Age, sex, and APOE gene-specific associations between dynapenic obesity and dementia in a large cohort.

OBJECTIVE: To investigate the associations between dynapenic obesity and the risk of dementia, and the modifying effects of age, sex, and the APOE gene, using a large population-based cohort. METHODS: 279,884 participants aged 55 and above from the UK Biobank were included. The participants were classified into four categories based on body mass index and hand grip strength: healthy, obesity, dynapenia, and dynapenic obesity. The incident dementia was identified based on linked hospital records and death register data. Cox proportional hazards regression models were used to estimate the associations, followed by age-, sex-, and apolipoprotein E (APOE) gene-stratified analyses. RESULTS: During the median follow-up of 12.4 years, 5,170 (1.8%) participants developed dementia. Compared with the healthy group, participants with dynapenic obesity had 67% higher dementia risk (hazard ratio [HR]: 1.67, 95% confidence interval [CI]: 1.44-1.94). Compared with the healthy group, higher risks of dementia in participants with dynapenic obesity were respectively observed in male (HR: 2.03, 95% CI: 1.65-2.50), younger (<65 years, HR: 1.97, 95% CI: 1.55-2.50), and non-ε4-carrier (HR: 1.97, 95% CI: 1.60-2.44) (all P for interaction <0.05). In participants under 65 years and non-ε4-carrier, those with dynapenic obesity had the highest risk of dementia (HR: 2.63, 95% CI: 1.91-3.62), compared with the healthy group (P for second order interaction = 0.026). CONCLUSIONS: Dynapenic obesity is associated with increased risks of dementia, especially in participants under 65 years and non-ε4-carrier, suggesting the importance of managing dynapenic obesity in the prevention of cognition-related disorders.

Mazabraud's syndrome in female patients: Two case reports.

BACKGROUND: Mazabraud's syndrome (MS) is a rare and slowly progressive benign disease characterized by the concurrent presence of fibrous dysplasia of bone and intramuscular myxoma, and is thought to be associated with mutations of the GNAS gene. To date, only about 100 cases of MS have been reported in the literature, but its standard treatment strategy remains unclear. CASE SUMMARY: We report two cases of MS in young women who underwent different treatments based on their symptoms and disease manifestations. The first patient, aged 37, received internal fixation and intravenous bisphosphonate for a pathological fracture of the right femoral neck, excision of a right vastus medialis myxoma was subsequently performed for pain control, and asymptomatic psoas myxomas were monitored without surgery. Genetic testing confirmed a GNAS gene mutation in this patient. The second patient, aged 24, underwent right vastus intermedius muscle myxoma resection, and conservative treatment for fibrous dysplasia of the ilium. These patients were followed-up for 17 months and 3 years, respectively, and are now in a stable condition. CONCLUSION: Various treatments have been selected for MS patients who suffer different symptoms. The main treatment for myxomas is surgical resection, while fibrous dysplasia is selectively treated if the patient experiences pathological fracture or severe pain. However, given the documented instances of malignant transformation of fibrous dysplasia in individuals with MS, close follow-up is necessary.

Giant Anisotropic Thermal Expansion Phase Transition of Silver Iodide Anionic Organic-Inorganic Hybrid.

Hybrid metal halide materials with charming phase transition behaviors have attracted considerable attention. In former works, much attention has been focused on the phase transition triggered by the order-disorder or displacement motions of the organic component. However, manipulating the variation of the inorganic component to achieve the phase transition has rarely been reported. Herein, two novel organic-inorganic hybrid materials, [THPM]n[AgX2]n (THPM = 3,4,5,6-tetrahydropyrimidin-1-ium, X = I for 1 and Br for 2) with the [AgX2]nn- anionic chain structure, were synthesized. At 293 K, the [AgX2]nn- chains in 1 were constructed by the tetramer units of Ag atoms, while that in 2 was assembled by the dimer structure. Upon heating to 355 K, owing to the variation of the metallophilic interaction between adjacent Ag atoms, a unique transformation process from tetramer to dimer in [AgI2]nn- chains of 1 can be detected and endow 1 with a giant anisotropic thermal expansion with linear strain of ∼7% and shear strain of ∼20%, which can be used as a mechanical actuator for switching. Alternatively, for 2, no phase transition process can be observed upon the temperature variation. This work provides an effective approach to design phase transition materials triggered by the inorganic part.

Impact of sarcopenic obesity on heart failure in people with type 2 diabetes and the role of metabolism and inflammation: A prospective cohort study.

AIMS: We aimed to prospectively evaluate the association of sarcopenic obesity (SO) with the incidence risk of heart failure (HF), and the mediating role of metabolomics and inflammation in people with type 2 diabetes (T2D). METHODS: 22,496 participants with T2D from the UK Biobank were included. SO was defined as the combination of obesity (body mass index ≥30 kg/m2) and sarcopenia (grip strength <27 kg in male or <16 kg in female). The incident HF was identified through linked hospital records. Cox proportional hazard regression models were used to estimate the associations. Mediation analysis was conducted to evaluate the mediating effect of the "metabolomic risk score" of HF, which was derived from 168 plasma metabolites through LASSO regression, and five inflammatory markers (e.g., C-reactive protein [CRP] level) on the aforementioned associations. RESULTS: 1946 (8.7 %) participants developed HF during a median follow-up of 12.0 years. Compared to participants with neither obesity nor sarcopenia, those with obesity & non-sarcopenia (hazard ratio [HR]: 1.80, 95 % confidence interval [CI]: 1.62, 2.00), sarcopenia & non-obesity (HR: 1.90, 95 % CI: 1.56, 2.31) and SO (HR: 2.29, 95 % CI: 1.92, 2.73) showed a higher risk of HF. The metabolomic risk score (20.0 %) and CRP (20.4 %) meditated this association. CONCLUSIONS: SO was associated with an increased risk of HF in people with T2D and metabolomics and inflammation partially mediated this association. Our findings suggest the importance of managing obesity and muscle strength simultaneously in preventing HF among people with T2D and shed light on the underlying mechanisms.

Controllable quantum scars induced by spin-orbit couplings in quantum dots.

Spin-orbit couplings (SOCs), originating from the relativistic corrections in the Dirac equation, offer nonlinearity in the classical limit and are capable of driving chaotic dynamics. In a nanoscale quantum dot confined by a two-dimensional parabolic potential with SOCs, various quantum scar states emerge quasi-periodically in the eigenstates of the system, when the ratio of confinement energies in the two directions is nearly commensurable. The scars, displaying both quantum interference and classical trajectory features on the electron density, due to relativistic effects, serve as a bridge between the classical and quantum behaviors of the system. When the strengths of Rashba and Dresselhaus SOCs are identical, the chaos in the classical limit is eliminated as the classical Hamilton's equations become linear, leading to the disappearance of all quantum scar states. Importantly, the quantum scars induced by SOCs are robust against small perturbations of system parameters. With precise control achievable through external gating, the quantum scar induced by Rashba SOC is fully controllable and detectable.

Self-Powered Biomimetic Pressure Sensor Based on Mn-Ag Electrochemical Reaction for Monitoring Rehabilitation Training of Athletes.

Self-powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual-response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO2/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper-like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open-circuit voltage of 0.927 V, a short-circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes' rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices.

Dietary patterns, metabolomics and frailty in a large cohort of 120 000 participants.

Objective: To examine the associations of dietary patterns with frailty and whether metabolic signatures (MSs) mediate these associations. Methods: We used UK Biobank data to examine (1) the associations of four dietary patterns (i.e., alternate Mediterranean diet [aMED], Recommended Food Score [RFS], Dietary Approaches to Stop Hypertension [DASH] and Mediterranean-DASH Intervention for Neurodegenerative Delay [MIND] diet) with frailty (measured by the frailty phenotype and the frailty index) using multivariable logistic regression (analytic sample 1: N = 124 261; mean age = 57.7 years), and (2) the mediating role of MSs (weighted sums of the metabolites selected from 168 plasma metabolites using the LASSO algorithm) in the above associations via mediation analysis (analytic sample 2: N = 26 270; mean age = 57.7 years). Results: Four dietary patterns were independently associated with frailty (all P < 0.001). For instance, compared to participants in the lowest tertile for RFS, those in the intermediate (odds ratio [OR]: 0.81; 95% confidence interval [CI]: 0.74, 0.89) and highest (OR: 0.62; 95% CI: 0.56, 0.68) tertiles had a lower risk of frailty. We found that 98, 68, 123 and 75 metabolites were associated with aMED, RFS, DASH and MIND, respectively, including 16 common metabolites (e.g., fatty acids, lipoproteins, acetate and glycoprotein acetyls). The MSs based on these metabolites partially mediated the association of the four dietary patterns with frailty, with the mediation proportion ranging from 26.52% to 45.83%. The results were robust when using another frailty measure, the frailty index. Conclusions: The four dietary patterns were associated with frailty, and these associations were partially mediated by MSs. Adherence to healthy dietary patterns may potentially reduce frailty development by modulating metabolites.

Investigating the synergy of Shikonin and Valproic acid in inducing apoptosis of osteosarcoma cells via ROS-mediated EGR1 expression.

BACKGROUND: Osteosarcoma is the most prevalent malignant bone tumour with a poor prognosis. Shikonin (SHK) is derived from the traditional Chinese medicine Lithospermum that has been extensively studied for its notable anti-tumour effects, including for osteosarcoma. However, its application has certain limitations. Valproic acid (VPA) is a histone deacetylase inhibitor (HDACI) that has recently been employed as an adjunctive therapeutic agent that allows chromatin to assume a more relaxed state, thereby enhancing anti-tumour efficacy. PURPOSE: This study was aimed to investigate the synergistic anti-tumour efficacy of SHK in combination with VPA and elucidate its underlying mechanism. METHODS/STUDY DESIGN: CCK-8 assays were utilized to calculate the combination index. Additional assays, including colony formation, acridine orange/ethidium bromide double fluorescent staining, and flow cytometry, were employed to evaluate the effects on osteosarcoma cells. Wound healing and transwell assays were utilized to assess cell mobility. RNA sequencing, PCR, and Western blot analyses were conducted to uncover the underlying mechanism. Rescue experiments were performed to validate the mechanism of apoptotic induction. The impact of SHK and VPA combination treatment on primary osteosarcoma cells was also assessed. Finally, in vivo experiments were conducted to validate its anti-tumour effects and mechanism. RESULTS: The combination of SHK and VPA synergistically inhibited the proliferation and migration of osteosarcoma cells in vitro and induced apoptosis in these cells. Through a comprehensive analysis involving RNA sequencing, PCR, Western blot, and rescue experiments, we have substantiated our hypothesis that the combination of SHK and VPA induced apoptosis via the ROS-EGR1-Bax axis. Importantly, our in vivo experiments corroborated these findings, demonstrating the potential of the SHK and VPA combination as a promising therapeutic approach for osteosarcoma. CONCLUSION: The combination of SHK and VPA exerted an anti-tumour effect by inducing apoptosis through the ROS-EGR1-Bax pathway. Repurposing the old drug VPA demonstrated its effectiveness as an adjunctive therapeutic agent for SHK, enhancing its anti-tumour efficacy and revealing its potential value. Furthermore, our study expanded the application of natural compounds in the anti-tumour field and overcame some of their limitations through combination therapy. Finally, we enhanced the understanding of the mechanistic pathways linking reactive oxygen species (ROS) accumulation and apoptosis in osteosarcoma cells. Additionally, we elucidated the role of EGR1 in osteosarcoma cells, offering novel strategies and concepts for the treatment of osteosarcoma.

Naringin ameliorates obesity via stimulating adipose thermogenesis and browning, and modulating gut microbiota in diet-induced obese mice.

Naringin, a natural flavanone primarily found in citrus fruits, has garnered increased attention due to its recognized antioxidative, anti-inflammatory, and cardioprotective attributes. However, the functions of naringin in regulating energy expenditure are poorly understood. In the present study, we observed that twelve weeks of naringin supplementation substantially reshaped the metabolic profile of high-fat diet (HFD)-fed mice, by inhibiting body weight gain, reducing liver weight, and altering body compositions. Notably, naringin exhibited a remarkable capacity to augment whole-body energy expenditure of the tested mice by enhancing the thermogenic activity of brown adipose tissue (BAT) and stimulating browning of inguinal white adipose tissue (iWAT). Furthermore, our results showed naringin supplementation modified gut microbiota composition, specifically increasing the abundance of Bifidobacterium and Lachnospiraceae_bacterium_28-4, while reducing the abundance of Lachnospiraceae_bacterium_DW59 and Dubosiella_newyorkensis. Subsequently, we also found naringin supplementation altered fecal metabolite profile, by significantly promoting the production of taurine, tyrosol, and thymol, which act as potent activators of thermoregulation. Interestingly, the metabolic effects of naringin were abolished upon gut microbiota depletion through antibiotic intervention, concurrently leading the disappearance of naringin-induced thermogenesis and protective actions on diet-induced obesity. This discovery revealed a novel food-driven cross-sectional communication between gut bacteria and adipose tissues. Collectively, our data indicate that naringin supplementation stimulates BAT thermogenesis, alters fat distribution, promotes the browning process, and consequently inhibits body weight gain; importantly these metabolic effects require the participation of gut bacteria.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images.

BACKGROUND: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC). METHODS: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS. RESULTS: Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression. CONCLUSION: DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

A High Working Temperature Multiferroic Induced by Inverse Temperature Symmetry Breaking.

Molecular-based multiferroic materials that possess ferroelectric and ferroelastic orders simultaneously have attracted tremendous attention for their potential applications in multiple-state memory devices, molecular switches, and information storage systems. However, it is still a great challenge to effectively construct novel molecular-based multiferroic materials with multifunctionalities. Generally, the structure of these materials possess high symmetry at high temperatures, while processing an obvious order-disorder or displacement-type ferroelastic or ferroelectric phase transition triggered by symmetry breaking during the cooling processes. Therefore, these materials can only function below the Curie temperature (Tc), the low of which is a severe impediment to their practical application. Despite great efforts to elevate Tc, designing single-phase crystalline materials that exhibit multiferroic orders above room temperature remains a challenge. Here, an inverse temperature symmetry-breaking phenomenon was achieved in [FPM][Fe3(µ3-O)(µ-O2CH)8] (FPM stands for 3-(3-formylamino-propyl)-3,4,5,6-tetrahydropyrimidin-1-ium, which acts as the counterions and the rotor component in the network), enabling a ferroelastoelectric phase at a temperature higher than Tc (365 K). Upon heating from room temperature, two-step distinct symmetry breaking with the mm2Fm species leads to the coexistence of ferroelasticity and ferroelectricity in the temperature interval of 365-426 K. In the first step, the FPM cations undergo a conformational flip-induced inverse temperature symmetry breaking; in the second step, a typical ordered-disordered motion-induced symmetry breaking phase transition can be observed, and the abnormal inverse temperature symmetry breaking is unprecedented. Except for the multistep ferroelectric and ferroelastic switching, this complex also exhibits fascinating nonlinear optical switching properties. These discoveries not only signify an important step in designing novel molecular-based multiferroic materials with high working temperatures, but also inspire their multifunctional applications such as multistep switches.

A circRNA ceRNA network involved in cognitive dysfunction after chronic cerebral hypoperfusion.

Chronic Cerebral Hypoperfusion (CCH) is associated with cognitive dysfunction, the underlying mechanisms of which remain elusive, hindering the development of effective therapeutic approaches. In this study, we employed an established CCH animal model to delve into neuropathological alterations like oxidative stress, inflammation, neurotransmitter synthesis deficits, and other morphological alterations. Our findings revealed that while the number of neurons remained unchanged, there was a significant reduction in neuronal fibers post-CCH, as evidenced by microtubule-associated protein 2 (MAP2) staining. Moreover, myelin basic protein (MBP) staining showed exacerbated demyelination of neuronal fibers. Furthermore, we observed increased neuroinflammation, proliferation, and activation of astrocytes and microglia, as well as synaptic loss and microglial-mediated synapse engulfment post-CCH. Utilizing RNA sequencing, differential expression analysis displayed alterations in both mRNAs and circRNAs. Following gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, both showed significant enrichment in immunological and inflammation-related terms and pathways. Importantly, the differentially expressed circular RNAs (DE circRNAs) exhibited a notable coexpression pattern with DE mRNAs. The ternary circRNA-miRNA-mRNA competing endogenous RNAs (ceRNA) network was constructed, and subsequent analysis reiterated the significance of neuroimmunological and neuroinflammatory dysfunction in CCH-induced neuropathological changes and cognitive dysfunction. This study underscores the potential role of circRNAs in these processes, suggesting them as promising therapeutic targets to mitigate the detrimental effects of CCH.

Micropyramid Array Bimodal Electronic Skin for Intelligent Material and Surface Shape Perception Based on Capacitive Sensing.

Developing electronic skins (e-skins) that are comparable to or even beyond human tactile perception holds significant importance in advancing the process of intellectualization. In this context, a machine-learning-motivated micropyramid array bimodal (MAB) e-skin based on capacitive sensing is reported, which enables spatial mapping applications based on bimodal sensing (proximity and pressure) implemented via fringing and iontronic effects, such as contactless measurement of 3D objects and contact recognition of Braille letters. Benefiting from the iontronic effect and single-micropyramid structure, the MAB e-skin in pressure mode yields impressive features: a maximum sensitivity of 655.3 kPa-1 (below 0.5 kPa), a linear sensitivity of 327.9 kPa-1 (0.5-15 kPa), and an ultralow limit of detection of 0.2 Pa. With the assistance of multilayer perceptron and convolutional neural network, the MAB e-skin can accurately perceive 6 materials and 10 surface shapes based on the training and learning using the collected datasets from proximity and pressure modes, thus allowing it to achieve the precise perception of different objects within one proximity-pressure cycle. The development of this MAB e-skin opens a new avenue for robotic skin and the expansion of advanced applications.

Progress on study of factors influencing the prognosis and complications of surgery for discoid meniscus injury in children / 中国骨伤

The discoid meniscus is a common congenital meniscal malformation that is prevalent mainly in Asians and often occurs in the lateral discoid meniscus. Patients with asymptomatic discoid meniscus are usually treated by conservative methods such as observation and injury avoidance, while patients with symptoms and tears need to be treated surgically. Arthroscopic saucerization combined with partial meniscectomy and meniscus repair is the most common surgical approach., and early to mid-term reports are good. The prognostic factors are the patient's age at surgery、follow-up time and type of surgery. Some patients experience complications such as prolonged postoperative knee pain, early osteoarthritis, retears and Osteochondritis dissecans. The incidence of prolonged postoperative knee pain was higher and the incidence of Osteochondritis dissecans was the lowest. Retears of the lateral meniscus is the main reason for reoperation.

A highly sensitive flexible capacitive pressure sensor with hierarchical pyramid micro-structured PDMS-based dielectric layer for health monitoring.

Herein, a flexible pressure sensor with high sensitivity was created using a dielectric layer featuring a hierarchical pyramid microstructure, both in simulation and fabrication. The capacitive pressure sensor comprises a hierarchically arranged dielectric layer made of polydimethylsiloxane (PDMS) with pyramid microstructures, positioned between copper electrodes at the top and bottom. The achievement of superior sensing performance is highly contingent upon the thickness of the dielectric layer, as indicated by both empirical findings and finite-element analysis. Specifically, the capacitive pressure sensor, featuring a dielectric layer thickness of 0.5 mm, exhibits a remarkable sensitivity of 0.77 kPa-1 within the pressure range below 1 kPa. It also demonstrates an impressive response time of 55 ms and recovery time of 42 ms, along with a low detection limit of 8 Pa. Furthermore, this sensor showcases exceptional stability and reproducibility with up to 1,000 cycles. Considering its exceptional achievements, the pressure sensor has been effectively utilized for monitoring physiological signals, sign language gestures, and vertical mechanical force exerted on objects. Additionally, a 5 × 5 sensor array was fabricated to accurately and precisely map the shape and position of objects. The pressure sensor with advanced performance shows broad potential in electronic skin applications.

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.

BACKGROUND: For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatment decisions making. However, the molecular immunohistochemical subtypes based on biopsy specimens are not always consistent with final results based on surgical specimens due to the high intra-tumoral heterogeneity. Given that, we aimed to develop and validate a deep learning radiopathomics (DLRP) model to preoperatively distinguish between luminal and non-luminal breast cancers at early stages based on preoperative ultrasound (US) images, and hematoxylin and eosin (H&E)-stained biopsy slides. METHODS: This multicentre study included three cohorts from a prospective study conducted by our team and registered on the Chinese Clinical Trial Registry (ChiCTR1900027497). Between January 2019 and August 2021, 1809 US images and 603 H&E-stained whole slide images (WSIs) from 603 patients with early-stage breast cancers were obtained. A Resnet18 model pre-trained on ImageNet and a multi-instance learning based attention model were used to extract the features of US and WSIs, respectively. An US-guided Co-Attention module (UCA) was designed for feature fusion of US and WSIs. The DLRP model was constructed based on these three feature sets including deep learning US feature, deep learning WSIs feature and UCA-fused feature from a training cohort (1467 US images and 489 WSIs from 489 patients). The DLRP model's diagnostic performance was validated in an internal validation cohort (342 US images and 114 WSIs from 114 patients) and an external test cohort (270 US images and 90 WSIs from 90 patients). We also compared diagnostic efficacy of the DLRP model with that of deep learning radiomics model and deep learning pathomics model in the external test cohort. FINDINGS: The DLRP yielded high performance with area under the curve (AUC) values of 0.929 (95% CI 0.865-0.968) in the internal validation cohort, and 0.900 (95% CI 0.819-0.953) in the external test cohort. The DLRP also outperformed deep learning radiomics model based on US images only (AUC 0.815 [0.719-0.889], p = 0.027) and deep learning pathomics model based on WSIs only (AUC 0.802 [0.704-0.878], p = 0.013) in the external test cohort. INTERPRETATION: The DLRP can effectively distinguish between luminal and non-luminal breast cancers at early stages before surgery based on pretherapeutic US images and biopsy H&E-stained WSIs, providing a tool to facilitate treatment decision making in early-stage breast cancers. FUNDING: Natural Science Foundation of Guangdong Province (No. 2023A1515011564), and National Natural Science Foundation of China (No. 91959127; No. 81971631).

Alteration of Cognitive Function in Aging and Alzheimer's Disease Mice Is Related to Dysfunction of the Neuroimmune System.

BACKGROUND: Both Alzheimer's disease (AD) and aging have aging-related cognitive dysfunction with a high incidence. These neurological diseases cause serious cognitive problems in patients' daily life. But the cognitive dysfunction mechanism in-depth of aging is far less known than that of AD. OBJECTIVE: To reveal the different mechanisms of AD and aging-related cognitive dysfunction, we compared the mechanisms of aging and AD through analysis of differentially expressed genes. METHODS: Mice were divided into four groups (3-month C57BL, 16-month C57BL, 3-month 3xTg AD mice, and 16-month 3xTg AD mice) according to genotype and age. The Morris water maze was employed to investigate the spatial cognition of mice. Differential expressions of genes of AD and aging were analyzed through RNA sequencing and GO, KEGG, Reactome analysis, and the dynamic change trend analysis. Microglia was stained with immunofluorescence and its numbers were counted for analysis. RESULTS: The cognitive function of elderly mice were worse through testing with the Morris water maze. The cognitive function of 16-month 3xTg AD mice were worse than 16-month C57BL mice. The alteration tendencies of DE genes were uncovered, and microglia numbers increased during aging and AD progression through immunofluorescence. CONCLUSION: These results suggest that immune-related pathways might play a critical role in aging and AD-related cognitive dysfunction. Our research will help to provide some new potential targets for treating cognitive dysfunction in aging and AD.

White matter injury detection based on preterm infant cranial ultrasound images.

Introduction: White matter injury (WMI) is now the major disease that seriously affects the quality of life of preterm infants and causes cerebral palsy of children, which also causes periventricular leuko-malacia (PVL) in severe cases. The study aimed to develop a method based on cranial ultrasound images to evaluate the risk of WMI. Methods: This study proposed an ultrasound radiomics diagnostic system to predict the WMI risk. A multi-task deep learning model was used to segment white matter and predict the WMI risk simultaneously. In total, 158 preterm infants with 807 cranial ultrasound images were enrolled. WMI occurred in 32preterm infants (20.3%, 32/158). Results: Ultrasound radiomics diagnostic system implemented a great result with AUC of 0.845 in the testing set. Meanwhile, multi-task deep learning model preformed a promising result both in segmentation of white matter with a Dice coefficient of 0.78 and prediction of WMI risk with AUC of 0.863 in the testing cohort. Discussion: In this study, we presented a data-driven diagnostic system for white matter injury in preterm infants. The system combined multi-task deep learning and traditional radiomics features to achieve automatic detection of white matter regions on the one hand, and design a fusion strategy of deep learning features and manual radiomics features on the other hand to obtain stable and efficient diagnostic performance.

Corrigendum: Treatment of avulsion fracture of posterior cruciate ligament tibial insertion by a minimally invasive approach in the posterior medial knee.

[This corrects the article DOI: 10.3389/fsurg.2022.885669.].

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation.

BACKGROUND AND PURPOSE: Tumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning. PATIENTS AND METHODS: Two datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence. RESULTS: The overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490-2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017-7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk. CONCLUSIONS: This study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.