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.

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.

The Impact of Normothermic Machine Perfusion and Acuity Circles on Waitlist Time, Mortality and Cost in Liver Transplantation: A Multi-Center Experience.

BACKGROUND: 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. METHODS: Adult patients listed for liver transplant (LT) at two academic centers 1/1/2015-9/1/2023 were included (n=2773) to allow all patients >6-months follow-up from listing. Routine NMP was implemented on 10/14/2022. Waitlist outcomes were compared from pre-NMP pre-acuity-circles (n=1,460), pre-NMP with acuity circles (n=842) and with NMP (n=381). RESULTS: Median waitlist time was 79days (IQR 20-232 d) at baseline, 49days (7-182) with acuity circles, and 14days (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. 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 MELD at LT was lowest with NMP, but MELD at listing was highest in this era (p<0.0001). Median DRI 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 healthcare 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). CONCLUSION: 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 healthcare costs.

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.

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).

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.

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.

Descriptions of a common belief in an 1813 Japanese beauty handbook regarding the influence of striped clothing on perceived body shape.

"Clothes with horizontal (or vertical) stripes are perceived as wider and shorter (slimmer and taller)." This belief is common yet inconsistent with the Helmholtz illusion. It has often attracted attention from researchers of perception. Despite the controversy among empirical studies, it is persistently supported by the general public. This article explores the early appearance of this common belief in Japan in historical records. Consequently, we discovered the descriptions of the common belief in a Japanese beauty handbook titled "Miyako Fuzoku Kewai Den [Cosmetic manners and customs in Edo]," published in 1813. In Japan, this belief was not born in modern times. Instead, it was established over 200 years ago, when vertical striped patterns on clothes were popularized.

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.

"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.

Effects of wearing a transparent face mask on perception of facial expressions.

Wearing face masks in public has become the norm in many countries post-2020. Although mask-wearing is effective in controlling infection, it has the negative side effect of occluding the mask wearer's facial expressions. The purpose of this study was to investigate the effects of wearing transparent masks on the perception of facial expressions. Participants were required to categorize the perceived facial emotion of female (Experiment 1) and male (Experiment 2) faces with different facial expressions and to rate the perceived emotion intensity of the faces. Based on the group, the participants were assigned to, the faces were presented with a surgical mask, a transparent mask, or without a mask. The results showed that wearing a surgical mask impaired the performance of reading facial expressions, both with respect to recognition and perceived intensity of facial emotions. Specifically, the impairments were robustly observed in fear and happy faces for emotion recognition, and in happy faces for perceived intensity of emotion in Experiments 1 and 2. However, the impairments were moderated by wearing a transparent mask instead of a surgical mask. During the coronavirus disease 2019 (COVID-19) pandemic, the transparent mask can be used in a range of situations where face-to-face communication is important.

The Attractiveness of Masked Faces Is Influenced by Race and Mask Attitudes.

This study tests the influence of wearing a protective face mask on the perceived attractiveness of the wearer. Participants who identified as White, and who varied in their ideological stance toward mask wearing, rated the attractiveness of facial photographs. The photos varied in baseline attractiveness (low, medium, and high), race (White and Asian), and whether or not the face was wearing a protective mask. Attitudes regarding protective masks were measured after the rating task using a survey to identify participants as either pro- or anti-mask. The results showed that masked individuals of the same race were generally rated as more attractive than unmasked individuals, but that masked individuals of another race were rated as less attractive than unmasked individuals. Moreover, pro-mask participants rated masked individuals as generally more attractive than unmasked individuals, whereas anti-maskers rated masked individuals as less attractive. A control experiment, replicating the procedure but replacing the protective masks with a partially occluding notebook, showed that these effects were mask-specific. These results demonstrate that perceived attractiveness is affected by characteristics of the viewer (attitudes toward protective masks), their relationship to the target (same or different race), and by circumstances external to both (pandemic).

Occlusion of faces by sanitary masks improves facial attractiveness of other races.

Recent studies provide mixed results regarding whether the perception of facial attractiveness is increased or decreased by partial occlusion with a sanitary mask. One set of studies demonstrated that occluding the bottom half of a face increased facial attractiveness. This effect is thought to occur because the occluded area is interpolated by an average facial representation that is perceived as attractive. However, several groups of studies showed that partial occlusion can increase or decrease perceived attractiveness depending on the attractiveness of the original (unoccluded) face, due to regression to the mean. To reconcile this inconsistency, we propose that the occluded area is interpolated not by an average facial representation, but by a template of moderate attractiveness, shaped by the distribution of each viewer's experience. This hypothesis predicts an interaction between occlusion and the attractiveness of the original face so that occluded attractive faces are rated as less attractive, while occluded unattractive faces are rated as more attractive. To examine this hypothesis, the present study used attractiveness-rating tasks with mask-free versus masked faces in own-race and other-races categories. Viewers were familiar with own-race faces and unfamiliar with other-races faces. If moderate-attractiveness interpolation were the explanatory factor, the interaction between the occlusion and the attractiveness of the original face should be found only in the rating of own-race faces. Consistent with this hypothesis, the interaction between the occlusion and the attractiveness of the original faces was significant only for the own-race faces. Specifically, wearing a sanitary mask decreased the facial attractiveness of attractive faces in the own-race, while it increased the attractiveness regardless of the level of facial attractiveness in other-races. These findings suggest that the occluded area of own-race faces is interpolated by a facial template of moderate attractiveness. The other-races template could be developed using familiar exemplars such as celebrities. Thus, interpolation by such a template should result in elevated attractiveness relative to that by an own-race template. Accordingly, the apparent inconsistency in the literature regarding the effect of partial occlusion on physical attractiveness can be explained in terms of differences in the template involving interpolation of the occluded area.

Effects of Masks Worn to Protect Against COVID-19 on the Perception of Facial Attractiveness.

Wearing a sanitary mask tended, in the main, to reduce the wearer's sense of perceived facial attractiveness before the COVID-19 epidemic. This phenomenon, termed the sanitary-mask effect, was explained using a two-factor model involving the occlusion of cues used for the judgment of attractiveness and unhealthiness priming (e.g., presumed illness). However, these data were collected during the pre-COVID-19 period. Thus, in this study, we examined whether the COVID-19 epidemic changed the perceived attractiveness and healthiness when viewing faces with and without sanitary masks. We also used questionnaires to evaluate beliefs regarding mask wearers. We found that the perception of mask-worn faces differed before versus after the onset of the COVID-19 epidemic. Specifically, mask-wearing improved wearers' sense of the attractiveness of faces, which were rated as less attractive when a mask was not worn after the onset of the COVID-19 epidemic. Furthermore, mask-worn faces were rated as healthier after the onset of the COVID-19. The proportion of respondents with negative associations regarding mask-wearing (e.g., unhealthiness) decreased relative to before the epidemic. We suggest that the weakening of this association altered the sanitary-mask effect with a relative emphasis on the occlusion component, reflecting the temporal impact of a global social incident (the COVID-19 epidemic) on the perception of facial attractiveness.

Risks of Living Donor Liver Transplantation Using Small-For-Size Grafts.

BACKGROUND: In living donor liver transplantation (LDLT), a graft-to-recipient weight ratio (GRWR) of under 0.8 is recognized as the critical graft size. Our aim was to compare the survival rates of recipients with small-for-size grafts (SFSG: GRWR <0.8), normal-sized grafts (NSG), and large-for-size grafts (LFSG: GRWR ≥ 3.5) and to investigate the mortality risk with SFSG. METHODS: Between 1991 and April 2019, we performed 188 LDLT surgeries. Recently, we added splenectomy when portal vein pressure is high (>17 mm Hg) to interrupt the splenic bloodstream. We divided all LDLT cases retrospectively into 3 groups: an SFSG group (n = 22), NSG group (n = 154), and LFSG group (n = 12). We investigated the survival rates in these groups. Furthermore, we divided the SFSG group into 2 subgroups: an SFSG with splenectomy (SFSG+S) group (n = 7) and an SFSG without splenectomy group. We investigated the occurrence rates of lethal complications such as portal vein thrombosis, hepatic artery thrombosis, and hepatic vein thrombosis. RESULTS: The 5-year survival rate in the SFSG group was significantly lower (52.8%) than in the other groups (NSG: 84.5%; LFSG: 83.3%), but that of the SFSG+S group was similar (80.0%) to that of other groups. There was no difference in the occurrence of postoperative complications such as portal vein thrombosis, hepatic artery thrombosis, or hepatic vein thrombosis between the SFSG+S group and other groups. CONCLUSIONS: Graft survival of LDLT using SFSG+S was as good as that of normal-sized grafts. Reducing portal vein pressure was important for SFSG.

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.

Reconstitution of NK cells expressing KIR3DL1 is associated with reduced NK cell activity and relapse of CML after allogeneic hematopoietic stem cell transplantation.

Although the prognosis of chronic myeloid leukemia (CML) in blastic crisis remains poor, some patients achieve long-term remission after allogeneic hematopoietic stem cell transplantation (allo-HSCT). This may be attributable to graft-versus-leukemia (GVL) effects by donor lymphocytes, but their regulating mechanisms are unclear. Antitumor natural killer (NK) cell immunity is assumed to be important in CML, and we have previously shown that allelic polymorphisms of killer immunoglobulin-like receptors (KIRs) and histocompatibility leukocyte antigens (HLAs) are associated with the response of CML to tyrosine kinase inhibitors. Here, we report a case of CML in blastic phase who received HLA-matched but KIR3DL1 allelic-mismatched allo-HSCT. After transplant, decreased BCR-ABL transcript levels and enhanced NK cell activity were transiently observed. However, reconstitution of KIR3DL1-expressing NK cells occurred, which was associated with diminished NK cell activity and increased BCR-ABL. This case indicates the potential significance of KIR3DL1 in NK cell-mediated GVL activity following allo-HSCT. To the best of our knowledge, this is the first report to analyze the association between sequential KIR3DL1 expression and activity of NK cells after allo-HSCT. Selecting donors with KIR3DL1-null alleles may maintain competent GVL effects and provide improved outcomes in allo-HSCT for CML.