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.

A high-throughput single cell-based antibody discovery approach against the full-length SARS-CoV-2 spike protein suggests a lack of neutralizing antibodies targeting the highly conserved S2 domain.

Coronavirus disease 2019 pandemic continues globally with a growing number of infections, but there are currently no effective antibody drugs against the virus. In addition, 90% amino acid sequence identity between the S2 subunit of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV S proteins attracts us to examine S2-targeted cross-neutralizing antibodies that are not yet well defined. We therefore immunized RenMab mice with the full-length S protein and constructed a high-throughput antibody discovery method based on single-cell sequencing technology to isolate SARS-CoV-2 S-targeted neutralizing antibodies and cross-neutralizing antibodies against the S2 region of SARS-CoV-2/SARS-CoV S. Diversity of antibody sequences in RenMab mice and consistency in B-cell immune responses between RenMab mice and humans enabled screening of fully human virus-neutralizing antibodies. From all the frequency >1 paired clonotypes obtained from single-cell V(D)J sequencing, 215 antibodies with binding affinities were identified and primarily bound S2. However, only two receptor-binding domain-targeted clonotypes had neutralizing activity against SARS-CoV-2. Moreover, 5' single-cell RNA sequencing indicated that these sorted splenic B cells are mainly plasmablasts, germinal center (GC)-dependent memory B-cells and GC B-cells. Among them, plasmablasts and GC-dependent memory B-cells were considered the most significant possibility of producing virus-specific antibodies. Altogether, using a high-throughput single cell-based antibody discovery approach, our study highlighted the challenges of developing S2-binding neutralizing antibodies against SARS-CoV-2 and provided a novel direction for the enrichment of antigen-specific B-cells.

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.

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.

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.

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.

Simultaneous measurement of axial strain and temperature based on a twin-core single-hole fiber with the optical Vernier effect.

An ultrasensitive optical fiber sensor based on the optical Vernier effect is proposed for the simultaneous measurement of axial strain and temperature. The sensor structure comprises two cascaded Mach-Zehnder interferometers (MZIs) with different free space ranges. The single MZI is built up by fusion splicing a segment of ∼3 mm twin-core single-hole fiber (TCSHF) between two pieces of ∼5 mm none core fibers (NCF). When acting separately, each MZI can respond linearly to the axial strain change with a sensitivity of ∼ 0.6 pm/µÎµ and temperature with a sensitivity of ∼34 pm/°C. When the two MZIs are cascaded in series, the sensitivities are amplified about 30 times because of the optical Vernier effect. Experimental results demonstrate that the cascaded structure exhibits a high axial strain sensitivity of ∼ 17 pm/µÎµ in the range of 0 to 2000 µÎµ and temperature sensitivity of ∼1.16 nm/°C in the range of 30 to 70 °C. Moreover, the cascaded structure can simultaneously measure the axial strain and temperature change in the acceptable error ranges.

Full-Stokes parameters detection enabled by a non-interleaved fiber-compatible metasurface.

Polarization of the optical field determines the way of light-matter interaction, which lays the foundation for various applications such as chiral spectroscopy, biomedical imaging, and machine vision. Currently, with the rise of the metasurface, miniaturized polarization detectors have attracted extensive interest. However, due to the limitation of the working area, it is still a challenge to integrate polarization detectors on the fiber end face. Here, we propose a design of compact non-interleaved metasurface that can be integrated on the tip of a large-mode-area photonic crystal fiber (LMA-PCF) to realize full-Stokes parameters detection. Through concurrent control over the dynamic phase and Pancharatnam-Berry (PB) phase, different helical phases are assigned to the two orthogonal circular polarization bases, of which the amplitude contrast and relative phase difference can be represented by two non-overlapped foci and an interference ring pattern, respectively. Therefore, the determination of arbitrary polarization states through the proposed ultracompact fiber-compatible metasurface can be achieved. Moreover, we calculated full-Stokes parameters according to simulation results and obtained that the average detection deviation is relatively low at 2.84% for 20 elucidated samples. The novel metasurface exhibits excellent polarization detection performance and overcomes the limitation of the small integrated area, which provides insights into the further practical explorations of ultracompact polarization detection devices.

Coherent OTDR with large dynamic range based on double-sideband linear frequency modulation pulse.

Rayleigh scattering-based distributed optical fiber sensors with long sensing distance and large dynamic range are highly desired for application scenarios such as vehicle tracking, structure health monitoring, and geological survey. To enlarge the dynamic range, we propose a coherent optical time domain reflectometry (COTDR) based on double-sideband linear frequency modulation (LFM) pulse. By utilizing I/Q demodulation, both the positive and negative frequency band of the Rayleigh backscattering (RBS) signal can be properly demodulated. Consequently, the dynamic range is doubled without increasing the bandwidth of signal generator, photodetector (PD), and oscilloscope. In the experiment, the chirped pulse with 10 µs pulse width and 498 MHz frequency sweeping range is launched into the sensing fiber. Single-shot strain measurement is achieved over 5 km single-mode fiber with a spatial resolution of 2.5 m and a strain sensitivity of 7.5 pε/H z. A vibration signal with 3.09 µÎµ peak-to-peak amplitude (corresponding to 461 MHz frequency shift) is successfully measured with the double-sideband spectrum, which cannot be properly recovered with the single-sideband spectrum.

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.

Simplified LDPC-assisted CNC algorithm for entropy-loaded discrete multi-tone in a 100G flexible-rate PON.

Passive optical networks (PONs) have been widely used in optical access networks to meet the requirement of the rapidly growing data traffic. However, the optical power budget of the worst optical network unit certainly limits the maximum capacity of PON. In this paper, we demonstrate a flexible-rate PON based on entropy-loaded clipping discrete multi-tone (DMT) for increasing the capacity. Meanwhile, clipping operation and simplified low-density parity-check (LDPC) assisted clipping-noise-cancellation (CNC) algorithm are proposed to improve the performance of DMT in peak-power constrained PON. In the simplified LDPC-assisted CNC algorithm, the iteration number of the sum-product algorithm in the LDPC decoding can be reduced to decrease the computational complexity almost without performance loss. The experimental results show that the simplified CNC algorithm can achieve approximately 1.8dB improvement of the optical receiver sensitivity at the 20% soft-decision forward-error-correction limit. The proposed flexible-rate PON has a wide-range data-rate adjustment from 12.5Gb/s to 100Gb/s under the optical power budget from 40dB to 26dB.

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.

Highly sensitive gas pressure sensor based on the hollow core Bragg fiber and harmonic Vernier effect.

A highly sensitive inline gas pressure sensor based on the hollow core Bragg fiber (HCBF) and harmonic Vernier effect (VE) is proposed and experimentally demonstrated. By sandwiching a segment of HCBF between the lead-in single-mode fiber (SMF) and the hollow core fiber (HCF), a cascaded Fabry-Perot interferometer is produced. The lengths of the HCBF and HCF are precisely optimized and controlled to generate the VE, achieving a high sensitivity of the sensor. Meanwhile, a digital signal processing (DSP) algorithm is proposed to research the mechanism of the VE envelope, thus providing an effective way to improve the sensor's dynamic range based on calibrating the order of the dip. Theoretical simulations are investigated and matched well with the experimental results. The proposed sensor exhibits a maximum gas pressure sensitivity of 150.02 nm/MPa with a low temperature cross talk of 0.00235 MPa/ ∘C. All these advantages highlight the sensor's enormous potential for gas pressure monitoring under various extreme conditions.

The effect of green coffee extract supplementation on obesity indices: critical umbrella review of interventional meta-analyses.

Despite a multitude of investigations assessing the impact of green coffee extract supplementation on obesity indices, there is still a great deal of heated debate regarding the benefits of this intervention in obesity management. Therefore, in order to clarify the effect of green coffee extract on waist circumference (WC), body mass index (BMI) and body weight (BW), we conducted an umbrella review of interventional meta-analyses. The Web of Science, Scopus, PubMed/Medline, and Embase databases were searched using specific keywords and word combinations. The umbrella meta-analysis was performed using the Stata software version 17 (Stata Corp. College Station, Texas, USA). We pooled effect sizes (ES) and confidence intervals (CI) for the outcomes using the random effects model (the DerSimonian and Laird method). In total, 5 eligible meta-analyses were included in the final quantitative assessment. Data pooled from 5 eligible papers revealed that green coffee extract can reduce BW (WMD: -1.22 kg, 95% CI: -1.53 to -0.92, p < 0.001), BMI (WMD: -0.48 kg/m2, 95% CI: -0.67 to -0.29, p < 0.001) and WC (WMD: -0.55 cm, 95% CI: -0.80 to -0.31, p < 0.001). Subgroup analyses highlighted that green coffee extract supplementation in dosages ≤600 mg/day and interventions lasting >7 wk are more likely to decrease BW. The present umbrella meta-analysis confirms the beneficial effects of green coffee extract in reducing WC, BMI, and BW. Thus, we may infer that green coffee extract can be used as a complementary therapy in the management of obesity.

MnO2 Decorated Metal-Organic Framework-Based Hydrogel Relieving Tumor Hypoxia for Enhanced Photodynamic Therapy.

Photodynamic therapy (PDT) has emerged as a promising cancer treatment modality; however, its therapeutic efficacy is greatly limited by tumor hypoxia. In this study, a metal-organic framework (MOF)-based hydrogel (MOF Gel) system that synergistically combines PDT with the supply of oxygen is designed. Porphyrin-based Zr-MOF nanoparticles are synthesized as the photosensitizer. MnO2 is decorated onto the surface of the MOF, which can effectively convert H2O2 into oxygen. Simultaneously, the incorporation of MnO2 -decorated MOF (MnP NPs) into a chitosan hydrogel (MnP Gel) serves to enhance its stability and retention at the tumor site. The results show that this integrated approach significantly improves tumor inhibition efficiency by relieving tumor hypoxia and enhancing PDT. Overall, the findings underscore the potential for employing nano-MOF-based hydrogel systems as promising agents for cancer therapy, thus advancing the application of multifunctional MOFs in cancer treatment.

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.