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Undertriaged patients have worse outcomes than appropriately triaged patients. Machine learning provides better triage prediction than conventional triage in emergency departments, but no machine learning-based undertriage prediction models have yet been developed for prehospital telephone triage. We developed and validated machine learning models for telephone triage. We conducted a retrospective cohort study with the largest after-hour house-call (AHHC) service dataset in Japan. Participants were ≥16 years and used the AHHC service between 1 November 2018 and 31 January 2021. We developed five prediction models based on support vector machine (SVM), lasso regression (LR), random forest (RF), gradient-boosted decision tree (XGB), and deep neural network (DNN). The primary outcome was undertriage, and predictors were telephone triage level and routinely available telephone-based data, including age, sex, 80 chief complaint categories and 10 comorbidities. We measured the area under the receiver operating characteristic curve (AUROC) for all the models. We identified 15,442 eligible patients (age: 38.4 ± 16.6, male: 57.2%), including 298 (1.9%; age: 58.2 ± 23.9, male: 55.0%) undertriaged patients. RF and XGB outperformed the other models, with the AUROC values (95% confidence interval; 95% CI) of the SVM, LR, RF, XGB and DNN for undertriage being 0.62 (0.55–0.69), 0.79 (0.74–0.83), 0.81 (0.76–0.86), 0.80 (0.75–0.84) and 0.77 (0.73–0.82), respectively. We found that RF and XGB outperformed other models. Our findings suggest that machine learning models can facilitate the early detection of undertriage and early intervention to yield substantially improved patient outcomes.KEY MESSAGESUndertriaged patients experience worse outcomes than appropriately triaged patients; thus, we developed machine learning models for predicting undertriage in the prehospital setting. In addition, we identified the predictors of risk factors associated with undertriage.Random forest and gradient-boosted decision tree models demonstrated better prediction performance, and the models identified the risk factors associated with undertriage.Machine learning models aid in the early detection of undertriage, leading to significantly improved patient outcomes and identifying undertriage-associated risk factors, including chief complaint categories, could help prioritize conventional telephone triage protocol revision. Undertriaged patients experience worse outcomes than appropriately triaged patients; thus, we developed machine learning models for predicting undertriage in the prehospital setting. In addition, we identified the predictors of risk factors associated with undertriage. Random forest and gradient-boosted decision tree models demonstrated better prediction performance, and the models identified the risk factors associated with undertriage. Machine learning models aid in the early detection of undertriage, leading to significantly improved patient outcomes and identifying undertriage-associated risk factors, including chief complaint categories, could help prioritize conventional telephone triage protocol revision.

Background: The coronavirus disease 2019 (COVID-19) pandemic has impacted the capacity for advance care planning between patients, families, and healthcare teams. The barriers to and facilitators of advance care planning vary with settings. This study sought to identify and review the barriers to and facilitators of advance care planning implementation for medical staff in different settings (e.g., hospitals, outpatients, care and nursing homes) during the COVID-19 pandemic. Methods: This study followed an overview of review design and was registered in the International Prospective Register of Systematic Reviews (CRD42022351362). A search of MEDLINE, CENTRAL, Web of Science, and Embase databases was performed through November 14, 2022. AMSTAR 2 was used to assess the risk of bias. Results: The final analyses included seven studies. Common barriers to advance care planning implementation included visitation restrictions, limited resources and personnel, and lack of coordination among health professionals. In care and nursing homes, the lack of palliative care physicians and the psychological burden on staff were identified as barriers. Using telemedicine for information-sharing was a common facilitator. In hospitals, facilitators were short-term training in palliative care and palliative care physicians joining the acute care team; in care homes and nursing homes, they were advance care planning education and emotional support for staff. Conclusions: Although inadequate staff education regarding advance care planning in hospitals and facilities and the lack of community-level information-sharing have long been noted, the pandemic highlighted these issues. Short-term training programs for staff and immediate information-sharing could facilitate advance care planning.

The development of an in vitro cell model that can be used to study severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research is expected. Here we conducted infection experiments in bronchial organoids (BO) and an BO-derived air-liquid interface model (BO-ALI) using 8 SARS-CoV-2 variants. The infection efficiency in BO-ALI was more than 1, 000 times higher than that in BO. Among the bronchial epithelial cells, we found that ciliated cells were infected with the virus, but basal cells were not. Ciliated cells died 7 days after the viral infection, but basal cells survived after the viral infection and differentiated into ciliated cells. Fibroblast growth factor 10 signaling was essential for this differentiation. These results indicate that BO and BO-ALI may be used not only to evaluate the cell response to SARS-CoV-2 and coronavirus disease 2019 (COVID-19) therapeutic agents, but also for airway regeneration studies., 気管支オルガノイドを用いた新型コロナウイルス研究とその創薬応用. 京都大学プレスリリース. 2022-05-30., COVID-19 Research Using Bronchial Organoids and Drug Discovery Applications. 京都大学プレスリリース. 2022-06-02.

A liver-on-a-chip (liver-chip) is a microfluidic device carrying liver cells such as human hepatocytes. It is used to reproduce a part of liver function. Many microfluidic devices are composed of polydimethylsiloxane (PDMS), which is a type of silicone elastomer. PDMS is easy to process and suitable for cell observation, but its high hydrophobicity carries the risk of drug absorption. In this study, we evaluated drug absorption to the PDMS device and investigated the drug responsiveness of human hepatocytes cultured in the PDMS device (hepatocyte-chips). First, the absorption rates of 12 compounds to the PDMS device were measured. The absorption rates of midazolam, bufuralol, cyclosporine A, and verapamil were 92.9, 71.7, 71.4, and 99.6%, respectively, but the other compounds were poorly absorbed. Importantly, the absorption rate of the compounds was correlated with their octanol/water distribution coefficient (log D) values (R2 = 0.76). Next, hepatocyte-chips were used to examine the response to drugs, which are typically used to evaluate hepatic functions. Using the hepatocyte-chips, we could confirm the responsiveness of drugs including cytochrome P450 (CYP) inducers and farnesoid X receptor (FXR) ligands. We believe that our findings will contribute to drug discovery research using PDMS-based liver-chips.

Genetic differences are a primary reason for differences in the susceptibility and severity of coronavirus disease 2019 (COVID-19). Because induced pluripotent stem (iPS) cells maintain the genetic information of the donor, they can be used to model individual differences in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionin vitro. Notably, undifferentiated human iPS cells themselves cannot be infected bySARS-CoV-2. Using adenovirus vectors, here we found that human iPS cells expressing the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) (ACE2-iPS cells) can be infected with SARS-CoV-2. In infected ACE2-iPS cells, the expression of SARS-CoV-2 nucleocapsid protein, the budding of viral particles, the production of progeny virus, double membrane spherules, and double-membrane vesicles were confirmed. We also evaluated COVID-19 therapeutic drugs in ACE2-iPS cells and confirmed the strong antiviral effects of Remdesivir, EIDD-2801, and interferon-beta. In addition, we performed SARS-CoV-2 infection experiments on ACE2-iPS/ES cells from 8 individuals. Male iPS/ES cells were more capable of producing the virus as compared with female iPS/ES cells. These findings suggest that ACE2-iPS cells can not only reproduce individual differences in SARS-CoV-2 infectionin vitro, but they are also a useful resource to clarify the causes of individual differences in COVID-19 due to genetic differences.Graphical Abstract

The purpose of this study was to evaluate the appearance of artifacts by four types of root canal filling sealers on cone-beam computed tomography (CBCT) images. Thirty standardized tooth models were given the radiopacity equivalent to human teeth, and root canal preparation was performed using WaveOne Gold. Root canal filling by a single-point method was performed using WaveOne Gold gutta-percha points and four types of root canal sealers: AH Plus (AH), CANALS (CA), BioRoot RCS (BR), and MTA Fillapex (MTA). Samples were taken by periapical radiography at 60 kV and scanned by CBCT at three tube voltages (70, 85, and 100 kV). The gray-scale values (GVs) of the periapical radiographs were measured and the aluminum equivalents were calculated. On the CBCT axial images, the artifact and dentin area GVs were measured and the rate of change in the GV (RCGV) was calculated as follows: RCGV (%) = (dentin area GV − artifact GV)/dentin area GV × 100. High-density areas with artifacts on the CBCT images were also measured. On the periapical radiographs, the aluminum equivalent was largest for AH and smallest for MTA. On the CBCT images, AH showed the largest values for both RCGV and the high-density areas, while BR and MTA showed comparable values. Correlations were found between the radiopacity on the periapical radiographs and the degree of artifacts on the CBCT images. These findings suggest that the greater the contrast in the 2D image, the higher the artifacts in the 3D image.

Background Acute mitral regurgitation could occur without common symptoms like hemodynamic instability, but with dyspnea, hemoptysis, and right‐sided infiltration on radiography. We report a case of severe alveolar hemorrhage caused by acute mitral regurgitation, which occurred in the absence of shock. Case Presentation A 40‐year‐old man presented with dyspnea with bloody phlegm and hypoxia, despite being hemodynamically stable. Chest radiography revealed right‐sided infiltration, and bronchoscopy showed fresh bloody phlegm in his tracheae. No specific findings were detected with any tests. After treatment with several medications and support with extracorporeal membrane oxygenation, his condition improved, although the etiology of the disease remained unknown. Transthoracic and transesophageal echocardiogram revealed severe mitral valve regurgitation with ruptured mitral chordae tendineae. These suggested that the sudden onset of mitral valve regurgitation had caused severe alveolar hemorrhage. Conclusion Severe alveolar hemorrhage, especially with right‐sided infiltration on chest radiography, should be considered a symptom of acute mitral regurgitation., Acute mitral regurgitation could occur without common symptoms like hemodynamic instability, but with dyspnea, hemoptysis, and right‐sided infiltration on radiography. Severe alveolar hemorrhage, especially with right‐sided infiltration on chest radiography, should be considered a symptom of acute mitral regurgitation.

Human hepatocytes are essential materials in pharmaceutical researches. Not only primary human hepatocytes (PHH) but also human iPS cell-derived hepatocyte-like cells (human iPS-HLCs) are expected to be applied as materials for pharmaceutical researches. To date, several culture media have been developed for culturing human hepatocytes. However, there have been no reports comparing these media to determine which is most suitable for culturing human hepatocytes. In this study, we compared five commercial media (Hepatocyte Culture Medium (HCM), HepatoZYME-SFM, Cellartis Power Primary HEP Medium, DMEM/F12, and William's E Medium (WEM)) to determine which is most suitable for culturing PHH and human iPS-HLCs. In hepatic differentiation of human iPS cells (day 14-25 of differentiation), albumin (ALB) and urea secretion abilities and CYP2C9, CYP2C19, and CYP3A4 activities were the highest when using HCM or WEM. During maintenance of human iPS-HLCs, ALB and urea producing abilities and CYP2C9, CYP2C19, and CYP3A4 activities were the highest when using HCM. Importantly, we found that human iPS-HLCs cultured in HCM were maintained for 3 weeks or more without impairment of their hepatic functions. These results suggest that it is necessary to select an optimal medium for hepatic differentiation and maintenance of human iPS-HLCs. In the case of PHH culture, there was little difference in hepatic functions among the five media. However, the CYP2C9, CYP2C19, and CYP3A4 activities were the highest when using HCM and WEM. In conclusion, it is important to select the optimal medium for specific application when carrying out pharmaceutical researches using human hepatocytes.

The present study aimed to investigate ecosystem dynamics in Tokyo Bay, a semi-enclosed bay surrounded by the Tokyo metropolitan area in Japan, which is one of the largest and most populous industrialized areas in the world. The bay has been subject to eutrophication since the 1960s, and excessive increase in phytoplankton biomass has led to hypoxia. Ecopath with Ecosim was used to simulate the phytoplankton dynamics, and it could closely reproduce the observed relative biomass. To evaluate the impacts of phytoplankton dynamics, hypoxia, and fishing on the dynamics, with a focus on high trophic levels (up to fish), 3 scenarios, “Yearly constant phytoplankton biomass,” “No hypoxia,” and “No fishing,” were tested. Comparisons with the “Control” scenario without any modifications suggested that (1) the dynamics was controlled by phytoplankton (bottom-up control), (2) hypoxia did not have a serious effect on the past dynamics, and (3) stopping fishing would not contribute to recover of the biomass of exploited fish. Predictions for future dynamics under the scenarios “DO deteriorated” and “DO unchanged” suggest that if DO deteriorates strongly enough to decrease the survival of most benthos, the ecosystem might undergo a non-negligible transformation through extinction or biomass decrease of some benthos.