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More than half of the world's population lives in cities, so the increase in urban waste production globally is mainly due to population growth, urbanization, and economic development, in the past decade, the utilization of waste to energy has provided positive benefits in terms of energy generation. By 2040 power generation will increase globally by 49%. By 2040, renewable energy sources are expected to meet 8% of the total global energy demand, With the development of the economy, waste management goes through several stages to reach the level of high technology as seen today. A sophisticated collection system, combined with an efficient separation process, enables high recovery and recycling rates. The method used in this study is qualitative with a literature study approach. The findings in this study show that China is the country that researches the most about wasto to energy, then the process carried out in the PLTSa Waste to Energy Policy Model recommendations in this study involves several related actors such as Business Entities, authorized Local Governments, and communities. In this case, waste to energy needs attention by local governments that have the authority to manage electricity by establishing provincial regulations in the electricity sector, establishing general electricity plans, and determining business licenses for providing electricity to business entities.

Food not only provides a feeling of fullness, but is also beneficial for health and disease prevention. One type of food that has health benefits is functional food, one of which is food bars. Foodbars are made from a mixture of nutritionally enriched blended food such as grains, dried fruit and nuts which are then formed into a solid and compact food. One of the local food ingredients that is used as a substitute for making food bars is okra and porang. The aim of this research was to determine the effect of adding okra flour and porang flour on the proximate and organoleptic composition of Foodbars. The research method used an experimental design, namely a one-factor Completely Randomized Design (CRD), with treatment comparison between okra flour and porang flour (15:10, 12.5:12.5, 10:15). Each treatment was repeated 5 times. The variables observed were water content, ash, crude fiber, fat, protein, carbohydrates, and preference test. The data obtained were analyzed for variance and if there were differences between treatments, they were further tested using the Duncan Multiple Range Test (DMRT) at the 5% level. The research results of the addition of 12.5g okra flour and 12.5g porang flour are food bars with the best treatment in physicochemical testing and meet the requirements of commercial food bars according to SNI and are liked by consumers with a water content of 11.11%, ash 4.88%, crude fiber 27 .20, fat 26.38%, protein 12.42%, and carbohydrates 45.21%

This research aims to analyze the to find out the response of using Millealab on the material comprehension of slow learners. This study used a qualitative approach with a case study method. The subjects in this study were slow learners grade 8 students at SMP Plus Rahmat Kediri, East Java. The instruments used in this research are observation, interview, and observation which were then analyzed inductively. The result show that virtual reality (VR) helps slow learners connect abstract concepts with real experieces, which supports their understanding. The findings have immportant implications in inclusive education, where VR can improve the cognitive growth and academic understanding of slow learners students.

Abstract The effect of fermented foods on healthy human gut microbiota structure and function, particularly its seasonal preference and frequent long-term consumption, has been largely uncharacterised. Here, we assess the gut microbiota and metabolite composition of 78 healthy Indian agrarian individuals who differ in the intake of fermented milk and soybean products by seasonal sampling during hot-humid summer, autumn and dry winter. Here we show that, seasonal shifts between the Prevotella- and Bifidobacterium/Ruminococcus-driven community types, or ecological states, and associated fatty acid derivatives, with a bimodal change in Bacteroidota community structure during summer, particularly in fermented milk consumers. Our results associate long-term fermented food consumption with reduced gut microbiota diversity and bacterial load. We identify taxonomic groups that drive the seasonal fluctuation and associated shifts between the two ecological states in gut microbiota. This understanding may pave the way towards developing strategies to sustain a healthy and resilient gut microbiota through dietary interventions.

Abstract Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. Testing multiple integration strategies, most of them yield multimodal models surpassing both the best unimodal models and established univariate biomarkers, such as PD-L1 expression. Additionally, several multimodal combinations demonstrate improved patient risk stratification compared to models built with routine clinical features only. Our study thus provides evidence of the superiority of multimodal over unimodal approaches, advocating for the collection of large multimodal NSCLC datasets to develop and validate robust and powerful immunotherapy biomarkers.

In hazardous environments like nuclear facilities, robotic systems are essential for executing tasks that would otherwise expose humans to dangerous radiation levels, which pose severe health risks and can be fatal. However, many operations in the nuclear environment require teleoperating robots, resulting in a significant cognitive load on operators as well as physical strain over extended periods of time. To address this challenge, we propose enhancing the teleoperation system with an assistive model capable of predicting operator intentions and dynamically adapting to their needs. The machine learning model processes robotic arm force data, analyzing spatiotemporal patterns to accurately detect the ongoing task before its completion. To support this approach, we collected a diverse dataset from teleoperation experiments involving glovebox tasks in nuclear applications. This dataset encompasses heterogeneous spatiotemporal data captured from the teleoperation system. We employ a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model to learn and forecast operator intentions based on the spatiotemporal data. By accurately predicting these intentions, the robot can execute tasks more efficiently and effectively, requiring minimal input from the operator. Our experiments validated the model using the dataset, focusing on tasks such as radiation surveys and object grasping. The proposed approach demonstrated an F1-score of 89% for task classification and an F1-score of 86% classification forecasted operator intentions over a 5-second window. These results highlight the potential of our method to improve the safety, precision, and efficiency of robotic operations in hazardous environments, thereby significantly reducing human radiation exposure.

Abstract Nonlinear responses of individual neurons are both experimentally established and considered fundamental for the functioning of neuronal circuitry. Consequently, one may envisage the collective dynamics of large networks of neurons exhibiting a large repertoire of nonlinear behaviors. However, an ongoing and central challenge in the modeling of neural dynamics involves the trade-off between tractability and biological realism. This is particularly important in exploring the range of possible dynamics of large networks. Our approach uses Gaussian white noise as a probe, thus capturing the full range of system responses and characteristics by using an approach inspired by the well-established Wiener − Volterra nonlinear system identification approach. We assess model behavior over a range of network architectures and noise stimulation rates and demonstrate non-monotonicity and nonlinearity as a system property. Perhaps surprisingly, our computational model suggests that recurrent systems of nonlinear neurons exhibit a range of complex behaviors that do not readily yield to linear modeling in every setting. Our results suggest that a linear interpretation of experimental data is likely to discount the critical importance of properties emerging from network architecture. The main contribution of this effort is to highlight the importance of the network’s architecture operating on the nonlinear properties of individual neurons and the experimental probing approaches of the circuitry.

Abstract Traditionally, the place-pitch ‘tonotopically’ organized auditory neural pathway was considered to be hard-wired. Cochlear implants restore hearing by arbitrarily mapping frequency-amplitude information. This study shows that recipients, after a long period of sound deprivation, preserve a level of auditory plasticity, enabling them to swiftly and concurrently learn speech understanding with two alternating, distinct frequency maps. During rehabilitation, subjects switched maps randomly on a daily basis, serving as their own control. After stating their preference, on average, subjects maintained their hearing performance with the non-preferred, legacy map over time. In addition, subjects continued to learn and improve with their map of preference. Being able to train and process the auditory information from two maps did not seem to be a competition over neural resources, such as would be the case in a typical zero-sum game. This shows a new level of flexibility in learning and long-term adaptation of the auditory system. Practically, the required novel study design halves the sample size while mitigating order effects associated with neural plasticity, benefitting sensory-oriented trials.

Abstract Objective A newborn with GRIN1‐related early infantile developmental and epileptic encephalopathy (DEE) with striking pharmacoresistance is described with emphasis on potential therapy with memantine and vigabatrin. Methods The term neonate manifested electrographic and electroclinical seizures from the first day of life with focal tonic seizures with apnea, bradycardia, and desaturations and later developed epileptic spasms and a hyperkinetic movement disorder. Multiple antiseizure medication trials were unsuccessful. Brain magnetic resonance imaging displayed extensive malformations of cortical development. Results Whole‐exome sequencing demonstrated a de novo novel GRIN1 variant (1916T > G,p.Phe639Cys), which can be associated with NMDA receptor dysfunction. Gain‐of‐function mutation was suspected based on phenotype correlation. Seizures markedly improved after initiation of memantine, an NMDA‐receptor antagonist. Memantine was complemented by the concurrent use of vigabatrin, initiated 4 days earlier due to emergence of epileptic spasms. Significant reduction in seizures facilitated discharge from neonatal intensive care unit. Interpretation GRIN1‐related disorders occur due to NMDA receptor dysfunction. Patients with gain‐of‐function GRIN1 mutations who present with the phenotype of DEE with extensive bilateral polymicrogyria may benefit from a trial of NMDA‐receptor antagonist therapy and vigabatrin. Further research is warranted to better understand this markedly pharmacoresistant condition and to investigate targeted therapies in GRIN1 DEE.

Type 2 diabetes mellitus (T2DM) is a global health concern, with diabetic neuropathy (DN) being a prevalent complication. Current DN treatments focus on blood glucose control and pain management, which show limited efficacy. This study explored the effects of autologous dendritic cell (DC) administration on improving DN symptoms. A quasi-experimental clinical trial was conducted on 28 DN patients at Gatot Soebroto Army Hospital. Patients received autologous DC administration, with their Toronto Clinical Neuropathy Score (TCNS), Transforming Growth Factor-β (TGF-β), and Vascular Cell Adhesion Molecule-1 (VCAM-1) levels measured before and at four weeks after treatment. The results show an average TCNS reduction from 8.93 to 7.5 (p < 0.001). TGF-β levels increased slightly from 41.16 ng/mL to 44.18 ng/mL (p > 0.05). VCAM-1 levels increased from 1389.75 ng/mL to 1403.85 ng/mL. Correlation analysis showed that TGF-β levels had a significant negative correlation with the TCNS (r = −0.353; p = 0.033) and VCAM-1 levels (r = −0.521; p = 0.002). Autologous DC administration significantly improves DN. While the changes in TGF-β and VCAM-1 levels were not statistically significant, their trends suggest that there was an anti-inflammatory effect. These findings highlight the potential of autologous DC therapy as a complementary approach to manage DN through inflammation reduction and nerve repair.

The dominant agricultural sector in Slovakia is crop production, with the majority of arable land dedicated to cultivating cereals (57%), followed by fodder crops (20%) and industrial crops (19%). Slovakia has technical and biophysical potential for expanding biomass production. However, it is crucial to identify optimal production practices, alternative costs, and environmental outputs. Farms become more vulnerable to the worldwide threat posed by climate change. Based on research, farmers can effectively mitigate the adverse effects of climate change by making necessary adjustments to their current farming techniques. Thus, by using an advanced tool like integrated farm models, farmers can evaluate and manage a range of risks related to their activities. This paper aims to present the application of integrated modelling frameworks at the farm level and propose a framework for studying the consequences of climate change through a scenario-based approach at the farm level. Integrated assessments provide new insights that complement those derived from more detailed assessments. Based on the model developed, the results of two research questions are provided. Since, from the viewpoint of the farmer, risk and unpredictability associated with lower yields are frequently the main causes of lower income, spatially explicit integrated modelling is applied, enabling economic optimisation of crop production on a selected farm with a focus on maximising net returns while considering biophysical parameters. The modelling results depict the distribution of selected crops on arable land and the most suitable management practices for crop production in terms of nitrogen application and irrigation utilisation. Additionally, we develop an integrated model proposing the estimation of the risk of yield variability and nitrogen emissions for three climate change scenarios for the simulated period of 2020-2100 on the model farm. In response to the problems posed by climate change, this integrated approach can assist evidence-based decision-making and sustainable agriculture practices.

Abstract Purpose To evaluate early response of retinal sensitivity (RS) and retinal morphology in diabetic macular edema (DME) patients after intravitreal anti-vascular endothelial growth factor (anti-VEGF) treatment. Methods Sixteen eyes of 12 DME patients were included in this study conducted prospectively. All eyes underwent functional and morphologic examination of the macular area using microperimetry and optical coherence tomography (OCT) before and after intravitreal anti-VEGF injection. To determine significant differences between the values, paired t test was used. A correlation between CMT and RS was made using Spearman’s test. Results Patients were evaluated at baseline, one week and one month after injection. The central macular thickness (CMT) decreased significantly from 449.33 ± 100.79 μm to 427.94 ± 85.76 μm to 357.93 ± 75.92 μm. The RS improved significantly from 7.94 ± 6.43 dB to 11.09 ± 7.42 dB at one week and to 14.22 ± 7.66 dB at one month after treatment. The CMT was significant negatively correlated to RS (r=-0.259, p =

Abstract The framework of the methodology presented in this study is an effort to integrate and optimize the agro-industry sector, especially energy in biogas. In this study, the technique of the system in functional analysis is shown systematically to translate various energy requirements in the factory as criteria for performance and functional design to be integrated, optimized, and energy efficient. The case study results indicated that biogas power plants, with a capacity of 1.5 MW, can produce around 13,140 MWh per year. The annual return on investment (ROI) is around 37.13%. With this ROI value, the payback period is 31 months. The overall reduction of greenhouse gases is approximately 77,826 tons CO2 eq/year. The potential value of carbon trading is about USD 3,113,040 per year. This strategic model presents a novel approach by integrating biogas energy production with a customized wastewater treatment system adapted to biodigesters’ effluent characteristics. It offers a sustainable, economically feasible, and scalable solution, combining resource recovery, waste minimization, and potential for carbon trading into a unified system. The novelty of this research lies in maximizing the utility of biogas plants by efficiently treating and reusing wastewater, creating a closed-loop, zero-waste process. Future research on hybrid systems integrating Biogas power plants by focusing on efficiency optimization, economic feasibility, environmental impacts, and innovative approaches like AI and blockchain could make the hybrid system a more robust, scalable, and sustainable solution. Thus, the framework based on the results of this study finds tools that can maximize and integrate energy sources, especially biogas, in the agro-industrial sector.

Tuberculosis (TB) is a contagious disease caused by Mycobacterium tuberculosis that most often affects the lungs. It is classified as an airborne disease since it spreads through the air when people with TB cough, sneeze, or spit. Indonesia is one of the countries with the total high TB burden worldwide. The estimated number of people who fell ill because of TB reached 845,000, with a death rate of 98,000, or equivalent to 11 deaths/hour. The control of TB in Indonesia has been carried out for more than seventy years, but Indonesia is still reported as the country with the second-highest TB burden in the world. The long-term use of anti-TB drugs or Multidrug-resistant TB (MDR-TB), an immunosuppressive agent, can cause fungal infections. Fungal infections can occur in the earlier stage of the disease, but the patients are only given anti-TB drugs. It takes longer for them to recover due to fungal coinfections. The purpose of this study was to find out the frequency distribution of tuberculosis based on the characteristics of patients (age, gender, and type of fungi) and to investigate the statistical distribution of fungi based on the characteristics of sputum i.e color (mucopurulent), consistency (viscosity), and blood presence (hemoptysis). This study used an analytical research design with an observational cross-sectional approach. The samples of this study were sputum taken from 98 patients collected using an accidental sampling technique. The results of the study revealed that, of 98 patients, 81 (82.7%) were adult, 63 (64.3%) were male, 41 (41.9%) were infected with Candida sp, 9 (9.1%) with Aspergillus sp, and 17 (17.3%) with mixed infection. Meanwhile, 31 (31.7%) samples were found negative. In addition, there was no significant relationship between the types of fungi and the characteristics of sputum.

Abstract Trigger valves are fundamental features in capillary-driven microfluidic systems that stop fluid at an abrupt geometric expansion and release fluid when there is flow in an orthogonal channel connected to the valve. The concept was originally demonstrated in closed-channel capillary circuits. We show here that trigger valves can be successfully implemented in open channels. We also show that a series of open-channel trigger valves can be placed alongside or opposite a main channel resulting in a layered capillary flow. We developed a closed form model for the dynamics of the flow at trigger valves based on the concept of average friction length and successfully validated the model against experiments. For the main channel, we discuss layered flow behavior in the light of the Taylor-Aris dispersion theory and in the channel turns by considering Dean theory of mixing. This work has potential applications in autonomous microfluidics systems for biosensing, at-home or point-of-care sample preparation devices, hydrogel patterning for 3D cell culture and organ-on-a-chip models.

Economics is characterized by a knowledge gap—a discontinuity between everyday and scientific understandings. An extensive empirical literature proves the so-called economic ignorance of the public. This has contributed to a disdain for the public among economists and provided an argument for more influence of experts. At the same time, many citizens have grown skeptical of scientific expertise, and economic expertise in particular. We question the supposed economic illiteracy of the public by pointing out serious methodological issues with the empirical literature on the economic knowledge of laypeople. Rather than seeking to meet laypeople on their own terms and in their own language, it instead tests their knowledge of (expert) concepts in academic language. More broadly, this literature assumes there is one body of economic knowledge to which some have access and others do not. We argue that economic knowledge is better understood as the multiple heterogeneous bodies of knowledge associated with different communities of practitioners. We argue that economics as a discipline should seek convergence between these bodies of knowledge through translation efforts. We demonstrate that Philip Wicksteed and Elinor Ostrom made efforts to further this convergence and suggest further constructive steps following methodological work in sociology and surveys of public understanding of economics based on interpretivist approaches. We argue that an economics which recognizes these multiple bodies of knowledge, and which aims at convergence, has the potential to improve economics education, foster mutual understanding between economists and the public, and remedy some of the mutual distrust between them.

Abstract Background There is limited population-based evidence on the prevalence of cognitive impairment in Mexico, a country with a rapidly aging population and where key risk factors, such as diabetes and obesity, are common. This study describes the distribution of cognitive impairment in adults from Mexico City. Methods This cross-sectional population-based study included participants from the Mexico City Prospective Study which recruited 150,000 adults aged ≥ 35 years in 1998–2004. In 2015–2019 about 10,000 survivors were resurveyed with identical information from the original survey and additional assessments including a cognitive assessment. The main analyses included those aged 50–89 years with complete cognitive assessment and covariate data at resurvey. Cognitive impairment was defined by a score ≤ 24 on the Mini Mental State Examination (MMSE). The distribution of MMSE scores and cognitive impairment by age, sex, and major disease risk factors (diabetes, hypertension, and adiposity) was analyzed among those with complete MMSE data and some degree of self-reported formal education. Results Of the 9,288 participants aged 50–89 years at the 2015–2019 resurvey with complete data, 8,197 reported having at least some years of formal education. Among these (mean age 66 years; 31% men), their mean MMSE score was 26.2 (SD 3.6) points, 1,941 (24%) had cognitive impairment, their mean body-mass index (BMI) was 28.6 (SD 5.5) kg/m2, 3,008 (37%) had hypertension and 2,467 (30%) had diabetes. The sex- and district-standardised prevalence of cognitive impairment increased strongly with age, from 10% in those 50–59 years to 55% in those aged 80–89. At any given age, the prevalence of cognitive impairment was higher in women than in men. After accounting for the effects of age, sex, and district there was little difference in the prevalence of cognitive impairment between participants with or without diabetes, hypertension, overweight or obesity (BMI ≥ 25 km/m2), or high levels of fat mass. Conclusions In this population of adults aged 50–89 years from Mexico City, the prevalence of cognitive impairment was high, particularly among women. The extent to which cognitive impairment relates to health outcomes in this population needs to be investigated.

This research aims to test and analyze the absolute and conditional convergence of per capita income from 38 districts/cities in East Java with the variables PAD, BOS and BOK during the period 2020 - 2022. According to the Chow, Hausmann test and Lagrange Multiplier, the panel data convergence model estimates using the fixed effect model method. Results show that in the districts/cities and observation period, divergent conditions occurred. Also, conditional variables did not have a significant influence on the growth of per capita income. This condition can occur because capital and technology are distributed unevenly between districts/cities. The implication of this research is to improve the allocation and distribution of the government budget, especially those related to School Operational Assistance (BOS) and Health Operational Assistance (BOK).

Abstract Extreme precipitation events are projected to intensify with global warming, threatening ecosystems and amplifying flood risks. However, observation-based estimates of extreme precipitation-temperature (EP-T) sensitivities show systematic spatio-temporal variability, with predominantly negative sensitivities across warmer regions. Here, we attribute this variability to confounding cloud radiative effects, which cool surfaces during rainfall, introducing covariation between rainfall and temperature beyond temperature’s effect on atmospheric moisture-holding capacity. We remove this effect using a thermodynamically constrained surface-energy balance, and find positive EP-T sensitivities across continents, consistent with theoretical arguments. Median EP-T sensitivities across observations shift from −4.9%/°C to 6.1%/°C in the tropics and −0.5%/°C to 2.8%/°C in mid-latitudes. Regional variability in estimated sensitivities is reduced by more than 40% in tropics and about 30% in mid and high latitudes. Our findings imply that projected intensification of extreme rainfall with temperature is consistent with observations across continents, after confounding radiative effect of clouds is accounted for.

Abstract Background Biologics for psoriasis demonstrate varying clinical outcome in real‐world practice, implying potential under‐ and overexposure. Objectives In this prospective cohort study we aimed to develop and validate an in‐house sandwich‐type enzyme‐linked immunosorbent assay (ELISA) for ixekizumab (IXE), and to explore whether there is an exposure‐response relationship in standard maintenance dose for IXE, and whether patient factors influence IXE exposure and clinical outcome. Methods This was a prospective, multicentric, cohort study in psoriasis patients treated with IXE according to standard dosing regimen (BIOLOPTIM‐IXE). IXE trough concentrations (TCs) in sera collected at multiple timepoints were measured using an in‐house immunoassay. Results Using MA‐IXE117E12 and MA‐IXE100F5‐biotin as the capture and detection antibodies, respectively, an ELISA was developed with an exposure‐response curve ranging from 10 to 0.16525 ng/mL. One hundred‐fifteen steady‐state serum samples from 48 patients (17 [35.4%] bio‐experienced; median body weight, 81.5 kg) were measured. Optimal responders (Psoriasis Area and Severity Index [PASI] ≤ 2) had significantly higher TCs than suboptimal responders (PASI > 2) (median TCs, 4.4 and 3.0 μg/mL, respectively; p = 0.026). Median cohort IXE TC was 4.1 µg/mL [2.8−6.1]. An optimal steady‐state IXE TC of 3.4 µg/mL was identified for clinical outcome defined by absolute PASI. Median TCs and absolute PASI were significantly lower and worse, respectively, in patients ≥ 90 kg (p

Abstract Background There are numerous papers focusing on diagnosing mental health disorders using unimodal and multimodal approaches. However, our literature review shows that the majority of these studies either use unimodal approaches to diagnose a variety of mental disorders or employ multimodal approaches to diagnose a single mental disorder instead. In this research we combine these approaches by first identifying and compiling an extensive list of mental health disorder markers for a wide range of mental illnesses which have been used for both unimodal and multimodal methods, which is subsequently used for determining whether the multimodal approach can outperform the unimodal approaches. Methods For this study we used the well known and robust multimodal DAIC-WOZ dataset derived from clinical interviews. Here we focus on the modalities text and audio. First, we constructed two unimodal models to analyze text and audio data, respectively, using feature extraction, based on the extensive list of mental disorder markers that has been identified and compiled by us using related and earlier studies. For our unimodal text model, we also propose an initial pragmatic binary label creation process. Then, we employed an early fusion strategy to combine our text and audio features before model processing. Our fused feature set was then given as input to various baseline machine and deep learning algorithms, including Support Vector Machines, Logistic Regressions, Random Forests, and fully connected neural network classifiers (Dense Layers). Ultimately, the performance of our models was evaluated using accuracy, AUC-ROC score, and two F1 metrics: one for the prediction of positive cases and one for the prediction of negative cases. Results Overall, the unimodal text models achieved an accuracy ranging from 78% to 87% and an AUC-ROC score between 85% and 93%, while the unimodal audio models attained an accuracy of 64% to 72% and AUC-ROC scores of 53% to 75%. The experimental results indicated that our multimodal models achieved comparable accuracy (ranging from 80% to 87%) and AUC-ROC scores (between 84% and 93%) to those of the unimodal text models. However, the majority of the multimodal models managed to outperform the unimodal models in F1 scores, particularly in the F1 score of the positive class (F1 of 1s), which reflects how well the models perform in identifying the presence of a marker. Conclusions In conclusion, by refining the binary label creation process and by improving the feature engineering process of the unimodal acoustic model, we argue that the multimodal model can outperform both unimodal approaches. This study underscores the importance of multimodal integration in the field of mental health diagnostics and sets the stage for future research to explore more sophisticated fusion techniques and deeper learning models.

Abstract Here we conduct a study involving 12 individuals with retinal dystrophy, neurological impairment, and skeletal abnormalities, with special focus on GPATCH11, a lesser-known G-patch domain-containing protein, regulator of RNA metabolism. To elucidate its role, we study fibroblasts from unaffected individuals and patients carrying the recurring c.328+1 G > T mutation, which specifically removes the main part of the G-patch domain while preserving the other domains. Additionally, we generate a mouse model replicating the patients’ phenotypic defects, including retinal dystrophy and behavioral abnormalities. Our results reveal a subcellular localization of GPATCH11 characterized by a diffuse presence in the nucleoplasm, as well as centrosomal localization, suggesting potential functions in RNA and cilia metabolism. Transcriptomic analysis performed on mouse retina detect dysregulation in both gene expression and splicing activity, impacting key processes such as photoreceptor light responses, RNA regulation, and primary cilia-associated metabolism. Proteomic analysis of mouse retina confirms the roles GPATCH11 plays in RNA processing, splicing, and transcription regulation, while also suggesting additional functions in synaptic plasticity and nuclear stress response. Our research provides insights into the diverse roles of GPATCH11 and identifies that the mutations affecting this protein are responsible for a recently characterized described syndrome.

The primary goal of this research is to examine the learning style inventories of English as a Foreign Language (EFL) students at Muhammadiyah University and to discuss how these tactics relate to various learning style traits. This research was conducted among students at Muhammadiyah University in Makassar, Indonesia. A questionnaire was distributed to 69 students, who were randomly selected from a population of 120 based on the Slovin formula. The study is part of a larger mixed-methods research initiative, with quantitative results reported in other publications. The qualitative insights gathered from interviews reveal that students exhibit a diverse array of learning methods influenced primarily by three key sensory modalities: storing, remembering, and recalling information. These findings have a substantial impact on the process of English language teaching, suggesting that tailoring instructional strategies to fit these identified learning styles can lead to more effective teaching practices and enhanced classroom engagement. Furthermore, the research contributes significantly to the broader study of language and communication learning inventories within educational and language training contexts, providing vital insights that can inform educators on how to adapt their teaching methods to meet the varied needs of their learners more effectively. Overall, this study underscores the importance of understanding learning styles in fostering a conducive learning environment.

Many countries, as well as several regions in Indonesia, are adopting digital government with the urgency that this approach is helpful as a bridge to good governance. However, more examination is needed to see both the opportunities and obstacles of digital government by assessing cases at the local level. This research analyses the potential and challenges of developing digital government locally with a case study in Central Sulawesi Province. The region was selected for analysis because Central Sulawesi has developed the necessary telecommunications infrastructure and internet access. The study relies on online research methods to collect data and information via the internet and other digital technology. This study employs NVivo 12 Plus for analysis. The findings of this research reveal that Central Sulawesi has great potential in developing digital government, such as optimising data management, accelerating administrative processes and increasing citizen involvement. However, the study also identifies challenges, such as poor access to digital infrastructure in rural areas and limited digital skills among government employees. Therefore, strong efforts are needed to expand the reach of internet access, improve digital skills and increase citizen participation in the development of digital government. This research provides an in-depth understanding of the potential and challenges of developing digital government in Central Sulawesi as well as relevant policy recommendations to increase digital adaptation at the local level.

Phosphaturic mesenchymal tumor (PMT) is a rare tumor causing bone complications and myopathy. Histologically, PMT displays a mix of spindled cells, osteoclast-like giant cells, basophilic matrix, and flocculent or “grungy” calcification. Here we describe a case of PMT in the right hip and proximal femur, initially suspected to be multiple myeloma, presenting with osteolytic lesions and elevated alkaline phosphatase. Tests for malignancy were negative, but a subsequent biopsy confirmed PMT. The patient underwent hip biopsy, femur resection, and hemiarthroplasty, with follow-up MRI recommended.

OBJECTIVE: This study evaluated the effectiveness of the promotion of postural shift intervention using a dynamic seat cushion on the 6-month incidence of neck and low-back pain among high-risk office workers. METHODS: In a cluster-randomized controlled trial (RCT), 133 office workers were randomly assigned, at cluster level, to intervention (N=67) and control (N=66) groups. The intervention group received a dynamic seat cushion to encourage postural shifts during sitting, while the control group received a placebo seat pad. Primary outcomes were 6-month incidence of neck and low-back pain. Secondary outcomes included sitting discomfort, pain intensity, disability, and trunk muscle performance. Analyses utilized Cox proportional hazard models. RESULTS: During the 6-month period, 15% of participants in the intervention group developed neck pain and 10% developed low-back pain. For the control group, this was 65% and 59%, respectively. Hazard rate (HR) ratios, after adjusting for biopsychosocial factors, indicated a protective effect of the intervention for neck pain [HR_adj 0.19, 95% confidence interval (CI) 0.09–0.39, P

Abstract Twenty-six fragment of wall paintings detached from the upper register of the Carolingian and Romanesque cycles of the church of St. John in Müstair (Switzerland) have been part of the Swiss National Museum collection since the beginning of the twentieth century. As some of these objects were in a critical state of conservation, a research project was launched to assess and document their conditions, and to gain knowledge about painting materials and execution techniques, in view of planning a conservation project. In a first phase, non-destructive analyses were carried out, using handheld XRF and portable FTIR spectroscopy; followed by the targeted collection of samples for detailed analysis in the laboratory. In parallel, similar investigations were carried out on the imprints left on the walls of the church’s attic. The results allowed the identification of the pigment palette and the execution technique. Besides earth pigments such as ochres, a lime-based white, probably bianco di San Giovanni, and limited amounts of lapis lazuli were used in both painting cycles. For the Carolingian cycle, Egyptian blue and mixtures of several lead-based pigments were also identified. In several instances, the deterioration of lead-based pigments resulted in shades of grey to black severely modifying the original appearance of the wall paintings. Additionally, both cycles have suffered from pigment alteration due to fire. The obtained results, together with iconographic considerations, allowed for an extended interpretation of possible original colour palette. Graphical Abstract

Abstract Background Congenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. Methods We used genome sequencing (GS) (n = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) (n = 154 CHD and n = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls. Results Of 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls. Conclusions A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.

This paper presents the design of a wall-following robot (WFR) with a rotating sensor compartment to reduce the number of distance sensors used. Two infrared (IR) sensors were fitted in the compartment that rotates back and forth at 45°, producing four measurement values at each rotation cycle. The WFR was regulated using a novel control scheme of PID controller with an override mode. A discrete PID controller in position form was used to run the WFR to follow straight wall segments or walls turning left, while an override mode governed the WFR to follow walls turning right. The sampling time was set to 300 ms. The parameters of the PID controller were tuned using a trial-and-error method. The Mean Absolute Errors (MAE) was selected as the cost function. The WFR conducted twelve trial runs along a trial track with a length of 200 cm, consisting of one right turn and one left turn. The parameters that yielded the lowest MAE of 0.90 cm were used for further tests. Subsequently, a closed track for testing was constructed with a length of 845 cm, consisting of 7 right turns and 2 left turns. The WFR completed five test runs successfully, each elapsing the test track twice. The lowest MAE during the tests was 1.06 cm. The favorable performance of the proposed WFR strengthens future development efforts to equip the robot with more hardware to fulfill specific tasks and to put the completion time into optimization consideration.

Abstract Background Popularity of electrical impedance tomography (EIT) and esophageal pressure (Pes) monitoring in the ICU is increasing, but there is uncertainty regarding their bedside use within a personalized ventilation strategy. We aimed to gather insights about the current experiences and perceived role of these physiological monitoring techniques, and to identify barriers and facilitators/solutions for EIT and Pes implementation. Methods Qualitative study involving (1) a survey targeted at ICU clinicians with interest in advanced respiratory monitoring and (2) an expert focus group discussion. The survey was shared via international networks and personal communication. An in-person discussion session on barriers, facilitators/solutions for EIT implementation was organized with an international panel of EIT experts as part of a multi-day EIT meeting. Pes was not discussed in-person, but we found the focus group results relevant to Pes as well. This was confirmed by the survey results and four additional Pes experts that were consulted. Results We received 138 survey responses, and 26 experts participated in the in-person discussion. Survey participants had diverse background [physicians (54%), respiratory therapists (19%), clinical researchers (15%), and nurses (6%)] with mostly > 10 year ICU experience. 84% of Pes users and 74% of EIT users rated themselves as competent to expert users. Techniques are currently primarily used during controlled ventilation for individualization of PEEP (EIT and Pes), and for monitoring lung mechanics and lung stress (Pes). EIT and Pes are considered relevant techniques to guide ventilation management and is helpful for educating clinicians; however, 57% of EIT users and 37% of Pes users agreed that further validation is needed. Lack of equipment/materials, evidence-based guidelines, clinical protocols, and/or the time-consuming nature of the measurements are main reasons hampering Pes and EIT application. Identified facilitators/solutions to improve implementation include international guidelines and collaborations between clinicians/researcher and manufacturers, structured courses for training and use, easy and user-friendly devices and standardized analysis pipelines. Conclusions This study revealed insights on the role and implementation of advanced respiratory monitoring with EIT and Pes. The identified barriers, facilitators and strategies can serve as input for further discussions to promote the development of EIT-guided or Pes-guided personalized ventilation strategies.

Abstract Background Neck and low back pain are prevalent issues among office workers due to prolonged sitting, necessitating effective interventions. Dynamic seat cushion, designed to promote postural shifts, have emerged as promising solutions to address this concern. This study aims to evaluate the effectiveness of a dynamic seat cushion on recovery and recurrence of neck and/or low back pain in office workers. Methods This study used 6-month follow-up data of a randomized controlled trial, involving 66 office workers who reported neck and/or low back pain during the trial. At baseline, participants were cluster-randomized into an intervention group, which received a dynamic seat cushion designed to encourage postural shifts, or a control group, which received a placebo seat pad. Health outcomes included recovery duration and recurrence of pain. Analyses utilized log rank test and Cox proportional hazard models. Results The recovery rate from neck and/or low back pain was 100% for the intervention group, and 86% for the control group. The median recovery duration of participants who reported pain during the 6-month period was 1 month in the intervention group and 3 months in the control group. The intervention group had a higher probability of recovery compared to the control group (HRadj 4.35, 95% CI 1.87–10.11; p

Abstract Background Normothermic machine perfusion of donor livers has become standard practice in the field of transplantation, allowing the assessment of organs and safe extension of preservation times. Alongside its clinical uses, there has been expanding interest in extended normothermic machine perfusion (eNMP) of livers as a potential vehicle for medical research. Reproducible extended normothermic machine perfusion has remained elusive due to its increased complexity and monitoring requirements. We set out to develop a reproducible protocol for the extended normothermic machine perfusion of whole human livers. Methods Human livers declined for transplantation were perfused using a blood-based perfusate at 36 °C using the Liver Assist device (XVIVO, Sweden), with continuous veno-venous haemofiltration in-parallel. We developed the protocol in a stepwise fashion. Results Perfusion techniques utilised included: targeted physiological vascular flows, phosphate replacement (to prevent hypophosphataemia), N-acetylcysteine (to prevent methaemoglobin accumulation), and the utilisation of sodium lactate as both a nutritional source and real-time measure of hepatocyte function. All five human livers perfused with the developed protocol showed preserved function with a median perfusion time of 168 h (range 120–184 h), with preserved viability throughout. Conclusions Livers can be reproducibly perfused in excess of 120 (range 121–184) hours with evidence of preserved hepatocyte and cholangiocyte function.

Aim: Assessing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibodies among healthcare workers (HCWs) is crucial in understanding the durability of humoral immune response due to vaccination and the post-pandemic era. Therefore, this study aimed to evaluate IgG antibody seroprevalence, IgG levels, and long-term durability responses after the coronavirus disease 2019 (COVID-19) pandemic in HCWs. Methods: The cross-sectional study recruited HCWs aged ≥ 18 years, vaccinated at least once, and without autoimmune diseases at Dr. Wahidin Sudirohusodo Hospital Makassar. Antibody titers against spike protein, nucleocapsid protein, and spike-nucleocapsid conjugate were quantified using dried blood spot (DBS) samples and multi-antigen profiling (xMAP) technology to measure seroprevalence. Results: The results showed that there was a total of 103 participants with the majority being female (59.22%), ≤ 40-year-old (87.38%), nurses (56.31%), had no comorbidities (88.35%), and were infected with COVID-19 (70.87%). A significant proportion received three times vaccination (76.7%), while 102 of 103 (99.03%) showed seropositivity. IgG showed the highest mean antibody titers for spike protein [10,819.38 ± 2,554.23 mean fluorescence intensity (MFI)] in the first 6–12 months after the last vaccinations. Meanwhile, the IgG titer (MFI) showed a long duration over 30 months. Vaccine significantly influenced spike protein antibody levels, with the highest observed in the group receiving a combination of two inactivated vaccines followed by two messenger ribonucleic acid (mRNA) vaccines (p < 0.05). Conclusions: HCWs showed a sustained humoral immune response to SARS-CoV-2 for over 24 months post-vaccination. The type and combination of vaccines administered were significantly correlated with the IgG antibody levels, suggesting the long-term efficacy of the vaccination regimens. The application of DBS and xMAP technology in the study facilitated the assessment of SARS-CoV-2 IgG responses, offering valuable insights into the dynamics of immune persistence following vaccination.

Abstract Perceptual expertise is typically domain-specific and rarely generalises beyond an expert’s domain of experience. Forensic feature-comparison examiners outperform the norm in domain-specific visual comparison, but emerging research suggests that they show advantages on other similar tasks outside their domain of expertise. For example, fingerprint examiners not only outperform novices in fingerprint comparison, but also in face comparison. Yet, the extent to which their skills generalise is poorly understood. In this study, we investigated the generalisability of perceptual expertise amongst forensic examiners by comparing their performance to novices and other examiners within and outside their area of expertise. We recruited 85 experts from three forensic disciplines (face, fingerprint, and firearms) and asked them to complete four different visual comparison tasks: faces, fingerprints, firearms, and novel-objects. Examiners displayed domain-specific expertise: they outperformed novices and other examiners within their domain of visual comparison expertise. Yet, some of their skill also generalised: examiners also outperformed novices outside their area of expertise. However, while individual differences in examiners’ performance within their domain of experience were associated with their performance in a novel comparison task, they were not related to their performance on tasks outside their expert domain. These results provide key insight into the domain-specific and domain-general contributions of forensic examiners’ perceptual expertise. Forensic expertise lends some generalisable skill to other visual comparison tasks, but best performance is still seen within examiners’ domain of expertise.

Abstract Background Proximal caries datasets for training artificial intelligence (AI) algorithms commonly include clinician-annotated radiographs. These conventional annotations are susceptible to observer variability, and early caries may be missed. Micro-computed tomography (CT), while not feasible in clinical applications, offers a more accurate imaging modality to support the creation of a reference-standard dataset for caries annotations. Herein, we present the Academic Center for Dentistry Amsterdam—Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset, which is the first dataset pairing dental radiographs and micro-CT scans to enable higher-quality annotations. Methods The ACTA-DIRECT dataset encompasses 179 paired micro-CT scans and radiographs of early proximal carious teeth, along with three types of annotations: conventional annotations on radiographs, micro-CT-assisted annotations on radiographs, and micro-CT annotations (reference standard). Three dentists independently annotated proximal caries on radiographs, both with and without micro-CT assistance, enabling determinations of interobserver agreement and diagnostic accuracy. To establish a reference standard, one dental radiologist annotated all caries on the related micro-CT scans. Results Micro-CT support improved interobserver agreement (Cohen’s Kappa), averaging 0.64 (95% confidence interval [CI]: 0.59–0.68) versus 0.46 (95% CI: 0.44–0.48) in its absence. Likewise, average sensitivity and specificity increased from 42% (95% CI: 34–51%) to 63% (95% CI: 54–71%) and from 92% (95% CI: 88–95%) to 95% (95% CI: 92–97%), respectively. Conclusion The ACTA-DIRECT dataset offers high-quality images and annotations to support AI-based early caries diagnostics for training and validation. This study underscores the benefits of incorporating micro-CT scans in lesion assessments, providing enhanced precision and reliability. Graphical Abstract

This paper presents the process of conducting the structural analysis of AlAinSat-1 CubeSat through a numerical solution using Siemens NX. AlAinSat-1 is a 3U remote-sensing CubeSat carrying two earth observation payloads. The CubeSat is scheduled for launch on SpaceX Falcon 9 rocket. To ensure the success of the mission and its ability to withstand the launch environment, several scenarios should be analyzed. For AlAinSat-1 model the finite element analysis (FEA) method is used, and four types of structural analyses are considered: modal, quasi-static, buckling, and random vibration analyses. The workflow cycle includes idealizing, meshing, assembling, applying connections and boundary conditions, and eventually running the simulation utilizing the Siemens Nastran solver. The simulation results of all analysis types indicate that the model can safely withstand the loads exerted during launch. Also, the numerical results of the Command and Data Handling Subsystem (CDHS) module of AlAinSat-1 are experimentally validated through a vibration test conducted using an LV8 shaker system. The module successfully passed the test based on the test success criteria provided by the launcher.

Abstract Compartmentalization is a vital aspect of living cells to orchestrate intracellular processes. In a similar vein, constructing dynamic and responsive sub-compartments is key to synthetic cell engineering. In recent years, liquid-liquid phase separation via coacervation has offered an innovative avenue for creating membraneless organelles (MOs) within artificial cells. Here, we present a lab-on-a-chip system to reversibly trigger peptide-based coacervates within cell-mimicking confinements. We use double emulsion droplets (DEs) as our synthetic cell containers while pH-responsive elastin-like polypeptides (ELPs) act as the coacervate system. We first present a high-throughput microfluidic DE production enabling efficient encapsulation of the ELPs. The DEs are then harvested to perform multiple MO formation-dissolution cycles using pH as well as temperature variation. For controlled long-term visualization and modulation of the external environment, we developed an integrated microfluidic device for trapping and environmental stimulation of DEs, with negligible mechanical force, and demonstrated a proof-of-principle osmolyte-based triggering to induce multiple MO formation-dissolution cycles. In conclusion, our work showcases the use of DEs and ELPs in designing membraneless reversible compartmentalization within synthetic cells via physicochemical triggers. Additionally, presented on-chip platform can be applied over a wide range of phase separation and vesicle systems for applications in synthetic cells and beyond.

Abstract Background Long-term deterioration in the mental health of healthcare workers (HCWs) has been reported during and after the COVID-19 pandemic. Determining the impact of COVID-19 incidence and mortality rates on the mental health of HCWs is essential to prepare for potential new pandemics. This study aimed to investigate the association of COVID-19 incidence and mortality rates with depressive symptoms over 2 years among HCWs in 20 countries during and after the COVID-19 pandemic. Methods This was a multi-country serial cross-sectional study using data from the first and second survey waves of the COVID-19 HEalth caRe wOrkErS (HEROES) global study. The HEROES study prospectively collected data from HCWs at various health facilities. The target population included HCWs with both clinical and non-clinical roles. In most countries, healthcare centers were recruited based on convenience sampling. As an independent variable, daily COVID-19 incidence and mortality rates were calculated using confirmed cases and deaths reported by Johns Hopkins University. These rates represent the average for the 7 days preceding the participants’ response date. The primary outcome was depressive symptoms, assessed by the Patient Health Questionnaire-9. A multilevel linear mixed model (LMM) was conducted to investigate the association of depressive symptoms with the average incidence and mortality rates. Results A total of 32,223 responses from the participants who responded to all measures used in this study on either the first or second survey, and on both the first and second surveys in 20 countries were included in the analysis. The mean age was 40.1 (SD = 11.1), and 23,619 responses (73.3%) were from females. The 9323 responses (28.9%) were nurses and 9119 (28.3%) were physicians. LMM showed that the incidence rate was significantly and positively associated with depressive symptoms (coefficient = 0.008, standard error 0.003, p = 0.003). The mortality rate was significantly and positively associated with depressive symptoms (coefficient = 0.049, se = 0.020, p = 0.017). Conclusions This is the first study to show an association between COVID-19 incidence and mortality rates with depressive symptoms among HCWs during the first 2 years of the outbreak in multiple countries. This study’s findings indicate that additional mental health support for HCWs was needed when the COVID-19 incidence and mortality rates increase during and after the early phase of the pandemic, and these findings may apply to future pandemics. Trial registration Clinicaltrials.gov, NCT04352634.

Abstract Microelectromechanical system-based microphones demand high ingress protection levels with regard to their use in harsh environment. Here, we develop environmental protective components comprising polyimide nanofibers combined onto polyether ether ketone fabric meshes and subsequently appraise their impact on the electroacoustic properties of high signal-to-noise-ratio microelectromechanical system-based microphones via industry-standard characterizations and theoretical simulations. Being placed directly on top of the microphone sound port, the nanofiber mesh die-cut parts with an inner diameter of 1.4 mm result in signal-to-noise-ratio and insertion losses of (2.05 ± 0.16) dB(A) and (0.30 ± 0.11) dBFS, respectively, in electroacoustic measurements. Hence, a high signal-to-noise-ratio value of (70.05 ± 0.17) dB(A) can be maintained by the mesh-protected microphone system. Due to their high temperature stability, acoustic performance, environmental robustness, and industry-scale batch production, these nanofibrous meshes reveal high potential to be practically implemented in high-market-volume applications of packaged microelectromechanical system-based microphones.

Background: The objective of this research was to test whether efficient tinnitus suppression could be achieved by electrical stimulation of the single most basal electrode contact of a cochlear implant. This approach simulates the effects of electrical stimulation using a round-window electrode. Methods: The study was performed in 10 adult cochlear implant patients showing complete or almost complete tinnitus suppression during electrical stimulation with their standard fitting-MAP. In all patients, tinnitus appeared again when the implant was switched off. Five Nucleus implant (1 CI532, 4 CI24RE CA) users and 5 Mi12xx series with FLEX28 electrodes with at least 6 months of CI experience were included. Two types of stimulation were presented at the most basal CI contact: a constant pulse train and a modulated pulse train. The variation in pulse rates was low rate (100-300 pps) and high (≥900 pps), and the current level ranged from the C-level to less than the T-level for both stimulation types. The effect of acute electrical stimulation at the most basal electrode contact was compared to the effect obtained with multichannel stimulation with the patient’s current fitting MAP. Electrical stimulation was paused between tests with different stimulation types until tinnitus returned to baseline intensity. Patients reported Visual Analog Scale (VAS) scores for tinnitus loudness and intrusiveness during normal CI use and for each single contact stimulation type. Results: Eight participants perceived complete suppression with one or more stimulation patterns. In 2 patients, suppression was less efficient than full-band CI stimulation. Louder stimuli are generally perceived as annoying and less effective in reducing tinnitus. In FLEX28 patients, it was also possible to obtain full tinnitus suppression with current amplitudes under the thresholds for auditory perception (this was not tested in patients with the Nucleus device). Conclusion: In 8 of the 10 included patients, we were able to obtain complete or almost complete tinnitus suppression with electrical stimulation at only 1 most basal electrode contact. Therefore, round-window stimulation with a single electrode may be a potential treatment for tinnitus in patients with significant residual hearing. The long-term effects of this therapy should be confirmed in future studies.

Background: Low Vision is an end-stage condition that cannot be cured. The best treatment for low vision is the early detection. However, there is still no integrated low vision data in health services, the lack of public knowledge about low vision, the low rate of case discovery, and the lack of optimal referral and treatment mechanisms for low vision are problems that must be addressed at this time. Purpose: This study aims to detect early low vision determinant factors using a self-assessment application. Methods: This study is analytical and quantitative research. Respondents for this research were from five selected populations in East Java who filled out the e-SIGALON application from September to December 2023. The respondents were suspected as having low vision if they had score of 6 or higher. The variables were analyzed using logistic binary regression, the validity and reliability test was also performed. Results: From 446 respondents, there were 237 people (53.14%) suspected of low vision but only 66 people came to referral hospital. The low vision suspect showed 12 of the 15 statistically significant questions (p

Introducción: la educación médica requiere una evolución constante y ha generado nuevas metodologías de enseñanza. Dentro de estas, el cine destaca por su utilidad para enseñar habilidades del humanismo médico. Objetivo: sintetizar la evidencia disponible sobre los beneficios y limitaciones del cine como herramienta en la educación médica. Metodología: se realizó una revisión sistemática exploratoria de la literatura disponible en las bases de datos indexadas con descriptores MeSH, acerca de los efectos del uso del cine en la educación médica en los últimos 23 años. Se seleccionaron 26 documentos. Resultados: Se hallaron estudios de 15 países, donde se describen los beneficios del cine para el desarrollo de pensamiento crítico, habilidades de humanismo médico e integración teórico- clínica; para lograr esto se requiere preparación de los docentes en el uso de esta metodología. Sin embargo, aún existen limitaciones en la aceptación e implementación de la “cinemeducación” por parte de las facultades de medicina. Conclusiones: El cine como herramienta educativa presenta beneficios para la generación de habilidades necesarias para el médico y solo presenta escasas dificultades para su implementación, fácilmente superables con entrenamiento docente en el uso de esta metodología.

This study addresses the critical need for enhanced accuracy in YOLOv8 models designed for visually impaired navigation systems. Existing models often struggle with consistency in object detection and distance estimation under varying environmental conditions, leading to potential safety risks. To overcome these challenges, this research implements a rigorous approach combining data augmentation and meticulous model optimization techniques. The process begins with the meticulous collection of a diverse dataset, essential for training a robust model. Subsequent preprocessing of images in the HSV color space ensures standardized input features, crucial for consistency in model training. Augmentation techniques are then applied to enrich the dataset, enhancing model generalization and robustness. The YOLOv8 model is trained using this augmented dataset, leading to significant enhancements in key performance metrics. Specifically, mean average precision (mAP) improved by 13.3%, from 0.75 to 0.85, precision increased by 10%, from 0.80 to 0.88, and recall rose by 10.3%, from 0.78 to 0.86. Further optimization efforts, including parameter tuning and the strategic integration of a Kalman Filter, notably improved object tracking and distance estimation capabilities. Final validation in real-world scenarios confirms the efficacy of the optimized model, demonstrating its readiness for practical deployment. This comprehensive approach showcases tangible advances in navigational assistance technology, significantly improving safety and reliability for visually impaired users.

Salak can grow well in the lowlands at an altitude of 200 m above sea level to an altitude of 700 meters above sea level with a wet climate type. The desired environment has a pH of 5-7, rainfall of 1500-3000 mm per year with a dry season of four to six months. The purpose of this study was to determine the differences in soluble sugar content, vitamin C content and total titratable acid of Sidimpuan salak fruit (Salacca sumatrana Becc) based on the three classifications of altitude. This research has been carried out in West Angkola District in three locations with an altitude of 500-650m above sea level, Padangsidimpuan Hutaimbaru in 3 garden locations with an altitude of 400-500 m above sea level and South Angkola there are 3 with an altitude of 200-300 m above sea level, starting in August to September 2021. Based on the results of this study, it is concluded that the difference in altitude of the place does not significantly affect the dissolved sugar content and vitamin C of Sidimpuan salak fruit but the altitude of the place has a significant effect on the total titratable acid of salak fruit, namely 1.4011% in West Angkola and 0.9822% Padangsidimpuan Hutaimbaru sub-district and South Angkola 1.2644%.

Abstract Freehand optical ultrasound (OpUS) imaging is an emerging ultrasound imaging paradigm that uses an array of fibre-optic, photoacoustic ultrasound sources and a single fibre-optic ultrasound detector to perform ultrasound imaging without the need for electrical components in the probe head. Previous freehand OpUS devices have demonstrated capability for real-time, video-rate imaging of clinically relevant targets, but have been hampered by poor ultrasound penetration, significant imaging artefacts and low frame rates, and their designs limited their clinical applicability. In this work we present a novel freehand OpUS imaging platform, including a fully mobile and compact acquisition console and an improved probe design. The novel freehand OpUS probe presented utilises optical waveguides to shape the generated ultrasound fields for improved ultrasound penetration depths, an extended fibre-optic bundle to improve system versatility and an overall ruggedised design with protective elements to improve probe handling and protect the internal optical components. This probe is demonstrated with phantoms and the first multi-participant in vivo imaging study conducted with freehand OpUS imaging probes, this represents several significant steps towards the clinical translation of freehand OpUS imaging.

Abstract Key Message Leaves of seedlings from five oak species (Quercus robur L.; Q. pubescens L.; Q. suber L.; Q. afares Pomel; Q. ilex L.) displayed large, mainly inter-specific, differences in leaf mass-to-area ratio (LMA) and lignin content, as well as in the 13C composition of bulk leaf biomass. The variation in leaf lignin content and LMA did not impact the offset between the 13C composition measured in bulk leaf material versus soluble sugars. This observation, as well as the similar correlations between intrinsic leaf water use efficiency and the 13C compositions of bulk material or soluble sugars extracted from leaves, confirms their reliable use as a proxy for the former even when there is a large variation in LMA or lignin among samples. Context Carbon isotope composition (δ 13 C) of bulk leaf biomass is frequently used as a proxy for intrinsic water use efficiency (iWUE) in large-scale intra- and inter-specific comparisons. However, post-photosynthetic 13C discrimination during the synthesis of lignin combined with differences in leaf mass-to-area ratio (LMA) may bias the relationship between δ 13 C of bulk leaf matter and iWUE and thus its use as a proxy of iWUE. Aims To quantify the impact of differences in lignin content and LMA on the relationship between δ 13 C of bulk leaf biomass and iWUE over a large gradient of lignin contents across five oak species (deciduous: Quercus robur, Q. pubescens, Q. afares and evergreen: Q. ilex and Q. suber). Methods We measured lignin content, LMA, and δ 13 C of bulk leaf biomass and of soluble sugars extracted from the leaves, as well as intrinsic water use efficiency (derived from leaf gas exchange) in seedlings of the five oak species grown under common conditions in a greenhouse and measured in a climate chamber. Results There was a large range (mainly across species) in lignin content (4 to 33%) and LMA (60–180 g m−2). δ 13 C of bulk leaf biomass and soluble sugars were tightly correlated, showing a significant mean offset of − 0.4‰. This offset was stable across species and not correlated to the lignin content of the leaves. A very loose correlation was found between the offset and LMA, mainly due to one species. Conclusion Our results are a demonstration that potential variations in leaf lignin content or LMA have no or only a little effect on the δ 13 C of bulk leaf biomass. They are unlikely to cause a bias when using bulk leaf δ 13 C as a proxy for variations in intrinsic water use efficiency among Mediterranean and temperate broad-leaf forest tree species.

Temperature and humidity are critical factors in oyster mushroom cultivation, and as such, it is imperative to manage and regulate these variables with the aid of modern technology. The primary goal of this community service initiative is to enhance the productivity and quality of oyster mushrooms, while also fostering the sustainability of cultivation efforts. This method encompasses training sessions on proper temperature and humidity control techniques, the implementation of monitoring equipment, and the establishment of an optimal cultivation environment. The outcomes of these efforts have revealed a notable enhancement in both the production and quality of oyster mushrooms. Additionally, farmers have expressed an increase in technical knowledge and a deeper understanding of the advantages associated with appropriate environmental control. This technology holds the potential to elevate farmers' income and positively influence the cultivation environment. In summary, the implementation of temperature and humidity control technology yields tangible benefits, ultimately promoting the sustainability of oyster mushroom cultivation and contributing to the enhancement of farmers' expertise.

Abstract Deregulation of transcription factors (TFs) leading to uncontrolled proliferation of tumor cells within the microenvironment represents a hallmark of cancer. However, the biological and clinical impact of transcriptional interference, particularly in multiple myeloma (MM) cells, remains poorly understood. The present study shows for the first time that MYC and JUNB, two crucial TFs implicated in MM pathogenesis, orchestrate distinct transcriptional programs. Specifically, our data revealed that expression levels of MYC, JUNB, and their respective downstream targets do not correlate and that their global chromatin-binding patterns are not significantly overlapping. Mechanistically, MYC expression was not affected by JUNB knockdown, and conversely, JUNB expression and transcriptional activity were not affected by MYC knockdown. Moreover, suppression of MYC levels in MM cells via targeting the master regulator BRD4 by either siRNA-mediated knockdown or treatment with the novel proteolysis targeting chimera (PROTAC) MZ-1 overcame bone marrow (BM) stroma cell/IL-6-induced MYC- but not MEK-dependent JUNB-upregulation and transcriptional activity. Consequently, targeting of the two non-overlapping MYC- and JUNB-transcriptoms by MZ-1 in combination with genetic or pharmacological JUNB-targeting approaches synergistically enhanced MM cell death, both in 2D and our novel dynamic 3D models of the BM milieu as well as in murine xenografts. In summary, our data emphasize the opportunity to employ MYC and JUNB dual-targeting treatment strategies in MM as another exciting approach to further improve patient outcomes.

Abstract Background Large variation in the prevalence of ankylosis and replacement resorption (ARR) is reported in the literature and most studies have relatively small patient numbers. The present retrospective study aimed to provide an overview on prevalence, location of, and associated risk factors with ARR based on a large sample of computed tomography (CT) / cone beam computed tomography (CBCT) scans of impacted teeth. The results should allow clinicians to better estimate the risk of ARR at impacted teeth. Methods The CT/CBCT scans of 5764 patients of a single center in Central Europe were screened with predefined eligibility criteria. The following parameters were recorded for the finally included population: gender, age, tooth type/position, number of impacted teeth per patient, and presence/absence of ARR. For teeth with ARR the tooth location in reference to the dental arch, tooth angulation, and part of the tooth affected by ARR were additionally registered. Results Altogether, 4142 patients with 7170 impacted teeth were included. ARR was diagnosed at 187 impacted teeth (2.6%) of 157 patients (3.7%); 58% of these patients were female and the number of teeth with ARR per patient ranged from 1 to 10. Depending on the tooth type the prevalence ranged from 0 (upper first premolars, lower central and lateral incisors) to 41.2% (upper first molars). ARR was detected at the crown (57.2%), root (32.1%), or at both (10.7%). After correcting for confounders, the odds for ARR significantly increased with higher age; further, incisors and first/second molars had the highest odds for ARR, while wisdom teeth had the lowest. More specifically, for 20-year-old patients the risk for ARR at impacted incisors and first/second molars ranged from 7.7 to 10.8%, but it approximately tripled to 27.3–35.5% for 40-year-old patients. In addition, female patients had significantly less often ARR at the root, while with increasing age the root was significantly more often affected by ARR than the crown. Conclusion ARR at impacted teeth is indeed a rare event, i.e., only 2.6% of 7170 impacted teeth were ankylosed with signs of replacement resorption. On the patient level, higher age significantly increased the odds for ARR and on the tooth level, incisors and first/second molars had the highest odds for ARR, while wisdom teeth had the lowest.