OBJECTIVES

This study aimed to describe the demographic profile, intervention sessions, goal attainment scaling (GAS), and health-related quality of life (HRQOL) of autistic children receiving speech and language therapy (SLT) in a higher educational institution in the Philippines.

Deidentified data from 18 autistic children aged 4–16 years (mean=8.2; SD=2.9) who received SLT for two months were analyzed. Their demographic profile, intervention sessions, GAS scores, and generic HRQOL scores were documented.

Most participants were school-age children (n=12; 66%) and were boys (n=14; 78%). After two months, the GAS scores of 11 participants (61%) increased by 1–2 points, whereas the scores of the remaining participants decreased (n=6; 33%) or did not change (n=1; 6%). Their mean generic HRQOL scores before and after SLT were 65.6 (SD=15.2) and 61.2 (SD=17.4), respectively.

While the GAS scores increased for most participants, their generic HRQOL scores did not show clinically significant changes after two months of SLT. This can be attributed to the few therapy sessions and short follow-up period. The findings highlight the need to provide long-term support to SLT services of autistic children in the Philippines to document more desirable quality of life outcomes.

Language ; Pathology ; Speech ; Speech-language Pathology ; Weights And Measures

Chinese medicine (CM) diagnosis intellectualization is one of the hotspots in the research of CM modernization. The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues, however, it is difficult to solve the problems such as excessive or similar categories. With the development of natural language processing techniques, text generation technique has become increasingly mature. In this study, we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues. The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory (BILSTM) with Transformer as the backbone network. Meanwhile, the CM diagnosis generation model Knowledge Graph Enhanced Transformer (KGET) was established by introducing the knowledge in medical field to enhance the inferential capability. The KGET model was established based on 566 CM case texts, and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence (LSTM-seq2seq), Bidirectional and Auto-Regression Transformer (BART), and Chinese Pre-trained Unbalanced Transformer (CPT), so as to analyze the model manifestations. Finally, the ablation experiments were performed to explore the influence of the optimized part on the KGET model. The results of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation 1 (ROUGE1), ROUGE2 and Edit distance of KGET model were 45.85, 73.93, 54.59 and 7.12, respectively in this study. Compared with LSTM-seq2seq, BART and CPT models, the KGET model was higher in BLEU, ROUGE1 and ROUGE2 by 6.00-17.09, 1.65-9.39 and 0.51-17.62, respectively, and lower in Edit distance by 0.47-3.21. The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance. Additionally, the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results. In conclusion, text generation technology can be effectively applied to CM diagnostic modeling. It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models. CM diagnostic text generation technology has broad application prospects in the future.
Humans ; Medicine, Chinese Traditional ; Pattern Recognition, Automated ; Asian People ; Language ; Learning

Purpose: The field of speech-language pathology (SLP) is a young profession in the Philippines compared and relative to the other health sciences in the country. The emergence of this profession is marked by the milestones laid by the development of the first speech pathology education and training program at the University of the Philippines (UP); the establishment of its national professional organization, the Philippine Association of Speech Pathologists (PASP); and the enactment of RA 11249 or the Speech Language Pathology Act, which created the Professional Regulatory Board for Speech-Language Pathology (PRB-SLP) under the Professional Regulation Commission (PRC). This article looks back at these early beginnings, focuses at the current status of the profession, and provides perspectives for its growth moving forward. Specifically, this article provides an overview of the education and training, professional organization, and local practice of Filipino SLPs. Some emerging issues about the local practice and research gaps are also discussed. Conclusions The SLP profession in the Philippines has come a long way in developing education and training programs, expanding its national professional organization, and obtaining regulation of the practice of this profession under the law. However, there is still much work to be done to ensure its growth and further its development as a health science. Among these, strengthening the body of research to respond to the evolving needs and distinct landscape of local practice could further the growth of SLP in the Philippines.
Speech-Language Pathology ; Philippines

Antimicrobial peptides (AMPs) are small molecule peptides that are widely found in living organisms with broad-spectrum antibacterial activity and immunomodulatory effect. Due to slower emergence of resistance, excellent clinical potential and wide range of application, AMP is a strong alternative to conventional antibiotics. AMP recognition is a significant direction in the field of AMP research. The high cost, low efficiency and long period shortcomings of the wet experiment methods prevent it from meeting the need for the large-scale AMP recognition. Therefore, computer-aided identification methods are important supplements to AMP recognition approaches, and one of the key issues is how to improve the accuracy. Protein sequences could be approximated as a language composed of amino acids. Consequently, rich features may be extracted using natural language processing (NLP) techniques. In this paper, we combine the pre-trained model BERT and the fine-tuned structure Text-CNN in the field of NLP to model protein languages, develop an open-source available antimicrobial peptide recognition tool and conduct a comparison with other five published tools. The experimental results show that the optimization of the two-phase training approach brings an overall improvement in accuracy, sensitivity, specificity, and Matthew correlation coefficient, offering a novel approach for further research on AMP recognition.
Anti-Bacterial Agents/chemistry* ; Amino Acid Sequence ; Antimicrobial Cationic Peptides/chemistry* ; Antimicrobial Peptides ; Natural Language Processing

With the gradual maturity of sequencing technology, many microbiome studies have published, driving the emergence and advance of related analysis tools. R language is the widely used platform for microbiome data analysis for powerful functions. However, tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data. How to choose suitable, efficient, convenient, and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers. We have organized 324 common R packages for microbiome analysis and classified them according to application categories (diversity, difference, biomarker, correlation and network, functional prediction, and others), which could help researchers quickly find relevant R packages for microbiome analysis. Furthermore, we systematically sorted the integrated R packages (phyloseq, microbiome, MicrobiomeAnalystR, Animalcules, microeco, and amplicon) for microbiome analysis, and summarized the advantages and limitations, which will help researchers choose the appropriate tools. Finally, we thoroughly reviewed the R packages for microbiome analysis, summarized most of the common analysis content in the microbiome, and formed the most suitable pipeline for microbiome analysis. This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub, which can help beginners to learn, also help analysts compare and test different tools. This paper systematically sorts the application of R in microbiome, providing an important theoretical basis and practical reference for the development of better microbiome tools in the future. All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.
Software ; Microbiota ; Sequence Analysis, DNA ; Language

Child ; Humans ; Speech ; Physicians, Primary Care ; Language Development Disorders/diagnosis* ; Speech Disorders

As a diagnostic method to guide the treatment of sinew/fascia diseases, jingjin (muscle regions of meridians) differentiation is an important component of syndrome differentiation system of acupuncture and moxibustion. In clinical practice, because of the limitations of the ideological guidance of the holistic view, the systemic and dialectical thinking and the syndrome element collection, the system of diagnosis and treatment of sinew/fascia diseases is not comprehensive. Through combing the origin of the holistic view of jingjin, the paper expounds the differentiation framework of sinew/fascia diseases from 4 aspects of differentiation, i.e. the location of disease, etiology, nature of disease and condition of disease. It suggests to construct jingjin differentiation system by taking the holistic ideas as the core, the syndrome element research as the common method and the evidence-based medicine as the theoretical basis so that the thinking of syndrome differentiation and the diagnostic approaches based on jingjin theory can be enriched.
Humans ; Acupuncture Therapy ; Evidence-Based Medicine ; Language ; Meridians ; Moxibustion ; Syndrome

OBJECTIVE: To explore the clinical characteristics and genetic etiology for two children with Neurodevelopmental disorder with hypotonia, stereotypic hand movements, and impaired language (MEDHSIL). METHODS: Two children who had visited the Ningbo Women and Children's Hospital on October 15, 2021 were selected as the study subjects. Whole exome sequencing (WES) was carried out for both patients. Candidate variants were verified by Sanger sequencing of their family members. RESULTS: The two children were respectively found to harbor a heterozygous c.138delC (p.Ile47Serfs*42) variant and a c.833del (p.L278*) variant of the MEF2C gene. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were predicted to be pathogenic (PVS1+PS2+PM2_Supporting). CONCLUSION The c.138delC and c.833del variants of the MEF2C gene probably underlay the pathogenesis of MEDHSIL in the two children. Above findings have enriched the mutational spectrum of the MEF2C gene and enabled genetic counseling for their families.
Child ; Humans ; Family ; Genetic Counseling ; Language ; MEF2 Transcription Factors/genetics* ; Muscle Hypotonia/genetics* ; Neurodevelopmental Disorders

OBJECTIVE: To explore the clinical and genetic characteristics of a boy with isolated maternal uniparental disomy of chromosome 20 [UPD(20)mat]. METHODS: A child who was admitted to the Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology on April 8,2021. was selected as the study subject. Phenotypic and endocrinological findings of the child were retrospectively analyzed. Whole exome sequencing (WES) and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) were carried out for detecting the UPD sequences and copy number variations. Both of his parents were verified by Sanger sequencing. Relevant literature was systematically reviewed. RESULTS: The child, a 3-year-and-8-month-old boy born to a 41-year-old mother by Cesarean delivery at 36⁺² gestational weeks due to oligohydramia, had a birth weight of 2 300 g and length of 46 cm. He was admitted to the NICU for feeding difficulties which had persisted despite of clinical management. At the age of 3.75, he had a height of 92.5 cm (< 3rd percentile; 25th ~ 50th percentile at 2.5 years) and a weight of 10.8 kg (< 3rd percentile; 50th percentile at 15 months). He had also presented with growth retardation, short stature, attention deficit and hyperactivity disorder (ADHD), mild mental retardation, and speech and language development disorders. He had simian creases in both hands but no additional dysmorphic signs, and his motor development was normal. Serum insulin, thyroid-stimulating hormone, and insulin growth factor binding protein 3 levels were within the normal ranges, though insulin growth factor-1 (IGF-1) was slightly decreased. Since that time he had continuously used atomoxetine hydrochloride capsules to control his ADHD. WES and MS-MLPA revealed the existence of UPD (20)mat. CONCLUSION The UPD(20)mat syndrome is characterized by feeding difficulties, growth retardation and short stature. The child in our case has been accompanied by ADHD and speech and language development disorders, which required long-term treatment. For women with advanced maternal age and suggestive phenotypes, genetic testing and counseling should be conducted.
Male ; Pregnancy ; Humans ; Child ; Female ; Infant ; Adult ; Chromosomes, Human, Pair 20 ; DNA Copy Number Variations ; Retrospective Studies ; Uniparental Disomy/genetics* ; Atomoxetine Hydrochloride ; Dwarfism ; Intercellular Signaling Peptides and Proteins ; Language Development Disorders ; Growth Disorders ; Insulins