Regulation mechanism of plant response to heavy metal stress mediated by endophytic fungi

Endophytic fungi exist widely in plants and play an important role in the growth and adaptation of plants. They could be used in phytoremediation techniques against heavy metal contaminated soil since beneficial microbial symbionts can endow plants with resistance to external heavy metal stresses. This review summarized the regulation mechanism of plant response to heavy metal stress mediated by endophytic fungi. Potential endophytic fungi in enhancing plant's adaption to heavy metal stresses include arbuscular mycorrhizal fungi, dark septate endophytic fungi, plant growth promoting endophytic fungi. The mechanisms involve coevolution strategy, immune regulation and detoxification transport to improve the ability of plants to adapt to heavy metal stress. They can increase the synthesis of host hormones and maintaining the balance of endogenous hormones, strengthen osmotic regulation, regulate carbon and nitrogen metabolism, and increase immune activity, antioxidant enzyme and glutathione activity. They also help to improve the detoxification transport and heavy metal emission capacity of the host by significantly producing iron carrier, metallothionein and 1-aminocyclopropane-1-carboxylic acid deaminase. The combination of endophytic fungi and hyperaccumulation plants provides a promising technology for the ecological restoration of heavy metal contaminated soil. Endophytic fungi reserves further development on enhancing host plant's adaptability to heavy metal stresses.

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.

[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.

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.

The amino acids, bacterial communities, and their correlations in Wuliangye-flavour liquor production

With the enhancement of people’s awareness of drinking health, the health factors in Wuliangye-flavour liquor is worth our attention. Bacterial communities in 4 layers of Zaopei from the same fermentation pit and amino acids as major health factors in 4 liquors directly related Zaopeis were investigated by Illumina MiSeq sequencing and liquid chromatography mass spectrometry, respectively. Results indicated that 18 amino acids were detected and 8 dominant bacteria (genus level) were observed. Meanwhile, total amino acids, 11 amino acids (Glu, Asp, Val, etc), bacterial diversity, and the percentages of Lactobacillus and Pseudomonas increased with the increase of Zaopei’s depth; 5 amino acids (Pro, Ser, Phe, etc) and the percentages of Pediococcus and Bacteroides first increased and then decreased with the increase of Zaopei’s depth. Moreover, 11 amino acids were significantly (P < 0.01) and strongly (|ρ| > 0.8) positively correlated with Lactobacillus and Pseudomonas numbers.