Semi-Supervised Deep Learning-Based Multi-component Spectral Calibration Modeling for UV-vis and Near-Infrared Spectroscopy without Information Loss.

Spectral analysis is an important method for characterizing and identifying chemical species. However, quantitative spectral analysis of multiple chemical properties in the real world has always been a challenging problem due to the strong correlation, massive noise, and serious information overlapping of the spectral features. Here, we present a new semi-supervised spectral calibration method based on information lossless decoupling of spectral features named NICEM. To realize the separation and extraction of key latent features, the method uses the flow-based model non-linear independent component estimation (NICE) to learn the sample distribution. The spectral data information is transformed into independent latent variables obeying Gaussian distribution by the reversible structure of deep network without information loss, so as to find the essential properties and realize the feature nonlinear decomposition. Moreover, the association between the input latent feature variables and attributes is evaluated by the maximum mutual information coefficient to eliminate the adverse effects of irrelevant information in the latent variable space and mine key information. Since the latent variables are independent in each dimension, the NICEM method is easier to establish an accurate semi-supervised multi-component calibration model even for high overlapping and complex spectral data. The applicability of the proposed spectral modeling method is demonstrated by using three ultraviolet-visible and near-infrared spectral data sets with 15 physical and chemical properties including diesel fuels, corn, and multi-metal ions solution. Results show that the proposed NICEM method has the highest determination coefficient (R2) and significantly improves extrapolation compared with the seven state-of-the-art methods. The proposed method is intuitive because it obviates complex feature engineering and prior knowledge and is a promising spectral calibration tool for quantitative analysis in other spectroscopy applications.

A one-year follow-up study on dynamic changes of leukocyte subsets and virus-specific antibodies of patients with COVID-19 in Sichuan, China.

Background: SARS-CoV-2 infection causes immune response and produces protective antibodies, and these changes may persist after patients discharged from hospital. Methods: This study conducted a one-year follow-up study on patients with COVID-19 to observe the dynamic changes of circulating leukocyte subsets and virus-specific antibodies. Results: A total of 66 patients with COVID-19 and 213 healthy patients with inactivated SARS-CoV-2 vaccination were included. The virus-specific total antibody, IgG and IgM antibody of patients after one year of recovery were higher than those of healthy vaccinated participants (94.13 vs 4.65, 2.67 vs 0.44, 0.09 vs 0.06, respectively) (P < 0.001). Neutrophil count (OR = 1.73, 95% CI: 1.10-2.70, P = 0.016) and neutrophil-to-lymphocyte ratio (OR = 1.59, 95% CI: 1.05-2.41, P = 0.030) at discharge were the influencing factors for the positivity of virus-specific IgG antibody in patients after one year of recovery. The counts of CD4+ and CD8+ T, B and NK cells increased with the time of recovery, and remained basically stable from 9 to 12 months after discharge. After 12 months, the positivity of IgG antibody was 85.3% and IgM was 11.8%, while the virus-specific antibody changed dynamically in patients within one year after discharge. Conclusions: The SARS-CoV-2 specific antibody of recovered patients showed dynamic fluctuation after discharge, while the leukocyte subsets gradually increased and basically stabilized after 9 months.

How to Reduce the Risk of Arteriovenous Fistula Dysfunction by Observing Prepump Arterial Pressure during Hemodialysis: A Multicenter Retrospective Study.

OBJECTIVE: Prepump arterial (Pa) pressure indicates the ease or difficulty with which the blood pump can draw blood from the vascular access (VA) during hemodialysis. Some studies have suggested that the absolute value of the Pa pressure to the extracorporeal blood pump flow (Qb) ratio set on the machine (|Pa/Qb|) can reflect the dysfunction of VA. This study was conducted to explore the impact of arteriovenous fistula (AVF) dysfunction and to explore the clinical reference value of |Pa/Qb|. METHODS: We retrospectively identified adults who underwent hemodialysis at 3 hospitals. Data were acquired from electronic health records. We evaluated the pattern of the association between |Pa/Qb| and AVF dysfunction during 1 year using a Cox proportional hazards regression model with restricted cubic splines. Then, the patients were grouped based on the results, and hazard ratios were compared for different intervals of |Pa/Qb|. RESULTS: A total of 490 patients were analyzed, with an average age of 55 (44, 66) years. There were a total of 85 cases of AVF dysfunction, of which 50 cases were stenosis and 35 cases were thrombosis. There was a U-shaped association between |Pa/Qb| and the risk of AVF dysfunction (p for nonlinearity <0.001). |Pa/Qb| values <0.30 and >0.52 increased the risk of AVF dysfunction. Compared with the group with a |Pa/Qb| value between 0.30 and 0.52, the groups with |Pa/Qb| <0.30 and |Pa/Qb| >0.52 had a 4.04-fold (p = 0.002) and 3.41-fold (p < 0.001) greater risk of AVF dysfunction, respectively. CONCLUSIONS: The appropriate range of |Pa/Qb| is between 0.30 and 0.52. When |Pa/Qb| is <0.30 or >0.52, the patient's AVF function or Qb setting should be reevaluated to prevent subsequent failure.

Simultaneous Determination of Metal Ions in Zinc Sulfate Solution Using UV-Vis Spectrometry and SPSE-XGBoost Method.

Excessive discharge of heavy metal ions will aggravate environment pollution and threaten human health. Thus, it is of significance to real-time detect metal ions and control discharge in the metallurgical wastewater. We developed an accurate and rapid approach based on the singular perturbation spectrum estimator and extreme gradient boosting (SPSE-XGBoost) algorithms to simultaneously determine multi-metal ion concentrations by UV-vis spectrometry. In the approach, the spectral data is expanded by multi-order derivative preprocessing, and then, the sensitive feature bands in each spectrum are extracted by feature importance (VI score) ranking. Subsequently, the SPSE-XGBoost model are trained to combine multi-derivative features and to predict ion concentrations. The experimental results indicate that the developed "Expand-Extract-Combine" strategy can not only overcome problems of background noise and spectral overlapping but also mine the deeper spectrum information by integrating important features. Moreover, the SPSE-XGBoost strategy utilizes the selected feature subset instead of the full-spectrum for calculation, which effectively improves the computing speed. The comparisons of different data processing methods are conducted. It outcomes that the proposed strategy outperforms other routine methods and can profoundly determine the concentrations of zinc, copper, cobalt, and nickel with the lowest RMSEP. Therefore, our developed approach can be implemented as a promising mean for real-time and on-line determination of multi-metal ion concentrations in zinc hydrometallurgy.

[Difference of Liver Enzymes in Different Metabolism States of Chronic Hepatitis B].

OBJECTIVE: To analyze the difference of liver enzymes in different metabolism state groups of chronic hepatitis B (CHB). METHODS: We use prospective cross-sectional study to analyze the difference of liver enzymes in different metabolism state groups in 110 cases of CHB, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) and glutamyl transferase (GGT). RESULTS: Regardless of the presence or absence of fatty liver, the levels of ALP and GGT were increased along with the deterioration of glucose metabolism (P<0.05).The levels of ALP and GGT in the presence of fatty liver group were higher than those in the absence of fatty liver group (P<0.05). The levels of AST, ALP and GGT showed the trend of increasing along with the increase of HOMA-IR and the decrease of HOMA-ß. There was no difference of liver enzymes among the groups with or without other metabolism disorder (P>0.05). CONCLUSION: In CHB, abnormal glucose metabolism and fatty liver can lead to the increase of ALP and GGT. The increase of HOMA-IR and the decrease of HOMA-ß may lead to the increase of AST, ALP and GGT. Other metabolism disorder did not show any effect on the level of liver enzymes.

Calibration-free self-absorption model for measuring nitric oxide concentration in a pulsed corona discharge.

The effect of self-absorption on emission intensity distributions can be used for species concentration measurements. A calculation model is developed based on the Beer-Lambert law to quantify this effect. And then, a calibration-free measurement method is proposed on the basis of this model by establishing the relationship between gas concentration and absorption strength. The effect of collision parameters and rotational temperature on the method is also discussed. The proposed method is verified by investigating the nitric oxide emission bands (A²Σ⁺→X²∏) that are generated by a pulsed corona discharge at various gas concentrations. Experiment results coincide well with the expectations, thus confirming the precision and accuracy of the proposed measurement method.

Dynamic Characteristics of Lymphocyte Subsets and Their Predictive Value for Disease Progression and Prognosis in Primary Infection and Unvaccinated COVID-19 Patients.

Aim: Our cohort study aimed to investigate the dynamic changes of lymphocyte subsets and their abilities to predict disease severity and prognosis in primary infection and unvaccinated COVID-19 patients. Methods: A total of 773 cases, including 718 primary infection and unvaccinated COVID-19 patients and 55 controls. COVID-19 patients were assigned to severe and nonsevere groups according to disease severity, as well as survival and death groups according to prognosis. Serum samples were collected to measure the numbers of total lymphocytes and lymphocyte subsets. The differences among different severity groups were analyzed. Spearman correlation was performed to assess associations between lymphocyte subsets and disease severity and prognosis. Meanwhile, receiver operating characteristic (ROC) curves were also analyzed to find optimal cutoff points. Results: At admission, the severe group demonstrated significantly lower total lymphocyte counts and percentages, CD3+ and CD3+CD4+ T cell counts and percentages, CD3+CD8+ T cell counts, CD19+ B cell counts and CD56+ NK cell counts and percentages than the nonsevere group. Meanwhile, compared with the survival group, the death group also had lower total lymphocyte counts and percentages, CD3+, CD3+CD4+ and CD3+CD8+ T cell counts. Additionally, differences in these parameters were also noticed within four weeks after admission. Furthermore, Spearman analysis reported that disease severity was negatively correlated with lymphocyte counts and percentages, CD3+, CD3+CD4+ and CD3+CD8+ T cell counts, CD3+ and CD3+CD4+ T cell percentages (r=-0.166, -0.179, -0.173, -0.186, -0.127, -0.117, -0.149, respectively)(all P<0.05). The prognosis of death was also negatively correlated with total lymphocyte counts and percentages, CD3+, CD3+CD4+ and CD3+CD8+ T cell counts (r=-0.125, -0.121, -0.123, -0.123, -0.091, respectively)(all P<0.05). Conclusion: In primary infection and unvaccinated COVID-19 patients total lymphocytes and T cell, B cell and NK cell subsets at COVID-19 onset play valuable roles in predicting disease severity and prognosis. Clinical Trial Registry: Chinese Clinical Trial Register ChiCTR2000034563.

Characteristics of acidic hydrothermal treatment for disintegration of spiramycin fermentation residue and degradation of residual antibiotics.

To recycle the nutrients in spiramycin (SPM) fermentation residue (SFR) through biological methods, acid hydrothermal treatment (AHT) was employed as pretreatment to enhance SFR biodegradability. The results showed that the degradation rate of residual SPM in SFR reached 100% after 120 min at 100℃ and 0.30 M acid with a 30.5% and 89.7% increase in proteins and polysaccharides, respectively. The SPM degradation was faster at higher acidity and temperature. However, elevated SPM concentration and the presence of protein, humic acid, and polysaccharide inhibited SPM degradation. The disintegration of SFR was evidenced by changes in its microstructure and could be predicted through the release of dissolved organic matter. Eight major SPM intermediates were identified with lower mutagenicity and antibacterial activity testing against Staphylococcus aureus. These results demonstrate that AHT not only disintegrates SFR but also degrades the residual SPM antibiotics, which implies the possibility for practical applications.

Effects of Two Different Straw Pellets on Yak Growth Performance and Ruminal Microbiota during Cold Season.

The Tianzhu white yaks (Bos grunniens) live on the Qinghai-Tibet Plateau. During winter, a lack of resources and low nutritional levels seriously affect their growth performance. In this study, we aimed to explore the effect of supplementation straw pellets on the growth performance and ruminal microbiota of yaks. Overall, at 6 (6M, n = 24), 18 (18M, n = 26), 30 (30M, n = 20), 42 (42M, n = 24), and 54 (54M, n = 22) month old Tianzhu white yaks were selected (total n = 116) and divided into the mixed straw + grazing (MSG), corn straw + grazing (CSG), and the grazing control (G) groups according to age and gender. Their growth performance was measured as per different dietary treatments. The rumen microbial community structure and levels of VFAs were analyzed from the 6M, 30M, and 54M male yaks from each group. The supplementary diets led to an increase in the ADG, which was the highest in the MSG group. The MSG group exhibited the highest level of acetate and total VFAs (TVFAs) among the three groups (p < 0.05). In addition, the 16S rRNA sequencing results proved that the microbial composition was dominated by the members of Firmicutes and Bacteroidetes. Christensenellaceae R-7 group was significantly abundant in the CSG and MSG groups compared to the G group (p < 0.05). Principal coordinate analysis (PCoA) revealed that the bacterial community structure of rumen in the MSG and CSG groups was considerably different from that in the G group; 6M samples exhibited different rumen microbial diversity compared with the other samples. Correlation analysis revealed that Christensenellaceae_R-7_group was positively correlated with the levels of acetate, TVFAs, and ADG. These results demonstrated that mixed straw pellets improved the growth performance of yaks, increased the abundance of Christensenellaceae R-7_group involved in cellulose degradation in the rumen, and produced large amounts of VFAs, which were absorbed by yaks, thus increasing their ADG. This study provides new insights into the effects of straw pellet supplementation on the changes in the rumen microbiota and growth performance of yaks.

Glucose metabolism continuous deteriorating in male patients with human immunodeficiency virus accepted antiretroviral therapy for 156 weeks.

BACKGROUND: The dynamic characteristics of glucose metabolism and its risk factors in patients living with human immunodeficiency virus (PLWH) who accepted primary treatment with the efavirenz (EFV) plus lamivudine (3TC) plus tenofovir (TDF) (EFV + 3TC + TDF) regimen are unclear and warrant investigation. AIM: To study the long-term dynamic characteristics of glucose metabolism and its contributing factors in male PLWH who accepted primary treatment with the EFV + 3TC + TDF regimen for 156 wk. METHODS: This study was designed using a follow-up design. Sixty-one male treatment-naive PLWH, including 50 cases with normal glucose tolerance and 11 cases with prediabetes, were treated with the EFV + 3TC + TDF regimen for 156 wk. The glucose metabolism dynamic characteristics, the main risk factors and the differences among the three CD4+ count groups were analyzed. RESULTS: In treatment-naive male PLWH, regardless of whether glucose metabolism disorder was present at baseline, who accepted treatment with the EFV + 3TC + TDF regimen for 156 wk, a continuous increase in the fasting plasma glucose (FPG) level, the rate of impaired fasting glucose (IFG) and the glycosylated hemoglobin (HbA1c) level were found. These changes were not due to insulin resistance but rather to significantly reduced islet ß cell function, according to the homeostasis model assessment of ß cell function (HOMA-ß). Moreover, the lower the baseline CD4+ T-cell count was, the higher the FPG level and the lower the HOMA-ß value. Furthermore, the main risk factors for the FPG levels were the CD3+CD8+ cell count and viral load (VL), and the factors contributing to the HOMA-ß values were the alanine aminotransferase level, VL and CD3+CD8+ cell count. CONCLUSION: These findings provide guidance to clinicians who are monitoring FPG levels closely and are concerned about IFG and decreased islet ß cell function during antiretroviral therapy with the EFV + 3TC + TDF regimen for long-term application.

Impact of diabetes itself and glycemic control status on tuberculosis.

Objectives: To explore the impact of diabetes itself and glycemic control status on tuberculosis (TB). Methods: A total of 3393 patients with TB and diabetes mellitus (DM) who were hospitalized in the Public Health Clinical Center of Chengdu from January 1, 2019, to December 31, 2021, were retrospectively included and divided into three groups according to baseline glycemic control status: two groups according to glycemic status at discharge, two groups according to cavity occurrence, three groups according to sputum results, and three groups according to lesion location. The influencing factors and the differences in cavity occurrence, sputum positivity and lesion location among different glycemic control groups or between different glycemic status groups were analyzed. Results: In this TB with DM cohort, most of the subjects were male, with a male to female ratio of 4.54:1, most of them were 45-59 years old, with an average age of 57.44 ± 13.22 years old. Among them, 16.8% (569/3393) had cavities, 52.2% (1770/3393) were sputum positive, 30.4% (1030/3393) had simple intrapulmonary lesions, 68.1% (2311/3393) had both intra and extrapulmonary lesions, only 15.8% (537/3393) had good glycemic control,16.0% (542/3393) and 68.2% (2314/3393) had fair and poor glycemic control, respectively. Compared with the non-cavity group, the sputum-negative group and the extrapulmonary lesion group, the cavity group, sputum-positive group, intrapulmonary lesion group and the intra and extrapulmonary lesion group all had higher fasting plasma glucose (FPG) and glycosylated hemoglobin A 1c (HbA1c) and lower good glycemic control rates at admission (all P<0.001). Another aspect, compared with the good glycemic control group, the poor glycemic control group had a higher cavity occurrence rate, sputum positive rate, and greater proportion of intrapulmonary lesions. Moreover, FPG and HbA1c levels and poor glycemic control were significantly positively correlated with cavity occurrence, sputum positivity, and intrapulmonary lesions and were the main risk factors for TB disease progression. On the other hand, cavity occurrence, sputum positivity, and intrapulmonary lesions were also main risk factors for hyperglycemia and poor glycemic control. Conclusion: Diabetes itself and glycemic control status could impact TB disease. Good glycemic control throughout the whole process is necessary for patients with TB and DM to reduce cavity occurrence and promote sputum negative conversion and lesion absorption.

Online rapid total nitrogen detection method based on UV spectrum and spatial interval permutation combination population analysis.

Rapidly and accurately detect the total nitrogen (TN) concentration is enormously important for surface water protection considering the critical role it plays in reflecting the eutrophication of surface water. However, traditional TN detection methods have to experience a tedious oxygen digestion process, which tremendously limits the detection speed of TN. To solve this problem, we propose a novel online rapid TN detection method. The transformations of nitrogenous substances during the oxidative digestion process are observed by using ultraviolet (UV) spectroscopy and the concentration of TN can be predicted by only using the variation of spectrum in the early oxygen digestion process. To select the most informative variables hidden in the collected three-dimension spectrum, a new wavelength selection algorithm called spatial interval permutation combination population analysis (siPCPA) is proposed, which considers the spatial-temporal relationships among each variable in the spectrum. By using the real surface water samples collected from Houhu Lake, Changsha, China, the effectiveness of our proposed new detection and selection methods are verified and compared with other state-of-the-art methods. As a result, the practical application experiment shows that our methods can determine the concentration of TN in 5 min with a relative error of less than 5%.

iPCPA: Interval permutation combination population analysis for spectral wavelength selection.

As one of the most important preprocessing procedures in spectral detection, wavelength selection approaches play an irreplaceable role in reducing the model overfitting and prediction errors. In this paper, we propose a two-step wavelength selection method called interval permutation combination population analysis (iPCPA), which improves the selective performance by combining three different wavelength selection algorithms. First, interval partial least squares (iPLS) is used as the rough selection step to efficiently exclude the uninformative variables in the spectrum, which reduces the variable space and ensures that the following selection step can focus on selecting informative variables. Then, permutation combination population analysis (PCPA) is proposed, which introduces the core idea of permutation analysis into the variable combination population analysis (VCPA) and hence improves its ability in evaluating the importance of informative variables. Six state-of-the-art wavelength selection methods are used to compare with iPCPA and their performances are tested by using three real spectral datasets: corn, beer, and soil datasets. The final experimental results prove that iPCPA has the best predictive abilities, combined with a good selective performance.

Follow-Up Study of the Cardiopulmonary and Psychological Outcomes of COVID-19 Survivors Six Months After Discharge in Sichuan, China.

PURPOSE: Some studies have shown that patients with coronavirus disease 2019 (COVID-19) still have sequelae after discharge. However, little is known about the long-term physical and psychological sequelae of patients, especially factors that influenced the prognosis. PATIENTS AND METHODS: Patients with COVID-19 were followed up for 6 months. The psychological status of patients was evaluated by DASS-21 questionnaire, while physical functions were determined using medical history, laboratory examination, thoracic computed tomography (CT), and echocardiography. RESULTS: Fifty patients infected with COVID-19 were enrolled, and 11 (22%) patients still showed symptoms related to COVID-19. The mean contents (cells/ul) of CD3+ cells, CD4+ and CD8+ T, B lymphocytes and NK cells of the survivors elevated significantly after 6-month discharge (P < 0.001). The frequency of ground-glass opacities and consolidations decreased from 90% to 42% (P < 0.001), and 54% to 20%, (P = 0.001), respectively, while the changes of reticulation and bronchiectasis were insignificant (P > 0.05). The frequency of left ventricular diastolic dysfunction decreased from 40% to 15% (P = 0.002). Depression was observed in 5 (12.5%) participants, stress in 3 (7.5%), anxiety in 6 (15%), and among them 1 (2.5%) showed extremely severe anxiety. Covariation analysis elucidated age might be a risk factor (OR: 1.09, 95% CI: 1.01-1.18, P = 0.038), while NK cell was a good prognostic factor for pulmonary recovery. The comorbidities were significantly positive correlated with persist pulmonary damage (r = 0.33, P = 0.020). Compared with patients with antiviral therapy, patients without antiviral therapy had higher anxiety score (3 vs 0, P = 0.033). CONCLUSION: After 6-month discharge, the persisting cardiopulmonary damage was observed in recovery patients, and psychological implications should not be ignored. Age, comorbidities, NK cell and antiviral therapy might be associated with the prognosis of COVID-19.

Overall reduced lymphocyte especially T and B subsets closely related to the poor prognosis and the disease severity in severe patients with COVID-19 and diabetes mellitus.

BACKGROUND: A dysregulated host immune response is common in patients with COVID-19. AIM: In this study, we aimed to define the characteristics of lymphocyte subsets and their relationship with disease progression in COVID-19 patients with or without diabetes mellitus (DM). METHODS: The baseline peripheral lymphocyte subsets were compared between 55 healthy controls and 95 patients with confirmed COVID-19, and between severe and non-severe COVID-19 patients with or without DM. RESULTS: The prevalence of DM in the COVID-19 group was 20%, and patients with severe COVID-19 had a higher prevalence of DM than those with non-severe disease (P = 0.006). Moreover, a significantly poor prognosis and a higher rate of severity were found in those with DM relative to those without DM (P = 0.001, 0.003). Generally, all lymphocytes and subsets of lymphocytes, especially B and T cells, were significant reduced in COVID-19 patients, particularly in those with DM. Patients with severe COVID-19 and DM had the lowest lymphocyte counts compared with those with severe COVID-19 without DM, and those with non-severe COVID-19 with or without DM. Partially decreased lymphocyte subsets, age and DM were closely related to disease progression and prognosis. CONCLUSIONS: These findings provide a reference for clinicians that immunomodulatory treatment may improve disease progression and prognosis of COVID-19 patients, especially those with severe disease with DM. Trial registration Chinese Clinical Trial Register ChiCTR2000034563.

Lattice Boltzmann simulations of thermal flows beyond the Boussinesq and ideal-gas approximations.

In this work, the recent lattice Boltzmann model with self-tuning equation of state (EOS) [R. Huang et al., J. Comput. Phys. 392, 227 (2019)]JCTPAH0021-999110.1016/j.jcp.2019.04.044 is improved in three aspects to simulate the thermal flows beyond the Boussinesq and ideal-gas approximations. First, an improved scheme is proposed to eliminate the additional cubic terms of velocity, which can significantly improve the numerical accuracy. Second, a local scheme is proposed to calculate the density gradient instead of the conventional finite-difference scheme. Third, a scaling factor is introduced into the lattice sound speed, which can be adjusted to effectively enhance numerical stability. The thermal Couette flow of a nonattracting rigid-sphere fluid, which is described by the Carnahan-Starling EOS, is first simulated, and the better performance of the present improvements on the numerical accuracy and stability is demonstrated. As a further application, the turbulent Rayleigh-Bénard convection in a supercritical fluid slightly above its critical point, which is described by the van der Waals EOS, is successfully simulated by the present lattice Boltzmann model. The piston effect of the supercritical fluid is successfully captured, which induces a fast and homogeneous increase of the temperature in the bulk region, and the time evolution from the initiation of heating to the final turbulent state is analyzed in detail and divided into five stages.

Lymphocyte subsets with the lowest decline at baseline and the slow lowest rise during recovery in COVID-19 critical illness patients with diabetes mellitus.

BACKGROUND: Host dysregulation of immune response was highly involved in the pathological process of Coronavirus disease 2019 (COVID-19), especially COVID-19 severe cases with DM. AIM: In this study we aimed at the dynamic change of peripheral lymphocyte and subsets during COVID-19 covery. METHODS: The peripheral lymphocyte and subsets of 95 confirmed cases with COVID-19 from baseline to four weeks were compared between critical illness and non-critical illness cases with or without DM. RESULTS: The dynamic characteristics of lymphocyte and subsets in COVID-19 patients was that it reduced significantly at one week, rapidly elevated to the peak at two weeks after onset, then gradually declined during recovery. The COVID-19 critical illness patients with DM had the lowest decline at one week and the slow lowest rise at two weeks after onset, while COVID-19 non-critical illness patients with DM had the rapid highest rise at two weeks after onset, both of them had similar lymphocyte and subsets at five weeks after onset and lower than those patients without DM. CONCLUSIONS: These findings provide a reference for clinicians that for COVID-19 patients with DM and the lowest decline of lymphocyte and subsets, immunomodulatory therapy as soon as possible might avoid or slow down disease progression; moreover for COVID-19 critical illness patients with or without DM and non-critical illness patients with DM, continuous immunomodulatory therapy in later stages of disease might speed up virus clearance, shorten hospital stay, improve disease prognosis in COVID-19 critical illness patients with DM.

It is time to implement prepump arterial pressure monitoring during hemodialysis: A retrospective multicenter study.

INTRODUCTION: Prepump arterial pressure (Pa) indicates the ease or difficulty with which the blood pump can draw blood from vascular access (inflow) during hemodialysis. The absolute prepump arterial pressure to blood pump speed (Qb) ratio (|Pa/Qb|) may reflect the dysfunction of other vascular accesses. There is no consensus on the impact of |Pa/Qb| on arteriovenous fistula dysfunction. This study aimed to demonstrate the impact of |Pa/Qb| on arteriovenous fistula dysfunction. METHODS: In this retrospective analysis, 490 hemodialysis patients with arteriovenous fistula from three hospitals were enrolled. Data were extracted from the I-Diapro database and hospital case systems. The absolute values for |Pa/Qb| and other data collected in the first month of enrollment were used to predict arteriovenous fistula dysfunction and determine the |Pa/Qb| cutoff value. Based on this value, patients were grouped, and 1-year arteriovenous fistula function was analyzed. Patients were followed until arteriovenous fistula dysfunction, until access type replacement, or for 12 months. RESULTS: The area under the receiver operating characteristic curve for fistula dysfunction over 1 year was 0.65, with an optimal |Pa/Qb| value, sensitivity, and specificity of 0.499, 60.7%, and 72.6%, respectively. |Pa/Qb| > 0.499 was associated with earlier intervention (317.37 ± 7.68 vs 345.96 ± 3.64 days), lower survival (p < 0.001), and a 3.26-fold greater risk of arteriovenous fistula dysfunction (p < 0.001) than |Pa/Qb| ⩽ 0.499. CONCLUSIONS: |Pa/Qb| was an independent risk factor for arteriovenous fistula dysfunction. Nurses should emphasize |Pa/Qb| monitoring and properly set blood pump speed according to this ratio to protect arteriovenous fistula function. |Pa/Qb| > 0.499 might be a predictive measure of arteriovenous fistula dysfunction.

Effect of the supports on catalytic activity of Pd catalysts for liquid-phase hydrodechlorination/hydrogenation reaction.

Carbon nanotubes (CNTs), activated carbon (AC), graphene, and aluminum oxide (Al2O3) supported 5% Pd catalysts were prepared by the conventional impregnation method, and catalytic activity was tested in the hydrogenation of 4-chlorophenol (4-CP) and nitrobenzene (NB) under ambient conditions (313 K and atmospheric pressure). It was found that catalytic activity was greatly affected by the supports. Moreover, Pd/CNTs catalyst exhibited much higher catalytic activity than the other three supported Pd catalysts. The mechanism of this phenomenon was studied through catalyst characterization (ICP-MS, Brunauer-Emmett-Teller [BET], TEM, and SEM). It was found that the mean particle size of Pd nanoparticles for Pd/CNTs (4.3 nm) was smaller than that for Pd/AC (6.9 nm), Pd/Al2O3 (5.0 nm), and Pd/graphene (5.2 nm). Moreover, the actual loading amounts of Pd and BET surface areas were not the main reasons for the different catalytic activity of the four supported Pd catalysts. Above all, the smaller Pd particles of Pd/CNTs enabled the Pd/CNTs catalyst to exhibit much higher catalytic activity for the hydrogenation reactions.

Rapid and effective removal of As(III) and As(V) using spore@Ti4+ microspheres.

Removing arsenic from aquatic environments has become an urgent problem worldwide. In this study, Ti4+- loaded bacterial spore were adopted as a novel adsorbent (spore@Ti4+ microspheres) for the adsorption efficient removal of arsenite (As(III)) and arsenate (As(V)). The developed adsorbents were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier transform infrared spectra (FTIR) and X-ray photoelectron spectroscopy (XPS). Results indicated that the adsorption kinetics was well described by a pseudo-second-order kinetic model, and the adsorption process rapidly achieved equilibrium within 15 min at pH 7.0. The adsorption mechanism was also investigated. The maximum adsorption capacities for As(III) and As(V) were 97.26 mg g-1 and 137.01 mg g-1, respectively, based on the isothermal studies. These properties suggest that spore@Ti4+ microspheres can be potentially applied in water treatment.