Olfactory EEG induced by odor: Used for food identification and pleasure analysis.

As the need for food authenticity verification increases, sensory evaluation of food odors has become widely recognized. This study presents a theory based on electroencephalography (EEG) to create an Olfactory Perception Dimensional Space (EEG-OPDS), using feature engineering and ensemble learning to establish material and emotional spaces based on odor perception and pleasure. The study examines the intrinsic connection between these two spaces and explores the mechanisms of integration and differentiation in constructing the OPDS. This method effectively visualizes various types of food odors while identifying their perceptual intensity and pleasantness. The average classification accuracy for odor recognition in an eight-category experiment is 96.1%. Conversely, the average classification accuracy for sensory pleasantness recognition in a two-category experiment is 98.8%. The theoretical approach proposed in this study, based on olfactory EEG signals to construct an OPDS, captures the subtle perceptual differences and individualized pleasantness responses to food odors.

Effect of pulsed electric field (PEF) on NaCl diffusion in beef and consequence on meat quality.

The impact of various field strength (2, 3, 4 kV/cm) and treatment time (60s and 90s) combinations on NaCl content and diffusion coefficient of beef were evaluated in the current study. Weight change, water content, water holding capacity, and texture of beef after brining were also explored. The results demonstrated pulsed electric field (PEF) pre-treatment significantly increased NaCl uptake when the brining time was 150 min (P < 0.05). The maximum NaCl content increased by 19.50% and the diffusion coefficient increased by 58.50%. Relatively mild PEF (60s) could improve beef qualities, but longer treatment time (90s) was detrimental to these qualities. Meanwhile, more complete myofibrillar structure and lower lipid oxidation extent were observed in the samples treated by PEF, contributing to the higher a* values. In conclusion, short processing time (60s) and high field strength (4 kV/cm) treatment is a potential strategy for meat brining acceleration and quality improvement in practical industrial production.

Photochemical fate of ß-blocker pindolol in riverine and its downstream coastal waters.

Pindolol (PIN) is a commonly used ß-blocker drug and has been frequently detected in various natural waters. Comprehensive understanding of its environmental photochemical transformation is necessary to assess its environmental risk. In this study, the photodegradation kinetics and mechanisms of PIN in both freshwater and coastal water were investigated for the first time. The photodegradation experiments were carried out by steady-state photochemical experiment under simulated sunlight irradiation. The results showed that the photodegradation rate of PIN in the freshwater of the Pearl River estuary was significantly faster than that in its downstream coastal water. In river water, PIN can undergo both direct photolysis and indirect photolysis induced by riverine dissolved organic matter (DOM) mainly through excited triplet-state of DOM and singlet oxygen, while direct photolysis dominated its degradation in coastal water. The promotion effect was found to be much greater for Suwannee River Natural Organic Matter (SRNOM) than that of the sampled riverine DOM, due to its high steady-state concentrations of reactive species. Interestingly, coastal DOM in northern and southern China were found to have similar promotion effects on PIN photodegradation for the first time, but both less than that of riverine DOM. A total of seven degradation products of PIN resulting from hydroxylation, hydrogen abstraction and cleavage of ether bond were identified. Biological toxicity of one products were found to be higher than that of PIN. These results are of significance for knowing the persistence and ecological risk of PIN in natural waters.

Robust deep learning from incomplete annotation for accurate lung nodule detection.

Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of extensive, meticulously annotated dataset. In this paper, we explore the utilization of an incompletely annotated dataset for pulmonary nodules detection and introduce the FULFIL (Forecasting Uncompleted Labels For Inexpensive Lung nodule detection) algorithm as an innovative approach. By instructing annotators to label only the nodules they are most confident about, without requiring complete coverage, we can substantially reduce annotation costs. Nevertheless, this approach results in an incompletely annotated dataset, which presents challenges when training deep learning models. Within the FULFIL algorithm, we employ Graph Convolution Network (GCN) to discover the relationships between annotated and unannotated nodules for self-adaptively completing the annotation. Meanwhile, a teacher-student framework is employed for self-adaptive learning using the completed annotation dataset. Furthermore, we have designed a Dual-Views loss to leverage different data perspectives, aiding the model in acquiring robust features and enhancing generalization. We carried out experiments using the LUng Nodule Analysis (LUNA) dataset, achieving a sensitivity of 0.574 at a False positives per scan (FPs/scan) of 0.125 with only 10% instance-level annotations for nodules. This performance outperformed comparative methods by 7.00%. Experimental comparisons were conducted to evaluate the performance of our model and human experts on test dataset. The results demonstrate that our model can achieve a comparable level of performance to that of human experts. The comprehensive experimental results demonstrate that FULFIL can effectively leverage an incomplete pulmonary nodule dataset to develop a robust deep learning model, making it a promising tool for assisting in lung nodule detection.

Depression risk in chronic tonsillitis patients underwent tonsillectomy: a global federated health network analysis.

Background: Tonsillectomy is a common surgery in the US, with possible postoperative complications. While small studies indicate postoperative depressive symptoms may occur, large-scale evidence is lacking on the tonsillectomy-depression link. Methods: We conducted a retrospective cohort study using the TriNetX US collaborative network, offering de-identified electronic health data from 59 collaborative healthcare organizations (HCOs) in the United States. In this study, people being diagnosed of chronic tonsillitis between January 2005 and December 2017 were enrolled. Patients deceased, with previous record of cancers or psychiatric events before index date were excluded. 14,874 chronic tonsillitis patients undergoing tonsillectomy were propensity score matched 1:1 to controls for age, sex, and race. New-onset depression risks were evaluated over 5 years post-tonsillectomy and stratified by age and sex. Confounders were adjusted for including demographics, medications, comorbidities and socioeconomic statuses. Results: After matching, the difference of key baseline characteristics including age, sex, comedications status and obesity status was insignificant between tonsillectomy and non-tonsillectomy groups. Tonsillectomy had a 1.29 times higher 5-year depression risk versus matched controls (95% CI, 1.19-1.40), with elevated risks seen at 1 year (HR=1.51; 95% CI, 1.28-1.79) and 3 years (HR=1.30; 95% CI, 1.18-1.43). By stratifications, risks were increased for both males (HR=1.30; 95% CI, 1.08-1.57) and females (HR=1.30; 95% CI, 1.18-1.42), and significantly higher in ages 18-64 years (HR=1.37; 1.26-1.49), but no significance observed for those 65 years and older. After performing sensitivity analyses and applying washout periods of 6, 12, and 36 months, the outcome remained consistent with unadjusted results. Conclusion: This real-world analysis found tonsillectomy was associated with a 30% higher 5-year depression risk versus matched non-tonsillectomy patients with chronic tonsillitis. Further mechanistic research is needed to clarify the pathophysiologic association between depression and tonsillectomy. Depression is not commonly mentioned in the current post-tonsillectomy care realm; however, the outcome of our study emphasized the possibility of these suffering condition after operation. Attention to psychological impacts following tonsillectomy is warranted to support patient well-being, leading to better management of post-tonsillectomy individuals.

Hidradenitis suppurativa as a potential risk factor of periodontitis: a multi-center, propensity-score-matched cohort study.

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease associated with systemic symptoms. Periodontitis, a prevalent dental disease, shares immune-mediated inflammatory characteristics with HS. This cohort study aims to evaluate the association between HS and periodontitis. Methods: Using the TriNetX research network, a global-federated database of electronic health records, we conducted a retrospective cohort study. People being diagnosed of HS were identified and propensity score matching was performed to identify proper control group, via balancing critical covariates Within the follow-up time of 1 year, 3 year and 5 years, hazard ratios were calculated to assess the risk of periodontitis in HS patients compared to controls. Results: Within the 53,968 HS patients and the same number of matched controls, the HS patients exhibited a significantly increased risk of developing periodontitis compared to controls after 3 years of follow-up (HR: 1.64, 95% CI: 1.11, 2.44) and 5 years of follow-up (HR: 1.64, 95% CI: 1.21, 2.24) of follow-up. Sensitivity analyses supported these findings under various matching models and washout periods. While comparing with patients with psoriasis, the association between HS and periodontitis remained significant (HR: 1.73, 95% CI: 1.23, 2.44). Conclusion: The observed increased risk suggests the need for heightened awareness and potential interdisciplinary care for individuals with HS to address periodontal health.

Incident Use of Hydroxychloroquine for the Treatment of Rheumatoid Arthritis and Systemic Lupus Erythematosus During the COVID-19 Pandemic.

OBJECTIVE: We studied whether the use of hydroxychloroquine (HCQ) for COVID-19 resulted in supply shortages for patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). METHODS: We used US claims data (IQVIA PHARMETRICS® Plus for Academics [PHARMETRICS]) and hospital electronic records from Spain (Institut Municipal d'Assistència Sanitària Information System [IMASIS]) to estimate monthly rates of HCQ use between January 2019 and March 2022, in the general population and in patients with RA and SLE. Methotrexate (MTX) use was estimated as a control. RESULTS: More than 13.5 million individuals (13,311,811 PHARMETRICS, 207,646 IMASIS) were included in the general population cohort. RA and SLE cohorts enrolled 135,259 and 39,295 patients, respectively, in PHARMETRICS. Incidence of MTX and HCQ were stable before March 2020. On March 2020, the incidence of HCQ increased by 9- and 67-fold in PHARMETRICS and IMASIS, respectively, and decreased in May 2020. Usage rates of HCQ went back to prepandemic trends in Spain but remained high in the United States, mimicking waves of COVID-19. No significant changes in HCQ use were noted among patients with RA and SLE. MTX use rates decreased during HCQ approval period for COVID-19 treatment. CONCLUSION: Use of HCQ increased dramatically in the general population in both Spain and the United States during March and April 2020. Whereas Spain returned to prepandemic rates after the first wave, use of HCQ remained high and followed waves of COVID-19 in the United States. However, we found no evidence of general shortages in the use of HCQ for both RA and SLE in the United States.

Investigating the Influence of Diverse Functionalized Carbon Nanotubes as Conductive Fibers on Paper-Based Sulfur Cathodes in Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are expected to be one of the next generations of high-energy-density battery systems due to their high theoretical energy density of 2600 Wh kg-1. Embracing the trends toward flexibility, lightweight design, and cost-effectiveness, paper-based electrodes offer a promising alternative to traditional coated cathodes in Li-S batteries. Within paper-based electrodes, conductive fibers such as carbon nanotubes (CNTs) play a crucial role. They help to form a three-dimensional network within the paper matrix to ensure structural integrity over extended cycling while mitigating the shuttle effect by confining sulfur within the cathode. Herein, we explore how variously functionalized CNTs, serving as conductive fibers, impact the physical and electrochemical characteristics of paper-based sulfur cathodes in Li-S batteries. Specifically, graphitized hydroxylated carbon nanotubes (G-CNTs) exhibit remarkable capacity at low currents owing to their excellent conductivity and interaction with lithium polysulfide (LiPS), achieving the highest initial specific capacity of 1033 mAh g-1 at 0.25 C (1.1 mA cm-2). Aminated multi-walled carbon nanotubes (NH2-CNTs) demonstrate an enhanced affinity for LiPS due to the -NH2 groups. However, the uneven distribution of these fibers may induce electrode surface passivation during charge-discharge cycles. Notably, hydroxylated multi-walled carbon nanotubes (OH-CNTs) can establish a uniform and stable 3D network with plant fibers, showcasing superior mechanical properties and helping to mitigate Li2S agglomeration while preserving the electrode porosity. The paper-based electrode integrated with OH-CNTs even retains a specific capacity of approximately 800 mAh g-1 at about 1.25 C (5 mA cm-2), demonstrating good sulfur utilization and rate capacity compared to other CNT variants.

Multi-grained Radiology Report Generation with Sentence-level Image-language Contrastive Learning.

The automatic generation of accurate radiology reports is of great clinical importance and has drawn growing research interest. However, it is still a challenging task due to the imbalance between normal and abnormal descriptions and the multi-sentence and multi-topic nature of radiology reports. These features result in significant challenges to generating accurate descriptions for medical images, especially the important abnormal findings. Previous methods to tackle these problems rely heavily on extra manual annotations, which are expensive to acquire. We propose a multi-grained report generation framework incorporating sentence-level image-sentence contrastive learning, which does not require any extra labeling but effectively learns knowledge from the image-report pairs. We first introduce contrastive learning as an auxiliary task for image feature learning. Different from previous contrastive methods, we exploit the multi-topic nature of imaging reports and perform fine-grained contrastive learning by extracting sentence topics and contents and contrasting between sentence contents and refined image contents guided by sentence topics. This forces the model to learn distinct abnormal image features for each specific topic. During generation, we use two decoders to first generate coarse sentence topics and then the fine-grained text of each sentence. We directly supervise the intermediate topics using sentence topics learned by our contrastive objective. This strengthens the generation constraint and enables independent fine-tuning of the decoders using reinforcement learning, which further boosts model performance. Experiments on two large-scale datasets MIMIC-CXR and IU-Xray demonstrate that our approach outperforms existing state-of-the-art methods, evaluated by both language generation metrics and clinical accuracy.

Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.

OBJECTIVES: We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis. MATERIALS AND METHODS: Periapical radiographs (PERs) and clinical data were collected. The CNNs including Alexnet, VGG16, and ResNet18 were trained on PER to establish the PER-CNN models for no periodontal bone loss (PBL) and PBL. The CAs including random forest (RF), support vector machine (SVM), naive Bayes (NB), logistic regression (LR), and k-nearest neighbor (KNN) were added to the PER-CNN model for control, stage I, stage II and stage III/IV periodontitis. Heat map was produced using a gradient-weighted class activation mapping method to visualize the regions of interest of the PER-Alexnet model. Clustering analysis was performed based on the ten PER-CNN scores and the clinical characteristics. RESULTS: The accuracy of the PER-Alexnet and PER-VGG16 models with the higher performance was 0.872 and 0.853, respectively. The accuracy of the PER-Alexnet + RF model with the highest performance for control, stage I, stage II and stage III/IV was 0.968, 0.960, 0.835 and 0.842, respectively. Heat map showed that the regions of interest predicted by the model were periodontitis bone lesions. We found that age and smoking were significantly related to periodontitis based on the PER-Alexnet scores. CONCLUSION: The PER-Alexnet + RF model has reached high performance for whole-case periodontal diagnosis. The CNN models combined with CA can assist dentists in quickly and accurately diagnosing the stage of periodontitis.

Characteristics of biological manganese oxides produced by manganese-oxidizing bacteria H38 and its removal mechanism of oxytetracycline.

Oxytetracycline (OTC) is widely used in clinical medicine and animal husbandry. Residual OTC can affect the normal life activities of microorganisms, animals, and plants and affect human health. Microbial remediation has become a research hotspot in the environmental field. Manganese oxidizing bacteria (MnOB) exist in nature, and the biological manganese oxides (BMO) produced by them have the characteristics of high efficiency, low cost, and environmental friendliness. However, the effect and mechanism of BMO in removing OTC are still unclear. In this study, Bacillus thuringiensis strain H38 of MnOB was obtained, and the conditions for its BMO production were optimized. The optimal conditions were determined as follows: optimal temperature = 35 °C, optimal pH = 7.5, optimal Mn(Ⅱ) initial concentration = 10 mmol/L. The results show that BMO are irregular or massive, mainly containing MnCO3, Mn2O3, and MnO2, with rich functional groups and chemical bonds. They have the characteristics of small particle size and large specific surface area. OTC (2.5 mg/L) was removed when the BMO dosage was 75 µmol/L and the solution pH was 5.0. The removal ratio was close to 100 % after 12 h of culture at 35 °C and 150 r/min. BMO can adsorb and catalyze the oxidation of OTC and can produce ·O2-, ·OH, 1O2, and Mn(Ⅲ) intermediate. Fifteen products and degradation pathways were identified, and the toxicity of most intermediates is reduced compared to OTC. The removal mechanism was preliminarily clarified. The results of this study are convenient for the practical application of BMO in OTC pollution in water and for solving the harm caused by antibiotic pollution.

Association between hidradenitis suppurativa and atopic diseases: a multi-center, propensity-score-matched cohort study.

Background: Cross-sectional evidence has suggested a high prevalence of atopic diseases in patients with hidradenitis suppurativa (HS). However, there is a lack of evidence based on longitudinal studies. This study aimed to assess the risk of different atopic diseases, including asthma, atopic dermatitis, and allergic rhinitis, in patients with HS. Methods: In this retrospective cohort study, data from the TriNetX research network were obtained. Patients with HS were enrolled, and a 1:1 propensity score matching was performed to select a non-HS control group. Matching covariates included age, sex, race, comorbidities, comedications, socioeconomic status, lab data, and medical utilization status. Hazard ratios (HR) for atopic diseases were assessed. Results: Over a 15-year follow-up period, patients with HS were found to be at a higher risk for atopic dermatitis (HR = 1.65; 95% CI, 1.44-1.90), asthma (HR = 1.41; 95% CI, 1.33-1.49), and allergic rhinitis (HR = 1.08; 95% CI, 1.03-1.13). A similar trend was observed in shorter follow-up periods. The association between HS, atopic dermatitis, and asthma was consistent across different age and sex subgroups. Conclusion: Atopic diseases including atopic dermatitis, asthma and allergic rhinitis are associated with HS. Further investigation is needed to assess the necessity of early screening for atopic diseases in patients with HS.

Intersphincteric resection following robotic-assisted versus laparoscopy-assisted total mesorectal excision for middle and low rectal cancer: a multicentre propensity score analysis of 1571 patients.

BACKGROUND: Robotic-assisted total mesorectal excision (RaTME) may be associated with reduced conversion to an open approach and a higher rate of complete total mesorectal excision (TME); however, studies on its advantages in intersphincteric resection (ISR) are inadequate. MATERIALS AND METHODS: This retrospective multicenter cohort study enroled consecutive patients who underwent RaTME and laparoscopy-assisted total mesorectal excision (LaTME) at four medical centres between January 2020 and March 2023. Propensity score matching (PSM), inverse probability of treatment weight (IPTW), and multivariate logistic regression analyses were performed. The primary outcome was the ISR rate. Secondary outcomes were coloanal anastomosis (CAA), conversion to open surgery, conversion to transanal TME, abdominoperineal resection, postoperative morbidity and mortality within 30 days, and pathological outcomes. RESULTS: Among the 1571 patients, 1211 and 450 underwent LaTME and RaTME, respectively, with corresponding ISR incidences of 5.3% and 8.4% ( P =0.024). After PSM and IPTW, RaTME remained associated with higher ISR rates (4.5% versus 9.4%, P =0.022 after PSM; 4.9% versus 9.2, P =0.005 after IPTW). This association remained in multivariate analysis after adjusting for other confounding factors. RaTME was further associated with a higher CAA rate, longer operating time, and higher hospitalization expenses. CONCLUSIONS: RaTME may facilitate ISR in middle and low rectal cancers, showing an independent association with a higher ISR incidence, with pathological outcomes and complications comparable to those of LaTME. However, it may also require a longer operating time and incur higher hospitalization expenses.

Dual Inhibition of CDK4/6 and XPO1 Induces Senescence With Acquired Vulnerability to CRBN-Based PROTAC Drugs.

BACKGROUND & AIMS: Despite the increasing number of treatment options available for liver cancer, only a small proportion of patients achieve long-term clinical benefits. Here, we aim to develop new therapeutic approaches for liver cancer. METHODS: A compound screen was conducted to identify inhibitors that could synergistically induce senescence when combined with cyclin-dependent kinase (CDK) 4/6 inhibitor. The combination effects of CDK4/6 inhibitor and exportin 1 (XPO1) inhibitor on cellular senescence were investigated in a panel of human liver cancer cell lines and multiple liver cancer models. A senolytic drug screen was performed to identify drugs that selectively killed senescent liver cancer cells. RESULTS: The combination of CDK4/6 inhibitor and XPO1 inhibitor synergistically induces senescence of liver cancer cells in vitro and in vivo. The XPO1 inhibitor acts by causing accumulation of RB1 in the nucleus, leading to decreased E2F signaling and promoting senescence induction by the CDK4/6 inhibitor. Through a senolytic drug screen, cereblon (CRBN)-based proteolysis targeting chimera (PROTAC) ARV-825 was identified as an agent that can selectively kill senescent liver cancer cells. Up-regulation of CRBN was a vulnerability of senescent liver cancer cells, making them sensitive to CRBN-based PROTAC drugs. Mechanistically, we find that ubiquitin specific peptidase 2 (USP2) directly interacts with CRBN, leading to the deubiquitination and stabilization of CRBN in senescent liver cancer cells. CONCLUSIONS: Our study demonstrates a striking synergy in senescence induction of liver cancer cells through the combination of CDK4/6 inhibitor and XPO1 inhibitor. These findings also shed light on the molecular processes underlying the vulnerability of senescent liver cancer cells to CRBN-based PROTAC therapy.

What affects the selection of diverting ileostomy in rectal cancer surgery: a single-center retrospective study.

BACKGROUND: The selection of diverting ileostomy (DI) is controversial. This study aimed to explore the factors affecting the selection of diverting ileostomy (DI) following laparoscopic low anterior resection for rectal cancer. METHODS: This retrospective, case-control study included patients who underwent laparoscopic-assisted sphincter-saving surgery for mid-low rectal cancer from January 2019 to June 2021. Univariate and multivariate analyses were performed on the patient's clinicopathological characteristics and pelvic dimensions measured by abdominopelvic electron beam computed tomography. RESULTS: A total of 382 patients were included in the analysis, of which 182 patients (47.6%) did not undergo DI, and 200 patients (52.4%) underwent DI. The univariate analysis suggested that male sex (p = 0.003), preoperative radiotherapy (p < 0.001), patients with an anastomosis below the levator ani plane (p < 0.001), the intertuberous distance (p < 0.001), the sacrococcygeal distance (p = 0.025), the mid pelvis anteroposterior diameter (p = 0.009), and the interspinous distance (p < 0.001) were associated with performing DI. Multivariate analysis confirmed that preoperative radiotherapy (p = 0.037, odds ratio [OR] = 2.98, 95% confidence interval [CI] = 1.07-8.30), anastomosis below the levator ani plane (p < 0.001, OR = 7.09, 95% CI = 4.13-12.18), and the interspinous distance (p = 0.047, OR = 0.97, 95% CI = 0.93-1.00) were independently associated with performing DI. CONCLUSION: Pelvic parameters also influence the choice of DI. According to this single-center experience, patients with a shorter interspinous distance, particularly narrow pelvic with an interspinous distance of < 94.8 mm, preoperative radiotherapy, and anastomosis below the levator ani plane, prefer to have a DI and should be adequately prepared by the physician.

Investigating the impact of protein S-sulfhydration modification on vascular diseases: A comprehensive review.

The post-translational modification of cysteine through redox reactions, especially S-sulfhydration, plays a critical role in regulating protein activity, interactions, and spatial arrangement. This review focuses on the impact of protein S-sulfhydration on vascular function and its implications in vascular diseases. Dysregulated S-sulfhydration has been linked to the development of vascular pathologies, including aortic aneurysms and dissections, atherosclerosis, and thrombotic diseases. The H2S signaling pathway and the enzyme cystathionine γ-lyase (CSE), which is responsible for H2S generation, are identified as key regulators of vascular function. Additionally, potential therapeutic targets for the treatment of vascular diseases, such as the H2S donor GYY4137 and the HDAC inhibitor entinostat, are discussed. The review also emphasizes the antithrombotic effects of H2S in regulating platelet aggregation and thrombosis. The aim of this review is to enhance our understanding of the function and mechanism of protein S-sulfhydration modification in vascular diseases, and to provide new insights into the clinical application of this modification.

IncidencePrevalence: An R package to calculate population-level incidence rates and prevalence using the OMOP common data model.

PURPOSE: Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM). MATERIALS AND METHODS: We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases. RESULTS: IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic. CONCLUSION: For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner.

Relay learning: a physically secure framework for clinical multi-site deep learning.

Big data serves as the cornerstone for constructing real-world deep learning systems across various domains. In medicine and healthcare, a single clinical site lacks sufficient data, thus necessitating the involvement of multiple sites. Unfortunately, concerns regarding data security and privacy hinder the sharing and reuse of data across sites. Existing approaches to multi-site clinical learning heavily depend on the security of the network firewall and system implementation. To address this issue, we propose Relay Learning, a secure deep-learning framework that physically isolates clinical data from external intruders while still leveraging the benefits of multi-site big data. We demonstrate the efficacy of Relay Learning in three medical tasks of different diseases and anatomical structures, including structure segmentation of retina fundus, mediastinum tumors diagnosis, and brain midline localization. We evaluate Relay Learning by comparing its performance to alternative solutions through multi-site validation and external validation. Incorporating a total of 41,038 medical images from 21 medical hosts, including 7 external hosts, with non-uniform distributions, we observe significant performance improvements with Relay Learning across all three tasks. Specifically, it achieves an average performance increase of 44.4%, 24.2%, and 36.7% for retinal fundus segmentation, mediastinum tumor diagnosis, and brain midline localization, respectively. Remarkably, Relay Learning even outperforms central learning on external test sets. In the meanwhile, Relay Learning keeps data sovereignty locally without cross-site network connections. We anticipate that Relay Learning will revolutionize clinical multi-site collaboration and reshape the landscape of healthcare in the future.

I-C-F-6 attenuates chronic cerebral hypoperfusion-induced neurological injury in mice by modulating microglia polarization.

Chronic cerebral hypoperfusion (CCH) is the leading cause of chronic cerebral dysfunction syndrome with its complex pathological mechanisms involving cortical and hippocampal neuronal loss, white matter lesions, and neuroinflammation. I-C-F-6 is a septapeptide, which has anti-inflammatory and anti-fibrotic effects. This study aimed to evaluate the neuroprotective effect of I-C-F-6 in chronic cerebral hypoperfusion (CCH)-induced neurological injury. C57BL/6 J mice were subjected to bilateral common carotid artery stenosis (BCAS), and BV2 microglia cells were induced with oxygen-glucose deprivation (OGD). In vivo, mice were divided randomly into four groups: Sham, BCAS, GBE (30 mg/kg), and I-C-F-6 (0.5 mg/kg). In vitro, microglia were divided randomly into four groups: control, OGD, I-C-F-6 (25 µg/mL), and Shikonin (800 nmol/L). Through LFB, TUNEL, and NeuN staining, we found that I-C-F-6 was able to mitigate myelin pathology and reduce the number of apoptotic neurons. Furthermore, immunofluorescence staining revealed that I-C-F-6 was able to reduce microglia clustering and downregulate NF-κB p65. We also observed a significant downregulation of M1 phenotype microglia signature genes, such as TNF-α, iNOS, and upregulation of anti-inflammatory cytokines, such as Arg-1 and IL-10, indicating that I-C-F-6 may mainly reduce polarization towards the M1 phenotype in microglia. Notably, I-C-F-6 downregulated the expression of NF-κB signaling pathway-related proteins IKK-ß and NF-κB p65, as well as pro-inflammatory cytokines IL-1ß and iNOS. In conclusion, I-C-F-6 can improve neurological damage, alleviate neuroinflammation, and inhibit microglia polarization to the M1 phenotype via the NF-κB signaling pathway.

A Milky Way-like barred spiral galaxy at a redshift of 3.

The majority of massive disk galaxies in the local Universe show a stellar barred structure in their central regions, including our Milky Way1,2. Bars are supposed to develop in dynamically cold stellar disks at low redshift, as the strong gas turbulence typical of disk galaxies at high redshift suppresses or delays bar formation3,4. Moreover, simulations predict bars to be almost absent beyond z = 1.5 in the progenitors of Milky Way-like galaxies5,6. Here we report observations of ceers-2112, a barred spiral galaxy at redshift zphot ≈ 3, which was already mature when the Universe was only 2 Gyr old. The stellar mass (M★ = 3.9 × 109 M⊙) and barred morphology mean that ceers-2112 can be considered a progenitor of the Milky Way7-9, in terms of both structure and mass-assembly history in the first 2 Gyr of the Universe, and was the closest in mass in the first 4 Gyr. We infer that baryons in galaxies could have already dominated over dark matter at z ≈ 3, that high-redshift bars could form in approximately 400 Myr and that dynamically cold stellar disks could have been in place by redshift z = 4-5 (more than 12 Gyrs ago)10,11.