Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells.

Metal halide perovskites of the general formula ABX3-where A is a monovalent cation such as caesium, methylammonium or formamidinium; B is divalent lead, tin or germanium; and X is a halide anion-have shown great potential as light harvesters for thin-film photovoltaics1-5. Among a large number of compositions investigated, the cubic α-phase of formamidinium lead triiodide (FAPbI3) has emerged as the most promising semiconductor for highly efficient and stable perovskite solar cells6-9, and maximizing the performance of this material in such devices is of vital importance for the perovskite research community. Here we introduce an anion engineering concept that uses the pseudo-halide anion formate (HCOO-) to suppress anion-vacancy defects that are present at grain boundaries and at the surface of the perovskite films and to augment the crystallinity of the films. The resulting solar cell devices attain a power conversion efficiency of 25.6 per cent (certified 25.2 per cent), have long-term operational stability (450 hours) and show intense electroluminescence with external quantum efficiencies of more than 10 per cent. Our findings provide a direct route to eliminate the most abundant and deleterious lattice defects present in metal halide perovskites, providing a facile access to solution-processable films with improved optoelectronic performance.

Neurodevelopmental disorder-associated CYFIP2 regulates membraneless organelles and eIF2α phosphorylation via protein interactors and actin cytoskeleton.

De novo variants in the Cytoplasmic FMR1-interacting protein 2 (CYFIP2) have been repeatedly associated with neurodevelopmental disorders and epilepsy, underscoring its critical role in brain development and function. While CYFIP2's role in regulating actin polymerization as part of the WAVE regulatory complex (WRC) is well-established, its additional molecular functions remain relatively unexplored. In this study, we performed unbiased quantitative proteomic analysis, revealing 278 differentially expressed proteins (DEPs) in the forebrain of Cyfip2 knock-out embryonic mice compared to wild-type mice. Unexpectedly, these DEPs, in conjunction with previously identified CYFIP2 brain interactors, included not only other WRC components but also numerous proteins associated with membraneless organelles (MLOs) involved in mRNA processing and translation within cells, including the nucleolus, stress granules, and processing bodies. Additionally, single-cell transcriptomic analysis of the Cyfip2 knock-out forebrain revealed gene expression changes linked to cellular stress responses and MLOs. We also observed morphological changes in MLOs in Cyfip2 knock-out brains and CYFIP2 knock-down cells under basal and stress conditions. Lastly, we demonstrated that CYFIP2 knock-down in cells, potentially through WRC-dependent actin regulation, suppressed the phosphorylation levels of the alpha subunit of eukaryotic translation initiation factor 2 (eIF2α), thereby enhancing protein synthesis. These results suggest a physical and functional connection between CYFIP2 and various MLO proteins and also extend CYFIP2's role within the WRC from actin regulation to influencing eIF2α phosphorylation and protein synthesis. With these dual functions, CYFIP2 may fine-tune the balance between MLO formation/dynamics and protein synthesis, a crucial aspect of proper mRNA processing and translation.

A single-component, light-assisted uncaging switch for endoproteolytic release.

Proteases function as pivotal molecular switches, initiating numerous biological events. Notably, potyviral protease, derived from plant viruses, has emerged as a trusted proteolytic switch in synthetic biological circuits. To harness their capabilities, we have developed a single-component photocleavable switch, termed LAUNCHER (Light-Assisted UNcaging switCH for Endoproteolytic Release), by employing a circularly permutated tobacco etch virus protease and a blue-light-gated substrate, which are connected by fine-tuned intermodular linkers. As a single-component system, LAUNCHER exhibits a superior signal-to-noise ratio compared with multi-component systems, enabling precise and user-controllable release of payloads. This characteristic renders LAUNCHER highly suitable for diverse cellular applications, including transgene expression, tailored subcellular translocation and optochemogenetics. Additionally, the plug-and-play integration of LAUNCHER into existing synthetic circuits facilitates the enhancement of circuit performance. The demonstrated efficacy of LAUNCHER in improving existing circuitry underscores its significant potential for expanding its utilization in various applications.

Proteomic Heterogeneity of the Extracellular Matrix Identifies Histologic Subtype-Specific Fibroblast in Gastric Cancer.

Gastric cancer (GC) is a highly heterogeneous disease regarding histologic features, genotypes, and molecular phenotypes. Here, we investigate extracellular matrix (ECM)-centric analysis, examining its association with histologic subtypes and patient prognosis in human GC. We performed quantitative proteomic analysis of decellularized GC tissues that characterizes tumorous ECM, highlighting proteomic heterogeneity in ECM components. We identified 20 tumor-enriched proteins including four glycoproteins, serpin family H member 1 (SERPINH1), annexin family (ANXA3/4/5/13), S100A family (S100A6/8/9), MMP14, and other matrisome-associated proteins. In addition, histopathological characteristics of GC reveals differential expression in ECM composition, with the poorly cohesive carcinoma-not otherwise specified (PCC-NOS) subtype being distinctly demarcated from other histologic subtypes. Integrating ECM proteomics with single-cell RNA sequencing, we identified crucial molecular markers in the PCC-NOS-specific stroma. PCC-NOS-enriched matrisome proteins and gene expression signatures of adipogenic cancer-associated fibroblasts (CAFadi) are closely linked, both associated with adverse outcomes in GC. Using tumor microarray analysis, we confirmed the CAFadi surface marker, ATP binding cassette subfamily A member 8 (ABCA8), predominantly present in PCC-NOS tumors. Our ECM-focused analysis paves the way for studies to determine their utility as biomarkers for patient stratification, offering valuable insights for linking molecular and histologic features in GC.

Resistive Gas Sensors Based on 2D TMDs and MXenes.

ConspectusGas sensors are used in various applications to sense toxic gases, mainly for enhanced safety. Resistive sensors are particularly popular owing to their ability to detect trace amounts of gases, high stability, fast response times, and affordability. Semiconducting metal oxides are commonly employed in the fabrication of resistive gas sensors. However, these sensors often require high working temperatures, bringing about increased energy consumption and reduced selectivity. Furthermore, they do not have enough flexibility, and their performance is significantly decreased under bending, stretching, or twisting. To address these challenges, alternative materials capable of operating at lower temperatures with high flexibility are needed. Two-dimensional (2D) materials such as MXenes and transition-metal dichalcogenides (TMDs) offer high surface area and conductivity owing to their unique 2D structure, making them promising candidates for realization of resistive gas sensors. Nevertheless, their sensing performance in pristine form is typically weak and unacceptable, particularly in terms of response, selectivity, and recovery time (trec). To overcome these drawbacks, several strategies can be employed to enhance their sensing properties. Noble-metal decoration such as (Au, Pt, Pd, Rh, Ag) is a highly promising method, in which the catalytic effects of noble metals as well as formation of potential barriers with MXenes or TMDs eventually contribute to boosted response. Additionally, bimetallic noble metals such as Pt-Pd and Au/Pd with their synergistic properties can further improve sensor performance. Ion implantation is another feasible approach, involving doping of sensing materials with the desired concentration of dopants through control over the energy and dosage of the irradiation ions as well as creation of structural defects such as oxygen vacancies through high-energy ion-beam irradiation, contributing to enhanced sensing capabilities. The formation of core-shell structures is also effective, creating numerous interfaces between core and shell materials that optimize the sensing characteristics. However, the shell thickness needs to be carefully optimized to achieve the best sensing output. To reduce energy consumption, sensors can operate in a self-heating condition where an external voltage is applied to the electrodes, significantly lowering the power requirements. This enables sensors to function in energy-constrained environments, such as remote or low-energy areas. An important advantage of 2D MXenes and TMDs is their high mechanical flexibility. Unlike semiconducting metal oxides that lack mechanical flexibility, MXenes and TMDs can maintain their sensing performance even when integrated onto flexible substrates and subjected to bending, tilting, or stretching. This flexibility makes them ideal for fabricating flexible and portable gas sensors that rigid sensors cannot achieve.

MDGA1 negatively regulates amyloid precursor protein-mediated synapse inhibition in the hippocampus.

Balanced synaptic inhibition, controlled by multiple synaptic adhesion proteins, is critical for proper brain function. MDGA1 (meprin, A-5 protein, and receptor protein-tyrosine phosphatase mu [MAM] domain-containing glycosylphosphatidylinositol anchor protein 1) suppresses synaptic inhibition in mammalian neurons, yet the molecular mechanisms underlying MDGA1-mediated negative regulation of GABAergic synapses remain unresolved. Here, we show that the MDGA1 MAM domain directly interacts with the extension domain of amyloid precursor protein (APP). Strikingly, MDGA1-mediated synaptic disinhibition requires the MDGA1 MAM domain and is prominent at distal dendrites of hippocampal CA1 pyramidal neurons. Down-regulation of APP in presynaptic GABAergic interneurons specifically suppressed GABAergic, but not glutamatergic, synaptic transmission strength and inputs onto both the somatic and dendritic compartments of hippocampal CA1 pyramidal neurons. Moreover, APP deletion manifested differential effects in somatostatin- and parvalbumin-positive interneurons in the hippocampal CA1, resulting in distinct alterations in inhibitory synapse numbers, transmission, and excitability. The infusion of MDGA1 MAM protein mimicked postsynaptic MDGA1 gain-of-function phenotypes that involve the presence of presynaptic APP. The overexpression of MDGA1 wild type or MAM, but not MAM-deleted MDGA1, in the hippocampal CA1 impaired novel object-recognition memory in mice. Thus, our results establish unique roles of APP-MDGA1 complexes in hippocampal neural circuits, providing unprecedented insight into trans-synaptic mechanisms underlying differential tuning of neuronal compartment-specific synaptic inhibition.

Antibody-mediated blockade for galectin-3 binding protein in tumor secretome abrogates PDAC metastasis.

The major challenges in pancreatic ductal adenocarcinoma (PDAC) management are local or distant metastasis and limited targeted therapeutics to prevent it. To identify a druggable target in tumor secretome and to explore its therapeutic intervention, we performed a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analysis of tumors obtained from a patient-derived xenograft model of PDAC. Galectin-3 binding protein (Gal-3BP) is identified as a highly secreted protein, and its overexpression is further validated in multiple PDAC tumors and primary cells. Knockdown and exogenous treatment of Gal-3BP showed that it is required for PDAC cell proliferation, migration, and invasion. Mechanistically, we revealed that Gal-3BP enhances galectin-3-mediated epidermal growth factor receptor signaling, leading to increased cMyc and epithelial-mesenchymal transition. To explore the clinical impact of these findings, two antibody clones were developed, and they profoundly abrogated the metastasis of PDAC cells in vivo. Altogether, our data demonstrate that Gal-3BP is an important therapeutic target in PDAC, and we propose its blockade by antibody as a therapeutic option for suppressing PDAC metastasis.

NDUFA12 as a Functional Target of the Anticancer Compound Ertredin in Human Hepatoma Cells As Revealed by Label-Free Chemical Proteomics.

Many attempts have been made to develop new agents that target EGFR mutants or regulate downstream factors in various cancers. Cell-based screening showed that a natural small molecule, Ertredin, inhibited the growth of EGFRvIII mutant cancer cells. Previous studies have shown that Ertredin effectively inhibits anchorage-independent 3D growth of sphere-forming cells transfected with EGFRvIII mutant cDNA. However, the underlying mechanism remains unclear. In this study, we investigated the target protein of Ertredin by combining drug affinity-responsive target stability (DARTS) assays with liquid chromatography-mass spectrometry using label-free Ertredin as a bait and HepG2 cell lysates as a proteome pool. NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 12 (NDUFA12) was identified as an Ertredin-binding protein that was responsible for its biological activity. The interaction between NDUFA12 and Ertredin was validated by DARTS and cellular thermal shift assays. In addition, the genetic knockdown of the identified target, NDUFA12, was shown to suppress cell proliferation. NDUFA12 was identified as a biologically relevant target protein of Ertredin that is responsible for its antitumor activity, and these results provide insights into the role of NDUFA12 as a downstream factor in EGFRvIII mutants.

New Function Annotation of PROSER2 in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to the absence of diagnostic markers and molecular targets. Here, we took an unconventional approach to identify new molecular targets for pancreatic cancer. We chose uncharacterized protein evidence level 1 without function annotation from extensive proteomic research on pancreatic cancer and focused on proline and serine-rich 2 (PROSER2), which ranked high in the cell membrane and cytoplasm. In our study using cell lines and patient-derived orthotopic xenograft cells, PROSER2 exhibited a higher expression in cells derived from primary tumors than in those from metastatic tissues. PROSER2 was localized in the cell membrane and cytosol by immunocytochemistry. PROSER2 overexpression significantly reduced the metastatic ability of cancer cells, whereas its suppression had the opposite effect. Proteomic analysis revealed that PROSER2 interacts with STK25 and PDCD10, and their binding was confirmed by immunoprecipitation and immunocytochemistry. STK25 knockdown enhanced metastasis by decreasing p-AMPK levels, whereas PROSER2-overexpressing cells increased the level of p-AMPK, indicating that PROSER2 suppresses invasion via the AMPK pathway by interacting with STK25. This is the first demonstration of the novel role of PROSER2 in antagonizing tumor progression via the STK25-AMPK pathway in PDAC. LC-MS/MS data are available at MassIVE (MSV000092953) and ProteomeXchange (PXD045646).

Refining Classification of Cholangiocarcinoma Subtypes via Proteogenomic Integration Reveals New Therapeutic Prospects.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficult diagnosis, and overall poor prognosis. The iCC molecular classification for developing precision medicine strategies was investigated. METHODS: Comprehensive genomic, transcriptomic, proteomic, and phosphoproteomic analyses were performed on treatment-naïve tumor samples from 102 patients with iCC who underwent surgical resection with curative intent. An organoid model was constructed for testing therapeutic potential. RESULTS: Three clinically supported subtypes (stem-like, poorly immunogenic, and metabolism) were identified. NCT-501 (aldehyde dehydrogenase 1 family member A1 [ALDH1A1] inhibitor) exhibited synergism with nanoparticle albumin-bound-paclitaxel in the organoid model for the stem-like subtype. The oncometabolite dysregulations were associated with different clinical outcomes in the stem-like and metabolism subtypes. The poorly immunogenic subtype harbors the non-T-cell tumor infiltration. Integrated multiomics analysis not only reproduced the 3 subtypes but also showed heterogeneity in iCC. CONCLUSIONS: This large-scale proteogenomic analysis provides information beyond that obtained with genomic analysis, allowing the functional impact of genomic alterations to be discerned. These findings may assist in the stratification of patients with iCC and in developing rational therapeutic strategies.

Origin of Enhanced Photoelectrochemical Activity of the n-CdS/p-type Semiconductor Interface: Homojunction or Heterojunction?

Surface engineering of photoelectrodes is considered critical for achieving efficient photoelectrochemical (PEC) cells, and various p-type materials have been investigated for use as photoelectrodes. Among these, the p-type semiconductor/n-type CdS heterojunction is the most successful photocathode structure because of its enhanced onset potential and photocurrent. However, it is determined that the main contributor to the enhanced activity is the Cd-doped layer and not the CdS layer. In this study, a Cd-doped n+p-buried homojunction of a CuInS2 photocathode is first demonstrated without a CdS layer. The homojunction exhibited a more active and stable PEC performance than the CdS/CuInS2 heterojunction. Moreover, it is confirmed that Cd doping is effective for other p-type materials. These results strongly suggest that the effects of Cd doping on photocathodes should be carefully investigated when designing CdS/p-semiconductor heterojunction photoelectrodes. They also indicate that the Cd-doped layer has great potential to replace the CdS layer in future photoelectrode designs.

Shortwave Infrared Imaging of a Quantum Dot-Based Magnetic Guidewire Toward Non-Fluoroscopic Peripheral Vascular Interventions.

Peripheral vascular interventions (PVIs) offer several benefits to patients with lower extremity arterial diseases, including reduced pain, simpler anesthesia, and shorter recovery time, compared to open surgery. However, to monitor the endovascular tools inside the body, PVIs are conducted under X-ray fluoroscopy, which poses serious long-term health risks to physicians and patients. Shortwave infrared (SWIR) imaging of quantum dots (QDs) has shown great potential in bioimaging due to the non-ionizing penetration of SWIR light through tissues. In this paper, a QD-based magnetic guidewire and its system is introduced that allows X-ray-free detection under SWIR imaging and precise steering via magnetic manipulation. The QD magnetic guidewire contains a flexible silicone tube encapsulating a QD polydimethylsiloxane (PDMS) composite, where HgCdSe/HgS/CdS/CdZnS/ZnS/SiO2 core/multi-shell QDs are dispersed in the PDMS matrix for SWIR imaging upon near-infrared excitation, as well as a permanent magnet for magnetic steering. The SWIR penetration of the QD magnetic guidewire is investigated within an artificial tissue model (1% Intralipid) and explore the potential for non-fluoroscopic PVIs within a vascular phantom model. The QD magnetic guidewire is biocompatible in its entirety, with excellent resistance to photobleaching and chemical alteration, which is a promising sign for its future clinical implementation.

Cs-treatments in Kesterite Thin-Film Solar Cells for Efficient Perovskite Tandems.

Cu2ZnSn(S,Se)4 (CZTSSe) thin film solar cells are an attractive choice for a bottom cell of the low-cost and environmental tandem solar cells with perovskite. However, the progress in developing efficient perovskite/CZTSSe tandem solar cells has been hindered by the lack of high performance of the CZTSSe bottom cell. Here, an efficient CZTSSe bottom cell is demonstrated by adopting a facile and effective CsF treatment process. It is found that the CsF treatment not only facilitates grain growth and improves phase homogeneity by suppressing the detrimental deep-level defects and secondary phases, but also induces larger band bending and stronger drift force at the P-N junction. As a result, the carrier extraction/transport can be effectively accelerated, while reducing the interfacial recombination. These combined effects eventually result in a significant performance enhancement from 8.38% to 10.20%. The CsF-treated CZTSSe solar cell is finally applied to the mechanically-stacked perovskite/CZTSSe 4-terminal tandem cell by coupling a semi-transparent perovskite top cell, which exhibits the highest reported tandem efficiency of 23.01%.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Adnp-mutant mice with cognitive inflexibility, CaMKIIα hyperactivity, and synaptic plasticity deficits.

ADNP syndrome, involving the ADNP transcription factor of the SWI/SNF chromatin-remodeling complex, is characterized by developmental delay, intellectual disability, and autism spectrum disorders (ASD). Although Adnp-haploinsufficient (Adnp-HT) mice display various phenotypic deficits, whether these mice display abnormal synaptic functions remain poorly understood. Here, we report synaptic plasticity deficits associated with cognitive inflexibility and CaMKIIα hyperactivity in Adnp-HT mice. These mice show impaired and inflexible contextual learning and memory, additional to social deficits, long after the juvenile-stage decrease of ADNP protein levels to ~10% of the newborn level. The adult Adnp-HT hippocampus shows hyperphosphorylated CaMKIIα and its substrates, including SynGAP1, and excessive long-term potentiation that is normalized by CaMKIIα inhibition. Therefore, Adnp haploinsufficiency in mice leads to cognitive inflexibility involving CaMKIIα hyperphosphorylation and excessive LTP in adults long after its marked expressional decrease in juveniles.

Cntnap2-dependent molecular networks in autism spectrum disorder revealed through an integrative multi-omics analysis.

Autism spectrum disorder (ASD) is a major neurodevelopmental disorder in which patients present with core symptoms of social communication impairment, restricted interest, and repetitive behaviors. Although various studies have been performed to identify ASD-related mechanisms, ASD pathology is still poorly understood. CNTNAP2 genetic variants have been found that represent ASD genetic risk factors, and disruption of Cntnap2 expression has been associated with ASD phenotypes in mice. In this study, we performed an integrative multi-omics analysis by combining quantitative proteometabolomic data obtained with Cntnap2 knockout (KO) mice with multi-omics data obtained from ASD patients and forebrain organoids to elucidate Cntnap2-dependent molecular networks in ASD. To this end, a mass spectrometry-based proteometabolomic analysis of the medial prefrontal cortex in Cntnap2 KO mice led to the identification of Cntnap2-associated molecular features, and these features were assessed in combination with multi-omics data obtained on the prefrontal cortex in ASD patients to identify bona fide ASD cellular processes. Furthermore, a reanalysis of single-cell RNA sequencing data obtained from forebrain organoids derived from patients with CNTNAP2-associated ASD revealed that the aforementioned identified ASD processes were mainly linked to excitatory neurons. On the basis of these data, we constructed Cntnap2-associated ASD network models showing mitochondrial dysfunction, axonal impairment, and synaptic activity. Our results may shed light on the Cntnap2-dependent molecular networks in ASD.

Resistive gas sensors for the detection of NH3gas based on 2D WS2, WSe2, MoS2, and MoSe2: a review.

Transition metal dichalcogenides (TMDs) with a two-dimensional (2D) structure and semiconducting features are highly favorable for the production of NH3gas sensors. Among the TMD family, WS2, WSe2, MoS2, and MoSe2exhibit high conductivity and a high surface area, along with high availability, reasons for which they are favored in gas-sensing studies. In this review, we have discussed the structure, synthesis, and NH3sensing characteristics of pristine, decorated, doped, and composite-based WS2, WSe2, MoS2, and MoSe2gas sensors. Both experimental and theoretical studies are considered. Furthermore, both room temperature and higher temperature gas sensors are discussed. We also emphasized the gas-sensing mechanism. Thus, this review provides a reference for researchers working in the field of 2D TMD gas sensors.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.

BACKGROUND: Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability. OBJECTIVE: The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers. METHODS: We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods. RESULTS: Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910). CONCLUSIONS: RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Impact of Preanesthetic Blood Pressure Deviations on 30-Day Postoperative Mortality in Non-Cardiac Surgery Patients.

BACKGROUND: Blood pressure readings taken before anesthesia often influence the decision to delay or cancel elective surgeries. However, the implications of these specific blood pressure values, especially how they compare to baseline, on postoperative in-hospital 30-day mortality remain underexplored. This research aimed to examine the effect of discrepancies between the baseline blood pressure evaluated in the ward a day before surgery, and the blood pressure observed just before the administration of anesthesia, on the postoperative mortality risks. METHODS: The study encompassed 60,534 adults scheduled for non-cardiac surgeries at a tertiary care center in Seoul, Korea. Baseline blood pressure was calculated as the mean of the blood pressure readings taken within 24 hours prior to surgery. The preanesthetic blood pressure was the blood pressure measured right before the administration of anesthesia. We focused on in-hospital 30-day mortality as the primary outcome. RESULTS: Our research revealed that a lower preanesthetic systolic or mean blood pressure that deviates by 20 mmHg or more from baseline significantly increased the risk of 30-day mortality. This association was particularly pronounced in individuals with a history of hypertension and those aged 65 and above. Higher preanesthetic blood pressure was not significantly associated with an increased risk of 30-day mortality. CONCLUSION: We found that a lower preanesthetic blood pressure compared to baseline significantly increased the 30-day postoperative mortality risk, whereas a higher preanesthetic blood pressure did not. Our study emphasizes the critical importance of accounting for variations in both baseline and preanesthetic blood pressure when assessing surgical risks and outcomes.

Pneumonia Prevalence Upon Chest Radiography According to Vaccination Status Among Patients Under 50 Years of Age With Coronavirus Disease 2019.

BACKGROUND: Coronavirus disease 2019 (COVID-19) vaccination is effective in preventing the disease transmission and progression. However, the relatively mild disease course of the omicron variant and the decrease in antibodies over time after vaccination raise questions about the effectiveness of vaccination, especially in young people. We compared the prevalence of pneumonia and chest X-ray severity score according to vaccination status among patients < 50 years old with COVID-19. METHODS: From January 17 to March 17, 2022, 579 patients with COVID-19, who were < 50 years old and had a known vaccination history in our institution, were all included in this study. All patients underwent initial chest radiography, and follow-up chest radiographs were obtained every two days until discharge. Pneumonia was scored from the radiographs using the Brixia scoring system. The scores of the six lung zones were added for a total score ranging from 0 to 18. Patients were divided into four groups according to 10-year age intervals. Differences between groups were analyzed using the χ² or Fisher's exact tests for categorical variables and the Kruskal-Wallis test or analysis of variance for continuous variables. RESULTS: Among patients aged 12-19 years, the prevalence of pneumonia did not differ depending on vaccination status (non-vaccinated vs. vaccinated, 1/47 [2.1%] vs. 1/18 [5.6%]; P = 0.577). Among patients in their 20s, the prevalence of pneumonia was significantly higher among non-vaccinated patients than among vaccinated patients (8/28, 28.6% vs. 7/138, 5.1%, P < 0.001), similar to patients in their 40s (32/52 [61.5%] vs. 18/138 [13.0%]; P < 0.001). The chest X-ray severity score was also significantly higher in non-vaccinated patients than that in vaccinated patients in their 20s to their 40s (P < 0.001), but not among patients aged 12-19 years (P = 0.678). CONCLUSION: In patients aged 20-49 years, vaccinated patients had a significantly lower prevalence of pneumonia and chest X-ray severity score than non-vaccinated patients.