Tag: pubmed

Int J Cancer. 2024 Sep 2. doi: 10.1002/ijc.35162. Online ahead of print.

ABSTRACT

Cancer patients are at a higher risk to develop severe COVID-19 symptoms after SARS-CoV-2 infection compared to the general population and regularly show an impaired immune response to SARS-CoV-2 vaccination. In our oncological center, 357 patients with hematological and oncological diseases were monitored for neutralizing antibodies from October 2021 over 12 months. All patients had received three anti-SARS-CoV-2 vaccinations with an mRNA-(Comirnaty/BionTech or Spikevax/Moderna) or a vector vaccine (Vakzevria/AstraZeneca or JCOVDEN/Johnson&Johnson). Neutralizing anti-SARS-CoV-2 IgG antibodies in the patients’ sera were detected within 3 months before, 3-10 weeks and 5-7 months after the booster vaccination (third vaccination). 112 patients developed a breakthrough SARS-CoV-2 infection during the observation period. High anti-SARS-Cov-2 antibody levels before infection significantly protected against symptomatic Covid-19 disease (p = .003). The median antibody titer in patients with asymptomatic Covid-19 disease was 2080 BAU/ml (binding antibody units per Milliliter) and 765 BAU/ml in symptomatic patients. 98% of the solid tumor patients reached seroconversion after the booster vaccination in comparison to 79% of the hematological patients. High antibody titers of >2080 BAU/ml after the booster vaccination were detected in 61% of the oncological and 34.8% of the hematological patients. 7-10 months after the booster vaccination, the anti-SARS-CoV-2 antibody titer declined to an average of 849 BAU/ml. Considering the heterogenous humoral immune response of cancer patients observed in this study, an individual vaccination strategy based on regular measurement of anti-SARS-CoV-2 antibody levels should be considered in contrast to fixed vaccination intervals.

PMID:39222267 | DOI:10.1002/ijc.35162

Support Care Cancer. 2024 Sep 2;32(9):627. doi: 10.1007/s00520-024-08816-5.

ABSTRACT

PURPOSE: Clinical guidelines recommend early palliative care for patients with advanced lung cancer. In rural and underserved community oncology practices with limited resources, both primary palliative care from an oncologist and specialty palliative care are needed to address patients’ palliative care needs. The aim of this study is to describe community oncology clinicians’ primary palliative care practices and perspectives on integrating specialty palliative care into routine advanced lung cancer treatment in rural and underserved communities.

METHODS: Participants were clinicians recruited from 15 predominantly rural community oncology practices in Kentucky. Participants completed a one-time survey regarding their primary palliative care practices and knowledge, barriers, and facilitators to integrating specialty palliative care into advanced-stage lung cancer treatment.

RESULTS: Forty-seven clinicians (30% oncologists) participated. The majority (72.3%) of clinicians worked in a rural county. Over 70% reported routinely asking patients about symptom and physical function concerns, whereas less than half reported routinely asking about key prognostic concerns. Roughly 30% held at least one palliative care misconception (e.g., palliative care is for only those who are stopping cancer treatment). Clinician-reported barriers to specialty palliative care referrals included fear a referral would send the wrong message to patients (77%) and concern about burdening patients with appointments (53%). Notably, the most common clinician-reported facilitator was a patient asking for a referral (93.6%).

CONCLUSION: Educational programs and outreach efforts are needed to inform community oncology clinicians about palliative care, empower patients to request referrals, and facilitate patients’ palliative care needs assessment, documentation, and standardized referral templates.

PMID:39222247 | DOI:10.1007/s00520-024-08816-5

Environ Monit Assess. 2024 Sep 2;196(10):874. doi: 10.1007/s10661-024-13004-3.

ABSTRACT

The present study deals with the assessment of different physicochemical parameters (pH, electrical conductivity (E.C.), turbidity, total dissolved solids (TDS), and dissolved oxygen) in different surface water such as pond, river, and canal water in four different seasons, viz. March, June, September, and December 2023. The research endeavors to assess the impact of a cationic polyelectrolyte, specifically poly(diallyl dimethyl ammonium chloride) (PDADMAC), utilized as a coagulation aid in conjunction with lime for water treatment. Employing a conventional jar test apparatus, turbidity removal from diverse water samples is examined. Furthermore, the samples undergo characterization utilizing X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The study also conducts correlation analyses on various parameters such as electrical conductivity (EC), pH, total dissolved solids (TDS), turbidity of raw water, polyelectrolyte dosage, and percentage of turbidity removal across different water sources. Utilizing the Statistical Package for Social Science (SPSS) software, these analyses aim to establish robust relationships among initial turbidity, temperature, percentage of turbidity removal, dosage of coagulant aid, electrical conductivity, and total dissolved solids (TDS) in pond water, river water, and canal water. A strong positive correlation could be found between the percentage of turbidity removal and the value of initial turbidity of all surface water. However, a negative correlation could be observed between the polyelectrolyte dosage and raw water’s turbidity. By elucidating these correlations, the study contributes to a deeper understanding of the effectiveness of PDADMAC and lime in water treatment processes across diverse environmental conditions. This research enhances our comprehension of surface water treatment methodologies and provides valuable insights for optimizing water treatment strategies to address the challenges posed by varying water sources and seasonal fluctuations.

PMID:39222246 | DOI:10.1007/s10661-024-13004-3

Psychol Sci. 2024 Sep 2:9567976241263344. doi: 10.1177/09567976241263344. Online ahead of print.

ABSTRACT

Statistical learning is a powerful mechanism that enables the rapid extraction of regularities from sensory inputs. Although numerous studies have established that statistical learning serves a wide range of cognitive functions, it remains unknown whether statistical learning impacts conscious access. To address this question, we applied multiple paradigms in a series of experiments (N = 153 adults): Two reaction-time-based breaking continuous flash suppression (b-CFS) experiments showed that probable objects break through suppression faster than improbable objects. A preregistered accuracy-based b-CFS experiment showed higher localization accuracy for suppressed probable (versus improbable) objects under identical presentation durations, thereby excluding the possibility of processing differences emerging after conscious access (e.g., criterion shifts). Consistent with these findings, a supplemental visual-masking experiment reaffirmed higher localization sensitivity to probable objects over improbable objects. Together, these findings demonstrate that statistical learning alters the competition for scarce conscious resources, thereby potentially contributing to established effects of statistical learning on higher-level cognitive processes that require consciousness.

PMID:39222160 | DOI:10.1177/09567976241263344

Support Care Cancer. 2024 Sep 2;32(9):624. doi: 10.1007/s00520-024-08832-5.

ABSTRACT

PURPOSE: The Palliative Care Outcomes Collaboration (PCOC) aims to enhance patient outcomes systematically. However, identifying crucial items and accurately determining PCOC phases remain challenging. This study aims to identify essential PCOC data items and construct a prediction model to accurately classify PCOC phases in terminal patients.

METHODS: A retrospective cohort study assessed PCOC data items across four PCOC phases: stable, unstable, deteriorating, and terminal. From July 2020 to March 2023, terminal patients were enrolled. A multinomial mixed-effect regression model was used for the analysis of multivariate PCOC repeated measurement data.

RESULTS: The dataset comprised 1933 terminally ill patients from 4 different hospice service settings. A total of 13,219 phases of care were analyzed. There were significant differences in the symptom assessment scale, palliative care problem severity score, Australia-modified Karnofsky performance status, and resource utilization groups-activities of daily living among the four PCOC phases of care. Clinical needs, including pain and other symptoms, declined from unstable to terminal phases, while psychological/spiritual and functional status for bed mobility, eating, and transfers increased. A robust prediction model achieved areas under the curves (AUCs) of 0.94, 0.94, 0.920, and 0.96 for stable, unstable, deteriorating, and terminal phases, respectively.

CONCLUSIONS: Critical PCOC items distinguishing between PCOC phases were identified, enabling the development of an accurate prediction model. This model enhances hospice care quality by facilitating timely interventions and adjustments based on patients’ PCOC phases.

PMID:39222130 | DOI:10.1007/s00520-024-08832-5

Rev Sci Tech. 2024 Aug;43:69-78. doi: 10.20506/rst.43.3519.

ABSTRACT

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on agricultural animals, livestock production systems and associated communities worldwide. As part of the objectives of GBADs’Animal Health Ontology theme, the programme reviewed conceptual frameworks, ontologies and classification systems in biomedical science. The focus was on data requirements in animal health and the connections between animal health and human and environmental health. In May 2023, the team conducted searches of recognised repositories of biomedical ontologies, including BioPortal, Open Biological and Biomedical Ontology Foundry, and Ontology Lookup Service, to identify animal and livestock ontologies and those containing relevant concepts. Sixteen ontologies were found, covering topics such as surveillance, anatomy and genetics. Notable examples include the Animal Trait Ontology for Livestock, the Animal Health Surveillance Ontology, the National Center for Biotechnology Information Taxonomy and the Uberon Multi-Species Anatomy Ontology. However, some ontologies lacked class definitions for a significant portion of their classes. The review highlights the need for domain evidence to support proposed models, critical appraisal of external ontologies before reuse, and external expert reviews along with statistical tests of agreements. The findings from this review informed the structural framework, concepts and rationales of the animal health ontology for GBADs. This animal health ontology aims to increase the interoperability and transparency of GBADs data, thereby enabling estimates of the impacts of animal diseases on agriculture, livestock production systems and associated communities globally.

PMID:39222110 | DOI:10.20506/rst.43.3519

Rev Sci Tech. 2024 Aug;43:96-107. doi: 10.20506/rst.43.3522.

ABSTRACT

The estimation of the global burden of animal diseases requires the integration of multidisciplinary models: economic, statistical, mathematical and conceptual. The output of one model often serves as input for another; therefore, consistency of the model components is critical. The Global Burden of Animal Diseases (GBADs) Informatics team aims to strengthen the scientific foundations of modelling by creating tools that address challenges related to reproducibility, as well as model, data and metadata interoperability. Aligning with these aims, several tools are under development: a) GBADs’Trusted Animal Information Portal (TAIL) is a data acquisition platform that enhances the discoverability of data and literature and improves the user experience of acquiring data. TAIL leverages advanced semantic enrichment techniques (natural language processing and ontologies) and graph databases to provide users with a comprehensive repository of livestock data and literature resources. b) The interoperability of GBADs’models is being improved through the development of an R-based modelling package and standardisation of parameter formats. This initiative aims to foster reproducibility, facilitate data sharing and enable seamless collaboration among stakeholders. c) The GBADs Knowledge Engine is being built to foster an inclusive and dynamic user community by offering data in multiple formats and providing user-friendly mechanisms to garner feedback from the community. These initiatives are critical in addressing complex challenges in animal health and underscore the importance of combining scientific rigour with user-friendly interfaces to empower global efforts in safeguarding animal populations and public health.

PMID:39222107 | DOI:10.20506/rst.43.3522

Physiol Genomics. 2024 Sep 2. doi: 10.1152/physiolgenomics.00045.2024. Online ahead of print.

ABSTRACT

The severity of respiratory syncytial virus (RSV) may be linked to host genetic susceptibility. Surfactant protein (SP) genetic variants have been associated with RSV severity, but the impact of SNP-SNP (single nucleotide polymorphism) interactions remains unexplored. Therefore, we employed a novel statistical model to investigate the association of SNP-SNP interactions of SFTP genes with RSV severity in two and three-interaction models. We analyzed available genotype and clinical data from prospectively enrolled 405 children diagnosed with RSV, categorizing them into moderate or severe RSV groups. Using Wang’s statistical model, we studied significant associations of SNP-SNP interactions with RSV severity in a case-control design. We observed, 1) association of three interactions with increased risk of severe RSV in a two-SNP model. One intragenic interaction was between SNPs of SFTPA2, and the other two were intergenic, involving SNPs of hydrophilic and hydrophobic SPs alone. 2) association of 22 interactions with RSV severity in a three-SNP model. Among these, 20 were unique, with 12 and 10 interactions associated with increased or decreased risk of RSV severity, respectively, and included at least one SNP of either SFTPA1 or SFTPA2. All interactions were intergenic, except one among SNPs of SFTPA1. The remaining interactions were either among SNPs of hydrophilic SPs alone (n=8) or among SNPs of both hydrophilic or hydrophobic SPs (n=11). Our findings indicate that SNPs of all SFTPs may contribute to genetic susceptibility to RSV severity. However, the predominant involvement of SFTPA1 and/or SFTPA2 SNPs in these interactions underscores their significance in RSV severity.

PMID:39222066 | DOI:10.1152/physiolgenomics.00045.2024

Brief Bioinform. 2024 Jul 25;25(5):bbae419. doi: 10.1093/bib/bbae419.

ABSTRACT

The human gut microbiota produces diverse, extensive metabolites that have the potential to affect host physiology. Despite significant efforts to identify metabolic pathways for producing these microbial metabolites, a comprehensive metabolic pathway database for the human gut microbiota is still lacking. Here, we present Enteropathway, a metabolic pathway database that integrates 3269 compounds, 3677 reactions, and 876 modules that were obtained from 1012 manually curated scientific literature. Notably, 698 modules of these modules are new entries and cannot be found in any other databases. The database is accessible from a web application (https://enteropathway.org) that offers a metabolic diagram for graphical visualization of metabolic pathways, a customization interface, and an enrichment analysis feature for highlighting enriched modules on the metabolic diagram. Overall, Enteropathway is a comprehensive reference database that can complement widely used databases, and a tool for visual and statistical analysis in human gut microbiota studies and was designed to help researchers pinpoint new insights into the complex interplay between microbiota and host metabolism.

PMID:39222063 | DOI:10.1093/bib/bbae419

Br J Dev Psychol. 2024 Sep 2. doi: 10.1111/bjdp.12520. Online ahead of print.

ABSTRACT

Examining mechanisms underlying sex differences in children’s play styles, we studied girls with congenital adrenal hyperplasia (CAH) who provide a test of the relative effects of prenatal androgens versus rearing, and of behavioural similarity versus gender identity and cognitions. In this exploratory study, 40 focal children (girls and boys with and without CAH), aged 3-8 years, played for 14 min with a same-sex peer in a task designed to elicit rough-and-tumble play. Time-indexed ratings of positive affect and vigour of activity were evaluated via network mapping for sex-related differences in both levels and play dynamics (temporal relations among behaviours). Results suggest influences of both gender identity-aligned social cognitions and prenatal androgens: there was greater dyadic synchrony between positive affect for girls (regardless of CAH status) than boys, but girls with CAH displayed positive affect levels and directed vigorous peer play dynamics similar to boys.

PMID:39222059 | DOI:10.1111/bjdp.12520