Fundamental Limits of the Spatial Control of Heterogeneous Nucleation on Biphilic Surfaces.

Condensation of water vapor on nonwetting surfaces, termed dropwise condensation, leads to rapid droplet removal and significantly improves heat transfer compared to wetting surfaces. However, the spatial distribution of heterogeneous nucleation sites during dropwise condensation is random. Furthermore, the low surface energy of the nonwetting substrate reduces the nucleation rate as predicted by classical nucleation theory. To achieve higher nucleation rates, biphilic surfaces having low nucleation energy barriers that rely on spatial heterogeneity of surface chemistry have been developed. Here, we use a robust method to create biphilic surfaces on flat and micropillar samples having various dimensions (pillar lengths: 10-15 µm, pillar heights: 0-15 µm) by utilizing lift-off microfabrication. Our fabrication approach leads to hydrophilic pillar tops and hydrophobic pillar sides and surrounding basal areas. To study water vapor condensation on the biphilic surfaces, we utilized optical microscopy in a controlled temperature and humidity environment. Interestingly, our studies show that while the majority of nucleation (≈100%) occurred only on the hydrophilic areas (pillar tops) for small pillar center-to-center spacing (pitch), the spatial control of heterogeneous nucleation broke down when the pitch increased. For larger pitches, we observed the nucleation of water droplets on the hydrophobic base in conjunction with hydrophilic pillar tops. Using theoretical models of vapor diffusion coupled with heat transfer and three-dimensional (3D) numerical simulations, we show that nucleation initiation on hydrophilic pillar tops leads to the formation of dry zones, preventing nucleation on hydrophobic regions. However, with increasing pitch, part of the hydrophobic region no longer feels the presence of the vapor depletion zone, resulting in subsequent nucleation at defect sites on the hydrophobic regions at the base. Our study offers insights into the fundamental limitations of biphilic condensation and offers avenues for their further improvement for applications such as boiling, icing, evaporation, and condensation.

Impact of Age on the Occurrence of Vascular Complications in Patients Undergoing Anterior Lumbar Approach Surgery.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To investigate the impact of age on incidence of vascular complications in patients undergoing anterior lumbar approach surgery. SUMMARY OF BACKGROUND DATA: Anterior approach lumbar spinal surgery may facilitate use of intervertebral devices with larger endplate coverage and increased lordosis. Despite the advantages of this approach, risks related to vascular injury in older patients have been described in the literature. METHODS: In total, 751 consecutive patients with degenerative spinal pathology who underwent stand-alone anterior lumbar interbody fusion (ALIF), ALIF combined with posterior fusion and/or instrumentation (360), total disc replacement (TDR), or hybrid procedures (ALIF and TDR) were included. Data collected included general patient descriptive data, surgery details, intraoperative vascular injury, and post-operative vascular complications (deep vein thrombosis (DVT) and/or pulmonary embolism (PE)). Rates of vascular complications were compared across age groups. Additionally, the mean age of patients was compared between those with vs. without vascular complications. RESULTS: Overall mean age was 50.4 years (range 20-83 years). Mean estimated blood loss was 91.3 ml (range 10 to 2800 ml). A total of 15 patients, 2.0%, had vascular complications. There were 10 cases (1.3%) of intraoperative injury to iliac arteries or iliolumbar veins (mean blood loss was 721 mL and all were repaired intraoperatively). Postoperatively, 6 patients (0.8%) developed DVT and/or PE (one patient had both). With respect to age, there were no significant differences in rates of intra-operative, post-operative, or combined vascular complication rates across the age group (P>0.38). Additionally, there were no statistically significant differences in the mean ages of patients with vs. those without vascular complications (P>0.17). CONCLUSION: Overall incidence of vascular complications was 2.0%. No relationship between vascular complications and age was demonstrated. These data suggest that increased age may not necessarily be an absolute contraindication for anterior lumbar approach surgery.

Integrative multi-omics analysis reveals ortho-topolin riboside exhibits anticancer activity by regulating metabolic pathways in radio-resistant triple negative breast cancer cells.

Radio-resistant triple negative breast cancer (TNBC) is resistant to conventional drugs and radiation therapy. ortho-topolin riboside (oTR) has been evaluated for its anticancer activity in several types of cancer cells. However, its anti-proliferative activity in radio-resistant TNBC cells has not yet been reported. Therefore, we investigated the anti-proliferative activity of oTR in radio-resistant TNBC cells, and performed metabolome, lipidome, transcriptome, and proteome profiling to reveal the mechanisms of the anticancer activity of oTR. oTR showed cytotoxicity against radio-resistant TNBC cells with an inhibitory concentration (IC50) value of 7.78 µM. Significantly decreased (p value < 0.05) basal and compensatory glycolysis were observed in the oTR-treated group than untreated group. Mitochondrial spare respiratory capacity, which is relevant to cell fitness and flexibility, was significantly decreased (p value < 0.05) in the oTR-treated group. The major metabolic pathways significantly altered by oTR according to metabolome, transcriptome, and proteome profiles were the glycerolipid/glycerophospholipid pathway (log2(FC) of MGLL = -0.13, log2(FC) of acylglycerol lipase = -1.35, log2(FC) of glycerol = -0.81), glycolysis (log2(FC) of EGLN1 = 0.16, log2(FC) of EGLN1 = 0.62, log2(FC) of glucose = -0.76, log2(FC) of lactate = -0.81), and kynurenine pathway (log2(FC) of KYNU = 0.29, log2(FC) of kynureninase = 0.55, log2(FC) of alanine = 0.72). Additionally, proline metabolism (log2(FC) of PYCR1 = -0.17, log2(FC) of proline = -0.73) was significantly altered in the metabolomic and transcriptomic profiles. The MAPK signaling pathway (log2(FC) of CCN1 = -0.15, log2(FC) of CCN family member 1 = -1.02) and Rap 1 signaling pathway (log2(FC) of PARD6B = -0.28, log2(FC) of PAR6B = -3.13) were also significantly altered in transcriptomic and proteomic profiles. The findings of this study revealed that oTR has anticancer activity in radio-resistant TNBC cells by affecting various metabolic pathways, suggesting the potential of oTR as a novel anticancer agent for radio-resistant TNBC patients.

Effects of volatile organic compounds and new particle formation on real-time hygroscopicity of PM2.5 particles in Seosan, Republic of Korea.

The hygroscopicity of PM2.5 particles plays an important role in PM2.5 haze in Northeast Asian countries by influencing particle growth and chemical composition. New particle formation (NPF) and atmospheric volatile organic compounds (VOCs) are factors that influence particle hygroscopicity. However, the lack of real-time hygroscopicity measurements has deterred the understanding of their effects on particle hygroscopicity. In this study, two intensive monitoring campaigns were conducted during the summer of 2021 and spring of 2022 using real-time aerosol instruments, including a humidified tandem differential mobility analyzer (HTDMA), in Seosan, Republic of Korea. The hygroscopicity parameter κ was calculated from the real-time HTDMA measurement data (κGf). The diurnal variations in κGf exhibited strong inverse linear correlations with the total concentration of VOCs (CTVOC) during the two campaigns. The higher atmospheric CTVOC in summer increased the growth rate of the particle diameter from 10 to 40 nm (6 nm/h) compared with that in spring (2.7 nm/h), resulting in a faster change in κGf for 40-nm particles in summer than in spring because of the increase in organic matter in the chemical compositions of particles. In addition, NPF events introduced additional tiny fresh particles into the atmosphere, which reduced the κGf of 40-nm particles and increased the intensity of the less hygroscopic peaks (κGf < 0.1) of κ-probability density functions (κ-PDF) in NPF days. However, 100-nm particles exhibited fewer changes in κGf than 40-nm particles, resulting in additional dominant hygroscopic peaks (κ âˆ¼ 0.2) of κ-PDFs in both NPF and non-NPF days. When κGf values measured in Seosan were compared with those in other Northeast Asian countries in the literature, the κ values for 40-nm particles were lower than those (κ > 0.2) measured in Beijing and Guangzhou, but those for 100-nm particles were close to those measured in the two cities.

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020-21 winter.

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020-21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42-, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3-, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42-, NO3-, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42- could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3-, and NH4+ concentrations in BJ when Gobi dust storms occur.

Prediction of Clinical Remission with Adalimumab Therapy in Patients with Ulcerative Colitis by Fourier Transform-Infrared Spectroscopy Coupled with Machine Learning Algorithms.

We aimed to develop prediction models for clinical remission associated with adalimumab treatment in patients with ulcerative colitis (UC) using Fourier transform-infrared (FT-IR) spectroscopy coupled with machine learning (ML) algorithms. This prospective, observational, multicenter study enrolled 62 UC patients and 30 healthy controls. The patients were treated with adalimumab for 56 weeks, and clinical remission was evaluated using the Mayo score. Baseline fecal samples were collected and analyzed using FT-IR spectroscopy. Various data preprocessing methods were applied, and prediction models were established by 10-fold cross-validation using various ML methods. Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed a clear separation of healthy controls and UC patients, applying area normalization and Pareto scaling. OPLS-DA models predicting short- and long-term remission (8 and 56 weeks) yielded area-under-the-curve values of 0.76 and 0.75, respectively. Logistic regression and a nonlinear support vector machine were selected as the best prediction models for short- and long-term remission, respectively (accuracy of 0.99). In external validation, prediction models for short-term (logistic regression) and long-term (decision tree) remission performed well, with accuracy values of 0.73 and 0.82, respectively. This was the first study to develop prediction models for clinical remission associated with adalimumab treatment in UC patients by fecal analysis using FT-IR spectroscopy coupled with ML algorithms. Logistic regression, nonlinear support vector machines, and decision tree were suggested as the optimal prediction models for remission, and these were noninvasive, simple, inexpensive, and fast analyses that could be applied to personalized treatments.