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The antidepressant efficacy and safety of seltorexant monotherapy in major depressive disorder (MDD) was investigated in a placebo-controlled, placebo lead-in, randomized, double-blind, phase 1b study. Participants were randomized to receive seltorexant (20 mg or 40 mg) or placebo. The treatment effect was assessed by changes in the Hamilton Rating Scale for Depression-17 item (HDRS17) from treatment-period baseline to week 5 in lead-in placebo non-responders (“enriched” intent-to-treat analysis set). As a secondary outcome, the effect of seltorexant on HDRS17was assessed in patients with and without subjective insomnia. Seltorexant’s effects on polysomnography, serum cortisol, and cortisol waking response were also measured. In total, 128 participants were enrolled, including 86 in the enriched sample (lead-in placebo non-responders). The mean changes from baseline (SD) in HDRS17score at week 5 differed significantly across arms: −7.0 (5.04) for seltorexant 20 mg, −5.5 (4.34) for seltorexant 40 mg, and −4.4 (3.67) for placebo (p = 0.0456), which was attributable to the difference between the 20 mg and placebo arms (p = 0.0049). Improvement in depression severity at week 5 for seltorexant 20 mg was greater in patients with higher baseline insomnia severity (nominal p = 0.0059). The treatment benefit in the 20 mg arm remained significant when HDRS scores were adjusted by removing the sleep items (nominal p = 0.0289). The mean HDRS17change versus placebo was numerically larger in the 20 mg than the 40 mg arm, consistent with data from a previous study in which seltorexant was administered adjunctively to conventional antidepressants. In secondary analyses, the waking cortisol response decreased in the 20 mg arm but not the 40 mg or placebo arms, and while total sleep increased more in the 40 mg arm, this arm also showed reduced REM onset latency and increased stage N1 sleep, which were not evident in the 20 mg arm. These biomarker data suggest mechanistic hypotheses that may account for the apparent curvilinear dose-response relationship of seltorexant. Trial Registration: ClinicalTrials.gov, NCT03374475.

We introduce a novel co-design method for autonomous moving agents’ shape attributes and locomotion by combining deep reinforcement learning and evolution with user control. Our main inspiration comes from evolution, which has led to wide variability and adaptation in Nature and has significantly improved design and behavior simultaneously. Our method takes an input agent with optional user-defined constraints, such as leg parts that should not evolve or are only within the allowed ranges of changes. It uses physics-based simulation to determine its locomotion and finds a behavior policy for the input design that is used as a baseline for comparison. The agent is randomly modified within the allowed ranges, creating a new generation of several hundred agents. The generation is trained by transferring the previous policy, which significantly speeds up the training. The best-performing agents are selected, and a new generation is formed using their crossover and mutations. The next generations are then trained until satisfactory results are reached. We show a wide variety of evolved agents, and our results show that even with only 10% of allowed changes, the overall performance of the evolved agents improves by 50%. If more significant changes to the initial design are allowed, our experiments’ performance will improve even more to 150%. Our method significantly improved motion tasks without changing body structures, and it does not require considerable computation resources as it works on a single GPU and provides results by training thousands of agents within 30 minutes.

Besides many other uses, dried Cannabismay be used for “tea” preparation. This study focused on a comprehensive characterization of an aqueous infusion prepared according to a common practice from three fairly different Cannabiscultivars. The transfer of 42 phytocannabinoids and 12 major bioactive compounds (flavonoids) into the infusion was investigated using UHPLC-HRMS/MS. Phytocannabinoid acids were transferred generally in a higher extent compared to their counterparts; in the case of Δ9-THC, it was only in the range of 0.4–1.9% of content in the Cannabisused. A dramatic increase of phytocannabinoids, mainly of the neutral species, occurred when cream was added during steeping, and the transfer of Δ9-THC into “tea” achieved a range of 53–64%. Under such conditions, drinking a 250 mL cup of such tea by a 70 kg person might lead to multiple exceedance of the Acute Reference Dose (ARfD), 1 μg/kg b.w., even in the case when using hemp with a Δ9-THC content below 1% in dry weight for preparation.

Improving access to kidney transplants remains a priority for the transplant community. However, many medical, psychosocial, geographic, and socioeconomic barriers exist that prevent or delay transplantation for candidates with certain conditions. There is a lack of consensus regarding how to best approach many of these issues and barriers, leading to heterogeneity in transplant centers’ management and acceptance practices for a variety of pretransplant candidate issues. In this review, we address several of the more common contemporary patient medical and psychosocial barriers frequently encountered by transplant programs. The barriers discussed here include kidney transplant candidates with obesity, older age, prior malignancy, cardiovascular disease, history of nonadherence, and cannabis use. Improving understanding of how to best address these specific issues can empower referring providers, transplant programs, and patients to address these issues as necessary to progress toward eventual successful transplantation.

Two existing generic force fields have been augmented with partial charges and tuned in order to give intercompatible all-atom empirical potentials that can satisfactorily represent the known crystal phase structures of the organic phloroglucinol (Phg) (C6H6O3) and inorganic hexachlorocyclotriphosphazene (HCCP) (N3P3Cl6) molecules at several temperatures. It has been proposed that HCCP-Phg network polymers could act as efficient H2barrier layers in hydrogen storage tanks for cars. However, essential requirements for modeling such networks are adequate representations of both monomers in their pure dense phases using a common form of force field. Tests of their ability to maintain stable crystal structures have been made using classical molecular dynamics (MD) simulations on large 800-molecule supercells. The force fields have been optimized to match the densities calculated from the experimental unit cell dimensions at ambient conditions as well as the intermolecular potential energy, as estimated from experimental enthalpies of sublimation. For Phg, the crystal structure is stabilized by a network of hydrogen bonds and the Coulombic interactions contribute to over 55% of the total intermolecular potential energy. In contrast, the crystal structure of HCCP is intrinsically stabilized by the van der Waals terms. Both optimized force fields reproduce very well the orthorhombic symmetry of their respective crystals under constant-pressure NPTconditions. The model parameters tuned at ambient temperature also give reasonable agreement with crystallographic data at lower temperatures.

In this article, we propose DeepTree, a novel method for modeling trees based on learning developmental rules for branching structures instead of manually defining them. We call our deep neural model “situated latent” because its behavior is determined by the intrinsic state -encoded as a latent space of a deep neural model- and by the extrinsic (environmental) data that is “situated” as the location in the 3D space and on the tree structure. We use a neural network pipeline to train a situated latent space that allows us to locally predict branch growth only based on a single node in the branch graph of a tree model. We use this representation to progressively develop new branch nodes, thereby mimicking the growth process of trees. Starting from a root node, a tree is generated by iteratively querying the neural network on the newly added nodes resulting in the branching structure of the whole tree. Our method enables generating a wide variety of tree shapes without the need to define intricate parameters that control their growth and behavior. Furthermore, we show that the situated latents can also be used to encode the environmental response of tree models, e.g., when trees grow next to obstacles. We validate the effectiveness of our method by measuring the similarity of our tree models and by procedurally generated ones based on a number of established metrics for tree form.

Purpose: This study aims to evaluate the cost-utility of intraoperative tranexamic acid (TXA) in adult spinal deformity (ASD) patients undergoing long posterior (≥ 5 vertebral levels) spinal fusion. Methods: A decision-analysis model was built for a hypothetical 60-year-old adult patient with spinal deformity undergoing long posterior spinal fusion. A comprehensive review of the literature was performed to obtain event probabilities, costs and health utilities at each node. Health utilities were utilized to calculate Quality-Adjusted Life Years (QALYs). A base-case analysis was carried out to obtain the incremental cost and effectiveness of intraoperative TXA. Probabilistic sensitivity analysis was performed to evaluate uncertainty in our model and obtain mean incremental costs, effectiveness, and net monetary benefits. One-way sensitivity analyses were also performed to identify the variables with the most impact on our model. Results: Use of intraoperative TXA was the favored strategy in 88% of the iterations. The mean incremental utility ratio for using intraoperative TXA demonstrated higher benefit and lower cost while being lower than the willingness-to-pay threshold set at $50,000 per quality adjusted life years. Use of intraoperative TXA was associated with a mean incremental net monetary benefit (INMB) of $3743 (95% CI 3492–3995). One-way sensitivity analysis reported cost of blood transfusions due to post-operative anemia to be a major driver of cost–utility analysis. Conclusion: Use of intraoperative TXAs is a cost-effective strategy to reduce overall perioperative costs related to post-operative blood transfusions. Administration of intraoperative TXA should be considered for long fusions in ASD population when not explicitly contra-indicated due to patient factors.

The Extracorporeal Life Support Organization (ELSO) maintains the world’s largest extracorporeal membrane oxygenation (ECMO) registry by volume, center participation, and international scope. This 2022 ELSO Registry Report describes the program characteristics of ECMO centers, processes of ECMO care, and reported outcomes. Neonates (0–28 days), children (29 days–17 years), and adults (≥18 years) supported with ECMO from 2009 through 2022 and reported to the ELSO Registry were included. This report describes adjunctive therapies, support modes, treatments, complications, and survival outcomes. Data are presented descriptively as counts and percent or median and interquartile range (IQR) by year, group, or level. Missing values were excluded before calculating descriptive statistics. Complications are reported per 1,000 ECMO hours. From 2009 to 2022, 154,568 ECMO runs were entered into the ELSO Registry. Seven hundred and eighty centers submitted data during this time (557 in 2022). Since 2009, the median annual number of adult ECMO runs per center per year increased from 4 to 15, whereas for pediatric and neonatal runs, the rate decreased from 12 to 7. Over 50% of patients were transferred to the reporting ECMO center; 20% of these patients were transported with ECMO. The use of prone positioning before respiratory ECMO increased from 15% (2019) to 44% (2021) for adults during the coronavirus disease-2019 (COVID-19) pandemic. Survival to hospital discharge was greatest at 68.5% for neonatal respiratory support and lowest at 29.5% for ECPR delivered to adults. By 2022, the Registry had enrolled its 200,000th ECMO patient and 100,000th patient discharged alive. Since its inception, the ELSO Registry has helped centers measure and compare outcomes across its member centers and strategies of care. Continued growth and development of the Registry will aim to bolster its utility to patients and centers.

People suffering from chronic insomnia are at an increased risk of physical and mental illness. The absenteeism rate for people with sleep disorders in Germany is more than twice as high as for people without. Therefore, appropriate diagnosis and treatment of sleep disorders is a considerable medical and social necessity.

Menschen, die unter chronischer Insomnie leiden, haben ein erhöhtes Risiko für körperliche und psychische Erkrankungen. Die Fehlzeitenquote ist bei Personen mit Schlafstörungen in Deutschland mehr als doppelt so hoch wie bei Personen ohne. Daher ist eine angemessene Diagnose und Therapie von Schlafstörungen eine wesentliche medizinische und gesellschaftliche Notwendigkeit.

Histopathological examination is a crucial step in the diagnosis and treatment of many major diseases. Aiming to facilitate diagnostic decision making and improve the workload of pathologists, we developed an artificial intelligence (AI)-based prescreening tool that analyses whole-slide images (WSIs) of large-bowel biopsies to identify typical, non-neoplastic, and neoplastic biopsies.

This article investigates an unconventional approach to solving the control of lateral displacement for railway bogie wheelsets using recurrent higher order neural units (HONUs). Although studies addressing control of independently rotating wheelsets have shown promising results, they are rarely applied by railway manufacturers. Research and developments in modern bogie design are trending toward active yaw control design as an extension to conventional wheelsets mechanics, particularly for higher speeds. We investigate a model-reference architecture for active control via setpoint tracking of lateral displacement. Then, a new HONU sliding mode architecture is derived to solve convergence for zero lateral displacements in higher running speeds which is a more profoundly complex issue in maintaining minimal hunting motion. Starting from the property of nonlinear polynomial architecture of HONUs with in-parameter linearity, we derive a time-variant state-space representation via nonlinear identical decomposition. Then, an input-to-state stability (ISS) approach is applied to prove the local asymptotic convergence of the applied algorithm in each state point and the bounded-input-bounded-state stability of the entire nonlinear adaptive control loop. Using ISS theory, we also prove the global asymptotic stability of the HONU sliding mode controller for the actively controlled wheelset system. The techniques are validated by simulations and a real roller rig system.

Wire electrical discharge machining (WEDM) is an unconventional machining technology that is indispensable in many industries. Machining is performed using the thermoelectric principle, while it is possible to machine all at least minimally electrically conductive materials. Due to the wide range of applications of WEDM, it is necessary to ensure the appropriate quality of machined surfaces, regardless of the thickness of the machined materials, while maintaining an acceptable cutting speed. For this purpose, this study was performed to analyse the effect of material thickness on the cutting speed, morphology and topography of Ampcoloy 35 material. In this study, thicknesses from 5 to 160 mm were analysed in 5 mm increments with the same machine parameter settings. The surface topography and morphology were studied using electron and light microscopy, and cross-sections of the sample were created to examine the condition of the subsurface layer. It was found that the values of Ra at the edge ranged from 1.8 to 3.2 µm and in the middle of the sample from 1.7 to 3 µm, while the trend of increasing Ra with thickness is not visible. It is clear from the morphology analysis that a rugged surface with more craters was created at the edges than in the middle of the sample, while segregated lead needles were also formed at the edges of the samples.

Soil and water salinity are increasing problems worldwide, causing significantly reduced crop yields. Alfalfa (Medicago sativaL.) is often listed as salt‐sensitive, but field testing of improved cultivars is limited. Forage systems and improved high‐quality alfalfa varieties are needed to enable crop production under high salinity (HS) conditions. The objective of this study was to measure the yield and quality response of alfalfa to high saline conditions in the field and to document the relative saline tolerance of its varieties. HS irrigation water (electrical conductivity of water, or ECw8.0–11.0 dS m−1) was applied to 33 nondormant alfalfa cultivars and were compared with low salinity (LS) treatments (ECw0.5–1.2 dS m−1) over 4 years in a Mediterranean environment on a clay loam soil utilizing a split‐plot design. Crops were harvested seven to eight times per year, and the forage quality was measured on selected harvests utilizing near‐infrared spectroscopy. The average yield loss due to HS treatment was 23.9% compared with LS treatment, but yields averaged 23.4 Mg ha−1under HS over the 3 full years of production. This level of production is considered to be economically viable in this region. Differences in salinity tolerance between lines were identified in the field; individual cultivars lost 5%–35% of their LS yield when grown under HS conditions. Forage quality was significantly improved under HS versus LS conditions, but improvements were negatively correlated with biomass yield (R2> 0.81), similar to responses observed in drought‐stressed alfalfa. These yield results confirm greenhouse studies, indicating that alfalfa is highly salt tolerant once established in the field, with potential for further improvement with tolerant cultivars. Salinity tolerance should be chosen based on total biomass yield as well as on the salinity tolerance index (HS yield relative to LS yield). Agronomic practices to mitigate salinity and sodicity are critical, along with improved cultivars. Salinity tolerance index (STI) of alfalfa cultivars. Alfalfa cultivars respond differently to salinity, with some showing dramatic declines and others showing modest declines due to saline conditions. However, some cultivars with high STI, nevertheless, were low yielding, and some with a low STI performed well under high and low saline conditions.

Acquired drug resistance to anticancer targeted therapies remains an unsolved clinical problem. Although many drivers of acquired drug resistance have been identified1–4, the underlying molecular mechanisms shaping tumour evolution during treatment are incompletely understood. Genomic profiling of patient tumours has implicated apolipoprotein B messenger RNA editing catalytic polypeptide-like (APOBEC) cytidine deaminases in tumour evolution; however, their role during therapy and the development of acquired drug resistance is undefined. Here we report that lung cancer targeted therapies commonly used in the clinic can induce cytidine deaminase APOBEC3A (A3A), leading to sustained mutagenesis in drug-tolerant cancer cells persisting during therapy. Therapy-induced A3A promotes the formation of double-strand DNA breaks, increasing genomic instability in drug-tolerant persisters. Deletion of A3A reduces APOBEC mutations and structural variations in persister cells and delays the development of drug resistance. APOBEC mutational signatures are enriched in tumours from patients with lung cancer who progressed after extended responses to targeted therapies. This study shows that induction of A3A in response to targeted therapies drives evolution of drug-tolerant persister cells, suggesting that suppression of A3A expression or activity may represent a potential therapeutic strategy in the prevention or delay of acquired resistance to lung cancer targeted therapy.

This work compares eight classical H2molecular models in the gas phase taken from the existing literature. All models are based on Lennard-Jones (LJ) 12-6 terms for the van der Waals interactions and hence easier to transfer to multiphase molecular simulations than more sophisticated potentials. The H2potentials tested include one-site, two-site, three-site, and five-site models, with the sites being either the H atoms, the center-of-mass of the H2molecule, or massless sites. For the multisite models, high-frequency H–H stretching modes can lead to poor equipartition of the kinetic energy, and the timestep for molecular dynamics (MD) simulations should be reduced to maintain a stable numerical integration of the equations of motion. As such, only those models with rigid bonds are considered. In the present case, 600 MD simulations of H2gas were carried out over a large range of temperatures (−50 to +90 °C) and at densities corresponding to a pressure range of 50 to 2000 bar, which include the operating conditions of on-board storage tanks in hydrogen-fueled vehicles. Most of the models under study were found to reproduce reasonably well the experimental pVTphase diagram as well as the solubility. Discrepancies only became significant at the highest densities tested, and these could be used to rank the different models. All model diffusion coefficients were essentially indistinguishable from experimental results, and as such, kinetically dominated dynamic properties could not be used as a criterion for the choice of model. Among the eight models tested, two of them, i.e., the two-site model of Yang and Zhong and the one-site model derived from Buch performed very well over the range of conditions tested. They represent a good compromise between realism, simplicity, and computational efficiency.

This letter summarizes and proves the concept of bounded-input bounded-state (BIBS) stability for weight convergence of a broad family of in-parameter-linear nonlinear neural architectures (IPLNAs) as it generally applies to a broad family of incremental gradient learning algorithms. A practical BIBS convergence condition results from the derived proofs for every individual learning point or batches for real-time applications.

The Northern Refuge of Lake Michigan was established under the auspices of the Great Lakes Fishery Commission in 1985 as an additional step toward restoring a self‐sustaining Lake Trout Salvelinus namaycushpopulation to the lake. The overall goal of our study was to assess progress toward Lake Trout rehabilitation in the Northern Refuge through 2021. We conducted annual (1992–2021) gill‐net surveys in the fall to assess the adult population and beam trawl surveys in the spring to assess naturally reproduced age‐0 Lake Trout. Spawner abundance averaged 45 fish • 305 m of gill net−1• day−1during 1992–1999, just 4 fish • 305 m of gill net−1• day−1during 2000–2014, and then 67 fish • 305 m of gill net−1• day−1during 2018–2021. Sea Lamprey Petromyzon marinuswounding rate decreased by nearly 90% between the 2000–2014 and 2015–2021 periods. The average annual mortality rate of adult Lake Trout decreased from 43% during the 1990s and 2000s to 22% during 2015–2021. All of these population dynamics were partly driven by changes in Lake Trout stocking rates, which declined by roughly 50% during 1994–1996 but then increased roughly twofold during 2006–2010 and remained at this higher level during 2010–2018. In 2021, early signs of natural recruitment of Lake Trout became evident. Beam trawling during June 2021 yielded a wild age‐0 Lake Trout, the first ever caught since the surveys began in 1992. In addition, 15 (4% of total catch) of the Lake Trout caught in the fall 2021 gill‐net survey were unclipped (wild) fish. Estimated ages of these wild fish indicated that natural recruitment had begun sometime around 2015. With Alewife Alosa pseudoharengusabundance in Lake Michigan at record low levels, Sea Lamprey wounding rate greatly reduced, and Lake Trout spawner abundance at relatively high levels, the outlook for Lake Trout rehabilitation in the Northern Refuge holds promise. Impact statementWe documented significant progress toward the goal of establishing a self‐sustaining Lake Trout population in the Northern Refuge of Lake Michigan during 2009–2021. Accomplishing this goal is a key step in stabilizing the ecosystem, but additional effort is still needed to reach the goal. We documented significant progress toward the goal of establishing a self‐sustaining Lake Trout population in the Northern Refuge of Lake Michigan during 2009–2021. Accomplishing this goal is a key step in stabilizing the ecosystem, but additional effort is still needed to reach the goal.

ObjectivesThe comparison of treatment efficacy for cerebral cavernous malformations (CCMs) has not yet been well researched.DesignPubMed, Cochrane Library, Science Direct, ISI Web of Science, Embase and additional sources were searched to identify cohort studies about the treatment of CCMs published between 1990 and 2020. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed; the Newcastle-Ottawa Scale was used to assess the risk of bias and to evaluate limitations based on selection/outcome biases. The cumulative incidences with 95% CIs were calculated using the random effects model. The models of Poisson distribution were applied to evaluate risk factors of poorer treatment outcome by calculating rate ratios within 100 person-years with 95% CIs.ResultsA total of 100 cohorts yielding 8994 patients treated for CCMs within 41 098 person-years of follow-up were analysed. The efficacy of ensuring the prevention of haemorrhage was 97% in surgical, 86% in radiosurgical and 77% in the conservative treatment. The lowest mortality (1%) was after radiosurgery, and the highest persistent morbidity (22%) was in natural history series. Deep-seated and brainstem CCMs were associated with higher bleeding rates. Lobar localisation was a protective factor in all analyses. Patients with history of previous haemorrhage were exposed to higher risk of rebleeding. Male gender was a protective factor associated with lower risk of post-treatment haemorrhage.ConclusionsSurgical resection of CCM is effective in ensuring the prevention of haemorrhage with acceptable morbidity and mortality, but conservative and radiosurgical management is a justified treatment alternative. Brainstem and deep-seated CCMs are predominantly associated with higher haemorrhage rates.

ObjectiveTo develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis.DesignA graph neural network was developed incorporating pathologist domain knowledge to classify 6591 whole-slides images (WSIs) of endoscopic large bowel biopsies from 3291 patients (approximately 54% female, 46% male) as normal or abnormal (non-neoplastic and neoplastic) using clinically driven interpretable features. One UK National Health Service (NHS) site was used for model training and internal validation. External validation was conducted on data from two other NHS sites and one Portuguese site.ResultsModel training and internal validation were performed on 5054 WSIs of 2080 patients resulting in an area under the curve-receiver operating characteristic (AUC-ROC) of 0.98 (SD=0.004) and AUC-precision-recall (PR) of 0.98 (SD=0.003). The performance of the model, named Interpretable Gland-Graphs using a Neural Aggregator (IGUANA), was consistent in testing over 1537 WSIs of 1211 patients from three independent external datasets with mean AUC-ROC=0.97 (SD=0.007) and AUC-PR=0.97 (SD=0.005). At a high sensitivity threshold of 99%, the proposed model can reduce the number of normal slides to be reviewed by a pathologist by approximately 55%. IGUANA also provides an explainable output highlighting potential abnormalities in a WSI in the form of a heatmap as well as numerical values associating the model prediction with various histological features.ConclusionThe model achieved consistently high accuracy showing its potential in optimising increasingly scarce pathologist resources. Explainable predictions can guide pathologists in their diagnostic decision-making and help boost their confidence in the algorithm, paving the way for its future clinical adoption.

ABSTRACTCOVID-19 vaccine uptake varied across countries, in part due to vaccine hesitancy fueled by a lack of trustworthy information. To help health workers provide evidence-based answers to common questions about COVID-19 vaccines and vaccination, and thereby, assist individuals´ decisions on vaccine acceptance, COVID-19 InfoVaccines, a joint WHO-EU project, was launched in February 2021 to support COVID-19 vaccine rollout in 6 Eastern European countries. COVID-19 InfoVaccines was made available in seven languages and shared on social media networks. A total of 262,592 users accessed COVID-19 InfoVaccines.com between February 11, 2021, and January 31st, 2023. The users were most interested in: general questions; vaccine efficacy and duration of protection; vaccine safety; vaccine co-administration, and dose-interval and interchangeability; though the interest in a specific theme varied in function of the epidemiological situation. A total of 118,510 (45.1%) and 46,644 (17.7%) users scrolled up to 35% and 75% of the COVID-19 InfoVaccines webpage, respectively. The average engagement rate was 71.61%. The users accessed COVID-19 InfoVaccines from 231 countries and territories, but the majority were in Ukraine (N = 38,404; 14.6%), Spain (N = 23,327; 8.9%), and Argentina (N = 21,167; 8.1%). Older Facebook users were more interested in COVID-19 information than younger individuals (X2p-value < .0001). Two hundred twenty-eight videos were shared on YouTube. The average Click-Through-Rate on Facebook was 7.82%, and that on YouTube was 4.4%, with 60 videos having a Click-Through-Rate >5%, falling in the range of average YouTube video Click-Through-Rate (2% – 10%). As misinformation about vaccines and vaccination spreads easily and can negatively impact health-related decisions, initiatives like COVID-19 InfoVaccines are crucial to facilitate access to reliable information.

Excessive deposition of fibrillar collagen in the interstitial extracellular matrix (ECM) of human lung tissue causes fibrosis, which can ultimately lead to organ failure. Despite our understanding of the molecular mechanisms underlying the disease, no cure for pulmonary fibrosis has yet been found. We screened a drug library and found that dextromethorphan (DXM), a cough expectorant, reduced the amount of excess fibrillar collagen deposited in the ECM in cultured primary human lung fibroblasts, a bleomycin mouse model, and a cultured human precision-cut lung slice model of lung fibrosis. The reduced extracellular fibrillar collagen upon DXM treatment was due to reversible trafficking inhibition of collagen type I (COL1) in the endoplasmic reticulum (ER) in TANGO1- and HSP47-positive structures. Mass spectrometric analysis showed that DXM promoted hyperhydroxylation of proline and lysine residues on various collagens (COL1, COL3, COL4, COL5, COL7, and COL12) and latent transforming growth factor–β–binding protein (LTBP1 and LTBP2) peptides, coinciding with their secretion block. Additionally, proteome profiling of DXM-treated cells showed increased thermal stability of prolyl-hydroxylases P3H2, P3H3, P3H4, P4HA1, and P4HA2, suggesting a change in their activity. Transcriptome analysis of profibrotic stimulated primary human lung fibroblasts and human ex vivo lung slices after DXM treatment showed activation of an antifibrotic program through regulation of multiple pathways, including the MMP-ADAMTS axis, WNT signaling, and fibroblast-to-myofibroblast differentiation. Together, these data obtained from in vitro, in vivo, and ex vivo models of lung fibrogenesis show that DXM has the potential to limit fibrosis through inhibition of COL1 membrane trafficking in the ER.

The study presented focuses on material research of La Tène rivets and represents the very first study conducted into this class of archaeological finds from the Bohemian region. The rivets examined come from two significant archaeological sites situated in this geographical area—a hillfort Kolo near Týnec nad Labem and an oppidum in Stradonice. The sets of the rivets selected for the study were dated to the Late La Tène period (second–first century BC)—in the context of Western Europe, the term Celtic period can also be found. Thorough material research of the objects utilised a range of methods such as scanning electron microscopy with energy dispersive analyser, atomic absorption spectrometry, X-ray micro-tomography scanning, laser ablation-inductively coupled plasma-mass spectrometry, and Raman spectrometry. As a result, the research has identified and described three different technologies used to produce the rivets. The rivets uncovered there were mostly produced by casting from a bronze alloy or by putting wrought iron pins into the bronze melt of rivet heads. In addition, a minority of the rivets were produced using forged wrought iron with their heads plated with a very thin bronze plate. The results of the elemental analysis showed that several of the rivets and most of the rivet heads were made of bronze alloys with a tin content of 2–10 wt.%. The lead content of bronze alloy rivets from both sites varies from 0.2 to 10.1 wt.%. It can be assumed, that lead was intentionally added to the bronze melt used to produce the majority of the artefacts examined. Also, several bronze rivet heads were found to be decorated with enamel, which is a type of soda-lime-silica high lead glass coloured with crystals of Cu2O (the Colour of the enamel was predominantly red). In conclusion, two different groups of enamels were distinguished: (a) enamels with PbO up to 20% and (b) enamels with a higher content of PbO reaching up to 40%.

Fecal microbiota transplantation (FMT) is a therapeutic intervention for inflammatory diseases of the gastrointestinal tract, but its clinical mode of action and subsequent microbiome dynamics remain poorly understood. Here we analyzed metagenomes from 316 FMTs, sampled pre and post intervention, for the treatment of ten different disease indications. We quantified strain-level dynamics of 1,089 microbial species, complemented by 47,548 newly constructed metagenome-assembled genomes. Donor strain colonization and recipient strain resilience were mostly independent of clinical outcomes, but accurately predictable using LASSO-regularized regression models that accounted for host, microbiome and procedural variables. Recipient factors and donor–recipient complementarity, encompassing entire microbial communities to individual strains, were the main determinants of strain population dynamics, providing insights into the underlying processes that shape the post-FMT gut microbiome. Applying an ecology-based framework to our findings indicated parameters that may inform the development of more effective, targeted microbiome therapies in the future, and suggested how patient stratification can be used to enhance donor microbiota colonization or the displacement of recipient microbes in clinical practice.

Seroconversion after COVID-19 vaccination is impaired in kidney transplant recipients. Emerging variants of concern such as the B.1.617.2 (delta) and the B.1.1.529 (omicron) variants pose an increasing threat to these patients. In this observational cohort study, we measured anti-S1 IgG, surrogate neutralizing, and anti-receptor-binding domain antibodies three weeks after a third mRNA vaccine dose in 49 kidney transplant recipients and compared results to 25 age-matched healthy controls. In addition, vaccine-induced neutralization of SARS-CoV-2 wild-type, the B.1.617.2 (delta), and the B.1.1.529 (omicron) variants was assessed using a live-virus assay. After a third vaccine dose, anti-S1 IgG, surrogate neutralizing, and anti-receptor-binding domain antibodies were significantly lower in kidney transplant recipients compared to healthy controls. Only 29/49 (59%) sera of kidney transplant recipients contained neutralizing antibodies against the SARS-CoV-2 wild-type or the B.1.617.2 (delta) variant and neutralization titers were significantly reduced compared to healthy controls (p< 0.001). Vaccine-induced cross-neutralization of the B.1.1.529 (omicron) variants was detectable in 15/35 (43%) kidney transplant recipients with seropositivity for anti-S1 IgG, surrogate neutralizing, and/or anti-RBD antibodies. Neutralization of the B.1.1.529 (omicron) variants was significantly reduced compared to neutralization of SARS-CoV-2 wild-type or the B.1.617.2 (delta) variant for both, kidney transplant recipients and healthy controls (p< .001 for all).

Seroconversion after COVID‐19 vaccination is impaired in kidney transplant recipients. Emerging variants of concern such as the B.1.617.2 (delta) and the B.1.1.529 (omicron) variants pose an increasing threat to these patients. In this observational cohort study, we measured anti‐S1 IgG, surrogate neutralizing, and anti‐receptor‐binding domain antibodies three weeks after a third mRNA vaccine dose in 49 kidney transplant recipients and compared results to 25 age‐matched healthy controls. In addition, vaccine‐induced neutralization of SARS‐CoV‐2 wild‐type, the B.1.617.2 (delta), and the B.1.1.529 (omicron) variants was assessed using a live‐virus assay. After a third vaccine dose, anti‐S1 IgG, surrogate neutralizing, and anti‐receptor‐binding domain antibodies were significantly lower in kidney transplant recipients compared to healthy controls. Only 29/49 (59%) sera of kidney transplant recipients contained neutralizing antibodies against the SARS‐CoV‐2 wild‐type or the B.1.617.2 (delta) variant and neutralization titers were significantly reduced compared to healthy controls (p< 0.001). Vaccine‐induced cross‐neutralization of the B.1.1.529 (omicron) variants was detectable in 15/35 (43%) kidney transplant recipients with seropositivity for anti‐S1 IgG, surrogate neutralizing, and/or anti‐RBD antibodies. Neutralization of the B.1.1.529 (omicron) variants was significantly reduced compared to neutralization of SARS‐CoV‐2 wild‐type or the B.1.617.2 (delta) variant for both, kidney transplant recipients and healthy controls (p< .001 for all). A third mRNA vaccine dose increases immunogenicity in most kidney transplant recipients but, in comparison to healthy controls, kidney recipients have significantly reduced cross‐neutralizing antibody activity against the immune‐escaping B.1.1.529 (omicron) variant.

Heat resistance, heat stableness and corrosion resistance are properties that predispose nickel superalloys such as Inconel 625, Mar-M247, Nimonic C 263 and B1914 to a very wide range of applications. Due to their mechanical properties, their machinability by conventional technologies is relatively difficult, so wire electrical discharge machining (WEDM) is widely used, where only one condition is placed on the material being machined, which is at least minimal electrical conductivity. Despite the fact that the main element of which these superalloys are always composed is nickel, their machinability by WEDM is quite different. For this reason, an extensive study comparing the machinability of the four above-mentioned nickel superalloys using WEDM was performed, examining the effect of setting the machine parameters on the cutting speed as well as on the quality of the surface and subsurface layer. It was found out that the cutting speed is different for individual materials with the same set of machine parameters and so that it is possible to significantly increase the quality of the machined surface for individual materials.

Nerve injury leads to chronic pain and exaggerated sensitivity to gentle touch (allodynia) as well as a loss of sensation in the areas in which injured and non-injured nerves come together1–3. The mechanisms that disambiguate these mixed and paradoxical symptoms are unknown. Here we longitudinally and non-invasively imaged genetically labelled populations of fibres that sense noxious stimuli (nociceptors) and gentle touch (low-threshold afferents) peripherally in the skin for longer than 10 months after nerve injury, while simultaneously tracking pain-related behaviour in the same mice. Fully denervated areas of skin initially lost sensation, gradually recovered normal sensitivity and developed marked allodynia and aversion to gentle touch several months after injury. This reinnervation-induced neuropathic pain involved nociceptors that sprouted into denervated territories precisely reproducing the initial pattern of innervation, were guided by blood vessels and showed irregular terminal connectivity in the skin and lowered activation thresholds mimicking low-threshold afferents. By contrast, low-threshold afferents—which normally mediate touch sensation as well as allodynia in intact nerve territories after injury4–7—did not reinnervate, leading to an aberrant innervation of tactile end organs such as Meissner corpuscles with nociceptors alone. Genetic ablation of nociceptors fully abrogated reinnervation allodynia. Our results thus reveal the emergence of a form of chronic neuropathic pain that is driven by structural plasticity, abnormal terminal connectivity and malfunction of nociceptors during reinnervation, and provide a mechanistic framework for the paradoxical sensory manifestations that are observed clinically and can impose a heavy burden on patients.

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The National Judicial College (NJC) in Reno, Nevada is the only national college for judges in the United States. It offers courses to both new and experienced judges, teaching them how to do their job effectively. The NJC also offers specialty courses on topics such as writing opinions, understanding financial statements, and handling self-represented litigants. In addition, the NJC has outreach programs, a judicial academy for lawyers aspiring to become judges, and a civics education program for students. The college has also worked with international judicial systems and has its own sports teams. [Extracted from the article]