Predictive factors of basic palliative and hospice care among patients with cancer visiting the emergency department in a Hungarian tertiary care center.

Introduction: Patients with advanced cancer tend to utilize the services of the health care system, particularly emergency departments (EDs), more often, however EDs aren't necessarily the most ideal environments for providing care to these patients. The objective of our study was to analyze the clinical and demographic characteristics of advanced patients with cancer receiving basic palliative care (BPC) or hospice care (HC), and to identify predictive factors of BPC and HC prior to their visit to the ED, in a large tertiary care center in Hungary. Methods: A retrospective, detailed analysis of patients receiving only BPC or HC, out of 1512 patients with cancer visiting the ED in 2018, was carried out. Sociodemographic and clinical data were collected via automated and manual chart review. Patients were followed up to determine length of survival. Descriptive and exploratory statistical analyses were performed. Results: Hospital admission, multiple (≥4x) ED visits, and respiratory cancer were independent risk factors for receiving only BPC (OR: 3.10, CI: 1.90-5.04; OR: 2.97, CI: 1.50-5.84; OR: 1.82, CI: 1.03-3.22, respectively), or HC (OR: 2.15, CI: 1.26-3.67; OR: 4.94, CI: 2.51-9.71; OR: 2.07, CI: 1.10-3.91). Visiting the ED only once was found to be a negative predictive factor for BPC (OR: 0.28, CI: 0.18-0.45) and HC (OR: 0.18, 0.10-0.31) among patients with cancer visiting the ED. Conclusions: Our study is the first from this European region to provide information regarding the characteristics of patients with cancer receiving BPC and HC who visited the ED, as well as to identify possible predictive factors of receiving BPC and HC. Our study may have relevant implications for health care planning strategies in practice.

Aromatase Inhibitors and Plasma Lipid Changes in Postmenopausal Women with Breast Cancer: A Systematic Review and Meta-Analysis.

Background: Women are typically diagnosed with estrogen receptor-positive breast cancer around the postmenopausal period when declining estrogen levels initiate changes in lipid profiles. Aromatase inhibitors (AI) are used to prevent the progression of cancer; however, a further reduction in estrogen levels may have detrimental effects on lipid levels, which was our working hypothesis. Methods: Our meta-analysis was conducted on the lipid profiles of postmenopausal breast cancer patients at baseline and at different treatment time points. Results: We identified 15 studies, including 1708 patients. Studies using anastrozole (ANA), exemestane (EXE), letrozole (LET), and tamoxifen (TMX) were involved. Subgroup analyses revealed that 3- and 12-month administrations of LET and EXE lead to negative changes in lipid profiles that tend to alter the lipid profile undesirably, unlike ANA and TMX. Conclusions: Our results suggest that, despite statistically significant results, EXE and LET may not be sufficient to cause severe dyslipidemia in patients without cardiovascular comorbidities according to the AHA/ACC Guideline on the Management of Blood Cholesterol. However, the results may raise the question of monitoring the effects of AIs in patients, especially those with pre-existing cardiovascular risk factors such as dyslipidemia.

Ethical dilemma arises from optimizing interventions for epidemics in heterogeneous populations.

Interventions to mitigate the spread of infectious diseases, while succeeding in their goal, have economic and social costs associated with them. These limit the duration and intensity of the interventions. We study a class of interventions which reduce the reproduction number and find the optimal strength of the intervention which minimizes the final epidemic size for an immunity inducing infection. The intervention works by eliminating the overshoot part of an epidemic, and avoids a second wave of infections. We extend the framework by considering a heterogeneous population and find that the optimal intervention can pose an ethical dilemma for decision and policymakers. This ethical dilemma is shown to be analogous to the trolley problem. We apply this optimization strategy to real-world contact data and case fatality rates from three pandemics to underline the importance of this ethical dilemma in real-world scenarios.

Towards Inferring Network Properties from Epidemic Data.

Epidemic propagation on networks represents an important departure from traditional mass-action models. However, the high-dimensionality of the exact models poses a challenge to both mathematical analysis and parameter inference. By using mean-field models, such as the pairwise model (PWM), the high-dimensionality becomes tractable. While such models have been used extensively for model analysis, there is limited work in the context of statistical inference. In this paper, we explore the extent to which the PWM with the susceptible-infected-recovered (SIR) epidemic can be used to infer disease- and network-related parameters. Data from an epidemics can be loosely categorised as being population level, e.g., daily new cases, or individual level, e.g., recovery times. To understand if and how network inference is influenced by the type of data, we employed the widely-used MLE approach for population-level data and dynamical survival analysis (DSA) for individual-level data. For scenarios in which there is no model mismatch, such as when data are generated via simulations, both methods perform well despite strong dependence between parameters. In contrast, for real-world data, such as foot-and-mouth, H1N1 and COVID19, whereas the DSA method appears fairly robust to potential model mismatch and produces parameter estimates that are epidemiologically plausible, our results with the MLE method revealed several issues pertaining to parameter unidentifiability and a lack of robustness to exact knowledge about key quantities such as population size and/or proportion of under reporting. Taken together, however, our findings suggest that network-based mean-field models can be used to formulate approximate likelihoods which, coupled with an efficient inference scheme, make it possible to not only learn about the parameters of the disease dynamics but also that of the underlying network.

MiRNAs in Lung Adenocarcinoma: Role, Diagnosis, Prognosis, and Therapy.

Lung cancer has emerged as a significant public health challenge and remains the leading cause of cancer-related mortality worldwide. Among various types of lung malignancies, lung adenocarcinoma (LUAD) stands as the most prevalent form. MicroRNAs (miRNAs) play a crucial role in gene regulation, and their involvement in cancer has been extensively explored. While several reviews have been published on miRNAs and lung cancer, there remains a gap in the review regarding miRNAs specifically in LUAD. In this review, we not only highlight the potential diagnostic, prognostic, and therapeutic implications of miRNAs in LUAD, but also present an inclusive overview of the extensive research conducted on miRNAs in this particular context.

Finding influential nodes in networks using pinning control: Centrality measures confirmed with electrochemical oscillators.

The spatiotemporal organization of networks of dynamical units can break down resulting in diseases (e.g., in the brain) or large-scale malfunctions (e.g., power grid blackouts). Re-establishment of function then requires identification of the optimal intervention site from which the network behavior is most efficiently re-stabilized. Here, we consider one such scenario with a network of units with oscillatory dynamics, which can be suppressed by sufficiently strong coupling and stabilizing a single unit, i.e., pinning control. We analyze the stability of the network with hyperbolas in the control gain vs coupling strength state space and identify the most influential node (MIN) as the node that requires the weakest coupling to stabilize the network in the limit of very strong control gain. A computationally efficient method, based on the Moore-Penrose pseudoinverse of the network Laplacian matrix, was found to be efficient in identifying the MIN. In addition, we have found that in some networks, the MIN relocates when the control gain is changed, and thus, different nodes are the most influential ones for weakly and strongly coupled networks. A control theoretic measure is proposed to identify networks with unique or relocating MINs. We have identified real-world networks with relocating MINs, such as social and power grid networks. The results were confirmed in experiments with networks of chemical reactions, where oscillations in the networks were effectively suppressed through the pinning of a single reaction site determined by the computational method.

Genomic Epidemiology and Evolution of Fowl Adenovirus 1.

Fowl adenovirus 1 (FAdV-1) is the main cause of gizzard erosion in chickens. Whole genome sequencing and sequence analyses of 32 FAdV-1 strains from a global collection provided evidence that multiple recombination events have occurred along the entire genome. In gene-wise phylogenies, only the adenoviral pol gene formed a tree topology that corresponded to whole genome-based phylogeny. Virus genetic features that were clearly connected to gizzard erosion were not identified in our analyses. However, some genome variants tended to be more frequently identified from birds with gizzard erosion and strains isolated from healthy birds or birds with non-specific pathologies tended to form common clusters in multiple gene phylogenies. Our data show that the genetic diversity is greater, and the evolutionary mechanisms are more complex within FAdV-1 than previously thought. The implications of these findings for viral pathogenesis and epidemiology await further investigation.

Necessary and sufficient conditions for exact closures of epidemic equations on configuration model networks.

We prove that it is possible to obtain the exact closure of SIR pairwise epidemic equations on a configuration model network if and only if the degree distribution follows a Poisson, binomial, or negative binomial distribution. The proof relies on establishing the equivalence, for these specific degree distributions, between the closed pairwise model and a dynamical survival analysis (DSA) model that was previously shown to be exact. Specifically, we demonstrate that the DSA model is equivalent to the well-known edge-based Volz model. Using this result, we also provide reductions of the closed pairwise and Volz models to a single equation that involves only susceptibles. This equation has a useful statistical interpretation in terms of times to infection. We provide some numerical examples to illustrate our results.

Synchronization, clustering, and weak chimeras in a densely coupled transcription-based oscillator model for split circadian rhythms.

The synchronization dynamics for the circadian gene expression in the suprachiasmatic nucleus is investigated using a transcriptional circadian clock gene oscillator model. With global coupling in constant dark (DD) conditions, the model exhibits a one-cluster phase synchronized state, in dim light (dim LL), bistability between one- and two-cluster states and in bright LL, a two-cluster state. The two-cluster phase synchronized state, where some oscillator pairs synchronize in-phase, and some anti-phase, can explain the splitting of the circadian clock, i.e., generation of two bouts of daily activities with certain species, e.g., with hamsters. The one- and two-cluster states can be reached by transferring the animal from DD or bright LL to dim LL, i.e., the circadian synchrony has a memory effect. The stability of the one- and two-cluster states was interpreted analytically by extracting phase models from the ordinary differential equation models. In a modular network with two strongly coupled oscillator populations with weak intragroup coupling, with appropriate initial conditions, one group is synchronized to the one-cluster state and the other group to the two-cluster state, resulting in a weak-chimera state. Computational modeling suggests that the daily rhythms in sleep-wake depend on light intensity acting on bilateral networks of suprachiasmatic nucleus (SCN) oscillators. Addition of a network heterogeneity (coupling between the left and right SCN) allowed the system to exhibit chimera states. The simulations can guide experiments in the circadian rhythm research to explore the effect of light intensity on the complexities of circadian desynchronization.

Retrospective study of cancer patients' predictive factors of care in a large, Hungarian tertiary care centre.

OBJECTIVES: To identify predictive factors of multiple emergency department (ED) visits, hospitalisation and potentially preventable ED visits made by patients with cancer in a Hungarian tertiary care centre. DESIGN: Observational, retrospective study. SETTING: A large, public tertiary hospital, in Somogy County, Hungary, with a level 3 emergency and trauma centre and a dedicated cancer centre. PARTICIPANTS: Patients above 18 years with a cancer diagnosis (International Classification of Diseases, 10th Revision codes of C0000-C9670) who visited the ED in 2018, who had received their diagnosis of cancer within 5 years of their first ED visit in 2018 or received their diagnosis of cancer latest within the study year. Cases diagnosed with cancer at the ED (new cancer diagnosis-related ED visits) were also included, constituting 7.9% of visits. PRIMARY OUTCOME MEASURES: Demographic and clinical characteristics were collected and the predictors of multiple (≥2) ED visits within the study year, admission to inpatient care following the ED visit (hospitalisation), potentially preventable ED visits and death within 36 months were determined. RESULTS: 2383 ED visits made by 1512 patients with cancer were registered. Predictive factors of multiple (≥2) ED visits were residing in a nursing home (OR 3.09, 95% CI 1.88 to 5.07) and prior hospice care (OR 1.87, 95% CI 1.05 to 3.31). Predictive factors for hospitalisation following an ED visit included a new cancer diagnosis-related visit (OR 1.86, 95% CI 1.30 to 2.66) and complaint of dyspnoea (OR 1.61, 95% CI 1.22 to 2.12). CONCLUSIONS: Being a resident of a nursing home and receiving prior hospice care significantly increased the odds of multiple ED visits, while new cancer-related ED visits independently increased the odds of hospitalisation of patients with cancer. This is the first study to report these associations from a Central-Eastern European country. Our study may shed light on the specific challenges of EDs in general and particularly faced by countries in the region.

Determinants of pupils' energy drink consumption - Findings from a Hungarian primary school.

Consumption of energy drinks is harmful in childhood and adolescence, and its increasing popularity makes it a public health threat in this age group. Our study aimed to assess energy drink (ED) consumption and identify the context and determinants of its consumption at a Hungarian primary school. A mixed-method approach was used for the research, including a survey filled in by 157 10-15-year-old pupils and World Café workshops (WCWs) involving pupils, home-room teachers, and Parental Council representatives (N = 39). The Jamovi 2.2.5. The software was used to perform descriptive statistics and logistic regression, and a causal loop diagram was created based on the results of the WCWs. The survey results revealed that almost one-third of the pupils consumed EDs regularly, and most daily consumers drank high amounts (500ml). Most students considered ED consumption unhealthy, yet every fifth drank them. Buying breakfast on the way to school increased the odds of ED consumption almost threefold. According to the WCWs' findings, the determinants of ED consumption were embedded in two critical contextual sets; one was the need for energy and concentration boost and the Perception of high social acceptance of ED consumption. Our results suggest that interventions to reduce students' ED consumption need to include increased parents' involvement in controlling their children's screen time and encouraging them to provide breakfast at home for their children. There is also an urgent need to restrict the marketing of EDs and strictly regulate access to EDs for under-18s.

Fruit Extract, Rich in Polyphenols and Flavonoids, Modifies the Expression of DNMT and HDAC Genes Involved in Epigenetic Processes.

Recently, the field of epigenetics has been intensively studied in relation to nutrition. In our study, the gene expression patterns of histone deacetylases (HDACs), which regulate the stability of histone proteins, and DNA methyltransferases (DNMTs), which regulate DNA methylation, were determined in mice. The animals were fed a human-equivalent dose of the aqueous extract of fruit seeds and peels, which is rich in flavonoids and polyphenols, for 28 days and then exposed to the carcinogen 7,12-dimethylbenz(a)anthracene (DMBA). The concentrations of trans-resveratrol and trans-piceid were determined in the consumed extract by HPLC and were 1.74 mg/L (SD 0.13 mg/L) and 2.37 mg/L (SD 0.32 mg/L), respectively, which corresponds to the consumption of 0.2-1 L of red wine, the main dietary source of resveratrol, in humans daily. Subsequently, 24 h after DMBA exposure, the expression patterns of the HDAC and DNMT genes in the liver and kidneys were determined by qRT-PCR. The DMBA-induced expression of the tested genes HDAC1, HDAC2, DNMT1, DNMT3A and DNMT3B was reduced in most cases by the extract. It has already been shown that inhibition of the DNMT and HDAC genes may delay cancer development and tumour progression. We hypothesise that the extract studied may exert chemopreventive effects.

The relationship between single nucleotide polymorphisms and skin cancer susceptibility: A systematic review and network meta-analysis.

Background: Single nucleotide polymorphisms (SNPs) interfere with the function of certain genes and thus may influence the probability of skin cancer. The correlation between SNPs and skin cancer (SC) lacks statistical power, however. Therefore, the purpose of this study was to identify the gene polymorphisms involved in skin cancer susceptibility using network meta-analysis and to determine the relationship between SNPs and SC risk. Methods: PubMed, Embase, and Web of Science were searched for articles including "SNP" and different types of SC as keywords between January 2005 and May 2022. The Newcastle-Ottawa Scale was used to assess bias judgments. The odds ratio (ORs) and their 95% confidence intervals (CIs) were determined to estimate heterogeneity within and between studies. Meta-analysis and network meta-analysis were carried out to identify the SNPs associated with SC. The P-score of each SNP was compared to obtain the rank of probability. Subgroup analyses were performed by cancer type. Results: A total of 275 SNPs from 59 studies were included in the study. Two subgroup SNP networks using the allele model and dominant model were analyzed. The alternative alleles of rs2228570 (FokI) and rs13181 (ERCC2) were the first-ranking SNPs in both subgroups one and two of the allele model, respectively. The homozygous dominant genotype and heterozygous genotype of rs475007 in subgroup one and the homozygous recessive genotype of rs238406 in subgroup two were most likely to be associated with skin cancer based on the dominant model. Conclusions: According to the allele model, SNPs FokI rs2228570 and ERCC2 rs13181 and, according to the dominant model, SNPs MMP1 rs475007 and ERCC2 rs238406 are closely linked to SC risk.

Tissue Tropism of H9N2 Low-Pathogenic Avian Influenza Virus in Broiler Chickens by Immunohistochemistry.

The H9N2 subtype of low-pathogenic avian influenza viruses (LPAIV) is a widespread pathogen of poultry that can also infect humans. The characterization of viral infections is a complex process, involving clinical, pathological, and virological investigations. The aim of this study was to adapt and optimize an immunohistochemical (IHC) technique developed for LPAIVs specifically for the detection of H9N2 virus antigens in infected tissues. Twenty-one-day-old broiler chickens were inoculated with three different strains of H9N2 virus by different infection routes (i.e., intranasal-intratracheal and intravenous) or co-infected with infectious bronchitis virus (IBV) and observed for 11 days post infection. The suggested IHC protocol was modified: (i) DAB (diamino-benzidine) was substituted with AEC (3-amino-9-ethyl carbazole) as chromogen; and (ii) indirect two-step immune reactions of monoclonal primary and peroxidase-labeled anti-mouse secondary antibodies were used instead of avidin-biotin complexes. Avian influenza virus antigen appears as a red precipitate in the nuclei of affected cells but can also be identified in the cytoplasm. Mild hyperemia and congestion were observed in the trachea, air sac, and lungs of the challenged birds, and fibrinous exudate was found at the bifurcation in a few cases. Neither gross pathological nor IHC lesions were found in the control group. Using the optimized protocol and an associated scoring scheme, it was demonstrated that the H9N2 strains tested exhibited respiratory and urinary tract tropism irrespective of the route of inoculation. On day 5, viral antigen was detected in the respiratory tract and kidney in 30-50% of the samples. On day 11, no IHC signal was observed, indicating the lack of viral replication. Slight differences in viral antigen expression were found between the different H9N2 virus strains, but, in contrast to highly pathogenic avian influenza (HPAI), no viral antigen was detected in the brain and pancreas. Thus, IHC can be considered as an informative, visual addition to the toolkit for the characterization of H9N2 LPAIV infections.

On Parameter Identifiability in Network-Based Epidemic Models.

Modelling epidemics on networks represents an important departure from classical compartmental models which assume random mixing. However, the resulting models are high-dimensional and their analysis is often out of reach. It turns out that mean-field models, low-dimensional systems of differential equations, whose variables are carefully chosen expected quantities from the exact model provide a good approximation and incorporate explicitly some network properties. Despite the emergence of such mean-field models, there has been limited work on investigating whether these can be used for inference purposes. In this paper, we consider network-based mean-field models and explore the problem of parameter identifiability when observations about an epidemic are available. Making use of the analytical tractability of most network-based mean-field models, e.g. explicit analytical expressions for leading eigenvalue and final epidemic size, we set up the parameter identifiability problem as finding the solution or solutions of a system of coupled equations. More precisely, subject to observing/measuring growth rate and final epidemic size, we seek to identify parameter values leading to these measurements. We are particularly concerned with disentangling transmission rate from the network density. To do this, we give a condition for practical identifiability and we find that except for the simplest model, parameters cannot be uniquely determined, that is, they are practically unidentifiable. This means that there exist multiple solutions (a manifold of infinite measure) which give rise to model output that is close to the data. Identifying, formalising and analytically describing this problem should lead to a better appreciation of the complexity involved in fitting models with many parameters to data.

Endoluminal Suture-technique for the Stomach Closure of an Experimental Model.

BACKGROUND/AIM: In the modern minimally invasive era, diagnostic and therapeutic endoscopic interventions are one of the most emerging fields. For the new operational techniques, it is a major aim to develop reliable instruments, such as suturing devices for flexible endoscopes. The aim of this study was to assess the feasibility of a safe and reproducible suturing technique with an endoluminal suturing device. MATERIALS AND METHODS: The evaluation of the technique was performed in twenty explanted special prepared porcine stomachs. Three different techniques were compared, single stitches, figure-of-eight, or Z-pattern and running sutures in terms of suturing time and bursting pressure. After verification of the reliability of the method, a 3 cm long full thickness incision on the stomach was closed with the endoscopic suturing device in four surviving animals. RESULTS: In our ex vivo studies, we have shown that the figure of 8 or Z- technique is the most optimal for stomach closure without considerable time-cost, thus this technique was chosen as the standard method for the in vivo study. The endoscopic stomach wall suturing was successful in all four cases, the postoperative period was uneventful and ended on the tenth postoperative day with autopsy. CONCLUSION: With the applied suturing device, the endoscopic suturing of the stomach is safe and reproducible, thus a human application may also be justified.

High antigenic diversity of serotype 1 infectious bursal disease virus revealed by antigenic cartography.

The antigenic characterization of IBDV, a virus that causes an immunosuppressive disease in young chickens, has been historically addressed using cross virus neutralization (VN) assay and antigen-capture enzyme-linked immunosorbent (AC-ELISA). However, VN assay has been usually carried out either in specific antibody negative embryonated eggs, for non-cell culture adapted strains, which is tedious, or on chicken embryo fibroblasts (CEF), which requires virus adaptation to cell culture. AC-ELISA has provided crucial information about IBDV antigenicity, but this information is limited to the epitopes included in the tested panel with a lack of information of overall antigenic view. The present work aimed at overcoming those technical limitations and providing an extensive antigenic landscape based on original cross VN assays employing primary chicken B cells, where no previous IBDV adaptation is required. Sixteen serotype 1 IBDV viruses, comprising both reference strains and documented antigenic variants were tested against eleven chicken post-infectious sera. The VN data were analysed by antigenic cartography, a method which enables reliable high-resolution quantitative and visual interpretation of large binding assay datasets. The resulting antigenic cartography revealed i) the existence of several antigenic clusters of IBDV, ii) high antigenic relatedness between some genetically unrelated viruses, iii) a highly variable contribution to global antigenicity of previously identified individual epitopes and iv) broad reactivity of chicken sera raised against antigenic variants. This study provides an overall view of IBDV antigenic diversity. Implementing this approach will be instrumental to follow the evolution of IBDV antigenicity and control the disease.

Optimal phase-selective entrainment of heterogeneous oscillator ensembles.

We develop a framework to design optimal entrainment signals that entrain an ensemble of heterogeneous nonlinear oscillators, described by phase models, at desired phases. We explicitly take into account heterogeneity in both oscillation frequency and the type of oscillators characterized by different Phase Response Curves. The central idea is to leverage the Fourier series representation of periodic functions to decode a phase-selective entrainment task into a quadratic program. We demonstrate our approach using a variety of phase models, where we entrain the oscillators into distinct phase patterns. Also, we show how the generalizability gained from our formulation enables us to meet a wide range of design objectives and constraints, such as minimum-power, fast entrainment, and charge-balanced controls.

Comparative Efficacy in Challenge Dose Models of a Toxin Expressing Whole-Cell Vaccine against Eight Serovars of Actinobacillus pleuropneumoniae in Pigs.

Actinobacillus pleuropneumoniae is a major economically significant bacterial respiratory pig pathogen, and whole cell vaccines are used to prevent disease. However, there is little data available on multi-serovar whole cell vaccine protection. Therefore, we determined the protective efficacies of a whole-cell A. pleuropneumoniae serovar 1 and 2 vaccine comprising ApxI-III toxins (C-vaccine, Coglapix®, Ceva, France) against serovars 1, 2, 4, 5, 6, 7, 9/11, and 13. The infection doses used induced disease representative of endemic field conditions, and standard protocols were used for all studies. Protection against homologous serovars 1 and 2 significantly reduced lung lesion scores (LLS) compared to positive controls: p = 0.00007 and p = 0.00124, respectively. The protection against heterologous serovars 4, 5, 6, 7, 9/11, and 13 also significantly reduced LLS: range p = 2.9 × 10-10 to p = 0.00953. As adjudged by the estimated random effect, reproducibility between studies was high. A highly significant serovar-independent reduction of pathological lung lesions by the C-vaccine was found for all the serovars tested (1, 2, 4, 5, 6, 7, 9/11, and 13). We conclude that the C-vaccine gives high serovar-independent protection against disease and is suitable for this use in the field.