Effect of the correlated color temperature of a phosphor-converted LED on indoor visible light communication.

Correlated color temperature (CCT) is an important parameter of the phosphor-converted LED (PC-LED); international standards specify its range in different scenarios. However, little has been done to investigate the effect of CCT on the performance of visible light communication (VLC). In this paper, we propose an analytical model for the transmission performance of an LED VLC system based on the dual components of blue and yellow light from the luminescence mechanism of the PC-LED. On this basis, the effects of CCT on the PC-LED's input current and output optical power between the dual components are analyzed. The simulation results show that the increase of CCT expands the modulation bandwidth of the PC-LED, and the trend of the BER with CCT is also related to the transmission data rate. In addition, the maximum data rate of the PC-LED with CCT from 2700 K to 6500 K under a certain transmission distance is also simulated in this paper.

High sensitivity distributed dynamic pressure sensor based on dual-linear frequency modulated optical frequency domain reflectometry.

In this Letter, we propose and experimentally demonstrate a highly sensitive distributed dynamic pressure sensor based on a dual-linear frequency modulated optical frequency domain reflectometry (OFDR) and a coating thickness-enhanced single-mode fiber (SMF). A dual-sideband linear frequency modulation (LFM) signal is used to interrogate the sensing fiber, which allows us to obtain a dual-sideband Rayleigh backscattering signal. Due to the opposite slopes of the two LFM sidebands, the Rayleigh backscattering spectra of the two sidebands drift in opposite directions when the fiber is disturbed. By subtracting the frequency shifts of the two spectra, we can double the system's sensitivity. We further enhance the sensitivity by using an SMF with a coating thickness of 200 µm. This results in a pressure sensitivity of 3979 MHz/MPa, a measurement accuracy of 0.76 kPa, and a spatial resolution of 35 cm over a 500 m optical fiber. Our system successfully detected a dynamic pressure change at a sampling rate of 1.25 kHz, demonstrating the sensor's excellent dynamic measuring capabilities.

Silver incorporated SeTe nanoparticles with enhanced photothermal and photodynamic properties for synergistic effects on anti-bacterial activity and wound healing.

Bacteria invade the host's immune system, thereby inducing serious infections. Current treatments for bacterial infections mostly rely on single modalities, which cannot completely inhibit bacteria. This study evaluates the therapeutic potential of SeTe-Ag NPs, designed with excellent photo responsiveness, with a particular focus on their dual-action antibacterial effect and wound healing properties. SeTe-Ag NPs exhibited promising synergistic antibacterial effects due to their superior photothermal and photodynamic properties. The investigation records substantial zones of inhibition of bacteria, demonstrating potent antibacterial effect. Furthermore, upon the irradiation of near-infrared (NIR) light, SeTe-Ag NPs exhibit remarkable antibiofilm and wound-healing capabilities. Overall, this study shows the applications of NIR-active SeTe-Ag NPs, which serve as a versatile platform for biomedical applications.

Hexadecanoic acid produced in the co-culture of S. cerevisiae and E.coli promotes oxidative stress tolerance of the S.cerevisiae cells.

Co-fermentation performed by Saccharomyces cerevisiae and Escherichia coli or other microbes has been widely used in industrial fermentation. Meanwhile, the co-cultured microbes might regulate each other's metabolisms or cell behaviors including oxidative stress tolerance through secreting molecules. Here, results based on the co-culture system of S. cerevisiae and E. coli suggested the promoting effect of E. coli on the oxidative stress tolerance of S. cerevisiae cells. The co-cultured E. coli could enhance S. cerevisiae cell viability through improving its membrane stability and reducing the oxidized lipid level. Meanwhile, promoting effect of the co-cultured supernatant on the oxidative stress tolerance of S. cerevisiae illustrated by the supernatant substitution strategy suggested that secreted compounds contained in the co-cultured supernatant contributed to the higher oxidative stress tolerance of S. cerevisiae. The potential key regulatory metabolite (i.e., hexadecanoic acid) with high content difference between co-cultured supernatant and the pure-cultured S. cerevisiae supernatant was discovered by GC-MS-based metabolomics strategy. And exogenous addition of hexadecanoic acid did suggest its contribution to higher oxidative stress tolerance of S. cerevisiae. Results presented here would contribute to the understanding of the microbial interactions and provide the foundation for improving the efficiency of co-fermentation performed by S. cerevisiae and E. coli.

The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients.

Background: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated. Methods: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use. Results: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation. Conclusion: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.

DEMA: A Deep Learning-Enabled Model for Non-Invasive Human Vital Signs Monitoring Based on Optical Fiber Sensing.

Optical fiber sensors are extensively employed for their unique merits, such as small size, being lightweight, and having strong robustness to electronic interference. The above-mentioned sensors apply to more applications, especially the detection and monitoring of vital signs in medical or clinical. However, it is inconvenient for daily long-term human vital sign monitoring with conventional monitoring methods under the uncomfortable feelings generated since the skin and devices come into direct contact. This study introduces a non-invasive surveillance system that employs an optical fiber sensor and advanced deep-learning methodologies for precise vital sign readings. This system integrates a monitor based on the MZI (Mach-Zehnder interferometer) with LSTM networks, surpassing conventional approaches and providing potential uses in medical diagnostics. This could be potentially utilized in non-invasive health surveillance, evaluation, and intelligent health care.

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data.

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

Sensing antibody functions with a novel CCR8-responsive engineered cell.

Human chemokine receptor 8 (CCR8) is a promising drug target for immunotherapy of cancer and autoimmune diseases. Monoclonal antibody-based CCR8 targeted treatment shows significant inhibition in tumor growth. The inhibition of CCR8 results in the improvement of antitumor immunity and patient survival rates by regulating tumor-resident regulatory T cells. Recently monoclonal antibody drug development targeting CCR8 has become a research hotspot, which also promotes the advancement of antibody evaluation methods. Therefore, we constructed a novel engineered customized cell line HEK293-cAMP-biosensor-CCR8 combined with CCR8 and a cAMP-biosensor reporter. It can be used for the detection of anti-CCR8 antibody functions like specificity and biological activity, in addition to the detection of antibody-dependent cell-mediated cytotoxicity and antibody-dependent-cellular-phagocytosis. We obtained a new CCR8 mAb 22H9 and successfully verified its biological activities with HEK293-cAMP-biosensor-CCR8. Our reporter cell line has high sensitivity and specificity, and also offers a rapid kinetic detection platform for evaluating anti-CCR8 antibody functions.

A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma treatment.

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

Medicarpin suppresses lung cancer cell growth in vitro and in vivo by inducing cell apoptosis.

Lung cancer (LC) is the leading cause of cancer deaths worldwide. Surgery, chemoradiotherapy, targeted therapy, and immunotherapy are considered dominant treatment strategies for LC in the clinic. However, drug resistance and meta-stasis are two major challenges in cancer therapies. Medicarpin (MED) is an isoflavone compound isolated from alfalfa, which is usually used in traditional medicine. This study was de sig ned to evaluate the anti-LC effect and reveal the underlying mechanisms of MED in vivo and in vitro. We found that MED could significantly inhibit proliferation, induce apoptosis, and cell cycle arrest of A549 and H157 cell lines. Basically, MED induced cell apoptosis of LC cells by upregu lating the expression of pro-apoptotic proteins BAX and Bak1, leading to the cleavage of caspase-3 (Casp3). Moreover, MED inhibited the proliferation of LC cells via downregulating the expression of proliferative protein Bid. Overall, MED inhibited LC cell growth in vitro and in vivo via suppressing cell proliferation and inducing cell apoptosis, suggesting the therapeutic potential of MED in treating LC.

Regulation of the PFK1 gene on the interspecies microbial competition behavior of Saccharomyces cerevisiae.

Saccharomyces cerevisiae is a widely used strain for ethanol fermentation; meanwhile, efficient utilization of glucose could effectively promote ethanol production. The PFK1 gene is a key gene for intracellular glucose metabolism in S. cerevisiae. Our previous work suggested that although deletion of the PFK1 gene could confer higher oxidative tolerance to S. cerevisiae cells, the PFK1Δ strain was prone to contamination by other microorganisms. High interspecies microbial competition ability is vital for the growth and survival of microorganisms in co-cultures. The result of our previous studies hinted us a reasonable logic that the EMP (i.e., the Embden-Meyerhof-Parnas pathway, the glycolytic pathway) key gene PFK1 could be involved in regulating interspecies competitiveness of S. cerevisiae through the regulation of glucose utilization and ethanol production efficiency. The results suggest that under 2% and 5% glucose, the PFK1Δ strain showed slower growth than the S288c wild-type and TDH1Δ strains in the lag and exponential growth stages, but realized higher growth in the stationary stage. However, relative high supplement of glucose (10%) eliminated this phenomenon, suggesting the importance of glucose in the regulation of PFK1 in yeast cell growth. Furthermore, during the lag growth phase, the PFK1Δ strain displayed a decelerated glucose consumption rate (P < 0.05). The expression levels of the HXT2, HXT5, and HXT6 genes decreased by approximately 0.5-fold (P < 0.05) and the expression level of the ZWF1 exhibited a onefold increase in the PFK1Δ strain compared to that in the S. cerevisiae S288c wild-type strain (P < 0.05).These findings suggested that the PFK1 inhibited the uptake and utilization of intracellular glucose by yeast cells, resulting in a higher amount of residual glucose in the medium for the PFK1Δ strain to utilize for growth during the reverse overshoot stage in the stationary phase. The results presented here also indicated the potential of ethanol as a defensive weapon against S. cerevisiae. The lower ethanol yield in the early stage of the PFK1Δ strain (P < 0.001) and the decreased expression levels of the PDC5 and PDC6 (P < 0.05), which led to slower growth, resulted in the strain being less competitive than the wild-type strain when co-cultured with Escherichia coli. The lower interspecies competitiveness of the PFK1Δ strain further promoted the growth of co-cultured E. coli, which in turn activated the ethanol production efficiency of the PFK1Δ strain to antagonize it from E. coli at the stationary stage. The results presented clarified the regulation of the PFK1 gene on the growth and interspecies microbial competition behavior of S. cerevisiae and would help us to understand the microbial interactions between S. cerevisiae and other microorganisms. KEY POINTS: • PFK1Δ strain could realize reverse growth overshoot at the stationary stage • PFK1 deletion decreased ethanol yield and interspecific competitiveness • Proportion of E. coli in co-culture affected ethanol yield capacity of yeast cells.

Simplified model for non-line-of-sight optical camera communication with a simple patterned reflective surface.

Most previous studies on non-line-of-sight optical camera communication (NLOS-OCC) were conducted as practical experiments; few relevant mathematical models have been proposed for simulation. This paper presents a simplified model for NLOS-OCC with a simple patterned reflective surface and proposes to directly decode the raw pixel values to improve the system performance. The model combines the mathematical models of a diffuse reflection channel and rolling shutter to obtain a normalized raw pixel value matrix of the pixel plane corresponding to the camera output image and realize visualization. Based on this model, we analyze the threshold selection and anti-interference ability of the conventional decoding scheme, and propose the sorting pre-decoding scheme: first sorting the pixel values by rows before decoding can effectively reduce the impact of the reflective surface pattern and enhance the system's anti-interference ability.

A community study of neutralizing antibodies against SARS-CoV-2 in China.

Background: The immune background of the overall population before and after the outbreak of SARS-CoV-2 in China remains unexplored. And the level of neutralizing antibodies is a reliable indicator of individual immunity. Objectives: This study aimed to assess the immune levels of different population groups during a viral outbreak and identify the factors influencing these levels. Methods: We measured the levels of neutralizing antibodies in 12,137 participants using the COVID19 Neutralizing Antibody Detection kit. The dynamics of neutralizing antibodies were analyzed using a generalized additive model, while a generalized linear model and multi-factor analysis of variance were employed to investigate the influencing factors. Additionally, statistical methods were used to compare neutralizing antibody levels among subgroups of the real-world population. Results: Participants who received booster doses exhibited significantly higher levels of neutralizing antibodies compared to those who received only one or two doses (p<0.001). Both elderly [22.55 (5.12, 62.03) IU/mL, 55%] and minors [21.41 (8.15, 45.06) IU/mL, 56%] showed lower positivity rates and neutralizing antibody levels compared to young adults [29.30 (9.82, 188.08) IU/mL, 62%] (p<0.001). Furthermore, the HIV-positive group demonstrated a slightly lower seropositivity rate compared to the healthy group across the three vaccination time points. Notably, three months after the large-scale infection, both the neutralizing antibody level and positivity rate in real-world populations were higher than the previous record [300 (300, 300) IU/mL, 89%; 27.10 (8.77, 139.28) IU/mL, 60%], and this difference was statistically significant. Conclusions: Increasing vaccine dosage enhances neutralizing antibody levels, resulting in greater and longer-lasting immunity. Monitoring immune levels in older individuals and those with AIDS is crucial. Additionally, the neutralizing antibodies generated from vaccination have not yet reached the threshold for achieving herd immunity, while individuals exhibit higher immune levels following a large-scale infection. These findings provide valuable insights for guiding new strategies in vaccine administration.

Classification models for predicting the bioactivity of pan-TRK inhibitors and SAR analysis.

Tropomyosin receptor kinases (TRKs) are important broad-spectrum anticancer targets. The oncogenic rearrangement of the NTRK gene disrupts the extracellular structural domain and epitopes for therapeutic antibodies, making small-molecule inhibitors essential for treating NTRK fusion-driven tumors. In this work, several algorithms were used to construct descriptor-based and nondescriptor-based models, and the models were evaluated by outer 10-fold cross-validation. To find a model with good generalization ability, the dataset was partitioned by random and cluster-splitting methods to construct in- and cross-domain models, respectively. Among the 48 models built, the model with the combination of the deep neural network (DNN) algorithm and extended connectivity fingerprints 4 (ECFP4) descriptors achieved excellent performance in both dataset divisions. The results indicate that the DNN algorithm has a strong generalization prediction ability, and the richness of features plays a vital role in predicting unknown spatial molecules. Additionally, we combined the clustering results and decision tree models of fingerprint descriptors to perform structure-activity relationship analysis. It was found that nitrogen-containing aromatic heterocyclic and benzo heterocyclic structures play a crucial role in enhancing the activity of TRK inhibitors. Workflow for generating predictive models for TRK inhibitors.

Adaptive decision threshold for an optical multipath-interference-impaired short-reach 50-Gbps PAM4 transmission.

The short-reach optical transmission systems based on intensity modulation and direct detection (IM/DD) are gradually evolving into the networks with complex link topologies and connections, especially inside the data center. Multipath interference (MPI) introduces irregular fluctuations in the 4-level pulse amplitude modulation (PAM4) signals and therefore affects the transmission performance. This Letter proposes an adaptive decision threshold (ADT) scheme to dynamically update the decision threshold, which can track the signal fluctuations in real time and mitigate the impact of MPI noise on the transmitted PAM4 signals. Numerical simulation results present that the proposed ADT scheme can significantly improve the bit error rate (BER) performance of the MPI-impaired PAM4 transmission system considering different MPI levels and laser linewidths. In a 50-Gbps PAM4 transmission system, the ADT can improve the MPI tolerance by more than beyond 6 dB when the BER reaches the KP4-forward error correction (FEC) criterion (2.4 × 10-4), presenting a better denoising performance than the existing MPI-mitigation algorithms A1 and A2. Moreover, the ADT scheme offers a lower computation complexity compared with A1 and A2, making it more practical for implementation.

Compressed sensing framework for BCG signals based on the optical fiber sensor.

A compressed sensing (CS) framework is built for ballistocardiography (BCG) signals, which contains two parts of an optical fiber sensor-based heart monitoring system with a CS module and an end-to-end deep learning-based reconstruction algorithm. The heart monitoring system collects BCG data, and then compresses and transmits the data through the CS module at the sensing end. The deep learning-based algorithm reconstructs compressed data at the received end. To evaluate results, three traditional CS reconstruction algorithms and a deep learning method are adopted as references to reconstruct the compressed BCG data with different compression ratios (CRs). Results show that our framework can reconstruct signals successfully when the CR grows from 50% to 95% and outperforms other methods at high CRs. The mean absolute error (MAE) of the estimated heartbeat rate (HR) is lower than 1 bpm when the CR is below 95%. The proposed CS framework for BCG signals can be integrated into the IoMT system, which has great potential in health care for both medical and home use.

Rapid and sensitive detection of aqueous ammonia harnessing nanocomposite functionalized tilted fiber Bragg grating.

A high sensitive aqueous ammonia sensor based on tilted fiber Bragg grating (TFBG) had been reported. The sensors were fabricated by a 10 ° TFBG coated by a membrane receptor named as Polyaniline/Graphene oxide on the surface of the fiber. The correlative concentrations of aqueous ammonia were demodulated by global monitoring of the envelope area of cladding modes in the transmitted spectrum of the TFBG. Tests have shown that the proposed sensor can provide a linear and rapid response of aqueous ammonia within 22 seconds, in a concentration range from 1-12 ppm. Moreover, the limit of detection can even reach 0.08 ppm, through the theoretical analysis of our experimental results. The proposed sensor has good performance, is easy to manufacture and of small size, making it a good choice for real-time, in-situ, label-free detection of aqueous ammonia in the future.

Signal processing integrated with fiber-optic Vernier effect for the simultaneous measurement of relative humidity and temperature.

A novel inline Fabry-Perot interferometer (FPI) for simultaneous relative humidity (RH) and temperature monitoring is proposed. The sensing probe consists of a section of hollow core Bragg fiber (HCBF) spliced with a single-mode fiber pigtail. The end-face of the HCBF is coated with Chitosan and ultraviolet optical adhesive (UVOA), forming two polymer layers using a well-designed fabrication process. The surfaces of the layers and splicing point will generate multiple-beam interference and form Vernier-effect (VE) related envelopes in the reflection spectrum. A signal processing (SP) method is proposed to demodulate the VE envelopes from a complicated superimposed raw spectrum. The principle of the SP algorithm is analyzed theoretically and verified experimentally. The sensor's RH and temperature response are studied, exhibiting a high sensitivity of about 0.437 nm/%RH and 0.29 nm/ ∘C, respectively. Using a matrix obtained from experiment results, the simultaneous RH and temperature measurement is achieved. Meanwhile, the simple fabrication process, compact size and potential for higher sensitivity makes our proposed structure integrated with the SP algorithm a promising sensor for practical RH and temperature monitoring.

Indoor receiving signal strength based visible light positioning enabled with equivalent virtual lamps.

Visible light positioning (VLP) has become one of the most potent alternative methods in indoor positioning scenarios. However, the system performance of VLP is largely related to the characteristics of the wireless optical channel. Limited access resulting from shadowing, obstacles, and multipath propagation between transmitters and photodetectors might lead to positioning failure. In this paper, we propose a mirror-assisted VLP method based on the received signal strength algorithm. By introducing specular reflection into the system model, multipath propagation can be effectively alleviated, making it possible to implement VLP with limited accessibility of LEDs. Simulation results show that the proposed approach, based on the assumption of equivalent virtual lamps, can mitigate the non-line-of-sight interference in a classical four-lamp room. Average positioning performance improves by 25% with the assistance of a mirror. In addition, trilateration positioning can be realized when only two light-emitting diodes are available in the target room. The positioning accuracy of the two-LED VLP can reach ∼30c m under scenarios considering non-line-of-sight reflections.

Label-Free DNA Detection Using Etched Tilted Bragg Fiber Grating-Based Biosensor.

A label-free-based fiber optic biosensor based on etched tilted Bragg fiber grating (TFBG) is proposed and practically demonstrated. Conventional phase mask technic has been utilized to inscribe tilted fiber Bragg grating with a tilt angle of 10°, while the etching has been accomplished with hydrofluoric acid. A composite of polyethylenimine (PEI)/poly(acrylic acid) (PAA) has been thermally deposited on the etched TFBG, followed by immobilization of probe DNA (pDNA) on this deposited layer. The hybridization of pDNA with the complementary DNA (cDNA) has been monitored using wavelength-dependent interrogation. The reproducibility of the probes has been demonstrated by fabricating three identical probes and their response has been investigated for cDNA concentration ranging from 0 µM to 3 µM. The maximum sensitivity has been found to be 320 pm/µM, with the detection limit being 0.65 µM. Furthermore, the response of the probes towards non-cDNA has also been investigated in order to establish its specificity.