Immunogenomic features of radiologically distinctive nodules in multiple primary lung cancer.

OBJECTIVES: To provide molecular and immunological attributes mechanistic insights for the management of radiologically distinctive multiple primary lung cancer (MPLC). METHODS: The Bulk RNA-seq data of MPLC were obtained from our center. The Bulk RNA-seq data and CT images of patients with single primary lung cancer (SPLC) were obtained from GSE103584. Immune infiltration algorithms were performed to investigate the disparities in the immunological microenvironment between the two groups. Single-cell gene analysis was used to explore immune cells composition and communication relationships between cells in MPLC. RESULTS: In MPLC, 11 pure ground-glass opacity nodules (pGGN) and 10 mixed GGN (mGGN) were identified, while in SPLC, the numbers were 18 pGGN and 22 mGGN, respectively. In MPLC, compared to pGGN, mGGN demonstrated a significantly elevated infiltration of CD8+ T cells. Single-cell gene analysis demonstrated that CD8+ T cells play a central role in the signaling among immune cells in MPLC. The transcription factors including MAFG, RUNX3, and TBX21 may play pivotal roles in regulation of CD8+ T cells. Notably, compared to SPLC nodules for both mGGN and pGGN, MPLC nodules demonstrated a significantly elevated degree of tumor-infiltrating immune cells, with this difference being particularly pronounced in mGGN. There was a positive correlation between the proportion of immune cells and consolidation/tumor ratio (CTR). CONCLUSIONS: Our findings provided a comprehensive description about the difference in the immune microenvironment between pGGN and mGGN in early-stage MPLC, as well as between MPLC and SPLC for both mGGN and pGGN. The findings may provide evidence for the design of immunotherapeutic strategies for MPLC.

Skin-Inspired, Highly Sensitive, Broad-Range-Response and Ultra-Strong Gradient Ionogels Prepared by Electron Beam Irradiation.

Skin, characterized by its distinctive gradient structure and interwoven fibers, possesses remarkable mechanical properties and highly sensitive attributes, enabling it to detect an extensive range of stimuli. Inspired by these inherent qualities, a pioneering approach involving the crosslinking of macromolecules through in situ electron beam irradiation (EBI) is proposed to fabricate gradient ionogels. Such a design offers remarkable mechanical properties, including excellent tensile properties (>1000%), exceptional toughness (100 MJ m-3), fatigue resistance, a broad temperature range (-65-200°C), and a distinctive gradient modulus change. Moreover, the ionogel sensor exhibits an ultra-fast response time (60 ms) comparable to skin, an incredibly low detection limit (1 kPa), and an exceptionally wide detection range (1 kPa-1 MPa). The exceptional gradient ionogel material holds tremendous promise for applications in the field of smart sensors, presenting a distinct strategy for fabricating flexible gradient materials.

Low-dose Olaparib improves septic cardiac function by reducing ferroptosis via accelerated mitophagy flux.

Sepsis is a dysregulated response to infection that can result in life-threatening organ failure, and septic cardiomyopathy is a serious complication involving ferroptosis. Olaparib, a classic targeted drug used in oncology, has demonstrated potential protective effects against sepsis. However, the exact mechanisms underlying its action remain to be elucidated. In our study, we meticulously screened ferroptosis genes associated with sepsis, and conducted comprehensive functional enrichment analyses to delineate the relationship between ferroptosis and mitochondrial damage. Eight sepsis-characterized ferroptosis genes were identified in sepsis patients, including DPP4, LPIN1, PGD, HP, MAPK14, POR, GCLM, and SLC38A1, which were significantly correlated with mitochondrial quality imbalance. Utilizing DrugBank and molecular docking, we demonstrated a robust interaction of Olaparib with these genes. Lipopolysaccharide (LPS)-stimulated HL-1 cells and monocytes were used to establish an in vitro sepsis model. Additionally, an in vivo model was developed using mice subjected to cecal ligation and perforation (CLP). Intriguingly, low-dose Olaparib (5 mg/kg) effectively targeted and mitigated markers associated with ferroptosis, concurrently improving mitochondrial quality. This led to a marked enhancement in cardiac function and a significant increase in survival rates in septic mice (p < 0.05). The mechanism through which Olaparib ameliorates ferroptosis in cardiac and leukocyte cells post-sepsis is attributed to its facilitation of mitophagy, thus favoring mitochondrial integrity. In conclusion, our findings suggest that low-dose Olaparib can improve mitochondrial quality by accelerating mitophagy flux, consequently inhibiting ferroptosis and preserving cardiac function after sepsis.

mTOR/miR-142-3p/PRAS40 signaling cascade is critical for tuberous sclerosis complex-associated renal cystogenesis.

BACKGROUND: Patients with tuberous sclerosis complex (TSC) develop renal cysts and/or angiomyolipomas (AMLs) due to inactive mutations of either TSC1 or TSC2 and consequential mTOR hyperactivation. The molecular events between activated mTOR and renal cysts/AMLs are still largely unknown. METHODS: The mouse model of TSC-associated renal cysts were constructed by knocking out Tsc2 specifically in renal tubules (Tsc2f/f; ksp-Cre). We further globally deleted PRAS40 in these mice to investigate the role of PRAS40. Tsc2-/- cells were used as mTOR activation model cells. Inhibition of DNA methylation was used to increase miR-142-3p expression to examine the effects of miR-142-3p on PRAS40 expression and TSC-associated renal cysts. RESULTS: PRAS40, a component of mTOR complex 1, was overexpressed in Tsc2-deleted cell lines and mouse kidneys (Tsc2f/f; ksp-Cre), which was decreased by mTOR inhibition. mTOR stimulated PRAS40 expression through suppression of miR-142-3p expression. Unleashed PRAS40 was critical to the proliferation of Tsc2-/- cells and the renal cystogenesis of Tsc2f/f; ksp-Cre mice. In contrast, inhibition of DNA methylation increased miR-142-3p expression, decreased PRAS40 expression, and hindered cell proliferation and renal cystogenesis. CONCLUSIONS: Our data suggest that mTOR activation caused by TSC2 deletion increases PRAS40 expression through miR-142-3p repression. PRAS40 depletion or the pharmacological induction of miR-142-3p expression impaired TSC2 deficiency-associated renal cystogenesis. Therefore, harnessing mTOR/miR-142-3p/PRAS40 signaling cascade may mitigate hyperactivated mTOR-related diseases.

Iron deficiency at birth and risk of hidden hearing loss in infants modification by socioeconomic status: mother-newborn cohort in Shenyang, China.

OBJECTIVE: The diagnosis of hidden hearing loss (HHL) in calm state has not yet been determined, while the nutritional status is not involved in its pathogenic risk factors. In utero iron deficiency (ID) may delay auditory neural maturation in infants. We evaluated the association between ID and HHL as well as the modification effect of socioeconomic status (SES) on this association in newborns. STUDY DESIGN: We included 859 mother-newborns from the baseline of this observational northeast cohort. Data on exposure assessment included iron status [maternal hemoglobin (Hb) and neonatal heel prick serum ferritin (SF)] and SES (occupation, education and income). Auditory neural maturation was reflected by auditory brainstem response (ABR) testing and electrocochleography (ECochG). RESULTS: Iron status and SES were independently and jointly associated with the prediction of neonatal HHL by logistic and linear regression model. The mediation effects were performed by Process. ID increased absolute latency wave V, interpeak latency (IPL) III-V, and summting potentials (SP) /action potentials (AP), which were combined as HHL. Low SES showed the highest risk of HHL and the highest levels of related parameters in ID newborns. Moreover, after Corona Virus Disease 2019 (COVID-19) were positive, preschool children who experience ID in neonatal period were more likely to suffer from otitis media with effusion (OME). High SES also showed similar risk effects. CONCLUSION: Both low and high SES may strengthen the risk of ID on neonatal HHL in Northeast China.

Infrared and Visible Image Fusion Algorithm Based on Double-Domain Transform Filter and Contrast Transform Feature Extraction.

Current challenges in visible and infrared image fusion include color information distortion, texture detail loss, and target edge blur. To address these issues, a fusion algorithm based on double-domain transform filter and nonlinear contrast transform feature extraction (DDCTFuse) is proposed. First, for the problem of incomplete detail extraction that exists in the traditional transform domain image decomposition, an adaptive high-pass filter is proposed to decompose images into high-frequency and low-frequency portions. Second, in order to address the issue of fuzzy fusion target caused by contrast loss during the fusion process, a novel feature extraction algorithm is devised based on a novel nonlinear transform function. Finally, the fusion results are optimized and color-corrected by our proposed spatial-domain logical filter, in order to solve the color loss and edge blur generated in the fusion process. To validate the benefits of the proposed algorithm, nine classical algorithms are compared on the LLVIP, MSRS, INO, and Roadscene datasets. The results of these experiments indicate that the proposed fusion algorithm exhibits distinct targets, provides comprehensive scene information, and offers significant image contrast.

Notoginsenoside R1 improves intestinal microvascular functioning in sepsis by targeting Drp1-mediated mitochondrial quality imbalance.

CONTEXT: Sepsis can result in critical organ failure, and notoginsenoside R1 (NGR1) offers mitochondrial protection. OBJECTIVE: To determine whether NGR1 improves organ function and prognosis after sepsis by protecting mitochondrial quality. MATERIALS AND METHODS: A sepsis model was established in C57BL/6 mice using cecum ligation puncture (CLP) and an in vitro model with lipopolysaccharide (LPS, 10 µg/mL)-stimulated primary intestinal microvascular endothelial cells (IMVECs) and then determine NGR1's safe dosage. Groups for each model were: in vivo-a control group, a CLP-induced sepsis group, and a CLP + NGR1 treatment group (30 mg/kg/d for 3 d); in vitro-a control group, a LPS-induced sepsis group, and a LPS + NGR1 treatment group (4 µM for 30 min). NGR1's effects on survival, intestinal function, mitochondrial quality, and mitochondrial dynamic-related protein (Drp1) were evaluated. RESULTS: Sepsis resulted in approximately 60% mortality within 7 days post-CLP, with significant reductions in intestinal microvascular perfusion and increases in vascular leakage. Severe mitochondrial quality imbalance was observed in IMVECs. NGR1 (IC50 is 854.1 µM at 30 min) targeted Drp1, inhibiting mitochondrial translocation, preventing mitochondrial fragmentation and restoring IMVEC morphology and function, thus protecting against intestinal barrier dysfunction, vascular permeability, microcirculatory flow, and improving sepsis prognosis. DISCUSSION AND CONCLUSIONS: Drp1-mediated mitochondrial quality imbalance is a potential therapeutic target for sepsis. Small molecule natural drugs like NGR1 targeting Drp1 may offer new directions for organ protection following sepsis. Future research should focus on clinical trials to evaluate NGR1's efficacy across various patient populations, potentially leading to novel treatments for sepsis.

[Exploration of cancer biological characteristics in people with different five movements and six climates constitution based on pan-cancer Bulk RNA-Seq].

According to the theory of five movements and six climates, the innate constitution plays a crucial role in determining the underlyingpa thological mechanisms of diseases later in life. Previous studies have demonstrated a close association between the constitution, as defined by the theory of five movements and six climates, and the development of various types of tumors. Furt hermore,the tumorsubtype determined by the constitution has prognostic implications. This highlights the potential of utilizing the fivemovements and six climates theory to guide the implementation of precision medicine strategies in thefield of oncology. However, no resear ch has yet been conducted to investigate the use of this theory in guiding the development of tumor molecular classification and precisi onmedicine strategies. The objective of this research is to uncover the biological characteristics of each constitution within a pancanc ercohort and identify potential anti-tumor drugs that are applicable to patients with different constitutional types. By doing so, we aimto c ontribute to the establishment of a precision medicine strategy for tumors derived from the original concepts of traditional Chi nesemedicine(TCM). In this study, we obtainedpan-cancer Bulk RNA-Seq data from UCSC Xena, GWAS cohort data from the UKBiobank, and cis-eQTLs data from eQ TLGen and GTEx V8. We employed machine learning methods to screen for hub genes associated with each constitution. Subsequently, we utilized informatics tools to explore the biological characteristics of each constitut iondefined by the theory of five movements and six bioclimates. Further, potential anti-tumor drugs suitable for patients with differen tconstitutional types were identified through mendelian randomization, molecular docking, and drug-like prediction techniques. Withinthe pan-cancer cohort, significant differences were observed among different constitutions in terms of progression-free interval, biological f unctions, immune cell abundance, tumor drug sensitivity, and immunotherapy response. These findings suggest that the five movements and six climates theory can guide tumor molecular classification and the development of precision medicine strategies. Moreover,the biological characteristics inherent to each constitution partially shed light on the scientific implications of Chinese medicinetheories, offering a fresh perspective towards clinical cancer treatment. Through molecular docking and drug-like prediction, several po tential anti-tumor drugs such as 17-beta-estradiol, serotonin, trans-resveratrol, and linoleic acid were identified. Overall, the util izationof multi-omics approaches pro vides a powerful tool to unravel the scientific foundations of TCM theories. The elucidation of themu lti-omics features associated witheach constitution in tumors serves as the basis for applying the five movements and six climates theoryto tumor molecular classification and the development of precision medicine strategies.

Association between residual islet beta-cell function and achieving the target of time in range in inpatients with type 2 diabetes undergoing antidiabetic treatment: An observation study.

AIM: To assess whether the beta-cell function of inpatients undergoing antidiabetic treatment influences achieving time in range (TIR) and time above range (TAR) targets. MATERIALS AND METHODS: This cross-sectional study included 180 inpatients with type 2 diabetes. TIR and TAR were assessed by a continuous glucose monitoring system, with target achievement defined as TIR more than 70% and TAR less than 25%. Beta-cell function was assessed by the insulin secretion-sensitivity index-2 (ISSI2). RESULTS: Following antidiabetic treatment, logistic regression analysis showed that lower ISSI2 was associated with a decreased number of inpatients achieving TIR (OR = 3.10, 95% CI: 1.19-8.06) and TAR (OR = 3.40, 95% CI: 1.35-8.55) targets after adjusting for potential confounders. Similar associations still existed in those participants treated with insulin secretagogues (TIR: OR = 2.91, 95% CI: 0.90-9.36, P = .07; TAR, OR = 3.14, 95% CI: 1.01-9.80) or adequate insulin therapy (TIR: OR = 2.84, 95% CI: 0.91-8.81, P = .07; TAR, OR = 3.24, 95% CI: 1.08-9.67). Furthermore, receiver operating characteristic curves showed that the diagnostic value of the ISSI2 for achieving TIR and TAR targets was 0.73 (95% CI: 0.66-0.80) and 0.71 (95% CI: 0.63-0.79), respectively. CONCLUSIONS: Beta-cell function was associated with achieving TIR and TAR targets. Stimulating insulin secretion or exogenous insulin treatment could not overcome the disadvantage of lower beta-cell function on glycaemic control.

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.

OBJECTIVES: To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. METHODS: A total of 542 patients with clinical stage 0-I peripheral LUAD and with preoperative CT data of 1-mm slice thickness were included. Maximal solid size on axial image (MSSA) was evaluated by two chest radiologists. MSSA, volume of solid component (SV), and mass of solid component (SM) were evaluated by DL. Consolidation-to-tumor ratios (CTRs) were calculated. For ground glass nodules (GGNs), solid parts were extracted with different density level thresholds. The prognosis prediction efficacy of DL was compared with that of manual measurements. Multivariate Cox proportional hazards model was used to find independent risk factors. RESULTS: The prognosis prediction efficacy of T-staging (TS) measured by radiologists was inferior to that of DL. For GGNs, MSSA-based CTR measured by radiologists (RMSSA%) could not stratify RFS and OS risk, whereas measured by DL using 0HU (2D-AIMSSA0HU%) could by using different cutoffs. SM and SV measured by DL using 0 HU (AISM0HU% and AISV0HU%) could effectively stratify the survival risk regardless of different cutoffs and were superior to 2D-AIMSSA0HU%. AISM0HU% and AISV0HU% were independent risk factors. CONCLUSION: DL algorithm can replace human for more accurate T-staging of LUAD. For GGNs, 2D-AIMSSA0HU% could predict prognosis rather than RMSSA%. The prediction efficacy of AISM0HU% and AISV0HU% was more accurate than of 2D-AIMSSA0HU% and both were independent risk factors. CLINICAL RELEVANCE STATEMENT: Deep learning algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma. KEY POINTS: • Deep learning (DL) algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma (LUAD). • For GGNs, maximal solid size on axial image (MSSA)-based consolidation-to-tumor ratio (CTR) measured by DL using 0 HU could stratify survival risk than that measured by radiologists. • The prediction efficacy of mass- and volume-based CTRs measured by DL using 0 HU was more accurate than of MSSA-based CTR and both were independent risk factors.