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As student bodies on college campuses in the United States (U.S.) continue to diversify, university counseling centers have begun to recognize the importance of hiring multilingual therapists and trainees to meet the needs of 66 million U.S. residents who speak languages other than English. The study used a qualitative approach to better understand the experiences of multilingual therapists and trainees working at university counseling centers in the U.S. Thirty-one participants (three men and 28 women; 27 senior staff and four trainees) completed an online survey with six open-ended questions. The following themes were identified: rewards and benefits of providing multilingual therapy, supervision experiences given, and organizational support provided to multilingual therapists. Senior staff participants also make suggestions for trainees who would like to practice multilingual therapy as well as support that agencies can offer to their multilingual therapists. Limitations, practical implications, and future research directions are discussed. [ABSTRACT FROM AUTHOR]

In recent years, large-scale international assessments have been increasingly used to evaluate and compare the quality of education across regions and countries. However, measurement variance between different versions of these assessments often posts threats to the validity of such cross-cultural comparisons. In this study, we investigated the cross-language, cross-cultural validity of the Programme for International Student Assessment 2006 Science assessment via three differential item functioning (DIF) analyses between the USA and Canada, Chinese Hong Kong and mainland China, and between the USA and mainland China. Furthermore, we explored three plausible causes of DIF via content analysis, namely language, curriculum and cultural differences. Our results revealed that differential curriculum coverage was the most serious cause of DIF among the three factors we investigated in this study, and differential content familiarity also contributed to DIF here. We discussed the implications of the findings for future international assessment development, and for how to best define 'scientific literacy' for students around the world.

Using remote sensing images to identify crop plots and estimate crop planting area is an important part of agricultural remote sensing monitoring. High-resolution remote sensing images can provide rich information regarding texture, tone, shape, and spectrum of ground objects. With the advancement of sensor and information technologies, it is now possible to categorize crops with pinpoint accuracy. This study defines crop mapping as a semantic segmentation problem; therefore, a deep learning method is proposed to identify the distribution of corn and soybean using the differences in the spatial and spectral features of crops. The study area is located in the southwest of the Great Lakes in the United States, where corn and soybean cultivation is concentrated. The proposed attention mechanism deep learning model, A2SegNet, was trained and evaluated using three years of Sentinel-2 data, collected between 2019 and 2021. The experimental results show that this method is able to fully extract the spatial and spectral characteristics of crops, and its classification effect is significantly better than that of the baseline method, and it has better classification performance than other deep learning models. We cross verified the trained model on the test sets of different years through transfer learning in both spatiotemporal and spatial dimensions. Proving the effectiveness of the attention mechanism in the process of knowledge transfer, A2SegNet showed better adaptability. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine similarities and differences in concepts of reflection among American and Japanese pre-service teachers majoring in early childhood education. Pre-service teachers completed a survey asking them to describe approaches and processes of reflection in their daily practice. The quantitative and qualitative data analysis revealed that both American and Japanese pre-service teachers considered reflection to be related to their thinking, improvement, and morals. However, although American pre-service teachers viewed reflection to be associated with teaching skills, none of their Japanese counterparts perceived it in this way. Their cultures clearly influenced their concepts of reflection: specifically, American pre-service teachers noted that college instructors encouraged them to write down their reflections, while their Japanese counterparts indicated that reflection was supported by talking to others. Reflection was perceived to be a disposition by American pre-service teachers, whereas their Japanese counterparts viewed it as a skill that they had already learned from early childhood. Implications for teacher education are also presented. (Contains 2 tables.)

Quantile treatment effects can be important causal estimands in the evaluation of biomedical treatments or interventions for health outcomes such as birthweight and medical cost. However, the existing estimators require either a propensity score model or a conditional density vector model is correctly specified, which is difficult to verify in practice. In this paper, we allow multiple models for propensity score and conditional density vector, then construct a class of calibration estimators based on multiple imputation and inverse probability weighting approaches via empirical likelihood. The resulting estimators multiply robust in the sense that they are consistent if any one of these models is correctly specified. Moreover, we propose another class of ensemble estimators to reduce computational burden while ensuring multiple robustness. Simulations are performed to evaluate the finite sample performance of the proposed estimators. Two applications to the birthweight of infants born in the United States and AIDS Clinical Trials Group Protocol 175 data are also presented. [ABSTRACT FROM AUTHOR]

The transmission of coronavirus disease‐2019 (COVID‐19) epidemic is a global emergency, which is worsened by the genetic mutations of SARS‐CoV‐2. However, till date, few statistical studies have researched the COVID‐19 spread patterns in terms of the variant cases. Hence, this paper aims to explore the associated risk factors of Delta variant, the most contagious strain of COVID‐19. The study collected the state‐level COVID‐19 Delta variant cases in the United States during a 12‐week period and included potential environmental, socioeconomic, and public prevention factors as independent variables. Instead of regarding the covariate effects as constant, this paper proposes a flexible Bayesian hierarchical model with spatio‐temporally varying coefficients to account for data heterogeneity. The method enables us to cluster the states into distinctive groups based on the temporal trends of the coefficients and simultaneously identify significant risk factors for each cluster. The findings contribute novel insight into the dynamics of covariate effects on the COVID‐19 Delta variant over space and time, which could help the government develop targeted prevention measures for vulnerable regions based on the selected risk factors. [ABSTRACT FROM AUTHOR]

Background: Adverse events induced by drug-drug interactions are a major concern in the United States. Current research is moving toward using electronic health record (EHR) data, including for adverse drug events discovery. One of the first steps in EHR-based studies is to define a phenotype for establishing a cohort of patients. However, phenotype definitions are not readily available for all phenotypes. One of the first steps of developing automated text mining tools is building a corpus. Therefore, this study aimed to develop annotation guidelines and a gold standard corpus to facilitate building future automated approaches for mining phenotype definitions contained in the literature. Furthermore, our aim is to improve the understanding of how these published phenotype definitions are presented in the literature and how we annotate them for future text mining tasks. Results: Two annotators manually annotated the corpus on a sentence-level for the presence of evidence for phenotype definitions. Three major categories (inclusion, intermediate, and exclusion) with a total of ten dimensions were proposed characterizing major contextual patterns and cues for presenting phenotype definitions in published literature. The developed annotation guidelines were used to annotate the corpus that contained 3971 sentences: 1923 out of 3971 (48.4%) for the inclusion category, 1851 out of 3971 (46.6%) for the intermediate category, and 2273 out of 3971 (57.2%) for exclusion category. The highest number of annotated sentences was 1449 out of 3971 (36.5%) for the "Biomedical & Procedure" dimension. The lowest number of annotated sentences was 49 out of 3971 (1.2%) for "The use of NLP". The overall percent inter-annotator agreement was 97.8%. Percent and Kappa statistics also showed high inter-annotator agreement across all dimensions. Conclusions: The corpus and annotation guidelines can serve as a foundational informatics approach for annotating and mining phenotype definitions in literature, and can be used later for text mining applications. [ABSTRACT FROM AUTHOR]

Objective: Suicide ideation and attempts are serious public health concerns in the U.S. Previous studies focus mainly on individual factors that cause suicide and therefore, it is imperative to examine the impact of the environment on the onset of suicide risk. This study explored the effects of perceived race/ethnicity-based discrimination (PD; perceived institutional discrimination and perceived interpersonal discrimination) on the change in suicidal thoughts and attempts among racial/ethnic minority (REM) participants at risk for depression over time using a longitudinal nationally representative dataset. Design and methods: The sample consisted a total of 1,253 REM participants from the National Epidemiologic Survey on Alcohol and Related Conditions Wave 1 and 2 datasets. Participants were categorized into three conditions: (1) no suicidal thoughts/attempts at Wave 1, who were at risk for onset of suicidal thoughts at Wave 2, (2) no suicidal thoughts/attempts at Wave 1, who were at risk for onset of both suicidal thoughts and attempts at Wave 2, and (3) had suicidal thoughts but no attempts at Wave 1, who were at risk for initiating suicidal attempt at Wave 2. Three logistic regressions were performed to examine the associations between PD and the three suicidal conditions, controlling for sociodemographic factors. Results: Regression results showed that perceived institutional discrimination predicted onset of suicidal thoughts for Condition 1 (OR = 1.67, 95% CI:1.05–2.66) and initiation of suicidal attempts for Condition 2 (OR = 2.67, 95% CI:1.30–5.48), whereas perceived interpersonal discrimination predicted onset of suicidal thoughts and attempts for Condition 1 (OR = 2.34, 95% CI:1.17–4.66). Conclusions: PD may have detrimental effects on suicidal behaviors among REM individuals with depressive symptoms. Development of suicide prevention programs needs to take into account PD and be specific for different at-risk groups. This also foregrounds the importance of promoting anti-discrimination policies/programs as a suicide preventive intervention for REM individuals with depressive symptoms. [ABSTRACT FROM AUTHOR]

With increasing trend of polypharmacy, drug-drug interaction (DDI)-induced adverse drug events (ADEs) are considered as a major challenge for clinical practice. As premarketing clinical trials usually have stringent inclusion/exclusion criteria, limited comedication data capture and often times small sample size have limited values in study DDIs. On the other hand, ADE reports collected by spontaneous reporting system (SRS) become an important source for DDI studies. There are two major challenges in detecting DDI signals from SRS: confounding bias and false positive rate. In this article, we propose a novel approach, propensity score-adjusted three-component mixture model (PS-3CMM). This model can simultaneously adjust for confounding bias and estimate false discovery rate for all drug-drug-ADE combinations in FDA Adverse Event Reporting System (FAERS), which is a preeminent SRS database. In simulation studies, PS-3CMM performs better in detecting true DDIs comparing to the existing approach. It is more sensitive in selecting the DDI signals that have nonpositive individual drug relative ADE risk (NPIRR). The application of PS-3CMM is illustrated in analyzing the FAERS database. Compared to the existing approaches, PS-3CMM prioritizes DDI signals differently. PS-3CMM gives high priorities to DDI signals that have NPIRR. Both simulation studies and FAERS data analysis conclude that our new PS-3CMM is a new method that is complement to the existing DDI signal detection methods. [ABSTRACT FROM AUTHOR]

The subseasonal predictability of surface temperature and precipitation is examined using two global ensemble prediction systems (ECMWF VarEPS and NCEP CFSv2), with an emphasis on the week 3–4 lead (i.e. 15–28 days ahead) fortnight-average anomaly correlation skill over the United States, in each calendar season. Although the ECMWF system exhibits slightly higher skill for both temperature and precipitation in general, these two systems show similar geographical variations in the week 3–4 skill in all seasons and encouraging skill in certain regions. The regions of skill are then interpreted in terms of large-scale teleconnection patterns. Over the southwest US in summer, the North American monsoon system leads to higher skill in precipitation and surface temperature, while high skill over northern California in spring is found to be associated with the seasonal variability of the Arctic Oscillation (AO). During winter, in particular, week 3–4 predictability is found to be higher during extreme phases of the El Niño–Southern Oscillation, Pacific-North American (PNA)/Tropical-Northern Hemisphere mode, and AO/North Atlantic Oscillation (NAO). Both forecast systems are found to predict these teleconnection indices quite skillfully, with the anomaly correlation of the wintertime NAO and PNA exceeding 0.5 for both models. In both models, the subseasonal contribution to the PNA skill is found to be larger than for the NAO, where the seasonal component is large. [ABSTRACT FROM AUTHOR]

Drug-drug interactions (DDIs) are a common cause of adverse drug events (ADEs). The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair-wise drug interactions, and methods to detect high-dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug-count response models for detecting high-dimensional drug combinations that induce myopathy. The "count" indicates the number of drugs in a combination. One model is called fixed probability mixture drug-count response model with a maximum risk threshold (FMDRM-MRT). The other model is called count-dependent probability mixture drug-count response model with a maximum risk threshold (CMDRM-MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug-count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high-dimensional drug combinatory effects on myopathy. CMDRM-MRT identified and validated (54; 374; 637; 442; 131) 2-way to 6-way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. The consistency of 2 mixture models' parameters and local false discovery rate estimates are evaluated through statistical simulation studies. [ABSTRACT FROM AUTHOR]

Drug interaction is a leading cause of adverse drug events and a major obstacle for current clinical practice. Pharmacovigilance data mining, pharmacokinetic modeling, and text mining are computation and informatic tools on integrating drug interaction knowledge and generating drug interaction hypothesis. We provide a comprehensive overview of these translational biomedical informatics methodologies with related databases. We hope this review illustrates the complementary nature of these informatic approaches and facilitates the translational drug interaction research. [ABSTRACT FROM AUTHOR]

This study examined the circumstances preceding suicide among Asian and Pacific Islander Americans (APIAs) and White American decedents using data from the National Violent Death Reporting System in the United States. After controlling for gender and age, APIAs had lower rates of recent disclosure of suicide ideation, recent mental health treatment, recent mental health problems, and intimate partner problems, but higher rates of school problems than White Americans. There were also significant Race × Age moderation effects for recent mental health, financial, and school problems and a significant Race × Gender moderation effect for intimate partner problems. [ABSTRACT FROM AUTHOR]

Background: Latinas have the highest rates of cervical cancer in the United States and the second highest rate of cervical cancer mortality. One factor in the disparity is the relatively low rate of screening for cervical cancer in this population.Methods: Eligible women who were out of adherence with cervical cancer screening (>3 years since their last Papanicolaou [Pap] test) were identified via medical record review by a federally qualified local health center. The effects of a low-intensity intervention (video delivered to participants' homes; n = 150) and a high-intensity intervention (video plus a home-based educational session; n = 146) on cervical cancer screening uptake in comparison with a control arm (usual care; n = 147) were investigated. A cost-effectiveness analysis of the interventions was conducted: all intervention costs were calculated, and the incremental cost-effectiveness ratio was computed. Finally, women with positive Pap tests were provided navigation by a community health educator to ensure that they received follow-up care.Results: A total of 443 Latinas participated. Seven months after randomization, significantly more women in the high-intensity arm received a Pap test (53.4%) in comparison with the low-intensity arm (38.7%; P < .001) and the usual-care arm (34.0%; P < .01). The incremental cost-effectiveness ratio for high-intensity women versus the control group amounted to $4.24. Twelve women had positive Pap tests, which encompassed diagnoses ranging from atypical squamous cells of unknown significance to invasive cancer; these women received navigation for follow-up care.Conclusions: A culturally appropriate, in-home, promotora-led educational intervention was successful in increasing cervical cancer screening among Latinas. Cancer 2017;123:666-674. © 2016 American Cancer Society. [ABSTRACT FROM AUTHOR]

During the past two decades, hydraulic fracturing has significantly improved oil and gas production from shale and tight sandstone reservoirs in the United States and elsewhere. Considering formation damage, water consumption, and environmental impacts associated with water-based fracturing fluids, efforts have been devoted to developing waterless fracturing technologies because of their potential to alleviate these issues. Herein, key theories and features of waterless fracturing technologies, including Oil-based and CO 2 energized oil fracturing, explosive and propellant fracturing, gelled LPG and alcohol fracturing, gas fracturing, CO 2 fracturing, and cryogenic fracturing, are reviewed. We then experimentally elaborate on the efficacy of liquid nitrogen in enhancing fracture initiation and propagation in concrete samples, and shale and sandstone reservoir rocks. In our laboratory study, cryogenic fractures generated were qualitatively and quantitatively characterized by pressure decay tests, acoustic measurements, gas fracturing, and CT scans. The capacity and applicability of cryogenic fracturing using liquid nitrogen are demonstrated and examined. By properly formulating the technical procedures for field implementation, cryogenic fracturing using liquid nitrogen could be an advantageous option for fracturing unconventional reservoirs. [ABSTRACT FROM AUTHOR]

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Freshwater wetlands are highly diverse, spatially heterogeneous, and seasonally dynamic systems that present unique challenges to remote sensing. Maximum likelihood and support vector machine-supervised classification were compared to map wetland plant species distributions in a deltaic environment using high-resolution WorldView-2 satellite imagery. The benefits of the sensor’s new coastal blue, yellow, and red-edge bands were tested for mapping coastal vegetation and the eight-band results were compared to classifications performed using band combinations and spatial resolutions characteristic of other available high-resolution satellite sensors. Unlike previous studies, this study found that support vector machine classification did not provide significantly different results from maximum likelihood classification. The maximum likelihood classifier provided the highest overall classification accuracy, at 75%, with user’s and producer’s accuracies for individual species ranging from 0% to 100%. Overall, maximum likelihood classification of WorldView-2 imagery provided satisfactory results for species distribution mapping within this freshwater delta system and compared favourably to results of previous studies using hyperspectral imagery, but at much lower acquisition cost and greater ease of processing. The red-edge and coastal blue bands appear to contribute the most to improved vegetation mapping capability over high-resolution satellite sensors that employ only four spectral bands. [ABSTRACT FROM PUBLISHER]

New Orleans has suffered from a significant population decline during 2000-2010, mainly due to Hurricane Katrina in 2005. Regression models are used here to explain the spatial variability of population change in New Orleans by variables such as proximity (distance or travel time) to the central business district ( CBD), a natural environment variable 'elevation', and two composite socio-demographic indices derived from variables in the census. The research reveals a U-shaped population-change profile with distance or travel time from the CBD, population loss bottomed at 4-5 kilometers (10-15 minutes) from the CBD and recovered towards both the CBD and suburbs. This suggests possible converging forces of suburbanization (that is, a nationwide trend that began long before the hurricane) and the CBD's anchoring role in the post-Katrina recovery. Greater population loss was also observed in the socioeconomically disadvantaged and lower-elevated areas, but neighborhoods of Hispanic concentration experienced less population loss. [ABSTRACT FROM AUTHOR]

Background: American Black men who have sex with men (MSM) are disproportionately affected by HIV, but the factors associated with this concentrated epidemic are not fully understood. Methods: Black MSM were enrolled in 6 US cities to evaluate a multi-component prevention intervention, with the current analysis focusing on the correlates of being newly diagnosed with HIV compared to being HIV-uninfected or previously diagnosed with HIV. Results: HPTN 061 enrolled 1553 Black MSM whose median age was 40; 30% self-identified exclusively as gay or homosexual, 29% exclusively as bisexual, and 3% as transgender. About 1/6th (16.2%) were previously diagnosed with HIV (PD); of 1263 participants without a prior HIV diagnosis 7.6% were newly diagnosed (ND). Compared to PD, ND Black MSM were younger (p<0.001); less likely to be living with a primary partner (p<0.001); more likely to be diagnosed with syphilis (p<0.001), rectal gonorrhea (p = 0.011) or chlamydia (p = 0.020). Compared to HIV-uninfected Black MSM, ND were more likely to report unprotected receptive anal intercourse (URAI) with a male partner in the last 6 months (p<0.001); and to be diagnosed with syphilis (p<0.001), rectal gonorrhea (p = 0.004), and urethral (p = 0.025) or rectal chlamydia (p<0.001). They were less likely to report female (p = 0.002) or transgender partners (p = 0.018). Multivariate logistic regression analyses found that ND Black MSM were significantly more likely than HIV-uninfected peers to be unemployed; have STIs, and engage in URAI. Almost half the men in each group were poor, had depressive symptoms, and expressed internalized homophobia. Conclusions: ND HIV-infected Black MSM were more likely to be unemployed, have bacterial STIs and engage in URAI than other Black MSM. Culturally-tailored programs that address economic disenfranchisement, increase engagement in care, screen for STIs, in conjunction with safer sex prevention interventions, may help to decrease further transmission in this heavily affected community. [ABSTRACT FROM AUTHOR]

We assessed associations in substance use, psychosocial characteristics, and HIV-related sexual risk behaviors, comparing characteristics of Black men who only have sex with other men only (BMSMO; n = 839) to Black men who have sex with men and women (BMSMW; n = 590). The study analyzed baseline data from the HIV Prevention Trials Network Brothers Study (HPTN 061), a feasibility study of a multi-component intervention for Black MSM in six US cities. Bivariate analyses compared BMSMO to BMSMW along demographics, substance use, psychosocial characteristics, and HIV-related sexual risk behaviors. Logistic regression models then assessed multivariable associations between being BMSMW and the odds of engaging in HIV-related sexual risk behaviors. Adjusted analyses revealed that BMSMW remained more likely to have unprotected anal intercourse while under the influence of alcohol (AOR: 1.45; 95 % CI:1.11–1.90) and were more likely to receive money/drugs for sex (AOR: 2.11; 95 % CI:1.48–3.03), compared to BMSMO. Substance use is an important factor to be considered when developing risk-reduction interventions for BMSMW. Structural interventions that address factors that may contribute to exchange sex among these men are also warranted. [ABSTRACT FROM AUTHOR]

Background: Black men who have sex with men (MSM) in the United States (US) are affected by HIV at disproportionate rates compared to MSM of other race/ethnicities. Current HIV incidence estimates in this group are needed to appropriately target prevention efforts. Methods: From July 2009 to October 2010, Black MSM reporting unprotected anal intercourse with a man in the past six months were enrolled and followed for one year in six US cities for a feasibility study of a multi-component intervention to reduce HIV infection. HIV incidence based on HIV seroconversion was calculated as number of events/100 person-years. Multivariate proportional hazards modeling with time-dependent covariates was used to identify correlates of HIV acquisition. Results: Of 1,553 Black MSM enrolled, 1,164 were HIV-uninfected at baseline and included in follow-up. Overall annual HIV incidence was 3.0% (95% confidence interval (CI): 2.0, 4.4%) and 5.9% among men ≤30 years old (95% CI: 3.6, 9.1%). Men ≤30 years old reported significantly higher levels of sexual risk and were more likely to have a sexually transmitted infection diagnosed during follow-up. Younger men also were more likely to not have a usual place for health care, not have visited a health care provider recently, and to have unmet health care needs. In multivariate analysis, age ≤30 years (hazard ratio (HR): 3.4; 95% CI: 1.4, 8.3) and unprotected receptive anal intercourse with HIV-positive or unknown status partners (HR: 4.1; 95% CI: 1.9, 9.1) were significantly associated with HIV acquisition. Conclusion: In the largest cohort of prospectively-followed Black MSM in the US, HIV incidence was high, particularly among young men. Targeted, tailored and culturally appropriate HIV prevention strategies incorporating behavioral, social and biomedical based interventions are urgently needed to lower these rates. [ABSTRACT FROM AUTHOR]

The purpose of this article is to investigate differences between the US and China in (1) employees' level of engagement in the five dimensions of organizational citizenship behavior (OCB) identified by Organ (), and (2) the effects of perceived distributive justice and perceived supervisor support on OCB. Results suggest that Chinese respondents have a higher level of sportsmanship and courtesy, but a lower level of civic virtue than the US respondents. In addition, perceived supervisor support is significantly related to all five OCB dimensions for the Chinese sample, whereas for the US sample, perceived distributive justice is significantly related to conscientiousness and sportsmanship and marginally related to altruism. A follow-up study was conducted in the US to examine the direct effects of such cultural factors as individualistic/collectivistic orientation and power distance orientation on each of the five OCB dimensions, and their moderating effects on the relationships of the five OCB dimensions with perceived supervisor support and perceived distributive justice. Results suggest an effect of individualistic/collectivistic orientation on the five OCB dimensions. No relationship was found between power distance orientation and OCB. Moreover, the results did not support our predictions regarding the moderating effects of individualistic/collectivistic orientation and power distance orientation on the relationships between OCB dimensions and perceived supervisor support or perceived distributive justice. [ABSTRACT FROM AUTHOR]

Ceftriaxone, an FDA-approved third-generation cephalosporin antibiotic, has antimicrobial activity against both gram-positive and gram-negative organisms. Generally, ceftriaxone is used for a variety of infections such as community-acquired pneumonia, meningitis and gonorrhea. Its primary molecular targets are the penicillin-binding proteins. However, other activities of ceftriaxone remain unknown. Herein, we report for the first time that ceftriaxone has antitumor activity in vitro and in vivo. Kinase profiling results predicted that Aurora B might be a potential ‘off’ target of ceftriaxone. Pull-down assay data confirmed that ceftriaxone could bind with Aurora B in vitro and in A549 cells. Furthermore, ceftriaxone (500 µM) suppressed anchorage-independent cell growth by targeting Aurora B in A549, H520 and H1650 lung cancer cells. Importantly, in vivo xenograft animal model results showed that ceftriaxone effectively suppressed A549 and H520 lung tumor growth by inhibiting Aurora B. These data suggest the anticancer efficacy of ceftriaxone for the treatment of lung cancers through its inhibition of Aurora B. [ABSTRACT FROM PUBLISHER]

Remote-sensing image classification based on the vegetation–impervious surface–soil (V-I-S) model and land-surface temperature (LST) has proved to be more efficient in characterizing the urban landscape than conventional spectral-based classification. However, current literature emphasizes discussion of the classifier's accuracy improvement achieved by the input of V-I-S fractions and LST over conventional spectral-based classification while ignoring the stability evaluation. Hence, this study proposes an evaluation framework for exploring the superiority of the input features and the stability of classifiers by integrating statistical randomization techniques and a kappa-error diagram. The evaluation framework was applied to case studies for demonstrating the superiority of V-I-S fractions and LST in the context of urban land-use classification with five different types of classifiers, including the maximum likelihood classifier (MLC), the tree classifier, the Bagging classifier, the random forest (RF) and the support vector machine (SVM). It followed that the use of V-I-S fractions and LST (1) could alleviate the ‘salt and pepper’ effect; (2) is preferred by tree and tree-based ensembles for branch splitting; (3) could produce classification trees with less complexity; (4) could benefit the stability of classifiers in addition to the accuracy improvement; and (5) could allow histograms following nearly normal distribution in its feature space, which boosts the performance of MLC. It is shown that MLC becomes comparable with modern classifiers when trained with V-I-S fractions and LST combination. Because of its adequacy and simplicity, MLC is recommended for urban land-use classification when V-I-S fractions and LST are used as the only input features. However, replacing them with, or including, the band reflectance might degrade MLC. A direct use of spectral band reflectance is not recommended for any of the classification approaches being considered in this study, except for SVM, which is the most robust classifier as it has a consistently high performance for all the input feature combinations. We recommend using tree-based ensemble classifiers or SVM when V-I-S fractions and LST as well as the band reflectance are all used in the classification. The proposed evaluation framework can also be applied to the assessment of input features and classifiers in other remote-sensing classification endeavours. [ABSTRACT FROM PUBLISHER]

This report offers a cross-cultural framework for defining and assessing cross-cultural competence via emphasis upon U.S. and Chinese perspectives. In doing so, the authors seek to "walk the talk" regarding cross-cultural exchange by illustrating how cross-cultural co-authorship can enrich the research process. Cross-Cultural Competence is defined and relevant factors that compose it are delineated. This is followed with an assessment approach that can be employedfor assessment of cross-cultural competence regarding effectiveness and improvement. In doing so, the researchers are seeking to underscore the relevance of cross-cultural competence with regard to both the theoretical concept itselfand how it can be practiced within cross-cultural authorship ofscholarly works such as this. [ABSTRACT FROM AUTHOR]

The objective of this paper is to study the direct and mediating effects on the motivation to become self-employed of a set of two individual factors (entrepreneurial self-efficacy and risk-taking) and five environmental factors (family self-employment background, social networks, social norms, legal system support and governmental support). Based on 535 cases from the United States, results show that legal system support, social networks, social norms, entrepreneurial self-efficacy and risk-taking had a strong impact on motivation for self-employment. Family self-employment history only had a direct effect and social networks and social norms only had an indirect effect on motivation for self-employment. Our study contributes to the literature by studying motivation for self-employment, at the "middle level" of complexity by providing a summary evaluation of a model involving 17 relationships among eight constructs. In so doing, we have also given substantial attention to context. Our results suggest the need to take into account individual and environmental factors systemically and contextually. Limitations and future research are discussed. [ABSTRACT FROM AUTHOR]

We assess the oil price sensitivities and oil risk premiums of NYSE listed oil & gas firms' returns by using a two-step regression analysis under two different arbitrage pricing models. Thus, we apply the Fama and French (1992) factor returns in a study of oil stocks. In all, we find that the return of oil stocks is positively associated with the return of the market, the increase of the spot crude oil price, and negatively with the firm's book-to-market ratio. The oil firms" sensitivities to the market, the oil price and the book-to-market ratio are positively priced by the market under the integrated model. However. both the size and significance of the oil risk premium are unstable. This suggests that increases in the oil price impact on expectations about the oil stocks' future return. The positive oil risk premium may disappear as investors change their perception of the effect of oil price changes on stock returns. [ABSTRACT FROM AUTHOR]

What role does Professional Development School preparation play in teacher retention? We surveyed PDS and non-PDS graduates of five school-university partnerships to investigate preparation for teaching, employment, proficiency, efficacy, and participation in professional activities. Retention rates were 79% or above, with higher PDS than non-PDS rates at two sites. Most graduates felt prepared, proficient, and effective. PDS graduates had significantly higher self and principal ratings at one site. We conclude that PDS programs have the potential to offer a valuable model for preparing teachers who will remain in the profession, but the quality of the PDS program is paramount. [ABSTRACT FROM AUTHOR]

The photomutagenicity of 16 polycyclic aromatic hydrocarbons (PAHs), all on the United States Environmental Protection Agency (US EPA) priority pollutant list, was studied. Concomitant exposing the Salmonella typhimurium bacteria strain TA102 to one of the PAHs and light (1.1 J/cm2 UVA+2.1 J/cm2 visible) without the activation enzyme S9, strong photomutagenic response is observed for anthracene, benz[a]anthracene, benzo[ghi]perylene, benzo[a]pyrene, indeno[1,2,3-cd]pyrene, and pyrene. Under the same conditions, acenaphthene, acenaphthylene, benzo[k]fluoranthene, chrysene, and fluorene are weakly photomutagenic. Benzo[b]fluoranthene, fluoranthene, naphthalene, phenanthrene, and dibenz[a,h]anthracene are not photomutagenic. These results indicate that PAHs can be activated by light and become mutagenic in Salmonella TA102 bacteria. At the same time, the mutagenicity for all the 16 PAHs was examined with the standard mutagenicity test with 10% S9 as the activation system. Benzo[b]fluoranthene, benzo[k]fluoranthene, chrysene, acenaphthylene, and fluorene are weakly mutagenic, while the rest of the PAHs are not. In general, the photomutagenicity of PAHs in TA102 does not correlate with their S9-activated mutagenicity in either TA102 or TA98/TA100 since they involve different activation mechanisms. [Copyright &y& Elsevier]

Land surface soil moisture (SM) monitoring is crucial for global water cycle and agricultural dryness research. The FengYun-3C Microwave Radiation Imager (FY-3C/MWRI) collects various Earth geophysical parameters, and the FY-3C/MWRI SM product (FY-3C VSM) has been widely applied to determine regional-scale surface SM contents. The FY-3C VSM retrieval accuracy in different seasons was evaluated by calculating the root mean square error (RMSE), unbiased RMSE (ubRMSE), mean absolute error (MAE), and correlation coefficient (R) values between the retrieved and measured SM. A lower accuracy in July (RMSE = 0.164 cm3/cm3, ubRMSE = 0.130 cm3/cm3, and MAE = 0.120 cm3/cm3) than in the other months was found due to the impacts of vegetation and climate variations. To show a detailed relationship between SM and multiple factors, including vegetation coverage, location, and elevation, quantile regression (QR) models were used to calculate the correlations at different quantiles. Except for the elevation at the 0.9 quantile, the QR models of the measured SM with the FY-3C VSM, MODIS NDVI, latitude, and longitude at each quantile all passed the significance test at the 0.005 level. Thus, the MODIS NDVI, latitude, and longitude were selected for error correction during the surface SM retrieval process using FY-3C VSM. Multivariate linear regression (MLR) and multivariate back-propagation neural network (MBPNN) models with different numbers of input variables were built to improve the SM monitoring results. The MBPNN model with three inputs (MBPNN-3) achieved the highest R (0.871) and lowest RMSE (0.034 cm3/cm3), MAE (0.026 cm3/cm3), and mean relative error (MRE) (20.7%) values, which were better than those of the MLR models with one, two, or three independent variables (MLR-1, -2, -3) and those of the MBPNN models with one or two inputs (MBPNN-1, -2). Then, the MBPNN-3 model was applied to generate the regional SM in the United States from January 2019 to October 2019. The estimated SM images were more consistent with the measured SM than the FY-3C VSM. This work indicated that combining FY-3C VSM data with the MBPNN-3 model could provide precise and reliable SM monitoring results. [ABSTRACT FROM AUTHOR]

Background: Glyphosate is the most widely used herbicide in the USA and worldwide. There has been considerable debate about its carcinogenicity. Epidemiological studies suggest that multiple myeloma (MM) and non-Hodgkin lymphoma (NHL) have a positive and statistically significant association with glyphosate exposure. As a B cell genome mutator, activation-induced cytidine deaminase (AID) is a key pathogenic player in both MM and B cell NHL. Methods: Vk*MYC is a mouse line with sporadic MYC activation in germinal center B cells and considered as the best available MM animal model. We treated Vk*MYC mice and wild-type mice with drinking water containing 1000 mg/L of glyphosate and examined animals after 72 weeks. Results: Vk*MYC mice under glyphosate exposure developed progressive hematological abnormalities and plasma cell neoplasms such as splenomegaly, anemia, and high serum IgG. Moreover, glyphosate caused multiple organ dysfunction, including lytic bone lesions and renal damage in Vk*MYC mice. Glyphosate-treated wild-type mice developed benign monoclonal gammopathy with increased serum IgG, anemia, and plasma cell presence in the spleen and bone marrow. Finally, glyphosate upregulated AID in the spleen and bone marrow of both wild-type and Vk*MYC mice. Conclusions: These data support glyphosate as an environmental risk factor for MM and potentially NHL and implicate a mechanism underlying the B cell-specificity of glyphosate-induced carcinogenesis observed epidemiologically. [ABSTRACT FROM AUTHOR]

Abstract: The Social Relations Model was used to compare cross-observer agreement and self-concept consistency in trait judgments in the United States, Mexico, Venezuela, and China. Target participants recruited friends and family members who comprised separate friend and family round-robin groups. Consistent with trait perspectives, in all cultures, (a) consensus and self-other agreement in trait judgments was found for most traits within the friend and family contexts, (b) across-context consensus was observed for at least some traits, and (c) self-concept consistency across contexts was substantial. Consistent with cultural psychology perspectives, consensus was generally greatest in the United States, intermediate in Mexico and Venezuela, and lowest in China. However, measures of dialecticism, self-construals, and cultural tightness failed to account for the cultural differences. [Copyright &y& Elsevier]

Non-small cell lung cancer (NSCLC) is the largest contributor to cancer mortality in the United States. Traditional chemotherapies are toxic and prone to the development of drug-resistance. Recently, several drug candidates were shown to induce lysosomal membrane permeabilization (LMP) in aggressive cancers. This has led to increased interest in lysosome dysregulation as a therapeutic target. However, approaches are needed to overcome two limitations of current lysosomal inhibitors: low specificity and potency. Here, we report the development of a transformable nanomaterial which is triggered to induce LMP of lysosomes in NSCLC. The nanomaterial consists of peptide amphiphiles, which self-assemble into nanoparticles, colocalize with the lysosome, and change conformation to nanofibrils due to lysosomal pH shift, which leads to the disruption of the lysosome, cell death, and cisplatin sensitization. We have found that this cell-penetrating transformable peptide nanoparticle (CPTNP) was cytotoxic to NSCLC cells in the low-micromolar range and it synergized cisplatin cytotoxicity four-fold. Moreover, we demonstrate CPTNP's promising antitumor effect in mouse xenograft models with limited toxicity when given in combination with low dose cisplatin chemotherapy. This is the first example of enhanced LMP via transformable peptide nanomaterial and offers a promising new strategy for cancer therapy. [ABSTRACT FROM AUTHOR]

Prior research has indicated that bisphosphonates (BPs) can improve periodontal disease because of their anti-osteoporosis properties. In vitro studies have shown that BPs induce cytotoxicity, inhibit wound healing, and thus affect periodontal disease. Denosumab and BPs have alternative indications. BP and denosumab are not known to correlate with gingival disorders. We assessed such a relationship by applying Bayesian and nonproportional analyses to data in the US FDA Adverse Event Reporting System (FAERS) database. The study analyzed BPs and denosumab-reported incidents with preferred terms found in the narrow Standardized MedDRA Queries for gingival disorders. A total of 5863 reported cases of gingival disorders were associated with five BPs (alendronate, pamidronate, ibandronate, risedronate, and zoledronate) and denosumab. More than 15% of patients with gingival disorders related to BPs and denosumab other than denosumab were hospitalized over short- or long-term periods. Our findings indicated BPs and denosumab had significant reporting odds ratios (ROR), proportional reporting ratios (PRR), and information components (IC) with respect to gingival disorders. Pamidronate had the highest association (ROR = 64.58, PRR = 57.99, IC = 5.71), while the weakest association was found with denosumab (ROR = 3.61, PRR = 3.60, IC = 1.77). Significant associations were found between the six drugs and gingival pain, gingival recession, gingivitis, periodontal disease, and periodontitis. In conclusion, our comprehensive overview of the correlations, clinical characteristics, and prognoses of BPs and denosumab-related gingival disorders suggests that these issues deserve continued surveillance and appropriate management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Zhang, Zhao and Fu.)

Introduction: The prevalence of diabetes, a common chronic disease, has shown a gradual increase, posing substantial burdens on both society and individuals. In order to enhance the effectiveness of diabetes risk prediction questionnaires, optimize the selection of characteristic variables, and raise awareness of diabetes risk among residents, this study utilizes survey data obtained from the risk factor monitoring system of the Centers for Disease Control and Prevention in the United States., Methods: Following univariate analysis and meticulous screening, a more refined dataset was constructed. This dataset underwent preprocessing steps, including data distribution standardization, the application of the Synthetic Minority Oversampling Technique (SMOTE) in combination with the Round function for equilibration, and data standardization. Subsequently, machine learning (ML) techniques were employed, utilizing enumerated feature variables to evaluate the strength of the correlation among diabetes risk factors., Results: The research findings effectively delineated the ranking of characteristic variables that significantly influence the risk of diabetes. Obesity emerges as the most impactful factor, overshadowing other risk factors. Additionally, psychological factors, advanced age, high cholesterol, high blood pressure, alcohol abuse, coronary heart disease or myocardial infarction, mobility difficulties, and low family income exhibit correlations with diabetes risk to varying degrees., Discussion: The experimental data in this study illustrate that, while maintaining comparable accuracy, optimization of questionnaire variables and the number of questions can significantly enhance efficiency for subsequent follow-up and precise diabetes prevention. Moreover, the research methods employed in this study offer valuable insights into studying the risk correlation of other diseases, while the research results contribute to heightened societal awareness of populations at elevated risk of diabetes., Competing Interests: JW was employed by the company E-link Wisdom Co., Ltd., Shenzhen, China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jiang, Yang, Liu, Xia, Yang, Gong, Wang and Wang.)

At every juncture in history, the design and identification of new drugs pose significant challenges. To gain valuable insights for future drug development, we conducted a detailed analysis of New Molecular Entitiy (NME) approved by the Food and Drug Administration (FDA) from 2012 to 2022 and focused on the analysis of first-in-class (FIC) small-molecules from a perspective of a medicinal chemist. We compared the change of numbers between all the FDA-approved NMEs and FIC, which could be more visual to analyze the changing trend of FIC. To get a more visual change of molecular physical properties, we computed the annual average trends in molecular weight for FIC across various therapeutic fields. Furthermore, we consolidated essential information into three comprehensive databases, which covered the indications, canonical SMILES, structural formula, research and development (R&D) institutions, molecular weight, calculated LogP (CLogP), and route of administration on all the small-molecule pharmaceutical. Through the analysis of the database of 11 years of approvals, we forecast the development trend of NME approval in the future.

Background: Copper (Cu) is a component that performs a crucial role in the normal function and development of the human body. Nonetheless, it is still largely unclear how Cu consumption in the diet relates to the risk for all-cause and cardiovascular disease (CVD) mortality., Methods: Data from the National Health and Nutrition Examination Survey from 2001-2018 were used to conduct a prospective cohort study of individuals between the ages of 20 years and above. Regression coefficients and 95% confidence intervals for the link between dietary Cu consumption and all-cause and cardiovascular-related mortality were computed utilizing univariate and multivariate-adjusted Cox proportional hazards models., Results: A total of 197.9 million non-institutionalized American citizens were represented by the NHANES's 39,784 participants. The link between Cu in the diet and all-cause mortality was discovered to be non-linear in our restricted cubic spline regression models. When comparing the highest with the lowest quartile of Cu consumption in the diet, the weighted multivariate hazard ratios for all-cause mortality were 0.91 (0.83-0.99) for Q2, 0.88 (0.80-0.97) for Q3, and 0.86 (0.76-0.98) for Q4 (P for trend = 0.017). An identical trend was observed for cardiovascular mortality, but the association is not significant., Conclusion: The most important discovery was that higher dietary Cu consumption was associated with a lower risk of all-cause mortality. This trend was also consistent with that of cardiovascular-related mortality, but the association is not significant., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background and Objective: Abemaciclib, a cyclin-dependent kinase 4 and 6 inhibitor, demonstrated efficacy in women with hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer. Because of the limitations of clinical trials, which are not representative of large real-world populations, rare events and long-term safety concerns cannot be detected. The current study aimed to evaluate the adverse events of abemaciclib through data mining of the Food and Drug Administration Adverse Event Reporting System (FAERS)., Methods: Reporting odds ratio and Bayesian confidence propagation neural network of information components were used to quantify the adverse event signals of abemaciclib from the third quarter of 2017 to the first quarter of 2022. Serious and non-serious cases were compared using the Mann-Whitney U test or Chi-squared test, and clinical priority was assigned to signals by scoring (range 0-10 points) five features using a rating scale., Results: A total of 6125 reports of abemaciclib as the "primary suspected" and 72 significant adverse events of abemaciclib were identified. Common adverse events, such as diarrhea, neutropenia, alanine transaminase, aspartate transaminase, and serum creatinine increases, and other adverse events, including thrombosis, deep vein thrombosis, pulmonary embolism, interstitial lung disease, and pneumonitis were of high concern. Of note, 17 preferred terms were classified as unexpected adverse events that uncovered in the label. In addition, 1, 26, and 45 adverse events were identified as strong, moderate, and weak clinical priorities. The median time to onset for strong, moderate, and weak clinical priority signals was 49, 22, and 28 days, respectively. All of the disproportionality signals had early failure type features, suggesting that adverse events of abemaciclib gradually decreased over time., Conclusions: The discovery of disproportionality signals could potentially prompt improved awareness of toxicities for abemaciclib, and the results of time to onset, serious and non-serious reports, and clinical priority analyses provided some supporting evidence for clinicians to manage adverse events., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Objective: Fluid extravasation is a potentially dangerous complication associated with shoulder arthroscopy. Most relevant studies have involved respiratory system, while the primary purpose was to reveal the effects of the fluid extravasation on cardiovascular system and postoperative function., Methods: The clinical data of 92 patients was retrospective analyzed, in which 84 cases with rotator cuff injury, three cases with shoulder instability, three cases with fractures of the greater tuberosity of the humerus, and two cases with frozen shoulder. All the patients were undergoing shoulder arthroscopy. The relationship between the basic information of the patients and cardiac index (CI) or pulse pressure variation (PPV) were evaluated by linear regression analysis. The change of CI or PPV at different states were evaluated by the one-way analysis of variance. The liquid retention (TR) and postoperative clinical outcomes was analyzed using linear regression., Results: The preoperative CI was affected by anesthesia status and body position, while PPV was not affected. Multivariate mixed-effects model analysis of CI found that there was a statistically significant difference in groups of older than 55 years old and those with obesity (BMI > 24). After the operation, the retention of irrigation fluid significantly influenced the circumference of the deltoid (P < 0.001 (95%CI: [0.30, 1.00])), but not on the circumference of the deltoid, neck, and arm. The multivariate analysis of the American Shoulder and Elbow Surgery (ASES) scores at 3 and 6 months after surgery showed that the fluid retention volume was correlated with the ASES score at 3 months after surgery, especially when the retention volume was greater than 2 L (P = 0.001 (95%). %CI: [-12.49, -3.22])., Conclusion: The retention of irrigation fluid after shoulder arthroscopic surgery causes swelling of local limbs, and has an effect on peripheral blood vessels, which is mainly reflected in its influence on PPV and the postoperative function. Therefore, surgeons need to improve their surgical technique, shorten the operation time and reduce fluid retention., (© 2022 The Authors. Orthopaedic Surgery published by Tianjin Hospital and John Wiley & Sons Australia, Ltd.)

Objective: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have significantly improved clinical effects on glycemic control. However, real-world data concerning the difference in gastrointestinal adverse events (AEs) among different GLP-1 RAs are still lacking. Our study aimed to characterize and compare gastrointestinal AEs among different marketed GLP-1 RAs (exenatide, liraglutide, dulaglutide, lixisenatide, and semaglutide) based on real-world data., Methods: Disproportionality analysis was used to evaluate the association between GLP-1 RAs and gastrointestinal adverse events. Data were extracted from the US FDA Adverse Event Reporting System (FAERS) database between January 2018 and September 2022. Clinical characteristics, the time-to-onset, and the severe proportion of GLP-1 RAs-associated gastrointestinal AEs were further analyzed., Results: A total of 21,281 reports of gastrointestinal toxicity were analyzed out of 81,752 adverse event reports, and the median age of the included patients was 62 (interquartile range [IQR] 54-70) years old. Overall GLP-1 RAs were associated with increased risk of gastrointestinal system disorders (ROR, 1.46; 95% CI, 1.44-1.49), which were further attributed to liraglutide (ROR, 2.39; 95% CI, 2.28-2.51), dulaglutide (ROR, 1.39; 95% CI, 1.36-1.42), and semaglutide (ROR, 3.00; 95% CI, 2.89-3.11). Adverse events uncovered in the labels included gastroesophageal reflux disease, gastritis, bezoar, breath odor, intra-abdominal hematoma, etc. Furthermore, it was observed that semaglutide had the greatest risk of nausea (ROR, 7.41; 95% CI, 7.10-7.74), diarrhea (ROR, 3.55; 95% CI, 3.35-3.77), vomiting (ROR, 6.67; 95% CI, 6.32-7.05), and constipation (ROR, 6.17; 95% CI, 5.72-6.66); liraglutide had the greatest risk of abdominal pain upper (ROR, 4.63; 95% CI, 4.12-5.21) and pancreatitis (ROR, 32.67; 95% CI, 29.44-36.25). Most gastrointestinal AEs tended to occur within one month. Liraglutide had the highest severe rate of gastrointestinal AEs (23.31%), while dulaglutide had the lowest, with a severe rate of 12.29%., Conclusion: GLP-1 RA were significantly associated with gastrointestinal AEs, and the association was further attributed to liraglutide, dulaglutide, and semaglutide. In addition, semaglutide had the greatest risk of nausea, diarrhea, vomiting, constipation, and pancreatitis, while liraglutide had the greatest risk of upper abdominal pain. Our study provided valuable evidence for selecting appropriate GLP-1 RAs to avoid the occurrence of GLP-1 RA-induced gastrointestinal AEs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Chen, Wang, Chen and Chen.)

In the past decade (2011-2020), there was a growing interest in the discovery and development of orphan drugs for the treatment of rare diseases. However, rare diseases only account for a population of 0.65‰-1‰ which usually occur with previously unknown biological mechanisms and lack of specific therapeutics, thus to increase the demands for the first-in-class (FIC) drugs with new biological targets or mechanisms. Considering the achievements in the past 10 years, a total of 410 drugs were approved by U.S. Food and Drug Administration (FDA), which contained 151 FIC drugs and 184 orphan drugs, contributing to make up significant numbers of the approvals. Notably, more than 50% of FIC drugs are developed as orphan drugs and some of them have already been milestones in drug development. In this review, we aim to discuss the FIC small molecules for the development of orphan drugs case by case and highlight the R&D strategy with novel targets and scientific breakthroughs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

This study was to verify the long-term survival efficacy of preoperative radiotherapy (preRT) for locally advanced rectal cancer (LARC) patients and identify potential long-term survival beneficiary. Using the Surveillance, Epidemiology, and End Results (SEER) database, 7582 LARC patients were eligible for this study between 2011 and 2015 including 6066 received preRT and 1516 received surgery alone. Initial results showed that preRT prolonged the median overall survival (OS) of LARC patients (HR 0.86, 95% CI 0.75-0.98, P < 0.05), and subgroup analysis revealed that patients with age > 65 years, stage III, T3, T4, N2, tumor size > 5 cm, tumor deposits, and lymph nodes dissection (LND) ≥ 12 would benefit more from preRT (all P < 0.05). A prognostic predicting nomogram was constructed using the independent risk factors of OS identified by multivariate Cox analysis (all P < 0.05), which exhibited better prediction of OS than the 8th American Joint Cancer Committee staging system on colorectal cancer. According to the current nomogram, patients in the high-risk subgroup had a shorter median OS than low-risk subgroup (HR 2.62, 95% CI 2.25-3.04, P < 0.001), and preRT could benefit more high-risk patients rather than low-risk patients. Hence, we concluded that preRT might bring long-term survival benefits to LARC patients, especially those with high risk., (© 2022. The Author(s).)

Background: While the pharmacokinetic (PK) mechanisms for many drug interactions (DDIs) have been established, pharmacovigilance studies related to these PK DDIs are limited. Using a large surveillance database, a translational informatics approach can systematically screen adverse drug events (ADEs) for many DDIs with known PK mechanisms., Methods: We collected a set of substrates and inhibitors related to the cytochrome P450 (CYP) isoforms, as recommended by the United States Food and Drug Administration (FDA) and Drug Interactions Flockhart table™. The FDA's Adverse Events Reporting System (FAERS) was used to obtain ADE reports from 2004 to 2018. The substrate and inhibitor information were used to form PK DDI pairs for each of the CYP isoforms and Medical Dictionary for Regulatory Activities (MedDRA) preferred terms used for ADEs in FAERS. A shrinkage observed-to-expected ratio (Ω) analysis was performed to screen for potential PK DDI and ADE associations., Results: We identified 149 CYP substrates and 62 CYP inhibitors from the FDA and Flockhart tables. Using FAERS data, only those DDI-ADE associations were considered that met the disproportionality threshold of Ω > 0 for a CYP substrate when paired with at least two inhibitors. In total, 590 ADEs were associated with 2085 PK DDI pairs and 38 individual substrates, with ADEs overlapping across different CYP substrates. More importantly, we were able to find clinical and experimental evidence for the paclitaxel-clopidogrel interaction associated with peripheral neuropathy in our study., Conclusion: In this study, we utilized a translational informatics approach to discover potentially novel CYP-related substrate-inhibitor and ADE associations using FAERS. Future clinical, population-based and experimental studies are needed to confirm our findings., (© 2021 British Pharmacological Society.)

Objectives: The present study aimed to evaluate the status and trends of robotic orthopedic surgery in a clinical setting using bibliometrics., Methods: All relevant publications on the clinical use of robotic surgery in orthopedics were searched from the Web of Science database. Subsequently, data were analyzed using bibliometrics. Visualizing data of bibliographic coupling, co-citation, and co-occurrence analysis were performed using VOSviewer., Results: In total, 224 clinical studies met the included standards between 2000 to 2019. Global publications presented an increasing annual trend, with the United States found to have the largest number of publications and robotic companies active in the field (n = 99), followed by China (n = 38), and the United Kingdom (n = 27). The institution with the most contributions was the Beijing Jishuitan Hospital in China (n = 15). The most productive scholars were Tian Wei and Mont Michael A, with 14 publications each. The top 30 most cited papers list showed 29 publications to be cited on more than 40 occassions. The journal with the most related and influential publications on robotic orthopedic surgery was the Journal of Arthroplasty. Fourteen types of robots were used, with the majority applied in knee and spinal surgery. MAKO was the most widely used robot in hip and knee surgery and Mazor in spinal surgery. Most studies were small sample populations of low-quality in this field. The top 20 most frequently used keywords were identified from 950 author keywords. Research on orthopedic robots were classified into two clusters by co-occurrence networks: spinal-related robotic surgery and joint-related robotic surgery., Conclusions: The present bibliometric study summarizes the clinical research of orthopedic robots on study type, sample size, type of surgery, robot information, surgical site, most popular keywords, most cited papers, journals, authors, institutions, and countries. These findings may assist the scholars better understand the current status and research trends to guide future practice and directions., (© 2021. The Author(s).)

Background: Cardiovascular diseases are the leading causes of death in China. However, present efforts to identify the risk factors for death in patients hospitalized with heart failure (HF) are primarily focused on in-hospital mortality and 30-day mortality in the United States. Thus, a model similar to the model used for predicting the risk in patients considered for cardiovascular surgical procedures is needed to evaluate the risk of the patients admitted with a diagnosis of HF., Objective: To identify variables that can predict post-discharge one-year HF mortality and develop a risk score to assess the risk of dying within one year., Methods: In the present study, 1,742 Chinese patients with HF were randomly divided into two groups: a derivation sample group and a test sample group. A Markov Chain Monte Carlo simulation method was used to identify variables that can predict the one-year post-discharge mortality. Variables with a frequency of >1% in the bivariate analysis and that were considered clinically meaningful were eligible for further modeling analyses. The posterior probability that a variable was statistically and significantly associated with the outcome was calculated as the total number of times that the variable's 95% CI did not overlap with 1 (i.e., the reference point) divided by the total number of iterations. A variable with a probability of 0.9 or higher was considered a robust risk factor for predicting the outcome, and this was included in the final variable list. The level of statistical significance adopted was 5%., Results: Five variables that could robustly predict the one-year post-discharge mortality were identified: age, female gender, New York Heart Association functional classification score >3, left atrial diameter, and body mass index. Both derivation and test models had a receiver operating curve area of 0.79. These selected variables were used to assess the one-year HF mortality risk score, and these were divided into three groups (low, moderate, and high). The high-risk group corresponds to nearly 86% of the deaths, while the moderate group corresponds to 12% of the deaths., Conclusion: A simple 5-variable risk score can be used to assess the one-year post-discharge mortality of hospitalized Chinese patients with HF.

Midlife blood pressure is associated with structural brain changes, cognitive decline, and dementia in late life. However, the relationship between early adulthood blood pressure exposure, brain structure and function, and cognitive performance in midlife is not known. A better understanding of these relationships in the preclinical stage may advance our mechanistic understanding of vascular contributions to late-life cognitive decline and dementia and may provide early therapeutic targets. To identify resting-state functional connectivity of executive control networks (ECNs), a group independent components analysis was performed of functional MRI scans of 600 individuals from the Coronary Artery Risk Development in Young Adults longitudinal cohort study, with cumulative systolic blood pressure (cSBP) measured at nine visits over the preceding 30 y. Dual regression analysis investigated performance-related connectivity of ECNs in 578 individuals (mean age 55.5 ± 3.6 y, 323 female, 243 Black) with data from the Stroop color-word task of executive function. Greater connectivity of a left ECN to the bilateral anterior gyrus rectus, right posterior orbitofrontal cortex, and nucleus accumbens was associated with better executive control performance on the Stroop. Mediation analyses showed that while the relationship between cSBP and Stroop performance was mediated by white matter hyperintensities (WMH), resting-state connectivity of the ECN mediated the relationship between WMH and executive function. Increased connectivity of the left ECN to regions involved in reward processing appears to compensate for the deleterious effects of WMH on executive function in individuals across the burden of cumulative systolic blood pressure exposure in midlife., Competing Interests: The authors declare no competing interest.

Microplastics (MPs) have emerged as contaminants of public health and environmental concern. Although studies have reported the occurrence of MPs in sediment, quantitative determination of polyethylene terephthalate (PET) and polycarbonate (PC) concentrations is limited. In this study, marine coastal and freshwater sediment collected from various locations in South Korea, Japan and the United States were analyzed for PET and PC MPs using a depolymerization method of sample preparation followed by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) detection. PET MPs were found in surface sediments from South Korea (n = 20), Japan (n = 4) and the United States (n = 43) at concentrations (dry weight) in the ranges of

Improving adverse drug event (ADE) prediction is highly critical in pharmacovigilance research. We propose a novel information component guided pharmacological network model (IC-PNM) to predict drug-ADE signals. This new method combines the pharmacological network model and information component, a Bayes statistics method. We use 33,947 drug-ADE pairs from the FDA Adverse Event Reporting System (FAERS) 2010 data as the training data, and the new 21,065 drug-ADE pairs from FAERS 2011-2015 as the validations samples. The IC-PNM data analysis suggests that both large and small sample size drug-ADE pairs are needed in training the predictive model for its prediction performance to reach an area under the receiver operating characteristic curve [Formula: see text]. On the other hand, the IC-PNM prediction performance improved to [Formula: see text] if we removed the small sample size drug-ADE pairs from the prediction model during validation.