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As the conversion rate of preclinical studies for cancer treatment is low, user-friendly models that mimic the pathological microenvironment and drug intake with high throughput are scarce. Animal models are key, but an alternative to reduce their use would be valuable. Vascularized tumor-on-chip models combine great versatility with scalable throughput and are easy to use. Several strategies to integrate both tumor and vascular compartments have been developed, but few have been used to assess drug delivery. Permeability, intra/extravasation, and free drug circulation are often evaluated, but imperfectly recapitulate the processes at stake. Indeed, tumor targeting and chemoresistance bypass must be investigated to design promising cancer therapeutics. In vitro models that would help the development of drug delivery systems (DDS) are thus needed. They would allow selecting good candidates before animal studies based on rational criteria such as drug accumulation, diffusion in the tumor, and potency, as well as absence of side damage. In this review, we focus on vascularized tumor models. First, we detail their fabrication, and especially the materials, cell types, and coculture used. Then, the different strategies of vascularization are described along with their classical applications in intra/extravasation or free drug assessment. Finally, current trends in DDS for cancer are discussed with an overview of the current efforts in the domain. [ABSTRACT FROM AUTHOR]

Sexual risk behavior (SRB) includes behavioral (sex without contraception, sexualized substance use, sex work, sexual partner violence, other sexual activities that harm oneself or others) and affective subtypes (sexuality-related feelings of shame/guilt, relationship impairments) and leads to psychosocial and health-related consequences. Young adults comprise a vulnerable group regarding the development of SRB. The study aimed to identify SRB patterns among young adults and their relation to sexuality-related risk factors. A cross-sectional online survey measured behavioral and affective aspects of SRB with nine items. Latent class analysis was conducted to identify patterns of SRB. Gender, sexual orientation, age of first intercourse, number of sexual partners, hypersexuality, and sexual dysfunction were captured as risk factors via multinomial logistic regression. Within this convenience sample (n = 609; nfemale = 365; nmale = 245; Mage = 23.1 years), the SRB patterns unremarkable (67%; low values in all SRB subtypes), shame-ridden (17%; high values in sexual feelings of shame/guilt) and risky sexual behavior (16%; high values in all subtypes of SRB, especially sexualized drug use) were identified. The shame-ridden and risky patterns were strongly associated with higher hypersexuality values, the risky pattern moreover with being non-heterosexual, of younger age at first sexual experience, and a higher number of sexual partners. Male and sexual minority participants demonstrated SRB more often than females and heterosexuals. Within prevention and treatment of SRB, it seems beneficial to address sexuality-related feelings of shame/guilt and addictive patterns (concerning sexual behaviors/substances) via gender- and diversity-sensitive measurements. [ABSTRACT FROM AUTHOR]

Functional networks (FNs) hold significant promise in understanding brain function. Independent component analysis (ICA) has been applied in estimating FNs from functional magnetic resonance imaging (fMRI). However, determining an optimal model order for ICA remains challenging, leading to criticism about the reliability of FN estimation. Here, we propose a SMART (splitting-merging assisted reliable) ICA method that automatically extracts reliable FNs by clustering independent components (ICs) obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders. We extend SMART ICA to multi-subject fMRI analysis, validating its effectiveness using simulated and real fMRI data. Based on simulated data, the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters. Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects, the resulting reliable group-level FNs are greatly similar between the two cohorts, and interestingly the subject-specific FNs show progressive changes while age increases. Furthermore, both small-scale and large-scale brain FN templates are provided as benchmarks for future studies. Taken together, SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data, while also providing linkages between different FNs. [ABSTRACT FROM AUTHOR]

Purpose: Physically harsh discipline is associated with poor developmental outcomes among children. These practices are more prevalent in areas experiencing poverty and resource scarcity, including in low- and middle-income countries. Designed to limit social desirability bias, this cross-sectional study in rural Uganda estimated caregiver preferences for physically harsh discipline; differences by caregiver sex, child sex, and setting; and associations with indicators of household economic stress and insecurity. Method: Three-hundred-fifty adult caregivers were shown six hypothetical pictographic scenarios depicting children whining, spilling a drink, and kicking a caregiver. Girls and boys were depicted engaging in each of the three behaviors. Approximately half of the participants were shown scenes from a market setting and half were shown scenes from a household setting. For each scenario, caregivers reported the discipline strategy they would use (time out, beating, discussing, yelling, ignoring, slapping). Results: Two thirds of the participants selected a physically harsh discipline strategy (beating, slapping) at least once. Women selected more physically harsh discipline strategies than men (b = 0.40; 95% confidence interval [CI], 0.26 to 0.54). Participants shown scenes from the market selected fewer physically harsh discipline strategies than participants shown scenes from the household (b = -0.51; 95% CI, -0.69 to -0.33). Finally, caregivers selected more physically harsh discipline strategies in response to boys than girls. Indicators of economic insecurity were inconsistently associated with preferences for physically harsh discipline. Conclusions: The high prevalence of physically harsh discipline preferences warrant interventions aimed at reframing caregivers' approaches to discipline. [ABSTRACT FROM AUTHOR]

According to the Intergovernmental Panel on Climate Change (IPCC) of the United Nations (UN), rise in atmospheric concentration of carbon dioxide (CO 2 ) due to anthropogenic factors is considered as the primary driver for global climate change. With almost every major corporation around the world working towards their "net-zero goals", it is becoming increasingly important to have more technologies that can help reduce carbon footprint. Achieving sequestration of CO 2 in the subsurface through Carbon Capture Utilization and Storage (CCUS) technologies like CO 2 -Enhanced Oil Recovery, CO 2 -Enhanced Geothermal Systems, CO 2 -Enhanced Coal Bed Methane, etc. is well accepted. We introduce yet another attractive CCUS opportunity through well rehabilitation. Aqua Freed® and Aqua Gard® are well-known well rehabilitation and preventive well maintenance technologies that utilize (inject underground) liquid CO 2 for the purpose. The goal of this study was to quantify the storage capacity of Aqua Freed® and Aqua Gard®, and establish their CCUS credentials. Depending on the well being serviced, these technologies can inject up to 40 US tons of CO 2 per well. Based on field data collection and statistical modeling, we estimated that 82–96% (median 90%) of the injected CO 2 remains in the subsurface post injection. Overall, our results and analysis of the US market suggest that using CO 2 for well rehabilitation and maintenance has a storage potential of several megatonnes of CO 2 annually in the US alone. [ABSTRACT FROM AUTHOR]

While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we can gain new insights into the biology and behavioral aspects of brain health. Resting-state fMRI (rs-fMRI) can be used to identify biomarkers of these conditions and study patterns of abnormal connectivity. In this work, we estimate mental health quality for individual participants using static functional network connectivity (sFNC) data from rs-fMRI. The deep learning model uses the sFNC data as input to predict four categories of mental health quality and visualize the neural patterns indicative of each group. We used guided gradient class activation maps (guided Grad-CAM) to identify the most discriminative sFNC patterns. The effectiveness of this model was validated using the UK Biobank dataset, in which we showed that our approach outperformed four alternative models by 4-18% accuracy. The proposed model's performance evaluation yielded a classification accuracy of 76%, 78%, 88%, and 98% for the excellent, good, fair, and poor mental health categories, with poor mental health accuracy being the highest. The findings show distinct sFNC patterns across each group. The patterns associated with excellent mental health consist of the cerebellar-subcortical regions, whereas the most prominent areas in the poor mental health category are in the sensorimotor and visual domains. Thus the combination of rs-fMRI and deep learning opens a promising path for developing a comprehensive framework to evaluate and measure mental health. Moreover, this approach had the potential to guide the development of personalized interventions and enable the monitoring of treatment response. Overall this highlights the crucial role of advanced imaging modalities and deep learning algorithms in advancing our understanding and management of mental health. [ABSTRACT FROM AUTHOR]

The presence of prolonged symptoms after COVID infection worsens the workability and quality of life. 200 adults with long COVID syndrome were enrolled after medical, physical, and mental screening, and were divided into two groups based on their performance. The intervention group (n = 100) received supervised rehabilitation at Department of Pulmonology, Semmelweis University with the registration number 160/2021 between 01/APR/2021–31/DEC/2022, while an age-matched control group (n = 100) received a single check-up. To evaluate the long-term effects of the rehabilitation, the intervention group was involved in a 2- and 3-month follow-up, carrying out cardiopulmonary exercise test. Our study contributes understanding long COVID rehabilitation, emphasizing the potential benefits of structured cardiopulmonary rehabilitation in enhancing patient outcomes and well-being. Significant difference was found between intervention group and control group at baseline visit in pulmonary parameters, as forced vital capacity, forced expiratory volume, forced expiratory volume, transfer factor for carbon monoxide, transfer coefficient for carbon monoxide, and oxygen saturation (all p < 0.05). Our follow-up study proved that a 2-week long, patient-centered pulmonary rehabilitation program has a positive long-term effect on people with symptomatic long COVID syndrome. Our data showed significant improvement between two and three months in maximal oxygen consumption (p < 0.05). Multidisciplinary, individualized approach may be a key element of a successful cardiopulmonary rehabilitation in long COVID conditions, which improves workload, quality of life, respiratory function, and status of patients with long COVID syndrome. [ABSTRACT FROM AUTHOR]

The oldest-old population, those aged ≥ 80 years, is the fastest-growing group in the United States (US), grappling with an increasingly heavy burden of dementia. We aimed to dissect the trends in dementia prevalence, mortality, and risk factors, and predict future levels among this demographic. Leveraging data from the Global Burden of Disease Study 2019, we examined the trends in dementia prevalence, mortality, and risk factors (with a particular focus on body mass index, BMI) for US oldest-old adults. Through decomposition analysis, we identified key population-level contributors to these trends. Predictive modeling was employed to estimate future prevalence and mortality levels over the next decade. Between 1990 and 2019, the number of dementia cases and deaths among the oldest-old in the US increased by approximately 1.37 million and 60,000 respectively. The population growth and aging were highlighted as the primary drivers of this increase. High BMI emerged as a growing risk factor. Females showed a disproportionately higher dementia burden, characterized by a unique risk factor profile, including BMI. Predictions for 2030 anticipate nearly 4 million dementia cases and 160,000 related deaths, with a marked increase in prevalence and mortality anticipated among those aged 80–89. The past 30 years have witnessed a notable rise in both the prevalence and mortality of dementia among the oldest-old in the US, accompanied by a significant shift in risk factors, with obesity taking a forefront position. Targeted age and sex-specific public health strategies that address obesity control are needed to mitigate the dementia burden effectively. [ABSTRACT FROM AUTHOR]

Purpose: To systematically review and meta-analyse the efficacy of resistance training on quality of life (QOL), fatigue, physical function, and muscular strength in people diagnosed with cancer undergoing chemotherapy. Methods: Electronic databases PubMed, Cochrane Central, CINAHL, SCOPUS and Web of Science were systematically searched for randomised controlled trials (RCTs) that compared the effects of resistance training to control on QOL, fatigue, physical function, and lower-body and upper-body muscular strength in adults undergoing chemotherapy. Standardised mean differences (SMDs) were pooled using a random effects model. Risk of bias was assess using the risk of bias tool for randomised trials (RoB 2). Results: Seven RCTs encompassing 561 participants were included. The pooled results of seven RCTs showed that resistance training during chemotherapy significantly improved lower-body strength (n = 555, SMD 0.33, 95% CI 0.12 to 0.53, moderate-quality evidence, I2 = 23%) compared to control. There was no evidence for an effect of resistance training on QOL (n = 373, SMD 0.13, 95% CI -0.15 to 0.42, low-quality evidence, I2 = 0%), fatigue (n = 373, SMD -0.08, 95% CI -0.37 to 0.22, low-quality evidence, I2 = 20%), physical function (n = 198, SMD 0.61, 95% CI -0.73 to 1.95, very low-quality evidence, I2 = 83%), or upper-body strength (n = 413, SMD 0.37, 95% CI -0.07 to 0.80, very low-quality evidence, I2 = 69%). Conclusions: Resistance training may improve lower-body strength in patients undergoing chemotherapy treatment compared to control. [ABSTRACT FROM AUTHOR]

Introduction: Inconsistency of sexual definitions may lead to misunderstandings when evaluating research data or delivering health education. Diverse sexual definitions are especially common with unidirectional genital contacts (only one participant is involved with their genitals). Our aim was to analyze sexual definitions of adolescents and the role of age, gender, previous sexual experience, anxiety, and body image as possible determinants of unidirectional intimate behavior definitions. Methods: Pooled cross-sectional survey data of 9th-grade Hungarian students (n = 612, mean age = 16.1 years, range from 15 to 18 years) were used from the baseline assessment (conducted in 2019 and 2020) of the Balassagyarmat Health Education Program. Our questionnaire was based on the Sexual Definitions Survey. The associations of definition of manual and oral stimulation with gender, age, sexual experience, trait anxiety, and body image were further examined in a multilevel logistic regression model. Results: The rating of different sexual behaviors as sex showed a hierarchy from kissing (10.3%) to vaginal intercourse (98.5%). Manual and oral stimulation was claimed to be sex by 73.4% and 84.3% of students. Girls (OR = 0.40; CI = 0.25–0.62) and older participants (OR = 0.75; CI = 0.59–0.96) were less likely to consider manual stimulation as sex. Conversely, previous sexual experience, anxiety, and body image were not significant predictors. Conclusions: Our study is the first to investigate sexual definitions among non-English-speaking adolescents. It contributes to the understanding of ambiguity regarding the definitions of oral and manual stimulation in this specific age group. Policy implications: As adolescents are the primary focus of sexual education, policies should take into consideration the semantic differences in sexual definitions, as these may influence the participants' interpretation of information and have an effect on their sexual behavior. [ABSTRACT FROM AUTHOR]

Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective studies is limited. Here, we analyze data of 352,277 participants from UK Biobank with 12.25-year follow-up. Compared with non-frail individuals, pre-frail and frail individuals have increased risk for incident depression independent of many putative confounds. Altogether, pre-frail and frail individuals account for 20.58% and 13.16% of depression cases by population attributable fraction analyses. Higher risks are observed in males and individuals younger than 65 years than their counterparts. Mendelian randomization analyses support a potential causal effect of frailty on depression. Associations are also observed between inflammatory markers, brain volumes, and incident depression. Moreover, these regional brain volumes and three inflammatory markers—C-reactive protein, neutrophils, and leukocytes—significantly mediate associations between frailty and depression. Given the scarcity of curative treatment for depression and the high disease burden, identifying potential modifiable risk factors of depression, such as frailty, is needed. Identifying modifiable risk factors that could prevent depression is important. Here, the authors show increased risks of incident depression in pre-frail and frail individuals and highlight the mediating role of brain structure and inflammation. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are highly toxic, carcinogenic substances. On soils contaminated with PAHs, crop cultivation, animal husbandry and even the survival of microflora in the soil are greatly perturbed, depending on the degree of contamination. Most microorganisms cannot tolerate PAH-contaminated soils, however, some microbial strains can adapt to these harsh conditions and survive on contaminated soils. Analysis of the metagenomes of contaminated environmental samples may lead to discovery of PAH-degrading enzymes suitable for green biotechnology methodologies ranging from biocatalysis to pollution control. In the present study, our goal was to apply a metagenomic data search to identify efficient novel enzymes in remediation of PAH-contaminated soils. The metagenomic hits were further analyzed using a set of bioinformatics tools to select protein sequences predicted to encode well-folded soluble enzymes. Three novel enzymes (two dioxygenases and one peroxidase) were cloned and used in soil remediation microcosms experiments. The experimental design of the present study aimed at evaluating the effectiveness of the novel enzymes on short-term PAH degradation in the soil microcosmos model. The novel enzymes were found to be efficient for degradation of naphthalene and phenanthrene. Adding the inorganic oxidant CaO2 further increased the degrading potential of the novel enzymes for anthracene and pyrene. We conclude that metagenome mining paired with bioinformatic predictions, structural modelling and functional assays constitutes a powerful approach towards novel enzymes for soil remediation. [ABSTRACT FROM AUTHOR]

An outbreak of SARS-CoV-2 (1 March to 10 May 2021) with an attack rate of 26.5% among approximately 1150 workers at a storage and distribution centre in England prompted a multidisciplinary outbreak investigation (5 May to 6 August 2021), with the aim of better understanding worker- and workplace-related risk factors for viral transmission in the warehousing sector. Overall, environmental factors (e.g., ventilation, humidity and temperature) were assessed to be appropriate at the facility. Nevertheless, 39 (51.3%) surface samples from across the site tested positive for low/ very low levels of SARS-CoV-2 RNA (Ct value ≥ 32.0 for all). Among the study participants, of whom 35.6% were confirmed or suspected cases, 95.5% reported having received COVID-19 prevention training, 100.0% reported handwashing, and 80.0% reported use of face coverings at work. Notably, 43.9% and 19.0% reported working with a symptomatic and a positive contact respectively. Furthermore, 80.5% and 46.3% had concerns regarding reduction in their income and future unemployment, respectively, due to self-isolation. The findings of this study suggest that, in addition to targeted workplace infection control measures and tailored work area specific risk assessments, an enhanced and equitable sick leave policy may help limit presenteeism and viral transmission in large workplaces. [ABSTRACT FROM AUTHOR]

The high mortality of patients with coronavirus disease 2019 (COVID-19) is effectively reduced by vaccination. However, the effect of vaccination on mortality among hospitalised patients is under-researched. Thus, we investigated the effect of a full primary or an additional booster vaccination on in-hospital mortality among patients hospitalised with COVID-19 during the delta wave of the pandemic. This retrospective cohort included all patients (n = 430) admitted with COVID-19 at Semmelweis University Department of Medicine and Oncology in 01/OCT/2021–15/DEC/2021. Logistic regression models were built with COVID-19-associated in-hospital/30 day-mortality as outcome with hierarchical entry of predictors of vaccination, vaccination status, measures of disease severity, and chronic comorbidities. Deceased COVID-19 patients were older and presented more frequently with cardiac complications, chronic kidney disease, and active malignancy, as well as higher levels of inflammatory markers, serum creatinine, and lower albumin compared to surviving patients (all p < 0.05). However, the rates of vaccination were similar (52–55%) in both groups. Based on the fully adjusted model, there was a linear decrease of mortality from no/incomplete vaccination (ref) through full primary (OR 0.69, 95% CI: 0.39–1.23) to booster vaccination (OR 0.31, 95% CI 0.13–0.72, p = 0.006). Although unadjusted mortality was similar among vaccinated and unvaccinated patients, this was explained by differences in comorbidities and disease severity. In adjusted models, a full primary and especially a booster vaccination improved survival of patients hospitalised with COVID-19 during the delta wave of the pandemic. Our findings may improve the quality of patient provider discussions at the time of admission. [ABSTRACT FROM AUTHOR]

It is proved that homeomorphic images of certain two-dimensional aperiodic tilings, such as Ammann A2 tilings, are recognizable, in both mathematical and practical senses. One implication of the results is that it is possible to search for distorted aperiodic structures in nature, where they may be hiding in plain sight. [ABSTRACT FROM AUTHOR]

Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging due to its large dimensionality and inherent multi-level covariance structure. In addition, as large-scale collaborative projects become commonplace in neuroimaging, data must increasingly be stored and analyzed from different locations. In such settings, substantial overhead can occur in terms of data transfer and coordination between participating research groups. In some cases, data cannot be pooled together due to privacy or regulatory concerns. In this work, we propose a decentralized LME model to perform a large-scale analysis of data from different collaborations without data pooling. This method is efficient as it overcomes the hurdles of data sharing and has lower bandwidth and memory requirements for analysis than the centralized modeling approach. We evaluate our model using features extracted from structural magnetic resonance imaging (sMRI) data. Results highlight gray matter reductions in the temporal lobe/insula and medial frontal regions in schizophrenia, consistent with prior studies. Our analysis also demonstrates that decentralized LME models achieve similar performance compared to the models trained with all the data in one location. We also implement the decentralized LME approach in COINSTAC, an open source, decentralized platform for federating neuroimaging analysis, providing an easy to use tool for dissemination to the neuroimaging community. [ABSTRACT FROM AUTHOR]

An improved terahertz (THz) emission from a spintronic ferromagnetic/nonmagnetic bilayer film was demonstrated by coupling with a metasurface. The spintronic bilayer was grown by the e-beam deposition of nanometer-thick Ni/Pt films on an MgO substrate. On the opposite side of the MgO substrate, the metasurface consisting of a metal line array of 10 μm width, 410 μm periodicity and 110 nm thickness were fabricated via standard UV photolithography and resistive evaporation deposition of gold. At the lower frequency range, the increase in the THz power for the metasurface-enhanced sample was as much as two orders of magnitude compared to a bare Ni/Pt spintronic emitter. A broadband enhancement in the THz power spectra was observed from 0.05 to 2 THz. The THz power enhancement spectrum of the spintronic THz emitter (STE) with metasurface shows good agreement with the calculated surface plasmon resonance frequencies. The optical fluence excitation dependence of the THz emission showed enhancement over a wide range of fluence values. Moreover, the THz emission enhancement is compared with that of a photoconductive antenna employing an identical metal line array structure. The metasurface design results in higher enhancement factor in the STE, which may be attributed to a better matching of its frequency range with the calculated resonance frequencies. This proposed design improves the efficiency at which a metal bilayer STE is launched into free space; thereby improving the signal-to-noise ratio. These results offer a way of conveniently making the investigation of STE physics, more feasible. [ABSTRACT FROM AUTHOR]

There are insufficient treatment options available for recovery related to cerebellar ataxia. Limited data using repetitive transcranial magnetic stimulation (rTMS) have demonstrated reduction of symptom burden, though associated with nonuniform cerebellar ataxia etiologies and differing rTMS treatment protocols. Additionally, there are limited available data for use of rTMS in individuals suffering from stroke-related symptoms. We present the case of a patient with chronic cerebellar ataxia following a hemorrhagic stroke who underwent inhibitory rTMS to bilateral cerebellar targets with demonstrated improvement in symptoms. [ABSTRACT FROM AUTHOR]

The goals of this study are to describe machine learning techniques employing computer-vision movement algorithms to automatically evaluate infants' general movements (GMs) in the writhing stage. This is a retrospective study of infants admitted 07/2019 to 11/2021 to a level IV neonatal intensive care unit (NICU). Infant GMs, classified by certified expert, were analyzed in two-steps (1) determination of anatomic key point location using a NICU-trained pose estimation model [accuracy determined using object key point similarity (OKS)]; (2) development of a preliminary movement model to distinguish normal versus cramped-synchronized (CS) GMs using cosine similarity and autocorrelation of major joints. GMs were analyzed using 85 videos from 74 infants; gestational age at birth 28.9 ± 4.1 weeks and postmenstrual age (PMA) at time of video 35.9 ± 4.6 weeks The NICU-trained pose estimation model was more accurate (0.91 ± 0.008 OKS) than a generic model (0.83 ± 0.032 OKS, p < 0.001). Autocorrelation values in the lower limbs were significantly different between normal (5 videos) and CS GMs (5 videos, p < 0.05). These data indicate that automated pose estimation of anatomical key points is feasible in NICU patients and that a NICU-trained model can distinguish between normal and CS GMs. These preliminary data indicate that machine learning techniques may represent a promising tool for earlier CP risk assessment in the writhing stage and prior to hospital discharge. [ABSTRACT FROM AUTHOR]

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions. [ABSTRACT FROM AUTHOR]

Significant plant- and industry-wide disruptions have occurred in the U.S. meatpacking industry during the past several years. The result has been a reinvigorated interest in the possibility that industry concentration has facilitated anticompetitive behavior and a torrent of public policy proposals to improve resiliency. In this paper, we provide a contemporary synopsis of meat processing concentration statistics with the use of annual plant-level food safety and inspection service (FSIS) data that cover all federally inspected livestock processing facilities in the U.S. for the past 30 years. Beyond considering traditional concentration measures (e.g., CR4 and HHI), we exploit the plant-level nature of the data and consider trends in processing facility consolidation, ownership changes, and how regional procurement markets have changed over time. [ABSTRACT FROM AUTHOR]

The vulnerability of fish populations to climate change is driven primarily by impacts on their most vulnerable life stages. The earliest life stages may, in many cases, be more thermally sensitive than juvenile and adult fish, as developing embryos cannot behaviourally thermoregulate. We quantified the survivorship of brook trout (Salvelinus fontinalis) embryos under a range of winter thermal regimes. In the laboratory, embryos from four populations with varying amounts of native or hatchery-introgressed ancestry were reared under four simulated winter thermal regimes relevant to the central portion of the species' range: ambient stream temperatures, ambient + 2 °C, ambient with a simulated winter snowmelt event, and ambient followed by an early rise to spring temperatures. Embryo survival (hatching success) differed significantly among populations across all thermal regimes, with the pure native population having the lowest survival. No consistent differences in survivorship across thermal regimes were detected, although native populations exhibited more among-family variability in response to thermal stress. Our study does not align closely with others that found reduced embryo survival under thermal stress, but concurs with observations of substantial intraspecific variation in thermal performance in coldwater fishes. Our results suggest that brook trout embryos may be somewhat resilient in the face of warmer and more variable incubation conditions, but it is likely that their resiliency varies among populations. Future experiments that include more extreme and variable conditions to clarify environmental limits of early life stages of brook trout would be useful for conservation planning. [ABSTRACT FROM AUTHOR]

Enzymatic processes play an increasing role in synthetic organic chemistry which requires the access to a broad and diverse set of enzymes. Metagenome mining is a valuable and efficient way to discover novel enzymes with unique properties for biotechnological applications. Here, we report the discovery and biocatalytic characterization of six novel metagenomic opine dehydrogenases from a hot spring environment (mODHs) (EC 1.5.1.X). These enzymes catalyze the asymmetric reductive amination between an amino acid and a keto acid resulting in opines which have defined biochemical roles and represent promising building blocks for pharmaceutical applications. The newly identified enzymes exhibit unique substrate specificity and higher thermostability compared to known examples. The feature that they preferably utilize negatively charged polar amino acids is so far unprecedented for opine dehydrogenases. We have identified two spatially correlated positions in their active sites that govern this substrate specificity and demonstrated a switch of substrate preference by site-directed mutagenesis. While they still suffer from a relatively narrow substrate scope, their enhanced thermostability and the orthogonality of their substrate preference make them a valuable addition to the toolbox of enzymes for reductive aminations. Importantly, enzymatic reductive aminations with highly polar amines are very rare in the literature. Thus, the preparative-scale enzymatic production, purification, and characterization of three highly functionalized chiral secondary amines lend a special significance to our work in filling this gap. Key points: • Six new opine dehydrogenases have been discovered from a hot spring metagenome • The newly identified enzymes display a unique substrate scope • Substrate specificity is governed by two correlated active-site residues [ABSTRACT FROM AUTHOR]

Centrifugal spinning is a fiber spinning method capable of producing fibers in the nanoscale diameter range from a multitude of polymers, including polyacrylonitrile (PAN). With a traditional centrifugal spinner, fiber can be rapidly spun and collected on static collection posts. However, the use of posts inevitably forms a dense fiber "ring" that is incompatible with roll-to-roll manufacturing processes. In this work, factors that influence throughput and scalability of highly aligned centrifugally spun PAN fibers are explored. A custom centrifugal setup is used to vertically translate collected fibers during the spinning process to distribute them over a large surface area. In addition, factors that affect PAN fiber diameter during the spinning process are investigated, including spinneret to collector distance, rotational speed, and humidity. Resulting data demonstrates that these factors can be independently optimized to reliably produce quality PAN fiber in the nanoscale diameter range. Furthermore, the fiber mass collection rate can be increased without affecting sample quality when the vertical translation speed is increased. This work demonstrates the potential scalability of centrifugal spinning to quickly produce large amounts of highly aligned nanofiber in a cheap, efficient, and reliable manner, and also lends the ability to be collected in a roll-to-roll fashion. [ABSTRACT FROM AUTHOR]

The aging population worldwide is facing a significant increase in age-related non-communicable diseases, including cardiovascular and brain pathologies. This comprehensive review paper delves into the impact of the exposome, which encompasses the totality of environmental exposures, on unhealthy aging. It explores how environmental factors contribute to the acceleration of aging processes, increase biological age, and facilitate the development and progression of a wide range of age-associated diseases. The impact of environmental factors on cognitive health and the development of chronic age-related diseases affecting the cardiovascular system and central nervous system is discussed, with a specific focus on Alzheimer's disease, Parkinson's disease, stroke, small vessel disease, and vascular cognitive impairment (VCI). Aging is a major risk factor for these diseases. Their pathogenesis involves cellular and molecular mechanisms of aging such as increased oxidative stress, impaired mitochondrial function, DNA damage, and inflammation and is influenced by environmental factors. Environmental toxicants, including ambient particulate matter, pesticides, heavy metals, and organic solvents, have been identified as significant contributors to cardiovascular and brain aging disorders. These toxicants can inflict both macro- and microvascular damage and many of them can also cross the blood–brain barrier, inducing neurotoxic effects, neuroinflammation, and neuronal dysfunction. In conclusion, environmental factors play a critical role in modulating cardiovascular and brain aging. A deeper understanding of how environmental toxicants exacerbate aging processes and contribute to the pathogenesis of neurodegenerative diseases, VCI, and dementia is crucial for the development of preventive strategies and interventions to promote cardiovascular, cerebrovascular, and brain health. By mitigating exposure to harmful environmental factors and promoting healthy aging, we can strive to reduce the burden of age-related cardiovascular and brain pathologies in the aging population. [ABSTRACT FROM AUTHOR]

Physical activity, including walking, has numerous health benefits in older adults, supported by a plethora of observational and interventional studies. Walking decreases the risk or severity of various health outcomes such as cardiovascular and cerebrovascular diseases, type 2 diabetes mellitus, cognitive impairment and dementia, while also improving mental well-being, sleep, and longevity. Dose-response relationships for walking duration and intensity are established for adverse cardiovascular outcomes. Walking's favorable effects on cardiovascular risk factors are attributed to its impact on circulatory, cardiopulmonary, and immune function. Meeting current physical activity guidelines by walking briskly for 30 min per day for 5 days can reduce the risk of several age-associated diseases. Additionally, low-intensity physical exercise, including walking, exerts anti-aging effects and helps prevent age-related diseases, making it a powerful tool for promoting healthy aging. This is exemplified by the lifestyles of individuals in Blue Zones, regions of the world with the highest concentration of centenarians. Walking and other low-intensity physical activities contribute significantly to the longevity of individuals in these regions, with walking being an integral part of their daily lives. Thus, incorporating walking into daily routines and encouraging walking-based physical activity interventions can be an effective strategy for promoting healthy aging and improving health outcomes in all populations. The goal of this review is to provide an overview of the vast and consistent evidence supporting the health benefits of physical activity, with a specific focus on walking, and to discuss the impact of walking on various health outcomes, including the prevention of age-related diseases. Furthermore, this review will delve into the evidence on the impact of walking and low-intensity physical activity on specific molecular and cellular mechanisms of aging, providing insights into the underlying biological mechanisms through which walking exerts its beneficial anti-aging effects. [ABSTRACT FROM AUTHOR]

Purpose of Review: Over the last decade, evidence suggests that a combination of behavioral and neuroimaging findings can help illuminate changes in functional dysconnectivity in schizophrenia. We review the recent connectivity literature considering several vital models, considering connectivity findings, and relationships with clinical symptoms. We reviewed resting state fMRI studies from 2017 to 2023. We summarized the role of two sets of brain networks (cerebello-thalamo-cortical (CTCC) and the triple network set) across three hypothesized models of schizophrenia etiology (neurodevelopmental, vulnerability-stress, and neurotransmitter hypotheses). Recent Findings: The neurotransmitter and neurodevelopmental models best explained CTCC-subcortical dysfunction, which was consistently connected to symptom severity and motor symptoms. Triple network dysconnectivity was linked to deficits in executive functioning, and the salience network (SN)–default mode network dysconnectivity was tied to disordered thought and attentional deficits. Summary: This paper links behavioral symptoms of schizophrenia (symptom severity, motor, executive functioning, and attentional deficits) to various hypothesized mechanisms. [ABSTRACT FROM AUTHOR]

Illness insight in schizophrenia (SZ) has an important impact on treatment outcome, integration into society and can vary over the course of the disorder. To deal with and treat reduced or absent illness insight, we need to better understand its functional and structural correlates. Previous studies showed regionally abnormal brain volume in brain areas related to cognitive control and self-reference. However, little is known about associations between illness insight and structural and functional network strength in patients with SZ. This study employed a cross-sectional design to examine structural and functional differences between patients with SZ (n = 74) and healthy controls (n = 47) using structural and resting-state functional magnetic resonance imaging (MRI). Voxel-based morphometry was performed on structural data, and the amplitude of low frequency fluctuations (ALFF) was calculated for functional data. To investigate abnormal structure/function interrelationships and their association with illness insight, we used parallel independent component analysis (pICA). Significant group (SZ vs. HC) differences were detected in distinct structural and functional networks, predominantly comprising frontoparietal, temporal and cerebellar regions. Significant associations were found between illness insight and two distinct structural networks comprising frontoparietal (pre- and postcentral gyrus, inferior parietal lobule, thalamus, and precuneus) and posterior cortical regions (cuneus, precuneus, lingual, posterior cingulate, and middle occipital gyrus). Finally, we found a significant relationship between illness insight and functional network comprising temporal regions (superior temporal gyrus). This study suggests that aberrant structural and functional integrity of neural systems subserving cognitive control, memory and self-reference are tightly coupled to illness insight in SZ. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate qualitative and quantitative differences in vascular density analysis of an established and a novel alternative for post-processing on optical coherence tomography angiography (OCTA) images in healthy individuals. OCTA examinations of 38 subjects were performed. After extracting the images, two semi-manual post-processing techniques, the already established Mexican hat filtering (MHF) and an alternative, the Shanbhag thresholding (ST) were applied. We assessed Vessel Density (VD), Skeleton Density (SkD) and Vessel Diameter Index (VDI). We analyzed the results in order to establish similarities or potentially relevant differences. Regarding SkD and VD, MHF generally gave higher values than ST. Simultaneously, mean values were also predominantly higher by MHF; however, standard deviations (SD) were higher by ST (range [mean ± SD]: 0.054 ± 0.038 to 0.134 ± 0.01 and 0.134 ± 0.095 to 0.362 ± 0.028 vs 0.012 ± 0.014 to 0.087 ± 0.03 and 0.039 ± 0.047 to 0.4 ± 0.095 for SkD and VD with MHF vs SkD and VD with ST, respectively). Values of VDI were considerably higher with ST than with MHF, while standard deviation was still significantly higher with ST (range [mean ± SD]: 2.459 ± 0.144 to 2.71 ± 0.084 and 2.983 ± 0.929 to 5.19 ± 1.064 for VDI with MHF and ST, respectively). The noise level reduction of the two methods were almost identical (noise levels: 65.8% with MHT and 65.24% with ST). Using MHF, the vascular network gets more fragmented by an average of 40% compared to ST. Both methods allow the segmentation of the vascular network and the examination of vascular density parameters, but they produce largely inconsistent results. To determine if these inconsistent results are clinically meaningful, and which method is more suitable for clinical use, our results provide further evidence that detailed understanding of the image analysis method is essential for reliable decision making for patients with retinal pathology. For longitudinal monitoring, use of the same image processing method is recommended. [ABSTRACT FROM AUTHOR]

TP53 variant interpretation is still challenging, especially in patients with attenuated Li–Fraumeni syndrome (LFS). We investigated the prevalence of pathogenic/likely pathogenic (P/LP) variants and LFS disease in the Hungarian population of cancer patients. By testing 893 patients with multiplex or familial cancer, we identified and functionally characterized novel splice variants of TP53 helping accurate variant classification. The differences among various semi-automated interpretation platforms without manual curation highlight the importance of focused interpretation as the automatic classification systems do not apply the TP53-specific criteria. The predicted frequency of the TP53 P/LP variants in Hungary is 0.3 per million which most likely underestimates the real prevalence. The higher detection rate of disease-causing variants in patients with attenuated LFS phenotype compared to the control population (OR 12.5; p < 0.0001) may raise the potential benefit of the TP53 genetic testing as part of the hereditary cancer panels of patients with multiple or familial cancer even when they do not meet Chompret criteria. Tumours developed at an earlier age in phenotypic LFS patients compared to the attenuated LFS patients which complicates genetic counselling as currently there are no different recommendations in surveillance protocols for LFS, phenotypic LFS, and attenuated LFS patients. [ABSTRACT FROM AUTHOR]

The Shelterin complex protein TPP1 interacts with human telomerase (TERT) by means of the TEL-patch region, controlling telomere homeostasis. Aberrations in the TPP1-TERT heterodimer formation might lead to short telomeres and severe diseases like dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. In the present study, we provide a thorough characterization of the structural properties of the TPP1's OB-domain by combining data coming from microsecond-long molecular dynamics calculations, time-series analyses, and graph-based networks. Our results show that the TEL-patch conformational freedom is influenced by a network of long-range amino acid communications that together determine the proper TPP1-TERT binding. Furthermore, we reveal that in TPP1 pathological variants Glu169Δ, Lys170Δ and Leu95Gln, the TEL-patch plasticity is reduced, affecting the correct binding to TERT and, in turn, telomere processivity, which eventually leads to accelerated aging of affected cells. Our study provides a structural basis for the design of TPP1-targeting ligands with therapeutic potential against cancer and telomeropathies. The binding interaction between the Shelterin complex protein TPP1 and the human telomerase enzyme can trigger telomerase maintenance, however, the conformational change of TPP1 functional for binding remains underexplored. Here, the authors characterize the structural properties of a group of amino acids named the TEL-patch within TPP1's oligosaccharide/oligonucleotide-domain by molecular dynamics simulation, time-series analyses, and graph-based networks, revealing their conformational plasticity and allosteric communication networks. [ABSTRACT FROM AUTHOR]

It is challenging to characterize single or a few biomolecules in physiological milieus without excluding the influences of surrounding environment. Here we utilize optical plasmonic trapping to construct a dynamic nanocavity, which reduces the diffraction-limited detection volume and provides reproducible electromagnetic field enhancements to achieve high-throughput single-molecule surface-enhanced Raman spectroscopy (SERS) characterizations in aqueous environments. Specifically, we study human Islet Amyloid Polypeptide (amylin, hIAPP) under different physiological pH conditions by combining spectroscopic experiments and molecular dynamics (MD) simulations. Based on a statistically significant amount of time-dependent SERS spectra, two types of low-populated transient species of hIAPP containing either turn or β-sheet structure among its predominant helix-coil monomers are characterized during the early-stage incubation at neutral condition, which play a crucial role in driving irreversible amyloid fibril developments even after a subsequent adjustment of pH to continue the prolonged incubation at acidic condition. Our results might provide profound mechanistic insight into the pH-regulated amyloidogenesis and introduce an alternative approach for investigating complex biological processes at the single-molecule level. Studying rare species in mixtures is challenging. Here, authors utilize on-and-off optical plasmonic trapping to control SERS-active nanocavity to analyse pH-dependent amylin species at single-molecule level, unveiling amyloid aggregation mechanisms. [ABSTRACT FROM AUTHOR]

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants (54 ADHD-Is and 53 ADHD-Cs and 54 healthy controls). Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (p = 1.46e-3), while the duration and contribution of frontal–parietal network (state D) were increased (p = 1.57e-3; p = 1.26e-4). Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I (p = 9.35e-5; p = 1.51e-8), suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD. [ABSTRACT FROM AUTHOR]

We study a system of nonlinear elliptic partial differential equations involving divergence-form operators. The problem under consideration is a natural generalization of the classical Brezis–Nirenberg problem. We find conditions on the domain, the coupling coefficients and the coefficients of the differential operator under which positive solutions are guaranteed to exist and conditions on these objects under which no positive solution exists. [ABSTRACT FROM AUTHOR]

The connections between citizenship education and mathematics education have been the focus of theoretical development and attention by educators interested in issues of justice, equity, power, criticality, and citizen engagement with societal issues, across schools, universities, and adult education levels. In this survey article, we contribute to new knowledge in the field by identifying and describing three interconnected layers of influence on the praxis of teaching and learning: (1) perspectives from citizenship education and mathematics education (e.g., kinds of citizenship, critical thinking in mathematics education); (2) institutional factors (e.g., policy, curricula, implementation within education systems); and (3) emerging influences (e.g., changing skill demands, innovations from communities of practice). In exploring the connections between citizenship education and mathematics education, we go beyond extant theory development and point to influences such as global disruptions, societal changes, systemic structures at the national and local levels, messaging in the media, and the role of teachers and learners. The holistic analysis of these influences enables identification of tensions and dilemmas, and issues of identity, autonomy, adoption, and systemic change. Together these point to multiple implications for educators, policy makers, and researchers aiming to enable informed and engaged citizens. [ABSTRACT FROM AUTHOR]

Microalgae produce many secondary metabolites that are biologically active, including compounds that inhibit microbial growth. These could potentially function as biofungicides. The first selection criteria for potential strains suitable in the phytosanitary market is good in vitro inhibition of growth against specific phytopathogenic fungi and oomycetes and higher biomass productivity rates. In the present study, water extracts were prepared from 280 strains comprising of 33 Cyanophyceae strains (13 genera), 157 Chlorophyceae strains (29 genera), 80 Trebouxiophyceae strains (19 genera), 5 Klebsormidiophyceae strains (1 genus) and 1 Zygnematophyceae strain. These were tested in vitro against 6 phytopathogenic fungi and 3 phytopathogenic oomycetes. In total, 45% of the species had mycelial growth inhibitory activity against at least one pathogen. Cyanobacteria had the highest "hit-rate" (64%), followed by the Chlorophyceae (49%) and Trebouxiophyceae (30%). Water extracts of 19 strains had fungicidal and/or oomyceticidal activity – these were predominantly Cyanobacteria. The Cyanobacteria displayed a wider spectrum of inhibition with five strains being active against three or more phytopathogenic strains. Trichormis variabilis MACC-304 and Tolypothrix tenuis MACC-205 had inhibitory activity against 6 phytopathogens and Nostoc linckia MACC-612 inhibited 4 phytopathogenic strains. Each Chlorophyta strain was only active against 1-2 strains. However, the daily productivity rates of Cyanobacteria were significantly lower than Chlorophyta strains. Further investigation of 15 Nostocales species (Nostocaceae, Tolypothrichaceae and Calotrichaceae) showed the Nostoc species generally had significantly lower biomass generation compared to other Nostocacaeae strains. The most promising strain was Tolypothrix tenuis MACC-205 which had the most potent, broad spectrum fungal and oomyceticidal inhibitory activity as well as significantly higher daily biomass productivity rates. Thus, Cyanobacteria can potentially be developed as an effective agricultural tool for environmentally-friendly disease management. [ABSTRACT FROM AUTHOR]

Future mathematics teachers must integrate their knowledge of mathematics, pedagogy, and learners to effectively teach mathematics. Historically, these different forms of knowledge were taught separately in teacher preparation and left to the preservice teacher to integrate on their own. This raises the question; what resources can be leveraged to promote knowledge integration in mathematics courses for teachers? In this study, we identified six instructional actions that were associated with potential knowledge integration when implemented within the environment of a mathematics course for preservice teachers. We posit these instructional actions can be implemented in concise and minimally invasive ways in a variety of mathematics content courses. Further unpacking of these instructional actions and considerations for implementation are provided. [ABSTRACT FROM AUTHOR]

Membrane environments affect protein structures and functions through protein-membrane interactions in a wide range of important biological processes. To better study the effects from the lipid's hydrophilic and hydrophobic interaction with protein on different membrane regions, we developed the lipid-coated nanoporous silver sheets to provide tunable supported lipid monolayer/bilayer environments for in situ surface-enhanced Raman vibrational spectroscopy (SERS) characterizations. Under the controllable surface pressure, lipid monolayer/bilayer was coated along the microscopic curved surface of nanoporous silver sheets to serve as a cell membrane mimic as well as a barrier to avoid protein denaturation while empowering the high SERS enhancements from the underlying metallic bases allowing detection sensitivity at low physiological concentrations. Moreover, we fine-tuned the lipid packing density and controlled the orientation of the deposited lipid bilayers and monolayers to directly monitor the protein structures upon interactions with various membrane parts/positions. Our results indicate that lysozyme adopted the α-helical structure in both hydrophilic and hydrophobic interaction with lipid membrane. Interestingly, alpha-synuclein folded into the α-helical structure on the negatively charged lipid heads, whereas the hydrophobic lipid tails induced the β-sheet structural conversion of alpha-synuclein originated from its unstructured monomers. These direct observations on protein hydrophilic and hydrophobic interaction with lipid membrane might provide profound insights into the formation of the β-sheet-containing alpha-synuclein oligomers for further membrane disruptions and amyloid genesis associated with Parkinson's disease. Hence, with the controllability and tunability of lipid environments, our platform holds great promise for more general applications in investigating the influences from membranes and the correlative structures of proteins under both hydrophilic and hydrophobic effects. [ABSTRACT FROM AUTHOR]

The interplay of positive and negative interactions between drug-sensitive and resistant cells influences the effectiveness of treatment in heterogeneous cancer cell populations. Here, we study interactions between estrogen receptor-positive breast cancer cell lineages that are sensitive and resistant to ribociclib-induced cyclin-dependent kinase 4 and 6 (CDK4/6) inhibition. In mono- and coculture, we find that sensitive cells grow and compete more effectively in the absence of treatment. During treatment with ribociclib, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture, termed facilitation in ecology. Molecular, protein, and genomic analyses show that resistant cells increase metabolism and production of estradiol, a highly active estrogen metabolite, and increase estrogen signaling in sensitive cells to promote facilitation in coculture. Adding estradiol in monoculture provides sensitive cells with increased resistance to therapy and cancels facilitation in coculture. Under partial inhibition of estrogen signaling through low-dose endocrine therapy, estradiol supplied by resistant cells facilitates sensitive cell growth. However, a more complete blockade of estrogen signaling, through higher-dose endocrine therapy, diminished the facilitative growth of sensitive cells. Mathematical modeling quantifies the strength of competition and facilitation during CDK4/6 inhibition and predicts that blocking facilitation has the potential to control both resistant and sensitive cancer cell populations and inhibit the emergence of a refractory population during cell cycle therapy. In cancer, interactions between treatment-sensitive and resistant cells can influence the effectiveness of therapies. Here, the authors use experimental and mathematical models to explore interactions between ER+ breast cancer cell lineages that are sensitive or resistant to CDK4/6 inhibition, revealing the role of facilitative growth. [ABSTRACT FROM AUTHOR]

The CO2 adsorption capacity of biochar derived from the slow pyrolysis of rice straw and the influence of surface modification via amine impregnation on the biochar were evaluated in this study. The biochar's (BC) surface characteristics, selectivity, adsorption capacity, and regenerability were compared to that of a commercial activated carbon (CAC). It was observed that the surface chemistry of the biochar greatly affects its ability to adsorb CO2. Tetraethylenepentamine (TEPA) was used to functionalize the surface of the samples. Under the scanning electron microscope (SEM), the BC sample was porous; however, modifying it caused some blockage in the sample. On the other hand, the CAC sample exhibited very fine particles while its modification showed no obvious qualitative change under the SEM. All the samples, both pure and modified BC and CAC, were identified to be selective to CO2. CAC gained the highest CO2 adsorption capacity of 9 wt%, followed by TEPA-50/CAC (5.7 wt%), BC (2.6 wt%), and TEPA-50/BC (2.4 wt%), under pure CO2 gas condition. Interestingly, under CO2-N2 gas mixture, the adsorption capacity of rice straw biochar is comparable to that of the commercial activated carbon. The biochar from rice straw can be an economic solid adsorbent for CO2 with further improvements. [ABSTRACT FROM AUTHOR]

Objective: It is unknown whether ustekinumab (UST) levels can predict clinical outcomes in Crohn's disease (CD) patients. We assessed the exposure–response relationship of UST trough concentrations with biochemical outcomes at week 24 in a prospective, real-world setting. Methods: We performed a prospective study in patients with CD starting UST in four academic centres in the Netherlands. All patients received a weight-adjusted intravenous (IV) UST induction dose, followed by one subcutaneous (SC) dose of 90 mg UST at 8 weeks. Maintenance therapy consisted of 90 mg subcutaneous UST every 8 or 12 weeks. Individual UST concentration time course during treatment were estimated using a population pharmacokinetic (PK) model. Quartile analysis and logistic regression were performed to analyse if UST concentrations at week 8 were associated with biochemical remission rates at week 24 (C-reactive protein (CRP) ≤ 5 mg/L and / or faecal calprotectin (FC) ≤ 250 mg/kg). Results: In total, 124 patients with CD were included. Patients achieving biochemical remission at week 12 and 24 had significantly higher UST levels at week 8 compared to patients without biochemical remission (6.6 µg/mL versus 3.9 µg/mL, P < 0.01 and 6.3 µg/mL versus 3.9 µg/mL, P < 0.01, respectively). In quartile analysis, patients with UST levels in the highest quartile (≥ 6.3 µg/mL at week 8) had higher biochemical remission rates at week 12 and week 24. There was no association between UST levels at and corticosteroid-free clinical remission rates. Conclusion: In this real-world cohort of patients with CD, UST levels in the highest quartile (≥ 6.3 µg/mL) at week 8 were associated with higher biochemical remission rates at week 24. [ABSTRACT FROM AUTHOR]

Whether endovascular thrombectomy (EVT) improves functional outcome in patients with large-vessel occlusion (LVO) stroke that do not comply with inclusion criteria of randomized controlled trials (RCTs) but that are considered for EVT in clinical practice is uncertain. We aimed to systematically identify patients with LVO stroke underrepresented in RCTs who might benefit from EVT. Following the premises that (i) patients without reperfusion after EVT represent a non-treated control group and (ii) the level of reperfusion affects outcome in patients with benefit from EVT but not in patients without treatment benefit, we systematically assessed the importance of reperfusion level on functional outcome prediction using machine learning in patients with LVO stroke treated with EVT in clinical practice (N = 5235, German-Stroke-Registry) and in patients treated with EVT or best medical management from RCTs (N = 1488, Virtual-International-Stroke-Trials-Archive). The importance of reperfusion level on outcome prediction in an RCT-like real-world cohort equaled the importance of EVT treatment allocation for outcome prediction in RCT data and was higher compared to an unselected real-world population. The importance of reperfusion level was magnified in patient groups underrepresented in RCTs, including patients with lower NIHSS scores (0–10), M2 occlusions, and lower ASPECTS (0–5 and 6–8). Reperfusion level was equally important in patients with vertebrobasilar as with anterior LVO stroke. The importance of reperfusion level for outcome prediction identifies patient target groups who likely benefit from EVT, including vertebrobasilar stroke patients and among patients underrepresented in RCT patients with low NIHSS scores, low ASPECTS, and M2 occlusions. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) are a first-line treatment for various metastatic solid tumors. Pneumonitis is a potentially devastating complication of ICI treatment and a leading cause of ICI-related mortality. Here, we evaluate whether abnormal pre-treatment pulmonary function tests (PFTs) or interstitial abnormalities on computed tomography of the chest (CT chest) prior to ICI are associated with the development of ICI-pneumonitis (ICI-p). Methods: We conducted a retrospective cohort study of consecutive patients who received at least one dose of ICI from 2011 to 2017 at The Ohio State University. Potential risk factors for ICI-p, including abnormal PFTs and CT chest, were recorded. These risk factors were compared between patients with and without pneumonitis. Results: In total, 1097 patients were included, 46 with ICI-p and 1051 without. Ninety percent of patients had pre-treatment chest imaging, while only 10% had pre-treatment PFTs. On multivariable analysis, interstitial abnormalities and reduced total lung capacity (TLC) were significantly associated with development of ICI-p (hazard ratio of 42.42 [95% CI; 15.04–119.67] and hazard ratio of 4.04 [95% CI; 1.32–12.37]), respectively. No other PFT abnormality was associated with increased risk of ICI-p. There was no significant difference in overall survival in patients who did or did not develop ICI-p (p = 0.332). Conclusions: Pre-existing interstitial abnormalities on CT chest and reduced TLC were strongly associated with developing ICI-p. Prospective studies are warranted to further explore the role of PFTs as a potential tool for identifying patients at highest risk for developing ICI-p. [ABSTRACT FROM AUTHOR]

Modelling languages play a central role in developing complex, critical systems. A precise, comprehensible, and high-quality modelling language specification is essential to all stakeholders using, implementing, or extending the language. Many good practices can be found that improve the understandability or consistency of the languages' semantics. However, designing a modelling language intended for a large audience is still challenging. In this paper, we investigate the challenges and typical issues with assessing the specifications of behavioural modelling language semantics. Our key insight is that the various stakeholder's understandings of the language's semantics are often misaligned, and the semantics defined in various artefacts (simulators, test suites) are inconsistent. Therefore assessment of semantics should focus on identifying and resolving these inconsistencies. To illustrate these challenges and techniques, we assessed parts of a state-of-the-art specification for a general-purpose modelling language, the Precise Semantics of UML State Machines (PSSM). We reviewed the text of the specification, analysed and executed PSSM's conformance test suite, and categorised our experiences according to questions generally relevant to modelling languages. Finally, we made recommendations for improving the development of future modelling languages by representing the semantic domain and traces more explicitly, applying diverse test design techniques to obtain conformance test suites, and using various tools to support early-phase language design. [ABSTRACT FROM AUTHOR]