Ulcerative colitis (UC) specifically affects the colon and rectum through multifactorial mechanisms associated with genetic alterations, environmental factors, microbiota, and mucosal immune ...dysregulation. In patients with corticosteroid-refractory UC, current therapies primarily employ antibodies against tumor necrosis factor-α, α4β7 integrin, and interleukin (IL)-12/23 p40; and a small-molecule Janus kinase inhibitor. Despite these revolutionary molecular targeting therapies introduced during the last two decades, 30%–55% of patients fail to respond such molecular targeting agents in the induction phase, requiring changes in treatment. Here we review basic and clinical research aimed to address this problem, focusing on the pathogenic effects of cytokines produced by innate and adaptive immune cells. For example, IL-1β, IL-6, tumor necrosis factor-α, T helper (Th) 1-, Th2-, and Th17-associated cytokines are expressed at relatively higher levels in the intestinal tissues of patients with UC. However, their expression levels depend on disease stage and patient characteristics. The complex pathology of UC may induce differences in responses to therapy. The findings of such studies strongly support the argument that future targeted therapies must focus on differences in cytokine levels associated with the stages of UC as well as on the distinct cytokine expression profiles of individual patients.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Epilepsy is a diverse brain disorder, and the pathophysiology of its various forms and comorbidities is largely unknown. A recent machine learning method enables us to estimate an individual's ..."brain-age" from MRI; this brain-age prediction is expected as a novel individual biomarker of neuropsychiatric disorders. The aims of this study were to estimate the brain-age for various categories of epilepsy and to evaluate clinical discrimination by brain-age for (1) the effect of psychosis on temporal lobe epilepsy (TLE), (2) psychogenic nonepileptic seizures (PNESs) from MRI-negative epilepsies, and (3) progressive myoclonic epilepsy (PME) from juvenile myoclonic epilepsy (JME). In total, 1196 T1-weighted MRI scans from healthy controls (HCs) were used to build a brain-age prediction model with support vector regression. Using the model, we calculated the brain-predicted age difference (brain-PAD: predicted age-chronological age) of the HCs and 318 patients with epilepsy. We compared the brain-PAD values based on the research questions. As a result, all categories of patients except for extra-temporal lobe focal epilepsy showed a significant increase in brain-PAD. TLE with hippocampal sclerosis presented a significantly higher brain-PAD than several other categories. The mean brain-PAD in TLE with inter-ictal psychosis was 10.9 years, which was significantly higher than TLE without psychosis (5.3 years). PNES showed a comparable mean brain-PAD (10.6 years) to that of epilepsy patients. PME had a higher brain-PAD than JME (22.0 vs. 9.3 years). In conclusion, neuroimaging-based brain-age prediction can provide novel insight into or clinical usefulness for the diverse symptoms of epilepsy.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Cancer-associated fibroblasts (CAFs) are a heterogenous group of activated fibroblasts and a major component of the tumor stroma. CAFs may be derived from fibroblasts, epithelial cells, endothelial ...cells, cancer stem cells, adipocytes, pericytes, or stellate cells. These complex origins may underlie their functional diversity, which includes pro-tumorigenic roles in extracellular matrix remodeling, the suppression of anti-tumor immunity, and resistance to cancer therapy. Several methods for targeting CAFs to inhibit tumor progression and enhance anti-tumor immunity have recently been reported. While preclinical studies have shown promise, to date they have been unsuccessful in human clinical trials against melanoma, breast cancer, pancreas cancer, and colorectal cancers. This review summarizes recent and major advances in CAF-targeting therapies, including DNA-based vaccines, anti-CAF CAR-T cells, and modifying and reprogramming CAF functions. The challenges in developing effective anti-CAF treatment are highlighted, which include CAF heterogeneity and plasticity, the lack of specific target markers for CAFs, the limitations in animal models recapitulating the human cancer microenvironment, and the undesirable off-target and systemic side effects. Overcoming these challenges and expanding our understanding of the basic biology of CAFs is necessary for making progress towards safe and effective therapeutic strategies against cancers in human patients.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In the past decades, immunotherapies against cancers made impressive progress. Immunotherapy includes a broad range of interventions that can be separated into two major groups: cell-based ...immunotherapies, such as adoptive T cell therapies and stem cell therapies, and immunomodulatory molecular therapies such as checkpoint inhibitors and cytokine therapies. Genetic engineering techniques that transduce T cells with a cancer-antigen-specific T cell receptor or chimeric antigen receptor have expanded to other cell types, and further modulation of the cells to enhance cancer targeting properties has been explored. Because cell-based immunotherapies rely on cells migrating to target organs or tissues, there is a growing interest in imaging technologies that non-invasively monitor transferred cells
in vivo
. Here, we review whole-body imaging methods to assess cell-based immunotherapy using a variety of examples. Following a review of preclinically used cell tracking technologies, we consider the status of their clinical translation.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
The optimal range of gestational weight gain (GWG) was recently raised in Japan. This may help reduce small-for-gestational-age (SGA) infants, but may also increase large-for-gestational-age (LGA) ...infants. This study performed hypothetical experiments to determine effective GWG advice based on quantile regression analysis. In a total of 354,401 singleton pregnancies registered in the perinatal database of the Japan Society of Obstetrics and Gynecology (2013-2017), the proportions of SGA and LGA were 9.33% and 11.13%, respectively. Using regression coefficients of GWG across the birth weight-for-gestational-age quantile distribution, we analyzed changes in their proportions by simulating a uniform 3-kg extra increase in GWG or an increase or decrease based on GWG adequacy. A hypothetical experiment of a uniform increase in GWG resulted in SGA and LGA proportions of 7.26% (95% confidence interval 7.15-7.36) and 14.51% (14.37-14.66), respectively. By contrast, assuming a 3-kg increase in women with inadequate GWG and a 3-kg decrease in women with excessive GWG resulted in SGA and LGA proportions of 8.42% (8.31-8.54) and 11.50% (11.37-11.62), respectively. Our real-world data analysis suggests that careful adjustment of GWG based on GWG adequacy will be effective in optimizing infant birth weight in Japan.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Fetal growth quality is associated with susceptibility to non-communicable diseases. Fetal size has been conventionally assessed using the averaged growth chart, but fetal growth velocity has ...recently been attracting attention as another important aspect of fetal development. Since fetal growth velocity may reflect fetal response to various conditions during the developmental process within the maternal constraint, it is reasonable to imagine that there might exist a physiological diversity in growth velocity patterns over time, which has never been explored. We conducted a retrospective cohort study designed to evaluate the heterogeneity of fetal growth velocity in singleton pregnancies in the Japanese population. We leveraged the high frequency of prenatal checkup to collect large numbers of ultrasound measurements of every fetus (N = 801) and computationally analyzed individual changes in growth per week. Latent class trajectory analysis identified three distinct velocity patterns. The variation in growth velocity appeared in the third trimester and corresponded to the differences in neonatal size. This heterogeneity was not simply explained by maternal factors and fetal sex, although those factors had time-varying effects on fetal size. Our findings regarding the heterogeneity in fetal growth velocity will aid in the comprehensive understanding of fetal development quality.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Engineered T cell receptor (TCR)-expressing T (TCR-T) cells are intended to drive strong anti-tumor responses upon recognition of the specific cancer antigen, resulting in rapid expansion in the ...number of TCR-T cells and enhanced cytotoxic functions, causing cancer cell death. However, although TCR-T cell therapy against cancers has shown promising results, it remains difficult to predict which patients will benefit from such therapy. We develop a mathematical model to identify mechanisms associated with an insufficient response in a mouse cancer model. We consider a dynamical system that follows the population of cancer cells, effector TCR-T cells, regulatory T cells (Tregs), and “non-cancer-killing” TCR-T cells. We demonstrate that the majority of TCR-T cells within the tumor are “non-cancer-killing” TCR-T cells, such as exhausted cells, which contribute little or no direct cytotoxicity in the tumor microenvironment (TME). We also establish two important factors influencing tumor regression: the reversal of the immunosuppressive TME following depletion of Tregs, and the increased number of effector TCR-T cells with antitumor activity. Using mathematical modeling, we show that certain parameters, such as increasing the cytotoxicity of effector TCR-T cells and modifying the number of TCR-T cells, play important roles in determining outcomes.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Background
Infliximab (IFX) is one of the treatments of choice for corticosteroid-refractory and corticosteroid-dependent ulcerative colitis (UC). A high serum trough level of IFX (TL) is reported to ...be associated with sustained efficacy during maintenance treatment. As part of a phase 3 randomized controlled trial of IFX in UC, we assessed the predictive value of the first TL at week 2 for short- and long-term response.
Methods
Patients received intravenous IFX 5 mg/kg or placebo at weeks 0, 2, and 6. Patients with evidence of a response by week 8 continued treatment at weeks 14 and 22. TL was measured by enzyme-linked immunosorbent assay. Post hoc analysis was then performed for TL and clinical outcomes.
Results
Clinical response rate at week 8, the primary end point, was significantly higher in the IFX group than placebo (
p
= 0.005). The incidence of adverse events between groups was similar. Week 2 TL was significantly associated with a 14-week clinical activity index (CAI) remission. In multiple logistic regression analysis, the week 2 TL-to-CAI ratio (TL/CAI, odds ratio 8.07; 95 % confidence interval 2.84–27.07,
p
< 0.001) was an independent factor correlating with 14-week CAI remission. The week 2 TL and TL/CAI were also significantly associated with 30-week mucosal healing.
Conclusions
IFX was confirmed to be effective and safe in this population. Our results suggest that the first TL at week 2, in combination with clinical evaluation, is useful for predicting both short- and long-term outcomes, allowing an earlier decision between continuing IFX or switching to other options.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ