Additional Signal Research Articles

Microplastics exacerbate tissue damage and promote carcinogenesis following liver infection in mice

Cancer is a leading cause of death worldwide, posing a substantial threat to human well-being. Microplastics (MPs) exposure can harm human health and the carcinogenicity of MP remains uncertain. In this study, we investigated carcinogenesis by MPs exposure. We observed MP significantly exacerbated hepatic injury in infectious conditions. In addition, cancer-related p53 and p21 signals are activated by MPs. Analysis of the liver transcriptomic landscape uncovered a noteworthy intensification of the carcinogenesis pathway by MPs compared with pre-infection. The transcription factor SALL2 could act as an oncogenic promoter in the promotion of cancer regulated by MPs. Further, big data analysis presents the correlation between MPs pollution and human hepatocellular carcinoma. This work revealed a toxic amplification effect of the non-bioactive MPs on the bioactive pathogens. This finding provides new insight into understanding the potential toxicity of the MPs.

Preclinical development of SGN-CD47M: Protease-activated antibody technology enables selective tumor targeting of the innate immune checkpoint receptor CD47.

CD47 is a cell surface glycoprotein that is expressed on normal human tissues and has a key role as a marker of self. Tumor cells have coopted CD47 overexpression to evade immune surveillance and thus blockade of CD47 is a highly active area of clinical exploration in oncology. However, clinical development of CD47-targeted agents has been complicated by its robust expression in normal tissues and the toxicities that arise from blocking this inhibitory signal. Further, pro-phagocytic signals are not uniformly expressed in tumors and antibody blockade alone is often not sufficient to drive antitumor activity. The inclusion of an IgG1 antibody backbone into therapeutic design has been shown to serve as an additional pro-phagocytic signal but also exacerbates toxicities in normal tissues. Therefore, a need persists for more selective therapeutic modalities targeting CD47. To address these challenges, we developed SGN-CD47M, a humanized anti-CD47 IgG1 monoclonal antibody linked to novel masking peptides through linkers designed to be cleaved by active proteases enriched in the tumor microenvironment. Masking technology has the potential to increase the amount of drug that reaches the tumor microenvironment, while concomitantly reducing systemic toxicities. We demonstrate that SGN-CD47M is well tolerated in cynomolgus monkeys and displays a 20-fold improvement in tolerability to hematologic toxicities when compared to the unmasked antibody. SGN-CD47M also displays preferential activation in the tumor microenvironment that leads to robust single-agent antitumor activity. For these reasons, SGN-CD47M may have enhanced antitumor activity and improved tolerability relative to existing therapies that target the CD47-SIRPα interaction.

A 23–29 GHz GaN Low-Noise Amplifier with Drain-to-Source Coupling Feedback

In this paper, a four-stage gallium nitride (GaN) low noise amplifier (LNA) using coupled-line (CL) feedback in a 0.15-μm GaN-on-SiC process is proposed. The electromagnetic coupling feedback between the drain and source of each transistor is employed to generate an additional signal path for neutralization, which enhances gain and improves stability performance. A series transmission line-capacitor-transmission line (TL-C-TL) network is introduced between stages of the LNA for wider band interstage matching. The measured results show that the designed LNA achieves a 3-dB bandwidth of 23.6 to 29.8 GHz, a peak gain of 23.7 dB at 25.8 GHz, and a minimum noise figure (NF) of 2.2 dB at 27.8 GHz. The output-referred 1-dB compression point (OP1dB) is 13 dBm. The total power consumption of the LNA is 200 mW.

Dynamic range extension method for sinusoidal phase modulating interferometer based on in-phase component signal reconstruction

Abstract The continuous increase of the amplitude of the measured vibration will cause spectrum aliasing in the interference signal of the sinusoidal phase modulating interferometer (SPMI), thereby constraining its measurement dynamic range (DR). To address this issue, a dynamic range extension method of SPMI based on the reconstruction of in-phase component signal is proposed. On the basis of conventional SPMI, an additional reference signal is introduced for estimating the phase modulation depth (PMD) and the major to minor axis ratio Re of the Lissajous ellipse formed by orthogonal interference signal pair and a phase demodulation algorithm named as PGC-ICR-DCM which integrates PGC-DCM algorithm and the in-phase component signal reconstruction (ICR) is proposed. Initially, the PMD is regulated to approximately 1.8412 rad, ensuring that the quadrature component signal can be accurately extracted from the mixed signal of the interference and carrier signals, even in the presence of spectrum aliasing in the original interference signal. Then, the undistorted quadrature component signal is used to reconstruct an in-phase component signal with the estimated value of Re. Finally, the reconstructed in-phase component signal and quadrature component signal are normalized, and a differential-and-cross-multiplying algorithm (DCM) is applied to obtain the measured vibration. A SPMI measurement system based on Michelson interferometer structure is constructed to experimentally validate the proposed method. The experimental results demonstrate that the proposed method can effectively extend the DR of the SPMI system in the presence of spectrum aliasing. The DR of the system is increased from 97.52 dB @ 55 Hz to 102.6 dB @ 55 Hz, with the maximum measurable amplitude increasing from 7728.75 nm @ 55Hz to 13705.16 nm @ 55 Hz.

Decorated Electrode Surfaces with Nanostructures and Metal-Organic Frameworks as Transducers for Sensing.

In this study, several materials are presented as modifiers of the screen-printed carbon electrodes with the aim of developing new sensing platforms for the voltammetric analysis of drugs. Specifically, Clotiapine and Sulfamethoxazole were selected as models for antipsychotics and antibiotics, respectively. Different nanostructures were studied as modifiers, including both transition metals and carbon-based materials. Moreover, biochar and two metal-organic frameworks (MOFs) were tested as well. The NH2-MIL-125(Ti) MOF showed an 80% improvement in the analytical signal of Sulfamethoxazole, but it partially overlapped with an additional signal associated with the loss of the MOF ligand. For this reason, several immobilization strategies were tested, but none of them met the requirements for the development of a sensor for this analyte. Conversely, carbon nanotubes and the NH2-MIL-101(Fe) MOF were successfully applied for the analysis of Clotiapine in the medicine Etumine®, with RSD below 2% and relative errors that did not exceed 9% in any case, which demonstrates the precision and accuracy achieved with the tested modifications. Despite these promising results, it was not possible to lower the limits of detection and quantification, so in this sense further investigation must be performed to increase the sensitivity of the developed sensors.

A Survey on Intent-aware Recommender Systems

Many modern online services feature personalized recommendations. A central challenge when providing such recommendations is that the reason why an individual user accesses the service may change from visit to visit or even during an ongoing usage session. To be effective, a recommender system should therefore aim to take the users’ probable intent of using the service at a certain point in time into account. In recent years, researchers have thus started to address this challenge by incorporating intent-awareness into recommender systems. Correspondingly, a number of technical approaches were put forward, including diversification techniques, intent prediction models or latent intent modeling approaches. In this paper, we survey and categorize existing approaches to building the next generation of Intent-Aware Recommender Systems (IARS). Based on an analysis of current evaluation practices, we outline open gaps and possible future directions in this area, which in particular include the consideration of additional interaction signals and contextual information to further improve the effectiveness of such systems.

Method for limiting the peak factor using an additional compensation signal in a system with orthogonal frequency division multiplexing for a Gaussian channel

Method for limiting the peak factor using an additional compensation signal in a system with orthogonal frequency division multiplexing for a Gaussian channel

CoMaSa:Context Multi-aware Self-attention for emotional response generation

Dialogue generation is an important research direction in natural language generation, and generating utterances with appropriate contextual emotion is a challenging task. The previous work incorporates commonsense knowledge as an auxiliary information source by simply concatenating or adding it to the embeddings of the dialogue context. They did not consider updating the commonsense knowledge from the perspective of context semantic information or selecting context from the perspective of commonsense knowledge semantic information. At the same time, they did not extract emotional information from dialogue context and commonsense knowledge to enhance the embeddings of the dialogue text. These defects may lead to the dialogue model’s inability to judge the semantic consistency between context and generated utterance, and result in the generation of utterance unassociated with the dialogue context and the corresponding context emotion being untrue. Our goal is to build an emotional dialogue generation model that can deeply integrate commonsense knowledge with dialogue context and achieve bidirectional semantic interaction and enhancement. Therefore, in this paper, we propose a context multi-aware self-attention emotion dialogue generation model that models from multiple aspects such as the semantic information, emotional information of context and external knowledge, it effectively alleviates the problems of generating utterance unrelated to the context and disordered emotional expressions in utterance. First, we adopt the transformer encoder as the basic framework and carefully construct a context-aware encoder capable of deeply extracting semantic information. Specifically, we ingeniously integrate different levels of positional information to simulate the natural flow of conversation between speakers. Then, we effectively integrate these positional information with the basic word embedding vectors, and enrich the dialogue’s embedding representation. Lastly, by introducing the attention mechanism, the model can precisely capture and extract context information closely related to the current situation and achieve a deep understanding and accurate grasp of the dialogue content. Second, we consider that the relationship between context and commonsense knowledge is not just a unidirectional selection but a more intimate bidirectional interaction. Therefore, we designed a bidirectional interaction attention component for context and external knowledge. Specifically, we use the method of iterative similarity matrices to calculate the bidirectional similarity relationship between context and external knowledge. Then, using the attention algorithm, we calculate the connectivity from context to commonsense knowledge and from commonsense knowledge to context. Finally, by combining the semantic embeddings of both aspects, we achieve bidirectional updating of context and external knowledge. Third, we establish an emotion-aware decoder based on multi-task learning, which includes an emotion classifier and an utterance generator. In the emotion classifier, we establish an auxiliary task for emotion recognition to help the model understand the process of emotional transition. We use the output of the emotion recognition model as an additional supervisory signal to better control the generation of emotional responses. In the utterance generator, we integrate the output of the emotion classifier with the interaction vector from the bidirectional interaction attention component. This fusion allows us to generate utterance that aligns with the emotional context. Our experiments on DailyDialog and ESConv datasets show that CoMaSa outperforms the baselines in terms of Perplexity, Distinct-1, Distinct-2, and human evaluation. The experiment demonstrates the effectiveness of our Context Multi-aware Self-attention model in the task of emotion generation.

Safety and pharmacokinetic properties of a new formulation of parenteral artesunate in healthy Thai volunteers

BackgroundParenteral artesunate is the first-line therapy for severe malaria. Artesunate, in its current formulation, must be prepared immediately before administration by first dissolving in sodium bicarbonate solution and then diluting in saline. A novel solvent for rapid and stable single step reconstitution of artesunate was recently developed showing improved solubility and stability. This study aimed to compare the safety and pharmacokinetic properties of the currently available and newly developed parenteral formulation of artesunate in healthy Thai volunteers.MethodsThis was an open-label, randomized, 4 periods, 4-treatments, 24-sequence, single-dose, cross-over study in 72 male and female healthy Thai volunteers. Frequent pharmacokinetic samples were collected in all volunteers at each dose occasion. Observed concentration–time profiles were analysed with a non-compartmental approach followed by a bioequivalence evaluation.ResultsBoth intramuscular and intravenous administrations of the new parenteral formulation of artesunate were safe and well-tolerated, with no additional safety signals compared to the currently used formulation. The pharmacokinetic properties of artesunate and its active metabolite, dihydroartemisinin, were well-characterized, and showed rapid conversion of artesunate into dihydroartemisinin. Intramuscular administration of the newly formulated artesunate resulted in almost complete bioavailability of dihydroartemisinin. The pharmacokinetic properties were similar between the old and new formulation.ConclusionsThe new and more easily prepared formulation of artesunate was safe and well-tolerated, with similar pharmacokinetic properties compared to the currently used formulation. Dihydroartemisinin, the active metabolite responsible for the majority of the anti-malarial effect, showed equivalent exposure after both intravenous and intramuscular administration of artesunate, suggesting that both routes of administration should generate comparable therapeutic effects.Trial registration: The study was registered to clinicaltrials.gov (#TCTR20170907002).

B-266 Therapeutic Drug Monitoring of Natalizumab and Anti-Natalizumab Antibodies

Abstract Background Natalizumab (NTZ) is a monoclonal antibody directed against the α4-integrin subunit of α4β1 and α4β7 integrins. NTZ is used to treat relapsing and remitting forms of multiple sclerosis. Although a majority of patients on standard dosing (intravenous 300 mg, every 4 weeks) reach therapeutic drug concentrations, about 10% of patients will eventually fail NTZ therapy due to the development of anti-NTZ antibodies. NTZ and anti-NTZ antibody concentrations in serum are used together to provide patient-specific pharmacokinetic and immunogenic assessment to aid in patient management. Methods Serum measurements of NTZ and anti-NTZ antibody levels are performed by lab developed electro-chemiluminescent immunoassays where assay design and principle are equivalent to biologic therapeutic drug monitoring described in our previous publication. The natalizumab drug assay is an immunoassay validated to measure free drug (pharmacodynamically active, ADA-unbound) in serum. The anti-natalizumab antibody assay utilizes a solution phase bridging method designed to measure total binding antibodies (including IgM & IgG subtypes). All anti-natalizumab antibody positive samples are confirmed for drug-specificity by an additional signal suppression step. The anti-natalizumab antibody assay is quantitative and drug-tolerant, meaning that circulating drug in patient serum does not interfere with anti-NTZ detection and quantitation. Results Here, we report concomitant measurement of NTZ and anti-NTZ antibody in 160 patient serum samples. Positive anti-NTZ levels from 24 to 235 ng/mL were found in 7.5% (12/160) patients. Anti-NTZ-free samples (148/160) had NTZ drug levels ranging from undetectable (<1.0) to 85 ug/mL. The mean and median drug level in 90 samples (results >1.0) was 10.8 and 2.7, respectively. 61/90 samples had therapeutic drug concentrations (at least 2.0 ug/mL). In the presence of anti-NTZ, 67% (8/12) had undetectable drug level and (4/12) had mean and median drug levels of 1.2 and 1.3, respectively, which is 9- or 2-fold lower than the mean and median drug levels of the anti-NTZ Ab -free group. Conclusions Low serum NTZ and high anti-NTZ are associated with loss of clinical efficacy, while elevated NTZ may increase progressive multifocal leukoencephalopathy risk. Assays to measure biologic drugs and their anti-drug antibodies in patient serum may be useful tools in dose optimization and patient management.

Neuroprotection by 4R-cembranoid against Gulf War Illness-related chemicals is mediated by ERK, PI3K, and CaMKII pathways

Gulf War Illness (GWI) has been consistently linked to exposure to pyridostigmine (PB), N,N-Diethyl-meta-toluamide (DEET), permethrin (PER), and traces of sarin. In this study, diisopropylfluorophosphate (DFP, sarin surrogate) and the GWI-related chemicals were found to reduce the number of functionally active neurons in rat hippocampal slices. These findings confirm a link between GWI neurotoxicants and N-Methyl-D-Aspartate (NMDA)-mediated excitotoxicity, which was successfully reversed by Edelfosine (a phospholipase Cβ (PLCβ3) inhibitor) and Flupirtine (a KCNQ/M (Kv7) channel agonist).To test whether 4R-cembranoid (4R), a nicotinic α7 acetylcholinesterase receptor (α7AChR) modulator known for its neuroprotective properties, can restore hippocampal neurons from glutamate-induced neurotoxicity, we exposed rat hippocampal slices with DFP for 10 min followed by 60 min treatment with 4R. We investigated the 4R mechanisms of neuroprotection after preincubation with LY294002, PD98059, and KN-62. The inhibition of the phosphatidylinositol 3-kinase (PI3K), mitogen-activated protein kinase kinase (MEK1/2), and calcium/calmodulin-dependent protein kinase (CaMKII) abrogated the protective effect of 4R against DFP-induced neurotoxicity. In separate experiments, after incubation with DFP, followed by 4R for 1 hr., cellular extracts were prepared for Western blotting of phospho-Akt, phospho-GSK3β, phosphorylated extracellular signal-regulated kinase (ERK)1/2, CaMKII and cAMP response element-binding protein (CREB). Our results show that DFP induces neuronal dysfunction by dephosphorylation, while 4R restores the phosphorylation of Akt, GSK3, ERK1/2, CREB, and CaMKII. Moreover, our proteomics analysis supported the notion that 4R activates additional signaling pathways related to enhancing neuronal signaling, synaptic plasticity, and apoptotic inhibition to promote cell survival against DFP, offering biomarkers for developing treatment against GWI.

Zero-Shot Image Caption Inference System Based on Pretrained Models

Recently, zero-shot image captioning (ZSIC) has gained significant attention, given its potential to describe unseen objects in images. This is important for real-world applications such as human–computer interaction, intelligent education, and service robots. However, the zero-shot image captioning method based on large-scale pretrained models may generate descriptions containing objects that are not present in the image, which is a phenomenon termed “object hallucination”. This is because large-scale models tend to predict words or phrases with high frequency, as seen in the training phase. Additionally, the method set a limitation to the description length, which often leads to an improper ending. In this paper, a novel approach is proposed to address and reduce the object hallucination and improper ending problem in the ZSIC task. We introduce additional emotion signals as guidance for sentence generation, and we find that proper emotion will filter words that do not appear in the image. Moreover, we propose a novel strategy that gradually extends the number of words in a sentence to confirm the generated sentence is properly completed. Experimental results show that the proposed method achieves the leading performance on unsupervised metrics. More importantly, the subjective examples illustrate the effect of our method in improving hallucination and generating properly ending sentences.

A novel application of laser speckle imaging technique for prediction of hypoxic stress of apples

BackgroundFruit storage methods such as dynamic controlled atmosphere (DCA) technology enable adjusting the level of oxygen in the storage room, according to the physiological state of the product to slow down the ripening process. However, the successful application of DCA requires precise and reliable sensors of the oxidative stress of the fruit. In this study, respiration rate and chlorophyll fluorescence (CF) signals were evaluated after introducing a novel predictors of apples' hypoxic stress based on laser speckle imaging technique (LSI).ResultsBoth chlorophyll fluorescence and LSI signals were equally good for stress detection in principle. However, in an application with automatic detection based on machine learning models, the LSI signal proved to be superior, due to its stability and measurement repeatability. Moreover, the shortcomings of the CF signal appear to be its inability to indicate oxygen stress in tissues with low chlorophyll content but this does not apply to LSI. A comparison of different LSI signal processing methods showed that method based on the dynamics of changes in image content was better indicators of stress than methods based on measurements of changes in pixel brightness (inertia moment or laser speckle contrast analysis). Data obtained using the near-infrared laser provided better prediction capabilities, compared to the laser with red light.ConclusionsThe study showed that the signal from the scattered laser light phenomenon is a good predictor for the oxidative stress of apples. Results showed that effective prediction using LSI was possible and did not require additional signals. The proposed method has great potential as an alternative indicator of fruit oxidative stress, which can be applied in modern storage systems with a dynamically controlled atmosphere.

Real-world diagnostic accuracy of lipoarabinomannan in three non-sputum biospecimens for pulmonary tuberculosis disease

Development of a non-sputum test using readily-obtainable biospecimens remains a global priority for tuberculosis (TB) control. We quantified lipoarabinomannan (LAM) concentrations, a pathogen biomarker for Mycobacterium tuberculosis, in urine, plasma and serum for real-world diagnostic accuracy of pulmonary TB among people living with and without HIV. We conducted a prospective diagnostic study among adults with TB symptoms in South Africa. We measured LAM concentrations in time-matched urine, plasma and serum with an electrochemiluminescence immunoassay using two capture antibodies (FIND 28 and S4-20). From the completed cohort, we randomly selected 210 participants (2 cases: 1 control) based on sensitivity estimates, and we compared diagnostic accuracy of LAM measurements against the microbiological reference standard. Urine and blood specimens from 210 of 684 adults enrolled were tested for LAM. Among 138TB-positive adults (41% female), median urine LAM was 137pg/mL and 52pg/mL by FIND 28 and S4-20, respectively. Average LAM concentrations were highest in HIV-positive participants with CD4+ T cells <200cells/mm3. Urine LAM by S4-20 achieved diagnostic sensitivity of 62% (95% CI: 53%-70%) and specificity of 99% (95% CI: 96%-100%). Plasma and serum LAM by FIND 28 showed similar sensitivity (70%, 95% CI: 62%-78%) and comparable specificities (90%, 95% CI: 82%-97%; 94%, 95% CI: 88%-99%). Diagnostic sensitivity of urine LAM by S4-20 was higher among participants without HIV (41%, 95% CI: 24%-61%) compared to HIV-positive participants with CD4 ≥200cells/mm3 (20%, 95% CI: 8%-39%). Detection of LAM was achievable in non-sputum specimens for pulmonary TB, but additional analyte concentration or signal amplification may be required to achieve diagnostic accuracy targets. Bill and Melinda Gates Foundation.

Fortification of cotton fabrics with dithiocarbamate-metal complexes to prepare durable antimicrobial fabrics

In this study, a simple and practical method is reported to fortify cotton fabrics with dithiocarbamate (DTC-Ct), dithiocarbamate-Cu (Cu-Ct) and dithiocarbamate-Ni (Ni-Ct) complexes via impregnation process to prepare durable antimicrobial fabrics. FTIR analysis indicates the presence of characteristic peaks corresponding to cellulose functional groups in the fortified fabrics. SEM micrographs illustrate the transition from a closed-packed, smooth surface in untreated cotton to a rough texture enveloped with metal complexes in fortified fabrics. EDX images confirm successful impregnation, with prominent peaks due to C and O in the untreated cotton, while additional signals of S, Cu, and Ni were observed in the fortified samples. TEM images revealed irregular, spherical nanoparticles within fortified cotton, compared with the rough surface of untreated fabrics. The average size of the treated cotton fabric fell within the range of 2.20–7.32, 3.83–28.50, and 2.70–7.32 nm for DTC-Ct, Cu-Ct and Ni-Ct, respectively. Untreated cotton fabric exhibits no inherent antibacterial properties, whereas fortified cotton fabrics demonstrate enhanced antibacterial efficacy against strains including Salmonella typhi, Enterobacter aerogenes, Shigella dysenteriae, and Klebsiella pneumonia, with Ni-Ct-fortified cotton proving most effective. Furthermore, the durability of additive adhesion to cotton fabrics was evaluated through washing tests, revealing robust adherence even after multiple cycles, with sustained antimicrobial inhibition observed for up to five wash cycles.

Development of a CRISPR/Cas12a-facilitated fluorescent aptasensor for sensitive detection of small molecules

The integration of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated proteins (Cas) exhibits superior performance in biosensor construction. And the distinctive role of aptamers in target recognition has long been a focal point of research. Through the combination of Cas12a with cis-cleavage activity and aptamer with specific recognition, a simple and rapid fluorescent biosensor has been constructed. Interestingly, with modified fluorescent and quenching groups at two ends, aptamers play a dual role: primarily as the elements for target recognition and additionally functioning act as the fluorescent probe for signal output. Coupling with cis-cleavage of Cas12a, the demand of additional signal probes is eliminated, thus simplifying the reaction system and enhancing result accuracy. Taking okadaic acid (OA) as a representative small molecule model to evaluate the sensor's performance, a simple and straightforward detection method was established. Following this, the universality of the constructed fluorescent aptasensor was validated by incorporating an adenosine triphosphate (ATP) aptamer. Consequently, the CRISPR/Cas12a-assisted aptasensor was demonstrated to serve as a versatile detection platform for small molecules in food safety and clinical diagnostics. In the forthcoming research endeavors, it can be further extended for applications in environmental analysis and various other fields.

Optimal pilot pattern for data‐aided channel estimation for MIMO‐OFDM wireless systems

AbstractThis article presents an optimal pilot pattern for the data‐aided channel estimation (DACE) scheme for both single‐input single‐output (SISO) and multiple‐input multiple‐output orthogonal frequency division multiplexing (MIMO‐OFDM) wireless systems. The research evaluates the performance of the DACE scheme using different comb‐type pilot patterns for both least square (LS) and linear minimum mean square error (LMMSE) channel estimators. In this regard, it is found that pilot spacing significantly influences system performance. Inserting pilot symbols in consecutive subcarriers cannot compensate for increased pilot spacing. Hence, the solution to this problem is to place pilot symbols at appropriate locations within the given spectrum. Moreover, data symbols which are reliably detected at the receiver are used as additional pilot signals to further enhance system performance. However, reliable data symbols need to be determined carefully because wrong detection results in severe performance degradation. In this respect, the proposed comb‐type pilot pattern using a single pilot subcarrier extracts the maximum number of reliable data symbols for the DACE scheme, improves channel estimation accuracy, and provides bandwidth optimization for MIMO‐OFDM systems. Furthermore, it outperforms all other pilot patterns in terms of system mean square error (MSE) and bit‐error‐rate (BER) performance.

Tenascin-C in the early lung cancer tumor microenvironment promotes progression through integrin αvβ1 and FAK.

Pre-cancerous lung lesions are commonly initiated by activating mutations in the RAS pathway, but do not transition to lung adenocarcinomas (LUAD) without additional oncogenic signals. Here, we show that expression of the extracellular matrix protein Tenascin-C (TNC) is increased in and promotes the earliest stages of LUAD development in oncogenic KRAS-driven lung cancer mouse models and in human LUAD. TNC is initially expressed by fibroblasts and its expression extends to tumor cells as the tumor becomes invasive. Genetic deletion of TNC in the mouse models reduces early tumor burden and high-grade pathology and diminishes tumor cell proliferation, invasion, and focal adhesion kinase (FAK) activity. TNC stimulates cultured LUAD tumor cell proliferation and migration through engagement of αv-containing integrins and subsequent FAK activation. Intringuingly, lung injury causes sustained TNC accumulation in mouse lungs, suggesting injury can induce additional TNC signaling for early tumor cell transition to invasive LUAD. Biospecimens from patients with stage I/II LUAD show TNC in regions of FAK activation and an association of TNC with tumor recurrence after primary tumor resection. These results suggest that exogenous insults that elevate TNC in the lung parenchyma interact with tumor-initiating mutations to drive early LUAD progression and local recurrence.

Adaptation of a Differential Scanning Calorimeter for Simultaneous Electromagnetic Measurements.

Although much information can be gained about thermally induced microstructural changes in metals through the measurement of their thermophysical properties using a differential scanning calorimeter (DSC), due to competing influences on the signal, not all microstructural changes can be fully characterised this way. For example, accurate characterisation of recrystallisation, tempering, and changes in retained delta ferrite in alloyed steels becomes complex due to additional signal changes due to the Curie point, oxidation, and the rate (and therefore the magnitude) of transformation. However, these types of microstructural changes have been shown to invoke strong magnetic and electromagnetic (EM) responses; therefore, simultaneous EM measurements can provide additional complementary data which can help to emphasise or deconvolute these complex signals and develop a more complete understanding of certain metallurgical phenomena. This paper discusses how a DSC machine has been modified to incorporate an EM sensor consisting of two copper coils printed onto either side of a ceramic substrate, with one coil acting as a transmitter and the other as a receiver. The coil is interfaced with a custom-built data acquisition system, which provides current to the transmit coil, records signals from the receive coil, and is controlled by a graphical user interface which allows the user to select multiple excitation frequencies. The equipment has a useable frequency range of approximately 1-100 kHz and outputs phase and magnitude readings at a rate of approximately 50 samples per second. Simultaneous DSC-EM measurements were performed on a nickel sample up to a temperature of 600 °C, with the reversable ferromagnetic to paramagnetic transition in the nickel sample invoking a clear EM response. The results show that the combined DSC-EM apparatus has the potential to provide a powerful tool for the analysis of thermally induced microstructural changes in metals, feeding into research on steel production, development of magnetic and conductive materials, and many more areas.

DNA template triggered copper nanoparticles generation coupled with hybridization chain reaction amplification for simultaneous detection of three mycotoxins in food samples

The co-occurrence of various mycotoxins in food, resulting from fungal infections, can lead to increased toxicity and enhanced harm through synergistic effects. In this work, a fluorescent assay was developed for simultaneous detection of zearalenone (ZEN), ochratoxin A (OTA) and aflatoxin B1 (AFB1) to address the issue of multiple mycotoxins co-contamination. Specific DNA hairpin-based aptamers were employed to recognize the mycotoxins and form a double-stranded DNA structure. Exonuclease III was introduced for the DNA cleavage, releasing single-stranded DNA triggers that could activate the assembling of DNA quadrilateral template. Copper nanoparticles were generated on the frame of DNA quadruplex template and produced fluorescent detection signals, while two hybridization chain reactions occurring on the different branches of the template and provided two additional detection signals. Inadequately reacted DNA chains were efficiently adsorbed and eliminated by Fe3O4@graphene oxide through magnetic separation. The limits of detection and linear ranges for ZEN, AFB1 and OTA were determined as 0.008 ng/mL, 0.003 ng/mL, 0.006 ng/mL and 0.010–100.000 ng/mL, 0.010–100.000 ng/mL, 0.010–50.000 ng/mL, respectively. Moreover, successful verification for real samples yielded recoveries from 99.2% to 102.7%, with a relative standard deviation of <5.23%. Artificially prepared toxic fungus infected samples were also analyzed. This method has demonstrated practical implications for the monitoring of food contaminants.