Culturally Adapting and Piloting a Psychoeducational Autism Intervention for Chinese Immigrant Families

Asian Americans are the fastest-growing racial minority in US, and Chinese Americans are the largest ethnic group among them. Meanwhile, there is a steady growth of children diagnosed with autism spectrum disorder (ASD). However, Asian children with ASD are under-diagnosed and underserved compared to White children. Thus, there is a critical need for culturally appropriate interventions addressing these health disparities. The current study culturally adapted and evaluated the feasibility, acceptability and preliminary effects of an empirically-supported parent psychoeducation intervention for Chinese immigrant families of young children with ASD. The study was conducted in two phases. Phase I focused on the cultural adaptation of the intervention. Focus groups were conducted with six Chinese immigrant parents and six providers serving this population. Recommendations for adaptation included shifting the delivery mode from in-person family visits to an online group format, involving both professionals and community health workers in delivering the intervention, and adding a brief meditation for each session. Phase II of the study focused on examining the feasibility, acceptability, and preliminary effects of the intervention. Twenty-seven Chinese immigrant mothers of young children with ASD were recruited from Chicago and NYC for the pilot phase. Overall, the adapted intervention was found to be feasible and acceptable, and showed promising preliminary effects on family outcomes, parental self-efficacy and frequency in using evidence-based strategies, and the number of evidence-based services children were receiving. This study provides important implications for culturally responsive parent psychoeducation interventions targeting diverse families of children with AS

Image1_Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer.JPEG

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.</p

Table1_Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer.DOCX

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.</p

Image2_Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer.PNG

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.</p

Image3_Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer.PNG

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.</p

Macroporous Aerogels Using High Internal Phase Pickering Emulsions for Adsorption of Dyes

The treatment of industrial printing and dyeing wastewater is the focus of the chemical environmental protection industry. Noticeably, the physical adsorption has attracted wide attention due to the selective dye adsorption, simple process, and convenient operation. New aerogels featuring low density and high porosity are regarded as ideal physical adsorption materials for sewage treatment. In this work, high internal phase Pickering emulsions were designed and prepared. The polysaccharide complex originating from sodium octenylsuccinate starch and chitosan serves as the stabilizer, water and hexane act as the external and internal phase, respectively. Acrylic acid was introduced into the external phase to initiate UV polymerization. The high internal phase Pickering emulsions as templates were removed through freeze-drying to produce aerogel materials with macroporous structures, the size of the pores: 43.54 ± 12.75 μm. The scanning electron microscopy (SEM) images show that the pore size of aerogel materials was similar to that of emulsion droplets, verifying the template role of emulsion in the polymerization process. In addition, aerogels possess good mechanical properties and can withstand a pressure of megapascal, exhibiting favorable stability when floating in water for a long time (6 months). Methyl violet, malachite green, methylene blue, and acridine orange in aqueous solution were selected as model dyes to explore the removal process and the mechanism. The adsorption was conformed to be the pseudo-second-order kinetic model and the Freundlich adsorption isotherm, namely, the dye adsorption of the aerogels was the multilayer adsorption on the uneven surface, and the mechanism of the adsorption was related to the π–π interaction

Efficient Synthesis of 2-Deoxy l-Ribose from l-Arabinose: Mechanistic Information on the 1,2-Acyloxy Shift in Alkyl Radicals

Conversion of the inexpensive l-arabinose 1 into the ethylthio ortho ester 7 followed by generation of the dialkoxyalkyl radical III produces the desired 2-deoxy-l-ribose triester 4 in excellent overall yield. It has been shown that the similar dialkoxyalkyl radical IV is not an intermediate in the 1,2-acyloxy shift of anomeric radical I

Percentage of respondents with knowledge of tobacco-related disease.

<p>Percentage of respondents with knowledge of tobacco-related disease.</p

Channels through which respondents got the anti-tobacco messages (past 30 days).

<p>Channels through which respondents got the anti-tobacco messages (past 30 days).</p

A High Energy Density Bromine-Based Flow Battery with Two-Electron Transfer

Bromine-based flow batteries have been widely used for large-scale energy storage because of their attractive features of low cost and high redox potential. At present, bromine redox chemistry mainly based on a single-electron electrochemical reaction of Br2/Br– and a higher valence to Br+ suffers from serious side reactions. Herein, a two-electron-transfer electrochemical reaction was realized by employing BrCl2–/Br– as a positive redox couple. In this design, the side reaction of Br+ could be inhibited by the introduction of Cl– via the complexing effect in an acid environment. As a proof of concept, by using TiO2+/Ti3+ as a negative redox couple, a Ti–Br–Cl flow battery (TBCFB) demonstrated a discharge capacity up to 96 Ah L–1 and continuously ran for more than 300 cycles without obvious performance decay. With the high redox potential, high energy density, and high stability, the BrCl2–/Br–-based flow batteries demonstrate very promising perspectives for large-scale energy storage applications