Rural Hospitals Experienced More Patient Volume Variability Than Urban Hospitals During The COVID-19 Pandemic, 2020-21.

Fluctuations in patient volume during the COVID-19 pandemic may have been particularly concerning for rural hospitals. We examined hospital discharge data from the Healthcare Cost and Utilization Project State Inpatient Databases to compare data from the COVID-19 pandemic period (March 8, 2020-December 31, 2021) with data from the prepandemic period (January 1, 2017-March 7, 2020). Changes in average daily medical volume at rural hospitals showed a dose-response relationship with community COVID-19 burden, ranging from a 13.2 percent decrease in patient volume in periods of low transmission to a 16.5 percent increase in volume in periods of high transmission. Overall, about 35 percent of rural hospitals experienced fluctuations exceeding 20 percent (in either direction) in average daily total volume, in contrast to only 13 percent of urban hospitals experiencing similar magnitudes of changes. Rural hospitals with a large change in average daily volume were more likely to be smaller, government-owned, and critical access hospitals and to have significantly lower operating margins. Our findings suggest that rural hospitals may have been more vulnerable operationally and financially to volume shifts during the pandemic, which warrants attention because of the potential impact on these hospitals' long-term sustainability.

Broad/narrowband switchable terahertz absorber based on Dirac semimetal and strontium titanate for temperature sensing.

A broadband and narrowband switchable terahertz (THz) absorber based on a bulk Dirac semimetal (BDS) and strontium titanate (STO) is proposed. Narrowband and broadband absorption can be switched by adjusting the Fermi level of the BDS. When the Fermi level of the BDS is 100 meV, the device is an absorber with three narrowband absorption peaks. The frequencies are 0.44, 0.86, and 1.96 THz, respectively, when the temperature of STO is 250 K. By adjusting the temperature of STO from 250 to 500 K, the blue shifts of the frequencies are approximately 0.14, 0.32, and 0.60 THz, respectively. The sensitivities of the three absorption peaks are 0.56, 1.27, and 2.38 GHz/K, respectively. When the Fermi level of the BDS is adjusted from 100 to 30 meV, the device can be switched to a broadband absorber with a bandwidth of 0.70 THz. By adjusting the temperature of STO from 250 to 500 K, the central frequency shifts from 1.40 to 1.79 THz, and the bandwidth broadens from 0.70 to 0.96 THz. The sensitivity of the central frequency is 1.57 GHz/K. The absorber also has a wide range of potential applications in multifunctional tunable devices, such as temperature sensors, stealth equipment, and filters.

Mortality for Time-Sensitive Conditions at Urban vs Rural Hospitals During the COVID-19 Pandemic.

Importance: COVID-19 pandemic-related disruptions to the health care system may have resulted in increased mortality for patients with time-sensitive conditions. Objective: To examine whether in-hospital mortality in hospitalizations not related to COVID-19 (non-COVID-19 stays) for time-sensitive conditions changed during the pandemic and how it varied by hospital urban vs rural location. Design, Setting, and Participants: This cohort study was an interrupted time-series analysis to assess in-hospital mortality during the COVID-19 pandemic (March 8, 2020, to December 31, 2021) compared with the prepandemic period (January 1, 2017, to March 7, 2020) overall, by month, and by community COVID-19 transmission level for adult discharges from 3813 US hospitals in the State Inpatient Databases for the Healthcare Cost and Utilization Project. Exposure: The COVID-19 pandemic. Main Outcomes and Measures: The main outcome measure was in-hospital mortality among non-COVID-19 stays for 6 time-sensitive medical conditions: acute myocardial infarction, hip fracture, gastrointestinal hemorrhage, pneumonia, sepsis, and stroke. Entropy weights were used to align patient characteristics in the 2 time periods by age, sex, and comorbidities. Results: There were 18 601 925 hospitalizations; 50.3% of patients were male, 38.5% were aged 18 to 64 years, 45.0% were aged 65 to 84 years, and 16.4% were 85 years or older for the selected time-sensitive medical conditions from 2017 through 2021. The odds of in-hospital mortality for sepsis increased 27% from the prepandemic to the pandemic periods at urban hospitals (odds ratio [OR], 1.27; 95% CI, 1.25-1.29) and 35% at rural hospitals (OR, 1.35; 95% CI, 1.30-1.40). In-hospital mortality for pneumonia had similar increases at urban (OR, 1.48; 95% CI, 1.42-1.54) and rural (OR, 1.46; 95% CI, 1.36-1.57) hospitals. Increases in mortality for these 2 conditions showed a dose-response association with the community COVID-19 level (low vs high COVID-19 burden) for both rural (sepsis: 22% vs 54%; pneumonia: 30% vs 66%) and urban (sepsis: 16% vs 28%; pneumonia: 34% vs 61%) hospitals. The odds of mortality for acute myocardial infarction increased 9% (OR, 1.09; 95% CI, 1.06-1.12) at urban hospitals and was responsive to the community COVID-19 level. There were significant increases in mortality for hip fracture at rural hospitals (OR, 1.32; 95% CI, 1.14-1.53) and for gastrointestinal hemorrhage at urban hospitals (OR, 1.15; 95% CI, 1.09-1.21). No significant change was found in mortality for stroke overall. Conclusions and Relevance: In this cohort study, in-hospital mortality for time-sensitive conditions increased during the COVID-19 pandemic. Mobilizing strategies tailored to the different needs of urban and rural hospitals may help reduce the likelihood of excess deaths during future public health crises.

Medicare Advantage in rural areas: implications for hospital sustainability.

OBJECTIVES: A growing number of Medicare beneficiaries in rural areas are enrolled in Medicare Advantage plans, which negotiate hospital reimbursement. This study examined the association between Medicare Advantage penetration levels in rural areas and hospital financial distress and closure. STUDY DESIGN: This retrospective cohort study followed rural general acute care hospitals open in 2008 through 2019 or until closure using Healthcare Cost and Utilization Project State Inpatient Databases for 14 states. METHODS: The primary independent variables were the percentage of Medicare Advantage stays out of total Medicare stays at the hospital and the percentage of Medicare Advantage beneficiaries out of total beneficiaries in the hospital's county. Financial distress was defined using the Altman Z score, where values less than or equal to 1.1 indicate financial distress and values greater than 2.8 indicate stability. The Z score was examined as a continuous outcome in hospital and county fixed-effects models. Risk of closure was examined using Cox proportional hazard models adjusted for hospital and market factors. RESULTS: Rural hospital Medicare Advantage penetration grew from 6.5% in 2008 to 20.6% in 2019. A 1-percentage point increase in hospital penetration was associated with an increase in financial stability of 0.04 units on the Altman Z score (95% CI, 0.00-0.08; P = .03) and a 4% reduction in risk of closure (HR, 0.96; 95% CI, 0.92-1.00; P = .04). Results were consistent when measuring Medicare Advantage penetration at the county level. CONCLUSIONS: Our findings counter the notion that Medicare Advantage plans financially hurt rural hospitals because they pay less generously than traditional Medicare.

A real-world study and network pharmacology analysis of EGFR-TKIs combined with ZLJT to delay drug resistance in advanced lung adenocarcinoma.

OBJECTIVE: This study aimed to explore the efficacy and safety of combining epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) with ZiLongJin Tablet (ZLJT) in delaying acquired resistance in advanced EGFR-mutant lung adenocarcinoma (LUAD) patients. Furthermore, we employed network pharmacology and molecular docking techniques to investigate the underlying mechanisms. METHODS: A retrospective comparative study was conducted on stage IIIc/IV LUAD patients treated with EGFR-TKIs alone or in combination with ZLJT at the Second Affiliated Hospital of the Air Force Medical University between January 1, 2017, and May 1, 2023. The study evaluated the onset of TKI resistance, adverse reaction rates, safety indicators (such as aspartate aminotransferase, alanine aminotransferase, and creatinine), and inflammatory markers (neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio) to investigate the impact of EGFR-TKI combined with ZLJT on acquired resistance and prognostic indicators. Additionally, we utilized the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine, PubChem, UniProt, and Swiss Target Prediction databases to identify the active ingredients and targets of ZLJT. We obtained differentially expressed genes related to EGFR-TKI sensitivity and resistance from the Gene Expression Omnibus database using the GSE34228 dataset, which included sensitive (n = 26) and resistant (n = 26) PC9 cell lines. The "limma" package in R software was employed to detect DEGs. Based on this, we constructed a protein‒protein interaction network, performed gene ontology and KEGG enrichment analyses, and conducted pathway network analysis to elucidate the correlation between the active ingredients in ZLJT and signaling pathways. Finally, molecular docking was performed using AutoDockVina, PYMOL 2.2.0, and Discovery Studio Client v19.1.0 software to simulate spatial and energy matching during the recognition process between predicted targets and their corresponding compounds. RESULTS: (1) A total of 89 patients were included, with 40 patients in the EGFR-TKI combined with ZLJT group (combination group) and 49 patients in the EGFR-TKI alone group (monotherapy group). The baseline characteristics of the two groups were comparable. There was a significant difference in the onset of resistance between the combination group and the monotherapy group (P < 0.01). Compared to the monotherapy group, the combination group showed a prolongation of 3.27 months in delayed acquired resistance. There was also a statistically significant difference in the onset of resistance to first-generation TKIs between the two groups (P < 0.05). (2) In terms of safety analysis, the incidence of adverse reactions related to EGFR-TKIs was 12.5% in the combination group and 14.3% in the monotherapy group, but this difference was not statistically significant (P > 0.05). There were no statistically significant differences in serum AST, ALT, CREA, TBIL, ALB and BUN levels between the two groups after medication (P > 0.05). (3) Regarding inflammatory markers, there were no statistically significant differences in the changes in neutrophil-to-lymphocyte Ratio(NLR) and Platelet-to-lymphocyte Ratio(PLR) values before and after treatment between the two groups (P > 0.05). (4) Network pharmacology analysis identified 112 active ingredients and 290 target genes for ZLJT. From the GEO database, 2035 differentially expressed genes related to resistant LUAD were selected, and 39 target genes were obtained by taking the intersection. A "ZLJT-compound-target-disease" network was successfully constructed using Cytoscape 3.7.0. GO enrichment analysis revealed that ZLJT mainly affected biological processes such as adenylate cyclase-modulating G protein-coupled receptor. In terms of cellular components, ZLJT was associated with the cell projection membrane. The molecular function primarily focused on protein heterodimerization activity. KEGG enrichment analysis indicated that ZLJT exerted its antitumor and anti-drug resistance effects through pathways such as the PI3K-Akt pathway. Molecular docking showed that luteolin had good binding activity with FOS (-9.8 kJ/mol), as did tanshinone IIA with FOS (-9.8 kJ/mol) and quercetin with FOS (-8.7 kJ/mol). CONCLUSION: ZLJT has potential antitumor progression effects. For patients with EGFR gene-mutated non-small cell LUAD, combining ZLJT with EGFR-TKI treatment can delay the occurrence of acquired resistance. The underlying mechanisms may involve altering signal transduction pathways, blocking the tumor cell cycle, inhibiting tumor activity, enhancing cellular vitality, and improving the bioavailability of combination therapy. The combination of EGFR-TKI and ZLJT represents an effective approach for the treatment of tumors using both Chinese and Western medicine.

Predictive value of serum ß2-microglobulin in cardiac valve calcification in maintenance hemodialysis patients.

Background: Cardiac valve calcification (CVC) is associated with adverse cardiovascular events. We studied the risk factors of CVC in maintenance hemodialysis (MHD) patients and the value of serum ß2-microglobulin (ß2-MG) levels in predicting the incidence of CVC. ß2-MG is a middle molecular weight toxin. In recent years, researchers found that elevated blood ß2-MG was associated with coronary, thoracic, and abdominal aortic calcifications with significant correlations. ß2-MG has been emerging as a strong biomarker for cardiovascular mortality in uremic patients but its role in CVC is not well studied. This study looked specifically at CVC occurrence in relation to ß2-MG for MHD patients. Methods: Patients who underwent MHD for more than 3 months in the First People's Hospital of Nantong City from November 2012 to November 2019 with complete available data were included in the study. The patients were divided into the CVC group and the non-CVC group. The general information and clinical laboratory indicators of the patients were collected in a retrospective manner. We analyzed the risk factors for developing CVC in MHD patients using binary logistic regression method. Receiver operating characteristic (ROC) curves were used to calculate the cut-off value of ß2-MG for predicting CVC. The decision tree (DT) method was used to classify and explore the probability of CVC in patients with MHD. Results: The ß2-MG in the CVC group was significantly higher than that in the non-CVC group (t=6.750, P<0.001). Multivariate binary logistic regression analysis showed that gender, age, serum ß2-MG, and hemodialysis (HD) adequacy (Kt/V urea) were independent risk factors for CVC in MHD patients. ROC analysis showed that a ß2-MG value of 25 µg/L was the best cut-off point for predicting CVC in MHD patients. According to binary logistic regression analysis, the ß2-MG ≥25 µg/L group was 3.39 times more likely to develop CVC than the ß2-MG <25 µg/L group [odds ratio (OR), 3.39; 95% confidence interval (CI), 1.63-7.06; P=0.001]. The DT model determined that serum ß2-MG ≥25 µg/L and age >69 years were important determinants for predicting CVC in MHD patients. Conclusions: Serum ß2-MG in MHD patients has a positive correlation with the severity and occurrence of CVC.

High-performance dual-tunable terahertz absorber based on strontium titanate and bulk Dirac semimetal for temperature sensing and switching function.

In this study, a perfect metamaterial absorber based on strontium titanate and bulk Dirac semimetals is proposed. When the temperature of strontium titanate was 300K, the dual-band absorptions were 99.74% and 99.99% at 1.227 and 1.552 THz, respectively. The sensitivities based on a transverse magnetic (TM) wave were 0.95 and 1.22 GHz/K; the sensitivity based on a transverse electric (TE) wave was 0.76 GHz/K. The TE and TM waves were modulated by inserting a bulk Dirac semimetal between the concave and convex devices. The modulation depth of the TE wave was 97.9% at 1.1 THz; the extinction ratio was 16.9 dB. The modulation depth of the TE wave at 1.435 THz was 95.9%; the extinction ratio was 13.89 dB. The TM wave modulation depth at 1.552 THz was 95.9%; the extinction ratio was 13.98 dB. Irrespective of a TE or TM wave, the terahertz absorber has good switching and temperature-sensing performance based on strontium titanate and bulk Dirac semimetals as well as broad application prospects in temperature sensing and switching devices.

Clinical evaluation on automatic segmentation results of convolutional neural networks in rectal cancer radiotherapy.

Purpose: Image segmentation can be time-consuming and lacks consistency between different oncologists, which is essential in conformal radiotherapy techniques. We aimed to evaluate automatic delineation results generated by convolutional neural networks (CNNs) from geometry and dosimetry perspectives and explore the reliability of these segmentation tools in rectal cancer. Methods: Forty-seven rectal cancer cases treated from February 2018 to April 2019 were randomly collected retrospectively in our cancer center. The oncologists delineated regions of interest (ROIs) on planning CT images as the ground truth, including clinical target volume (CTV), bladder, small intestine, and femoral heads. The corresponding automatic segmentation results were generated by DeepLabv3+ and ResUNet, and we also used Atlas-Based Autosegmentation (ABAS) software for comparison. The geometry evaluation was carried out using the volumetric Dice similarity coefficient (DSC) and surface DSC, and critical dose parameters were assessed based on replanning optimized by clinically approved or automatically generated CTVs and organs at risk (OARs), i.e., the Planref and Plantest. Pearson test was used to explore the correlation between geometric metrics and dose parameters. Results: In geometric evaluation, DeepLabv3+ performed better in DCS metrics for the CTV (volumetric DSC, mean = 0.96, P< 0.01; surface DSC, mean = 0.78, P< 0.01) and small intestine (volumetric DSC, mean = 0.91, P< 0.01; surface DSC, mean = 0.62, P< 0.01), ResUNet had advantages in volumetric DSC of the bladder (mean = 0.97, P< 0.05). For critical dose parameters analysis between Planref and Plantest, there was a significant difference for target volumes (P< 0.01), and no significant difference was found for the ResUNet-generated small intestine (P > 0.05). For the correlation test, a negative correlation was found between DSC metrics (volumetric, surface DSC) and dosimetric parameters (δD95, δD95, HI, CI) for target volumes (P< 0.05), and no significant correlation was found for most tests of OARs (P > 0.05). Conclusions: CNNs show remarkable repeatability and time-saving in automatic segmentation, and their accuracy also has a certain potential in clinical practice. Meanwhile, clinical aspects, such as dose distribution, may need to be considered when comparing the performance of auto-segmentation methods.

Th1 or Th2 cytokines are correlated with Tregs and T cell subsets and pregnancy outcomes in patients with autoimmune thyroid disease during early, middle, late pregnancy, and postpartum period.

Autoimmune thyroid disease (AITD) is a T lymphocytes-mediated autoimmune disorder affecting pregnant women. The current study sought to determine the correlations between T helper-1 (Th1)/T helper-2 (Th2) cytokines and regulatory T cells (Tregs) and T cell subsets and pregnancy outcomes in AITD patients during early pregnancy (T1), middle pregnancy (T2), late pregnancy (T3), and postpartum period (PP). A total of 60 patients with Graves' disease, 60 patients with Hashimoto's thyroiditis, and 30 healthy pregnant women were initially enrolled in the study. Thyroid hormones and antibodies, Th1 or Th2 cytokines, transforming growth factor-ß, Tregs, CD4+ T helper cells (CD4+), CD8+ T helper cells (CD8+) levels were determined by means of Maglumi2000 automatic chemiluminescence instrument, enzyme-linked immunosorbent assay, and flow cytometry. Our findings demonstrated higher IFN-γ and IL-2 levels, along with lower IL-4, IL-10, TGF-ß, Treg, and CD4+/CD8+ levels in AITD patients during T1, T2, T3, and PP. Furthermore, the TGF-ß, Treg, and CD4+/CD8+ levels were lower in the IFN-γ/IL-2 high expression group but higher in the IL-4/IL-10 high expression group. The IFN-γ and IL-2 levels were higher, while IL-4 and IL-10 level were lower in AITD patients with adverse pregnancy outcomes. Lastly, Th1 cytokines were higher and Th2 cytokines were lower in AITD patients and elicited correlation with Tregs and CD4+/CD8+ levels. Collectively, our findings highlighted that up-regulation of Th1 cytokines may increase the percentage of adverse pregnancy outcomes in AITD patients.

Enhanced mechanism of copper doping in magnetic biochar for peroxymonosulfate activation and sulfamethoxazole degradation.

Magnetic biochar is excellent for separation and peroxymonosulfate (PMS) activation. Copper doping could improve the catalytic capability of magnetic biochar significantly. In this study, cow dung biochar is applied to investigate the effects of copper doping on the magnetic biochar, focusing on the specific influence on the consumption of active sites, the production of oxidative species and the toxicity of degradation intermediates. The results showed that copper doping promoted the uniform distribution of iron sites on the biochar surface and reduced iron aggregation. At the same time, copper doping interpreted the biochar with larger specific surface area, which was beneficial to the adsorption and degradation of sulfamethoxazole (SMX). The SMX degradation kinetic constant with copper-doped magnetic biochar was 0.0403 min-1, which was 1.45 times than that of magnetic biochar. Besides, copper doping might accelerate the consumption of CO, Fe0, Fe2+ sites and hinder the activation of PMS at copper-related sites. Furthermore, copper doping promoted the PMS activation by magnetic biochar through accelerated electron transfer. For the oxidative species, copper doping accelerated the production of hydroxyl radicals, singlet oxygen, and superoxide radicals in solution and inhibited the generation of sulfate radicals. In addition, SMX could be directly decomposed into less toxic intermediates in the copper-doped magnetic biochar/PMS system. In conclusion, this paper provides insight and analysis of the advantages of copper doping on the magnetic biochar, which helps to facilitate the design and practical application of bimetallic biochar.

Influence and mechanism of water matrices on H2O2-based Fenton-like oxidation processes: A review.

Water matrices often coexist with the target pollutant during H2O2-based Fenton-like processes, which affects H2O2 activation and pollutant removal. Specifically, water matrices include inorganic anions (such as chloride, sulfate, nitrate, bicarbonate, carbonate and phosphate ions) and natural organic matters (such as humic acid (HA) and fulvic acid (FA)). In this review, the roles and mechanisms of water matrices in various Fenton-like systems were analyzed and summarized comprehensively. Carbonate and phosphate ions usually act as inhibitors. In contrast, the effects of other water matrices are usually controversial. Generally, water matrices can inhibit pollutants degradation through scavenging OH, forming low reactive radicals, adsorbing on catalyst sites, and changing solution pH. However, inorganic anions can exhibit a promotion effect, which is attributed to their complexation with copper ions in mixed contaminants as well as with cobalt and copper ions in catalysts. Furthermore, the photo-reactivity of nitrate and the generation of secondary radicals with long lifetime are conducive to the promotion of inorganic anions. Besides, HA (FA) can be activated by external energy or act as electron shuttle, thus displaying a facilitative effect. This review will provide guidance for the practical applications of the Fenton-like process.

A critical review on correlating active sites, oxidative species and degradation routes with persulfate-based antibiotics oxidation.

At present, numerous heterogeneous catalysts have been synthesized to activate persulfate (PS) and produce various reactive species for antibiotic degradation from water. However, the systematic summary of the correlation among catalyst active sites, PS activation pathway and pollutant degradation has not been reported. This review summarized the effect of metal-based, carbon-based and metal-carbon composite catalysts on the degradation of antibiotics by activating PS. Metal and non-metal sites are conducive to inducing different oxidation pathways (SO4•-, •OH radical oxidation and 1O2 oxidation, mediated electron transfer, surface-bound reactive complexes and high-valent metal oxidation). SO4•- and •OH are easy to attack CH, S-N, CN bonds, CC double bonds and amino groups in antibiotics. 1O2 is more selective to the structure of the aniline ring and amino group, and also to attacking CS, CN and CH bonds. Surface-bound active species can cleave CC, SN, CS and CN bonds. Other non-radical pathways may also induce different antibiotic degradation routes due to differences in oxidation potential and electronic properties. This critical review clarified the functions of active sites in producing different reactive species for selective oxidation of antibiotics via featured pathways. The outcomes will provide valuable guidance of oriented-regulation of active sites in heterogeneous catalysts to produce on-demand reactive species toward high-efficiency removing antibiotics from water.

Machine learning for predicting accuracy of lung and liver tumor motion tracking using radiomic features.

Background: Internal tumor motion is commonly predicted using external respiratory signals. However, the internal/external correlation is complex and patient-specific. The purpose of this study was to develop various models based on the radiomic features of computed tomography (CT) images to predict the accuracy of tumor motion tracking using external surrogates and to find accurate and reliable tracking algorithms. Methods: Images obtained from a total of 108 and 71 patients pathologically diagnosed with lung and liver cancers, respectively, were examined. Real-time position monitoring motion was fitted to tumor motion, and samples with fitting errors greater than 2 mm were considered positive. Radiomic features were extracted from internal target volumes of average intensity projections, and cross-validation least absolute shrinkage and selection operator (LassoCV) was used to conduct feature selection. Based on the radiomic features, a total of 26 separate models (13 for the lung and 13 for the liver) were trained and tested. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to assess performance. Relative standard deviation was used to assess stability. Results: Thirty-three and 22 radiomic features were selected for the lung and liver, respectively. For the lung, the AUC varied from 0.848 (decision tree) to 0.941 [support vector classifier (SVC), logistic regression]; sensitivity varied from 0.723 (extreme gradient boosting) to 0.848 [linear support vector classifier (linearSVC)]; specificity varied from 0.834 (gaussian naive bayes) to 0.936 [multilayer perceptron (MLP), wide and deep (W&D)]; and MLP and W&D had better performance and stability than the median. For the liver, the AUC varied from 0.677 [light gradient boosting machine (Light)] to 0.892 (logistic regression); sensitivity varied from 0.717 (W&D) to 0.862 (MLP); specificity varied from 0.566 (Light) to 0.829 (linearSVC); and logistic regression, MLP, and SVC had better performance and stability than the median. Conclusions: Respiratory-sensitive radiomic features extracted from CT images of lung and liver tumors were proved to contain sufficient information to establish an external/internal motion relationship. We developed a rapid and accurate method based on radiomics to classify the accuracy of monitoring a patient's external surface for lung and liver tumor tracking. Several machine learning algorithms-in particular, MLP-demonstrated excellent classification performance and stability.

Multifunctional terahertz absorber based on the Dirac semimetal and vanadium dioxide.

In this paper, a multifunctional terahertz (THz) absorber based on Dirac semimetal and vanadium dioxide (V O 2) is proposed. By modulating the temperature of V O 2, the absorber can be switched between the narrow band and wide band. When V O 2 is in the metallic state, the absorber has a broadband absorption effect with a bandwidth of approximately 4 THz. It has the advantages of insensitivity to polarization and wide-angle absorption. When V O 2 is in the insulating state, the absorber has two absorption peaks with absorptivity exceeding 90% and sensitivities of 297.7 and 402 GHz/RIU, and thus can be used as a highly sensitive sensor for cell detection. When the Fermi level of the Dirac semimetal is changed, the absorption characteristics can be modulated. The absorber has broad application prospects in multifunctional modulated devices.

Overlooked impacts of natural organic matter conversion in a Fe(II)-induced peroxymonosulfate activation system for river water remediation.

The peroxymonosulfate (PMS) process may be hindered severely due to natural organic matter (NOM) conversion in the treatment of emerging pollutants from river water, becoming a critical engineering and technical issue. In this study, a Fe(II)-induced river water (RW)/PMS catalytic system was constructed for investigating molecular transformation of NOM and related influence mechanism to sulfamethoxazole (SMX) degradation. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis indicated that NOM molecules containing no more than one heteroatom in river may be attacked by hydroxyl radicals (OH) and then polymerized, converting into molecules with two or three heteroatoms during PMS oxidation. Based on the correlation analysis, CHONP-NOM, CHOSP-NOM and CHONSP-NOM showed a significant inhibition against SMX degradation, while CHONS-NOM exhibited a moderate inhibitory effect. Besides, more condensed aromatic structures, carbohydrates and tannins were generated via reactive species (OH and sulfate radicals (SO4-)) oxidation, radical addition and polymerization reactions. Notably, condensed aromatic structures, carbohydrates and tannins presented weak, modest and strong inhibition to SMX degradation, respectively. Based on the current results, the inhibition of target pollutants degradation would be mitigated via regulation of NOM molecules in a Fe(II)-induced PMS activation system, providing valuable information to reduce NOM impact. In addition, this study paves the way to achieve efficient removal of emerging pollutants from river water.

Application of MXene-based materials in Fenton-like systems for organic wastewater treatment: A review.

Recently, Fenton-like systems have been widely explored and applied for the removal of organic matter from wastewater. Two-dimensional (2D) MXene-based materials exhibit excellent adsorption and catalysis capacity for organic pollutants removal, which has been reported widely. However, there is no summary on the application of MXene-based materials in Fenton-like systems for organic matter removal. In this review, four types of MXene-based materials were introduced, including 2D MXene, MXene/Metal complex, MXene/Metal oxide complex, and MXene/3D carbon material complex. In addition, the Fenton-like system usually consists of adsorption and degradation processes. The oxidation process might contain hydrogen peroxide (H2O2) or persulfate (PS) oxidants. This review summarizes the performance and mechanisms of organic pollutants adsorption and oxidants activation by MXene-based materials systematically. Finally, the existing problems and future research directions of MXene-based materials are proposed in Fenton-like wastewater treatment systems.

Correlation between lactate dehydrogenase and QTc interval prolongation in maintenance hemodialysis patients: a cross-sectional study.

BACKGROUND: Corrected QT (QTc) interval prolongation is one of the common causes of sudden cardiac death in patients with maintenance hemodialysis (MHD) patients. However, there are few studies on QTc prolongation in MHD patients. The concentration of lactate dehydrogenase (LDH) in hemodialysis population increased, and LDH was associated with the mortality of MHD patients. This study aimed to investigate the relationship between QTc interval prolongation and LDH in MHD patients. METHODS: This is a cross-sectional observational study. Patients who underwent MHD for more than 3 months in the Second Affiliated Hospital of Nantong University from November 2012 to November 2019 with complete data were selected as the research subjects. The patients were divided into the normal QTc interval group and the QTc interval prolongation group. The general data of patients and clinical laboratory indicators were collected retrospectively from the electronic medical record system. Pearson correlation analysis and binary logistic regression were used to analyze the correlation between LDH and QTc interval prolongation; the cut-off value of LDH predicting QTc interval prolongation was calculated by receiver operating characteristic (ROC) curve. RESULTS: The LDH level in the prolonged QTc interval group was significantly higher than that in the normal group (301.96±110.91 vs. 215.39±67.65, t=-8.03, P<0.001). QTc interval and LDH (r=0.386) were positively correlated. Binary logistic regression analysis showed that LDH, serum potassium <4 mmol/L, serum phosphorus, and left ventricular end-diastolic diameter (LVDd) were independent related factors for QTc interval prolongation. The ROC curve results showed that LDH =220 U/L was the best cutoff point for predicting QTc interval prolongation in MHD patients, with a sensitivity of 81.45% and a specificity of 59.35%. Binary logistic regression analysis showed that the LDH >220 U/L group was 6.34 times more likely to have QTc interval prolongation than the LDH ≤220 U/L group (OR 6.34, 95% CI: 3.47-11.58, P<0.001). CONCLUSIONS: LDH in MHD patients is closely related to QTc interval prolongation. Serum LDH, ionic calcium, serum phosphorus and potassium may predict QTc interval prolongation. Monitoring related indicators can remind clinicians to intervene as soon as possible to reduce the potential risk of arrhythmia and sudden cardiac death (SCD).

Aqueous Suzuki couplings mediated by a hydrophobic catalyst.

The catalytic activity of [(Ph2P-o-C6H4)2N]PdCl in aerobic aqueous Suzuki couplings is described. Though hydrophobic, this molecular catalyst is competent in cross-coupling reactions of arylboronic acids with a variety of electronically activated, unactivated, and deactivated aryl iodides, bromides, and chlorides upon heating in aqueous solutions under aerobic conditions to give biphenyl derivatives without the necessity of amphiphiles even in the presence of an excess amount of mercury.

Efficacy and treatment-related adverse events of multi-targeted tyrosine kinase inhibitors in advanced non-small-cell lung cancer: a meta-analysis of randomized controlled trials.

BACKGROUND: Multitargeted tyrosine kinase inhibitors (TKIs) are used to treat advanced non-small cell lung cancer (NSCLC). Their efficacy and safety have been studied in randomized controlled trials. AIM: This meta-analysis aimed to summarize the most up-to-date evidence regarding the efficacy and adverse events of TKIs in NSCLC treatment. METHOD: Randomized controlled trials were searched from PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials. The intervention arm was the TKI-containing group, and the control arm was the TKI-free group. Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival, and adverse events were extracted and synthesized. The last search was performed in April 2022. Two researchers independently screened articles, extracted data, and evaluated the quality of the included studies. The Cochrane risk-of-bias tool was used to assess the quality of each study. Random or fixed-effect models were used in statistical methods. I2 statistics were used to assess heterogeneity. RESULTS: Thirty-one studies (12,517 patients) were included. Compared to the control group, the TKI group had significantly higher ORR (relative risk RR 1.52, 95% confidence interval, CI [1.29, 1.80], P < 0.05), DCR (RR 1.34, 95%CI [1.19, 1.51], P < 0.05), and prolonged PFS (hazard ratio HR 0.67, 95%CI [0.59, 0.77], P < 0.05). The TKI group showed a higher rate of adverse events (RR 1.70, 95%CI [1.34, 2.16], P < 0.05) and grade 3-5 adverse events (RR 1.59, 95% CI [1.35, 1.88], P < 0.05). CONCLUSION: TKIs could increase ORR and DCR and prolong PFS for advanced NSCLC. Adverse events should be closely monitored.

Discussion of tumor mutation burden as an indicator to predict efficacy of immune checkpoint inhibitors: A case report.

There are many treatment options for advanced lung cancer, among which immunotherapy has developed rapidly and benefited a lot of patients. However, immunotherapy can only benefit a subgroup of patients, and how to select patients suitable for this therapy is critical. Tumor mutation burden (TMB) is one of the important reference indicators for immune checkpoint inhibitors (ICIs). However, there are many factors influencing the usage of this indicator, which will lead to considerable consequences if not treated well. In this study, we performed a case study on a male advanced lung squamous cell carcinoma patient of age 83. The patient suffered from "cough and sputum", and did chest CT scans on 24 October 2018, which showed "a mass-like mass in the anterior segment of the right lung upper lobe, about 38mm×28mm". He was treated with systemic chemotherapy; however, the tumor was still under progression. Although PD-L1 was not tested in gene testing, he had a TMB value of 10.26 mutations/Mb with a quantile value 88.63%. Thus, "toripalimab injection" was added as immunotherapy and the size of the lesion decreased. In summary, we adopted a clinical case as the basis to explore the value and significance of TMB in immunotherapy in this study. We hope that more predictive molecular markers will be discovered, which will bring more treatment methods for advanced lung cancer.