Impact of neem oil biodiesel blends on physical and chemical properties of particulate matter emitted from diesel engines.

The global searchlight for sustainable alternative fuels to reduce emissions produced from the combustion of fossil fuels illuminates biofuels owing to their matching properties with fossil fuels. This is the impetus for this study which systematically examines the impact of neem biodiesel (NB) blends with pure diesel on the physical and chemical properties of particulate matter (PM) from diesel engines. Pure diesel (B0) and four fuel blends, namely, B5, B10, B15 and B20 are examined.

Rapid Microbial Profiling through Multimodal Biosensors for Transversal Analysis.

The intricate interactions between host and microbial communities hold significant implications for biology and medicine. However, traditional microbial profiling methods face limitations in processing time, measurement of absolute abundance, detection of low biomass, discrimination between live and dead cells, and functional analysis. This study introduces a rapid multimodal microbial characterization platform, Multimodal Biosensors for Transversal Analysis (MBioTA), for capturing the taxonomy, viability, and functional genes of the microbiota.

Enhancing trabecular CT scans based on deep learning with multi-strategy fusion.

Trabecular bone analysis plays a crucial role in understanding bone health and disease, with applications like osteoporosis diagnosis. This paper presents a comprehensive study on 3D trabecular computed tomography (CT) image restoration, addressing significant challenges in this domain. The research introduces a backbone model, Cascade-SwinUNETR, for single-view 3D CT image restoration.

Adaptive fractional-order nonsingular terminal sliding mode control and sequential quadratic programming torque distribution for lateral stability of FWID-EVs with actuator constraints.

This paper proposes a novel sliding mode control (SMC) algorithm for direct yaw moment control of four-wheel independent drive electric vehicles (FWID-EVs). The algorithm integrates adaptive law theory, fractional-order theory, and nonsingular terminal sliding mode reaching law theory to reduce chattering, handle uncertainty, and avoid singularities in the SMC system. A sequential quadratic programming (SQP) method is also proposed to optimize the yaw moment distribution under actuator constraints.

A Gated Recurrent Generative Transfer Learning Network for Fault Diagnostics Considering Imbalanced Data and Variable Working Conditions.

Transfer learning (TL) and generative adversarial networks (GANs) have been widely applied to intelligent fault diagnosis under imbalanced data and different working conditions. However, the existing data synthesis methods focus on the overall distribution alignment between the generated data and real data, and ignore the fault-sensitive features in the time domain, which results in losing convincing temporal information for the generated signal. For this reason, a novel gated recurrent generative TL network (GRGTLN) is proposed.

Semantic Segmentation of Gastric Polyps in Endoscopic Images Based on Convolutional Neural Networks and an Integrated Evaluation Approach.

Convolutional neural networks (CNNs) have received increased attention in endoscopic images due to their outstanding advantages. Clinically, some gastric polyps are related to gastric cancer, and accurate identification and timely removal are critical. CNN-based semantic segmentation can delineate each polyp region precisely, which is beneficial to endoscopists in the diagnosis and treatment of gastric polyps.

Long noncoding RNA MALAT1 is dynamically regulated in leader cells during collective cancer invasion.

Cancer cells collectively invade using a leader-follower organization, but the regulation of leader cells during this dynamic process is poorly understood. Using a dual double-stranded locked nucleic acid (LNA) nanobiosensor that tracks long noncoding RNA (lncRNA) dynamics in live single cells, we monitored the spatiotemporal distribution of lncRNA during collective cancer invasion. We show that the lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) is dynamically regulated in the invading fronts of cancer cells and patient-derived spheroids.

Physical properties and structural characteristics of particulate matter emitted from a diesel engine fueled with biodiesel blends.

This research explores the influence of renewable fuels, including three kinds of biodiesel along with ethanol on the physical properties and structural characteristics of particulate matter (PM) emitted from a diesel engine in comparison with pure diesel. After adding 10 vol% of grape seed biodiesel, coffee biodiesel and eucalyptus oil into diesel, three biodiesel blended fuels (10% grape seed biodiesel (DGs10), 10% spent coffee ground biodiesel (DC10) and eucalyptus oil biodiesel (DEu10)) were produced and tested in this study. Besides, one ethanol blend containing 9 vol% of ethanol and 1 vol% of biodiesel (blend stabilizer) was also tested to do the comparison.

A sticky-end probe biosensor for homogeneous detection of transcription factor binding activity.

Transcription factors are essential regulators of various physiological and pathological processes. However, detecting transcription factor-DNA binding activities is often time-consuming and labor-intensive. Homogeneous biosensors that are compatible with mix-and-measure protocols have the potential to simplify the workflow for therapeutic screening and disease diagnostics.

Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview.

Gastrointestinal (GI) cancers are the major cause of cancer-related mortality globally. Medical imaging is an important auxiliary means for the diagnosis, assessment and prognostic prediction of GI cancers. Radiomics is an emerging and effective technology to decipher the encoded information within medical images, and traditional machine learning is the most commonly used tool.

Transient nuclear deformation primes epigenetic state and promotes cell reprogramming.

Cell reprogramming has wide applications in tissue regeneration, disease modelling and personalized medicine. In addition to biochemical cues, mechanical forces also contribute to the modulation of the epigenetic state and a variety of cell functions through distinct mechanisms that are not fully understood. Here we show that millisecond deformation of the cell nucleus caused by confinement into microfluidic channels results in wrinkling and transient disassembly of the nuclear lamina, local detachment of lamina-associated domains in chromatin and a decrease of histone methylation (histone H3 lysine 9 trimethylation) and DNA methylation.

A reconfigurable microfluidic building block platform for high-throughput nonhormonal contraceptive screening.

Identifying nonhormonal contraceptives will have profound impacts on avoiding side effects of hormonal birth control methods, minimizing pregnancy complications and infant mortality rates, and promoting family planning. However, phenotypic screening of contraceptives is challenging due to the diverse procedures associated with oocyte culture, biochemical assays, and molecular imaging. This study reports a multifunctional microfluidic platform comprising reconfigurable building blocks and interfaces to implement various cell-based drug screening protocols.

Nrf2 Modulates the Hybrid Epithelial/Mesenchymal Phenotype and Notch Signaling During Collective Cancer Migration.

Hybrid epithelial/mesenchymal cells (E/M) are key players in aggressive cancer metastasis. It remains a challenge to understand how these cell states, which are mostly non-existent in healthy tissue, become stable phenotypes participating in collective cancer migration. The transcription factor Nrf2, which is associated with tumor progression and resistance to therapy, appears to be central to this process.

Diagnosis of Bloodstream Infections: An Evolution of Technologies towards Accurate and Rapid Identification and Antibiotic Susceptibility Testing.

Bloodstream infections (BSI) are a leading cause of death worldwide. The lack of timely and reliable diagnostic practices is an ongoing issue for managing BSI. The current gold standard blood culture practice for pathogen identification and antibiotic susceptibility testing is time-consuming.

Physical, chemical, and cell toxicity properties of mature/aged particulate matter (PM) trapped in a diesel particulate filter (DPF) along with the results from freshly produced PM of a diesel engine.

The lifetime and efficiency of diesel particulate filters (DPFs) strongly depend on the proper and periodic cleaning and servicing. Unfortunately, in some cases, inappropriate methods are applied to clean the DPFs, e.g.

Physicochemical and cell toxicity properties of particulate matter (PM) from a diesel vehicle fueled with diesel, spent coffee ground biodiesel, and ethanol.

The literature shows that information about the physical, chemical, and cell toxicity properties of particulate matter (PM) from diesel vehicles is not rich as the existence of a remarkable number of studies about the combustion, performance, and emissions of diesel vehicles using renewable liquid fuels, particularly biodiesels and alcohols. Also, the PM analyses from combustion of spent coffee ground biodiesel have not been comprehensively explored. Therefore, this research is presented.

Optimizing locked nucleic acid modification in double-stranded biosensors for live single cell analysis.

Double-stranded (ds) biosensors are homogeneous oligonucleotide probes for detection of nucleic acid sequences in biochemical assays and live cell imaging. Locked nucleic acid (LNA) modification can be incorporated in the biosensors to enhance the binding affinity, specificity, and resistance to nuclease degradation. However, LNA monomers in the quencher sequence can also prevent the target-fluorophore probe binding, which reduces the signal of the dsLNA biosensor.

Automatic detection of multiple types of pneumonia: Open dataset and a multi-scale attention network.

The quick and precise identification of COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, mycoplasma pneumonia, and normal lung on chest CT images play a crucial role in timely quarantine and medical treatment. However, manual identification is subject to potential misinterpretations and time-consumption issues owing the visual similarities of pneumonia lesions. In this study, we propose a novel multi-scale attention network (MSANet) based on a bag of advanced deep learning techniques for the automatic classification of COVID-19 and multiple types of pneumonia.

Intratumoral Heterogeneity Promotes Collective Cancer Invasion through NOTCH1 Variation.

Cellular and molecular heterogeneity within tumors has long been associated with the progression of cancer to an aggressive phenotype and a poor prognosis. However, how such intratumoral heterogeneity contributes to the invasiveness of cancer is largely unknown. Here, using a tumor bioengineering approach, we investigate the interaction between molecular subtypes within bladder microtumors and the corresponding effects on their invasiveness.

A transparent low intensity pulsed ultrasound (LIPUS) chip for high-throughput cell stimulation.

We report an on-chip platform for low-intensity pulsed ultrasound (LIPUS) stimulation of cells directly cultured on a biocompatible surface of a transparent ultrasound transducer (TUT) fabricated using lithium niobate. The high light transmittance (>80%) and compact size (3 mm × 3 mm × 2 mm) of TUTs allowed easy integration with powerful optical microscopy techniques with no additional acoustic coupling and risk for contamination. TUTs were excited with varying acoustic excitation parameters (voltage amplitude and duty cycle) and resulting live cell calcium signaling was simultaneously imaged using time-lapse confocal microscopy, while the temperature change was measured by a thermocouple.

Adaptive event-based robust passive fault tolerant control for nonlinear lateral stability of autonomous electric vehicles with asynchronous constraints.

This work solves the robust passive fault-tolerant control problem for autonomous electric vehicles based on an adaptive event triggered mechanism. Firstly, given the system uncertainties from the tire dynamics and the longitudinal speed, the T-S fuzzy model method is used to approximate the vehicle lateral dynamics. Secondly, taking the communication constraints caused by band-limited networks into account, an adaptive event-triggered scheme is introduced in the process of the control design.

A Rapid Single-Cell Antimicrobial Susceptibility Testing Workflow for Bloodstream Infections.

Bloodstream infections are a significant cause of morbidity and mortality worldwide. The rapid initiation of effective antibiotic treatment is critical for patients with bloodstream infections. However, the diagnosis of bloodborne pathogens is largely complicated by the matrix effect of blood and the lengthy blood tube culture procedure.

Why is the world not yet ready to use alternative fuel vehicles?

Despite the improvement in technologies for the production of alternative fuels (AFs), and the needs for using more AFs for motor vehicles for the reductions in air pollution and greenhouse gases, the number of alternative fuel vehicles (AFVs) in the global transportation sector has not been increasing significantly (there are even small drops for adapting some AFs through the projections) in recent years and even in the near future with projections to 2050. And gasoline and diesel fuels will remain as the main energy sources for motor vehicles. After reviewing the latest advantages and disadvantages of AFVs, including flexible-fuel, gas, electric, hybrid electric, and fuel cell electric vehicles, it is found that the higher price of AFVs, compared to that of gasoline and diesel vehicles, might be one of the main barriers for their wider adoption.

Decoding leader cells in collective cancer invasion.

Collective cancer invasion with leader-follower organization is increasingly recognized as a predominant mechanism in the metastatic cascade. Leader cells support cancer invasion by creating invasion tracks, sensing environmental cues and coordinating with follower cells biochemically and biomechanically. With the latest developments in experimental and computational models and analysis techniques, the range of specific traits and features of leader cells reported in the literature is rapidly expanding.