Cardiogenic control of affective behavioural state.

Emotional states influence bodily physiology, as exemplified in the top-down process by which anxiety causes faster beating of the heart1-3. However, whether an increased heart rate might itself induce anxiety or fear responses is unclear3-8. Physiological theories of emotion, proposed over a century ago, have considered that in general, there could be an important and even dominant flow of information from the body to the brain9. Here, to formally test this idea, we developed a noninvasive optogenetic pacemaker for precise, cell-type-specific control of cardiac rhythms of up to 900 beats per minute in freely moving mice, enabled by a wearable micro-LED harness and the systemic viral delivery of a potent pump-like channelrhodopsin. We found that optically evoked tachycardia potently enhanced anxiety-like behaviour, but crucially only in risky contexts, indicating that both central (brain) and peripheral (body) processes may be involved in the development of emotional states. To identify potential mechanisms, we used whole-brain activity screening and electrophysiology to find brain regions that were activated by imposed cardiac rhythms. We identified the posterior insular cortex as a potential mediator of bottom-up cardiac interoceptive processing, and found that optogenetic inhibition of this brain region attenuated the anxiety-like behaviour that was induced by optical cardiac pacing. Together, these findings reveal that cells of both the body and the brain must be considered together to understand the origins of emotional or affective states. More broadly, our results define a generalizable approach for noninvasive, temporally precise functional investigations of joint organism-wide interactions among targeted cells during behaviour.

Ultrahigh Sensitivity for Thermographic Human-Machine Interface via Precious Metals Atomic Layer Deposition on V-MXene: Computational and Experimental Exploration.

Global healthcare based on the Internet of Things system is rapidly transforming to measure precise physiological body parameters without visiting hospitals at remote patients and associated symptoms monitoring. 2D materials and the prevailing mood of current ever-expanding MXene-based sensing devices motivate to introduce first the novel iridium (Ir) precious metal incorporated vanadium (V)-MXene via industrially favored emerging atomic layer deposition (ALD) techniques. The current work contributes a precise control and delicate balance of Ir single atomic forms or clusters on the V-MXene to constitute a unique precious metal-MXene embedded heterostructure (Ir-ALD@V-MXene) in practical real-time sensing healthcare applications to thermography with human-machine interface for the first time. Ir-ALD@V-MXene delivers an ultrahigh durability and sensing performance of 2.4% °C-1 than pristine V-MXene (0.42% °C-1), outperforming several conventionally used MXenes, graphene, underscoring the importance of the Ir-ALD innovative process. Aberration-corrected advanced ultra-high-resolution transmission/scanning transmission electron microscopy confirms the presence of Ir atomic clusters on well-aligned 2D-layered V-MXene structure and their advanced heterostructure formation (Ir-ALD@V-MXene), enhanced sensing mechanism is investigated using density functional theory (DFT) computations. A rational design empowering the Ir-ALD process on least explored V-MXene can potentially unfold further precious metals ALD-process developments for next-generation wearable personal healthcare devices.

Sox17 Deficiency Promotes Pulmonary Arterial Hypertension via HGF/c-Met Signaling.

BACKGROUND: In large-scale genomic studies, Sox17, an endothelial-specific transcription factor, has been suggested as a putative causal gene of pulmonary arterial hypertension (PAH); however, its role and molecular mechanisms remain to be elucidated. We investigated the functional impacts and acting mechanisms of impaired Sox17 (SRY-related HMG-box17) pathway in PAH and explored its potential as a therapeutic target. METHODS: In adult mice, Sox17 deletion in pulmonary endothelial cells (ECs) induced PAH under hypoxia with high penetrance and severity, but not under normoxia. RESULTS: Key features of PAH, such as hypermuscularization, EC hyperplasia, and inflammation in lung arterioles, right ventricular hypertrophy, and elevated pulmonary arterial pressure, persisted even after long rest in normoxia. Mechanistically, transcriptomic profiling predicted that the combination of Sox17 deficiency and hypoxia activated c-Met signaling in lung ECs. HGF (hepatocyte grow factor), a ligand of c-Met, was upregulated in Sox17-deficient lung ECs. Pharmacologic inhibition of HGF/c-Met signaling attenuated and reversed the features of PAH in both preventive and therapeutic settings. Similar to findings in animal models, Sox17 levels in lung ECs were repressed in 26.7% of PAH patients (4 of 15), while those were robust in all 14 non-PAH controls. HGF levels in pulmonary arterioles were increased in 86.7% of patients with PAH (13 of 15), but none of the controls showed that pattern. CONCLUSIONS: The downregulation of Sox17 levels in pulmonary arterioles increases the susceptibility to PAH, particularly when exposed to hypoxia. Our findings suggest the reactive upregulation of HGF/c-Met signaling as a novel druggable target for PAH treatment.

Fitness costs of Tn1546-type transposons harboring the vanA operon by plasmid type and structural diversity in Enterococcus faecium.

BACKGROUND: This study analyzed the genetic traits and fitness costs of vancomycin-resistant Enterococcus faecium (VREfm) blood isolates carrying Tn1546-type transposons harboring the vanA operon. METHODS: All E. faecium blood isolates were collected from eight general hospitals in South Korea during one-year study period. Antimicrobial susceptibility testing and vanA and vanB PCR were performed. Growth rates of E. faecium isolates were determined. The vanA-positive isolates were subjected to whole genome sequencing and conjugation experiments. RESULTS: Among 308 E. faecium isolates, 132 (42.9%) were positive for vanA. All Tn1546-type transposons harboring the vanA operon located on the plasmids, but on the chromosome in seven isolates. The plasmids harboring the vanA operon were grouped into four types; two types of circular, nonconjugative plasmids (Type A, n = 50; Type B, n = 46), and two types of putative linear, conjugative plasmids (Type C, n = 16; Type D, n = 5). Growth rates of vanA-positive E. faecium isolates were significantly lower than those of vanA-negative isolates (P < 0.001), and reduction in growth rate under vancomycin pressure was significantly larger in isolates harboring putative linear plasmids than in those harboring circular plasmids (P = 0.020). CONCLUSIONS: The possession of vanA operon was costly to bacterial hosts in antimicrobial-free environment, which provide evidence for the importance of reducing vancomycin pressure for prevention of VREfm dissemination. Fitness burden to bacterial hosts was varied by type and size of the vanA operon-harboring plasmid.

Machine learning-derived model for predicting poor post-treatment quality of life in Korean cancer survivors.

PURPOSE: A substantial number of cancer survivors have poor quality of life (QOL) even after completing cancer treatment. Thus, in this study, we used machine learning (ML) to develop predictive models for poor QOL in post-treatment cancer survivors in South Korea. METHODS: This cross-sectional study used online survey data from 1,005 post-treatment cancer survivors in South Korea. The outcome variable was QOL, which was measured using the global QOL subscale of the European Organization of Cancer and Treatment for Cancer Quality of Life Questionnaire, where a global QOL score < 60.4 was defined as poor QOL. Three ML models (random forest (RF), support vector machine, and extreme gradient boosting) and three deep learning models were used to develop predictive models for poor QOL. Model performance regarding accuracy, area under the receiver operating characteristic curve, F1 score, precision, and recall was evaluated. The SHapely Additive exPlanation (SHAP) method was used to identify important features. RESULTS: Of the 1,005 participants, 65.1% had poor QOL. Among the six models, the RF model had the best performance (accuracy = 0.85, F1 = 0.90). The SHAP method revealed that survivorship concerns (e.g., distress, pain, and fatigue) were the most important factors that affected poor QOL. CONCLUSIONS: The ML-based prediction model developed to predict poor QOL in Korean post-treatment cancer survivors showed good accuracy. The ML model proposed in this study can be used to support clinical decision-making in identifying survivors at risk of poor QOL.

Self-Management Using eHealth Technologies for Liver Transplant Recipients: Scoping Review.

BACKGROUND: Liver transplantation has become increasingly common as a last-resort treatment for end-stage liver diseases and liver cancer, with continually improving success rates and long-term survival rates. Nevertheless, liver transplant recipients face lifelong challenges in self-management, including immunosuppressant therapy, lifestyle adjustments, and navigating complex health care systems. eHealth technologies hold the potential to aid and optimize self-management outcomes, but their adoption has been slow in this population due to the complexity of post-liver transplant management. OBJECTIVE: This study aims to examine the use of eHealth technologies in supporting self-management for liver transplant recipients and identify their benefits and challenges to suggest areas for further research. METHODS: Following the Arksey and O'Malley methodology for scoping reviews, we conducted a systematic search of 5 electronic databases: PubMed, CINAHL, Embase, PsycINFO, and Web of Science. We included studies that (1) examined or implemented eHealth-based self-management, (2) included liver transplant recipients aged ≥18 years, and (3) were published in a peer-reviewed journal. We excluded studies that (1) were case reports, conference abstracts, editorials, or letters; (2) did not focus on the posttransplantation phase; (3) did not focus on self-management; and (4) did not incorporate the concept of eHealth or used technology solely for data collection. The quality of the selected eHealth interventions was evaluated using (1) the Template for Intervention Description and Replication guidelines and checklist and (2) the 5 core self-management skills identified by Lorig and Holman. RESULTS: Of 1461 articles, 15 (1.03%) studies were included in the final analysis. Our findings indicate that eHealth-based self-management strategies for adult liver transplant recipients primarily address lifestyle management, medication adherence, and remote monitoring, highlighting a notable gap in alcohol relapse interventions. The studies used diverse technologies, including mobile apps, videoconferencing, and telehealth platforms, but showed limited integration of decision-making or resource use skills essential for comprehensive self-management. The reviewed studies highlighted the potential of eHealth in enhancing individualized health care, but only a few included collaborative features such as 2-way communication or tailored goal setting. While adherence and feasibility were generally high in many interventions, their effectiveness varied due to diverse methodologies and outcome measures. CONCLUSIONS: This scoping review maps the current literature on eHealth-based self-management support for liver transplant recipients, assessing its potential and challenges. Future studies should focus on developing predictive models and personalized eHealth interventions rooted in patient-generated data, incorporating digital human-to-human interactions to effectively address the complex needs of liver transplant recipients. This review emphasizes the need for future eHealth self-management research to address the digital divide, especially with the aging liver transplant recipient population, and ensure more inclusive studies across diverse ethnicities and regions.

Targeting FLT3-TAZ signaling to suppress drug resistance in blast phase chronic myeloid leukemia.

BACKGROUND: Although the development of BCR::ABL1 tyrosine kinase inhibitors (TKIs) rendered chronic myeloid leukemia (CML) a manageable condition, acquisition of drug resistance during blast phase (BP) progression remains a critical challenge. Here, we reposition FLT3, one of the most frequently mutated drivers of acute myeloid leukemia (AML), as a prognostic marker and therapeutic target of BP-CML. METHODS: We generated FLT3 expressing BCR::ABL1 TKI-resistant CML cells and enrolled phase-specific CML patient cohort to obtain unpaired and paired serial specimens and verify the role of FLT3 signaling in BP-CML patients. We performed multi-omics approaches in animal and patient studies to demonstrate the clinical feasibility of FLT3 as a viable target of BP-CML by establishing the (1) molecular mechanisms of FLT3-driven drug resistance, (2) diagnostic methods of FLT3 protein expression and localization, (3) association between FLT3 signaling and CML prognosis, and (4) therapeutic strategies to tackle FLT3+ CML patients. RESULTS: We reposition the significance of FLT3 in the acquisition of drug resistance in BP-CML, thereby, newly classify a FLT3+ BP-CML subgroup. Mechanistically, FLT3 expression in CML cells activated the FLT3-JAK-STAT3-TAZ-TEAD-CD36 signaling pathway, which conferred resistance to a wide range of BCR::ABL1 TKIs that was independent of recurrent BCR::ABL1 mutations. Notably, FLT3+ BP-CML patients had significantly less favorable prognosis than FLT3- patients. Remarkably, we demonstrate that repurposing FLT3 inhibitors combined with BCR::ABL1 targeted therapies or the single treatment with ponatinib alone can overcome drug resistance and promote BP-CML cell death in patient-derived FLT3+ BCR::ABL1 cells and mouse xenograft models. CONCLUSION: Here, we reposition FLT3 as a critical determinant of CML progression via FLT3-JAK-STAT3-TAZ-TEAD-CD36 signaling pathway that promotes TKI resistance and predicts worse prognosis in BP-CML patients. Our findings open novel therapeutic opportunities that exploit the undescribed link between distinct types of malignancies.

Self-Formation of a Ru/ZnO Multifunctional Bilayer for the Next-Generation Interconnect Technology via Area-Selective Atomic Layer Deposition.

This study suggests a Ru/ZnO bilayer grown using area-selective atomic layer deposition (AS-ALD) as a multifunctional layer for advanced Cu metallization. As a diffusion barrier and glue layer, ZnO is selectively grown on SiO2 , excluding Cu, where Ru, as a liner and seed layer, is grown on both surfaces. Dodecanethiol (DDT) is used as an inhibitor for the AS-ALD of ZnO using diethylzinc and H2 O at 120 °C. H2 plasma treatment removes the DDT adsorbed on Cu, forming inhibitor-free surfaces. The ALD-Ru film is then successfully deposited at 220 °C using tricarbonyl(trimethylenemethane)ruthenium and O2 . The Cu/bilayer/Si structural and electrical properties are investigated to determine the diffusion barrier performance of the bilayer film. Copper silicide is not formed without the conductivity degradation of the Cu/bilayer/Si structure, even after annealing at 700 °C. The effect of ZnO on the Ru/SiO2 structure interfacial adhesion energy is investigated using a double-cantilever-beam test and is found to increase with ZnO between Ru and SiO2 . Consequently, the Ru/ZnO bilayer can be a multifunctional layer for advanced Cu interconnects. Additionally, the formation of a bottomless barrier by eliminating ZnO on the via bottom, or Cu, is expected to decrease the via resistance for the ever-shrinking Cu lines.

Small interfering RNA (siRNA)-based therapeutic applications against viruses: principles, potential, and challenges.

RNA has emerged as a revolutionary and important tool in the battle against emerging infectious diseases, with roles extending beyond its applications in vaccines, in which it is used in the response to the COVID-19 pandemic. Since their development in the 1990s, RNA interference (RNAi) therapeutics have demonstrated potential in reducing the expression of disease-associated genes. Nucleic acid-based therapeutics, including RNAi therapies, that degrade viral genomes and rapidly adapt to viral mutations, have emerged as alternative treatments. RNAi is a robust technique frequently employed to selectively suppress gene expression in a sequence-specific manner. The swift adaptability of nucleic acid-based therapeutics such as RNAi therapies endows them with a significant advantage over other antiviral medications. For example, small interfering RNAs (siRNAs) are produced on the basis of sequence complementarity to target and degrade viral RNA, a novel approach to combat viral infections. The precision of siRNAs in targeting and degrading viral RNA has led to the development of siRNA-based treatments for diverse diseases. However, despite the promising therapeutic benefits of siRNAs, several problems, including impaired long-term protein expression, siRNA instability, off-target effects, immunological responses, and drug resistance, have been considerable obstacles to the use of siRNA-based antiviral therapies. This review provides an encompassing summary of the siRNA-based therapeutic approaches against viruses while also addressing the obstacles that need to be overcome for their effective application. Furthermore, we present potential solutions to mitigate major challenges.

Deep learning reconstruction in pediatric brain MRI: comparison of image quality with conventional T2-weighted MRI.

INTRODUCTION: Deep learning-based MRI reconstruction has recently been introduced to improve image quality. This study aimed to evaluate the performance of deep learning reconstruction in pediatric brain MRI. METHODS: A total of 107 consecutive children who underwent 3.0 T brain MRI were included in this study. T2-weighted brain MRI was reconstructed using the three different reconstruction modes: deep learning reconstruction, conventional reconstruction with an intensity filter, and original T2 image without a filter. Two pediatric radiologists independently evaluated the following image quality parameters of three reconstructed images on a 5-point scale: overall image quality, image noisiness, sharpness of gray-white matter differentiation, truncation artifact, motion artifact, cerebrospinal fluid and vascular pulsation artifacts, and lesion conspicuity. The subjective image quality parameters were compared among the three reconstruction modes. Quantitative analysis of the signal uniformity using the coefficient of variation was performed for each reconstruction. RESULTS: The overall image quality, noisiness, and gray-white matter sharpness were significantly better with deep learning reconstruction than with conventional or original reconstruction (all P < 0.001). Deep learning reconstruction had significantly fewer truncation artifacts than the other two reconstructions (all P < 0.001). Motion and pulsation artifacts showed no significant differences among the three reconstruction modes. For 36 lesions in 107 patients, lesion conspicuity was better with deep learning reconstruction than original reconstruction. Deep learning reconstruction showed lower signal variation compared to conventional and original reconstructions. CONCLUSION: Deep learning reconstruction can reduce noise and truncation artifacts and improve lesion conspicuity and overall image quality in pediatric T2-weighted brain MRI.