Engineering the electronic structure of sub-nanometric Ru clusters via Pt single-atom modification for highly efficient electrocatalytic hydrogen evolution.

Developing electrocatalysts with high activity toward the hydrogen evolution reaction (HER) is a prerequisite for hydrogen fuel generation and sustainable development, but current Pt-based catalysts usually suffer from high cost and unsatisfactory performance in non-acidic media. In this work, we report an environmentally friendly and pyrolysis-free synthesis strategy to prepare an efficient catalyst, CNT-NPA-PtRu, with Pt single-atom engineered sub-nanometric Ru clusters anchored at phytic acid-modified carbon nanotubes for electrochemical HER at all pH conditions. The electronic structure of active sub-nanometric Ru clusters was optimized, which further enhanced the HER activity. The synthesized CNT-NPA-PtRu catalyst presents superior performance, reaching the current density of 10 mA cm-2 with only 18.3, 18.7 and 15 mV overpotential in alkaline, acidic and neutral electrolyte, respectively. Experimental results and theoretical calculations reveal that the single Pt atom on the sub-nanometric Ru cluster surface could modulate the electronic structure of Ru and subsequently optimize the adsorption of reaction intermediates, thus promoting HER performance. These findings underscore the importance of engineering the electronic structure of sub-nanometric clusters and offer an effective approach for the generation of high-performance electrocatalysts for HER.

New-QiangGuYin-Containing Serum Inhibits Osteoclast-Derived Exosome Secretion and Down-Regulates Notum to Promote Osteoblast Differentiation.

New-QiangGuYin (N-QGY), the addition of sea buckthorn on the basis of QGY formula, is herbal formula widely used clinically in China for the treatment of osteoporosis (OP), but its mechanism warrants further exploration. The mechanisms of QGY and N-QGY in the treatment of OP are probed from the perspective of osteoclast-osteoblast balance. Thirty Sprague-Dawley rats are randomly divided into N-QGY group, QGY group, and Control group. Beyond control rats that orally took normal saline, other rats are orally administered with isometric N-QGY or QGY twice every day for 3 days. The drug-containing serum and control serum are prepared and their effects on osteoclast-derived exosome secretion are determined by bicinchoninic acid assay (BCA), nanoparticle tracking analysis, and Western blot. GW4869 and Interleukin-1ß (IL-1ß) are adopted as the exosome inhibitor and inducer, respectively. Exosome uptake, cell counting kit-8, alkaline phosphatase (ALP) staining, alizarin red staining, enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction, and Western blot are performed to examine the effects of altered osteoclast exosome content on osteogenic differentiation of mesenchymal stem cells (MSCs). N-QGY, QGY, and GW4869 inhibit osteoclast-derived exosome secretion and exosome uptake by MSCs, whereas IL-1ß exerted the opposite effects (p < 0.05). Different from IL-1ß, N-QGY, QGY, and GW4869 partially elevated MSC viability, osteocalcin secretion, ALP, RUNX Family Transcription Factor 2 (RUNX2) and Osteopontin (OPN) expressions, and calcium deposition in the osteoclast-MSCs coculture system (p < 0.05). Mechanically, osteoclasts increased Notum protein level but decreased ß-catenin level, which is enhanced by IL-1ß but is reversed by GW4869, QGY, and N-QGY (p < 0.05). And the effect of N-QGY is more conspicuous than that of QGY (P<0.05). N-QGY-containing serum inhibits exosome levels in osteoclasts, thereby enhancing osteogenic differentiation of MSCs via inhibition of Notum protein and promotion of ß-catenin protein.

The impact of medium-chain triglycerides on weight loss and metabolic health in individuals with overweight or obesity: A systematic review and meta-analysis.

BACKGROUNDS: The efficacy of medium-chain triglycerides (MCTs) for weight management and mitigating metabolic disorders among individuals with overweight and obesity remains a topic of ongoing discussion. Notably, there is a gap in the distinction between pure MCTs and medium-long-chain triglycerides (MLCTs). METHODS: This meta-analysis investigates the efficacy of MCTs on weight loss and glucolipid metabolism in these populations, explicitly evaluating the differential effects of pure MCTs and MLCTs. We performed a random-effects meta-analysis on relevant studies examining weight loss and glucolipid parameters, incorporating a subgroup analysis conducted based on intervention types, pure MCTs versus MLCTs. RESULTS: Our findings revealed diets enriched with MCTs are more effective in achieving weight reduction (WMD: -1.53%; 95% CI: -2.44, -0.63; p < 0.01), particularly those containing pure MCTs (WMD: -1.62%; 95% CI: -2.78, -0.46; p < 0.01), compared to long-chain fatty acids (LCTs) enriched diets. However, our subgroup analysis indicates that an MLCTs-enriched diet did not significantly reduce weight loss. Additionally, MCTs-enriched diets were associated with significant reductions in blood triglyceride levels and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) scores, compared to LCTs-enriched diets. CONCLUSIONS: Hence, the authors recommend incorporating pure MCTs in dietary interventions for individuals with overweight and obesity, particularly those with comorbidities such as dyslipidemia and impaired glucose metabolism.

Rational designing NiVO3@CoNi-MOF heterostructures on activated carbon cloth for high-performance asymmetric supercapacitors and oxygen evolution reaction.

Binder-free self-supported carbon cloth electrode provides novel strategies for the preparation of MOFs, effectively improving the conductivity and promoting charge transfer. Combining MOFs with vanadate to form a unique heterogeneous structure provides a large specific surface area and more active sites, further enhancing the kinetics of MOFs. Herein, a self-supported carbon cloth electrode is prepared by in-situ growth of CoNi-MOFs on activated carbon cloth (AC) and coating with NiVO3. The heterostructure increases the specific surface area and exposes more active sites to promote the adsorption and diffusion of ions, thus enhancing the kinetic activity and optimizing charge storage behavior. As expected, the NiVO3@CoNi-MOF/AC exhibits a specific capacitance of up to 19.20 F/cm2 at 1 mA/cm2. The asymmetric supercapacitors (ASCs) assembled by NiVO3@CoNi-MOF/AC and annealed activated carbon cloth achieve an energy density of 1.27 mWh/cm2 at a power density of 4 mW/cm2 and have a capacitance retention of 96.43 % after 10,000 cycles. In addition, the NiVO3@CoNi-MOF/AC as electrocatalyst has an overpotential of 370 mV at 10 mA/cm2 and a Tafel slope of 208 mV dec-1, demonstrating remarkable electrocatalytic oxygen evolution reaction performance. These unique heterostructures endow the electrode with more electrochemical selectivity and provide new key insights for designing multifunctional materials.

Characterization and the first complete genome sequence of a novel strain of Bergeyella porcorum isolated from pigs in China.

BACKGROUND: Bergeyella porcorum is a newly identified bacterium that has an ambiguous relationship with pneumonia in pigs. However, few studies have adequately characterized this species. RESULTS: In this study, we analyzed the morphological, physiological, and genomic characteristics of the newly identified B. porcorum sp. nov. strain QD2021 isolated from pigs. The complete genome sequence of the B. porcorum QD2021 strain consists of a single circular chromosome (2,271,736 bp, 38.51% G + C content), which encodes 2,578 genes. One plasmid with a size of 70,040 bp was detected. A total of 121 scattered repeat sequences, 319 tandem repeat sequences, 4 genomic islands, 5 prophages, 3 CRISPR sequences, and 51 ncRNAs were predicted. The coding genes of the B. porcorum genome were successfully annotated across eight databases (NR, GO, KEGG, COG, TCDB, Pfam, Swiss-Prot and CAZy) and four pathogenicity-related databases (PHI, CARD, VFDB and ARDB). In addition, a comparative genome analysis was performed to explore the evolutionary relationships of B. porcorum QD2021. CONCLUSIONS: To our knowledge, this is the first study to provide fundamental phenotypic and whole-genome sequences for B. porcorum. Our results extensively expand the current knowledge and could serve as a valuable genomic resource for future research on B. porcorum.

Vortex electromagnetic wave imaging with orbital angular momentum and waveform degrees of freedom.

The vortex electromagnetic wave has shown great prospects of radar applications, due to the orbital angular momentum (OAM) degree of freedom. However, the radiation energy convergence of the OAM beam remains a hard problem to be solved for radar target imaging in realistic scenario. In this paper, an OAM beam generation method is developed exploiting the OAM and waveform degrees of freedom simultaneously, which can collimate the beams with different OAM modes. Furthermore, the echo demodulation and the imaging methods are proposed to reconstruct the target profiles in the range and azimuth domain. Simulation and experimental results both validate that the OAM-based radar imaging can achieve azimuthal super-resolution beyond the diffraction limit of the array aperture. This work can advance the system design of vortex electromagnetic wave radar and its real-world applications.

Shortened Cerebral Circulation Time Predicts Resistance to Obliteration in High-Flow Brain Arteriovenous Malformations After Stereotactic Radiosurgery.

BACKGROUND AND OBJECTIVES: Treatment selection for brain arteriovenous malformations (BAVMs) is complicated by BAVM size, location, and hemodynamics. Quantitative digital subtraction angiography is used to quantify the hemodynamic impact of BAVMs on cerebral circulation. This study investigated the association between cerebral circulation time and the complete obliteration (CO) rate of BAVMs after stereotactic radiosurgery (SRS). METHODS: We analyzed the data of 143 patients who underwent SRS for BAVMs between January 2011 and December 2019 in our institute. Their pre-SRS magnetic resonance imaging and angiography images were analyzed to acquire BAVM characteristics and quantitative digital subtraction angiography parameters. Modified cerebral circulation time (mCCT) was defined as the time difference between the bolus arrival time of the ipsilateral cavernous internal carotid artery and that of the parietal vein, as determined from the lateral view of images obtained using digital subtraction angiography. Cox regression with hazard ratios and Kaplan-Meier analyses were conducted to determine the associations between the parameters and BAVM CO after SRS. RESULTS: Of the 143 patients, 101 (70.6%) achieved BAVM CO. According to the multivariate analyses, an increased mCCT (hazard ratio: 1.24, P = .041) was the independent factor associated with BAVM CO after adjustment for age, sex, hemorrhagic presentation, a BAVM volume of >5 cm3, and a margin dose of >18 Gy. Individuals with an mCCT of ≤2.32 s had a lower 36-month probability of BAVM CO than did those with an mCCT of >2.32 s (44.1% ± 6.8% vs 63.3% ± 5.6%, P = .034). CONCLUSION: The hemodynamic impact of high-flow BAVM demonstrated by a shortened mCCT is associated with a lower BAVM CO rate after SRS.

Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system.

BACKGROUND: The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). METHODS: Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve. RESULTS: The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort. CONCLUSION: This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.

Construction of multi-scale feature fusion segmentation model of MRI knee images based on dual attention mechanism weighted aggregation.

BACKGROUND: Early diagnosis of knee osteoarthritis is an important area of research in the field of clinical medicine. Due to the complexity in the MRI imaging sequences and the diverse structure of cartilage, there are many challenges in the segmentation of knee bone and cartilage. Relevant studies have conducted semantic fusion processing through splicing or summing forms, which results in reduced resolution and the accumulation of redundant information. OBJECTIVE: This study was envisaged to construct an MRI image segmentation model to improve the diagnostic efficiency and accuracy of different grade knee osteoarthritis by adopting the Dual Attention and Multi-scale Feature Fusion Segmentation network (DA-MFFSnet). METHODS: The feature information of different scales was fused through the Multi-scale Attention Downsample module to extract more accurate feature information, and the Global Attention Upsample module weighted lower-level feature information to reduce the loss of key information. RESULTS: The collected MRI knee images were screened and labeled, and the study results showed that the segmentation effect of DA-MFFSNet model was closer to that of the manually labeled images. The mean intersection over union, the dice similarity coefficient and the volumetric overlap error was 92.74%, 91.08% and 7.44%, respectively, and the accuracy of the differential diagnosis of knee osteoarthritis was 84.42%. CONCLUSIONS: The model exhibited better stability and classification effect. Our results indicated that the Dual Attention and Multi-scale Feature Fusion Segmentation model can improve the segmentation effect of MRI knee images in mild and medium knee osteoarthritis, thereby offering an important clinical value and improving the accuracy of the clinical diagnosis.

Reshaping the Tumor Microenvironment of KRASG12D Pancreatic Ductal Adenocarcinoma with Combined SOS1 and MEK Inhibition for Improved Immunotherapy Response.

KRAS inhibitors have demonstrated exciting preclinical and clinical responses, although resistance occurs rapidly. Here, we investigate the effects of KRAS-targeting therapies on the tumor microenvironment using a library of KrasG12D, p53-mutant, murine pancreatic ductal adenocarcinoma-derived cell lines (KPCY) to leverage immune-oncology combination strategies for long-term tumor efficacy. Our findings show that SOS1 and MEK inhibitors (SOS1i+MEKi) suppressed tumor growth in syngeneic models and increased intratumoral CD8+ T cells without durable responses. Single-cell RNA sequencing revealed an increase in inflammatory cancer-associated fibroblasts (iCAF), M2 macrophages, and a decreased dendritic cell (DC) quality that ultimately resulted in a highly immunosuppressive microenvironment driven by IL6+ iCAFs. Agonist CD40 treatment was effective to revert macrophage polarization and overcome the lack of mature antigen-presenting DCs after SOS1i+MEKi therapy. Treatment increased the overall survival of KPCY tumor-bearing mice. The addition of checkpoint blockade to SOS1i+MEKi combination resulted in tumor-free mice with established immune memory. Our data suggest that KRAS inhibition affects myeloid cell maturation and highlights the need for combining KRAS cancer-targeted therapy with myeloid activation to enhance and prolong antitumor effects. SIGNIFICANCE: Combination of SOS1 and MEK inhibitors increase T cell infiltration while blunting pro-immune myeloid cell maturation and highlights the need for combining KRAS cancer-targeted therapy with myeloid activation to enhance and prolong anti-tumor effects.

Ultrasmall copper nanoclusters as an efficient antibacterial agent for primary peritonitis therapy.

The urgent need to develop biocompatible, non-resistant antibacterial agents to effectively combat Gram-negative bacterial infections, particularly for the treatment of peritonitis, presents a significant challenge. In this study, we introduce our water-soluble Cu30 nanoclusters (NCs) as a potent and versatile antibacterial agent tailored for addressing peritonitis. The as-synthesized atomically precise Cu30 NCs demonstrate exceptional broad-spectrum antibacterial performance, and especially outstanding bactericidal activity of 100% against Gram-negative Escherichia coli (E. coli). Our in vivo experimental findings indicate that the Cu30 NCs exhibit remarkable therapeutic efficacy against primary peritonitis caused by E. coli infection. Specifically, the treatment leads to a profound reduction of drug-resistant bacteria in the peritoneal cavity of mice with peritonitis by more than 5 orders of magnitude, along with the resolution of pathological features in the peritoneum and spleen. Additionally, comprehensive in vivo biosafety assessment underscores the remarkable biocompatibility, low biotoxicity, as well as efficient hepatic and renal clearance of Cu30 NCs, emphasizing their potential for in vivo application. This investigation is poised to advance the development of novel Cu NC-based antibacterial agents for in vivo antibacterial treatment and the elimination of abdominal inflammation.

Near-unity quantum yield and long-term emission stability in halide perovskite nanocrystal glass composite.

Metal halide perovskites are promising optoelectronic materials due to their outstanding luminescent properties. However, the instability of perovskites has long been the bottleneck to their practical applications. Here Cs4PbBr6 nanocrystals based glass composite (Cs4PbBr6 NCs@glass) are successfully prepared, which displays green emission color (520 nm), narrow bandwidth (23 nm) and a near-unity photoluminescence quantum yield (PLQY). The H2O molecules permeating in the lattice of Cs4PbBr6 were found to be a crucial role in the subband energy emission. The Cs4PbBr6 NCs@glass has excellent emission stability; maintains 93 % of initial PL intensity after ultraviolet light irradiation for over 5000 h. In addition, by adjusting the halogen content, we have achieved tunable emission color from blue (450 nm) to green (520 nm) and red (670 nm) on Cs4PbX6 NCs@glass (X = Cl, Br, I), which covers up to 127 % of the National Television Systems Board (NTSC) standard system. Our finding indicates the commercial applications of perovskite materials in lighting and display.

The prevention effect of Limosilactobacillus reuteri on acute kidney injury by regulating gut microbiota.

Acute kidney injury (AKI) has considerably high morbidity and mortality but we do not have proper treatment for it. There is an urgent need to develop new prevention or treatment methods. Gut microbiota has a close connection with renal diseases and has become the new therapy target for AKI. In this study, we found the oral administration of the probiotic Limosilactobacillus reuteri had a prevention effect on the AKI induced by lipopolysaccharide (LPS). It reduced serum concentration of creatinine and urea nitrogen and protected the renal cells from necrosis and apoptosis. Meanwhile, L. reuteri improved the gut barrier function, which is destroyed in AKI, and modulated the gut microbiota and relevant metabolites. Compared with the LPS group, L. reuteri increased the proportion of Proteobacteria and reduced the proportion of Firmicutes, changing the overall structure of the gut microbiota. It also influenced the fecal metabolites and changed the metabolite pathways, such as tyrosine metabolism, pentose and glucuronate interconversions, galactose metabolism, purine metabolism, and insulin resistance. These results showed that L. reuteri is a potential therapy for AKI as it helps in sustaining the gut barrier integrity and modulating gut microbiota and related metabolites.

Kidney-Sparing Surgery Has Equivalent Oncological Outcomes to Radical Nephroureterectomy for Ureteral Urothelial Carcinoma.

Introduction and Objective: Kidney-sparing surgery (KSS) for upper tract urothelial cancer (UTUC) has gained increasing interest recently. However, there is limited contemporary data regarding the role of KSS in ureteral urothelial carcinoma. Therefore, we investigated the survival outcomes of ureteral urothelial carcinoma after KSS from a large, prospective international UTUC registry. Methods: The Clinical Research Office of the Endourology Society-Urothelial Carcinomas of the Upper Tract (CROES-UTUC) Registry included patients with UTUC who received KSS or radical nephroureterectomy (RNU) between 2014 and 2019. In this study, we included patients with ureteral UTUC only. Study outcomes included overall survival (OS), cancer-specific survival (CSS), upper tract recurrence-free survival (RFS), intravesical RFS, progression-free survival (PFS), and metastasis-free survival (MFS). Propensity score matching (PSM) was performed to balance the tumor features' differences between groups. Results: Of the 391 patients with ureteral UTUC, 309 (79.0%) received RNU and 82 (21.0%) received KSS by ureteroscopy with laser ablation (n = 28) or segmental resection (n = 54). After PSM, there were no differences in OS (p = 0.525), CSS (p = 0.487), upper tract RFS (p = 0.147), intravesical RFS (p = 0.989), PFS (p = 0.617), and MFS (p = 0.336) between KSS and RNU. There were no significant differences between ureteroscopic ablation and segmental resection in OS, CSS, intravesical RFS, PFS, and MFS with RNU. Proximal ureteral UTUC had worse OS and CSS outcomes than other tumor locations following segmental resection. Conclusions: In patients with ureteral UTUC, no significant differences in long-term survival outcomes were observed between KSS and RNU. Proximal ureteral UTUC had worse survival outcomes over other tumor locations following segmental resection.

Effect of crystal facets in plasmonic catalysis.

While the role of crystal facets is well known in traditional heterogeneous catalysis, this effect has not yet been thoroughly studied in plasmon-assisted catalysis, where attention has primarily focused on plasmon-derived mechanisms. Here, we investigate plasmon-assisted electrocatalytic CO2 reduction using different shapes of plasmonic Au nanoparticles - nanocube (NC), rhombic dodecahedron (RD), and octahedron (OC) - exposing {100}, {110}, and {111} facets, respectively. Upon plasmon excitation, Au OCs doubled CO Faradaic efficiency (FECO) and tripled CO partial current density (jCO) compared to a dark condition, with NCs also improving under illumination. In contrast, Au RDs maintained consistent performance irrespective of light exposure, suggesting minimal influence of light on the reaction. Temperature experiments ruled out heat as the main factor to explain such differences. Atomistic simulations and electromagnetic modeling revealed higher hot carrier abundance and electric field enhancement on Au OCs and NCs than RDs. These effects now dominate the reaction landscape over the crystal facets, thus shifting the reaction sites when comparing dark and plasmon-activated processes. Plasmon-assisted H2 evolution reaction experiments also support these findings. The dominance of low-coordinated sites over facets in plasmonic catalysis suggests key insights for designing efficient photocatalysts for energy conversion and carbon neutralization.

Deterministic Gradient-Descent Learning of Linear Regressions: Adaptive Algorithms, Convergence Analysis and Noise Compensation.

Weight learning forms a basis for the machine learning and numerous algorithms have been adopted up to date. Most of the algorithms were either developed in the stochastic framework or aimed at minimization of loss or regret functions. Asymptotic convergence of weight learning, vital for good output prediction, was seldom guaranteed for online applications. Since linear regression is the most fundamental component in machine learning, we focus on this model in this paper. Aiming at online applications, a deterministic analysis method is developed based on LaSalle's invariance principle. Convergence conditions are derived for both the first-order and the second-order learning algorithms, without resorting to any stochastic argument. Moreover, the deterministic approach makes it easy to analyze the noise influence. Specifically, adaptive hyperparameters are derived in this framework and their tuning rules disclosed for the compensation of measurement noise. Comparison with four most popular algorithms validates that this approach has a higher learning capability and is quite promising in enhancing the weight learning performance.

Causal Relationship Between Endometriosis and Pelvic Inflammatory Diseases: Mendelian Randomization Study.

Objective: This study explores the causal relationship between endometriosis and pelvic inflammatory diseases (PID). Methods: The study utilized genome-wide association study (GWAS) datasets for endometriosis ("finn-b-N14_ENDOMETRIOSIS") and PID ("finn-b-N14_OTHFEMPELINF"). Subsequently, two-sample Mendelian randomization (MR) analyses were conducted using inverse variance weighting (IVW), Egger regression (MR-Egger), and weighted median (WM) methods. Heterogeneity was evaluated using Cochran's Q test, and in case of detected outliers, they were removed for re-evaluation of MR causality. Results: From the endometriosis GWAS dataset, 33 single nucleotide polymorphisms (SNPs) were selected as instrumental variables. All three methods, IVW (OR = 1.39, P < 1×10-8), MR-Egger (OR = 1.41, P = 0.003), and WM (OR = 1.37, P = 1.16×10-5) confirmed a causal relationship between endometriosis and PID. The association between endometriosis and pelvic inflammation remained unaffected by the exclusion of individual SNPs. Lastly, Cochran's Q test and funnel plots showed no evidence of SNP asymmetry. Conclusion: The results of the MR analysis support a potential causal relationship between endometriosis and an increased risk of PID.

Study on the efficacy and mechanism of treatment of manganese-containing wastewater by pulse-alternating current coagulation.

To assess the effectiveness and underlying mechanism of pulse-alternating current coagulation (PACC) for treating manganese-laden wastewater, we examined the influence of various parameters. Specifically, we investigated the impact of current density, initial pH, initial Mn2+ concentration, electrolyte concentration, and alternating current frequency on the removal efficacy. The removal mechanism was meticulously examined using an adsorption kinetics analysis, Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS), Fourier Transform Infrared Spectrum (FTIR), and X-ray Photoelectron Spectroscopy (XPS). The findings indicated that the concentration of Re(Mn2+) was 99.09% under the specified conditions: j = 2.5 A·m-2, pH0 = 7, c0(Mn2+) = 50 mg·dm-3, f = 500 Hz, c0(NaCl) = 500 mg·dm-3 and t = 40 min. When Re(Mn2+) = 98%, the energy consumption (EEC) was significantly lower for PACC at 1.23 kWh·m-3, compared to 1.52 kWh·m-3 for direct current condensation (DCC). This indicated a reduction in EEC by 19.1% when using PACC over DCC. The adsorption process of Mn2+ by the iron sol adheres to the principles of pseudo-second order kinetics. The primary component of flocs generated in the PACC process is α-FeOOH. The mechanism of Mn2+ removal in the PACC process involved the synthesis of Mn oxides, the formation of metal hydroxide precipitates and adsorption by nano-iron sol. This study provides a theoretical basis and technical support for the application of PACC technology in the field of manganese-containing wastewater treatment.

Development and application of a machine learning-based predictive model for obstructive sleep apnea screening.

Objective: To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF) to provide substantial support for early clinical diagnosis and intervention. Methods: We conducted a retrospective analysis of clinical data from 439 patients who underwent polysomnography at the Affiliated Hospital of Xuzhou Medical University between October 2019 and October 2022. Predictor variables such as demographic information [age, sex, height, weight, body mass index (BMI)], medical history, and Epworth Sleepiness Scale (ESS) were used. Univariate analysis was used to identify variables with significant differences, and the dataset was then divided into training and validation sets in a 4:1 ratio. The training set was established to predict OSA severity grading. The validation set was used to assess model performance using the area under the curve (AUC). Additionally, a separate analysis was conducted, categorizing the normal population as one group and patients with moderate-to-severe OSA as another. The same univariate analysis was applied, and the dataset was divided into training and validation sets in a 4:1 ratio. The training set was used to build a prediction model for screening moderate-to-severe OSA, while the validation set was used to verify the model's performance. Results: Among the four groups, the LightGBM model outperformed others, with the top five feature importance rankings of ESS total score, BMI, sex, hypertension, and gastroesophageal reflux (GERD), where Age, ESS total score and BMI played the most significant roles. In the dichotomous model, RF is the best performer of the five models respectively. The top five ranked feature importance of the best-performing RF models were ESS total score, BMI, GERD, age and Dry mouth, with ESS total score and BMI being particularly pivotal. Conclusion: Machine learning-based prediction models for OSA disease grading and screening prove instrumental in the early identification of patients with moderate-to-severe OSA, revealing pertinent risk factors and facilitating timely interventions to counter pathological changes induced by OSA. Notably, ESS total score and BMI emerge as the most critical features for predicting OSA, emphasizing their significance in clinical assessments. The dataset will be publicly available on my Github.