Stimuli-responsive, methyl cellulose-based, interpenetrating network hydrogels: Non-covalent design, injectability, and controlled release.

This paper demonstrates the molecular design of stimuli-responsive, methyl cellulose-based, injectable hydrogels consisting of two orthogonal supramolecular networks. Rapidly injectable hydrogels that undergo autonomous gelation without permanent cross-links are crucial for biomedical applications due to minimal invasiveness, adaptability to irregular target sites, and precise spatiotemporal control. However, they often lack sufficient mechanical strength, physicochemical stability, and high biocompatibility. Herein, we develop a molecular design of a non-covalent double-network system by strategically incorporating specific host-guest cross-linking sites into a thermo-responsive network, which is reinforced by interpenetration with a cellulose-based network via their sequential formation. The resulting hydrogel, composed of non-cytotoxic materials, demonstrates high cell viability (>90 %) until its concentration of 25 mg mL-1, rapid self-healing within 1 min, suitable injection pressure (1.1 kPa), and drug release behavior controllable by heat, chemicals, or ultrasound. Therefore, the hydrogel could be loaded with diclofenac (3.5 mg mL-1), a non-steroidal anti-inflammatory drug, and treat osteoarthritis when injected into a rat knee joint, achieving results comparable to those in a control group without osteoarthritis. This system thus holds promise for the delivery of various drugs as a responsive vector, offering synergistic effects via the inclusion of functional polymeric networks or exogenous additives for bio- or environment-related applications.

Assessment of safety: In vitro reverse mutation and in vivo acute oral toxicity tests of three biomass products from amino acid-producing Corynebacterium glutamicum.

Microbial fermentation has emerged as a pivotal process for sustainable production of essential goods and chemicals. Corynebacterium glutamicum is a proficient platform organism that contributes significantly to amino acid production through microbial fermentation. Despite its recognized safety, challenges persist in efficiently biosynthesizing natural products compared with other organisms. This study evaluated the safety of biomass products from bioengineered C. glutamicum through two different toxicological studies: a bacterial reverse mutation test (AMES test) and an acute oral toxicity test in rats. Three types of dried fermentation biomass products, each engineered for the enhanced production of specific amino acids (L-lysine, L-threonine, and L-tryptophan), were examined. The tests were conducted in compliance with Organization for Economic Co-operation and Development guidelines and revealed no mutagenicity or acute toxicity at the tested doses. These findings suggest the safety of biomass products from bioengineered C. glutamicum as potential feed materials, although further toxicity studies are recommended for comprehensive evaluation. This study underscores the importance of stringent safety assessments for advancing biotechnological applications and provides valuable insights into the potential utilization of microbial fermentation products in various industries. Moreover, this study highlights the significance of regulatory compliance and adherence to international standards to ensure the safety and efficacy of novel biotechnological products.

Molecular detection and genomic characterization of Samak Micromys paramyxovirus-1 and -2 in Micromys minutus, Republic of Korea.

BACKGROUND: The discovery of viruses in small mammalian populations, particularly rodents, has expanded the family Paramyxoviridae. The overlap in habitats between rodents and humans increases the risk of zoonotic events, underscoring the importance of active surveillance. Rodent species, such as Apodemus agrarius, are natural hosts for Paramyxoviridae in the Republic of Korea (ROK). However, it is unknown whether Paramyxoviridae is present in Micromys minutus, another common rodent. METHOD: Here, we screened M. minutus collected from the Gangwon Province in the ROK for paramyxoviruses using nested polymerase chain reaction and confirm positive samples by next-generation metagenomic sequencing. Complete paramyxovirus genomes were further characterized by phylogenetic analysis, amino acid similarity, secondary structure, and cophylogeny. RESULT: Overall, 57 of 145 (39.3%) M. minutus kidney samples tested positive for paramyxoviruses. Among them, four whole genome sequences were identified and clustered within the genus Jeilongvirus. One sequence was determined as Samak Micromys paramyxovirus 1 (SMPV-1; 19,911 nucleotides long) and three sequences as Samak Micromys paramyxovirus 2 (SMPV-2; 18,199 nucleotides long). SMPV-1 has a smaller hydrophobic gene and a longer glycoprotein gene than SMPV-2. Cophylogenetic analysis suggests that SMPV-1 evolved through co-divergence, whereas SMPV-2 was inferred to have undergone transfer events. CONCLUSION: These findings highlight the prevalence of paramyxoviruses in the wild and the potential of M. minutus as a natural viral reservoir. The discovery of SMPV-1 and SMPV - 2 also reveals the genetic diversity and evolutionary history of the genus Jeilongvirus in the Paramyxoviridae.

Participatory science methods to monitor water quality and ground truth remote sensing of the Chesapeake Bay.

Measurements by volunteer scientists using participatory science methods in combination with high resolution remote sensing can improve our ability to monitor water quality changes in highly vulnerable and economically valuable nearshore and estuarine habitats. In the Chesapeake Bay (USA), tidal tributaries are a focus of watershed and shoreline management efforts to improve water quality. The Chesapeake Water Watch program seeks to enhance the monitoring of tributaries by developing and testing methods for volunteer scientists to easily measure chlorophyll, turbidity, and colored dissolved organic matter (CDOM) to inform Bay stakeholders and improve algorithms for analogous remote sensing (RS) products. In the program, trained volunteers have measured surface turbidity using a smartphone app, HydroColor, calibrated with a photographer's gray card. In vivo chlorophyll and CDOM fluorescence were assessed in surface samples with hand-held fluorometers (Aquafluor) located at sample processing "hubs" where volunteers drop off samples for same day processing. In validation samples, HydroColor turbidity and Aquafluor in vivo chlorophyll and CDOM fluorescence were linear estimators of standard analytical measures of turbidity, chlorophyll and CDOM, respectively, with R2 values ranging from 0.65 to 0.85. Updates implemented in a new version (v2) of HydroColor improved the precision of estimates. These methods are being used for both repeat sampling at fixed sites of interest and ad-hoc "blitzes" to synoptically sample tributaries all around the Bay in coordination with satellite overpasses. All data is accessible on a public database (serc.fieldscope.org) and can be a resource to monitor long-term trends in the tidal tributaries as well as detect and diagnose causes of events of concern such as algal blooms and storm-induced reductions in water clarity.

Plant disease recognition datasets in the age of deep learning: challenges and opportunities.

Although plant disease recognition has witnessed a significant improvement with deep learning in recent years, a common observation is that current deep learning methods with decent performance tend to suffer in real-world applications. We argue that this illusion essentially comes from the fact that current plant disease recognition datasets cater to deep learning methods and are far from real scenarios. Mitigating this illusion fundamentally requires an interdisciplinary perspective from both plant disease and deep learning, and a core question arises. What are the characteristics of a desired dataset? This paper aims to provide a perspective on this question. First, we present a taxonomy to describe potential plant disease datasets, which provides a bridge between the two research fields. We then give several directions for making future datasets, such as creating challenge-oriented datasets. We believe that our paper will contribute to creating datasets that can help achieve the ultimate objective of deploying deep learning in real-world plant disease recognition applications. To facilitate the community, our project is publicly available at https://github.com/xml94/PPDRD with the information of relevant public datasets.

TNF Promoter Hypomethylation Is Associated With Mucosal Inflammation in IBD and Anti-TNF Response.

Background and Aims: Inflammatory bowel diseases (IBDs) are chronic inflammatory conditions influenced heavily by environmental factors. DNA methylation is a form of epigenetic regulation linking environmental stimuli to gene expression changes and inflammation. Here, we investigated how DNA methylation of the tumor necrosis factor (TNF) promoter differs between inflamed and uninflamed mucosa of IBD patients, including anti-TNF responders and nonresponders. Methods: We obtained mucosal biopsies from 200 participants (133 IBDs and 67 controls) and analyzed TNF promoter methylation using bisulfite sequencing, comparing inflamed with uninflamed segments, in addition to paired inflamed/uninflamed samples from individual patients. We conducted similar analyses on purified intestinal epithelial cells from bowel resections. We also compared TNF methylation levels of inflamed and uninflamed mucosa from a separate cohort of 15 anti-TNF responders and 17 nonresponders. Finally, we sequenced DNA methyltransferase genes to identify rare variants in IBD patients and functionally tested them using rescue experiments in a zebrafish genetic model of DNA methylation deficiency. Results: TNF promoter methylation levels were decreased in inflamed mucosa of IBD patients and correlated with disease severity. Isolated intestinal epithelial cells from inflamed tissue showed proportional decreases in TNF methylation. Anti-TNF nonresponders showed lower levels of TNF methylation than responders in uninflamed mucosa. Our sequencing analysis revealed 2 missense variants in DNA methyltransferase 1, 1 of which had reduced function in vivo. Conclusion: Our study reveals an association of TNF promoter hypomethylation with mucosal inflammation, suggesting that IBD patients may be particularly sensitive to inflammatory environmental insults affecting DNA methylation. Together, our analyses indicate that TNF promoter methylation analysis may aid in the characterization of IBD status and evaluation of anti-TNF therapy response.

Association between fatty liver index and cardiometabolic multimorbidity: evidence from the cross-sectional national health and nutrition examination survey.

Background: Metabolic dysfunction associated steatotic liver disease (MASLD) contributes to the cardiometabolic diseases through multiple mechanisms. Fatty liver index (FLI) has been formulated as a non-invasive, convenient, and cost-effective approach to estimate the degree of MASLD. The current study aims to evaluate the correlation between FLI and the prevalent cardiometabolic multimorbidity (CMM), and to assess the usefulness of FLI to improve the detection of the prevalent CMM in the general population. Methods: 26,269 subjects were enrolled from the National Health and Nutrition Examination Survey 1999-2018. FLI was formulated based on triglycerides, body mass index, γ -glutamyltransferase, and waist circumference. CMM was defined as a history of 2 or more of diabetes mellitus, stroke, myocardial infarction. Results: The prevalence of CMM was 10.84%. With adjustment of demographic, anthropometric, laboratory, and medical history covariates, each standard deviation of FLI leaded to a 58.8% risk increase for the prevalent CMM. The fourth quartile of FLI had a 2.424 times risk for the prevalent CMM than the first quartile, and a trend towards higher risk was observed. Smooth curve fitting showed that the risk for prevalent CMM increased proportionally along with the elevation of FLI. Subgroup analysis demonstrated that the correlation was robust in several conventional subpopulations. Receiver-operating characteristic curve analysis revealed an incremental value of FLI for detecting prevalent CMM when adding it to conventional cardiometabolic risk factors (Area under the curve: 0.920 vs. 0.983, P < 0.001). Results from reclassification analysis confirmed the improvement from FLI. Conclusion: Our study demonstrated a positive, linear, and robust correlation between FLI and the prevalent CMM, and our findings implicate the potential usefulness of FLI to improve the detection of prevalent CMM in the general population.

Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research.

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 µg/m3, 34 %, Secondary sulfate: 5.67 µg/m3, 22 %, Motor vehicle: 1.83 µg/m3, 7.2 %, Biomass burning: 2.30 µg/m3, 9.1 %, Residual oil combustion: 1.66 µg/m3, 6.5 %, Industry: 2.15 µg/m3, 8.5 %, Incinerator: 1.39 µg/m3, 5.5 %, Coal combustion: 0.363 µg/m3, 1.4 %, Road dust/soil: 0.941 µg/m3, 3.7 %, Aged sea salt: 0.356 µg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 µg/m3, 28 %, Sulfate: 8.27 µg/m3, 18 %, Motor vehicle: 3.77 µg/m3, 8.4 %, Biomass burning: 2.70 µg/m3, 6.0 %, Incinerator: 4.50 µg/m3, 10 %, Coal combustion: 3.52 µg/m3, 7.8 %, Industry: 5.01 µg/m3, 11 %, Road dust/soil: 2.92 µg/m3, 6.5 %, Aged sea salt: 1.63 µg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Universal health coverage saves more lives among severely ill COVID-19 patients: A difference-in-differences analysis of individual patient data in South Korea.

BACKGROUND: Universal health coverage (UHC) ensures affordability of a variety of essential health services for the general population. Although UHC could mitigate the harmful effects of coronavirus disease 2019 (COVID-19) on patients and their socioeconomic position, the debate on UHC's scope and ability to improve health outcomes is ongoing. This study aimed to identify the impact of UHC policy withdrawal on the health outcomes of South Korea's severely ill COVID-19 patients. METHODS: We used a propensity score matching (PSM) and difference-in-differences combined model. This study's subjects were 44,552 hospitalized COVID-19 patients contributing towards health insurance claims data, COVID-19 notifications and vaccination data extracted from the National Health Information Database and the Korea Disease Control and Prevention Agency from 1 December 2020 to 30 April 2022. After PSM, 2460 patients were included. This study's exposures were severity of illness and UHC policy change. The primary outcome was the case fatality rate (CFR) for COVID-19, which was defined as death within 30 days of a COVID-19 diagnosis. There were four secondary outcomes, including time interval between diagnosis and hospitalization (days), length of stay (days), total medical expenses (USD) and the time interval between diagnosis and death (days). RESULTS: After the UHC policy's withdrawal, the severely ill patients' CFR increased to 284 per 1000 patients [95% confidence interval (CI) 229.1-338.4], hospitalization days decreased to 9.61 days (95% CI -11.20 to -8.03) and total medical expenses decreased to 5702.73 USD (95% CI -7128.41 to -4202.01) compared with those who were not severely ill. CONCLUSIONS: During the pandemic, UHC may have saved the lives of severely ill COVID-19 patients; therefore, expanding services and financial coverage could be a crucial strategy during public health crises.

Cysteine-rich 61 inhibition attenuates hepatic insulin resistance and improves lipid metabolism in high-fat diet fed mice and HepG2 cells.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is strongly associated with insulin resistance development. Hepatic lipid accumulation and inflammation are considered the main drivers of hepatic insulin resistance in MASLD. Cysteine-rich 61 (Cyr61 also called CCN1), a novel secretory matricellular protein, is implicated in liver inflammation, and its role in MASLD is not clearly understood. Therefore, we investigated the role of Cyr61 in hepatic insulin resistance and lipid metabolism as major factors in MASLD pathogenesis. In high-fat diet (HFD)-fed C57BL/6J mice, Cyr61 was downregulated or upregulated via viral transduction. Measurements of glucose homeostasis, histological assessment of liver tissues, and gene expression and signaling pathways of lipogenesis, fatty acid oxidation, and inflammation were performed using liver samples from these mice. Cyr61 levels in HepG2 cells were reduced using RNAi-mediated gene knockdown. Inflammation and insulin resistance were evaluated using real-time polymerase chain reaction and western blotting. HFD/AAV-shCyr61 mice exhibited enhanced glucose tolerance via the protein kinase B pathway, reduced hepatic inflammation, decreased lipogenesis, and increased fatty acid oxidation. Notably, HFD/AAV-shCyr61 mice showed elevated protein expression of sirtuin 6 and phosphorylated-AMP-activated protein kinase. In vitro experiments demonstrated that inhibition of Cyr61 downregulated pro-inflammatory cytokines such as interleukin-1 beta, IL-6, and tumor necrosis factor-alpha via the nuclear factor kappa B/c-Jun N-terminal kinase pathway, and alleviated insulin resistance. Cyr61 affected hepatic inflammation, lipid metabolism, and insulin resistance. Inhibition of Cyr61 reduced inflammation, recovered insulin resistance, and altered lipid metabolism in vivo and in vitro. Therefore, Cyr61 is a potential therapeutic target in MASLD.

White matter microstructural integrity as a key to effective propagation of gamma entrainment in humans.

Gamma entrainment through sensory stimulation has the potential to reduce the pathology of Alzheimer's disease in mouse models. However, clinical trials in Alzheimer's disease (AD) patients have yielded inconsistent results, necessitating further investigation. This single-center pre-post intervention study aims to explore the influence of white matter microstructural integrity on gamma rhythm propagation from the visual cortex to AD-affected regions in 31 cognitively normal volunteers aged ≥ 65. Gamma rhythm propagation induced by optimal FLS was measured. Diffusion tensor imaging was employed to assess the integrity of white matter tracts of interest. After excluding 5 participants with a deficit in steady-state visually evoked potentials, 26 participants were included in the final analysis. In the linear regression analyses, gamma entrainment was identified as a significant predictor of gamma propagation (p < 0.001). Furthermore, the study identified white matter microstructural integrity as a significant predictor of gamma propagation by flickering light stimulation (p < 0.05), which was specific to tracts that connect occipital and temporal or frontal regions. These findings indicate that, despite robust entrainment of gamma rhythms in the visual cortex, their propagation to other regions may be impaired if the microstructural integrity of the white matter tracts connecting the visual cortex to other areas is compromised. Consequently, our findings have expanded our understanding of the prerequisites for effective gamma entrainment and suggest that future clinical trials utilizing visual stimulation for gamma entrainment should consider white matter tract microstructural integrity for candidate selection and outcome analysis.

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.

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.

[MR Imaging Features of Pediatric Bone Marrow]. / 소아 골수의 MR 영상 소견.

MRI plays a crucial role in bone marrow (BM) assessment, and has very high sensitivity in diagnosing marrow disorders. However, for radiologists who may not frequently encounter pediatric imaging, distinguishing pathologic BM lesion from normal BM can be challenging. Conditions involving the BM in pediatric patients, such as leukemia and metastatic neuroblastoma, often manifest with diverse musculoskeletal symptoms and may be diagnosed using musculoskeletal MRI examinations. Accurate interpretation of pediatric MRI requires not only an understanding of the normal composition of BM but also an awareness of agerelated developmental changes in the marrow and familiarity with conditions that commonly involve pediatric BM. We aim to describe the composition of normal BM and outline the normal and abnormal MRI findings in pediatric BM. Additionally, we aim to present clinical cases of malignant BM disorders including leukemia, neuroblastoma metastasis, and other malignant BM disorders.

Detection of EGFR exon 20 insertion mutations in non-small cell lung cancer: implications for consistent nomenclature in precision medicine.

Epidermal growth factor receptor (EGFR) exon 20 insertion mutations (E20ins) are the third most frequent mutations observed in non-small cell lung cancer, accounting for approximately 1-10% of all EGFR mutations. In the era of precision medicine and targeted therapies, consistent naming of genetic alterations is crucial to avoid confusion and errors. However, the annotation of EGFR E20ins mutations has been inconsistent, leading to confusion in the scientific literature and product documentation. In this study, our primary objective was to investigate the usage of different annotation related to EGFR E20ins in independent studies. Additionally, we assessed the distribution of EGFR E20ins mutations and estimated the detection coverage expected from each available EGFR E20ins detection assay. A total of 1,418 EGFR E20ins mutations were collected from six studies (FoundationInsights, Geneseeq Technology Inc, mobocertinib phase I/II trial, poziotinib phase II trial, sunvozertinib phase I trial, and Samsung Medical Center) and reorganised according to Human Genome Variation Society (HGVS) nomenclature. Our analysis revealed that the majority of EGFR E20ins mutations requiring correction were 'insertion' or 'deletion-insertion', which should be appropriately designated as 'duplication'. Additionally, duplicated variants were reported using different annotations in each study, and furthermore, even identical variant sequences were annotated differently within the same study. In all six studies, p.A767_V769dup and p.S768_D770dup were the most frequently observed EGFR E20ins. The Oncomine Dx Target Test showed the highest patient coverage at 77.2%, followed by the Droplex EGFR Mutation Test v2 with a patient coverage of 70.5% for EGFR E20ins patients. To ensure comprehensive coverage in real-world settings, it is essential to standardise the annotations for each variant, for example using the HGVS nomenclature. The accurate classification and analysis of drug responsiveness in EGFR E20ins necessitate consideration of the nomenclature, particularly with respect to the locations where the actual mutations occur.

The Analysis of in vitro Fertilization Outcomes after Fertility-Preserving Therapy for Endometrial Hyperplasia or Carcinoma.

OBJECTIVES: This study aimed to evaluate the clinical efficacy of fertility-preserving therapy through in vitro fertilization (IVF) procedures in women who were pathologically diagnosed with endometrial hyperplasia or carcinoma. DESIGN: A retrospective cohort study on fertility-preserving therapy was conducted. Participants/Materials, Setting: A total of 82 women were enrolled who had simple endometrial hyperplasia (SH), complex hyperplasia (CH), complex atypical hyperplasia (CAH), and endometrioid endometrial carcinoma stage IA (EC IA) and underwent IVF at Gangnam CHA fertility center between January 2008 and December 2020. METHODS: The primary endpoints were oncologic outcomes and subsequent reproductive outcomes of patients who underwent fertility-preserving treatments analyzed by χ2 test or Fisher's exact test. RESULTS: Of the 82 patients, 33 had a cumulative clinical pregnancy (40.2%), and 25 had a cumulative live birth (30.5%) through IVF procedures following pathologic confirmation of complete remission or non-progressive status. The cumulative clinical pregnancy rates and live birth rates for SH were 50.0% and 30.0%, for CH were 37.8% and 28.9%, for CAH were 25.0% and 25.0%, and for EC were 38.5% and 38.5%, respectively. There were no significant differences in cumulative clinical pregnancy rates or live birth rates when comparing the four groups. There was a difference in endometrial thickness between medroxyprogesterone acetate (MPA) treatment group and intrauterine device (IUD) group (p = 0.036); however, there were no significant differences in clinical pregnancy rates among MPA, IUD, and MPA+IUD groups. LIMITATIONS: Because of the retrospective nature of the study, many factors relevant to the treatment decision were not strictly controlled. CONCLUSIONS: All endometrial hyperplasia and carcinoma groups had competent cumulative live birth rates by IVF procedures. There may be differences in endometrial thickness depending on the treatment methods, but this does not affect clinical pregnancy rates. Therefore, the fertility-preserving treatment for endometrial hyperplasia and carcinoma is a safe and feasible method that results in good IVF outcomes.

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.

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.

Is replacing missing values of PM2.5 constituents with estimates using machine learning better for source apportionment than exclusion or median replacement?

East Asian countries have been conducting source apportionment of fine particulate matter (PM2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved.