Comparison of two single-pill dual combination antihypertensive therapies in Chinese patients: a randomized, controlled trial.

BACKGROUND: Current hypertension guidelines recommend combination of an angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker with a calcium-channel blocker or thiazide diuretic as initial antihypertensive therapy in patients with monotherapy uncontrolled hypertension. However, to what extent these two different combinations are comparable in blood pressure (BP)-lowering efficacy and safety remains under investigation, especially in the Chinese population. We investigated the BP-lowering efficacy and safety of the amlodipine/benazepril and benazepril/hydrochlorothiazide dual therapies in Chinese patients. METHODS: In a multi-center, randomized, actively controlled, parallel-group trial, we enrolled patients with stage 1 or 2 hypertension from July 2018 to June 2021 in 20 hospitals and community health centers across China. Of the 894 screened patients, 560 eligible patients were randomly assigned to amlodipine/benazepril 5/10 mg (n = 282) or benazepril/hydrochlorothiazide 10/12.5 mg (n = 278), with 213 and 212 patients, respectively, who completed the study and had a valid repeat ambulatory BP recording during follow-up and were included in the efficacy analysis. The primary outcome was the change from baseline to 24 weeks of treatment in 24-h ambulatory systolic BP. Adverse events including symptoms and clinically significant changes in physical examinations and laboratory findings were recorded for safety analysis. RESULTS: In the efficacy analysis (n = 425), the primary outcome, 24-h ambulatory systolic BP reduction, was - 13.8 ± 1.2 mmHg in the amlodipine/benazepril group and - 12.3 ± 1.2 mmHg in the benazepril/hydrochlorothiazide group, with a between-group difference of - 1.51 (p = 0.36) mmHg. The between-group differences for major secondary outcomes were - 1.47 (p = 0.18) in 24-h diastolic BP, - 2.86 (p = 0.13) and - 2.74 (p = 0.03) in daytime systolic and diastolic BP, and - 0.45 (p = 0.82) and - 0.93 (p = 0.44) in nighttime systolic and diastolic BP. In the safety analysis (n = 560), the incidence rate of dry cough was significantly lower in the amlodipine/benazepril group than in the benazepril/hydrochlorothiazide group (5.3% vs 10.1%, p = 0.04). CONCLUSIONS: The amlodipine/benazepril and benazepril/hydrochlorothiazide dual therapies were comparable in ambulatory systolic BP lowering. The former combination, compared with the latter, had a greater BP-lowering effect in the daytime and a lower incidence rate of dry cough. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03682692. Registered on 18 September 2018.

Circadian Rest-Activity Rhythms, Delirium Risk, and Progression to Dementia.

OBJECTIVE: Delirium is a complex neurocognitive syndrome suspected to be bidirectionally linked to dementia. Circadian rhythm disturbances likely contribute to dementia pathogenesis, but whether these disturbances are related to delirium risk and progression to all-cause dementia is unknown. METHODS: We analyzed continuous actigraphy data from 53,417 middle-aged or older UK Biobank participants during a median 5 years of follow-up. Four measures were used to characterize the 24-hour daily rest-activity rhythms (RARs): normalized amplitude, acrophase representing the peak activity time, interdaily stability, and intradaily variability (IV) for fragmentation of the rhythm. Cox proportional hazards models examined whether RARs predicted incident delirium (n = 551) and progression to dementia (n = 61). RESULTS: Suppressed 24-hour amplitude, lowest (Q1) versus highest (Q4) quartile (hazard ratio [HR]Q1 vs Q4 = 1.94, 95% confidence interval [CI] = 1.53-2.46, p < 0.001), and more fragmented (higher IV: HRQ4 vs Q1 = 1.49, 95% CI = 1.18-1.88, p < 0.001) rhythms predicted higher delirium risk, after adjusting for age, sex, education, cognitive performance, sleep duration/disturbances, and comorbidities. In those free from dementia, each hour of delayed acrophase was associated with delirium risk (HR = 1.13, 95% CI = 1.04-1.23, p = 0.003). Suppressed 24-hour amplitude was associated with increased risk of progression from delirium to new onset dementia (HR = 1.31, 95% CI = 1.03-1.67, p = 0.03 for each 1-standard deviation decrease). INTERPRETATION: Twenty-four-hour daily RAR suppression, fragmentation, and potentially delayed acrophase were associated with delirium risk. Subsequent progression to dementia was more likely in delirium cases with suppressed rhythms. The presence of RAR disturbances before delirium and prior to progression to dementia suggests that these disturbances may predict higher risk and be involved in early disease pathogenesis. ANN NEUROL 2023;93:1145-1157.

The impacts of biologic treatment on metabolic profiling in psoriasis.

Psoriasis is an immune-mediated inflammatory disease commonly accompanied by various metabolic disorders. It is widely known that biologics could affect the metabolic status and comorbidities in psoriasis patients, however, the effects of biologics on metabolism in psoriasis patients remain poorly understood. The aim of this study was to elucidate the characteristic changes of metabolic profiling in psoriasis vulgaris (PsV) patients before and after applying biologics. Plasma samples were collected from a retrospective cohort of 43 PsV patients. Non-targeted metabolomics analyses were performed using liquid chromatography-mass spectrometry (LC-MS) to compare the metabolic profiles before and after applying adalimumab (ADA) or ixekizumab (IXE) for 4 weeks. Additionally, correlation analyses were conducted to investigate the associations between metabolite expression levels and clinical characteristics. The biologics significantly affected the metabolic profiles of PsV patients especially in glycerophospholipids (GPs). First, phosphatidylcholine (PC), unsaturated lysophosphatidylcholine (LPC), unsaturated lysophosphatidic acid (LPA) and unsaturated lysophosphatidylethanolamine (LPE) were significantly up-regulated, whereas phosphatidylethanolamine (PE), saturated LPC, saturated LPA and saturated LPE were predominantly down-regulated after biologic treatment. What is more, the changes in PE and LPA were mainly observed after applying IXE instead of ADA. Second, we also found GPs including PC, unsaturated LPC, unsaturated LPA and unsaturated LPE were primarily negatively correlated with disease severity, whereas, PE, saturated LPC, saturated LPA and saturated LPE displayed inverse correlations. Biologics could affect GP metabolism and facilitate the transition of metabolic status from a pro-inflammatory to an anti-inflammatory phenotype in PsV patients.

Defining the Minimal Important Change and Meaningful Change Value of the Disease Activity Index for Psoriatic Arthritis: A Chinese Longitudinal Study.

OBJECTIVE: To determine the minimal important change (MIC) and meaningful change value (MCV) of the Disease Activity Index for Psoriatic Arthritis (DAPSA) and the effect size (ES) of DAPSA. METHODS: This was a retrospective cohort study, recruiting 106 patients who agreed to participate in the research from the Department of Dermatology, Xiangya Hospital, between November 1, 2019, and April 1, 2023. An anchor-based method using linear regression analyses was used to determine the MICs and MCVs of the DAPSA. The anchor question assessed whether the patient's well-being had changed since their previous visit, employing a 5-point Likert scale that ranged from "much improved" to "much deteriorated." RESULTS: The overall MIC value was 8.4 (95% CI 0.01-16.75). The MIC improvement was 9.5 (95% CI 0.89-18.14) and MIC deterioration was 1.1 (95% CI -9.81 to 12.05). The overall MCV was 10.5 (95% CI 4.34-16.72). MCV improvement was 11.4 (95% CI 5.95-16.95) and MCV deterioration was 1.1 (95% CI -9.81 to 12.05). The ES was 0.6. CONCLUSION: A change in DAPSA of 8.4 is indicative of an MIC, offering physicians an additional means to contextualize the patient's perception of disease activity during treatment, and a change in DAPSA of 10.5 is likely to be regarded as MCV. These values can enhance the utility of DAPSA in psoriatic arthritis clinical trials.

Imaging ultra-weak UV light below 100 pW cm-2 using a 4H-SiC photodetector with an Al2O3 interfacial layer.

Weak light detection is crucial in various practical applications such as night vision systems, flame monitoring, and underwater operations. Decreasing the dark current of a photodetector can effectively mitigate noises, consequently enhancing the signal-to-noise ratio and overall weak light detection performance. Herein, we demonstrate a 4H-SiC UV photodetector capable of detecting extremely weak UV light. This device comprises a photosensitive layer of 4H-SiC, two TiN electrodes and an atomically thin Al2O3 interfacial layer between TiN and the C surface of 4H-SiC. Under 360 nm UV light illumination, the proposed Al2O3 device demonstrates an ultra-low dark current of 18 fA, possibly benefiting from the effective passivation of interfacial carriers, and a boosted photo-to-dark current ratio of 6.7 × 107. Consequently, it achieves a weak-light detection limit as low as 31.8 pW cm-2, significantly outperforming the control device lacking Al2O3. When compared to previously reported SiC photodetectors, our Al2O3 device boasts an exceptional large linear dynamic range of 172 dB. Leveraging this, we construct a photodetector array capable of clearly imaging an object under ultra-weak light illumination below the 100 pW cm-2 level. The proposed photodetector represents a significant advancement in the development of highly sensitive image sensors for weak light detection.

Pestanoid A, a Rearranged Pimarane Diterpenoid Osteoclastogenesis Inhibitor from a Marine Mesophotic Zone Chalinidae Sponge-Associated Fungus, Pestalotiopsis sp. NBUF145.

One novel rearranged pimarane diterpenoid, pestanoid A (1), and two reported molecules, nodulisporenones A (2) and B (3), were discovered from Pestalotiopsis sp. NBUF145 fungus associated with a 62 m deep mesophotic ("twilight") zone Chalinidae sponge. The structures of 1-3 were identified by spectrometry, spectroscopy, quantum-chemical calculations, and X-ray crystallography. Compounds 1 and 2 inhibited bone marrow monocyte osteoclastogenesis in vitro with the IC50 values 4.2 ± 0.2 µM and 3.0 ± 0.4 µM, respectively, without observed cytotoxicity. Both 1 and 2 suppressed the receptor activator of NF-kB ligand-induced MAPK and NF-κB signaling by inhibiting the phosphorylation of ERK1/2-JNK1/2-p38 MAPKs and NF-κB nuclear translocation.

Delineating cognitive resilience using fractal regulation: Cross-sectional and longitudinal evidence from the Rush Memory and Aging Project.

INTRODUCTION: Degradation of fractal patterns in actigraphy independently predicts dementia risk. Such observations motivated the study to understand the role of fractal regulation in the context of neuropathologies. METHODS: We examined associations of fractal regulation with neuropathologies and longitudinal cognitive changes in 533 older participants who were followed annually with actigraphy and cognitive assessments until death with brain autopsy performed. Two measures for fractal patterns were extracted from actigraphy, namely, α1 (representing the fractal regulation at time scales of <90 min) and α2 (for time scales 2 to 10 h). RESULTS: We found that larger α1 was associated with lower burdens of Lewy body disease or cerebrovascular disease pathologies; both α1 and α2 were associated with cognitive decline. They explained an additional significant portion of the variance in the rate of cognitive decline above and beyond neuropathologies. DISCUSSION: Fractal patterns may be used as a biomarker for cognitive resilience against dementia-related neuropathologies.

Discovery of Natural Potent HMG-CoA Reductase Degraders for Lowering Cholesterol.

Exploitation of key protected wild plant resources makes great sense, but their limited populations become the major barrier. A particular strategy for breaking this barrier was inspired by the exploration of a resource-saving fungal endophyte Penicillium sp. DG23, which inhabits the key protected wild plant Schisandra macrocarpa. Chemical studies on the cultures of this strain afforded eight novel indole diterpenoids, schipenindolenes A-H (1-8), belonging to six diverse skeleton types. Importantly, semisyntheses suggested some key nonenzymatic reactions constructing these molecules and provided targeted compounds, in particular schipenindolene A (Spid A, 1) with low natural abundance. Remarkably, Spid A was the most potent HMG-CoA reductase (HMGCR) degrader among the indole diterpenoid family. It degraded statin-induced accumulation of HMGCR protein, decreased cholesterol levels and acted synergistically with statin to further lower cholesterol. Mechanistically, transcriptomic and proteomic profiling suggested that Spid A potentially activated the endoplasmic reticulum-associated degradation (ERAD) pathway to enhance the degradation of HMGCR, while simultaneously inhibiting the statin-activated expression of many key enzymes in the cholesterol and fatty acid synthesis pathways, thereby strengthening the efficacy of statins and potentially reducing the side effects of statins. Collectively, this study suggests the potential of Spid A for treating cardiovascular disease.

Insights into ZmWAKL in maize kernel development: genome-wide investigation and GA-mediated transcription.

BACKGROUND: The functional roles of the Wall Associated Kinase (WAK) and Wall Associated Kinase Like (WAKL) families in cellular expansion and developmental processes have been well-established. However, the molecular regulation of these kinases in maize development is limited due to the absence of comprehensive genome-wide studies. RESULTS: Through an in-depth analysis, we identified 58 maize WAKL genes, and classified them into three distinct phylogenetic clusters. Moreover, structural prediction analysis showed functional conservation among WAKLs across maize. Promoter analysis uncovered the existence of cis-acting elements associated with the transcriptional regulation of ZmWAKL genes by Gibberellic acid (GA). To further elucidate the role of WAKL genes in maize kernels, we focused on three highly expressed genes, viz ZmWAKL38, ZmWAKL42 and ZmWAKL52. Co-expression analyses revealed that their expression patterns exhibited a remarkable correlation with GA-responsive transcription factors (TF) TF5, TF6, and TF8, which displayed preferential expression in kernels. RT-qPCR analysis validated the upregulation of ZmWAKL38, ZmWAKL42, ZmWAKL52, TF5, TF6, and TF8 following GA treatment. Additionally, ZmWAKL52 showed significant increase of transcription in the present of TF8, with ZmWAKL52 localizing in both the plasma membrane and cell wall. TF5 positively regulated ZmWAKL38, while TF6 positively regulated ZmWAKL42. CONCLUSIONS: Collectively, these findings provide novel insights into the characterization and regulatory mechanisms of specific ZmWAKL genes involved in maize kernel development, offering prospects for their utilization in maize breeding programs.

Evaluation of A Computer-Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors.

Prostate cancer (PCa) is the most common noncutaneous cancer in men in the Western world. In addition to accurate diagnosis, Gleason grading and tumor volume estimates are critical for patient management. Computer-aided detection (CADe) software can be used to facilitate the diagnosis and improve the diagnostic accuracy and reporting consistency. However, preanalytical factors such as fixation and staining of prostate biopsy specimens and whole slide images (WSI) on scanners can vary significantly between pathology laboratories and may, therefore, impact the quality of WSI and utility of CADe algorithms. We evaluated the performance of a CADe software in predicting PCa on WSIs of prostate biopsy specimens and focused on whether there were any significant differences in image quality between WSIs obtained on different scanners and specimens from different histopathology laboratories. Thirty prostate biopsy specimens from 2 histopathology laboratories in the United States were included in this study. The hematoxylin and eosin slides of the biopsy specimens were scanned on 3 scanners, generating 90 WSIs. These WSIs were then analyzed using a CADe software (INIFY Prostate, Algorithm), which identified and annotated all areas suspicious for PCa and calculated the tumor volume (percentage area of the biopsy core involved). Study pathologists then reviewed the Algorithm's annotations and tumor volume calculation to confirm the diagnosis and identify benign glands that were misclassified as cancer (false positive) and cancer glands that were misclassified as benign (false negative). The CADe software worked equally well on WSIs from all 3 scanners and from both laboratories, with similar sensitivity and specificity. The overall sensitivity was 99.4%, and specificity was 97%. The percentage of suspicious cancer areas calculated by the Algorithm was similar for all 3 scanners. For WSIs with small foci of cancer (<1 mm), the Algorithm identified all cancer glands (sensitivity, 100%). Preanalytical factors had no significant impact on whole slide imaging and subsequent application of a CADe software. Prediction accuracy could potentially be further improved by processing biopsy specimens in a centralized histology laboratory and training the Algorithm on WSIs from the same laboratory in order to minimize variations in preanalytical factors and optimize the diagnostic performance of the Algorithm.

Highly Efficient and Stable Perovskite Solar Cells: Competitive Crystallization Strategy and Synergistic Passivation.

Defects of perovskite (PVK) films are one of the main obstacles to achieving high-performance perovskite solar cells (PSCs). Here, the authors fabricated highly efficient and stable PSCs by introducing prolinamide (ProA) into the PbI2 precursor solution, which improves the performance of PSCs by the competitive crystallization and efficient defect passivation of perovskite. The theoretical and experimental results indicate that ProA forms an adduct with PbI2 , competes with free I- to coordinate with Pb2+ , leads to the increase of the energy barrier of crystallization, and slows down the crystallization rate. Furthermore, the dual-site synergistic passivation of ProA is revealed by density functional theory (DFT) calculations and experimental results. ProA effectively reduces non-radiative recombination in the resultant films to improve the photovoltaic performance of PSCs. Notably, ProA-assisted PSCs achieve 24.61% power conversion efficiency (PCE) for the champion device and the stability of PSCs devices under ambient and thermal environments is improved.

Prediction of biochemical nonresolution in patients with chronic drug-induced liver injury: A large multicenter study.

BACKGROUND AND AIMS: To clarify high-risk factors and develop a nomogram model to predict biochemical resolution or biochemical nonresolution (BNR) in patients with chronic DILI. APPROACH AND RESULTS: Retrospectively, 3655 of 5326 patients with chronic DILI were enrolled from nine participating hospitals, of whom 2866 underwent liver biopsy. All of these patients were followed up for over 1 year and their clinical characteristics were retrieved from electronic medical records. The endpoint was BNR, defined as alanine aminotransferase or aspartate aminotransferase >1.5× upper limit of normal or alkaline phosphatase >1.1× ULN, at 12 months from chronic DILI diagnosis. The noninvasive high-risk factors for BNR identified by multivariable logistic regression were used to establish a nomogram, which was validated in an independent external cohort. Finally, 19.3% (707 of 3655) patients presented with BNR. Histologically, with the increase in liver inflammation grades and fibrosis stages, the proportion of BNR significantly increased. The risk of BNR was increased by 21.3-fold in patients with significant inflammation compared to none or mild inflammation (p < 0.001). Biochemically, aspartate aminotransferase and total bilirubin, platelets, prothrombin time, sex, and age were associated with BNR and incorporated to construct a nomogram model (BNR-6) with a concordance index of 0.824 (95% CI, 0.798-0.849), which was highly consistent with liver histology. These results were successfully validated both in the internal cohort and external cohort. CONCLUSIONS: Significant liver inflammation is a robust predictor associated with biochemical nonresolution. The established BNR-6 model provides an easy-to-use approach to assess the outcome of chronic DILI.

Cytotoxic C-20 non-oxygenated ent-kaurane diterpenoids from Isodon wardii.

Twenty new ent-kaurane diterpenoids, wardiisins A-T (1-20), along with two previously undescribed artefactual compounds (21 and 22) and twelve known analogues (23-34), were isolated from the aerial part of Isodon wardii. Their structures were elucidated by comprehensive analysis of spectroscopic data and single-crystal X-ray diffraction, and most of them were found to bear unusual C-12 oxygenation. Compounds 4, 7, 8, 19, 20, 21 exhibited remarkable cytotoxicity against the cancer cell lines HL-60, SMMC-7721, A-549, MDA-MB-231, and SW480, with IC50 values ranging from 0.3 to 5.2 µM. Moreover, 7 was found to induce G2/M cell cycle arrest and promote apoptosis in SW480 cell lines.

WFS1 protein expression correlates with clinical progression of optic atrophy in patients with Wolfram syndrome.

BACKGROUND: Wolfram syndrome (WFS) is a rare disorder characterised by childhood-onset diabetes mellitus and progressive optic atrophy. Most patients have variants in the WFS1 gene. We undertook functional studies of WFS1 variants and correlated these with WFS1 protein expression and phenotype. METHODS: 9 patients with a clinical diagnosis of WFS were studied with quantitative PCR for markers of endoplasmic reticulum (ER) stress and immunoblotting of fibroblast protein extracts for WFS1 protein expression. Luciferase reporter assay was used to assess ATF-6 dependent unfolded protein response (UPR) activation. RESULTS: 6 patients with compound heterozygous nonsense mutations in WFS1 had no detectable WFS1 protein expression; 3 patients with missense variants had 4%, 45% and 48% WFS1 protein expression. One of these also had an OPA1 mutation and was reclassified as autosomal dominant optic atrophy-plus syndrome. There were no correlations between ER stress marker mRNA and WFS1 protein expression. ERSE-luciferase reporter indicated activation of the ATF6 branch of UPR in two patients tested. Patients with partial WFS1 expression showed milder visual acuity impairment (asymptomatic or colour blind only), compared with those with absent expression (registered severe vision impaired) (p=0.04). These differences remained after adjusting for duration of optic atrophy. CONCLUSIONS: Patients with WFS who have partial WFS1 protein expression present with milder visual impairment. This suggests a protective effect of partial WFS1 protein expression on the severity and perhaps progression of vision impairment and that therapies to increase residual WFS1 protein expression may be beneficial.

Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch. OBJECTIVE: We proposed and tested a convolutional neural network called SleepInceptionNet, which allows sleep classification of a single epoch using a single-channel electroencephalogram (EEG). METHODS: SleepInceptionNet is based on our systematic evaluation of the effects of different EEG preprocessing methods, EEG channels, and convolutional neural networks on automatic sleep staging performance. The evaluation was performed using polysomnography data of 883 participants (937,975 thirty-second epochs). Raw data of individual EEG channels (ie, frontal, central, and occipital) and 3 specific transformations of the data, including power spectral density, continuous wavelet transform, and short-time Fourier transform, were used separately as the inputs of the convolutional neural network models. To classify sleep stages, 7 sequential deep neural networks were tested for the 1D data (ie, raw EEG and power spectral density), and 16 image classifier convolutional neural networks were tested for the 2D data (ie, continuous wavelet transform and short-time Fourier transform time-frequency images). RESULTS: The best model, SleepInceptionNet, which uses time-frequency images developed by the continuous wavelet transform method from central single-channel EEG data as input to the InceptionV3 image classifier algorithm, achieved a Cohen κ agreement of 0.705 (SD 0.077) in reference to the gold standard polysomnography. CONCLUSIONS: SleepInceptionNet may allow real-time automated sleep staging in free-living conditions using a single-channel EEG, which may be useful for on-demand intervention or treatment during specific sleep stages.

Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application.

BACKGROUND: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently. OBJECTIVE: This study aimed to develop an image-artificial intelligence (AI)-based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis. METHODS: A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform. RESULTS: The proposed image-AI-based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users. CONCLUSIONS: An image-AI-based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists' accurate assessment in the real world and chronic disease self-management in patients with psoriasis.

Research on a Method of Locating Civil Aviation Radio Interference Sources Based on Time Difference of Arrival and Frequency Difference of Arrival for Four Unmanned Aerial Vehicles.

Monitoring and analyzing radio interference sources play a crucial role in ensuring the safe operation of civil aviation navigation, communication, airport management, and air traffic control. Traditional ground monitoring methods are slow and inadequate for tracking aerial and mobile interference sources effectively. Although flight methods such as helicopters and airships can effectively monitor aerial interference, the flight approval process is time-consuming and expensive. This paper investigates a novel approach to locating civil aviation radio interference sources using four unmanned aerial vehicles (UAVs) to address this issue. It establishes a model for aerial positioning of radio interference sources with the four UAVs and proposes a method for time synchronization and data communication among them. The paper conducts simulations of the four-UAV time-frequency difference positioning method, analyzing the geometric accuracy dilution with different deployment configurations of the UAVs, positioning biases, and root mean square errors (RMSEs) under varying interference source movement speeds. The simulation results provide crucial data to support subsequent experiments.

Correlates of Person-Specific Rates of Change in Sensor-Derived Physical Activity Metrics of Daily Living in the Rush Memory and Aging Project.

This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. A series of linear mixed-effect models were used to identify covariates independently associated with the level and annual rate of change of TDPA. Though, person-specific rates of change varied during a mean follow-up of 5 years, 1079 of 1083 showed declining TDPA. The average decline was 16%/year, with a 4% increased rate of decline for every 10 years of age older at baseline. Following variable selection using multivariate modeling with forward and then backward elimination, age, sex, education, and 3 of 27 non-demographic covariates including motor abilities, a fractal metric, and IADL disability remained significantly associated with declining TDPA accounting for 21% of its variance (9% non-demographic and 12% demographics covariates). These results show that declining TDPA occurs in many very old adults. Few covariates remained correlated with this decline and the majority of its variance remained unexplained. Further work is needed to elucidate the biology underlying TDPA and to identify other factors that account for its decline.

Technology Trends for Massive MIMO towards 6G.

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and performance of future massive MIMO systems will be amplified through the incorporation of cutting-edge technologies, structures, and strategies. These include intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), Terahertz (THz) communications, and cell-free architectures. In addition, an array of diverse applications built on the foundation of massive MIMO will continue to proliferate and thrive. These encompass wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, and inter-planetary communications, among others.

Daytime napping and Alzheimer's dementia: A potential bidirectional relationship.

INTRODUCTION: Daytime napping is frequently seen in older adults. The longitudinal relationship between daytime napping and cognitive aging is unknown. METHODS: Using data from 1401 participants of the Rush Memory and Aging Project, we examined the longitudinal change of daytime napping inferred objectively by actigraphy, and the association with incident Alzheimer's dementia during up to 14-year follow-up. RESULTS: Older adults tended to nap longer and more frequently with aging, while the progression of Alzheimer's dementia accelerates this change by more than doubling the annual increases in nap duration/frequency. Longer and more frequent daytime naps were associated with higher risk of Alzheimer's dementia. Interestingly, more excessive (longer or more frequent) daytime napping was correlated with worse cognition a year later, and conversely, worse cognition was correlated with more excessive naps a year later. DISCUSSION: Excessive daytime napping and Alzheimer's dementia may possess a bidirectional relationship or share common pathophysiological mechanisms.