Table_1_Relationship between immune nutrition index and all-cause and cause-specific mortality in U.S. adults with chronic kidney disease.docx

ObjectiveThe available evidence regarding the association of immune nutrition status with chronic kidney disease (CKD) is limited. Thus, the present study examined whether immunonutrition indices were associated with renal function and mortality among CKD individuals.Research design and methodsThis study enrolled 6,099 U.S. adults with CKD from the NHANES 2005–2018 database. Participants were matched with National Death Index records until 31 December 2019 to determine mortality outcomes. The time-dependent receiver operating characteristic was utilized to identify the most effective index among the prognostic nutritional index (PNI), system inflammation score (SIS), Naples prognostic score (NPS), and controlling nutritional status (CONUT) for predicting mortality. Cox regression models were employed to evaluate the associations of immunonutrition indices with mortality in participants with CKD.ResultsThe PNI exhibited the strongest predictive power among the four indices evaluated and the restricted cubic spline analysis revealed a cutoff value of 51 for the PNI in predicting mortality. During a median follow-up of 72 months (39–115 months), a total of 1,762 (weighted 24.26%) CKD participants died from all causes. The Kaplan–Meier curve demonstrated a reduced risk of death for the subjects with a higher PNI compared to those in the lower group. Besides, after adjusting for multiple potential confounders, a higher PNI remained an independent predictor for lower risks of all-cause mortality (HR 0.80, 95%CI: 0.71–0.91, p ConclusionIn CKD, a higher PNI level was significantly associated with lower mortality from all causes and CVD. Thus, the clinical utility of this immunonutrition indicator may facilitate risk stratification and prevent premature death among patients with CKD.</p

Characterization of a Chloride-Activated Surface Complex and Corresponding Enhancement Mechanism by SERS Saturation Effect

Chemical enhancement in surface-enhanced Raman scattering (SERS) may involve the presence of s charge-transfer (CT) complex either by direct binding (covalent) to the metal or by indirect binding with the assistance of an electrolyte ion. The electrolyte (e.g., NaCl, MgSO₄) is very necessary for both direct binding and indirect binding. For the direct binding complex, the electrolyte functions as aggregation agents to create hot spots, while for the indirect binding complex, the electrolyte is used to not only assist the formation of the CT complex but also create hot spots by aggregating nanoparticles. Thus, it is difficult to identify the types of complexes by direct observation. In this article, the types of CT complexes can be distinguished via simply observing the change of saturation point of SERS intensity. The saturation point for indirect binding complex can easily be shifted to higher concentration by simply increasing the concentration of chloride, but the saturation point for the direct binding complex is almost unchanged. Correspondingly, the type of chemical enhancement can be studied further after the complexes are confirmed. Thus, this new method is a very simple and effective way to characterize the types of CT complexes and chemical enhancement

sj-csv-5-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-csv-5-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

sj-csv-9-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-csv-9-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

sj-csv-2-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-csv-2-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

sj-ipynb-6-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-ipynb-6-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

sj-csv-4-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-csv-4-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

sj-ipynb-8-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-ipynb-8-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p

Well-Defined Phase-Controlled Cobalt Phosphide Nanoparticles Encapsulated in Nitrogen-Doped Graphitized Carbon Shell with Enhanced Electrocatalytic Activity for Hydrogen Evolution Reaction at All-pH

Rational design and development of highly active, low-cost, and stable nonprecious metal electrocatalysts for hydrogen evolution reaction (HER) is extremely critical for making the water splitting process more economical and energy-saving. Herein, phase-controlled cobalt phosphide nanoparticles encapsulated in a nitrogen-doped graphitized carbon shell (termed CoxP@NC) were prepared by hydrogen reduction of organic–inorganic cobalt phosphonate hybrid materials with different Co/P molar ratios. Compared with the synthesized pure-phase CoP@NC and Co2P@NC, the hybrid-phase CoP/Co2P@NC exhibits enhanced HER activity at all-pH values, affording low overpotentials of 126 mV (0.5 M H2SO4, pH = 0), 198 mV (1.0 M KOH, pH = 14), and 459 mV (1.0 M PBS, pH = 7) to achieve a current density of 10 mA cm–2. The high activity is ascribed to the doping of the N atom, enough accessible electrocatalytic active boundary sites, and synergistic interaction among the components, especially the electronic effect of CoP and Co2P. Additionally, the unique core–shell structure of CoP/Co2P@NC efficiently prevents the agglomeration and corrosion of metallic cores during the HER and consequently endows it high stability and durability. This study not only offers us an efficient electrocatalyst for HER at all-pH but also opens a novel strategy to synthesize core–shell catalysts for various applications

sj-csv-3-asp-10.1177_00037028231212941 - Supplemental material for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network

Supplemental material, sj-csv-3-asp-10.1177_00037028231212941 for An Iterative Curve-Fitting Baseline Correction Method for Raman Spectra Driven by Neural Network by Sicen Dong, Yuping Liu, Hanxiang Yu, Yuqing Wang and Junchi Wu in Applied Spectroscopy</p