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The coronavirus disease (COVID-19) is the global public health challenge currently persisting at a grand scale. A method that meets the rapid quantitative detection of antibodies to assess the body’s immune response from natural COVID-19 illness or vaccines’ effects is urgently needed. In the present study, an attempt was made to integrate a newly designed spectrometer to the COVID-19 test strip procedure; this augmentation provides the quantitative capacity to a lateral flow immunoassay (LFIA). Optical interpretation of results by quantitative α index, rather than visual qualification, can be done quickly, in 5–10 minutes. The developed product was compared with several other serological IgM/IgG antibody reagents on the market by recruiting 111 participants suspected of having COVID-19 infection from March to May 2020 in a hospital. Taking RT-PCR as the diagnostic gold standard, the quantitative spectral LIFA platform could correctly detect all 12 COVID-19 patients. Concerning RT-PCR negative patients, all three antibody testing methods found positive cases. The optical-based platform exhibited the ability of early detection of immunoglobulins of RT-PCR negative patients. There was an apparent trend that elevation of IgM levels in the acute phase of infection; then IgG levels rose later. It exhibited the risk of a false-negative diagnosis of RT-PCR in COVID-19 testing. The significant detection ability of this new optical-based platform demonstrated clinical potential.

Focal adhesion kinase (FAK), a non-receptor tyrosine kinase, is overexpressed and activated in many cancer types. FAK regulates diverse cellular processes, including growth factor signaling, cell cycle progression, cell survival, cell motility, angiogenesis, and the establishment of immunosuppressive tumor microenvironments through kinase-dependent and kinase-independent scaffolding functions in the cytoplasm and nucleus. Mounting evidence has indicated that targeting FAK, either alone or in combination with other agents, may represent a promising therapeutic strategy for various cancers. In this review, we summarize the mechanisms underlying FAK-mediated signaling networks during tumor development. We also summarize the recent progress of FAK-targeted small-molecule compounds for anticancer activity from preclinical and clinical evidence.

Fine design of surface charge properties of polyamide membranes is crucial for selective ionic and molecular sieving. Traditional membranes face limitations due to their inherent negative charge and limited charge modification range. Herein, we report a facile ionic liquid-decoupled bulk/interfacial diffusion strategy to elaborate the double charge flips of polyamide membranes, enabling on-demand transformation from inherently negative to highly positive and near-neutral charges. The key to these flips lies in the meticulous utilization of ionic liquid that decouples intertwined bulk/interfacial diffusion, enhancing interfacial while inhibiting bulk diffusion. These charge-tunable polyamide membranes can be customized for impressive separation performance, for example, profound Cl − /SO 4 2− selectivity above 470 in sulfate recovery, ultrahigh Li + /Mg 2+ selectivity up to 68 in lithium extraction, and effective divalent ion removal in pharmaceutical purification, surpassing many reported polyamide nanofiltration membranes. This advancement adds a new dimension to in the design of advanced polymer membranes via interfacial polymerization. Currently polyamide membranes fabricated by interfacial polymerization are limited by inherently negative charge as well as narrow charge tailoring window restricting the application of these membranes. Here, the authors report a facile ionic liquid-decoupled bulk/interfacial diffusion strategy to fabricate polyamide membranes which can transform on-demand from inherently negative to highly positive and near-neutral charge.

Intergenerational relationships that highlight learning characteristics are created in interpersonal conflicts and lifelong education. Realizing the high-quality development of intergenerational learning has become a key problem. A primary school in eastern China united communities and families to create an efficient intergenerational learning project. This study aims to explore how this intergenerational learning is created. A principal, a teacher, two community educators, and five family members were recruited as the unstructured interview participants to collect data. This study finds that the school, community, and families play irreplaceable roles in creating intergenerational learning. Influenced by educational policies and education responsibilities, the school proactively designed the intergenerational learning project that takes grandparents to school in interaction with the community and families. Adhering to the principle of social services and age-friendly, the community provides sufficient educational resources for implementing intergenerational learning through collaborative support. Considering the generation gap and integration between grandparents and grandchildren, families as participating identities make intergenerational learning from possible imagination into real practice. This study highlights the theoretical framework of how intergenerational learning is created in school-community-family collaboration. The practical implications for optimizing intergenerational relationships and coping with population aging are further emphasized.

The introduction of immune checkpoint inhibitors has demonstrated significant improvements in survival for subsets of cancer patients. However, they carry significant and sometimes life-threatening toxicities. Prompt prediction and monitoring of immune toxicities have the potential to maximise the benefits of immune checkpoint therapy. Herein, we develop a digital nanopillar SERS platform that achieves real-time single cytokine counting and enables dynamic tracking of immune toxicities in cancer patients receiving immune checkpoint inhibitor treatment - broader applications are anticipated in other disease indications. By analysing four prospective cytokine biomarkers that initiate inflammatory responses, the digital nanopillar SERS assay achieves both highly specific and highly sensitive cytokine detection down to attomolar level. Significantly, we report the capability of the assay to longitudinally monitor 10 melanoma patients during immune inhibitor blockade treatment. Here, we show that elevated cytokine concentrations predict for higher risk of developing severe immune toxicities in our pilot cohort of patients. There is a clinical need to monitor immune-related toxicities of immune checkpoint blockade therapy. Here, the authors develop a digital SERS platform for multiplexed single cytokine counting to track immune-toxicities and demonstrate the ability to use pre-screening to identify patients at higher risk.

Conversion of clean solar energy to chemical fuels is one of the promising and up-and-coming applications of metal–organic frameworks. However, fast recombination of photogenerated charge carriers in these frameworks remains the most significant limitation for their photocatalytic application. Although the construction of homojunctions is a promising solution, it remains very challenging to synthesize them. Herein, we report a well-defined hierarchical homojunction based on metal–organic frameworks via a facile one-pot synthesis route directed by hollow transition metal nanoparticles. The homojunction is enabled by two concentric stacked nanoplates with slightly different crystal phases. The enhanced charge separation in the homojunction was visualized by in-situ surface photovoltage microscopy. Moreover, the as-prepared nanostacks displayed a visible-light-driven carbon dioxide reduction with very high carbon monooxide selectivity, and excellent stability. Our work provides a powerful platform to synthesize capable metal–organic framework complexes and sheds light on the hierarchical structure-function relationships of metal–organic frameworks. Homojunctions are very promising in photocatalysis, but challenging to achieve. Herein, authors report a well-defined hierarchical metal–organic framework-based homojunction, formed via a one-pot synthesis route directed by hollow transition metal nanoparticles, as photocatalysts for CO 2 reduction.

Re-employment of retired teachers is regarded as a method to move towards productive aging and improve education quality. Existing studies have provided new knowledge on retired teachers’ value, recruitment, and teaching, especially in higher education. However, the logic of practice and impact of retired urban teachers supporting impoverished rural schools in western China has not been systematically reported. A principal, a vice-principal, three young and middle-aged teachers, and four urban retired teachers from an impoverished rural primary school in western China were recruited and interviewed. The practical model and theoretical construction of urban retired teachers supporting impoverished rural schools based on Chinese culture are dynamically elaborated in the inter-embedding of social support and endogenous development theory, as well as interview data. It is found that practicing classroom teaching, promoting classroom construction, and assisting school governance are typical behaviors of urban retired teachers supporting impoverished rural schools through external input. In addition, helping young and middle-aged teachers optimize curriculum and teaching, and providing professional training in educational policy, practice, and theory, are effective practices for urban retired teachers to help impoverished rural schools realize endogenous development. This theoretical logic offers a unique pedagogical contribution to understanding the challenges of an aging society and empowering impoverished rural schools. Moreover, this study highlights the practical value and policy implications of maximizing retired teachers’ human resources and narrowing the gap between urban and rural education.

Leptin, a hormone produced in white adipose tissue, acts in the brain to communicate fuel status, suppress appetite following a meal, promote energy expenditure and maintain blood glucose stability 1 , 2 . Dysregulation of leptin or its receptors (LEPR) results in severe obesity and diabetes 3 – 5 . Although intensive studies on leptin have transformed obesity and diabetes research 2 , 6 , clinical applications of the molecule are still limited 7 , at least in part owing to the complexity and our incomplete understanding of the underlying neural circuits. The hypothalamic neurons that express agouti-related peptide (AGRP) and pro-opiomelanocortin (POMC) have been hypothesized to be the main first-order, leptin-responsive neurons. Selective deletion of LEPR in these neurons with the Cre– loxP system, however, has previously failed to recapitulate, or only marginally recapitulated, the obesity and diabetes that are seen in LEPR-deficient Lepr db/db mice, suggesting that AGRP or POMC neurons are not directly required for the effects of leptin in vivo 8 – 10 . The primary neural targets of leptin are therefore still unclear. Here we conduct a systematic, unbiased survey of leptin-responsive neurons in streptozotocin-induced diabetic mice and exploit CRISPR–Cas9-mediated genetic ablation of LEPR in vivo. Unexpectedly, we find that AGRP neurons but not POMC neurons are required for the primary action of leptin to regulate both energy balance and glucose homeostasis. Leptin deficiency disinhibits AGRP neurons, and chemogenetic inhibition of these neurons reverses both diabetic hyperphagia and hyperglycaemia. In sharp contrast to previous studies, we show that CRISPR-mediated deletion of LEPR in AGRP neurons causes severe obesity and diabetes, faithfully replicating the phenotype of Lepr db/db mice. We also uncover divergent mechanisms of acute and chronic inhibition of AGRP neurons by leptin (presynaptic potentiation of GABA (γ-aminobutyric acid) neurotransmission and postsynaptic activation of ATP-sensitive potassium channels, respectively). Our findings identify the underlying basis of the neurobiological effects of leptin and associated metabolic disorders. A subset of neurons in the hypothalamus is identified as the primary site of action for regulating energy balance and glucose homeostasis by leptin.

Background Accurate etiology diagnosis is crucial for central nervous system infections (CNS infections). The diagnostic value of metagenomic next-generation sequencing (mNGS), an emerging powerful platform, remains to be studied in CNS infections. Methods We conducted a single-center prospective cohort study to compare mNGS with conventional methods including culture, smear and etc. 248 suspected CNS infectious patients were enrolled and clinical data were recorded. Results mNGS reported a 90.00% (9/10) sensitivity in culture-positive patients without empirical treatment and 66.67% (6/9) in empirically-treated patients. Detected an extra of 48 bacteria and fungi in culture-negative patients, mNGS provided a higher detection rate compared to culture in patients with (34.45% vs. 7.56%, McNemar test, p < 0.0083) or without empirical therapy (50.00% vs. 25.00%, McNemar test, p > 0.0083). Compared to conventional methods, positive percent agreement and negative percent agreement was 75.00% and 69.11% separately. mNGS detection rate was significantly higher in patients with cerebrospinal fluid (CSF) WBC > 300 * 10 6 /L, CSF protein > 500 mg/L or glucose ratio ≤ 0.3. mNGS sequencing read is correlated with CSF WBC, glucose ratio levels and clinical disease progression. Conclusion mNGS showed a satisfying diagnostic performance in CNS infections and had an overall superior detection rate to culture. mNGS may held diagnostic advantages especially in empirically treated patients. CSF laboratory results were statistically relevant to mNGS detection rate, and mNGS could dynamically monitor disease progression.

Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, which makes the prognostic prediction challenging. Ferroptosis, an iron-dependent form of regulated cell death, can be induced by sorafenib. However, the prognostic value of ferroptosis-related genes in HCC remains to be further elucidated. In this study, the mRNA expression profiles and corresponding clinical data of HCC patients were downloaded from public databases. The least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to construct a multigene signature in the TCGA cohort. HCC patients from the ICGC cohort were used for validation. Our results showed that most of the ferroptosis-related genes (81.7%) were differentially expressed between HCC and adjacent normal tissues in the TCGA cohort. Twenty-six differentially expressed genes (DEGs) were correlated with overall survival (OS) in the univariate Cox regression analysis (all adjusted < 0.05). A 10-gene signature was constructed to stratify patients into two risk groups. Patients in the high-risk group showed significantly reduced OS compared with patients in the low-risk group ( < 0.001 in the TCGA cohort and = 0.001 in the ICGC cohort). The risk score was an independent predictor for OS in multivariate Cox regression analyses (HR> 1, < 0.01). Receiver operating characteristic (ROC) curve analysis confirmed the signature's predictive capacity. Functional analysis revealed that immune-related pathways were enriched, and immune status were different between two risk groups. In conclusion, a novel ferroptosis-related gene signature can be used for prognostic prediction in HCC. Targeting ferroptosis may be a therapeutic alternative for HCC.