Layer-Dependent Superconductivity in Iron-Based Superconductors CsCa2Fe4As4F2 and CaKFe4As4.

In the quasi-two-dimensional superconductor NbSe2, the superconducting transition temperature (Tc) is layer-dependent, decreasing by about 60% in the monolayer limit. However, for the extremely anisotropic copper-based high-Tc superconductor Bi2Sr2CaCu2O8+δ (Bi-2212), the Tc of the monolayer is almost identical with that of its bulk counterpart. To clarify the effect of dimensionality on superconductivity, here, we successfully fabricate ultrathin flakes of iron-based high-Tc superconductors CsCa2Fe4As4F2 and CaKFe4As4. It is found that the Tc of monolayer CsCa2Fe4As4F2 (after tuning to the optimal doping by ionic liquid gating) is about 20% lower than that of the bulk crystal, while the Tc of three-layer CaKFe4As4 decreases by 46%, showing a more pronounced dimensional effect than that of CsCa2Fe4As4F2. By carefully examining their anisotropy and the c-axis coherence length, we reveal the general trend and empirical law of the layer-dependent superconductivity in these quasi-two-dimensional superconductors.

Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning.

BACKGROUND: Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory. METHOD: One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics. RESULTS: Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model. CONCLUSIONS: Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Risk stratification models for predicting preventable hospitalization in commercially insured late middle-aged adults with depression.

BACKGROUND: A significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods. METHODS: This retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM). RESULTS: Our predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM. CONCLUSIONS: Our study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US.

Effect of Older vs Younger Age on Anthropometric and Metabolic Variables During Treatment of Psychotic Depression With Sertraline Plus Olanzapine: The STOP-PD II Study.

OBJECTIVE: To examine the effect of older versus younger age on change in anthropometric and metabolic measures during extended treatment of psychotic depression with sertraline plus olanzapine. METHODS: Two hundred and sixty-nine men and women aged 18-85 years with an episode of psychotic depression were treated with open-label sertraline plus olanzapine for up to 12 weeks. Participants who remained in remission following an 8-week stabilization phase were eligible to participate in a 36-week randomized controlled trial (RCT) that compared the efficacy and tolerability of sertraline plus olanzapine with sertraline plus placebo. Weight, waist circumference and plasma lipids, glucose, HbA1c, and insulin were measured at regular intervals during the acute, stabilization and randomized phases of the study. Linear mixed models were used to analyze the trajectories of anthropometric and metabolic measures. RESULTS: Participants aged 60 years or older experienced less weight gain and less increase in cholesterol during the combined acute and stabilization phases of the study compared with those aged 18-59 years. At the acute-stabilization termination visit, mean weight in older participants was 6.5 lb. less than premorbid weight, whereas it was 17.9 lb. more than premorbid weight in younger participants. In the RCT, there was a significant interaction of treatment and age group for the trajectory of weight, but the post hoc tests that compared age groups within each treatment arm were not statistically significant. There were no clinically significant differences between younger and older participants in glycemic measures. CONCLUSION: Older patients with psychotic depression experienced less increase in weight and total cholesterol than their younger counterparts during acute and stabilization treatment with sertraline plus olanzapine. In the older group, weight gained during the acute and stabilization phases appeared to be partial restoration of weight lost during the index episode of depression, whereas weight gain in younger participants was not.

Ultra-low thermal conductivity and high thermoelectric performance of monolayer BiP3: a first principles study.

The thermoelectric properties of monolayer triphosphide BiP3 are studied via first principles calculations and Boltzmann transport equation. First, the Seebeck coefficient, electrical conductivity and electron thermal conductivity at different temperatures are calculated using the Boltzmann transport equation with relaxation time approximation. It has been observed that BiP3 has a large power factor (265 × 10-4 W K-2 m-1, 700 K). Then, by analyzing the second-order interatomic force constant (IFCS), the atomic structure and phonon dispersion were studied, and the thermal conductivity of monolayer BiP3 was predicted in the temperature range of 300-800 K, and it was found that it had a very low thermal conductivity (2.13 W m-1 K-1) at room temperature. The thermal conductivity is mainly contributed by the branches of acoustics along in-plane transverse (TA). Finally, the maximum ZT value of monolayer BiP3 is 3.06 at 700 K, when the electron doping concentration is 2.35 × 1011 cm-2, which indicates that it is a promising thermoelectric material.

Quadruple-layer group-IV tellurides: low thermal conductivity and high performance two-dimensional thermoelectric materials.

Through first-principles calculations, we report the thermoelectric properties of two-dimensional (2D) hexagonal group-IV tellurides XTe (X = Ge, Sn and Pb), with quadruple layers (QL) in the Te-X-X-Te stacking sequence, as promising candidates for mid-temperature thermoelectric (TE) materials. The results show that 2D PbTe exhibits a high Seebeck coefficient (∼1996 µV K-1) and a high power factor (6.10 × 1011 W K-2 m-1 s-1) at 700 K. The lattice thermal conductivities of QL GeTe, SnTe and PbTe are calculated to be 2.29, 0.29 and 0.15 W m-1 K-1 at 700 K, respectively. Using our calculated transport parameters, large values of the thermoelectric figure of merit (ZT) of 0.67, 1.90, and 2.44 can be obtained at 700 K under n-type doping for 2D GeTe, SnTe, and PbTe, respectively. Among the three compounds, 2D PbTe exhibits low average values of sound velocity (0.42 km s-1), large Grüneisen parameters (∼2.03), and strong phonon scattering. Thus, 2D PbTe shows remarkable mid-temperature TE performance with a high ZT value under both p-type (2.39) and n-type (2.44) doping. The present results may motivate further experimental efforts to verify our predictions.

Association Between Residential Neighborhood Social Conditions and Health Care Utilization and Costs.

BACKGROUND: Social factors are important drivers of health. However, it is unclear to what extent neighborhood social conditions are associated with total and preventable health care utilization and costs. OBJECTIVES: To examine the association of neighborhood social conditions with total annual and potentially preventable Medicare costs. RESEARCH DESIGN AND SUBJECTS: Retrospective cohort study. Medicare claims data from 2013 to 2014 linked with neighborhood social conditions at the US census block group level of 2013 for 93,429 Medicare fee-for-service and dually eligible patients. MEASURES: Neighborhood social conditions were measured by Area Deprivation Index at the census block group level, categorized into quintiles. Outcomes included total annual and potentially preventable utilization and costs. RESULTS: After adjustment for demographics and comorbidities, patients with the least disadvantaged social conditions had higher total annual Medicare costs [$427; 95% confidence interval (CI), $200-$655] and similar potentially preventable costs (-$23; 95% CI, -$56 to $10) as compared with patients with the intermediate level social conditions. Patients with the most disadvantaged social conditions had similar total Medicare costs (-$22; 95% CI, -$342 to $298) but higher potentially preventable costs ($53; 95% CI, $1-$104) than patients with the intermediate level social conditions. CONCLUSIONS: Disadvantaged neighborhood conditions are associated with lower total annual Medicare costs but higher potentially preventable costs after controlling for demographic, medical, and other patient characteristics. Socioeconomic barriers may limit access and use of primary care and disease management services, resulting in a higher proportion of their health care costs going to potentially preventable care.

Identifying Patients with Persistent Preventable Utilization Offers an Opportunity to Reduce Unnecessary Spending.

BACKGROUND: Improving care for high-cost patients is increasingly important for improving the value of healthcare. Most prior research has focused on identifying patients with high costs, but the extent to which these costs are potentially preventable remains unclear. OBJECTIVE: To identify patients with persistent preventable utilization and compare their characteristics with high-cost patients. DESIGN: Descriptive analysis using Medicare claims data from 2013 to 2014. PARTICIPANTS: Medicare fee-for-service and dual-eligible beneficiaries (N = 515,689) from the New York metropolitan area who were continuously enrolled in Medicare Parts A and B in 2013 and 2014. MAIN MEASURES: The primary analysis focuses on patients with persistent preventable utilization (at least one preventable emergency department visit, hospitalization, or 30-day readmission in both 2013 and 2014) and high-cost patients in 2014 (top 10% of total annual spending). We compared demographic, medical, behavioral, and social characteristics and total and preventable healthcare utilization between these two groups. KEY RESULTS: Patients with persistent preventable utilization accounted for 4.8% of the overall patient population, 13.4% of overall costs, but 46.2% of preventable costs among all Medicare patients. Compared with high-cost patients, patients with persistent preventable utilization had lower median healthcare costs ($33,383 vs. $56,552), but their median potentially preventable costs were seven times higher ($7151 vs. $928). We also found that 1.9% of patients could be categorized in both the persistent preventable utilization group and the high-cost group. This subset of patients had the highest median Medicare costs and preventable costs and represented over 30% of total preventable spending and 9.4% of overall costs among all Medicare patients. CONCLUSION: Designing and targeting interventions for patients with persistent preventable utilization may offer an important opportunity to reduce unnecessary utilization and promote high-value care.

Two Interventions for PatientsWith Major Depression and Severe Chronic Obstructive Pulmonary Disease: Impact on Quality of Life.

OBJECTIVE: Clinically significant depression occurs in approximately 40% of chronic obstructive pulmonary disease (COPD) patients, and both illnesses severely impair quality of life. This study tests the hypothesis that problem-solving integrated with a treatment adherence intervention, the Problem Solving-Adherence (PSA), is superior to a personalized treatment adherence intervention, the Personalized Intervention for Depressed Patients with COPD (PID-C), alone in improving quality of life in depressed COPD patients. METHODS: After screening 633 admissions for acute rehabilitation, we studied quality of life in 87 participants with major depression (by Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) and severe COPD randomly assigned to 14 sessions of PID-C or PSA over 26 weeks. Quality of life was assessed using the Word Health Organization Quality of Life-BREF at baseline and weeks 10, 14, and 26. RESULTS: The hypothesis was not supported. Exploratory latent class growth modeling identified two quality of life trajectories. In 80.5% of participants, quality of life remained unchanged and improved in the remaining 19.5% during the first 14 weeks. Patients with a stable quality trajectory had higher qualityof life at baseline and a stronger sense of personal agency. CONCLUSION: Maintaining quality of life is a favorable outcome in depressed patients with COPD whose course is one of deterioration. These findings highlight the usefulness of PID-C, an easy to learn, personalized adherence enhancement intervention that, after further testing, may be integrated into the rehabilitation and care of depressed COPD patients.

Novel two-dimensional tetragonal vanadium carbides and nitrides as promising materials for Li-ion batteries.

Two-dimensional (2D) materials, owing to their unique properties, have shown great potential for energy storage. In this work, we predict two types of new 2D transition metal carbides and nitrides, namely, tetragonal V2C2 and V2N2 (tetr-V2C2 and tetr-V2N2) monolayer sheets. Comprehensive first-principle calculations show that these two 2D systems exhibit dynamic (thermal) stabilities and intrinsic metallic nature. Compared with the commercialized graphite anode material, tetr-V2C2 and tetr-V2N2 monolayer sheets exhibit lower Li diffusion barrier of 89 and 94 meV, higher theoretical capacity of 412 and 425 mA h g-1 and lower average open circuit of 0.468 and 0.583 V, respectively. Combining those advanced features, our proposed tetr-V2C2 and tetr-V2N2 monolayer sheets are both promising candidates as anode materials for lithium-ion batteries (LIBs) in the future.

Effect of Continuing Olanzapine vs Placebo on Relapse Among Patients With Psychotic Depression in Remission: The STOP-PD II Randomized Clinical Trial.

Importance: Psychotic depression is a severely disabling and potentially lethal disorder. Little is known about the efficacy and tolerability of continuing antipsychotic medication for patients with psychotic depression in remission. Objective: To determine the clinical effects of continuing antipsychotic medication once an episode of psychotic depression has responded to combination treatment with an antidepressant and antipsychotic agent. Design, Setting, and Participants: Thirty-six week randomized clinical trial conducted at 4 academic medical centers. Patients aged 18 years or older had an episode of psychotic depression acutely treated with sertraline plus olanzapine for up to 12 weeks and met criteria for remission of psychosis and remission or near-remission of depressive symptoms for 8 weeks before entering the clinical trial. The study was conducted from November 2011 to June 2017, and the final date of follow-up was June 13, 2017. Interventions: Participants were randomized either to continue olanzapine (n = 64) or switch from olanzapine to placebo (n = 62). All participants continued sertraline. Main Outcomes and Measures: The primary outcome was risk of relapse. Main secondary outcomes were change in weight, waist circumference, lipids, serum glucose, and hemoglobin A1c (HbA1c). Results: Among 126 participants who were randomized (mean [SD] age, 55.3 years [14.9 years]; 78 women [61.9%]), 114 (90.5%) completed the trial. At the time of randomization, the median dosage of sertraline was 150 mg/d (interquartile range [IQR], 150-200 mg/d) and the median dosage of olanzapine was 15 mg/d (IQR, 10-20 mg/d). Thirteen participants (20.3%) randomized to olanzapine and 34 (54.8%) to placebo experienced a relapse (hazard ratio, 0.25; 95% CI, 0.13 to 0.48; P < .001). The effect of olanzapine on the daily rate of anthropometric and metabolic measures significantly differed from placebo for weight (0.13 lb; 95% CI, 0.11 to 0.15), waist circumference (0.009 inches; 95% CI, 0.004 to 0.014), and total cholesterol (0.29 mg/dL; 95% CI, 0.13 to 0.45) but was not significantly different for low-density lipoprotein cholesterol (0.04 mg/dL; 95% CI, -0.01 to 0.10), high-density lipoprotein cholesterol (-0.01 mg/dL; 95% CI, -0.03 to 0.01), triglyceride (-0.153 mg/dL; 95% CI, -0.306 to 0.004), glucose (-0.02 mg/dL; 95% CI, -0.12 to 0.08), or HbA1c levels (-0.0002 mg/dL; 95% CI, -0.0021 to 0.0016). Conclusions and Relevance: Among patients with psychotic depression in remission, continuing sertraline plus olanzapine compared with sertraline plus placebo reduced the risk of relapse over 36 weeks. This benefit needs to be balanced against potential adverse effects of olanzapine, including weight gain. Trial Registration: ClinicalTrials.gov Identifier: NCT01427608.

Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital.

BACKGROUND: Acute respiratory failure occurs frequently in hospitalized patients and often starts before ICU admission. A risk stratification tool to predict mortality and risk for mechanical ventilation (MV) may allow for earlier evaluation and intervention. We developed and validated an automated electronic health record (EHR)-based model-Accurate Prediction of Prolonged Ventilation (APPROVE)-to identify patients at risk of death or respiratory failure requiring >= 48 h of MV. METHODS: This was an observational study of adults admitted to four hospitals in 2013 or a fifth hospital in 2017. Clinical data were extracted from the EHRs. The 2013 patients were randomly split 50:50 into a derivation/validation cohort. The qualifying event was death or intubation leading to MV >= 48 h. Random forest method was used in model derivation. APPROVE was calculated retrospectively whenever data were available in 2013, and prospectively every 4 h after hospital admission in 2017. The Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) were calculated at the same times as APPROVE. Clinicians were not alerted except for APPROVE in 2017cohort. RESULTS: There were 68,775 admissions in 2013 and 2258 in 2017. APPROVE had an area under the receiver operator curve of 0.87 (95% CI 0.85-0.88) in 2013 and 0.90 (95% CI 0.84-0.95) in 2017, which is significantly better than the MEWS and NEWS in 2013 but similar to the MEWS and NEWS in 2017. At a threshold of > 0.25, APPROVE had similar sensitivity and positive predictive value (PPV) (sensitivity 63% and PPV 21% in 2013 vs 64% and 16%, respectively, in 2017). Compared to APPROVE in 2013, at a threshold to achieve comparable PPV (19% at MEWS > 4 and 22% at NEWS > 6), the MEWS and NEWS had lower sensitivity (16% for MEWS and NEWS). Similarly in 2017, at a comparable sensitivity threshold (64% for APPROVE > 0.25 and 67% for MEWS and NEWS > 4), more patients who triggered an alert developed the event with APPROVE (PPV 16%) while achieving a lower false positive rate (FPR 5%) compared to the MEWS (PPV 7%, FPR 14%) and NEWS (PPV 4%, FPR 25%). CONCLUSIONS: An automated EHR model to identify patients at high risk of MV or death was validated retrospectively and prospectively, and was determined to be feasible for real-time risk identification. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02488174 . Registered on 18 March 2015.

Exploration of the linkage elements of porcupine antagonists led to potent Wnt signaling pathway inhibitors.

The Wnt signaling pathway is a pivotal developmental pathway. It operates through control of cellular functions such as proliferation, differentiation, migration and polarity. Aberrant Wnt signaling has been implicated in the formation and metastasis of tumors. Porcupine is a component of the Wnt signaling pathway. It is a member of the membrane-bound O-acyltransferase family of proteins. Porcupine catalyzes the palmitoylation of Wnt proteins, a process which is essential to their secretion and activity. Here we report a novel series of compounds obtained by a scaffold hybridization strategy from two known porcupine inhibitor classes. The leading compound 62 demonstrated subnanomolar (IC50 0.11 nM) inhibition of Wnt signaling in a paracrine cellular reporter gene assay. Compound 62 also potently inhibited Wnt secretion into culture medium, an indication of direct inhibition of the porcupine protein. Furthermore, compound 62 showed excellent chemical, plasma and liver microsomal stabilities. Collectively, these results strongly support further optimization of this novel scaffold to develop better Wnt pathway inhibitors.

Employing the Interpretable Ensemble Learning Approach to Predict the Bandgaps of the Halide Perovskites.

Halide perovskite materials have broad prospects for applications in various fields such as solar cells, LED devices, photodetectors, fluorescence labeling, bioimaging, and photocatalysis due to their bandgap characteristics. This study compiled experimental data from the published literature and utilized the excellent predictive capabilities, low overfitting risk, and strong robustness of ensemble learning models to analyze the bandgaps of halide perovskite compounds. The results demonstrate the effectiveness of ensemble learning decision tree models, especially the gradient boosting decision tree model, with a root mean square error of 0.090 eV, a mean absolute error of 0.053 eV, and a determination coefficient of 93.11%. Research on data related to ratios calculated through element molar quantity normalization indicates significant influences of ions at the X and B positions on the bandgap. Additionally, doping with iodine atoms can effectively reduce the intrinsic bandgap, while hybridization of the s and p orbitals of tin atoms can also decrease the bandgap. The accuracy of the model is validated by predicting the bandgap of the photovoltaic material MASn1-xPbxI3. In conclusion, this study emphasizes the positive impact of machine learning on material development, especially in predicting the bandgaps of halide perovskite compounds, where ensemble learning methods demonstrate significant advantages.

Trends in Early-Stage Cervical Cancer Management in the US: A National Cancer Database Analysis.

The Laparoscopic Approach to Cervical Cancer (LACC) trial was published in 2018 and demonstrated that minimally invasive surgery (MIS) yields inferior survival outcomes in early-stage cervical cancer compared to open surgery. This study investigates how the results of the LACC trial have impacted the selection of the primary treatment modality and adjuvant radiation utilization in early-stage cervical cancer. Using the National Cancer Database (NCDB), we compared patients with stage IA2-IB1 cervical cancer before (1/2016-12/2017) and after (1/2019-12/2020) the LACC trial. A total of 7930 patients were included: 4609 before and 3321 after the LACC trial. There was a decline in MIS usage from 67% pre-LACC to 35% thereafter (p < 0.001). In both the pre- and post-LACC periods, patients undergoing radical MIS more frequently had small volume disease (pre-LACC tumors ≤ 2 cm, 48% MIS vs. 41% open, p = 0.023; post-LACC stage IA2, 22% vs. 15%, p = 0.002). Pre-LACC, MIS radical hysterectomy was associated with White race (82% vs. 77%, p = 0.001) and private insurance (63% vs. 54%, p = 0.004), while there was no difference in socioeconomic factors in the post-LACC period. Although the proportion of patients treated with primary chemoradiation remained stable, the post-LACC cohort had a younger median age (52.47 vs. 56.37, p = 0.005) and more microscopic disease cases (13% vs. 5.4%, p = 0.002). There was no difference in the rate of radiation after radical hysterectomy before and after the trial (26% vs. 24%, p = 0.3). Conclusions: Post-LACC, patients were less likely to undergo MIS but received adjuvant radiation at similar rates, and primary chemoradiation patients were younger and more likely to have microscopic disease.

Comparative study of urea-15N fate in pure bamboo and bamboo-broadleaf mixed forests.

Objectives: Bamboo is a globally significant plant with ecological, environmental, and economic bene-fits. Choosing suitable native tree species for mixed planting in bamboo forests is an effective measure for achieving both ecological and economic benefits of bamboo forests. However, little is currently known about the impact of bamboo forests on nitrogen cycling and utilization efficiency after mixing with other tree species. Therefore, our study aims to compare the nitrogen cycling in pure bamboo forests with that in mixed forests. Methods: Through field experiments, we investigated pure Qiongzhuea tumidinoda forests and Q. tumidinoda-Phellodendron chinense mixed forests, and utilized 15N tracing technology to explore the fertilization effects and fate of urea-15N in different forest stands. Results: The results demonstrated the following: 1) in both forest stands, bamboo culms account for the highest biomass percentage (42.99%-51.86%), while the leaves exhibited the highest nitrogen concentration and total nitrogen uptake (39.25%-44.52%/29.51%-33.21%, respectively) Additionally, the average nitrogen uptake rate of one-year-old bamboo is higher (0.25 mg kg-1 a-1) compared to other age groups. 2) the urea-15N absorption in mixed forests (1066.51-1141.61 g ha-1, including 949.65-1000.07 g ha-1 for bamboo and 116.86-141.54 g ha-1 for trees) was significantly higher than that in pure forests (663.93-727.62 g ha-1, P<0.05). Additionally, the 15N recovery efficiency of culms, branches, leaves, stumps, and stump roots in mixed forests was significantly higher than that in pure forests, with increases of 43.14%, 69.09%, 36.84%, 51.63%, 69.18%, 34.60%, and 26.89%, respectively. 3) the recovery efficiency of urea-15N in mixed forests (45.81%, comprising 40.43% for bamboo and 5.38% for trees) and the residual urea-15N recovery rate in the 0-60 cm soil layer (23.46%) are significantly higher compared to those in pure forests (28.61%/18.89%). This could be attributed to the nitrogen losses in mixed forests (30.73%, including losses from ammonia volatilization, runoff, leaching, and nitrification-denitrification) being significantly lower than those in pure forests (52.50%). Conclusion: These findings suggest that compared to pure bamboo forests, bamboo in mixed forests exhibits higher nitrogen recovery efficiency, particularly with one-year-old bamboo playing a crucial role.

The Impact of Back Optic Zone Design in Orthokeratology on Visual Performance.

Purpose: To evaluate the visual performance in adolescents undergoing orthokeratology (OrthoK) treatment with two different optical zone diameters (OZDs). Methods: This randomized, double-masked, self-controlled prospective study was conducted at Tianjin Eye Hospital (Tianjin, China) in June 2022. Thirty-six eligible schoolchildren were enrolled and fitted with corneal refractive therapy lenses with two sizes of OZDs (5 mm [5OZ] and 6 mm [6OZ]). Each participant was randomized to wear the 5OZ in one eye and the 6OZ in the contralateral eye. Subjective visual quality was assessed using visual acuity, refraction, contrast sensitivity function, and visual symptoms, and the objective optical quality was assessed using ocular higher order aberrations (HOAs) and modulation transfer function (MTF). Results: Thirty-five myopic children completed a 1-month follow-up visit. The 5OZ lens induced significantly smaller treatment zone diameters than the 6OZ lens (P < 0.001). Subjective visual quality did not differ significantly between the two groups. Compared to baseline, aberrations of Z40, coma-like, spherical-like, and total HOAs in both groups increased significantly (P < 0.05). For the 3-mm pupils, spherical aberration in the 5OZ group was significantly higher than that in the 6OZ group (P < 0.05). The MTF value of the 6OZ group was significantly higher than that of 5OZ group for 0.3 and 1.5 cycles per degree for the 3-mm pupils (P = 0.006 and P = 0.026, respectively). However, HOAs or MTF did not differ significantly between the two groups for the 5-mm pupils. Conclusions: The difference induced by varying OZD was significant only in the smaller pupil condition. The selection of OZD in OrthoK designs in real-world patient management should be done while considering individual pupil size. Translational Relevance: This study revealed that the objective visual quality of small OZD lenses was only slightly affected for the small pupil size.

First-Principle Studies on Local Lattice Distortions and Thermodynamic Properties in Non-Stoichiometric Thorium Monocarbide.

Thorium monocarbide (ThC) is interesting as an alternative fertile material to be used in nuclear breeder systems and thorium molten salt reactors because of its high thermal conductivity, good irradiation performance, and wide homogeneous composition range. Here, the influence of carbon vacancy site and concentration on lattice distortions in non-stoichiometric ThC1-x (x = 0, 0.03125, 0.0625, 0.125, 0.1875, 0.25, or 0.3125) is systematically investigated using first-principle calculations by the projector augmented wave (PAW) method. The energy, mechanical parameters, and thermodynamic properties of the ThC1-x system are calculated. The results show that vacancy disordering has little influence on the total energy of the system at a constant carbon vacancy concentration using the random substitution method. As the concentration of carbon vacancies increases, significant lattice distortion occurs, leading to poor structural stability in ThC1-x systems. The changes in lattice constant and volume indicate that ThC0.75 and ThC0.96875 represent the boundaries between two-phase and single-phase regions, which is consistent with our experiments. Furthermore, the structural phase of ThC1-x (x = 0.25-0.3125) transforms from a cubic to a tetragonal structure due to its 'over-deficient' composition. In addition, the elastic moduli, Poisson's ratio, Zener anisotropic factor, and Debye temperature of ThC1-x approximately exhibit a linear downward trend as x increases. The thermal expansion coefficient of ThC1-x (x = 0-0.3125) exhibits an obvious 'size effect' and follows the same trend at high temperatures, except for x = 0.03125. Heat capacity and Helmholtz free energy were also calculated using the Debye model; the results showed the C vacancy defect has the greatest influence on non-stoichiometric ThC1-x. Our results can serve as a theoretical basis for studying the radiation damage behavior of ThC and other thorium-based nuclear fuels in reactors.

Influence of social deprivation index on in-hospital outcomes of COVID-19.

While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.

An Assessment of Race as a Risk Factor for Doxorubicin-Related Cardiotoxicity in Diffuse Large B-Cell Lymphoma.

BACKGROUND: Doxorubicin carries a risk of congestive heart failure (CHF). Black race has been suggested as a risk factor for doxorubicin-related cardiotoxicity, but data are limited. We assessed whether HF occurs at higher rates in Black patients compared to White patients who receive doxorubicin for DLBCL, and evaluated race as an independent risk factor for the development of HF after adjusting for known risk factors. PATIENTS AND METHODS: We used SEER-Medicare to identify patients 66 years and older with DLBCL. We excluded patients with CHF documented prior to diagnosis with DLBCL. We assessed for hypertension, type 2 diabetes, coronary artery disease, and arrhythmias prior to diagnosis with DLBCL. The primary outcome was documented CHF at any point following DLBCL diagnosis. Secondary outcomes included CHF in the first year following diagnosis and death. We performed analyses additionally stratified by cumulative dose of doxorubicin. RESULTS: Our study population consisted of 8,604 patients (White 96.8%, Black 3.2%). In both Kaplan-Meier and competing risk analyses, we observed no significant difference in the incidence of CHF between Black and White patients, both before and after adjusting for covariates. Finally, we observed no significant differences in the incidence of CHF by race after stratification by cumulative doxorubicin dose. CONCLUSIONS: CHF is common following doxorubicin chemotherapy for DLBCL in older patients. No association was observed between Black race and the onset of heart failure in this setting. Rigorous screening for known clinical risk factors is likely more relevant than race in treatment selection and optimization.