The Effect of Information Exposure on Stigma Toward the COVID-19 Patient Mediated by Perceived Risk, Attribution of Blame and Protection Norm Conformity.

This study employed the model of stigma communication (MSC) to analyze how exposure to COVID-19-related information affected stigma-related information sharing about people who contracted COVID-19 during the pandemic and examined the cognitive process of the MSC in a collectivist culture. Based on a survey of 526 social media users during the COVID-19 pandemic in China, the study found that exposure to contact tracing information and pandemic control information had different impact on stigma-related information sharing through a series of cognitive variables. A dual-path model showed that perceived personal risk influenced stigma-related information sharing through attribution of blame toward the infected (the personal path), while perceived social risk influenced stigma-related information sharing through protection norm conformity (the social path). Compared to the personal path, the social path is more salient in shaping stigmatized attitudes and behaviors. The findings and discussions added to our understanding of the intricate stigma communication process in a collectivist culture.

Compassionate care during the COVID-19 pandemic.

BACKGROUND: There was a substantial documented call for healthcare professionals to provide compassionate care during the COVID-19 pandemic and significant criticism voiced when it was lacking. This study aimed to explore perspectives on compassionate care among healthcare professionals providing care during the COVID-19 pandemic. The study focuses on healthcare professionals who participated in a wide range of COVID-19 measures, including testing, quarantine, diagnosis, and care provision (patients with COVID-19 or patients with other illnesses and comorbid with COVID-19). METHODS: A qualitative design with an interpretative phenomenological analysis approach was used. Twenty frontline healthcare professionals (15 nurses and five physicians) who had worked in COVID-19 facilities in China were interviewed individually. RESULTS: Participants stated that a commitment to 'offering oneself' and 'balancing the advantages/disadvantages' in providing care during the pandemic were key to alleviate population-level suffering. On a personal level, they described a desire for obtaining 'mutual support' and improving 'professional competencies' to safeguard their physical and mental well-being. Two professional competencies were notable: coping with grief and implementing infection control across the organization. Additionally, they emphasized the importance of receiving support from the health care organization, the public, and leaders in creating an 'environment conducive to fostering compassionate care.' CONCLUSION: Healthcare professionals recognized the centrality of compassionate care during the pandemic which entailed a commitment to offering themselves, the balancing of advantages and disadvantages in order to find the best solution, as well as the need to safeguard themselves using professional competencies. Such findings can enrich the contemporary understanding of compassion, including when it is lacking. Support from the healthcare organization, the public, and leadership were crucial in fostering compassionate care in healthcare professionals during the pandemic and in moving the field forward in the future.

Motifs in SARS-CoV-2 evolution.

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of coevolving sites in the alignment (motifs), identified via coevolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the coevolutionary coupling of pairs and manifest as coevolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness, and robustness. Lastly, we study how well each lineage is classified by such a system.

Perception of eHealth Programs for Cardiovascular Health: Qualitative Systematic Review and Meta-synthesis.

BACKGROUND: Despite emerging evidence on the effectiveness of eHealth interventions in improving cardiovascular health, little is known about the perception of use and efficacy of these interventions and real-world application. OBJECTIVE: We sought to develop an in-depth understanding of the perceptions of eHealth interventions in improving cardiovascular health. METHODS: This is a systematic review and meta-synthesis of qualitative studies. A comprehensive search of multiple databases and a manual search of the references list were conducted. Meta-synthesis of qualitative data was performed to review and interpret the findings. The study report followed the ENTREQ checklist. RESULTS: Four themes emerged regarding perceptions of eHealth interventions: preferred eHealth intervention design features, enabling healthcare professionals' support, eHealth engagement for health benefits, and barriers to eHealth engagement. Intervention design features should integrate motivational elements, use an eHealth literacy lens, and enhance cultural relevance. Healthcare professionals appreciated these new working methods but voiced concern about competency building. Real-world usage initiation was driven by perceived needs and usefulness, whereas persistent engagement was inspired by intrinsic motivation in participants. CONCLUSIONS: eHealth interventions were appreciated as a valuable opportunity for providing alternative/supplementary cardiac care for health optimization. Participants commented on the need for more explicit and accurate health information presentation, and they appreciated the motivational elements in empowering them with self-determination over daily self-care behaviors. Professionals raised the need for specific guidance to enhance competency and intervention fidelity when delivering eHealth care.

The arithmetic topology of genetic alignments.

We propose a novel mathematical paradigm for the study of genetic variation in sequence alignments. This framework originates from extending the notion of pairwise relations, upon which current analysis is based on, to k-ary dissimilarity. This dissimilarity naturally leads to a generalization of simplicial complexes by endowing simplices with weights, compatible with the boundary operator. We introduce the notion of k-stances and dissimilarity complex, the former encapsulating arithmetic as well as topological structure expressing these k-ary relations. We study basic mathematical properties of dissimilarity complexes and show how this approach captures watershed moments of viral dynamics in the context of SARS-CoV-2 and H1N1 flu genomic data.

Explicating the Cognitive Process of a Physician's Trust in Patients: A Moderated Mediation Model.

Trust is considered a critical factor in the physician-patient relationship. However, little is known about the development and impact of physicians trusting their patients. A model that is premised on the integrated model of organizational trust was proposed in this article to reveal the cognitive processes involved in physicians' trust, with perceived integrity and the ability of the patient as antecedents and the physicians' communication efficacy as the outcome. A cross-sectional survey of 348 physicians in Zhejiang province, China, revealed that a physician's trust in a patient mediated the relationship between the physicians' perception of the integrity and ability of the patient, and the physician's communication efficacy. The physicians' educational backgrounds and work experience were also found to moderate an indirect effect: a lower level of education and longer work experience intensified the impact of the perceived integrity and ability of the patient on the physician's trust, while shorter work experience made the association between the physician's trust and communication efficacy more salient. This paper provided implications for both physician and patient sides.

Is Mental Illness like Any Other Medical Illness? Causal Attributions, Supportive Communication and the Social Withdrawal Inclination of People with Chronic Mental Illnesses in China.

The saying "mental illness is like any other illness" has increasingly become pervasive in promoting mental health literacy among the public in China. This discourse is based on the fact that mental illness is attributed to primarily biogenetic causes. This study comprises an investigation of the impact of causal attributions of mental illness on the social withdrawal inclination of people with chronic mental illnesses (PCMIs) in China. Drawing on attribution theory and a sample of PCMIs, the current authors further question the effectiveness of biogenetic discourse to combat social stigma and to integrate PCMIs into society. In addition, in response to the proliferation of discussion on the digital inclusion of those with mental disabilities, this study constructs a structural model in which the varied effects of supportive communication are used as bridging factors, including face-to-face, telephonic and social media communication. The results indicate a stronger social withdrawal inclination when the PCMIs attributed their illnesses to biogenetic causes. In addition, biogenetic attribution was also found to potentially hinder the PCMIs from using the telephone and social media to seek supportive communication, while psychosocial attribution was found to have potential to combat PCMIs' social withdrawal inclination. In this vein, this study calls for further investigation on the conditional factors upon which digital inclusion might work for PCMIs in China.

Multiscale Feedback Loops in SARS-CoV-2 Viral Evolution.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The viral genome is considered to be relatively stable and the mutations that have been observed and reported thus far are mainly focused on the coding region. This article provides evidence that macrolevel pandemic dynamics, such as social distancing, modulate the genomic evolution of SARS-CoV-2. This view complements the prevalent paradigm that microlevel observables control macrolevel parameters such as death rates and infection patterns. First, we observe differences in mutational signals for geospatially separated populations such as the prevalence of A23404G in CA versus NY and WA. We show that the feedback between macrolevel dynamics and the viral population can be captured employing a transfer entropy framework. Second, we observe complex interactions within mutational clades. Namely, when C14408T first appeared in the viral population, the frequency of A23404G spiked in the subsequent week. Third, we identify a noncoding mutation, G29540A, within the segment between the coding gene of the N protein and the ORF10 gene, which is largely confined to NY (>95%). These observations indicate that macrolevel sociobehavioral measures have an impact on the viral genomics and may be useful for the dashboard-like tracking of its evolution. Finally, despite the fact that SARS-CoV-2 is a genetically robust organism, our findings suggest that we are dealing with a high degree of adaptability. Owing to its ample spread, mutations of unusual form are observed and a high complexity of mutational interaction is exhibited.

Genetic robustness of let-7 miRNA sequence-structure pairs.

Genetic robustness, the preservation of evolved phenotypes against genotypic mutations, is one of the central concepts in evolution. In recent years a large body of work has focused on the origins, mechanisms, and consequences of robustness in a wide range of biological systems. In particular, research on ncRNAs studied the ability of sequences to maintain folded structures against single-point mutations. In these studies, the structure is merely a reference. However, recent work revealed evidence that structure itself contributes to the genetic robustness of ncRNAs. We follow this line of thought and consider sequence-structure pairs as the unit of evolution and introduce the spectrum of extended mutational robustness (EMR spectrum) as a measurement of genetic robustness. Our analysis of the miRNA let-7 family captures key features of structure-modulated evolution and facilitates the study of robustness against multiple-point mutations.

Geometric Characterization of Data Sets with Unique Reduced Gröbner Bases.

Model selection based on experimental data is an important challenge in biological data science. Particularly when collecting data is expensive or time-consuming, as it is often the case with clinical trial and biomolecular experiments, the problem of selecting information-rich data becomes crucial for creating relevant models. We identify geometric properties of input data that result in an unique algebraic model, and we show that if the data form a staircase, or a so-called linear shift of a staircase, the ideal of the points has a unique reduced Gröbner basis and thus corresponds to a unique model. We use linear shifts to partition data into equivalence classes with the same basis. We demonstrate the utility of the results by applying them to a Boolean model of the well-studied lac operon in E. coli.

A Boltzmann Sampler for 1-Pairs with Double Filtration.

Recently, a framework considering RNA sequences and their RNA secondary structures as pairs led to some information-theoretic perspectives on how the semantics encoded in RNA sequences can be inferred. This pairing arises naturally from the energy model of RNA secondary structures. Fixing the sequence in the pairing produces the RNA energy landscape, whose partition function was discovered by McCaskill. Dually, fixing the structure induces the energy landscape of sequences. The latter has been considered originally for designing more efficient inverse folding algorithms and subsequently enhanced by facilitating the sampling of sequences. We present here a partition function of sequence/structure pairs, with endowed Hamming distance and base pair distance filtration. This partition function is an augmentation of the previous mentioned (dual) partition function. We develop an efficient dynamic programming routine to recursively compute the partition function with this double filtration. Our framework is capable of dealing with RNA secondary structures as well as 1-structures, where a 1-structure is an RNA pseudoknot structure consisting of "building blocks" of genus 0 or 1. In particular, 0-structures, consisting of only "building blocks" of genus 0, are exactly RNA secondary structures. The time complexity for calculating the partition function of 1-pairs, that is, sequence/structure pairs where the structures are 1-structures, is O(h3b3n6), where h, b, n denote the Hamming distance, base pair distance, and sequence length, respectively. The time complexity for the partition function of 0-pairs is O(h2b2n3).

An Efficient Dual Sampling Algorithm with Hamming Distance Filtration.

Recently, a framework considering ribonucleic acid (RNA) sequences and their RNA secondary structures as pairs has led to new information theoretic perspectives on how the semantics encoded in RNA sequences can be inferred. In this context, the pairing arises naturally from the energy model of RNA secondary structures. Fixing the sequence in the pairing produces the RNA energy landscape, whose partition function was discovered by McCaskill. Dually, fixing the structure induces the energy landscape of sequences. The latter has been considered for designing more efficient inverse folding algorithms. In this work, we present the dual partition function filtered by Hamming distance, together with a Boltzmann sampler using novel dynamic programming routines for the loop-based energy model. The time complexity of the algorithm is [Formula: see text], where [Formula: see text] are Hamming distance and sequence length, respectively, reducing the time complexity of samplers, reported in the literature by [Formula: see text]. We then present two applications, the first in the context of the evolution of natural sequence-structure pairs of microRNAs and the second in constructing neutral paths. The former studies the inverse folding rate (IFR) of sequence-structure pairs, filtered by Hamming distance, observing that such pairs evolve toward higher levels of robustness, that is, increasing IFR. The latter is an algorithm that constructs neutral paths: given two sequences in a neutral network, we employ the sampler to construct short paths connecting them, consisting of sequences all contained in the neutral network.

[Rapid quantitative analysis of hydrocarbon composition of furfural extract oils using attenuated total reflection infrared spectroscopy].

A set of rapid analysis system for hydrocarbon composition of heavy oils was designed using attenuated total reflection FTIR spectrometer and chemometrics to determine the hydrocarbon composition of furfural extract oils. Sixty two extract oil samples were collected and their saturates and aromatics content data were determined according to the standard NB/SH/T0509-2010, then the total contents of resins plus asphaltenes were calculated by the subtraction method in the percentage of weight. Based on the partial least squares (PLS), calibration models for saturates, aromatics, and resin+asphaltene contents were established using attenuated total reflection FTIR spectroscopy, with their SEC, 1.43%, 0.91% and 1.61%, SEP, 1.56%, 1.24% and 1.81%, respectively, meeting the accuracy and repeatability required for the standard. Compared to the present standard method, the efficiency of hydrocarbon composition analysis for furfural extract oils is significantly improved by the new method which is rapid and simple. The system could also be used for other heavy oil analysis, with excellent extension and application foreground.