamics of this prototypical molecular machine.

Increasing the accuracy of single-molecule data analysis using tMAVEN.

Time-dependent single-molecule experiments contain rich kinetic information about the functional dynamics of biomolecules. A key step in extracting this information is the application of kinetic models, such as hidden Markov models (HMMs), which characterize the molecular mechanism governing the experimental system. Unfortunately, researchers rarely know the physicochemical details of this molecular mechanism a priori, which raises questions about how to select the most appropriate kinetic model for a given single-molecule data set and what consequences arise if the wrong model is chosen. To address these questions, we have developed and used time-series modeling, analysis, and visualization environment (tMAVEN), a comprehensive, open-source, and extensible software platform. tMAVEN can perform each step of the single-molecule analysis pipeline, from preprocessing to kinetic modeling to plotting, and has been designed to enable the analysis of a single-molecule data set with multiple types of kinetic models. Using tMAVEN, we have systematically investigated mismatches between kinetic models and molecular mechanisms by analyzing simulated examples of prototypical single-molecule data sets exhibiting common experimental complications, such as molecular heterogeneity, with a series of different types of HMMs. Our results show that no single kinetic modeling strategy is mathematically appropriate for all experimental contexts. Indeed, HMMs only correctly capture the underlying molecular mechanism in the simplest of cases. As such, researchers must modify HMMs using physicochemical principles to avoid the risk of missing the significant biological and biophysical insights into molecular heterogeneity that their experiments provide. By enabling the facile, side-by-side application of multiple types of kinetic models to individual single-molecule data sets, tMAVEN allows researchers to carefully tailor their modeling approach to match the complexity of the underlying biomolecular dynamics and increase the accuracy of their single-molecule data analyses.

Insights into estrogen impact in oral health & microbiome in COVID-19.

BACKGROUND: COVID-19 emerged in late 2019 and has occasioned more than 765 millions cumulative cases and 6.9 millions of deaths globally. Notably, around 70% of patients with severe COVID-19 are men. Therefore, it is to be presumed that women have a hormonal protector factor in inflammation and ACE2 expression. On the other hand, oral health status, and local microbiome can be key factors to respiratory viral infections control. Nevertheless, it has been poorly investigated. In our study 20 premenopausal, 18 postmenopausal and 22 men with COVID-19 were included. Oral health status, viral load, lingual ACE2 expression, as well as microbiome, estrogens and cytokines in saliva were analyzed. RESULTS: Our results showed a lower expression of ACE2 in tongue cells of postmenopausal compared with premenopausal (p = 0.05), and a strong negative correlation between saliva estrogen and viral load (r = -0.76; p = 0.001). Respect to IFN-γ (p = 0.05), IL-1ß, TNF-α, IL-18, and IL-23 levels were increased in postmenopausal. Oral microbiome signature of premenopausal was characterized by Prevotella melaninogenica (Log2 = 26.68; p = 1.34e-10), Haemophilus (Log2 = 23.99; p = 2.96e-9), and Alloprevotella (Log2 = 7.92; p = 0.0001). On the other hand, Leptotrichia (Log2 = -18.74; p = 0.001), Tanerella (Log2 = -17.08; p = 0.004), and Clostridiales (Log2 = -2.88; p = 0.04) represented the poor oral health group compared with the adequate group which was enriched with the commensal microorganism Neisseria perflava (Log2 = 26.70; p = 1.74e-7). Furthermore, the high viral load group was characterized by Prevotella nanceiensis (Log2 = 19.60; p = 6.06e-8), Prevotella melaninogenica (Log2 = 21.45; p = 9.59e-6), Alloprevotella (Log2 = 23.50; p = 2.70e-7) and bacteria from the red complex Porphyromonas endodentalis (Log2 = 21.97; p = 1.38e-7). CONCLUSIONS: Postmenopausal and men have a poor oral health status which could be related to a detrimental progression of COVID-19 also linked to a lower expression of ACE2, lower saliva estrogen levels and oral dysbiosis. Nevertheless, functional studies are required for a deeper knowledge.

Barriers to early diagnosis and management of oral cancer in Latin America and the Caribbean.

OBJECTIVE: This study aimed to explore perceived barriers to early diagnosis and management of oral cancer, as well as potential pathways for improvement in Latin America and the Caribbean (LAC). METHODS: This cross-sectional study used a self-administered online questionnaire created via the Research Electronic Data Capture platform. The survey was distributed to health professionals trained in Oral Medicine, Oral Pathology, Oral and Maxillofacial Surgery, and Dentists with clinical and academic expertise in oral potentially malignant disorder (OPMD) and oral cancer. Data obtained were systematically organized and analyzed descriptively using Microsoft Excel. RESULTS: Twenty-three professionals from 21 LAC countries participated. Major barriers included the limited implementation of OPMD and oral cancer control plans (17.4%), low compulsory reporting for OPMD (8.7%) and oral cancer (34.8%), unclear referral pathways for OPMD (34.8%) and oral cancer (43.5%), and a shortage of trained professionals (8.7%). Participants endorsed the utility of online education (100%) and telemedicine (91.3%). CONCLUSION: The survey highlights major perceived barriers to early diagnosis and management of OPMD and oral cancer in LAC, as well as potential avenues for improvement.

Plant virus evolution under strong drought conditions results in a transition from parasitism to mutualism.

Environmental conditions are an important factor driving pathogens' evolution. Here, we explore the effects of drought stress in plant virus evolution. We evolved turnip mosaic potyvirus in well-watered and drought conditions in Arabidopsis thaliana accessions that differ in their response to virus infection. Virus adaptation occurred in all accessions independently of watering status. Drought-evolved viruses conferred a significantly higher drought tolerance to infected plants. By contrast, nonsignificant increases in tolerance were observed in plants infected with viruses evolved under standard watering. The magnitude of this effect was dependent on the plant accessions. Differences in tolerance were correlated to alterations in the expression of host genes, some involved in regulation of the circadian clock, as well as in deep changes in the balance of phytohormones regulating defense and growth signaling pathways. Our results show that viruses can promote host survival in situations of abiotic stress, with the magnitude of such benefit being a selectable trait.

Exact Results for Non-Newtonian Transport Properties in Sheared Granular Suspensions: Inelastic Maxwell Models and BGK-Type Kinetic Model.

The Boltzmann kinetic equation for dilute granular suspensions under simple (or uniform) shear flow (USF) is considered to determine the non-Newtonian transport properties of the system. In contrast to previous attempts based on a coarse-grained description, our suspension model accounts for the real collisions between grains and particles of the surrounding molecular gas. The latter is modeled as a bath (or thermostat) of elastic hard spheres at a given temperature. Two independent but complementary approaches are followed to reach exact expressions for the rheological properties. First, the Boltzmann equation for the so-called inelastic Maxwell models (IMM) is considered. The fact that the collision rate of IMM is independent of the relative velocity of the colliding spheres allows us to exactly compute the collisional moments of the Boltzmann operator without the knowledge of the distribution function. Thanks to this property, the transport properties of the sheared granular suspension can be exactly determined. As a second approach, a Bhatnagar-Gross-Krook (BGK)-type kinetic model adapted to granular suspensions is solved to compute the velocity moments and the velocity distribution function of the system. The theoretical results (which are given in terms of the coefficient of restitution, the reduced shear rate, the reduced background temperature, and the diameter and mass ratios) show, in general, a good agreement with the approximate analytical results derived for inelastic hard spheres (IHS) by means of Grad's moment method and with computer simulations performed in the Brownian limiting case (m/mg→∞, where mg and m are the masses of the particles of the molecular and granular gases, respectively). In addition, as expected, the IMM and BGK results show that the temperature and non-Newtonian viscosity exhibit an S shape in a plane of stress-strain rate (discontinuous shear thickening, DST). The DST effect becomes more pronounced as the mass ratio m/mg increases.

Impact of virtual reality-based therapy on post-stroke depression: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Post-stroke depression is the most common neuropsychiatric consequence and reduces rehabilitation effectiveness. However, the efficacy of virtual reality (VR) on mental health treatment for patients after a stroke is uncertain. AIMS: The aim of this study was to evaluate the efficacy of VR as a co-adjuvant form of treatment to reduce depression in stroke patients admitted to neurorehabilitation units. METHODS: We systematically searched medical databases including PubMed, CINAHL, PsycINFO, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov from inception to November 16, 2023. Clinical trials comparing the use of VR as an adjuvant form of treatment in stroke patients' rehabilitation with the usual treatment were included. Pooled standardized mean differences were calculated using a random-effects model. Subgroup analyses were performed according to type of stroke, VR characteristics, and the scale used to measure depression. Meta-regression analysis was performed for intervention duration and to determine the mean age of the participants. RESULTS: Eight studies and 388 stroke patients were included. The VR interventions were associated with a lower risk of depression in patients (ES = -0.69; 95% CI [-1.05, -0.33]; I2 = 57.6%; p ≤ .02). The estimates were not affected by the type of stroke, the type of VR used, the blinding process, the type of scale used to detect depression, the duration of the intervention (weeks and minutes), and the total number of sessions. Meta-regression shows that younger samples (p = .00; 95% CI [0.01, 0.08) and longer interventions (p = < .05; 95% CI [-0.00, -0.00) lead to a greater reduction in depression. LINKING EVIDENCE TO ACTION: This review provides an important basis for treating depression in patients after a stroke. Professionals working in stroke neurorehabilitation units should consider VR as a form of co-adjuvant treatment for depression in patients. SYSTEMATIC REVIEW REGISTRATION: CRD42022303968.

Characterizing the Conformational Free-Energy Landscape of RNA Stem-Loops Using Single-Molecule Field-Effect Transistors.

We have developed and used single-molecule field-effect transistors (smFETs) to characterize the conformational free-energy landscape of RNA stem-loops. Stem-loops are one of the most common RNA structural motifs and serve as building blocks for the formation of complex RNA structures. Given their prevalence and integral role in RNA folding, the kinetics of stem-loop (un)folding has been extensively characterized using both experimental and computational approaches. Interestingly, these studies have reported vastly disparate timescales of (un)folding, which has been interpreted as evidence that (un)folding of even simple stem-loops occurs on a highly rugged conformational energy landscape. Because smFETs do not rely on fluorophore reporters of conformation or mechanical (un)folding forces, they provide a unique approach that has allowed us to directly monitor tens of thousands of (un)folding events of individual stem-loops at a 200 µs time resolution. Our results show that under our experimental conditions, stem-loops (un)fold over a 1-200 ms timescale during which they transition between ensembles of unfolded and folded conformations, the latter of which is composed of at least two sub-populations. The 1-200 ms timescale of (un)folding we observe here indicates that smFETs report on complete (un)folding trajectories in which unfolded conformations of the RNA spend long periods of time wandering the free-energy landscape before sampling one of several misfolded conformations or the natively folded conformation. Our findings highlight the extremely rugged landscape on which even the simplest RNA structural elements fold and demonstrate that smFETs are a unique and powerful approach for characterizing the conformational free-energy of RNA.

The Association of Chinese Ethnicity and Language Preference with Advance Directive Completion Among Older Patients in an Integrated Health System.

BACKGROUND: Little is known about possible differences in advance directive completion (ADC) based on ethnicity and language preference among Chinese Americans on a regional level. OBJECTIVE: To understand the association of ethnicity and language preference with ADC among Chinese Americans. DESIGN: Retrospective cohort analysis with direct standardization. PARTICIPANTS: A total of 31,498 Chinese and 502,991 non-Hispanic White members enrolled in Kaiser Permanente Northern California during the entire study period between 2013 and 2017 who were 55 or older as of January 1, 2018. MAIN MEASURES: We compared the proportion of ADC among non-Hispanic White and Chinese patients, and also analyzed the rates according to language preference within the Chinese population. We calculated ADC rates with direct standardization using covariates previously found in literature to be significant predictors of ADC such as age and utilization. KEY RESULTS: Among Chinese members, 60% preferred English, 16% preferred another language without needing an interpreter, and 23% needed an interpreter. After standardizing for age and utilization, non-Hispanic Whites were more than twice as likely to have ADC as Chinese members (20.6% (95% confidence interval (CI): 20.5-20.7%) vs. 10.0% (95% CI: 9.6-10.3%), respectively). Among Chinese members, there was an inverse association between preference for a language other than English and ADC (13.3% (95% CI: 12.8-13.8%) if preferring English, 6.1% (95% CI: 5.4-6.7%) if preferring non-English language but not needing an interpreter, and 5.1% (95% CI: 4.6-5.6%) if preferring non-English language and needing an interpreter). CONCLUSIONS: Chinese members are less likely to have ADC relative to non-Hispanic White members, and those preferring a language other than English are most affected. Further studies can assess reasons for lower ADC among Chinese members, differences in other Asian American populations, and interventions to reduce differences among Chinese members especially among those preferring a language other than English.

Can Apparent Diffusion Coefficient (ADC) maps replace Diffusion Tensor Imaging (DTI) maps to predict the volumetric response of meningiomas to Gamma Knife Radiosurgery?

PURPOSE: Noninvasive methods are desired to predict the treatment response to Stereotactic Radiosurgery (SRS) to improve individual tumor management. In a previous study, we demonstrated that Diffusion Tensor Imaging (DTI)-derived parameter maps significantly correlate to SRS response. This study aimed to analyze and compare the predictive value of intratumoral ADC and DTI parameters in patients with meningiomas undergoing radiosurgery. METHODS: MR images of 70 patients treated with Gamma Knife SRS for WHO grade I meningiomas were retrospectively reviewed. MR acquisition included pre- and post-treatment DWI and DTI sequences, and subtractions were calculated to assess for radiation-induced changes in the parameter values. RESULTS: After a mean follow-up period (FUP) of 52.7 months, 69 of 70 meningiomas were controlled, with a mean volume reduction of 34.9%. Whereas fractional anisotropy (FA) values of the initial exam showed the highest correlation to tumor volume change at the last FU (CC = - 0.607), followed by the differences between first and second FU values of FA (CC = - 0.404) and the first longitudinal diffusivity (LD) value (CC = - 0.375), the correlation coefficients of all ADC values were comparably low. Nevertheless, all these correlations, except for ADC measured at the first follow-up, reached significance. CONCLUSION: For the first time, the prognostic value of ADC maps measured in meningiomas before and at first follow-up after Gamma Knife SRS, was compared to simultaneously acquired DTI parameter maps. Quantities assessed from ADC maps present significant correlations to the volumetric meningioma response but are less effective than correlations with DTI parameters.

Myositis autoantibodies detected by line blot immunoassay: clinical associations and correlation with antibody signal intensity.

The aim of this study is to assess the relationship between myositis specific (MSA) and myositis associated (MAA) antibodies and diagnosis (including idiopathic inflammatory myopathies [IIM] and other systemic autoimmune diseases [SAID]), and to explore the impact of antibody signal intensity in diagnostic accuracy. We retrospectively reviewed all the serum samples obtained from patients tested for MSA/MAA by line immunoassay (LIA) between 01/01/2018 and 31/12/2020 in Ramón y Cajal University Hospital (Spain). Clinical true positive (CTP) MSAs and MAAs were defined as those patients with IIM or SAID with phenotypes expected of that MSA/MAA. Patients who did not have a phenotype compatible with that antibody were classified as clinical false positive (CFP). One hundred and thirty positive samples were analysed. Forty-six patients (33.38%) were classified as IIM, forty-two (32.3%) as SAID and forty-two (32.3%) as non-IIM/SAID. Among these 130 patients, 164 MSA/MAA were detected. Eighty-five (51.8%) positive MSA/MAA were classified as CTP, and seventy-nine (48.2%) as CFP. Strongly positive antibodies were more frequently CTP (35/47, 74.5%) than weak positives (54/68, 36.8%), (p ˂ 0.001). Antibodies classified as CTP had a higher signal intensity than CFP (36.77 AU vs 20.00 AU, CI95% 7.79-22.09, p ˂ 0.001). The probability of a CFP was associated to negative ANA, low ANA titer, and multiple positive MSA/MAA (p Ë‚ 0.001). In this study, we confirmed that CFP results using LIA are frequent, and are associated with low signal intensity MSA/MAA, negative ANA, lower titer ANA, and with multiple positive samples.

The alarmones (p)ppGpp directly regulate translation initiation during entry into quiescence.

Many bacteria exist in a state of metabolic quiescence where energy consumption must be minimized so as to maximize available resources over a potentially extended period of time. As protein synthesis is the most energy intensive metabolic process in a bacterial cell, it would be an appropriate target for down-regulation during the transition from growth to quiescence. We observe that when Bacillus subtilis exits rapid growth, a subpopulation of cells emerges with very low protein synthetic activity. This phenotypic heterogeneity requires the production of the nucleotides (p)ppGpp, which we show are sufficient to inhibit protein synthesis in vivo. We then show that one of these molecules, ppGpp, inhibits protein synthesis by preventing the allosteric activation of the essential GTPase Initiation Factor 2 (IF2) during translation initiation. Finally, we demonstrate that the observed attenuation of protein synthesis during the entry into quiescence is a consequence of the direct interaction of (p)ppGpp and IF2.

A Deep Learning Image System for Classifying High Oleic Sunflower Seed Varieties.

Sunflower seeds, one of the main oilseeds produced around the world, are widely used in the food industry. Mixtures of seed varieties can occur throughout the supply chain. Intermediaries and the food industry need to identify the varieties to produce high-quality products. Considering that high oleic oilseed varieties are similar, a computer-based system to classify varieties could be useful to the food industry. The objective of our study is to examine the capacity of deep learning (DL) algorithms to classify sunflower seeds. An image acquisition system, with controlled lighting and a Nikon camera in a fixed position, was constructed to take photos of 6000 seeds of six sunflower seed varieties. Images were used to create datasets for training, validation, and testing of the system. A CNN AlexNet model was implemented to perform variety classification, specifically classifying from two to six varieties. The classification model reached an accuracy value of 100% for two classes and 89.5% for the six classes. These values can be considered acceptable, because the varieties classified are very similar, and they can hardly be classified with the naked eye. This result proves that DL algorithms can be useful for classifying high oleic sunflower seeds.

Oral Pyogenic Granuloma: A Narrative Review.

Pyogenic granuloma (PG) is a benign vascular lesion found predominantly in the oral cavity. Characterized by rapid growth and propensity to bleed, PG presents diagnostic challenges due to its similarity and alarming proliferation. This narrative review synthesizes current knowledge on the epidemiology, etiopathogenesis, clinical manifestations, and management of oral PG, with emphasis on recent advances in diagnostic and therapeutic approaches. The epidemiology of the injury is meticulously analyzed, revealing a higher incidence in women and a wide range of ages of onset. It delves into the etiopathogenesis, highlighting the uncertainty surrounding the exact causal factors, although historical attributions suggest an infectious origin. It exhaustively analyzes the clinical and histopathological aspects of oral PG, offering information on its various presentations and the importance of an accurate diagnosis to guide effective treatment. It details treatment strategies, emphasizing the personalized approach based on individual patient characteristics. This comprehensive review consolidates current knowledge on oral PG, highlighting the need for further research to clarify its pathogenesis and optimize treatment protocols.

Walking as a cultural act and a profit for the landscape. A case study in the Iberian Peninsula.

Walking as a means of travel, when done voluntarily, becomes a cultural act that can have a beneficial effect both for the people who carry out the routes and for the space itself that is walked on. The fact of moving at a slow speed allow us to recover a more appropriate pace to enjoy the landscape, to reconnect with nature and with the position of human in the world, while improving our health. In contemporary society, some cultural tourist routes have become successful destinations, with the continuous arrival of thousands of visitors throughout the year. Thus, the historical cultural route Way of St. James has become a globally successful cultural tourism product. Close to this destination, the Ribeira Sacra, that has been recently designated by the regional government as a Cultural Landscape, with the intention of preserving its historical legacy, may be in the future a privileged destination in Galicia for walking. The research carried out allows us to ensure that this fact, taking long walks following routes with a rich cultural content, has a positive impact on the space from two different processes that are reinforced as the routes become more popular. First, from the recovery and promotion of an alternative communication network between different places. And second, through a series of laws and regulations that protect historic trails and adjacent landscapes.

Multiplexed genomic encoding of non-canonical amino acids for labeling large complexes.

Stunning advances in the structural biology of multicomponent biomolecular complexes (MBCs) have ushered in an era of intense, structure-guided mechanistic and functional studies of these complexes. Nonetheless, existing methods to site-specifically conjugate MBCs with biochemical and biophysical labels are notoriously impracticable and/or significantly perturb MBC assembly and function. To overcome these limitations, we have developed a general, multiplexed method in which we genomically encode non-canonical amino acids (ncAAs) into multiple, structure-informed, individual sites within a target MBC; select for ncAA-containing MBC variants that assemble and function like the wildtype MBC; and site-specifically conjugate biochemical or biophysical labels to these ncAAs. As a proof-of-principle, we have used this method to generate unique single-molecule fluorescence resonance energy transfer (smFRET) signals reporting on ribosome structural dynamics that have thus far remained inaccessible to smFRET studies of translation.