Dual Caregiving and Mental Health Among Long-Term Care Nursing Assistants: The Moderating Role of Social Support.

AIM: To investigate the association of long-term care nursing assistants' dual caregiving roles with mental health and to determine whether social support moderates this relationship. DESIGN: A cross-sectional survey. METHODS: We surveyed 962 certified long-term care nursing assistants working in long-term care and medical facilities across Taiwan from October 2022 to July 2023. 'Dual caregiving roles' denote the fulfilment of caregiving duties both at work and within families. Mental health was evaluated using the 5-item Brief Symptom Rating Scale. Logistic regression analysis was utilized to investigate the association of dual caregiving roles and psychological job demands with poor mental health. Moreover, we explored whether family, colleague, and supervisor support moderated the association between dual caregiving roles and poor mental health. RESULTS: Among long-term care nursing assistants, 15% had dual caregiving responsibilities. Individuals with both dual caregiving roles and high psychological job demands faced the highest risk of poor mental health compared to those without dual caregiving roles and low psychological job demands. Having dual caregiving roles was associated with poor mental health compared to workers without such roles. Additionally, support from family, colleagues, and supervisors mitigates the association between caregivers' dual caregiving roles and poor mental health. CONCLUSION: A substantial proportion of long-term care nursing assistants had dual caregiving roles, leading to an additional mental health burden when combined with high psychological job demands. High social support attenuated this association. IMPLICATIONS FOR THE PROFESSION: Long-term care nursing assistants with dual caregiving roles had poorer mental health outcomes. Yet, support from family, colleagues, and supervisors mitigated these effects. These results emphasize the importance of enhancing social support to protect the mental well-being of long-term care nursing assistants managing both formal and informal caregiving duties. REPORTING METHOD: This study adheres to the STROBE guideline of reporting. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Paper-Recorded ECG Digitization Method with Automatic Reference Voltage Selection for Telemonitoring and Diagnosis.

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground-background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed to ensure consistency in amplitude, rather than solely in shape, for digital signals. The original signal reconstruction algorithm was validated with the MIT-BIH and PTB databases by comparing the difference between the reconstructed and the original signals. Moreover, the mean of the Pearson correlation coefficient was 0.97 and 0.98, respectively, while the mean absolute errors were 0.324 and 0.241, respectively. The method proposed in this study converts paper-recorded ECGs into a digital format, enabling direct analysis using software. Automated techniques for acquiring and restoring ECG reference voltages enhance the reconstruction accuracy. This innovative approach facilitates data storage, medical communication, and remote ECG analysis, and minimizes errors in remote diagnosis.

Electron-Spin Regulation Driving Heterointerface Electron Distribution and Phase Transition toward Ultrafast and Durable Sodium Storage.

Phase engineering is an effective strategy for modulating the electronic structure and electron transfer mobility of cobalt selenide (CoSe2) with remarkable sodium storage. Nevertheless, it remains challenging to improve fast-charging and cycling performance. Herein, a heterointerface coupling induces phase transformation from cubic CoSe2 to orthorhombic CoSe2 accompanied by the formation of MoSe2 to construct a CoSe2/MoSe2 heterostructure decorated with N-doped carbon layer on a 3D graphene foam (CoSe2/MoSe2@NC/GF). The incorporated Mo cations in the bridged o-CoSe2/MoSe2 not only act an electron donor to regulate charge-spin configurations with more active electronic states but also trigger the upshift of d/p band centers and a decreased ∆d-p band center gap, which greatly enhances ion adsorption capability and lowers the ion diffusion barrier. As expected, the CoSe2/MoSe2@NC/GF anode demonstrates a high-rate capability of 447 mAh g-1 at 2 A g-1 and an excellent cyclability of 298 mAh g-1 at 1 A g-1 over 1000 cycles. The work deepens the understanding of the elaborate construction of heterostructured electrodes for high-performance SIBs.

Molecular approaches for the management of papaya ringspot virus infecting papaya: a comprehensive review.

Papaya ringspot virus (PRSV) is a catastrophic disease that causes huge yield losses in papaya cultivation around the world. Yield losses in severely infected plants can be upto 100%. Because of this disease, papaya cultivation has been shifted to other crops in some areas of the world. Many conventional methods and breeding approaches are used against this disease, which turns out to be less effective. Considering the yield loss caused by PRSV in papaya, it is high time to focus on alternative control methods. To implement effective management strategies, molecular approaches such as Marker Assisted Breeding (MAS) or transgenic methods involving post-transcriptional gene silencing targeting the genome viz., coat protein, replicase gene, or HC Pro can be pursued. However, the public's reluctance to widely accept the transgenic approach due to health and environmental concerns necessitates a consideration of non-transgenic alternatives. Prioritizing safety and ensuring efficient virus control, non-transgenic approaches which encompass cross-protection, genome editing, and topical applications of dsRNA to induce gene silencing within the host, can be adopted. This review aims to provide comprehensive insights of various molecular tools used in managing PRSV which in turn will help in sustainable agriculture.

IDH2 mutation accelerates TPO-induced myelofibrosis with enhanced S100a8/a9 and NFκB signaling in vivo.

Introduction: IDH2 mutation is an unfavorable prognostic factor in patients with primary myelofibrosis (PMF) but its effect on myelofibrosis (MF) remains largely unclear. Methods: In this study, we aimed to elucidate the roles of IDH2 mutation in the development and progression of MF by transcriptomic and molecular techniques using the Idh2 R172K transgenic mice. Results: We found that thrombopoietin (TPO)-overexpressed Idh2 R172K (Idh2 R172K + TPO) mice had accelerated progression to MF, compared with TPO-overexpressed Idh2-wild (WT + TPO) mice, showing activation of multiple inflammatory pathways, among which nuclear factor κB (NFκB) was the most significantly enhanced. Single-cell transcriptomes of the marrow cells in early MF showed that S100a8/a9 expression was mainly confined to neutrophil progenitors in the WT + TPO mice, but highly expressed in several types of myeloid precursor cells, including the megakaryocyte progenitors in the Idh2 R172K + TPO group. Furthermore, Idh2 R172K mice at age of 18 months had larger spleens, increased S100a8/a9-Tlr4 expression, and elevated serum S100a8/a9 levels compared with WT mice. PMF patients with IDH2 mutations had higher bone marrow plasma S100A8/A9 levels than those without IDH2 mutations. Conclusion: Overall, our findings showed that IDH2 mutation induced proinflammatory effects, which further exacerbated MF, as evidenced by the increase in S100a8/a9 levels and NFκB hyperactivation in Idh2 R172K + TPO mice.

Patient-centered care in diabetes care-concepts, relationships and practice.

We still do not have comprehensive knowledge of which framework of patient-centered care (PCC) is appropriate for diabetes care, which elements of PCC are evidence-based, and the mechanism by which PCC elements are associated with outcomes through mediators. In this review, we elaborate on these issues. We found that for diabetes care, PCC elements such as autonomy support (patient individuality), cooperation and collaboration (system-level approach), com-munication and education (behavior change techniques), emotional support (biopsychosocial approach), and family/other involvement and support are critically important. All of these factors are directly associated with different patient outcomes and indirectly associated with outcomes through patient activation. We present the practical implications of these PCC elements.

Prognostic impact of bridge or neoadjuvant induction chemotherapy in patients with resected oral cavity cancer: A nationwide cohort study.

BACKGROUND: While surgery remains the primary treatment for oral squamous cell carcinoma (OCSCC), induction chemotherapy (IC) can be used as a bridging or neoadjuvant therapy. This nationwide study in Taiwan examines the survival outcomes of OCSCC patients who received IC before surgery. METHODS: We analyzed data from 29,891 patients with OCSCC. Of these, 29,058 initially underwent surgery (OP group), whereas 833 received IC before surgery (IC + OP group). A propensity score (PS)-matched analysis (4, 1 ratio, 3260 vs. 815 patients) was performed considering tumor subsite, sex, age, Charlson comorbidity index, clinical T1-T4b tumors, clinical N0-3 disease, and clinical stage I-IV. RESULTS: In the PS-matched cohort, the 5-year disease-specific survival (DSS) and overall survival (OS) rates were 65% and 57%, respectively. When comparing the OP and IC + OP groups, the 5-year DSS rates were 66% and 62%, respectively (p = 0.1162). Additionally, the 5-year OS rates were 57% and 56%, respectively (p = 0.9917). No significant intergroup differences in survival were observed for specific subgroups with cT4a tumors, cT4b tumors, cN3 disease, pT4b tumors, and pN3 disease. However, for patients with pT4a tumors, the OP group demonstrated superior 5-year outcomes compared to the IC + OP group, with a DSS of 62% versus 52% (p = 0.0006) and an OS of 53% versus 44% (p = 0.0060). Notably, patients with cT2-3, cN1, and c-Stage II disease in the IC + OP group were significantly more likely to achieve pT0-1 status (p < 0.05). CONCLUSIONS: Following PS matching, the IC + OP group generally exhibited similar prognosis to the OP group. However, for pT4a tumors, the OP group showed superior 5-year outcomes. While IC may not universally improve survival, it could be advantageous for patients who respond positively to the treatment.

Encapsulation of Sn Sub-nanoclusters in Multichannel Carbon Matrix for High-Performance Potassium-ion Batteries.

Sub-nanoclusters with ultra-small particle sizes are particularly significant to create advanced energy storage materials. Herein, Sn sub-nanoclusters encapsulated in nitrogen-doped multichannel carbon matrix (denoted as Sn-SCs@MCNF) are designed by a facile and controllable route as flexible anode for high-performance potassium ion batteries (PIBs). The uniformly dispersed Sn sub-nanoclusters in multichannel carbon matrix can be precisely identified, which ensure us to clarify the size influence on the electrochemical performance. The sub-nanoscale effect of Sn-SCs@MCNF restrains electrode pulverization and enhances the K+ diffusion kinetics, leading to the superior cycling stability and rate performance. As freestanding anode in PIBs, Sn-SCs@MCNF manifests superior K+ storage properties, such as exceptional cycling stability (331 mAh g-1 after 150 cycles at 100 mA g-1) and rate capability. Especially, the Sn-SCs@MCNF||KFe[Fe(CN)6] full cell demonstrates impressive reversible capacity of 167 mAh g-1 at 0.4 A g-1 even after 200 cycles. Theoretical calculations clarify that the ultrafine Sn sub-nanoclusters are beneficial for electron transfer and contribute to the lower energy barriers of the intermediates, thereby resulting in promising electrochemical performance. Comprehensive investigation for the intrinsic K+ storage process of Sn-SCs@MCNF is revealed by in situ analysis. This work provides vital guidance to design sub-nanoscale functional materials for high-performance energy-storage devices.

Evaluation of the Alveolar Crest and Cemento-Enamel Junction in Periodontitis Using Object Detection on Periapical Radiographs.

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth's bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with a maximum accuracy of 97.01%. An instance segmentation developed in this study accurately extracts regions of interest, enabling the generation of masks for tooth bone and tooth crown with accuracies of 93.48% and 96.95%. Finally, a novel detection algorithm is proposed to automatically mark the CEJ and ALC of symptomatic teeth, facilitating faster accurate assessment of bone loss severity by dentists. The PA image database used in this study, with the IRB number 02002030B0 provided by Chang Gung Medical Center, Taiwan, significantly reduces the time required for dental diagnosis and enhances healthcare quality through the techniques developed in this research.

Sulfidation-reoxidation enhances heavy metal immobilization by vivianite.

Iron minerals in nature are pivotal hosts for heavy metals, significantly influencing their geochemical cycling and eventual fate. It is generally accepted that, vivianite, a prevalent iron phosphate mineral in aquatic and terrestrial environments, exhibits a limited capacity for adsorbing cationic heavy metals. However, our study unveils a remarkable phenomenon that the synergistic interaction between sulfide (S2-) and vivianite triggers an unexpected sulfidation-reoxidation process, enhancing the immobilization of heavy metals such as cadmium (Cd), copper (Cu), and zinc (Zn). For instance, the combination of vivianite and S2- boosted the removal of Cd2+ from the aqueous phase under anaerobic conditions, and ensured the retention of Cd stabilized in the solid phase when shifted to aerobic conditions. It is intriguing to note that no discrete FeS formation was detected in the sulfidation phase, and the primary crystal structure of vivianite largely retained its integrity throughout the whole process. Detailed molecular-level investigations indicate that sulfidation predominantly targets the Fe(II) sites at the corners of the PO4 tetrahedron in vivianite. With the transition to aerobic conditions, the exothermic oxidation of CdS and the S sites in vivianite initiates, rendering it thermodynamically favorable for Cd to form multidentate coordination structures, predominantly through the Cd-O-P and Cd-O-Fe bonds. This mechanism elucidates how Cd is incorporated into the vivianite structure, highlighting a novel pathway for heavy metal immobilization via the sulfidation-reoxidation dynamics in iron phosphate minerals.

Pharmacological activation of pyruvate dehydrogenase by dichloroacetate protects against obesity-induced muscle atrophy in vitro and in vivo.

Obesity-induced muscle atrophy leads to physical impairment and metabolic dysfunction, which are risky for older adults. The activity of pyruvate dehydrogenase (PDH), a critical regulator of glucose metabolism, is reduced in obesity. Additionally, PDH activator dichloroacetate (DCA) improves metabolic dysfunction. However, the effects of PDH activation on skeletal muscles in obesity remain unclear. Thus, this study aimed to evaluate the effects of PDH activation by DCA treatment on obesity-induced muscle atrophy in vitro and in vivo and elucidate the possible underlying mechanisms. Results showed that PDH activation by DCA treatment ameliorated muscle loss, decreased the cross-sectional area, and reduced grip strength in C57BL/6 mice fed a high-fat diet (HFD). Elevation of muscle atrophic factors atrogin-1 and muscle RING-finger protein-1 (MuRF-1) and autophagy factors LC3BII and p62 were abrogated by DCA treatment in palmitate-treated C2C12 myotubes and in the skeletal muscles of HFD-fed mice. Moreover, p-Akt, p-FoxO1, and p-FoxO3 protein levels were reduced and p-NF-κB p65 and p-p38 MAPK protein levels were elevated in palmitate-treated C2C12 myotubes, which were restored by DCA treatment. However, the protective effects of DCA treatment against myotube atrophy were reversed by treatment with Akt inhibitor MK2206. Taken together, our study demonstrated that PDH activation by DCA treatment can alleviate obesity-induced muscle atrophy. It may serve as a basis for developing novel strategies to prevent obesity-associated muscle loss.

Insights into CLC-0's Slow-Gating from Intracellular Proton Inhibition.

The opening of the Torpedo CLC-0 chloride (Cl-) channel is known to be regulated by two gating mechanisms: fast gating and slow (common) gating. The structural basis underlying the fast-gating mechanism is better understood than that of the slow-gating mechanism, which is still largely a mystery. Our previous study on the intracellular proton (H+i)-induced inhibition of the CLC-0 anionic current led to the conclusion that the inhibition results from the slow-gate closure (also called inactivation). The conclusion was made based on substantial evidence such as a large temperature dependence of the H+i inhibition similar to that of the channel inactivation, a resistance to the H+i inhibition in the inactivation-suppressed C212S mutant, and a similar voltage dependence between the current recovery from the H+i inhibition and the recovery from the channel inactivation. In this work, we further examine the mechanism of the H+i inhibition of wild-type CLC-0 and several mutants. We observe that an anion efflux through the pore of CLC-0 accelerates the recovery from the H+i-induced inhibition, a process corresponding to the slow-gate opening. Furthermore, various inactivation-suppressed mutants exhibit different current recovery kinetics, suggesting the existence of multiple inactivated states (namely, slow-gate closed states). We speculate that protonation of the pore of CLC-0 increases the binding affinity of permeant anions in the pore, thereby generating a pore blockage of ion flow as the first step of inactivation. Subsequent complex protein conformational changes further transition the CLC-0 channel to deeper inactivated states.

Auxiliary Diagnosis of Dental Calculus Based on Deep Learning and Image Enhancement by Bitewing Radiographs.

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 to identify individual teeth accurately. This system boasts an impressive precision rate of 97.48%, a recall (sensitivity) of 96.81%, and a specificity rate of 98.25%. Furthermore, this study introduces a novel approach to enhancing interdental edges through an advanced image-enhancement algorithm. This algorithm combines the use of a median filter and bilateral filter to refine the accuracy of convolutional neural networks in classifying dental calculus. Before image enhancement, the accuracy achieved using GoogLeNet stands at 75.00%, which significantly improves to 96.11% post-enhancement. These results hold the potential for streamlining dental consultations, enhancing the overall efficiency of dental services.

Effectiveness of early palliative care in patients with head and neck cancer in Taiwan.

BACKGROUND: Early palliative care (EPC) benefits some cancers, but its clinical outcomes differ depending on patients' racial and ethnic disparities, and customs. To determine whether EPC improves symptoms, emotional distress, and quality of life among Taiwanese patients with early or advanced-stage head and neck cancer (HNC). METHODS: Based on participants' pathological stages, they were categorized as having early and advanced-stage HNC. Those willing and unwilling to undergo EPC were assigned to the EPC and standard groups, respectively. Their daily cancer-related symptoms were assessed using the Distress Thermometer (DT) and MD Anderson Symptom Inventory (MDASI), whose scores' concurrent validity was evaluated using the European Organization for Research and Treatment of Core Quality of Life (EORTC-QLQ-C30) and Head and Neck 35 (EORTC-QLQ-H&N35) questionnaires. RESULTS: Patients (n = 93) diagnosed with HNC at Taiwan's Chia-Yi Christian Hospital from November 2020 to October 2022 were recruited. The patients voluntarily split into two groups: EPC groups and standard groups (23 and 11 in early-stage; 46 and 13 in advanced-stage, respectively). DT assessment showed significant emotional distress improvements for all patients with HNC who received EPC. The EORTC-QLQ-C30 questionnaire indicated that, compared to standard interventions, EPC groups significantly improved the quality of life and some symptoms for both early and advanced-stage HNC patients. However, the EORTC-QLQ-H&N35 questionnaire found no significant difference between the two groups. Furthermore, advanced-stage patients' anticancer treatment completion rates with EPC and standard interventions were 95.35% and 75%, respectively. CONCLUSION: EPC improves symptoms, emotional distress, quality of life, and treatment completion rates in Taiwanese patients with early or advanced-stage HNC. Nonetheless, further extensive clinical studies are required for validation.

Prognostic impact of elective tracheotomy in resected oral cavity squamous cell carcinoma: A nationwide cohort study.

BACKGROUND: Elective tracheotomy is commonly performed in resected oral squamous cell carcinoma (OCSCC) to maintain airway patency. However, the indications for this procedure vary among surgeons. This nationwide study evaluated the impact of tracheotomy on both the duration of in-hospital stay and long-term survival outcomes in patients with OCSCC. METHODS: A total of 18,416 patients with OCSCC were included in the analysis, comprising 7981 patients who underwent elective tracheotomy and 10,435 who did not. The primary outcomes assessed were 5-year disease-specific survival (DSS) and overall survival (OS). To minimize potential confounding factors, a propensity score (PS)-matched analysis was performed on 4301 patients from each group. The duration of hospital stay was not included as a variable in the PS-matched analysis. RESULTS: Prior to PS matching, patients with tracheotomy had significantly lower 5-year DSS and OS rates compared to those without (71% vs. 82%, p < 0.0001; 62% vs. 75%, p < 0.0001, respectively). Multivariable analysis identified tracheotomy as an independent adverse prognostic factor for 5-year DSS (hazard ratio = 1.10 [1.03-1.18], p = 0.0063) and OS (hazard ratio = 1.10 [1.04-1.17], p = 0.0015). In the PS-matched cohort, the 5-year DSS was 75% for patients with tracheotomy and 76% for those without (p = 0.1488). Five-year OS rates were 66% and 67%, respectively (p = 0.0808). Prior to PS matching, patients with tracheotomy had a significantly longer mean hospital stay compared to those without (23.37 ± 10.56 days vs. 14.19 ± 8.34 days; p < 0.0001). Following PS matching, the difference in hospital stay duration between the two groups remained significant (22.34 ± 10.25 days vs. 17.59 ± 9.54 days; p < 0.0001). CONCLUSIONS: While elective tracheotomy in resected OCSCC patients may not significantly affect survival, it could be associated with prolonged hospital stays.

Evaluation of Spectrum-Aided Visual Enhancer (SAVE) in Esophageal Cancer Detection Using YOLO Frameworks.

The early detection of esophageal cancer presents a substantial difficulty, which contributes to its status as a primary cause of cancer-related fatalities. This study used You Only Look Once (YOLO) frameworks, specifically YOLOv5 and YOLOv8, to predict and detect early-stage EC by using a dataset sourced from the Division of Gastroenterology and Hepatology, Ditmanson Medical Foundation, Chia-Yi Christian Hospital. The dataset comprised 2741 white-light images (WLI) and 2741 hyperspectral narrowband images (HSI-NBI). They were divided into 60% training, 20% validation, and 20% test sets to facilitate robust detection. The images were produced using a conversion method called the spectrum-aided vision enhancer (SAVE). This algorithm can transform a WLI into an NBI without requiring a spectrometer or spectral head. The main goal was to identify dysplasia and squamous cell carcinoma (SCC). The model's performance was evaluated using five essential metrics: precision, recall, F1-score, mAP, and the confusion matrix. The experimental results demonstrated that the HSI model exhibited improved learning capabilities for SCC characteristics compared with the original RGB images. Within the YOLO framework, YOLOv5 outperformed YOLOv8, indicating that YOLOv5's design possessed superior feature-learning skills. The YOLOv5 model, when used in conjunction with HSI-NBI, demonstrated the best performance. It achieved a precision rate of 85.1% (CI95: 83.2-87.0%, p < 0.01) in diagnosing SCC and an F1-score of 52.5% (CI95: 50.1-54.9%, p < 0.01) in detecting dysplasia. The results of these figures were much better than those of YOLOv8. YOLOv8 achieved a precision rate of 81.7% (CI95: 79.6-83.8%, p < 0.01) and an F1-score of 49.4% (CI95: 47.0-51.8%, p < 0.05). The YOLOv5 model with HSI demonstrated greater performance than other models in multiple scenarios. This difference was statistically significant, suggesting that the YOLOv5 model with HSI significantly improved detection capabilities.

Colorectal cancer-specific IFNß delivery overcomes dysfunctional dsRNA-mediated type I interferon signaling to increase the abscopal effect of radiotherapy.

BACKGROUND: Cancer-intrinsic type I interferon (IFN-I) production triggered by radiotherapy (RT) is mainly dependent on cytosolic double-stranded DNA (dsDNA)-mediated cGAS/STING signaling and increases cancer immunogenicity and enhances the antitumor immune response to increase therapeutic efficacy. However, cGAS/STING deficiency in colorectal cancer (CRC) may suppress the RT-induced antitumor immunity. Therefore, we aimed to evaluate the importance of the dsRNA-mediated antitumor immune response induced by RT in patients with CRC. METHODS: Cytosolic dsRNA level and its sensors were evaluated via cell-based assays (co-culture assay, confocal microscopy, pharmacological inhibition and immunofluorescent staining) and in vivo experiments. Biopsies and surgical tissues from patients with CRC who received preoperative chemoradiotherapy (neoCRT) were collected for multiplex cytokine assays, immunohistochemical analysis and SNP genotyping. We also generated a cancer-specific adenovirus-associated virus (AAV)-IFNß1 construct to evaluate its therapeutic efficacy in combination with RT, and the immune profiles were analyzed by flow cytometry and RNA-seq. RESULTS: Our studies revealed that RT stimulates the autonomous release of dsRNA from cancer cells to activate TLR3-mediated IFN-I signatures to facilitate antitumor immune responses. Patients harboring a dysfunctional TLR3 variant had reduced serum levels of IFN-I-related cytokines and intratumoral CD8+ immune cells and shorter disease-free survival following neoCRT treatment. The engineered cancer-targeted construct AAV-IFNß1 significantly improved the response to RT, leading to systematic eradication of distant tumors and prolonged survival in defective TLR3 preclinical models. CONCLUSION: Our results support that increasing cancer-intrinsic IFNß1 expression is an immunotherapeutic strategy that enhances the RT-induced antitumor immune response in locally patients with advanced CRC with dysfunctional TLR3.

A Deep Learning Approach to Classify Fabry Cardiomyopathy from Hypertrophic Cardiomyopathy Using Cine Imaging on Cardiac Magnetic Resonance.

A challenge in accurately identifying and classifying left ventricular hypertrophy (LVH) is distinguishing it from hypertrophic cardiomyopathy (HCM) and Fabry disease. The reliance on imaging techniques often requires the expertise of multiple specialists, including cardiologists, radiologists, and geneticists. This variability in the interpretation and classification of LVH leads to inconsistent diagnoses. LVH, HCM, and Fabry cardiomyopathy can be differentiated using T1 mapping on cardiac magnetic resonance imaging (MRI). However, differentiation between HCM and Fabry cardiomyopathy using echocardiography or MRI cine images is challenging for cardiologists. Our proposed system named the MRI short-axis view left ventricular hypertrophy classifier (MSLVHC) is a high-accuracy standardized imaging classification model developed using AI and trained on MRI short-axis (SAX) view cine images to distinguish between HCM and Fabry disease. The model achieved impressive performance, with an F1-score of 0.846, an accuracy of 0.909, and an AUC of 0.914 when tested on the Taipei Veterans General Hospital (TVGH) dataset. Additionally, a single-blinding study and external testing using data from the Taichung Veterans General Hospital (TCVGH) demonstrated the reliability and effectiveness of the model, achieving an F1-score of 0.727, an accuracy of 0.806, and an AUC of 0.918, demonstrating the model's reliability and usefulness. This AI model holds promise as a valuable tool for assisting specialists in diagnosing LVH diseases.

Artificial Intelligence Model for a Distinction between Early-Stage Gastric Cancer Invasive Depth T1a and T1b.

Background: Endoscopic submucosal dissection (ESD) is a widely accepted treatment for patients with mucosa (T1a) disease without lymph node metastasis. However, the inconsistency of inspection quality of tumor staging under the standard tool combining endoscopic ultrasound (EUS) with computed tomography (CT) scanning makes it restrictive. Methods: We conducted a study using data augmentation and artificial intelligence (AI) to address the early gastric cancer (EGC) staging problem. The proposed AI model simplifies early cancer treatment by eliminating the need for ultrasound or other staging methods. We developed an AI model utilizing data augmentation and the You-Only-Look-Once (YOLO) approach. We collected a white-light image dataset of 351 stage T1a and 542 T1b images to build, test, and validate the model. An external white-light images dataset that consists of 47 T1a and 9 T1b images was then collected to validate our AI model. The result of the external dataset validation indicated that our model also applies to other peer health institutes. Results: The results of k-fold cross-validation using the original dataset demonstrated that the proposed model had a sensitivity of 85.08% and an average specificity of 87.17%. Additionally, the k-fold cross-validation model had an average accuracy rate of 86.18%; the external data set demonstrated similar validation results with a sensitivity of 82.98%, a specificity of 77.78%, and an overall accuracy of 82.14%. Conclusions: Our findings suggest that the AI model can effectively replace EUS and CT in early GC staging, with an average validation accuracy rate of 86.18% for the original dataset from Linkou Cheng Gun Memorial Hospital and 82.14% for the external validation dataset from Kaohsiung Cheng Gun Memorial Hospital. Moreover, our AI model's accuracy rate outperformed the average EUS and CT rates in previous literature (around 70%).