Effects of Prophylactic Antibiotics on Intestinal Microflora Diversity in Preterm Infants: A Meta-analysis.

Objective: This meta-analysis aims to investigate the effects of prenatal prophylactic antibiotics on the diversity of intestinal flora in premature infants, with a focus on elucidating the rationale behind this investigation and the potential impact of altered intestinal flora on the health of preterm infants, such as increased susceptibility to infections, impaired nutrient absorption, and compromised immune function. Methods: Relevant literature consistent with the effects of prenatal prophylactic antibiotics on intestinal flora diversity in preterm infants was systematically searched and screened from both domestic and foreign databases, including Wanfang Medical Center, CNKNET, VIpp, and PubMed. Meta-analysis was performed using RevMan 5.2 software. Inclusion criteria for the study were: (1) comparison of prophylactic antibiotic use versus non-use, (2) no restrictions on subjects' characteristics, (3) follow-up loss < 20%, (4) institutional approval, (5) publication within the time frame from January 2017 to December 2022, (6) minimal missing data or suppliable by author contact, and (7) no major errors in sequencing or detection. Outcome measures included intestinal flora composition, phylum flora content, abundance index, and Shannon index, comparing antibiotic-treated and non-treated groups. RevMan 5.2 software was used for statistical analysis. Counting data was expressed as risk ratio (RR), and weighted mean difference (WMD) or standard mean difference (SMD) was selected as analysis statistics. Results: The study encompassed five Chinese literature sources, with one deemed low quality and four high quality. No significant publication bias was observed. Among the included studies, a significant reduction in the intestinal flora abundance index ACE was noted in the treated group compared to the non-treated group (RR: -8.10, 95% CI: -8.81 to -7.40, P < .00001). ACE estimates species richness in a microbial community by considering both abundant and rare species. Higher ACE values indicate greater diversity. Similarly, the Shannon diversity index was lower in the medication group compared to the non-medication group (RR: 0.73, 95% CI: 0.64 to 0.82, P < .00001). Shannon Diversity Index measures species diversity and evenness within a community. Higher values indicate higher diversity, considering both the number of species and their relative abundance. Analysis of Firmicutes content revealed a higher level in the treated group (RR: -6.44, 95% CI: -7.26 to -5.63, P < .00001). Additionally, lower Proteus (RR: 10.96, 95% CI: 9.47 to 12.45, P < .00001) and Klebsiella (RR: 15.96, 95% CI: 15.31 to 16.62, P < .00001) content was observed in the treated group. Conversely, Enterococcus content was higher in the treated group (RR: 2.18, 95% CI: 1.84 to 2.52, P < .00001), along with a higher proportion of Enterococcus (RR: 0.45, 95% CI: 0.27 to 0.76, P = .003). These findings collectively suggest that prophylactic antibiotic use in preterm infants significantly alters the composition of intestinal flora. Conclusion: Our findings suggest that prophylactic antibiotic use in preterm infants leads to a notable reduction in intestinal flora diversity, potentially impacting their health outcomes. Decreased microbial diversity has been linked to gastrointestinal issues, infections, and weakened immune function. These results highlight the importance of cautious antibiotic use in this vulnerable population and the need for further research to better understand and mitigate the potential health implications.

Effect of Chemical Composition on the Thermoplastic Formability and Nanoindentation of Ti-Based Bulk Metallic Glasses.

A series of Ti41Zr25Be34-xNix (x = 4, 6, 8, 10 at.%) and Ti41Zr25Be34-xCux (x = 4, 6, 8 at.%) bulk metallic glasses were investigated to examine the influence of Ni and Cu content on the viscosity, thermoplastic formability, and nanoindentation of Ti-based bulk metallic glasses. The results demonstrate that Ti41Zr25Be30Ni4 and Ti41Zr25Be26Cu8 amorphous alloys have superior thermoplastic formability among the Ti41Zr25Be34-xNix and Ti41Zr25Be34-xCux amorphous alloys due to their low viscosity in the supercooled liquid region and wider supercooled liquid region. The hardness and modulus exhibit obvious variations with increasing Ni and Cu content in Ti-based bulk metallic glasses, which can be attributed to alterations in atomic density. Optimal amounts of Ni and Cu in Ti-based bulk metallic glasses enhance thermoplastic formability and mechanical properties. The influence of Ni and Cu content on the hardness of Ti-based bulk metallic glasses is discussed from the perspective of the mean atomic distance.

Comparison of Cold-Sprayed Coatings of Copper-Based Composite Deposited on AZ31B Magnesium Alloy and 6061 T6 Aluminum Alloy Substrates.

Copper-coated graphite and copper mixture powders were deposited on AZ31B magnesium alloy and 6061 T6 aluminum alloy substrates under different process parameters by a solid-state cold spray technique. The microstructure of the copper-coated graphite and copper composite coatings was visually examined using photographs taken with an optical microscope and a scanning electron microscope. The surface roughness of the coatings was investigated with a 3D profilometer. The thickness of the coatings was determined through the analysis of the microstructure images, while the adhesion of the coatings was characterized using the scratch test method. The results indicate that the surface roughness of the coatings sprayed on the two different substrates gradually decreases as gas temperature and gas pressure increase. Additionally, the thickness and adhesion of the coatings deposited on the two different substrates both increase with an increase in gas temperature and gas pressure. Comparing the surface roughness, thickness, and adhesion of the coatings deposited on the two different substrates, the surface roughness and adhesion of the coatings on the soft substrate are greater than those of the coatings on the hard substrate, while the thickness of the coatings is not obviously affected by the hardness of the substrate. Furthermore, it is noteworthy that the surface roughness, thickness, and adhesion of the copper-coated graphite and copper composite coatings sprayed on the two different substrates exhibit a distinct linear relationship with particle velocity.

Nitric acid oxidation and urea modification of carbon fibres as biofilm carriers.

Carbon fibres (CF) are commonly used as carriers in biofilm-based wastewater treatment. The surface properties of the CF are herein modified using a combination of nitric acid oxidation and urea to optimise the carrier to immobilise bacterial cells. The capacity of the CF carriers to immobilise bacterial cells and activated sludge is evaluated using bacterial cell adhesion and sludge immobilisation tests. The total interaction energy profiles between the CF supports and bacterial cells were calculated according to the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory to explain the mechanism by which these modifications enhance this immobilisation capacity. CF-U has a high capacity for immobilising bacterial cells and activated sludge (3.7 g-sludge/g-CF supports) owing to its low total interaction energy. Nitric acid oxidation reduced the diiodomethane contact angle of CF from 55.1° to 38.5°, which reduced the Lifshitz-van der Waals interaction energy, while urea modification further increased the zeta potential of CF from 12.8 mV to -0.7 mV, thereby reducing the electrostatic interaction energy. Experiments and DLVO theory both determined that a combination of nitric acid oxidation and urea modification significantly enhanced the ability of CF to immobilise microorganisms.

Anisotropic Bi-Layer Hydrogel Actuator with pH-Responsive Color-Changing and Photothermal-Responsive Shape-Changing Bi-Functional Synergy.

Stimuli-responsive color-changing and shape-changing hydrogels are promising intelligent materials for visual detections and bio-inspired actuations, respectively. However, it is still an early stage to integrate the color-changing performance and shape-changing performance together to provide bi-functional synergistic biomimetic devices, which are difficult to design but will greatly expand further applications of intelligent hydrogels. Herein, we present an anisotropic bi-layer hydrogel by combining a pH-responsive rhodamine-B (RhB)-functionalized fluorescent hydrogel layer and a photothermal-responsive shape-changing melanin-added poly (N-isopropylacrylamide) (PNIPAM) hydrogel layer with fluorescent color-changing and shape-changing bi-functional synergy. This bi-layer hydrogel can obtain fast and complex actuations under irradiation with 808 nm near-infrared (NIR) light due to both the melanin-composited PNIPAM hydrogel with high efficiency of photothermal conversion and the anisotropic structure of this bi-hydrogel. Furthermore, the RhB-functionalized fluorescent hydrogel layer can provide rapid pH-responsive fluorescent color change, which can be integrated with NIR-responsive shape change to achieve bi-functional synergy. As a result, this bi-layer hydrogel can be designed using various biomimetic devices, which can show the actuating process in the dark for real-time tracking and even mimetic starfish to synchronously change both the color and shape. This work provides a new bi-layer hydrogel biomimetic actuator with color-changing and shape-changing bi-functional synergy, which will inspire new strategies for other intelligent composite materials and high-level biomimetic devices.

Polyurethane Shape Memory Polymer/pH-Responsive Hydrogel Hybrid for Bi-Function Synergistic Actuations.

Stimuli-responsive actuating hydrogels response to the external stimulus with complex deformation behaviors based on the programmable anisotropic structure design are one of the most important smart soft materials, which have great potential applications in artificial muscles, smart values, and mini-robots. However, the anisotropic structure of one actuating hydrogel can only be programmed one time, which can only provide single actuating performance, and subsequently, has severely limited their further applications. Herein, we have explored a novel SMP/hydrogel hybrid actuator through combining polyurethane shape memory polymer (PU SMP) layer and pH-responsive polyacrylic-acid (PAA) hydrogel layer by a napkin with UV-adhesive. Owing to both the super-hydrophilicity and super-lipophilicity of the cellulose-fiber based napkin, the SMP and the hydrogel can be bonded firmly by the UV-adhesive in the napkin. More importantly, this bilayer hybrid 2D sheet can be programmed by designing a different temporary shape in heat water which can be fixed easily in cool water to achieve various fixed shapes. This hybrid with a fixed temporary shape can achieve complex actuating performance based on the bi-functional synergy of temperature-triggered SMP and pH-responsive hydrogel. The relatively high modulus PU SMP achieved high to 87.19% and 88.92% shape-fixing ratio, respectively, correspond to bending and folding shapes. The hybrid actuator can actuate with the 25.71 °/min actuating speed. Most importantly, one SMP/hydrogel bi-layer hybrid sheet was repeatedly programmed at least nine times in our research to fix various temporary 1D, 2D and 3D shapes, including bending, folding and spiraling shapes. As a result, only one SMP/hydrogel hybrid can provide various complex stimuli-responsive actuations, including the reversable bending-straightening, spiraling-unspiraling. A few of the intelligent devices have been designed to simulate the movement of the natural organisms, such as bio-mimetic "paw", "pangolin" and "octopus". This work has developed a new SMP/hydrogel hybrid with excellent multi-repeatable (≥9 times) programmability for high-level complex actuations, including the 1D to 2D bending and the 2D to 3D spiraling actuations, which also provides a new strategy to design other new soft intelligent materials and systems.

A Nanoclay-Enhanced Hydrogel for Self-Adhesive Wearable Electrophysiology Electrodes with High Sensitivity and Stability.

Hydrogel-based wet electrodes are the most important biosensors for electromyography (EMG), electrocardiogram (ECG), and electroencephalography (EEG); but, are limited by poor strength and weak adhesion. Herein, a new nanoclay-enhanced hydrogel (NEH) has been reported, which can be fabricated simply by dispersing nanoclay sheets (Laponite XLS) into the precursor solution (containing acrylamide, N, N'-Methylenebisacrylamide, ammonium persulfate, sodium chloride, glycerin) and then thermo-polymerizing at 40 °C for 2 h. This NEH, with a double-crosslinked network, has nanoclay-enhanced strength and self-adhesion for wet electrodes with excellent long-term stability of electrophysiology signals. First of all, among existing hydrogels for biological electrodes, this NEH has outstanding mechanical performance (93 kPa of tensile strength and 1326% of breaking elongation) and adhesion (14 kPa of adhesive force), owing to the double-crosslinked network of the NEH and the composited nanoclay, respectively. Furthermore, this NEH can still maintain a good water-retaining property (it can remain at 65.4% of its weight after 24 h at 40 °C and 10% humidity) for excellent long-term stability of signals, on account of the glycerin in the NEH. In the stability test of skin-electrode impedance at the forearm, the impedance of the NEH electrode can be stably kept at about 100 kΩ for more than 6 h. As a result, this hydrogel-based electrode can be applied for a wearable self-adhesive monitor to highly sensitively and stably acquire EEG/ECG electrophysiology signals of the human body over a relatively long time. This work provides a promising wearable self-adhesive hydrogel-based electrode for electrophysiology sensing; which, will also inspire the development of new strategies to improve electrophysiological sensors.

Identifying Patient-Ventilator Asynchrony on a Small Dataset Using Image-Based Transfer Learning.

Mechanical ventilation is an essential life-support treatment for patients who cannot breathe independently. Patient-ventilator asynchrony (PVA) occurs when ventilatory support does not match the needs of the patient and is associated with a series of adverse clinical outcomes. Deep learning methods have shown a strong discriminative ability for PVA detection, but they require a large number of annotated data for model training, which hampers their application to this task. We developed a transfer learning architecture based on pretrained convolutional neural networks (CNN) and used it for PVA recognition based on small datasets. The one-dimensional signal was converted to a two-dimensional image, and features were extracted by the CNN using pretrained weights for classification. A partial dropping cross-validation technique was developed to evaluate model performance on small datasets. When using large datasets, the performance of the proposed method was similar to that of non-transfer learning methods. However, when the amount of data was reduced to 1%, the accuracy of transfer learning was approximately 90%, whereas the accuracy of the non-transfer learning was less than 80%. The findings suggest that the proposed transfer learning method can obtain satisfactory accuracies for PVA detection when using small datasets. Such a method can promote the application of deep learning to detect more types of PVA under various ventilation modes.

Optimizing carbon fibre supports for bioreactors by nitric acid oxidation and calcium ion coverage according to extended DLVO theory.

Optimizing supports for microorganisms is required for bioreactors. Carbon fibres (CF) were employed as supports for microorganisms. To optimize CF supports for immobilizing bacterial cells, we used methods of nitric acid oxidation and calcium ion coverage. We evaluated the capacity of these CF supports (untreated CF, nitric acid oxidation CF and Ca2+-covered CF) via bacterial cell adhesion tests, based on extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory. The results implied that because of the high hamaker constants, oxidized CF supports had higher capacity in this regard than untreated CF supports. However, the growing oxygen groups increased the negative zeta potential of CF supports, thus likely to reduce their capacity, in accordance with XDLVO theory. Since the Ca2+ coverage could decrease the negative zeta potentials of CF without reducing the hamaker constants, it could enhance the capacity of oxidized CF supports. We concluded that a combination of nitric acid oxidation and Ca2+ coverage could increase the capacity of CF supports to immobilize bacterial cells.

Carbon nanotubes/carbon fiber hybrid material: a super support material for sludge biofilms.

Carbon fiber (CF) is widely used as a sludge biofilm support material for wastewater treatment. Carbon nanotubes/carbon fiber (CNTs/CF) hybrid material was prepared by ultrasonically assisted electrophoretic deposition (EPD). CF supports (CF without handling, CF oxidized by nitric acid, CNTs/CF hybrid material) were evaluated by sludge immobilization tests, bacterial cell adsorption tests and Derjaguin -Landau -Verwey -Overbeek (DLVO) theory. We found that the CNTs/CF hybrid material has a high capacity for adsorbing activated sludge, nitrifying bacterial sludge and pure strains (Escherichia coli and Staphylococcus aureus). CNTs deposited on CF surface easily wound around the curved surface of bacterial cell which resulted in capturing more bacterial cells. DLVO theory indicated the lowest total interaction energy of CNTs/CF hybrid material, which resulted in the highest bacteria cell adsorption velocity. Experiments and DLVO theory results proved that CNTs/CF hybrid material is a super support material for sludge biofilms.