High biocompatible FITC-conjugated silica nanoparticles for cell labeling in both in vitro and in vivo models.

Fluorescence nanosilica-based cell tracker has been explored and applied in cell biological research. However, the aggregation of these nanoparticles at physiological pH is still the main limitation. In this research, we introduced a novel fluorescence nano-based cell tracker suitable for application in live cells. The silica-coated fluorescein isothiocyanate isomer (FITC-SiO2) nanoparticles (NPs) were modified with carboxymethylsilanetriol disodium salt (FITC-SiO2-COOH), integrating the dianion form of FITC molecules. This nanosystem exhibited superior dispersion in aqueous solutions and effectively mitigated dye leakage. These labeled NPs displayed notable biocompatibility and minimal cytotoxicity in both in vitro and in vivo conditions. Significantly, the NPs did not have negative implications on cell migration or angiogenesis. They successfully penetrated primary fibroblasts, human umbilical vein endothelial cells and HeLa cells in both 2D and 3D cultures, with the fluorescence signal enduring for over 72 h. Furthermore, the NP signals were consistently observed in the developing gastrointestinal tract of live medaka fish larvae for extended periods during phases of subdued digestive activity, without manifesting any apparent acute toxicity. These results underscore the promising utility of FITC-SiO2-COOH NPs as advanced live cell trackers in biological research.

Damage Localization and Severity Assessment of a Cable-Stayed Bridge Using a Message Passing Neural Network.

Cable-stayed bridges are damaged by multiple factors such as natural disasters, weather, and vehicle load. In particular, if the stayed cable, which is an essential and weak component of the cable-stayed bridge, is damaged, it may adversely affect the adjacent cables and worsen the bridge structure condition. Therefore, we must accurately determine the condition of the cable with a technology-based evaluation strategy. In this paper, we propose a deep learning model that allows us to locate the damaged cable and estimate its cross-sectional area. To obtain the data required for the deep learning training, we use the tension data of the reduced area cable, which are simulated in the Practical Advanced Analysis Program (PAAP), a robust structural analysis program. We represent the sensor data of the damaged cable-stayed bridge as a graph composed of vertices and edges using tension and spatial information of the sensors. We apply the sensor geometry by mapping the tension data to the graph vertices and the connection relationship between sensors to the graph edges. We employ a Graph Neural Network (GNN) to use the graph representation of the sensor data directly. GNN, which has been actively studied recently, can treat graph-structured data with the most advanced performance. We train the GNN framework, the Message Passing Neural Network (MPNN), to perform two tasks to identify damaged cables and estimate the cable areas. We adopt a multi-task learning method for more efficient optimization. We show that the proposed technique achieves high performance with the cable-stayed bridge data generated from PAAP.

Synthesis of ZnO/Au Nanorods for Self Cleaning Applications.

Zinc oxide (ZnO) is a well-known semiconductor with valuable characteristics: wide direct band gap of ˜3.3 eV, large exciton binding energy of 60 meV at room temperature, high efficient photocatalyst, etc. which have been applied in many fields such as optical devices (LEDs, laser), solar cells and sensors. Besides, various low dimensional structures of ZnO in terms of nanoparticles, nanorods, nanoneedles, nanotetrapods find applications in technology and life. This material is also appealing due to the diversity of available processing methods including both chemical and physical approaches such as: hydrothermal, sol-gel, chemical vapor deposition and sputtering. In this report, ZnO nanorods are prepared by hydrothermal method assisted with galvanic-cell effect. The effect of counter electrode materials on the morphology and structure of obtained product was studied. Scanning electron microscopy (SEM) images of the product showed that counter electrodes made of aluminum offers nanorods of higher quality than other materials in terms of uniform size, high density and good preferred orientation. The as-prepared nanorods were then sputtered with gold (Au). ZnO/Au nanostructures show excellent photocatalyst activities which were demonstrated by complete photodegradation of methylene blue (Mb) under UV irradiation and high decomposition rate k of 0.011 min-1.

Multi-Sensor Data Fusion in A Real-Time Support System for On-Duty Firefighters.

While working on fire ground, firefighters risk their well-being in a state where any incident might cause not only injuries, but also fatality. They may be incapacitated by unpredicted falls due to floor cracks, holes, structure failure, gas explosion, exposure to toxic gases, or being stuck in narrow path, etc. Having acknowledged this need, in this study, we focus on developing an efficient portable system to detect firefighter's falls, loss of physical performance, and alert high CO level by using a microcontroller carried by a firefighter with data fusion from a 3-DOF (degrees of freedom) accelerometer, 3-DOF gyroscope, 3-DOF magnetometer, barometer, and a MQ7 sensor using our proposed fall detection, loss of physical performance detection, and CO monitoring algorithms. By the combination of five sensors and highly efficient data fusion algorithms to observe the fall event, loss of physical performance, and detect high CO level, we can distinguish among falling, loss of physical performance, and the other on-duty activities (ODAs) such as standing, walking, running, jogging, crawling, climbing up/down stairs, and moving up/down in elevators. Signals from these sensors are sent to the microcontroller to detect fall, loss of physical performance, and alert high CO level. The proposed algorithms can achieve 100% of accuracy, specificity, and sensitivity in our experimental datasets and 97.96%, 100%, and 95.89% in public datasets in distinguishing between falls and ODAs activities, respectively. Furthermore, the proposed algorithm perfectly distinguishes between loss of physical performance and up/down movement in the elevator based on barometric data fusion. If a firefighter is unconscious following the fall or loss of physical performance, an alert message will be sent to their incident commander (IC) via the nRF224L01 module.

Successful Clipping of a Giant Anterior Inferior Cerebellar Artery Aneurysm with Combined Transpetrosal Approach.

BACKGROUND: The anterior inferior cerebellar artery (AICA) aneurysms are rare lesions whose treatment can be challenging. There are only a few previous reports of surgical treatment for such lesions. OBJECTIVES: We present a case of a basilar-AICA aneurysm undergoing surgery with the combined transpetrosal approach. CASE DESCRIPTION: A 58-year-old female patient presented clinical signs including headache, diplopia, and right hemiparesis. The radiological imaging showed a basilar-AICA aneurysm measuring 25 × 19 mm. The patient was operated via left combined transpetrosal approach. The outcome was graded mRankin 1. Follow-up computerized tomographic angiography showed no aneurysmal residual and total preservation of basilar artery. DISCUSSIONS: Surgical indication's purposes were aneurysmal elimination and reduction of mass effect. Combined transpetrosal approach: proximal segment control and enough space for clipping manipulation. Clipping techniques: Temporary clip for aneurysmal collapsing, "orienting clip". CONCLUSION: Giant basilar-AICA aneurysm is very rare lesion. Combined transpetrosal approach is appropriate for surgical clipping. Good surgical outcome is achieved with complete elimination of aneurysm.

Lactate Metabolism Is Strongly Modulated by Fecal Inoculum, pH, and Retention Time in PolyFermS Continuous Colonic Fermentation Models Mimicking Young Infant Proximal Colon.

The metabolism of lactate impacts infant gut health and may lead to acute accumulation of lactate and/or H2 associated with pain and crying of colicky infants. Because gut microbiota studies are limited due to ethical and safety concerns, in vitro fermentation models were developed as powerful tools to assess effects of environmental conditions on the gut microbiota. In this study, we established a continuous colonic fermentation model (PolyFermS), inoculated with immobilized fecal microbiota and mimicking the proximal colon of 2-month-old infants. We investigated the effects of pH and retention time (RT) on lactate metabolism and of lactate-utilizing bacteria (LUB) exhibiting little or no H2 production. We observed that a drop in pH from 6.0 to 5.0 increased the number of lactate-producing bacteria (LPB) and decreased LUB concomitantly with lactate accumulation. Increasing RT from 5 to 10 h at pH 5.0 resulted in complete lactate consumption associated with increased LUB. Supplementation with dl-lactate (60 mM) to mimic lactate accumulation promoted propionate and butyrate production with no effect on acetate production. We further demonstrated that lactate-utilizing Propionibacterium avidum was able to colonize the reactors 4 days after spiking, suggesting its ability to compete with other lactate-utilizing bacteria producing H2 In conclusion, we showed that PolyFermS is a suitable model for mimicking young infant colonic microbiota. We report for the first time pH and RT as strong drivers for composition and metabolic activity of infant gut microbiota, especially for the metabolism of lactate, which is a key intermediate product for ecology and infant health.IMPORTANCE The metabolism of lactate is important for infant gut health and may lead to acute lactate and/or H2 accumulation, pain, and crying as observed in colicky infants. Functional human studies often faced ethical challenges due to invasive medical procedures; thus, in this study, we implemented PolyFermS fermentation models to mimic the infant proximal colon, which were inoculated with immobilized fecal microbiota of two 2-month-old infants. We investigated the impact of pH, retention time, and accumulation of dl-lactate on microbiota composition and metabolic activity. We found that a drop in pH from 6.0 to 5.0 led to increased LPB and decreased LUB concomitantly with lactate accumulation. Increasing the RT resulted in complete lactate consumption associated with increased LUB. Our data highlight for the first time the impact of key abiotic factors on the metabolism of lactate, which is an important intermediate product for ecology and infant health.

Highly Accurate Step Counting at Various Walking States Using Low-Cost Inertial Measurement Unit Support Indoor Positioning System.

Accurate step counting is essential for indoor positioning, health monitoring systems, and other indoor positioning services. There are several publications and commercial applications in step counting. Nevertheless, over-counting, under-counting, and false walking problems are still encountered in these methods. In this paper, we propose to develop a highly accurate step counting method to solve these limitations by proposing four features: Minimal peak distance, minimal peak prominence, dynamic thresholding, and vibration elimination, and these features are adaptive with the user's states. Our proposed features are combined with periodicity and similarity features to solve false walking problem. The proposed method shows a significant improvement of 99.42% and 96.47% of the average of accuracy in free walking and false walking problems, respectively, on our datasets. Furthermore, our proposed method also achieves the average accuracy of 97.04% on public datasets and better accuracy in comparison with three commercial step counting applications: Pedometer and Weight Loss Coach installed on Lenovo P780, Health apps in iPhone 5s (iOS 10.3.3), and S-health in Samsung Galaxy S5 (Android 6.01).

Trophic Interactions of Infant Bifidobacteria and Eubacterium hallii during L-Fucose and Fucosyllactose Degradation.

Fucosyllactoses (2'- or 3'-FL) account for up to 20% of human milk oligosaccharides (HMOs). Infant bifidobacteria, such as Bifidobacterium longum subsp. infantis, utilize the lactose moiety to form lactate and acetate, and metabolize L-fucose to 1,2-propanediol (1,2-PD). Eubacterium hallii is a common member of the adult gut microbiota that can produce butyrate from lactate and acetate, and convert 1,2-PD to propionate. Recently, a Swiss cohort study identified E. hallii as one of the first butyrate producers in the infant gut. However, the global prevalence of E. hallii and its role in utilization of HMO degradation intermediates remains unexplored. Fecal 16S rRNA gene libraries (n = 857) of humans of all age groups from Venezuela, Malawi, Switzerland, and the USA were screened for the occurrence of E. hallii. Single and co-culture experiments of B. longum subsp. infantis and E. hallii were conducted in modified YCFA containing acetate and glucose, L-fucose, or FL. Bifidobacterium spp. (n = 56) of different origin were screened for the ability to metabolize L-fucose. Relative abundance of E. hallii was low (10-5-10-3%) during the first months but increased and reached adult levels (0.01-10%) at 5-10 years of age in all four populations. In single culture, B. longum subsp. infantis grew in the presence of all three carbohydrates while E. hallii was metabolically active only with glucose. In co-culture E. hallii also grew with L-fucose or FL. In co-cultures grown with glucose, acetate, and glucose were consumed and nearly equimolar proportions of formate and butyrate were formed. B. longum subsp. infantis used L-fucose and produced 1,2-PD, acetate and formate in a ratio of 1:1:1, while 1,2-PD was used by E. hallii to form propionate. E. hallii consumed acetate, lactate and 1,2-PD released by B. longum subsp. infantis from FL, and produced butyrate, propionate, and formate. Beside B. longum subsp. infantis, Bifidobacterium breve, and a strain of B. longum subsp. suis were able to utilize L-fucose. This study identified a trophic interaction of infant bifidobacteria and E. hallii during L-fucose degradation, and pointed at E. hallii as a metabolically versatile species that occurs in infants and utilizes intermediates of bifidobacterial HMO fermentation.

Iron Modulates Butyrate Production by a Child Gut Microbiota In Vitro.

UNLABELLED: The aim of this study was to investigate the effect of iron (Fe) availability on butyrate production in the complex bacterial ecosystem of the human gut. Hence, different Fe availabilities were mimicked in an in vitro colonic fermentation model (the polyfermenter intestinal model called PolyFermS) inoculated with immobilized gut microbiota from a child and in batch cultures of the butyrate producer Roseburia intestinalis. Shifts in the microbial community (16S rRNA sequencing and quantitative PCR), metabolic activity (high-performance liquid chromatography), and expression of genes involved in butyrate production were assessed. In the PolyFermS, moderate Fe deficiency resulted in a 1.4-fold increase in butyrate production and a 5-fold increase in butyryl-coenzyme A (CoA):acetate CoA-transferase gene expression, while very strong Fe deficiency significantly decreased butyrate concentrations and butyrate-producing bacteria compared with the results under normal Fe conditions. Batch cultures of R. intestinalis grown in a low-Fe environment preferentially produced lactate and had reduced butyrate and hydrogen production, in parallel with upregulation of the lactate dehydrogenase gene and downregulation of the pyruvate:ferredoxin-oxidoreductase gene. In contrast, under high-Fe conditions, R. intestinalis cultures showed enhanced butyrate and hydrogen production, along with increased expression of the corresponding genes, compared with the results under normal-Fe conditions. Our data reveal the strong regulatory effect of Fe on gut microbiota butyrate producers and on the concentrations of butyrate, which contributes to the maintenance of host gut health. IMPORTANCE: Fe deficiency is one of the most common nutritional deficiencies worldwide and can be corrected by Fe supplementation. In this in vitro study, we show that environmental Fe concentrations in a continuous gut fermentation model closely mimicking a child's gut microbiota strongly affect the composition of the gut microbiome and its metabolic activity, particularly butyrate production. The differential expression of genes involved in the butyrate production pathway under different Fe conditions and the enzyme cofactor role of Fe explain the observed modulation of butyrate production. Our data reveal that the level of dietary Fe reaching the colon affects the microbiome, and its essential function of providing the host with beneficial butyrate.