A pre-post evaluation of a digital intervention to improve psychosocial outcomes of caregivers of people living with cancer in Vietnam.

OBJECTIVES: To evaluate a co-designed intervention using digital resources "Vietnam Cancer Caring Coping" (V-CCC) on the health literacy, depression, and quality of life of caregivers supporting a cancer patient in oncology hospitals in Vietnam. METHODS: A pre-post quantitative evaluation with adult cancer caregivers across regional Oncology hospitals in Vietnam (Ho Chi Minh City, Da Nang, Can Tho, and Hue). Participants completed baseline and follow-up measures of health literacy (HLS-SF12) depression (PHQ-9) and Health-related Quality of Life (5Q-5D-5L). Participants accessed and reviewed V-CCC for a 2-week period. RESULTS: Two hundred and thirty-four caregivers completed pre and post-tests. Most participants were female (n = 143, 61%), married (n = 165, 70%), aged 18-44 (n = 155, 66%), lived rurally (n = 157, 67%). All health literacy scores of participants in post-intervention were significantly higher than that in pre-intervention across all domain's healthcare, disease prevention, and health promotion as well as the total score (p < 0.001). A significant reduction in the proportion of caregivers reporting PHQ-9 moderately severe/severe depression post-intervention was demonstrated (10.2 vs. 6.1%, respectively (p ≤ 0.001). No significant differences were observed pre and post-intervention across four 5Q-5D-5L health dimensions: mobility, self-care, usual activities, and pain/discomfort. Regarding anxiety/depression as measured by 5Q-5D-5L the proportion of participants who reported having moderate, severe, and extreme problems in pre- and post-intervention was statistically significant (32 vs. 24%), respectively (p = 0.0028). CONCLUSION: Co-designed digital resources can reduce health literacy inequities and improve psychological outcomes for cancer caregivers.

Long-term performance and stability of molecular shotgun lipidomic analysis of human plasma samples.

The stability of the lipid concentration levels in shotgun lipidomics analysis was tracked over a period of 3.5 years. Concentration levels in several lipid classes, such as phospholipids, were determined in human plasma lipid extracts. Impact of the following factors on the analysis was investigated: sample amount, internal standard amount, and sample dilution factor. Moreover, the reproducibility of lipid profiles obtained in both polarity modes was evaluated. Total number of samples analyzed was approximately 6800 and 7300 samples in negative and positive ion modes, respectively, out of which 610 and 639 instrument control samples were used in stability calculations. The assessed shotgun lipidomics approach showed to be remarkably robust and reproducible, requiring no batch corrections. Coefficients of variation (CVs) of lipid mean concentration measured with optimized analytical parameters were typically less than 15%. The high reproducibility indicated that no lipid degradation occurred during the monitored time period.

A novel method for assigning functional linkages to proteins using enhanced phylogenetic trees.

MOTIVATION: Functional linkages implicate pairwise relationships between proteins that work together to implement biological tasks. During evolution, functionally linked proteins are likely to be preserved or eliminated across a range of genomes in a correlated fashion. Based on this hypothesis, phylogenetic profiling-based approaches try to detect pairs of protein families that show similar evolutionary patterns. Traditionally, the evolutionary pattern of a protein is encoded by either a binary profile of presence and absence of this protein across species or an occurrence profile that indicates the distribution of copies of this protein across species. RESULTS: In our study, we characterize each protein by its enhanced phylogenetic tree, a novel graphical model of the evolution of a protein family with explicitly marked by speciation and duplication events. By topological comparison between enhanced phylogenetic trees, we are able to detect the functionally associated protein pairs. Because the enhanced phylogenetic trees contain more evolutionary information of proteins, our method shows greater performance and discovers functional linkages among proteins more reliably compared with the conventional approaches.

Understanding family-based health insurance enrolment among informal sector workers in a rural district of Vietnam: Adverse selection and key determinants.

Background: Challenges remain in the implementation of family-based health insurance (FHI) - the key strategy for achieving universal health coverage in Vietnam. Objectives: To explore the experiences of and factors influencing enrolment in FHI among informal sector workers (ISW) in a rural district in Vietnam. Methods: A cross-sectional study was conducted from January to June 2016 in Tien Du, a rural district in Bac Ninh province. Secondary data were extracted from provincial social insurance databases to identify the rate of FHI among ISW in the district. Qualitative data were collected from 55 participants: 20 semi-structured in-depth interviews (IDI) and 6 focus group discussions (FGD). Data were transcribed verbatim. Thematic analysis was conducted. Results: Only 25.1% of ISW had FHI. Those individuals with FHI tended to be older or already experiencing health problems or have 'risky' jobs. The key determinants of adverse selection from different levels included: individual, family and health system. Conclusions: Low health insurance uptake remains an issue for ISW. Policy makers should consider raising awareness of FHI and improve the quality of primary health services, simplify the procedures of enrolment and claim for ISW. Additional government premium subsidy is required to increase FHI enrolment among ISW.

Semi-nested RT-PCR enables sensitive and high-throughput detection of SARS-CoV-2 based on melting analysis.

BACKGROUND: Asymptomatic transmission was found to be the Achilles' heel of the symptom-based screening strategy, necessitating the implementation of mass testing to efficiently contain the transmission of COVID-19 pandemic. However, the global shortage of molecular reagents and the low throughput of available realtime PCR facilities were major limiting factors. METHODS: A novel semi-nested and heptaplex (7-plex) RT-PCR assay with melting analysis for detection of SARS-CoV-2 RNA has been established for either individual testing or 96-sample pooled testing. The complex melting spectrum collected from the heptaplex RT-PCR amplicons was interpreted with the support of an artificial intelligence algorithm for the detection of SARS-CoV-2 RNA. The analytical and clinical performance of the semi-nested RT-PCR assay was evaluated using RNAs synthesized in-vitro and those isolated from nasopharyngeal samples. RESULTS: The LOD of the assay for individual testing was estimated to be 7.2 copies/reaction. Clinical performance evaluation indicated a sensitivity of 100% (95% CI: 97.83-100) and a specificity of 99.87% (95% CI: 99.55-99.98). More importantly, the assay supports a breakthrough sample pooling method, which makes possible parallel screening of up to 96 samples in one real-time PCR well without loss of sensitivity. As a result, up to 8,820 individual pre-amplified samples could be screened for SARS-CoV-2 within each 96-well plate of realtime PCR using the pooled testing procedure. CONCLUSION: The novel semi-nested RT-PCR assay provides a solution for highly multiplex (7-plex) detection of SARS-CoV-2 and enables 96-sample pooled detection for increase of testing capacity. .

Overexpression of fibroblast growth factor receptors FGFR1 and FGFR2 in renal cell carcinoma.

OBJECTIVE: Fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) has recently emerged as a critical event in the transformation and tumorigenicity of several murine and human tumors. This pathway could be a mechanism driving angiogenesis in patients with metastatic renal cell carcinoma (RCC). Membrane antigens such as FGFR expressed in RCC are attractive targets for new therapeutic and diagnostic applications. This study evaluated the expression of FGFR1 and FGFR2 in RCC. MATERIAL AND METHODS: Formalin-fixed, paraffin-embedded specimens of 100 primary tumors and 40 metastatic lymph nodes removed from 140 untreated RCC patients were evaluated by immunohistochemistry with FGFR1 and FGFR2 antibodies. The extent of FGFR expression was compared with 40 specimens of normal human kidney tissue (selected from the surgical diagnostic files). Significant differences in the immunoexpression of FGFR among these groups were assessed bychi-squared and Fisher's exact tests using a semi-quantitative scoring system on the extent of stained cells and intensity of corresponding immunostained cells (0 to 3+). RESULTS: Expression of FGFR1 was observed in 98% (98/100) of primary renal tumors and in 82.5% (33/40) of lymph-node metastases. Intensity was 3+ in allcases. Nuclear expression of FGFR1 was found in 68% (95/140). FGFR2 staining was seen in 4% (4/100) of primary tumors and in 5% (2/40) of lymph-node metastases. FGFR2 was expressed in RCC of non-clear cell histology. FGFR1 expression was significantly lower in the normal kidney tissue(p = 0.001) and was detected in 2.5% of cases (1/40); no FGFR2 expression was found. CONCLUSION: This study has shown for the first time that FGFR1 is highly expressed in RCC patients.

Use of machine learning in prediction of granule particle size distribution and tablet tensile strength in commercial pharmaceutical manufacturing.

In the manufacturing of pharmaceutical Oral Solid Dosage (OSD) forms, Particle Size Distribution (PSD) and Tensile Strength (TS) are common in-process tests that are controlled in order to achieve the quality targets of the end-product. The Quality by Design (QbD) concept elaborates process understanding and sufficient controls. However, for older pharmaceutical products upscaled to commercial phase with Quality by Testing (QbT) approach, the knowhow of the product-specific critical parameters is often limited. In this study, two predictive machine learning (ML) models were used for a commercial tablet product, for which historical data of raw materials, production, in-process controls and condition monitoring were available. With the aforementioned data, the aim was to predict the PSD and the TS that indicate the product quality. The feature importance was used to evaluate the parameter importance for the PSD and the TS. Partial dependence, in turn, was used to estimate the parameter impact on the predicted TS. The study illustrates the capability of the ML models to bring additional value for commercial products through the enhanced product-related knowhow.

Evaluation of different domain-based methods in protein interaction prediction.

Protein-protein interactions (PPIs) play an important role in many biological functions. PPIs typically involve binding between domains, the basic units of protein folding, evolution and function. Identifying domain-domain interactions (DDIs) would aid understanding PPI networks. Recently, many computational methods aimed to infer DDIs from databases of interacting proteins and subsequently used the inferred DDIs to predict new PPIs. We attempt to describe systematically current domain-based approaches including the association method, maximum likelihood estimation and parsimonious explanation method. The performance of these methods at inferring DDIs and predicting PPIs was evaluated comparatively. We observe that each method generates artefacts in certain situations and discuss biases in the available benchmark sets.

Beyond LDL-C lowering: distinct molecular sphingolipids are good indicators of proprotein convertase subtilisin/kexin type 9 (PCSK9) deficiency.

OBJECTIVES: Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) has been proposed to be a potential new therapeutic target for treatment of hypercholesterolaemia. However, little is known about the effects of PCSK9 inhibition on the lipidome. METHODS: We performed molecular lipidomic analyses of plasma samples obtained from PCSK9-deficient mice, and serum of human carriers of a loss-of-function variant in the PCSK9 gene (R46L). RESULTS: In both mouse and man, PCSK9 deficiency caused a decrease in several cholesteryl esters (CE) and short fatty acid chain containing sphingolipid species such as CE 16:0, glucosyl/galactosylceramide (Glc/GalCer) d18:1/16:0, and lactosylceramide (LacCer) d18:1/16:0. In mice, the changes in lipid concentrations were most prominent when animals were given regular chow diet. In man, a number of molecular lipid species was shown to decrease significantly even when LDL-cholesterol was non-significantly reduced by 10% only. Western diet attenuated the lipid lowering potency of PCSK9 deficiency in mice. CONCLUSIONS: Plasma molecular lipid species may be utilized for characterizing novel compounds inhibiting PCSK9 and as sensitive efficacy markers of the PCSK9 inhibition.

Inferring the physical connectivity of complex networks from their functional dynamics.

BACKGROUND: Biological networks, such as protein-protein interactions, metabolic, signalling, transcription-regulatory networks and neural synapses, are representations of large-scale dynamic systems. The relationship between the network structure and functions remains one of the central problems in current multidisciplinary research. Significant progress has been made toward understanding the implication of topological features for the network dynamics and functions, especially in biological networks. Given observations of a network system's behaviours or measurements of its functional dynamics, what can we conclude of the details of physical connectivity of the underlying structure? RESULTS: We modelled the network system by employing a scale-free network of coupled phase oscillators. Pairwise phase coherence (PPC) was calculated for all the pairs of oscillators to present functional dynamics induced by the system. At the regime of global incoherence, we observed a Significant pairwise synchronization only between two nodes that are physically connected. Right after the onset of global synchronization, disconnected nodes begin to oscillate in a correlated fashion and the PPC of two nodes, either connected or disconnected, depends on their degrees.Based on the observation of PPCs, we built a weighted network of synchronization (WNS), an all-to-all functionally connected network where each link is weighted by the PPC of two oscillators at the ends of the link. In the regime of strong coupling, we observed a Significant similarity in the organization of WNSs induced by systems sharing the same substrate network but different configurations of initial phases and intrinsic frequencies of oscillators.We reconstruct physical network from the WNS by choosing the links whose weights are higher than a given threshold. We observed an optimal reconstruction just before the onset of global synchronization.Finally, we correlated the topology of the background network to the observed change of the functional activities in the system. CONCLUSIONS: The results presented in this study indicate a strong relationship between the structure and dynamics of complex network systems. As coupling strength increases, synchronization emerges among hub nodes and recruits small-degree nodes. The results show that the onset of global synchronization in the system hinders the reconstruction of an underlying complex structure. Our analysis helps to clarify how the synchronization is achieved in systems of different network topologies.