Enhancing Prognostication and Treatment Response Evaluation in Primary CNS Lymphoma with 18F-FDG PET/CT.

BACKGROUND: The role of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) in the prognostication and response evaluation of primary central nervous system lymphoma (PCNSL) remains inadequately defined. METHODS: We conducted a retrospective analysis of 268 consecutive newly diagnosed patients with PCNSL between 2006 and 2020. Of these patients, 105 and 110 patients were included to evaluate the prognostic value of baseline and post-treatment 18F-FDG-PET/CT scans, respectively. Tumor uptake was considered positive when it exceeded that of the contralateral brain upon visual assessment. Quantitative analysis of baseline 18F-FDG-PET/CT included measurement of the maximal standardized uptake value (SUVmax), total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG). RESULTS: The median age of the 268 patients was 62 years (range: 17-85), with 55% being male. The median progression-free survival (PFS) was 24.5 months (95% confidence interval [CI], 19.9-29.1), and the median overall survival (OS) was 34.5 months (95% CI, 22.9-46.1). The average SUVmax was 15.3 ± 5.7 and the mean TMTV and TLG were 12.6 ± 13.9 cm3 and 135.0 ± 152.7 g, respectively. Patients with a baseline TMTV ≥17.0 cm3 had significantly shorter OS (12.5 vs. 74.0 months, p=0.011). Post-treatment metabolic response by 18F-FDG-PET/CT significantly predicted PFS (median: 10.5 vs. 46.0 months, p=0.001) and OS (median: 21.0 vs. 62.0 months, p=0.002), whereas anatomic response by contrast-enhanced MRI showed no statistically significant differences in PFS (p=0.130) or OS (p=0.540). CONCLUSION: Baseline TMTV and post-treatment metabolic response, as assessed by 18F-FDG-PET/CT, are significant prognostic factors in patients with PCNSL.

Clinical application of whole-genome sequencing of solid tumors for precision oncology.

Genomic alterations in tumors play a pivotal role in determining their clinical trajectory and responsiveness to treatment. Targeted panel sequencing (TPS) has served as a key clinical tool over the past decade, but advancements in sequencing costs and bioinformatics have now made whole-genome sequencing (WGS) a feasible single-assay approach for almost all cancer genomes in clinical settings. This paper reports on the findings of a prospective, single-center study exploring the real-world clinical utility of WGS (tumor and matched normal tissues) and has two primary objectives: (1) assessing actionability for therapeutic options and (2) providing clarity for clinical questions. Of the 120 patients with various solid cancers who were enrolled, 95 (79%) successfully received genomic reports within a median of 11 working days from sampling to reporting. Analysis of these 95 WGS reports revealed that 72% (68/95) yielded clinically relevant insights, with 69% (55/79) pertaining to therapeutic actionability and 81% (13/16) pertaining to clinical clarity. These benefits include the selection of informed therapeutics and/or active clinical trials based on the identification of driver mutations, tumor mutational burden (TMB) and mutational signatures, pathogenic germline variants that warrant genetic counseling, and information helpful for inferring cancer origin. Our findings highlight the potential of WGS as a comprehensive tool in precision oncology and suggests that it should be integrated into routine clinical practice to provide a complete image of the genomic landscape to enable tailored cancer management.

Age at Menarche and Its Association With Adult-Onset Metabolic Syndrome and Related Disorders in Women: A Cross-Sectional Study of a Nationally Representative Sample Over 10 Years.

The prevalence of metabolic syndrome (MetS) as well as related social costs and efforts is increasing. The purpose of this study was to investigate the association between age at menarche and the risk of MetS, obesity, diabetes, and cardiovascular disease (CVD) in women over 30 years, using data from the Korean National Health and Nutrition Examination Survey (2010-2020). The analysis of 30 916 participants showed that early menarche (before 11 years) significantly increased the risk of obesity, diabetes, and MetS compared with the median age of 14 years. Late menarche (after 17 years) was also linked to MetS and related disorders. The relationship between age at menarche (at <10 years and >19 years) and the risk of MetS and related disorders exhibited a reversed J-shaped (し) pattern characterized by a pronounced increased risk among those who experience early menarche, whereas the increased risk associated with late menarche was less consistent. These results will help to decrease the risk of MetS and related disorders by enabling early intervention in early and late menarche age groups.

Assessment of imaging risks for recurrence after stereotactic radiosurgery for brain metastases (IRRaS-BM).

BACKGROUND: The identification of viable tumors and radiation necrosis after stereotactic radiosurgery (SRS) is crucial for patient management. Tumor habitat analysis involving the grouping of similar voxels can identify subregions that share common biology and enable the depiction of areas of tumor recurrence and treatment-induced change. This study aims to validate an imaging biomarker for tumor recurrence after SRS for brain metastasis by conducting tumor habitat analysis using multi-parametric MRI. METHODS: In this prospective study (NCT05868928), patients with brain metastases will undergo multi-parametric MRI before SRS, and then follow-up MRIs will be conducted every 3 months until 24 months after SRS. The multi-parametric MRI protocol will include T2-weighted and contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. Using k-means voxel-wise clustering, this study will define three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) on T1- and T2-weighted images and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable) on apparent diffusion coefficient maps and cerebral blood volume maps. Using RANO-BM criteria as the reference standard, via Cox proportional hazards analysis, the study will prospectively evaluate associations between parameters of the tumor habitats and the time to recurrence. The DICE similarity coefficients between the recurrence site and tumor habitats will be calculated. DISCUSSION: The tumor habitat analysis will provide an objective and reliable measure for assessing tumor recurrence from brain metastasis following SRS. By identifying subregions for local recurrence, our study could guide the next therapeutic targets for patients after SRS. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov (NCT05868928).

Diagnostic and prognostic implications of bacteremia in patients with complicated pleural infection.

Objectives: The clinical significance of bacteremia in patients with complicated pleural infection is still uncertain. We aimed to examine the incidence and clinical significance of bacteremia in patients with complicated pleural infection. Methods: This retrospective study comprised of consecutive patients who received pleural drainage due to complicated parapneumonic effusion or empyema. The clinical, laboratory, and radiologic data and clinical outcome were compared between patients with and without bacteremia. Additionally, the factors associated with overall mortality were evaluated in these patients. Results: Of 341 patients included in the analysis, 25 (7 %) had a positive blood culture. Blood culture testing added 2 % identification of causative pathogen compared to pleural fluid culture alone. By multivariable analysis, radiologic features of cavitary lesion, a RAPID score≥5, and a positive microbial culture in pleural fluid were independently associated with bacteremia. Despite these clinical distinctions, there was ultimately no significant difference in in-hospital mortality between patients with and without bacteremia (3 vs. 4 %, p=1.0). The only factor significantly associated with overall mortality among patients with complicated pleural infections was a higher RAPID score [HR=1.96 (95 % CI=1.35-2.84)]. Conclusions: The rate of bacteremia in patients with complicated pleural infection was 7 %. Blood culture testing demonstrated limited diagnostic yield and had minimal impact on clinical outcomes compared to pleural fluid culture. Therefore, it seems that blood culture testing is more advantageous for specific patients with suspected pleural infection who have cavitary lesions or a RAPID score≥5.

Aster × chusanensis Growth and Phenolic Acid Composition under Different Cultivation Temperatures.

Plants of the Asteraceae family have been cultivated worldwide for economic, medicinal, and ornamental purposes, including genera such as Aster, Helianthus, and Cosmos. Numerous studies examined their secondary metabolites; however, those of Aster × chusanensis, which is a natural hybrid species in South Korea, are unclear, and optimized propagation methods should be identified. We analyzed phenolic acid concentrations in each part of Aster × chusanensis through HPLC. Further, we investigated the growth characteristics and secondary metabolite concentrations under various growth temperatures using division propagation, followed by growing at 20, 25, and 30 °C in a growth chamber. Chlorogenic acid was the primary compound, which was particularly high in the leaves. The growth characteristics did not differ significantly between temperatures, and 30 °C was most efficient for phenolic acid biosynthesis. Our results provide valuable information on optimized propagation and secondary metabolite concentrations under different temperatures of Aster × chusanensis.

Incorporating Supramaximal Resection into Survival Stratification of IDH-Wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis.

PURPOSE: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. EXPERIMENTAL DESIGN: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared to a previous RTOG RPA model. RESULTS: In the developmental cohort, the RPA model included age, MGMTp methylation status, KPS, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis (class I: median overall survival [OS] 57.3 months), while low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared to the previous RTOG RPA model. CONCLUSIONS: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology.

OBJECTIVE: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). MATERIALS AND METHODS: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. RESULTS: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. CONCLUSION: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

The tidyomics ecosystem: enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

The tidyomics ecosystem: Enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.

Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability.

BACKGROUND AND OBJECTIVES: To develop a clinically reliable deep learning model to differentiate glioblastoma (GBM) from solitary brain metastasis (SBM) by providing predictive uncertainty estimates and interpretability. METHODS: A total of 469 patients (300 GBM, 169 SBM) were enrolled in the institutional training set. Deep ensembles based on DenseNet121 were trained on multiparametric MRI. The model performance was validated in the external test set consisting of 143 patients (101 GBM, 42 SBM). Entropy values for each input were evaluated for uncertainty measurement; based on entropy values, the datasets were split to high- and low-uncertainty groups. In addition, entropy values of out-of-distribution (OOD) data from unknown class (257 patients with meningioma) were compared to assess uncertainty estimates of the model. The model interpretability was further evaluated by localization accuracy of the model. RESULTS: On external test set, the area under the curve (AUC), accuracy, sensitivity and specificity of the deep ensembles were 0.83 (95 % confidence interval [CI] 0.76-0.90), 76.2 %, 54.8 % and 85.2 %, respectively. The performance was higher in the low-uncertainty group than in the high-uncertainty group, with AUCs of 0.91 (95 % CI 0.83-0.98) and 0.58 (95 % CI 0.44-0.71), indicating that assessment of uncertainty with entropy values ascertained reliable prediction in the low-uncertainty group. Further, deep ensembles classified a high proportion (90.7 %) of predictions on OOD data to be uncertain, showing robustness in dataset shift. Interpretability evaluated by localization accuracy provided further reliability in the "low-uncertainty and high-localization accuracy" subgroup, with an AUC of 0.98 (95 % CI 0.95-1.00). CONCLUSIONS: Empirical assessment of uncertainty and interpretability in deep ensembles provides evidence for the robustness of prediction, offering a clinically reliable model in differentiating GBM from SBM.

Development of a Simple Scoring System for Predicting Discharge Safety from the Medical ICU to Low-Acuity Wards: The Role of the Sequential Organ Failure Assessment Score, Albumin, and Red Blood Cell Distribution Width.

Despite advancements in artificial intelligence-based decision-making, transitioning patients from intensive care units (ICUs) to low-acuity wards is challenging, especially in resource-limited settings. This study aimed to develop a simple scoring system to predict ICU discharge safety. We retrospectively analyzed patients admitted to a tertiary hospital's medical ICU (MICU) between July 2016 and December 2021. This period was divided into two phases for model development and validation. We identified risk factors associated with unexpected death within 14 days of MICU discharge and developed a predictive scoring system that incorporated these factors. We verified the system's performance using validation data. In the development cohort, 522 patients were discharged from the MICU, and 42 (8.04%) died unexpectedly. In multivariate analysis, the Sequential Organ Failure Assessment (SOFA) score (odds ratio [OR] 1.26, 95% confidence interval [CI] 1.13-1.41), red blood cell distribution width (RDW) (OR 1.20, 95% CI 1.07-1.36), and albumin (OR 0.37, 95% CI 0.16-0.84) were predictors of unexpected death. Each variable was assigned a weighted point in the scoring system, and the area under the curve (AUC) was 0.788 (95% CI 0.714-0.855). The scoring system was performed using an AUC of 0.738 (95% CI 0.653-0.822) in the validation cohort of 343 patients with 9.62% of unexpected deaths. When a cut-off of 0.032 was applied, a sensitivity and a specificity of 81.8% and 55.2%, respectively, were achieved. This simple bedside predictive score for ICU discharge uses the SOFA score, albumin level, and RDW to aid in timely decision-making and optimize critical care facility allocation in resource-limited settings.

The Association between Low Fetal Fraction of Non-Invasive Prenatal Testing and Adverse Pregnancy Outcomes for Placental Compromise.

(1) Background: Non-invasive prenatal testing (NIPT) is a screening test for fetal aneuploidy using cell-free fetal DNA. The fetal fragments (FF) of cell-free DNA (cfDNA) are derived from apoptotic trophoblast of the placenta. The level of fetal cfDNA is known to be influenced by gestational age, multiple pregnancies, maternal weight, and height. (2) Methods: This study is a single-center retrospective observational study which examines the relationship between the fetal fraction (FF) of cell-free DNA in non-invasive prenatal testing (NIPT) and adverse pregnancy outcomes in singleton pregnancies. A total of 1393 samples were collected between 10 weeks and 6 days, and 25 weeks and 3 days of gestation. (3) Results: Hypertensive disease of pregnancy (HDP) occurred more frequently in the low FF group than the normal FF group (5.17% vs. 1.91%, p = 0.001). Although the rates of small for gestational age (SGA) and placental abruption did not significantly differ between groups, the composite outcome was significantly higher in the low FF group (7.76% vs. 3.64%, p = 0.002). Furthermore, women who later experienced complications such as HDP or gestational diabetes mellitus (GDM) had significantly lower plasma FF levels compared to those without complications (p < 0.001). After adjustments, the low FF group exhibited a significantly higher likelihood of placental compromise (adjusted odds ratio: 1.946). (4) Conclusions: Low FF in NIPT during the first and early second trimesters is associated with adverse pregnancy outcomes, particularly HDP, suggesting its potential as a predictive marker for such outcomes.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals.

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

The effect of inhaler prescription on the development of lung cancer in COPD: a nationwide population-based study.

BACKGROUND: COPD is associated with the development of lung cancer. A protective effect of inhaled corticosteroids (ICS) on lung cancer is still controversial. Hence, this study investigated the development of lung cancer according to inhaler prescription and comorbidties in COPD. METHODS: A retrospective cohort study was conducted based on the Korean Health Insurance Review and Assessment Service database. The development of lung cancer was investigated from the index date to December 31, 2020. This cohort included COPD patients (≥ 40 years) with new prescription of inhalers. Patients with a previous history of any cancer during screening period or a switch of inhaler after the index date were excluded. RESULTS: Of the 63,442 eligible patients, 39,588 patients (62.4%) were in the long-acting muscarinic antagonist (LAMA) and long-acting ß2-agonist (LABA) group, 22,718 (35.8%) in the ICS/LABA group, and 1,136 (1.8%) in the LABA group. Multivariate analysis showed no significant difference in the development of lung cancer according to inhaler prescription. Multivariate analysis, adjusted for age, sex, and significant factors in the univariate analysis, demonstrated that diffuse interstitial lung disease (DILD) (HR = 2.68; 95%CI = 1.86-3.85), a higher Charlson Comorbidity Index score (HR = 1.05; 95%CI = 1.01-1.08), and two or more hospitalizations during screening period (HR = 1.19; 95%CI = 1.01-1.39), along with older age and male sex, were independently associated with the development of lung cancer. CONCLUSION: Our data suggest that the development of lung cancer is not independently associated with inhaler prescription, but with coexisting DILD, a higher Charlson Comorbidity Index score, and frequent hospitalization.

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Advanced Immunomodulatory Biomaterials for Therapeutic Applications.

The multifaceted biological defense system modulating complex immune responses against pathogens and foreign materials plays a critical role in tissue homeostasis and disease progression. Recently developed biomaterials that can specifically regulate immune responses, nanoparticles, graphene, and functional hydrogels have contributed to the advancement of tissue engineering as well as disease treatment. The interaction between innate and adaptive immunity, collectively determining immune responses, can be regulated by mechanobiological recognition and adaptation of immune cells to the extracellular microenvironment. Therefore, applying immunomodulation to tissue regeneration and cancer therapy involves manipulating the properties of biomaterials by tailoring their composition in the context of the immune system. This review provides a comprehensive overview of how the physicochemical attributes of biomaterials determine immune responses, focusing on the physical properties that influence innate and adaptive immunity. This review also underscores the critical aspect of biomaterial-based immune engineering for the development of novel therapeutics and emphasizes the importance of understanding the biomaterials-mediated immunological mechanisms and their role in modulating the immune system.

Inhibition of DAPK3 Suppresses Radiation-Induced Cellular Senescence by Activation of a PGC1α-Dependent Metabolism Pathway in Brain Endothelial Cells.

In the brain, environmental changes, such as neuroinflammation, can induce senescence, characterized by the decreased proliferation of neurons and dendrites and synaptic and vascular damage, resulting in cognitive decline. Senescence promotes neuroinflammatory disorders by senescence-associated secretory phenotypes and reactive oxygen species. In human brain microvascular endothelial cells (HBMVECs), we demonstrate that chronological aging and irradiation increase death-associated protein kinase 3 (DAPK3) expression. To confirm the role of DAPK3 in HBMVEC senescence, we disrupted DAPK3 activity using small interfering RNA (siRNA) or a dominant-negative mutant (DAPK3-P216S), which reduced cellular senescence phenotypes, as assessed by changes in tube formation, senescence-associated beta-galactosidase activity, and cell proliferation. In endothelial cells, DAPK3 promotes cellular senescence by regulating the phosphorylation and inactivation of peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC1α) via the protein kinase B pathway, resulting in the decreased expression of mitochondrial metabolism-associated genes, such as ATP5G1, BDNF, and COX5A. Our studies show that DAPK3 is involved in cellular senescence and PGC1α regulation, suggesting that DAPK3 regulation may be important for treating aging-related brain diseases or the response to radiation therapy.