Longitudinal joint modeling for assessing parallel interactive development of latent ability and processing speed using responses and response times.

To measure the parallel interactive development of latent ability and processing speed using longitudinal item response accuracy (RA) and longitudinal response time (RT) data, we proposed three longitudinal joint modeling approaches from the structural equation modeling perspective, namely unstructured-covariance-matrix-based longitudinal joint modeling, latent growth curve-based longitudinal joint modeling, and autoregressive cross-lagged longitudinal joint modeling. The proposed modeling approaches can not only provide the developmental trajectories of latent ability and processing speed individually, but also exploit the relationship between the change in latent ability and processing speed through the across-time relationships of these two constructs. The results of two empirical studies indicate that (1) all three models are practically applicable and have highly consistent conclusions in terms of the changes in ability and speed in the analysis of the same data set, and (2) additional analysis of the RT data and acquisition of individual processing speed measurements can reveal the parallel interactive development phenomena that are difficult to detect using RA data alone. Furthermore, the results of our simulation study demonstrate that the proposed Bayesian Markov chain Monte Carlo estimation algorithm can ensure accurate model parameter recovery for all three proposed longitudinal joint models. Finally, the implications of our findings are discussed from the research and practice perspectives.

Novel Autophagy-Related Blood Biomarkers Associated with Immune Cell Infiltration in Ankylosing Spondylitis.

Background: This study aims to identify new therapeutic targets and explore the molecular mechanism of ankylosing spondylitis (AS), a rheumatic immune disease that mainly affects the sacroiliac and spinal joints. Despite extensive research, the exact cause of AS is still unknown. The research team utilized a bioinformatics approach to achieve their objectives. Methods: The GSE73754 dataset was downloaded from GEO database. Autophagy-related genes (ARGs) were collected from the Human Autophagy-dedicated Database. The limma package was used to screen for differentially expressed genes (DEGs), which were then intersected with the autophagy-related genes (ARGs) to identify differentially expressed autophagy-related genes (DEARGs). Subsequently, the DEARGs associated with AS were subjected to GO-BP and KEGG enrichment analyses using the clusterProfiler package. Core genes were identified using the cytoHubba plug-in of Cytoscape and were validated by clinical blood samples. Additionally, the Cell algorithm was utilized to evaluate the proportion of immune cell infiltration. Results: A total of 29 DEARGs were identified, which were found to be mainly enriched in autophagy, apoptosis, and necroptosis through functional enrichment analysis. Two core genes, HSPA5 and SQSTM1, were confirmed to have diagnostic value in AS. Immune cell infiltration analysis revealed CD8+ T cells, CD8+ T effector memory (Tem), natural killer (NK) cells, T gamma delta (Tgd) cells, and T-helper 1 (Th1) cells as major participants in AS development. Furthermore, HSPA5 expression was significantly correlated with Th1 cells, CD8+ T cells, CD4+ memory cells, and macrophages. Conclusion: This study suggested that HSPA5 and SQSTM1 can serve as useful diagnostic biomarkers for AS. These findings lay the foundation for identifying crucial mRNAs in the whole blood of AS patients, which may aid in the development of novel markers for AS.

Joint modeling of action sequences and action time in computer-based interactive tasks.

Process data refers to data recorded in computer-based assessments that reflect the problem-solving processes of participants and provide greater insight into how they solve problems. Action time, namely the amount of time required to complete a state transition, is also included in such data along with actions. In this study, an action-level joint model of action sequences and action time is proposed, in which the sequential response model (SRM) is used as the measurement model for action sequences, and a new log-normal action time model is proposed as the measurement model for action time. The proposed model can be regarded as an extension of the SRM by incorporating action time within the joint-hierarchical modeling framework and as an extension of the conventional item-level joint models in process data analysis. Results of the empirical and simulation studies demonstrated that the model setup was justified, model parameters could be interpreted, parameter estimates were accurate, and taking into account participants' action time further was beneficial for obtaining a deep understanding of participants' behavioral patterns. Overall, the proposed action-level joint model provides an innovative modeling framework for analyzing process data in computer-based assessments from the latent variable modeling perspective.

Don't worry about the anchor-item setting in longitudinal learning diagnostic assessments.

Previous longitudinal assessment experiences for multidimensional continuous latent constructs suggested that the set of anchor items should be proportionally representative of the total test forms in content and statistical characteristics and that they should be loaded on every domain in multidimensional tests. In such cases, the set of items containing the unit Q-matrix, which is the smallest unit representing the whole test, seems to be the natural choice for anchor items. Two simulation studies were conducted to verify the applicability of these existing insights to longitudinal learning diagnostic assessments (LDAs). The results mainly indicated that there is no effect on the classification accuracy regardless of the unit Q-matrix in the anchor items, and even not including the anchor items has no impact on the classification accuracy. The findings of this brief study may ease practitioners' worries regarding anchor-item settings in the practice application of longitudinal LDAs.

Light-driven redox deracemization of indolines and tetrahydroquinolines using a photocatalyst coupled with chiral phosphoric acid.

The integration of oxidation and enantioselective reduction enables a redox deracemization to directly access enantioenriched products from their corresponding racemates. However, the solution of the kinetically microscopic reversibility of substrates used in this oxidation/reduction unidirectional event is a great challenge. To address this issue, we have developed a light-driven strategy to enable an efficient redox deracemization of cyclamines. The method combines a photocatalyst and a chiral phosphoric acid in a toluene/aqueous cyclodextrin emulsion biphasic co-solvent system to drive the cascade out-of-equilibrium. Systemic optimizations achieve a feasible oxidation/reduction cascade sequence, and mechanistic investigations demonstrate a unidirectional process. This single-operation cascade route, which involves initial photocatalyzed oxidation of achiral cyclamines to cyclimines and subsequent chiral phosphoric acid-catalyzed enantioselective reduction of cyclimines to chiral cyclamines, is suitable for constructing optically pure indolines and tetrahydroquinolines.

One-stage and lightweight CNN detection approach with attention: Application to WBC detection of microscopic images.

White blood cell (WBC) detection in microscopic images is indispensable in medical diagnostics; however, this work, based on manual checking, is time-consuming, labor-intensive, and easily results in errors. Using object detectors for WBCs with deep convolutional neural networks can be regarded as a feasible solution. In this paper, to improve the examination precision and efficiency, a one-stage and lightweight CNN detector with an attention mechanism for detecting microscopic WBC images, and a white blood cell detection vision system are proposed. The method integrates different optimizing strategies to strengthen the feature extraction capability through the combination of an improved residual convolution module, hybrid spatial pyramid pooling module, improved coordinate attention mechanism, efficient intersection over union (EIOU) loss and Mish activation function. Extensive ablation and contrast experiments on the latest public Raabin-WBC dataset verify the effectiveness and robustness of the proposed detector for achieving a better overall detection performance. It is also more efficient than other existing studies for blood cell detection on two additional classic public BCCD and LISC datasets. The novel detection approach is significant and flexible for medical technicians to use for blood cell microscopic examination in clinical practice.

Elucidation of the Key Therapeutic Targets and Potential Mechanisms of Marmesine against Knee Osteoarthritis via Network Pharmacological Analysis and Molecular Docking.

Background: Marmesine, a major active ingredient isolated from Radix Angelicae biseratae (Duhuo), has been reported to have multiple pharmacological activities. However, its therapeutic effects against knee osteoarthritis (OA) remain poorly investigated. The present study is aimed at uncovering the core targets and signaling pathways of marmesine against osteoarthritis using a combined method of bioinformatics and network pharmacology. Methods: We utilized SwissTargetPrediction and PharmMapper to collect the potential targets of marmesine. OA-related differentially expressed genes (DEGs) were identified from GSE98918 dataset. Then, the intersection genes between DEGs and candidate genes of marmesine were subjected to protein-protein interaction (PPI) network construction and functional enrichment analysis. The core targets were verified using the molecular docking technology. Results: A total of 320 marmesine-related genes and 5649 DEGs and 60 ingredient-disease targets between them were identified. The results of functional enrichment analyses revealed that response to oxygen levels, neuroinflammatory response, PI3K-Akt signaling pathway, MAPK signaling pathway, FoxO signaling pathway, and osteoclast differentiation was identified as the potential mechanisms of marmesine against OA. EGFR, CASP3, MMP9, PPARG, and MAPK1 served as hub genes regulated by marmesine in the treatment of OA, and the molecular docking further verified the results. Conclusion: Marmesine exerts the therapeutic effects against OA through multitarget and multipathways, in which EGFR, CASP3, MMP9, PPARG, and MAPK1 might be hub genes. Our research indicated that the combination of bioinformatics and network pharmacology could serve as an effective approach for investigating the potential mechanisms of natural product.

A Chemoenzymatic Cascade Combining a Hydration Catalyst with an Amine Dehydrogenase: Synthesis of Chiral Amines.

The combination of biocatalysis and transition-metal catalysis can complement synthetic gaps only in a chemical or biological process. However, the intrinsic mutual deactivation between enzymatic and chemical species is a significant challenge in a single operation. To address the above issue, we developed an encapsulated Au/carbene combined with a free amine dehydrogenase as a co-catalyst system that enables an efficient hydration/amination enantioselective cascade process to be accomplished. The mechanistic investigation discloses dual catalysis comprised of alkyne hydration, followed by a reductive amination process.

Integrated Suzuki Cross-Coupling/Reduction Cascade Reaction of meta-/para-Chloroacetophenones and Arylboronic Acids under Batch and Continuous Flow Conditions.

Overcoming the incompatibility of a pair of conflicting catalysts via a flow methodology has great significance in the practical applications for multistep organic transformations. In this study, a multiple continuous-flow system is developed, which can boost the reactivity and selectivity in a sequential enantioselective cascade reaction. During this process, a periodic mesoporous organosilica-supported Pd/carbene species as a Suzuki cross-coupling catalyst is packed in the first column reactor, whereas another periodic mesoporous organosilica-supported Ru/diamine species as an asymmetric transfer hydrogenation catalyst is packed in the second column reactor. As we envisioned, the initially Pd-catalyzed cross-coupling reaction of meta-/para-chloroacetophenones and aryl boronic acids followed by the subsequentially Ru-catalyzed reduction provides chiral biarylols with enhanced yields and enantioselectivities. Furthermore, the advantages of the easy handling and the simple procedure make this system an attractive application in a scale-up preparation of optically pure organic molecules under environmentally-friendly conditions.

Facile synthesis of benzo[b]thiophenes via metal-free radical-triggered intramolecular C-S bond formation.

A facile method for the synthesis of benzo[b]thiophenes with good to excellent yields via metal-free intramolecular C-S bond formation has been developed by utilizing I2 as a catalyst and O2 from air as an oxidant (20 examples). Its notable features such as catalytic I2, intramolecular C-S bond formation, short reaction times, and broad functional group tolerance make this strategy highly attractive. The purification of products only needs washing with solvents, thereby avoiding traditional chromatography and recrystallization, which belongs to group-assisted purification (GAP) chemistry.