Signal Response Research Articles

Secure Triggering Frame-Based Dynamic Power Saving Mechanism against Battery Draining Attack in Wi-Fi-Enabled Sensor Networks.

Wireless local area networks (WLANs) have recently evolved into technologies featuring extremely high throughput and ultra-high reliability. As WLANs are predominantly utilized in Internet of Things (IoT) and Wi-Fi-enabled sensor applications powered by coin cell batteries, these high-efficiency, high-performance technologies often cause significant battery depletion. The introduction of the trigger frame-based uplink transmission method, designed to enhance network throughput, lacks adequate security measures, enabling attackers to manipulate trigger frames. Devices receiving such frames must respond immediately; however, if a device receives a fake trigger frame, it fails to enter sleep mode, continuously sending response signals and thereby increasing power consumption. This problem is specifically acute in next-generation devices that support multi-link operation (MLO), capable of simultaneous transmission and reception across multiple links, rendering them more susceptible to battery draining attacks than conventional single-link devices. To address this, this paper introduces a Secure Triggering Frame-Based Dynamic Power Saving Mechanism (STF-DPSM) specifically designed for multi-link environments. Experimental results indicate that even in a multi-link environment with only two links, the STF-DPSM improves energy efficiency by an average of approximately 55.69% over conventional methods and reduces delay times by an average of approximately 44.7% compared with methods that consistently utilize encryption/decryption and integrity checks.

Transcriptome Profiling of Gene Expression in Atlantic Salmon (Salmo salar) at Early Stage of Development.

For Atlantic salmon development, the most critical phase is the early development stage from egg to fry through alevin. However, the studies investigating the early development of Atlantic salmon based on RNA-seq are scarce and focus only on one stage of development. Therefore, using the RNA-seq technology, the assessment of different gene expressions of various early development stages (egg, alevin, and fry) was performed on a global scale. Over 22GB of clean data was generated from 9 libraries with three replicates for each stage with over 90% mapping efficiency. A total of 5534 genes were differentially expressed, among which 19, 606, and 826 genes were specifically expressed in each stage, respectively. The transcriptome analysis showed that the number of differentially expressed genes (DEGs) increased as the Atlantic salmon progressed in development from egg to fry stage. In addition, gene ontology enrichment demonstrated that egg and alevin stages are characterized by upregulation of genes involved in spinal cord development, neuron projection morphogenesis, axonogenesis, and cytoplasmic translation. At the fry stage, upregulated genes were enriched in the muscle development process (muscle cell development, striated muscle cell differentiation, and muscle tissue development), immune system (defense response and canonical NF-kappaB signal transduction), as well as epidermis development. These results suggest that the early development of Atlantic salmon is characterized by a dynamic shift in gene expression and DEGs between different stages, which provided a solid foundation for the investigation of Atlantic salmon development.

Unveiling the molecular dynamics of low temperature preservation in postharvest lotus seeds: a transcriptomic perspective

BackgroundPostharvest quality deterioration poses a significant challenge to the commercial value of fresh lotus seeds. Low temperature storage is widely employed as the primary method for preserving postharvest lotus seeds during storage and transportation.ResultsThis approach effectively extends the storage life of lotus seeds, resulting in distinct physiological changes compared to room temperature storage, including a notable reduction in starch, protein, H2O2, and MDA content. Here, we conducted RNA-sequencing to generate global transcriptome profiles of postharvest lotus seeds stored under room or low temperature conditions. Principal component analysis (PCA) revealed that gene expression in postharvest lotus seeds demonstrated less variability during low temperature storage in comparison to room temperature storage. A total of 14,547 differentially expressed genes (DEGs) associated with various biological processes such as starch and sucrose metabolism, energy metabolism, and plant hormone signaling response were identified. Notably, the expression levels of DEGs involved in ABA signaling were significantly suppressed in contrast to room temperature storage. Additionally, nine weighted gene co-expression network analysis (WGCNA)-based gene molecular modules were identified, providing insights into the co-expression relationship of genes during postharvest storage.ConclusionOur findings illuminate transcriptional differences in postharvest lotus seeds between room and low temperature storage, offering crucial insights into the molecular mechanisms of low temperature preservation in lotus seeds.

GBF1 deficiency causes cataracts in human and mouse.

Any opacification of the lens can be defined as cataracts, and lens epithelium cells play a crucial role in guaranteeing lens transparency by maintaining its homeostasis. Although several causative genes of congenital cataracts have been reported, the mechanisms underlying lens opacity remain unclear. In this study, a large family with congenital cataracts was collected and genetic analysis revealed a pathological mutation (c.3857C > T, p.T1287I) in the GBF1 gene; all affected individuals in the family carried this heterozygous mutation, while unaffected family members did not. Functional studies in human lens epithelium cell line revealed that this mutation led to a reduction in GBF1 protein levels. Knockdown of endogenous GBF1 activated XBP1s in the unfolded protein response signal pathway, and enhances autophagy in an mTOR-independent manner. Heterozygous Gbf1 knockout mice also displayed typic cataract phenotype. Together, our study identified GBF1 as a novel causative gene for congenital cataracts. Additionally, we found that GBF1 deficiency activates the unfolded protein response and leads to enhanced autophagy, which may contribute to lens opacity.

Eu3+-functionalized covalent organic framework for ratiometric fluorescence detection and adsorption of tetracycline and information steganography.

Functional materials with organic/inorganic composites as the main matrix and rare earth ion complexes as the guest have shown a very broad application prospect for antibiotic sensors. However, Eu3+-complex often relies on a single fluorescence response signal, which is susceptible to changes in the detection environment and cannot simultaneously detect and remove tetracycline (TC). Herein, green fluorescent covalent two-dimensionalorganic framework (COF-TD) is synthesized, followed by modification of Eu3+ to synthesize COF-TD@Eu3+. In the ratiometric sensor, Eu3+ serves as the recognition site and specific response probe for TC, while COF-TD is the fluorescence reference and carrier for Eu3+. Due to the antenna effect, TC enhances the red fluorescence of Eu3+, while the green fluorescence of COF-TD remainsalmost stable. Based on the change of fluorescence intensity and fluorescence color from green to red, the efficient ratiometric sensing can be finished in 1min. The developed method shows high sensitivitywith a detection limit of 0.3μM and highselectivity to TC which makes the methodapplicableto detect TC in traditional Chinese medicine preparations. In addition, due to the high specific surface area of COFs and specific adsorption sites, COF-TD@Eu3+ also shows good performance for TC removal. The findings show that the maximum adsorption capacity is 137.3mgg-1 and the adsorption equilibrium is reached in 30min. Smartphone assisted COF-TD@Eu3+ for both ratiometric fluorescence detection and detecting the absorption ofTC is proposed for the first time. The molecular cryptosteganography that transforms the selective response of COF-TD@Eu3+ to binary strings is anticipated to advance utilization of nanomaterials in logic sensing and information safety.

A Bioinformatic Strategy for Investigating the Mechanism of Hispolon in the Treatment of Triple-Negative Breast Cancer Combined with In vitro Experiments.

Hispolon, a phenolic compound isolated from the medicinal yellow fungal mulberry, exhibits a strong anti-triple-negative breast cancer (TNBC) effect. However, the antitumor mechanisms of Hispolon have not been fully explored. In this study, we systematically investigated the mechanism of Hispolon against TNBC based on bioinformatics and in vitro experiments. The Hispolon-related targets were first collected from the SwissTarget database. Differential Expression Genes (DEG) were screened between TNBC and normal breast tissue using the Gene Expression Comprehensive (GEO) dataset. The overlapping targets between Hispolon and DEG were analyzed by plotting Venn maps. Protein-protein interaction (PPI) network was constructed to analyze the interactions among these targets. The focus was on mining the core targets of anti-TNBC effects of Hispolon via the Cytohubba and MCODE plugin of Cytoscape 3.7.2 software. We performed survival analysis on these core targets to screen the best-matched targets, including EGFR, KIT, and PLAU. This correlated strongly with our validation of Hispolon by molecular docking. In addition, Gene Ontology (GO) anal-ysis and KEGG pathway analysis were performed using R software (ClusterProfiler package). Finally, in vitro experiments were performed to assess the accuracy of predicted target genes. The ADME results suggested that Hispolon has great potential to develop into a drug. Twenty overlapping targets were screened by matching the 107 targets of Hispolon to the 2,013 targets of TNBC DEG. Seven core targets of Hispolon against TNBC were initially identified, including EGFR, IGFBP3, MMP9, MMP2, MMP1, PLAU, and KIT. GO enrich-ment analysis demonstrated that the biological process of Hispolon acting on TNBC mainly involves lymphocyte activation in immune response and phosphatidylinositol-mediated signal-ing. Additionally, the relaxin signaling pathway, estrogen signaling pathway, proteoglycans in cancer, and others might be the key pathways of Hispolon against TNBC. Furthermore, Hispo-lon inhibited the proliferation of MDA-MB-231 cells in a concentration-dependent manner and regulated the RNA and protein expression of the core targets EGFR, PLAU, and KIT for the treatment of TNBC. In this study, the polygenic pharmacological mechanism of action of Hispolon against TNBC was explored through network pharmacology and in vitro experiments, provid-ing a new insight into the mechanism of TCM monomer against TNBC.

Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance.

Clinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.

70 Circulating leptin and immune-related transcriptomic patterns in clear cell renal cell carcinoma

Abstract Background Obesity has been associated with better outcomes in localized and metastatic clear cell renal cell carcinoma (ccRCC), as well as improved survival on immunotherapy treatment. However, the mechanisms underlying this association remain unclear. Leptin is an adipokine secreted by adipocytes, and circulating levels of leptin are higher in individuals with obesity. Additionally, leptin promotes inflammation and angiogenesis and has been proposed as pro-tumorigenic in colorectal and breast cancer. In this study, we examined how circulating leptin levels relate to both tumor and perinephric fat transcriptomic patterns in a cohort of ccRCC patients by evaluating the associations with body mass index (BMI), sex, and immune-related gene expression patterns. Methods We conducted a retrospective cohort study of 92 treatment-naïve ccRCC patients undergoing nephrectomy at Memorial Sloan Kettering Cancer Center. Available data included circulating leptin from fasting blood samples, clinical characteristics from medical records, and, in a subset of patients, RNA sequencing from tumor and perinephric fat specimens. We analyzed differentially expressed genes (DEG) according to circulating leptin levels using Gene Set Enrichment Analysis (GSEA) to describe pathways that were enriched in patients with high levels of leptin. We performed analysis for the whole cohort and stratified by sex based on differences in leptin levels. Results From the 92 patients with available peripheral leptin measurements, 51 and 44 had available tumor and perinephric fat RNA sequencing data, respectively. Of these, 64 (70%) were male, the median age was 60 years old, and most tumors were low grade and stage. Leptin distribution was significantly different in males than females, with circulating leptin levels of 7 ng/ml (IQR 4-14) and 22 ng/ml (IQR 9-52), respectively. Higher BMI was associated with higher leptin levels, with a correlation coefficient of 0.63 (p<0.001) in males and 0.77 (p<0.001) in females. GSEA of tumor DEGs by circulating leptin, showed upregulation of pathways related to adaptive immune activity in patients with higher leptin levels across sexes, although this association was attenuated in females. Strikingly, in the perinephric fat there were stark differences in opposite directions in female and male specimens, with females showing significantly enriched transcription of genes associated with B cell signaling, humoral and adaptive immune responses. Conclusions Higher leptin levels were associated with a modest increase of immune-related gene expression in the tumors in both males and females, but significantly different directional changes were observed in the perinephric fat. Circulating leptin may be involved in peritumoral immune responses which may link host factors to sex related tumor outcomes. Further studies should aim to address the relationship between leptin activity and the tumor and fat microenvironment. DOD CDMRP Funding: yes

Stress pathway outputs are encoded by pH-dependent clustering of kinase components

Signal processing by intracellular kinases controls near all biological processes but how signal pathway functions evolve with changed cellular context is poorly understood. Functional specificity of c-Jun N-terminal Kinases (JNK) are partly encoded by signal strength. Here we reveal that intracellular pH (pHi) is a significant component of the JNK network and defines signal response to specific stimuli. We show pHi regulates JNK activity in response to cell stress, with the relationship between pHi and JNK activity dependent on specific stimuli and upstream kinases activated. Using the optogenetic clustering tag CRY2, we show that an increase in pHi promotes the light-induced phase transition of ASK1 to augment JNK activation. While increased pHi similarly promoted CRY2-tagged JNK2 to form light-induced condensates, this attenuated JNK activity. Mathematical modelling of feedback signalling incorporating pHi and differential contributions by ASK1 and JNK2 condensates was sufficient to delineate signal responses to specific stimuli. Taking pHi and ASK1/JNK2 signal contributions into consideration may delineate oncogenic versus tumour suppressive JNK functions and cancer cell drug responses.

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study

BackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals’ functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored.MethodsThe main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection.ResultsResults indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD.ConclusionsThis study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.

Transdermal characteristic study of bovine sialoglycoproteins with anti-skin aging and accelerating skin wound healing.

Sialoglycoproteins play important roles in various biological processes, including cell adhesion, immune response, and cell signaling. Our previous studies indicated that the bovine sialoglycoproteins could be developed as a reagent against skin aging and as a new candidate for accelerating skin wound healing as well as inhibiting scar formation. However, transdermal characteristic of the bovine sialoglycoproteins is still unknown. This study investigated the transdermal permeation of the bovine sialoglycoproteins through porcine skin using the Franz diffusion cell method. Our study showed that the bovine sialoglycoproteins could penetrate through the porcine skin with a linear permeation pattern described by the regression equation N% = 11.49 t-3.858, with a high coefficient of determination (R2 = 0.9903). The histochemical results demonstrated the widespread distribution of the bovine sialoglycoproteins between the epidermal and dermal layers, which suggesting parts of the bovine sialoglycoproteins had ability to traverse the epidermal barrier. The results of the lectin microarrays indicated highly enriched glycopatterns on the bovine sialoglycoproteins, which also appeared in permeated porcine skin. The LC-MS/MS analysis further showed that the bovine sialoglycoproteins were composed of approximately 100 proteins with molecular weight ranging from 748.4 kDa to 10 kDa, and there were 23 specific bovine sialoglycoproteins with molecular weight ranging from 69.2 kDa to 10 kDa to be characterized in permeated porcine skin. Parts of the bovine sialoglycoproteins with molecular weight less than 69.2 kDa had ability to traverse the epidermal barrier. Understanding the permeation characteristics of the bovine sialoglycoproteins for developing innovative formulations with therapeutic benefits, contributing to advancements in cosmetic and dermatological fields.

An afferent nerve-like electronic device with somatic mechanical perception and sensation management

Tactile and pain perception are essential for biological skin to interact with the external environment. This complex interplay of sensations allows for the detection of potential threats and appropriate responses to stimuli. However, the challenge is to enable flexible electronics to respond to mechanical stimuli such as biological skin, and researchers have not clearly reported the successful integration of somatic mechanical perception and sensation management functions into neuro-like electronics. In this work, an afferent nerve-like device with a pressure sensor and a perception management module is proposed. The pressure sensor comprises two conductive fabric layers and an ionic hydrogel, forming a capacitor structure that emulates the swift transition from tactile to pain perception under mechanical stimulation. Drawing inspiration from the neuronal “gate control” mechanism, the sensation management module adjusts signals in response to rubbing, accelerating the discharge process and reducing the perception duration, thereby replicating the inhibitory effect of biological neurons on pain following tactile interference. This integrated device, encompassing somatic mechanical perception and sensation management, holds promise for applications in soft robotics, prosthetics, and human-machine interaction.

Polyvinyl alcohol /chitosan biomimetic hydrogel enhanced by MXene for excellent electromagnetic shielding and pressure sensing

Traditional electromagnetic shielding materials are difficult to realize practical applications due to excessive fillers, poor mechanical properties, and difficulty in preservation, etc. Hydrogel is a biomaterial with good biocompatibility and sustainability, which not only can overcome the aforementioned issues, but its biomimetic hierarchical porous structure also enables multifunctional applications. In this paper, a honeycomb-like unidirectional porous wall structured hydrogel is prepared by a simple freeze-thaw cycle and salting out method. Polyvinyl alcohol (PVA) and chitosan (CS) form a double cross-linked network (DN) enhanced by MXene, resulting in excellent mechanical and flexibility. Due to the synergistic effects of MXene, water, Fe3O4, abundant interfaces and micrometer porous wall structure, the electromagnetic shielding performance is enhanced. EMI SE increases by 30.7 dB as the MXene concentration increases from 0 to 1.5 wt%, and EMI SE increases from 7.9 to 66.7 dB as the water content increases from 0 to 76 %. Besides this, we encapsulate the hydrogel into a simple sensor, the signal response is rapid, the response /recovery time is 50/100 ms respectively, and it exhibits good sensitivity (0.0187 kPa−1). Different signals are generated based on variations in pressure, which holds significant importance for the development of wearable flexible sensors and information encoding.

Transcriptomic Plasticity of the Circadian Clock in Response to Photoperiod: A Study in Male Melatonin-Competent Mice.

Seasonal daylength, or circadian photoperiod, is a pervasive environmental signal that profoundly influences physiology and behavior. In mammals, the central circadian clock resides in the suprachiasmatic nuclei (SCN) of the hypothalamus where it receives retinal input and synchronizes, or entrains, organismal physiology and behavior to the prevailing light cycle. The process of entrainment induces sustained plasticity in the SCN, but the molecular mechanisms underlying SCN plasticity are incompletely understood. Entrainment to different photoperiods persistently alters the timing, waveform, period, and light resetting properties of the SCN clock and its driven rhythms. To elucidate novel candidate genes for molecular mechanisms of photoperiod plasticity, we performed RNA sequencing on whole SCN dissected from mice raised in long (light:dark [LD] 16:8) and short (LD 8:16) photoperiods. Fewer rhythmic genes were detected in mice subjected to long photoperiod, and in general, the timing of gene expression rhythms was advanced 4-6 h. However, a few genes showed significant delays, including Gem. There were significant changes in the expression of the clock-associated gene Timeless and in SCN genes related to light responses, neuropeptides, gamma aminobutyric acid (GABA), ion channels, and serotonin. Particularly striking were differences in the expression of the neuropeptide signaling genes Prokr2 and Cck, as well as convergent regulation of the expression of 3 SCN light response genes, Dusp4, Rasd1, and Gem. Transcriptional modulation of Dusp4 and Rasd1 and phase regulation of Gem are compelling candidate molecular mechanisms for plasticity in the SCN light response through their modulation of the critical NMDAR-MAPK/ERK-CREB/CRE light signaling pathway in SCN neurons. Modulation of Prokr2 and Cck may critically support SCN neural network reconfiguration during photoperiodic entrainment. Our findings identify the SCN light response and neuropeptide signaling gene sets as rich substrates for elucidating novel mechanisms of photoperiod plasticity. Data are also available at http://circadianphotoperiodseq.com/, where users can view the expression and rhythmic properties of genes across these photoperiod conditions.

Evaluating machine learning techniques for enhanced glaucoma screening through Pupillary Light Reflex analysis

Glaucoma is a leading cause of irreversible visual field degradation, significantly impacting ocular health. Timely identification and diagnosis of this condition are critical to prevent vision loss. A range of diagnostic techniques is employed to achieve this, from traditional methods reliant on expert interpretation to modern, fully computerized diagnostic approaches. The integration of computerized systems designed for the early detection and classification of clinical indicators of glaucoma holds immense potential to enhance the accuracy of disease diagnosis. Pupillary Light Reflex (PLR) analysis emerges as a promising avenue for glaucoma screening, mainly due to its cost-effectiveness compared to exams such as Optical Coherence Tomography (OCT), Humphrey Field Analyzer (HFA), and fundoscopic examinations. The noninvasive nature of PLR testing obviates the need for disposable components and agents for pupil dilation. This facilitates multiple successive administrations of the test and enables the possibility of remote execution. This study aimed to improve the automated diagnosis of glaucoma using PLR data, conducting an extensive comparative analysis incorporating neural networks and machine learning techniques. It also compared the performance of different data processing methods, including filtering techniques, feature extraction, data balancing, feature selection, and their effects on classification. The findings offer insights and guidelines for future methodologies in glaucoma screening utilizing pupillary light response signals.

Crosstalk between the DNA damage response and cellular senescence drives aging and age-related diseases.

Cellular senescence is a crucial process of irreversible cell-cycle arrest, in which cells remain alive, but permanently unable to proliferate in response to distinct types of stressors. Accumulating evidence suggests that DNA damage builds over time and triggers DNA damage response signaling, leading to cellular senescence. Cellular senescence serves as a platform for the perpetuation of inflammatory responses and is central to numerous age-related diseases. Defects in DNA repair genes or senescence can cause premature aging disease. Therapeutic approaches limiting DNA damage or senescence contribute to a rescued phenotype of longevity and neuroprotection, thus suggesting a mechanistic interaction between DNA damage and senescence. Here, we offer a unique perspective on the crosstalk between the DNA damage response pathway and senescence as well as their contribution to age-related diseases. We further summarize recent progress on the mechanisms and therapeutics of senescence, address existing challenges, and offering new insights and future directions in the senescence field.

Differential Abundance of DNA Damage Sensors and Innate Immune Signaling Proteins in Inositol Polyphosphate 4-Phosphatase Type II–Negative Triple-Negative Breast Cancer Classified by Immunotype

The influence of neoplastic cells on the tumor microenvironment is poorly understood. In this study, eight patient samples representing two immunotypes of triple-negative breast cancer (TNBC), defined by quantitative histologic criteria as T-cell desert and T-cell infiltrated (TCI), were compared via label-free quantitative protein mass spectrometry of material extracted directly from targeted regions of formalin-fixed, paraffin-embedded tissue sections. Of 2934 proteins quantitated, 439 were significantly differentially abundant, among which 361 were overabundant in TCI-TNBC. The 361-protein group included proteins involved in major histocompatibility complex-I antigen processing and presentation, viral defense, DNA damage response, and innate immune signaling. Immunohistochemical validation of selected proteins showed good positive correlation between neoplastic cell histoscores and label-free quantitation. Extension of immunohistochemical analysis to a total of 58 inositol polyphosphate 4-phosphatase type II-negative TNBC confirmed elevated levels of the DNA damage sensor interferon-γ-inducible protein 16, inflammasome adaptor ASC, and pore-forming protein gasdermin D in TCI-TNBC neoplastic cells. By contrast, cGMP-AMP synthase inhibitor BAF was elevated in the neoplastic cells of T-cell desert TNBC. These findings demonstrate a previously unknown correlation between the degree of T-cell infiltration in inositol polyphosphate 4-phosphatase type II-negative TNBC and the levels, in cognate neoplastic cells, of proteins that modulate innate immune signaling in response to DNA damage.

Advances in functional studies of plant MYC transcription factors.

Myelocytomatosis (MYC) transcription factors (TFs) belong to the basic helix-loop-helix (bHLH) family in plants and play a central role in governing a wide range of physiological processes. These processes encompass plant growth, development, adaptation to biotic and abiotic stresses, as well as secondary metabolism. In recent decades, significant strides have been made in comprehending the multifaceted regulatory functions of MYCs. This advancement has been achieved through the cloning of MYCs and the characterization of plants with MYC deficiencies or overexpression, employing comprehensive genome-wide 'omics' and protein-protein interaction technologies. MYCs act as pivotal components in integrating signals from various phytohormones' transcriptional regulators to orchestrate genome-wide transcriptional reprogramming. In this review, we have compiled current research on the role of MYCs as molecular switches that modulate signal transduction pathways mediated by phytohormones and phytochromes. This comprehensive overview allows us to address lingering questions regarding the interplay of signals in response to environmental cues and developmental shift. It also sheds light on the potential implications for enhancing plant resistance to diverse biotic and abiotic stresses through genetic improvements achieved by plant breeding and synthetic biology efforts.

A Highly Sensitive and Rapid Enzyme Biosensor Based on AuNPs/CS@cMWCNTS for Detecting Fusarium Acid

Fusarium acid (FSA) serves as a highly sensitive biomarker for the early warning of bulb rot in Lanzhou lily caused by Fusarium oxysporum infection. Realizing its highly sensitive, accurate, and rapid detection is crucial for the early warning and control of lily bulb rot. Herein, an enzyme biosensor based on the enzyme inhibition principle was developed for the rapid detection of FSA. Firstly, chitosan-functionalized carboxylated multi-walled carbon nanotubes (CS@cMWCNTS) and gold nanoparticles (AuNPs) were modified on a bare electrode by drop coating and electrochemical deposition methods, respectively. Subsequently, dopamine β-hydroxylase (DBH) was firmly immobilized on the electrode surface through the gold-sulfur bond. Because the activity of DBH can be inhibited by FSA, which leads to a noticeable change in the signal response during the conversion of dopamine (DA) to norepinephrine (NA). Under optimized experimental conditions, the sensor exhibits an excellent linear relationship in the concentration range of 1.00 × 10−5 μg ml−1 ∼ 1.00 × 103 μg ml−1 with the correlation coefficient of 0.9856 and the detection limit is 4.60pg ml−1. Additionally, the sensor showed good stability, repeatability (RSD 1.85%), and selectivity. The method was applied to analyze FSA in the extraction from Lanzhou lily with a recovery higher than 97.59% and RSD less than 1.383%. This method enables the highly sensitive and rapid detection of FSA in real samples, and provides scientific basis and technical support for early warning of diseases and accurate implementation of prevention and control strategies in crop planting and production.

Low-Molecular Weight Branched Polyethylenimine Reduces Cytokine Secretion from Human Immune System Monocytes Stimulated with Bacterial and Fungal PAMPs.

The innate immune system is an evolutionarily conserved pathogen recognition mechanism that serves as the first line of defense against tissue damage or pathogen invasion. Unlike the adaptive immunity that recruits T-cells and specific antibodies against antigens, innate immune cells express pathogen recognition receptors (PRRs) that can detect various pathogen-associated molecular patterns (PAMPs) released by invading pathogens. Microbial molecular patterns, such as lipopolysaccharide (LPS) from Gram-negative bacteria, trigger signaling cascades in the host that result in the production of pro-inflammatory cytokines. LPS stimulation produces a strong immune response and excessive LPS signaling leads to dysregulation of the immune response. However, dysregulated inflammatory response during wound healing often results in chronic non-healing wounds that are difficult to control. In this work, we present data demonstrating partial neutralization of anionic LPS molecules using cationic branched polyethylenimine (BPEI). The anionic sites on the LPS molecules from Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) are the lipid A moiety and BPEI binding create steric factors that hinder the binding of PRR signaling co-factors. This reduces the production of pro-inflammatory TNF-α cytokines. However, the anionic sites of Pseudomonas aeruginosa (P. aeruginosa) LPS are in the O-antigen region and subsequent BPEI binding slightly reduces TNF-α cytokine production. Fortunately, BPEI can reduce TNF-α cytokine expression in response to stimulation by intact P. aeruginosa bacterial cells and fungal zymosan PAMPs. Thus low-molecular weight (600 Da) BPEI may be able to counter dysregulated inflammation in chronic wounds and promote successful repair following tissue injury.