Development of a colloidal gold-based immunochromatographic assay for rapid detection of nasal mucosal secretory IgA against SARS-CoV-2.

Introduction: Infection with SARS-CoV-2 begins in the upper respiratory tract and can trigger the production of mucosal spike-specific secretory IgA (sIgA), which provides protection against reinfection. It has been recognized that individuals with high level of nasal spike-specific IgA have a lower risk of reinfection. However, mucosal spike-specific sIgA wanes over time, and different individuals may have various level of spike-specific sIgA and descending kinetics, leading to individual differences in susceptibility to reinfection. A method for detecting spike-specific sIgA in the nasal passage would be valuable for predicting the risk of reinfection so that people at risk can have better preparedness. Methods: In this study, we describe the development of a colloidal gold-based immunochromatographic (ICT) strip for detecting SARS-CoV-2 Omicron spike-specific sIgA in nasal mucosal lining fluids (NMLFs). Results: The ICT strip was designed to detect 0.125 µg or more spike-specific sIgA in 80 µL of NMLFs collected using a nasal swab. Purified nasal sIgA samples from individuals who recently recovered from an Omicron BA.5 infection were used to demonstrate that this ICT strip can specifically detect spike-specific sIgA. The signal levels positively correlated with neutralizing activities against XBB. Subsequent analysis revealed that people with low or undetectable levels of spike-specific sIgA in the nasal passage were more susceptible to SARS-CoV-2 reinfection. Conclusions: This nasal spike-specific sIgA ICT strip provides a non-invasive, rapid, and convenient method to assess the risk of reinfection for achieving precision preparedness.

Silicon-Cantilever-Enhanced Single-Fiber Photoacoustic Acetylene Gas Sensor.

A single-fiber photoacoustic (PA) sensor with a silicon cantilever beam for trace acetylene (C2H2) gas analysis was proposed. The miniature gas sensor mainly consisted of a microcantilever and a non-resonant PA cell for the real-time detection of acetylene gas. The gas diffused into the photoacoustic cell through the silicon cantilever beam gap. The volume of the PA cell in the sensor was about 14 µL. By using a 1 × 2 fiber optical coupler, a 1532.8 nm distributed feedback (DFB) laser and a white light interference demodulation module were connected to the single-fiber photoacoustic sensor. A silicon cantilever was utilized to improve the performance when detecting the PA signal. To eliminate the interference of the laser-reflected light, a part of the Fabry-Perot (F-P) interference spectrum was used for phase demodulation to achieve the highly sensitive detection of acetylene gas. The minimum detection limit (MDL) achieved was 0.2 ppm with 100 s averaging time. In addition, the calculated normalized noise equivalent absorption (NNEA) coefficient was 4.4 × 10-9 W·cm-1·Hz-1/2. The single-fiber photoacoustic sensor designed has great application prospects in the early warning of transformer faults.

A novel fault classification feature extraction method for rolling bearing based on multi-sensor fusion technology and EB-1D-TP encoding algorithm.

To improve the accuracy of bearing fault diagnosis in a multisensor monitoring environment, it is necessary to obtain more accurate and effective fault classification features for bearings. Accordingly, a bearing fault classification feature extraction method based on multisensor fusion technology and an enhanced binary one-dimensional ternary pattern (EB-1D-TP) algorithm were proposed in this study. First, an optimal equalization weighting algorithm was established to realize high-precision fusion of bearing signals by introducing an optimal equalization factor and determining the theoretical optimal equalization factor value. Second, an enhanced binary encoding method similar to balanced ternary encoding was developed, which increases the difference between the different fault features of the bearing. Finally, the new sequence obtained after encoding was used as the input to a support vector machine to classify and diagnose the faults of the rolling bearing. The experimental results show that the algorithm can significantly improve the accuracy and speed of rolling-bearing fault classification. Combining fusion-encoding features with other intelligent classification methods, the classification results were improved.

Analysis on the inherent noise tolerance of feedforward network and one noise-resilient structure.

In the past few decades, feedforward neural networks have gained much attraction in their hardware implementations. However, when we realize a neural network in analog circuits, the circuit-based model is sensitive to hardware nonidealities. The nonidealities, such as random offset voltage drifts and thermal noise, may lead to variation in hidden neurons and further affect neural behaviors. This paper considers that time-varying noise exists at the input of hidden neurons, with zero-mean Gaussian distribution. First, we derive lower and upper bounds on the mean square error loss to estimate the inherent noise tolerance of a noise-free trained feedforward network. Then, the lower bound is extended for any non-Gaussian noise cases based on the Gaussian mixture model concept. The upper bound is generalized for any non-zero-mean noise case. As the noise could degrade the neural performance, a new network architecture is designed to suppress the noise effect. This noise-resilient design does not require any training process. We also discuss its limitation and give a closed-form expression to describe the noise tolerance when the limitation is exceeded.

Adaptive enhancement of acoustic resolution photoacoustic microscopy imaging via deep CNN prior.

Acoustic resolution photoacoustic microscopy (AR-PAM) is a promising medical imaging modality that can be employed for deep bio-tissue imaging. However, its relatively low imaging resolution has greatly hindered its wide applications. Previous model-based or learning-based PAM enhancement algorithms either require design of complex handcrafted prior to achieve good performance or lack the interpretability and flexibility that can adapt to different degradation models. However, the degradation model of AR-PAM imaging is subject to both imaging depth and center frequency of ultrasound transducer, which varies in different imaging conditions and cannot be handled by a single neural network model. To address this limitation, an algorithm integrating both learning-based and model-based method is proposed here so that a single framework can deal with various distortion functions adaptively. The vasculature image statistics is implicitly learned by a deep convolutional neural network, which served as plug and play (PnP) prior. The trained network can be directly plugged into the model-based optimization framework for iterative AR-PAM image enhancement, which fitted for different degradation mechanisms. Based on physical model, the point spread function (PSF) kernels for various AR-PAM imaging situations are derived and used for the enhancement of simulation and in vivo AR-PAM images, which collectively proved the effectiveness of proposed method. Quantitatively, the PSNR and SSIM values have all achieve best performance with the proposed algorithm in all three simulation scenarios; The SNR and CNR values have also significantly raised from 6.34 and 5.79 to 35.37 and 29.66 respectively in an in vivo testing result with the proposed algorithm.

Intranasal booster using an Omicron vaccine confers broad mucosal and systemic immunity against SARS-CoV-2 variants.

The highly contagious SARS-CoV-2 Omicron subvariants severely attenuated the effectiveness of currently licensed SARS-CoV-2 vaccines based on ancestral strains administered via intramuscular injection. In this study, we generated a recombinant, replication-incompetent human adenovirus type 5, Ad5-S-Omicron, that expresses Omicron BA.1 spike. Intranasal, but not intramuscular vaccination, elicited spike-specific respiratory mucosal IgA and residential T cell immune responses, in addition to systemic neutralizing antibodies and T cell immune responses against most Omicron subvariants. We tested intranasal Ad5-S-Omicron as a heterologous booster in mice that previously received intramuscular injection of inactivated ancestral vaccine. In addition to inducing serum broadly neutralizing antibodies, there was a significant induction of respiratory mucosal IgA and neutralizing activities against Omicron subvariants BA.1, BA.2, BA.5, BA.2.75, BF.7 as well as pre-Omicron strains Wildtype, Beta, and Delta. Serum and mucosal neutralizing activities against recently emerged XBB, BQ.1, and BQ.1.1 could also be detected but were much lower. Nasal lavage fluids from intranasal vaccination contained multimeric IgA that can bind to at least 10 spike proteins, including Omicron subvariants and pre-Omicron strains, and possessed broadly neutralizing activities. Intranasal vaccination using Ad5-S-Omicron or instillation of intranasal vaccinee's nasal lavage fluids in mouse nostrils protected mice against Omicron challenge. Taken together, intranasal Ad5-S-Omicron booster on the basis of ancestral vaccines can establish effective mucosal and systemic immunity against Omicron subvariants and multiple SARS-CoV-2 variants. This candidate vaccine warrants further development as a safe, effective, and user-friendly infection and transmission-blocking vaccine.

A nasal spray vaccination device based on Laval nozzle and its experimental test.

In order to realize the application of the nasal spray vaccination in the prevention and protection of respiratory infectious diseases, a nasal spray vaccination device is designed in this paper. The device uses a Laval nozzle structure to generate a high-speed airflow that impinges on the vaccine reagent and forms nebulized particles. Through optimizing of the Laval nozzle structure and testing experiments on spray particle size, spray velocity, spray angle and spray rate, a set of parameters which is applicable to actual nasal spray vaccination is obtained. The experimental results show that when the air source pressure is 2 bar, the spray angle is about 15°, the diameter of the spray particles Dv50 is about 17 µm, the volume fraction of particles with diameter smaller than 10um is about 24%, the spray rate is close to 300 µl/s. The vaccine activity tests demonstrate that under these conditions, not only the biological activity of vaccines is guaranteed, but also the delivery efficiency is well assured.

Health-Related Quality of Life Following Robotic-Assisted or Video-Assisted Lobectomy in Patients With Non-Small Cell Lung Cancer: Results From the RVlob Randomized Clinical Trial.

BACKGROUND: Robot-assisted lobectomy (RAL) is increasingly used as an alternative to video-assisted lobectomy (VAL) for resectable non-small cell lung cancer (NSCLC). However, there is little evidence of any difference in postoperative health-related quality of life (HRQoL) between these two approaches. RESEARCH QUESTION: Is RAL superior to VAL in improving quality of life in patients with resectable NSCLC? STUDY DESIGN AND METHODS: We performed a single-center, open-label randomized clinical trial from May 2017 to May 2020 with 320 enrolled patients undergoing RAL or VAL for resectable NSCLC (RVlob trial; NCT03134534). Postoperative pain was evaluated by visual analog score or numeric rating score on postoperative day 1 and at weeks 4, 24, and 48. The European Organization for Research and Treatment of Cancer (EORTC) Core Quality of Life Questionnaire (QLQ-C30), EORTC Quality of Life Questionnaire in Lung Cancer (QLQ-LC13), and the European Quality of Life 5 Dimensions (EQ-5D) questionnaire were also administered at weeks 4, 24, and 48 after surgery. RESULTS: One hundred and fifty-seven patients underwent RAL and 163 underwent VAL. The mean pain score of patients after RAL was significantly lower at week 4 (2.097 ± 0.111 vs 2.431 ± 0.108; P = .032). QLQ-C30 and QLQ-LC13 summary scores (P > .05) were similar for both RAL and VAL during the first 48 weeks of follow-up. HRQoL scores assessed with the EQ-5D questionnaire were also comparable between the two groups (P > .05) during the whole study period. INTERPRETATION: Both RAL and VAL showed satisfactory and comparable HRQoL and postoperative pain up to 48 weeks after surgery, despite some minor statistical differences at week 4. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT03134534; URL: www. CLINICALTRIALS: gov.

Booster vaccination is required to elicit and maintain COVID-19 vaccine-induced immunity in SIV-infected macaques.

ABSTRACTProlonged infection and possible evolution of SARS-CoV-2 in patients living with uncontrolled HIV-1 infection highlight the importance of an effective vaccination regimen, yet the immunogenicity of COVID-19 vaccines and predictive immune biomarkers have not been well investigated. Herein, we report that the magnitude and persistence of antibody and cell-mediated immunity (CMI) elicited by an Ad5-vectored COVID-19 vaccine are impaired in SIV-infected macaques with high viral loads (> 105 genome copies per ml plasma, SIVhi) but not in macaques with low viral loads (< 105, SIVlow). After a second vaccination, the immune responses are robustly enhanced in all uninfected and SIVlow macaques. These responses also show a moderate increase in 70% SIVhi macaques but decline sharply soon after. Further analysis reveals that decreased antibody and CMI responses are associated with reduced circulating follicular helper T cell (TFH) counts and aberrant CD4/CD8 ratios, respectively, indicating that dysregulation of CD4+ T cells by SIV infection impairs the COVID-19 vaccine-induced immunity. Ad5-vectored COVID-19 vaccine shows no impact on SIV loads or SIV-specific CMI responses. Our study underscores the necessity of frequent booster vaccinations in HIV-infected patients and provides indicative biomarkers for predicting vaccination effectiveness in these patients.

The influence of prostate volume on clinical parameters in prostate cancer screening.

PURPOSE: The purpose of the study was to evaluate the diagnostic significance of two new and a few clinical markers for prostate cancer (PCa) at various prostate volumes (PV). METHODS: The study subjects were divided into two groups. Among them, there were 70 cases in the PV ≤30 ml group (benign prostatic hyperplasia [BPH]: 32 cases, PCa: 38 cases) and 372 cases in the PV > 30 ml group (BPH: 277 cases, PCa: 95 cases). SPSS 26.0 and GraphPad Prism 8.0 were used to construct their receiver operating characteristic (ROC) curves for diagnosing PCa and calculating their area under the ROC curve (AUC). RESULTS: In the PV ≤30 ml group, the diagnostic parameters based on prostate-specific antigen (PSA) had a decreased diagnostic significance for PCa. In the PV > 30 ml group, PSAD (AUC = 0.709), AVR (AVR = Age/PV, AUC = 0.742), and A-PSAD (A-PSAD = Age×PSA/PV, AUC = 0.736) exhibited moderate diagnostic significance for PCa, which was better than PSA-AV (AUC = 0.672), free PSA (FPSA, AUC = 0.509), total PSA (TPSA, AUC = 0.563), (F/T) PSA (AUC = 0.540), and (F/T)/PSAD (AUC = 0.663). Compared with AVR, A-PSAD exhibited similar diagnostic significance for PCa, but higher than PSA density (PSAD). CONCLUSIONS: Choosing appropriate indicators for different PVs could contribute to the early screening and diagnosis of PCa. The difference in the diagnostic value of two new indicators (A-PSAD and AVR), and PSAD for PCa may require further validation by increasing the sample size.

Deep and Domain Transfer Learning Aided Photoacoustic Microscopy: Acoustic Resolution to Optical Resolution.

Acoustic resolution photoacoustic micros- copy (AR-PAM) can achieve deeper imaging depth in biological tissue, with the sacrifice of imaging resolution compared with optical resolution photoacoustic microscopy (OR-PAM). Here we aim to enhance the AR-PAM image quality towards OR-PAM image, which specifically includes the enhancement of imaging resolution, restoration of micro-vasculatures, and reduction of artifacts. To address this issue, a network (MultiResU-Net) is first trained as generative model with simulated AR-OR image pairs, which are synthesized with physical transducer model. Moderate enhancement results can already be obtained when applying this model to in vivo AR imaging data. Nevertheless, the perceptual quality is unsatisfactory due to domain shift. Further, domain transfer learning technique under generative adversarial network (GAN) framework is proposed to drive the enhanced image's manifold towards that of real OR image. In this way, perceptually convincing AR to OR enhancement result is obtained, which can also be supported by quantitative analysis. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values are significantly increased from 14.74 dB to 19.01 dB and from 0.1974 to 0.2937, respectively, validating the improvement of reconstruction correctness and overall perceptual quality. The proposed algorithm has also been validated across different imaging depths with experiments conducted in both shallow and deep tissue. The above AR to OR domain transfer learning with GAN (AODTL-GAN) framework has enabled the enhancement target with limited amount of matched in vivo AR-OR imaging data.

Indium doped bismuth subcarbonate nanosheets for efficient electrochemical reduction of carbon dioxide to formate in a wide potential window.

Electrochemical carbon dioxide (CO2) reduction reaction (E-CO2RR) to formate with high selectivity driven by renewable electricity is one of the most promising routes to carbon neutrality. Herein, we developed a novel indium (In)-doped bismuth subcarbonate (BOC) nanosheets (BOC-In-x NSs) through transformation of In-doped bismuth (Bi) nanoblocks (Bi-In-x NBs). The BOC-In-0.1 NSs achieved a maximum Faraday efficiency of formate (FEformate) nearly 100% with high stability (22 h) and an appreciable average FEformate of 93.5% in a wide potential window of 450 mV. The experimental and theoretical calculations indicate that the incorporation of In into BOC nanosheets enhanced the adsorption of CO2 and the intermediates during the process of E-CO2RR, and reduced the energy barrier for the formation of formate.

Deep learning enhanced Rydberg multifrequency microwave recognition.

Recognition of multifrequency microwave (MW) electric fields is challenging because of the complex interference of multifrequency fields in practical applications. Rydberg atom-based measurements for multifrequency MW electric fields is promising in MW radar and MW communications. However, Rydberg atoms are sensitive not only to the MW signal but also to noise from atomic collisions and the environment, meaning that solution of the governing Lindblad master equation of light-atom interactions is complicated by the inclusion of noise and high-order terms. Here, we solve these problems by combining Rydberg atoms with deep learning model, demonstrating that this model uses the sensitivity of the Rydberg atoms while also reducing the impact of noise without solving the master equation. As a proof-of-principle demonstration, the deep learning enhanced Rydberg receiver allows direct decoding of the frequency-division multiplexed signal. This type of sensing technology is expected to benefit Rydberg-based MW fields sensing and communication.

Chemical reprogramming of human somatic cells to pluripotent stem cells.

Cellular reprogramming can manipulate the identity of cells to generate the desired cell types1-3. The use of cell intrinsic components, including oocyte cytoplasm and transcription factors, can enforce somatic cell reprogramming to pluripotent stem cells4-7. By contrast, chemical stimulation by exposure to small molecules offers an alternative approach that can manipulate cell fate in a simple and highly controllable manner8-10. However, human somatic cells are refractory to chemical stimulation owing to their stable epigenome2,11,12 and reduced plasticity13,14; it is therefore challenging to induce human pluripotent stem cells by chemical reprogramming. Here we demonstrate, by creating an intermediate plastic state, the chemical reprogramming of human somatic cells to human chemically induced pluripotent stem cells that exhibit key features of embryonic stem cells. The whole chemical reprogramming trajectory analysis delineated the induction of the intermediate plastic state at the early stage, during which chemical-induced dedifferentiation occurred, and this process was similar to the dedifferentiation process that occurs in axolotl limb regeneration. Moreover, we identified the JNK pathway as a major barrier to chemical reprogramming, the inhibition of which was indispensable for inducing cell plasticity and a regeneration-like program by suppressing pro-inflammatory pathways. Our chemical approach provides a platform for the generation and application of human pluripotent stem cells in biomedicine. This study lays foundations for developing regenerative therapeutic strategies that use well-defined chemicals to change cell fates in humans.

Human pluripotent stem-cell-derived islets ameliorate diabetes in non-human primates.

Human pluripotent stem-cell-derived islets (hPSC-islets) are a promising cell resource for diabetes treatment1,2. However, this therapeutic strategy has not been systematically assessed in large animal models physiologically similar to humans, such as non-human primates3. In this study, we generated islets from human chemically induced pluripotent stem cells (hCiPSC-islets) and show that a one-dose intraportal infusion of hCiPSC-islets into diabetic non-human primates effectively restored endogenous insulin secretion and improved glycemic control. Fasting and average pre-prandial blood glucose levels significantly decreased in all recipients, accompanied by meal or glucose-responsive C-peptide release and overall increase in body weight. Notably, in the four long-term follow-up macaques, average hemoglobin A1c dropped by over 2% compared with peak values, whereas the average exogenous insulin requirement reduced by 49% 15 weeks after transplantation. Collectively, our findings show the feasibility of hPSC-islets for diabetic treatment in a preclinical context, marking a substantial step forward in clinical translation of hPSC-islets.

Clinical research analysis based on prostate cancer screening diagnosis.

This study aimed to analyse the clinical characteristics and risk factors of patients with positive prostate biopsy at 4-20 ng/mL of prostate-specific antigen (PSA), construct a new parameter based on this characteristics and assess its diagnostic value for prostate cancer (PCa). Logistic regression analysis was used to clarify the risk factors of PCa, and a new parameter based on the results was constructed. Compare the diagnostic value of various diagnostic parameters for PCa. Logistic multivariate regression analysis revealed that age (OR, 5.269; 95%CI, 2.762-10.050), comorbid diabetes (OR, 2.437; 95%CI, 1.162-5.111), PSA (OR, 2.462; 95%CI, 1.198-5.059) and prostate volume (PV) (OR, 0.227; 95%CI, 0.100-0.516) are risk factors for PCa. The age, PSA and PV of patients were combined to construct a new parameter, that is A-PSAD = (age × total PSA [TPSA])/PV]. The area under the receiver-operating characteristic curve(AUC) of A-PSAD (0.728) for PCa diagnosis was higher than the AUCs of TPSA (0.581), free prostate-specific antigen (0.514), (F/T)PSA (0.535) and PSAD (0.696), with significant differences. Age, history of diabetes, TPSA and PV are risk factors for PCa(PSA:4-20ng/mL); in addition, A-PSAD has a moderate diagnostic value for PCa and may become a new indicator for PCa screening.

Robotic-assisted Versus Video-assisted Thoracoscopic Lobectomy: Short-term Results of a Randomized Clinical Trial (RVlob Trial).

OBJECTIVE: To determine whether RAL affects perioperative outcomes and long-term efficacy in NSCLC patients, compared with traditional VAL. SUMMARY OF BACKGROUND DATA: RAL is a promising treatment for NSCLC. However, its efficacy has not been fully evaluated. METHODS: A single-center, open-labeled prospective randomized clinical trial was launched in May 2017 to compare the efficacy of RAL and VAL. By May 2020, 320 patients were enrolled. The perioperative results of RAL and VAL were compared. RESULTS: The 320 enrolled patients were randomly assigned to the RAL group (n = 157) and the VAL group (n = 163). Perioperative outcomes were comparable between the 2 groups, including the length of hospital stay (P = 0.76) and the rate of postoperative complications (P = 0.45). No perioperative mortality occurred in either group. The total amount of chest tube drainage {830 mL [interquartile range (IQR), 550-1130 mL] vs 685 mL [IQR, 367.5-1160 mL], P = 0.007} and hospitalization costs [$12821 (IQR, $12145-$13924) vs $8009 (IQR, $7014-$9003), P < 0.001] were significantly higher in the RAL group. RAL group had a significantly higher number of LNs harvested [11 (IQR, 8-15) vs 10 (IQR, 8-13), P = 0.02], higher number of N1 LNs [6 (IQR, 4-8) vs 5 (IQR, 3-7), P = 0.005], and more LN stations examined [6 (IQR, 5-7) vs 5 (IQR, 4-6), P < 0.001]. CONCLUSIONS: Both RAL and VAL are safe and feasible for the treatment of NSCLC. RAL achieved similar perioperative outcomes, together with higher LN yield. Further follow-up investigations are required to evaluate the long-term efficacy of RAL. (ClinicalTrials.gov identifier: NCT03134534).

Review of Approaches to Developing Intersegmental Plane during Segmentectomy.

In recent years, with the popularity of computed tomography (CT) scanning, early lung cancer has been found in a large number of patients, and segmentectomy has been widely used in clinical practice. The development of intersegmental plane is the most critical step in segmentectomy. At present, there are many methods to identify the intersegmental plane. Also, dissection of the intersegmental plane has been a challenge for thoracic surgeons for decades because of the complicated anatomic variations. This study focuses on the safety and efficacy of relevant methods in both identification and dissection of the intersegmental plane in segmentectomy.

GLI3 Promotes Invasion and Predicts Poor Prognosis in Colorectal Cancer.

PURPOSE: The epithelial-mesenchymal transition (EMT) is a key hallmark of cancer which promotes malignant progression, especially during the process of cancer invasion. A better understanding of EMT will help elucidate the molecular mechanism underlying colorectal cancer (CRC) metastasis and may provide new insights into the identification of potential biomarkers and therapeutic targets. METHODS: A series of bioinformatic approaches were combined and identify GLI3 as a potential key regulator in EMT. In vitro experiments were performed to knockdown GLI3 expression in two CRC cell lines and to reveal the oncogenic role of GLI3 in CRC. qRT-PCR and western blot were performed to show the influence of GLI3 in EMT and downstream pathways. The Kaplan-Meier analysis and log-rank test were used to evaluate the prognostic value of GLI3 in CRC patients. RESULTS: GLI3 was identified as a key regulator in coexpression and protein-protein interaction (PPI) networks involved in EMT. Bioinformatic analyses indicated that GLI3 had a high correlation with EMT markers in CRC. In vitro experiments showed that GLI3 knockdown attenuated the migratory and invasive capacities of CRC cells via influencing EMT property, especially by regulating phosphorylation of ERK signaling pathway. In addition, higher expression of GLI3 predicts worse prognosis in CRC patients. CONCLUSIONS: In summary, we presented the first evidence that GLI3 could promote the migratory and invasive capacities of CRC cells by regulating the EMT process. Our study might provide some useful clues to a better understanding of GLI3 in EMT during CRC progression.