Deep Learning Assisted Classification of T1ρ-MR Based Intervertebral Disc Degeneration Phases.

BACKGROUND: According to the T1ρ value of nucleus pulposus, our previous study has found that intervertebral disc degeneration (IDD) can be divided into three phases based on T1ρ-MR, which is helpful for the selection of biomaterial treatment timing. However, the routine MR sequences for patients with IDD are T1- and T2-MR, T1ρ-MR is not commonly used due to long scanning time and extra expenses, which limits the application of T1ρ-MR based IDD phases. PURPOSE: To build a deep learning model to achieve the classification of T1ρ-MR based IDD phases from routine T1-MR images. STUDY TYPE: Retrospective. POPULATION: Sixty (M/F: 35/25) patients with low back pain or lower limb radiculopathy are randomly divided into training (N = 50) and test (N = 10) sets. FIELD STRENGTH/SEQUENCES: 1.5 T MR scanner; T1-, T2-, and T1ρ-MR sequence (spin echo). ASSESSMENT: The T1ρ values of the nucleus pulposus in intervertebral discs (IVDs) were measured. IVDs were divided into three phases based on the mean T1ρ value: pre-degeneration phase (mean T1ρ value >110 msec), rapid degeneration phase (mean T1ρ value: 80-110 msec), and late degeneration phase (mean T1ρ value <80 msec). After measurement, the T1ρ values, phases, and levels of IVDs were input into the model as labels. STATISTICAL TESTS: Intraclass correlation coefficient, area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall (P < 0.05 was considered significant). RESULTS: In the test dataset, the model achieved a mean average precision of 0.996 for detecting IVD levels. The diagnostic accuracy of the T1ρ-MR based IDD phases was 0.840 and the AUC was 0.871, the average AUC of 5-folds cross validation was 0.843. DATA CONCLUSION: The proposed deep learning model achieved the classification of T1ρ-MR based IDD phases from routine T1-MR images, which may provide a method to facilitate the application of T1ρ-MR in IDD. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Association between triglyceride glucose index-related indices with gallstone disease among US adults.

BACKGROUND: Triglyceride glucose (TyG) index combined with obesity-related indicators [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist to height ratio (TyG-WHtR), triglyceride glucose-waist circumference (TyG-WC)], represents emerging methodologies for assessing insulin resistance. The objective of this investigation was to explore the correlation between TyG-related indices and gallstone disease. METHODS: The study included 3740 adults from the 2017-2020 period of the National Health and Nutrition Examination Survey. TyG-BMI, TyG-WC, and TyG-WHtR were integrated as both continuous and categorical variables within the multivariate logistic model, respectively to evaluate the connection between various TyG-related indices and gallstone disease. Additionally, restriction cubic splines and subgroup analysis were employed to deepen our understanding of this relationship. RESULTS: When analyzed as continuous variables, positive correlations were observed between TyG-BMI, TyG-WC, TyG-WHtR and gallstone disease. The OR(95%CI) were 1.063(1.045,1.082) for TyG-BMI (per 10-unit), 1.026(1.018,1.034) for TyG-WC (per 10-unit) and 1.483(1.314,1.676) for TyG-WHtR (per 1-unit), respectively. When categorized into quartiles, these three TyG-related indices still show statistically significant associations with gallstone disease. Descending in order, the diagnostic capability for gallstone disease is demonstrated as follows: TyG-WHtR (AUC = 0.667), TyG-BMI (AUC = 0.647), and TyG-WC (AUC = 0.640). CONCLUSION: There were significantly positive associations between TyG-related indices, including TyG-BMI, TyG-WC, and TyG-WHtR, and gallstone disease. Of these indices, TyG-WHtR demonstrated the most favorable performance in identifying the risk of gallstone disease.

N-glycosylation on hemagglutinin head reveals inter-branch antigenic variability of avian influenza virus H5-subtypes.

H5-subtype avian influenza virus (AIV) is globally prevalent and undergoes frequent antigenic drift, necessitating regular updates to vaccines. One of the many influencing elements that cause incompatibility between vaccinations and epidemic strains is the dynamic alteration of glycosylation sites. However, the biological significance of N-glycosylation in the viral evolution and antigenic changes is unclear. Here, we performed a systematic analysis of glycosylation sites on the HA1 subunit of H5N1, providing insights into the changes of primary glycosylation sites, including 140 N, 156 N, and 170 N within the antigenic epitopes of HA1 protein. Multiple recombinant viruses were then generated based on HA genes of historical vaccine strains and deactivated for immunizing SPF chickens. Inactivated recombinant strains showed relatively closer antigenicity compared to which has identical N-glycosylation patterns. The N-glycosylation modification discrepancy highlights the inter-branch antigenic diversity of H5-subtype viruses in avian influenza and serves as a vital foundation for improving vaccination tactics.

Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis.

Conventional approaches to dietary assessment are primarily grounded in self-reporting methods or structured interviews conducted under the supervision of dietitians. These methods, however, are often subjective, potentially inaccurate, and time-intensive. Although artificial intelligence (AI)-based solutions have been devised to automate the dietary assessment process, prior AI methodologies tackle dietary assessment in a fragmented landscape (e.g., merely recognizing food types or estimating portion size), and encounter challenges in their ability to generalize across a diverse range of food categories, dietary behaviors, and cultural contexts. Recently, the emergence of multimodal foundation models, such as GPT-4V, has exhibited transformative potential across a wide range of tasks (e.g., scene understanding and image captioning) in various research domains. These models have demonstrated remarkable generalist intelligence and accuracy, owing to their large-scale pre-training on broad datasets and substantially scaled model size. In this study, we explore the application of GPT-4V powering multimodal ChatGPT for dietary assessment, along with prompt engineering and passive monitoring techniques. We evaluated the proposed pipeline using a self-collected, semi free-living dietary intake dataset comprising 16 real-life eating episodes, captured through wearable cameras. Our findings reveal that GPT-4V excels in food detection under challenging conditions without any fine-tuning or adaptation using food-specific datasets. By guiding the model with specific language prompts (e.g., African cuisine), it shifts from recognizing common staples like rice and bread to accurately identifying regional dishes like banku and ugali. Another GPT-4V's standout feature is its contextual awareness. GPT-4V can leverage surrounding objects as scale references to deduce the portion sizes of food items, further facilitating the process of dietary assessment.

Insect herbivory on woody broadleaf seedlings along a subtropical elevational gradient supports the resource concentration hypothesis.

PREMISE: Theories of plant-herbivore interactions hold that seedlings are more vulnerable to herbivory in warmer and more stable climates at lower elevations. Hypotheses of plant apparency, resource concentration, and resource availability have been proposed to explain variability in leaf herbivory. However, seasonal differences in the effects of these hypotheses on leaf herbivory on seedlings remain unclear. METHODS: We evaluated the three herbivory hypotheses by comparing the percentage and frequency of leaf herbivory in understory broadleaf seedlings in a subtropical forest in May (spring) and October (autumn) along an elevational gradient (290-1370 m a.s.l.). In total, we measured 2890 leaves across 696 seedlings belonging to 95 species and used beta regressions to test the effects of plant apparency (e.g., leaf area, seedling height), resource concentration (e.g., plant species diversity), and resource availability (e.g., canopy openness, soil available N and P) on leaf herbivory. RESULTS: Seedlings exhibited unimodal patterns of leaf herbivory along elevation, with drivers of leaf herbivory varying by the month. Variation in the frequency of leaf herbivory was best explained by the resource concentration hypothesis (e.g., plant species diversity) in both months, and herbivory was lower on seedlings in sites with higher plant diversity. Plant apparency hypothesis (e.g., leaf area, seedling height) was weakly supported only in spring, and the evidence for resource availability hypothesis (e.g., canopy openness, soil nutrients) was mixed. CONCLUSIONS: This study supports the resource concentration hypothesis and reveals the importance of seasonal difference on understanding leaf herbivory patterns and the drivers of plant diversity in subtropical forests.

Do the benefits of homeownership on mental health vary by race and poverty status? An application of doubly robust estimation for causal inference.

While empirical studies have observed that homeownership is associated with improved mental health conditions, research indicates that this relationship might vary by race. Moreover, such a White-Black disparity in the impacts of homeownership on mental health could be complexed by poverty status, as maintaining one's homeownership could be a financial burden for people living in poverty status, defined by the US official poverty threshold. We add to the existing literature by analyzing the impacts of homeownership on psychological distress, simultaneously disaggregating by race and poverty status using survey data from the Panel Study on Income Dynamics from the 2017 and 2019 waves (N = 7059). Propensity score weighting and doubly robust estimation are applied to estimate causal inference for the impact of 2017 homeownership on 2019 psychological distress using negative binomial models. First, we found the impacts of homeownership on reducing psychological distress are significant for White Americans, not for Black Americans. Second, we found such a White-Black disparity is only observable for populations not living in poverty. On the other hand, for populations living in poverty, homeownership no longer lowers psychological distress for either race. Findings suggest that financial support and mental health support are needy to address inequality in the impacts of homeownership on mental health, which could simultaneously vary by poverty status and race. Implications are discussed.

Enhancing Electrochemical Sensing through Molecular Engineering of Reduced Graphene Oxide-Solution Interfaces and Remote Floating-Gate FET Analysis.

Two-dimensional nanomaterials such as reduced graphene oxide (rGO) have captured significant attention in the realm of field-effect transistor (FET) sensors due to their inherent high sensitivity and cost-effective manufacturing. Despite their attraction, a comprehensive understanding of rGO-solution interfaces (specifically, electrochemical interfacial properties influenced by linker molecules and surface chemistry) remains challenging, given the limited capability of analytical tools to directly measure intricate solution interface properties. In this study, we introduce an analytical tool designed to directly measure the surface charge density of the rGO-solution interface leveraging the remote floating-gate FET (RFGFET) platform. Our methodology involves characterizing the electrochemical properties of rGO, which are influenced by adhesion layers between SiO2 and rGO, such as (3-aminopropyl)trimethoxysilane (APTMS) and hexamethyldisilazane (HMDS). The hydrophilic nature of APTMS facilitates the acceptance of oxygen-rich rGO, resulting in a noteworthy pH sensitivity of 56.8 mV/pH at the rGO-solution interface. Conversely, hydrophobic HMDS significantly suppresses the pH sensitivity from the rGO-solution interface, attributed to the graphitic carbon-rich surface of rGO. Consequently, the carbon-rich surface facilitates a denser arrangement of 1-pyrenebutyric acid N-hydroxysuccinimide ester linkers for functionalizing capturing probes on rGO, resulting in an enhanced sensitivity of lead ions by 32% in our proof-of-concept test.

Partnerships and collaboration drive innovative graduate training in materials informatics.

Holistic and intentional training prepares next-generation materials informatics leaders and workforce for expedited materials discovery and design.

Pt on Atomic-Layered WO3 Islands: Electronic Tuning of Platinum-Tungsten Heterostructures for Highly Efficient Low-Temperature VOC Combustion.

Adjusting the electronic state of noble metal catalysts on a nanoscale is crucial for optimizing the performance of nanocatalysts in many important environmental catalytic reactions, particularly in volatile organic compound (VOC) combustion. This study reports a novel strategy for optimizing Pt catalysts by modifying their electronic structure to enhance the electron density of Pt. The research illustrates the optimal 0.2Pt-0.3W/Fe2O3 heterostructure with atomic-thick WO3 layers as a bulking block to electronically modify supported Pt nanoparticles. Methods such as electron microscopy, X-ray photoelectron spectroscopy, and in situ Fourier transform infrared spectroscopy confirm Pt's electron-enriched state resulting from electron transfer from atomic-thick WO3. Testing for benzene oxidation revealed enhanced low-temperature activity with moderate tungsten incorporation. Kinetic and mechanistic analyses provide insights into how the enriched electron density benefits the activation of oxygen and the adsorption of benzene on Pt sites, thereby facilitating the oxidation reaction. This pioneering work on modifying the electronic structure of supported Pt nanocatalysts establishes an innovative catalyst design approach. The electronic structure-performance-dependent relationships presented in this study assist in the rational design of efficient VOC abatement catalysts, contributing to clean energy and environmental solutions.

Evolutionary dynamics and comparative pathogenicity of clade 2.3.4.4b H5 subtype avian influenza viruses, China, 2021-2022.

The recent concurrent emergence of H5N1, H5N6, and H5N8 avian influenza viruses (AIVs) has led to significant avian mortality globally. Since 2020, frequent human-animal interactions have been documented. To gain insight into the novel H5 subtype AIVs (i.e., H5N1, H5N6 and H5N8), we collected 6102 samples from various regions of China between January 2021 and September 2022, and identified 41 H5Nx strains. Comparative analyses on the evolution and biological properties of these isolates were conducted. Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b, with 13 related to H5N1, 19 to H5N6, and 9 to H5N8. Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8, exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015-2022 worldwide. H5N1 showed a higher rate of evolution in 2021-2022 and more sites under positive selection pressure in 2015-2022. The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations. Further hemagglutination inhibition assay suggested that some A(H5N1) viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains. Mammalian challenge assays demonstrated that the H5N8 virus (21GD001_H5N8) displayed the highest pathogenicity in mice, followed by the H5N1 virus (B1557_H5N1) and then the H5N6 virus (220086_H5N6), suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts. Based on the above results, we speculate that A(H5N1) viruses have a higher risk of emergence in the future. Collectively, these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b, contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs.

Perforation of barium sulfate enterography in an infant: A case report.

RATIONALE: Barium peritonitis is an inflammatory response that occurs when barium accidentally enters the abdominal cavity during a barium test. In extreme circumstances, it has the potential to harm various organs and even result in death. PATIENT CONCERNS: A 3-month-old infant was diagnosed with multiple organ failure after severe barium peritonitis. DIAGNOSIS: Multiple organ dysfunction is associated with barium peritonitis. INTERVENTIONS: The infant underwent surgical intervention and received ventilator support, anti-infection therapy, myocardial nutrition, liver and kidney protection, rehydration, circulation stabilization, and other symptomatic supportive care. OUTCOMES: The patient experienced clinical death after treatment and resuscitation was unsuccessful. LESSONS: Barium enema perforation complications are uncommon, but can lead to fatal injuries with a high mortality rate. This case highlights the importance of raising awareness among clinicians about the risks of gastroenterography in infants and children and actively preventing and avoiding similar serious complications. The mortality rate can be reduced by timely multidisciplinary consultation and joint management once a perforation occurs.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq.

BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. RESULTS: A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CONCLUSION: CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

Genome-Wide Identification of the WRKY Gene Family and Functional Characterization of CpWRKY5 in Cucurbita pepo.

The WRKY gene family is crucial for regulating plant growth and development. However, the WRKY gene is rarely studied in naked kernel formation in hull-less Cucurbita pepo L. (HLCP), a natural mutant that lacks the seed coat. In this research, 76 WRKY genes were identified through bioinformatics-based methods in C. pepo, and their phylogenetics, conserved motifs, synteny, collinearity, and temporal expression during seed coat development were analyzed. The results showed that 76 CpWRKYs were identified and categorized into three main groups (I-III), with Group II further divided into five subgroups (IIa-IIe). Moreover, 31 segmental duplication events were identified in 49 CpWRKY genes. A synteny analysis revealed that C. pepo shared more collinear regions with cucumber than with melon. Furthermore, quantitative RT-PCR (qRT-PCR) results indicated the differential expression of CpWRKYs across different varieties, with notable variations in seed coat development between HLCP and CP being attributed to differences in CpWRKY5 expression. To investigate this further, CpWRKY5-overexpression tobacco plants were generated, resulting in increased lignin content and an upregulation of related genes, as confirmed by qRT-PCR. This study offers valuable insights for future functional investigations of CpWRKY genes and presents novel information for understanding the regulation mechanism of lignin synthesis.

Preparation, evaluation and application of MRI detectable sunitinib-loaded calcium alginate/poly(acrylic acid) hydrogel microspheres.

Transcatheter arterial chemoembolization (TACE) is an effective method for the treatment of unresectable hepatocellular carcinoma. Although many embolic agents have been developed in TACE, there are few ideal embolic agents that combine drug loading, imaging properties and vessel embolization. Here, we developed novel magnetic embolic microspheres that could simultaneously load sunitinib malate (SU), be detected by magnetic resonance imaging (MRI) and block blood vessels. Calcium alginate/poly (acrylic acid) hydrogel microspheres (CA/PAA-MDMs) with superparamagnetic iron oxide nanoparticles (SPIONs) modified by citric acid were prepared by a drip and photopolymerization method. The embolization and imaging properties of CA/PAA-MDMs were evaluated through a series of experiments such as morphology, X-ray diffraction and X-ray photoelectron spectroscopy, magnetic responsiveness analysis, elasticity, cytotoxicity, hemolysis test, in vitro MRI evaluation, rabbit ear embolization and histopathology. In addition, the ability of drug loading and drug release of CA/PAA-MDMs were investigated by using sunitinib (SU) as the model drug. In conclusion, CA/PAA-MDMs showed outstanding drug loading capability, excellent imaging property and embolization effect, which would be expected to be used as a potential biodegradable embolic agent in the clinical interventional therapy.

Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?

Background: Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT. Methods: This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0-2) based on pathological tumor regression grade (pTRG). Predictive texture features were extracted from pre- and post-treatment ADC maps to construct a TA model using RandomForest. The ADC model was developed by manually measuring pre- and post-treatment ADC values and calculating their changes. Simultaneously, subjective evaluations based on magnetic resonance imaging assessment of TRG were performed by two experienced radiologists. Model performance was compared using the area under the curve (AUC) and DeLong test. Results: A total of 299 patients from two centers were divided into three cohorts: the primary cohort (center A; n = 194, with 36 non-responders and 158 responders), the internal validation cohort (center A; n = 49, with 9 non-responders) and external validation cohort (center B; n = 56, with 33 non-responders). The TA model was constructed by post_mean, mean_change, post_skewness, post_entropy, and entropy_change, which outperformed both the ADC model and subjective evaluations with an impressive AUC of 0.997 (95% confidence interval [CI], 0.975-1.000) in the primary cohort. Robust performances were observed in internal and external validation cohorts, with AUCs of 0.919 (95% CI, 0.805-0.978) and 0.938 (95% CI, 0.840-0.985), respectively. Conclusions: The TA model has the potential to serve as an imaging biomarker for identifying nonresponse to NCT in LARC patients, providing a valuable reference for these patients considering additional radiation therapy.

Evolution and Antigenic Differentiation of Avian Influenza A(H7N9) Virus, China.

We characterized the evolution and molecular characteristics of avian influenza A(H7N9) viruses isolated in China during 2021-2023. We systematically analyzed the 10-year evolution of the hemagglutinin gene to determine the evolutionary branch. Our results showed recent antigenic drift, providing crucial clues for updating the H7N9 vaccine and disease prevention and control.

B-Type Natriuretic Peptide Inhibits the Expression and Function of SERCA2a in Heart Failure.

B-type natriuretic peptide (BNP) possesses protective cardiovascular properties; however, there has not been sufficient serious consideration of the side effects of BNP. As for sarcoplasmic/endoplasmic reticulum calcium ATPase 2a (SERCA2a), it was once considered a new target for the treatment of heart failure (HF). Nevertheless, clinical trials of SERCA2a gene therapy in HF have finally become unsuccessful. Research has found that elevated BNP levels and decreased SERCA2a expression are two important HF characteristics, which are always negatively correlated. We hypothesize that BNP inhibits SERCA2a expression and, therefore, exerts negative effects on SERCA2a expression and function.The effects of BNP on endogenous SERCA2a expression and function were tested in mice with HF induced by transverse aortic constriction and neonatal rat cardiomyocytes (NRCM). Furthermore, to verify the effects of BNP on exogenous SERCA2a gene transduction efficacy, BNP was added to the myocardium and cardiomyocytes infected with an adenovirus overexpressing SERCA2a.In vivo, BNP levels were increased, SERCA2a expression was reduced in both the BNP intervention and HF groups, and BNP reduced the overexpressed exogenous SERCA2a protein in the myocardium. Our in vitro data showed that BNP dose-dependently inhibited the total and exogenous SERCA2a expression in NRCM by activating the cGMP-dependent protein kinase G. BNP also inhibited the effects of SERCA2a overexpression on Ca2+ transience in NRCM.The expression and function of endogenous and exogenous SERCA2a are inhibited by BNP. The opposite relationship between BNP and SERCA2a should be given serious attention in the treatment of HF via BNP or SERCA2a gene therapy.

Tumor-infiltrating immune cells and survival in head and neck squamous cell carcinoma: a retrospective computational study.

The immune infiltration profiles of the tumor microenvironment have effects on the prognosis of head and neck squamous cell carcinoma (HNSCC). Whereas, HNSCC is a heterogeneous group of tumors, but past work has not taken this into consideration. Herein, we investigate the associations between survival and the function of immune cells in different tumorigenic sites of HNSCC. 1149 samples of HNSCC were collected from publicly accessible databases. Based on gene expression data, CIBERSORTx was applied to determine the proportion of 22 immune cell subpopulations. In the Cox regression model, the associations between overall survival, disease-free survival, and immune cells were examined, modeling gene expression and immune cell proportion as quartiles. Consensus cluster analysis was utilized to uncover immune infiltration profiles. Regardless of tumor sites, CD8+ T cells and activated CD4 memory T cells were associated with favorable survival, while eosinophils were the opposite. The survival of the hypopharynx, oral cavity, and larynx subsites was somewhat affected by immune cells, while the survival of the oropharynx subsite potentially was the most impacted. High expression of TIGIT, CIITA, and CXCR6 was linked to better survival, mainly in the oropharynx subsite. Immune cell clusters with four distinct survival profiles were discovered, of which the cluster with a high CD8+ T cell content had a better prognosis. The immune-infiltration pattern is related to the survival of HNSCC to varying degrees depending on the tumor sites; forthcoming studies into immune-mediated infiltration profiles will lay the groundwork for treating HNSCC with precision therapy.

Targeting JMJD1C to selectively disrupt tumor Treg cell fitness enhances antitumor immunity.

Regulatory T (Treg) cells are critical for immune tolerance but also form a barrier to antitumor immunity. As therapeutic strategies involving Treg cell depletion are limited by concurrent autoimmune disorders, identification of intratumoral Treg cell-specific regulatory mechanisms is needed for selective targeting. Epigenetic modulators can be targeted with small compounds, but intratumoral Treg cell-specific epigenetic regulators have been unexplored. Here, we show that JMJD1C, a histone demethylase upregulated by cytokines in the tumor microenvironment, is essential for tumor Treg cell fitness but dispensable for systemic immune homeostasis. JMJD1C deletion enhanced AKT signals in a manner dependent on histone H3 lysine 9 dimethylation (H3K9me2) demethylase and STAT3 signals independently of H3K9me2 demethylase, leading to robust interferon-γ production and tumor Treg cell fragility. We have also developed an oral JMJD1C inhibitor that suppresses tumor growth by targeting intratumoral Treg cells. Overall, this study identifies JMJD1C as an epigenetic hub that can integrate signals to establish tumor Treg cell fitness, and we present a specific JMJD1C inhibitor that can target tumor Treg cells without affecting systemic immune homeostasis.

Risk and Protective Factors for Parental Involvement and Early Indicators of School Achievement in Alaska.

OBJECTIVES: Parental involvement can affect child school readiness, which in turn influences subsequent child learning outcomes. While social support, stress, caregiver psychological distress, and drinking could affect parental involvement, it is unknown whether and how these factors influence downstream child learning outcomes through parental involvement and child school readiness. This study tests those associations. METHODS: Using de-identified data provided by the Alaska Longitudinal Child Abuse and Neglect Linkage project (N = 683), we use Structural Equation Modeling to assess direct and indirect effects of paths embedded in the proposed model. RESULTS: This study found statistically significant indirect effects: (1) path linking stress faced by caregivers to child reading proficiency through caregiver psychological distress, parental involvement, and child school readiness, (2) path linking stress faced by caregivers to child reading proficiency through caregiver drinking, parental involvement, and child school readiness, and (3) path linking social support for caregivers to child reading proficiency through caregiver psychological distress, parental involvement, and child school readiness. Post-estimation showed that the sum of the magnitude of total effects of stress and the magnitude of total effects of support is significantly larger than either alone. CONCLUSIONS FOR PRACTICE: Findings suggest that reducing caregiver stress and offering social support could not only benefit caregivers but learning outcomes of their children as well. For child learning outcomes, simultaneously reducing stress and offering social support for caregivers, rather than just one of them alone, is suggested. These results are important for children, particularly for those raised by caregivers experiencing psychological distress or drinking issues.