Size Heterogeneity Research Articles

The Contribution of Inherited Thrombophilia to Venous Thromboembolism in Cancer Patients.

Although the relationship between venous thromboembolism (VTE) and cancer has been a subject of study, knowledge of the contribution of thrombophilia to thrombosis in patients with cancer is still very limited. The aim of this article is to collect present knowledge on the contribution of inherited thrombophilia to VTE in cancer patients. We performed a search in Google Scholar and PubMed and selected 21 from 76 returned articles. Then we made a narrative review of the selected articles. We describe 11 studies on the contribution of inherited thrombophilia to VTE in cancer patients in general and 10 on that contribution in specific types of cancer: 1 in colorectal cancer, 4 in breast cancer, 1 in gynecologic cancer and 4 in hematopoietic malignancies. All studies investigate the relation of factor V Leiden (FVL) to VTE, 13 that of the prothrombin G20210A mutation (PTG20210A) and 7 studies also investigate other inherited thrombophilias, such methylenetetrahydrofolate reductase gene mutations, although only 2 investigate the contribution of deficiencies of the natural anticoagulants. Studies are very heterogeneous, in design and sample size and conclusions differ considerably. There is no consensus on the contribution of inherited thrombophilia to VTE in cancer patients except for acute lymphoblastic leukemia in children. Probably, that contribution is not the same for all types of cancer and more studies are needed to bring more knowledge on this subject.

Navigating Lp(a) Measurement Challenges: From Guidelines to Laboratory Perspectives

This comprehensive review delves into the evolving landscape of Lp(a) measurement standardsand examines the discordance and challenges in cardiovascular risk assessment in the contextof Lp(a). Acknowledging the shifting trends towards universal screening for Lp(a) endorsed by international societies working on risk assessment, management, and prevention of cardiovascular diseases, this review highlights the divergence in recommendations and the lackof consensus on Lp(a) risk thresholds. Ethnic variations in Lp(a) levels and ongoing clinical trial stargeting Lp(a) underscore the urgency of a unified and standardized approach to Lp(a) measurement. This article explores the intricacies of Lp(a) isoform size heterogeneity, availablemeasurement approaches, and the reporting unit challenge for the molecule. Emphasis is placed on collaborative efforts, transparent calibration, and the pivotal role of laboratories in ensuring the precision and reliability of Lp(a) measurements. The discussion encompasses thecall for unified calibration standards, highlighting the need for continuous external quality assessment and transparent reporting in clinical laboratories until a standardized Lp(a) measurement system is established.

Nonlinear bias toward complex contagion in uncertain transmission settings.

Current epidemics in the biological and social domains are challenging the standard assumptions of mathematical contagion models. Chief among them are the complex patterns of transmission caused by heterogeneous group sizes and infection risk varying by orders of magnitude in different settings, like indoor versus outdoor gatherings in the COVID-19 pandemic or different moderation practices in social media communities. However, quantifying these heterogeneous levels of risk is difficult, and most models typically ignore them. Here, we include these features in an epidemic model on weighted hypergraphs to capture group-specific transmission rates. We study analytically the consequences of ignoring the heterogeneous transmissibility and find an induced superlinear infection rate during the emergence of a new outbreak, even though the underlying mechanism is a simple, linear contagion. The dynamics produced at the individual and group levels are therefore more similar to complex, nonlinear contagions, thus blurring the line between simple and complex contagions in realistic settings. We support this claim by introducing a Bayesian inference framework to quantify the nonlinearity of contagion processes. We show that simple contagions on real weighted hypergraphs are systematically biased toward the superlinear regime if the heterogeneity of the weights is ignored, greatly increasing the risk of erroneous classification as complex contagions. Our results provide an important cautionary tale for the challenging task of inferring transmission mechanisms from incidence data. Yet, it also paves the way for effective models that capture complex features of epidemics through nonlinear infection rates.

Computational multigene interactions in virus growth and infection spread.

Viruses persist in nature owing to their extreme genetic heterogeneity and large population sizes, which enable them to evade host immune defenses, escape antiviral drugs, and adapt to new hosts. The persistence of viruses is challenging to study because mutations affect multiple virus genes, interactions among genes in their impacts on virus growth are seldom known, and measures of viral fitness are yet to be standardized. To address these challenges, we employed a data-driven computational model of cell infection by a virus. The infection model accounted for the kinetics of viral gene expression, functional gene-gene interactions, genome replication, and allocation of host cellular resources to produce progeny of vesicular stomatitis virus, a prototype RNA virus. We used this model to computationally probe how interactions among genes carrying up to eleven deleterious mutations affect different measures of virus fitness: single-cycle growth yields and multicycle rates of infection spread. Individual mutations were implemented by perturbing biophysical parameters associated with individual gene functions of the wild-type model. Our analysis revealed synergistic epistasis among deleterious mutations in their effects on virus yield; so adverse effects of single deleterious mutations were amplified by interaction. For the same mutations, multicycle infection spread indicated weak or negligible epistasis, where single mutations act alone in their effects on infection spread. These results were robust to simulation in high- and low-host resource environments. Our work highlights how different types and magnitudes of epistasis can arise for genetically identical virus variants, depending on the fitness measure. More broadly, gene-gene interactions can differently affect how viruses grow and spread.

Small bodies global gravity inversion via the level-set method

We propose an approach to infer large-scale heterogeneities within a small celestial body from measurements of its gravitational potential, provided for instance by spacecraft radio-tracking. The non-uniqueness of the gravity inversion is here mitigated by limiting the solutions to piecewise-constant density distributions, thus composed of multiple regions of uniform density (mass anomalies) dispersed in a background medium. The boundary of each anomaly is defined implicitly as the 0-level surface of a scalar field (called the level-set function), so that by modifying this field the shape and location of the anomaly are varied. The gravitational potential associated with a density distribution is here computed via a line-integral polyhedron method, yielding the coefficients of its spherical harmonics expansion. The density distribution is then adjusted via an iterative least-squares approach with Tikhonov regularization, estimating at every iteration corrections to the level-set function, the density contrast of each anomaly, and the background density, in order to minimize the residuals between the predicted gravity coefficients and those measured. Given the non-convexity of the problem and the lack of prior knowledge assumed (save for the shape of the body), the estimation process is repeated for several random initial distributions, and the resulting solutions are clustered based on global properties independent of the input measurements. This provides families of candidate interior models in agreement with the data, and the spread of the local density values across each family is used to assess the uncertainties associated with the estimated distributions. We present multiple synthetic tests with increasingly more realistic settings (in terms of gravity resolution and precision, and of shape, size and distribution of the internal heterogeneities), showing that our method is generally able to retrieve a ground-truth mass distribution even with noisy data. For further validation, we present an application of the method to real data, namely the Bennu gravity coefficients measured by the OSIRIS-REx team.

Computational Design of Low Melting Eutectics of Molten Salts: A Combined Machine Learning and Thermodynamic Modeling Approach.

We develop a computational framework combining thermodynamic and machine learning models to predict the melting temperatures of molten salt eutectic mixtures (Teut). The model shows an accuracy of ∼6% (mean absolute percentage error) over the entire data set. Using this approach, we screen millions of combinatorial eutectics ranging from binary to hexanary, predict new mixtures, and propose design rules that lead to low Teut. We show that heterogeneity in molecular sizes, quantified by the molecular volume of the components, and mixture configurational entropy, quantified by the number of mixture components, are important factors that can be exploited to design low Teut mixtures. While predicting eutectic composition with existing techniques had proved challenging, we provide some preliminary models for estimating the compositions. The high-throughput screening technique presented here is essential to design novel mixtures for target applications and efficiently navigate the vast design space of the eutectic mixtures.

Multimodal and multiscale strengthening mechanisms in Al-Ni-Zr-Ti-Mn alloy processed by laser powder bed fusion additive manufacturing

The unique thermokinetics of laser-powder bed fusion additive manufacturing (L-PBFAM) has been exploited for development of a novel high-strength Al-Ni-Ti-Zr-Mn alloy. The addition of 0.5 wt% Mn leads to extraordinary improvement in ultimate tensile strength (502 MPa) and work hardening due to the activation of two Mn-induced strengthening mechanisms. First, by a bimodal particle strengthening effect due to Al31Mn6Ni12 nano-quasi-crystal particles rejected in inter-dendritic spaces and fibrous Al3Ni eutectic dendritic channels, which predominately contributes to the strength improvement, and second by solid solution strengthening from remaining Mn entrapped in Al. These mechanisms supplement the particle strengthening effect imparted by coherent and incoherent Al3(Ti,Zr) co-precipitates present at melt pool boundaries, dislocation strengthening due to solidification induced strain, and Hall-Petch and backstress strengthening effect due to heterogenous grain size distribution occurring at various length scales. The solidification dynamics and hierarchical heat distribution that are associated with L-PBFAM resulted in complex spatial variations in these strengthening phenomena and were investigated via a high-throughput multiscale structure–property correlation that involved thermokinetic simulation, X-ray diffraction, high-resolution nanoindentation mapping, and site-specific transmission electron microscopy of the alloy.

AGING AND NUMERACY: A META-ANALYSIS

Abstract Numeracy, the ability to competently make use of numbers and numerical information, is a unique cognitive ability associated with diverse positive outcomes across the lifespan. Often included as a covariate in studies of cognitive aging, there is some scattered evidence of lower numeracy in older adults when compared to younger adults. Importantly, one longitudinal study found evidence of a quadratic decline in numeracy starting in later middle-age. The current study systematically reviews the literature on aging and numeracy as measured by one of three frequently implemented objective measures: the Lipkus numeracy scale (Lipkus et al., 2001), Weller et al.’s Rasch-based numeracy scale (2013), and the Berlin Numeracy Test (Cokely et al., 2012). Effect sizes were calculated from two types of studies: those including age as a categorical extreme group comparison variable or as a continuous variable from adult lifespan samples. Hedge’s g was computed as the effect size in the former studies and Pearson’s r was calculated as the effect size for the latter. For comparison across studies in a single random-effects model, Pearson’s r effect sizes were mathematically transformed into Hedge’s g’s. Type of sample (extreme group vs. adult lifespan) and age range were included in a second mixed-effects model to account for heterogeneity in effect sizes. Initial results show lower numeracy in older adults, but reduced effect size estimates in lifespan samples compared to those using extreme group comparisons. The implications for using linear estimates of effect size for the quadratic relationship between age and numeracy are discussed.

Investigating the impact of x‐ray computed tomography imaging on soluble organic matter in the Murchison meteorite: Implications for Bennu sample analyses

AbstractX‐ray computed tomography (XCT) is a valuable reconnaissance tool for three‐dimensional imaging and identification of distinct lithologies in extraterrestrial samples. It will be used as part of the preliminary examination of samples returned from asteroid (101955) Bennu by the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS‐REx) mission. However, it must first be established whether x‐rays generated during XCT could degrade or alter the organic composition of the returned samples by radiolysis. To test this, we split a crushed sample of the Murchison CM2 meteorite, kept one portion as a control, and irradiated the other portion up to the maximum x‐ray dosage (~180 Gy) that a Bennu sample would experience during an XCT imaging experiment. We then extracted organic compounds from both splits and conducted (i) nontargeted soluble organic analyses to compare the chemical distributions of C‐, H‐, O‐, N‐, and S‐bearing species and (ii) targeted measurements to quantify the abundances of 96 individual soluble organic molecules that included protein amino acids, amines, carboxylic acids, hydroxy acids, carbonyl compounds, polycyclic aromatic hydrocarbons, alcohols, sugars, and N‐heterocycles. We found that XCT imaging of the Murchison meteorite had no measurable impact on the relative abundances or enantiomeric compositions of most of the soluble organic compounds targeted in this study. Elevated total abundances of several soluble organic compound classes were observed in the XCT‐scanned Murchison sample relative to the control. This is likely related to particle size heterogeneity and specific surface area differences between the sample aliquots used for the extractions, rather than a result of the x‐ray exposure. Assuming the samples returned from asteroid Bennu by OSIRIS‐REx have a similar composition to carbonaceous chondrites, these data provide confidence that XCT will not significantly alter their soluble organic compositions.

Effects of heat stress on feed intake, milk yield, milk composition, and feed efficiency in dairy cows: A meta-analysis

Heat stress compromises dairy production by decreasing feed intake and milk yield, and it may also alter milk composition and feed efficiency. However, little information is available for evaluating such effects across different levels of heat stress and cows enrolled in heat stress studies. The objectives of this study were to evaluate the effects of heat stress on dry matter intake (DMI), energy-corrected milk (ECM), milk composition, and feed efficiency (kg ECM/kg DMI) and to investigate the relationship between such effects and heat stress intervention and animal characteristics by using meta-analytical approaches. Data from 31 studies (34 trials) fulfilled the inclusion criteria and were used for analysis. Results showed that heat stress decreased DMI, ECM, and milk protein concentration, but did not alter milk fat concentration or feed efficiency. Meta-regression confirmed that such reductions in DMI and ECM were significantly associated with increasing temperature-humidity index (THI). Over the period of heat stress, for each unit increase in THI, DMI and ECM decreased by 4.13% and 3.25%, respectively, in mid-lactation cows. Regression models further revealed the existence of a strong interaction between THI and lactation stage, which partially explained the large heterogeneity in effect sizes of DMI and ECM. The results indicated a need for more research on the relationship between the effect of heat stress and animal characteristics. This study calls for the implementation of mitigation strategies in heat-stressed herds due to the substantial decrease in productivity.

Endoscopic full-thickness resection for gastric submucosal tumors: Japanese multicenter prospective study.

Early gastric cancer endoscopic resection (ER) is prominent in Japan. However, evidence regarding ER of gastric submucosal tumors (SMT) is limited. This prospective multicenter phase II study investigated the efficacy and safety of endoscopic full-thickness resection (EFTR) for gastric SMT. Endoscopic full-thickness resection indication for gastric SMT was 11-30 mm, histologically proven or clinically suspicious (irregular margin, increasing size, or internal heterogeneity) gastrointestinal stromal tumors (GIST), with no ulceration and intraluminal growth type. The primary end-point was the complete ER (ER0) rate, with a sample size of 42. We enrolled 46 patients with 46 lesions between September 2020 and May 2023 at seven Japanese institutions. The mean ± SD (range) endoscopic tumor size was 18.8 ± 4.5 (11-28) mm. The tumor resection and defect closure times were 54 ± 26 (22-125) min and 33 ± 28 (12-186) min, respectively. A 100% ER0 was achieved in all 46 patients. The EFTR procedure was accomplished in all patients without surgical intervention. One patient had delayed perforation and was managed endoscopically. GIST accounted for 76% (n = 35) of the cases. R0, R1, and RX rates were 33 (77%), 3 (6.5%), and 7 (15%), respectively. Endoscopic full-thickness resection for gastric SMT of 11-30 mm is efficacious. It warrants further validation in a large-scale cohort study to determine the long-term outcome of this treatment for patients with gastric GIST.

Modeling of summer maize transpiration considering morphogenesis

Plant transpiration research is the foundation for improving the efficiency of agricultural water resource utilization and ensuring food production safety. It is an important content of agricultural production and water resource utilization research. However, spatial heterogeneities of leaf size and positions affect the estimation of transpiration. In this study, summer maize on the North China Plain was taken as the research object. Based on the measured data of the photosynthetic apparatus, morphogenesis and stem flow meter, the transpiration variation rule of summer maize leaves was analyzed, and the spatial distribution model of photosynthetically active radiation based on plant morphogenesis was constructed. Considering the spatial heterogeneities of leaf size and positions, the individual-plant scale transpiration model was upgraded. The reliability of transpiration model at individual plant scale was verified. The results showed that: i) the transpiration rate of leaves with different leaf positions, positive and negative leaves at the same leaf position and different parts of the same leaf were significantly different. ii) Based on the measured data, the structure of summer maize with spatial coordinates was obtained, and a calculation model for solar radiation reaching the top of the plants and a calculation model for photosynthetically active radiation reaching the surface of the leaves were constructed. Based on the different absorption, reflection, and transmission of radiation by summer maize leaves, the photosynthetically active radiation of each part of the leaves was characterized. iii) A plant transpiration model was constructed by combining the leaf panel transpiration model with the spatial distribution model of photosynthetically active radiation in summer maize plants, and, the determination coefficients between the simulated and the measured values of the individual plant scale transpiration rate were all above 0.95, the consistency index was close to 1.0, and the RMSE was in range of 12.41–16.64 g h−1. The individual plant transpiration obtained after simulated accumulation could meet the simulation accuracy. The results achieved the scale improvement of the leaf transpiration to individual plant transpiration.

Simultaneous separation and analysis of multiple doxorubicin hydrochloride liposomes forms in serum by circular nonuniform electric field gel electrophoresis

BackgroundLiposomal formulations have traditionally been considered the most therapeutically effective drug delivery systems (DDS). However, their pharmacokinetics study and efficacy assessment are still challenging given size heterogeneity and unknown forms in vivo. The pharmacodynamic evaluation that solely analyzes total drug concentration is unfit for the liposomal formulation study. Hence, it is crucial to develop effective strategies for the separation and analysis of different forms of liposomal formulations in order to contribute to the study of pharmacokinetic profiles associated with both liposome-incorporated and non-liposomal drugs. (84) ResultsA laboratory-built circular nonuniform electric field gel electrophoresis (CNEFGE) system was developed in this study for simultaneous separation and analysis of various forms of doxorubicin hydrochloride (DOX•HCl) liposomes. Liposomes were effectively fractionized based on their size and higher concentration in situ in the concentration zone, obtaining liposome recovery >95 % and a 3.04 concentration factor. It was found that the technique could be used to evaluate not only the size distribution of liposomes but also the drug loading capacity related to size. The charge-to-size-based separation mechanism has also allowed the simultaneous separation of liposome-entrapped drugs, protein-bound drugs, and free drugs in various forms, and the technique has been successfully employed in serum. Moreover, the quantification analysis of liposomes incubated with serum for 72 h showed that the proportion of the ratio of DOX•HCl in liposome-entrapped drugs, protein-bound drugs, and free drugs is approximately 97:2:1. (143) SignificanceUsing the separation principle of gel electrophoresis and the electrification characteristics of drug carriers, this study developed and implemented an efficient approach for the simultaneous separation and concentration of multiple forms of drug liposomes in vivo. This approach offers a wide range of applications in the pharmacokinetics, efficacy, and safety evaluation of drug carriers and liposomes. (56).

Micro-Fracturing in Granitic Rocks During Uniaxial Loading: The Role of Grain Size Heterogeneity

Micro-Fracturing in Granitic Rocks During Uniaxial Loading: The Role of Grain Size Heterogeneity

Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas.

Ribosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq yields genome-wide insight into translational dynamics and post-transcriptional control of gene expression. Here, we provide details on the Ribo-seq method and the subsequent analysis with the unicellular model alga Chlamydomonas reinhardtii (Chlamydomonas) for generating high-resolution data covering more than 10 000 different transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5' and 3' sections of transcripts and characteristics of eukaryotic translation termination, which are fundamentally distinct for chloroplast translation. In chloroplasts, a heterogeneous RPF size distribution along the coding sequence indicates specific regulatory phases during protein synthesis. For example, local accumulation of small RPFs correlates with local slowdown of psbA translation, possibly uncovering an uncharacterized regulatory step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light-harvesting complex proteins, LHCs. By providing high-quality datasets for all subcellular genomes and attaching our data to the Chlamydomonas reference genome, we aim to make ribosome profiles easily accessible for the broad research community. The data can be browsed without advanced bioinformatic background knowledge for translation output levels of specific genes and their splice variants and for monitoring genome annotation.

Multi‐Ancestry Genetics for Alzheimer’s Disease: Alzheimer’s Disease Genetics Consortium

AbstractBackgroundAlzheimer’s disease (AD) affects individuals of all races and ethnicities, yet large‐scale genetic research to compare genetic makeups for risk or protection of AD between multi‐ancestry datasets is limited. The Alzheimer’s Disease Genetics Consortium (ADGC) assembled the largest multi‐ancestry dataset including 56,241 subjects from non‐Hispanic Whites (NHW), African Americans (AA), Hispanics (HI), and East Asians (EAS) to understand ancestral similarities and differences in genetic risk and protective variants for AD.MethodWe established a Steering Committee with 5 members, 4 main Workgroups including Primary Meta‐Analysis, Follow‐Up Analysis, Secondary Analysis, and Method Evaluation, and 3 affiliated Workgroups consisting of Phenotype Harmonization, Imputation Development, and genome‐wide association study (GWAS)/whole genome sequencing (WGS) Integration. A new computing infrastructure was developed for shared analytic space on Amazon Web Services (AWS), where all members from different institutes accessed to genetic and phenotypic data and conducted analysis under the master analysis plan with centrally developed pipelines and scripts. We conducted ancestry‐specific GWAS using single nucleotide polymorphisms (SNPs) for AD, cross‐ancestry meta‐analysis of 4 ancestry GWASs, fine‐mapping for allelic heterogeneity in known and novel loci for AD, and pathway analysis.ResultWe confirmed 12 known including APOE ɛ4 and ɛ2 variants and identified 2 novel loci for AD in cross‐ancestry meta‐analysis with P<5.4×10−8. African and Asian ancestry subjects displayed greater heterogeneity in effect sizes and significant levels with the previously known AD loci for AD. Ancestry‐specific fine‐mapping indicated presence of potential distinct causal variants across different ancestry groups from multiple known AD loci. Two APOE alleles had greatest effect sizes among East Asians compared to others (EAS>NHW>AA>HI), while we failed to observe significant association signals with AD in SHARPIN and TREM2 regions from African Americans. Of two novel loci, the association signal in the LRRC4C‐API5 region was contributed from all four ancestry groups; in contrast, the signal in the LHX5‐AS1‐RBM19 region was predominantly from Hispanics.ConclusionGenetic risk profiling in multi‐ancestry datasets provided unique opportunity to understand ancestry‐specific and cross‐ancestry genetic risk factors for AD. Further evaluation of these established and novel loci for AD by integrating GWAS and WGS data from ADSP is underway

Brains in focus: Uncovering protein aggregate changes across Alzheimer’s disease with single‐molecule imaging

AbstractBackgroundOligomers are increasingly implicated in Alzheimer’s disease (AD)1. The characteristics of these protein aggregates remain largely unknown due to their low biological concentration, solubility, small size and structural heterogeneity. This study aims to better classify the diverse protein aggregates found in human brains across AD onset and progression.MethodsPost‐mortem flash‐frozen brain samples (n = 28) spanning the full range of AD stages (Braak 0‐VI) were obtained from London Neurodegenerative Diseases Brain Bank: two brain regions, middle temporal gyrus (MTG) and primary somatosensory cortex (SOM), were obtained from 14 donors. The post‐mortem tissues were homogenised to extract proteins into liquid fractions for single‐molecule studies. Antibodies, including 6E10, HT7, AT8 and SC‐12767, were selected to bind aggregates of amyloid‐β, tau, phosphorylated tau and α‐synuclein respectively. Ultra‐sensitive single‐molecule array (Simoa®) assays measured protein aggregate quantities in the homogenates. Single‐molecule pull‐down (SiMPull) assays, imaged by super‐resolution fluorescence microscopy, measured aggregate size and shape within the homogenates. BCA assays quantified the total protein content of the homogenates for normalisation.ResultsMorphological differences in tau aggregates were observed between disease stages with super‐resolution microscopy. Quantities of phosphorylated and total tau aggregates tend to increase significantly in the MTG and SOM from mid‐stage AD onwards according to Simoa® assays. In comparison to tau, aggregate quantities of amyloid‐β and α‐synuclein displayed less variation between non‐diseased controls and different AD stages.ConclusionsSingle‐molecule techniques can sensitively detect a broad range of protein aggregates from human brains. Novel differences in the morphologies and quantities of aggregates have been identified across AD stages. There is strong potential for uncovering the specific protein aggregates responsible for AD with these methods. This could facilitate earlier disease detection and more effective treatment targeting. 1 Hardy, J. & Selkoe, D. J. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297, 353‐356 (2002).

Evaluating the effects of S-ketamine on postoperative delirium in elderly patients following total hip or knee arthroplasty under intraspinal anesthesia: a single-center randomized, double-blind, placebo-controlled, pragmatic study protocol

IntroductionPostoperative delirium (POD) is an acute, transient brain disorder associated with decreased postoperative quality of life, dementia, neurocognitive changes, and mortality. A small number of trials have explored the role of S-ketamine in the treatment of POD due to its neuroprotective effects. Surprisingly, these trials have failed to yield supportive results. However, heterogeneity in delirium assessment methodologies, sample sizes, and outcome settings as well as deficiencies in S-ketamine use methods make the evidence provided by these studies less persuasive. Given the severe impact of POD on the health of elderly patients and the potential for S-ketamine to prevent it, we believe that designing a large sample size, and rigorous randomized controlled trial for further evaluation is necessary.MethodsThis is a single-center, randomized, double-blind, placebo-controlled, pragmatic study. Subjects undergoing total hip or knee arthroplasty will be randomized in a 1:1 ratio to intervention (n = 186) and placebo (n = 186) groups. This trial aims to explore the potential role of S-ketamine in the prevention of POD. Its primary outcome is the incidence of POD within 3 postoperative days. Secondary outcomes include the number of POD episodes, the onset and duration of POD, the severity and subtype of POD, pain scores and opioid consumption, sleep quality, clinical outcomes, and safety outcomes.DiscussionTo our knowledge, this is the first pragmatic study that proposes to use S-ketamine to prevent POD. We reviewed a large body of literature to identify potential preoperative confounding variables that may bias associations between the intervention and primary outcome. We will use advanced statistical methods to correct potential confounding variables, improving the test’s power and external validity of test results. Of note, the patient population included in this trial will undergo intraspinal anesthesia. Although large, multicenter, randomized controlled studies have found no considerable difference in the effects of regional and general anesthesia on POD, patients receiving intraspinal anesthesia have less exposure to at-risk drugs, such as sevoflurane, propofol, and benzodiazepines, than patients receiving general anesthesia. At-risk drugs have been shown to negatively interfere with the neuroprotective effects of S-ketamine, which may be the reason for the failure of a large number of previous studies. There is currently a lack of randomized controlled studies evaluating S-ketamine for POD prevention, and our trial helps to fill a gap in this area.Trial registration: http://www.chictr.org.cn, identifier ChiCTR2300075796.

Reversed phase high performance liquid chromatography for monitoring type-16 human papilloma virus like particles

Quantification of virus like particles (VLPs) is challenging due to the large size and structural heterogeneity of the molecule. Structural heterogeneity arises due to random assemblage of L1 protein with other host cell proteins. With multiple VLPs under development as potential biotherapeutic products, defining their identity, purity and potency is of great interest. Most analytical methods used at present for VLP quantification are laborious and at best semi-quantitative. Thus, there is a need for an analytical technique that is capable of quantitatively estimating both purity and titre at all stages of the process. In this study, we propose use of Reversed phase chromatography for separation and identification of VLP L1 proteins in inhouse crude and purified samplesand quantification of L1 protein at different process points. The proposed method takes about 20 min and has been demonstrated to be highly sensitive, robust, and selective as confirmed through mass spectrometry.

Analysis of the Impact of Carbon Finance on Digital Green Technology Innovation of Enterprises

Abstract Carbon finance, as a financial tool for adapting to and mitigating global climate change, can guide enterprises to help develop digital green technological innovation and ultimately realize the transition to a low-carbon economy. This paper selects relevant control variables and applies the spatial econometric model to analyze the impact of carbon financial trading policy on enterprises’ green technological innovation, and examines the different impacts of the policy on the number of green invention-based patent applications and the number of green utility model patent applications, respectively. To examine the heterogeneity of regions and enterprise size, the samples were further grouped. Finally, a gray correlation model is used to study the main drivers of the intrinsic interactions among the three systems of digital technology innovation, carbon finance, and industrial policy. Most of the gray correlations between technological innovation and carbon finance indicators are located between 0.5 and 0.7, and the average value of the correlations of all the indicators is higher than 0.60, with only four lower than 0.65, and the highest indicator is 0.666. It indicates that the correlation between carbon finance and digital green technological innovation among enterprises is high.