Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease.

Alcoholic-associated liver disease (ALD) and metabolic dysfunction-associated steatotic liver disease (MASLD) show a high prevalence rate worldwide. As gut microbiota represents current state of ALD and MASLD via gut-liver axis, typical characteristics of gut microbiota can be used as a potential diagnostic marker in ALD and MASLD. Machine learning (ML) algorithms improve diagnostic performance in various diseases. Using gut microbiota-based ML algorithms, we evaluated the diagnostic index for ALD and MASLD. Fecal 16S rRNA sequencing data of 263 ALD (control, elevated liver enzyme [ELE], cirrhosis, and hepatocellular carcinoma [HCC]) and 201 MASLD (control and ELE) subjects were collected. For external validation, 126 ALD and 84 MASLD subjects were recruited. Four supervised ML algorithms (support vector machine, random forest, multilevel perceptron, and convolutional neural network) were used for classification with 20, 40, 60, and 80 features, in which three nonsupervised ML algorithms (independent component analysis, principal component analysis, linear discriminant analysis, and random projection) were used for feature reduction. A total of 52 combinations of ML algorithms for each pair of subgroups were performed with 60 hyperparameter variations and Stratified ShuffleSplit tenfold cross validation. The ML models of the convolutional neural network combined with principal component analysis achieved areas under the receiver operating characteristic curve (AUCs) > 0.90. In ALD, the diagnostic AUC values of the ML strategy (vs. control) were 0.94, 0.97, and 0.96 for ELE, cirrhosis, and liver cancer, respectively. The AUC value (vs. control) for MASLD (ELE) was 0.93. In the external validation, the AUC values of ALD and MASLD (vs control) were > 0.90 and 0.88, respectively. The gut microbiota-based ML strategy can be used for the diagnosis of ALD and MASLD.ClinicalTrials.gov NCT04339725.

Very high cycle fatigue behavior of SAE52100 bearing steel by ultrasonic nanocrystalline surface modification.

In this paper, the SAE52100 bearing steel contained large quantities of cementite dispersed in ferrite matrix was subjected to the ultrasonic nanocrystalline surface modification (UNSM) treatment that aims for the extension of fatigue life. The microstructure and fatigue life of the untreated and treated specimens were studied by using electron backscattered diffraction (EBSD) and transmission electron microscopy (TEM), and a developed ultra-high cycle fatigue test (UFT). After UNSM treatment, the coarse ferrite grains (- 10 µm) were refined to nanosize (- 200 nm), therefore, nanostructured surface layers were fabricated. Meanwhile, in the deformed layer, the number density and area fraction of cementite were increased up to - 400% and - 550%, respectively, which increased with the decrease in depth from the topmost treated surface. The improvement of hardness (from 200 Hv to 280 Hv) and high cycles fatigue strength by - 10% were considered the contribution of the developed nanostructure in the UNSM treated specimen.

Microstructural refinement of Al-Si alloy upon ultrasonic nanocrystalline surface modification treatment.

In this work, an Al-7 wt.% Si alloy, which is widely used as the structural materials in the automotive and aerospace industries for their high specific strength, was subjected to ultrasonic nanocrystalline surface modification (UNSM) treatment. After UNSM treatment, the effect of UNSM on the microstructural evolution of both Al grain and the dispersed Si particles was studied by using scanning electron microscope (SEM) and transmission electron microscope (TEM). Experimental results show that the ultra-fine grain (UFG, - 400 nm in size) structure is developed in the top surface layer (up to - 15 µm in depth). The coarse Si particles were refined and well dispersed in the UFG Al matrix. Cross-sectional TEM observation revealed that the grain refinement mechanism involved the formation of new grain boundaries dividing the coarse grain into UFG structure. Nanotwin and nanosize Si were formed within the original coarse Si particles. The presence of dispersed Si particles in the Al matrix accelerated the Al grain refinement process.

Tribological characteristics of corrugated nano-scale dimpled and nanostructured surfaces.

The effects of ultrasonic nanocrystalline surface modification (UNSM) on the tribological characteristics of two different Cu-based alloys sintered on low carbon steel were investigated using a ball-on-disk reciprocating tribometer with a hardened bearing steel ball under oil-lubricated conditions. Experimental results showed that both the UNSM-treated Cu-based alloy specimens reduced the friction coefficient and enhanced the wear resistance compared to those of the polished specimens. Improvements in tribological characteristics of the UNSM-treated specimens may be attributed to the corrugated nano-scale dimpled and nanostructured surfaces and increased hardness. Addition of the 0.52% ferrum to Cu-based alloy is found to be beneficial in improving the tribological characteristics and in reducing the grain size. Scanning electron microscopy (SEM) was utilized to analyze the worn surfaces and characterize the wear mechanisms of the polished and UNSM-treated specimens. SEM analyses showed that the UNSM could reduce the abrasive wear which was the dominant wear mechanism of both Cu-based alloys specimens. In addition, the density and porosity measurement of both sintered Cu-based alloys revealed that the density increased and the porosity decreased after UNSM.

Wear behavior of Cu-Zn alloy by ultrasonic nanocrystalline surface modification.

The ultrasonic nanocrystalline surface modification (UNSM) was applied to disk specimens made of Cu-Zn alloy in order to investigate the UNSM effects under five various conditions on wear of deformation twinning. In this paper, ball-on-disk test was conducted, and the results of UNSM-treated specimens showed that surface layer dislocation density and multi-directional twins were abruptly increased, and the grain size was altered into nano scale. UNSM delivers force onto the workpiece surface 20,000 times per second with 1,000 to 4,000 contact counts per square millimeter. The UNSM technology creates nanocrystalline and deformation twinning on the workpiece surface. One of the main concepts of this study is that defined phenomena of the UNSM technology, and the results revealed that nanocrystalline and deformation twinning depth might be controlled by means of impact energy of UNSM technology. EBSD and TEM analyses showed that deformation layer was increased up to 268 microm, and initial twin density was 0.001 x 10(6) cm(-2) and increased up to 0.343 x 10(6) cm(-2). Wear volume loss was also decreased from 703 x 10(3) mm3 to 387 x 10(3) mm3. Wear behavior according to deformation depth was observed under three different combinations. This is related to deformation depth which was created by UNSM technology.

The evaluation of the micro-tracks and micro-dimples on the tribological characteristics of thrust ball bearings.

One of the primary remedies for tribological problems is surface modification. The reduction of the friction between the ball and the raceway of bearings is a very important goal of the development of bearing technology. A low friction has a positive effect in terms of the extension of the fatigue life, avoidance of a temperature rise, and prevention of premature failure of bearings. Therefore, this research sought to investigate the effects of micro-tracks and micro-dimples on the tribological characteristics at the contact point between the ball and the raceway of thrust ball bearings (TBBs). The ultrasonic nanocrystal surface modification (UNSM) technology was applied using different intervals (feed rates) to the TBB raceway surface to create micro-tracks and micro-dimples. The friction coefficient after UNSM at 50 microm intervals showed marked sensitivity and a significant reduction of 30%. In this study, the results showed that more micro-dimples yield a lower friction coefficient.

The effect of ultrasonic nanocrystalline surface modification on the high-frequency fretting wear behavior of AISI304 steel.

The fact that one of fundamental characteristics of fretting is the very small sliding amplitude dictates the unique feature of wear mechanism. Ultrasonic Nanocrystalline Surface Modification (UNSM) technology was applied in order to investigate its effect on the high-frequency fretting wear behavior of AISI304 steel. Its influence on the fretting wear is also reported in this paper with these treated and untreated samples. UNSM delivers force onto the workpiece surface 20,000 times per second with 1,000 to 4,000 contact counts per square millimeter. UNSM creates homogenous nanocrystalline structures as well on the surface. UNSM process is expected to eliminate or significantly retard the formation of fretting wear. Nanocrystalline structure generation after UNSM has been reported to produce its unique structure and to offer a variety of beneficial properties compared to conventionally treated materials. A deformed layer of 220 microm exhibits high dislocation density, where top layer transformed to a nanostructure of the grain size in 23 nm and mechanical twins were observed. Deformation-induced martensite was observed to form at the intersections of mechanical twins, whose volume fraction has increased up to 38.4% and wear loss rate at 800,000 cycles has decreased by 40%. In this paper, experimental results are discussed to elucidate potential mechanism of high-frequency fretting wear.