Precise Regulation on the Bond Dissociation Energy of Exocyclic C-N Bonds in Various N-Heterocycle Electron Donors via Machine Learning.

Heterocycles with saturated N atoms (HetSNs) are widely used electron donors in organic light-emitting diode (OLED) materials. Their relatively low bond dissociation energy (BDE) of exocyclic C-N bonds has been closely related to material intrinsic stability and even device lifetime. Thus, it is imperative to realize fast prediction and precise regulation of those C-N BDEs, which demands a deep understanding of the relationship between the molecular structure and BDE. Herein, via machine learning (ML), we rapidly and accurately predicted C-N BDEs in various HetSNs and found that five-membered HetSNs (5-HetSNs) have much higher BDEs than almost all 6-HetSNs, except emerging boron-N blocks. Thorough analysis disclosed that high aromaticity is the foremost factor accounting for the high BDE of 5-HetSNs, and introducing intramolecular hydrogen-bond or electron-withdrawing moieties could also increase BDE. Importantly, the ML models performed well in various realistic OLED materials, showing great potential in characterizing material intrinsic stability for high-throughput virtual-screening and material design efforts.

Deep Learning Sequence Models for Transcriptional Regulation.

Deciphering the regulatory code of gene expression and interpreting the transcriptional effects of genome variation are critical challenges in human genetics. Modern experimental technologies have resulted in an abundance of data, enabling the development of sequence-based deep learning models that link patterns embedded in DNA to the biochemical and regulatory properties contributing to transcriptional regulation, including modeling epigenetic marks, 3D genome organization, and gene expression, with tissue and cell-type specificity. Such methods can predict the functional consequences of any noncoding variant in the human genome, even rare or never-before-observed variants, and systematically characterize their consequences beyond what is tractable from experiments or quantitative genetics studies alone. Recently, the development and application of interpretability approaches have led to the identification of key sequence patterns contributing to the predicted tasks, providing insights into the underlying biological mechanisms learned and revealing opportunities for improvement in future models.

Causal relationship between feelings and cognitive decline: An univariable and multivariable Mendelian randomization study.

BACKGROUND: While the impact of depression on cognition is well-documented, the relationship between feelings and cognition has received limited attention. AIM: To explore the potential association between feelings and cognition with a two-sample Mendelian randomization (MR) analysis. METHODS: Our analysis utilized genome-wide association data on various feelings (fed-up feelings, n = 453071; worrier/anxious feelings, n = 450765; guilty feelings, n = 450704; nervous feelings, n = 450700; sensitivity/hurt feelings, n = 449419; miserableness, n = 454982; loneliness/isolation, n = 455364; happiness, n = 152348) in the European population and their impact on cognitive functions (intelligence, n = 269867). Conducting a univariable MR (UVMR) analysis to assess the relationship between feelings and cognition. In this analysis, we applied the inverse variance weighting (IVW), weighted median, and MR Egger methods. Additionally, we performed sensitivity analysis (leave-one-out analysis), assessed heterogeneity (using MR-PRESSO and Cochran's Q test), and conducted multiple validity test (employing MR-Egger regression). Subsequently, a multivariable MR (MVMR) analysis was employed to examine the impact of feelings on cognition. IVW served as the primary method in the multivariable analysis, complemented by median-based and MR-Egger methods. RESULTS: In this study, UVMR indicated that sensitivity/hurt feelings may have a negative causal effect on cognition (OR = 0.63, 95%CI: 0.43-0.92, P = 0.017). After adjustment of other feelings using MVMR, a direct adverse causal effect on cognition was observed (ORMVMR = 0.39, 95%CI: 0.17-0.90, PMVMR = 0.027). While a potential increased risk of cognitive decline was observed for fed-up feelings in the UVMR analysis (ORUVMR = 0.64, 95%CI: 0.42-0.97, PUVMR = 0.037), this effect disappeared after adjusting for other feelings (ORMVMR = 1.42, 95%CI: 0.43-4.74, PMVMR = 0.569). These findings were generally consistent across MV-IVW, median-based, and MR-Egger analyses. MR-Egger regression revealed pleiotropy in the impact of worrier/anxious feelings on cognition, presenting a challenge in identifying the effect. Notably, this study did not demonstrate any significant impact of guilty feelings, nervous feelings, miserableness, or loneliness/isolation on cognition. Due to a limited number of instrumental variables for happiness, this study was unable to analyze the relationship between happiness and cognition. CONCLUSION: This MR study finds that sensitivity/hurt feelings are associated with cognitive decline, while the link between worrier/anxious feelings and cognition remains inconclusive. Insufficient evidence supports direct associations between happiness, guilty feelings, nervous feelings, miserableness, loneliness/isolation, and cognition.

Actual and Virtual Parks Benefit Quality of Life and Physical Activity: A Cluster Trial.

Urban parks provide connectedness to nature as a health resilience environment for promoting health. Virtual reality can provide opportunities for urban citizens to be exposed to natural elements with health benefits. The purpose was to explore the effects of actual and virtual parks on the quality of life and physical activity of urban residents. The study design was a cluster trial. Participants were healthy adults aged 20-50 years, recruited from three college campuses, and randomly assigned to two experimental groups (n = 30, 32) and one control group (n = 30). The intervention with virtual or actual parks was conducted for 30 min a session once a week for 12 weeks. Outcomes were measured using self-reported questionnaires, including the World Health Organization Quality-of-Life Scale-BREF and International Physical Activity Questionnaire-Short Form. In total, 84 participants completed the interventions and post-intervention measures. Results showed that participants who experienced actual parks had significant increases in the social quality of life and light-intensity physical activity and had decreased body weight. Participants who experienced the virtual parks experienced a significant increase in their mental quality of life. Participants in the experimental groups of both kinds of parks had significant improvements in their self-rated health, physical and environmental quality of life, and sedentary time after the intervention. Urban parks are an important natural resource for citizens' health and physical activity promotion. Virtual parks can simulate actual parks and have similar health benefits and are thus are recommended for citizens who lack opportunities and motivation to go to actual parks.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research.

BACKGROUND: As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease's etiology and response to drugs. OBJECTIVE: We designed the Alzheimer's Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics. METHODS: We designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base. RESULTS: AlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones. CONCLUSIONS: AlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

Charge-mode Neural Stimulator with a Capacitor-reuse Residual Charge Detector and Active Charge Balancing for Epileptic Seizure Suppression.

This study proposes a charge-mode neural stimulator for electrical stimulation systems that utilizes a capacitor-reuse technique with a residual charge detector and achieves active charge balancing simultaneously. The design is mainly used for epilepsy suppression systems to achieve real-time symptom relief during seizures. A charge-mode stimulator is adopted in consideration of the complexity of circuit design, the high voltage tolerance of transistors, and system integration requirements in the future. The residual charge detector allows users to understand the current stimulus situation, enabling them to make optimal adjustments to the stimulation parameters. On the basis of the information on actual stimulation charge, active charge balancing can effectively prevent the accumulation of mismatched charges on electrode impedance. The capacitor- and phase-reuse techniques help realize high integration of the overall stimulator circuit in consideration of the commonality of the use of a capacitor and charging/discharging phase in the stimulation circuit and charge detector. The proposed charge-mode neural stimulator is implemented in a TSMC 0.18 µm 1P6M CMOS process with a core area of 0.2127 mm2. Measurement results demonstrate the accuracy of the stimulation's functionality and the programmable stimulus parameters. The effectiveness of the proposed charge-mode neural stimulator for epileptic seizure suppression is verified through animal experiments.

Deep Learning-Assisted Diffusion Tensor Imaging for Evaluation of the Physis and Metaphysis.

Diffusion tensor imaging of physis and metaphysis can be used as a biomarker to predict height change in the pediatric population. Current application of this technique requires manual segmentation of the physis which is time-consuming and introduces interobserver variability. UNET Transformers (UNETR) can be used for automatic segmentation to optimize workflow. Three hundred and eighty-five DTI scans from 191 subjects with mean age of 12.6 years ± 2.01 years were retrospectively used for training and validation. The mean Dice correlation coefficient was 0.81 for the UNETR model and 0.68 for the UNET. Manual extraction and segmentation took 15 min per volume, whereas both deep learning segmentation techniques took < 1 s per volume and were deterministic, always producing the same result for a given input. Intraclass correlation coefficient (ICC) for ROI-derived femur diffusion metrics was excellent for tract count (0.95), volume (0.95), and FA (0.97), and good for tract length (0.87). The results support the hypothesis that a hybrid UNETR model can be trained to replace the manual segmentation of physeal DTI images, therefore automating the process.

Synthesis and Antifungal Properties of 1,2,4-Triazole Schiff Base Agents Based on a 3D-QSAR Model.

Based on our previous research, a 3D-QSAR model (q2=0.51, ONC=5, r2=0.982, F=271.887, SEE=0.052) was established to predict the inhibitory effects of triazole Schiff base compounds on Fusarium graminearum, and its predictive ability was also confirmed through the statistical parameters. According to the results of the model design, 30 compounds with superior bioactivity compared to the template molecule 4 were obtained. Seven of these compounds (DES2-6, DES9-10) with improved biological activity and readily available raw materials were successfully synthesized. Their structures were confirmed through HRMS, NMR, and single crystal X-ray diffraction analysis (DES-5). The bioactivity of the final products was investigated through an in vitro antifungal assay. There was little difference in the EC50 values between the experimental and predicted values of the model, demonstrating the reliability of the model. Especially, DES-3 (EC50=9.915 mg/L) and DES-5 (EC50=9.384 mg/L) exhibited better inhibitory effects on Fusarium graminearum compared to the standard drug (SD) triadimenol (EC50=10.820 mg/L). These compounds could serve as potential new fungicides for future research. The interaction between the final products and isocitrate lyase (ICL) was investigated through molecular docking. Compounds with R groups that have a higher electron-donating capacity were found to be biologically active.

High-intensity interval training versus moderate-intensity continuous training for localized prostate cancer under active surveillance: a systematic review and network meta-analysis.

BACKGROUND: High-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) have been increasingly adopted for localized prostate cancer (PCa) under active surveillance (AS). However, it is unclear which training modality is the most favorable in terms of cardiorespiratory fitness and biochemical progression. METHODS: We searched PubMed, Cochrane and Embase for relevant RCTs. PRISMA guideline was adopted to ensure optimal conduct of this study. Serum prostate specific antigen (PSA) and peak VO2 were selected as primary outcomes and PSA doubling time (PSADT) and testosterone were selected as secondary outcomes. Only articles written in English were included. Cochrane risk-of-bias tool was used for risk of bias evaluation. RESULTS: A total of 501 studies were selected. Six RCTs with 222 patients were included for data extraction and analysis. High-intensity interval training (HIIT) group demonstrated significantly lower PSA compared with usual care (UC) (MD = -1.4; 95%CI = -2.77 to -0.03) and moderate-intensity continuous training (MICT) group (MD = -1.67; 95%CI = -3.30 to -0.05). Both HIIT and MICT showed significantly improved peak VO2 compared with UC. No significant difference was observed in PSADT and testosterone among different training modalities and UC. Regarding peak VO2, MICT had the highest surface under cumulative ranking curve (SUCRA) scores (98.1%). For serum PSA, HIIT had the highest probability (97.8%) to be the training with the highest efficacy. The potential source of bias mainly came from poorly performed allocation concealment and blinding strategies. CONCLUSIONS: The present study indicated that HIIT and MICT showed considerable cardiorespiratory benefits for localized PCa. HIIT was preferred over MICT in biochemical progression control in terms of decreasing serum PSA levels. However, MICT was favored over HIIT regarding cardiorespiratory benefits. The findings of this study may facilitate future lifestyle intervention, particularly in the form of physical training, for individuals diagnosed with localized PCa under AS.

The feasibility, efficacy, and safety of RDN procedure using CO2 angiography through radial artery in severe chronic kidney disease patients.

The recent evidence regarding the effectiveness of renal denervation (RDN) in blood pressure control is becoming increasingly substantial. However, many studies have excluded populations with severely impaired kidney function, even though these individuals have a higher prevalence of hypertension compared to the general population, and controlling their blood pressure is more challenging. The effectiveness and safety of RDN in patients with severe chronic kidney disease (CKD) lack strong evidence support. Concerns about worsening kidney function still exist, particularly in patients with CKD stage 5. We conducted an observational study involving 10 patients who were using at least 3 different antihypertensive medications and had an estimated glomerular filtration rate (eGFR) < 45 mL/min/1.73 m2 but had not undergone dialysis. For these patients, we performed RDN via the radial artery approach, with the assistance of carbon dioxide (CO2) angiography. Utilizing this approach, the systolic 24-hour ambulatory blood pressure monitoring did not exhibit a significant decrease at 3 months; however, a significant reduction was observed at 6 months after RDN. We also minimized contrast agent usage, observed no kidney function decline 3 months post-RDN, and experienced no vascular-related complications. Using the radial artery approach and CO2 angiography assistance for RDN may be an effective and safe blood pressure control method for patients with severe kidney impairment.

Costs and Cardiovascular Benefits of a Fourth-Generation Synchronous Telehealth Program on Mortality and Cardiovascular Outcomes for Patients With Atrial Fibrillation: Retrospective Cohort Study.

BACKGROUND: The prevalence of atrial fibrillation (AF) continues to increase in modern aging society. Patients with AF are at high risk for multiple adverse cardiovascular events, including heart failure, stroke, and mortality. Improved medical care is needed for patients with AF to enhance their quality of life and limit their medical resource utilization. With advances in the internet and technology, telehealth programs are now widely used in medical care. A fourth-generation telehealth program offers synchronous and continuous medical attention in response to physiological parameters measured at home. Although we have previously shown the benefits of this telehealth program for some patients with a high risk of cardiovascular disease, its benefits for patients with AF remains uncertain. OBJECTIVE: This study aims to investigate the benefits of participating in a fourth-generation telehealth program for patients with AF in relation to cardiovascular outcomes. METHODS: This was a retrospective cohort study. We retrospectively searched the medical records database of a tertiary medical center in Northern Taiwan between January 2007 and December 2017. We screened 5062 patients with cardiovascular disease and enrolled 537 patients with AF, of which 279 participated in the telehealth program and 258 did not. Bias was reduced using the inverse probability of treatment weighting adjustment based on the propensity score. Outcomes were collected and analyzed, including all-cause readmission, admission for heart failure, acute coronary syndrome, ischemic stroke, systemic embolism, bleeding events, all-cause mortality, and cardiovascular death within the follow-up period. Total medical expenses and medical costs in different departments were also compared. Subgroup analyses were conducted on ischemic stroke stratified by several subgroup variables. RESULTS: The mean follow-up period was 3.0 (SD 1.7) years for the telehealth group and 3.4 (SD 1.9) years for the control group. After inverse probability of treatment weighting adjustment, the patients in the telehealth program had significantly fewer ischemic strokes (2.0 vs 4.5 events per 100 person-years; subdistribution hazard ratio [SHR] 0.45, 95% CI 0.22-0.92) and cardiovascular deaths (2.5 vs 5.9 events per 100 person-years; SHR 0.43, 95% CI 0.18-0.99) at the follow-up. The telehealth program particularly benefited patients comorbid with vascular disease (SHR 0.11, 95% CI 0.02-0.53 vs SHR 1.16, 95% CI 0.44-3.09; P=.01 for interaction). The total medical expenses during follow-up were similar in the telehealth and control groups. CONCLUSIONS: This study demonstrated the benefits of participating in the fourth-generation telehealth program for patients with AF by significantly reducing their ischemic stroke risk while spending the same amount on medical expenses.

Sono-anatomy of the middle cervical sympathetic ganglion verified with pathology.

Objectives: Cervical discomfort and other symptoms may be attributable to the middle cervical sympathetic ganglion. The aim of this study was to explore the sonographic features of this ganglion in anatomical specimens and cadavers and evaluate the feasibility of its visualization using high-resolution ultrasonography. Methods: We examined three cervical sympathetic-ganglion specimens and two fresh cadavers using high-resolution ultrasound to explore the sonographic features of this ganglion. Basic imaging characteristics examined included the shape, echo intensity, and location of the ganglion. Core-needle biopsy was performed to examine the suspected middle cervical sympathetic ganglion in the two fresh cadavers and verify the accuracy of the sonographic identification via pathological examination. Results: The middle cervical sympathetic ganglion appeared on high-resolution ultrasonography as an oval-shaped hypoechoic structure, with at least one continuous hypoechoic line connected to each ending in the anatomical specimens and fresh cadavers, and it was distinctly different from the adjacent lymph nodes. Discussion: Based on an adequate understanding of both its location and sonographic features, the direct visualization of the middle cervical sympathetic ganglion using high-resolution ultrasonography is feasible.

Hormonal and reproductive factors in relation to the risk of rheumatoid arthritis in women: a prospective cohort study with 223 526 participants.

OBJECTIVE: This study aimed to examine rheumatoid arthritis (RA) risk associated with hormonal and reproductive factors in women from the large cohort of the UK Biobank. METHODS: Data on hormonal and reproductive factors in women were collected from a prospective cohort of 223 526 UK Biobank participants. The potential relationship between reproductive factors and RA risk was assessed using restricted cubic spline. Hazard ratios (HR) were estimated using Cox proportional hazard regressions. RESULTS: During a median follow-up of 12.39 years, 3313 women with RA were identified. Age at menarche >14 years was associated with a greater RA risk (HR 1.13, 95% CI 1.02 to 1.26) compared with menarche at 13. The multiple adjusted HR for RA in women with menopause at <45 years was 1.46. Reproductive years <33 increased the risk of RA (HR 1.39, 95% CI 1.21 to 1.59). Compared with those with 2 children, women with ≥4 children were associated with a higher risk of RA (HR 1.18, 95% CI 1.04 to 1.34). Women who had a hysterectomy (HR 1.40, 95% CI 1.25 to 1.56) or oophorectomy (HR 1.21, 95% CI 1.08 to 1.35) had a higher risk of RA than those without a hysterectomy or oophorectomy. Both hormone replacement therapy (HRT) use (HR 1.46, 95% CI 1.35 to 1.57) and HRT duration (HR 1.02, 95% CI 1.01 to 1.03) were associated with a higher risk of RA. CONCLUSIONS: Some hormonal and reproductive factors were associated with a higher risk of RA. Hormonal and reproductive factors should be considered in risk assessment and formulating management plans in female patients with RA.

Comparison of lung cancer occurring in fibrotic versus non-fibrotic lung on chest CT.

PURPOSE: Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. METHODS: This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. RESULTS: Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p < 0.01). Adenocarcinoma was the most common cell type in both groups but more frequent in cancers occurring in non-fibrotic tissue. In the non-fibrotic lung, 1 of 126 (0.8%) of nodules measuring 1 to 6 mm were cancer. In contrast, 5 of 49 (10.2%) of nodules in fibrosis measuring 1 to 6 mm represented biopsy-proven cancer (p < 0.01). The doubling time for squamous cell cancer was shorter in the fibrotic lung compared to non-fibrotic lung, however, the difference was not statistically significant (p = 0.24). 15 incident lung nodules on second CT obtained ≤ 18 months after first CT scan was found in fibrotic lung and eight (53%) were diagnosed as cancer. CONCLUSIONS: Nodules occurring in fibrotic lung tissue are more likely to be cancer than nodules in the nonfibrotic lung. Incident pulmonary nodules in pulmonary fibrosis have a high likelihood of being cancer.

Lung nodule malignancy classification with associated pulmonary fibrosis using 3D attention-gated convolutional network with CT scans.

BACKGROUND: Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. PURPOSE: To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. MATERIALS AND METHODS: We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: (1) nodule alone (microenvironment removed); (2) nodule with surrounding lung microenvironment; and (3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, tenfold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). RESULTS: The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. CONCLUSION: The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.

Early identification of delayed wound healing in complex diabetic foot ulcers treated with a dermal regeneration template: a novel clinical target and its risk factors.

BACKGROUND: The dermal regeneration template (DRT), a tissue-engineered skin substitute composing a permanent dermal matrix and an upper temporary silicone layer that serves as the epidermis, has demonstrated efficacy in treating uncomplicated diabetic foot ulcers (DFUs). Our institution has obtained good outcomes with DRT in patients with more complicated DFUs. Because of its chronicity, the authors are working to identify a clinical target that anticipates delayed healing early in the treatment in addition to determining the risk factors linked to this endpoint to increase prevention. MATERIALS AND METHODS: This retrospective single-center study analyzed patients with DFUs who underwent wound reconstruction using DRT between 2016 and 2021. The patients were categorized into poor or good graft-take groups based on their DRT status on the 21st day after the application. Their relationship with complete healing (CH) rate at day 180 was analyzed. Variables were collected for risk factors for poor graft take at day 21. Independent risk factors were identified after multivariable analysis. The causes of poor graft take were also reported. RESULTS: This study examined 80 patients (38 and 42 patients in the poor and good graft-take groups, respectively). On day 180, the CH rate was 86.3% overall, but the poor graft-take group had a significantly lower CH rate (76.3 vs. 95.2%, P =0.021) than the good graft-take group. Our analysis identified four independent risk factors: transcutaneous oxygen pressure less than 30 mmHg (odds ratio, 154.14), off-loading device usage (0.03), diabetic neuropathy (6.51), and toe wound (0.20). The most frequent cause of poor graft take was infection (44.7%), followed by vascular compromise (21.1%) and hematoma (15.8%). CONCLUSION: Our study introduces the novel concept of poor graft take at day 21 associated with delayed wound healing. Four independent risk factors were identified, which allows physicians to arrange interventions to mitigate their effects or select patients more precisely. DRT represents a viable alternative to address DFUs, even in complicated wounds. A subsequent split-thickness skin graft is not always necessary to achieve CH.

The rare circulating tumor microemboli as a biomarker contributes to predicting early colorectal cancer recurrences after medical treatment.

Early prognosis of cancer recurrence remains difficult partially due to insufficient and ineffective screening biomarkers or regimes. This study evaluated the rare circulating tumor microemboli (CTM) from liquid biopsy individually and together with circulating tumor cells (CTCs) and serum CEA/CA19-9 in a panel, on early prediction of colorectal cancer (CRC) recurrence. Stained CTCs/CTM were detected by a microfluidic chip-based automatic rare-cell imaging platform. ROC, AUC, Kaplan-Meier survival, and Cox proportional hazard models regarding 4 selected biomarkers were analyzed. The relative risk, odds ratio, predictive accuracy, and positive/negative predictive value of biomarkers individually and in combination, to predict CRC recurrence were assessed and preliminarily validated. The EpCAM+Hochest+CD45- CTCs/CTM could be found in all cancer stages, where more recurrences were observed in late-stage cases. Significant correlations between CTCs/CTM with metastatic stages and clinical treatment were illustrated. CA19-9 and CTM could be seen as independent risk factors in patient survivals, while stratified patients by grouped biomarkers on the Kaplan-Meier analyses presented more significant differences in predicting CRC recurrences. By monitoring the panel of selected biomarkers, disease progressions of 4 CRC patients during follow-up visits after first treatments within 3 years were predicted successfully. This study unveiled the value of rare CTM on clinical studies and a panel of selected biomarkers on predicting CRC recurrences in patients at the early time after medical treatment, in which the CTM and serum CA19-9 could be applied in clinical surveillance and CRC management to improve the accuracy.

Staphylococcus aureus lysate induces an IgE response via memory B cells in nasal polyps.

BACKGROUND: Locally increased IgE levels plays a pathologic role in chronic rhinosinusitis with nasal polyps (CRSwNP). OBJECTIVE: This study aimed to investigate whether Staphylococcus aureus could induce aberrant IgE synthesis in CRSwNP and the potential mechanisms involved. METHODS: Total IgE, IL-4, IL-5, and IL-13 concentrations in the supernatants of the cultures stimulated with S aureus lysate were assessed by ELISA. S aureus-induced cellular responses were investigated by single-cell RNA sequencing. Flow cytometry and quantitative reverse transcription PCR were used to analyze B-cell subsets and stimulated cell ε-germline transcript expression, respectively. IgE-positive B-cell and germinal center localization were assessed by immunohistochemistry and immunofluorescence. RESULTS: S aureus lysate induced IgE production in the supernatants of nasal polyp (NP) tissues but not in those of healthy nasal mucosa. Moreover, IgE levels increased from days 2 to 4 after stimulation, paralleling the enhanced ε-germline transcript, IL-5, and IL-13 expression. Single-cell RNA sequencing revealed that there were increased IL-5 and IL-13 in group 2 innate lymphoid cells and identified a clonal overlap between unstimulated memory B cells and S aureus-stimulated plasma cells. The enriched IgE within NPs was mainly produced by IgE-negative memory B cells. Cellular evidence indicated that the IgE memory response to S aureus might also exist in the peripheral blood of CRSwNP patients. The S aureus-induced IgE memory response was associated with elevated IgE levels in NPs, asthma, and postoperative CRSwNP recurrence. CONCLUSIONS: S aureus induced an IgE response via IgE-negative memory B cells in CRSwNP patients, possibly contributing to CRSwNP development.

A Direct Current-Sensing VCO-Based 2nd-Order Continuous-Time Sigma-Delta Modulator for Biosensor Readout Applications.

A second-order voltage-controlled oscillator (VCO)-based continuous-time sigma-delta modulator (CTSDM) for current-sensing readout applications is proposed. Current signals from the sensor can directly be quantized by the proposed VCO-based CTSDM, which does not require any extra trans-impedance amplifiers. With the proportional-integral (PI) structure and a VCO phase integrator, the capability of second-order noise shaping is available to reduce the in-band quantization noise. The PI structure can be simply realized by a resistor in series with the integrating capacitor, which can reduce the architecture complexity and maintain the stability of the system. The current-steering digital-to-analog converter with tail and sink current sources is used on the feedback path for the subtraction of the current-type input signal. All the components of the circuit are scaling friendly and applicable to current-sensing readout applications in the Internet of Things (IoT). The proposed VCO-based CTSDM implemented in a 0.18-µm standard CMOS process has a measured signal-to-noise and distortion ratio (SNDR) of 74.6 dB at 10 kHz bandwidth and consumes 44.8 µw only under a supply voltage of 1.2 V, which can achieve a Figure-of-Merit (FoM) of 160.76 dB.