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Indonesia and many other developing countries have a vast youth population, yet limited facilities for physics learning. The major purposes of this study are to develop low-cost, technology-enhanced physical and virtual laboratories and to investigate their effects on various learning objectives, including conceptual understanding, inquiry performance, scientific inquiry self-efficacy, and enjoyment. The virtual laboratory (VL) used the physics education technology to simulate a pendulum, while the physical laboratory (PL) was a technology-enhanced physical laboratory utilizing the Camera Stopwatch and Smart Tools applications. In this quasiexperimental design, a total of 68 secondary school students in Indonesia were randomly assigned to the PL and VL settings. The participants conducted the pendulum experiment guided by an inquiry worksheet along with pre- and postconceptual tests, scientific inquiry self-efficacy, and enjoyment questionnaires. The result revealed that the guided inquiry-based VL was as effective as the PL for simple concepts, but was more effective for improving difficult concepts and scientific inquiry self-efficacy. Nevertheless, the PL group performed better on crucial inquiry activities, that is, planning, experimenting, and further improvement of the experiment. Moreover, both the PL and VL significantly promoted enjoyment. It was concluded that the PL and VL were successful for achieving different learning objectives.

Alzheimer's disease (AD), also known as senile dementia, is a progressive neurodegenerative disease. The etiology and pathogenesis of AD have not yet been elucidated. We examined common differentially expressed genes (DEGs) from different AD tissue microarray datasets by meta-analysis and screened the AD-associated genes from the common DEGs using GCBI. Then we studied the gene expression network using the STRING database and identified the hub genes using Cytoscape. Furthermore, we analyzed the microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and single nucleotide polymorphisms (SNPs) associated with the AD-associated genes, and then identified feed-forward loops. Finally, we performed SNP analysis of the AD-associated genes. Our results identified 207 common DEGs, of which 57 have previously been reported to be associated with AD. The common DEG expression network identified eight hub genes, all of which were previously known to be associated with AD. Further study of the regulatory miRNAs associated with the AD-associated genes and other genes specific to neurodegenerative diseases revealed 65 AD-associated miRNAs. Analysis of the miRNA associated transcription factor-miRNA-gene-gene associated TF (mTF-miRNA-gene-gTF) network around the AD-associated genes revealed 131 feed-forward loops (FFLs). Among them, one important FFL was found between the gene , hsa-miR-27a, and the transcription factor MYC. Furthermore, SNP analysis of the AD-associated genes identified 173 SNPs, and also found a role in AD for miRNAs specific to other neurodegenerative diseases, including hsa-miR-34c, hsa-miR-212, hsa-miR-34a, and hsa-miR-7. The regulatory network constructed in this study describes the mechanism of cell regulation in AD, in which miRNAs and lncRNAs can be considered AD regulatory factors.

The prognosis of stroke is related to insulin resistance (IR), and post-stroke depression (PSD) is a prevalent psychological consequence following a stroke. The triglyceride-to-glucose (TyG) index and the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio are simple and accurate markers of insulin resistance. However, the relationship between early-onset PSD and TyG index or TG/HDL-C ratio remains unknown. The Hamilton Depression Scale-17 item (HAMD-17) was used to assess the severity of depression. After two weeks of acute ischemic stroke (AIS), patients with HAMD-17 ≥ 7 were defined as early-onset post-stroke depression. Among the 543 recruited patients, a total of 206 (38%) patients were diagnosed with early-onset PSD. The logistic regression model determined that early-onset PSD was independently associated with the TyG index (odds ratio [OR], 1.915; 95% confidence interval [CI] 1.665–2.115, P < 0.001) and TG/HDL-C ratio (OR, 1.458; 95% CI 1.213–1.965, P = 0.002). The area under curve (AUC) of TyG index, TG/HDL-C ratio, and TyG index combined TG/HDL-C ratio to predict early-onset PSD was 0.765, 0.705, and 0.813, respectively. According to our research, the TG/HDL-C ratio and the TyG index could serve as independent risk factors and prediction indicators for early-onset PSD.

Solving clinical problems requires an individual to apply not only domain-specific medical knowledge and cognitive skills for reasoning, but also to be consciously aware of, monitor, and evaluate their thinking processes (i.e., metacognition). The purpose of this study was to map critical metacognitive dimensions of clinical problem solving and to explore the structural relationships among them, which may help frame a conceptual framework and better pedagogy for effective intervention. A context-specific inventory was adapted and modified from a domain-general instrument to capture essential metacognitive skills for learning and solving clinical problems. This inventory was administered to 72 undergraduate medical students to survey their capabilities in five dimensions: knowledge of cognition, objectives, problem representation, monitoring, and evaluation. The interplay among these dimensions was further examined using partial least squares structural equation modeling. Our findings revealed that the medical students fell short of some expert-like, metacognitive, and regulatory competence, even after receiving years of medical education and on-site training. In particular, they did not know when a holistic understanding of a problem had been reached. Many of them often do not have a set of clear diagnostic procedures in mind, nor do they concurrently monitor their thinking during diagnostic reasoning. Moreover, their lack of self-improving approaches seemed to worsen their learning. Finally, the structural equation model indicated that knowledge of cognition and objectives significantly predicted problem representation, suggesting that medical learners' knowledge of and goals for learning are influential in framing the clinical problems at hand. A significant linear prediction path was observed from problem representation, monitoring, to evaluation, signifying a possible sequenced process of clinical problem solving. Metacognitive-based instruction can help improve clinical problem-solving skills and awareness of potential biases or errors.

This study aims to examine the effectiveness of metacognitive scaffolding in different inquiry tasks related to optics. Two high school classes participated in this study. One class, the treatment group (n = 33), which integrated metacognitive prompts into the simulation-based inquiry, was compared to the other class, the control group (n = 34), which received only simulation-based inquiry. Students' conceptual understanding, integrated science process skills, confidence judgment, and inquiry performance were measured using a multiple-choice pretest and post-test and worksheets. The results show that the students' conceptual understanding and confidence judgments on conceptual understanding in both groups significantly increased from the pretest to the post-test. Incorporating metacognitive scaffolds into inquiry-based learning better facilitated the improvement of integrated science process skills as well as the confidence judgment on the process skills, especially in the more complex tasks. The metacognitive scaffolding could be applied to various inquiry activities to enhance students' control of variables, data interpretation, and graph comprehension.

BackgroundHeadache disorders are widely prevalent and pose a considerable economic burden on individuals and society. Globally, misdiagnosis and inadequate treatment of primary headache disorders remain significant challenges, impeding the effective management of such conditions. Despite advancements in headache management over the last decade, a need for comprehensive evaluations of the status of primary headache disorders in China regarding diagnosis and preventative treatments persists.MethodsIn the present study, we analyzed the established queries in the Survey of Fibromyalgia Comorbidity with Headache (SEARCH), focusing on previous diagnoses and preventative treatment regimens for primary headache disorders. This cross-sectional study encompassed adults diagnosed with primary headache disorders who sought treatment at 23 hospitals across China between September 2020 to May 2021.ResultsThe study comprised 2,868 participants who were systematically examined. Migraine and tension-type headaches (TTH) constituted a majority of the primary headache disorders, accounting for 74.1% (2,124/2,868) and 23.3% (668/2,868) of the participants, respectively. Medication overuse headache (MOH) affected 8.1% (231/2,868) of individuals with primary headache disorders. Over half of the individuals with primary headache disorders (56.6%, 1,624/2,868) remained undiagnosed. The previously correct diagnosis rates for migraine, TTH, TACs, and MOH were 27.3% (580/2,124), 8.1% (54/668), 23.2% (13/56), and 3.5% (8/231), respectively. The misdiagnosis of “Nervous headache” was found to be the most prevalent among individuals with migraine (9.9%, 211/2,124), TTH (10.0%, 67/668), trigeminal autonomic cephalalgias (TACs) (17.9%, 10/56), and other primary headache disorders (10.0%, 2/20) respectively. Only a minor proportion of individuals with migraine (16.5%, 77/468) and TTH (4.7%, 2/43) had received preventive medication before participating in the study.ConclusionsWhile there has been progress made in the rate of correct diagnosis of primary headache disorders in China compared to a decade ago, the prevalence of misdiagnosis and inadequate treatment of primary headaches remains a veritable issue. As such, focused efforts are essential to augment the diagnosis and preventive treatment measures related to primary headache disorders in the future.

BackgroundAlthough headache disorders are common, the current diagnostic approach is unsatisfactory. Previously, we designed a guideline-based clinical decision support system (CDSS 1.0) for diagnosing headache disorders. However, the system requires doctors to enter electronic information, which may limit widespread use.MethodsIn this study, we developed the updated CDSS 2.0, which handles clinical information acquisition via human–computer conversations conducted on personal mobile devices in an outpatient setting. We tested CDSS 2.0 at headache clinics in 16 hospitals in 14 provinces of China.ResultsOf the 653 patients recruited, 18.68% (122/652) were suspected by specialists to have secondary headaches. According to “red-flag” responses, all these participants were warned of potential secondary risks by CDSS 2.0. For the remaining 531 patients, we compared the diagnostic accuracy of assessments made using only electronic data firstly. In Comparison A, the system correctly recognized 115/129 (89.15%) cases of migraine without aura (MO), 32/32 (100%) cases of migraine with aura (MA), 10/10 (100%) cases of chronic migraine (CM), 77/95 (81.05%) cases of probable migraine (PM), 11/11 (100%) cases of infrequent episodic tension-type headache (iETTH), 36/45 (80.00%) cases of frequent episodic tension-type headache (fETTH), 23/25 (92.00%) cases of chronic tension-type headache (CTTH), 53/60 (88.33%) cases of probable tension-type headache (PTTH), 8/9 (88.89%) cases of cluster headache (CH), 5/5 (100%) cases of new daily persistent headache (NDPH), and 28/29 (96.55%) cases of medication overuse headache (MOH). In Comparison B, after combining outpatient medical records, the correct recognition rates of MO (76.03%), MA (96.15%), CM (90%), PM (75.29%), iETTH (88.89%), fETTH (72.73%), CTTH (95.65%), PTTH (79.66%), CH (77.78%), NDPH (80%), and MOH (84.85%) were still satisfactory. A patient satisfaction survey indicated that the conversational questionnaire was very well accepted, with high levels of satisfaction reported by 852 patients.ConclusionsThe CDSS 2.0 achieved high diagnostic accuracy for most primary and some secondary headaches. Human–computer conversation data were well integrated into the diagnostic process, and the system was well accepted by patients. The follow-up process and doctor–client interactions will be future areas of research for the development of CDSS for headaches.

Plants employ cell-surface receptor-like kinases to detect extrinsic and intrinsic signals, thus make a trade-off between growth and immunity. The receptor-like cytoplasmic kinases on the cytoplasmic side act as downstream components involved in the activation, transmission, and integration of intracellular signals. In Arabidopsis thaliana , the RLCK BOTRYTIS-INDUCED KINASE1 (BIK1) associates with multiple RLKs to regulate pathogen defense responses and brassinosteroid (BR) signaling. However, little is known about the biological functions of BIK1 in developmental processes in Arabidopsis. In this study, we established that mutation of ERECTA (ER), an important RLK, counteracts the developmental effects of loss of BIK1 function. BIK1 and ER play opposing roles in leaf morphogenesis and inflorescence architecture. Moreover, we confirmed that BIK1 is required to maintain appropriate auxin response during leaf margin morphogenesis. Finally, we found that BIK1 interacts with ER-family proteins and directly phosphorylates ER. Our findings might provide novel insight into the function of BIK1 in leaf and inflorescence development.

BackgroundThe aim of the study was to investigate whether MwoA and MwA are different manifestations of a single disease, distinct clinical entities, or located at two poles of a spectrum.MethodsIn this cross-sectional study, 5438 patients from 10 hospitals in China were included: 4651 were diagnosed with migraine without aura (MwoA) and 787 with migraine with aura (MwA). We used a validated standardized electronic survey to collect multidimensional data on headache characteristics and evaluated the similarities and differences between migraine subtypes. To distinguish migraine subtypes, we employed correlational analysis, factor analysis of mixed data (FAMD), and decision tree analysis.ResultsCompared to MwA, MwoA had more severe headaches, predominantly affected females, were more easily produced by external factors, and were more likely to have accompanying symptoms and premonitory neck stiffness. Patients with MwA are heterogeneous, according to correlation analysis; FAMD divided the subjects into three clear clusters. The majority of the differences between MwoA and MwA were likewise seen when typical aura with migraine headache (AWM) and typical aura with non-migraine headache (AWNM) were compared. Furthermore, decision trees analysis revealed that the chaotic MwA data reduced the decision tree’s accuracy in distinguishing MwoA from MwA, which was significantly increased by splitting MwA into AWM and AWNM.ConclusionsThe clinical phenomics of headache phenotype varies gradually from MwoA to AWM and AWNM, and AWM is a mid-state between MwoA and AWNM. We tend to regard migraine as a spectrum disorder, and speculate that different migraine subtypes have different “predominant regions” that generate attacks.

Mind mapping is a powerful technique that is often used for teaching declarative knowledge, but seldom implemented to record procedural knowledge. The present study focused on the latter. During a 12-week public presentation course, self-developed mind mapping software was utilized as a learning tool and an instrument to collect and analyze user behavior logs while summarizing and revising procedural knowledge. The participants were 53 working adults. They were divided into successful and unsuccessful mapping profiles based on their improvement. The pre- and post-tests on presentation skills, lag sequential analysis on log data, and interviews suggested that participants showing successful mapping behavior prioritized readability and ease of navigation of their maps. Their counterparts with unsuccessful mapping behavior tended to overload their maps and overuse highlighting. The discovery of actions and behavior patterns during the creation and revision of mind maps corresponding to successful/unsuccessful mind mapping profiles provides important suggestions to enhance existing digital mind mapping tools and to diagnose students who are falling behind. The implementation of mind mapping for procedural learning expands the area of mind mapping research and enlarges our understanding of teaching procedural knowledge.