Browse Articles

Blood-triggered self-sealing and tissue adhesive hemostatic nanofabric

Screening conditions and constructs for attempted genetic transformation of C. elegans by Agrobacterium

Manipulating gene expression within a model organism is important for reverse genetic experimentation, and while techniques to generate transgenic C. elegans are available, they are optimised for creating individual lines. The ability to create libraries of genetically modified animals using C. elegans as a model would make new types of experiments possible and would speed up studies of animal physiology. Here, we describe a range of constructs designed to establish a high-throughput method of C. elegans transformation mediated by gene transfer from Agrobacterium. We demonstrate that C. elegans are able to survive on Agrobacterium as a sole food source, and screen conditions for Agrobacterium-mediated transformation in this organism. While we do not achieve routine gene transfer from Agrobacterium to C. elegans, we suggest that this technique has potential following further optimization. The success of the approach would enable rapid and high-throughput transformation of C. elegans, providing an improvement on currently available methods . Here we provide details of optimization conditions tested, and a useful resource of T-binary constructs for use by the scientific community.

High accuracy identification of maize seed varieties based on a lightweight improved YOLOv8

Cryo-EM Structure of the relaxosome, a complex essential for bacterial mating and the spread of antibiotic resistance genes

Abstract Bacterial mating, or conjugation, was discovered nearly 80 years ago as a process transferring genes from one bacterial cell (the donor) to another (the recipient). It requires three key multiprotein complexes in the donor cell: a DNA-processing machinery called the relaxosome, a double-membrane spanning type 4 secretion system (T4SS), and an extracellular appendage termed pilus. While the near-atomic resolution structures of the T4SS and pilus are already known, that of the relaxosome has not been reported to date. Here, we describe the cryo-EM structure of the fully assembled relaxosome encoded by the paradigm F plasmid in two different states corresponding to distinct functional steps along the DNA processing reaction. By varying the structures of model DNAs we delineate conformational changes required to initiate conjugation. Mutational studies of the various protein-protein and protein-DNA interaction hubs suggest a complex sensitive to trigger signals, that could arise from cell-to-cell contacts with recipient cells.

Nanopore-based targeted next-generation sequencing (tNGS): A versatile technology specialized in detecting low bacterial load clinical specimens

Introduction The 2024 global tuberculosis report indicated that the epidemiological situation of tuberculosis remains concerning. Current tuberculosis detection methods have limitations, highlighting the urgent need to develop more convenient, effective, and widely utilized detection technologies in clinical settings to facilitate early diagnosis and treatment guidance for tuberculosis. Nanopore-based targeted next-generation sequencing (tNGS) offers advantages such as convenience, efficiency, and long-read sequencing, making it a commonly used method for mycobacteria identification. Methods This study compared the detection efficiency of tNGS with Xpert MTB/RIF, MTB culture, and AFB smear in sputum samples, BALF samples, and pathological tissue samples to evaluate the clinical applicability of tNGS in diagnosing tuberculosis and low bacterial load tuberculosis, including extrapulmonary and smear-negative cases. Results Among the four detection methods, tNGS demonstrated the highest efficiency, sensitivity, specificity, and AUC values, which are 93.4%, 94.7%, and 0.94, respectively. This method was particularly advantageous for detecting tuberculosis in patients with low bacterial loads, as evidenced by a significantly different positive detection rate in histopathological specimens compared to other methods (P < 0.001). Furthermore, tNGS achieved overall positive detection rates of 93.8% for smear-negative tuberculosis patients and 89.1% for culture-negative tuberculosis patients, both of which were significantly higher than those of other detection methods (P < 0.05). Additionally, tNGS could directly identify bacterial strains and detect mutations associated with drug resistance. In this study, the agreement rate between tNGS strain identification of NTM and the final diagnosis was 94.1%. Among the 21 identified mutation sites associated with rifampicin resistance, one (Pro454His) was located outside RRDR. Conclusion It is anticipated that tNGS will play a crucial clinical role in the early prevention and control of tuberculosis in the future.

Temperature-induced microstructural evolution and fractal characteristics of high-enthalpy Chumathang granite for enhanced geothermal energy

Abstract Micro-structural attributes of Chumathang granite from Leh, India, were experimentally determined in the temperature range from 25 to 600 °C for enhanced geothermal systems (EGS). P-wave velocity, thermal crack generation, and pore attributes were analyzed using a combination of pulse ultrasonic velocity study, 3D X-ray tomography and low-pressure gas adsorption experiments, respectively. Results indicate that thermal crack development is driven by mineral composition and differential thermal expansion, with a significant increase in the thermal damage factor between 450 $$^\circ{\rm C}$$ ∘ C and 600 $$^\circ{\rm C}$$ ∘ C , accompanied by visible cracks at 600 $$^\circ{\rm C}$$ ∘ C . Surface area and pore volume decreased up to 300 $$^\circ{\rm C}$$ ∘ C due to mineral dissolution, then slightly increased up to 600 $$^\circ{\rm C}$$ ∘ C due to microfracture formation. Pore size distribution showed a dominance of coarser mesopores, and fractal dimensions decreased with temperature, reflecting simpler pore geometries. These findings enhance the understanding of granite’s microstructural changes under thermal stress, informing the optimization of EGS heat extraction efficiency.

Multiplex base editing to protect from CD33 directed drugs for immune and gene therapy

Encapsulation improves viability and stability of spray-dried Lactococcus lactis A12 for inclusion in fish feed

During probiotics manufacturing, drying is a crucial process for stabilization of probiotics after fermentation, since drying condition could affect viability and functionality as well as physical properties such as moisture content and water activity, which play key role in stability of dried probiotics during storage. Therefore, this study aimed to evaluate the effect of spray-drying parameters on the survival of Lactococcus lactis A12 after drying and exposure to gastrointestinal conditions. A combined mixture-process design was carried out by evaluating three factors: whey (10–30% w/v), maltodextrin (10–30% w/v), and atomization pressure (1.0–1.5 bar). As the main results, a high concentration of whey (30% w/v), low concentration of maltodextrin (10% w/v), and high atomization pressure (1.4 bar) improved survival of spray-dried L. lactis A12 after drying and exposure to pH 3.00 or bile salts with survival rates ranged within 69.25 to 86.24%, 65.89–98.93%, and 89.09–100%, respectively. Under optimal conditions, spray-dried probiotic powder with wall materials (encapsulated) exhibited higher glass transition temperature (64.44 vs 12.65 °C), and lower hygroscopicity (12.65 vs 64.44%) than spray-dried probiotic without wall materials (non-encapsulated). Moreover, SD probiotic powder exhibited the highest survival rate (85.88%) at 4 °C during 60 days of storage in comparison to 25 °C and 37 °C which did not survive. Finally, spray-dried L. lactis A12 was included in fish feed and exhibited a survival rate of 80.83% when it was stored at 4 °C after 60 days. It can be concluded that the use of encapsulating materials, particularly whey and maltodextrin, improved the physical and thermal stability of L. lactis A12 powder during drying and storage. Also, the results from the stability of supplemented fish feed suggested that L. lactis A12 could be included in fish feed.

Author Correction: Tanshinone IIA affects the malignant growth of Cholangiocarcinoma cells by inhibiting the PI3K-Akt-mTOR pathway

On-chip 3D potency assay for prediction of clinical outcomes for cell therapy candidates for osteoarthritis

The impact of computer science education in primary schools: Evidence from a randomized controlled trial in Iraq

With the growing digitization of society, there is a need to enhance computational thinking as an indispensable skill for modern daily life. Consequently, computer science education for children at early ages has become increasingly important. This study conducts a randomized controlled trial to examine the impact of the interventions using educational robotics as well as computer-aided mathematics drills (via a “math app”) on students’ performance in primary schools in Basra, Iraq. We provide several new empirical findings. First, the short-run impact of robotics-based learning on computational thinking is positive and statistically significant for girls, particularly poor performing girls, but not for boys. Second, the impact on computational thinking is augmented by introducing a math app, further improving computational thinking. Together, these two interventions also enhance general intelligence. Third, the positive impact was still evident more than three months after the interventions for girls who received both computer science and math education, suggesting their complementarity. Our results show that computer science education using educational robots in primary schools is effective in enhancing computational thinking and relevant skills.

MBLSTM is a contextual interaction refined method for time series prediction

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis

Glucagon-like peptide 1 level and risk of death within 90 days after intensive care unit admission: A substudy of the IVOIRE cohort

Background Elevated plasma levels of glucagon-like peptide-1 (GLP-1) have been associated with poor clinical outcome in patients with sepsis. This study investigated the association between GLP-1 levels, and survival at 90 days in a large cohort of critically ill patients. Methods All patients aged ≥ 18 years admitted to the intensive care unit (ICU) in a large university hospital, and receiving ≥1 life support therapy for organ failure were eligible for inclusion. Plasma samples were taken within 24h of ICU admission. We measured GLP-1 using a commercial ELISA kit. Cumulative probability of death at 90 days (D90) was plotted using the Kaplan-Meier method by quartiles of GLP-1. The effect of GLP-1 quartile on D90 survival was analyzed using a Cox proportional hazards model. Results A total of 507 patients had GLP-1 dosage; mean age 64.5 ± 14.5 years; 179 (35.3%) women. GLP-1 levels ranged from 0.03 to 129.2 (median 7.3[IQR:3.3;19.1]). Higher mean age, SOFA, SAPS II, and LPS 3HM were found in patients with higher GLP-1 quartile by univariate analysis. Overall, 229 patients (45.2%) died within 90 days. The cumulative probability of death was significantly associated with GLP-1 quartile (p log rank<0.0001). After adjustment for age, SOFA, renal replacement therapy and vasopressor treatment, a significantly increased risk was observed only for patients with the highest quartile of GLP-1 (adjusted hazard ratio 1.65 [1.06; 2.56] for 4th vs 1st quartile of GLP-1). Conclusion After adjusting for demographic and clinical characteristics, only the highest quartile of GLP-1 remained independently associated with an increased risk of death at 90 days after admission to ICU.

Deep cryo treated tungsten carbide tools on AISI 1045 steel turning through grey relational analysis and preference selection index

Abstract Global competition and increasing environmental concerns have compelled manufacturing industries to reduce energy consumption and enhance product quality. This, in turn, helps increase the production rate. In this context, the machining performance is largely influenced by the selection of process parameters and the condition of the cutting tool. The present study is based on an experiment involving the use of an uncoated, deep cryogenically treated tungsten carbide tool for machining AISI 1045 steel. The outcomes were evaluated using Grey Relational Analysis (GRA) and the Preference Selection Index (PSI). Both ANOVA methods indicated that feed rate, cutting speed, the use of deep cryo-treated tools, and depth of cut had the most significant effects. The optimal parameter settings identified include a deep cryo-treated tool, a cutting speed of 120 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 1.00 mm. This approach demonstrated that the feed rate had the greatest influence on flank wear and surface roughness, both of which were also significantly affected by cutting speed and depth of cut. Moreover, the deep cryo-treated tool outperformed the untreated tool, resulting in reductions in surface roughness and flank wear by 17% and 7%, respectively. Deep Cryogenic Treatment (DCT) has thus shown promise in enhancing the performance of tungsten carbide cutting tools used in machining operations. This study specifically investigated the effect of DCT on tool wear and surface finish during the turning of AISI 1045 steel.

Chondrocyte fatty acid oxidation drives osteoarthritis via SOX9 degradation and epigenetic regulation

Abstract Osteoarthritis is the most prevalent age-related degenerative joint disease and is closely linked to obesity. However, the underlying mechanisms remain unclear. Here we show that altered lipid metabolism in chondrocytes, particularly enhanced fatty acid oxidation (FAO), contributes to osteoarthritis progression. Excessive FAO causes acetyl-CoA accumulation, thereby altering protein-acetylation profiles, where the core FAO enzyme HADHA is hyperacetylated and activated, reciprocally boosting FAO activity and exacerbating OA progression. Mechanistically, elevated FAO reduces AMPK activity, impairs SOX9 phosphorylation, and ultimately promotes its ubiquitination-mediated degradation. Additionally, acetyl-CoA orchestrates epigenetic modulation, affecting multiple cellular processes critical for osteoarthritis pathogenesis, including the transcriptional activation of MMP13 and ADAMTS7. Cartilage-targeted delivery of trimetazidine, an FAO inhibitor and AMPK activator, demonstrates superior efficacy in a mouse model of metabolism-associated post-traumatic osteoarthritis. These findings suggest that targeting chondrocyte-lipid metabolism may offer new therapeutic strategies for osteoarthritis.

Linguistic challenges of writing papers in English for scholarly publication: Perceptions of Chinese academics in science and engineering

This study investigates the linguistic challenges encountered by Chinese academics in science and engineering when writing for English-language scholarly publications. Employing a mixed-methods approach, the research draws on survey responses from 732 participants and insights from semi-structured interviews with 13 interviewees. Sentence construction emerged as the most significant challenge, followed by issues with vocabulary selection, cohesive devices, coherence, and grammar, with notable variation across academic ranks. Common strategies to address these challenges include utilizing online tools, seeking peer support, and employing professional editing services. The findings offer actionable recommendations for tailored academic writing training, institutional support, and the integration of advanced technological tools, aiming to enhance publication success rates among non-native English-speaking scholars.

Phylogenetic insights into Leishmania species circulating among humans, vectors, and reservoir hosts in Shiraz, Southern Iran: implications for leishmaniasis control

WNK1 signalling regulates amino acid transport and mTORC1 activity to sustain acute myeloid leukaemia growth

Abstract The lack of curative therapies for acute myeloid leukaemia (AML) remains an ongoing challenge despite recent advances in the understanding of the molecular basis of the disease. Here we identify the WNK1-OXSR1/STK39 pathway as a previously uncharacterised dependency in AML. We show that genetic depletion and pharmacological inhibition of WNK1 or its downstream phosphorylation targets OXSR1 and STK39 strongly reduce cell proliferation and induce apoptosis in leukaemia cells in vitro and in vivo. Furthermore, we show that the WNK1-OXSR1/STK39 pathway controls mTORC1 signalling via regulating amino acid uptake through a mechanism involving the phosphorylation of amino acid transporters, such as SLC38A2. Our findings underscore an important role of the WNK1-OXSR1/STK39 pathway in regulating amino acid uptake and driving AML progression.

Cyber security Enhancements with reinforcement learning: A zero-day vulnerabilityu identification perspective

A zero-day vulnerability is a critical security weakness of software or hardware that has not yet been found and, for that reason, neither the vendor nor the users are informed about it. These vulnerabilities may be taken advantage of by malicious people to execute cyber-attacks leading to severe effects on organizations and individuals. Given that nobody knows and is aware of these weaknesses, it becomes challenging to detect and prevent them. For the real-time zero-day vulnerabilities detection, we bring out a novel reinforcement learning (RL) methodology with the help of Deep Q-Networks (DQN). It works by learning the vulnerabilities without any prior knowledge of vulnerabilities, and it is evaluated using rigorous statistical metrics. Traditional methods are surpassed by this one that is able to adjust to changing threats and cope with intricate state spaces while providing scalability to cybersecurity personnel. In this paper, we introduce a new methodology that uses reinforcement learning for zero-day vulnerability detection. Zero-day vulnerabilities are security weaknesses that have never been exposed or published and are considered highly dangerous for systems and networks. Our method exploits reinforcement learning, a sub-type of machine learning which trains agents to make decisions and take actions to maximize an approximation of some underlying cumulative reward signal and discover patterns and features within data related to zero-day discovery. Training of the agent could allow for real-time detection and classification of zero-day vulnerabilities. Our approach will have the potential as a powerful tool of detection and defense against zero-day vulnerabilities and probably brings significant benefits to security experts and researchers in the field of cyber-security. The new method of discovering vulnerabilities that this approach provides has many comparative advantages over the previous approaches. It is applicable to systems with complex behaviour, such as the ones presented throughout this thesis, and can respond to new security threats in real time. Moreover, it does not require any knowledge about vulnerability itself. Because of that, it will discover hidden weak points. In the present paper, we analyzed the statistical evaluation of forecasted values for several parameters in a reinforcement learning environment. We have taken 1000 episodes for training the model and a further 1000 episodes for forecasting using the trained model. We used statistical measures in the evaluation, which showed that the Alpha value was at 0.10, thereby indicating good accuracy in the forecast. Beta was at 0.00, meaning no bias within the forecast. Gamma was also at 0.00, resulting in a very high level of precision within the forecast. MASE was 3.91 and SMAPE was 1.59, meaning that a very minimal percentage error existed within the forecast. The MAE value was at 6.34, while the RMSE was 10.22, meaning a relatively low average difference within actuals and the forecasted values. Results The results demonstrate the effectiveness of reinforcement learning models in solving complex problems and suggest that the model improves in accuracy with more training data added.