Decreased femoral trochlea axial orientation corrected by derotational distal femur osteotomy in patients with patellar dislocation yields satisfactory outcomes.

PURPOSE: The femoral trochlea axial orientation has been shown to be a better predictor of patellar dislocation than the femoral anteversion angle. However, no study has investigated the importance of the femoral trochlea axial orientation in the surgical treatment of patellar dislocation. It is aimed to explore the pathological threshold of the femoral trochlea axial orientation and its guiding implications for surgical interventions in the study. METHODS: Sixty-four patients with patellar dislocation and 64 controls were included for measurement of the femoral trochlea axial orientation. The ability to predict the patellar dislocation and the pathologic threshold of the femoral trochlea axial orientation were evaluated using the receiver operating characteristic curve. One hundred patients with medial patellofemoral ligament reconstruction and 25 patients with derotational distal femur osteotomy were divided into two groups based on the femoral trochlea axial orientation cut-off value and their postoperative knee functions, and patellar tilt angles were compared. RESULTS: There were significant differences in the femoral trochlea axial orientation (60.8 ± 7.9 vs. 67.8 ± 4.6, p < 0.05) between patients with patellar dislocation and the normal population. The sensitivity and specificity of the femoral trochlea axial orientation were 0.641 and 0.813, respectively, at the femoral trochlea axial orientation smaller than 63.8°. Amongst patients having had isolated medial patellofemoral ligament reconstruction with decreased femoral trochlea axial orientation, knee function was poorer after surgery. The prognosis of patients with the femoral trochlea axial orientation correction in derotational distal femur osteotomy was better than that for patients without correction. CONCLUSIONS: The femoral trochlea axial orientation had good predictive efficiency for patellar dislocation. Isolated medial patellofemoral ligament reconstruction is not sufficiently effective for patients with patellar dislocation and decreased femoral trochlea axial orientation. Patients with a decreased femoral trochlea axial orientation can have better surgical outcomes after correction by derotational distal femur osteotomy. LEVEL OF EVIDENCE: Level III.

Type B thymomas in patients with myasthenia gravis display a distinctive pattern of αß TCR and IL-7 receptor α expression on CD4+CD8+ thymocytes.

Thymoma is closely associated with myasthenia gravis (MG). However, due to the heterogeneity of thymoma and the intricate pathogenesis of MG, it remains unclear why some patients with thymoma develop MG and others do not. In this study, we conducted a comparative phenotype analysis of thymocytes in type B thymomas in patients with MG (MG (+) thymomas) and without MG (MG (-) thymomas) via fluorescence-activated cell sorting (FACS). Our results show that the developmental stages defined by the expression of CD3, CD4, and CD8 were largely maintained in both MG (+) and MG (-) thymomas, with CD4+CD8+ cells constituting the majority of thymocytes in type B thymoma, and no significant difference between this cell population was observed in MG (+) and MG (-) thymomas.We discovered that CD4+CD8+ thymocytes in MG (+) thymomas expressed low levels of αß TCR and high levels of IL-7 receptor α (IL-7Rα), whereas in MG (-) thymomas, CD4+CD8+ thymocytes exhibited the opposite pattern of αß TCR and IL-7Rα expression. These results suggest that the positive and negative selection processes of CD4+CD8+ thymocytes might differ between MG (+) thymomas and MG (-) thymomas. The expression of the Helios transcription factor is induced during negative selection and marks a group of T cells that have undergone negative selection and are likely to be deleted due to strong TCR binding with self-peptides/MHC ligands. We observed that the percentage of Helios-positive CD4SP T cells was greater in MG (-) than in MG (+) thymomas. Thus, the differentially regulated selection process of CD4+CD8+ thymocytes, which involves TCR and IL-7/IL-7Rα signaling, is associated with the presence of MG in type B thymomas.

Multiple coronary heart diseases are risk factors for mental health disorders: A mendelian randomization study.

BACKGROUND: Previous observational studies have suggested associations between Coronary Heart Disease (CHD) and Mental Health Disorders (MHD). However, the causal nature of these relationships has remained elusive. OBJECTIVE: The purpose of this study is to elucidate the causal relationships between eight distinct types of CHD and six types of MHD using Mendelian randomization (MR) analysis. METHODS: The MR analysis employed a suite of methods including inverse variance-weighted (IVW), MR-Egger, weighted mode, weighted median, and simple mode techniques. To assess heterogeneity, IVW and MR-Egger tests were utilized. MR-Egger regression also served to investigate potential pleiotropy. The stability of IVW results was verified by leave-one-out sensitivity analysis. RESULTS: We analyzed data from over 2,473,005 CHD and 803,801 MHD patients, informed by instrumental variables from large-scale genomic studies on European populations. The analysis revealed a causal increase in the risk of Major Depressive Disorder and Mania associated with Coronary Artery Disease and Myocardial Infarction. Heart Failure was found to causally increase the risk for Bipolar Disorder and Schizophrenia. Atrial Fibrillation and Ischemic Heart Diseases were positively linked to Generalized Anxiety Disorder and Mania, respectively. There was no significant evidence of an association between Hypertensive Heart Disease, Hypertrophic Cardiomyopathy, Pulmonary Heart Disease, and MHD. Reverse MR analysis indicated that MHD do not serve as risk factors for CHD. CONCLUSIONS: The findings suggest that specific types of CHD may act as risk factors for certain MHDs. Consequently, incorporating psychological assessments into the management of patients with CHD could be advantageous.

Lung cancer cell-intrinsic IL-15 promotes cell migration and sensitizes murine lung tumors to anti-PD-L1 therapy.

BACKGROUND: IL-15 plays a vital role in enhancing NK cell- and T-cell-mediated antitumor immune responses; however, the direct effect of IL-15 on tumor cells has not been fully elucidated. Herein, we investigated the effect of IL-15 on lung adenocarcinoma cells. METHODS: Silencing and overexpression techniques were used to modify endogenous IL-15 expression in tumor cells. Transwell assays were used to assess tumor cell migration and invasion; a live-cell analysis system was used to evaluate cell motility; cellular morphological changes were quantified by confocal fluorescence microscopy; the molecular mechanisms underlying the effect of IL-15 on tumor cells were analyzed by western blotting; and RhoA and Cdc42 activities were evaluated by a pulldown assay. NCG and C57BL/6 mouse models were used to evaluate the functions of IL-15 in vivo. RESULTS: Cancer cell-intrinsic IL-15 promoted cell motility and migration in vitro and metastasis in vivo via activation of the AKT-mTORC1 pathway; however, exogenous IL-15 inhibited cell motility and migration via suppression of the RhoA-MLC2 axis. Mechanistic analysis revealed that both the intracellular and extracellular IL-15-mediated effects required the expression of IL-15Rα by tumor cells. Detailed analyses revealed that the IL-2/IL-15Rß and IL-2Rγ chains were undetected in the complex formed by intracellular IL-15 and IL-15Rα. However, when exogenous IL-15 engaged tumor cells, a complex containing the IL-15Rα, IL-2/IL-15Rß, and IL-2Rγ chains was formed, indicating that the differential actions of intracellular and extracellular IL-15 on tumor cells might be caused by their distinctive modes of IL-15 receptor engagement. Using a Lewis lung carcinoma (LLC) metastasis model, we showed that although IL-15 overexpression facilitated the lung metastasis of LLC cells, IL-15-overexpressing LLC tumors were more sensitive to anti-PD-L1 therapy than were IL-15-wild-type LLC tumors via an enhanced antitumor immune response, as evidenced by their increased CD8+ T-cell infiltration compared to that of their counterparts. CONCLUSIONS: Cancer cell-intrinsic IL-15 and exogenous IL-15 differentially regulate cell motility and migration. Thus, cancer cell-intrinsic IL-15 acts as a double-edged sword in tumor progression. Additionally, high levels of IL-15 expressed by tumor cells might improve the responsiveness of tumors to immunotherapies.

Deep learning system for true- and pseudo-invasion in colorectal polyps.

Over 15 million colonoscopies were performed yearly in North America, during which biopsies were taken for pathological examination to identify abnormalities. Distinguishing between true- and pseudo-invasion in colon polyps is critical in treatment planning. Surgical resection of the colon is often the treatment option for true invasion, whereas observation is recommended for pseudo-invasion. The task of identifying true- vs pseudo-invasion, however, could be highly challenging. There is no specialized software tool for this task, and no well-annotated dataset is available. In our work, we obtained (only) 150 whole-slide images (WSIs) from the London Health Science Centre. We built three deep neural networks representing different magnifications in WSIs, mimicking the workflow of pathologists. We also built an online tool for pathologists to annotate WSIs to train our deep neural networks. Results showed that our novel system classifies tissue types with 95.3% accuracy and differentiates true- and pseudo-invasions with 83.9% accuracy. The system's efficiency is comparable to an expert pathologist. Our system can also be easily adjusted to serve as a confirmatory or screening tool. Our system (available at http://ai4path.ca ) will lead to better, faster patient care and reduced healthcare costs.

LiNi0.5Mn1.5O4 Joins to Alleviate Self-Discharge of Anion-Graphite Intercalation Compounds.

A straightforward hybrid approach of a blend cathode is put forward to alleviate self-discharged anion-graphite intercalation compounds in dual-ion batteries. The self-discharge mechanism of the LiNi0.5Mn1.5O4/graphite blend cathode is investigated by conventional electrochemical tests and in situ X-ray diffraction measurements. A charging behavior between electrode materials during self-discharge has been discovered. This work will contribute to advancing the practical implementation of dual-ion batteries and provide valuable theoretical support for the research of blend electrodes.

The role of halogens in Au-S bond cleavage for energy-differentiated catalysis at the single-bond limit.

The transformation from one compound to another involves the breaking and formation of chemical bonds at the single-bond level, especially during catalytic reactions that are of great significance in broad fields such as energy conversion, environmental science, life science and chemical synthesis. The study of the reaction process at the single-bond limit is the key to understanding the catalytic reaction mechanism and further rationally designing catalysts. Here, we develop a method to monitor the catalytic process from the perspective of the single-bond energy using high-resolution scanning tunneling microscopy single-molecule junctions. Experimental and theoretical studies consistently reveal that the attack of a halogen atom on an Au atom can reduce the breaking energy of Au-S bonds, thereby accelerating the bond cleavage reaction and shortening the plateau length during the single-molecule junction breaking. Furthermore, the distinction in catalytic activity between different halogen atoms can be compared as well. This study establishes the intrinsic relationship among the reaction activation energy, the chemical bond breaking energy and the single-molecule junction breaking process, strengthening our mastery of catalytic reactions towards precise chemistry.

Differences in Physiological Performance and Gut Microbiota between Deep-Sea and Coastal Aquaculture of Thachinotus Ovatus: A Metagenomic Approach.

Aquaculture has become the fastest growing sector in global agriculture. The environmental degradation, diseases, and high density of mariculture has made for an inevitable shift in mariculture production from coastal to deep-sea areas. The influence that traditional coastal and emerging deep-sea farming environments exert on aquatic growth, immunity and gut microbial flora is unclear. To address this question, we compared the growth performance, physiological indicators and intestinal microbiological differences of deep-sea and coastal aquaculture in the Guangxi Beibu Gulf of China. The results showed that the growth performance and the complement of C3 and C4 (C3, C4), superoxide dismutase (SOD), and lysozyme (LYS), these physiological and biochemical indicators in the liver, kidney, and muscle of Trachinotus ovatus (T. ovatus), showed significant differences under different rearing conditions. Metagenome sequencing analysis showed Ascomycota, Pseudomonadota, and Bacillota were the three dominant phyla, accounting for 52.98/53.32 (coastal/deep sea), 24.30/22.13, and 10.39/11.82%, respectively. Aligned against the CARD database, a total of 23/2 (coastal/deep-sea) antibiotic resistance genes were screened and grouped into 4/2 genotypes. It indicated that compared with deep-sea fish, higher biological oxygen levels (3.10 times), inorganic nitrogen (110.00 times) and labile phosphate levels (29.00 times) in coastal waters might contributed to the existence of eutrophication with antibiotic resistance. The results of the study can provide complementary data on the study of the difference between deep-sea farming and traditional coastal farming, serving as a reference to future in-depth work on the transformation of fisheries development and scientific standardization of deep-sea farming.

Highly Sensitive and Quantitative Magnetic Nanoparticle-Based Lateral Flow Immunoassay with an Atomic Magnetometer.

Lateral flow immunoassay (LFIA) is a simple point-of-care method for detecting various analytes. However, the lack of test result precision and poor quantification are the main bottlenecks of LFIA. Although magnetic nanoparticles (MNPs) have gained prominence as potent labels in LIFA, the quantitative detection method for trace biomarkers remains to be improved. Here, we propose a promising real-time biosensing platform based on a highly sensitive atomic magnetometer to fulfill the quantitative detection of MNP-based lateral flow immunochromatographic assays. The strategy entails obtaining the residual flux density component spectrum by continuously and linearly scanning the trace MNP label and then resolving the magnetization and quantity from the spectrum. Moreover, we exploit the theoretical model of the magnetic dipole to verify the method's reliability. Regarding carcinoembryonic antigen detection, the atomic magnetometer exhibits a low detection limit of ∼0.01 ng mL-1 with a 100-fold enhancement factor compared to optical detection methods and a more straightforward mechanism than other magnetic detection approaches. Together, these results provide valuable insight for the potential application of atomic magnetometer quantum measurement techniques in intelligent diagnosis and treatment.

Schizochytrium sp. Extracted Lipids Prevent Alopecia by Enhancing Antioxidation and Inhibiting Ferroptosis of Dermal Papilla Cells.

Alopecia has gradually become a problem that puzzles an increasing number of people. Dermal papilla cells (DPCs) play an important role in hair follicle (HF) growth; thus, exploring the effective chemicals or natural extracts that can remediate the growth of DPCs is vital. Our results showed that Schizochytrium sp.-extracted lipids (SEL) significantly promoted proliferation (up to 1.13 times) and survival ratio (up to 2.45 times) under oxidative stress. The treatment with SEL can protect DPCs against oxidative stress damage, reducing the reactive oxygen species (ROS) level by 90.7%. The relative gene transcription and translation were thoroughly analyzed using RNA-Seq, RT-qPCR, and Western blot to explore the mechanism. Results showed that SEL significantly inhibited the ferroptosis pathway and promoted the expression of antioxidant genes (up to 1.55-3.52 times). The in vivo application of SEL improved hair growth, with the length of new hair increasing by 16.7% and the length of new HF increasing by 92.6%, and the period of telogen shortening increased by 40.0%. This study proposes a novel therapeutic option for alopecia, with the effect and regulation mechanism of SEL on DPC systematically clarified.

TGFß Antagonizes IFNγ-Mediated Adaptive Immune Evasion via Activation of the AKT-Smad3-SHP1 Axis in Lung Adenocarcinoma.

IFNγ-mediated signaling in tumor cells can induce immunosuppressive responses and cause tumor resistance to immunotherapy. Blocking TGFß promotes T lymphocyte infiltration and turns immunologically cold tumors into hot tumors, thereby improving the efficacy of immunotherapy. Several studies have shown that TGFß inhibits IFNγ signaling in immune cells. We thus sought to determine whether TGFß affects IFNγ signaling in tumor cells and plays a role in the development of acquired resistance to immunotherapy. TGFß stimulation of tumor cells increased SHP1 phosphatase activity in an AKT-Smad3-dependent manner, decreased IFNγ-mediated tyrosine phosphorylation of JAK1/2 and STAT1, and suppressed the expression of STAT1-dependent immune evasion-related molecules, e.g., PD-L1, IDO1, herpes virus entry mediator (HVEM), and galectin-9 (Gal-9). In a lung cancer mouse model, dual blockade of TGFß and PD-L1 led to superior antitumor activity and prolonged survival compared with anti-PD-L1 therapy alone. However, prolonged combined treatment resulted in tumor resistance to immunotherapy and increased expression of PD-L1, IDO1, HVEM, and Gal-9. Interestingly, after initial anti-PD-L1 monotherapy, dual TGFß and PD-L1 blockade promoted both immune evasion gene expression and tumor growth compared with that in tumors treated with continuous PD-L1 monotherapy. Alternatively, treatment with JAK1/2 inhibitor following initial anti-PD-L1 therapy effectively suppressed tumor growth and downregulated immune evasion gene expression in tumors, indicating the involvement of IFNγ signaling in immunotherapy resistance development. These results demonstrate an unappreciated effect of TGFß on the development of IFNγ-mediated tumor resistance to immunotherapy. SIGNIFICANCE: Blocking TGFß facilitates IFNγ-mediated resistance to anti-PD-L1 therapy due to the role of TGFß in inhibiting IFNγ-induced immunoevasion by increasing SHP1 phosphatase activity in tumor cells.

Intrinsic piezoelectricity of 2D violet phosphorene.

Violet phosphorene (VP) has an extensive range of potential uses in piezoelectric gadgets due to its excellent electron transport capabilities. Nevertheless, VP materials are devoid of the piezoelectric effect because of the absence of ionic polarity. In this study, the piezoelectric capacity of the VP nano-sheet was investigated. According to the findings, the VP exhibited precise in-plane and out-of-plane piezoelectricity. For both in-plane as well as out-of-plane applications, the monolayer of VP had a characteristic direct piezoelectric reaction, and piezoelectric hysteresis loops were established at an electric field excitation of -18 V to +18 V. According to calculations using the density functional theory, VP has inside inherent dipoles. Outcomes from piezoelectric force microscopy, in particular, for VP with a thickness of 17.6 nm revealed that d33 is up to 12.65 pm V-1 and d31 is up to 1.03 pm V-1. The thickness-relied piezoelectric results demonstrated that VP's piezoelectric capabilities degraded as width increased.

Compact Artificial Neural Network Based on Task Attention for Individual SSVEP Recognition With Less Calibration.

OBJECTIVE: Recently, artificial neural networks (ANNs) have been proven effective and promising for the steady-state visual evoked potential (SSVEP) target recognition. Nevertheless, they usually have lots of trainable parameters and thus require a significant amount of calibration data, which becomes a major obstacle due to the costly EEG collection procedures. This paper aims to design a compact network that can avoid the over-fitting of the ANNs in the individual SSVEP recognition. METHOD: This study integrates the prior knowledge of SSVEP recognition tasks into the attention neural network design. First, benefiting from the high model interpretability of the attention mechanism, the attention layer is applied to convert the operations in conventional spatial filtering algorithms to the ANN structure, which reduces network connections between layers. Then, the SSVEP signal models and the common weights shared across stimuli are adopted to design constraints, which further condenses the trainable parameters. RESULTS: A simulation study on two widely-used datasets demonstrates the proposed compact ANN structure with proposed constraints effectively eliminates redundant parameters. Compared to existing prominent deep neural network (DNN)-based and correlation analysis (CA)-based recognition algorithms, the proposed method reduces the trainable parameters by more than 90% and 80% respectively, and boosts the individual recognition performance by at least 57% and 7% respectively. CONCLUSION: Incorporating the prior knowledge of task into the ANN can make it more effective and efficient. The proposed ANN has a compact structure with less trainable parameters and thus requires less calibration with the prominent individual SSVEP recognition performance.

Reversible Diode with Tunable Band Alignment for Photoelectricity-Induced Artificial Synapse.

The advent of big data era has put forward higher requirements for electronic nanodevices that have low energy consumption for their application in analog computing with memory and logic circuit to address attendant energy efficiency issues. Here, a miniaturized diode with a reversible switching state based on N-n MoS2 homojunction used a bandgap renormalization effect through the band alignment type regulated by both dielectric and polarization, controllably switched between type-I and type-II, which can be simulated as artificial synapse for sensing memory processing because of its rectification, nonvolatile characteristic and high optical responsiveness. The device demonstrates a rectification ratio of 103 . When served as memory retention time, it can attain at least 7000 s. For the synapse simulation, it has an ultralow-level energy consumption because of the pA-level operation current with 5 pJ for long-term potentiation and 7.8 fJ for long-term depression. Furthermore, the paired pulse facilitation index reaches up to 230%, and it realizes the function of optical storage that can be applied to simulate visual cells.

Exploring Electronic Characteristics of Acceptor-Donor-Acceptor-Type Molecules by Single-Molecule Charge Transport.

The electronic characteristics of organic optoelectronic materials determine the performance of corresponding devices. Clarifying the relationship between molecular structure and electronic characteristics at the single-molecule level can help to achieve high performance for organic optoelectronic materials and devices, especially for organic photovoltaics. In this work, a typical acceptor-donor-acceptor (A-D-A)-type molecule is explored by combining theoretical and experimental studies to reveal the intrinsic electronic characteristics at the single-molecule level. Specifically, the A-D-A-type molecule with 1,1-dicyano methylene-3-indanone (INCN) acceptor units exhibits an enhanced conductance in single-molecule junctions when compared with the control donor molecule, because the acceptor units of the A-D-A-type molecule contribute additional transport channels. In addition, through opening the S∙∙∙O noncovalent conformational lock by protonation to expose the -S anchoring sites, the charge transport of the D central part is detected, proving that the conductive orbitals contributed by the INCN acceptor groups can penetrate the whole A-D-A molecule. These results provide important insights into the development of high-performance organic optoelectronic materials and devices toward practical applications.

Automatic Metric Search for Few-Shot Learning.

Few-shot learning (FSL) aims to learn a model that can identify unseen classes using only a few training samples from each class. Most of the existing FSL methods adopt a manually predefined metric function to measure the relationship between a sample and a class, which usually require tremendous efforts and domain knowledge. In contrast, we propose a novel model called automatic metric search (Auto-MS), in which an Auto-MS space is designed for automatically searching task-specific metric functions. This allows us to further develop a new searching strategy to facilitate automated FSL. More specifically, by incorporating the episode-training mechanism into the bilevel search strategy, the proposed search strategy can effectively optimize the network weights and structural parameters of the few-shot model. Extensive experiments on the miniImageNet and tieredImageNet datasets demonstrate that the proposed Auto-MS achieves superior performance in FSL problems.

Enhancing Detection of Multi-Frequency-Modulated SSVEP Using Phase Difference Constrained Canonical Correlation Analysis.

OBJECTIVE: Multi-frequency-modulated visual stimulation scheme has been shown effective for the steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) recently, especially in increasing the visual target number with less stimulus frequencies and mitigating the visual fatigue. However, the existing calibration-free recognition algorithms based on the traditional canonical correlation analysis (CCA) cannot provide the merited performance. APPROACH: To improve the recognition performance, this study proposes a phase difference constrained CCA (pdCCA), which assumes that the multi-frequency-modulated SSVEPs share a common spatial filter over different frequencies and have a specified phase difference. Specifically, during the CCA computation, the phase differences of the spatially filtered SSVEPs are constrained using the temporal concatenation of the sine-cosine reference signals with the pre-defined initial phases. MAIN RESULTS: We evaluate the performance of the proposed pdCCA-based method on three representative multi-frequency-modulated visual stimulation paradigms (i.e., based on the multi-frequency sequential coding, the dual-frequency, and the amplitude modulation). The evaluation results on four SSVEP datasets (Dataset Ia, Ib, II, and III) show that the pdCCA-based method can significantly outperform the current CCA method in terms of recognition accuracy. It improves the accuracy by 22.09% in Dataset Ia, 20.86% in Dataset Ib, 8.61% in Dataset II, and 25.85% in Dataset III. SIGNIFICANCE: The pdCCA-based method, which actively controls the phase difference of the multi-frequency-modulated SSVEPs after spatial filtering, is a new calibration-free method for multi-frequency-modulated SSVEP-based BCIs.

On the value of label and semantic information in domain generalization.

In this work, we tackle the domain generalization (DG) problem aiming to learn a universal predictor on several source domains and deploy it on an unseen target domain. Many existing DG approaches were mainly motivated by domain adaptation techniques to align the marginal feature distribution but ignored conditional relations and labeling information in the source domains, which are critical to ensure successful knowledge transfer. Although some recent advances started to take advantage of conditional semantic distributions, theoretical justifications were still missing. To this end, we investigate the theoretical guarantee for a successful generalization process by focusing on how to control the target domain error. Our results reveal that to control the target risk, one should jointly control the source errors that are weighted according to label information and align the semantic conditional distributions between different source domains. The theoretical analysis then leads to an efficient algorithm to control the label distributions as well as match the semantic conditional distributions. To verify the effectiveness of our method, we evaluate it against recent baseline algorithms on several benchmarks. We also conducted experiments to verify the performance under label distribution shift to demonstrate the necessity of leveraging the labeling and semantic information. Empirical results show that the proposed method outperforms most of the baseline methods and shows state-of-the-art performances.

Episodic task agnostic contrastive training for multi-task learning.

Learning knowledge from different tasks to improve the general learning performance is crucial for designing an efficient algorithm. In this work, we tackle the Multi-task Learning (MTL) problem, where the learner extracts the knowledge from different tasks simultaneously with limited data. Previous works have been designing the MTL models by taking advantage of the transfer learning techniques, requiring the knowledge of the task index, which is not realistic in many practical scenarios. In contrast, we consider the scenario that the task index is not explicitly known, under which the features extracted by the neural networks are task agnostic. To learn the task agnostic invariant features, we implement model agnostic meta-learning by leveraging the episodic training scheme to capture the common features across tasks. Apart from the episodic training scheme, we further implemented a contrastive learning objective to improve the feature compactness for a better prediction boundary in the embedding space. We conduct extensive experiments on several benchmarks compared with several recent strong baselines to demonstrate the effectiveness of the proposed method. The results showed that our method provides a practical solution for real-world scenarios, where the task index is agnostic to the learner and can outperform several strong baselines, achieving state-of-the-art performances.

The association between financial support of adult children to their parents and informal care provision in China and its differences in household registration, residence arrangement and community-based care services: 2008 ~ 2018.

BACKGROUND: The changes in demographic and family structures have weakened the traditional norms of filial piety and intergenerational relationships dramatically. This study aims to examine the dynamic association between financial support of adult children to their parents and informal care provision in China and its differences in household registration, residence arrangement and community-based care services. METHODS: Data was derived from the 2008-2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), which is a longitudinal survey of a nationally representative sample of individuals aged 60 and over. Random effects model was used to assess the association between financial support and informal care provision of adult children to their parents. RESULTS: It was found that financial support showed an upward trend while informal care provision showed a download trend from 2008 to 2018. The result indicated a significant and negative association between financial support and informal care provision of adult children to their parents (B = -0.500, 95% confidence interval (CI) = -0.761 to -0.239). And the association was significant among elderly people who were from urban areas (B = -0.628, 95% CI = -0.970 to -0.287), co-resided with adult children (B = -0.596, 95% CI = -0.939 to -0.253), and had community-based services (B = -0.659, 95% CI = -1.004 to -0.315). CONCLUSION: Financial support was negatively associated with informal care provision of adult children to their parents in China, and the association has differences in household registration, residence arrangement and community-based care services. It is suggested that policymakers should prioritize planning interventions for elderly care services and establish a family caregiver support system.