Regression models for average hazard.

Limitations of using the traditional Cox's hazard ratio for summarizing the magnitude of the treatment effect on time-to-event outcomes have been widely discussed, and alternative measures that do not have such limitations are gaining attention. One of the alternative methods recently proposed, in a simple 2-sample comparison setting, uses the average hazard with survival weight (AH), which can be interpreted as the general censoring-free person-time incidence rate on a given time window. In this paper, we propose a new regression analysis approach for the AH with a truncation time τ. We investigate 3 versions of AH regression analysis, assuming (1) independent censoring, (2) group-specific censoring, and (3) covariate-dependent censoring. The proposed AH regression methods are closely related to robust Poisson regression. While the new approach needs to require a truncation time τ explicitly, it can be more robust than Poisson regression in the presence of censoring. With the AH regression approach, one can summarize the between-group treatment difference in both absolute difference and relative terms, adjusting for covariates that are associated with the outcome. This property will increase the likelihood that the treatment effect magnitude is correctly interpreted. The AH regression approach can be a useful alternative to the traditional Cox's hazard ratio approach for estimating and reporting the magnitude of the treatment effect on time-to-event outcomes.

Twelve-year conversion of rice paddy to wetland does not alter SOC content but decreases C decomposition and N mineralization in Japan.

Land-use change worldwide has been driven by anthropogenic activities, which profoundly regulates terrestrial C and N cycles. However, it remains unclear how the dynamics and decomposition of soil organic C (SOC) and N respond to long-term conversion of rice paddy to wetland. Here, soil samples from five soil depths (0-25 cm, 5 cm/depth) were collected from a continuous rice paddy and an adjacent wetland (a rice paddy abandoned for 12 years) on Shonai Plain in northeastern Japan. A four-week anaerobic incubation experiment was conducted to investigate soil C decomposition and N mineralization. Our results showed that SOC in the wetland and rice paddy decreased with soil depth, from 31.02 to 19.66 g kg-1 and from 30.26 to 18.86 g kg-1, respectively. There was no significant difference in SOC content between wetland and rice paddy at any depth. Soil total nitrogen (TN) content in the wetland (2.61-1.49 g kg-1) and rice paddy (2.91-1.78 g kg-1) showed decreasing trend with depth; TN was significantly greater in the rice paddy than in the wetland at all depths except 20-25 cm. Paddy soil had significantly lower C/N ratios but significantly larger decomposed C (Dec-C, CO2 and CH4 production) and mineralized N (Min-N, net NH4+-N production) than wetland soil across all depths. Moreover, the Dec-C/Min-N ratio was significantly larger in wetland than in rice paddy across all depths. Rice paddy had higher exponential correlation between Dec-C and SOC, Min-N and TN than wetland. Although SOC did not change, TN decreased by 14.1% after the land-use conversion. The Dec-C and Min-N were decreased by 32.7% and 42.2%, respectively, after the12-year abandonment of rice paddy. Conclusively, long-term conversion of rice paddy to wetland did not distinctly alter SOC content but increased C/N ratio, and decreased C decomposition and N mineralization in 0-25 cm soil depth.

Nationwide prospective registry database of patients with newly diagnosed untreated pleural mesothelioma in Japan.

Due to the scarcity of large-sized prospective databases, the Japanese Joint Committee for Lung Cancer Registry conducted a nationwide prospective registry for newly diagnosed and untreated pleural mesothelioma. All new cases diagnosed pathologically as any subtype of pleural mesothelioma in Japan during the period between April 1, 2017, to March 31, 2019, were included before treatment. Data on survival were collected in April 2021. The eligible 346 patients (285 men [82.3%]; 61 women [17.7%]; median age, 71.0 years [range, 44-88]) were included for analysis. Among these patients, 138 (39.9%) underwent surgery, 164 (47.4%) underwent non-surgical therapy, and the remaining 44 (12.7%) underwent best supportive care. The median overall survival for all 346 patients was 19.0 months. Survival rates at 1, 2, and 3 years for all patients were, 62.8%, 42.3%, and 26.5%, respectively. Median overall survival was significantly different among patients undergoing surgery, non-surgical treatment, and best supportive care (32.2 months vs. 14.0 months vs. 3.8 months, p < 0.001). The median overall survival of patients undergoing pleurectomy/decortication and extrapleural pneumonectomy was 41.8 months and 25.0 months, respectively. Macroscopic complete resection resulted in longer overall survival than R2 resection and partial pleurectomy/exploratory thoracotomy (41.8 months vs. 32.2 months vs. 16.8 months, p < 0.001). Tumor shape, maximum tumor thickness, and sum of three level thickness were significant prognostic factors. The data in the prospective database would serve as a valuable reference for clinical practice and further studies for pleural mesothelioma.

Association of atmospheric temperature with out-of-hospital natural deaths occurrence before and during the COVID-19 pandemic in Osaka, Japan.

In this study, we aimed to investigate the relationship between out-of-hospital natural death (OHND) and ambient temperature and examine the seriousness of the impact of the coronavirus disease-2019 (COVID-19) pandemic on this relationship. We used data from the Osaka Prefectural Office of Medical Examiners between 2018 and 2022 and performed a retrospective observational study. A Poisson regression model was applied to examine the relationship between OHND and temperature in Osaka City. The relative risk of OHND at 5 °C and 32 °C compared to the minimum mortality temperature increased from 1.81 in the pre-COVID-19 period to 2.03 in the post-COVID-19 period at 5 °C and from 1.29 in the pre-COVID-19 period to 1.60 in the post-COVID-19 period at 32 °C. The increase in relative risk per 1 °C increase from the pre- to post-COVID-19 period was 1.0551 (rate ratio [RR], p = 0.003) in the hot environment and 1.0233 (RR, p = 0.013) in the cold environment, which was larger than that in the hot environment. Although the risk of OHND increased at both temperatures, the change in OHND risk during post-COVID-19 was larger in the hot environment than in the cold environment, implicating the effect of pandemics in the current scenario of global warming.

Frequentist analysis of basket trials with one-sample Mantel-Haenszel procedures.

Recent substantial advances of molecular targeted oncology drug development is requiring new paradigms for early-phase clinical trial methodologies to enable us to evaluate efficacy of several subtypes simultaneously and efficiently. The concept of the basket trial is getting of much attention to realize this requirement borrowing information across subtypes, which are called baskets. Bayesian approach is a natural approach to this end and indeed the majority of the existing proposals relies on it. On the other hand, it required complicated modeling and may not necessarily control the type 1 error probabilities at the nominal level. In this article, we develop a purely frequentist approach for basket trials based on one-sample Mantel-Haenszel procedure relying on a very simple idea for borrowing information under the common treatment effect assumption over baskets. We show that the proposed Mantel-Haenszel estimator for the treatment effect is consistent under two limiting models of the large strata and sparse data limiting models (dually consistent) and propose dually consistent variance estimators. The proposed estimators are interpretable even if the common treatment effect assumptions are violated. Then, we can design basket trials in a confirmatory matter. We also propose an information criterion approach to identify effective subclasses of baskets.

Running exercise and food restriction affect bone chemical properties in young female rats.

PURPOSE: To investigate the effects of a combination of running and food restriction on the chemical properties of the bone in young female rats using Raman spectroscopy. Furthermore, we investigated whether the chemical property parameters correlated with the bone-breaking strength. METHODS: Female Sprague-Dawley rats (7 weeks old) were randomly divided into four groups: sedentary and ad libitum feeding (SED, n = 8), voluntary running exercise and ad libitum feeding (EX, n = 8), sedentary and 30% food-restricted (SED-FR, n = 8), and voluntary running exercise and 30% food-restricted (EXFR, n = 8). The experiment was conducted for a period of 12 weeks. Four parameters measured by Raman spectroscopy were used to evaluate the bone chemical quality. RESULTS: Exercise and restriction had significant interactions on the mineral to matrix ratio. The mineral- to-matrix ratio in the SED-FR group was significantly higher than that in the SED group and significantly lower in the EX-FR group than that in the SED-FR group. Running exercise had significant effects on increasing the crystallinity and carbonate-to-phosphate ratio. In the ad libitum intake condition, there were significant positive correlations between breaking energy and crystallinity (r = 0.593) and between breaking energy and carbonate-to-phosphate ratio (r = 0.854). CONCLUSION: Our findings show that running exercise and food restriction, alone or in combination, affect the chemical properties of bone. Furthermore, under ad libitum intake conditions, positive correlations were found between the breaking energy and crystallinity, or carbonate-to-phosphate ratio.

DTAmetasa: An R shiny application for meta-analysis of diagnostic test accuracy and sensitivity analysis of publication bias.

Meta-analysis of diagnostic test accuracy (DTA) is a powerful statistical method for synthesizing and evaluating the diagnostic capacity of medical tests and has been extensively used by clinical physicians and healthcare decision-makers. However, publication bias (PB) threatens the validity of meta-analysis of DTA. Some statistical methods have been developed to deal with PB in meta-analysis of DTA, but implementing these methods requires high-level statistical knowledge and programming skill. To assist non-technical users in running most routines in meta-analysis of DTA and handling with PB, we developed an interactive application, DTAmetasa. DTAmetasa is developed as a web-based graphical user interface based on the R shiny framework. It allows users to upload data and conduct meta-analysis of DTA by "point and click" operations. Moreover, DTAmetasa provides the sensitivity analysis of PB and presents the graphical results to evaluate the magnitude of the PB under various publication mechanisms. In this study, we introduce the functionalities of DTAmetasa and use the real-world meta-analysis to show its capacity for dealing with PB.

Predictors of Survival in Patients With Ischemic Stroke and Active Cancer: A Prospective, Multicenter, Observational Study.

Background Limited data exist on the prognostic factors for patients with ischemic stroke and active cancer. Methods and Results We conducted a prospective, multicenter, observational study in Japan, including patients with acute ischemic stroke and active cancer, to investigate the prognostic factors. We followed up the patients for 1 year after stroke onset. The patients were divided into 2 groups according to cryptogenic stroke and known causes (small-vessel occlusion, large-artery atherosclerosis, cardioembolism, and other determined cause), and survival was compared. The hazard ratios (HRs) and 95% CIs for mortality were calculated using Cox regression models. We identified 135 eligible patients (39% women; median age, 75 years). Of these patients, 51% had distant metastasis. A total of 65 (48%) and 70 (52%) patients had cryptogenic stroke and known causes, respectively. Patients with cryptogenic stroke had significantly shorter survival than those with known causes (HR [95% CI], 3.11 [1.82-5.32]). The multivariable Cox regression analysis revealed that distant metastasis, plasma D-dimer levels, venous thromboembolism (either deep venous thrombosis or pulmonary embolism) complications at stroke onset were independent predictors of mortality after adjusting for potential confounders. Cryptogenic stroke was associated with prognosis in univariable analysis but was not significant in multivariable analysis. The plasma D-dimer levels stratified the prognosis of patients with ischemic stroke and active cancer. Conclusions The prognosis of patients with acute ischemic stroke and active cancer varied considerably depending on stroke mechanism, distant metastasis, and coagulation abnormalities. The present study confirmed that coagulation abnormalities were crucial in determining the prognosis of such patients.

Contralateral lower limb radiculopathy by extraforaminal disc herniation following oblique lumbar interbody fusion in degenerative lumbar disorder: illustrative cases.

BACKGROUND: Contralateral lower limb radiculopathy is a potential early complication of oblique lumbar interbody fusion (OLIF) in degenerative lumbar disorders. Among several pathologies related to contralateral radiculopathy following OLIF, extraforaminal disc herniation during the OLIF procedure is very rare. OBSERVATIONS: Case 1 is a 68-year-old male underwent L4-5 and L5-6 OLIF for recurrent lumbar canal stenosis-expressed right leg pain and muscle weakness after surgery. Case 2 is a 76-year-old female on whom L4-5 OLIF was performed for L4 degenerative spondylolisthesis and who presented right leg pain and numbness postoperatively. In both patients, OLIF cages were inserted into the posterior part of the disc space or obliquely and the extraforaminal extruded disc compressed opposite exiting nerve roots (L5 root in case 1 and L4 root in case 2) as shown on magnetic resonance imaging (MRI). Surgical decompression with discectomy was required for pain relief and neurological improvement in both cases. LESSONS: When emerging from new-onset opposite limb radiculopathy attributed to the OLIF procedure, extraforaminal disc herniation should be considered a potential pathology and MRI is useful for early diagnosis and selecting a subsequent management, including surgery.

Association between cerebrospinal fluid parameters and developmental and neurological status in glucose transporter 1 deficiency syndrome.

OBJECTIVE: In glucose transporter 1 deficiency syndrome (Glut1DS), cerebrospinal fluid glucose (CSFG) and CSFG to blood glucose ratio (CBGR) show significant differences among groups classified by phenotype or genotype. The purpose of this study was to investigate the association between these biochemical parameters and Glut1DS severity. METHODS: The medical records of 45 patients who visited Osaka University Hospital between March 2004 and December 2021 were retrospectively examined. Neurological status was determined using the developmental quotient (DQ), assessed using the Kyoto Scale of Psychological Development 2001, and the Scale for the Assessment and Rating of Ataxia (SARA). CSF parameters included CSFG, CBGR, and CSF lactate (CSFL). RESULTS: CSF was collected from 41 patients, and DQ and SARA were assessed in 24 and 27 patients, respectively. Simple regression analysis showed moderate associations between neurological status and biochemical parameters. CSFG resulted in a higher R2 than CBGR in these analyses. CSF parameters acquired during the first year of life were not comparable to those acquired later. CSFL was measured in 16 patients (DQ and SARA in 11 and 14 patients, respectively). Although simple regression analysis also showed moderate associations between neurological status and CSFG and CSFL, the multiple regression analysis for DQ and SARA resulted in strong associations through the use of a combination of CSFG and CSFL as explanatory variables. CONCLUSION: The severity of Glut1DS can be predicted from CSF parameters. Glucose and lactate are independent contributors to the developmental and neurological status in Glut1DS.

Major Causes of Death among Older Adults after the Great East Japan Earthquake: A Retrospective Study.

This retrospective study investigated the 3-year impact of the Great East Japan Earthquake (GEJE) of 2011 on deaths due to neoplasm, heart disease, stroke, pneumonia, and senility among older adults in the primarily affected prefectures compared with other prefectures, previous investigations having been more limited as regards mortality causes and geographic areas. Using death certificates issued between 2006 and 2015 (n = 7,383,253), mortality rates (MRs) and risk ratios (RRs) were calculated using a linear mixed model with the log-transformed MR as the response variable. The model included interactions between the area category and each year of death from 2010 to 2013. The RRs in the interaction significantly increased to 1.13, 1.17, and 1.28 for deaths due to stroke, pneumonia, and senility, respectively, in Miyagi Prefecture in 2011, but did not significantly increase for any of the other areas affected by the GEJE. Moreover, increased RRs were not reported for any of the other years. The risk of death increased in 2011; however, this was only significant for single-year impact. In 2013, decreased RRs of pneumonia in the Miyagi and Iwate prefectures and of senility in Fukushima Prefecture were observed. Overall, we did not find evidence of strong associations between the GEJE and mortality.

Adjusting for publication bias in meta-analysis via inverse probability weighting using clinical trial registries.

Publication bias is a major concern in conducting systematic reviews and meta-analyses. Various sensitivity analysis or bias-correction methods have been developed based on selection models, and they have some advantages over the widely used trim-and-fill bias-correction method. However, likelihood methods based on selection models may have difficulty in obtaining precise estimates and reasonable confidence intervals, or require a rather complicated sensitivity analysis process. Herein, we develop a simple publication bias adjustment method by utilizing the information on conducted but still unpublished trials from clinical trial registries. We introduce an estimating equation for parameter estimation in the selection function by regarding the publication bias issue as a missing data problem under the missing not at random assumption. With the estimated selection function, we introduce the inverse probability weighting (IPW) method to estimate the overall mean across studies. Furthermore, the IPW versions of heterogeneity measures such as the between-study variance and the I2 measure are proposed. We propose methods to construct confidence intervals based on asymptotic normal approximation as well as on parametric bootstrap. Through numerical experiments, we observed that the estimators successfully eliminated bias, and the confidence intervals had empirical coverage probabilities close to the nominal level. On the other hand, the confidence interval based on asymptotic normal approximation is much wider in some scenarios than the bootstrap confidence interval. Therefore, the latter is recommended for practical use.

Impact of S-1 adjuvant chemotherapy longer than 6 months on survival in patients with resected pancreatic cancer: a nationwide survey by the Japan Pancreas Society based on real-world data.

BACKGROUND: Based on the Japan Adjuvant Study Group of Pancreatic Cancer 01 study, the standard duration of adjuvant chemotherapy with S-1 (an oral 5-fluorouracil prodrug consisting of tegafur, gimeracil, and oteracil) in patients with resected pancreatic ductal adenocarcinoma (PDAC) was considered to be 6 months, but the impact of increasing its duration on postoperative survival was unknown. Here, the authors investigated this question by reviewing real-world data from a large cohort of patients with PDAC. METHODS: In total, 3949 patients who underwent surgery for PDAC during the study period followed by S-1 adjuvant chemotherapy in board-certified institutions were included. Based on the duration of S-1 chemotherapy, two subgroups were defined: a standard-duration group that included patients who were treated for 180 ± 30 days and a longer duration group that included patients who received treatment for >210 days. RESULTS: The median duration of S-1 chemotherapy was 167 days, with a mean ± standard deviation of 200 ± 193 days. After excluding patients who had a recurrence within 210 days after the initiation of adjuvant chemotherapy, postoperative recurrence-free survival (RFS) and overall survival (OS) in the standard-duration group (n = 1473) and the longer duration group (n = 975) were compared. RFS and OS did not differ significantly between the standard-duration and longer duration groups (5-year RFS: 37.8% vs. 36.2% respectively; p = .6186; 5-year OS: 52.8% vs. 53.4%, respectively; p = .5850). The insignificant difference was verified by multivariate analysis and propensity-score matching analysis. CONCLUSIONS: The current findings suggest that extending S-1 adjuvant chemotherapy beyond 6 months has no significant additional effect on survival in patients with PDAC. This could be useful in determining whether to extend S-1 chemotherapy in patients who have completed the standard 6-month treatment.

A likelihood-based sensitivity analysis for publication bias on the summary receiver operating characteristic in meta-analysis of diagnostic test accuracy.

In meta-analysis of diagnostic test accuracy, the summary receiver operating characteristic (SROC) curve is a recommended method to summarize the diagnostic capacity of a medical test in the presence of study-specific cutoff values. The SROC curve can be estimated by bivariate modeling of pairs of sensitivity and specificity across multiple diagnostic studies, and the area under the SROC curve (SAUC) gives the aggregate estimate of diagnostic test accuracy. However, publication bias is a major threat to the validity of the estimates. To make inference of the impact of publication bias on the SROC curve or the SAUC, we propose a sensitivity analysis method by extending the likelihood-based sensitivity analysis of Copas. In the proposed method, the SROC curve or the SAUC are estimated by maximizing the likelihood constrained by different values of the marginal probability of selective publication under different mechanisms of selective publication. A cutoff-dependent selection function is developed to model the selective publication mechanism via the t $$ t $$ -type statistics or P $$ P $$ -value of the linear combination of the logit-transformed sensitivity and specificity from the published studies. It allows us to model selective publication suggested by the funnel plots of sensitivity, specificity, or diagnostic odds ratio, which are often observed in practice. A real meta-analysis of diagnostic test accuracy is re-analyzed to illustrate the proposed method, and simulation studies are conducted to evaluate its performance.

The usefulness of the total metabolic tumor volume for predicting the postoperative recurrence of thoracic esophageal squamous cell carcinoma.

BACKGROUND: Induction or adjuvant therapies are not always beneficial for thoracic esophageal squamous cell carcinoma (ESCC) patients, and it is thus important to identify patients at high risk for postoperative ESCC recurrence. We investigated the usefulness of the total metabolic tumor volume (TMTV) for predicting the postoperative recurrence of thoracic ESCC. METHODS: We retrospectively analyzed the cases of 163 thoracic ESCC patients (135 men, 28 women; median age of 66 [range 34-82] years) treated at our hospital in 2007-2012. The TMTV was calculated from the fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in the primary lesion and lymph node metastases. The optimal cut-off values for relapse and non-relapse were obtained by the time-dependent receiver operating curve analyses. Relapse-free survival (RFS) was evaluated by the Kaplan-Meier method, and between-subgroup differences in survival were analyzed by log-rank test. The prognostic significance of metabolic parameters and clinicopathological variables was assessed by a Cox proportional hazard regression analysis. The difference in the failure patterns after surgical resection was evaluated using the χ2-test. RESULTS: The optimal cut-off value of TMTV for discriminating relapse from non-relapse was 3.82. The patients with a TMTV ≥3.82 showed significantly worse prognoses than those with low values (p < 0.001). The TMTV was significantly related to RFS (model 1 for preoperative risk factors: TMTV: hazard ratio [HR] =2.574, p = 0.004; model 2 for preoperative and postoperative risk factors: HR = 1.989, p = 0.044). The combination of the TMTV and cN0-1 or pN0-1 stage significantly stratified the patients into low-and high-risk recurrence groups (TMTV cN0-1, p < 0.001; TMTV pN0-1, p = 0.004). The rates of hematogenous and regional lymph node metastasis were significantly higher in the patients with TMTV ≥3.82 than those with low values (hematogenous metastasis, p < 0.001, regional lymph node metastasis, p = 0.011). CONCLUSIONS: The TMTV was a more significantly independent prognostic factor for RFS than any other PET parameter in patients with resectable thoracic ESCC. The TMTV may be useful for the identifying thoracic ESCC patients at high risk for postoperative recurrence and for deciding the patient management.

Identification of mild cognitive impairment subtypes predicting conversion to Alzheimer's disease using multimodal data.

Mild cognitive impairment (MCI) is a high-risk condition for conversion to Alzheimer's disease (AD) dementia. However, individuals with MCI show heterogeneous patterns of pathology and conversion to AD dementia. Thus, detailed subtyping of MCI subjects and accurate prediction of the patients in whom MCI will convert to AD dementia is critical for identifying at-risk populations and the underlying biological features. To this end, we developed a model that simultaneously subtypes MCI subjects and predicts conversion to AD and performed an analysis of the underlying biological characteristics of each subtype. In particular, a heterogeneous mixture learning (HML) method was used to build a decision tree-based model based on multimodal data, including cerebrospinal fluid (CSF) biomarker data, structural magnetic resonance imaging (MRI) data, APOE genotype data, and age at examination. The HML model showed an average F1 score of 0.721, which was comparable to the random forest method and had significantly more predictive accuracy than the CART method. The HML-generated decision tree was also used to classify-five subtypes of MCI. Each MCI subtype was characterized in terms of the degree of abnormality in CSF biomarkers, brain atrophy, and cognitive decline. The five subtypes of MCI were further categorized into three groups: one subtype with low conversion rates (similar to cognitively normal subjects); three subtypes with moderate conversion rates; and one subtype with high conversion rates (similar to AD dementia patients). The subtypes with moderate conversion rates were subsequently separated into a group with CSF biomarker abnormalities and a group with brain atrophy. The subtypes identified in this study exhibited varying MCI-to-AD conversion rates and differing biological profiles.

Pharmacotherapy alleviates pathological changes in human direct reprogrammed neuronal cell model of myotonic dystrophy type 1.

Myotonic dystrophy type 1 (DM1) is a trinucleotide repeat disorder affecting multiple organs. However, most of the research is focused on studying and treating its muscular symptoms. On the other hand, despite the significant impact of the neurological symptoms on patients' quality of life, no drug therapy was studied due to insufficient reproducibility in DM1 brain-specific animal models. To establish DM1 neuronal model, human skin fibroblasts were directly converted into neurons by using lentivirus expressing small hairpin RNA (shRNA) against poly-pyrimidine tract binding protein (PTBP). We found faster degeneration in DM1 human induced neurons (DM1 hiNeurons) compared to control human induced neurons (ctrl hiNeurons), represented by lower viability from 10 days post viral-infection (DPI) and abnormal axonal growth at 15 DPI. Nuclear RNA foci were present in most of DM1 hiNeurons at 10 DPI. Furthermore, DM1 hiNeurons modelled aberrant splicing of MBNL1 and 2, MAPT, CSNK1D and MPRIP at 10 DPI. We tested two drugs that were shown to be effective for DM1 in non-neuronal model and found that treatment of DM1 hiNeurons with 100 nM or 200 nM actinomycin D (ACT) for 24 h resulted in more than 50% reduction in the number of RNA foci per nucleus in a dose dependent manner, with 16.5% reduction in the number of nuclei containing RNA foci at 200 nM and treatment with erythromycin at 35 µM or 65 µM for 48 h rescued mis-splicing of MBNL1 exon 5 and MBNL 2 exons 5 and 8 up to 17.5%, 10% and 8.5%, respectively. Moreover, erythromycin rescued the aberrant splicing of MAPT exon 2, CSNK1D exon 9 and MPRIP exon 9 to a maximum of 46.4%, 30.7% and 19.9%, respectively. These results prove that our model is a promising tool for detailed pathogenetic examination and novel drug screening for the nervous system.

Female Athlete Triad and Male Athlete Triad Syndrome Induced by Low Energy Availability: An Animal Model.

Energy availability (EA) is defined the difference in energy intake and exercise energy expenditure. Reduction of EA (i.e. Low energy availability, LEA) often causes abnormalities of reproduction system and drastic bone loss in some female athletes, the phenomenon is called as female athlete triad. More than ever before, it is considered a serious problem, the reason of these are (1) the syndrome occurred in female athletes but also male athletes, (2) LEA is leads to dysfunction of various organs other than reproductive system (Relative energy deficiency in sport, RED-S). On the other hand, we have focused on this syndrome and have proposed novel insights into the physiological effects of LEA on bone and solutions through nutritional treatment by recreating it in animal models. In this review, we will summarize the epidemiological and physiological perspectives of these diseases from historical background to recent findings, and introduce the usefulness of using animal models to explore mechanisms and treatments.

Sample size calculation for the augmented logrank test in randomized clinical trials.

In randomized clinical trials, incorporating baseline covariates can improve the power in hypothesis testing for treatment effects. For survival endpoints, the Cox proportional hazards model with baseline covariates as explanatory variables can improve the standard logrank test in power. Although this has long been recognized, this adjustment is not commonly used as the primary analysis and instead the logrank test followed by the estimation of the hazard ratio between treatment groups is often used. By projecting the score function for the Cox proportional hazards model onto a space of covariates, the logrank test can be more powerful. We derive a power formula for this augmented logrank test under the same setting as the widely used power formula for the logrank test and propose a simple strategy for sizing randomized clinical trials utilizing historical data of the control treatment. Through numerical studies, the proposed procedure was found to have the potential to reduce the sample size substantially as compared to the standard logrank test. A concern to utilize historical data is that those might not reflect well the data structure of the study to design and then the sample size calculated might not be accurate. Since our power formula is applicable to datasets pooled across the treatment arms, the validity of the power calculation at the design stage can be checked in blind reviews.