Early tumor shrinkage as a prognostic predictor in chemotherapy-naïve patients with locally advanced pancreatic cancer treated with modified FOLFIRINOX or gemcitabine plus nab-paclitaxel combination therapy: An exploratory analysis of JCOG1407.

BACKGROUND: Early tumor shrinkage (ETS) is a prognostic predictor for patients treated with chemotherapy in colorectal cancer, although scarce studies evaluated its potential in locally advanced pancreatic cancer (LAPC). In this exploratory analysis of JCOG1407, a randomized phase II study comparing modified 5-fluorouracil, levofolinate, irinotecan, and oxaliplatin (mFOLFIRINOX) and gemcitabine plus nab-paclitaxel (GnP), we evaluated whether ETS can predict prognosis of patients with LAPC. METHODS: Of the 126 patients enrolled in JCOG1407, 112 with measurable lesions were included in this study. ETS was defined as a ≥20 % reduction in tumor diameter compared with baseline at the initial imaging assessment 6-10 weeks after initiating chemotherapy. Patients were divided into the ETS (achieved ETS) and non-ETS (failed to achieve ETS) groups based on their ETS status. The impact of ETS on overall survival (OS) was compared using multivariable Cox regression analysis. RESULTS: Fourteen of 55 (25.5 %) and 24 of 57 (42.1 %) patients in the mFOLFIRINOX and GnP arms, respectively, achieved ETS. In the overall population, mFOLFIRINOX arm, and GnP arm, the median OS in the ETS and non-ETS groups was 27.1 and 20.4, 29.8 and 20.6, and 24.1 and 20.4, months, respectively. The adjusted hazard ratios of OS for the ETS group in the overall population, mFOLFIRINOX arm, and GnP arm were 0.451 (95 % confidence interval [CI]: 0.270-0.754), 0.371 (95 % CI: 0.149-0.926), and 0.508 (95 % CI: 0.255-1.004), respectively. CONCLUSIONS: ETS may be a prognostic predictor in chemotherapy-naïve patients with LAPC treated with mFOLFIRINOX or GnP.

Exploring the Role of Neutrophil-Related Genes in Osteosarcoma via an Integrative Analysis of Single-Cell and Bulk Transcriptome.

BACKGROUND: The involvement of neutrophil-related genes (NRGs) in patients with osteosarcoma (OS) has not been adequately explored. In this study, we aimed to examine the association between NRGs and the prognosis as well as the tumor microenvironment of OS. METHODS: The OS data were obtained from the TARGET-OS and GEO database. Initially, we extracted NRGs by intersecting 538 NRGs from single-cell RNA sequencing (scRNA-seq) data between aneuploid and diploid groups, as well as 161 up-regulated differentially expressed genes (DEGs) from the TARGET-OS datasets. Subsequently, we conducted Least Absolute Shrinkage and Selection Operator (Lasso) analyses to identify the hub genes for constructing the NRG-score and NRG-signature. To assess the prognostic value of the NRG signatures in OS, we performed Kaplan-Meier analysis and generated time-dependent receiver operating characteristic (ROC) curves. Gene enrichment analysis (GSEA) and gene set variation analysis (GSVA) were utilized to ascertain the presence of tumor immune microenvironments (TIMEs) and immunomodulators (IMs). Additionally, the KEGG neutrophil signaling pathway was evaluated using ssGSEA. Subsequently, PCR and IHC were conducted to validate the expression of hub genes and transcription factors (TFs) in K7M2-induced OS mice. RESULTS: FCER1G and C3AR1 have been identified as prognostic biomarkers for overall survival. The findings indicate a significantly improved prognosis for OS patients. The effectiveness and precision of the NRG signature in prognosticating OS patients were validated through survival ROC curves and an external validation dataset. The results clearly demonstrate that patients with elevated NRG scores exhibit decreased levels of immunomodulators, stromal score, immune score, ESTIMATE score, and infiltrating immune cell populations. Furthermore, our findings substantiate the potential role of SPI1 as a transcription factor in the regulation of the two central genes involved in osteosarcoma development. Moreover, our analysis unveiled a significant correlation and activation of the KEGG neutrophil signaling pathway with FCER1G and C3AR1. Notably, PCR and IHC demonstrated a significantly higher expression of C3AR1, FCER1G, and SPI1 in Balb/c mice induced with K7M2. CONCLUSIONS: Our research emphasizes the significant contribution of neutrophils within the TIME of osteosarcoma. The newly developed NRG signature could serve as a good instrument for evaluating the prognosis and therapeutic approach for OS.

Effect of butylated hydroxytoluene (BHT) concentrations on polymerization shrinkage stress and other physicochemical properties of experimental resin composites.

The present study examined different concentrations of the butylated hydroxytoluene (BHT) inhibitor on the kinetics of conversion, polymerization shrinkage stress, and other correlated physicochemical properties of experimental resin composites (ERC). A model composite was formulated with 75 wt% filler containing 0.5 wt% camphorquinone and 1 wt% amine with BHT concentrations of 0.01 wt% (BHT-0.01); 0.1 wt% (BHT-0.1); 0.25 wt% (BHT-0.25); 0.5 wt% (BHT-0.5); 1 wt% (BHT-1), and control (no BHT). They were tested on polymerization shrinkage stress (PSS; n = 5), degree of conversion (DC; n = 3), maximum polymerization rate (RpMAX; n = 5), water sorption (Wsp; n = 0), and solubility (Wsl; n = 10), flexural strength (FS; n = 10), flexural modulus (FM; n = 10), Knoop microhardness (KH; n = 10), and microhardness reduction (HR; n = 10). Data concerning these tests were submitted to one-way ANOVA and Tukey's test (α = 0.05; ß = 0.2). BHT-0.25, BHT-0.5, and BHT-1 showed a gradually significant decrease in PSS (p = 0.037); however, BHT-1 demonstrated a decrease in the physicochemical properties tested. Thus, within the limitations of this study, it was possible to conclude that BHT concentrations between 0.25 and 0.5 wt% are optimal for reducing shrinkage stress without affecting other physicochemical properties of ERCs.

Partial Scapholunate Interosseous Ligament Injuries: A Systematic Review of Treatment Options.

Purpose This systematic review summarizes the existing evidence on treatment options and outcomes for partial scapholunate interosseous ligament (pSLIL) injuries. Methods A systematic electronic search of Medline, Embase, and CINAHL was performed from inception through to February 13, 2022. All primary research articles addressing the treatment of pSLIL tears were eligible for inclusion regardless of timing of surgery, surgical technique, or rehabilitation. The PRISMA Checklist guided the reporting and data abstraction. Descriptive statistics and forest plots are presented. Results A total of 14 studies with 342 patients were included for analysis. Treatments were categorized into four groups: electrothermal shrinkage (ES), arthroscopic capsuloplasty (AC), open capsulodesis (OC), and no treatment (NT). There were five studies in the ES group ( N = 69, mean age = 34.3 ± 3.3 years), three studies in the AC group ( N = 138, mean age = 32.2 ± 3.8 years), five studies in the OC group ( N = 123, mean age of 30.7 ± 7.8 years), and one study in the NT group ( N = 12, mean age = 43 years, range = 28-67 years). The average postintervention visual analog scale pain score for the ES group was 1.4 ± 0.5 (from 5.7 ± 1.8), for the AC group was 3.2 ± 1.3 (from 6.6 ± 0), for the OC group was 2.3 ± 2.1 (from 5.6 ± 1.6), and for the NT group was 3.2 (from 7.6). The wrist extension range of motion improved postoperatively for all intervention groups (ES = 66.3°-70.7°; AC = 67°-74.5°; and OC = 48.9°-63.5°), whereas it remained unchanged for the NT group (46°-45°). Grip strength also improved in all intervention groups (ES = 17.9-29.9 kg; AC = 24.0-32.2 kg; and OC = 15.8-26.6 kg), while the NT group remained unchanged (25-24 kg). The radiographic scapholunate gap improved postoperatively in all groups that reported pre- and postintervention (ES = 2.2-1.9 mm; OC = 2.5-1.8 mm) and slightly worsened in the NT group (2.5-2.7 mm). In the ES group, there were three complications (11.5%, no major complications), in the AC group there was one major complication (0.9%, complex regional pain syndrome [CRPS]), and in the OC group there were six complications (15.4%, four major complications-CRPS). Conclusion All interventional treatment options (ES, AC, and OC) provided significant improvements in patient-reported pain, range of motion, grip strength, and radiographic parameters, with low complication rates. In comparison, no improvement in range of motion or grip strength was noted in the NT group. Therefore, surgical management of pSLIL injuries is an effective and relatively safe treatment option. Further studies comparing the outcomes of specific surgical treatments are warranted to further elucidate the optimal management option for pSLIL tears. Level of Evidence Level III, systematic review of Level III-IV studies.

Radiomic analysis reveals diverse prognostic and molecular insights into the response of breast cancer to neoadjuvant chemotherapy: a multicohort study.

BACKGROUND: Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. METHODS: This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. RESULTS: The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. CONCLUSIONS: Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

Bayesian Hierarchical Models for Subgroup Analysis.

In conventional subgroup analyses, subgroup treatment effects are estimated using data from each subgroup separately without considering data from other subgroups in the same study. The subgroup treatment effects estimated this way may be heterogenous with high variability due to small sample sizes in some subgroups and much different from the treatment effect in the overall population. A Bayesian hierarchical model (BHM) can be used to derive more precise, and less heterogenous estimates of subgroup treatment effects that are closer to the treatment effect in the overall population. BHM assumes exchangeability in treatment effect across subgroups after adjusting for effect modifiers and other relevant covariates. In this article, we will discuss the technical details for applying one-way and multi-way BHM using summary-level statistics, and patient-level data for subgroup analysis. Four case studies based on four new drug applications are used to illustrate the application of these models in subgroup analyses for continuous, dichotomous, time-to-event, and count endpoints.

Fatigue analysis of ambient-cured geopolymer concrete for high-traffic pavements.

The building sector is growing at a rapid rate, leading to an increased demand for construction materials. Concrete made with Ordinary Portland Cement (OPC) has long been the preferred choice due to its excellent bonding properties and versatility as demanded by construction process. However, the manufacturing of Ordinary Portland Cement (OPC) leads to negative impacts on the environment, with the cement sector responsible for around 5-8% of global CO2 emissions. In addition, the manufacture of OPC necessitates significant amounts of natural raw materials and energy. Contrastingly, using geopolymers promises to save substantial amounts of energy and reduce CO2 emissions. This potential has sparked growing interest in the application of geopolymers within transportation infrastructure. For pavements, the workability requirement is less, and hence, geopolymer concrete (GPC) is a viable option, but fatigue-resistance of GPC is not seen reported in literatures. This article evaluates the properties of geopolymer concrete with low-calcium fly ash partially replaced with ground granular blast furnace slag (GGBS) with 8 M NaOH alkaline solution and cured under ambient atmospheric conditions to evaluate its usage in pavements and develop an environmentally sustainable and durable GPC capable of withstanding heavy traffic. The study involves adjusting the pavement quality concrete (PQC) mix design; evaluating the mechanical characteristics, abrasion resistance, and shrinkage strain of the GPC; and analyzing its microstructure. Additionally, the study compares the fatigue life of GPC to that of PQC using various Weibull distribution approaches. The results showed that GPC4 (70% Fly ash and 30% GGBS) mix achieved best results at 28 days, with a compressive strength of 45.68 MPa, split tensile strength of 3.76 MPa, and flexural strength of 4.62 MPa. Also, shrinkage strains were nearly 31% lesser than PQC at 90 days. In addition, developing GPC needs 27% lesser embodied energy than PQC. Fatigue analysis prove that ambient cured fly ash-GGBS based geopolymer concrete with 8 M NaOH exhibits less stress development than PQC at medium loads, even though it is brittle. Thus, the study proves that it is suitable as a material for pavements to resist medium-loaded traffic-resisting pavements.

Linked shrinkage to improve estimation of interaction effects in regression models.

Objectives: The addition of two-way interactions is a classic problem in statistics, and comes with the challenge of quadratically increasing dimension. We aim to a) devise an estimation method that can handle this challenge and b) to aid interpretation of the resulting model by developing computational tools for quantifying variable importance. Methods: Existing strategies typically overcome the dimensionality problem by only allowing interactions between relevant main effects. Building on this philosophy, and aiming for settings with moderate n to p ratio, we develop a local shrinkage model that links the shrinkage of interaction effects to the shrinkage of their corresponding main effects. In addition, we derive a new analytical formula for the Shapley value, which allows rapid assessment of individual-specific variable importance scores and their uncertainties. Results: We empirically demonstrate that our approach provides accurate estimates of the model parameters and very competitive predictive accuracy. In our Bayesian framework, estimation inherently comes with inference, which facilitates variable selection. Comparisons with key competitors are provided. Large-scale cohort data are used to provide realistic illustrations and evaluations. The implementation of our method in RStan is relatively straightforward and flexible, allowing for adaptation to specific needs. Conclusions: Our method is an attractive alternative for existing strategies to handle interactions in epidemiological and/or clinical studies, as its linked local shrinkage can improve parameter accuracy, prediction and variable selection. Moreover, it provides appropriate inference and interpretation, and may compete well with less interpretable machine learners in terms of prediction.

Physical properties of experimental light-curing pattern resins based on poly (n-butyl methacrylate) or poly(iso-butyl methacrylate).

Experimental light-curing pattern resins were fabricated to produce pattern resin materials with adequate dimensional stability. The light-curing pattern resins consisted of poly(n-butyl methacrylate) or poly(iso-butyl methacrylate) (PiBMA) polymers and methacrylate monomers. The physical properties, amount of residual ash after burning, Vickers hardness, flexural strength, and volumetric polymerization shrinkage of each material were determined. The data obtained for the prepared resins were compared with those of a commercially available pattern resin, Palavit G (PG). A lower amount of residual ash was observed for some of the prepared resins than for PG. The Vickers hardness and flexural strength values of all experimental resins were lower than those of PG. The volumetric polymerization shrinkage of all the experimental resins based on PiBMA was lower than that of PG. These results suggest that acrylic light-curing resin materials based on PiBMA may be useful for patterning and indexing during soldering.

Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees.

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.

Innovative strategies in yacon drying: Ethanol pretreatment and intermittent microwave drying.

The yacon roots are rich in fructooligosaccharides (FOS) and highly perishable. Drying is crucial for food quality and extending shelf life. However, preserving thermosensitive compounds, such as FOS, poses a challenge in conventional drying methods. In this regard, microwave drying and ethanol pretreatment (ET) have emerged as promising solutions for maintaining nutrients and reducing drying time (DT). The objective of this study was to assess how ET and sample temperature affect quality and process parameters during intermittent microwave drying of yacon. Drying at 52°C treated with ethanol was the one that stood out for presenting the highest fructan retention (64.1%), low DT, lower energy consumption (EC) (364.00 ± 5.03 kWh kg water-1), higher retention of antioxidant capacity (73.9%) and total phenolic content (77.5%), and slight variation in color parameters. Therefore, microwave drying with a controlled temperature of yacon pretreated with ethanol effectively reduces DT and EC by maintaining quality parameters.

Two-Tier Efficient QoE Optimization for Partitioning and Resource Allocation in UAV-Assisted MEC.

Unmanned aerial vehicles (UAVs) have increasingly become integral to multi-access edge computing (MEC) due to their flexibility and cost-effectiveness, especially in the B5G and 6G eras. This paper aims to enhance the quality of experience (QoE) in large-scale UAV-MEC networks by minimizing the shrinkage ratio through optimal decision-making in computation mode selection for each user device (UD), UAV flight trajectory, bandwidth allocation, and computing resource allocation at edge servers. However, the interdependencies among UAV trajectory, binary task offloading mode, and computing/network resource allocation across numerous IoT nodes pose significant challenges. To address these challenges, we formulate the shrinkage ratio minimization problem as a mixed-integer nonlinear programming (MINLP) problem and propose a two-tier optimization strategy. To reduce the scale of the optimization problem, we first design a low-complexity UAV partition coverage algorithm based on the Welzl method and determine the UAV flight trajectory by solving a traveling salesman problem (TSP). Subsequently, we develop a coordinate descent (CD)-based method and an alternating direction method of multipliers (ADMM)-based method for network bandwidth and computing resource allocation in the MEC system. Extensive simulations demonstrate that the CD-based method is simple to implement and highly efficient in large-scale UAV-MEC networks, reducing the time complexity by three orders of magnitude compared to convex optimization methods. Meanwhile, the ADMM-based joint optimization method achieves approximately an 8% reduction in shrinkage ratio optimization compared to baseline methods.

A Study on the Application Performance of High-Aspect-Ratio Nano-Ettringite in Photocurable Resin Composites.

In this study, the impact of the addition of high-aspect-ratio nano-ettringite to photocurable epoxy acrylate resin was explored. The nano-ettringite samples were modified using γ-Aminopropyltriethoxysilane (KH-550) and γ-methacryloxypropyl trimethoxy silane (KH-570). Then, 3 wt% or 6 wt% KH-550-modified, KH-570-modified, and unmodified nano-ettringite samples were dispersed into resin via ultrasonic treatment in conjunction with mechanical stirring. The grafting effects of nano-ettringite onto KH-550 or KH-570 were analyzed through scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and thermogravimetric (TG) analysis. The results demonstrate that KH-550 and KH-570 have been successfully grafted onto the surface of nano-ettringite. In addition, this study also focuses on the variations of composite materials in the viscosity, shrinkage, tensile strength, and elongation at break. The results indicate that increased dosages of unmodified, KH-550-modified, and KH-570-modified nano-ettringite led to increased viscosity of the composite while reducing shrinkage. At the same dosage, the photocurable resin containing KH-570-modified nano-ettringite demonstrated a lower shrinkage and a higher tensile strength. From the analysis of tensile fracture surfaces, it was observed that compared to the KH-550 modified and unmodified variants, the KH-570 modified nano-ettringite exhibits superior dispersibility in photocurable epoxy acrylate resin. Notably, when the amount of KH-570-modified nano-ettringite was 3 wt%, the highest tensile strength of the composite was 64.61 MPa, representing a 72.57% increase compared to the blank sample. Furthermore, the incorporation of KH-570-modified nano-ettringite as a filler provides a new perspective for improving the performance of photocurable epoxy acrylate resin composites.

Thermodynamic and network characteristics of optimized lysine-modified kutki (Panicum sumatrense) millet starch hydrogels.

Three-dimensional polymeric network of hydrogels avoids its dissolution into the aqueous region. Hydrogels must have strong structural integrity to be used for drug/nutraceutical delivery. A three factor-three-level Box-Behnken design was used to understand the effects of starch concentration, NaCl, and pH on the textural and structural integrity of Lysine modified kutki millet starch hydrogels. Various kinetic models were fitted to the time-course measurement of shrinkage behavior of both conventionally (CDHG) and freeze-dried (FDHG) hydrogel. Increasing the swelling temperature (5-50 °C) showed values of higher molecular weight of polymer chains between neighboring crosslinks ( M c ) ¯ (g/mol) for FDHG (9539.59-56,769.72) than CDHG (1096.28-11,420.48). Similarly, mesh size (ξ) was more for FDHG (38.63-109.53 Ȧ) than CDHG (10.97-42.74 Ȧ). However, other network parameters such as polymer volume fraction ( ∅ p ) was lower for FDHG (0.229-0.146) than CDHG (0.3882-0.222). These values suggest low swelling power of CDHG compared to FDHG. Thermodynamically, FDHG took less energy to swell than CDHG. The study showed that FDHG has better properties than CDHG and could be employed in nutraceutical delivery. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-024-05953-x.

Will urban scale affect health services inequity? The empirical evidence from cities in China.

Background: The equity of public resources triggered by city shrinkage is a global challenge. Significantly, the impact of city shrinkage on the allocation of health service resources needs to be better understood. This study explores the impact of population change on government investment and health service delivery in shrinking cities. Data and method: Using data from China's Urban Statistical Yearbook (2010-2020), we employ regression discontinuity (RD) and fixed-effect models to examine the causal relationship between city shrinkage and health service provision. Result: Shrinking cities show significant disparities in health resources, particularly in bed numbers (-1,167.58, p < 0.05) and doctor availability (-538.54, p < 0.05). Economic development (p < 0.01) and financial autonomy (p < 0.01) influence hospital bed distribution. Investments in public services (primary schools and teachers, p < 0.01) affect health resource delivery. Robustness tests support our results. Conclusion: This study reveals how city shrinkage disrupts health service provision and equity, establishing a causal relationship between city shrinkage/expansion and health resource allocation, emphasizing the imbalance caused by urban population changes. City expansion intensifies competition for health resources, while shrinking cities struggle to provide adequate resources due to government reluctance. Policymakers should adapt health resource allocation strategies to meet patient demands in changing urban landscapes.

Controlled shrinkage of cellulose nanofibril films to enhance mechanical and barrier properties.

Standalone cellulose nanofibril (CNF) films have a natural tendency to shrink upon drying from wet conditions due to capillary drying stresses. This shrinkage happens in both the radial direction, and the vertical direction. In this study, we prepared two types of CNF films- one in a restrained condition that did not allow shrinkage in the radial direction but enabled it in the vertical direction and another with 11 % radial shrinkage but limited vertical shrinkage. The radial shrinkage led to a more porous structure than the vertical shrinkage, which brought about poorer oxygen/moisture barrier performance. However, the density and oxygen permeability of the films converged to a similar value upon a simple thermocompression process. Radial shrinkage resulted in 140 % and 90 % higher strain at break and toughness in films with a significant sacrifice in strength and modulus. Scanning electron microscopy revealed that radial shrinkage formed wavy layers in the core structure leaving more free space, whereas vertical shrinkage formed flatter layers. Radial shrinkage is likely to produce a thicker individual layer in the core structure of CNF films than vertical shrinkage. The insight from this study will help tune the mechanical and barrier performance of CNF films and their composites.

Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data.

The estimation of haplotype structure and frequencies provides crucial information about the composition of genomes. Techniques, such as single-individual haplotyping, aim to reconstruct individual haplotypes from diploid genome sequencing data. However, our focus is distinct. We address the challenge of reconstructing haplotype structure and frequencies from pooled sequencing samples where multiple individuals are sequenced simultaneously. A frequentist method to address this issue has recently been proposed. In contrast to this and other methods that compute point estimates, our proposed Bayesian hierarchical model delivers a posterior that permits us to also quantify uncertainty. Since matching permutations in both haplotype structure and corresponding frequency matrix lead to the same reconstruction of their product, we introduce an order-preserving shrinkage prior that ensures identifiability with respect to permutations. For inference, we introduce a blocked Gibbs sampler that enforces the required constraints. In a simulation study, we assessed the performance of our method. Furthermore, by using our approach on two distinct sets of real data, we demonstrate that our Bayesian approach can reconstruct the dominant haplotypes in a challenging, high-dimensional set-up.

GSOOA-1DDRSN: Network traffic anomaly detection based on deep residual shrinkage networks.

One of the critical technologies to ensure cyberspace security is network traffic anomaly detection, which detects malicious attacks by analyzing and identifying network traffic behavior. The rapid development of the network has led to explosive growth in network traffic, which seriously impacts the user's information security. Researchers have delved into intrusion detection as an active defense technology to address this challenge. However, traditional machine learning methods struggle to capture complex threats and attack patterns when dealing with large-scale network data. In contrast, deep learning methods have the advantages of automatically extracting features from network traffic data and strong generalization capabilities. Aiming to enhance the ability of network anomaly traffic detection, this paper proposes a network traffic anomaly detection based on Deep Residual Shrinkage Network (DRSN), namely "GSOOA-1DDRSN". This method uses an improved Osprey optimization algorithm to select the most relevant and essential features in network traffic, reducing the features' dimensionality. For better detection performance of network traffic anomalies, a one-dimensional deep residual shrinkage network (1DDRSN) is designed as a classifier. Validation is performed using the NSL-KDD and UNSW-NB15 datasets and compared with other methods. The experimental results show that GSOOA-1DDRSN has improved multi-classification accuracy, precision, recall, and F1 Score by approximately 2 % and 3 %, respectively, compared to the 1DDRSN model on two datasets. Additionally, it reduces the time computation costs by 20 % and 30 % on these datasets. Furthermore, compared to other models, GSOOA-1DDRSN offers superior classification accuracy and effectively reduces the number of features.

Analysis of gene expression in microglial apoptotic cell clearance following spinal cord injury based on machine learning algorithms.

Spinal cord injury (SCI) is a severe neurological complication following spinal fracture, which has long posed a challenge for clinicians. Microglia play a dual role in the pathophysiological process after SCI, both beneficial and detrimental. The underlying mechanisms of microglial actions following SCI require further exploration. The present study combined three different machine learning algorithms, namely weighted gene co-expression network analysis, random forest analysis and least absolute shrinkage and selection operator analysis, to screen for differentially expressed genes in the GSE96055 microglia dataset after SCI. It then used protein-protein interaction networks and gene set enrichment analysis with single genes to investigate the key genes and signaling pathways involved in microglial function following SCI. The results indicated that microglia not only participate in neuroinflammation but also serve a significant role in the clearance mechanism of apoptotic cells following SCI. Notably, bioinformatics analysis and lipopolysaccharide + UNC569 (a MerTK-specific inhibitor) stimulation of BV2 cell experiments showed that the expression levels of Anxa2, Myo1e and Spp1 in microglia were significantly upregulated following SCI, thus potentially involved in regulating the clearance mechanism of apoptotic cells. The present study suggested that Anxa2, Myo1e and Spp1 may serve as potential targets for the future treatment of SCI and provided a theoretical basis for the development of new methods and drugs for treating SCI.

Impact of chitosan extracted from shrimp shells on the shrinkage and mechanical properties of cement-based composites using dendritic fibrous nanosilica.

Dendritic fibrous nanosilica (DFNS) was functionalized using microcrystalline chitosan, derived from shrimp exoskeletons, to act as a robust anchor, resulting in DFNS@Chitosan. In order to prevent the restacking of chitosan sheets, the supramolecular polymerized chitosan not only served as a spacer but was also incorporated into cement-based composites. The physical-chemical characteristics of DFNS@Chitosan were assessed through various analytical techniques such as TEM, SEM, TGA, FTIR, AFM, XPS, and EDX. The potency and auto-induced contraction of Cement-based composite materials fortified with DFNS@Chitosan were probed. The incorporation of DFNS@Chitosan resulted in an increase in both compressive and interfacial stretching potency of the cement-based composites. Furthermore, the presence of DFNS@Chitosan effectively inhibited the occurrence of auto-induced contraction in the cement-based paste. This research endeavor is anticipated to promote an alternative utilization of DFNS and shrimp waste shells in the development of sustainable building materials.