[Optimized pathway to schistosomiasis elimination in China: a scrutiny using a marginal benefit approach]

Following concerted efforts for over 7 decades, great achievements have been gained in the national schistosomiasis control program of China. Currently, China is moving towards the stage of schistosomiasis elimination, when the major task is to make full use of available resources to improve schistosomiasis surveillance and response to sustainably consolidate gained schistosomiasis control achievements and prevent re-emerging schistosomiasis. There is therefore an urgent need for optimization of interventions for schistosomiasis elimination. Based on analysis of socioeconomic features at different stages of the national schistosomiasis control program in China, this review discusses the relationship between the needs of assessment of schistosomiasis elimination interventions and the optimized strategy of schistosomiasis elimination at different stages of the national schistosomiasis control program using a marginal benefit approach and proposes the optimized schistosomiasis elimination strategy that allows the highest marginal benefit with currently available schistosomiasis elimination costs, so as to provide the optimal strategic pathway to schistosomiasis elimination and facilitate the achievement of the targets set in Healthy China 2030.

Three-Dimensional Numerical Simulation of the Performance and Transport Phenomena of Oxygen Evolution Reactions in a Proton Exchange Membrane Water Electrolyzer

Proton exchange membrane (PEM) water electrolysis, which is one of methods of hydrogen production with the most potential, has attracted more attention due to its energy conversion and storage potential. In this paper, a steady state, three-dimensional mathematical model coupled with the electrochemical and mass transfer physical fields for a PEM water electrolyzer was established. The influence of the different operation parameters on the cell performance was discussed. Moreover, the different patterns of the flow field, such as parallel, serpentine, multi-serpentine, and interdigitate flow fields, were simulated to reveal their influence on the mass transfer and current distribution and how they consequently affected the cell performance. The results of the numerical modeling were in good agreement with the experimental data. The results demonstrated that a higher temperature led to a better mass transfer, current distribution, and cell performance. By comparing the polarization curve, current, velocity, and pressure distribution, the results also indicated that the PEM water electrolyzer with a parallel flow field had the best performance. The results in this study can help in optimizing the design of PEM water electrolyzers.

Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer

AIM

To develop and validate a nomogram model that combines computed tomography (CT)-based radiological factors extracted from deep-learning and clinical factors for the early predictions of immune checkpoint inhibitor-related pneumonitis (ICI-P).

MATERIALS AND METHODS

Forty ICI-P patients and 101 patients without ICI-P were divided randomly into the training (n=113) and test (n=28) sets. The convolution neural network (CNN) algorithm was used to extract the CT-based radiological features of predictable ICI-P and calculated the CT score of each patient. A nomogram model to predict the risk of ICI-P was developed by logistic regression.

RESULTS

CT score was calculated from five radiological features extracted by the residual neural network-50-V2 with feature pyramid networks. Four predictors of ICI-P in the nomogram model included a clinical feature (pre-existing lung diseases), two serum markers (absolute lymphocyte count and lactate dehydrogenase), and a CT score. The area under curve of the nomogram model in the training (0.910 versus 0.871 versus 0.778) and test (0.900 versus 0.856 versus 0.869) sets was better than the radiological and clinical models. The nomogram model showed good consistency and better clinical practicability.

CONCLUSION

The nomogram model that combined CT-based radiological factors and clinical factors can be used as a new non-invasive tool for the early prediction of ICI-P in lung cancer patients after immunotherapy with low cost and low manual input.

Aeroengine Working Condition Recognition Based on MsCNN-BiLSTM

Aeroengine working condition recognition is a pivotal step in engine fault diagnosis. Currently, most research on aeroengine condition recognition focuses on the stable condition. To identify the aeroengine working conditions including transition conditions and better achieve the fault diagnosis of engines, a recognition method based on the combination of multi-scale convolutional neural networks (MsCNNs) and bidirectional long short-term memory neural networks (BiLSTM) is proposed. Firstly, the MsCNN is used to extract the multi-scale features from the flight data. Subsequently, the spatial and channel weights are corrected using the weight adaptive correction module. Then, the BiLSTM is used to extract the temporal dependencies in the data. The Focal Loss is used as the loss function to improve the recognition ability of the model for confusable samples. L2 regularization and DropOut strategies are employed to prevent overfitting. Finally, the established model is used to identify the working conditions of an engine sortie, and the recognition results of different models are compared. The overall recognition accuracy of the proposed model reaches over 97%, and the recognition accuracy of transition conditions reaches 94%. The results show that the method based on MsCNN-BiLSTM can effectively identify the aeroengine working conditions including transition conditions accurately.

A metagenomic insight into the Yangtze finless porpoise virome

The Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) inhabiting the Yantze River, China is critically endangered because of the influences of infectious disease, human activity, and water contamination. Viral diseases are one of the crucial factors that threatening the health of Yangtze finless porpoise. However, there are few studies which elaborate the viral diversity of Yangtze finless. Therefore, this study was performed to investigate the viral diversity of Yangtze finless by metagenomics. Results indicated that a total of 12,686,252 high-quality valid sequences were acquired and 2,172 virus reads were recognized. Additionally, we also obtained a total of 10,600 contigs. Phages was the most abundant virus in the samples and the ratio of DNA and RNA viruses were 69.75 and 30.25%, respectively. Arenaviridae, Ackermannviridae and Siphoviridae were the three most predominant families in all the samples. Moreover, the majority of viral genus were Mammarenavirus, Limestonevirus and Lambdavirus. The results of gene prediction indicated that these viruses play vital roles in biological process, cellular component, molecular function, and disease. To the best of our knowledge, this is the first report on the viral diversity of Yangtze finless porpoise, which filled the gaps in its viral information. Meanwhile, this study can also provide a theoretical basis for the establishment of the prevention and protection system for virus disease of Yangtze finless porpoise.

Biogeographic patterns of potential pathogenic bacteria in the middle and lower reaches of the Yangtze River as well as its two adjoining lakes, China

Understanding the distribution patterns and shaping factors of bacterial pathogens in aquatic ecosystems, especially in natural waters, are critical to the control of pathogen transmission. In this study, using 16S rRNA gene amplicon sequencing, we explored the composition and biogeographic dynamics of potential bacterial pathogens in the middle and lower reaches of the Yangtze River, as well as its two vast adjoining lakes (Dongting Lake and Poyang Lake). The pathogen community belonged to 12 potential pathogenic groups, with “intracellular parasites,” “animal parasites or symbionts” and “human pathogens all” occupying 97.5% in total. The potential pathogen community covered seven phyla with Proteobacteria (69.8%) and Bacteroidetes (13.5%) the most predominant. In addition, 53 genera were identified with Legionella (15.2%) and Roseomonas (14.2%) the most dominant. The average relative abundance, alpha diversity and microbial composition of the potential bacterial pathogens exhibited significant biogeographical variations among the different sections. An in-depth analysis reflected that environmental variables significantly structured the potential bacterial pathogens, including water physiochemical properties (i.e., chlorophyll-a, total nitrogen and transparency), heavy metals (i.e., As and Ni), climate (i.e., air temperature) and land use type (i.e., waters). Compared to the overall bacterial community which was composed of both pathogenic and non-pathogenic bacteria, the pathogen community exhibited distinct microbial diversity patterns and shaping factors. This signifies the importance of different variables for shaping the pathogen community. This study represents one attempt to explore pathogen diversity patterns and their underlying drivers in the Yangtze River, which provides a foundation for the management of pathogenic bacteria.

[Preparation and characterization of a recombinant poly-epitopic vaccine EgG1Y162-2 (4) against cystic echinococcosis based on the linker GSGGSG]

OBJECTIVE

To perform prokaryotic expression and preliminary characterization of the recombinant poly-epitope vaccine EgG1Y162-2 (4) against cystic echinococcosis.

METHODS

The recombinant poly-epitope vaccine EgG1Y162-2 (4) against Echinococcus granulosus based on the linker GSGGSG was subjected to structural three-dimensional (3D) modeling using immunoinformatics to analyze the structural changes and evaluate the antigenicity of the vaccine. The pET30a-EgG1Y162-2 (4) recombinant plasmid was generated using double digestion with EcoR I and Sal I, and then transformed into competent cells. Following protein induction with isopropyl-β-D-thiogalactoside (IPTG), the prokaryotic expression proteins were characterized using Western blotting, and the antigenicity of the recombinant protein was analyzed using sera from cystic echinococcosis patients and health volunteers.

RESULTS

The four EgG1Y162-2 proteins coupled by the 3D structure of the recombinant vaccine EgG1Y162-2 (4) presented independent and effective expression and good antigenicity. The highest protein expression was detected in the supernatant following induction of the recombinant plasmid pET30a-EgG1Y162-2 (4) by 0.2 mmol/L IPTG at 37 °C for 4 h, and a pure protein component was seen following elution with 60 mmol/L imidazole. Western blotting analysis of the recombinant multiepitope protein HIS-EgG1Y162-2 (4) showed a band at approximately 39 kDa, and this band was recognized by sera from cystic echinococcosis patients.

CONCLUSIONS

A recombinant poly-epitope vaccine EgG1Y162-2 (4) against cystic echinococcosis has been successfully constructed, which provides a preliminary basis for researches on recombinant multi-epitope vaccine against cystic echinococcosis.

Detection of SARS-CoV-2 VOC-Omicron using commercial sample-to-answer real-time RT-PCR platforms and melting curve-based SNP assays

Objectives

The World Health Organization (WHO) had designated the SARS-CoV-2 lineage B.1.1.529 as the new Variant of Concern Omicron (VOC-Omicron) on 26^th November 2021¹. Real-time reverse transcription polymerase chain reaction (RT-PCR), single nucleotide polymorphisms (SNP) and whole genome sequencing (WGS) tests were widely employed to detect SARS-CoV-2 and its variant. Yet, the SARS-CoV-2 Omicron detection performance of commercial real-time RT-PCR platforms and SARS-CoV-2 spike SNP assays remain to be elucidated.

Methods

In the first part of this study, we evaluated the VOC-Omicron detection performance of three commercial RT-PCR sample-to-answer platforms i.e. Roche cobas® 6800/8800, Roche cobas® Liat®, and Cepheid GeneXpert® systems. The detection performances were compared to one commercial conventional real-time RT-PCR assay (TIB MOLBIOL LightMix Modular SARS and Wuhan CoV E-gene) and one in-house real-time RT-PCR assay targeting RNA-dependent RNA polymerase (RdRP) gene of SARS-CoV-2 in the WHO COVID-19 Reference Laboratory at Public Health Laboratory Services Branch, Centre for Health Protection, Department of Health, The Government of the Hong Kong Special Administrative Region. In the second part of this study, we evaluated the SNP detection performance of four TIB MOLBIOL melting curve-based assays (1. Spike S371L/S373P, 2. Spike E484A, 3. Spike E484K and 4. Spike N501Y) in clinical samples obtained from hospitalized COVID-19 patients in Hong Kong. The SNP results were compared to whole genome sequences generated by Illumina platform.

Results

The VOC-Omicron detection limits of three commercial sample-to-answer assays were tested to be ≤ 2.35 Log₁₀ dC/ml. The detection performances of the sample-to-answer platforms were comparable to the two tested conventional real-time RT-PCR assays. The test sensitivities of TIB MOLBIOL VirSNiP SARS-CoV-2 Spike S371L/S373P assay and the Spike E484A assays were 100% and 96.6% respectively and the test specificities of both assays were 100%. An aberrant melting peak at Tm 42-44°C was observed when the specimens with Omicron variant were tested with the TIB MOLBIOL VirSNiP SARS-CoV-2 Spike E484K assay. Notably, the TIB MOLBIOL VirSNiP SARS-CoV-2 Spike N501Y assay failed to detect the spike N501Y mutation of Omicron variant in the tested specimens.

Conclusions

The SARS-CoV-2 detection sensitivity of three commercial platforms, Roche cobas® 6800/8800, Roche cobas® Liat®, and Cepheid GeneXpert® systems were shown not to be impacted by the large number of mutations of VOC-Omicron. Also, the signature mutations i.e. Spike S371L/Spike S373P and Spike E484A in VOC-Omicron were correctly identified by the TIB MOLBIOL VirSNiP SARS-CoV-2 Spike S371L/S373P and VirSNiP SARS-CoV-2 Spike E484A assays. Unexpected findings including a shifted melting peak or absence of amplification curve/melting peak were observed when specimens with Omicron variant were tested with the TIB MOLBIOL VirSNiP SARS-CoV-2 Spike E484K assay and Spike N501Y assay, suggesting a potential alert for Omicron variant, prior confirmation by whole genome sequencing.

Structural visualization of transient interactions between the cis-acting acyltransferase and acyl carrier protein of the salinomycin modular polyketide synthase

Transient protein–protein interactions between cis-acting acyltransferase (AT) and acyl carrier protein (ACP) domains are critical for the catalysis and processivity of modular polyketide synthases (mPKSs), but are challenging for structural characterization due to the intrinsically weak binding affinity. Here, a stable complex of cis-acting AT and ACP domains from the ninth module of the salinomycin mPKS was obtained using a maleimide cross-linker and the structure of the complex was determined at 2.6 Å resolution. The crystal structure shows that the AT in combination with the ketosynthase (KS)-to-AT linker forms a C-shaped architecture to embrace the ACP. The large hydrolase subdomain of the AT serves as a major binding platform for the ACP, while the small ferredoxin-like subdomain of the AT and the KS-to-AT linker cooperate with each other to constrain binding of the ACP. The importance of interface residues in cis-acting AT–ACP interactions was confirmed by mutagenesis assays. The interaction mode observed in the cis-acting AT–ACP complex is completely different from those observed in trans-acting AT–ACP complexes, where the ACP primarily contacts the small domain of the AT. The complex structure provides detailed mechanistic insights into AT–ACP recognition in cis-AT mPKSs.

[Research advances on the techniques for diagnosing burn wound depth]

The accurate diagnosis of burn wound depth is particularly important for evaluating the disease prognosis of burn patients. In the past, the diagnosis of burn wound depth often relied on the subjective judgment of doctors. With the continuous development of diagnostic technology, the methods for judging the depth of burn wound have also been updated. This paper mainly summarizes the research progress in the applications of indocyanine green angiography, laser Doppler imaging, laser speckle contrast imaging, and artificial intelligence in the diagnosis of burn wound depth, and compares the advantages and disadvantages of these techniques, so as to provide ideas for accurate diagnosis of burn wound depth.

An angular-resolved scattered-light diagnostic for laser-plasma instability studies

We developed an angular-resolved scattered-light diagnostic station (ARSDS) to extend the study of laser-plasma instabilities (LPIs) by simultaneously diagnosing their features at different angles in a single shot. The ARSDS angularly samples the scattered light using an array of fibers with flexible setups. The collected light is detected with an imaging spectrometer, a streaked spectrometer, or a fiber-optic spectrometer to provide time-integrated/time-resolved spectral information. The ARSDS was implemented at Shenguang-II Upgrade laser facility for the double-cone ignition campaigns. Preliminary results confirm the importance of an angular-resolved detection due to the angular dependence of LPI processes, such as stimulated Raman scattering.

[Utilizing modern tissue typing technologies to promote precision kidney transplantation]

Improving quality is the primary goal of the kidney transplantation community in China. Promoting new technologies for tissue typing, including adopting high-resolution human leucocyte antigen (HLA) typing methods to ensure the integrity and uniqueness of the donor and recipient HLA genotype, combining modified cytological method and purified single antigen technology to improve the accuracy of HLA antibody detection, etc., can assess the donor-recipient's mismatch load and the immune risk of recipients more precisely, so as to guide the scientific allocation of organs and individualized immunosuppressive regime, which can contribute to the long-term survival of recipients. This is the embodiment of the core essence of"precision medicine"in the field of kidney transplantation.

[18F]AlF-NOTA-FAPI-04: FAP-targeting specificity, biodistribution, and PET/CT imaging of various cancers

PURPOSE

In this pilot study, we developed a new tracer, [¹⁸F]AlF-labeled FAPI-04 chelated with NOTA, denoted as [¹⁸F]AlF-NOTA-FAPI-04, and tested the specificity, biodistribution, and clinical application for PET/computed tomography (CT) imaging of various types of cancers in patients.

METHODS

In vitro binding specificity of FAPI-04 to FAP was verified in U87 cells confocal of a fluorescence-labeled variant. In vivo imaging, competition, and dynamic scanning analyses were conducted to evaluate [¹⁸F]AlF-NOTA-FAPI-04 imaging in xenograft mouse model using small-animal PET/CT. The application of [¹⁸F]AlF-NOTA-FAPI-04 was analyzed by imaging different types of cancers in patients.

RESULTS

Both in vitro and in vivo results showed high binding specificity of FAPI-04 to FAP. High intratumoral uptake and fast body clearance of the tracer were observed in the xenograft mouse model and cancer patients. High-contrast images and negligible radiation exposure to normal tissue were observed on [¹⁸F]AlF-NOTA-FAPI-04 PET/CT in 28 patients with 8 different types of cancers. Five of 28 patients underwent PET/CT scanning at 1 h, 2 h, and 4 h after intravenous injection of [¹⁸F]AlF-NOTA-FAPI-04. Seven patients with advanced lung cancer underwent dual-tracer imaging, and 44 and 37 metastatic lesions were detected by [¹⁸F]AlF-NOTA-FAPI-04 PET/CT and [¹⁸F]F-FDG PET/CT, respectively. Overall, 80.0% of metastatic lesions was identified by both [¹⁸F]AlF-NOTA-FAPI-04 and ¹⁸F-FDG, 17.8% by [¹⁸F]AlF-NOTA-FAPI-04 PET/CT only, and 2.2% by [¹⁸F]FDG PET/CT only.

CONCLUSION

[¹⁸F]AlF-NOTA-FAPI-04 offers high specificity as a tracer for FAP imaging and allows fast imaging with high contrast in tumors. [¹⁸F]AlF-NOTA-FAPI-04 is better at identifying metastatic lesions in patients with advanced lung cancer than [¹⁸F]FDG, and its use may facilitate tumor staging.

Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations

OBJECTIVES

To develop and validate an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect different patterns of fetal intracranial abnormality in standard sonographic reference planes for screening for congenital central nervous system (CNS) malformations.

METHODS

Neurosonographic images from normal fetuses and fetuses with CNS malformations at 18-40 gestational weeks were retrieved from the databases of two tertiary hospitals in China and assigned randomly (ratio, 8:1:1) to training, fine-tuning and internal validation datasets to develop and evaluate the PAICS. The system was built based on a real-time convolutional neural network (CNN) algorithm, You Only Look Once, version 3 (YOLOv3). An image dataset from a third tertiary hospital was used to further validate, externally, the performance of the PAICS and to compare its performance with that of sonologists with different levels of expertise. Furthermore, a prospective video dataset was employed to evaluate the performance of the PAICS in a real-time scan scenario. The diagnostic accuracy, sensitivity, specificity and area under the receiver-operating-characteristics curve (AUC) were calculated to assess the performance of the PAICS and to compare this with the performance of sonologists with different levels of experience.

RESULTS

In total, 43 890 images from 16 297 pregnancies and 169 videos from 166 pregnancies were used to develop and validate the PAICS. The system achieved excellent performance in identifying 10 types of intracranial image pattern, with macro- and microaverage AUCs, respectively, of 0.933 (95% CI, 0.798-1.000) and 0.977 (95% CI, 0.970-0.985) for the internal validation image dataset, 0.902 (95% CI, 0.816-0.989) and 0.898 (95% CI, 0.885-0.911) for the external validation image dataset and 0.969 (95% CI, 0.886-1.000) and 0.981 (95% CI, 0.974-0.988) in the real-time scan setting. The performance of the PAICS was comparable to that of expert sonologists in terms of macro- and microaverage accuracy (P = 0.863 and P = 0.775, respectively), sensitivity (P = 0.883, P = 0.846) and AUC (P = 0.891, P = 0.788), but required significantly less time (0.025 s per image for PAICS vs 4.4 s for experts, P < 0.001).

CONCLUSIONS

Both in the image dataset and in the real-time scan setting, the PAICS achieved excellent diagnostic performance for various fetal CNS abnormalities. Its performance was comparable to that of experts, but it required less time. A CNN algorithm can be trained to detect fetal CNS abnormalities. The PAICS has the potential to be an effective and efficient tool in screening for fetal CNS malformations in clinical practice. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Tumor angiogenesis at baseline identified by 18F-Alfatide II PET/CT may predict survival among patients with locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy

Background

The study investigated the predictive value of tumor angiogenesis observed by ¹⁸F-ALF-NOTA-PRGD2 II (denoted as ¹⁸F-Alfatide II) positron emission tomography (PET)/computed tomography (CT) before concurrent chemoradiotherapy (CCRT) for treatment response and survival among patients with locally advanced non-small cell lung cancer (LA-NSCLC).

Methods

Patients with unresectable stage IIIA or IIIB NSCLC (AJCC Cancer Staging 7th Edition) who received CCRT were included in this prospective study. All patients had undergone ¹⁸F-Alfatide PET/CT scanning before CCRT, and analyzed parameters included maximum uptake values (SUV_max) of primary tumor (SUV_P) and metastatic lymph nodes (SUV_LN) and mean uptake value of blood pool (SUV_blood). Tumor-to-background ratios (TBRs) and changes in tumor diameter before and after CCRT (ΔD) were calculated. The ratios of SUV_P to SUV_blood, SUV_LN to SUV_blood, and SUV_P to SUV_LN were denoted as TBR_P, TBR_LN, and T/LN. Short-term treatment response, progression-free survival (PFS), and overall survival (OS) were evaluated.

Results

Of 38 enrolled patients, 28 completed CCRT. SUV_P, SUV_LN, TBR_P, TBR_LN and T/LN showed significant correlation with PFS (all P < 0.05). SUV_P was negatively correlated with OS (P = 0.005). SUV_P and TBR_P were higher in non-responders than in responders (6.55 ± 2.74 vs. 4.61 ± 1.94, P = 0.039; 10.49 ± 7.58 vs. 7.73 ± 6.09, P = 0.023). ΔD was significantly greater in responders (2.78 ± 1.37) than in non-responders (-0.16 ± 1.33, P < 0.001). Exploratory receiver operating characteristic curve analysis identified TBR_P (area under the curve [AUC] = 0.764, P = 0.018), with a cutoff value of 6.52, as the only parameter significantly predictive of the response to CCRT, with sensitivity, specificity, and accuracy values of 71.43%, 78.57%, and 75.00%, respectively. ROC curve analysis also identified SUV_P (AUC = 0.942, P < 0.001, cutoff value 4.64) and TBR_P (AUC = 0.895, P = 0.001, cutoff value 4.95) as predictive of OS with high sensitivity (84.21%, 93.75%), specificity (100.00%, 66.67%), and accuracy (89.29%, 82.14%).

Conclusions

Evaluation of tumor angiogenesis by ¹⁸F-Alfatide II at baseline may be useful in predicting the short-term response to CCRT as well as PFS and OS in patients with LA-NSCLC.