Deep learning using an end-to-end convolutional neural network (ConvNet) has been applied to several electroencephalography (EEG)-based brain–computer interface tasks to extract feature maps and classify the target output. However, the EEG analysis remains challenging since it requires consideration of various architectural design components that influence the representational ability of extracted features. This study proposes an EEG-based emotion classification model called the multi-kernel temporal and spatial convolution network (MultiT-S ConvNet). The multi-scale kernel is used in the model to learn various time resolutions, and separable convolutions are applied to find related spatial patterns. In addition, we enhanced both the temporal and spatial filters with a lightweight gating mechanism. To validate the performance and classification accuracy of MultiT-S ConvNet, we conduct subject-dependent and subject-independent experiments on EEG-based emotion datasets: DEAP and SEED. Compared with existing methods, MultiT-S ConvNet outperforms with higher accuracy results and a few trainable parameters. Moreover, the proposed multi-scale module in temporal filtering enables extracting a wide range of EEG representations, covering short- to long-wavelength components. This module could be further implemented in any model of EEG-based convolution networks, and its ability potentially improves the model’s learning capacity. The brain—computer interface (BCI) technology is a technology that acquires brain signals and interprets neuronal information into the desired action. BCI has been used in various medical and non-medical applications , such asTherefore, the capability of developed EEG methods should consider several aspects, including interpretability, performance, and usability for real-world applications. Ascertaining methods aim to understand complex EEG signals derived from the human brain extracting their informative features and classifying them. Conventionally, beneficial knowledge is extracted from raw EEG signals by manually defined features and reported through statistical reports. For instance, frequency bands in slow to hyperactivity brain waves reflect the distinction in the intensity of emotions . PositivRecently, many studies have applied deep learning (DL) to extract and interpret EEG signals. An end-to-end convolutional neural network (ConvNet or CNN) is constructed on the basis of a shared-weight architecture that can reasonably learn joint optimization of feature extraction and classification. The appropriate design, such as the layer’s depth and width, kernel size, and optimizer, becomes an essential consideration that significantly affects the representational ability and classification performance. It has been demonstrated that deep and shallow convolution networks can automatically extract essential temporal and spatial information from raw EEG signals . NeverthAccordingly, achieving good EEG data analysis performance using DL-based techniques requires a wide range of useful representations while preserving optimized trainable parameters. This study proposes an architecture called multi-kernel temporal and spatial convolution for EEG-based emotion classification. We present (1) multi-kernel learning for temporal convolution and (2) filter recalibration with a lightweight gating mechanism. The proposed model makes the classification process more efficient by factoring the kernel into a series of operations to capture various short and long patterns. Then, separable convolution is applied for spatial learning by considering each channel separately and convolving over electrode channels. Moreover, we recalibrate weights after temporal and spatial convolving to utilize the limited data available. We compare our model with existing techniques and investigate task accuracy by conducting classification experiments on BCI datasets.In the classification of emotions learned from EEG signals, feature extraction is an essential step in which these emotions are represented and categorized into the desired labels. Conventionally, EEG features can be categorized into three domains: time, frequency, and time–frequency domains . The timMoreover, in addition to frequency or temporal features, spatial features can be extracted using multi-channel electrodes. Each part of the human brain can convey different information through the asymmetric hemisphere. For example, the frontal lobe is associated with reasoning, parts of speech, and emotion. The temporal lobe is associated with the perception and recognition of auditory stimuli, whereas the occipital lobe is responsible for vision. For this reason, EEG signals require a method that can manipulate both temporal and spatial information for feature learning and classification. A common spatial pattern (CSP)  is a matT, time) and spatial dimensions . Then, the convolutional operation is applied to extract informative features through three types of filtering, i.e., convolving across time, space, and both time and space, respectively, as shown in k represents a specific kernel size, is applied to both time and channel domains. In addition, there is a need to determine the suitable size for learning various representations and distinctions. Typically, the kernel size is manually defined and used in feature extractors in CNNs. A single-scale kernel might be trapped with a limited amount of representations. Especially for EEG feature extraction, the learning of representations needs to be diverse and capable of effectively extracting temporal and spatial features.In recent years, the use of end-to-end CNNs (ConvNets) has been introduced for effective and reasonable EEG analysis in feature extraction and classification tasks. First, the raw EEG signals are measured in microvolts  has been used for EEG decoding with a single-layer temporal filter, and then, the output is fed into multi-layer spatial convolution and pooling layers, as shown in Moreover, another critical aspect that affects informative features and learning ability is reducing the network size while maintaining good performance. One of the simpler networks is a separable convolution that enables networks to construct informative features by fusing both spatial and channel information. The operation consists of spatial mapping independently performed over each input channel and feed-forward mapping to project the output onto a new feature space. These operations enable networks to construct informative features by fusing spatial and temporal information within local receptive fields at each layer. A compact CNN for EEG-based BCI, called EEGNet, is introduced to construct an EEG-specific model with separable convolution . The numThis study proposes an end-to-end CNN called multi-kernel temporal and spatial convolution (MultiT-S ConvNet) for EEG-based emotion recognition. The proposed model enables multi-scale representation learning and improves classification performance. The model consists of three parts, namely, a temporal learner, spatial learner, and classifier, which simultaneously learn discriminative representations in the time and electrode channel dimensions. The model architecture is depicted in In this study, we hypothesize that multi-kernel filters can improve temporal representations learned from raw EEG data. Considering the kernel design of temporal convolution, the larger size can learn higher resolutions in the time domain but necessitates high computational costs. On the other hand, a smaller kernel size essentially learns low-level features or shorter temporal patterns in the time domain and can reduce computational costs. Multi-scale convolution kernels combining long and short patterns are applied by factoring a kernel into various kernel sizes that would independently convolve and map them in order. Learning a wide range of representations while avoiding high computational costs can improve the performance of EEG classification. The main advantage of this architecture is significant quality gain at a modest increase in computational requirements compared with shallower and narrower architectures. Accordingly, we specifically adopted four kernels of length 25 ms (=5 samples under the sampling rate of 200 Hz), 50 ms (=10 samples), 100 ms (=20 samples), and 200 ms (=40 samples). These choices were based on four frequency bands, namely, theta (4–7 Hz), alpha (8–12 Hz), beta (13–32 Hz), and gamma (>33 Hz), extensively used to characterize brain states/activities. The sampling rate is also considered because wavelengths can be captured with the same time scale, even from different datasets. These multi-kernels can capture an extensive range of representations in EEG signals. The larger kernel size can learn various informative features, along longer temporal patterns. Meanwhile, the smaller kernel size specifically extracts shorter temporal patterns.T is 400 data points for the SEED dataset) based on the change in emotion over time. We duplicate the input into four modules and convolve them using four different kernel sizes: The raw EEG signals in For each time step  is further applied to adaptively recalibrate the gathering of informative feature responses by explicitly modeling interdependencies between feature maps . Adding Moreover, after spatial processing in The outputs from the previous module are flattened into one vector representing all extracted features and linearly transformed into classification logits with an FCN. For binary classification, the final layer unit is 1. The loss function is binary cross-entropy, and the activation function is a sigmoid function. While 3 classes classification, the final layer unit is 3. The loss function is categorical cross-entropy, and the activation function is a softmax function. The final output is a discrete emotion label with probability.To validate the method’s performance, feature extractability, and classification accuracy, we examined and compared it with existing methods. The experiments and results consist of subject-dependent and independent classification on the SEED and DEAP datasets.This study conducted experiments on two open-access datasets: SEED (SJTU emotion EEG dataset)  and DEAPThis study conducted SEED experiments in a three-class classification, including positive, neutral, and negative labels, and a binary classification with less complexity and fewer data considered positive and negative labels. On the other hand, DEAP employed 2D models rated by subjects caused discrepancies between movie types and real subject emotions. To simplify the problem, we investigate a binary classification of valence and arousal scores with positive and negative labels.In baseline experiments, the PSD with four bands was used as extracted features, along with ML classifiers. The baseline classifiers related to EEG analysis comprise the KNN, RF, and FCN. These models were tuned by grid search with the optimal hyperparameters selected, resulting in the most accurate performance. Accordingly, the number of neighbors for the KNN classification is set to 21. The number of RF trees is set to 100. The FCN has 2 hidden layers with 100 nodes, which are then forwarded to the output layer. The activation function is the logistic sigmoid function. Adam optimization is applied while training the FCN model.Moreover, we compare the performance of MultiT-S ConvNet against existing models, including the Deep ConvNet, Shallow ConvNet, and EEGNet models. The Deep ConvNet architecture  consistsAll models were examined on the subject-dependent and independent classification of the SEED and DEAP datasets. In the subject-dependent experiments, 5-fold cross-validation was applied, experimenting with different partitions of 80% training data and 20% test data; 30% of the training data were held out for validation of free parameters, and the model parameters were optimized on the basis of the remaining 70%. Moreover, the validation set was randomly picked on the desired subject, and the 5-fold cross-validation was applied to all subjects. For the subject-independent experiment, we applied the leave-one-out cross-validation to access model performance. The model was trained using data from all but one subject and tested on the held-out subject; 30% of the training data were randomly selected for free-parameter validation without balancing among subjects.The performance metric was classification accuracy. Moreover, we show the chance level, which is the obtained accuracy when consistently predicting the majority class. To verify multiple comparisons, analysis of variance (ANOVA) was applied to determine whether the means in the desired group were significantly different. Then, Dunnett’s test was used to observe the many-to-one comparisons with our proposed method.p < 0.01). Moreover, MultiT-S ConvNet achieves the highest accuracy in all experiments. For two-class and three-class classifications, the subject-dependent results are 95.2 ± 3.2% and 86.0 ± 5.3% respectively, whereas the subject-independent results are 75.1 ± 8.4% and 54.6 ± 6.8% respectively. RF outperforms other baseline techniques by a significant level (p < 0.05). The accuracy of all DL models is significantly higher than KNN (p < 0.01) and FCN (p < 0.05) models. However, there is no statistical difference among deep learning models (p > 0.05), except in three-class and subject-independent experiments, where the accuracy of MultiT-S ConvNet is significantly higher than that of EEGNet (p < 0.05).For the SEED dataset experiments, we performed two-class and three-class classification to study both subject-dependent and subject-independent results. The two-class experiment uses two-thirds of the three-class dataset to simplify the problem’s complexity and additional investigation. Their accuracy is shown in p < 0.01). Nevertheless, these chance levels could not be achieved in the subject-independent experiments.Using the DEAP dataset, we conducted four experiments of valence and arousal binary classification on both subject dependence and subject independence. The classes were defined by emotion scores, where 1 to 4 is a negative class, and 5 to 9 is a positive class. DEAP dataset’s results are shown in p < 0.05). For EEGNet with multi-kernel temporal convolution, the number of trainable parameters increases from 13,537 to 16,177, but it achieves a significantly better accuracy of 74.00% than the original EEGNet of 70.15% (p < 0.01). However, there is no significant difference between Shallow ConvNet with and without multi-kernel convolution (p > 0.05). Moreover, we trained the MultiT-S ConvNet model without SE blocks to observe their effects on the learning performance. The accuracy of our model without SE Blocks decreases from 75.13% to 73.95% (p < 0.05).To verify the effectiveness of our temporal filtering, we further investigate the effect of temporal convolution on the other CNN models. Based on the first blocks of each model in In this study, the accuracy performance was examined using SEED and DEAP, which are well-known EEG emotion datasets. In addition, existing models and our proposed model were implemented with similar settings, including data segmentation, pre-processing, parameter tuning, and evaluation metrics, to ensure the reliability of model performance comparison. The experiments and results demonstrate that all ConvNets with appropriate design choices can outperform traditional approaches in terms of accuracy performances in all classification experiments. Moreover, this study compares MultiT-S ConvNet against existing ConvNet models in terms of accuracy performance in EEG-based emotion classification, as shown in p < 0.01) in both subject-dependent and independent experiments. For the DEAP dataset, only the ConvNet-based techniques reached the chance level (p < 0.01) in the subject-dependent experiments. In contrast, for the DEAP dataset, none of the models could surpass the chance level in subject-independent experiments. Many studies using the DEAP dataset have mainly conducted subject-dependent experiments because the data distribution of each subject in this dataset is highly diverse and varied. Observing the topoplots of PSD features in 4 frequency bands by human eyesight shows that the SEED dataset plots can be distinguished, whereas the DEAP dataset plots are very similar. In terms of subject-dependent and subject-independent learning, subject-dependent performance outperforms subject-independent performance significantly in all experiments. Consequently, the individual distribution directly affects learning performance. Moreover, our results are comparable and consistent with existing studies in terms of average accuracy [According to the result, the SEED dataset is more uncomplicated to classify than the DEAP dataset because it contains different sources of emotional labels and the cleanliness of the signals. For the emotion states, the SEED dataset uses the movie types, whereas the DEAP dataset uses a subject questionnaire. This ambiguity directly affects the classification performance and trustworthiness of each dataset. Based on the SEED dataset results, all the obtained accuracy reached the chance level  network on a three-back task , and emoIn conclusion, a well-designed end-to-end convolution network is a promising feature extraction and classification tool in EEG-based emotion analysis. We proposed multi-kernel filtering to increase the variation of temporal representations and further recalibrate both temporal and spatial features using the lightweight gating mechanism. The results show that our MultiT-S ConvNet outperforms the traditional and existing models. However, there are some limitations in the current study that could be addressed in future research. This study focused on discrete emotion recognition with the type of movie stimuli. In the future, the applicability of the MultiT-S network will be explored in brain disease recognition, such as epilepsy and Alzheimer’s disease. In addition, this proposed model could be further developed to allow detecting and analyzing dynamic changes in EEG signals over time. Ultimately, our module could be added to any model of EEG-based convolution networks and its ability could improve the learning effect of other existing models when there is a limited dataset.


By approximately 70-years-old, two out of three Americans experience some cognitive impairment . Cognitive abilities that often decline with age include working and short-term memory , both important for encoding and retaining information . Depending on severity, affected individuals may face difficulties performing daily tasks. Beyond biological mechanisms, Self-Life Acceptance  and personality  may relate to variations in cognitive status. We collected measures of Self-Life Acceptance, Neuroticism, and Openness to investigate their relations to older adults’ cognitive status . The sample was comprised of older adults clearly experiencing memory difficulties . In a hierarchical regression, the interaction between Self-Life Acceptance and Neuroticism predicted higher cognitive status. Deconstructing this effect, for older people with low-to-moderate Neuroticism, having worse cognitive status was related to greater feelings of Self-Life Acceptance. These individuals show resilience; when cognitive status is worse, acceptance of oneself and life appears to ‘kick in’ allowing individuals to maintain well-being in the face of memory difficulties. Self-Life Acceptance, however, is not present for those high in Neuroticism. In a second regression, less Self-Life Acceptance and higher Openness were also related to better cognitive status. Our findings show psychosocial factors can predict variations in cognitive status. This work provides a window into how older individuals with different personality traits and varying capacity for resilience cope with memory loss.


Bladder calcification is a rare presentation that was first interpreted to be related to a urea-splitting bacterial infection. Aside from infection, other hypotheses such as schistosomiasis, tuberculosis, cancer, and cytokine-induced inflammatory processes have also been reported. Severe coronavirus disease 2019 (COVID-19) is known for its provoking cytokine storm and uninhibited systematic inflammation, and calcification over the coronary artery or lung has been reported as a long-term complication.We presented a 68 years old man who had persistent lower urinary tract symptoms after recovery from severe COVID-19. No urea-splitting bacteria were identified from urine culture.Cystoscopy examination revealed diffuse bladder mucosal and submucosa calcification.Transurethral removal of the mucosal calcification with lithotripsy.The patient’s lower urinary tract symptoms improved, and stone analysis showed 98% calcium phosphate and 2% calcium oxalate. No newly formed calcifications were found at serial follow-up.Diffuse bladder calcification may be a urinary tract sequela of COVID-19 infection. Patients with de novo lower urinary tract symptoms after severe COVID-19 should be further investigated. Bladder calcification is a rare condition that describes calcification of either the bladder mucosal or submucosal layer. The causative pathogens are urease-producing bacteria, of which Corynebacterium urealyticum (CU) is commonly reported. Schistosomiasis, tuberculosis, cancer, and cytokine-induced inflammatory processes have also been reported to be associated with calcium deposition. As more coronavirus disease 2019 (Covid-19) studies have been published during the pandemic, growing evidence suggests a strong correlation between severe Covid-19 and a tremendously provoked cytokine storm. As more observational studies have found that patients with Covid-19 may report lower urinary tract symptoms due to viral cystitis, the manifestation of the urinary tract system in patients with Covid-19 is of great interest to the community. Here, we report a patient who had newly developed frequency and nocturia after severe Covid-19, and was diagnosed with bladder calcification.A 68-year-old man presented to our urology clinic with urinary frequency and nocturia. He had hypertension and atrial fibrillation and was treated with amiodarone (200 mg QD). Two months prior, he had intermittent fever and productive cough and was diagnosed with severe Covid-19. No history of Covid-19 vaccination was contributed before. Rapid progression to acute respiratory distress syndrome was observed  was isolated from urine culture. During cystoscopy, among all quadrants of the bladder wall, there were white and flaky submucosal calcifications, and some caused mucosal breaks and stone formation . Third, no CU aimed antibiotics were administered during the treatment, and no progression of bladder wall encrustation was noted in two cystoscopy exams at one month interval.Our interpretation that bladder calcifications may be related to Covid-19 was based on the following clinical findings. First, the patient had no history of urolithiasis and presented with de novo urinary frequency and nocturia after severe Covid-19 infection. Moreover, the urine was neutral, and only non-urease-producing pathogens were identified from repeat urine cultures throughout the course (Candida species during Covid-19 hospitalization and We report the case of a 68-year-old man with bladder submucosal calcification who recovered from severe Covid-19. Bladder calcification may be a urinary tract sequela of Covid-19, and more biomedical studies are warranted to confirm our findings.We would like to acknowledge the support of the Far Eastern Memorial Hospital. We would also like to acknowledge the contributions of our colleagues.P.Y. Cheng contributed to the conception and design, acquisition of data, and major contributor in writing of the manuscript. All authors contributed to material support.


Early childhood radiation exposure carries an enhanced radiation risk of about two to three times as high as in adults. The objective of this study was to determine local diagnostic reference levels for the most frequent pediatric x-ray examinations in Addis Ababa, Ethiopia.A cross-sectional study was conducted on 18 public and private hospitals/clinics in Addis Ababa. A total of 864 pediatric patients, undergoing eight types of routine x-ray examinations with 13 projections were evaluated from December 18/2017 to March 17 /2018. All pediatrics were categorized under four age groups. Anthropometric and radiographic parameters of each patient were recorded .The minimum, maximum, mean and third quartile values of entrance surface dose were analyzed using SPSS version 23. Finally, the suggested local diagnostic reference levels were compared with national and international reference dose values.Of the 864 pediatric patients, chest (AP/PA), lower and upper extremity (AP/PA) accounted for 501(58%), 110 (13%) and 103 (12%) respectively, accounting to 714(83%) of the total pediatric x-ray examinations. The suggested local diagnostic reference levels of chest X-ray (AP/PA) examinations in mGy were:  for age group , respectively. Similarly, for same age group  the suggested local diagnostic reference levels of lower and upper extremities in mGy were:  and , respectively.The suggested local diagnostic reference levels were slightly higher than the national and international guidance levels, indicating the need for establishment of diagnostic reference levels in the country. The clinical value of radiography for the diagnosis of pediatric disease is unquestionable. However, the use is not entirely without risk due to the biological effect of x-rays. InapproIt is normal for a patient undergoing x-ray examination to expect that the radiation dose received in different hospitals for the same procedure will be within a narrow range. However, wide variations in patient dose for the same type of X-ray examination and for the same examination have been evident from various dose surveys –10 whichth%) value of entrance surface doses for pediatric patients undergoing common X-ray examinations in eighteen hospitals /clinics Addis Ababa, thereby to suggest the first LDRL, in Addis Ababa, Ethiopia.For these reasons the objective of the present research work was to calculate the third quartile  through personal communication. All hospitals /clinics (public and private) performing pediatric X-ray examination were included. All X-ray machines, radiographers/technologists and all pediatric patients who visited Addis Ababa Hospitals/ clinics were the source Population. While all selected X-ray machines, radiographers and or technologists on duty and pediatric patients were the study population.Data collection procedure: Initially, self-administered questionnaires regarding the X-ray unit was prepared in English and distributed to the radiographers working in the study hospitals/clinics. Completed questionnaires were checked for completeness and consistency and collected from respective institutions.The tube output (o/p) was measured in a scatter-free geometry, for a peak tube voltage of 80 kVp, 20 current-exposure time (mAs) and a focus-to-detector distance (FFD) of 100 cm, using a calibrated Unfors RaySafe XI dosimeter. While measuring the entrance surface dose in air, relevant anthropometric and exposure parameters  were recorded for each patient undergoing the specified diagnostic procedure. The ESD was calculated in the present work using the following relations.A value of 1.35 was used in this study for Back Scatter Factor. Eight types of routine x-ray examinations with different projections were evaluated in order to know the higher incidence of projection. These projection were:-Abdomen(AP), Cervical spine(AP), Chest(AP/PA), Lower Extremities(AP/PA), Lumbar spine(AP), Pelvis(AP), Skull(AP/PA+LATERAL) and Upper extremity(AP/PA) x-rays. Besides AP/PA projection, lateral projection was evaluated only for the Skull x-ray, as the ddata on lateral projections of the rest examinations were not dense enough to allow statistical analysis.As far as effective dose or individual estimation of radiation risk is not a worry, AP and PA projections were not studied in a different way one from another. If effective dose or individual estimation of radiation risk was the concern of this study, then AP position should be studied in a different way from PA, because location of body organs (depth from the surface) differs for both positions and hence different organ dose on AP and PA. To define local diagnostic reference levels (LDRLs) children were categorized into four age groups , of weight, radiographic data, and LDRL of this study along with DRLs published by national and international values for similar age groups and X-Ray projections were documented in In this study, a marked irregularity was observed among operators during their selection of exposure factors. The use of optimal tube potential and tube loading in chest radiography has received a considerable amount of discussion in the radiological literature ,15,21. AIn this study the calculated third quartile ESDs (LDRLs) of chest were found to be greater than the corresponding DRLs of and 19)19) in alIn conclusion, the author of this manuscript concludes that, the values of local diagnostic reference levels (LDRLs) presented in this work are suitable to be adopted for the paediatric diagnostic X-ray examinations in Addis Ababa, Ethiopia. It can be used as a baseline upon which future dose measurements can be compared. Furthermore, similar type of large-scale survey should be undertaken to establish national DRLs in the case of paediatric X-ray examinations.


The cyanobacterial blooms produced by eutrophic water bodies have become a serious environmental issue around the world. After cellular lysing or algaecide treatment, microcystins (MCs), which are regarded as the most frequently encountered cyanobacterial toxins in fresh water, are released into water. Among all the variants of MCs, MC-LR has been widely studied due to its severe hepatotoxicity. Since 1992, various studies have identified the important roles of MC-LR in the origin and progression of primary liver cancers (PLCs), although few reviews have focused on it. Therefore, this review aims to summarize the major achievements and shortcomings observed in the past few years. Based on the available literature, the mechanisms of how MC-LR induces or promotes PLCs are elucidated in this review. This review aims to enhance our understanding of the role that MC-LR plays in PLCs and provides a rational approach for future applications. Cyanobacteria can produce a family of hepatotoxins called microcystins (MCs), which are the most frequently encountered cyanotoxins in fresh water [Contamination with harmful cyanobacterial blooms has become a serious environmental issue around the world . Cyantoxsh water ,5. More sh water ,7. MC-LRsh water ,9. The ush water ,11,12. MMC-LR can easily enter cells via organic anion transporting polypeptides (OATPs) and accumulate in the target organs through blood circulation. As such, MC-LR can damage almost every system in the body, including the digestive system  ranks as the sixth most common cancer and the third leading cause of cancer-related death in the world, accounting for more than 800,000 deaths in 2020 . The mai−1 could induce liver fibrosis in mice. Furthermore, MC-LR was found to be able to enter and activate hepatic stellate cells, resulting in differentiation and impacting Hedgehog signaling in cells [Most chronic liver diseases, including hepatocellular carcinoma and intrahepatic cholangiocarcinoma, have been confirmed to be related to liver fibrosis ,36. Gu ein cells . Howeverin cells .Nonalcoholic steatohepatitis (NASH) causes extracellular matrix remodeling in the liver and is a risk factor for HCC. MC-LR has been shown to increase lipid accumulation in the liver tissues ,39,40. HHepatocellular carcinoma (HCC) is the most common type of primary liver cancer, comprising 75%–85% of cases, with China being one of the most high-risk areas for HCC in the world . Early sClinical and experimental studies both show that MC-LR plays a significant role in the incidence of HCC. This section summarizes the role of MC-LR in the origin of HCC in experimental and clinical studies. Experimental studies have revealed the effects of MC-LR on hepatocytes and the liver. Clinical and epidemiological studies include research into the association between freshwater/serum MC-LR content and the incidence of HCC. iK values below 0.1 nM. The hyper-phosphorylation of cytokeratins is closely associated with liver tumor promotion [−1 MC-LR could promote abnormal liver cell proliferation beginning at 1 d post exposure, and that proteins related to the Akt and MAPK signaling pathways were hyper-phosphorylated in mice liver via the inhibition of PP2A activity [Phosphatase 2A (PP2A)—one of the major cellular Ser/Thr protein phosphatases in cells—is widely considered as a tumor suppressor due to its function in DNA repair, autophagy, proliferation, differentiation, and apoptosis ,44,45. Iromotion , and treromotion . Abnormaactivity ,49. −1, the mRNA and protein levels of CYP2E1 were obviously increased, indicating that acute MC-LR exposure can induce the accumulation of ROS in the liver [Oxidative stress has been recognized as a liver cancer-initiating stress response . MC-LR che liver . These fOxidative DNA damage is confirmed to play a role in the development of some cancers ,57,58. OAccording to their location, shape, and length, non-coding RNAs (ncRNAs) are divided into different classes. Among them, microRNA (miRNA), circular RNA (circRNA), and long ncRNA (lncRNA) are the three major types of ncRNA with distinct functions in cancers . MiRNAs are small single-stranded RNAs containing an average of 22 nucleotides. MiRNAs can downregulate the expression of their target genes by binding to recognition sequences, resulting in miRNA-mediated target gene degradation and translational decay or repression ,63. An aCircular RNAs (circRNAs) are generated by back-spliced exons at the pre-mRNA stage to form covalently closed continuous loop structures without a 5ʹ or 3ʹ polarity structure ,71. CircEpigenetic alterations, including DNA methylation, were proven to be involved in the development and progression of hepatocarcinoma. The methylation of promoter CpG islands can inhibit gene transcription and cause the silencing of tumor suppressor genes as well as mutations and deletions ,76. ChenEarly clinical studies mainly focused on the relationship between HCC and the quality of drinking water . These dRecently, Zheng et al. conducted a clinical case-control study to investigate the relationship between serum MC-LR and HCC risk. Blood samples were collected from HCC patients and control subjects and were analyzed for serum MC-LR using ELISA. In this research, serum MC-LR was confirmed to be an independent risk factor for HCC in humans, with a negative interaction with aflatoxin and an obvious positive interaction with the hepatitis B virus or alcohol .COX regression analysis was conducted, and the results showed that a serum MC-LR concentration of ≥0.97 ng·mL−1 was related to an increased risk of tumor relapse. Thus, serum MC-LR could worsen prognosis in patients with HCC [Although early research from 1992 discovered that MC-LR participated in diethyl-nitrosamine-induced HCC , few stuwith HCC . Intrahepatic cholangiocarcinoma (ICC) is a rare, highly aggressive, and often fatal primary epithelial cancer arising from the intrahepatic bile duct. Most ICCs develop in non-cirrhotic livers, and mass-forming ICCs are typically characterized by a hypo-vascularized tumor stroma and prominent desmoplastic stroma, making it different from conventional HCCs ,86. ReceIn the past few years, the special effects of MC-LR on ICC have been demonstrated, and all these results have indicated that MC-LR might participate in the onset of ICC. Yan et al. conducted a study to investigate the toxic effects of MC-LR on intrahepatic biliary epithelial cells in vivo and in vitro. After chronic exposure, MC-LR-treated mice exhibited an obviously thickened bile duct morphology and bile duct hyperplasia. MC-LR can activate the ERK-RSK signaling in human primary intrahepatic biliary epithelial cells (HiBECs) and promote cell proliferation via inhibiting PP2A activity . In addition to the direct effects on HiBECs induced by MC-LR, Yan et al. also focused on the interaction between HiBECs and surrounding cells after exposure to MC-LR in vivo and in vitro studies. A growing number of macrophages were evaluated as being in the portal area after exposure to MC-LR. To explore the molecular mechanism involved in this progression, a co-culture system including THP-1 cells and HiBECs was implemented in the presence of MC-LR. During exposure to MC-LR, the HiBECs had a large chemotactic effect on THP-1 cells and induced M2-type polarization. In turn, inflammatory factors in the medium of polarized THP-1 cells can induce the abnormal proliferation and migration of HiBECs via the activation of related pathways in HiBECs . These rThe prognosis for ICC remains dismal, despite the development of advanced therapeutic tools . PreviouMicrocystin-LR (MC-LR) has been shown to participate in the origin and progression of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) . MC-LR wThe role of microcystin-LR (MC-LR) in primary liver cancers (PLCs) has been studied extensively, but there are still many problems to be solved. Firstly, the effects of MC-LR on the prognosis of hepatocellular carcinoma (HCC) have not been entirely confirmed. Although Lei et al. discovered that MC-LR can worsen the prognosis of HCC patients, patients who were not positive for chronic hepatitis B virus infection were not included, and those who were heavy drinkers were also not included in the study, severely reducing the reliability of the research. The molecular mechanism of MC-LR that is involved in the prognosis of HCC has not yet been explained with clarity and carefulness. Secondly, the scope of future studies should be expanded to include an in-depth focus on the role of MC-LR in intrahepatic cholangiocarcinoma (ICC), with the second incidence in PLCs. Previous studies have identified that MC-LR is associated with the origin and prognosis of ICC. However, the influence of MC-LR on the incidence of ICC in humans has not been confirmed. Past clinical studies have focused mainly on the relationship between MC-LR and HCC. In addition, how the mechanism of MC-LR induces pathological alteration in intrahepatic bile ducts and causes physiopathology changes still requires further study. A better understanding of MC-LR in PLCs may accelerate the progress of novel therapeutics to prevent liver cancer and may improve patient prognosis.


In this issue, there are seven original articles and one publication in the category of clinical genomics. In this editorial, I would like to focus on two original articles about genome-wide association studies (GWAS). There have been great successes in large-scale GWAS to identify novel single-nucleotide polymorphisms (SNPs) associated with traits of interest. By combining independent, large-scale GWAS, meta-analyses have revealed additional SNPs. These SNPs have now been utilized for Mendelian randomization analyses for causal inference. There continue to be challenging methodological issues in GWAS, such as the analysis of longitudinal genetic data, gene-gene interactions, and gene-environment interactions.Dr. Wonil Chung , and his collaborators considered a Bayesian mixed model for longitudinal genetic data. In their earlier work, they demonstrated that their Bayesian method showed a higher statistical power than cross-sectional analysis for detecting SNP-time interactions. Through an analysis of Korea Association Resource (KARE) data for various longitudinal obesity traits, they demonstrated how to apply their Bayesian method in a more effective way. They conducted a two-stage analysis. In the first stage, they performed GWAS analyses of cross-sectional traits and applied a meta-analysis to identify candidate SNPs. In the second stage, they applied the Bayesian method to a subset of SNPs selected in the first stage. The main objective of the Bayesian method was to discover SNPs associated with traits of interest and SNP–time interactions. The application of their Bayesian method to KARE data successfully identified several novel SNPs associated with longitudinal obesity-related traits and significant SNP-time interactions.Dr. Mira Park  and her collaborators proposed an entropy-based gene-gene interaction analysis. In genetic association studies, using entropy-based mutual information is advantageous in that it does not depend on parametrization. For binary traits, both entropy and conditional entropy can be easily derived. For quantitative traits, however, these values cannot easily be obtained because quantitative traits require an exact evaluation of entropy by estimating the probability density function. Dr. Park and her collaborators proposed a method of combining the kernel density estimation and the entropy estimation with the probability density function. Through extensive simulation studies, they showed that the proposed method performed better or comparably well in detecting gene-gene interactions compared to existing methods, such as multifactor dimensionality reduction.New research topics have continued to emerge in GWAS. For example, polygenic risk scores have been popularly used in building prediction models using SNPs. I believe that the Bayesian method of Dr. Chung can be easily extended to estimate more accurate polygenic risk scores. Furthermore, Dr. Park’s work on gene-gene interactions can also be utilized in deriving polygenic risk scores that have both marginal genetic effects and interaction effects.


Gastrointestinal (GI) cancers occur in the alimentary tract and accessory organs. They exert a global burden with high morbidity and mortality. Inside the tumor microenvironment, dendritic cells (DCs) are the most efficient antigen-presenting cells and are necessary for adaptive immune responses such as T and B-cell maturation. However, the subsets of DCs revealed before were mostly based on flow cytometry and bulk sequencing. With the development of single-cell RNA sequencing (scRNA-seq), the tumor and microenvironment heterogeneity of GI cancer has been illustrated. In this review, we summarize the classification and development trajectory of dendritic cells at the single-cell level in GI cancer. Additionally, we focused on the interaction of DCs with T cells and their effect on the response to immunotherapy. Specifically, we focused on the newly identified tumor-infiltrating dendritic cells and discuss their potential function in antitumor immunity. Gastrointestinal carcinoma refers to malignancies that occur in the alimentary tract and accessory organs. It consists of six main types of cancer: oesophageal cancer (OC), gastric cancer (GC), liver cancer (LC), gallbladder and biliary tract cancer (BTC), pancreatic cancer (PC) and colorectal cancer (CRC) . There wAt present, the main treatments for GI cancers include surgery, chemotherapy, radiotherapy and targeted therapy, and the rise of immunotherapy improves the ways against the tumors and has gradually become the first-line therapy in GI cancer. Apart from pancreatic cancer, most clinical trials of GI cancer combine the anti-PD-1 antibody with sequential chemotherapy or targeted therapy to create new therapeutic paradigms –7. AlthoDendritic cells (DCs), as the most efficient antigen-presenting cells, bridge the innate and adaptive immune systems. In the tumor microenvironment, DCs represent a heterogeneous group. Single-cell RNA sequencing can identify new DC subpopulations. Additionally, new insights provided by the single-cell transcriptome and spatial transcriptome will likely reveal a plethora of new immunotherapeutic interventions targeting specific DC subsets or their products for the treatment of a variety of human disorders, including cancers. In this review, we focus on high-resolution data on dendritic cells in GI cancer.+ lymphoid progenitor cells  or tumor-specific antigen (TSA) to generate antigen-specific cytotoxic T cells is crucial in antitumor immunity , conventional dendritic cells (cDC) and plasmacytoid dendritic cells (pDC), all come from common dendritic progenitors (CDPs), common monocyte progenitors (cMoPs)  and IL-7or cells . In one es later . In anotimmunity . Furtherimmunity .+DCs, have been considered to be crucial for trafficking to the lymph nodes and activating CD8+ T cells . They have four main functions, phagocytosis, antigen presentation, costimulatory/inhibitory ability and cytokine secretion ability, to regulate immunity. As professional phagocytes, DCs have separate pathways to process endogenous and exogenous antigens –16. Afte T cells . Additioe tumors . Additioegulated . AltogetintCD100+ , characterized by CD34ntCD100+ . Moreovef humans . AXL+DCsr origin . Howeverresponse .+cDC2s and T-bet-cDC2s, in mice , and effector memory T cells (CD8+ T cells highly expressing SELL GZMK) to regulate multiple kinds of T cells  are able to interact with CD8+T cells. Moreover, Cheng et al. performed a pan-cancer scRNA-seq and found that the proportion of cDC2s was higher than that of cDC1s in tumors. Some research found that ascites from hepatocarcinoma patients were enriched with DCs expressing FCER1A (DC-FCER1A)  .+ or PD-L1- DCs were nearest to PD-L1+ or PD-L1- tumor cells, respectively  specifically originate from stromal cells located in the primary lymphoid organs, secondary lymphoid organs and TLSs . FDCs maHowever, the spatial information of DCs is relatively limited. Many studies utilizing spatial transcriptomics have not paid much attention to dendritic cell distribution and its potential role in presenting antigens in tumors , 55. TheThe single-cell transcriptome and spatial transcriptome have revealed the DC atlas of human Figure 1+ cells/peripheral blood mononuclear cells (PBMCs) engrafted in severe combined immunodeficiency mice. Zhao et al. established the humice platform of liver cancer. Flow cytometry monitors at least twenty-one human immune subsets, including pDC and mDC, in peripheral blood and various cytokine secretion in sera for 8 weeks. Then, the patients’ tumors were implanted subcutaneously in the humice. They found that the therapeutic effect of pembrolizumab was significantly better than that of ipilimumab. There were obvious toxic and side effects in humice when using ipilimumab, which is consistent with the clinical information  refers to human CD34ormation . TherefoDC-based immunotherapy mainly refers to DC-based cancer vaccines. DC vaccines are mostly based on Mo-DCs from patients, which are accessible and have a mature culture protocol. Monocytes can be induced to differentiate into DCs stimulated by IL-4 and GM-CSF and to mature by LPS –64, whic+ cDC1s along with CCL5+ CD8 effector memory T cells were enriched, and an elevated cDC1 gene signature was correlated with longer overall survival  to hamper anti-tumor immunity. Therefore, the future strategy to develop novel DC vaccines is to elicit a CD8+ T-cell response and prevent it from being changed by the immunosuppressive tumor microenvironment, thus eliminating the tumor burden.Currently, scRNA-seq has identified novel subclusters and the precise function of DCs. In summary, conventional dendritic cells (cDC1 and cDC2) are the most efficient antigen presenting cells in the tumor draining lymph nodes and tumor microenvironment. The immunotherapy response is correlated with the interaction of cDCs and tumor-specific T cells. However, cDC1s and cDC2s can also differentiate into a subset of regulatory DCs , the Biotechnology Innovation Plan from Beijing Sungen Biomedical Technology Co., Ltd (2022066 to MD), and the Excellent Young Scientists Fund Program (overseas) from National Natural Science Fund (2021HY-7 to MD). The funder Beijing Sungen Biomedical Technology Co., Ltd was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


E  is the first malaria vaccine to reach Phase IV assessments. The World Health Organization-commissioned Malaria Vaccine Implementation Programme (MVIP) is coordinating the delivery of RTS,S/AS01E through routine national immunization programmes in areas of 3 countries in sub-Saharan Africa. The first doses were given in the participating MVIP areas in Malawi on 23 April, Ghana on 30 April, and Kenya on 13 September 2019. The countries participating in the MVIP have little or no baseline incidence data on rare diseases, some of which may be associated with immunization, a deficit that could compromise the interpretation of possible adverse events reported following the introduction of a new vaccine in the paediatric population. Further, effects of vaccination on malaria transmission, existing malaria control strategies, and possible vaccine-mediated selective pressure on Plasmodium falciparum variants, could also impact long-term malaria control. To address this data gap and as part of its post-approval commitments, GSK has developed a post-approval plan comprising of 4 complementary Phase IV studies that will evaluate safety, effectiveness and impact of RTS,S/AS01E through active participant follow-up in the context of its real-life implementation.Following a 30-year development process, RTS,S/AS01P. falciparum genetic diversity in the periods before and after vaccine implementation.EPI-MAL-002 (NCT02374450) is a pre-implementation safety surveillance study that is establishing the background incidence rates of protocol-defined adverse events of special interest. EPI-MAL-003 (NCT03855995) is an identically designed post-implementation safety and vaccine impact study. EPI-MAL-005 (NCT02251704) is a cross-sectional pre- and post-implementation study to measure malaria transmission intensity and monitor the use of other malaria control interventions in the study areas, and EPI-MAL-010 (EUPAS42948) will evaluate the E vaccine safety, effectiveness and impact. The studies are currently being conducted in the MVIP areas. Their implementation has provided opportunities and posed challenges linked to conducting large studies in regions where healthcare infrastructure is limited. The results from these studies will support ongoing evaluation of RTS,S/AS01E’s benefit-risk and inform decision-making for its potential wider implementation across sub-Saharan Africa.GSK’s post-approval plan has been designed to address important knowledge gaps in RTS,S/AS01 E (GlaxoSmithKline (GSK), Belgium) is a pre-erythrocytic Plasmodium falciparum malaria vaccine developed for routine immunization of young children living in malaria-endemic countries. In the pivotal Phase III trial, 4 doses of RTS,S/AS01E administered to children aged 5 months or older reduced clinical malaria by 39% and severe malaria by 29% over 4 years of follow-up [E was associated with a reduction in overall hospitalizations, and hospitalizations due to malaria, severe anaemia and the need for blood transfusion [E was generally well tolerated and although more reactogenic than control vaccines, local and systemic symptoms were generally transient and mild-to-moderate in intensity [E recipients versus controls after vaccination in children aged 5 months or older, with the risk mainly during the first 3 days after vaccination [E-vaccinated children than in children vaccinated with control vaccines [E compared to girls vaccinated with control vaccines, without differences in risk factors, time to death or causes of death that could explain the results. No such difference was observed in boys. Detailed case evaluation indicated that these imbalances were likely to be chance findings due to unexpectedly low rates of meningitis in the control group , or a low mortality rate in girls in the control group, or the lack of biological plausibility to explain the causal relationship to RTS,S/AS01E vaccination [RTS,S/AS01E received a positive scientific opinion from the European Medicines Agency [E impact and safety remained. The WHO, therefore, adopted the recommendations of the Strategic Advisory Group of Experts on Immunization and the Malaria Policy Advisory Committee who jointly endorsed pilot implementation of the vaccine in 3–5 settings in sub-Saharan Africa [In 2015, RTS,S/AS01n Africa . Under tn Africa .E would be first introduced in selected areas in Ghana, Kenya and Malawi by the respective routine national immunization programmes in the framework of the Malaria Vaccine Implementation Programme (MVIP). Authorization for use of RTS,S/AS01E in this context was granted on 24 April 2018 by the Ghana Food and Drug Board, 11 May 2018 by the Kenya Pharmacy and Poisons Board, and 16 May 2018 by the Malawi Pharmacy and Medicines Regulatory Authority. Vaccination started on 23 April 2019 in Malawi, 30 April 2019 in Ghana and 13 September 2019 in Kenya [E is the first vaccine to be implemented as a complementary tool to existing interventions under the Global Technical Strategy for Malaria, 2016–2030 [E should be used for the prevention of P. falciparum malaria in children living in regions with moderate to high malaria transmission as part of a comprehensive malaria control strategy [In April 2017, the WHO announced that RTS,S/AS01E. Key aspects of the MVIP have been summarized by the WHO in an on-line series of question and answers, in a summary of key milestones in the journey to vaccine implementation, and in the 2021 SAGE report of the RTS,S/AS01E vaccine [E vaccine doses necessary to the MVIP (up to 10 million doses) [E introduction, the MVIP evaluates the vaccine safety, impact, and effectiveness in order to generate information necessary to inform potential future policy for the deployment of RTS,S/AS01E on a broader scale. A first step is the WHO-commissioned Malaria Vaccine Pilot Evaluation (MVPE). This consists of household surveys, and sentinel hospital and community mortality surveillance, building on routine systems. The MVPE will measure the programmatic feasibility of delivering a 4-dose vaccine schedule, vaccine safety in routine use, and the impact of the malaria vaccine on severe malaria and all-cause mortality. This evaluation is largely based on passive follow-up and comparison of the occurrence of vaccine safety and impact study endpoints between vaccine implementation areas (exposed clusters) and areas where the vaccine is not yet implemented (unexposed clusters) [E vaccine safety, effectiveness, impact, and the potential effect of vaccination on the genetic diversity of circulating parasite strains. This paper presents an overview of GSK’s post-approval plan currently being conducted in the MVIP areas [E benefit-risk profile, and to informing decisions for its potential wider implementation across malaria endemic areas of Africa.The MVIP is a collaboration between selected countries and international private and public partners established by the WHO to coordinate, support and evaluate the introduction of RTS,S/AS01 vaccine –12. GSK n doses) . In addilusters) . Second,IP areas . The chaE, GSK’s post-approval plan is designed to assess vaccine safety, impact, and effectiveness in a real-life setting. It comprises 4 GSK-sponsored Phase IV studies , and the post-vaccine introduction study, EPI-MAL-003 (NCT03855995), are compared. For operational reasons, the before-after comparison is being conducted in Ghana and Kenya only. In addition, because the Ministries of Health of the implementing countries are not introducing RTS,S/AS01E into all national areas, vaccine safety and impact will also be assessed using a contemporaneous comparison between exposed and unexposed areas of the study endpoints. Moreover, since annual and/or geographical variations in malaria incidence may occur as a result of changes in malaria transmission intensity or in malaria control intervention coverage, these potential confounders are monitored in the EPI-MAL-005 study (NCT02251704).Many low and lower-middle income countries where malaria is endemic have little or no data on background incidence rates of rare diseases such as those that may be reported as adverse events following immunization. This may prevent robust post-authorization vaccine safety and effectiveness monitoring, and can lead to delays in detecting safety signals, potentially contributing to vaccine hesitancy related to the new vaccine, or to other vaccines introduced in the future. In these settings, disease surveillance studies conducted prior to vaccine introduction can be used to determine reliable background rates of specific diseases/events that can be compared with post-introduction observations. In order to further monitor the benefit-risk profile of RTS,S/AS01P. falciparum parasite prevalence (as a proxy for transmission intensity) and malaria control intervention coverage over 10 annual surveys in the EPI-MAL-002 and EPI-MAL-003 study areas. Results from EPI-MAL-005 will be used to adjust the temporal and contemporaneous comparison analyses for potential year-to-year variation during the conduct of EPI-MAL-002 and EPI-MAL-003. Finally, because P. falciparum has evolved multiple mechanisms to vary cell surface antigens and evade the host’s immune response, an ancillary study to EPI-MAL-005, EPI-MAL-010 (EUPAS42948), has been designed to monitor parasite genetic diversity before and after vaccine implementation.EPI-MAL-005 is an observational cross-sectional study assessing E vaccine introduction. To assess vaccine safety, effectiveness and impact, these baseline incidence rates will be compared with rates documented in the post-implementation study EPI-MAL-003 which commenced when RTS,S/AS01E vaccination was introduced by the Ministries of Health  but not others (unexposed clusters). Thus, in addition to the before-after comparison, EPI-MAL-003 also includes a contemporaneous comparison of endpoints of interest between vaccinated and unvaccinated study participants.Study EPI-MAL-002 is designed to collect incidence data of pre-defined health outcomes, i.e., adverse events of special interest (AESI). These include rare events potentially associated with vaccination Table , meningiGSK’s Phase IV study package is fully embedded in the MVIP. Therefore, selection of participating clusters depended on the cluster identification process led by the Ministries of Health according to the WHO guidance . EPI-MALHaemophilus influenzae type b vaccine, through direct invitation or when hospitalized before routine immunization. Similarly, EPI-MAL-003 is enrolling children presenting for routine immunization, regardless of their future vaccination status with RTS,S/AS01E.To allow direct comparisons of endpoints, EPI-MAL-002 and EPI-MAL-003 are strictly identical in terms of design and conduct. Both are multi-country observational studies with prospective cohort event monitoring. Children < 18 months of age are enrolled during routine immunization with the pentavalent diphtheria-tetanus-pertussis-hepatitis B and E in children in the exposed clusters in EPI-MAL-003) consists of active surveillance for outpatient and inpatient visits by each enrolled participant and of 10 home visits conducted according to a specific time frame (prospective cohort). In addition, hospital-based disease surveillance is organized across the entire study area for infants and children who are not enrolled in the prospective cohort. In other words, throughout the whole study period, all hospitalized children under the age of 5 years who are not already enrolled in the prospective cohort and who live within the study areas are eligible for enrolment in the hospital-based disease surveillance.In both studies, follow-up until approximately 5 years of age  [E will compare malaria-related events in vaccinated and unvaccinated children from exposed clusters enrolled in active surveillance. Vaccine impact  will be investigated by comparing the incidence of malaria-related events in unvaccinated children (either from EPI-MAL-002 or from EPI- MAL-003 unexposed clusters) with the incidence of events in children from EPI-MAL-003 exposed clusters .The study objectives are to estimate the incidence of protocol-defined events, including AESI, meningitis, other adverse events leading to hospitalization, death, and malaria . AESI Table  are evenrtality) , 3. EstiE vaccine introduction.The studies are conducted in the setting of routine medical practice and local laboratory testing (first-line testing), and include a strong support component comprised of study-specific trainings, telemedicine support, second-line laboratory testing, and consultation with an external expert panel for final case classification. These tools are likely to enhance case detection and ascertainment rates. Both EPI-MAL-002 and EPI-MAL-003 use identical surveillance in order to allow a robust comparison of study outcomes before and after the RTS,S/AS01Freely given and written or witnessed and thumb-printed informed consent is obtained from each study participant’s parent/legal representative prior to study participation. Protocol-specified procedures include the collection of demographic data, vaccination records, medical history, medical care episodes, adverse events, use of malaria control measures, development delays or death, and a physical examination when contacts between study staff and subjects occur. The protocol requires collection of a sample of 5 ml of blood for testing at an external laboratory (second-line laboratory) in all suspected cases of AESI and meningitis. All study participants are treated according to good medical and routine practices . In caseIncidence rates of safety endpoints will be calculated and compared based on both before-after and between cluster comparisons using a univariable and multivariable Poisson regression model adjusted for specific covariates, including if applicable, those identified in EPI-MAL-005. The vaccination status of participants will be confirmed using data from individual vaccination cards, vaccination registers and health and demographic surveillance system (HDSS) or equivalent surveillance system. Incidence rates will be computed using person-time denominators for group of interest. Each child will contribute person-time until study end or 5 years of age, whichever occurs first.In addition, the potential risk of meningitis is being monitored in near real time using the maximized sequential probability ratio test (MaxSPRT) method . MaxSPRTE on the incidence of malaria will be estimated [Vaccine effectiveness (direct effect) and impact  of RTS,S/AS01stimated . Cases oE vaccination [EPI-MAL-002 started in January 2016 and an interim analysis has been conducted to provide preliminary results from 14,329 children who participated in the prospective cohort monitoring prior to the introduction of RTS,S/AS01cination . EPI-MALE will lead to a reduction in the incidence of malaria disease in vaccinated subjects in EPI-MAL-003 compared to baseline rates recorded in EPI-MAL-002. However, annual fluctuations in malaria incidence occur due to changes in transmission intensity influenced by rainfall patterns or changes in how malaria control interventions are used. By monitoring malaria transmission intensity and the coverage of malaria control interventions in the EPI-MAL-002 and EPI-MAL-003 study sites during the conduct of these studies, EPI-MAL-005 will allow a more accurate estimate of the true impact of RTS,S/AS01E vaccination. This study will contribute to the analysis of vaccine effectiveness and vaccine impact by identifying variables to be used as covariates to adjust the before-after and between cluster comparisons.It is expected that the use of RTS,S/AS01EPI-MAL-005 has a cross-sectional design with yearly surveys coinciding with the recruitment and follow-up periods of the EPI-MAL-002 and EPI-MAL-003 studies. At each survey, 600 participants aged 6 months to < 10 years are randomly selected from the sites participating in the survey in that year, stratified by age group. The selection process will be repeated every year meaning that the subjects will be different in each cross-sectional survey except if they are re-selected in a subsequent survey by chance. The surveys occur during the period of peak malaria transmission that varies from end September to mid-December in western African sites, from end April to mid-August in eastern and southern African sites , 20.P. falciparum parasite prevalence , and of the use of malaria control interventions .The co-primary study objectives are estimation of At each survey, demographic information, medical and vaccination history, information on healthcare-seeking behaviors in the previous 14 days, fever in the last 24 h, and use of malaria control measures , are recorded for all participants. During the survey visit, axillary body temperature is measured, and a capillary blood sample is collected for malaria testing by microscopy and nucleic acid amplification tests . In the event of fever at the time of the visit, or fever or other symptoms/signs of clinical malaria reported in the previous 24 h, a rapid diagnostic test is conducted, and the participant treated if the test is positive. Participants identified as being parasite-positive following microscopy are treated according to national guidelines.E vaccination status and gender. Annual fluctuations in parasite prevalence are estimated using the Cochran-Armitage trend test. The agreement between parasitaemia as measured by microscopy versus nucleic acid amplification tests is assessed using the Cohen’s Kappa coefficient and the Landis and Koch scale. A risk factor analysis for malaria infection is conducted using a multivariable logistic regression analysis.Parasite prevalence and use of malaria control measures are computed by study site, age group, RTS,S/AS01The study started in October 2014 and the first two surveys have been published . At the P. falciparum is a pathogen with high variability and a high number of different circulating haplotypes. The parasite uses numerous mechanisms to vary cell surface antigens and evade the host immune response. For this reason, there is a potential concern that widespread implementation of RTS,S/AS01E could drive the selection of specific parasite variants or alter the number of parasite haplotypes over time by exerting selective pressure. EPI-MAL-010 is an ancillary study to EPI-MAL-005 that will monitor the genetic diversity of circumsporozoite protein sequences in the P. falciparum parasite population before and after vaccine implementation.Although the central NANP amino acid repeat sequence of the circumsporozoite protein used as a major component of the RTS,S vaccine antigen is normally well conserved across parasite strains, P. falciparum parasitaemia confirmed by microscopy and/or nucleic acid amplification tests, and collected before and after RTS,S/AS01E implementation in two study sites: Kintampo (Ghana) in Western Africa and Kombewa (Kenya) in Eastern Africa.EPI-MAL-010 has a longitudinal, cross-sectional study design and uses capillary blood samples collected from participants enrolled in EPI-MAL-005 over 7 survey years. Samples are from participants aged 6 months to < 5 years with P. falciparum haplotype prevalence  and frequency  in participants aged 6 months to < 5 years vaccinated or not with RTS,S/AS01E.This study is estimating P. falciparum by microscopy and/or nucleic acid amplification tests. Trends in the prevalence of specific P. falciparum haplotypes with a frequency of at least 5% will be assessed by a logistic regression model. Multinomial logistic regression will be used to describe the annual fluctuations in haplotype frequency using the 3D7 haplotype as the reference group.Amplicon sequencing is conducted on samples tested positive for Considering the specificities of the study setting, GSK together with its local scientific partners, conducted comprehensive study feasibility assessments in which both scientific and operational aspects were carefully balanced to allow generation of robust data. During the planning phase, global experts provided advice on study design and execution. Evolving circumstances, external constraints and the involvement of multiple stakeholders required adaptability and flexibility, balancing an optimal study design with real-world constraints. Designing, setting-up and conducting a complex post-approval plan in sub-Saharan Africa brings some important setting-specific considerations: (1) data collection needs to be performed using prospective follow-up because existing data collection systems and databases may be sub-optimal or absent; (2) vaccine safety, effectiveness and impact data have to be collected in a healthcare environment where case detection and ascertainment may be challenging because of limited healthcare infrastructure and diagnostic capability; (3) there may be limited access to health care in remote settings; (4) background incidence rates of many diseases including study-specific endpoints are limited or not available; (5) standard laboratory procedures may not exist across all study sites; and (6) sample storage and transportation from remote locations can be challenging.E, and have developed capability in terms of training, experience and quality of healthcare that resulted from previous study participation. However, for some sites without such past experience, additional investment was required to set up baseline structures and procedures; (2) the existence of a HDSS, part of the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH), or of an equivalent surveillance system. HDSS sites have a demographic database in place that updates, on a regular basis, the number of births, deaths, immigrations and emigrations, and potentially vaccinations and population health outcomes. The number of HDSS sites in Ghana, Kenya and Malawi being limited, a population census had to be fully established or partially enhanced in approximately half of the study sites.More information on key parameters that were considered in the framework of the study feasibility assessment is provided below. Study site selection was based on specific criteria: (1) the existence of pre-existing scientific research infra-structure capable of expanding beyond routine data collection. Several of the finally selected study sites have research experience in conducting clinical trials with RTS,S/AS01The EPI-MAL-002 and EPI-MAL-003 studies are mainly based on data collection in the framework of routine medical practice, which may hamper the ascertainment of diseases requiring more advanced diagnostic tools. A full understanding of the structure and capacity of the healthcare system in each country where the studies were planned was required, including the assessment of the capacities for case detection and the ascertainment of study endpoints in each study site. As an outcome of this assessment, specific tools were put in place during the study preparation and conduct to enhance case detection and diagnostic capabilities. These include regular and ongoing medical and pharmacovigilance trainings, telemedicine support , the distribution of job aids, the support of local laboratories and the set-up of a central reference laboratory  for blood and CSF testing. These enhancement tools should increase the likelihood of reaching the highest possible level of diagnostic certainty. For the key endpoint of meningitis, medical and non-medical staffs have received training on meningitis case detection and ascertainment, which includes information on the national guidelines for case management (including lumbar puncture and testing of CSF) with secondary testing to be performed at a central laboratory when sample volume permits.This multi-country initiative involves key local and global public health partners. The scientific and operational constraints and the complexity of the study set-up provide opportunities for collaborations and alignment in healthcare approaches between countries to promote best practice. However, turnover of trained personal in the study areas is likely to be an ongoing challenge.Within countries, the MVIP, and more specifically the study design, set-up and conduct, promote collaboration between different authorities, such as routine healthcare system, diagnostic services, national immunization services, epidemiological research, and National Malaria Control Programmes.E vaccination has been observed during the pandemic thus far, although it might be expected that hospitalization practices may change in order to limit admissions to children with serious or critical conditions and avoid hospital crowding. However, the potential impact of COVID-19 on the evaluation of AESI as determined in pre-vaccination pre-COVID-19 period requires continuous monitoring of the situation. Sensitivity analyses may be conducted considering COVID-19 pandemic periods for both studies.Despite best laid plans, the coronavirus disease 2019 (COVID-19) pandemic in Africa continues to unfold and its impact is evolving. In this environment, the MVIP is continuing and measures are being taken to protect the welfare and safety of participants and study staff, and to ensure data integrity . No majoE in a real-life setting is a unique and complex undertaking that requires the establishment of large-scale and strong partnerships. Assessing the benefit-risk profile of a 3-dose primary schedule vaccine with a 4th dose booster administered beyond the usual Expanded Programme on Immunization schedule in low and lower-middle income countries requires the establishment of ad-hoc tools and quality control methods to allow collection of robust and reliable data. Whilst technical and operational expertise is key to achieve this goal, human and financial resource needs should not be underestimated. The effort has been based on the WHO-led MVIP, existing research platforms and expertise in the implementing countries, and significant commitment by GSK. The experience with RTS,S/AS01E in sub-Saharan Africa highlights important aspects to be considered when planning and implementing a vaccine post-approval plan in low and lower-middle income countries. The RTS,S/AS01E experience will pave the way for the development and implementation of new generation malaria vaccines, and of other vaccines for the developing world.The implementation and the safety, effectiveness and impact evaluation of RTS,S/AS01


P < 0.001, W = −7.43) and depression  by the final session. These benefits were sustained at post-treatment and post-partum follow ups. Future research should further explore the effectiveness of this treatment in a randomized controlled trial.Trauma-related symptoms and post-traumatic stress disorder (PTSD) are common during pregnancy and have adverse effects on pregnancy and birth outcomes, post-partum maternal mental health, and child development. The arousal symptoms associated with PTSD, including heightened or dysregulated physiology, may contribute to these adverse outcomes. Low-income minoritized women may be at highest risk given more lifetime exposure to trauma and limited access to mental health care. While evidence-based psychotherapies for PTSD exist, none are targeted to non-treatment seeking individuals nor specifically integrated with prenatal care. Thus, we developed and tested the efficacy of a short-term (four sessions) brief (30–45 min) psychotherapeutic intervention designed to address PTSD symptoms in pregnant women receiving prenatal care at two urban medical centers. Participants were 32 pregnant women with an average gestational age of 18.5 weeks at the time of enrollment. The sample was overwhelmingly non-Caucasian, single, and reported very low income. Participants completed measures of trauma-related symptoms , and depression  at baseline, twice during treatment, post-treatment, and at 10–14 weeks post-partum. The intervention was successful at significantly decreasing symptoms of PTSD (PCL score = −20.27, 95% CI: −25.62, −14.92,  Post-traumatic stress disorder (PTSD) is a prevalent public health concern accounting for significant disability . In natiDuring pregnancy, PTSD is specifically associated with increased risk for both maternal and child morbidity  and otheIn utero exposure to maternal psychological distress and anxiety are also related to long-term adverse behavioral sequelae in children, including higher levels of newborn irritability, , and meet DSM-IV-TR diagnostic criteria for PTSD or pPTSD. For the purposes of this study, pPTSD was defined as meeting symptom criteria for clusters A (trauma), B (re-experiencing), and C (avoidance) or A, B, and D   and the Barnes Jewish Hospital System affiliated with the Washington University in St. Louis School of Medicine between July 2014 and September 2019. Consecutive pregnant women between 12arousal) . BecauseAfter providing written informed consent, all participants were administered the Structured Clinical Interview for Diagnosis (SCID) DSM-IV, The Perceived Stress Scale (PSS), the Edinburgh Post-natal Depression Scale, (EPDS), the Post-traumatic Stress Disorder Checklist (PCL-IV), the Adverse Childhood Experiences Questionnaire (ACE), and the TLEQ (Traumatic Life Experiences Questionnaire). Those who met study criteria for PTSD or pPTSD were invited to take part in the brief psychotherapy intervention.The PSS assesses how unpredictable, uncontrollable, overloaded, and stressful they perceive their life to be . On 10 qThe EPDS assesses depressive symptomatology over the past week . AlthougThe PCL-4 is a standardized self-report rating scale for PTSD that comprises 17 items that correspond to the DSM-IV-TR version of PTSD symptoms . For theThe ACE-Q assesses 10 types of adversity experienced before age 18: abuse , neglect , and household dysfunction  . Each exThe TLEQ assesses whether an individual has been exposed to events which are conceptualized in the DSM-IV as being sufficiently aversive to result in a feeling of helplessness, horror or fear and thus qualify as a trauma . The TLETraditionally, primary care-mental health treatments (for depression) are brief and problem-focused, compared to specialized psychological interventions in which longer session durations and frequency are the norm , 56. ThiThe newly developed psychotherapeutic intervention used in this study, consisted of four 30–40 min sessions targeted at psychoeducation, cognitive restructuring, behavior activation, and mindfulness. Our brief psychotherapy builds upon a treatment devised for delivery in primary care settings and is meant to be convenient for patients and cost effective for practitioners. It uses components from cognitive behavior therapy (CBT),  and MindSession 1 focuses on gathering information about the patient's symptoms, developing rapport, and providing education about PTSD symptoms. Discussing common symptoms and typical reactions to trauma can assist the patient in recognizing how these symptoms may be disruptive to her functioning. Helping patients develop a deeper understanding of their symptoms can normalize the symptoms, which leads to relief for some individuals . Behavior activation is an important step in this treatment because it acts as a proxy for exposure in helping a patient to overcome avoidance behaviors. It has also been shown to be an effective treatment for depression, which is often comorbid with PTSD symptoms  between sites, (ii) between those who completed at least one intervention session compared to none, (iii) between those missing one or more intervention session with those who completed all intervention sessions, and (iv) between those missing their 10–14 week follow-up and those who completed their 10–14 week follow-up; differences were tested with two-sample t-tests or Fisher's exact tests, as appropriate. There were no significant differences in demographics for any of these comparisons, so models did not account for site and missing longitudinal data was assumed to be missing completely at random.Demographic data was summarized for Continuous longitudinal assessment variables  were modeled as repeated measures outcomes using generalized estimating equations models (GEEs) with exchangeable correlation structures; binary outcomes  were modeled in this framework with a logit link. Adjusted models included number of completed treatment visits. Gestational age at baseline was considered as a covariate but as it did not have any significant effect on the significance or direction of any of the adjusted results it was not ultimately included in the models.t-tests, as appropriate, to determine if they were significant predictors of number of visits completed or completing the intervention. Then, each of these continuous variables was added as a predictor in the GEE models to determine if they had significant effects on mean levels of outcomes over time. To determine if total ACE or total TLEQ had an effect on outcomes over time, an interaction was tested in each model between each of these predictors with time.When arousal symptoms were analyzed, a PCL item score of ≥3 was used to determine whether an item was endorsed. DSM-IV-TR criteria for meeting the arousal cluster require endorsement of 2 out of 5 items. Severity was calculated by summing the scores of the five arousal items. Total number of ACEs experienced and total TLEQ score were considered as important predictors of these longitudinal psychological outcomes, and it was hypothesized that they would predict engagement in the study treatment , 45. FirF statistics for ANOVAs, and t statistics for two-sample t-tests. Statistical analyses were conducted in R version 4.0.5  from robust standard errors in GEE models, on 4.0.5 .Demographic information is presented in One hundred eighty five (185) women were approached about the study, 32 screened positive for eligibility and consented to participate, and 23 completed the baseline visit. Of those 23, 18 completed measures at visit 2; 16 at visit 4, 15 at post-treatment follow-up, and 11 at the final follow-up, 10–14 weeks post-partum. See P < 0.001, W = −7.43) after adjusting for number of completed treatment visits. This effect remained at both follow-up time points; with PCL-C score remaining significantly lower than at baseline at the post-treatment follow-up  and at post-partum follow-up at 10–14 weeks post-partum . See At baseline, mean PCL-C score was 56.4 (SD 8.9). At the final session of the intervention (visit 4), PCL had decreased an average of 20.27 points , and this effect remained significant at the post-treatment follow-up visit , as well as at the post-partum follow-up visit .Given our specific interest in the relationship of arousal in PTSD to adverse pregnancy outcomes,  we invesP < 0.001, W = 4.90), post-treatment , and post-partum follow-ups . For these analyses, severity of arousal symptoms was determined by the sum of scores on PCL-IV items corresponding to cluster D (items 13–17).Similarly, when we investigated the change in severity of the arousal symptoms, we found significant and sustained decreases in arousal symptom severity at visit 4 , and this change was sustained at both follow-up time points .Lastly, we investigated changes in whether criteria were met for the arousal symptoms cluster of the PTSD diagnosis; 2 out of 5 arousal cluster symptoms. Compared to baseline, at visit 4 there was a significant decrease in the likelihood of meeting criteria for the arousal symptom cluster (D) . Over the course of the intervention and follow-up period, there were significant sustained decreases in depression score, as measured by the EPDS. By visit 4, the adjusted mean difference in EPDS score compared to baseline was −4.81 , and results remained consistent at the post-treatment follow-up  and post-partum follow-up . See P = 0.003, W = −2.77), post-treatment  and post-partum follow-up , as well as significantly lower odds of having an EPDS score >13 at these visits .At baseline, mean EPDS score was 13.3 .We examined change in score for the PCL, EPDS, PSS, and number of arousal symptoms at each treatment session to determine whether there was a treatment effect by session. For all measures except the PCL, treatment effects did not become evident until session 4. For PCL scores, improvement was seen beginning at session 2 in both unadjusted models and those models that adjusted for the number of completed treatment visits .Neither ACE nor TLEQ scores had a significant impact on treatment engagement, as measured by number of completed visits  such that higher TLEQ scores were associated with increases in depression symptoms from pregnancy to post-partum.Finally, we tested separate interactions between both ACE and TLEQ and time to determine whether an individual's ACE or TLEQ score affected the trajectory of improvement longitudinally over the four follow-up periods for depression, perceived stress, and PTSD symptoms. Our findings indicate a relationship between TLEQ and EPDS, analyzed continuously,  and adjusted (P = 0.003) models; with an association showing higher ACE scores were associated with more depressive symptoms in both the unadjusted  and adjusted  models. However, this latter result should be interpreted with caution since the range of ACE scores was truncated at the post-partum follow-up timepoint , post-partum N = 11, limiting the generalizability of this result.Similarly, ACE scores significantly affected EPDS trajectory over time in both unadjusted  and NIMH K23MH107831 (LH).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Antimicrobial Resistance (AMR) is one of the most alarming public health issues around the world. Carbapenem, colistin, and tigecycline are currently the last-resort antibiotics for the treatment against multidrug resistant bacteria. This Research Topic integrates recent studies on the transmission dynamics and control strategies of AMR to these important drugs. It is about the mechanism of spread and the mitigation approaches of AMR.In this Research Topic collection, nearly half of the articles covered the critical role of plasmids in AMR dissemination.mcr-1 has been frequently harbored on multiple transferable plasmids and spread worldwide. This gene encoded the MCR-1 enzyme that modified LPS and attenuated bacterial affinity with colistin  was more likely to emerge in K. pneumoniae than E. coli when exposed to colistin. This result partly explained why HLCR was more common in K. pneumoniae than E. coli in clinical sections.On the one hand, plasmids carrying resistant genes acted as vehicles for horizontal gene transfer. Taking colistin resistance as an example, a well-documented gene, tet(X3) and tet(X4) were recently reported, alarming the possible horizontal spread of resistance  in Escherichia fergusonii, along with two chromosome-bearing tet(X6) in Proteus cibarius, from chicken feces. Apart from tet(X) and its variants, Xu et al. revealed that tet(A) mutation occurred under selective pressure could also lead to tigecycline resistance in K. pneumoniae. In their study, induction experiment was performed in which 71.4% (20/28) of tet(A)-carrying tigecycline resistance K. pneumoniae developed tet(A) mutations. And twelve (12/20) of them successfully transferred their tet(A)-mutant plasmids to E. coli EC600 by conjugation and led to an elevated level of tigecycline MIC in recipients . These data indicated that mutations of tet(A) in conjugative plasmids may contribute to the tigecycline resistance in K. pneumoniae and E. coli.Concerning tigecycline resistance, the plasmid-borne Liu et al. analyzed 84 non-duplicate IncX3 plasmids reported across China from 2011 to 2021. And all these plasmids harbored carbapenemase genes, among which 81 were blaNDM carrying and 3 were blaOXA−181-carrying. In those NDM-positive plasmids, the NDM-5-positive ones were dominant and recovered from diverse sources, including clinical specimens, animals, environment and retail food, suggesting the wide spread of NDM-5-producing isolates through the transfer of IncX3 plasmids. However, NDM-1-positive IncX3 plasmids were mainly identified in the hospital section, which was disseminated at a limited level compared with NDM-5. The genetic context of blaNDM on IncX3 plasmid could be classified into five subtypes, two of which have been identified in Enterobacter cloacae chromosome and IncF & IncA/C plasmids, respectively. This indicated that the blaNDM gene environment could be transmitted by different plasmids and bacterial species. The other two studies reported KPC-2-carrying plasmids in China from P. aeruginosa  and E. coli , respectively . In all the three plasmids, KPC-2 was bracketed by Insertion Sequence (IS), suggesting the potential role of IS in promoting the spread of KPC-2 among different plasmids.To better understand the evolution of plasmids related to carbapenem resistance, one study by Zhang et al. found that, to cause colistin-resistance in K. pneumoniae under drug pressure, ISKpn72 on a plasmid could be inserted into mgrB gene with a higher efficiency than the ISKpn72 from chromosome. More importantly, this plasmid was conjugative, providing a clue about the widespread of mgrB inactivation among K. pneumoniae in hospitals  with a blaKPC−2 in chromosome. Interestingly, sequence analysis showed that the chromosomal blaKPC−2 was carried in a 24 kb IS with high similarity to the blaKPC−2-habouring plasmids in P. mirabilis  from the intensive care unit (ICU) and provided a glimpse of intraspecies replacement in the hospital. According to phylogenetic analysis, both ST4496-KL47 and ST11-KL64 were likely to originated from ST11-KL47. However, ST4496-KL47 was less competitive than ST11-KL64 and disappeared after 6 months. While ST11-KL64 increased virulence by capsule biosynthesis locus recombination and acquired the potential to be the dominant CRKP in hospital. In addition, the serotype was found to be associated with antimicrobial resistance in this Research Topic. The study by Luo et al. indicated that, for clinical Salmonella isolates in China, colistin resistance mainly distributed in S. Enteritidis  and S. Typhimurium , while the resistant rate of the former was significantly higher than that of the latter.In recent years, the progress in whole genome sequencing (WGS) made it easier to study the AMR transmission in a deeper level. Using this technique, two studies investigated the evolution of AMR isolates. To put AMR under control, various strategies need to be executed, including constant surveillance of drug resistance, fast diagnosis of AMR bacteria infections and development of novel therapy.Chang et al. revealed the epidemiology and change of antimicrobial resistance rates in children patients with non-typhoidal Salmonella infection from 2012 to 2019. And the report by Paveenkittiporn et al. provided comprehensive information to the prevalence of mcr-positive Carbapenem-Resistant Enterobacteriaceae (CRE) among patients in Thailand from 2016 to 2019. Another study by Ma et al. investigated AMR in clinical Ureaplasma spp. and addressed the lack of data in this field in China. In their research, the most active antibiotics were azithromycin, josamycin, and clarithromycin. These data provided updates of the prevalence of AMR in hospitals and facilitated clinicians for the rational use of antibiotics.Firstly, the spread of drug resistance needs to be put under surveillance. The work by Han et al. investigated the performance of three lateral flow chromatographic assays  in determining carbapenemases among CRE. As a result, the NG-test Carba 5 detected all of its targeted carbapenemases  in 15 min with both sensitivity and specificity at 100%. The RESIST-5 O.O.K.N.V. detected KPC, NDM, VIM and OXA-48-like with the sensitivity and specificity at 99.4 and 100%, respectively. The IMP K-SeT, as a complementary test of RESIST-5 O.O.K.N.V for IMP determination, detected all six IMP producers in the research. This result showed that all the above detection methods could simplify the complex workflow for carbapenemases identification for infection control purposes and epidemiological surveillance. For upgrading detection approaches, Jia et al. developed an AI-Blue-Carba test, an improved version of Blue-Carba, to determine carbapenemase-producing Gram-negative bacteria. In this research, “deep learning” was innovatively combined with traditional Blue-Carba, which allowed elevated efficiency for the detection of carbapenemases (within 15 min) and was user-friendly. Through using AI-Blue-Carba, the author planned to create a co-networking platform with a hospital which would promisingly facilitate the monitoring of carbapenemases and infection treatment in clinical sections. Another study explored a method for fast detection of Staphylococcus aureus from patients with diabetic foot infections . In this method, loop-mediated isothermal amplification (LAMP) and clustered regularly interspaced short palindromic repeats (CRISPR) techniques were coupled. Through targeting nuc and mecA, the CRISPR-LAMP assay successfully identified S. aureus strains and distinguished methicillin-resistant S. aureus (MRSA) from methicillin-resistant S. aureus (MSSA) in clinical samples. Due to its visualized fluorescent result with easy interpretation criteria, this method could help the point-of-care diagnosis against MRSA. More tools are worth being investigated for fast and precise diagnosis of AMR, like aptamers and CRISPR-Cas suggested in the review by Pereira et al. The former (aptamers) could recognize bacteria through binding to cell surface receptors, antigens or unknown targets, while the latter (CRISPR-Cas) could recognize and cleave the targeted bacterial nucleic acid. Their application for diagnostics has been demonstrated in different studies to offer shorter turnaround time comparing with the conventional AMR phenotypic tests , highlighting the potential of these techniques to be refined and used as guidance to clinical antimicrobial prescriptions.Secondly, reliable methods for rapid detection of AMR are of great importance in helping clinicians selecting effective antibiotics precisely, optimizing the treatment and preventing the aggravation of infection by Multi-Drug Resistant (MDR) microbes. To compare the currently available methods for fast carbapenemase detection, Wu et al. evaluated its in vitro antibiogram by testing the minimum inhibitory concentrations (MICs) of lefamulin against 634 clinical respiratory pathogens across China. They demonstrated that lefamulin had excellent antimicrobial activity with a broad-spectrum coverage of respiratory pathogens, including MRSA/MSSA, methicillin-resistant/sensitive S. epidermidis (MRSE/MSSE), Streptococcus. pneumoniae, β-hemolytic Streptococcus, Haemophilus influenzae, H. parainfluenzae, Morazella catarrhalis, and Mycoplasma. pneumoniae. The in vitro activity of lefamulin supported the use of this drug as an alternative treatment option for CABP in China. Apart from new drugs, a reasonable combination of currently available antibiotics is another choice. Chen et al. found that CRKP developed resistance in tigecycline-induced descendants, while in the meantime, also presented stable hypersensitivities to other antibiotics, especially aminoglycosides, showing significantly lower MICs. Further genetic analysis suggested that the loss of AMR plasmids may play a role in this phenomenon. These new findings supported the combination therapy of tigecycline and aminoglycosides against CRKP infections.Thirdly, the development of innovative therapies are urgently needed for anti-infective purpose. One straight forward way is selecting new antimicrobial candidates. A novel antibiotic, named lefamulin, has been approved by the U.S. Food and Drug Administration in 2019 against community-acquired bacterial pneumonia (CABP). And To summarize, this Research Topic brought together a number of articles addressing the dynamics of AMR transmission and novel strategies of controlling AMR bacteria infection. Based on these new insights, plasmids were re-emphasized as a critical driving force in the spread and evolution of bacterial drug resistance, not only as mobile gene carriers, but also gene lenders to chromosomes. To overcome the problem of AMR, medical progress is being made in the fields of novel therapies and fast infection diagnosis which promotes the rational use of antimicrobials in the future.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This work was supported by the Laboratory of Lingnan Modern Agriculture Project (NT2021006) and China Agriculture Research System (CARS-36).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.