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Abstract Objective To outline the preliminary development and validation of a questionnaire for diagnosing epilepsy and distinguishing focal and generalized epilepsy among infants and children in Indonesia, where electroencephalography and pediatric neurologists are generally not available. Methods A 10‐question questionnaire comprising of 43 items was developed through literature review and expert panel discussions. Then, the questionnaire was administered by pediatricians to 75 children aged 1 month to 18 years old presenting with >1 episode of unprovoked seizures at an interval of >24 h. Subsequently, the questionnaire was assessed for content validity with item‐level and scale‐level content validity indices and ratio, construct validity with item‐total correlation tests, criterion validity with diagnostic parameter assessments, and inter‐rater reliability using Cohen's kappa (κ) and internal consistency with Cronbach's alpha (α) coefficient. Results The questionnaire exhibited favorable internal validity and reliability in diagnosing epilepsy and distinguishing focal and generalized epilepsy, with excellent content (both indices and ratio at 1) and construct validity (rcount > rtable at p

Abstract Understanding thermal transport mechanisms in phase change materials is critical to elucidating the microscopic picture of phase transitions and advancing thermal energy conversion and storage. Experiments consistently show that cubic phase germanium telluride (GeTe) has an unexpected increase in lattice thermal conductivity with rising temperature. Despite its ubiquity, resolving its origin has remained elusive. In this work, we carry out temperature-dependent lattice thermal conductivity calculations for cubic GeTe through efficient, high-order machine-learned models and additional corrections for coherence effects. We corroborate the calculated phonon properties with our inelastic X-ray scattering measurements. Our calculated lattice thermal conductivity values agree well with experiments and show a similar increasing trend. Through additional bonding strength calculations, we propose that a major contributor to the increasing lattice thermal conductivity is the strengthening of second-nearest neighbor interactions. The findings herein serve to deepen our understanding of thermal transport in phase-change materials.

Objectives The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.

This study aims to fill the gap and explore how Islamic parties have attempted to legalize Islamic law in both countries over the past three decades. Most scholarly works on Islamic revivalism in Indonesia and Malaysia focus on it as a sociocultural phenomenon. However, there is a lack of scholarship investigating Islamic revivalism through a political approach. This article employs qualitative research methodology, drawing on academic books, journal articles, reports, and online news to examine the efforts of Islamic parties to legalize Islamic law in Indonesia and Malaysia. The findings suggest that the accessibility of political channels significantly influences these efforts. During the Mahathir era in Malaysia, the availability of political channels facilitated the goal of legalizing Islamic law. Conversely, the agenda for legalizing Islamic law was hindered in Indonesia during the Soeharto era due to limited political channels. Additionally, the moderation of Islamic parties affects the agenda for legalizing Islamic law in both countries. In post-Soeharto Indonesia, the incorporation of moderation by Islamic parties has led to a decrease in prioritizing the agenda of legalizing Islamic law. On the other hand, in Malaysia during and after the Mahathir era, the persistence of the obsession with legalizing Islamic law was due to Islamic parties distancing themselves from moderate positions.

Classification rule mining represents a significant field of machine learning, facilitating informed decision-making through the extraction of meaningful rules from complex data. Many classification methods cannot simultaneously optimize both explainability and different performance metrics at the same time. Metaheuristic optimization-based solutions, inspired by natural phenomena, offer a potential paradigm shift in this field, enabling the development of interpretable and scalable classifiers. In contrast to classical methods, such rule extraction-based solutions are capable of classification by taking multiple purposes into consideration simultaneously. To the best of our knowledge, although there are limited studies on metaheuristic based classification, there is not any method that optimize more than three objectives while increasing the explainability and interpretability for classification task. In this study, data sets are treated as the search space and metaheuristics as the many-objective rule discovery strategy and study proposes a metaheuristic many-objective optimization-based rule extraction approach for the first time in the literature. Chaos theory is also integrated to the optimization method for performance increment and the proposed chaotic rule-based SPEA2 algorithm enables the simultaneous optimization of four different success metrics and automatic rule extraction. Another distinctive feature of the proposed algorithm is that, in contrast to classical random search methods, it can mitigate issues such as correlation and poor uniformity between candidate solutions through the use of a chaotic random search mechanism in the exploration and exploitation phases. The efficacy of the proposed method is evaluated using three distinct data sets, and its performance is demonstrated in comparison with other classical machine learning results.

ABSTRACT Background: A staggering 99% of infant undernutrition mortality comes from Sub-Saharan Africa and South Asia. Despite multiple interventions focusing on nutrition adequacy, 2.7 million children worldwide remain associated with undernutrition-related mortality. The lack of impact from multiple interventions toward undernutrition reflects a strong reason to believe that EED is the missing link that sustains undernutrition in low-to-middle-income countries (LMICs). EED is a sub-clinical condition caused by repeated oral enteropathogenic and non-pathogenic fecal microbes exposure that causes intestinal villous malformation, multi-omics changes, chronic intestinal and systemic inflammation, and gut dysbiosis. EED impacts the absorptive capacity and the integrity of the gut, causing a cycle of undernutrition in children. There is currently no protocol for the diagnosis and treatment of EED, hence EED is widely believed to be highly prevalent and underdiagnosed in LMICs. Objective: To our knowledge, this is the first systematic review to study the impact of nutritional interventions on EED. Previous studies yielded inconsistent results, hence the synthesis of this information is essential in attaining a deeper understanding of EED to formulate new targets of intervention against child undernutrition. Methods: This systematic review is registered to PROSPERO (CRD42022363157) in accordance to PRISMA, using keywords referring to nutrient supplementation, EED, and child growth failure. Results: Eleven articles were eligible for review, comprising randomized controlled trials performed mainly in the African continent, with a total of 5689 healthy children eligible for analysis. Conclusion: The systematic review illustrates that nutritional interventions have a minimal impact on EED biomarkers and linear growth and reflects the importance of understanding better the mechanisms causing EED and its consequences. It appears that the anabolic contribution of nutrition intervention to child growth is negated by EED.

Al-Sheikh Muḥammad al-Tāhir ibn ‘Āshūr, who lived between 1296 AH (1879 AD) and 1393 AH (1973 AD), is considered one of the eminent intellectuals of the modern era and an influential figure among the generation of writers and scholars. He is described as the pioneer of Maqasid thought in contemporary jurisprudence and has developed in this regard the book Maqāṣid al-Sharī‘ah al-Islāmiyyah (The Objectives of the Islamic Shariah), as well as his famous book of Quranic exegesis al-Taḥrīr wa al-Tanwīr. To this effect, this study identifies the reformist features of al-Tāhir ibn ‘Āshūr in his books and writings that brought about a renaissance in various branches of knowledge such as Shariah, tafsīr, and education. A review of the literature suggests that al-Tāhir ibn ‘Āshūr’s reformist ideas have not received sufficient academic attention. Therefore, the study raised some questions, including: Who is Tāhir ibn ‘Āshūr? What were Tāhir ibn ‘Āshūr’s reformist viewpoints, and how did he propagate them out, most particularly in education? The study follows the descriptive approach to trace Ibn ‘Āshūr’s biography as well as the analytical approach in discussing the thought of al-Tāhir ibn ‘Āshūr on the scientific and educational level. The study concludes that Muḥammad al-Ṭāhir ibn ‘Āshūr (may Allah have mercy on him) is one of the eminent intellectuals in the Islamic world, whose innovative views and great writings came as a revolution against tradition and inertia and a revolution against intellectual inaction and civilizational stagnation.

Background Expression of breast milk is a strategy to ensures continuous breastfeeding during temporary separation of infant from the mother. Handling and storage of expressed breast milk (EBM) should be based on established recommendations because these practices can affect milk quality and safety. Objective To describe perceptions and practices of EBM handling and storage, compare with commonly used recommendations and associated factors influencing these practices among mothers in Jakarta, Indonesia, Methods Mothers who practiced expressed breastfeeding (EBF) to their 6-12 weeks-old infants completed questionnaires about their peceptions and practices on how they handle and storage EBM. The differences in perceptions and practices about expressed breastfeeding management were analyzed using the Chi-square or Fisher's exact test. Results Among 30 mothers, 14/30 gave EBF exclusively, 19/30 used breast pump, and 26/30 expressed ³6 times/day. Infants in this study received expressed milk 5-10 times per day. Maternal age and resource of information were factors significantly associated with mother’s perceptions, while maternal age, education, and parity were significantly associated with the practices of EBM handling and storage. Conclusion This study reveals inconsistent perceptions and practices on expressed milk handling and storage by the mothers. They have good knowledge about the theoretical aspects of expressed breastfeeding, but some other techniques are poor, which can be detrimental to the health of the infants. Further study is needed to find more efficient and optimal methods of expressed milk handling and storage, necessitating thoughtful consideration of better practices and recommendations.

BackgroundThere are several studies on thyroid functions and thyroid gland features in patients with leprosy in the literature. The relationship between them have not been clarified yet. These studies are time-expired and don't contain ultrasonography examination. The purpose of the study is to investigate thyroid functions and gland characteristics in leprosy patients by ultrasonography (US) and current laboratory techniques.Patients and methodsThis retrospective study was conducted by collecting the data of patients with lepramatous leprosy. Serum thyroid-stimulating hormone, free triiodothyronine, free thyroxine, anti-thyroid peroxidase, antithyroglobulin, and thyroglobulin values and thyroid ultrasonography reports were collected from previous records.ResultsThe mean age is 75.12±9.89 years of total 17 subjects and 10 patients (58.8%) were male. Thyroid US was performed on 14 of the patients, nodules were detected in a total of 7 (50%) patients. The mean FT3, FT4, TSH, Anti-Tpo, Anti-TG, and TG values of the patients were found to be within normal limits.ConclusionIn the present study, no changes were detected in the thyroid functions and structures of the patients with Lepromatous Leprosy. We consider that prospective randomized studies that will include larger sample sizes are needed to determine whether there is a relationship between leprosy and thyroid disease.

This study aims to describe the types of languages used and the loyalty to the Indonesian language in public spaces in Pamekasan. The research data consists of 704 linguistic objects in public spaces in Pamekasan such as street names, brand names, and business establishments, names of places of worship, names of trade complexes, names of offices, names of educational institutions, names of hospitals, building names, organization names, names of public facilities, road signs, and banners and product service advertisements. The results revealed the use of multiple languages in public spaces in Pamekasan, with eight language variations, including Indonesian, Indonesian and English, Indonesian and Arabic, English, Indonesian and Javanese, Indonesian and Madurese, Madurese, and other languages. Language loyalty to Indonesian in public spaces in Pamekasan was found to be relatively high, with pure Indonesian language use at 63%, Indonesian and other languages at 28%, and the use of regional and foreign languages at 9%. Abstrak Penelitian ini bertujuan untuk mendeskripsikan jenis bahasa dan bagaimana kesetiaan berbahasa Indonesia di ruang publik Pamekasan. Data penelitian ini sejumlah 704 objek linguistik di ruang publik Pamekasan seperti nama jalan, merk dagang & lembaga usaha, nama tempat ibadah, nama kompleks perdagangan, nama perkantoran, nama lembaga pendidikan, nama rumah sakit, nama gedung, nama organisasi, nama fasilitas umum, nama rambu umum & penunjuk jalan, dan nama spanduk dan iklan layanan produk. Hasilnya ditemukan multilingualisme penggunaan bahasa di ruang publik Pamekasan dengan 8 jenis variasi bahasa yakni bahasa Indonesia, bahasa Indonesia & Inggris, bahasa Indonesia & Arab, bahasa Inggris, bahasa Indonesia & Jawa, bahasa Indonesia & Madura, bahasa Madura, dan bahasa lainnya. Kesetiaan berbahasa Indonesia di ruang publik Pamekasan ditemukan masih cukup tinggi. Penggunaan bahasa Indonesia murni ditemukan sebanyak 63%, bahasa Indonesia dan bahasa lain 28%, dan bahasa daerah dan bahasa asing sebanyak 9%.

Lead generation is the process of gaining potential customers’ interest to increase future sales, and it is an essential part of many businesses’ (amusement parks, theme parks, clubs, etc.) sales processes as their membership is more expensive. The main objective of these businesses is to increase the count of customers. By generating sales leads, a club/park can find leads who have already expressed interest in its products and services and access their audience potential, allowing them to focus on future marketing and sales efforts on those leads that are more likely to convert. The current work focuses on how to convert a lead to a customer in optimum number of days. We collect two kinds of data: customer data and lead generation data. The customer data consists of all the leads who have taken the membership, and the lead generation data consists of all current leads. The details of those converted from a lead into a customer in the last 60 days are filtered out from the customer data. Using this data, patterns are generated, which are used to predict the following activity (step) for qualified leads, along with the optimal number of days required to complete that activity. This optimal number of days is found using the Hybrid Chaotic Pattern Search Algorithm (HCPSA). This novel approach here helps in boosting sales by prioritizing leads who have expressed interest and identifying the optimal window for converting them into paying customers. This strategy holds significant potential to benefit businesses across various industries.

Fuel cell systems (FCSs) have been widely used for niche applications in the market. Furthermore, the research community has worked on using FCSs for different sectors, such as transportation, stationary power generation, marine and maritime, aerospace, military and defense, telecommunications, and material handling. The reformation of various fuels, such as methanol, methane, and diesel can be utilized to generate hydrogen for FCSs. This study introduces an advanced convolutional neural network (CNN) model designed to accurately forecast hydrogen yield and carbon monoxide volume percentages during the reformation processes of methane, methanol, and diesel. Moreover, the CNN model has been tailored to accurately estimate methane conversion rates in methane reforming processes. The proposed CNN models are created by combining the 3D-CNN and 2D-CNN models. The Keras Tuner approach in Python is employed in this study to find the ideal values for different hyperparameters such as batch size, learning rate, time steps, and optimization method selection. The accuracy of the proposed CNN model is evaluated by using the root mean square error (RMSE), mean absolute percentage error (MAE), mean absolute error (MAE), and R2. The results indicate that the proposed CNN model is better than other artificial intelligence (AI) techniques and standard CNN for performance estimation of reforming processes of methane, diesel, and methanol. The results also show that the suggested CNN model can be used to accurately estimate critical output parameters for reforming various fuels. The proposed method performs better in CO prediction than the support vector machine (SVM), with an R2 of 0.9989 against 0.9827. This novel methodology not only improves performance estimation for reforming processes but also provides a valuable tool for accurately estimating output parameters across various fuel types.

This study, a descriptive and methodological type of research, was conducted to evaluate the validity and reliability of the Turkish adaptation of the Attitudes to Fertility and Childbearing Scale (AFCS), developed by Söderberg et al. (2015). The sample of this study consisted of 224 women who had not given birth yet and who were between the ages of 20-30. The scale is a Likert-type measuring instrument consisting of 21 items, in three dimensions. Internal consistency analyses were conducted to determine its reliability. After confirming the linguistic validity, expert opinions were obtained for the content validity. Furthermore, the Item Content Validity Index (I-CVI) and the Scale Content Validity Index (S-CVI) were used to assess its content validity. The construct validity was performed using confirmatory factor analysis. As a result of the confirmatory factor analysis carried out for the construct validity, a three-factor structure of the scale was found to have a good level of model fitness indices (RMSEA=0.067, SRMR=0.075, CFI=0.96). As a result of the scale reliability analysis, the internal consistency coefficient was found to be 0.82 for the total scale and internal consistency reliability coefficients of the sub-scales were found to be 0.93 for the "importance of fertility for the future" sub-scale, 0.87 for the "childbearing as a hindrance at present" sub-scale, and 0.81 for the "social identity" sub-scale. AFCS is a valid and reliable measurement tool that can be used to measure the fertility and childbearing attitudes of women in a fertile age.

In electrical sensing applications, achieving a uniform electric field at the sensing region is required to eliminate the compounding effect of particle location on the signal magnitude. To generate a uniform electric field in a microfluidic platform, 3D electrodes based on conductive electrolyte liquids have been developed before, where the ionic conductivity of the electrolyte was sufficient for impedance measurements at low frequencies (typically lower than 50 MHz). However, electrolyte liquids cannot be used as electrodes at microwave frequencies (>1 GHz) due to the low mobility of ions. Here, we used Galinstan, a room-temperature liquid metal, to microfabricate 3D liquid electrodes connected to a microwave resonator — and all integrated within a microfluidic system. By generating a highly uniform electric field, a mixture of 20 μm and 30 μm diameter polystyrene particles were measured and analyzed without any calibration for particle position. The results demonstrate the utility of liquid electrodes in enhancing the electrical characteristics of microwave resonant sensors.

Background This study aimed to determine the prevalence of sarcopenia and its associated factors in community-dwelling older adults at risk of malnutrition based on the Mini Nutritional Assessment (MNA), Prognostic Nutritional Index (PNI), and Geriatric Nutritional Risk Index (GNRI). Methods The study participants were 345 adults aged >65 years who visited Geriatric Internal Medicine outpatient clinics. The study included people without acute illness for whom the risk of malnutrition could be assessed and appropriate measurements taken. At the baseline visit, participants’ data and measurements were gathered. The primary data included sociodemographic details, anthropometric measurements, malnutrition screening tests, and functional assessments. Results The participants’ mean age was 76.21±5.59 years, and 57.1% were men (n=97). The prevalence rate of sarcopenia was 45.5%. Compared to individuals without sarcopenia, those with it were older; had lower MNA, PNI, and GNRI scores; and had lower muscle mass, muscle strength, and lower leg circumferences (p

Introduction: Iron deficiency anemia is the most common cause of anemia worldwide, and increased iron requirement during pregnancy increases the risk of anemia. Anemia in pregnancy is associated with adverse pregnancy outcomes such as low birth weight, preterm and intrauterine growth restriction. This study used a Rule-based Intelligent Classification Models to predict socio-demographic, nutritional, antenatal care and obstetric factors on iron deficiency anemia during pregnancy Methods: This retrospective study was a secondary analysis of a community-based cross-sectional study conducted between January and June 2019 in the province of Elazig in eastern Turkey. Data of 495 pregnant women were included in the study iron deficiency anemia was defined as hemoglobin lt; 11 g/dl, and ferritin lt; 30 µg/L. Rule-based machine learning methods were used to predict factors associated with anemia during pregnancy. Results: The mean age of 495 pregnant women were 30.06 ± 5.15 years. The prevalence of anemia was 27.9% in study population. Maternal age, educational status, occupation, nutrition education status, nutritional property, gravida, and parity were significantly related to anemia. Jrip, OneR, and PART algorithms estimated factors associated with anemia with 96.36%, 85.45%, and 97.98% accuracy, respectively. Conclusion: Rule-based machine learning algorithm may offer a new approach to risk factors for iron deficiency anemia during pregnancy. With the use of this model, it is possible to predict the risk of anemia both before and during pregnancy and to take preventative measures.

The benefits of probiotics for animal health are widely recognised. In this study, we investigated the effects of dietary supplementation with Bacillus subtilis C-3102 on diet digestibility, faecal characteristics, intestinal shedding of microbiota, and hematological characteristics in healthy dogs. Adult Golden Retriever dogs (n = 18) were divided into three groups: the control group (no B. subtilis), the BS1 group (1 × 109 CFU/g of B. subtilis), and the BS2 group (2 × 109 CFU/g of B. subtilis). Dogs were fed for a 30-day administration period, and total faeces were collected in the last five days. On the first and last days of the study, blood samples were taken to determine hematological characteristics. In addition, the dry matter content, faecal consistency score, faecal output, pH, ammonia level, and quantity of short- and branched-chain fatty acids (SCFAs and BCFAs) in faecal samples were also evaluated. Results revealed that the dry matter, fibre, organic matter, and protein digestibility coefficients were higher in BS1 and BS2 (p

Abstract Using dynamical system analysis, we investigate some cosmological consequences of Rastall gravity coupled to a scalar field (called the Klein–Gordon–Rastall theory) with exponential scalar potential turned on in higher dimensions. From the critical points of the autonomous equations, we can determine the dominant components of the energy density in different cosmic eras. We obtain a fixed point representing a scalar field-matter-dominated era which corresponds to either a late-time or past-time attractor depending on the parameters used. According to this point, the inflationary phase, corresponding to past-time attractors, is given by unstable nodes, whilst the dark energy era, corresponding to late-time attractors, is represented by stable nodes. In the inflationary sector, power-law inflation can still occur in this Klein–Gordon–Rastall cosmological model. On the other hand, in the late-time sector, we find a nontrivial interplay between a scalar field with an exponential potential and the non-conservative energy-momentum tensor of the non-relativistic matter field (baryonic-dark matter) in curved spacetime plays a role as the dark energy. Based on such features, the Klein–Gordon–Rastall cosmology could be a promising candidate for describing both the early and late-time universe.

Congenital complete heart block is a rare disease. Pacemaker implantation is indicated in neonates with a heart rate of less than 50 beats per minute. This case report aims to emphasize perioperative management of two cases of congenital complete heart block that underwent pacemaker implantation bed to bed after being delivered by cesarean section. Since these patients are prone to fatal cardiac decompensation and unresponsive to pharmacological therapies, it requires some measures in anesthetic management and good teamwork with other specialties.

It is a known fact that gastrointestinal diseases are extremely common among the public. The most common of these diseases are gastritis, reflux, and dyspepsia. Since the symptoms of these diseases are similar, diagnosis can often be confused. Therefore, it is of great importance to make these diagnoses faster and more accurate by using computer-aided systems. Therefore, in this article, a new artificial intelligence-based hybrid method was developed to classify images with high accuracy of anatomical landmarks that cause gastrointestinal diseases, pathological findings and polyps removed during endoscopy, which usually cause cancer. In the proposed method, firstly trained InceptionV3 and MobileNetV2 architectures are used and feature extraction is performed with these two architectures. Then, the features obtained from InceptionV3 and MobileNetV2 architectures are merged. Thanks to this merging process, different features belonging to the same images were brought together. However, these features contain irrelevant and redundant features that may have a negative impact on classification performance. Therefore, Dandelion Optimizer (DO), one of the most recent metaheuristic optimization algorithms, was used as a feature selector to select the appropriate features to improve the classification performance and support vector machine (SVM) was used as a classifier. In the experimental study, the proposed method was also compared with different convolutional neural network (CNN) models and it was found that the proposed method achieved better results. The accuracy value obtained in the proposed model is 93.88%.

Background Cholestasis can lead to several complications, including portal hypertension and risk of gastrointestinal bleeding. However, there is a paucity of studies on the risk factors and prevalence of gastrointestinal tract bleeding in children with chronic cholestasis, particularly in Indonesia. Objective To determine the prevalence and risk factors for gastrointestinal bleeding in children with chronic cholestasis in Cipto Mangunkusumo Hospital, Jakarta, Indonesia. Methods This was a retrospective cohort study in a national referral hospital in Indonesia. Medical records of children with chronic cholestasis who visited the gastroenterohepatology outpatient clinic were collected for five years. Data on clinical symptoms, etiologies, and complications were obtained. Results A total of 97 participants were recruited on this study. The median age of the group was 0.31 years old. The most common causes of chornic cholestasis were biliary atresia, toxoplasma, other infections, rubella, cytomegalovirus, and herpes simplex virus (TORCH) infection, and urinary tract infection. Gastrointestinal bleeding occurred in 27.8% of patients, with hematemesis-melena being the most prevalent symptom. We found that liver cirrhosis, splenomegaly, thrombocytopenia, portal hypertension, and esophageal varices were all highly related with gastrointestinal bleeding. Splenomegaly, thrombocytopenia, and esophageal varices were associated with an increased risk of gastrointestinal bleeding in children with chronic cholestasis (P=0.018, P=0.008, and P=0.039, respectively). Conclusions The prevalence of gastrointestinal tract bleeding in children with chronic cholestasis is 27.8%, with splenomegaly, thrombocytopenia, and esophageal varices as significant risk factors.

Latar belakang. Anak dengan penyakit ginjal kronik yang memerlukan hemodialisis merupakan kelompok risiko tinggi terjadinya infeksi virus hepatitis C. Infeksi virus hepatitis C pada anak dengan penyakit ginjal kronik memerlukan diagnosis dan tata laksana adekuat untuk mencegah progresifitas penyakit dan komplikasi menjadi karsinoma hepatoselular. Tujuan. Menelaah lebih lanjut diagnosis dan tata laksana infeksi virus hepatitis C pada anak dengan penyakit ginjal kronik di Indonesia. Metode. Penelusuran pustaka database elektronik, yaitu instrumen pencari Pubmed®, EBSCOHost®, dan penelusuran manual. Kata kunci yang digunakan adalah (“children” atau “pediatric”) dan “hepatitis C” dan “end stage renal disease” dan “treatment” dengan menggunakan batasan. Penelitian berbentuk kasus-kontrol, kohort, maupun potong lintang, dipublikasikan dalam bahasa Indonesia atau Inggris, dan diterbitkan dalam 20 tahun terakhir (2002-2022). Hasil. Ditemukan enam artikel yang relevan terhadap pertanyaan klinis. Hasil telaah kritis dan telaah berdasarkan validity, importance dan applicability. Kesimpulan. Hepatitis C pada anak seringkali tanpa gejala atau gejala ringan, memerlukan konfirmasi melalui pemeriksaan molekular. Terapi VHC pada anak PGK yang menjalani hemodialisis kontroversial, tetapi dosis disesuaikan interferon dan ribavirin dapat mencegah progresi penyakit. Klinisi harus mendiagnosis dan mengelola infeksi VHC pada anak PGK untuk mendukung eliminasi hepatitis pada 2030 sesuai target WHO

Depression, malnutrition, and the healthy eating index were assessed in this study of people aged 65 and up who sought treatment at an outpatient clinic for internal medicine. Participants were elderly people from Malatya, Turkiye, who had applied to the outpatient clinic for internal medicine. The three-day dietary recall method was used to obtain the records of food consumption among the elderly. The calculation of Healthy Eating Index-2015 (HEI-2015) scores from food consumption. Geriatric Depression Scale (GDS) was used to define probable depression, and Mini Nutrition Questionnaire-Short Form (MNA-SF) was used to determine nutritional status, using face-to-face interviews. The study were 185 individuals included. The mean age of individuals was 72.19±6.92 years. According to MNA-SF results, 32.3% of women and 27.4% of men were found to be malnourished. The mean body mass ındex (BMI) value of the individuals was 25.73±2.85 kg/cm2, and the BMI value of 56.22% of the individuals was within the normal range. The depression score mean was 8.86±4.73. Depression scores are higher in women, those with low monthly education and income, those who use multiple drugs, those with a low HEI-2015 score, and those who use them. There is a relationship between depression score and eating score. As the nutrition score and the HEI-2015 score decrease, the depression score increases. This study indicates that depressed older people consume less food. Early detection of depression and malnutrition is beneficial. Older adults should routinely use brief, easy-to-obtain diagnostic tools such as the MNA and GDS questionnaires to treat these related health issues quickly and effectively. [Med-Science 2023; 12(3.000): 922-8]

Latar belakang. Kolestasis adalah suatu kondisi gangguan aliran empedu yang memengaruhi asupan nutrisi dan perkembangan anak. Tujuan. Penelitian ini bertujuan mengevaluasi hubungan status nutrisi dan morbiditas pada anak dengan kolestasis kronik. Metode. Studi ini menggunakan metode kohort retrospektif yang melibatkan 97 pasien anak dengan kolestasis kronik. Data antropometri, usia, jenis kelamin, penyebab dasar penyakit, dan morbiditas pasien kemudian dikumpulkan dan dievaluasi. Status nutrisi dinilai berdasarkan kurva WHO 2006. Hasil. Hasil menunjukkan bahwa 46% pasien mengalami kondisi gizi buruk dan 27% gizi kurang berdasarkan pengukuran Lingkar Lengan Atas (LLA) per usia, sementara 66% pasien termasuk ke dalam kategori pendek dan 30% sangat pendek berdasarkan tinggi badan (TB) per usia. Studi ini menunjukkan hubungan antara common cold dan gizi buruk pada anak dengan kolestasis kronik. Kesimpulan. Meski terdapat hubungan antara pruritus, gangguan gastrointestinal, dan perdarahan saluran cerna dengan status gizi, tetapi tidak menunjukkan hasil yang signifikan setelah analisis multivariat. Faktor lain seperti organomegali, asites, dan defisiensi nutrisi tertentu juga berkontribusi terhadap penurunan nafsu makan dan berpotensi mengakibatkan gizi buruk pada anak. Penemuan ini menegaskan pentingnya tatalaksana gizi yang komprehensif dan penanganan dini bagi pasien anak dengan kolestasis kronik.

Abstract The interplay between magnetism and electronic band topology enriches topological phases and has promising applications. However, the role of topology in magnetic fluctuations has been elusive. Here, we report evidence for topology stabilized magnetism above the magnetic transition temperature in magnetic Weyl semimetal candidate CeAlGe. Electrical transport, thermal transport, resonant elastic X-ray scattering, and dilatometry consistently indicate the presence of locally correlated magnetism within a narrow temperature window well above the thermodynamic magnetic transition temperature. The wavevector of this short-range order is consistent with the nesting condition of topological Weyl nodes, suggesting that it arises from the interaction between magnetic fluctuations and the emergent Weyl fermions. Effective field theory shows that this topology stabilized order is wavevector dependent and can be stabilized when the interband Weyl fermion scattering is dominant. Our work highlights the role of electronic band topology in stabilizing magnetic order even in the classically disordered regime.