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The interaction of H, H2, and MgH2 with graphene is investigated using the density functional theory to explore the possibility of exploiting graphene or functionalized graphene as a hydrogen storage medium. The H atom is positioned at various distances from the graphene surface and the energetics are computed in detail. The extent of interaction of the s electron of H with graphene's pz electrons is well brought out. Similar investigations are carried out for H2, MgH2. In the case of H atom, a HC covalent bond is formed. This process turns out to be a prerequisite for proton transfer through graphene. Interactions of H2 and MgH2 with graphene are different from that of H. It leads to the conclusion that functionalized graphene will better substrate/candidate for applications like hydrogen storage. [ABSTRACT FROM AUTHOR]

Real-world data (RWD) in the medical field, such as electronic health records (EHRs) and medication orders, are receiving increasing attention from researchers and practitioners. While structured data have played a vital role thus far, unstructured data represented by text (e.g., discharge summaries) are not effectively utilized because of the difficulty in extracting medical information. We evaluated the information gained by supplementing structured data with clinical concepts extracted from unstructured text by leveraging natural language processing techniques. Using a machine learning-based pretrained named entity recognition tool, we extracted disease and medication names from real discharge summaries in a Japanese hospital and linked them to medical concepts using medical term dictionaries. By comparing the diseases and medications mentioned in the text with medical codes in tabular diagnosis records, we found that: (1) the text data contained richer information on patient symptoms than tabular diagnosis records, whereas the medication-order table stored more injection data than text. In addition, (2) extractable information regarding specific diseases showed surprisingly small intersections among text, diagnosis records, and medication orders. Text data can thus be a useful supplement for RWD mining, which is further demonstrated by (3) our practical application system for drug safety evaluation, which exhaustively visualizes suspicious adverse drug effects caused by the simultaneous use of anticancer drug pairs. We conclude that proper use of textual information extraction can lead to better outcomes in medical RWD mining., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Antiaromatic porphyrinoids have attracted significant attention owing to their unique electronic properties and potential applications. However, synthesis of antiaromatic contracted porphyrinoids is challenging owing to the inherent instability associated with smaller ring sizes. In this study, we report the synthesis and characterization of the first stable trioxa[16]triphyrin(2.1.1), a novel 16π antiaromatic contracted porphyrinoid. We utilized a core modification approach to stabilize the [16]triphyrin(2.1.1). X-ray crystallographic analysis revealed a nearly planar structure. Electrochemical studies demonstrated reversible oxidation behavior and a small HOMO-LUMO gap, which was consistent with its antiaromatic nature. Chemical oxidation yielded an aromatic [14]triphyrin(2.1.1) dication, highlighting the antiaromaticity-aromaticity switching capability of this system. This synthesis involved the discovery of a key intermediate, dihydrotrioxatriphyrin(2.1.1), which underwent oxidative dehydrogenation to yield the target compound. Theoretical calculations suggested that dihydrotrioxatriphyrin(2.1.1) formed via a rare 16π electrocyclic reaction. The successful synthesis and characterization of this stable trioxa[16]triphyrin(2.1.1) underscores the potential of the core modification strategies for the rational design of novel antiaromatic systems with tunable properties. Moreover, the discovery of the rare 16π electrocyclic reaction advances the understanding of high-order pericyclic processes and may inspire new synthetic strategies for complex macrocyclic compounds., (© 2024 Wiley‐VCH GmbH.)

Toxic metals present in drinking water pose a serious threat to the environment and human beings when present in abundance. In this work, we investigated the sensing ability of quantum dots (pristine CQDs, boron/nitrogen/sulphur (B/N/S)-doped CQDs, and BNQDs) of various sizes and morphologies (rectangular, circular, and triangular) towards toxic metals such as arsenic (As), cobalt (Co), nickel (Ni), copper (Cu), and lead (Pb) using quantum chemical density functional theory calculations in both gas and water phases. We probed the structural, electronic, and optical properties of the QDs. All the modelled QDs are energetically stable. Frontier molecular orbital analysis predicted that BNQDs are more chemically stable than all other CQDs. UV-vis absorption and Raman spectra analyses helped to understand the optical properties of all the QDs. Further, adsorption studies revealed that triangular pristine CQDs and sulphur-doped CQDs show higher adsorption affinity towards the toxic metals. The magnitude of adsorption energies follows the trend Ni > Pb > As > Cu > Co in most of the QDs. Several pristine and doped CQDs exhibited chemisorption towards the toxic metals, and hence, they can be used as adsorbents. However, a majority of BNQDs showed physisorption towards the metals, and therefore, they can be used as efficient optical sensors compared to CQDs. Further, the sensing ability of the QDs was explored through optical phenomena such as changes in UV-vis absorption spectra and fluorescence after metal adsorption. When compared to pristine CQDs and B/N/S-doped CQDs, metal complexation caused significant changes in the UV-vis absorbance peak intensities in BNQDs along with peak shifts. Moreover, metal interaction with the QDs increased their fluorescence lifetime with the highest values observed in Co-adsorbed triangular H 18 C 46 (152.30 ns), Pb-adsorbed rectangular H 15 C 30 S (21.29 ns), and As-adsorbed circular B 27 N 27 H 18 (2.99 μs) among pristine CQDs, B/N/S-doped CQDs, and BNQDs, respectively. Overall, we believe that our first-of-its-kind computational prediction of the optical sensing ability of tailor-made zero-dimensional systems such as QDs will be a great aid for experimentalists in designing novel and rapid optical probes to detect toxic metals in drinking water., Competing Interests: The authors declare no competing financial interest., (This journal is © The Royal Society of Chemistry.)

It has been a long-standing challenge to develop high-performance solid-state hydrogen storage materials operated under near-ambient conditions. In this work, we propose a new strategy of using noble gases for space holding to design porous titanium carbides with abundant open metal sites for hydrogen storage. By using machine learning and graph theory-assisted universal structure searching methods, we obtain 28 porous titanium carbides from three precursors (TiC dimer, C atom, and Kr atom) under 30 GPa of pressure. The stability and hydrogen storage performance of the resulting structures are further assessed and validated through density function theory and grand canonical Monte Carlo simulations with a DFT-fitted force field. Finally, p -TiC 2 is identified as a promising quasi-molecular hydrogen storage material with capacity of 4.0 wt % and 106.0 g/L at 230 K and 16 bar.

Purpose: We evaluated the electromyography (EMG)-based neuromuscular monitoring detectability of our novel stimulating electrode attachment method compared to the original Nihon-Kohden (Tokyo, Japan) attachment method., Methods: This single-center randomized, double-blind, controlled pilot study enrolled 32 patients aged ≥ 18 years, undergoing scheduled laparoscopic surgery. The EMG electrode NM-345Y™ was attached to one forearm using the Nihon-Kohden method (Pattern N-K) and the other forearm using our novel method (Pattern Cross). The allocation to each attachment method was determined post-randomization. In Pattern Cross, the NM-345Y™ was attached such that the line connecting the anode and cathode crosses the ulnar nerve. Patients received 0.9 mg/kg rocuronium after calibration with the forearm in 90-degree supination. Following tracheal intubation, the forearm was positioned in 0-degree pronation. Intraoperatively, 0.2 mg/kg rocuronium was administered if the train-of-four (TOF) count one persisted for 1 min on either side. Post-surgery, the forearm position was returned to 90-degree supination, and rocuronium was antagonized with sugammadex. TOF and post-tetanic count (PTC) were simultaneously measured bilaterally every 15 s and 5 min, respectively, from post-calibration to tracheal extubation., Results: The time to first PTC appearance was significantly shorter by 33 min in the Pattern Cross group than in the Pattern N-K group (95% Confidence interval: 1-66, p = 0.043). Following sugammadex administration, TOF ratios ≥ 0.9 were achieved in 72% of patients in the Pattern N-K group and 97% of those in the Pattern Cross group (p = 0.025)., Conclusions: Crossing the line connecting the anode and cathode with the ulnar nerve stabilizes EMG-based neuromuscular monitoring detectability., (© 2024. The Author(s) under exclusive licence to Japanese Society of Anesthesiologists.)

We investigate hydrogen sorption on open copper sites in various ligand coordinations of metal-organic frameworks (MOFs), including the triangular T(CuL 3 ) in MFU-4l, the linear L(CuL 2 ) in NU2100, and the paddlewheel P(CuL 4 ) 2 in HKUST-1 from an electronic structure perspective using DFT calculations. The ligand-field-induced splitting of d states and spd hybridizations in copper are thoroughly examined. The hybridization between Cu s, p, and d orbitals occurs in various forms to optimize the Coulomb repulsion of different ligand fields. Despite the Cu + oxidation state, which is typically conducive to strong Kubas interactions with hydrogen molecules, the vacant spd z 2 hybrid orbitals of the open copper site in the L(CuL 2 ) coordination are unsuitable for facilitating electron forward donation, thereby preventing effective hydrogen adsorption. In contrast, the vacant spd z 2 hybrid orbitals in the T(CuL 3 ) and P(CuL 4 ) 2 coordinations can engage in electron forward donations, forming bonding states between the Cu spd z 2 and H 2 σ bonding orbitals. The forward donation in the T(CuL 3 ) configuration is significantly stronger than in the P(CuL 4 ) 2 configuration due to both the lower energy of the vacant orbitals and the larger contributions of p and d z 2 characters to the hybrid orbital. Additionally, the occupied Cu pd xz / yz and pd x 2 - y 2 hybrid orbitals in the T(CuL 3 ) configuration promote electron back donation to the H 2 σ* antibonding orbital, leading to the formation of π bonding states. In the P(CuL 4 ) 2 coordination, the repulsion from the electron density distributed over the surrounding ligands prevents the H 2 molecule from approaching the copper center closely enough for the back donation to occur. The complete Kubas interaction, involving both forward and back electron donations, results in a large dihydrogen-copper binding energy of 37.6 kJ mol -1 in the T(CuL 3 ) coordination. In contrast, the binding energy of 10.6 kJ mol -1 in the P(CuL 4 ) 2 coordination is primarily driven by electrostatic interactions with a minor contribution of the Kubas-like forward donation interaction. This analysis highlights the pivotal role of coordination environments in determining the hydrogen sorption properties of MOFs., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The browsing history of a medical institution's website can potentially reveal or identify information about the health condition of the website visitor through browser cookies and fingerprints. In Japan, although the Personal Information Protection Law was revised in April 2022, the use of access analysis services to collect browsing history on medical institution websites has not been investigated. Therefore, this study investigates the actual usage of access analysis services on Japanese medical institution websites and compares it with the current situation in France, which follows the General Data Protection Regulation. The results revealed that the larger the size of the hospital, the higher the percentage of adoption of access analytics services in Japan. However, the implementation of a system for obtaining consent for the use of access analysis in Japan was found to be poor compared to that of French medical institutions. While access analysis tools are used in the websites of several medical institutions in Japan, the implementation of the process of obtaining consent to acquire browsing history is poor.

The rapid increase in data storage worldwide demands a substantial amount of energy consumption annually. Studies looking at low power consumption accompanied by high-performance memory are essential for next-generation memory. Here, Graphdiyne oxide (GDYO), characterized by facile resistive switching behavior, is systematically reported toward a low switching voltage memristor. The intrinsic large, homogeneous pore-size structure in GDYO facilitates ion diffusion processes, effectively suppressing the operating voltage. The theoretical approach highlights the remarkably low diffusion energy of the Ag ion (0.11 eV) and oxygen functional group (0.6 eV) within three layers of GDYO. The Ag/GDYO/Au memristor exhibits an ultralow operating voltage of 0.25 V with a GDYO thickness of 5 nm; meanwhile, the thicker GDYO of 29 nm presents multilevel memory with an ON/OFF ratio of up to 10 4 . The findings shed light on memory resistive switching behavior, facilitating future improvements in GDYO-based devices toward opto-memristors, artificial synapses, and neuromorphic applications.

Different from conventional 2D sliding ferroelectrics with polarization switchable in the out-of-plane via interlayer sliding, we show the existence of in-plane sliding ferroelectricity in a bilayer of a pentagon-based van der Waals heterostructure formed by vertically stacking an experimentally synthesized penta-PdSe 2 sheet and a crystal lattice well-matched penta-PtSe 2 sheet. From the 128 sliding patterns, four stable configurations are found that exhibit in-plane sliding ferroelectricity with an ultralow polarization switching barrier of 1.91 meV/atom and a high ferroelectric polarization of ±17.11 × 10 -10 C m -1 . Following the ferroelectric transition among the stable sliding configurations, significant changes in carrier mobility, electrical conductivity, and second harmonic generation are identified. In particular, the ferroelectric stacking configurations are found to possess a negative Poisson's ratio, facilitating the experimental characterization of the sliding ferroelectric effect. This study demonstrates that pentagonal sheets can be used to realize 2D in-plane sliding ferroelectrics going beyond the existing ones.

Background: We evaluated the effectiveness of the BNT162b2 vaccine against infection, symptomatic infection, and hospitalization in older people during the Delta-predominant period (July 1 to September 30, 2021)., Methods: We performed a population-based cohort study in an older adult population aged ≥65 years using data from the Vaccine Effectiveness, Networking, and Universal Safety Study conducted from January 1, 2019, to September 30, 2021, in Japan. We matched BNT162b2-vaccinated and -unvaccinated individuals in a 1:1 ratio on the date of vaccination of the vaccinated individual. We evaluated the effectiveness of the vaccine against infection, symptomatic infection, and coronavirus disease (COVID-19)-related hospitalization by comparing the vaccinated and unvaccinated groups. We estimated the risk ratio and risk difference using the Kaplan-Meier method with inverse probability weighting. The vaccine effectiveness was calculated as (1 - risk ratio) × 100%., Results: The study included 203,574 matched pairs aged ≥65 years. At 7 days after the second dose, the vaccine effectiveness of BNT162b2 against infection, symptomatic infection, and hospitalization was 78.1% (95% confidence interval [CI], 65.2-87.8%), 79.1% (95% CI, 64.6-88.9%), and 93.5% (95% CI, 83.7-100%), respectively., Conclusion: BNT162b2 was highly effective against infection, symptomatic infection, and hospitalization in Japan's older adult population aged ≥65 years during the Delta-predominant period.

There is a longstanding difficulty that time-dependent density functional theory relying on adiabatic local density approximation is not applicable to the electron dynamics, for example, for an initially excited state, such as in photochemical reactions. To overcome this, we develop non-adiabatic excited-state time-dependent GW molecular dynamics (TDGW) on the basis of the extended quasiparticle theory. Replacing Kohn-Sham orbitals/energies with correlated, interacting quasiparticle orbitals/energies allows the full correspondence to the excited-state surfaces and corresponding total energies, with satisfying extended Koopmans' theorem. We demonstrate the power of TDGW using methane photolysis, CH4→CH3•+H, an important initiation reaction for combustion/pyrolysis and hydrogen production of methane. We successfully explore several possible pathways and show how this reaction dynamics is captured accurately through simultaneously time-tracing all quasiparticle levels. TDGW scales as O(NB3-4), where NB is the number of basis functions, which is distinctly advantageous to performing dynamics using configuration interaction and coupled cluster methods., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Introduction: Bronchopulmonary dysplasia (BPD) poses a substantial global health burden. Individualized treatment strategies based on early prediction of the development of BPD can mitigate preterm birth complications; however, previously suggested predictive models lack early postnatal applicability. We aimed to develop predictive models for BPD and mortality based on immediate postnatal clinical data., Methods: Clinical information on very preterm and very low birth weight infants born between 2008 and 2018 was extracted from a nationwide Japanese database. The gradient boosting decision trees (GBDT) algorithm was adopted to predict BPD and mortality, using predictors within the first 6 h postpartum. We assessed the temporal validity and evaluated model adequacy using Shapley additive explanations (SHAP) values., Results: We developed three predictive models using data from 39,488, 39,096, and 40,291 infants to predict "death or BPD," "death or severe BPD," and "death before discharge," respectively. These well-calibrated models achieved areas under the receiver operating characteristic curve of 0.828 (95% CI: 0.828-0.828), 0.873 (0.873-0.873), and 0.887 (0.887-0.888), respectively, outperforming the multivariable logistic regression models. SHAP value analysis identified predictors of BPD, including gestational age, size at birth, male sex, and persistent pulmonary hypertension. In SHAP value-based case clustering, the "death or BPD" prediction model stratified infants by gestational age and persistent pulmonary hypertension, whereas the other models for "death or severe BPD" and "death before discharge" commonly formed clusters of low mortality, extreme prematurity, low Apgar scores, and persistent pulmonary hypertension of the newborn., Conclusions: GBDT models for predicting BPD and mortality, designed for use within 6 h postpartum, demonstrated superior prognostic performance. SHAP value-based clustering, a data-driven approach, formed clusters of clinical relevance. These findings suggest the efficacy of a GBDT algorithm for the early postnatal prediction of BPD., Competing Interests: Yoshimasa Kawazoe belongs to the “Artificial Intelligence and Digital Twin Development in Healthcare, Graduate School of Medicine, The University of Tokyo” which is an endowment department. However, the sponsors had no influence over the interpretation, writing, or publication of this work. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Yoneda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Neural differentiation is triggered by the activation of multiple signaling pathways initiated by various neurotrophic factors. An elucidation of these mechanisms is anticipated to facilitate the prevention of diseases and the development of novel therapeutic approaches. Alternative small-molecule inducers for neuroscience studies are required instead of protein-based reagents for more efficient and convenient experiments. We demonstrated that small molecules of thieno[2,3-b]pyridine derivatives that induce neural differentiation, compounds 3a and 9a in particular, exhibited significant neuritogenic activity in rat pheochromocytoma (PC12) cells. Moreover, 3a displayed pronounced fluorescence and a discernible Stokes shift. Furthermore, the outcome of the experiment conducted on the NGF-insensitive clones of rat PC12 cells, and the results of the intercellular uptake analyses suggested that the 3a-mediated activation of neural differentiation occurred independently of the TrkA receptor. Therefore, 3a portrays potential applicability both as a small molecule reagent to replace novel neurotrophic factors and as a potent fluorescent reagent for various techniques, including bioimaging., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective . For response-adapted adaptive radiotherapy (R-ART), promising biomarkers are needed to predict post-radiotherapy (post-RT) responses using routine clinical information obtained during RT. In this study, a patient-specific biomechanical model (BM) of the head and neck squamous cell carcinoma (HNSCC) was proposed using the pre-RT maximum standardized uptake value (SUV max ) of 18 F-fluorodeoxyglucose (FDG) and tumor structural changes during RT as evaluated using computed tomography (CT). In addition, we evaluated the predictive performance of BM-driven imaging biomarkers for the treatment response of patients with HNSCC who underwent concurrent chemoradiotherapy (CCRT). Approach . Patients with histologically confirmed HNSCC treated with definitive CCRT were enrolled in this study. All patients underwent CT two times as follows: before the start of RT (pre-RT) and 3 weeks after the start of RT (mid-RT). Among these patients, 67 patients who underwent positron emission tomography/CT during the pre-RT period were included in the final analysis. The locoregional control (LC), progression-free survival (PFS), and overall survival (OS) prediction performances of whole tumor stress change (TS) between pre- and mid-RT computed using BM were assessed using univariate, multivariate, and Kaplan-Meier survival curve analyses, respectively. Furthermore, performance was compared with the pre and post-RT SUV max , tumor volume reduction rate (TVRR) during RT, and other clinical prognostic factors. Main results . For both univariate, multivariate, and survival curve analyses, the significant prognostic factors were as follows ( p < 0.05): TS and TVRR for LC; TS and pre-RT FDG-SUV max for PFS; and TS only for OS. In addition, for 2 year LC, PFS, and OS prediction, TS showed a comparable predictive performance to post-RT FDG-SUV max . Significance . BM-driven TS is an effective prognostic factor for tumor treatment response after CCRT. The proposed method can be a feasible functional imaging biomarker that can be acquired during RT using only routine clinical data and may provide useful information for decision-making during R-ART., (© 2024 Institute of Physics and Engineering in Medicine.)

Important pieces of information related to patient symptoms and diagnosis are often written in free-text form in clinical texts. To utilize these texts, information extraction using natural language processing is required. This study evaluated the performance of named entity recognition (NER) and relation extraction (RE) using machine-learning methods. The Japanese case report corpus was used for this study, which had 113 types of entities and 36 types of relations that were manually annotated. There were 183 cases comprising 2,194 sentences after preprocessing. In addition, a machine learning model based on bidirectional encoder representations from transformers was used. The results revealed that the maximum micro-averaged F1 scores of NER and RE were 0.912 and 0.759, respectively. The results of this study are comparable to those of previous studies. Hence, these results could be of substantial baseline accuracy.

Transformation of patient data extracted from a database into fixed-length numerical vectors requires expertise in topical medical knowledge as well as data manipulation-thus, manual feature design is labor-intensive. In this study, we propose a machine learning-based method to for this purpose applicable to electronic medical data recorded during hospitalization, which utilizes unsupervised feature extraction based on graph embedding. Unsupervised learning is performed on a heterogeneous graph using Graph2Vec, and the inclusion of clinically useful data in the obtained embedding representation is evaluated by predicting readmission within 30 days of discharge based on it. The embedded representations are observed to improve predictive performance significantly as the information contained in the graph increases, indicating the suitability of the proposed method for feature design corresponding to clinical information.

Background: Post-authorization safety studies (PASSs) of vaccines are important. PASSs enable the evaluation of association between vaccination and adverse events following immunization through common study designs. Clinical trials during vaccine development typically include a few thousand to 10,000 participants while a PASS might aim to detect a few adverse events per 100,000 vaccine recipients. While all available data may be utilized, prior consideration of power analyses are nonetheless crucial for interpretation in cases where statistically significant differences are not found., Methods: This research primarily examined cohort study design and self-controlled case series (SCCS) design, estimating the power of a PASS under plausible conditions., Results: Both the cohort study and SCCS designs necessitated large sample sizes or high event counts to guarantee adequate power. The SCCS design is particularly suited to evaluating rare adverse events. However, extremely rare events may not yield sufficient occurrences, thereby resulting in low power. Although the SCCS design can more efficiently control for time-invariant confounding in principle, it solely estimates relative measures. A cohort study design might be preferred if confounding can be adequately managed as it also estimates absolute measures. It may be an easy decision to use all the data at hand for either design. We found it necessary to estimate the sample size and number of events to be used in the study based on a priori information and anticipated results., Competing Interests: Shuntaro Sato reports personal fees from Nippon Boehringer Ingelheim Co., Ltd, outside the submitted work; Tomohiro Katsuta received payment for lectures from Merck Sharp & Dohme Corp. The other authers declare that they have no competing interests., (©2024 Sato et al.)

Dopant-induced electron redistribution on transition metal-based materials has long been considered an emerging new electrocatalyst that is expected to replace noble-metal-based electrocatalysts in natural seawater electrolysis; however, their practical applications remain extremely daunting due to their sluggish kinetics in natural seawater. In this work, we developed a facile strategy to synthesize the 3D sponge-like hierarchical structure of Ru-doped NiCoFeP nanosheet arrays derived from metal-organic frameworks with remarkable hydrogen evolution reaction (HER) performance in natural seawater. Based on experimental results and density functional theory calculations, Ru-doping-induced charge redistribution on the surface of metal active sites has been found, which can significantly enhance the HER activity. As a result, the 3D sponge-like hierarchical structure of Ru-NiCoFeP nanosheet arrays achieves low overpotentials of 52, 149, and 216 mV at 10, 100, and 500 mA cm -2 in freshwater alkaline, respectively. Notably, the electrocatalytic activity of the Ru-NiCoFeP electrocatalyst in simulated alkaline seawater and natural alkaline seawater is nearly the same as that in freshwater alkaline. This electrocatalyst exhibits superior catalytic properties with outstanding stability under a high current density of 85 mA cm -2 for more than 100 h in natural seawater, which outperforms state-of-the-art 20% Pt/C at high current density. Our work provides valuable guidelines for developing a low-cost and high-efficiency electrocatalyst for natural seawater splitting.

The diversity of patient information recorded on electronic medical records generally, presents a challenge for converting it into fixed-length vectors that align with clinical characteristics. To address this issue, this study aimed to utilize an unsupervised graph representation learning method to transform the unstructured inpatient information from electronic medical records into a fixed-length vector. Infograph, one of the unsupervised graph representation learning algorithms was applied to the graphed inpatient information, resulting in embedded vectors of fixed length. The embedded vectors were then evaluated for whether the clinical information was preserved in it. The results indicated that the embedded representation contained information that could predict readmission within 30 days, demonstrating the feasibility of using unsupervised graph representation learning to transform patient information into fixed-length vectors that retain clinical characteristics., (©2023 AMIA - All rights reserved.)

A woman in her 70s was hospitalized and was diagnosed with liver abscess and managed with antibiotics in a previous hospital. However, she experienced altered consciousness and neck stiffness during treatment. She was then referred to our hospital. On investigation, we found that she had meningitis and right endophthalmitis concurrent with a liver abscess. Klebsiella pneumoniae was detected from both cultures of the liver abscess and effusion from the cornea. A string test showed a positive result. Therefore, she was diagnosed with invasive liver abscess syndrome. Although she recovered from the liver abscess and meningitis through empiric antibiotic treatment, her right eye required ophthalmectomy. In cases where a liver abscess presents with extrahepatic complications, such as meningitis and endophthalmitis, the possibility of invasive liver abscess syndrome should be considered, which is caused by a hypervirulent K. pneumoniae.

Background: To address the lack of an active vaccine safety surveillance system in Japan, the Vaccine Effectiveness, Networking, and Universal Safety (VENUS) study was initiated in 2021 as a pilot system using existing health insurance claims data and vaccination records., Methods: This study evaluated the value of the VENUS study by assessing the incidence of immune thrombocytopenic purpura (ITP) and Guillain-Barré syndrome (GBS) following vaccination with the 23-valent pneumococcal polysaccharide vaccine (PPSV23) using a self-controlled case series (SCCS) design., Results: Incidence rate ratios for ITP during 28-day and 42-day risk periods were 0.89 (95% confidence interval [CI], 0.12-6.4), and 0.58 (95% CI, 0.081-4.2), respectively. Neither was statistically significant. Incidence rate ratios could not be estimated for GBS due to the limited sample size., Conclusion: The VENUS study can provide valuable insights to facilitate the establishment of an advanced vaccine monitoring system in Japan., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)