Low Sensitivity Research Articles

Expanding the applications of the wear-resistant titanium aluminum nitride thin-film to include temperature sensing

This study investigates an approach to temperature sensing by integrating Titanium Aluminum Nitride (TiAlN), originally engineered for wear and corrosion applications, as a temperature sensor within a multilayered thin film system. A nitride multilayer system was developed by physical vapor deposition (PVD) using a single four-target magnetron sputtering chamber; intermediate vacuum interruption steps were employed for masking procedures. The multilayer architecture design aimed to provide the sensor layer with mechanical protection and electrical shielding. Structural and electrical characterization of the TiAlN single layer revealed semiconductor behavior and stable electrical resistance up to 750 °C, with minimal signal stabilization requirements. Despite the higher Al content, the TiAlN temperature sensor exhibited a cubic crystal structure characterized by diffuse nanolayers resulting from a two-fold rotational deposition and target configuration. Detailed examination of the multilayer system cross-section, containing the TiAlN sensor, was conducted by scanning transmission electron microscopy (STEM). The analysis revealed its columnar morphology with the presence of typical PVD growth defects, including voids and droplets. While the presence of these defects may impact the electrical characteristics of the sensor, the selected experimental conditions effectively maintained the structural integrity of the multilayer system, despite the vacuum interruptions caused by masking procedures. Validation experiments confirmed the functionality of the multilayer system for temperature measurements up to 400 °C. The signal acquisition system addressed room temperature resistance variations and low sensitivity (thermistor coefficient ∼100 K), resulting in a measured error of approximately 6%. This study demonstrates promising results of TiAlN as a temperature sensor within a multilayered system, expanding its range of potential applications.

Association between insulin sensitivity and lean mass loss during weight loss.

The study objective was to assess the relationship between insulin sensitivity and changes in total lean mass (LM) and appendicular LM (ALM) during weight loss. Individuals were randomly assigned to either a standard or a moderately reduced carbohydrate diet for 16 weeks. Body composition was assessed using dual-energy x-ray absorptiometry and insulin sensitivity index (SI) using an intravenous glucose tolerance test. Multiple linear regression was used to determine whether baseline SI was predictive of changes in total LM and ALM. Participants (n = 57; baseline BMI 32.1 ± 3.8 kg/m2) lost an average of 6.8 ± 3.2 kg of body weight (p < 0.001), with 1.5 ± 2.6 kg coming from LM (p < 0.05) and 0.5 ± 0.73 kg from ALM (p < 0.05). Multiple regression analysis demonstrated that SI was inversely associated with changes in total LM (kilograms; β = 0.481, p < 0.001), after adjusting for baseline LM, fat mass, acute insulin response to glucose, and weight loss. Similar results were seen when assessing ALM loss (β = 0.359, p < 0.05). Identifying individuals with low insulin sensitivity prior to weight loss interventions may allow for a personalized approach aiming at minimizing LM loss.

Deciphering the environmental adaptation and functional trait of core and noncore bacterial communities in impacted coral reef seawater

Microorganisms play pivotal roles in different biogeochemical cycles within coral reef waters. Nevertheless, our comprehension of the microbially mediated processes following environmental perturbation is still limited. To gain a deeper insight into the environmental adaptation and nutrient cycling, particularly within core and noncore bacterial communities, it is crucial to understand reef ecosystem functioning. In this study, we delved into the microbial community structure and function of seawater in a coral reef under different degrees of anthropogenic disturbance. To achieve this, we harnessed the power of 16S rRNA gene high-throughput sequencing and metagenomics techniques. The results showed that a continuous temporal succession but little spatial heterogeneity in the bacterial communities of core and noncore taxa and functional profiles involved in nitrogen (N) and phosphorus (P) cycling. Eutrophication state (i.e., nutrient concentration and turbidity) and temperature played pivotal roles in shaping both the microbial community composition and functional traits of coral reef seawater. Within this context, the core subcommunity exhibited a remarkably broader habitat niche breadth, stronger phylogenetic signals and lower environmental sensitivity when compared to the noncore taxa. Null model analysis further revealed that the core subcommunity was governed primarily by stochastic processes, while deterministic processes played a more significant role in shaping the noncore subcommunity. Furthermore, our observations indicated that changes in function related to N cycling were correlated to the variations in noncore taxa, while core taxa played a more substantial role in critical processes such as P cycling. Collectively, these findings facilitated our knowledge about environmental adaptability of core and noncore bacterial taxa and shed light on their respective roles in maintaining diverse nutrient cycling within coral reef ecosystems.

Lungs Tumor Classification using Convolutional Neural Network

The research focuses on classifying lung cancer using the VGG-19 architecture. The datasets were sourced from Iraq-Oncology Teaching Hospital with 70% of the data allocated for training and 30% for testing. Performance metrics were computed to evaluate the effectiveness of the classification method. Python is utilized for designing the algorithm and executed using Goggle Colab. The lung tumor classification using VGG-19 offers an accuracy of 95%, sensitivity of 88.79%, specificity of 98.25 %, and F1-Score of 93.28%. However, the low sensitivity value indicates that the VGG-19 architecture is not accurately predicting benign and malignant cases.

A skeleton-based method for exercise recognition based on 3D coordinates of human joints

&lt;p&gt;The aim of the work is to develop the method of identification and comparison of poses and exercises performed by a person that will have a low sensitivity to data errors. This method uses their formal descriptions in the form of conjunctions of logical statements and should work regardless of the shooting angle at which the video was taken and the proportions of the person on it. Each statement describes the position of the joints relative to each other along one of the axes. The joint coordinates are corrected by taking into account the length of the bones that connect them that eliminates the necessity to process outliers and it also improves the accuracy of joints positioning. Removal of errors out of the data using the method of averaging the graph along each axis at every step. In order to do this, consecutive points are grouped so that the difference between the maximum and the minimum does not exceed the error. The groups are then filtered to leave only those in which both are smaller or both are larger. The proposed method of identification requires just a modern smartphone and has no restrictions on how to take video of exercises.&lt;/p&gt;

Nanopore single molecule ATP detection based on the dual effects of specific capturing and signal amplification

Adenosine triphosphate (ATP) plays a crucial role in energy metabolism. Some serious diseases such as Alzheimer’s disease are related to abnormal ATP concentrations. Fast, sensitive, and specific ATP detection is important and challenging in disease diagnosis and biomedical research. In present study, conical nanopore was designed and employed to detect ATP at single molecule level. For overcoming the inherent defects such as non-selectivity and low sensitivity of nanopore in sensing small target molecule, two collaborative improvements of specific identification and signal amplification were proposed. We first used split aptamer capture probes (H1 and S1) to anchor ATP molecule, and then used auxiliary probes (H2 and H3) to form a long-nicked duplex ATP-DNA concatemer by hybridization chain reaction (HCR). Referring ATP-DNA concatemer rather than native ATP to nanopore sensor, characteristic current signals with high signal-to-noise ratio were obtained. By such indirect way, specific and sensitive ATP detection was realized with a linear range from 20 pM to 5 nM and a detection limit of 3.9 pM (S/N = 3). Additionally, the sensor exhibited many merits such as simplify, anti-interference, and especially allowing ATP detection in real sample. So, we believe that the nanopore sensor has good application prospects in screening and management of ATP-related diseases.

Evaluation of CINA® LVO artificial intelligence software for detection of large vessel occlusion in brain CT angiography

ObjectiveTo systematically evaluate the ability of the CINA® LVO software to detect large vessel occlusions eligible for mechanical thrombectomy on CTA using conventional neuroradiological assessment as gold standard. MethodsRetrospectively, two hundred consecutive patients referred for a brain CTA and two hundred patients that had been subject for endovascular thrombectomy, with an accessible preceding CTA, were assessed for large vessel occlusions (LVO) using the CINA® LVO software. The patients were sub-grouped by occlusion site. The original radiology report was used as ground truth and cases with disagreement were reassessed. Two-by-two tables were created and measures for LVO detection were calculated. ResultsA total of four-hundred patients were included; 221 LVOs were present in 215 patients (54%). The overall specificity was high for LVOs in the anterior circulation (93%). The overall sensitivity for LVOs in the anterior circulation was 54% with the highest sensitivity for the M1 segment of the middle cerebral artery (87%) and T-type internal carotid occlusions (84%). The sensitivity was low for occlusions in the M2 segment of the middle cerebral artery (13 and 0% for proximal and distal M2 occlusions respectively) and in posterior circulation occlusions (0%, not included in the intended use of the software). ConclusionsLVO detection sensitivity for the CINA® LVO software differs largely depending on the location of the occlusion, with low sensitivity for detection of some LVOs potentially eligible for mechanical thrombectomy. Further development of the software to increase sensitivity to all LVO locations would increase the clinical usefulness.

Advancing hydrogen storage predictions in metal-organic frameworks: A comparative study of LightGBM and random forest models with data enhancement

The escalating consumption of fossil fuels has given rise to a substantial upsurge in greenhouse gas concentrations and global temperatures, which, in turn, has triggered severe climate-related consequences. The critical imperative to reduce CO2 emissions and combat global warming has spurred extensive investigations into clean energy alternatives, with hydrogen emerging as a compelling zero-emission energy source. As a pivotal component of clean energy strategies, hydrogen requires designing compact, lightweight, and efficient storage systems. This study focuses on the development and evaluation of machine learning models for predicting the efficiency of Metal-Organic Frameworks (MOFs) in hydrogen storage, a key aspect of advancing clean energy technologies. MOFs, a class of nanoporous materials, show remarkable potential for hydrogen storage due to their high surface area and porosity. However, selecting the most suitable MOF for this application from a vast array of possible structures is a daunting task. In this context, machine learning algorithms offer an efficient alternative for predicting MOF suitability by considering their structural and chemical properties. We used ensemble learning methods, specifically Light Gradient Boosting Machine (LightGBM) and Random Forest (RF), to predict hydrogen uptake of MOFs based on a dataset of 219 experimentally tested samples. Two modeling scenarios were considered: one using the entire dataset, and the other involving strategic data pre-processing, including outlier removal and feature engineering. The results demonstrate that the measures taken to refine the dataset significantly enhance the predictive performance of the developed models, reducing prediction errors and improving overall goodness of fit. Specifically, the Mean Absolute Error (MAE) values for both the LightGBM and random forest models were reduced from 0.48 and 0.94, respectively, to 0.16 for both models, and the coefficients of determination (R2) increased substantially from 0.84 and 0.72 to 0.95, in both cases. Moreover, feature importance analysis unveiled that pressure-related features make the most significant contributions to the formation of tree ensembles during the model training process. A parametric sensitivity analysis was conducted revealing that H2 uptake in MOFs is most sensitive to changes in adsorption enthalpy, followed by surface area and temperature, while showing lower sensitivity to variations in pressure, consistent with established literature. These results underscore the pivotal role of data enhancement methods in refining machine learning models and can be instrumental in accelerating the development and optimization of MOF materials for clean energy applications.

Accuracy of elastography versus biopsy in assessing severity of liver fibrosis in young Fontan patients.

We performed a single-centre retrospective study comparing the accuracy of non-invasive elastography with liver biopsy in accurate assessment of Fontan-associated liver disease. Fontan patients who underwent combined assessment with a percutaneous liver biopsy and non-invasive elastography between January 2015 and December 2023 at our Children's hospital were included. Liver biopsies were classified using the Congestive Hepatic Fibrosis Score as early Fontan-associated liver disease (scores 1, 2) and advanced Fontan-associated liver disease (score 3/bridging fibrosis and score 4/cirrhosis). Elastography values were categorised as advanced Fontan-associated liver disease for liver elasticity >2.1 m/s by ultrasound and liver stiffness >5 KPa on magnetic resonance elastography. We included 130 patients (116 children, 89%, mean age at biopsy: 14.6 years ± 3.6) who underwent liver biopsy at a mean duration of 11.1 years (±0.3) following Fontan surgery. Advanced Fontan-associated liver disease was noted in 41 (31.5%) patients with 13 (10%) showing frank cirrhosis. Pre-biopsy ultrasound showed advanced liver fibrosis in 18/125 (14%), with low sensitivity (23%), high specificity (90%), and low accuracy (68%, k = 0.1) in diagnosing advanced Fontan-associated liver disease. Similarly, pre-biopsy magnetic resonance elastography showed advanced fibrosis in 23/86 (27%) of patients, with low sensitivity (30%), fair specificity (75%), and low accuracy (63%, k = 0.1). Interestingly, advanced Fontan-associated liver disease was missed by ultrasound in 29% and by magnetic resonance elastography in 25% of patients. Advanced Fontan-associated liver disease was associated with lower platelet count (p = 0.02) and higher Gamma-glutamyl Transferase levels (p = 0.02). Advanced hepatic fibrosis is common among paediatric Fontan patients. Non-invasive elastography may overestimate and underestimate the degree of liver fibrosis, and therefore, liver biopsy may be required for confirming disease severity.

Discriminant analysis of ecological factors influencing sarcopenia in older people in South Korea

This study aimed to investigate the ecological system factors that influence discrimination of sarcopenia among older individuals living in contemporary society. Data analysis included information from 618 older adults individuals aged 65 years or older residing in South Korea. To assess variations in ecological system factors related to SARC-F scores, we conducted correlation analysis and t-tests. Discriminant analysis was used to identify factors contributing to group discrimination. The key findings are summarized as follows. First, significant differences at the p &amp;lt; 0.001 level were observed between the SARC-F score groups in various aspects, including attitudes toward life, wisdom in life, health management, social support, media availability, sports environment, collectivist values, and values associated with death. Further, service environment differences were significant at p &amp;lt; 0.01 level, while social belonging and social activities exhibited significance at p &amp;lt; 0.05. Second, factors influencing group discrimination based on the SARC-F scores were ranked in the following order: health management, attitudes toward life, fear of own death, wisdom in life, physical environment, sports environment, media availability, social support, fear of the own dying, collectivist values, service environment, social activities, and social belonging. Notably, the SARC-F tool, which is used for sarcopenia discrimination, primarily concentrates on physical functioning and demonstrates relatively low sensitivity. Therefore, to enhance the precision of sarcopenia discrimination within a score-based group discrimination process, it is imperative to incorporate ecological system factors that exert a significant influence. These modifications aimed to enhance the clarity and precision of the text in an academic context.

Evaluating Frequency Domain Reflectometry as a Tool for Lithium-Ion Battery Health Prognosis

Monitoring battery aging is crucial for maintaining reliability and performance. This study investigates Frequency Domain Reflectometry (FDR) as a tool for monitoring lithium-ion battery State-of-Health (SoH). While FDR has been applied in battery research, the existing literature fails to address SoH assessment and lacks studies on larger battery samples to provide more meaningful results. In this work, nineteen cells initially underwent Electrochemical Impedance Spectroscopy (EIS) to assess their degradation levels during cyclic aging. This work evaluates FDR’s effectiveness in monitoring battery health indicators, such as capacity and equivalent series resistance (ESR), by correlating these with FDR-measured impedance between 300 kHz and 1 GHz. Analytical comparison between impedance measured before and after de-embedding processes were presented. The results show FDR reactance within 300 kHz–40 MHz correlates with EIS-measured ESR, suggesting its potential as a SoH indicator. However, reduced sensitivity and accuracy, particularly after de-embedding, may limit practical applicability. Additionally, resonance-based analysis was conducted to explore the relationship between changes in circuit resonance and cell dielectric permittivity. Despite having the lowest sensitivity, the method showed that the resonance frequencies of cells remain relatively constant, mirroring behaviours associated with changes in resistive properties. Overall, this study provides insights into FDR’s potential for battery diagnostics while highlighting avenues for future research to enhance effectiveness in real-world scenarios.

Diagnosis and Management of Pediatric Neuropsychiatric Systemic Lupus Erythematosus: An Update.

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a potentially serious and life-threatening complication of SLE. The presentation and severity of neuropsychiatric involvement in SLE may show considerable variability. The disease can affect the neural tissue directly or may be associated with vascular involvement, mainly associated with anti-phospholipid (aPL) antibodies. A direct causal link with SLE may sometimes be challenging since there are many confounding factors and the symptoms may be non-specific. Despite its remarkable sensitivity in detecting hemorrhagic and ischemic stroke, transverse myelitis and ischemic infarction, magnetic resonance imaging (MRI) lacks the spatial resolution required to identify microvascular involvement. When standard MRI fails to detect a suspicious lesion, it is advisable to use advanced imaging modalities such as positron emission tomography (PET), single photon emission computed tomography (SPECT) or quantitative MRI, if available. Even with these advanced modalities, the specificity of neuroimaging in NPSLE remains inadequate (60-82% for MRI). Neuropsychiatric syndromes, such as cerebrovascular events, seizures and cognitive impairments appear to be associated with serum aPL antibodies. Some studies have shown that anti-ribosomal P antibodies have a low sensitivity for NPSLE and a limited contribution to the differentiation of different clinical entities. Treatment has two main goals: symptomatic relief and treatment of the disease itself. Commonly used immunosuppressants for NPSLE include cyclophosphamide (CYC), azathioprine (AZA), and mycophenolate mofetil (MMF). According to EULAR's current recommendation, strong immunosuppressants such as CYC and rituximab (RTX) should be preferred. Biologics have also been used in NPSLE. Fingolimod, eculizumab, and JAK inhibitors are potential drugs in the pipeline. Developing targeted therapies will be possible by a better understanding of the pathological mechanisms.

Clinical phenotypes of adults with monogenic and syndromic genetic obesity.

Considering limited evidence on diagnostics of genetic obesity in adults, we evaluated phenotypes of adults with genetic obesity. Additionally, we assessed the applicability of Endocrine Society (ES) recommendations for genetic testing in pediatric obesity. We compared clinical features, including age of onset of obesity and appetite, between adults with non-syndromic monogenic obesity (MO), adults with syndromic obesity (SO), and adults with common obesity (CO) as control patients. A total of 79 adults with genetic obesity (32 with MO, 47 with SO) were compared with 186 control patientswith CO. Median BMI was similar among the groups: 41.2, 39.5, and 38.7 kg/m2 for patients with MO, SO, and CO, respectively. Median age of onset of obesity was 3 (IQR: 1-6) years in patients with MO, 9 (IQR: 4-13) years in patients with SO, and 21 (IQR: 13-33) years in patients with CO (p < 0.001). Patients with genetic obesity more often reported increased appetite: 65.6%, 68.1%, and 33.9% in patients with MO, SO, and CO, respectively (p < 0.001). Intellectual deficit and autism spectrum disorder were more prevalent in patients with SO (53.2% and 21.3%) compared with those with MO (3.1% and 6.3%) and CO (both 0.0%). The ES recommendations were fulfilled in 56.3%, 29.8%, and 2.7% of patients with MO, SO, and CO, respectively (p < 0.001). We found distinct phenotypes in adult genetic obesity. Additionally, we demonstrated low sensitivity for detecting genetic obesity in adults using pediatric ES recommendations, necessitating specific genetic testing recommendations in adult obesity care.

An enhanced cross-sectional HIV incidence estimator that incorporates prior HIV test results.

Incidence estimation of HIV infection can be performed using recent infection testing algorithm (RITA) results from a cross-sectional sample. This allows practitioners to understand population trends in the HIV epidemic without having to perform longitudinal follow-up on a cohort of individuals. The utility of the approach is limited by its precision, driven by the (low) sensitivity of the RITA at identifying recent infection. By utilizing results of previous HIV tests that individuals may have taken, we consider an enhanced RITA with increased sensitivity (and specificity). We use it to propose an enhanced estimator for incidence estimation. We prove the theoretical properties of the enhanced estimator and illustrate its numerical performance in simulation studies. We apply the estimator to data from a cluster-randomized trial to study the effect of community-level HIV interventions on HIV incidence. We demonstrate that the enhanced estimator provides a more precise estimate of HIV incidence compared to the standard estimator.

Chest x-ray has low sensitivity to detect silicosis in artificial stone benchtop industry workers.

Chest x-ray (CXR) remains a core component of health monitoring guidelines for workers at risk of exposure to crystalline silica. There has however been a lack of evidence regarding the sensitivity of CXR to detect silicosis in artificial stone benchtop industry workers. Paired CXR and high-resolution computed tomography (HRCT) images were acquired from 110 artificial stone benchtop industry workers. Blinded to the clinical diagnosis, each CXR and HRCT was independently read by two thoracic radiologists from a panel of seven, in accordance with International Labour Office (ILO) methodology for CXR and International Classification of HRCT for Occupational and Environmental Respiratory Diseases. Accuracy of screening positive (ILO major category 1, 2 or 3) and negative (ILO major category 0) CXRs were compared with identification of radiological features of silicosis on HRCT. CXR was positive for silicosis in 27/110 (24.5%) workers and HRCT in 40/110 (36.4%). Of the 83 with a negative CXR (ILO category 0), 15 (18.1%) had silicosis on HRCT. All 11 workers with ILO category 2 or 3 CXRs had silicosis on HRCT. In 99 workers ILO category 0 or 1 CXRs, the sensitivity of screening positive CXR compared to silicosis identified by HRCT was 48% (95%CI 29-68) and specificity 97% (90-100). Compared to HRCT, sensitivity of CXR was low but specificity was high. Reliance on CXR for health monitoring would provide false reassurance for many workers, delay management and underestimate the prevalence of silicosis in the artificial stone benchtop industry.

Advanced Nanostructured All‐Waterborne Thiol‐Ene/Reduced Graphene Oxide Humidity Sensors with Outstanding Selectivity

AbstractThe current‐state of polymer‐based humidity sensors faces numerous limitations, including energy‐costly synthesis, low sensitivity, and slow response times. This study presents innovative approach to overcome these challenges, based on a robust all‐water‐borne in situ miniemulsion polymerization. The use of water throughout the entire process mitigates the negative environmental impact. Thiol‐ene polymers reinforced with reduced graphene oxide (rGO) with concentrations ranging from 0.2–1.0 wt% are selected to fabricate these chemoresistive sensors. The selected thiol‐enes present high hydrophobicity and a semicrystalline nature, suggesting resistance to early delamination even under prolonged exposure to humidity. Incorporating rGO not only imparts electrical conductivity but also enhances mechanical and water resistance of the composite films. The 0.6% rGO composite exhibits optimal resistance for humidity sensing, demonstrating rapid and consistent responses across three exposure cycles to water vapor concentrations ranging 800–5000 ppm. Moreover, the sensor exhibits remarkable selectivity toward water vapors over these of toluene, propanol, and 4‐methyl‐2‐pentanol, attributed to the high surface hydrophilicity and inherent porosity of the waterborne film, and network structuring of rGO platelets within the matrix. In summary, this study pioneers a novel approach to polymer‐based humidity sensing, addressing key limitations while offering enhanced sensitivity, rapid response times, and superior selectivity.

Exposure of cattle to tick-borne encephalitis virus in the historical endemic zone in north-eastern France

BackgroundTick-borne encephalitis (TBE) is a severe human neuroinfection caused by TBE virus (TBEV). TBEV is transmitted by tick bites and by the consumption of unpasteurized dairy products from infected asymptomatic ruminants. In France, several food-borne transmission events have been reported since 2020, raising the question of the level of exposure of domestic ungulates to TBEV. In this study, our objectives were (i) to estimate TBEV seroprevalence and quantify antibodies titres in cattle in the historical endemic area of TBEV in France using the micro virus neutralisation test (MNT) and (ii) to compare the performance of two veterinary cELISA kits with MNT for detecting anti-TBEV antibodies in cattle in various epidemiological contexts. A total of 344 cattle sera from four grid cells of 100 km² in Alsace-Lorraine (endemic region) and 84 from western France, assumed to be TBEV-free, were investigated.ResultsIn Alsace-Lorraine, cattle were exposed to the virus with an overall estimated seroprevalence of 57.6% (95% CI: 52.1–62.8%, n = 344), varying locally from 29.9% (95% CI: 21.0–40.0%) to 92.1% (95% CI: 84.5–96.8%). Seroprevalence did not increase with age, with one- to three-year-old cattle being as highly exposed as older ones, suggesting a short-life duration of antibodies. The proportion of sera with MNT titres lower than 1:40 per grid cell decreased with increased seroprevalence. Both cELISA kits showed high specificity (> 90%) and low sensitivity (less than 78.1%) compared with MNT. Sensitivity was lower for sera with neutralising antibodies titres below 1:40, suggesting that sensitivity of these tests varied with local virus circulation intensity.ConclusionsOur results highlight that cattle were highly exposed to TBEV. Screening strategy and serological tests should be carefully chosen according to the purpose of the serological study and with regard to the limitations of each method.

Progress of circulating tumor DNA methylation for gastric cancer screening and management

Circulating tumor DNA (ctDNA) is cell-free DNA released by tumors or circulating tumor cells, containing abundant tumor-specific information that can serve as biomarkers for cancer early screening, monitoring, prognosis, and prediction of treatment response. This is particularly attractive in the field of gastric cancer, where high-quality screening, monitoring, and prediction methods are currently lacking. Gastric cancer exhibits significant tumor heterogeneity, with large differences in genetic and epigenetic characteristics among different subgroups. Methylated ctDNA has high sensitivity and specificity, which can help clarify tumor genotyping and facilitate the formulation of precise diagnostic and therapeutic strategies. Furthermore, numerous studies have confirmed the unique advantages of methylated DNA in predicting treatment response, adjuvant therapy, and drug resistance assessment, which may be used in the future to enhance the efficacy of chemotherapy regimens and improve patient chemotherapeutic response, and even treat multidrug resistance. However, there are several challenges associated with methylated ctDNA, such as low sensitivity and specificity at single-target sites, limited association between some gastric cancer subtypes and ctDNA, off-target risks, and the lack of large-scale and high-quality clinical research evidence. This review mainly summarizes current research on the methylation status of ctDNA in gastric cancer and connects these findings to early screening, recurrence monitoring, and potential treatment opportunities for gastric cancer. With advances in technology and the deepening of interdisciplinary research, ctDNA detection will reveal more disease information and become an essential foundation for gastric cancer research and precision medicine treatment.

Highly sensitive extraction-free saliva-based molecular assay for rapid diagnosis of SARS-CoV-2.

Three years after the SARS-CoV-2 outbreak, there are no molecular tests that combine low-cost and straightforward sample preparation, effective sample handling, minimal reagent and disposable requirements, high sensitivity, and high throughput required for mass screening. Existing rapid molecular techniques typically sacrifice certain requirements to meet others. Yet, localized outbreaks of novel viral diseases happen daily in different parts of the world. In this context, respiratory diseases are of specific importance, as they are frequently airborne and highly contagious, with the potential for a rapid global spread. The widely accepted opinion is that another pandemic is just a question of time. To ensure that the containment efforts for the upcoming "disease X" are successful, introducing rapid, high-throughput, and highly sensitive diagnostic methods for detecting and identifying pathogens is critical. A few months into the pandemic, saliva was suggested as a diagnostic matrix for SARS-CoV-2 detection. The collection of saliva does not require swabs and is minimally invasive. In particular, extraction-free saliva-based assays require fewer reagents and disposables, and therefore are faster and cheaper, offering an appealing alternative for low-income countries. Unfortunately, current extraction-free saliva-based detection methods, such as direct RT-qPCR or isothermal amplification, have either low sensitivity or low throughput. Therefore, we believe that the presented highly sensitive ht-OMBi platform and the extraction-free saliva-based molecular assay can become an essential tool in the infectious disease monitoring toolbox.

Cross-Cultural Adaptation and Validation of the Portuguese Version of the SARC-F in Community-Dwelling Older Adults

(1) Background: The goal of this study was to analyze the reliability and validity of the Portuguese version of the SARC-F in older adults. (2) Methods: A total of 100 participants (77.1 ± 7.36 years, 73% women) were included in the study. In a first phase, the Portuguese SARC-F was adapted following the standardized forward–backward translation procedure, and internal consistency as well as inter-rater and test–retest reliability of the Portuguese SARC-F were analyzed. Secondly, clinical validation was evaluated by comparing the SARC-F total score with five operational definitions of sarcopenia and with other sarcopenia-related measurements. Discriminant validity, with respect to low muscle mass and strength and physical function were analyzed. (3) Results: The Portuguese SAR-F showed acceptable internal consistency (Cronbach α = 0.82), excellent inter-rater reliability (total score), and substantial to excellent test–retest reliability (ICC = 0.891 for the total score). Specificity ranged from 72.5% (FNIH) to 73.4 (IGWS), and negative predictive values went from 91.8% (EWGSOP1) to 97.3% (FNIH), but low sensitivity and positive predictive value were observed. The Portuguese SARC-F showed a moderate ability to discriminate people with low muscle strength (AUC = 0.78) and gait speed (AUC = 0.89). (4) Conclusions: The Portuguese SARC-F is a valid and reliable tool for ruling out sarcopenia in community-dwelling older adults and can discriminate between people with low handgrip strength and gait speed.