Existence of solutions for fractional interval--valued differential equations by the method of upper and lower solutions

In this work we firstly study some important properties of fractional calculus for interval-valued functions and introduce the concepts of upper and lower solutions for intervalvalued Caputo fractional differential equations. Then, we prove an existence result for intervalvalued Caputo fractional differential equations by use of the method of upper and lower solutions. Finally several examples will be presented to illustrate our abstract results

Wetland expansion on the continental shelf of the northern South China Sea during deglacial sea level rise

To identify environmental causes for past changes in vegetation in subtropical East Asia, we present carbon isotope compositions of plant-wax n-alkanes and provide estimates of the C4-plant contribution across the past four glacial terminations and interglacials, based on cores recovered from the northern South China Sea. Our results show a comparable C4-plant contribution between the Last Glacial Maximum (LGM) and the Holocene. An increase of the C4-plant contribution by 15–20% is found for Terminations IV, II and I relative to subsequent interglacial peaks, coeval with an expansion of Cyperaceae and Poaceae. In contrast, Termination V reveals a lower C4-plant contribution than Marine Isotope Stage (MIS) 11c. The data exhibit a long-term trend, with a stepwise increase of the C4-plant contribution across interglacials MIS 11c, 9e, 7e and 1. We suggest that no substantial changes in humidity levels over glacial-interglacial cycles occurred facilitating a similar C3/C4-plant ratio for the LGM and the Holocene. Instead, deglacial sea-level rises caused an extensive development of floodplains and wetlands on the exposed continental shelf, providing habitats for the spread of C4 sedges and grasses. The progressive subsidence of Chinese coastal areas and the broadening of the continental shelf over the late Quaternary explains the nearly absence of C4 plant occurrence during Termination V and a gradual increase of the C4-plant contribution across interglacial peaks. Taken together, changes in coastal environments should be considered when interpreting marine-based vegetation reconstructions from subtropical Asia

Primary tumor type prediction based on US nationwide genomic profiling data in 13,522 patients.

Timely and accurate primary tumor diagnosis is critical, and misdiagnoses and delays may cause undue health and economic burden. To predict primary tumor types based on genomics data from a de-identified US nationwide clinico-genomic database (CGDB), the XGBoost-based Clinico-Genomic Machine Learning Model (XC-GeM) was developed to predict 13 primary tumor types based on data from 12,060 patients in the CGDB, derived from routine clinical comprehensive genomic profiling (CGP) testing and chart-confirmed electronic health records (EHRs). The SHapley Additive exPlanations method was used to interpret model predictions. XC-GeM reached an outstanding area under the curve (AUC) of 0.965 and Matthews correlation coefficient (MCC) of 0.742 in the holdout validation dataset. In the independent validation cohort of 955 patients, XC-GeM reached 0.954 AUC and 0.733 MCC and made correct predictions in 77% of non-small cell lung cancer (NSCLC), 86% of colorectal cancer, and 84% of breast cancer patients. Top predictors for the overall model (e.g. tumor mutational burden (TMB), gender, and KRAS alteration), and for specific tumor types (e.g., TMB and EGFR alteration for NSCLC) were supported by published studies. XC-GeM also achieved an excellent AUC of 0.880 and positive MCC of 0.540 in 507 patients with missing primary diagnosis. XC-GeM is the first algorithm to predict primary tumor type using US nationwide data from routine CGP testing and chart-confirmed EHRs, showing promising performance. It may enhance the accuracy and efficiency of cancer diagnoses, enabling more timely treatment choices and potentially leading to better outcomes

An investigation into taxpayer consciousness of their marginal income tax rates

This research paper investigates the level of marginal income tax rate consciousness of taxpayers in Singapore. It was hypothesized in this paper that (1) the general Singapore population will tend to overestimate their marginal income tax rate, (2) higher income will lead to higher probability of an individual over or underestimating his marginal income tax rate, and (3) 8 identified factors have significant impact in explaining the difference in the level of marginal income tax rate consciousness

Primary tumor type prediction based on US nationwide genomic profiling data in 13,522 patients

Timely and accurate primary tumor diagnosis is critical, and misdiagnoses and delays may cause undue health and economic burden. To predict primary tumor types based on genomics data from a de-identified US nationwide clinico-genomic database (CGDB), the XGBoost-based Clinico-Genomic Machine Learning Model (XC-GeM) was developed to predict 13 primary tumor types based on data from 12,060 patients in the CGDB, derived from routine clinical comprehensive genomic profiling (CGP) testing and chart-confirmed electronic health records (EHRs). The SHapley Additive exPlanations method was used to interpret model predictions. XC-GeM reached an outstanding area under the curve (AUC) of 0.965 and Matthew's correlation coefficient (MCC) of 0.742 in the holdout validation dataset. In the independent validation cohort of 955 patients, XC-GeM reached 0.954 AUC and 0.733 MCC and made correct predictions in 77% of non-small cell lung cancer (NSCLC), 86% of colorectal cancer, and 84% of breast cancer patients. Top predictors for the overall model (e.g. tumor mutational burden (TMB), gender, and KRAS alteration), and for specific tumor types (e.g., TMB and EGFR alteration for NSCLC) were supported by published studies. XC-GeM also achieved an excellent AUC of 0.880 and positive MCC of 0.540 in 507 patients with missing primary diagnosis. XC-GeM is the first algorithm to predict primary tumor type using US nationwide data from routine CGP testing and chart-confirmed EHRs, showing promising performance. It may enhance the accuracy and efficiency of cancer diagnoses, enabling more timely treatment choices and potentially leading to better outcomes

Maternal polyunsaturated fatty acids and risk for autism spectrum disorder in the MARBLES high-risk study.

Lay abstractPrior studies suggest that maternal polyunsaturated fatty acids intake during pregnancy may have protective effects on autism spectrum disorder in their children. However, they did not examine detailed timing of maternal polyunsaturated fatty acid intake during pregnancy, nor did they evaluate plasma concentrations. This study investigates whether maternal polyunsaturated fatty acids in defined time windows of pregnancy, assessed by both questionnaires and biomarkers, are associated with risk of autism spectrum disorder and other non-typical development in the children. Food frequency questionnaires were used to estimate maternal polyunsaturated fatty acid intake during the first and second half of pregnancy. Gas chromatography measured maternal plasma polyunsaturated fatty acid concentrations in the third trimester. In all, 258 mother-child pairs from a prospective cohort were included. All mothers already had a child with autism spectrum disorder and were planning a pregnancy or pregnant with another child. Children were clinically assessed longitudinally and diagnosed at 36 months. For polyunsaturated fatty acid intake from questionnaires, we only found mothers consuming more omega-3 in the second half of pregnancy were 40% less likely to have children with autism spectrum disorder. For polyunsaturated fatty acid concentrations in the third-trimester plasma, we did not observe any statistical significance in relation to the risk of autism spectrum disorder. However, our study confirmed associations from previous studies between higher maternal docosahexaenoic acid and eicosapentaenoic acid plasma concentrations in the late pregnancy and reduced risk for non-typical development. This study markedly advanced understandings of whether and when maternal polyunsaturated fatty acid intake influences risk for autism spectrum disorder and sets the stage for prevention at the behavioral and educational level

The Association Between Insurance and Transfer of Noninjured Children From Emergency Departments.

Study objectiveAmong children requiring hospital admission or transfer, we seek to determine whether insurance is associated with the decision to either admit locally or transfer to another hospital.MethodsThis cross-sectional study used Healthcare Cost and Utilization Project 2012 Nationwide Emergency Department Sample. Pediatric patients receiving care in emergency departments (EDs) who were either admitted or transferred were included. Clinical Classifications Software was used to categorize patients into noninjury diagnostic cohorts. Multivariable logistic regression models adjusting for potential confounders, including severity of illness and comorbidities, and incorporating nationally representative weights were used to determine the association between insurance and the odds of transfer relative to admission.ResultsA total of 240,620 noninjury pediatric ED events met inclusion criteria. Patient and hospital characteristics, including older age and nonteaching hospitals, were associated with greater odds of transfer relative to admission. Patients who were uninsured or had self-pay had higher odds of transfer (odds ratio [OR] 3.84; 95% confidence interval [CI] 2.08 to 7.09) relative to admission compared with those with private insurance. Uninsured and self-pay patients also had higher odds of transfer across all 13 diagnostic categories, with ORs ranging from 2.96 to 12.00. Patients with Medicaid (OR 1.05; 95% CI 0.90 to 1.22) and other insurances (OR 1.14; 95% CI 0.87 to 1.48) had similar odds of transfer compared with patients with private insurance.ConclusionChildren without insurance and those considered as having self-pay are more likely to be transferred to another hospital than to be admitted for inpatient care within the same receiving hospital compared with children with private insurance. This study reinforces ongoing concerns about disparities in the provision of pediatric ED and inpatient care

Multi‐Bioinspired Functional Conductive Hydrogel Patches for Wound Healing Management

Abstract Many hydrogel patches are developed to solve the pervasive and severe challenge of complex wound healing, while most of them still lack satisfactory controllability and comprehensive functionality. Herein, inspired by multiple creatures, including octopuses and snails, a novel muti‐functional hydrogel patch is presented with controlled adhesion, antibacterial, drug release features, and multiple monitoring functions for intelligent wound healing management. The patch with micro suction‐cup actuator array and a tensile backing layer is composed of tannin grafted gelatin, Ag‐tannin nanoparticles, polyacrylamide (PAAm) and poly(N‐isopropylacrylamide) (PNIPAm). In virtue of the photothermal gel‐sol transition of tannin grafted gelatin and Ag‐tannin nanoparticles, the patches exert a dual anti‐microbial effect and temperature‐sensitive snail mucus‐like features. In addition, as the “suction‐cups” consisting of thermal responsive PNIPAm can undergo a contract‐relax transformation, the medical patches can adhere to the objects reversibly and responsively, and release their loaded vascular endothelial growth factor (VEGF) controllably for wound healing. More attractively, benefiting from their fatigue resistance, self‐healing ability of the tensile double network hydrogel, and electrical conductivity of Ag‐tannin nanoparticles, the proposed patches can report multiple wound physiology parameters sensitively and continuously. Thus, it is believed that this multi‐bioinspired patch has immense potential for future wound healing management

The Association Between Insurance and Transfer of Noninjured Children From Emergency Departments.

Study objectiveAmong children requiring hospital admission or transfer, we seek to determine whether insurance is associated with the decision to either admit locally or transfer to another hospital.MethodsThis cross-sectional study used Healthcare Cost and Utilization Project 2012 Nationwide Emergency Department Sample. Pediatric patients receiving care in emergency departments (EDs) who were either admitted or transferred were included. Clinical Classifications Software was used to categorize patients into noninjury diagnostic cohorts. Multivariable logistic regression models adjusting for potential confounders, including severity of illness and comorbidities, and incorporating nationally representative weights were used to determine the association between insurance and the odds of transfer relative to admission.ResultsA total of 240,620 noninjury pediatric ED events met inclusion criteria. Patient and hospital characteristics, including older age and nonteaching hospitals, were associated with greater odds of transfer relative to admission. Patients who were uninsured or had self-pay had higher odds of transfer (odds ratio [OR] 3.84; 95% confidence interval [CI] 2.08 to 7.09) relative to admission compared with those with private insurance. Uninsured and self-pay patients also had higher odds of transfer across all 13 diagnostic categories, with ORs ranging from 2.96 to 12.00. Patients with Medicaid (OR 1.05; 95% CI 0.90 to 1.22) and other insurances (OR 1.14; 95% CI 0.87 to 1.48) had similar odds of transfer compared with patients with private insurance.ConclusionChildren without insurance and those considered as having self-pay are more likely to be transferred to another hospital than to be admitted for inpatient care within the same receiving hospital compared with children with private insurance. This study reinforces ongoing concerns about disparities in the provision of pediatric ED and inpatient care