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Abstract Background The incidence of lung cancer combined with pulmonary tuberculosis has been increasing, but there is relatively limited published literature on the topic of lung cancer combined with tuberculosis (LC‐PTB) from a bibliometric perspective. Therefore, in this study, we aimed to quantitatively analyze the LC‐PTB‐related literature to better understand the current status of this field and identify future research trends. Methods We searched for articles related to LC‐PTB using the Web of Science Core Collection (SCI‐E) and conducted a visual analysis of publication quantity, countries, institutions, authors, journals, references, and keywords using bibliometric software (CiteSpace, VOSviewer, and Scimago Graphica). Results As of January 8, 2024, a total of 460 publications related to LC‐PTB were included for analysis from 3705 retrieved records. The number of publications has been increasing almost yearly, with most from China (n = 123), followed by the United States (n = 77). Taipei Medical University contributed the most publications (n = 11). Jing‐Yang Huang and Yung‐Po Liaw (eight documents each) ranked first among the included authors. The Journal of Thoracic Oncology was the most productive academic journal on LC‐PTB. The aggregation of key nodes in the co‐citation network and the chronological sequence indicated that LC‐PTB research has shifted from initial hotspots such as lung diseases, bronchitis, and exposure to recent areas, including immunotherapy, immune checkpoint inhibitors, and nivolumab. Conclusion In this study, we visualized the current status of LC‐PTB research as well as future trends using bibliometric methods, providing new insights into the differential diagnosis of LC‐PTB and its related promoting mechanisms.

Abstract Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.

Abstract The persistent threat of tuberculosis (TB) on a global scale hasprompted a reevaluation of preventive strategies, with a particular focus onthe Bacille Calmette‐Guérin (BCG) vaccine's role in revaccination. Theresurgence underscores an urgent need for enhanced measures, prompting acritical examination of BCG revaccination strategies. Drawing from the researchof Paulo Cesar Pereira dos Santos and a synthesis of randomized controlledtrials (RCTs), this review identifies key considerations for refining BCGrevaccination's efficacy against Mycobacterium tuberculosis (MTB) andTB. The main body of this review integrates four principal domains essentialfor optimizing BCG revaccination: the timing of revaccination, the assessmentof various BCG strains, the evaluation of the vaccine's effectiveness on MTBand non‐tuberculous mycobacteria (NTM) strains, and the enhancement of RCTmethodologies. Determining the optimal revaccination timing is paramount forbolstering immunity, especially in regions with high TB prevalence. Theanalysis of different BCG strains provides insights into strain‐specificimmunogenicity, informing vaccine deployment strategies. Additionally,understanding the vaccine's impact on a range of mycobacterial infections iscrucial for its broader application in various microbial contexts. The reviewemphasizes the refinement of RCT designs to ensure robust and consistentoutcomes, facilitating the reproducibility of results in diverse settings. Itproposes a strategy that not only suggests modifications to revaccinationpractices to increase global TB prevention effectiveness but also calls forcontinuous research to improve BCG revaccination methodologies. The paperadvocates for a standardized, evidence‐driven approach to global TB preventionthat takes into account regional epidemiological differences. In conclusion,this review significantly contributes to the discourse on TB prevention,advocating for evidence‐based, standardized approaches that could potentiallytransform the role of BCG revaccination in global TB prevention efforts. Thefindings support current initiatives aimed at developing policies based onsolid evidence, ensuring the scientific integrity and practical relevance ofBCG revaccination strategies.

Semantic segmentation of remote sensing images plays a critical role in areas such as urban change detection, environmental protection, and geohazard identification. Convolutional Neural Networks (CNNs) have been excessively employed for semantic segmentation over the past few years; however, a limitation of the CNN is that there exists a challenge in extracting the global context of remote sensing images, which is vital for semantic segmentation, due to the locality of the convolution operation. It is informed that the recently developed Transformer is equipped with powerful global modeling capabilities. A network called TCNet is proposed in this article, and a parallel-in-branch architecture of the Transformer and the CNN is adopted in the TCNet. As such, the TCNet takes advantage of both Transformer and CNN, and both global context and low-level spatial details could be captured in a much shallower manner. In addition, a novel fusion technique called Interactive Self-attention is advanced to fuse the multilevel features extracted from both branches. To bridge the semantic gap between regions, a skip connection module called Windowed Self-attention Gating is further developed and added to the progressive upsampling network. Experiments on three public datasets (i.e., Bijie Landslide Dataset, WHU Building Dataset, and Massachusetts Buildings Dataset) depict that TCNet yields superior performance over state-of-the-art models. The IoU values obtained by TCNet for these three datasets are 75.34% (ranked first among 10 models compared), 91.16% (ranked first among 13 models compared), and 76.21% (ranked first among 13 models compared), respectively.

Abstract Background Latent tuberculosis infection (LTBI) often progresses to active tuberculosis, necessitating the development of novel vaccine to prevent LTBI. In this study, we aimed to design a Mycobacterium tuberculosis (M. tuberculosis) vaccine that could elicit a potent immune response to prevent LTBI. Methods We used bioinformatics and immunoinformatics techniques to develop a multi‐epitope vaccine (MEV) called C624P. The vaccine contained six cytotoxic T lymphocytes (CTL), two helper T lymphocytes (HTL), and four B‐cell epitopes derived from six antigens associated with LTBI and the Mycobacterium tuberculosis region of difference. We added Toll‐like receptor (TLR) agonists and PADRE peptide to the MEV to enhance its immunogenicity. We then analyzed the C624P vaccine's physical and chemical properties, spatial structure, molecular docking with TLRs, and immunological features. Results The C624P vaccine displayed good antigenicity and immunogenicity scores of 0.901398 and 3.65609, respectively. The vaccine structure was stable, with 42.82% α‐helix content, a Z‐value of −7.84, and a favored Ramachandran plot area of 85.84% after majorization. Molecular docking analysis showed that the C624P vaccine could bind tightly to TLR2 (−1011.0 kcal/mol) and TLR4 (−941.4 kcal/mol). Furthermore, the C624P vaccine effectively stimulated T and B lymphocytes, resulting in high levels of Th1 cytokines such as IFN‐γ and IL‐2. Conclusions The C624P vaccine represents a promising MEV for preventing LTBI. The vaccine's good antigenicity, immunogenicity, stability, and ability to activate immune responses suggest its effectiveness in preventing LTBI. Our study demonstrated the utility of bioinformatics and immunoinformatics techniques in designing safe and effective tuberculosis vaccines.

Abstract The baroclinic component of the sea surface height, referred to as steric height, is governed by geostrophically balanced motions and unbalanced internal waves, and thus is an essential indicator of ocean interior dynamics. Using yearlong measurements from a mooring array, we assess the distribution of upper‐ocean steric height across frequencies and spatial scales of O (1–20 km) in the northeast Atlantic. Temporal decomposition indicates that the two largest contributors to steric height variance are large‐scale atmospheric forcing (32.8%) and mesoscale eddies (34.1%), followed by submesoscale motions (15.2%), semidiurnal internal tides (8%), super‐tidal variability (6.1%) and near‐inertial motions (3.8%). Structure function diagnostics further reveal the seasonality and scale dependence of steric height variance. In winter, steric height is dominated by balanced motions across all resolved scales, whereas in summer, unbalanced internal waves become the leading‐order contributor to steric height at scales of O (1 km).

Abstract Although tuberculosis (TB) is an infectious disease, the progression of the disease following Mycobacterium tuberculosis (MTB) infection is closely associated with the host's immune response. In this review, a comprehensive analysis of TB prevention, diagnosis, and treatment was conducted from an immunological perspective. First, we delved into the host's immune response mechanisms against MTB infection as well as the immune evasion mechanisms of the bacteria. Addressing the challenges currently faced in TB diagnosis and treatment, we also emphasized the importance of protein, genetic, and immunological biomarkers, aiming to provide new insights for early and personalized diagnosis and treatment of TB. Building upon this foundation, we further discussed intervention strategies involving chemical and immunological treatments for the increasingly critical issue of drug‐resistant TB and other forms of TB. Finally, we summarized TB prevention, diagnosis, and treatment challenges and put forward future perspectives. Overall, these findings provide valuable insights into the immunological aspects of TB and offer new directions toward achieving the WHO's goal of eradicating TB by 2035.

IntroductionThe Bacillus Calmette-Guérin (BCG) vaccine, currently used against tuberculosis (TB), exhibits inconsistent efficacy, highlighting the need for more potent TB vaccines.Materials and methodsIn this study, we employed reverse vaccinology techniques to develop a promising multi-epitope vaccine (MEV) candidate, called PP13138R, for TB prevention. PP13138R comprises 34 epitopes, including B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes. Using bioinformatics and immunoinformatics tools, we assessed the physicochemical properties, structural features, and immunological characteristics of PP13138R.ResultsThe vaccine candidate demonstrated excellent antigenicity, immunogenicity, and solubility without any signs of toxicity or sensitization. In silico analyses revealed that PP13138R interacts strongly with Toll-like receptor 2 and 4, stimulating innate and adaptive immune cells to produce abundant antigen-specific antibodies and cytokines. In vitro experiments further supported the efficacy of PP13138R by significantly increasing the population of IFN-γ+ T lymphocytes and the production of IFN-γ, TNF-α, IL-6, and IL-10 cytokines in active tuberculosis patients, latent tuberculosis infection individuals, and healthy controls, revealing the immunological characteristics and compare the immune responses elicited by the PP13138R vaccine across different stages of Mycobacterium tuberculosis infection.ConclusionThese findings highlight the potential of PP13138R as a promising MEV candidate, characterized by favorable antigenicity, immunogenicity, and solubility, without any toxicity or sensitization.

The safety of people and property in mountainous regions can be affected by landslides, and measurement of vertical ground formation is a vital component of landslide monitoring and forecasting. Over the past few years, UAV images have gained increasing popularity in the landslide monitoring; however, studies on the measurement accuracy of UAV image-based landslide surface deformation monitoring are relatively limited. In this study, a series of outdoor model tests are conducted to investigate the measurement accuracy of the digital difference-based software of CloudCompare, Global Mapper, and PolyWorks in UAV image-based vertical ground deformation measurement. The results indicate that when the resolution of the input UAV image is better than 3.0 cm/pixel, all the selected software can recognize the ground deformation zones with vertical ground deformation larger than 5.0 cm; under different vertical ground deformation scenarios, the vertical ground deformation measurement obtained with Global Mapper tends to be more accurate, and the medium error of the measurement ranges from 1.5 cm to 4.0 cm. Neither the medium error of measurement nor the standard deviation of measurement error is greatly affected by the magnitude of vertical ground deformation. The statistical analysis of measurement error suggests that the measurement errors of the selected software all follow normal distributions; then, based on the statistics of the measurement errors, the 95% confidence intervals of the vertical ground deformations obtained from the selected software could be obtained. Furthermore, Global Mapper software is applied to identify and measure the vertical deformation of the Dangchuan landslides in Heifangtai, and the results indicate that this software can accurately identify the landslide deformation area and locate the related ranges.

Summary: Lung cancer (LC) and tuberculosis (TB) are two major global public health problems, and the incidence of LC-TB is currently on the rise. Therefore effective clinical interventions are crucial for LC-TB. The aim of this review is to provide up-to-date information on the immunological profile and therapeutic biomarkers in patients with LC-TB. We discuss the immune mechanisms involved, including the immune checkpoints that play an important role in the treatment of patients with LC-TB. In addition, we explore the susceptibility of patients with LC to TB and summarise the latest research on LC-TB. Finally, we discuss future prospects in this field, including the identification of potential targets for immune intervention. In conclusion, this review provides important insights into the complex relationship between LC and TB and highlights new advances in the detection and treatment of both diseases.

Landslide forecasting and prediction is a frontier scientific issue that has received widespread attention in the field of geohazard prevention and control. The current research framework focuses on the deformation behavior characteristics and external dynamic factors of landslides and faces the dual bottleneck problems of low universality and low prediction accuracy.Based on the current research status, this paper systematically clarifies the connotation of the rheological-mechanical behavior and strength weakening effect of the sliding zone, explicates the evolution mechanism of the progressive failure of the landslide, summarizes the types of landslide prediction models, and introduces the typical models among them.Based on the comprehensively existing achievements, it is pointed out that the main problems of the current research are: ①the physical-mechanical models of landslide evolution are required to be extended; ②the prediction and forecasting models fail to fully integrate with landslide evolution and physical-mechanical model; ③the compatibility problem between physical-mechanical model prediction and multi-field monitoring data have not been practically solved. Given the above problems, the challenges of landslide prediction and forecasting models based on physical-mechanical processes are elaborated. Based on multidisciplinary integration and intersection, a new research strategy for landslide forecasting study is proposed. The new strategy requires the establishment of a physical-mechanical model of the landslide evolution process based on the structural properties and rheological-mechanical behavior of the slip zone. On this basis, a numerical forecasting mode for landslides is established by closely integrating real-time multi-field monitoring data that enables real-time dynamic updating of landslide physical-mechanical processes. This strategy is designed to achieve a theoretical and technical breakthrough.

BackgroundTuberculosis (TB) prevention and control among groups living together, such as students, workers, older adults in nursing homes, and prisoners, present many challenges due to their particular age and environmental factors, which can make them more susceptible to TB clusters with significant societal impact. This study aimed to evaluate a TB cluster outbreak epidemic in a university and provide suggestions for improving TB control strategies for groups living together.MethodsPulmonary TB screening and close-contact investigation were conducted using acid-fast staining, sputum culture, GeneXpert testing, tuberculin skin testing (TST), interferon-gamma release assay (IGRA), and chest computed tomography (CT). GraphPad Prism 9.5.1 was utilized for data analysis. Collected epidemic data were comprehensively analyzed by rate comparison.ResultsThe TB cluster outbreak epidemic was identified with an index case confirmed positive. The initial screening was conducted on potential close contacts of the index case, and the TST’s positive rate (diameter ≥ 5 mm) and strong positive rate (diameter ≥ 15 mm) among these close contacts were 65.60% (21/32) and 34.40% (11/32), respectively. Moreover, the latent TB infection (LTBI) rate (diameter ≥ 10 mm) was 43.75% (14/32), and the IGRA’s positive rate was 9.30% (3/32). Chest CT scans did not reveal any abnormalities. Surprisingly, 5 of the close contacts developed active TB in the second screening, accompanied by changes from negative to positive TST and/or IGRA results, after 3 months of follow-up. Accordingly, we expanded the screening scope to include another 28 general contacts. We found that the positive rate (78.00%, 25/32), strong positive rate (50.00%, 16/32), and LTBI rate (62.50%, 20/32) of the 32 close contacts were significantly higher than those of the additional general contacts (28.00%, 8/28; 14.3%, 4/28; 25.00%, 7/28), as indicated by p

BackgroundThe incidence of non-tuberculous mycobacterial pulmonary disease (NTM-PD) has increased in recent years. However, the clinical and immunologic characteristics of NTM-PD patients have received little attention.MethodsNTM strains, clinical symptoms, underlying diseases, lung CT findings, lymphocyte subsets, and drug susceptibility tests (DSTs) of NTM-PD patients were investigated. Then, the counts of immune cells of NTM-PD patients and their correlation were evaluated using principal component analysis (PCA) and correlation analysis.Results135 NTM-PD patients and 30 healthy controls (HCs) were enrolled from 2015 to 2021 in a certain tertiary hospital in Beijing. The number of NTM-PD patients increased every year, and Mycobacterium intracellulare (M. intracellulare), M. abscessus, M. avium, and M. kansasii were the major pathogens of NTM-PD. The main clinical symptoms of NTM-PD patients were cough and sputum production, and the primary lung CT findings were thin-walled cavity, bronchiectasis, and nodules. In addition, we identified 23 clinical isolates from 87 NTM-PD patients with strain records. The DST showed that almost all of M. abscessus and M. avium and more than half of the M. intracellulare and M. avium complex groups were resistant to anti-tuberculosis drugs tested in this study. M. xenopi was resistant to all aminoglycosides. M. kansasii was 100% resistant to kanamycin, capreomycin, amikacin, and para-aminosalicylic acid, and sensitive to streptomycin, ethambutol, levofloxacin, azithromycin, and rifamycin. Compared to other drugs, low resistance to rifabutin and azithromycin was observed among NTM-PD isolates. Furthermore, the absolute counts of innate and adaptive immune cells in NTM-PD patients were significantly lower than those in HCs. PCA and correlation analysis revealed that total T, CD4+, and CD8+ T lymphocytes played an essential role in the protective immunity of NTM-PD patients, and there was a robust positive correlation between them.ConclusionThe incidence of NTM-PD increased annually in Beijing. Individuals with bronchiectasis and COPD have been shown to be highly susceptible to NTM-PD. NTM-PD patients is characterized by compromised immune function, non-specific clinical symptoms, high drug resistance, thin-walled cavity damage on imaging, as well as significantly reduced numbers of both innate and adaptive immune cells.

BackgroundAbout a quarter of the world’s population with latent tuberculosis infection (LTBI) are the main source of active tuberculosis. Bacillus Calmette Guerin (BCG) cannot effectively control LTBI individuals from developing diseases. Latency-related antigens can induce T lymphocytes of LTBI individuals to produce higher IFN-γ levels than tuberculosis patients and normal subjects. Herein, we firstly compared the effects of M. tuberculosis (MTB) ag85ab and 7 latent DNA vaccines on clearing latent MTB and preventing its activation in the mouse LTBI model.MethodsA mouse LTBI model was established, and then immunized respectively with PBS, pVAX1 vector, Vaccae vaccine, ag85ab DNA and 7 kinds of latent DNAs (including rv1733c, rv2660c, rv1813c, rv2029c, rv2628, rv2659c and rv3407) for three times. The mice with LTBI were injected with hydroprednisone to activate the latent MTB. Then, the mice were sacrificed for the bacterial count, histopathological examination, and immunological evaluation.ResultsUsing chemotherapy made the MTB latent in the infected mice, and then using hormone treatment reactivated the latent MTB, indicating that the mouse LTBI model was successfully established. After the mouse LTBI model was immunized with the vaccines, the lung colony-forming units (CFUs) and lesion degree of mice in all vaccines group were significantly decreased than those in the PBS group and vector group (P

Bacille Calmette-Guérin (BCG) is the only approved vaccine for tuberculosis (TB) prevention worldwide. BCG has an excellent protective effect on miliary tuberculosis and tuberculous meningitis in children or infants. Interestingly, a growing number of studies have shown that BCG vaccination can induce nonspecific and specific immunity to fight against other respiratory disease pathogens, including SARS-CoV-2. The continuous emergence of variants of SARS-CoV-2 makes the protective efficiency of COVID-19-specific vaccines an unprecedented challenge. Therefore, it has been hypothesized that BCG-induced trained immunity might protect against COVID-19 infection. This study comprehensively described BCG-induced nonspecific and specific immunity and the mechanism of trained immunity. In addition, this study also reviewed the research on BCG revaccination to prevent TB, the impact of BCG on other non-tuberculous diseases, and the clinical trials of BCG to prevent COVID-19 infection. These data will provide new evidence to confirm the hypotheses mentioned above.

BackgroundWith the increasing incidence of tuberculosis (TB) and the shortcomings of existing TB vaccines to prevent TB in adults, new TB vaccines need to be developed to address the complex TB epidemic.MethodThe dominant epitopes were screened from antigens to construct a novel epitope vaccine termed HP13138PB. The immune properties, structure, and function of HP13138PB were predicted and analyzed with bioinformatics and immunoinformatics. Then, the immune responses induced by the HP13138PB were confirmed by enzyme-linked immunospot assay (ELISPOT) and Th1/Th2/Th17 multi-cytokine detection kit.ResultThe HP13138PB vaccine consisted of 13 helper T lymphocytes (HTL) epitopes, 13 cytotoxic T lymphocytes (CTL) epitopes, and 8 B-cell epitopes. It was found that the antigenicity, immunogenicity, and solubility index of the HP13138PB vaccine were 0.87, 2.79, and 0.55, respectively. The secondary structure prediction indicated that the HP13138PB vaccine had 31% of α-helix, 11% of β-strand, and 56% of coil. The tertiary structure analysis suggested that the Z-score and the Favored region of the HP13138PB vaccine were -4.47 88.22%, respectively. Furthermore, the binding energies of the HP13138PB to toll-like receptor 2 (TLR2) was -1224.7 kcal/mol. The immunoinformatics and real-world experiments showed that the HP13138PB vaccine could induce an innate and adaptive immune response characterized by significantly higher levels of cytokines such as interferon-gamma (IFN-γ), tumor necrosis factor-α (TNF-α), interleukin-4 (IL-4), and IL-10.ConclusionThe HP13138PB is a potential vaccine candidate to prevent TB, and this study preliminarily evaluated the ability of the HP13138PB to generate an immune response, providing a precursor target for developing TB vaccines.

BackgroundOur previous study developed a novel peptide-based vaccine, MP3RT, to fight against tuberculosis (TB) infection in a mouse model. However, the consistency between the immunoinformatics predictions and the results of real-world animal experiments on the MP3RT vaccine remains unclear.MethodIn this study, we predicted the antigenicity, immunogenicity, physicochemical parameters, secondary structure, and tertiary structure of MP3RT using bioinformatics technologies. The immune response properties of the MP3RT vaccine were then predicted using the C-ImmSim server. Finally, humanized mice were used to verify the characteristics of the humoral and cellular immune responses induced by the MP3RT vaccine.ResultsMP3RT is a non-toxic and non-allergenic vaccine with an antigenicity index of 0.88 and an immunogenicity index of 0.61, respectively. Our results showed that the MP3RT vaccine contained 53.36% α-helix in the secondary structure, and the favored region accounted for 98.22% in the optimized tertiary structure. The binding affinities of the MP3RT vaccine to the human leukocyte antigen (HLA)-DRB1*01:01 allele, toll-like receptor-2 (TLR-2), and TLR-4 receptors were -1234.1 kcal/mol, -1066.4 kcal/mol, and -1250.4 kcal/mol, respectively. The results of the C-ImmSim server showed that the MP3RT vaccine could stimulate T and B cells to produce immune responses, such as high levels of IgM and IgG antibodies, IFN-γ, TNF-α, and IL-2 cytokines. Results from real-world animal experiments showed that the MP3RT vaccine could stimulate the humanized mice to produce high levels of IgG and IgG2a antibodies and IFN-γ+ T lymphocytes. Furthermore, the levels of IFN-γ, IL-2, and IL-6 cytokines in mice immunized with the MP3RT vaccine were significantly higher than those in the control group.ConclusionMP3RT is a highly antigenic and immunogenic potential vaccine that can effectively induce Th1-type immune responses in silico analysis and animal experiments. This study lays the foundation for evaluating the value of computational tools and immunoinformatic techniques in reverse vaccinology research.

Puccinia triticina, which is the causative agent of wheat leaf rust, is widely spread in China and most other wheat-planting countries around the globe. Cultivating resistant wheat cultivars is the most economical, effective, and environmentally friendly method for controlling leaf rust-caused yield damage. Exploring the source of resistance is very important in wheat resistance breeding programs. In order to explore more effective resistance sources for wheat leaf rust, the resistance of 112 wheat accessions introduced from the U.S. National Plant Germplasm System were identified using a mixture of pathogenic isolates of THTT, THTS, PHTT, THJT and THJS which are the most predominant races in China. As a result, all of these accessions showed high resistance at seedling stage, of which, ninety-nine accessions exhibited resistance at adult plant stage. Eleven molecular markers of eight effective leaf rust resistance genes in China were used to screen the 112 accessions. Seven effective leaf rust resistance genes Lr9, Lr19, Lr24, Lr28, Lr29, Lr38 and Lr45 were detected, except Lr47. Twenty-three accessions had only one of those seven effective leaf rust resistance gene. Eleven accessions carried Lr24+Lr38, and 7 accessions carried Lr9+Lr24+Lr38, Lr24+Lr38+Lr45, Lr24+Lr29+Lr38 and Lr19+Lr38+Lr45 respectively. The remaining seventy-one accessions had none of those eight effective leaf rust resistance genes. This study will provide theoretical guidance for rational utilization of these introduted wheat accessions directly or for breeding the resistant wheat cultivars.

Powdery mildew of wheat (Triticum aestivum), caused by Blumeria graminis f.sp. tritici (Bgt), is a destructive disease that seriously threatens the yield and quality of its host. Identifying resistance genes is the most attractive and effective strategy for developing disease-resistant cultivars and controlling this disease. In this study, a wheat breeding line Yannong 99102-06188 (YN99102), an elite derivative line from the same breeding process as the famous wheat cultivar Yannong 999, showed high resistance to powdery mildew at the whole growth stages. Genetic analysis was carried out using Bgt isolate E09 and a population of YN99102 crossed with a susceptible parent Jinhe 13–205 (JH13–205). The result indicated that a single recessive gene, tentatively designated pmYN99102, conferred seedling resistance to the Bgt isolate E09. Using bulked segregant exome capture sequencing (BSE-Seq), pmYN99102 was physically located to a ~33.7 Mb (691.0–724.7 Mb) interval on the chromosome arm 2BL, and this interval was further locked in a 1.5 cM genetic interval using molecular markers, which was aligned to a 9.0 Mb physical interval (699.2–708.2 Mb). Based on the analysis of physical location, origin, resistant spectrum, and inherited pattern, pmYN99102 differed from those of the reported powdery mildew (Pm) resistance genes on 2BL, suggesting pmYN99102 is most likely a new Pm gene/allele in the targeted interval. To transfer pmYN99102 to different genetic backgrounds using marker-assisted selection (MAS), 18 closely linked markers were tested for their availability in different genetic backgrounds for MAS, and all markers expect for YTU103-97 can be used in MAS for tracking pmYN99102 when it transferred into those susceptible cultivars.

ABSTRACT Latent tuberculosis infection (LTBI) is the primary source of tuberculosis (TB) but there is no suitable detection method to distinguish LTBI from active tuberculosis (ATB). In this study, five antigens of Mycobacterium tuberculosis belonging to LTBI and regions of difference (RDs) were selected to predict Th1 and cytotoxic T lymphocyte (CTL) epitopes. The immunodominant Th1 and CTL peptides were identified in mouse models, and their performance in distinguishing LTBI from ATB was determined in mice and humans. Ten Th1 and ten CTL immunodominant peptides were predicted and synthesized in vitro. The enzyme-linked immunosorbent spot assay results showed that the combination of five Th1 peptides (area under the curve [AUC] = 1, P

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is a prevalent global infectious disease and a leading cause of mortality worldwide. Currently, the only available vaccine for TB prevention is Bacillus Calmette–Guérin (BCG). However, BCG demonstrates limited efficacy, particularly in adults. Efforts to develop effective TB vaccines have been ongoing for nearly a century. In this review, we have examined the current obstacles in TB vaccine research and emphasized the significance of understanding the interaction mechanism between MTB and hosts in order to provide new avenues for research and establish a solid foundation for the development of novel vaccines. We have also assessed various TB vaccine candidates, including inactivated vaccines, attenuated live vaccines, subunit vaccines, viral vector vaccines, DNA vaccines, and the emerging mRNA vaccines as well as virus-like particle (VLP)-based vaccines, which are currently in preclinical stages or clinical trials. Furthermore, we have discussed the challenges and opportunities associated with developing different types of TB vaccines and outlined future directions for TB vaccine research, aiming to expedite the development of effective vaccines. This comprehensive review offers a summary of the progress made in the field of novel TB vaccines.

To understand the effectiveness of hydrocarbon generation, expelling and retention capacities of coaly source rocks, carbonaceous mudstones and mudstones in coal layers and interlayers of different sedimentary environments and ages were selected to carry out the simulation experiments with a semi-open system operated at high tempera-ture and high pressure, and a corresponding model of evolution was established. With different depositional environments, the type Ⅱ2 coaly source rocks expelled oil in the oil generation window with gas generated. Therefore, they worked as source rocks for both of oil and gas. However, for the coaly source rocks of type Ⅲ kerogen, the generated oil was mainly retained during the oil generation window and basically did not expel. As a result, this type of source rock was regarded as source rocks of gas only. The conversion rate of hydrocarbon generation was mainly controlled by the type of organic matter, while the ability to expel hydrocarbons was controlled by lithology and organic matter abundance. For each unit mass of rock, coal rocks has much higher conversion rates than the carbonaceous mudstones and mudstones in their interlayers. In the full evolution stage of coal rock, both low-rank and high-rank coals had strong ability for hydrocarbon gas generation and oil-and-gas retention, which showed a good potential for coal bearing methane development.

BackgroundLatent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but there are no specific methods for diagnosing and preventing LTBI.MethodsDominant T and B cell epitopes predicted from five antigens related to LTBI and Mycobacterium tuberculosis region of difference (LTBI-RD) were used to construct a novel polypeptide molecule (PPM). Then, the physicochemical properties, secondary structure, tertiary structure of the PPM, and its binding ability to toll-like receptor 2 (TLR2) and TLR4 were analyzed by bioinformatics tools. Finally, immune stimulation and expression optimization of the PPM were carried out.ResultsFour helper T lymphocytes (HTL) epitopes, five cytotoxic T lymphocytes (CTL) epitopes, and three B cell epitopes were predicted and screened from five LTBI-RD related antigens. These epitopes were connected in series with linkers and adjuvants to construct a novel PPM termed C543P. The results indicated that antigenicity and immunogenicity scores of the C543P candidate were 0.936399 and 1.36469, respectively. The structural analysis results showed that the C543P candidate had good stability. Its secondary structure contained 43.6% α-helix, the Z-score after tertiary structure optimization was −7.9, and the Ramachandran diagram showed that 88.77% amino acid residues of the C543P candidate were in the allowable region. Furthermore, the C543P candidate showed an excellent affinity to TLR2 (−1091.7kcal/mol) and TLR4 (−1102.7kcal/mol). In addition, we also analyzed the immunological characteristics of the C543P candidate. Immune stimulation prediction showed that the C543P candidate could effectively activate T and B lymphocytes and produce high levels of Th1 cytokines such as IFN-γ and IL-2.ConclusionWe constructed a novel PPM with acceptable antigenicity, immunogenicity, stability, and ability to induce robust immune responses. This study provides a new diagnostic biomarker or peptides-based vaccine for LTBI diagnosis and prevention.

Abstract The contributions of the current analytical models on the prediction of the stability of the slope subjected to slide head toppling failure mechanisms, have always focused on the idealized geometry comprising regular blocks dipping into the slope face. Besides, the influence of groundwater and stabilizations from the lowermost block of the slope have been overlooked in the available literature. In this article, the analytical solutions that incorporates the kinematic mechanisms of the jointed rock slope under the influence of groundwater and stabilizing the lowermost block subjected to slide head toppling are derived based on the limit equilibrium. Furthermore, a real slide head toppling failure case history was studied to illustrate the effectiveness of the presented analytical solutions. The investigation results indicate that the presence of groundwater in the jointed rock slope, lowers the distributions of the normal and shear forces thereby inducing slide head toppling. Reinforcing the lowermost block of the slope, enhances the distributions of the normal and shear forces thus improving the stability of the jointed rock slope. The study results depict that the presented analytical solutions can provide an accurate and efficient stability analyses of the jointed rock slope subjected to slide head toppling failure mechanisms considering the presence of groundwater and stabilization effects.

The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic aperture radar (InSAR) is often adopted for measuring the ground deformation rate of the permafrost area, the effectiveness of which is, however, degraded in areas with geometric distortions in synthetic aperture radar (SAR) images. In this study, a method that integrates InSAR and the random forest method is proposed for an improved permafrost stability mapping on the Tibetan Plateau; to demonstrate the application of the proposed method, the permafrost stability mapping in a small area located in the central region of the Tibetan Plateau is studied. First, the ground deformation rate in the concerned area is studied with InSAR, in which 67 Sentinel-1 scenes taken in the period from 2014 to 2020 are collected and analyzed. Second, the relationship between the environmental factors (i.e., topography, land cover, land surface temperature, and distance to road) and the permafrost stability is mapped with the random forest method based on the high-quality data extracted from the initial InSAR analysis. Third, the permafrost stability in the whole study area is mapped with the trained random forest model, and the issue of data scarcity in areas where the terrain visibility of SAR images is poor or InSAR results are not available in permafrost stability mapping can be overcome. Comparative analyses demonstrate that the integration of the InSAR and the random forest method yields a more effective permafrost stability mapping compared with the sole application of InSAR analysis.

Background: Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but a preventive vaccine against LTBI is lacking. Methods: In this study, dominant helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), and B-cell epitopes were identified from nine antigens related to LTBI and regions of difference (RDs). These epitopes were used to construct a novel multiepitope vaccine (MEV) based on their antigenicity, immunogenicity, sensitization, and toxicity. The immunological characteristics of the MEV were analyzed with immunoinformatics technology and verified by enzyme-linked immunospot assay and Th1/Th2/Th17 cytokine assay in vitro. Results: A novel MEV, designated PP19128R, containing 19 HTL epitopes, 12 CTL epitopes, 8 B-cell epitopes, toll-like receptor (TLR) agonists, and helper peptides, was successfully constructed. Bioinformatics analysis showed that the antigenicity, immunogenicity, and solubility of PP19128R were 0.8067, 9.29811, and 0.900675, respectively. The global population coverage of PP19128R in HLA class I and II alleles reached 82.24% and 93.71%, respectively. The binding energies of the PP19128R-TLR2 and PP19128R-TLR4 complexes were −1324.77 kcal/mol and −1278 kcal/mol, respectively. In vitro experiments showed that the PP19128R vaccine significantly increased the number of interferon gamma-positive (IFN-γ+) T lymphocytes and the levels of cytokines, such as IFN-γ, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-10. Furthermore, positive correlations were observed between PP19128R-specific cytokines in ATB patients and individuals with LTBI. Conclusions: The PP19128R vaccine is a promising MEV with excellent antigenicity and immunogenicity and no toxicity or sensitization that can induce robust immune responses in silico and in vitro. This study provides a vaccine candidate for the prevention of LTBI in the future.

This article introduces a drone image stitching based on mesh-guided deformation and ground constraint, which can closely match the characteristics of images and achieve precise registration and acquire ideal stitching effect. The traditional methods use the homography model to align the image, which causes artifacts in the result of stitching the images with parallax. To overcome this situation, the image is divided into meshes and the mesh vertices of the target image are used to guide the warping. A new energy function is designed to represent the deformation characteristics of the image. We propose a new alignment term by using local homography and a local scale term by using the edge information of the mesh. The established mesh-guided deformation model can overcome image parallax caused by some external factors and eliminate the ghostly parts of the result. Moreover, imaged scene is not effectively planar and some fluctuations exist in the scene of the images, which will distort the stitching result. We propose a ground constraint with the ground plane as the main plane to reduce projection distortions in non-overlapping areas between images. Finally, the method of creating groundtruth is proposed, which can evaluate the naturalness of results and make comparison more reasonable. Several sets of challenging drone images are tested, and the experimental results show that our stitching system has good results.

Abstract Fundamentally, river plume dynamics are controlled by the buoyancy due to river effluent and mixing induced by local forcing such as winds and tides. Rarely the influence of far-field internal waves on the river plume dynamics is documented. Our 5-day fix-point measurements and underway acoustic profiling identified hydrodynamic processes on the dispersal pathway of the Pearl River plume. The river plume dispersal was driven by the SW monsoon winds that induced the intrusion of cold water near the bottom. The river effluent occupied the surface water, creating strong stratification and showing on-offshore variability due to tidal fluctuations. However, intermittent disruptions weakened stratification due to wind mixing and perturbations by nonlinear internal waves (NIWs) from the northern South China Sea (NSCS). During events of NIW encounter, significant drawdowns of the river plume up to 20 m occurred. The EOF deciphers and ranks the contributions of abovementioned processes: (1) the stratification/mixing coupled by wind-driven plume water and NIWs disruptions (81.7%); (2) the variation caused by tidal modulation (6.9%); and (3) the cold water intrusion induced by summer monsoon winds (5.1%). Our findings further improve the understanding of the Pearl River plume dynamics influenced by the NIWs from the NSCS.

The goal of unmanned aerial vehicle (UAV) image mosaicking is to create natural- looking mosaics without artifacts due to the parallax of the image and relative camera motion. UAV remote sensing is a low-altitude technology and the UAV imaged scene is not effectively planar, yielding parallax on the images. Moreover, when an object in 3-D is mapped to an image plane, different surfaces have different projections. These projections vary with the viewpoint in a sequence of UAV images, which causes artifacts near some tall buildings in the stitched images. To solve these problems, we propose a novel stitching method based on multiregion guided local projection deformation, which can significantly reduce ghosting due to these projections vary with the viewpoint and the parallax. In the proposed method, the image is initially meshed and each cell corresponds to a local homography for image matching, which can reduce misalignment artifacts in the results compared with 2-D projective transforms or global homography. Then, we divide the overlapping regions of input images into multiple regions by classifying feature points. The partitioned regions which serve well scene constraints, are employed to guide the calculation of local homography. Specifically, instead of calculating local homography by the distance between all the feature points in the image and the vertices of the grid, we propose a strategy where multiple regions have different weights for calculating local homography, which can significantly reduce ghosting near some tall buildings. The benefits of the proposed approach are demonstrated using a variety of challenging cases.

Background. Several studies have shown that lymphocyte subsets can mediate the occurrence of osteoporosis (OP); however, the predictive ability of lymphocyte subsets in senile OP has not been elucidated. Purpose. To investigate the ability of lymphocyte subsets to predict senile osteoporosis (OP). Methods and Materials. This study included 44 patients with senile OP and 44 without OP. Dual-energy X-ray absorptiometry (DEXA) was used to determine bone mineral density (BMD). Flow cytometry was used to analyze the absolute counts of the lymphocyte subsets and cytokine levels. Finally, the correlation between BMD and lymphocyte subset counts in the two groups was analyzed. Results. There were no significant differences in age, sex, or weight between the OP and non-OP groups. The absolute counts of total T lymphocytes and CD8+ T lymphocytes in the OP group were significantly lower than those in the non-OP group. The levels of IFN-γ or TNF-α in the OP group were significantly higher or lower, respectively, than those in the non-OP group. PCA showed that age, BMI, total T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes, and B lymphocytes were the principal components of senile OP. The linear regression equation showed that BMD of the right femoral neck significantly decreased with a decline in CD8+ T lymphocyte counts. Conclusion. BMD decreased with a decrease in CD8+ T lymphocytes. The mechanism by which lower lymphocyte subsets lead to lower BMD may be related to abnormal bone metabolism caused by immune aging. Therefore, we considered that CD8+ T lymphocytes could be used to predict the incidence of senile OP.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO’s End TB Strategy.

Tuberculosis (TB) is one of humanity’s three major infectious diseases. Diabetes mellitus (DM) is a metabolic disease characterized by hyperglycemia due to impaired insulin secretion or impaired insulin function. It has been reported that DM is a primary risk factor for TB disease. Given the increasing public health threat to people’s health, more and more studies have focused on diabetes complicated by TB. Hyperglycemia can affect the function of human immune cells, promote primary infections and reactivation of TB, and increase the susceptibility and severity of TB. However, the immunological mechanism behind it is still not clear. By reviewing the related articles on tuberculosis complicated with diabetes published in recent years, this paper expounds on the effect of hyperglycemia on innate immunity and adaptive immunity of patients with TB. This review provides new insights for elucidating the immunological mechanism of TB complicated with DM and lays the foundation for finding potential targets for preventing and treating TB combined with DM.

This study was aimed at screening differentially expressed genes (DEGs) and exploring the potential immune mechanism induced by the Bacillus Calmette-Guerin (BCG) vaccine in a humanized mouse model. Candidate DEGs between mice vaccinated with BCG or injected with PBS were identified through transcriptomics, and their biological functions, signaling pathways, and protein interaction networks were analyzed through bioinformatics. A total of 1035 DEGs were identified by transcriptomics: 398 up-regulated and 637 down-regulated. GO analysis indicated that these DEGs were significantly enriched in cell adhesion, oxygen transport, receptor complex, carbohydrate binding, serine-type endopeptidase activity, and peroxidase activity terms. KEGG analysis indicated that these DEGs were involved in the Rap1 signaling pathway, axon guidance, PI3K-Akt signaling pathway, natural killer cell mediated cytotoxicity, and cytokine-cytokine receptor interaction. Protein interaction network analysis demonstrated that the Myc, Vegfa, and Itgb3 proteins had the highest aggregation degree, aggregation coefficient, and connectivity. The BCG vaccine induced 1035 DEGs in humanized mice. Among them, the differentially expressed down-regulated genes myc and itgb3 involved in the PI3K-Akt signaling pathway may play essential roles in the immune mechanism of the BCG vaccine.

Tuberculosis (TB) is a serious public health problem worldwide. The combination of various anti-TB drugs is mainly used to treat TB in clinical practice. Despite the availability of effective antibiotics, effective treatment regimens still require long-term use of multiple drugs, leading to toxicity, low patient compliance, and the development of drug resistance. It has been confirmed that immune recognition, immune response, and immune regulation of Mycobacterium tuberculosis (Mtb) determine the occurrence, development, and outcome of diseases after Mtb infection. The research and development of TB-specific immunotherapy agents can effectively regulate the anti-TB immune response and provide a new approach toward the combined treatment of TB, thereby preventing and intervening in populations at high risk of TB infection. These immunotherapy agents will promote satisfactory progress in anti-TB treatment, achieving the goal of “ultra-short course chemotherapy.” This review highlights the research progress in immunotherapy of TB, including immunoreactive substances, tuberculosis therapeutic vaccines, chemical agents, and cellular therapy.

As an ancient infectious disease, tuberculosis (TB) is still the leading cause of death from a single infectious agent worldwide. Latent TB infection (LTBI) has been recognized as the largest source of new TB cases and is one of the biggest obstacles to achieving the aim of the End TB Strategy. The latest data indicate that a considerable percentage of the population with LTBI and the lack of differential diagnosis between LTBI and active TB (aTB) may be potential reasons for the high TB morbidity and mortality in countries with high TB burdens. The tuberculin skin test (TST) has been used to diagnose TB for > 100 years, but it fails to distinguish patients with LTBI from those with aTB and people who have received Bacillus Calmette–Guérin vaccination. To overcome the limitations of TST, several new skin tests and interferon-gamma release assays have been developed, such as the Diaskintest, C-Tb skin test, EC-Test, and T-cell spot of the TB assay, QuantiFERON-TB Gold In-Tube, QuantiFERON-TB Gold-Plus, LIAISON QuantiFERON-TB Gold Plus test, and LIOFeron TB/LTBI. However, these methods cannot distinguish LTBI from aTB. To investigate the reasons why all these methods cannot distinguish LTBI from aTB, we have explained the concept and definition of LTBI and expounded on the immunological mechanism of LTBI in this review. In addition, we have outlined the research status, future directions, and challenges of LTBI differential diagnosis, including novel biomarkers derived from Mycobacterium tuberculosis and hosts, new models and algorithms, omics technologies, and microbiota.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, which infects more than 23% of the world’s population. With the emergence of drug-resistant TB (DR-TB) and latent TB infection (LTBI), rapid diagnosis of DR-TB and LTBI has become a challenge for the prevention and control of TB. Herein, we highlight these challenges and discuss emerging clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostics in TB detection. Currently, the clinical diagnosis of M. tuberculosis infection mainly depends on pathogenic and molecular biological methods, including sputum smear, sputum culture, and Xpert. Although CRISPR-based diagnostics have not been applied to the clinical diagnosis of TB, they have shown exciting preponderances in TB diagnosis compared with traditional methods, including higher sensitivity, less sample input, and shorter turnaround time. CRISPR-based diagnostics represent a potential tool to address the challenges and natural weaknesses associated with traditional TB diagnosis methods. Based on the currently available data, we suggest that future CRISPR-based TB diagnostics should be developed in the direction of automation, modularization, diversification, and intelligence. By combining the CRISPR platform with various systems, such as microfluidic chips, droplet microfluidics, electrochemical techniques, and optical systems, the specificity and sensitivity of TB diagnosis may be revolutionized.

In this study, spatial coherence tunable random lasing is proposed by designing a random laser with separate coupling configuration between the gain medium and the scattering part. By using the polymer dispersion liquid crystal (PDLC) film with tunable scattering coefficient for supplying random scattering feedback and output modification, red, green and blue random lasers are obtained. By applying or removing electric field to manipulate the scattering intensity of the PDLC film, intensity and spatial coherence of these random lasing are then switched between the high or low state. This work demonstrates that controlling the external scattering intensity is an effective method to manipulate the spatial coherence of random lasing.

Background: Multidrug-resistant pulmonary tuberculosis (MDR-PTB) has become a major cause of high morbidity and mortality related to TB. Conventional drug regimens are ineffective for the treatment of MDR-PTB patients with cavities. This study aimed to evaluate the clinical efficacy and safety of one-way endobronchial valves (EBVs) for the treatment of cavities in MDR-PTB patients. Methods: MDR-PTB patients with positive sputum cultures, sputum smears, and cavities were treated with EBVs in the drainage bronchus of the pulmonary cavity between November 2013 and March 2018. The participants comprised those who had failed previous anti-tuberculosis therapy, as determined by drug susceptibility testing. Results: Thirty-five MDR-PTB patients were included, three of whom were lost during follow-up. The size of the lung cavity was reduced in all of the patients after EBV implantation, including the three lost to follow-up. In the remaining 32 patients, the sputum culture conversion (SCC) rate reached 100%, and the cavity closure rate was 68.8%. There were no significant differences in the cavity closure rate between patients aged ≤40 and >40 years, between the upper and lower lobes, or between the use and non-use of linezolid groups (p > 0.05). Interestingly, the cavity closure rate was higher in women than in men (p = 0.005). Moreover, the cavity closure rate correlated with the time to SCC (correlation coefficient, 0.8933; p < 0.0001). There were no severe adverse events in the patients treated with EBV implantation. Conclusion: EBV installation is effective and safe for the treatment of cavities in MDR-PTB patients. The efficacy of EBV treatment may not be affected by age, disease course, or the location of the lung lobe in the cavity.

Feature matching, which refers to the establishment of accurate correspondence between two sets of feature points, plays an important role in the field of computer vision and remote sensing. Focusing on the characteristics of remote sensing images, this paper proposes a new algorithm for robust feature matching based on non-rigid transformation, which formulates the feature matching problem as a probabilistic model. Specifically, we first utilize the scale-invariant feature transform to establish the initial feature correspondences between an image pair, and the thin-plate spline is adopted for non-rigid transformation modeling, where a local geometric constraint is introduced to maintain local structures of neighboring feature points after the transformation. Under the Bayesian framework, we seek a maximum a posteriori solution of our model by using the expectation-maximization algorithm. In addition, without sacrificing the matching accuracy, we provide a fast implementation to reduce the computational complexity of the algorithm based on sparse approximation. We verify the performance of our method on a large number of remote sensing images, and the qualitative and quantitative results reveal its superiority over the state-of-the-art.

Building segmentation for Unmanned Aerial Vehicle (UAV) imagery usually requires pixel-level labels, which are time-consuming and expensive to collect. Weakly supervised semantic segmentation methods for image-level labeling have recently achieved promising performance in natural scenes, but there have been few studies on UAV remote sensing imagery. In this paper, we propose a reliable label-supervised pixel attention mechanism for building segmentation in UAV imagery. Our method is based on the class activation map. However, classification networks tend to capture discriminative parts of the object and are insensitive to over-activation; therefore, class activation maps cannot directly guide segmentation network training. To overcome these challenges, we first design a Pixel Attention Module that captures rich contextual relationships, which can further mine more discriminative regions, in order to obtain a modified class activation map. Then, we use the initial seeds generated by the classification network to synthesize reliable labels. Finally, we design a reliable label loss, which is defined as the sum of the pixel-level differences between the reliable labels and the modified class activation map. Notably, the reliable label loss can handle over-activation. The preceding steps can significantly improve the quality of the pseudo-labels. Experiments on our home-made UAV data set indicate that our method can achieve 88.8% mIoU on the test set, outperforming previous state-of-the-art weakly supervised methods.

Coronavirus disease 2019 (COVID-19), which broke out at the end of 2019, is a global pandemic and seriously threatens human health. Vaccination is the most effective way to prevent and control COVID-19. At present, more than 13 COVID-19 vaccines have been urgently authorized for use, but the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has brought unprecedented challenges to the protective efficiency of these COVID-19 vaccines. In particular, the recent emergence of Delta and Omicron variants, which are rapidly spreading worldwide, may bring many challenges to the medical systems. Interestingly, previous studies have shown that the Bacillus Calmette-Guerin (BCG) vaccine used to prevent tuberculosis can induce non-specific trained immunity, protecting against infectious diseases caused by respiratory viruses. Therefore, there is a hypothesis that BCG plays an essential role in reducing the incidence, severity, hospitalization, and mortality of COVID-19 and enhancing the protection efficiency of the COVID-19 vaccine. To confirm this hypothesis, 56 clinical trials have been conducted globally to assess BCG’s protective effectiveness against COVID-19 infection. Herein, this review discussed the trained immunity induced by BCG and its underlying mechanisms and summarised BCG’s latest research progress in preventing COVID-19, especially the ongoing clinical trials. We hope this review will provide new strategies for fighting against COVID-19.