Resistive gas sensors for the detection of NH3 gas based on 2D WS2, WSe2, MoS2, and MoSe2: A review.

Transition metal dichalcogenides (TMDs) with a two-dimensional (2D) structure and semiconducting features are highly favorable for the production of NH3 gas sensors. Among the TMD family, WS2, WSe2, MoS2, and MoSe2 exhibit high conductivity and a high surface area, along with high availability, reasons for which they are favored in gas-sensing studies. In this review, we have discussed the structure, synthesis, and NH3 sensing characteristics of pristine, decorated, doped, and composite-based WS2, WSe2, MoS2, and MoSe2 gas sensors. Both experimental and theoretical studies are considered. Furthermore, both room temperature and higher temperature gas sensors are discussed. We also emphasized the gas-sensing mechanism. Thus, this review provides a reference for researchers working in the field of 2D TMD gas sensors.

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers.

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues.

Deep Learning Analysis with Gray Scale and Doppler Ultrasonography Images to Differentiate Graves' Disease.

CONTEXT: Thyrotoxicosis requires accurate and expeditious differentiation between Graves' disease (GD) and thyroiditis to ensure effective treatment decisions. OBJECTIVE: This study aimed to develop a machine learning algorithm using ultrasonography and Doppler images to differentiate thyrotoxicosis subtypes, with a focus on GD. METHODS: This study included patients who initially presented with thyrotoxicosis and underwent thyroid ultrasonography at a single tertiary hospital. A total of 7,719 ultrasonography images from 351 patients with GD and 2,980 images from 136 patients with thyroiditis were used. Data augmentation techniques were applied to enhance the algorithm's performance. Two deep learning models, Xception and EfficientNetB0_2, were employed. Performance metrics such as accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score were calculated for both models. Image pre-processing, neural network model generation, and neural network training results verification were performed using DEEP:PHI® platform. RESULTS: The Xception model achieved 84.94% accuracy, 89.26% sensitivity, 73.17% specificity, 90.06% PPV, 71.43% NPV, and an F1 score of 89.66 for the diagnosis of GD. The EfficientNetB0_2 model exhibited 85.31% accuracy, 90.28% sensitivity, 71.78% specificity, 89.71% PPV, 73.05% NPV, and an F1 score of 89.99. CONCLUSION: Machine learning models based on ultrasound and Doppler images showed promising results with high accuracy and sensitivity in differentiating GD from thyroiditis.

Effects of bilateral tDCS over DLPFC on response inhibition, craving, and brain functional connectivity in Internet gaming disorder: A randomized, double-blind, sham-controlled trial with fMRI.

Background and aims: Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables. Methods: Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group. Results: A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT. Discussion and conclusion: Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

Soft Sensors and Actuators for Wearable Human-Machine Interfaces.

Haptic human-machine interfaces (HHMIs) combine tactile sensation and haptic feedback to allow humans to interact closely with machines and robots, providing immersive experiences and convenient lifestyles. Significant progress has been made in developing wearable sensors that accurately detect physical and electrophysiological stimuli with improved softness, functionality, reliability, and selectivity. In addition, soft actuating systems have been developed to provide high-quality haptic feedback by precisely controlling force, displacement, frequency, and spatial resolution. In this Review, we discuss the latest technological advances of soft sensors and actuators for the demonstration of wearable HHMIs. We particularly focus on highlighting material and structural approaches that enable desired sensing and feedback properties necessary for effective wearable HHMIs. Furthermore, promising practical applications of current HHMI technology in various areas such as the metaverse, robotics, and user-interactive devices are discussed in detail. Finally, this Review further concludes by discussing the outlook for next-generation HHMI technology.

Comprehensive evaluation of magnetic resonance imaging sequences for signal intensity based assessment of anterior cruciate ligament healing following surgical treatment.

Normalized signal intensity (SI) obtained from magnetic resonance imaging (MRI) has been used to track anterior cruciate ligament (ACL) postoperative remodeling. We aimed to assess the effect of MRI sequence (PD: proton density-weighted; T2: T2-weighted; CISS: constructive interference in steady state) on postoperative changes in healing ACLs/grafts. We hypothesized that CISS is better at detecting longitudinal SI and texture changes of the healing ACL/graft compared to the common clinical sequences (PD and T2). MR images of patients who underwent ACL surgery were evaluated and separated into groups based on surgical procedure (Bridge-Enhanced ACL Repair (BEAR; n = 50) versus ACL reconstruction (ACLR; n = 24)). CISS images showed decreasing SI across all timepoints in both the BEAR and ACLR groups (p < 0.01), PD and T2 images showed decreasing SI in the 6-to-12- and 12-to-24-month postoperative timeframes in the BEAR group (p < 0.02), and PD images additionally showed decreasing SI between 6- and 24-months postoperation in the ACLR group (p = 0.02). CISS images showed texture changes in both the BEAR and ACLR groups, showing increases in energy and decreases in entropy in the 6-to-12- and 6-to-24-month postoperative timeframes in the BEAR group (p < $\lt $ 0.04), and increases in energy, decreases in entropy, and increases in homogeneity between 6 and 24 months postoperation in the ACLR group (p < 0.04). PD images showed increases in energy and decreases in entropy between 6- and 24-months postoperation in the ACLR group (p < 0.008). Finally, CISS was estimated to require a smaller sample size than PD and T2 to detect SI differences related to postoperative remodeling.

Deep learning-based, fully automated, pediatric brain segmentation.

The purpose of this study was to demonstrate the performance of a fully automated, deep learning-based brain segmentation (DLS) method in healthy controls and in patients with neurodevelopmental disorders, SCN1A mutation, under eleven. The whole, cortical, and subcortical volumes of previously enrolled 21 participants, under 11 years of age, with a SCN1A mutation, and 42 healthy controls, were obtained using a DLS method, and compared to volumes measured by Freesurfer with manual correction. Additionally, the volumes which were calculated with the DLS method between the patients and the control group. The volumes of total brain gray and white matter using DLS method were consistent with that volume which were measured by Freesurfer with manual correction in healthy controls. Among 68 cortical parcellated volume analysis, the volumes of only 7 areas measured by DLS methods were significantly different from that measured by Freesurfer with manual correction, and the differences decreased with increasing age in the subgroup analysis. The subcortical volume measured by the DLS method was relatively smaller than that of the Freesurfer volume analysis. Further, the DLS method could perfectly detect the reduced volume identified by the Freesurfer software and manual correction in patients with SCN1A mutations, compared with healthy controls. In a pediatric population, this new, fully automated DLS method is compatible with the classic, volumetric analysis with Freesurfer software and manual correction, and it can also well detect brain morphological changes in children with a neurodevelopmental disorder.

Transcriptional regulation of genetic variants in the SLC40A1 promoter.

Solute carrier 40A1 (SLC40A1) encodes ferroportin, which is the only known transmembrane protein that exports elemental iron from mammalian cells and is essential for iron homeostasis. Mutations in SLC40A1 are associated with iron-overload disorders. In addition to ferroportin diseases, SLC40A1 expression is downregulated in various cancer types. Despite the clinical significance of the SLC40A1 transporter, only a few studies have investigated genetic variants in SLC40A1. The present study was performed to identify genetic variations in the SLC40A1 promoter and functionally characterize each variant using in vitro assays. We investigated four haplotypes and five variants in the SLC40A1 promoter. We observed that haplotype 3 (H3) had significantly lower promoter activity than H1, whereas the activity of H4 was significantly higher than that of H1. Luciferase activity of H2 was comparable to that of H1. In addition, four variants of SLC40A1, c.-1355G>C, c.-662C>T, c.-98G>C, and c.-8C>G, showed significantly increased luciferase activity compared to the wild type (WT), whereas c.-750G>A showed significantly decreased luciferase activity compared to the WT. Three transcription factors, cAMP response element-binding protein-1 (CREB-1), chicken ovalbumin upstream promoter transcription factor 1, and hepatic leukemia factor (HLF), were predicted to bind to the promoter regions of SLC40A1 near c.-662C>T, c.-98G>C, and c.-8C>G, respectively. Among these, CREB-1 and HLF bound more strongly to the variant sequences than to the WT and functioned as activators of SLC40A1 transcription. Collectively, our findings indicate that the two SLC40A1 promoter haplotypes affect SLC40A1 transcription, which is regulated by CREB-1 and HLF.

The effect of genetic variants of SLC22A18 on proliferation, migration, and invasion of colon cancer cells.

Solute carrier family (SLC) transporters are expressed in the digestive system and play important roles in maintaining physiological functions in the body. In addition, SLC transporters act as oncoproteins or tumor-suppressor proteins during the development, progression, and metastasis of various digestive system cancers. SLC22A18, a member of the SLC22 gene family, is an orphan transporter with an unknown endogenous substrate. Previous study revealed that SLC22A18 is downregulated in colorectal cancer tissues and that it acts as a suppressor in colorectal cancer, although the effects of SLC22A18 variants on colon cancer cell proliferation, migration, and invasion are unknown. Therefore, in this study, we identified SLC22A18 variants found in multiple populations by searching public databases and determined the in vitro effects of these missense variations on transporter expression and cancer progression. Our results indicated that three missense SLC22A18 variants-p.Ala6Thr, p.Arg12Gln, and p.Arg86His-had significantly lower cell expression than the wild type, possibly owing to intracellular degradation. Furthermore, these three variants caused significantly higher proliferation, migration, and invasion of colon cancer cells than the wild type. Our findings suggest that missense variants of SLC22A18 can potentially serve as biomarkers or prognostic tools that enable clinicians to predict colorectal cancer progression.

Metabolic Syndrome, Modifiable Lifestyle Factors, and Sleep-Disordered Breathing: The Hispanic Community Health Study.

BACKGROUND: US Hispanics/Latinos are disproportionately susceptible to metabolic syndrome (MetS), attributed in part to systemic inequities related to health and lifestyle factors such as low physical activity (PA) levels, diet quality, alcohol use, tobacco use, and sleep disorder. Gender and heritage group differences are vastly understudied and need to be examined in this heterogeneous population. PURPOSE: To examine the relationships between select health and lifestyle factors and MetS among Hispanic gender and heritage subgroups (Hypothesis 1) and determine whether gender and heritage moderate those relationships (Hypothesis 2). METHODS: Participants included 14,155 Hispanic Americans aged 18-76 (59% female, mean age 45.92 ± 13.97) from seven heritage subgroups. This secondary analysis of cross-sectional data from the observational Hispanic Community Health Study/Study of Latinos (HCHS/SOL) dataset used hierarchical multinomial logistic regression to test Hypothesis 1; the dependent variable, MetS, included three categories delineating absence of MetS and presence of MetS with or without related medication use. Hayes' PROCESS macro tested Hypothesis 2. RESULTS: Low PA and sleep-disordered breathing (SDB) each had significant (p < .001) predictive value of MetS group membership, whereas both low and high alcohol use (p < .001) were associated with decreased MetS risk. Cigarette pack-years were not significantly associated with MetS outcomes. Gender moderated the association between MetS and alcohol use (p < .001), cigarette pack-years (p < .001), and SDB (p < .001) such that the effects on MetS were higher in females than males. The association between MetS and diet quality (p < .001) was stronger among males than in females. CONCLUSIONS: Gender and heritage differences were prominent among study variables.

3'-Sialyllactose alleviates bone loss by regulating bone homeostasis.

Osteoporosis is a common skeletal disease that results in an increased risk of fractures. However, there is no definitive cure, warranting the development of potential therapeutic agents. 3'-Sialyllactose (3'-SL) in human milk regulates many biological functions. However, its effect on bone metabolism remains unknown. This study aimed to investigate the molecular mechanisms underlying the effect of 3'-SL on bone homeostasis. Treatment of human bone marrow stromal cells (hBMSCs) with 3'-SL enhanced osteogenic differentiation and inhibited adipogenic differentiation of hBMSCs. RNA sequencing showed that 3'-SL enhanced laminin subunit gamma-2 expression and promoted osteogenic differentiation via the phosphatidylinositol 3­kinase/protein kinase B signaling pathway. Furthermore, 3'-SL inhibited the receptor activator of nuclear factor κB ligand-induced osteoclast differentiation of bone marrow-derived macrophages through the nuclear factor κB and mitogen­activated protein kinase signaling pathway, ameliorated osteoporosis in ovariectomized mice, and positively regulated bone remodeling. Our findings suggest 3'-SL as a potential drug for osteoporosis.

Weight change in patients with new-onset type 2 diabetes mellitus and its association with remission: Comprehensive real-world data.

AIMS: We aimed to investigate weight change in patients with new-onset type 2 diabetes mellitus and the association of weight loss on diabetes remission in Korean adults. MATERIALS AND METHODS: We used the health examination database of the Korean National Health Insurance Service. Patients diagnosed with type 2 diabetes mellitus from 2009 to 2012 were enrolled and followed to 2017. The baseline body weight was measured at the health examination closest to the time the patient was enrolled, and the change was calculated by examining the weight measured at the subsequent examination within 2 years. Remission was defined as fasting blood glucose less than 126 mg/dl at two or more consecutive health examinations after stopping medication. RESULTS: In total, 114, 874 patients with new-onset type 2 diabetes mellitus were analysed. Of these, 23 156 (20.2%) lost more than 5% of their body weight, and 2429 (2.1%) achieved remission. The adjusted odds ratio for remission in the weight loss group was 2.56 (95% confidence interval 2.35-2.79) compared with the group with stable body weight. Sensitivity analysis according to the degree of weight change showed that the greater weight loss, the higher the likelihood of remission. In the subgroup analysis, the effects of weight loss on remission were significantly greater in subgroups of age <65 years, male sex and body mass index >25. CONCLUSION: Weight loss within the first 2 years of treating type 2 diabetes mellitus was associated with diabetes remission. Physicians should pay more attention to weight management in new-onset type 2 diabetes mellitus, particularly for young and obese individuals.

Colorimetric Detection of HER2-Overexpressing-Cancer-Derived Exosomes in Mouse Urine Using Magnetic-Polydiacetylene Nanoparticles.

Breast cancer (BC) is a major global health problem, with ≈20-25% of patients overexpressing human epidermal growth factor receptor 2 (HER2), an aggressive marker, yet access to early detection and treatment varies across countries. A low-cost, equipment-free, and easy-to-use polydiacetylene (PDA)-based colorimetric sensor is developed for HER2-overexpressing cancer detection, designed for use in low- and middle-income countries (LMICs). PDA nanoparticles are first prepared through thin-film hydration. Subsequently, hydrophilic magnetic nanoparticles and HER2 antibodies are sequentially conjugated to them. The synthesized HER2-MPDA can be concentrated and separated by a magnetic field while inheriting the optical characteristics of PDA. The specific binding of HER2 antibody in HER2-MPDA to HER2 receptor in HER2-overexpressing exosomes causes a blue-to-red color change by altering the molecular structure of the PDA backbone. This colorimetric sensor can simultaneously separate and detect HER2-overexpressing exosomes. HER2-MPDA can detect HER2-overexpressing exosomes in the culture medium of HER2-overexpressing BC cells and in mouse urine samples from a HER2-overexpressing BC mouse model. It can selectively isolate and detect only HER2-overexpressing exosomes through magnetic separation, and its detection limit is found to be 8.5 × 108 particles mL-1. This colorimetric sensor can be used for point-of-care diagnosis of HER2-overexpressing BC in LMICs.

Label-Free and Colorimetric Detection of Influenza A Virus via Receptor-Mediated Viral Fusion with Plasmonic Vesicles.

The rapid transmission and numerous re-emerging human influenza virus variants that spread via the respiratory system have led to severe global damage, emphasizing the need for detection tools that can recognize active and intact virions with infectivity. Here, this work presents a plasmonic vesicle-mediated fusogenic immunoassay (PVFIA) comprising gold nanoparticle (GNP) encapsulating fusogenic polymeric vesicles (plasmonic vesicles; PVs) for the label-free and colorimetric detection of influenza A virus (IAV). The PVFIA combines two sequential assays: a biochip-based immunoassay for target-specific capture and a PV-induced fusion assay for color change upon the IAV-PV fusion complex formation. The PVFIA demonstrates excellent specificity in capturing the target IAV, while the fusion conditions and GNP induce a significant color change, enabling visual detection. The integration of two consecutive assays results in a low detection limit (100.7919 EID50 mL-1 ) and good reliability (0.9901), indicating sensitivity that is 104.208 times higher than conventional immunoassay. Leveraging the PV viral membrane fusion activity renders the PVFIA promising for point-of-care diagnostics through colorimetric detection. The innovative approach addresses the critical need for detecting active and intact virions with infectivity, providing a valuable tool with which to combat the spread of the virus.

Corrigendum: Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg.

[This corrects the article DOI: 10.3389/fneur.2023.1221892.].

Association between Smoking Status and the Risk of Hip Fracture in Patients with Type 2 Diabetes: A Nationwide Population-Based Study.

BACKGRUOUND: Limited longitudinal evidence exists regarding the potential association between smoking status and hip fracture among individuals with type 2 diabetes. We investigated this association using large-scale, nationwide cohort data for the Korean population. METHODS: This nationwide cohort study included 1,414,635 adults aged 40 and older who received Korean National Health Insurance Service health examinations between 2009 and 2012. Subjects with type 2 diabetes were categorized according to their smoking status, amount smoked (pack-years), number of cigarettes smoked per day, and duration of smoking. The results are presented as hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between smoking status parameters and risk of hip fracture in multivariable Cox proportional hazard regression analysis. RESULTS: Compared with never-smokers, an increased adjusted HR (aHR) for hip fracture was observed in current smokers (1.681; 95% CI, 1.578 to 1.791), and a comparable aHR for hip fracture was found in former smokers (1.065; 95% CI, 0.999 to 1.136). For former smokers who had smoked 20 pack-years or more, the risk was slightly higher than that for never-smokers (aHR, 1.107; 95% CI, 1.024 to 1.196). The hip fracture risk of female former smokers was similar to that of female current smokers, but the hip fracture risk in male former smokers was similar to that of male never-smokers. CONCLUSION: Smoking is associated with an increased risk of hip fracture in patients with type 2 diabetes. Current smokers with diabetes should be encouraged to quit smoking because the risk of hip fracture is greatly reduced in former smokers.

Correction: Heated tobacco product use and its relationship to quitting combustible cigarettes in Korean adults.

[This corrects the article DOI: 10.1371/journal.pone.0251243.].

Effect of Denosumab on Bone Density in Postmenopausal Osteoporosis: A Comparison with and without Calcium Supplementation in Patients on Standard Diets in Korea.

The side effects and safety issues tied to calcium supplementation raise questions about its necessity in osteoporosis treatment. We retrospectively evaluated 189 postmenopausal osteoporosis patients treated with denosumab for 12 months. Patients exhibited neither renal dysfunction nor compromised general dietary intake. Patients were divided into three groups as follows: group A, weekly vitamin D 7000 IU; group B, daily vitamin D 1000 IU with elemental calcium 100 mg; and group C, daily vitamin D 1000 IU with elemental calcium 500 mg. All groups showed significant increases in bone density: +6.4 ± 4.7% for the lumbar spine, +2.2 ± 3.5% for the femoral neck, and +2.4 ± 3.8% for the total hip in group A; +7.0 ± 10.9% for the lumbar spine, +2.3 ± 5.2% for the femoral neck, and +2.4 ± 3.8% for the total hip in group B; and + 6.7 ± 8.7% for the lumbar spine, +2.5 ± 8.4% for the femoral neck, and +2.3 ± 4.0% for the total hip in group C. Serum calcium levels increased over time in all three groups with no significant difference. Changes in CTX and P1NP levels did not differ between the groups (all p > 0.05). With regular dietary intake, calcium supplementation levels showed no significant effect on bone density, bone marker changes, or hypocalcemia incidence during denosumab treatment.

Room Temperature Chemiresistive Gas Sensors Based on 2D MXenes.

Owing to their large surface area, two-dimensional (2D) semiconducting nanomaterials have been extensively studied for gas-sensing applications in recent years. In particular, the possibility of operating at room temperature (RT) is desirable for 2D gas sensors because it significantly reduces the power consumption of the sensing device. Furthermore, RT gas sensors are among the first choices for the development of flexible and wearable devices. In this review, we focus on the 2D MXenes used for the realization of RT gas sensors. Hence, pristine, doped, decorated, and composites of MXenes with other semiconductors for gas sensing are discussed. Two-dimensional MXene nanomaterials are discussed, with greater emphasis on the sensing mechanism. MXenes with the ability to work at RT have great potential for practical applications such as flexible and/or wearable gas sensors.