Genetic analysis of the circumsporozoite gene in Plasmodium falciparum isolates from Cameroon: Implications for efficacy and deployment of RTS,S/AS01 vaccine.

Current understanding of genetic polymorphisms and natural selection in Plasmodium falciparum circumsporozoite (PfCSP), the leading malaria vaccine, is crucial for the development of next-generation vaccines, and such data is lacking in Africa. Blood samples were collected among Plasmodium-infected individuals living in four Cameroonian areas (Douala, Maroua, Mayo-Oulo, Pette). DNA samples were amplified using nested PCR protocols, sequenced, and BLASTed. Single nucleotide polymorphisms (SNPs) were analysed in each PfCSP region, and their impact on PfCSP function/structure was predicted in silico. The N-terminal region showed a limited polymorphism with four haplotypes, and three novel SNPs (N68Y, R87W, K93E) were found. Thirty-five haplotypes were identified in the central region, with several variants (e.g., NVNP and KANP). The C-terminal region was also highly diverse, with 25 haplotypes and eight novel SNPs (N290D, N308I, S312G, K317A, V344I, D356E, E357L, D359Y). Most polymorphic codon sites were mainly observed in the Th2R subregion in isolates from Douala and Pette. The codon site 321 was under episodic positive selection. One novel (E357L) and three known (K322I, G349D, D359Y) SNPs show an impact on function/structure. This study showed extensive genetic diversity with geographical patterns and evidence of the selection of Cameroonian PfCSP central and C-terminal regions.

Permutation conditional mutual information to quantify TMS-evoked cortical connectivity in disorders of consciousness.

Objective.To improve the understanding and diagnostic accuracy of disorders of consciousness (DOC) by quantifying transcranial magnetic stimulation (TMS) evoked electroencephalography connectivity using permutation conditional mutual information (PCMI).Approach.PCMI can characterize the functional connectivity between different brain regions. This study employed PCMI to analyze TMS-evoked cortical connectivity (TEC) in 154 DOC patients and 16 normal controls, focusing on optimizing parameter selection for PCMI (Data length, Order length, Time delay). We compared short-range and long-range PCMI values across different consciousness states-unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and normal (NOR)-and assessed various feature selection and classification techniques to distinguish these states.Main results.(1) PCMI can quantify TEC. We found optimal parameters to be Data length: 500 ms; Order: 3; Time delay: 6 ms. (2) TMS evoked potentials (TEPs) for NOR showed a rich response, while MCS patients showed only a few components, and UWS patients had almost no significant components. The values of PCMI connectivity metrics demonstrated its usefulness for measuring cortical connectivity evoked by TMS. From NOR to MCS to UWS, the number and strength of TEC decreased. Quantitative analysis revealed significant differences in the strength and number of TEC in the entire brain, local regions and inter-regions among different consciousness states. (3) A decision tree with feature selection by mutual information performed the best (balanced accuracy: 87.0% and accuracy: 83.5%). This model could accurately identify NOR (100.0%), but had lower identification accuracy for UWS (86.5%) and MCS (74.1%).Significance.The application of PCMI in measuring TMS-evoked connectivity provides a robust metric that enhances our ability to differentiate between various states of consciousness in DOC patients. This approach not only aids in clinical diagnosis but also contributes to the broader understanding of cortical connectivity and consciousness.

Selection signatures for high altitude adaptation in livestock: A review.

High altitude adapted livestock species (cattle, yak, goat, sheep, and horse) has critical role in the human socioeconomic sphere and acts as good source of animal source products including milk, meat, and leather, among other things. These species sustain production and reproduction even in harsh environments on account of adaptation resulting from continued evolution of beneficial traits. Selection pressure leads to various adaptive strategies in livestock whose footprints are evident at the different genomic sites as the "Selection Signature". Scrutiny of these signatures provides us crucial insight into the evolutionary process and domestication of livestock adapted to diverse climatic conditions. These signatures have the potential to change the sphere of animal breeding and further usher the selection programmes in right direction. Technological revolution and recent strides made in genomic studies has opened the routes for the identification of selection signatures. Numerous statistical approaches and bioinformatics tools have been developed to detect the selection signature. Consequently, studies across years have identified candidate genes under selection region found associated with numerous traits which have a say in adaptation to high-altitude environment. This makes it pertinent to have a better understanding about the selection signature, the ways to identify and how to utilize them for betterment of livestock populations as well as farmers. This review takes a closer look into the general concept, various methodologies, and bioinformatics tools commonly employed in selection signature studies and summarize the results of recent selection signature studies related to high-altitude adaptation in various livestock species. This review will serve as an informative and useful insight for researchers and students in the field of animal breeding and evolutionary biology.

Do sexual differences in life strategies make male lizards more susceptible to parasite infection?

Female and male hosts may maximise their fitness by evolving different strategies to compensate for the costs of parasite infections. The resulting sexual dimorphism might be apparent in differential relationships between parasite load and body condition, potentially reflecting differences in energy allocation to anti-parasitic defences. For example, male lacertids with high body condition may produce many offspring while being intensely parasitised. In contrast, female lacertids may show a different outcome of the trade-offs between body condition and immunity, aiming to better protect themselves from the harm of parasites. We predicted that females would have fewer parasites than males and a lower body condition across parasitaemia levels because they would invest resources in parasite defence to mitigate the costs of infection. In contrast, the male strategy to maximise access to females would imply some level of parasite tolerance and, thus, higher parasitaemia. We analysed the relationship between the body condition of lizards and the parasitemias of Karyolysus and Schellackia, two genera of blood parasites with different phylogenetic origins, in 565 females and 899 males belonging to 10 species of the Lacertidae (Squamata). These lizards were sampled over a period of 12 years across 34 sampling sites in southwestern Europe. The results concerning the Karyolysus infections were consistent with the predictions, with males having similar body condition across parasitaemia levels even though they had higher infection intensities than females. On the other hand, females with higher levels of Karyolysus parasitaemia had lower body condition. This is consistent with the prediction that different life strategies of male and female lacertids can explain the infection patterns of Karyolysus. In contrast, the parasitaemia of Schellackia was consistently low in both male and female hosts, with no significant effect on the body condition of lizards. This suggests that lizards of both sexes maintain this parasite below a pathogenic threshold.

Los machos y hembras pueden maximizar su eficacia biológica mediante la evolución diferencial de estrategias que compensen los costes asociados con las infecciones parasitarias. Por ejemplo, los machos con una alta condición corporal pueden producir muchas crías aun estando altamente parasitados. Mientras que es común que las hembras inviertan más energía en protegerse frente a los parásitos, lo que podría comprometer el mantenimiento de su condición corporal. Nuestra hipótesis es que las diferencias sexuales en la asignación de energía pueden quedar de manifiesto al analizar la relación entre la intensidad de infección con la condición corporal. También esperamos que las hembras tengan menos parásitos que los machos y que su condición corporal esté correlacionada negativamente con su carga parasitaria. Por el contrario, esperamos que los machos tengan más parásitos en parte porque su estrategia implicaría cierto nivel de tolerancia si con ello pueden incrementar su inversión reproductiva. Hemos analizado la relación entre la condición corporal y las parasitemias de Schellackia y Karyolysus, dos parásitos sanguíneos, en 565 hembras y 899 machos de 10 especies de la familia Lacertidae (Squamata) durante 12 años en 34 localidades en el suroeste de Europa. El patrón para Karyolysus fue coherente con las predicciones, ya que la condición corporal de los machos no se correlacionó con su parasitemia, a pesar de que estas fueron mayores que en las hembras. Mientras que la relación fue negativa en las hembras. Por lo que el patrón de infección de Karyolysus concuerda con las diferentes estrategias de inversión energética en machos y hembras. Sin embargo, en el caso de Schellackia las parasitemias fueron más bajas en hospedadores de ambos sexos y su parasitemia no se correlacionó con la condición corporal. Este resultado sugiere que Schellackia es mantenido en umbrales subpatogénicos.

Selection with two alleles of X-linkage and its application to the fitness component analysis of OdsH in Drosophila.

In organisms with the XY sex-determination system, there is an imbalance in the inheritance and transmission of the X chromosome between males and females. Unlike an autosomal allele, an X-linked recessive allele in a female will have phenotypic effects on its male counterpart. Thus, genes located on the X chromosome are of particular interest to researchers in molecular evolution and genetics. Here we present a model for selection with two alleles of X-linkage to understand fitness components associated with genes on the X chromosome. We apply this model to the fitness analysis of an X-linked gene, OdsH (16D), in the fruit fly Drosophila melanogaster. The function of OdsH is involved in sperm production and the gene is rapidly evolving under positive selection. Using site-directed gene targeting, we generated functional and defective OdsH variants tagged with the eye-color marker gene white. We compare the allele frequency changes of the two OdsH variants, each directly competing against a wild-type OdsH allele in concurrent but separate experimental populations. After twenty generations, the two genetically modified OdsH variants displayed a 40% difference in allele frequencies, with the functional OdsH variant demonstrating an advantage over the defective variant. Using maximum likelihood estimation (MLE), we determined the fitness components associated with the OdsH alleles in males and females. Our analysis revealed functional aspects of the fitness determinants associated with OdsH, and that sex-specific fertility and viability consequences both contribute to selection on an X-linked gene.

Selection criteria and method for deep inspiration breath-hold in patients with left breast cancer undergoing PMRT/IMRT.

Purpose: This study explored whether a free-breathing mean heart dose (FB-MHD) of 4 Gy is a reliable dose threshold for selecting left breast cancer patients after modified radical mastectomy suitable for deep inspiration breath-hold (DIBH) and developed anatomical indicators to predict FB-MHD for rapid selection. Materials and methods: Twenty-three patients with left breast cancer treated with DIBH were included to compare FB and DIBH plans. The patients were divided into the high-risk (FB-MHD ≥ 4 Gy) and low-risk (FB-MHD < 4 Gy) groups to compare dose difference, normal tissue complication probability (NTCP) and the DIBH benefits. Another 30 patients with FB only were included to analyze the capacity of distinguishing high-risk heart doses patients according to anatomical metrics, such as cardiac-to-chest Euclidean distance (CCED), cardiac-to-chest gap (CCG), and cardiac-to-chest combination (CCC). Results: All heart doses were significantly lower in patients with DIBH plans than in those with FB plans. Based on FB-MHD of 4 Gy cutoff, the heart dose, NTCP for cardiac death, and benefits from DIBH were significantly higher in the high-risk group than in the low-risk group. The CCED was a valid anatomical indicator with the largest area under the curve (AUC) of 0.83 and maintained 95 % sensitivity and 70 % specificity at the optimal cutoff value of 2.5 mm. Conclusions: An FB-MHD of 4 Gy could be used as an efficient dose threshold for selecting patients suitable for DIBH. The CCED may allow a reliable prediction of FB-MHD in left breast cancer patients at CT simulation.

Inferring ecological selection from multidimensional community trait distributions along environmental gradients.

Understanding the drivers of community assembly is critical for predicting the future of biodiversity and ecosystem services. Ecological selection ubiquitously shapes communities by selecting for individuals with the most suitable trait combinations. Detecting selection types on key traits across environmental gradients and over time has the potential to reveal the underlying abiotic and biotic drivers of community dynamics. Here, we present a model-based predictive framework to quantify the multidimensional trait distributions of communities (community trait spaces), which we use to identify ecological selection types shaping communities along environmental gradients. We apply the framework to over 3600 boreal forest understory plant communities with results indicating that directional, stabilizing, and divergent selection all modify community trait distributions and that the selection type acting on individual traits may change over time. Our results provide novel and rare empirical evidence for divergent selection within a natural system. Our approach provides a framework for identifying key traits under selection and facilitates the detection of processes underlying community dynamics.

Genetic differentiation across a steep and narrow environmental gradient: Quantitative genetic and genomic insights into Lake Superior populations of Quercus rubra.

Adaptive differentiation of traits and underlying loci can occur at a small geographical scale if natural selection is stronger than countervailing gene flow and drift. We investigated this hypothesis using coupled quantitative genetic and genomic approaches for a wind-pollinated tree species, Quercus rubra, along the steep, narrow gradient of the Lake Superior coast that encompasses four USDA Hardiness Zones within 100 km. For the quantitative genetic component of this study, we examined phenotypic differentiation among eight populations in a common garden, measuring seed mass, germination, height, stem diameter, leaf number, specific leaf area and survival. For the genomic component, we quantified genetic differentiation for 26 populations from the same region using RAD-seq. Because hybridisation with Quercus ellipsoidalis occurs in other parts of the species' range, we included two populations of this congener for comparison. In the common garden study, we found a strong signal of population differentiation that was significantly associated with at least one climate factor for nine of 10 measured traits. In contrast, we found no evidence of genomic differentiation among populations based on FST or any other measures. However, both distance-based and genotype-environment association analyses identified loci showing the signature of selection, with one locus in common across five analyses. This locus was associated with the minimum temperature of the coldest month, a factor that defines the climate zones and was also significant in the common garden analyses. In addition, we documented introgression from Q. ellipsoidalis into Q. rubra, with rates of introgression correlated with the climate gradient. In sum, this study reveals signatures of selection at the quantitative trait and genomic level consistent with climate adaptation, a pattern that is more often documented at a much broader geographical scale, especially in long-lived wind-pollinated species.

Meta-Analysis and Machine Learning Models for Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge.

Anaerobic biodegradation rates (half-lives) of organic chemicals are pivotal for environmental risk assessment and remediation. Traditional experimental evaluation, constrained by prolonged, oxygen-free conditions, struggles to keep pace with emerging contaminants. Data-driven machine learning (ML) models serve as promising complements. However, reported quantitative structure-biodegradation relationships or ML models on anaerobic biodegradation are mostly based on small data sets (<100 records) and neglect experimental conditions, usually achieving compromised predictions. This work aimed to develop ML models for predicting the biodegradation half-lives of organic pollutants in anaerobic environments (i.e., sediment/soil and sludge). Focusing on important features of both chemicals and experimental conditions, we first curated two data sets, one for sediment/soil (SED) and the other for sludge (SLD), covering 978 records for 206 chemicals from the literature, and then conducted a meta-analysis. Next, we built a binary classification (half-life of 30 days as the cutoff) model with an accuracy of 81% and a regression model with R2 of 0.56 for SED based on LightGBM (80% and 0.31 for SLD based on Extra tree, respectively). The model interpretations underscored the significance of experimental conditions (e.g., temperature and inoculum dosage), as evidenced by their high feature importance, and the models were found to correctly capture the effects of chemical substructures, for example, branched structures and aromatic rings prolonged half-lives while methyl group and ortho-substitution on rings shortened half-lives. The applicability domains of the models were also defined, resulting in reasonable prediction for the half-lives of 41% (SED) or 67% (SLD) of over 4000 persistent, bioaccumulative, and toxic chemicals. Overall, this study pioneers ML models for predicting the anaerobic degradation half-lives, offering valuable support for future evaluation and implementation of chemical anaerobic biodegradation.

PEMPS: a phylogenetic software tool to model the evolution of metabolic pathways.

BACKGROUND: Metabolic pathways support the enzyme flux that converts input chemicals into energy and cellular building blocks. With a constant rate of input, steady-state flux is achieved when metabolite concentrations and reaction rates remain constant over time. Individual genes undergo mutation, while selection acts on higher level functions of the pathway, such as steady-state flux where applicable. Modeling the evolution of metabolic pathways through mechanistic sets of ordinary differential equations is a piece of the genotype-phenotype map model for interpreting genetic variation and inter-specific differences. Such models can generate distinct compensatory changes and adaptive changes from directional selection, indicating single nucleotide polymorphisms and fixed differences that could affect phenotype. If used for inference, this would ultimately enable detection of selection on metabolic pathways as well as inference of ancestral states for metabolic pathway function. RESULTS: A software tool for simulating the evolution of metabolic pathways based upon underlying biochemistry, phylogenetics, and evolutionary considerations is presented. The Python program, Phylogenetic Evolution of Metabolic Pathway Simulator (PEMPS), implements a mutation-selection framework to simulate the evolution of the pathway over a phylogeny by interfacing with COPASI to calculate the steady-state flux of the metabolic network, introducing mutations as alterations in parameter values according to a model, and calculating a fitness score and corresponding probability of fixation based on the change in steady-state flux value(s). Results from simulations are consistent with a priori expectations of fixation probabilities and systematic change in model parameters. CONCLUSIONS: The PEMPS program simulates the evolution of a metabolic pathway with a mutation-selection modeling framework based on criteria like steady-state flux that is designed to work with SBML-formatted kinetic models, and Newick-formatted phylogenetic trees. The Python software is run on the Linux command line and is available at https://github.com/nmccloskey/PEMPS .

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin.

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Implementation contexts and strategies for alternative peripherally inserted central catheter material and design selection: A qualitative exploration using CFIR/ERIC approach.

AIM: To explore the implementation contexts and strategies that influence the uptake and selection of alternative peripherally inserted central catheter (PICC) materials and design. DESIGN: Qualitative evaluation of end user perspectives within a randomized control trial of different PICC materials and design. METHODS: Semi-structured interviews with key stakeholders were undertaken via an adapted, rapid-analytic approach using the Consolidated Framework for Implementation Research. Outcomes were mapped against the Expert Recommendations for Implementing Change (ERIC) tool for strategies to guide innovation in PICC practice. RESULTS: Participants (n = 23) represented a combination of users and inserters/purchasers, from adult and paediatric settings. Dominant themes included intervention characteristics (intervention source), inner setting (structural characteristics) and individuals involved (self-efficacy). Strategies emerging to support a change from ERIC mapping (n = 16) included promotion of intervention adaptability, inclusion of staff and consumer perspectives and sufficient funding. Implementation contexts such as inner setting and individuals involved equally impacted PICC success and implementation effectiveness and enabled a greater understanding of barriers and facilitators to intervention implementation in this trial. CONCLUSION: Trial evidence is important, but healthcare decision-making requires consideration of local contexts especially resourcing. Implementation contexts for Australian healthcare settings include a practical, strategic toolkit for the implementation of alternative PICC materials and designs. REPORTING METHOD: This study adhered to COREQ guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

The heritability of fitness in a wild annual plant population with hierarchical size structure.

The relative magnitude of additive genetic versus residual variation for fitness traits is important in models for predicting the rate of evolution and population persistence in response to changes in the environment. In many annual plants, lifetime reproductive fitness is correlated with end-of-season plant biomass, which can vary significantly from plant to plant in the same population. We measured end-of-season plant biomasses and obtained SNP genotypes of plants in a dense, natural population of the annual plant species Impatiens capensis with hierarchical size structure. These data were used to estimate the amount of heritable variation for position in the size hierarchy and for plant biomass. Additive genetic variance for position in the size hierarchy and plant biomass were both significantly different from zero. These results are discussed in relationship to theory for the heritability of fitness in natural populations and ecological factors that potentially influence heritable variation for fitness in this species.

MiRAGE: mining relationships for advanced generative evaluation in drug repositioning.

MOTIVATION: Drug repositioning, the identification of new therapeutic uses for existing drugs, is crucial for accelerating drug discovery and reducing development costs. Some methods rely on heterogeneous networks, which may not fully capture the complex relationships between drugs and diseases. However, integrating diverse biological data sources offers promise for discovering new drug-disease associations (DDAs). Previous evidence indicates that the combination of information would be conducive to the discovery of new DDAs. However, the challenge lies in effectively integrating different biological data sources to identify the most effective drugs for a certain disease based on drug-disease coupled mechanisms. RESULTS: In response to this challenge, we present MiRAGE, a novel computational method for drug repositioning. MiRAGE leverages a three-step framework, comprising negative sampling using hard negative mining, classification employing random forest models, and feature selection based on feature importance. We evaluate MiRAGE on multiple benchmark datasets, demonstrating its superiority over state-of-the-art algorithms across various metrics. Notably, MiRAGE consistently outperforms other methods in uncovering novel DDAs. Case studies focusing on Parkinson's disease and schizophrenia showcase MiRAGE's ability to identify top candidate drugs supported by previous studies. Overall, our study underscores MiRAGE's efficacy and versatility as a computational tool for drug repositioning, offering valuable insights for therapeutic discoveries and addressing unmet medical needs.

A two-tier feature selection method for predicting mortality risk in ICU patients with acute kidney injury.

Acute kidney injury (AKI) is one of the most important lethal factors for patients admitted to intensive care units (ICUs), and timely high-risk prognostic assessment and intervention are essential to improving patient prognosis. In this study, a stacking model using the MIMIC-III dataset with a two-tier feature selection approach was developed to predict the risk of in-hospital mortality in ICU patients admitted for AKI. External validation was performed using separate MIMIC-IV and eICU-CRD. The area under the curve (AUC) was calculated using the stacking model, and features were selected using the Boruta and XGBoost feature selection methods. This study compares the performance of a stacking model using two-tier feature selection with a model using single-tier feature selection (XGBoost: 85; Boruta: 83; two-tier: 0.91). The predictive effectiveness of the stacking model was further validated by using different datasets (Validation 1: 0.83; Validation 2: 0.85) and comparing it with a simpler model and traditional clinical scores (SOFA: 0.65; APACH IV: 0.61). In addition, this study combined interpretable techniques and causal inference to analyze the causal relationship between features and predicted outcomes.

Daily activities of older adults before and during the COVID pandemic.

OBJECTIVES: This study examines how older adults' (65 years old plus) daily activities shifted in the years around the coronavirus disease (COVID) pandemic. METHODS: Using data from American Time Use Survey, this study compares activities across the pre-pandemic (2019 to March 2020), early-pandemic (May to December 2020), and pandemic-normal (2021) periods. RESULTS: In the first year of the pandemic, there was less time spent on average on leisure outside the home, traveling, and with nonhousehold members, and more time alone and at home, compared with before the pandemic. Moving beyond averages, sequence and cluster analyses find 5 similar typologies of days across the three periods, characterized by days predominated by (a) housework, (b) leisure at home, (c) TV, (d) a combination of leisure at home and outside with TV, and (e) paid work. Duration of time across various daily activities differed, however, even for the same clusters. For example, in days predominated by indoor leisure, adults spent 405 min in this activity before the pandemic, 432 min during the early-pandemic period, and 549 min during the pandemic-normal period. We also observed changes in the proportion of older adults in each cluster. Across the pre-pandemic and early-pandemic periods, the proportion of days predominated by leisure at home increased (9.9%-17.9%) whereas the proportion belonging to days predominated by housework decreased (45.7%-17.6%). DISCUSSION: COVID-19 shifted the daily life of older adults, and our findings are consistent with selection, optimization, and compensation theory, documenting that older adult adapted across the first 2 years of the pandemic.

Sexual selection may support phenotypic plasticity in male coloration of an African cichlid fish.

The expression of sexually selected traits, such as ornaments or body coloration, is often influenced by environmental conditions. While such phenotypic plasticity is often thought to precede evolutionary change, plasticity itself can also be a target of selection. However, the selective forces supporting the evolution and persistence of plasticity in sexual traits are often unclear. Using the cichlid fish Astatotilapia burtoni, we show that variation in the level of mate competition may promote plasticity in body coloration. In this species, males can change between yellow and blue colour. We found that experimentally increased competition over mating territories led to a higher proportion of males expressing the yellow phenotype. The expression of yellow coloration was found to be beneficial because yellow males won more staged dyadic contests and exhibited a lower level of oxidative stress than blue males. However, females were more likely to spawn with blue males in mate choice experiments, suggesting that expression of blue coloration is sexually more attractive. The ability to adjust colour phenotype according to the local competitive environment could therefore promote the persistence of plasticity in coloration.

Key Issues of Economic Evaluations for Health Technology Assessment in China: A Nationwide Expert Survey.

OBJECTIVES: Health technology assessment (HTA) is increasingly crucial in medicine price negotiations in China, yet previous appraisals revealed national discrepancies on key economic evaluation issues: willingness-to-pay threshold, pricing models for multi-indication medicines, and comparator selection principles. This study aimed to collect expert opinions on these issues for future HTA evaluations. METHODS: A nationwide anonymous web-based survey encompassing experts across academia, HTA, consultancy/contract research organization/industry, service provider, and payer. In 2023, a generic invitation containing a web link to the questionnaire was disseminated via WeChat using convenience and snowball sampling. Agreement rates for questionnaire views were analyzed using descriptive statistics. The relationship between participants' responses and demographics was examined using appropriate logistic models. RESULTS: A total of 303 responses were received from experts in 34 cities. Key expert views include a suggested base willingness-to-pay threshold ranging from 0.5 to 1.5 times gross domestic product (52.1% agreement); elevated thresholds for childhood diseases, rare diseases, end-of-life diseases, and first-in-class medicines (>78.0% agreement); a single pricing model for multi-indication medicines (60.4% agreement); consideration of multiple medicines as comparators (79.9% agreement); and avoiding the use of centrally procured medicines as comparators for medicines with a time to market of less than 3 years (71.0% agreement). Participants who are service provider had lower odds of selecting higher thresholds (odds ratio 0.26; P < .01) than responders from consultancy/contract research organization/industry. CONCLUSIONS: Expert views indicate the need for substantial changes in China's current HTA methods, highlighting the need for increased investment in HTA processes and expertise cultivation.

Material compatibility and processing challenges in droplet deposition modelling additive manufacturing: A study on pharmaceutical excipients Polyvinylpyrrolidone/vinyl acetate (PVP/VA) and Polycaprolactone (PCL).

Additive manufacturing (AM) enables the production of complex, lightweight, and customized components with superior quality. Selecting the right materials considering their thermal properties, printability, and layer adhesion is crucial in melting-based AM techniques. This study investigates Droplet Deposition Modelling (DDM), an innovative material extrusion process that utilizes thermoplastic granules. DDM is distinguished by its shorter manufacturing times and a wider range of materials, setting it apart from traditional material extrusion methods such as fused filament fabrication. We investigated the printability and part quality in DDM using two common pharmaceutical excipients: Polyvinylpyrrolidone/vinyl acetate 6:4 (PVP/VA), which is highly brittle, and Polycaprolactone (PCL), known for its low solubility and role in controlled drug release. Different ratios of PVP/VA and PCL were compounded via hot melt extrusion (HME) and used in DDM to study the impact of ingredient content on printability and part quality, employing geometrical models to assess material compatibility and printability. The study revealed that increasing PVP/VA content leads to higher viscosity, reduced flowability, and uneven deposition, with formulations of 80 % and 100 % PVP/VA showing poor processability. In contrast, formulations with 60 % and 40 % PVP/VA exhibited smooth processing and compatibility with DDM. We identified processing temperature and Drop Aspect Ratio (DAR) as key factors influencing material printability and part quality. Elevated processing temperatures and reduced DAR were found to increase interface temperatures, reduce diffusion, and potentially cause the 'elephant feet' issue. Additionally, smaller droplet sizes and material characteristics, such as higher interfacial tension in PCL, could lead to coalescence. Our findings highlight the complexities in optimizing DDM processing parameters and material blends, underscoring the need for careful formulation design to achieve high-quality 3D printed products.

A simulation-guided approach to the selection of RPLC columns for platform small molecule separations.

Simulations were conducted to evaluate the potential of several hundred reversed-phase columns to separate small molecules. By calculating the retention factor of compounds in randomly generated virtual mixtures via the HSM (hydrophobic subtraction model) and applying basic chromatography theory, the simulation can estimate the retention time and peak width of every virtual compound and calculate the resolution between every adjacent pair of compounds. A preferred column set based on the number of successful separations of randomly generated virtual mixtures was developed. The tandem-column liquid chromatography (TC-LC) approach can separate 53.2 % of the 16-compound samples using 20 tandem-column pairs, while a single-column approach can only separate 42.6 % of the 16-compound samples with 20 single columns. The preferred set of columns obtained from the simulation was almost the same as the empirical set of columns previously obtained. In screening applications, TC-LC can achieve a comparably successful separation factor (selectivity) with a smaller column inventory (nine 50-mm columns) compared to the larger inventory needed by single-column LC (twenty-one 100-mm columns).