COVID-19 vaccines reduce mortality in hospitalized patients with oxygen requirements: Differences between vaccine subtypes. A multicontinental cohort study.

The aim of this study was to analyze whether the coronavirus disease 2019 (COVID-19) vaccine reduces mortality in patients with moderate or severe COVID-19 disease requiring oxygen therapy. A retrospective cohort study, with data from 148 hospitals in both Spain (111 hospitals) and Argentina (37 hospitals), was conducted. We evaluated hospitalized patients for COVID-19 older than 18 years with oxygen requirements. Vaccine protection against death was assessed through a multivariable logistic regression and propensity score matching. We also performed a subgroup analysis according to vaccine type. The adjusted model was used to determine the population attributable risk. Between January 2020 and May 2022, we evaluated 21,479 COVID-19 hospitalized patients with oxygen requirements. Of these, 338 (1.5%) patients received a single dose of the COVID-19 vaccine and 379 (1.8%) were fully vaccinated. In vaccinated patients, mortality was 20.9% (95% confidence interval [CI]: 17.9-24), compared to 19.5% (95% CI: 19-20) in unvaccinated patients, resulting in a crude odds ratio (OR) of 1.07 (95% CI: 0.89-1.29; p = 0.41). However, after considering the multiple comorbidities in the vaccinated group, the adjusted OR was 0.73 (95% CI: 0.56-0.95; p = 0.02) with a population attributable risk reduction of 4.3% (95% CI: 1-5). The higher risk reduction for mortality was with messenger RNA (mRNA) BNT162b2 (Pfizer) (OR 0.37; 95% CI: 0.23-0.59; p < 0.01), ChAdOx1 nCoV-19 (AstraZeneca) (OR 0.42; 95% CI: 0.20-0.86; p = 0.02), and mRNA-1273 (Moderna) (OR 0.68; 95% CI: 0.41-1.12; p = 0.13), and lower with Gam-COVID-Vac (Sputnik) (OR 0.93; 95% CI: 0.6-1.45; p = 0.76). COVID-19 vaccines significantly reduce the probability of death in patients suffering from a moderate or severe disease (oxygen therapy).

Phenotype- and species-specific skin proteomic signatures for incision-induced pain in humans and mice.

BACKGROUND: Acute pain after surgery is common and often leads to chronic post-surgical pain, but neither treatment nor prevention is currently sufficient. We hypothesised that specific protein networks (protein-protein interactions) are relevant for pain after surgery in humans and mice. METHODS: Standardised surgical incisions were performed in male human volunteers and male mice. Quantitative and qualitative sensory phenotyping were combined with unbiased quantitative mass spectrometry-based proteomics and protein network theory. The primary outcomes were skin protein signature changes in humans and phenotype-specific protein-protein interaction analysis 24 h after incision. Secondary outcomes were interspecies comparison of protein regulation as well as protein-protein interactions after incision and validation of selected proteins in human skin by immunofluorescence. RESULTS: Skin biopsies in 21 human volunteers revealed 119/1569 regulated proteins 24 h after incision. Protein-protein interaction analysis delineated remarkable differences between subjects with small (low responders, n=12) and large incision-related hyperalgesic areas (high responders, n=7), a phenotype most predictive of developing chronic post-surgical pain. Whereas low responders predominantly showed an anti-inflammatory protein signature, high responders exhibited signatures associated with a distinct proteolytic environment and persistent inflammation. Compared to humans, skin biopsies in mice habored even more regulated proteins (435/1871) 24 h after incision with limited overlap between species as assessed by proteome dynamics and PPI. Immunohistochemistry confirmed the expression of high priority candidates in human skin biopsies. CONCLUSIONS: Proteome profiling of human skin after incision revealed protein-protein interactions correlated with pain and hyperalgesia, which may be of potential significance for preventing chronic post-surgical pain. Importantly, protein-protein interactions were differentially modulated in mice compared to humans opening new avenues for successful translational research.

Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.

Comprehensive, reproducible and precise analysis of large sample cohorts is one of the key objectives of quantitative proteomics. Here, we present an implementation of data-independent acquisition using its parallel acquisition nature that surpasses the limitation of serial MS2 acquisition of data-dependent acquisition on a quadrupole ultra-high field Orbitrap mass spectrometer. In deep single shot data-independent acquisition, we identified and quantified 6,383 proteins in human cell lines using 2-or-more peptides/protein and over 7100 proteins when including the 717 proteins that were identified on the basis of a single peptide sequence. 7739 proteins were identified in mouse tissues using 2-or-more peptides/protein and 8121 when including the 382 proteins that were identified based on a single peptide sequence. Missing values for proteins were within 0.3 to 2.1% and median coefficients of variation of 4.7 to 6.2% among technical triplicates. In very complex mixtures, we could quantify 10,780 proteins and 12,192 proteins when including the 1412 proteins that were identified based on a single peptide sequence. Using this optimized DIA, we investigated large-protein networks before and after the critical period for whisker experience-induced synaptic strength in the murine somatosensory cortex 1-barrel field. This work shows that parallel mass spectrometry enables proteome profiling for discovery with high coverage, reproducibility, precision and scalability.

WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics.

This article has been withdrawn by the authors. This article did not comply with the editorial guidelines of MCP. Specifically, single peptide based protein identifications of 9-19% were included in the analysis and discussed in the results and conclusions. We wish to withdraw this article and resubmit a clarified, corrected manuscript for review.

Standardized Profiling of The Membrane-Enriched Proteome of Mouse Dorsal Root Ganglia (DRG) Provides Novel Insights Into Chronic Pain.

Chronic pain is a complex disease with limited treatment options. Several profiling efforts have been employed with the aim to dissect its molecular underpinnings. However, generated results are often inconsistent and nonoverlapping, which is largely because of inherent technical constraints. Emerging data-independent acquisition (DIA)-mass spectrometry (MS) has the potential to provide unbiased, reproducible and quantitative proteome maps - a prerequisite for standardization among experiments. Here, we designed a DIA-based proteomics workflow to profile changes in the abundance of dorsal root ganglia (DRG) proteins in two mouse models of chronic pain, inflammatory and neuropathic. We generated a DRG-specific spectral library containing 3067 DRG proteins, which enables their standardized quantification by means of DIA-MS in any laboratory. Using this resource, we profiled 2526 DRG proteins in each biological replicate of both chronic pain models and respective controls with unprecedented reproducibility. We detected numerous differentially regulated proteins, the majority of which exhibited pain model-specificity. Our approach recapitulates known biology and discovers dozens of proteins that have not been characterized in the somatosensory system before. Functional validation experiments and analysis of mouse pain behaviors demonstrate that indeed meaningful protein alterations were discovered. These results illustrate how the application of DIA-MS can open new avenues to achieve the long-awaited standardization in the molecular dissection of pathologies of the somatosensory system. Therefore, our findings provide a valuable framework to qualitatively extend our understanding of chronic pain and somatosensation.

New targeted approaches for the quantification of data-independent acquisition mass spectrometry.

The use of data-independent acquisition (DIA) approaches for the reproducible and precise quantification of complex protein samples has increased in the last years. The protein information arising from DIA analysis is stored in digital protein maps (DIA maps) that can be interrogated in a targeted way by using ad hoc or publically available peptide spectral libraries generated on the same sample species as for the generation of the DIA maps. The restricted availability of certain difficult-to-obtain human tissues (i.e., brain) together with the caveats of using spectral libraries generated under variable experimental conditions limits the potential of DIA. Therefore, DIA workflows would benefit from high-quality and extended spectral libraries that could be generated without the need of using valuable samples for library production. We describe here two new targeted approaches, using either classical data-dependent acquisition repositories (not specifically built for DIA) or ad hoc mouse spectral libraries, which enable the profiling of human brain DIA data set. The comparison of our results to both the most extended publically available human spectral library and to a state-of-the-art untargeted method supports the use of these new strategies to improve future DIA profiling efforts.

Native Piezo2 Interactomics Identifies Pericentrin as a Novel Regulator of Piezo2 in Somatosensory Neurons.

The ability of somatosensory neurons to perceive mechanical stimuli relies on specialized mechanotransducing proteins and their molecular environment. Only recently has the identity of a major transducer of mechanical forces in vertebrates been revealed by the discovery of Piezo2. Further work has established its pivotal role for innocuous touch in mice. Therefore, Piezo2 offers a unique platform for the molecular investigation of somatosensory mechanosensation. We performed a mass spectrometry-based interactomics screen on native Piezo2 in somatosensory neurons of mouse dorsal root ganglia (DRG). Stringent and quantitative data analysis yielded the identity of 36 novel binding partners of Piezo2. The biological significance of this data set is reflected by functional experiments demonstrating a role for Pericentrin in modulating Piezo2 activity and membrane expression in somatosensory neurons. Collectively, our findings provide a framework for understanding Piezo2 physiology and serve as a rich resource for the molecular dissection of mouse somatosensation.

Exploring novel paths towards protein signatures of chronic pain.

Pain is a major symptom of many medical conditions and the worldwide number one reason for people to seek medical assistance. It affects the quality of life of patients and poses a heavy financial burden on society with high costs of treatment and lost productivity. Furthermore, the treatment of chronic pain presents a big challenge as pain therapeutics often lack efficacy and exhibit minimal safety profiles. The latter can be largely attributed to the fact that current therapies target molecules with key physiological functions throughout the body. In light of these difficulties, the identification of proteins specifically involved in chronic pain states is of paramount importance for designing selective interventions. Several profiling efforts have been employed with the aim to dissect the molecular underpinnings of chronic pain, both on the level of the transcriptome and proteome. However, generated results are often inconsistent and non-overlapping, which is largely due to inherent technical constraints. A potential solution may be offered by emerging strategies capable of performing standardized and reproducible proteome analysis, such as data-independent acquisition-mass spectrometry (DIA-MS). We have recently demonstrated the applicability of DIA-MS to interrogate chronic pain-related proteome alterations in mice. Based on our results, we aim to provide an overview on DIA-MS and its potential to contribute to the comprehensive characterization of molecular signatures underlying pain pathologies.

A novel mechanism for nicotinic potentiation of glutamatergic synapses.

Selective strengthening of specific glutamatergic synapses in the mammalian hippocampus is critical for encoding new memories. This is most commonly achieved by input-specific Hebbian-type plasticity involving glutamate-dependent coincident presynaptic and postsynaptic depolarization. Our results demonstrate a novel mechanism by which nicotinic signaling, independently of coincident fast glutamatergic transmission, increases synaptic strength in the hippocampus. Electrophysiological recordings from rat hippocampal neurons in culture revealed that 1-3 h of exposure to 1 µm nicotine, even with action potentials being blocked, produced increases in both the frequency and amplitude of miniature EPSCs. Possible mechanisms were analyzed both in mouse organotypic slice culture and in rat cell culture by inducing the cells to express super-ecliptic pHluorin-tagged GluA1-containing AMPA receptors, which fluoresce only on the cell surface. Pharmacological and genetic manipulation of the cells, in combination with fluorescence-recovery-after-photobleaching experiments, revealed that nicotine, acting through α7-containing nicotinic acetylcholine receptors on the postsynaptic neuron, induces the stabilization and accumulation of GluA1-containing AMPA receptors on dendritic spines. The process relies on intracellular calcium signaling, PDZ [postsynaptic density-95 (PSD-95)/Discs large (Dlg)/zona occludens-1 (ZO-1)] interactions with members of the PSD-95 family, and lateral diffusion of the GluA1 receptors on the cell surface. These findings define a new avenue by which nicotinic signaling modulates synaptic mechanisms thought to subserve learning and memory.

Annexin A2 regulates TRPA1-dependent nociception.

The transient receptor potential A1 (TRPA1) channel is essential for vertebrate pain. Even though TRPA1 activation by ligands has been studied extensively, the molecular machinery regulating TRPA1 is only poorly understood. Using an unbiased proteomics-based approach we uncovered the physical association of Annexin A2 (AnxA2) with native TRPA1 in mouse sensory neurons. AnxA2 is enriched in a subpopulation of sensory neurons and coexpressed with TRPA1. Furthermore, we observe an increase of TRPA1 membrane levels in cultured sensory neurons from AnxA2-deficient mice. This is reflected by our calcium imaging experiments revealing higher responsiveness upon TRPA1 activation in AnxA2-deficient neurons. In vivo these findings are associated with enhanced nocifensive behaviors specifically in TRPA1-dependent paradigms of acute and inflammatory pain, while heat and mechanical sensitivity as well as TRPV1-mediated pain are preserved in AnxA2-deficient mice. Our results support a model whereby AnxA2 limits the availability of TRPA1 channels to regulate nociceptive signaling in vertebrates.

Lateral mobility of presynaptic α7-containing nicotinic receptors and its relevance for glutamate release.

Surface diffusion of postsynaptic receptors shapes synaptic transmission. Presynaptic receptors also influence transmission, but the relevance of their mobility for synaptic function is unknown. Using single-particle tracking with quantum dots, we show that calcium-permeable α7-containing nicotinic acetylcholine receptors (α7-nAChRs), capable of promoting transmitter release, are mobile on presynaptic terminals but constrained in synaptic space on rat hippocampal neurons in culture. Additional immobilization of presynaptic α7-nAChRs by antibody crosslinking increases glutamate release capacity as seen in the frequency of spontaneous miniature postsynaptic currents and the size of the readily releasable pool of transmitter. Conversely, blocking glutamate release by targeting tetanus toxin to individual synapses increases α7-nAChR dwell time at presynaptic sites. The effects on release require functional α7-nAChRs and may to depend on CAST/ELKS (calpastatin/glutamine, leucine, lysine, and serine-rich protein), which an unbiased proteomic screen yielded. The results support a new homeostatic regulatory mechanism in which α7-nAChR restrain may be adjusted as needed at presynaptic sites via active zone proteins to maintain transmitter release capability.

PMCA2 via PSD-95 controls calcium signaling by α7-containing nicotinic acetylcholine receptors on aspiny interneurons.

Local control of calcium concentration within neurons is critical for signaling and regulation of synaptic communication in neural circuits. How local control can be achieved in the absence of physical compartmentalization is poorly understood. Challenging examples are provided by nicotinic acetylcholine receptors that contain α7 nicotinic receptor subunits (α7-nAChRs). These receptors are highly permeable to calcium and are concentrated on aspiny dendrites of interneurons, which lack obvious physical compartments for constraining calcium diffusion. Using functional proteomics on rat brain, we show that α7-nAChRs are associated with plasma membrane calcium-ATPase pump isoform 2 (PMCA2). Analysis of α7-nAChR function in hippocampal interneurons in culture shows that PMCA2 activity limits the duration of calcium elevations produced by the receptors. Unexpectedly, PMCA2 inhibition triggers rapid calcium-dependent loss of α7-nAChR clusters. This extreme regulatory response is mediated by CaMKII, involves proteasome activity, depends on the second intracellular loop of α7-nAChR subunits, and is specific in that it does not alter two other classes of calcium-permeable ionotropic receptors on the same neurons. A critical link is provided by the scaffold protein PSD-95 (postsynaptic density-95), which is associated with α7-nAChRs and constrains their mobility as revealed by single-particle tracking on neurons. The PSD-95 link is required for PMCA2-mediated removal of α7-nAChR clusters. This three-component combination of PMCA2, PSD-95, and α7-nAChR offers a novel mechanism for tight control of calcium dynamics in neurons.

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics.

Introduction: Metaproteomics is a rapidly advancing field that offers unique insights into the taxonomic composition and the functional activity of microbial communities, and their effects on host physiology. Classically, data-dependent acquisition (DDA) mass spectrometry (MS) has been applied for peptide identification and quantification in metaproteomics. However, DDA-MS exhibits well-known limitations in terms of depth, sensitivity, and reproducibility. Consequently, methodological improvements are required to better characterize the protein landscape of microbiomes and their interactions with the host. Methods: We present an optimized proteomic workflow that utilizes the information captured by Parallel Accumulation-Serial Fragmentation (PASEF) MS for comprehensive metaproteomic studies in complex fecal samples of mice. Results and discussion: We show that implementing PASEF using a DDA acquisition scheme (DDA-PASEF) increased peptide quantification up to 5 times and reached higher accuracy and reproducibility compared to previously published classical DDA and data-independent acquisition (DIA) methods. Furthermore, we demonstrate that the combination of DIA, PASEF, and neuronal-network-based data analysis, was superior to DDA-PASEF in all mentioned parameters. Importantly, DIA-PASEF expanded the dynamic range towards low-abundant proteins and it doubled the quantification of proteins with unknown or uncharacterized functions. Compared to previous classical DDA metaproteomic studies, DIA-PASEF resulted in the quantification of up to 4 times more taxonomic units using 16 times less injected peptides and 4 times shorter chromatography gradients. Moreover, 131 additional functional pathways distributed across more and even uniquely identified taxa were profiled as revealed by a peptide-centric taxonomic-functional analysis. We tested our workflow on a validated preclinical mouse model of neuropathic pain to assess longitudinal changes in host-gut microbiome interactions associated with pain - an unexplored topic for metaproteomics. We uncovered the significant enrichment of two bacterial classes upon pain, and, in addition, the upregulation of metabolic activities previously linked to chronic pain as well as various hitherto unknown ones. Furthermore, our data revealed pain-associated dynamics of proteome complexes implicated in the crosstalk between the host immune system and the gut microbiome. In conclusion, the DIA-PASEF metaproteomic workflow presented here provides a stepping stone towards a deeper understanding of microbial ecosystems across the breadth of biomedical and biotechnological fields.

Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study.

Background: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of hospitalizations and admission to intensive care units. There is an urgent need for easily implementable and clinically effective Early Warning Scores (EWSs) that can predict the risk of complications within the next 24-48 hr. Although EWSs have been used in the evaluation of COVID-19 patients, there are several clinical limitations to their use. Moreover, no models have been tested on geographically distinct populations or population groups with varying levels of immune protection. Methods: We developed and validated COVID-19 Early Warning Score (COEWS), an EWS that is automatically calculated solely from laboratory parameters that are widely available and affordable. We benchmarked COEWS against the widely used NEWS2. We also evaluated the predictive performance of vaccinated and unvaccinated patients. Results: The variables of the COEWS predictive model were selected based on their predictive coefficients and on the wide availability of these laboratory variables. The final model included complete blood count, blood glucose, and oxygen saturation features. To make COEWS more actionable in real clinical situations, we transformed the predictive coefficients of the COEWS model into individual scores for each selected feature. The global score serves as an easy-to-calculate measure indicating the risk of a patient developing the combined outcome of mechanical ventilation or death within the next 48 hr.The discrimination in the external validation cohort was 0.743 (95% confidence interval [CI]: 0.703-0.784) for the COEWS score performed with coefficients and 0.700 (95% CI: 0.654-0.745) for the COEWS performed with scores. The area under the receiver operating characteristic curve (AUROC) was similar in vaccinated and unvaccinated patients. Additionally, we observed that the AUROC of the NEWS2 was 0.677 (95% CI: 0.601-0.752) in vaccinated patients and 0.648 (95% CI: 0.608-0.689) in unvaccinated patients. Conclusions: The COEWS score predicts death or MV within the next 48 hr based on routine and widely available laboratory measurements. The extensive external validation, its high performance, its ease of use, and its positive benchmark in comparison with the widely used NEWS2 position COEWS as a new reference tool for assisting clinical decisions and improving patient care in the upcoming pandemic waves. Funding: University of Vienna.

Proteome and Network Analysis Provides Novel Insights Into Developing and Established Chemotherapy-Induced Peripheral Neuropathy.

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating side-effect of cancer therapies. So far, the development of CIPN cannot be prevented, neither can established CIPN be reverted, often leading to the cessation of necessary chemotherapy. Thus, there is an urgent need to explore the mechanistic basis of CIPN to facilitate its treatment. Here we used an integrated approach of quantitative proteome profiling and network analysis in a clinically relevant rat model of paclitaxel-induced peripheral neuropathy. We analysed lumbar rat DRG at two critical time points: (1) day 7, right after cessation of paclitaxel treatment, but prior to neuropathy development (pre-CIPN); (2) 4 weeks after paclitaxel initiation, when neuropathy has developed (peak-CIPN). In this way we identified a differential protein signature, which shows how changes in the proteome correlate with the development and maintenance of CIPN, respectively. Extensive biological pathway and network analysis reveals that, at pre-CIPN, regulated proteins are prominently implicated in mitochondrial (dys)function, immune signalling, neuronal damage/regeneration, and neuronal transcription. Orthogonal validation in an independent rat cohort confirmed the increase of ß-catenin (CTNNB1) at pre-CIPN. More importantly, detailed analysis of protein networks associated with ß-catenin highlights translationally relevant and potentially druggable targets. Overall, this study demonstrates the enormous value of combining animal behaviour with proteome and network analysis to provide unprecedented insights into the molecular basis of CIPN. In line with emerging approaches of network medicine our results highlight new avenues for developing improved therapeutic options aimed at preventing and treating CIPN.

Deep proteome profiling reveals signatures of age and sex differences in paw skin and sciatic nerve of naïve mice.

The age and sex of studied animals profoundly impact experimental outcomes in biomedical research. However, most preclinical studies in mice use a wide-spanning age range from 4 to 20 weeks and do not assess male and female mice in parallel. This raises concerns regarding reproducibility and neglects potentially relevant age and sex differences, which are largely unknown at the molecular level in naïve mice. Here, we employed an optimized quantitative proteomics workflow in order to deeply profile mouse paw skin and sciatic nerves (SCN) - two tissues implicated in nociception and pain as well as diseases linked to inflammation, injury, and demyelination. Remarkably, we uncovered significant differences when comparing male and female mice at adolescent (4 weeks) and adult (14 weeks) age. Our analysis deciphered protein subsets and networks that were correlated with the age and/or sex of mice. Notably, among these were proteins/biological pathways with known (patho)physiological relevance, e.g., homeostasis and epidermal signaling in skin, and, in SCN, multiple myelin proteins and regulators of neuronal development. Extensive comparisons with available databases revealed that various proteins associated with distinct skin diseases and pain exhibited significant abundance changes in dependence on age and/or sex. Taken together, our study uncovers hitherto unknown sex and age differences at the level of proteins and protein networks. Overall, we provide a unique proteome resource that facilitates mechanistic insights into somatosensory and skin biology, and integrates age and sex as biological variables - a prerequisite for successful preclinical studies in mouse disease models.

Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study.

New SARS-CoV-2 variants, breakthrough infections, waning immunity, and sub-optimal vaccination rates account for surges of hospitalizations and deaths. There is an urgent need for clinically valuable and generalizable triage tools assisting the allocation of hospital resources, particularly in resource-limited countries. We developed and validate CODOP, a machine learning-based tool for predicting the clinical outcome of hospitalized COVID-19 patients. CODOP was trained, tested and validated with six cohorts encompassing 29223 COVID-19 patients from more than 150 hospitals in Spain, the USA and Latin America during 2020-22. CODOP uses 12 clinical parameters commonly measured at hospital admission for reaching high discriminative ability up to 9 days before clinical resolution (AUROC: 0·90-0·96), it is well calibrated, and it enables an effective dynamic risk stratification during hospitalization. Furthermore, CODOP maintains its predictive ability independently of the virus variant and the vaccination status. To reckon with the fluctuating pressure levels in hospitals during the pandemic, we offer two online CODOP calculators, suited for undertriage or overtriage scenarios, validated with a cohort of patients from 42 hospitals in three Latin American countries (78-100% sensitivity and 89-97% specificity). The performance of CODOP in heterogeneous and geographically disperse patient cohorts and the easiness of use strongly suggest its clinical utility, particularly in resource-limited countries.

While COVID-19 vaccines have saved millions of lives, new variants, waxing immunity, unequal rollout and relaxation of mitigation strategies mean that the pandemic will keep on sending shockwaves across healthcare systems. In this context, it is crucial to equip clinicians with tools to triage COVID-19 patients and forecast who will experience the worst forms of the disease. Prediction models based on artificial intelligence could help in this effort, but the task is not straightforward. Indeed, the pandemic is defined by ever-changing factors which artificial intelligence needs to cope with. To be useful in the clinic, a prediction model should make accurate prediction regardless of hospital location, viral variants or vaccination and immunity statuses. It should also be able to adapt its output to the level of resources available in a hospital at any given time. Finally, these tools need to seamlessly integrate into clinical workflows to not burden clinicians. In response, Klén et al. built CODOP, a freely available prediction algorithm that calculates the death risk of patients hospitalized with COVID-19 (https://gomezvarelalab.em.mpg.de/codop/). This model was designed based on biochemical data from routine blood analyses of COVID-19 patients. Crucially, the dataset included 30,000 individuals from 150 hospitals in Spain, the United States, Honduras, Bolivia and Argentina, sampled between March 2020 and February 2022 and carrying most of the main COVID-19 variants (from the original Wuhan version to Omicron). CODOP can predict the death or survival of hospitalized patients with high accuracy up to nine days before the clinical outcome occurs. These forecasting abilities are preserved independently of vaccination status or viral variant. The next step is to tailor the model to the current pandemic situation, which features increasing numbers of infected people as well as accumulating immune protection in the overall population. Further development will refine CODOP so that the algorithm can detect who will need hospitalisation in the next 24 hours, and who will need admission in intensive care in the next two days. Equipping primary care settings and hospitals with these tools will help to restore previous standards of health care during the upcoming waves of infections, particularly in countries with limited resources.

Lateral mobility of nicotinic acetylcholine receptors on neurons is determined by receptor composition, local domain, and cell type.

The lateral mobility of surface receptors can define the signaling properties of a synapse and rapidly change synaptic function. Here we use single-particle tracking with Quantum Dots to follow nicotinic acetylcholine receptors (nAChRs) on the surface of chick ciliary ganglion neurons in culture. We find that both heteropentameric alpha3-containing receptors (alpha3*-nAChRs) and homopentameric alpha7-containing receptors (alpha7-nAChRs) access synaptic domains by lateral diffusion. They have comparable mobilities and display Brownian motion in extrasynaptic space but are constrained and move more slowly in synaptic space. The two receptor types differ in the nature of their synaptic restraints. Disruption of lipid rafts, PDZ-containing scaffolds, and actin filaments each increase the mobility of alpha7-nAChRs in synaptic space while collapse of microtubules has no effect. The opposite is seen for alpha3*-nAChRs where synaptic mobility is increased only by microtubule collapse and not the other manipulations. Other differences are found for regulation of alpha3*-nAChR and alpha7-nAChR mobilities in extrasynaptic space. Most striking are effects on the immobile populations of alpha7-nAChRs and alpha3*-nAChRs. Disruption of either lipid rafts or PDZ scaffolds renders half of the immobile alpha3*-nAChRs mobile without changing the proportion of immobile alpha7-nAChRs. Similar results were obtained with chick sympathetic ganglion neurons, though regulation of receptor mobility differed in at least one respect from that seen with ciliary ganglion neurons. Control of nAChR lateral mobility, therefore, is determined by mechanisms that are domain specific, receptor subtype dependent, and cell-type constrained. The outcome is a system that could tailor nicotinic signaling capabilities to specific needs of individual locations.

A proteome signature for acute incisional pain in dorsal root ganglia of mice.

ABSTRACT: After surgery, acute pain is still managed insufficiently and may lead to short-term and long-term complications including chronic postsurgical pain and an increased prescription of opioids. Thus, identifying new targets specifically implicated in postoperative pain is of utmost importance to develop effective and nonaddictive analgesics. Here, we used an integrated and multimethod workflow to reveal unprecedented insights into proteome dynamics in dorsal root ganglia (DRG) of mice after plantar incision (INC). Based on a detailed characterization of INC-associated pain-related behavior profiles, including a novel paradigm for nonevoked pain, we performed quantitative mass-spectrometry-based proteomics in DRG 1 day after INC. Our data revealed a hitherto unknown INC-regulated protein signature in DRG with changes in distinct proteins and cellular signaling pathways. In particular, we show the differential regulation of 44 protein candidates, many of which are annotated with pathways related to immune and inflammatory responses such as MAPK/extracellular signal-regulated kinases signaling. Subsequent orthogonal assays comprised multiplex Western blotting, bioinformatic protein network analysis, and immunolabeling in independent mouse cohorts to validate (1) the INC-induced regulation of immune/inflammatory pathways and (2) the high priority candidate Annexin A1. Taken together, our results propose novel potential targets in the context of incision and, therefore, represent a highly valuable resource for further mechanistic and translational studies of postoperative pain.

Participation of HERG channel cytoplasmic structures on regulation by the G protein-coupled TRH receptor.

Human ether-a-go-go-related gene (HERG) channels heterologously expressed in Xenopus oocytes are regulated by the activation of G protein-coupled hormone receptors that, like the thyrotropin-releasing hormone (TRH) receptor, activate phospholipase C. Previous work with serially deleted HERG mutants suggested that residues 326-345 located in the proximal domain of the channels amino terminus might be required for the hormonal modulation of HERG activation. Generation of new channel mutants deleted in this region further point to the amino acid sequence between residues 326 and 332 as a possible determinant of the TRH effects, but individual or combined single-point mutations in this sequence demonstrate that maintenance of its consensus sites for phosphorylation and/or interaction with regulatory components is not important for the modulatory response(s). The TRH-induced effects also remained unaltered when a basic amino acid cluster located between residues 362 and 366 is eliminated. Additionally, no effect of TRH was observed in channels carrying single-point mutations at the beginning of the intracellular loop linking transmembrane domains S4 and S5. Our results indicate that a correct structural arrangement of the amino terminal domains is essential for the hormone-induced modifications of HERG activation. They also suggest that the hormonal regulatory action is transmitted to the transmembrane channel core through interactions between the cytoplasmic domains and the initial portion of the S4-S5 linker.