We designed and constructed a green, sustainable, and nongenetically modified organism (non-GMO) bioprocess to efficiently coproduce D-tagatose, bioethanol, and microbial protein from whey powder. First, a one-pot biosynthesis process involving lactose hydrolysis and D-galactose redox reactions for D-tagatose production was established in vitro via a three-enzyme cascade. Second, a nicotinamide adenine dinucleotide phosphate-dependent galactitol dehydrogenase mutant, D36A/I37R, based on the nicotinamide adenine dinucleotide-dependent polyol dehydrogenase from Paracoccus denitrificans was created through rational design and screening. Moreover, an NADPH recycling module was created in the oxidoreductive pathway, and the tagatose yield increased by 3.35-fold compared with that achieved through the pathway without the cofactor cycle. The reaction process was accelerated using an enzyme assembly with a glycine–serine linker, and the tagatose production rate was 9.28-fold higher than the initial yield. Finally, Saccharomyces cerevisiae was introduced into the reaction solution, and 266.5 g of D-tagatose, 371.3 g of bioethanol, and 215.4 g of dry yeast (including 38% protein) were obtained from 1 kg of whey powder (including 810 g lactose). This study provides a promising non-GMO process for functional food (D-tagatose) production. Moreover, this process fully utilized whey powder, demonstrating good atom economy.

Background, There were about 1,090,000 gastric cancer cases in 2020 in China. The incidence and mortality rates ranked the fifth and third among all kinds of cancers in China. Early diagnosis plays an important role in the treatment and prognosis of gastric cancer.plasma exosome lncRNAs, has become a promissing biomarkers with high specificity and sensitivity for early diagnosis of cancers. In this study, the exosomes in the plasma of patients with early gastric cancer were isolated by a commercial kit. After identified by electron microscopy observation, particle size analysis and Western-blot verification, the lncRNAs in the exosomes were extracted. The lncRNAs differentially expressed in the plasma exosomes of patients with gastric cancer were analysized by high-throughput RNA sequencing. The differentially expressed lncRNAs were verified by RT-qPCR in 93 patients with early gastric cancer and 49 normal controls. Electron microscopy, particle size analysis and Western blot showed that exosomes were successfully isolated from plasma. RNA-Seq results show that 76 lncRNAs were up-regulated and 260 lncRNAs were down regulated in plasma exosomes of early gastric cancer patients compared with normal controls. RT-qPCR analysis indicated that a total of 6 lncRNAs were significantly and differentially expressed in gastric cancer patients compared to normal controls, with 2 highly expressed and 4 lowly expressed (p < 0.05). The survival curve analysis indicated that lncmstrg.2441832.8 and lncmstrg.2312697 had higher sensitivity and specificity for the diagnosis of gastric cancer, respectively and AUC curve areas were 0.6211 and 0.631, p < 0.05, respectively, which were greater than the traditional clinical detection indexes CEA (0.61) and AFP (0.57). When combined lncmstrg.2441832.8 and lncmstrg.2312697 in gastric cancer diagnosis, AUC curve area reached 0.73, which was greater than CA199 (0.71). Conclusion, lncmstrg.2441832.8 and lncmstrg.2312697 may be a potential and promissing biomarkers for early diagnosis of gastric cance

Background: Laparoscopic liver resection (LLR) has not been widely accepted for recurrent liver cancer (RLC). This study aims to conduct a systematic review of the current literature for determining LLR effectiveness and safety for patients with RLC. Methods: Before April 2022, a comprehensive literature search was undertaken in Web of Science, PubMed, and Embase relied on a specified search strategy for eligible propensity score matching (PSM) studies comparing LLR or OLR. Meta-analysis of operative times, duration of stay, mortality, blood loss, overall survival rate, blood transfusion, recurrence-free survival rate, and overall complications was undertaken using a random/fixed-effects model. Results: Eight PSM studies of LLR versus OLR were incorporated, including 1128 patients. The current meta-analysis revealed nonsignificant variations between the two groups in overall survival rate, operation time, blood transfusion, mortality, overall complications, and long-term recurrence-free survival rate. Alternatively, when LLR is compared to OLR, LLR results in lower blood loss (p=0.002) and a shorter hospitalization (p=0.04). Conclusion: Although both techniques appear equal, LLR seems to have certain advantages over OLR. Notably, the evidence quality is generally confined to cohort studies, necessitating the performance of a high-quality randomized trial that compares both approaches. Keywords: Laparoscopic surgery, Liver resection, Recurrent liver cancer, Propensity score matching, Meta-analysis.

The application of metabolomics for studying modifications in host metabolism due to viral infections has proven to be a game-changing approach. Prior to our study, only one other ‘omics’ study has been carried out that investigates the interplay between the host and CCHFV and its subsequent pathogenesis. We employed NMR spectroscopy, given its advantages in terms of reproducibility, minimal sample preparation, and capability to analyze complex biofluids. Our methodology builds upon the proven success of metabolomics in the research of other viral hemorrhagic fevers such as Ebola, Marburg, and Dengue. Our research underlines the critical role of SAH, a metabolite involved in numerous biochemical reactions. We provide new insights into the metabolic alterations occurring in CCHF patients. These alterations not only shed light on the disease’s pathogenesis but also pave the way for potential biomarkers and therapeutic targets. Among all the metabolites detected, S-Adenosyl-L-homocysteine and Carnosine stood out as the most prevalent, warranting further exploration of their roles in CCHFV pathogenesis and their potential as therapeutic targets.

Cystic fibrosis-related hepatobiliary involvement (CFHBI) is a term used to describe a spectrum of hepatobiliary involvement ranging from benign elevation of transaminase levels to advanced cystic fibrosis associated liver disease (aCFLD). While CFHBI is common among people with cystic fibrosis (PwCF), aCFLD is rare impacting only approximately 5-10% of the CF population. Importantly though, aCFLD is the third leading cause of death among PwCF, is an independent predictor of all-cause mortality and is associated with significant morbidity. Despite this recognition, our ability to predict those patients at greatest risk for aCFLD, identify early aCFLD and monitor incremental progression of CFHBI is lacking. Here we review the strengths and weaknesses of the common biomarkers and imaging modalities used in the evaluation and monitoring of CFHBI, as well as the current understanding of genetic modifiers related to aCFLD.

The development of emotional competence is an important milestone during early childhood. Beyond early experience within the family, the (preschool) classroom is a relevant socialization context, and both teachers and peers may contribute to children’s emotion-related outcomes. Tracking changes in the emotion regulation competence of N = 173 preschool children (age in months: M = 43.3, SD = 6.6, 45% girls) over 6 months, the current study investigated whether and how peers contribute to differences in the development of emotion regulation in preschool classrooms. The research questions were addressed by examining three different kinds of peer groups: Classroom-level peer group, friendship group, and high-status peers. Teachers rated children’s emotion regulation competence and empathic co-regulation behavior at three assessment points. Multilevel growth modeling provided evidence that friendship-group empathic co-regulation (empathy, helping, and comforting behavior) predicted changes in preschoolers’ emotion regulation over time, confirming that friendship groups influence young children’s emotional development.

This paper is concerned with high moment and pathwise error estimates for both velocity and pressure approximations of the Euler-Maruyama scheme for time discretization and its two fully discrete mixed finite element discretizations. Optimal rates of convergence are established for all pth moment errors for p≥2 using a novel bootstrap technique. The almost optimal rates of convergence are then obtained using Kolmogorov’s theorem based on the high moment error estimates. Unlike for the velocity error estimate, the high moment and pathwise error estimates for the pressure approximation are proved in a time-averaged norm. In addition, the impact of noise types on the rates of convergence for both velocity and pressure approximations is also addressed. Finally, numerical experiments are also provided to validate the proven theoretical results and to examine the dependence/growth of the error constants on the moment order p.

Dolutegravir-Induced Acquired Sideroblastic Anemia in a HIV Positive Patient: A Challenging Hematologic Complication

Lately we've been seeing more cases of atypical mycobacterial infections, mostly in housewives and fishermen who have experienced some kind of trauma, like stabbings. However, it's rare to have it occur due to cosmetic injection, like in this case with a female patient who contracted the Mycobacterium chelonae-abscessus complex as a

The paper starts from the challenge of the critical cases in difference operator stability for neutral functional differential equations (NFDE). Such cases occur in the NFDE associated to 1 D hyperbolic partial differential equations (PDE) dynamics in Mechanical and Hydraulic Engineering. For some of such applications it resulted that the aforementioned critical (non-asymptotic) stability is connected to the character and level of the energy losses. It is shown that suitable choice of the losses to be taken into account can remove the critical stability properties and give the difference operator the asymptotic stability thus ensuring asymptotic stability for the system’s dynamics and also other asymptotic properties.

The anomalous variation in the diversion of flow and sediment at the major bifurcation nodes of the Pearl River network in recent years has been generally recognised and accepted, yet the underlying mechanisms have not been revealed. In this study, a large-scale two-dimensional flow-sediment numerical model of the Pearl River estuary was constructed using the TELEMAC-MASCARET modelling system. Additionally, synchronous field surveys from the dry season of 2016 and wet season of 2017 were used to validate the model. The complex branches system of the Pearl River network was generalised. The theoretical models for calculating the water diversion ratio of complex estuarine river networks were proposed. The water diversion ratio at each river network node is related to the Manning's roughness coefficient, the average cross-sectional water depth, the water surface slope, the length of the branches, and the average cross-sectional area from the river network nodes to the main estuary outlets. Specifically, the average cross-sectional water depth is the main driver of the formation of the water diversion ratios at the nodes in the Pearl River network. The sediment diversion ratios at the primary and secondary lateral branching nodes, are significantly higher than the water diversion ratios in the dry season, which explains the uneven distribution of flow and sediment. Sediment mining and reclamation are the main factors that have affected the variation in flow and sediment diversion ratios in the Pearl River network over recent decades.

This paper addresses the boundary control problem of the transport equation. Namely, we propose a control method, which is merely a delayed output feedback relying on a partial pole placement idea, that consists in assigning an appropriate exponential decay rate to the closed-loop system's solution. The proposed control structure appearing in the transport boundary, which has proven its effectiveness in controlling finite dimensional systems, consists of an autoregressive relation linking the transport equation's input and output. The obtained result provides an analytical lower bound for the solution's exponential decay.

Long-term studies of cyclic rodent populations have contributed fundamentally to the development of population ecology. Previous research has shown macroecological patterns of population dynamics in relation to latitude, but without disentangling the role of underlying ecological and climate drivers. We collected 26 rodent time-series from the tundra biome and assessed how population dynamics characteristics of the most prevalent species varied with latitude and environmental variables. While we could not find a relationship between latitude and population cycle peak interval, other characteristics of population dynamics had latitudinal patterns. The environmental predictor variables provided insight into causes of these patterns, as i) increased proportion of optimal habitat in the landscape led to higher population cycle amplitudes in all species and ii) mid-winter climate variability had negative impacts on cycle amplitude in Norwegian lemmings and grey-sided voles. These results indicate that biome-scale climate and landscape change can be expected to have profound impacts on rodent population cycles and that the macro-ecology of such functionally important tundra ecosystem characteristics is likely to be subjected to transient dynamics.

A document by Ayad Tareq Imam. Click on the document to view its contents.

Component-based software development has been regarded as one of the newest trends in the software development industry. In some ways, component-based software development focuses on reusability. In fact, high-quality software components refer to components that are highly cohesion internally, and also have the least coupling with other components, or in other words, are independent. Thus, using such components will lead to faster software development. In this way, this study aims to identify reusable components in software. To do this, first, software components were extracted from the source code of software systems. To identify reusable components, an artificial neural network algorithm has been used. On the other hand, the reusable components recognized by the evolutionary particle swarm optimization algorithm have been clustered. In this study, the particle swarm optimization algorithm was modified to apply to clustering problems. Finally, with the help of these clusters, the KNN classifier was trained, and during identifying reused inputs, the cluster to which the input belongs was determined by the classifier. This way, we will have a library of reusable components, where similar components are placed in a cluster. The proposed algorithm was experimentally evaluated on nine open-source software systems belonging to different domains. The results of this study show that the counted software components are potentially reusable and confirm the research findings.

Anemia occurs when the hemoglobin (Hgb) value falls below a certain reference range. It requires many blood tests, radiological images, and tests for diagnosis and treatment. By processing medical data from patients with artificial intelligence and machine learning methods, disease predictions can be made for newly ill individuals and decision-support mechanisms can be created for physicians with these predictions. Thanks to these methods, which are very important in reducing the margin of error in the diagnoses made by doctors, the evaluation of data records in health institutions is also important for patients and hospitals. In this study, three hybrid models are proposed to classify non-anemia records, Hgb-anemia, folate deficiency anemia (FDA), iron deficiency anemia (IDA), and B12 deficiency anemia by combining artificial intelligence and machine learning methods TreeBagger with Crow Search Algorithm (CSO), Chicken Swarm Optimization Algorithm (CSO) and JAYA methods. The proposed hybrid models aim to achieve high performance by better emphasizing the importance of parameters. To solve the multiclass anemia classification problem, fuzzy logic-based parameter optimization is applied to improve the class-based accuracy as well as the overall accuracy in the dataset. The classification performances of the proposed methods are evaluated using accuracy, F-score, precision, and recall criteria to build a prediction model to identify the anemia type of anemic patients. A result of the study on the dataset taken from the Kaggle database found that the three proposed hybrid methods outperformed other studies using the same dataset and similar studies in the literature.

Aquaporins (AQPs) are intrinsic membrane proteins responsible for facilitating water transport across biological membranes. AQPs found in plant membrane vesicles (MV) have been related to the functionality and stability of the vesicles. In this study, we focused on AQPs obtained from Brassica oleracea var. L. italica (broccoli) by the great potential for different biotechnological applications. To gain further insight into the role of AQPs in MV and advance the biotechnological applications of AQPs, we describe the heterologous overexpression of two broccoli AQPs (BoPIP1;2 and BoPIP2;2) in Pichia pastoris, resulting in the purification of both AQPs with high yield (0.14 and 0.99 mg per gram cells for BoPIP1;2 and BoPIP2;2, respectively). We reconstituted purified AQPs in liposomes to study their functionality, showing no changes in size compared to liposomes. BoPIP2;2 facilitated water transport, which was preserved for seven days at 4oC and 25ºC but not at 37oC, whereas BoPIP1;2 did not enhance water transport across the proteoliposome membrane. Additionally, BoPIP2;2 was incorporated into liposomes to encapsulate a resveratrol extract in proteoliposome vesicles, resulting in increased entrapment efficiency compared to conventional liposomes. Molecular docking identified potential binding sites for resveratrol in PIP2s, highlighting the role of AQPs in the improved entrapment efficiency of resveratrol. Moreover, a modelling study was conducted, demonstrating interactions between a plant AQP and human integrin, which may be a benefit to increase contact and internalization by the human target cells. Thus, our results suggest that AQPs-based alternative encapsulation systems can be used in specifically target biotechnological applications.

In this paper we study the spectral properties of a family of discrete one-dimensional quasi-periodic Schrödinger operators (depending on a phase theta). In large disorder, under some suitable conditions on v and a diophantine rotation number, we prove using basically K.A.M theory that the spectrum of this operator is pure point for all θ∈[0 ,2 π) with exponential decaying eigenfunctions.