UNASSIGNED: The National Research Mentoring Network (NRMN) is a National Institutes of Health-funded program for diversifying the science, technology, engineering, math, and medicine research workforce through the provision of mentoring, networking, and professional development resources. The NRMN provides mentoring resources to members through its online platform-MyNRMN.
UNASSIGNED: MyNRMN helps members build a network of mentors. Our goal was to expand enrollment and mentoring connections, especially among those who have been historically underrepresented in biomedical training and the biomedical workforce.
UNASSIGNED: To improve the ease of enrollment, we implemented the split testing of iterations of our user interface for platform registration. To increase mentoring connections, we developed multiple features that facilitate connecting via different pathways.
UNASSIGNED: Our improved user interface yielded significantly higher rates of completed registrations (P<.001). Our analysis showed improvement in completed enrollments that used the version 1 form when compared to those that used the legacy form (odds ratio 1.52, 95% CI 1.30-1.78). The version 2 form, with its simplified, 1-step process and fewer required fields, outperformed the legacy form (odds ratio 2.18, 95% CI 1.90-2.50). By improving the enrollment form, the rate of MyNRMN enrollment completion increased from 57.3% (784/1368) with the legacy form to 74.5% (2016/2706) with the version 2 form. Our newly developed features delivered an increase in connections between members.
UNASSIGNED: Our technical efforts expanded MyNRMN\'s membership base and increased connections between members. Other platform development teams can learn from these efforts to increase enrollment among underrepresented groups and foster continuing, successful engagement.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

BACKGROUND: With an overarching goal of increasing diversity and inclusion in biomedical sciences, the National Research Mentoring Network (NRMN) developed a web-based national mentoring platform (MyNRMN) that seeks to connect mentors and mentees to support the persistence of underrepresented minorities in the biomedical sciences. As of May 15, 2024, the MyNRMN platform, which provides mentoring, networking, and professional development tools, has facilitated more than 12,100 unique mentoring connections between faculty, students, and researchers in the biomedical domain.
OBJECTIVE: This study aimed to examine the large-scale mentoring connections facilitated by our web-based platform between students (mentees) and faculty (mentors) across institutional and geographic boundaries. Using an innovative graph database, we analyzed diverse mentoring connections between mentors and mentees across demographic characteristics in the biomedical sciences.
METHODS: Through the MyNRMN platform, we observed profile data and analyzed mentoring connections made between students and faculty across institutional boundaries by race, ethnicity, gender, institution type, and educational attainment between July 1, 2016, and May 31, 2021.
RESULTS: In total, there were 15,024 connections with 2222 mentees and 1652 mentors across 1625 institutions contributing data. Female mentees participated in the highest number of connections (3996/6108, 65%), whereas female mentors participated in 58% (5206/8916) of the connections. Black mentees made up 38% (2297/6108) of the connections, whereas White mentors participated in 56% (5036/8916) of the connections. Mentees were predominately from institutions classified as Research 1 (R1; doctoral universities-very high research activity) and historically Black colleges and universities (556/2222, 25% and 307/2222, 14%, respectively), whereas 31% (504/1652) of mentors were from R1 institutions.
CONCLUSIONS: To date, the utility of mentoring connections across institutions throughout the United States and how mentors and mentees are connected is unknown. This study examined these connections and the diversity of these connections using an extensive web-based mentoring network.

UNASSIGNED: High biodiversity in the tropics is good for ecosystem services; however, challenges in taxonomy and identification usually come from such high biodiversity. Spiders are no exception to the challenges. Identifying spiders in tropical places like Thailand is difficult and time consuming. To reduce the difficulty of identifying Thai spiders, a data retrieval system for geographical occurrence and photographic identification was conducted to deploy on an online platform, Spiders in Thailand (SIT) via the website \"spiderthailand.info\". This allows professional arachnologists and amateur spider lovers to visit and check the geographical distribution of Thai spiders and to quickly access pictures for comparative photographic identification. To facilitate Thai spider identification, there were two parts, the database and the website, which are connected to each other. Data of Thai spiders were extracted from the World Spider Catalog to build a database comprising geographical occurrence and pictures of spider species in Thailand. The database was then linked with the website to display data.
UNASSIGNED: The dataset of pictures and illustrations extracted from taxonomic literature of the World Spider Catalog were included in the database for connecting with the online platform, Spiders in Thailand (SIT) via the website \"spiderthailand.info\" which facilitated access to pictures and illustrations, expediting the identification of Thai spider specimens. Geographical occurrences of Thai spiders consisted of 1419 records belonging to 670 species of 228 genera and 50 families. Amongst those, 461 species from 133 genera of 41 families were distributed only in Thailand. Around Thailand, 756 geographical localities were reported for spider occurrences. From 76 provinces and one additional special administrative area (Bangkok), 58 provinces showed occurrence records of spiders and 18 provinces showed non-occurrence records. Those provinces of non-occurrence records of spiders were Amnat Charoen, Ang Thong, Bueng Kan, Chai Nat, Maha Sarakham, Mukdahan, Nakhon Phanom, Nong Bua Lam Phu, Nonthaburi, Phayao, Phichit, Phra Nakhon Si Ayutthaya, Samut Prakan, Samut Sakhon, Si Sa Ket, Sing Buri, Uthai Thani and Yasothon. Most spiders were reported from Chiang Mai Province.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects.
RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of \"interaction-affinity-binding sites\". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN.
CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.

The ability to listen is critical in the task of language learning. Although listening has the least pedagogical attention, the growing emphasis on communication and language proficiency makes listening skills prominent in the language classroom. This paper aims to analyse the effectiveness of the Blended model to improve teaching listening skills, by instigating a top-down approach through Cognitive Load Theory. The top-down approach aids the students with the background knowledge of the audio with information like context, situation, phrases, etc. The blended model enables the teacher to facilitate students through the technological platform to process their listening input. A questionnaire was adopted for data collection and a semi-structured interview was performed from 60 samples from prefinal year Engineering students selected through purposive sampling techniques and grouped as experimental N = 30 and control N = 30 groups. The experimental group was trained with a top-down approach with the support of LMS. The control group was provided with the same listening material but taught in the conventional method. The purpose of this study is to show the statistically significant impact of employing technology inside the language classroom to teach listening skills. Findings showed that samples in the experimental group could identify the relevant and non-relevant information from the audio, conceptualise the audio content and predict the information beforehand. The difficulties that the students and teachers faced and the remedial measures to overcome them are also discussed. The following objectives were established for the study through mixed methods of enhancing listening skills through Cognitive Load Theory (CLT). •To explore the effect of intervention through a top-down approach with the support of technology (LMS) on enhancing the listening skills of the students.•How the blending of synchronous and asynchronous and a top-down approach develops the predicting skills of the students during the listening comprehension exercises.•To adapt procedures involved in enhancing the self-paced learning efficacy and reducing listening anxiety in ESL learners.

UNASSIGNED: The prevalence of food allergy (FA) has risen in recent decades, yet there is limited data on the cognition and beliefs of FA among the parents of FA children.
UNASSIGNED: To investigate the prevalence of FA and assess the knowledge and perception of FA among parents of FA children in Wuhan, China.
UNASSIGNED: Online questionnaires were conducted for the parents of 3- to 16-year-old children. They reported symptoms of suspected FA in the screening questionnaire were interviewed for further diagnostic evaluation. All the parents of the suspected FA children completed the subsequent assessments of the knowledge and perception on FA as well as their attitude towards the current online platforms.
UNASSIGNED: A total of 1963 children were recruited. The prevalence of self-reported FA was 10.2% (95% CI: 8.1-12.4%) and the physician-diagnosed FA was 6.2% (95% CI: 5.1-7.2%) in 3- to 16-year-olds in Wuhan. And the children with family history (57.9%) were predisposed to developing FA (P＜0.001). The total Brief Illness Perception Questionnaire (B-IPQ) score was 41.3 ± 10.0 among the parents. The B-IPQ scores correlated with symptom onset, but not with family history or other atopic comorbidities. The parents who never sought treatments obtained lower B-IPQ scores on most items compared to those who received treatments. The accuracy rate of the FA knowledge questionnaire was 56.7%. 11.6% of participants reported that children\'s FA had an impact on their lives. 67.2% of participants had searched information of FA online, among whom 80% expected to obtain professional suggestions on management and prevention strategies of FA from online platform.
UNASSIGNED: In 3- to 16-year-old children in Wuhan, the prevalence of self-reported and physician-diagnosed FA was 10.2% and 6.2% respectively. Parents\' knowledge of FA was insufficient and only a small proportion of parents perceived that their lives and careers have been affected considerably by FA of their children. Patient education and current online platforms should be improved among parents of FA children.

Preventing the progressive deterioration of works of art over time is a topic of great interest to collectors and museums. With this aim, time capsules where environmental conditions remain unchanged are well known for preserving art. In this paper, a prototype of an IoT time capsule is presented with a focus on low cost in order to make it accessible to private collectors or small museums with tight budgets. Valencian \'sainetes\' (small plays), which are considered materials of artistic interest, have been placed in a \"time capsule\", which is a manually made container with insulating materials for keeping small pieces for a long time. Environmental control has been performed with a low-cost microcontroller, sensors and actuators connected to a free online IoT platform. This platform recorded data and made decisions based on these data, sending cooling or heating orders to an environmental control system. The results obtained are very satisfactory and open interesting perspectives for future research. However, they also highlight some relevant technical and economic limitations that will have to be considered in the future.

Hypertriglyceridemia is a risk factor for cardiovascular diseases. Internet usage in China is increasing, giving rise to large-scale data sources, especially to access, disseminate, and discuss medical information. Social media listening (SML) is a new approach to analyze and monitor online discussions related to various health-related topics in diverse diseases, which can generate insights into users\' experiences and expectations. However, to date, no studies have evaluated the utility of SML to understand patients\' cognizance and expectations pertaining to the management of hypertriglyceridemia.
The aim of this study was to utilize SML to explore the disease cognition level of patients with hypertriglyceridemia, choice of intervention measures, and the status quo of online consultations and question-and-answer (Q&A) search platforms.
An infosurveillance study was conducted wherein a disease-specific comprehensive search was performed between 2004 and 2020 in Q&A search and online consultation platforms. Predefined single and combined keywords related to hypertriglyceridemia were used in the search, including disease, symptoms, diagnosis, and treatment indicators; lifestyle interventions; and therapeutic agents. The search output was aggregated using an aggregator tool and evaluated.
Disease-specific consultation data (n=69,845) and corresponding response data (n=111,763) were analyzed from 20 data sources (6 Q&A search platforms and 14 online consultation platforms). Doctors from inland areas had relatively high voice volumes and appear to exert a substantial influence on these platforms. Patients with hypertriglyceridemia engaging on the internet have an average level of cognition about the disease and its intervention measures. However, a strong demand for the concept of the disease and \"how to treat it\" was observed. More emphasis on the persistence of the disease and the safety of medications was observed. Young patients have a lower willingness for drug interventions, whereas patients with severe hypertriglyceridemia have a clearer intention to use drug intervention and few patients have a strong willingness for the use of traditional Chinese medicine.
Findings from this disease-specific SML study revealed that patients with hypertriglyceridemia in China actively seek information from both online Q&A search and consultation platforms. However, the integrity of internet doctors\' suggestions on lifestyle interventions and the accuracy of drug intervention recommendations still need to be improved. Further, a combined prospective qualitative study with SML is required for added rigor and confirmation of the relevance of the findings.