Machine Perfusion or Straight to Transplant? Predictive Value of Flavin Mononucleotide Levels in Flush Solution of Human Liver Allograft.

OBJECTIVE: This study examined the predictive value of Flavin Mononucleotide (FMN) levels in the flush solution used during cold storage of donor livers on outcomes post-transplantation. BACKGROUND: Static cold storage for liver grafts induces hypoxia with subsequent impaired mitochondrial function and Flavin Mononucleotide (FMN) release upon reperfusion. METHODS: This study enrolled 62 recipients who received whole liver grafts from donation after brain death (n=50) and circulatory death donors (n=12) between June 2022 and July 2023. FMN concentrations were measured in flush solutions on the back-table. ROC-curve analysis identified an FMN level cut-off for graft survival. Post-transplant outcomes were examined according to FMN levels. RESULTS: FMN level was significantly associated with graft survival, with an area-under-the-curve (AUC) of 0.858 (95%CI: 0.754-0.963, P<0.001), outperforming the donor risk index (AUC 0.571, 95%CI: 0.227-0.915, P=0.686). The study cohort was divided into low-FMN (<37.5 ng/mL, n=40) and high-FMN groups (≥37.5 ng/mL, n=22). The low-FMN group had superior one-year graft survival compared with the high-FMN group (100% vs. 77%, P=0.003). Levels of transaminases within 7 days post-transplant were significantly higher in the high-FMN group (P=0.003). The high-FMN group developed acute rejections (41% vs. 15%, P=0.023) and early allograft dysfunction (50% vs. 20%, P=0.014) more frequently. Median comprehensive complication index in the high-FMN group was significantly higher (54 [interquartile range, 40-78] vs. 42 [interquartile range, 28-52], P=0.017). CONCLUSION: The FMN level measured in donor livers' cold storage flush solution is a valid biomarker to predict post-transplant outcomes. Liver grafts with high FMN levels may benefit from machine perfusion to improve outcomes.

Impact of Back-to-Base Normothermic Machine Perfusion on Complications and Costs: A Multicenter, Real-World Risk-Matched Analysis.

OBJECTIVE: Assess cost and complication outcomes after liver transplantation (LT) using normothermic machine perfusion (NMP). BACKGROUND: End-ischemic NMP is often used to aid logistics, yet its impact on outcomes after LT remains unclear, as does its true impact on costs associated with transplantation. METHODS: Deceased donor liver recipients at 2 centers (January 1, 2019, to June 30, 2023) were included. Retransplants, splits, and combined grafts were excluded. End-ischemic NMP (OrganOx-Metra) was implemented in October 2022 for extended-criteria donation after brain death (DBDs), all donations after circulatory deaths (DCDs), and logistics. NMP cases were matched 1:2 with static cold storage controls (SCS) using the Balance-of-Risk [donation after brain death (DBD)-grafts] and UK-DCD Score (DCD-grafts). RESULTS: Overall, 803 transplantations were included, 174 (21.7%) receiving NMP. Matching was achieved between 118 NMP-DBDs with 236 SCS; and 37 NMP-DCD with 74 corresponding SCS. For both graft types, median inpatient comprehensive complications index values were comparable between groups. DCD-NMP grafts experienced reduced cumulative 90-day comprehensive complications index (27.6 vs 41.9, P =0.028). NMP also reduced the need for early relaparotomy and renal replacement therapy, with subsequently less frequent major complications (Clavien-Dindo ≥IVa). This effect was more pronounced in DCD transplants. NMP had no protective effect on early biliary complications. Organ acquisition/preservation costs were higher with NMP, yet NMP-treated grafts had lower 90-day pretransplant costs in the context of shorter waiting list times. Overall costs were comparable for both cohorts. CONCLUSIONS: This is the first risk-adjusted outcome and cost analysis comparing NMP and SCS. In addition to logistical benefits, NMP was associated with a reduction in relaparotomy and bleeding in DBD grafts, and overall complications and post-LT renal replacement for DCDs. While organ acquisition/preservation was more costly with NMP, overall 90-day health care costs-per-transplantation were comparable.

The impact of normothermic machine perfusion and acuity circles on waitlist time, mortality, and cost in liver transplantation: A multicenter experience.

Ex situ normothermic machine perfusion (NMP) helps increase the use of extended criteria donor livers. However, the impact of an NMP program on waitlist times and mortality has not been evaluated. Adult patients listed for liver transplant (LT) at 2 academic centers from January 1, 2015, to September 1, 2023, were included (n=2773) to allow all patients ≥6 months follow-up from listing. Routine NMP was implemented on October 14, 2022. Waitlist outcomes were compared from pre-NMP pre-acuity circles (n=1460), pre-NMP with acuity circles (n=842), and with NMP (n=381). Median waitlist time was 79 days (IQR: 20-232 d) at baseline, 49 days (7-182) with acuity circles, and 14 days (5-56) with NMP ( p <0.001). The rate of transplant-per-100-person-years improved from 61-per-100-person-years to 99-per-100-person-years with acuity circles and 194-per-100-person-years with NMP ( p <0.001). Crude mortality without transplant decreased from 18.3% (n=268/1460) to 13.3% (n=112/843), to 6.3% (n=24/381) ( p <0.001) with NMP. The incidence of mortality without LT was 15-per-100-person-years before acuity circles, 19-per-100 with acuity circles, and 9-per-100-person-years after NMP ( p <0.001). Median Model for End-Stage Liver Disease at LT was lowest with NMP, but Model for End-Stage Liver Disease at listing was highest in this era ( p <0.0001). The median donor risk index of transplanted livers at baseline was 1.54 (1.27-1.82), 1.66 (1.42-2.16) with acuity circles, and 2.06 (1.63-2.46) with NMP ( p <0.001). Six-month post-LT survival was not different between eras ( p =0.322). The total cost of health care while waitlisted was lowest in the NMP era ($53,683 vs. $32,687 vs. $23,688, p <0.001); cost-per-day did not differ between eras ( p =0.152). The implementation of a routine NMP program was associated with reduced waitlist time and mortality without compromising short-term survival after liver transplant despite increased use of riskier grafts. Routine NMP use enables better waitlist management with reduced health care costs.

Precise Discrimination for Multiple Etiologies of Dementia Cases Based on Deep Learning with Electroencephalography.

INTRODUCTION: It is critical to develop accurate and universally available biomarkers for dementia diseases to appropriately deal with the dementia problems under world-wide rapid increasing of patients with dementia. In this sense, electroencephalography (EEG) has been utilized as a promising examination to screen and assist in diagnosing dementia, with advantages of sensitiveness to neural functions, inexpensiveness, and high availability. Moreover, the algorithm-based deep learning can expand EEG applicability, yielding accurate and automatic classification easily applied even in general hospitals without any research specialist. METHODS: We utilized a novel deep neural network, with which high accuracy of discrimination was archived in neurological disorders in the previous study. Based on this network, we analyzed EEG data of healthy volunteers (HVs, N = 55), patients with Alzheimer's disease (AD, N = 101), dementia with Lewy bodies (DLB, N = 75), and idiopathic normal pressure hydrocephalus (iNPH, N = 60) to evaluate the discriminative accuracy of these diseases. RESULTS: High discriminative accuracies were archived between HV and patients with dementia, yielding 81.7% (vs. AD), 93.9% (vs. DLB), 93.1% (vs. iNPH), and 87.7% (vs. AD, DLB, and iNPH). CONCLUSION: This study revealed that the EEG data of patients with dementia were successfully discriminated from HVs based on a novel deep learning algorithm, which could be useful for automatic screening and assisting diagnosis of dementia diseases.

Effects of wearing an opaque or transparent face mask on the perception of facial expressions: A comparative study between Japanese school-aged children and adults.

The negative side effects of mask-wearing on reading facial emotional cues have been investigated in several studies with adults post-2020. However, little is known about children. This study aimed to determine the negative influence of mask-wearing on reading emotions of adult faces by Japanese school-aged children, compared to Japanese adults. We also examined whether this negative influence could be alleviated by using a transparent face mask instead of an opaque one (surgical mask). The performance on reading emotions was measured using emotion categorization and emotion intensity rating tasks for adult faces. As per the findings, the accuracy of emotion recognition in children was impaired for various facial expressions (disgust, fear, happy, neutral, sad, and surprise faces), except for angry faces. Conversely, in adults, it was impaired for a few facial expressions. The perceived intensity for happy faces with a surgical mask was weaker in both children and adults than in those without the mask. A negative influence of wearing surgical masks was generally not observed for faces wearing a transparent mask in both children and adults. Thus, negative side effects of mask-wearing on reading emotions are observed for more facial expressions in children than in adults; transparent masks can help remedy these.

Coherent angular signal amplification using an optical cavity.

Precision angular sensing is an essential technology in physical experiments. Unlike length sensing with a laser beam, it has been thought that sensitivity to the angular motion cannot be enhanced with the help of an optical cavity. A method of angular signal amplification using an optical cavity, called the cavity-amplified angular sensor (CAAS), is proposed. By adjusting or compensating for the Gouy phase of the cavity, the electric field of the laser generated in proportion to the target rotation is coherently stacked in the proposed method. The advantage of this method over other angular sensors is its high sensitivity with the small sensing spot size. Three possible optical configurations are considered, of which two experimentally available ones are investigated. The angular signal amplification is demonstrated for both of them. Based on the theoretical calculation for a realistic model, the fundamental angular sensing noise level is expected to be as low as 10-15rad/Hz1/2, with a 1 mm laser beam size and 10 mW laser power.

Silver(I)-Ion-Mediated Cytosine-Containing Base Pairs: Metal Ion Specificity for Duplex Stabilization and Susceptibility toward DNA Polymerases.

Spectroscopic characterization of AgI -ion-mediated C-AgI -A and C-AgI -T base pairs found in primer extension reactions catalyzed by DNA polymerases was conducted. UV melting experiments revealed that C-A and C-T mismatched base pairs in oligodeoxynucleotide duplexes are specifically stabilized by AgI ions in 1:1 stoichiometry in the same manner as a C-C mismatched base pair. Although the stability of the mismatched base pairs in the absence of AgI ions is in the order C-A≈C-T>C-C, the stabilizing effect of AgI ions follows the order C-C>C-A≈C-T. However, the comparative susceptibility of dNTPs to AgI -mediated enzymatic incorporation into the site opposite templating C is dATP>dTTP≫dCTP, as reported. The net charge, as well as the size and/or shape complementarity of the metal-mediated base pairs, or the stabilities of mismatched base pairs in the absence of metal ions, would be more important than the stability of the metallo-base pairs in the replicating reaction catalyzed by DNA polymerases.

Monitoring of human herpesviruses-6 and -7 DNA in saliva samples during the acute and convalescent phases of exanthem subitum.

The amounts of the DNAs of human herpesviruses-6 (HHV-6) and -7 (HHV-7) in saliva samples were monitored during the acute and convalescent phases of exanthem subitum (ES) to elucidate the kinetics of virus shedding after ES. A total of 247 saliva samples were collected from 17 children (5 males and 12 females: 8-31 months old at onset). The monitoring period ranged from 152 to 721 days after onset, and in 15 children it was longer than 1 year. Among the 17 cases, 16 were attributed to HHV-6B, while a single case was attributed to HHV-7. Detection rates and average amounts of HHV-6 DNA in saliva samples after ES attributed to HHV-6B were low in the acute phase, increased to the maximum in the convalescent phase at 3-7 months, and then decreased. In addition, to investigate the source of infection, saliva samples from the older siblings (age 3-9 years) and parents of ES patients and children with a history of ES were also examined. The detection rate of HHV-6 DNA in saliva samples from 3- to 9-year-old children was significantly higher than the rate in adult saliva samples. Taken together, these findings suggest that the saliva of children in the convalescent phase of ES might be a more likely source of HHV-6 infection than that of adults. J. Med. Virol. 89:696-702, 2017. © 2016 Wiley Periodicals, Inc.

Cytosolic Prostaglandin E Synthase Is Involved in c-Fos Expression in Rat Fibroblastic 3Y1 Cells.

Cytosolic prostaglandin (PG) E synthase (cPGES/p23) plays a role in the biosynthesis of PGE2 and in the molecular chaperone machinery. Studies of knockout mice lacking cPGES/p23 have demonstrated that cPGES/p23 is essential in fetal mouse development. A cDNA microarray analysis revealed that a lack of cPGES/p23 decreases the expression of some immediate early genes, such as c-fos and activating transcription factor 3 (ATF3). Here we report the involvement of cPGES/p23 in c-Fos expression. A stable knockdown of cPGES/p23 in cultured fibroblasts not only reduced serum-induced c-Fos expression, but also decreased the phosphorylation of extracellular signal regulated kinase (ERK). These results suggest that cPGES/p23 is involved in the activation of ERK to promote c-Fos expression.

Bifunctional porphyrin catalysts for the synthesis of cyclic carbonates from epoxides and CO2: structural optimization and mechanistic study.

We prepared bifunctional Mg(II) porphyrin catalysts 1 for the solvent-free synthesis of cyclic carbonates from epoxides and CO2. The activities of 1d, 1h, and 1i, which have Br(-), Cl(-), and I(-) counteranions, respectively, increased in the order 1i < 1h < 1d. Catalysts 1d and 1j-m, which bear four tetraalkylammonium bromide groups with different alkyl chain lengths, showed comparable but slightly different activities. Based on the excellent catalyst 1d, we synthesized Mg(II) porphyrin 1o with eight tetraalkylammonium bromide groups, which showed even higher catalytic activity (turnover number, 138,000; turnover frequency, 19,000 h(-1)). The catalytic mechanism was studied by using 1d. The yields were nearly constant at initial CO2 pressures in the 1-6 MPa range, suggesting that CO2 was not involved in the rate-determining step in this pressure range. No reaction proceeded in supercritical CO2, probably because the epoxide (into which the catalyst dissolved) dissolved in and was diluted by the supercritical CO2. Experiments with (18)O-labeled CO2 and D-labeled epoxide suggested that the catalytic cycle involved initial nucleophilic attack of Br(-) on the less hindered side of the epoxide to generate an oxyanion, which underwent CO2 insertion to afford a CO2 adduct; subsequent intramolecular ring closure formed the cyclic carbonate and regenerated the catalyst. Density functional theory calculations gave results consistent with the experimental results, revealing that the quaternary ammonium cation underwent conformational changes that stabilized various anionic species generated during the catalytic cycle. The high activity of 1d and 1o was due to the cooperative action of the Mg(II) and Br(-) and a conformational change (induced-fit) of the quaternary ammonium cation.

Regulated incorporation of two different metal ions into programmed sites in a duplex by DNA polymerase catalyzed primer extension.

Metal-mediated base pairs formed by the coordination of metal ions to natural or artificial bases impart unique chemical and physical properties to nucleic acids and have attracted considerable interest in the field of nanodevices. Ag(I) ions were found to mediate DNA polymerase catalyzed primer extension through the formation of a C-Ag(I)-T base pair, as well as the previously reported C-Ag(I)-A base pair. The comparative susceptibility of dNTPs to Ag(I)-mediated enzymatic incorporation into the site opposite cytosine in the template was shown to be dATP>dTTP≫dCTP. Furthermore, two kinds of metal ions, Ag(I) and Hg(II), selectively mediate the incorporation of thymidine 5'-triphosphate into sites opposite cytosine and thymine in the template, respectively. In other words, the regulated incorporation of different metal ions into programmed sites in the duplex by DNA polymerase was successfully achieved.

A case with temporal spikes on electroencephalography induced by over 80 sessions of electroconvulsive therapy.

Background: Electroconvulsive therapy (ECT) is widely recognized as one of the most effective treatments for various psychiatric disorders and is generally considered safe. However, a few reports have mentioned that multiple ECT sessions could induce electroencephalography (EEG) abnormalities and epileptic seizures, a serious side effect of ECT. We experienced a case with EEG abnormalities after multiple ECT sessions and aimed to share our insights on conducting ECT safely. Case Presentation: We present the case of a 73-year-old female diagnosed with major depressive disorder. She underwent regular ECT sessions to alleviate her psychiatric symptoms. However, after more than 80 sessions, previously undetected EEG abnormalities were observed. Since the patient did not have clinical seizures, we were able to continue ECT at longer intervals without the use of antiepileptic drugs. Conclusion: Our case suggests the importance of routine EEG testing in patients undergoing prolonged ECT. While careful monitoring is necessary, continuing ECT without antiepileptic medication in patients with EEG abnormalities could be permissible.

Hidden cases of epilepsy in cognitive impairment clinics: Exploring the use of a portable device for simplified electroencephalography testing.

Late-onset epilepsy, particularly focal impaired awareness seizures, often present without convulsions and can cause memory impairment. This can lead patients to initially seek consultation at memory clinics, potentially delaying referral to epilepsy specialists. We report on three patients, aged 40s to 70s, admitted for cognitive evaluation who were finally diagnosed with epileptic seizures as the underlying cause of their symptoms. Notably, all initially presented to local clinics with symptoms suggesting cognitive impairment. Despite initial diagnostic uncertainty, all patients exhibited epileptic activity on electroencephalography (EEG) and responded positively to antiepileptic drugs, suggesting epileptic mechanisms were involved in their symptoms. Both traditional clinical EEG systems and newly developed, one-minute portable EEG devices were used in their evaluations. The portable device, medically approved in Japan, successfully captured sharp-waves like activities with the same durations, amplitudes, and shapes as traditional devices. This highlights its potential to improve epilepsy diagnosis and future screening due to its portability and ease of use. Implementing portable EEG devices could promote timely and appropriate treatment, preventing misdiagnosis of neurological conditions.

Utilizing portable electroencephalography to screen for pathology of Alzheimer's disease: a methodological advancement in diagnosis of neurodegenerative diseases.

Background: The current biomarker-supported diagnosis of Alzheimer's disease (AD) is hindered by invasiveness and cost issues. This study aimed to address these challenges by utilizing portable electroencephalography (EEG). We propose a novel, non-invasive, and cost-effective method for identifying AD, using a sample of patients with biomarker-verified AD, to facilitate early and accessible disease screening. Methods: This study included 35 patients with biomarker-verified AD, confirmed via cerebrospinal fluid sampling, and 35 age- and sex-balanced healthy volunteers (HVs). All participants underwent portable EEG recordings, focusing on 2-minute resting-state EEG epochs with closed eyes state. EEG recordings were transformed into scalogram images, which were analyzed using "vision Transformer(ViT)," a cutting-edge deep learning model, to differentiate patients from HVs. Results: The application of ViT to the scalogram images derived from portable EEG data demonstrated a significant capability to distinguish between patients with biomarker-verified AD and HVs. The method achieved an accuracy of 73%, with an area under the receiver operating characteristic curve of 0.80, indicating robust performance in identifying AD pathology using neurophysiological measures. Conclusions: Our findings highlight the potential of portable EEG combined with advanced deep learning techniques as a transformative tool for screening of biomarker-verified AD. This study not only contributes to the neurophysiological understanding of AD but also opens new avenues for the development of accessible and non-invasive diagnostic methods. The proposed approach paves the way for future clinical applications, offering a promising solution to the limitations of advanced diagnostic practices for dementia.

A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study.

Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise and accessible diagnostic methods continues, the efficacy of electroencephalography (EEG) combined with deep convolutional neural networks (DCNNs) in varied clinical settings remains unverified, particularly for pathologies underlying MCI such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and idiopathic normal-pressure hydrocephalus (iNPH). Addressing this gap, our study evaluates the generalizability of a DCNN trained on EEG data from a single hospital (Hospital #1). For data from Hospital #1, the DCNN achieved a balanced accuracy (bACC) of 0.927 in classifying individuals as healthy (n = 69) or as having AD, DLB, or iNPH (n = 188). The model demonstrated robustness across institutions, maintaining bACCs of 0.805 for data from Hospital #2 (n = 73) and 0.920 at Hospital #3 (n = 139). Additionally, the model could differentiate AD, DLB, and iNPH cases with bACCs of 0.572 for data from Hospital #1 (n = 188), 0.619 for Hospital #2 (n = 70), and 0.508 for Hospital #3 (n = 139). Notably, it also identified MCI pathologies with a bACC of 0.715 for Hospital #1 (n = 83), despite being trained on overt dementia cases instead of MCI cases. These outcomes confirm the DCNN's adaptability and scalability, representing a significant stride toward its clinical application. Additionally, our findings suggest a potential for identifying shared EEG signatures between MCI and dementia, contributing to the field's understanding of their common pathophysiological mechanisms.

Predicting postoperative delirium after cardiovascular surgeries from preoperative portable electroencephalography oscillations.

Introduction: Postoperative delirium (POD) is common and life-threatening, however, with intensive interventions, a potentially preventable clinical syndrome. Although electroencephalography (EEG) is a promising biomarker of delirium, standard 20-leads EEG holds difficulties for screening usage in clinical practice. Objective: We aimed to develop an accurate algorithm to predict POD using EEG data obtained from portable device. Methods: We recruited 128 patients who underwent scheduled cardiovascular surgery. Cognitive function assessments were conducted, and portable EEG recordings were obtained prior to surgery. Results: Among the patients, 47 (36.7%) patients with POD were identified and they did not significantly differ from patients without POD in sex ratio, age, cognitive function, or treatment duration of intensive care unit. However, significant differences were observed in the preoperative EEG power spectrum densities at various frequencies, especially gamma activity, between patients with and without POD. POD was successfully predicted using preoperative EEG data with a machine learning algorithm, yielding accuracy of 86% and area under the receiver operating characteristic curve of 0.93. Discussion: This study provides new insights into the objective and biological vulnerability to delirium. The developed algorithm can be applied in general hospitals without advanced equipment and expertise, thereby enabling the reduction of POD occurrences with intensive interventions for high-risk patients.

Development of postoperative delirium prediction models in patients undergoing cardiovascular surgery using machine learning algorithms.

Associations between delirium and postoperative adverse events in cardiovascular surgery have been reported and the preoperative identification of high-risk patients of delirium is needed to implement focused interventions. We aimed to develop and validate machine learning models to predict post-cardiovascular surgery delirium. Patients aged ≥ 40 years who underwent cardiovascular surgery at a single hospital were prospectively enrolled. Preoperative and intraoperative factors were assessed. Each patient was evaluated for postoperative delirium 7 days after surgery. We developed machine learning models using the Bernoulli naive Bayes, Support vector machine, Random forest, Extra-trees, and XGBoost algorithms. Stratified fivefold cross-validation was performed for each developed model. Of the 87 patients, 24 (27.6%) developed postoperative delirium. Age, use of psychotropic drugs, cognitive function (Mini-Cog < 4), index of activities of daily living (Barthel Index < 100), history of stroke or cerebral hemorrhage, and eGFR (estimated glomerular filtration rate) < 60 were selected to develop delirium prediction models. The Extra-trees model had the best area under the receiver operating characteristic curve (0.76 [standard deviation 0.11]; sensitivity: 0.63; specificity: 0.78). XGBoost showed the highest sensitivity (AUROC, 0.75 [0.07]; sensitivity: 0.67; specificity: 0.79). Machine learning algorithms could predict post-cardiovascular delirium using preoperative data.Trial registration: UMIN-CTR (ID; UMIN000049390).

Attentional bias to direct gaze in a dot-probe paradigm.

Previous research has suggested that a singly presented facial stimulus having a direct gaze holds spatial attention. This study examined whether facial stimulus having a direct gaze can also capture spatial attention in a relative dot-probe paradigm (facial stimulus having a direct gaze was presented concurrently with that having an averted gaze). The results showed that participants oriented their spatial attention to a facial stimulus having a direct gaze rather than to that with an averted gaze. This attentional bias depended on gaze-perception mechanisms as observed in the lack of attentional bias to a direct gaze from unnatural-looking eyes (i.e., white pupil/iris and black sclera). These findings raise the possibility that the attentional effect implicated in the perception of a direct gaze is induced regardless of the stimulus context.

Ag(I) ion mediated formation of a C-A mispair by DNA polymerases.

Silver turns up the A-C: In the presence of Ag(I) ions, a DNA polymerase incorporated deoxyadenosine (from dATP) at the site opposite cytosine in the template strand to afford the full-length product (see scheme), meaning that DNA polymerases prefer a C-Ag(I)-A base pair to the more thermodynamically stable C-Ag(I)-C base pair.

"Time-based" workplace smoking bans during working hours (including and excluding lunchtime) and combustible cigarette and heated tobacco product use: a cross-sectional analysis of the 2020 JASTIS study.

Although some private companies have implemented "time-based" workplace smoking bans covering all working hours including lunchtime, little is known about their impact on tobacco use. We examined associations between workplace smoking bans during working hours (including and excluding lunchtime) versus no ban and workers' combustible cigarette and heated tobacco product (HTP) use. We used data from the Japan "Society and New Tobacco" Internet Survey 2020 and in total 4,222 workers aged 20-74 were included in the analyses. Using inverse probability weighting, prevalence ratios (PRs) and 95% confidence interval (CI) for tobacco use were calculated according to "time-based" smoke-free policies: workplace smoking bans for working hours including lunchtime (lunchtime ban), workplace smoking ban for working hours excluding lunchtime (lunchtime allowed), and no ban for working hours (no ban). The PRs of "lunchtime ban" for workers' use of combustible cigarettes and HTPs were lower than "no ban": 0.43 (CI: 0.29, 0.63) for combustible cigarette use and 0.61 (CI: 0.41, 0.90) for HTPs use. Meanwhile, the PRs for "lunchtime allowed" was not significant: 0.84 (CI: 0.70, 1.01) for combustible cigarettes use and 1.15 (CI: 0.94, 1.40) for HTPs use. Workplace bans on smoking during working hours which include lunchtime may successfully reduce workers' combustible cigarette and HTP use, but allowing their use during lunchtime may reduce the effectiveness of the ban. Not only conventional "place-based" smoke-free policies, but also "time-based" smoke-free policies are useful for tobacco control in the workplace.