A TeZla micromixer for interrogating the early and broad folding landscape of G-quadruplex via multistage velocity descending.

Biomacromolecular folding kinetics involves fast folding events and broad timescales. Current techniques face limitations in either the required time resolution or the observation window. In this study, we developed the TeZla micromixer, integrating Tesla and Zigzag microstructures with a multistage velocity descending strategy. TeZla achieves a significant short mixing dead time (40 µs) and a wide time window covering four orders of magnitude (up to 300 ms). Using this unique micromixer, we explored the folding landscape of c-Myc G4 and its noncanonical-G4 derivatives with different loop lengths or G-vacancy sites. Our findings revealed that c-Myc can bypass folding intermediates and directly adopt a G4 structure in the cation-deficient buffer. Moreover, we found that the loop length and specific G-vacancy site could affect the folding pathway and significantly slow down the folding rates. These results were also cross-validated with real-time NMR and circular dichroism. In conclusion, TeZla represents a versatile tool for studying biomolecular folding kinetics, and our findings may ultimately contribute to the design of drugs targeting G4 structures.

The VLPFC-Engaged Voluntary Emotion Regulation: Combined TMS-fMRI Evidence for the Neural Circuit of Cognitive Reappraisal.

A clear understanding of the neural circuit underlying emotion regulation (ER) is important for both basic and translational research. However, a lack of evidence based on combined neuroimaging and neuromodulation techniques calls into question (1) whether the change of prefrontal-subcortical activity intrinsically and causally contributes to the ER effect; and (2) whether the prefrontal control system directly modulates the subcortical affective system. Accordingly, we combined fMRI recordings with transcranial magnetic stimulation (TMS) to map the causal connections between the PFC and subcortical affective structures (amygdala and insula). A total of 117 human adult participants (57 males and 60 females) were included in the study. The results revealed that TMS-induced ventrolateral PFC (VLPFC) facilitation led to enhanced activity in the VLPFC and ventromedial PFC (VMPFC) as well as attenuated activity in the amygdala and insula during reappraisal but not during nonreappraisal (i.e., baseline). Moreover, the activated VLPFC intensified the prefrontal-subcortical couplings via the VMPFC during reappraisal only. This study provides combined TMS-fMRI evidence that downregulating negative emotion involves the prefrontal control system suppressing the subcortical affective system, with the VMPFC serving as a crucial hub within the VLPFC-subcortical network, suggesting an indirect pathway model of the ER circuit. Our findings outline potential protocols for improving ER ability by intensifying the VLPFC-VMPFC coupling in patients with mood and anxiety disorders.SIGNIFICANCE STATEMENT Using fMRI to examine the TMS effect, we uncovered that the opposite neural changes in prefrontal (enhanced) and subcortical (attenuated) regions are not a byproduct of emotion regulation (ER); instead, this prefrontal-subcortical activity per se causally contributes to the ER effect. Furthermore, using TMS to amplify the neural changes within the ER circuit, the "bridge" role of the VMPFC is highlighted under the reappraisal versus nonreappraisal contrast. This "perturb-and-measure" approach overcomes the correlational nature of fMRI data, helping us to identify brain regions that causally support reappraisal (the VLPFC and VMPFC) and those that are modulated by reappraisal (the amygdala and insula). The uncovered ER circuit is important for understanding the neural systems underlying reappraisal and valuable for translational research.

Enhancing ventrolateral prefrontal cortex activation mitigates social pain and modifies subsequent social attitudes: Insights from TMS and fMRI.

Social pain, a multifaceted emotional response triggered by interpersonal rejection or criticism, profoundly impacts mental well-being and social interactions. While prior research has implicated the right ventrolateral prefrontal cortex (rVLPFC) in mitigating social pain, the precise neural mechanisms and downstream effects on subsequent social attitudes remain elusive. This study employed transcranial magnetic stimulation (TMS) integrated with fMRI recordings during a social pain task to elucidate these aspects. Eighty participants underwent either active TMS targeting the rVLPFC (n = 41) or control stimulation at the vertex (n = 39). Our results revealed that TMS-induced rVLPFC facilitation significantly reduced self-reported social pain, confirming the causal role of the rVLPFC in social pain relief. Functional connectivity analyses demonstrated enhanced interactions between the rVLPFC and the dorsolateral prefrontal cortex, emphasizing the collaborative engagement of prefrontal regions in emotion regulation. Significantly, we observed that negative social feedback led to negative social attitudes, whereas rVLPFC activation countered this detrimental effect, showcasing the potential of the rVLPFC as a protective buffer against adverse social interactions. Moreover, our study uncovered the impact role of the hippocampus in subsequent social attitudes, a relationship particularly pronounced during excitatory TMS over the rVLPFC. These findings offer promising avenues for improving mental health within the intricate dynamics of social interactions. By advancing our comprehension of the neural mechanisms underlying social pain relief, this research introduces novel intervention strategies for individuals grappling with social distress. Empowering individuals to modulate rVLPFC activation may facilitate reshaping social attitudes and successful reintegration into communal life.

Centrifugo-Pneumatic Reciprocating Flowing Coupled with a Spatial Confinement Strategy for an Ultrafast Multiplexed Immunoassay.

Immunoassays serve as powerful diagnostic tools for early disease screening, process monitoring, and precision treatment. However, the current methods are limited by high costs, prolonged processing times (>2 h), and operational complexities that hinder their widespread application in point-of-care testing. Here, we propose a novel centrifugo-pneumatic reciprocating flowing coupled with spatial confinement strategy, termed PRCM, for ultrafast multiplexed immunoassay of pathogens on a centrifugal microfluidic platform. Each chip consists of four replicated units; each unit allows simultaneous detection of three targets, thereby facilitating high-throughput parallel analysis of multiple targets. The PRCM platform enables sequential execution of critical steps such as solution mixing, reaction, and drainage by coordinating inherent parameters, including motor rotation speed, rotation direction, and acceleration/deceleration. By integrating centrifugal-mediated pneumatic reciprocating flow with spatial confinement strategies, we significantly reduce the duration of immune binding from 30 to 5 min, enabling completion of the entire testing process within 20 min. As proof of concept, we conducted a simultaneous comparative test on- and off-the-microfluidics using 12 negative and positive clinical samples. The outcomes yielded 100% accuracy in detecting the presence or absence of the SARS-CoV-2 virus, thus highlighting the potential of our PRCM system for multiplexed point-of-care immunoassays.

Fully Integrated and High-Throughput Microfluidic System for Multiplexed Point-Of-Care Testing.

For every epidemic outbreak, the prevention and treatments in resource-limited areas are always out of reach. Critical to this is that high accuracy, stability, and more comprehensive analytical techniques always rely on expensive and bulky instruments and large laboratories. Here, a fully integrated and high-throughput microfluidic system is proposed for ultra-multiple point-of-care immunoassay, termed Dac system. Specifically, the Dac system only requires a handheld portable device to automatically recycle repetitive multi-step reactions including on-demand liquid releasing, dispensing, metering, collecting, oscillatory mixing, and discharging. The Dac system performs high-precision enzyme-linked immunosorbent assays for up to 17 samples or targets simultaneously on a single chip. Furthermore, reagent consumption is only 2% compared to conventional ELISA, and microbubble-accelerated reactions shorten the assay time by more than half. As a proof of concept, the multiplexed detections are achieved by detecting at least four infection targets for two samples simultaneously on a singular chip. Furthermore, the barcode-based multi-target results can rapidly distinguish between five similar cases, allowing for accurate therapeutic interventions. Compared to bulky clinical instruments, the accuracy of clinical inflammation classification is 92.38% (n = 105), with a quantitative correlation coefficient of R2 = 0.9838, while the clinical specificity is 100% and the sensitivity is 98.93%.

Clostridium butyricum inhibits the inflammation in children with primary nephrotic syndrome by regulating Th17/Tregs balance via gut-kidney axis.

BACKGROUND: Primary nephrotic syndrome (PNS) is a common glomerular disease in children. Clostridium butyricum (C. butyricum), a probiotic producing butyric acid, exerts effective in regulating inflammation. This study was designed to elucidate the effect of C. butyricum on PNS inflammation through the gut-kidney axis. METHOD: BALB/c mice were randomly divided into 4 groups: normal control group (CON), C. butyricum control group (CON+C. butyricum), PNS model group (PNS), and PNS with C. butyricum group (PNS+C. butyricum). The PNS model was established by a single injection of doxorubicin hydrochloride (DOX) through the tail vein. After 1 week of modeling, the mice were treated with C. butyricum for 6 weeks. At the end of the experiment, the mice were euthanized and associated indications were investigated. RESULTS: Since the successful modeling of the PNS, the 24 h urine protein, blood urea nitrogen (BUN), serum creatinine (SCr), urine urea nitrogen (UUN), urine creatinine (UCr), lipopolysaccharides (LPS), pro-inflammatory interleukin (IL)-6, IL-17A were increased, the kidney pathological damage was aggravated, while a reduction of body weights of the mice and the anti-inflammatory IL-10 significantly reduced. However, these abnormalities could be dramatically reversed by C. butyricum treatment. The crucial Th17/Tregs axis in PNS inflammation also was proved to be effectively regulated by C. butyricum treatment. This probiotic intervention notably affected the expression levels of signal transducer and activator of transcription 3 (STAT3), Heme oxygenase-1 (HO-1) protein, and retinoic acid-related orphan receptor gamma t (RORγt). 16S rRNA sequencing showed that C. butyricum could regulate the composition of the intestinal microbial community and found Proteobacteria was more abundant in urine microorganisms in mice with PNS. Short-chain fatty acids (SCFAs) were measured and showed that C. butyricum treatment increased the contents of acetic acid, propionic acid, butyric acid in feces, acetic acid, and valeric acid in urine. Correlation analysis showed that there was a closely complicated correlation among inflammatory indicators, metabolic indicators, microbiota, and associated metabolic SCFAs in the gut-kidney axis. CONCLUSION: C. butyricum regulates Th17/Tregs balance via the gut-kidney axis to suppress the immune inflammatory response in mice with PNS, which may potentially contribute to a safe and inexpensive therapeutic agent for PNS.

All-in-one detection of breast cancer-derived exosomal miRNA on a pen-based paper chip.

Exosomal microRNAs (miRNAs) play a pivotal role in intercellular communication, regulating gene expression in target cells, and hold significant promise as cancer biomarkers for early detection and screening. However, achieving precise and viable detection of exosomal miRNAs remains a challenge. This paper proposes an all-in-one detection strategy for breast cancer-derived exosomal miRNA-21 on a pen-based paper chip (PPC). The PPC is constructed using a modified automatic pen and lateral flow assay (LFA), which results in a cost-effective fabrication process. The user only needs to add the sample and trigger the top of the self-contained PPC after a period of time to complete the entire detection process. To enhance the sensitivity of exosomal miRNA testing, an enzyme-free catalyzed hairpin assembly (CHA) is further introduced, enabling highly sensitive detection of miRNA-21 with a limit of detection (LOD) of 25 fmol. Additionally, the detection of miRNAs in differentially-expressed cells and clinical samples has also been successfully achieved with high specificity. Overall, the proposed PPC provides an effective tool for detecting early cancer, monitoring diseases, and establishing point of care testing (POCT).

Why people engage in corrupt collaboration: an observation at the multi-brain level.

Recent studies suggest that corrupt collaboration (i.e. acquiring private benefits with joint immoral acts) represents a dilemma between the honesty and reciprocity norms. In this study, we asked pairs of participants (labeled as A and B) to individually toss a coin and report their outcomes; their collective benefit could be maximized by dishonestly reporting (a corrupt behavior). As expected, the likelihood of corrupt behavior was high; this probability was negatively correlated with player A's moral judgment ability but positively correlated with player B's empathic concern (EC). Functional near-infrared spectroscopy data revealed that the brain-to-brain synchronization in the right dorsolateral prefrontal cortex was associated with fewer corrupt behaviors, and that it mediated the relationship between player A's moral judgment ability and corrupt collaboration. Meanwhile, the right temporal-parietal junction synchronization was associated with more corrupt behaviors, and that it mediated the relationship between player B's EC and corrupt collaboration. The roles of these 2 regions are interpreted according to the influence of the honesty and reciprocity norms on corrupt collaboration. In our opinion, these findings provide insight into the underlying mechanisms and modulating factors of corrupt collaboration.

Volumetric compression develops noise-driven single-cell heterogeneity.

Recent studies have revealed that extensive heterogeneity of biological systems arises through various routes ranging from intracellular chromosome segregation to spatiotemporally varying biochemical stimulations. However, the contribution of physical microenvironments to single-cell heterogeneity remains largely unexplored. Here, we show that a homogeneous population of non-small-cell lung carcinoma develops into heterogeneous subpopulations upon application of a homogeneous physical compression, as shown by single-cell transcriptome profiling. The generated subpopulations stochastically gain the signature genes associated with epithelial-mesenchymal transition (EMT; VIM, CDH1, EPCAM, ZEB1, and ZEB2) and cancer stem cells (MKI67, BIRC5, and KLF4), respectively. Trajectory analysis revealed two bifurcated paths as cells evolving upon the physical compression, along each path the corresponding signature genes (epithelial or mesenchymal) gradually increase. Furthermore, we show that compression increases gene expression noise, which interplays with regulatory network architecture and thus generates differential cell-fate outcomes. The experimental observations of both single-cell sequencing and single-molecule fluorescent in situ hybridization agrees well with our computational modeling of regulatory network in the EMT process. These results demonstrate a paradigm of how mechanical stimulations impact cell-fate determination by altering transcription dynamics; moreover, we show a distinct path that the ecology and evolution of cancer interplay with their physical microenvironments from the view of mechanobiology and systems biology, with insight into the origin of single-cell heterogeneity.

Deregulated transcription factors and poor clinical outcomes in cancer patients.

Transcription factors are a group of proteins, which possess DNA-binding domains, bind to DNA strands of promoters or enhancers, and initiate transcription of genes with cooperation of RNA polymerase and other co-factors. They play crucial roles in regulating transcription during embryogenesis and development. Their physiological status in different cell types is also important to maintain cellular homeostasis. Therefore, any deregulation of transcription factors will lead to the development of cancer cells and tumor progression. Based on their functions in cancer cells, transcription factors could be either oncogenic or tumor suppressive. Furthermore, transcription factors have been shown to modulate cancer stem cells, epithelial-mesenchymal transition (EMT) and drug response; therefore, measuring deregulated transcription factors is hypothesized to predict treatment outcomes of patients with cancers and targeting deregulated transcription factors could be an encouraging strategy for cancer therapy. Here, we summarize the current knowledge of major deregulated transcription factors and their effects on causing poor clinical outcome of patients with cancer. The information presented here will help to predict the prognosis and drug response and to design novel drugs and therapeutic strategies for the treatment of cancers by targeting deregulated transcription factors.

Connecting the Human Microbiome and Pancreatic Cancer.

Pancreatic cancer is a deadly disease that is increasing in incidence throughout the world. There are no clear causal factors associated with the incidence of pancreatic cancer; however, some correlation to smoking, diabetes and alcohol has been described. Recently, a few studies have linked the human microbiome (oral and gastrointestinal tract) to pancreatic cancer development. A perturbed microbiome has been shown to alter normal cells while promoting cancer-related processes such as increased cell signaling, immune system evasion and invasion. In this article, we will review in detail the alterations within the gut and oral microbiome that have been linked to pancreatic cancer and explore the ability of other microbiomes, such as the lung and skin microbiome, to contribute to disease development. Understanding ways to identify a perturbed microbiome can result in advancements in pancreatic cancer research and allow for prevention, earlier detection and alternative treatment strategies for patients.

FGF19/FGFR4-mediated elevation of ETV4 facilitates hepatocellular carcinoma metastasis by upregulating PD-L1 and CCL2.

BACKGROUND & AIMS: Metastasis remains the major reason for the high mortality of patients with hepatocellular carcinoma (HCC). This study was designed to investigate the role of E-twenty-six-specific sequence variant 4 (ETV4) in promoting HCC metastasis and to explore a new combination therapy strategy for ETV4-mediated HCC metastasis. METHODS: PLC/PRF/5, MHCC97H, Hepa1-6, and H22 cells were used to establish orthotopic HCC models. Clodronate liposomes were used to clear macrophages in C57BL/6 mice. Gr-1 monoclonal antibody was used to clear myeloid-derived suppressor cells (MDSCs) in C57BL/6 mice. Flow cytometry and immunofluorescence were used to detect the changes of key immune cells in the tumour microenvironment. RESULTS: ETV4 expression was positively related to higher tumour-node-metastasis (TNM) stage, poor tumour differentiation, microvascular invasion, and poor prognosis in human HCC. Overexpression of ETV4 in HCC cells transactivated PD-L1 and CCL2 expression, which increased tumour-associated macrophage (TAM) and MDSC infiltration and inhibited CD8+ T-cell accumulation. Knockdown of CCL2 by lentivirus or CCR2 inhibitor CCX872 treatment impaired ETV4-induced TAM and MDSC infiltration and HCC metastasis. Furthermore, FGF19/FGFR4 and HGF/c-MET jointly upregulated ETV4 expression through the ERK1/2 pathway. Additionally, ETV4 upregulated FGFR4 expression, and downregulation of FGFR4 decreased ETV4-enhanced HCC metastasis, which created a FGF19-ETV4-FGFR4 positive feedback loop. Finally, anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib prominently inhibited FGF19-ETV4 signalling-induced HCC metastasis. CONCLUSIONS: ETV4 is a prognostic biomarker, and anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib may be effective strategies to inhibit HCC metastasis. IMPACT AND IMPLICATIONS: Here, we reported that ETV4 increased PD-L1 and chemokine CCL2 expression in HCC cells, which resulted in TAM and MDSC accumulation and CD8+ T-cell inhibition to facilitate HCC metastasis. More importantly, we found that anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib markedly inhibited FGF19-ETV4 signalling-mediated HCC metastasis. This preclinical study will provide a theoretical basis for the development of new combination immunotherapy strategies for patients with HCC.

On-Line Dual-Active Valves Based Centrifugal Microfluidic Chip for Fully Automated Point-of-Care Immunoassay.

There remains an unmet need for a fully integrated microfluidic platform that can automatically perform multistep and multireagent immunoassays. Here, we proposed a novel online dual-active valve-based centrifugal microfluidic chip, termed DAVM, for fully automatic point-of-care immunoassay. Practically, the puncture valve, one of the dual active valves, is capable of achieving precise, on-demand, sequential release of prestored reagents, while the other valve-reversible active valve enables controlled retention and drainage of the reaction solutions. Thereby, our technology mitigates the challenges of hydrophilic/hydrophobic modifications and unstable valve control performance commonly observed in passive valve controls. As a proof of concept, the indirect enzymatic immunoblotting technique was employed on DAVM for fully automated immunological analysis of eight targets, yielding outcomes within an hour. Furthermore, we conducted a comparative analysis of 28 clinical samples with autoimmune diseases. According to 224 clinical data, the sample testing concordance rate between DAVM and the traditional instrument was 82%, with a target compliance rate of 97%. Therefore, our DAVM system has powerful potential for fully automated immunoassays.

Handyfuge Microfluidic for On-Site Antibiotic Susceptibility Testing.

Low-cost, rapid, and accurate acquisition of minimum inhibitory concentrations (MICs) is key to limiting the development of antimicrobial resistance (AMR). Until now, conventional antibiotic susceptibility testing (AST) methods are typically time-consuming, high-cost, and labor-intensive, making them difficult to accomplish this task. Herein, an electricity-free, portable, and robust handyfuge microfluidic chip was developed for on-site AST, termed handyfuge-AST. With simply handheld centrifugation, the bacterial-antibiotic mixtures with accurate antibiotic concentration gradients could be generated in less than 5 min. The accurate MIC values of single antibiotics (including ampicillin, kanamycin, and chloramphenicol) or their combinations against Escherichia coli could be obtained within 5 h. To further meet the growing demands of point-of-care testing, we upgraded our handyfuge-AST with a pH-based colorimetric strategy, enabling naked eye recognition or intelligent recognition with a homemade mobile app. Through a comparative study of 60 clinical data (10 clinical samples corresponding to six commonly used antibiotics), the accurate MICs by handyfuge-AST with 100% categorical agreements were achieved compared to clinical standard methods (area under curves, AUCs = 1.00). The handyfuge-AST could be used as a low-cost, portable, and robust point-of-care device to rapidly obtain accurate MIC values, which significantly limit the progress of AMR.

The role of ventrolateral prefrontal cortex on voluntary emotion regulation of social pain.

The right ventrolateral prefrontal cortex (rVLPFC) is highly engaged in emotion regulation of social pain. However, there is still lack of both inhibition and excitement evidence to prove the causal relationship between this brain region and voluntary emotion regulation. This study used high-frequency (10 Hz) and low-frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) to separately activate or inhibit the rVLPFC in two groups of participants. We recorded participants' emotion ratings as well as their social attitude and prosocial behaviors following emotion regulation. Also, we used eye tracker to record the changes of pupil diameter to measure emotional feelings objectively. A total of 108 healthy participants were randomly assigned to the activated, inhibitory or sham rTMS groups. They were required to accomplish three sequential tasks: the emotion regulation (cognitive reappraisal) task, the favorability rating task, and the donation task. Results show that the rVLPFC-inhibitory group reported more negative emotions and showed larger pupil diameter while the rVLPFC-activated group showed less negative emotions and reduced pupil diameter during emotion regulation (both compared with the sham rTMS group). In addition, the activated group gave more positive social evaluation to peers and donated more money to a public welfare activity than the rVLPFC-inhibitory group, among which the change of social attitude was mediated by regulated emotion. Taken together, these findings reveal that the rVLPFC plays a causal role in voluntary emotion regulation of social pain and can be a potential brain target in treating deficits of emotion regulation in psychiatric disorders.

Programmable Gravity Self-Driven Microfluidic Chip for Point-of-Care Multiplied Immunoassays.

Point-of-care testing (POCT) is experiencing a groundbreaking transformation with microfluidic chips, which offer precise fluid control and manipulation at the microscale. Nevertheless, chip design or operation for existing platforms is rather cumbersome, with some even heavily depending on external drivers or devices, impeding their broader utilization. This study develops a unique programmable gravity self-driven microfluidic chip (PGSMC) capable of simultaneous multi-reagent sequential release, multi-target analysis, and multi-chip operation. All necessary reagents are introduced in a single step, and the process is initiated simply by flipping the PGSMC vertically, eliminating the need for additional steps or devices. Additionally, it demonstrates successful immunoassays in less than 60 min for antinuclear antibodies testing, compared to more than 120 min by traditional methods. Assessment using 25 clinically diagnosed cases showcases remarkable sensitivity (96%), specificity (100%), and accuracy (99%). These outcomes underscored its potential as a promising platform for POCT with high accuracy, speed, and reliability, highlighting its capability for automated fluid control.

Semiparametric distributed lag quantile regression for modeling time-dependent exposure mixtures.

Studying time-dependent exposure mixtures has gained increasing attentions in environmental health research. When a scalar outcome is of interest, distributed lag (DL) models have been employed to characterize the exposures effects distributed over time on the mean of final outcome. However, there is a methodological gap on investigating time-dependent exposure mixtures with different quantiles of outcome. In this paper, we introduce semiparametric partial-linear single-index (PLSI) DL quantile regression, which can describe the DL effects of time-dependent exposure mixtures on different quantiles of outcome and identify susceptible periods of exposures. We consider two time-dependent exposure settings: discrete and functional, when exposures are measured in a small number of time points and at dense time grids, respectively. Spline techniques are used to approximate the nonparametric DL function and single-index link function, and a profile estimation algorithm is proposed. Through extensive simulations, we demonstrate the performance and value of our proposed models and inference procedures. We further apply the proposed methods to study the effects of maternal exposures to ambient air pollutants of fine particulate and nitrogen dioxide on birth weight in New York University Children's Health and Environment Study (NYU CHES).

Wavelength-tunable broadband lasers based on nanomaterials.

Nanomaterials are widely used in the fields of sensors, optoelectronics, biophotonics and ultrafast photonics due to their excellent mechanical, thermal, optical, electrical and magnetic properties. Particularly, owing to their nonlinear optical properties, fast response time and broadband operation, nanomaterials are ideal saturable absorption materials in ultrafast photonics, which contribute to the improvement of laser performance. Therefore, nanomaterials are of great importance to applications in wavelength-tunable broadband pulsed lasers. Herein, we review the integration and applications of nanomaterials in wavelength-tunable broadband ultrafast photonics. Firstly, the two integration methods, which are direct coupling and evanescent field coupling, and their characteristics are introduced. Secondly, the applications of nanomaterials in wavelength-tunable broadband lasers are summarized. Finally, the development of nanomaterials and broadband tunable lasers is reviewed and discussed.

Prognostic significance of cyclin D1 expression pattern in HPV-negative oral and oropharyngeal carcinoma: A deep-learning approach.

BACKGROUND: We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma. METHODS: The clinicopathological data of 610 patients with human papillomavirus-negative oral/oropharyngeal squamous cell carcinoma were analyzed retrospectively. Cox univariate and multivariate risk regression analyses were performed to compare cyclin D1 expression pattern scoring with the traditional scoring method-cyclin D1 expression level scoring-in relation to patients' overall and progression-free survival. An image recognition model employing the cyclin D1 expression pattern scoring system was established by YOLOv5 algorithms. From this model, two independent survival prediction models were established using the DeepHit and DeepSurv algorithms. RESULTS: Cyclin D1 had three expression patterns in oral and oropharyngeal squamous cell carcinoma cancer nests. Superior to cyclin D1 expression level scoring, cyclin D1 expression pattern scoring was significantly correlated with the prognosis of patients with oral squamous cell carcinoma (p < 0.0001) and oropharyngeal squamous cell carcinoma (p < 0.05). Moreover, it was an independent prognostic risk factor in both oral squamous cell carcinoma (p < 0.0001) and oropharyngeal squamous cell carcinoma (p < 0.05). The cyclin D1 expression pattern-derived image recognition model showed an average test set accuracy of 78.48% ± 4.31%. In the overall survival prediction models, the average concordance indices of the test sets established by DeepSurv and DeepHit were 0.71 ± 0.02 and 0.70 ± 0.01, respectively. CONCLUSION: Combined with the image recognition model of the cyclin D1 expression pattern, the survival prediction model had a relatively good prediction effect on the overall survival prognosis of patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.

Distributed Compressive Sensing for Wireless Signal Transmission in Structural Health Monitoring: An Adaptive Hierarchical Bayesian Model-Based Approach.

Signal transmission plays an important role in the daily operation of structural health monitoring (SHM) systems. In wireless sensor networks, transmission loss often occurs and threatens reliable data delivery. The massive amount of data monitoring also leads to a high signal transmission and storage cost throughout the system's service life. Compressive Sensing (CS) provides a novel perspective on alleviating these problems. Based on the sparsity of vibration signals in the frequency domain, CS can reconstruct a nearly complete signal from just a few measurements. This can improve the robustness of data loss while facilitating data compression to reduce transmission demands. Extended from CS methods, distributed compressive sensing (DCS) can exploit the correlation across multiple measurement vectors (MMV) to jointly recover the multi-channel signals with similar sparse patterns, which can effectively enhance the reconstruction quality. In this paper, a comprehensive DCS framework for wireless signal transmission in SHM is constructed, incorporating the process of data compression and transmission loss together. Unlike the basic DCS formulation, the proposed framework not only activates the inter-correlation among channels but also provides flexibility and independence to single-channel transmission. To promote signal sparsity, a hierarchical Bayesian model using Laplace priors is built and further improved as the fast iterative DCS-Laplace algorithm for large-scale reconstruction tasks. Vibration signals (e.g., dynamic displacement and accelerations) acquired from real-life SHM systems are used to simulate the whole process of wireless transmission and test the algorithm's performance. The results demonstrate that (1) DCS-Laplace is an adaptative algorithm that can actively adapt to signals with various sparsity by adjusting the penalty term to achieve optimal performance; (2) compared with CS methods, DCS methods can effectively improve the reconstruction quality of multi-channel signals; (3) the Laplace method has advantages over the OMP method in terms of reconstruction performance and applicability, which is a better choice in SHM wireless signal transmission.