The proposal of parameter β provides an effective solution to the challenge of motion-blurred object detection. Then, the optimized anchor-free branches of the FSAF module are plugged into the YOLOv3 single-shot detector and work jointly with the anchor-based branches of the YOLOv3 detector in both training and inference, which efficiently improves the detection precision of the detector for tiny and dense objects. Experimental results show that the method proposed is superior to other typical thermal infrared vehicle and pedestrian detection algorithms due to 72.2% mean average precision (mAP).In complex scenes, it is a huge challenge to accurately detect motion-blurred, tiny, and dense objects in the thermal infrared images. To solve this problem, robust thermal infrared vehicle and pedestrian detection method is proposed in this paper. An important weight parameter  Thermal infrared object detection technology, due to its noncontact and passive detection characteristics, overcomes the shortcomings of radar object detection technology’s poor portability and the difficulty in detecting the objects in radar blind areas. It has broken through the limitations of optical object detection technology, which has a poor capability to penetrate smoke and dense fog and cannot work all day, and has become a research hotspot in the fields of military reconnaissance, traffic management, and autonomous driving.With the improvement of the level of thermal infrared detectors and the computing power of graphics processing unit (GPU), the algorithms for thermal infrared object detection and recognition continue to emerge. The previous traditional infrared object detection algorithms generally used the strategy of sliding windows to select the region proposal ,2,3,4,5,As the performance of handcrafted features reaches the limit, the development of object detection technology reached a period of stagnation after 2010. Until 2012, the success of AlexNet  in the IThe above two categories of algorithms are mainly used in the detection of optical objects. However, infrared images have a lower resolution than optical images and are susceptible to ambient temperature, especially for some tiny objects that only occupy a few pixels in the infrared images, which brings a huge challenge to infrared object detection. Moreover, it becomes quite difficult to accurately locate the infrared objects in the situation where the objects are dense and mutually occluded. Aiming at the above problems, Yi et al.  combinedBesides, motion blur of the object is another huge challenge to infrared object detection. Motion blur is mainly caused by the relative movement between the camera, the object, and the background, which will lead to strong noise and background clutter interference in the infrared imaging system, making the object signal relatively weak. More specifically, the problem of motion blur will make thermal infrared objects lack effective shape and texture features, resulting in a sharp decrease in the robustness of the detector.To solve the above problems, this paper proposes a robust thermal infrared vehicle and pedestrian detection method. Specifically speaking, an important weight parameter e (FSAF)  module ie (FSAF)  structure (FSAF)  loss ande (FSAF)  algorithThe rest of this paper is organized as follows. The algorithm’s general structure is the optimized FSAF module that is plugged into the YOLOv3 network architecture, as shown in The general concept of the FSAF module is online feature selection applied to the training of multi-level anchor-free branches, and it addresses two limitations brought up by the conventional anchor-based detection: (1) heuristic-guided feature selection; (2) overlap-based anchor sampling. The basic concept of overlap-based anchor sampling is that instance boxes are matched to anchor boxes based on the Intersection over Union (IoU) overlap, and each instance is always matched to the closest anchor box(es). The general concept of each instance refers to each target in the infrared image, for example, different pedestrians represent different instances in the image. The general concept of heuristic-guided feature selection is that anchor boxes are associated with a certain level of feature map by human-defined rules, such as box size. Therefore, the selected feature level for each instance is purely based on ad hoc heuristics. The motivation of the FSAF module is to let each instance select the best level of feature freely to optimize the network, so there should be no anchor boxes to constrain the feature selection in the module. Instead, the FSAF module encodes the instances in an anchor-free manner to learn the parameters for classification and regression. Besides, the FSAF module calculates the sum of classification loss and regression loss for each feature level of all anchor-free branches in the online feature selection process. The classification loss is focal loss , the regThe three pyramid levels refer to the three different scale feature maps of the YOLOv3 network, which correspond to the 79th, 91st, and 103rd layers of the YOLOv3 feature pyramid layer, respectively, as shown in In the FSAF module, IoU loss is adopted for box regression optimization. Compared with IoU loss, CIoU loss can quickly converge and improve performance, so CIoU loss is employed for box regression optimization in this paper, which further optimizes the FSAF module. The basic concept of CIoU loss is introduced in The weight parameter Generally, when the detector conducts the bounding box regression task, mean square error (MSE) loss and IoU loss can be applied to benefit the IoU metric, but they still suffer from the problems of slow convergence and inaccurate regression. To figure out these problems, CIoU loss is adopted to conduct bounding box regression task, i.e.,Then, the trade-off parameter The reason why we choose CIoU loss as bounding box regression loss of the proposed detector is that CIoU loss considers three important geometric factors, i.e., overlap area, central point distance, and aspect ratio, which will effectively increase the mAP scores of infrared multi-category object detection.After a lot of research, we found that the online feature selection loss function of the FSAF module is relatively simple. When the summations of During training, The proposal of the weight parameter According to the subsequent experimental results, the proposal of the weight parameter It is worth noting that when the anchor-free branches of the FSAF module with the weight parameter The YOLOv3 detector adopts a similar concept to FPN. Three pyramid levels of the feature maps are used to predict objects of different scales after feature fusion and tensor concatenation. As shown in the anchor-based branch structure of the YOLOv3 detector in In this paper, we add the anchor-free branches of the optimized FSAF module to the 79th, 91st, and 103rd layers of the YOLOv3 network structure, respectively. Limited by the space, Generally speaking, non-maximum suppression (NMS)  is the lTherefore, the Soft-NMS algorithm instead of NMS is used to select the final detection boxes in the experiment, which enhances the detection performance of the mutually occluded objects. The Soft-NMS algorithm decays the detection scores of all other objects as a continuous function of their overlap with the detection which has the maximum score, i.e.,In the subsequent experiments, the value of the parameter In the experiment, a total of 5322 infrared images were collected through vehicle-mounted infrared thermal imager from dozens of complex scenes, such as campuses, highways, squares, and so on. The image size was 640 × 480 pixels, and the horizontal resolutions and vertical resolutions were both 96 dpi. Referring to the ImageNet Det dataset, MS COCO  dataset The infrared image dataset contains a total of 42,907 labeled instances, and an average image contains about eight labeled instances. Referring to the evaluation metric of the PASCAL VOC dataset, the infrared image dataset uses average precision (AP) with an IoU threshold of 0.5 to evaluate the performance of the dataset. Specifically, for each category in the infrared image dataset, the precision values corresponding to all recall points under the precision-recall curve were averaged to obtain AP, and then the average of AP of all categories was mAP.All the experiments were run on a GTXG1080Ti with 11 GB memory, and the Tensorflow framework based on deep learning was used. In the process of training the detection model, we iteratively trained 36k times on our infrared image dataset, where training dataset, validation dataset, and test dataset were 60%, 20%, and 20%, respectively. The initial learning rate was 0.001, which was divided by 10 at 28k and again at 32k iterations. Weight decay was 0.0005 and momentum was 0.9. Furthermore, we conducted the data augmentation operation by using flip transformation, which flips the original image horizontally or vertically.β is necessary, it effectively optimizes the FSAF module and overcomes the challenge of the low detection accuracy of the FSAF module for motion-blurred objects. As shown in The weight parameter However, increasing the value of the weight parameter CIoU loss is effective, it makes the detection boxes of multi-category objects more accurate in the infrared images. The Soft-NMS algorithm is significant, it enhances the detection performance of the mutually occluded objects in the thermal infrared images. In complex scenes, pedestrians and vehicles will mutually occlude, and the detection boxes will overlap inevitably. As shown in the green dashed boxes in As shown in The improved detector proposed in this paper is robust, it enhances the detection performance of the detector for tiny and dense objects in infrared images. We evaluate the contribution of several important elements to our detector, including anchor-based branches, anchor-free branches, CIoU loss, and Soft-NMS. Results are reported in We first trained the YOLOv3 detector and the improved detector, using two efficient strategies including CIOU loss and Soft-NMS, respectively. When jointly optimized with anchor-based branches, the anchor-free branches of the optimized FSAF module help to learn the instances which are hard to be modeled by anchor-based branches, leading to the increased mAP scores , the FPS of the YOLOv3 detector is 20 (In future work, some strategies based on reinforcement learning  can be tIt is worth noting that the proposed method has some potential directions for further research. For example, the proposed detector can be trained on some typical optical datasets or remote sensing datasets, such as MS COCO dataset, PASCAL VOC dataset, or DOTA  dataset,This paper proposes a robust thermal infrared vehicle and pedestrian detection method in complex scenes. An important weight parameter


The global coronavirus disease 2019 (COVID-19) situation threatens not only the health of populations, but also the coherence and function of health care systems. Patients with systemic inflammatory disorders feel the overwhelming strain of COVID-19, since their disease, administered treatments, and associated comorbidities may all contribute to increased vulnerability to infection. At the same time, monitoring the activity status of rheumatic diseases and adjusting the treatments where appropriate, are important for preventing flares and other complications, which could pose additional health risks. Considering the urgent need to maintain physical distancing and self-quarantine as much as possible, we herein discuss the challenges and possible solutions pertaining to the assessment and monitoring of patients with systemic inflammatory diseases. We also discuss issues related to the prescription and supply of anti-rheumatic drugs, as well as opportunities provided by the use of technological and wireless tools. From an optimistic viewpoint, the end of this pandemic may leave us with an important legacy in utilising and implementing e-health solutions that may both improve the clinical care standards for patients with systemic inflammatory diseases and also reduce the burden placed on healthcare systems. However, under these circumstances, the regular follow-up of disease activity, the monitoring of anti-rheumatic drug’s effectiveness and toxicity with the relevant laboratory tests, the continuity in medicines’ access, and, more importantly, the surveillance of rheumatic patients regarding COVID-19 infection all become very challenging and highly demanding tasks. Rheumatology departments have to adapt to this new situation and increase their flexibility to provide advice and care to patients with systemic rheumatic diseases.The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges on physicians, patients, and health systems with several unanswered questions regarding the course, treatment, and long-term outcomes of the disease. The rapid and uncontrolled dissemination of the infection globally has clearly raised concerns about the care of several groups of patients, especially immunocompromised individuals such as those suffering from cancer, haematological malignancies, systemic inflammatory diseases, as well as transplanted persons. Particularly, in the case of rheumatic patients, the immune response to virus is perceived to be lower, due to both the disease itself and iatrogenic effects associated with the administration of corticosteroids and immunosuppressive drugs. On the other hand, maintaining disease remission in patients with systemic inflammatory disorders during a pandemic infection is of outmost importance for several reasons including the higher risk of infection in sub-optimally controlled disease state and flare-ups,9 ankylosing spondylitis  and lupus (Systemic Lupus Activity Questionnaire [SLAQ]),10 and thus may be useful tools, especially for patients who have already been acquainted in using them. However, major therapeutic decisions such as initiation, switching or discontinuation of DMARDs should be based on objective clinical assessment coupled with the patient self-assessment of her/his own disease status. Remote monitoring for laboratory investigations could be implemented by electronic messages sent directly by patients and/or laboratories to departmental portals or to physicians’ e-mail address. Should routine blood tests be safely delayed after clinical judgment including consideration of dose and duration of treatment, prior haematological or biochemical abnormalities as well as accommodations for social distancing at laboratory, patients should be advised accordingly with accurate guidance when and where to get blood work done.Even during the COVID-19 outbreak, patients with systemic rheumatic disorders need to continue to have some kind of follow-up to monitor disease status and safe administration of treatment. For clinically quiescent patients, visits could be rescheduled or transitioned to telemedicine in order to minimize physical contact for both medical professional and patients. Clinic staff should provide information about preferred telephone or video platforms for online consultations and documentation . Of note, a number of patient-completed indices exist have been validated for assessment of disease activity status in rheumatoid arthritis ,In all instances, patients should be contacted by telephone for any new or concerning symptoms, as face-to-face visits may be inevitable in many occasions, such as new cases with evolving symptoms, or patients at risk for significant negative outcomes without evaluation. In this case use of appropriate personal protective equipment  and appointments when volumes are lowest are essential. Last but not least, patients should be encouraged to call their physicians with questions, especially medical problems, between visits, providing that such communications are in line with national Data protection regulations.11 Accordingly, such individuals should be particularly stringent in following recommendations for social distancing measures and unnecessary movement. In case of appearance of symptoms suggestive of COVID-19 infection such as fever, cough and dyspnoea, the primary care provider or rheumatologist are probably the first to be contacted via telephone or other remote device. Although self-isolation is recommended if symptoms are mild, the immunosuppressive net-state of rheumatic patients imposes more urgent action regarding testing for COVID-19 compared to the general population accompanied by the necessity for prompt clinical assessment especially if symptoms persist. Immediate rheumatology consultation regarding anti-rheumatic therapy and consideration for impatient care should be considered after individualized approach.12Traditionally, patients with systemic autoimmune diseases are classified as being at higher risk for infections. Nonetheless, the “net” state of immunosuppression may show inter-individual variation and also depend on the dose and immunosuppressive potency of administered treatments.14 Through special arrangements with the pharmacists, drug prescriptions (including biologics) can now be dispensed in “paperless” ways, such as via barcoded e-mails or text messages sent to smartphones, without the need for wet signatures. Similarly, dispensing of synthetic and biologic DMARDs can be automatically renewed up to a period that varies across countries from three to twelve months, which also helps to minimize visits to physicians and pharmacists. Such practice, however, should be accompanied by vigilant patient monitoring as outlined above, in order to avoid any unnecessary drug exposure and associated adverse events.The COVID-19 pandemic has also imposed significant challenges on the prescription and access to chronic disease treatments, including anti-rheumatic drugs, due to multiple reasons such as the infrequency or even cancelling of patient visits, movement restrictions and possible shortages in the production and/or supply of selected drug compounds. To overcome these, several countries across the globe have enabled fast-track electronic prescription processes to help protect people most at-risk in the community from possible exposure to the virus.Another relevant issue is the physical process of obtaining drug refills, including biological (or targeted synthetic) DMARDs, in particular the need for patients (or their authorized proxies) to move to pharmacies and get the needed medications. To facilitate this, some national health care systems have gradually implemented free-of-charge drug delivery options, and similar initiatives are also supported by several drug pharma companies in the context of their Patient Support Programs.15 A notable example is hydroxychloroquine, officially labelled for the treatment of cutaneous lupus, systemic lupus erythematosus, and rheumatoid arthritis, which has yielded signs for possible efficacy against the COVID-19 virus.17 This caused a tremendous worldwide increase in the demand for drug supply by the hospital units treating COVID-19 cases. At the same time, publicity over the possible therapeutic use of the drug led to excessive drug prescription to outpatients. Inevitably, hydroxychloroquine supplies ran into temporary shortage, thus causing anxiety to Rheumatologists and patients, especially those with SLE, due to the well-known risk for disease exacerbation upon drug withdrawal. Coordinated actions to set more stringent rules for hydroxychloroquine prescription and increase global drug production has gradually restored the supply and availability of the compound although close monitoring of the situation will be required over the ensuring months.Finally, concerns have been raised over the possible shortage in the production and/or supply of certain medications including anti-rheumatic agents. Although, to date, the COVID-19 pandemic has not significantly impacted industrial drug production, the availability of certain agents has been challenged due to their redirection for the treatment of COVID-19 infection and/or its complications.18 The tight control and monitoring of disease activity as well as the adjustment of treatment to accomplish the predefined target, require frequent follow-up visits which are difficult to be achieved with the traditional management approach in rheumatology clinics. Therefore, there is an emerging need for the implementation of e-health applications in daily clinical practice, which can allow the reduction of face-to-face communication, the easier collection of clinical data, as well as the engagement of patients in treatment and other health-related decisions. Mobile health systems consisting of personal technology tools such home PCs or mobile phones, remote video consultation, virtual clinics and other web-based applications could overcome barriers of rheumatology personnel shortage, timely access to health information, and prioritisation of patients who may require a clinical evaluation and prevent delay in treatment modification.19 However, remote patient monitoring in the field of rheumatic diseases is in its infancy compared to other chronic diseases, such as diabetes mellitus and hypertension, despite some promising data from large registries and clinical trials.21 Undoubtedly, mobility and other restrictions due to the COVID-19 pandemic represent an excellent opportunity not only for rheumatologists, but also for the patients to familiarise themselves with modern technology modalities and innovative tools to implement remote monitoring and consulting in the daily practice setting. Given that the duration of the post-pandemic period is uncertain, with some models predicting that epidemiologic surveillance should be maintained as late as 2024 to anticipate the possibility of COVID-19 resurgence,22 the appropriate use of e-health modalities may generate unlimited possibilities for various types of interaction between rheumatology care providers and patients, and result in transformation of rheumatology care by effective communication and empowerment of patients. The design of user-friendly, flexible electronic tools able to fulfil disease-specific needs, the support of adaptable wireless technologies, the minimisation of technical problems which interrupt network communication as well as the compliance with legal and ethical issues are important aspects for the successful introduction and widest usage of modern technology applications during this period and the future.Over the last decade “treat-to-target” has become a standard treatment strategy leading to improved long term outcomes for patients suffering from systemic rheumatic diseases.The COVID-19 pandemic inevitably affects the care of patients with complex rheumatic diseases on several grounds, but also conveys unique challenges and opportunities for rheumatology centres. The optimal management of patients with systemic diseases remains the overhanging goal of rheumatology practice during this lockdown period despite practical issues and travel restrictions. The incorporation of modern technology tools could assist in remote monitoring and medical advice when required in order to ensure the best possible outcomes for rheumatic patients during this pandemic period.


Fingerprints are an important kind of material evidence with the key function in personal identification, which are unique and life-long to everyone. Latent (invisible) fingerprints are common at the crime scene, needing to be visualized with proper methods in order to identify sources of the fingerprints in routine forensic practice. Fluorescent imaging of latent fingerprints has the advantage of high contrast, sensitivity, selectivity, and less dependency on instruments. Taking the environment and users' safety into consideration, organic materials for fluorescent imaging of latent fingerprints are reviewed mainly in recent 5 years. New strategies of fingerprint reagents and improved performances established for fingerprint development based on fluorescent organic materials are discussed in the view of forensic practice. In addition, we briefly highlight current challenges of recent fluorescent imaging works based on organic materials for the latent fingerprints development in forensic practice. Fingerprints have been one of the most important gold biometric features for personal identification in the forensic science field for more than 100 years, because of the uniqueness and lasting consistency over the lifetime. A fingerprint is an impression of the pattern of ridges (raised) and furrows (recessed) formed when a finger makes contact with a surface. Most fingerprints are invisible to the naked eye at the crime scene, also known as latent fingerprints (LFPs). LFPs could be exploited as a potential key evidence in countless cases of serious crime, requiring a special development process in order to visualize them by the police or other authorities. To identify individuals with fingerprints, there are three levels of fingerprint recognition. The first-level features are macro details mainly used for the pattern classification, not distinctive enough to recognize fingerprint. The second-level features (minutia points) are distinctive and stable, widely used for distinguishing the uniqueness of fingerprint, while the third-level features (pores and ridge contours) are the dimension attributes of the ridges to provide more accurate and robust details for accurate fingerprint recognition. Nowadays, many methods exist as standard methods for the development of the LFPs on common substrates in routine forensic practice  are widely applied in materials and biomedical fields because of the controllable size, facile synthesis, ease of functionalization, excellent biocompatibility, optical transparency, and low toxicity, SiNP is a good matrix for organic dyes to improve the affinity to fingerprint residues in recent research  with AIE feature were reported to develop LFPs down to the second-level details on different non-porous substrates by a portable wet method in the THF/water mixture for a 2-min enhancement  was applied for LFP imaging in the DMSO/H2O mixture over a non-porous glass slide , and yellow tapes. Fluorescent images of LFPs on different substrates exhibited clear blue fingerprint patterns under 365-nm UV light, maintaining sufficiently high resolution and contrast between the ridges and spaces, as seen in Aggregation-induced enhanced emission-active conjugated polyelectrolyte was confirmed the ability for LFP imaging with high resolution on multiple smooth non-porous substrates without any additional treatment. The LFP development process was accomplished simply by immersing fingerprint-loaded substrate into the solution for ~1 min, followed by shaking off the residual polymer solution and air drying. The images revealed clearly the third-level details with high selectivity and high contrast (Malik et al., Given the value of fingerprint evidence in criminal investigations, the main thrust of this mini-review is to remain focused on increasing the likelihood of LFP development based on fluorescent organic materials. Despite traditional LFP powders and fuming methods as standard processes for the development of LFPs in forensic practice for years, there has been significant research to discover new fluorescent imaging methods that offer operational advantages. As LFP development is daily work of crime science investigators and forensic scientists that may perform everywhere, LFP-developing reagents should be friendly to the environment and users. Fluorescent organic materials with various improvers possess excellent biocompatibility, low or no cytotoxicity, low cost, convenience, and environment friendliness, showing excellent performance as LFP development reagents with less dependency on instruments, high contrast, and room operating temperature in the mentioned research. As fluorescent organic materials applied for LFP imaging, the handing of LFPs can be in powder dusting or wet methods, which are common in standard processes for the development of LFPs in forensic practice, making the new technology easy to accept, and promote.Despite the remarkable applicability and performances of various fluorescent organic materials, there are still challenges that need to be addressed. First, most of the research focus on the application of several LFP substrates. The ideal LFP developing method should be useful on both porous and non-porous, both dry and wet surfaces, so more LFP substrates should be discussed in the comprehensive evaluation of a new method.The fluorescent imaging of LFPs with low background has obvious advantages of sensitivity and convenience over traditional LFP development, achieving LFP images with high contrast and resolution. Taking the three levels of features into consideration, most of the research reached the second-level or third-level precision with the potential of further practical applications, even validated by the scientific protocol of the Police Automated Fingerprint Identification System or computer-assisted evaluation programs. Moreover, smartphones and a specific designed digital-processing program for imaging enhancement are applied for the analysis of the LFP imaging results. In practice, fingerprints from crime scene are always incomplete or damaged and need more details of third-level precision to be recognized. Fluorescent imaging methods with third-level precision or imaging enhancement are of great practical significance. Meanwhile, the conditions of the research were ideal, and some reported works talked about aged LFPs, but overlapped LFPs, immersed LFPs, and DNA-recovered LFPs were barely mentioned. Finally, antibodies, aptamers, or molecular imprinting materials combined with QDs or rare earth nanomaterials were successfully applied for fingerprint residues in fingerprints, such as illegal drugs and explosives, but these highly selective reagents have not been combined with fluorescent organic materials (Lam et al., Continued research in this field will require expertise in chemical synthesis, material science, life science, and advanced spectroscopy, and thus, there is ample room for forensic science researchers to help improve and extend the key forensic technique. Active research in this area will continue into the foreseeable future in order to promote and improve latent fingerprint development to assist with the efficiency of criminal investigations and personal identifications.JL and FM conceived the concept, conducted literature survey, drafted, and revised the manuscript. All the authors organized figures and approved 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.


The roots of modern-style ecosystems go back to the Carnian (ca. 233 Ma), a time of global climate change and extinction. The Carnian Pluvial Episode (Late Triassic) was a time of global environmental changes and possibly substantial coeval volcanism. The extent of the biological turnover in marine and terrestrial ecosystems is not well understood. Here, we present a meta-analysis of fossil data that suggests a substantial reduction in generic and species richness and the disappearance of 33% of marine genera. This crisis triggered major radiations. In the sea, the rise of the first scleractinian reefs and rock-forming calcareous nannofossils points to substantial changes in ocean chemistry. On land, there were major diversifications and originations of conifers, insects, dinosaurs, crocodiles, lizards, turtles, and mammals. Although there is uncertainty on the precise age of some of the recorded biological changes, these observations indicate that the Carnian Pluvial Episode was linked to a major extinction event and might have been the trigger of the spectacular radiation of many key groups that dominate modern ecosystems. The Carnian, Late Triassic , marks aRecent field studies show that the CPE was a global phenomenon . ThAustrotrachyceras in the Julian  are scarce because most Triassic oceanic crust and sediment has been subducted, and the accreted fragments are often deformed and thermally altered. Nonetheless, a climatic signal can be deduced from the successions in Japan , where tDuring the CPE, a major change in shallow carbonate systems saw the shift from microbially dominated carbonate-producing ecosystems (carbonate factories) to less productive metazoan-dominated ecosystems, with the appearance of modern-style scleractinian coral reefs . This coincided with the first C-isotope excursion at the onset of the CPE  1, 2, 5 extended2) in Earth history  records . ThDaxatina, Trachyceras, and Austrotrachyceras  and produced diverse morphologies (High-resolution biodiversity data (at biozone level) can be compiled for ammonoids and conodonts, the principal biostratigraphic markers for the marine Late Triassic . This alchyceras  and highchyceras . The AusConodonts also underwent a major turnover during the CPE  Many crinoid groups, such as Encrinidae and Isocrinina . These cPithonella group; Prinsiosphaera makes up >50% of rock volume in the Rhaetian pelagic chalks of Sicily  suffered a major crisis during the CPE, when all groups experienced a decline in diversity of 51 to 62%  seem to have experienced a major expansion event in the Carnian. The oldest known rhynchocephalian is from the Ladinian of Germany, Vellberg [Middle Triassic; (Odontochelys), with a fully developed plastron  and a dorsal carapace composed of neural plates (early stages of carapace formation), was found in the Wayao Formation of China (Proganochelys), are from the Norian of Germany  . ThBiodiversity data  and 3. W3 production from neritic environments into deeper waters  reef communities is indeed a remarkable characteristic of the CPE when compared to other extinction events. During the end-Triassic extinction, coral reefs were severely damaged and fully recovered only in the middle Jurassic . During the KTR, terrestrial biodiversity exceeded that in the sea, and the angiosperms rose to ecological dominance  are found in Vancouver Island [Daonella bivalves, which are Ladinian in age, are present on Vancouver Island and Wrangell Mountain  that could also have also played a role in triggering the observed changes . As hypothesized for other LIP-related events, release of additional 13C-depleted CO2 from ocean floor methane clathrates (δ13C = −60‰) and/or organic-rich sediments (δ13C = −35 to −50‰) could have increased the greenhouse effect and contributed to the NCIE  on reaction with water. Acid rain affects terrestrial ecosystems by acidifying soils, lakes, and streams and damages plants and aquatic animals  time of extinction and may be linked to the Carnian explosive diversification of many key modern groups of plants and animals. Evidence indicates a possible cascade of events similar to other mass extinctions: LIP eruption as the trigger, release of volcanic gases, rapid shifts in temperature and δ1) Stratigraphic resolution needs improvement through additional radioisotopic dates and magnetostratigraphy to better constrain the timing of extinction and radiation and their temporal link with the CPE. Existing data indicate that most of the observed biological changes actually happened during the CPE, but for many groups, especially for terrestrial fauna and flora, the age uncertainty is still too large to define a precise link with this event.13C records across the CPE, from both continental and marine settings, and from different latitudes.2) Records of carbon cycling would benefit from additional δ2 are needed through the CPE.3) Reconstructions of atmospheric pCO4) Records of anoxia, nutrient feedbacks, and sulfur cycling are sparse or absent; hence, state-of-the-art geochemical techniques like Fe and P speciation, S-isotope analysis, and trace metal analysis could help to better define and constrain the complex series of biogeochemical phenomena that mark the CPE.5) Improving the resolution of the existing palaeobiology databases like the PBDB. The CPE extinction is a within-stage event that is difficult to capture given the current resolution of data stored in the major databases: Our meta-analysis shows that a rigorous and detailed revision of the PBDB entries and improvement of resolution (at biozone level in the case of ammonoids and conodonts) actually reveal the major turnover that marks the CPE and that previously was only qualitatively defined.6) It is crucial to better constrain the age of the Wrangellia eruptions with improved radioisotopic dating to precisely fix the onset of the LIP volcanism and its duration and calculate the rates at which the magma was erupted and the gases were released into the atmosphere-ocean-land system. More geochemical data  are also needed to trace Wrangellia volcanism in the sedimentary record and therefore understand the causal relationships with the observed biological changes.Integrating detailed stratigraphic, geochemical, and radioisotope data will clarify the sequence of events and possible cause-and-effect relationships, so helping in understanding this unique interval in Earth history and the intimate causes of the extinction and, maybe most crucially, the unique diversification event that led to the formation of modern ecosystems. This will also put the CPE in the framework of long-term changes that characterize the entire Triassic. Last, understanding the complex interactions between volcanism, environmental, and biological changes during the CPE might reveal crucial information about the mechanisms that initially controlled the Mesozoic transition toward the modern Earth system.


The pain, which originates from the viscera of the upper abdomen, is transmitted by visceral afferent fibers that relay the impulses through the splanchnic nerves and the celiac plexus. As illustrated in ,3.Abdominal pain is a significant debilitating problem that is common in cancer patients, dramatically affecting quality of life and survival,2. Although therapies employing imaging-guided percutaneous methods reduce the need for potent analgesics and the associated toxicity, such procedures are not widely disseminated and are underused,4-8.The management of cancer-related abdominal pain is complex and challenging, often requiring the chronic use of high doses of opioids, which in turn are generally associated with several adverse effects,10. It involves the infusion of a neurolytic agent, typically sterile absolute alcohol, through a fine needle inserted into the retroperitoneum, adjacent to nerve fibers and the ganglia of the celiac plexus. The neurolytic agent disrupts the neural network, interrupting the pain pathways,11. Imaging guidance for CPN is most often performed by computed tomography (CT), which has replaced fluoroscopy and ultrasound for that purpose,12.Celiac plexus neurolysis (CPN) is a technique that provides permanent interruption of plexus pain transmission through chemical ablation, potentially improving pain control while dramatically reducing opioid consumptionThe first step in CT-guided NPC is pre-procedure planning. Preoperative images should be reviewed in detail to determine the positioning of the patient, as well as to select the puncture site, needle path, and neurolytic injection site . The preVarious approaches to CPN can be taken, including anterior and posterior approaches, the bilateral posterior paravertebral approach being the one most frequently employed . Local aAfter CT-guided puncture and verification of the correct positioning of the needle(s), with or without injection of 1-2 mL of iodinated contrast agent, a total volume of 40-60 mL of the neurolytic agent  is infused . At our As a tool for palliative pain management, CPN is safe and effective, with a relatively low complication rate. It should be offered to patients as a key component of a multidisciplinary approach to the control of intractable chronic abdominal pain. Proper use and knowledge of imaging examinations and of the technique are invaluable to ensuring satisfactory results.


Pathogenic microorganisms exploit host metabolism for sustained survival by rewiring its metabolic interactions. Therefore, several metabolic changes are induced in both pathogen and host cells in the course of infection. A systems-based approach to elucidate those changes includes the integrative use of genome-scale metabolic networks and molecular omics data, with the overall goal of better characterizing infection mechanisms for novel treatment strategies. This review focuses on novel aspects of metabolism-oriented systems-based investigation of pathogen-human interactions. The reviewed approaches are the generation of dual-omics data for the characterization of metabolic signatures of pathogen-host interactions, the reconstruction of pathogen-host integrated genome-scale metabolic networks, which has a high potential to be applied to pathogen-gut microbiota interactions, and the structure-based analysis of enzymes playing role in those interactions. The integrative use of those approaches will pave the way for the identification of novel biomarkers and drug targets for the prediction and prevention of infectious diseases. One major focus of systems biology in medical research is the integrated use of high-throughput omics data and molecular interaction networks, with the overall goal of elucidating molecular mechanisms of diseases to identify potential biomarkers and personalized treatment strategies. A wealth of research has been conducted to apply this approach on infectious diseases by focusing on cell metabolism. This included collecting transcriptomic, proteomic, or metabolomic data from pathogens or infected hosts on one side, and developing interaction models focusing on the enzymes and reactions of crucial metabolic pathways on the other side Bumann, .Rather than investigating host and pathogen metabolisms separately, novel systems biology based approaches consider the pathogen-host interaction (PHI) system as a whole to elucidate the mechanisms of infection. Here, omics data is collected from both organisms in a single experiment, termed dual-omics data, focusing on all the molecules within the PHI system . The bacteria CjR is now resistant to many antibiotics. Therefore, there is a need to predict new drug targets based on unique and new pathways of the resistant CjR. In the first phase, the authors used the complete protein set of the resistant CjR to prioritize the essential proteins of CjR taking role in unique metabolic pathways. These unique pathways were pathogen specific only, therefore, absent in the host organism. In the next step, the authors filtered out the human homolog proteins. Finally, using this subtractive genomics strategy, they identified 38 eligible therapeutic targets, about 10 of which were metabolic enzymes. They studied corresponding 3D structural interactions with FDA-approved drugs. Additionally, they identified peptidoglycan biosynthesis as a pathway based drug target, to be explored by experimental methods. To help future research, a comprehensive database was also made, and it has 3D structure and other related data of the listed drug targets.Hossain et al.  presenteEntamoeba histolytica, Leishmania donovani, Trichomonas vaginalis, and Salmonella typhimurium. Since the Sulfur metabolism pathway is absent in human and all other mammals, the enzymes taking role in this pathway were best considered as drug targets and subjected to the structure based methods to predict potential strong binders , which is the main source of nosocomial infection worldwide, Uddin et al. (The pathogens and host relationship is governed by the Protein-Protein Interactions (PPIs) and several of those interactions can involve enzymes. With methicillin resistant n et al.  developen et al.  the pathWith the birth of dual-omics technologies, we have entered a new era where interactions between pathogens and their host can be directly predicted to unravel molecular mechanisms of infectious diseases. Although integrated pathogen-host GMNs are currently scarce, we believe that the increase in the number of dual omics datasets, especially dual RNA-seq studies, will pave the way for the reconstruction of more and more integrated GMNs . MappingTÇ conceived the study. TÇ, GP, RU, and SD wrote the manuscript.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.


As a spontaneous facial expression, a micro-expression can reveal the psychological responses of human beings. Thus, micro-expression recognition can be widely studied and applied for its potentiality in clinical diagnosis, psychological research, and security. However, micro-expression recognition is a formidable challenge due to the short-lived time frame and low-intensity of the facial actions. In this paper, a sparse spatiotemporal descriptor for micro-expression recognition is developed by using the Enhanced Local Cube Binary Pattern (Enhanced LCBP). The proposed Enhanced LCBP is composed of three complementary binary features containing Spatial Difference Local Cube Binary Patterns , Temporal Direction Local Cube Binary Patterns , and Temporal Gradient Local Cube Binary Patterns . With the application of Enhanced LCBP, it would no longer be a problem to provide binary features with spatiotemporal domain complementarity to capture subtle facial changes. In addition, due to the redundant information existing among the division grids, which affects the ability of descriptors to distinguish micro-expressions, the Multi-Regional Joint Sparse Learning is designed to perform feature selection for the division grids, thus paying more attention to the critical local regions. Finally, the Multi-kernel Support Vector Machine (SVM) is employed to fuse the selected features for the final classification. The proposed method exhibits great advantage and achieves promising results on four spontaneous micro-expression datasets. Through further observation of parameter evaluation and confusion matrix, the sufficiency and effectiveness of the proposed method are proved. As a spontaneous, low-intensity facial expression, micro-expression (ME) is a non-verbal way of expressing emotions, and it reveals the inner emotional state of human beings . LastingSince MEs are almost imperceptible to human beings, their subtlety and brevity impose significant challenges for observation with the naked eye. In this field, Ekman developed the first ME training tool (METT) . After MThe ME recognition research based on computer vision includes three steps: pre-processing, feature representation, and classification . The devBased on reports, LBP, a typical handcrafted technique, is widely used in various pattern recognition tasks due to its outstanding advantages, such as computational efficiency, robustness to gray-scale changes, and rotation invariance. Similarly, as a three-dimensional (3D) extension of LBP, local binary patterns from three orthogonal planes (LBP-TOP) was first applied for the ME recognition task , which cIn this paper, a sparse spatiotemporal descriptor for ME recognition using Enhanced Local Cube Binary Pattern (Enhanced LCBP) is developed to classify MEs. The framework of the proposed method is shown in The structure of this paper is as follows: State-of-the-art ME recognition methods can be broadly classified into three categories: optical flow, LBP descriptors, and deep learning algorithms. The related work of these three methods is briefly reviewed in this section.The purpose of optical-flow estimation is to observe the facial motion information between adjacent frames. The optical-flow-based techniques calculate the pixel changes in the time domain and the correlation between adjacent frames to find the correspondence of facial action between the previous frame and the current frame. To answer the challenges of short duration and low intensity of MEs, Liu et al.  proposedTaken together, the optical-flow field can effectively convey temporal micro-level variations in MEs. Since OP-based features can describe the location and geometry of refined facial landmarks, they require a more precise facial alignment process. This brings some complexity to the ME recognition process and the current models. Meanwhile, its sensitivity to illumination changes makes it highly susceptible to background noise, which causes the OP-based method to amplify local facial details while also amplifying redundant information.Since the spatiotemporal features play an important role in identifying ME, these LBP-based studies on ME recognition have gradually developed towards improvement in encoding time-domain representations. Earlier work explored extending different coding patterns to three orthogonal planes to develop descriptors that are robust to time-domain changes, including LBP-TOP , CentralThe LBP technique is more effective than the optical flow technique and therefore has a broader application. The coding patterns of existing methods are based on capturing time-domain information in three orthogonal planes. For these reasons, the motion cues in other directions, and the temporal correlation between adjacent frames are ignored to some extent. Although the LBP-based approach provides a refined description of the local texture, the relationship between different local regions and the relationship between the same local locations in different temporal sequences can still not be disregarded. Additionally, the higher feature dimensions and the redundancy of representations also constrain the model’s recognition performance. Based on the above discussion, it is not surprising to see that research on ME recognition based on LBP technology still has great promise. In particular, an effective combination of multiple coding patterns and correlation modeling between descriptors will make the results of the ME recognition approach more compelling.In recent years, with its advantages of avoiding manual function design, the success of deep learning in a wide range of applications has been witnessed. Many researchers have tried to apply deep learning techniques to the field of ME recognition. Khor et al.  proposedIndeed, the application of deep learning has provided an important boost to the study of ME recognition. Although deep learning models have been applied in studies of ME recognition with good results in some studies, the limited sample size still constrains the maximization of its potential. According to some reports, the main problem for researchers with deep learning models is in dealing with limited training data. Moreover, due to the trigger mechanism and spontaneity of MEs, it is extremely complex to construct large datasets for ME recognition tasks by deliberately controlling the subtle movements of facial muscles.In accordance with the above discussion, the main idea of our solution is adequately extending the advantages of binary patterns to the time-domain for capturing rich facial movements, which is the key to ME recognition algorithms. For this purpose, three important issues need to be considered. To begin with, a suitable binary feature descriptor needs to be developed for the ME recognition task. Maintaining this binary encoding pattern with its theoretical simplicity, high computational efficiency, and excellent spatial texture representation capabilities is important. Unlike the traditional LBP-TOP, simply extending to the three orthogonal planes cannot capture the expected spatiotemporal variation. Due to the demand for spatiotemporal information for the ME recognition, we developed spatial and temporal descriptors emphasizing the complementary properties of the temporal and spatial domains. The proposed Enhanced LCBP integrates spatial differences, temporal directions, and temporal intensity changes in local regions, which aims to provide more evidence of facial action to predict MEs.Second, Enhanced LCBP requires capturing local representations by division grids. Within this context, it is necessary to consider not only the relationships between the local regions triggered by MEs, but also the redundancy of information caused by the fusion of multiple descriptors. For this purpose, to enhance the sparsity and discriminability of the representation, the Multi-Regional Joint Sparse Learning is proposed to implement feature selection between different grids. Specifically, to prevent over-fitting caused by the high-dimensional vector, the Third, the existing literature  reports (1)In order to achieve our goal of fully exploiting the implied spatiotemporal information, an Enhanced LCBP binary descriptor is proposed that encodes subtle changes from different aspects, including spatial differences, temporal directions, and temporal intensity changes. Our research focuses on extracting the complementary features by integrating the spatial and temporal descriptors, thereby obtaining richer temporal variations that are robust to subtle facial action. With the help of descriptors, it is possible to provide binary representations containing more detail changes in the spatiotemporal domain, thus the discriminatory information implicit in the image sequence could be revealed;(2)Second, to alleviate the interference of high-dimensional vectors on the learning algorithm, the Multi-Regional Joint Sparse Learning is designed to conduct feature selection, and thereby the discriminatory power of the representation is enhanced. Moreover, the proposed feature selection model can effectively model the intrinsic correlation among local regions, which can be utilized to focus the attention on important local regions, thus clearly describing the local spatial changes triggered by facial MEs;(3)Sparse representations of spatial and temporal domains are mapped to different kernel spaces, aiming to exploit the different mapping capabilities of the individual kernel, which are further integrated into the synthetic kernel space. This takes full advantage of the more accurate and powerful classification capabilities of the multi-kernel SVM, especially for the fusion of multiple descriptors in our model, whose benefits are clear.To summarize, the contribution of this paper is presented as follows:As shown in The image feature descriptor, a fundamental but crucial technique for pattern recognition research, has the core design requirements of robustness and differentiation. Especially for challenging recognition tasks, developing image descriptors with more applicable features for different tasks is an effective way to improve the method overall. For challenging tasks like ME recognition, the effectiveness of the method can be enhanced by developing image descriptors with more adaptability for different tasks. As an excellent demonstration, LBP-TOP extends the encoding coverage to the three orthogonal planes in response to the loss of time-domain information in LBP, thus it can become one of the mainstream descriptors for ME recognition. To be specific, LBP considers capturing spatial textures, using the relationship between the center pixel and neighboring pixels. The difference between neighboring and center pixels is coded as 1 when it is non-negative, and 0 otherwise. Further, LBP-TOP extends this center-neighbor relationship to the three orthogonal planes. As shown in Despite the fact that LBP-TOP integrates clues that exist in both the time-domain and spatial-domain, it has some limitations. Facial spatial features are the basis of emotional state analysis. The LBP-based methods all employ texture analysis of the XY plane to obtain facial spatial representations. However, for video image sequences, the correlation in spatial-domain is closely related to temporal domain variation. Specifically, due to the continuous spatial difference between two adjacent frames in the image sequence, this leads to a spatial coherence between adjacent frames that correlates with temporal variation, and the temporal facial action can be represented by spatial differences in binary features. This implies that the spatial difference not only expresses the relationship of spatial texture, but also reveals variation at the temporal level. In this context, the more detailed descriptions of spatial features and spatial differences can provide powerful clues to the ME recognition task. However, this correlation of local spatial differences between adjacent frames is easily disregarded. In other words, the missing consideration of the variation between the local spatial regions at different moments leads to an incomplete representation of the spatial coherence between adjacent frames. Simply focusing on spatial texture is not effective in capturing spatial differences. Therefore, the spatial difference needs to be further supplemented to the binary features.According to reports , the spaMoreover, while feature encoding in the three orthogonal planes does compensate for the loss of time-domain information, the problem of missing time-domain information remains. This is mainly reflected in the fact that the coding range is confined to three orthogonal plane areas. For the different feature encoding methods, the main purpose of encoding is to measure the facial action trend of the central pixels in the local region, which includes the temporal directions and the temporal intensity changes. Moreover, all of this spatiotemporal information, which manifests as changes in pixel brightness, is triggered by facial action. For the direction of facial action, our previous research of ME recognition demonstrates that facial actions are not limited to the temporal orthogonal planes . Herein,Similar to the representation of the temporal directions, the temporal intensity changes in local regions are also the key to ME recognition. With respect to the facial action, the temporal intensity changes reveal the dominant information of the facial action trend. Therefore, the intensity changes in local regions are also important to supplement the spatiotemporal information of binary features.Based on the above discussion, complementary descriptors need to be applied to capture different spatiotemporal features. This is the main distinction between handcrafted techniques and deep learning, and it is for this reason that there are binary features allowing the customization of encoding schemes for different tasks. Meanwhile, it has been reported that the encoding in cube space is more conducive to capturing valid ME information than the three-dimensional orthogonal plane, since the latter may introduce noise from features acquired indirectly . TherefoAccording to the above discussion, the spatial difference between adjacent frames within the same local area, i.e., within the cube space, is often an easily ignored problem. To supply spatial differences between adjacent frames, the Spatial Difference LCBP is proposed to enrich the spatial representation of binary features. Since the different binary patterns are essentially encoded around the relationship of the central pixel to the neighboring pixels, this eliminates the problem of light variation to some extent while gaining the advantage of better computational efficiency and gray-scale invariance. Along these lines, we extend this idea to encoding spatial difference, hoping to enrich feature representations by focusing on the variation in the relationship between different central pixels and neighboring pixels. Unlike LBP, the proposed binary pattern measures the relationship between different central pixels and the fixed neighboring pixels. s(·) is the sign function, which is used to calculate the binary codes. Specifically, the three central pixels of the cube (red positions) calculate the difference with the neighboring pixels of the fixed frame (blue positions), respectively. The Spatial Difference LCBP code for each center pixel can be defined as:As shown in The histograms of the difference among the three center pixels and the neighboring pixels are calculated separately, and finally cascaded into a complete Spatial Difference LCBP feature, which contains the spatial central differences associated with the temporal variation. For this purpose, the trend of the central pixels within the cube is emphasized, and more evidence of facial movement is added to the spatial features.Discussion based on the statistical diagram of the motion direction indicates the importance of temporal direction in facial action, which is the purpose of the proposed Temporal Direction LCBP.In our previous research , the comThus, as an improvement of LCBP, the proposed Temporal Direction LCBP exploits the directional response values in the multiple temporal planes to provide more evidence of facial actions, complementing the direction encoding in the XT and YT planes that the LCBP ignores. As shown in To be specific, the In the above equation, The four Temporal Direction LCBP codes extracted from the In addition to the temporal direction and spatial differences, the intensity changes of the central pixels are also critical to describe facial action. An efficient way to represent the temporal intensity changes is to use the gradient information of the central pixels in the time domain direction. This is because the gradient information reflects the changing relationship of the central pixels at different moments, which provides an adequate clue for the description of temporal intensity.Specifically, as shown in (1)the binary code is 11 when (2)the binary code is 00 when (3)the binary code is 10 when (4)the binary code is 11 when Temporal Gradient LCBP defines the gradient changes by the following four cases:In all four cases, the intensity changes in the temporal direction are judged by two inter-frame gradient variation, so that the sampling range covers all pixels in the cube space. The first two cases reveal that the local region contains continuously displaced motions along the same direction, usually indicating a significant change in the brightness of the pixel. By contrast, the latter two cases imply that the temporal direction of the local region displacement is unstable, usually indicating that the brightness variation of the pixel is fluctuating. The feature histogram is calculated based on the four cases as a Temporal Gradient LCBP feature, which constitutes a complete Enhanced LCBP feature with the other two binary features. The more compact and discriminative representation is further obtained using the Multi-Regional Joint Sparse Learning model while ensuring that time and space domain variations are encoded.For the LBP-based ME recognition method, MEs are predicted by the feature of the local areas extracted from the descriptor. Since the statistical features used in the LBP-based methods do not contain local location information, dividing the image into grids is the solution to extract the location information.In fact, it is clear that not all grids contain valid recognition features for predicting MEs. Some of these grid features are redundant, which reduces the efficiency of the LBP-based classification scheme. The facial action units account for the creation of such redundant features. Specifically, the Facial Action Coding System (FACS) define basic facial movement units based on the dynamic characteristics of particular facial muscles, and the MEs can be decomposed into individual action units, which are the typical features that are used to distinguish different kinds of emotions. Thus, for different local regions, the Multi-Regional Joint Sparse Learning is proposed to quantify their various contributions to the recognition task.As mentioned earlier, we hope to select those facial regions that trigger MEs, since only these facial grids contribute significantly to the recognition task. To address this issue, the linear regression regularization is an effective solution to perform Multi-Regional Joint Sparse Learning. Regularization is an implementation of the structural risk minimization strategy, which selects models with both less empirical risk and model complexity by adding a regularization term to the empirical risk. Furthermore, the global feature selection is formulated as a multi-task regression problem by treating the feature selection for each facial grid as a single regression task. Consider a multi-task regression problem with 𝛽 facial grids, an efficient approach is to estimate the feature selection weights W by minimizing the following objective function:Further, since the variation in appearance between different classes is not evident, this negatively affects the discriminative power of the representations. In order to enhance the inter-class differences of the representation, the inter-class distance penalty term is introduced to constrain the feature distance among the different classes, which allows the inter-class distance to be improved. Thus, we add the constraint of interclass distance to the proposed Multi-Regional Joint Sparse Learning model.Moreover, the limited training sample results in a greater feature dimension compared with the sample size. In response, dimensionality reduction is an effective strategy to address the risk of over-fitting. Least Absolute Shrinkage and Selection Operator (LASSO) is a regression analysis method that performs both feature selection and regularization. It can be used for parameter selection through parameter reduction; thus, the purpose of dimensionality reduction can be achieved. Although LASSO can produce some regression coefficients strictly equal to 0 to obtain models with strong explanatory power, it needs to choose several single variables instead of general factor selection, to represent the pixels of each image . For thiThe third term in Equation (10) is the constraint of interclass distance.Since the proposed objective function contains the lgorithm  can be uSecond, the function posed in , Hρ , ChineseSMIC contains 164 ME videos across 16 subjects. All samples are classified into three categories, i.e., Positive (51 samples), Negative (70 samples), and Surprising (43 samples). SMIC data are available in three versions: high-speed camera (HS) version at 100 fps, normal vision camera (VIS) version at 25 fps, and near-infrared camera (NIR) version at 25 fps. In this paper, the HS samples are used for experiments.CASME-I contains 195 ME video clips from 19 subjects. All samples are coded with the onset frames, apex frames and offset frames, and marked with action units (AUs) and expression states. There are eight classes of MEs in this database, i.e., Tense, Disgust, Repression, Surprise, Happiness, Fear, Sadness, and Contempt. Due to the limited sample size in the categories of Happiness, Fear, Contempt, and Sadness, we chose the remaining four categories: Tension (69 samples), Disgust (44 samples), Repression (38 samples), and Surprise (20 samples) for the experiment.CASME-II is an updated version of CASME-I and contains 247 ME videos from 26 subjects. All samples were classified into seven classes, i.e., Disgust, Repression, Surprise, Happiness, Others, Fear, and Sadness, and all samples were also marked with onset frame, apex frame, offset frame, and action units (AUs). The temporal resolution of CASME-II was improved from 60 fps in CASME-I to 200 fps. The spatial resolution has also improved, with a partial face resolution of 280 × 340. Because of the limited sample size in the Fear and Sadness groups, the remaining five classes were selected for the experiment, i.e., Disgust (64 samples), Repression (27 samples), Surprise (25 samples), Happiness (32 samples), and Others (99 samples).SAMM database contains 159 ME video clips from 29 subjects. All samples were recorded at a time resolution of 200 frames per second. These samples were divided into seven AU based objective classes. For the convenience of the comparison with our previous research, the samples used for the experiment were divided into five classes based on the emotional link of AUs in FACS, which consisted of Happiness (24 samples), Surprise (13 samples), Anger (20 samples), Disgust (8 samples), and Sadness (3 samples).(1)pre-cropped video frames provided in SMIC, CASME, and CASME-II were used as experimental data. For images in SAMM, facial images are extracted using the Dlib face detection  and resi(2)due to the different time lengths of these four datasets, the temporal interpolation model (TIM)  is used (3)leave-one-subject-out (LOSO) cross-validation  is used (4)overall recognition accuracy and F1 scores are used to evaluate the performance of the model. Recognition accuracy can be calculated by the following equation:For the convenience in the analysis of the results, our implementation follows the same data pre-processing and evaluation protocol as in the previous work:The binary feature histogram of Enhanced LCBP consists of three complementary spatial and temporal descriptors, i.e., Spatial Difference LCBP, Temporal Direction LCBP, Temporal Gradient LCBP. In addition, there are three parameters that need to be adjusted in the objective function of our proposed Multi-Regional Joint Sparse Learning, i.e., Furthermore, since grid division parameters affect model performance, fewer grids result in insufficient location information and detailed changes, while excessive grids may bring the noise. Therefore, we discuss the impact of different grid division parameters on recognition performance. The experimental result is shown in To assess the performance of the proposed method, we compared the results with other mainstream approaches based on four published datasets. Based on the LOSO results obtained by the proposed method, the confusion matrix is calculated to assess the model’s recognition performance for each category. As shown in Finally, we compare the best results obtained by our method with the baseline method and the other representative algorithms. Since the performance of different protocols varies substantially, we only compare methods that use the same LOSO strategy. The baseline methods include LBP-TOP  and LBP-In this paper, a sparse binary descriptor for ME recognition based on the Enhanced LCBP is proposed. In comparison to other binary descriptors, the proposed Enhanced LCBP contains the complementary spatial and temporal binary features that allows a greater focus on capturing spatial differences and temporal directions. Moreover, Multi-Regional Joint Sparse Learning is proposed to measure the contribution of different regions, guaranteeing a similar sparse pattern between features of different image grids. Moreover, the interclass distance constraint allows the proposed method to capture more discriminating binary representations. The effect of the Enhanced LCBP descriptor and Multi-Regional Joint Sparse Learning on recognition performance is quantitatively evaluated through parameter experiments. The results show that the combination of Enhanced LCBP and Multi-Regional Joint Sparse Learning can effectively improve the performance of the model. The comparison results with mainstream methods on four datasets show that our approach achieves promising results. This work will contribute to the further exploration of sparse binary descriptors, which will improve the prediction of MEs, and thus combining the advantages of handcrafted features with deep learning technology will be our future work.


At the time of writing, it is unclear how the COVID-19 pandemic will play out in rapidly urbanising regions of the world. In these regions, the realities of large overcrowded informal settlements, a high burden of infectious and non-communicable diseases, as well as malnutrition and precarity of livelihoods, have raised added concerns about the potential impact of the COVID-19 pandemic in these contexts. COVID-19 infection control measures have been shown to have some effects in slowing down the progress of the pandemic, effectively buying time to prepare the healthcare system. However, there has been less of a focus on the indirect impacts of these measures on health behaviours and the consequent health risks, particularly in the most vulnerable. In this current debate piece, focusing on two of the four risk factors that contribute to >80% of the NCD burden, we consider the possible ways that the restrictions put in place to control the pandemic, have the potential to impact on dietary and physical activity behaviours and their determinants. By considering mitigation responses implemented by governments in several LMIC cities, we identify key lessons that highlight the potential of economic, political, food and built environment sectors, mobilised during the pandemic, to retain health as a priority beyond the context of pandemic response. Such whole-of society approaches are feasible and necessary to support equitable healthy eating and active living required to address other epidemics and to lower the baseline need for healthcare in the long term. In rapidly urbanising low- and middle-income countries (LMIC), the realities of large overcrowded informal settlements, a double burden of infectious and non-communicable diseases (NCDs), malnutrition and the precarity of livelihoods  have raiThese restrictions have the potential to impact NCD risk factors such as dietary intake and physical activity behaviours , by limiThis debate piece will describe how the implementation of restrictions to limit the spread of the pandemic may impact diet and physical activity behaviours, as well as their determinants. We also reflect on the experiences from mitigation interventions mobilised by several governments to respond to this pandemic, and the potential for these to be leveraged beyond COVID-19 in order to retain health as a priority.With the implementation of measures to prevent further spread of COVID-19 infections, LMICs are experiencing two inter-related pandemics. Our public health response to the COVID-19 pandemic may be exacerbating behaviours such as unhealthy food consumption, physical inactivity and sedentary behaviour. These aforementioned behaviours are considered the key drivers of obesity epidemic globally, and obesity is a risk factor for adverse outcomes of COVID-19 infection .External dimensions of the food environment include the availability, price, vendor and product properties, and promotional information. By comparison, personal dimensions of the food environment are the accessibility, affordability, convenience and desirability of food sources and products. These food environment exposures, which vary considerably between and within high-, middle- and low-income countries, influence food choices, dietary habits, and food security ,6.The COVID-19-related closures of national borders threaten food supply especially in countries already facing food insecurities and those largely dependent on food imports. As a result, maintaining adequate food production, import, storage and transportation can be precarious for both external and personal dimensions of the food environment. The dynamics of purchasing and consumption of healthy food in this context, driven by limited access to fresh foods and refrigeration, has highlighted the growing wealth inequality within countries.For many, the new reality of shelter-in-place measures has resulted in an increase in cooking and eating at home. On one hand, this presents an opportunity for preparing more healthy meals at home. However, a lack of nutritional knowledge and cooking skills, increased snacking behaviour, unavailability and increased costs of healthy foods , and theThese measures are also resulting in a staggering loss of jobs and livelihoods that further impact on people’s ability to afford healthy foods. The predominance of the informal economic sector and absence of robust social safety schemes in LMICs further compound food affordability. In these circumstances, without social welfare measures, the most vulnerable are left with no choice but to defy social distancing measures to avoid hunger.COVID-19 control measures inevitably disrupt routine daily activities and may have positive or negative consequences on physical activity behaviours. Stay-at-home orders and curfew measures result in reduced travelling, which in many cases includes walking, potentially reducing the opportunity for physical activity. Reduced regular physical activity alone, or compounded by unhealthy eating may result in an increased risk or worsening of chronic conditions such as obesity, diabetes, hypertension and cardiovascular disease , which aMany governments in LMICs have implemented measures to minimise COVID-19 risk while working to address underlying social inequities that further increase vulnerability to disease. In so doing, the emergency has highlighted the possibility of previously considered impossible or unfeasible actions .Wide-ranging multisectoral action to reduce inequalities is possible at pace when there is social and political will. The response to the COVID-19 pandemic has seen unprecedented multisectoral action compared to responses to the ongoing obesity pandemic. Of note, governments have led coordination of multisectoral responses, removing bureaucratic processes that could hinder support for vulnerable communities.For example, in Kenya, the Ministry of Agriculture has partnered with county governors to aggregate information on the volumes and prices of staples and nutritious foods in order to ensure affordability . County Beyond this pandemic, it would be important to reflect on and evaluate the experience of these endeavours to inform longer term strategies to make fresh foods more locally available within neighbourhoods.COVID-19 has revealed significant flaws in our existing urban infrastructure. These flaws include economic systems that reduce resilience to food insecurity, and streets that prioritize motorised traffic, making physical activity for leisure or travel unsafe. Understandably, the majority of emergency mitigation responses have focused on food security. However, some settings such as Bogota, Colombia have created new space for walking and cycling  while thThere is a need for public health interventions jointly to reinforce democracy, the rights of the individual and the collective good. In the context of acute response to emergencies, varying approaches have been adopted including extensive tracing using big data and deployment of the police to enforce movement restriction measures. If rights are side-lined, these measures potentially compromise data privacy and individual rights if applied in a discriminatory manner. This highlights the importance of a rights-based approach to public health, recognising that the right to health is dependent upon other human rights  and that even well-intended enforcement could bring harms. A rights-based approach could similarly be applied to addressing the obesity pandemic. For example, governance of urban space could ensure that organizations charged with enforcing lockdown measures are thoroughly oriented in equitable governance approaches, and partner with community stakeholders to improve access to neighbourhood resources including safe spaces for physical activity. Additionally, it can include collaboration with key actors to facilitate access to space for urban agriculture for the poor.While the impacts of these interventions are yet to be evaluated, these examples hint at the potential for whole-of-society approaches to building stronger systems for health and lower the baseline need for healthcare. In the long term, it is vital that the economic, political, food and built environment sectors mobilised during the pandemic are encouraged (and governed) to retain health as a priority. Societies that support and enable healthy eating and active living are vital to reduce vulnerability to COVID-19 and other diseases and pandemics in the long term.We note the following reflections from these pandemic responses that could be applied to current and future epidemics and pandemics to support equitable access to healthy diets and physical activity:


Inflammatory bowel disease (IBD) is a serious public health problem worldwide. Current therapeutic strategies that use anti-inflammatory drugs, immunosuppressants, and biological treatments are often ineffective and have adverse health effects. In this regard, the use of natural compounds aimed at key pathogenic therapeutic targets in IBD attracts universal attention. Seaweed is a valuable source of structurally diverse biologically active compounds. The materials presented in the review indicate that seaweed extracts and polysaccharides are effective candidates for the development of drugs, biological food additives, and functional nutrition products for the treatment and prevention of IBD. The structural features of algal polysaccharides provide the possibility of exposure to therapeutic targets of IBD, including proinflammatory cytokines, chemokines, adhesion molecules, nuclear factor NF-kB, intestinal epithelial cells, reactive oxygen and nitrogen. Further study of the relationship between the effect of polysaccharides from different types of algae, with different structure and molecular weights on immune and epithelial cells, intestinal microorganisms will contribute to a deeper understanding of their mechanisms and will help in the development of drugs, dietary supplements, functional foods for the treatment of patients with IBD. Inflammatory bowel disease (IBD) is a group of idiopathic chronic inflammatory intestinal conditions. The two main disease categories are Crohn’s disease (CrD) and ulcerative colitis (UC), which occupy one of the leading positions of diseases of the gastrointestinal tract due to the severity, frequency of complications and mortality ,2. Late The etiology of IBD is still unknown, despite a long history of study. From a modern perspective, the pathogenesis of IBD is considered as the interaction of several factors Advances in gene sequencing technology have identified more than 160 susceptibility genes associated with IBD, but these genes are not the main reason for the increase in the number of diseases ,9. The rImmunological dysregulation in IBD is characterized by dysfunction of the effector and regulatory cells of innate acquired immunity, which leads to the uncontrolled release of soluble inflammatory mediators with the subsequent development of pathological changes ,14. T ceAccording to the current recommendations, anti-inflammatory drugs  and immunosuppressants , biological drugs  can be used for the treatment of IBD , surgicaGiven the serious side effects associated with conventional treatment, the search for new sources of drugs to improve the clinical symptoms of IBD remains essential. Recent advances in the study of IBD pathogenesis have opened up prospects for the development of new treatment strategies aimed at therapeutic targets and associated with the use of areactogenic and effective natural compounds that can block the adhesion and migration of leukocytes into the inflamed intestinal mucosa and inhibit cytokines, normalize the intestinal microflora, maintain clinical remission and accelerate mucous healing intestinal membrane ,26.In this regard, marine algae represent a huge bioresource of natural ingredients ,28. ReceThis work includes a review of current ideas about the possibility of using extracts and polysaccharides of seaweed as the basis for drugs, dietary supplements and functional food products for the prevention and treatment of inflammatory bowel diseases.Brown seaweed is a large group of multicellular photoautotrophic organisms. Alginates and fucoidans are two of the best-known seaweed biopolymers and have experimentally and clinically proven pharmacological effects, such as hypolipidemic, hypoglycemic, antioxidant, anti-inflammatory, anticoagulant, metal-binding, and immunomodulating ,42,43,44Fucoidans are complex highly sulfated, usually branched polysaccharides in the range from several tens to several thousand kDa, often containing, in addition to fucose residues, glucose, galactose, xylose, mannose and uronic acids, as well as acetyl groups ,45. Fucod-mannuronic and α-l-guluronic acids [Alginic acids are found in all brown seaweeds (Phaeophyceae) in a proportion of 18% to 40% of the total plant mass . These aic acids . Alginatic acids . The algic acids . Alginatic acids . Alginicic acids .d-glucans which consist of β-(1→3)-linked d-glucose residues. They differ from each other with regard to their length and branching structure [Laminarans are low molecular weight (5–10 kDa) β-tructure ,54. The tructure . Laminartructure ,56,57. The main structural component of red algae is sulfated polysaccharides —carrageenans, agars, porphyrin, xylan—which have no analogs among other plant polysaccharides. The structural features of these polysaccharides are determined by the species affiliation of algae, their habitat conditions and determine a wide range of biological activity .O-substituted residues and are divided into carrageenans kappa (k), iota (i) and lambda (λ) [Carrageenans are a family of sulfated hydrocolloids whose polymer chain is built from galactose residues and its derivatives with alternating α-(1-3) and β-(1-4) bonds. Carrageenans are classified by location and the amount of sulfate groups in the monosaccharide residues and the presence of 3,6-angirogalactose in 4-mbda (λ) ,58. Carrmbda (λ) ,60. Carrmbda (λ) . RecentlUlva and Enteromorpha sp.) that has sulfate, rhamnose, xylose, iduronic and glucuronic acids as the main constituents [Ulvan is the major water-soluble polysaccharide found in green seaweed of the order Ulvales  as well as receptor IL-23R and IL-6, with no alteration to the T regulatory cell (TREG)–related targets.Matsumoto et al.  examinedn et al.  showed tO’Shea et al.  studied ® Synergy, which is a highly characterized, certified organic complex of fucoidan and marine polyphenols, sourced from wild Fucus vesiculosus seaweed) and depyrogenated fucoidan in DSS mouse model of acute colitis and depyrogenated fucoidan in DSS mouse model of acute colitis. Orally administered polysaccharides significantly ameliorated symptoms of colitis based on retention of body weight, as well as reduced diarrhea and fecal blood loss, compared to the untreated colitis group. Colon and spleen weight in mice treated with oral fucoidan was also significantly lower, indicating reduced inflammation and edema. The macroscopic changes induced by oral fucoidan correlated significantly with substantially decreased production of inflammatory cytokines by the colon tissue. It is noteworthy that deterioration in the condition of animals and an increase in the level of certain pro-inflammatory cytokines in the colon tissue was noted with intraperitoneal administration of depyrogenized fucoidan. The authors propose the oral use of fucoidan as an effective and well-tolerated maintenance therapy for a long period of time to reduce inflammation and maintain the integrity of the intestinal epithelium.Lean et al.  evaluateTanoue et al.  in an inThe authors of these publications suggest that algae polysaccharides could, therefore, represent a novel nutraceutical option for the management of IBD and suggest using them as an effective and well-tolerated maintenance therapy for a long period of time to reduce inflammation and maintain the integrity of the intestinal epithelium.Treatment with the methanolic extract significantly attenuates body weight loss and severe clinical symptoms in mice with experimental colitis induced by DSS. This was associated with a remarkable amelioration of colonic architecture and a significant reduction in pro-inflammatory cytokine production in the intestinal tissue. The authors attribute this effect to the ability of the extract to reduce the rate of migration of lymphoid cells into the focus of inflammation and directly inhibit the secretion of cytokines by immunocytes ,89.Caulerpa mexicana [The authors also believe that these effects on clinical symptoms and on histological parameters could be due to the presence of antioxidant compounds, such as β-carotene and α-tocopherol that have been isolated from mexicana  and inhimexicana .Eucheuma cottonii with a high content of polysaccharides in experimental colitis is described by Sudirman et al. [The efficacy of oral administration of an ethanol extract of the red alga n et al. . ExtractLymphocyte-endothelial interactions mediated by adhesion molecules, such as selectins, integrins, cadherins, etc., play an important role in the migration and involvement of leukocytes in places of inflammation and can also be used as potential therapeutic targets for chronic intestinal inflammation . SelectiZhang et al.  also fouThese results prove that sulfated polysaccharides, possessing the properties of glycosaminoglycan mimetics, block adhesion molecules and inhibit the migration of leukocytes, having a positive effect in the treatment of inflammatory bowel diseasesThe data accumulated to date show that oxidative stress plays a significant role in the pathogenesis and progression of IBD, being a potential pathogenic and critical factor in the occurrence, progression, and severity of the disease, and not a consequence of chronic inflammation of the intestinal mucosa ,99. SeveAn important role in the pathogenesis of IBD is given to reducing the effectiveness of the epithelial barrier. The epithelial barrier consists of several important elements, including the intact epithelial monolayer and the locking intercellular contacts  in which the membranes of neighboring cells are maximally brought together and are “cross-linked” by specialized proteins claudins and occludins . A large2O2-induced destruction of intestinal epithelial barrier function in a dose-dependent manner significantly increased transepithelial resistance, which indicates a direct increase in the barrier function of the intestinal epithelium and prevented a violation of paracellular permeability, increasing the expression of claudin-1. The authors suggest that fucoidan, which increases the epithelial protective function and promotes epithelial regeneration, might serve as an appropriate therapy for the treatment of IBD.Iraha et al.  showed tLaminaria japonica and three types of fermented aqueous extracts of L. japonica in LPS-stimulated Caco-2 cells. All four extracts enhanced intestinal barrier function, preventing inhibition of tight junction-related protein levels, decreased monolayer permeability, and significantly reduced nitric oxide and IL-6 production.Yang et al.  investigA significant increase in the intestinal epithelial barrier and the immune function of cells when using low-molecular-weight fucoidan and high-stability fucoxanthin was shown in the same model .Thus, the above examples show that algae polysaccharides can affect intestinal health by decreasing intestinal inflammation and enhancing barrier function by partially regulating dense compounds and associated proteins . Further studies of more TJ-linked proteins will establish the exact mechanism of action of polysaccharides and confirm their potential benefit as a suitable therapeutic agent for the treatment of inflammatory bowel diseases.The concept of altered intestinal microbiome or dysbiosis is the significant IBD research event of the last decade. Newer molecular and genetic diagnostic tools have elucidated distinct changes in the gut microbiota in IBD patients and clarified the deficiencies of innate immunity . IBD begAccording to the latest definition, prebiotics include substrates that are selectively used by host microorganisms that provide health benefits . SubstanFucus evanescens are shown by Kuznetsova et al. [B. bifidum enriched with polysaccharides from brown alga F. evanescens [Lactobacillus and Ruminococcaceae in the microbiota of the cecum of mice injected with fucoidan from Ascophyllum nodosum and L. japonica was noted in Reference [In recent years, much attention has been paid to the use of polysaccharides from algae as prebiotics, which are not broken down by upper enzymes and can be degraded in the colon by enzymes of bifidobacteria and lactobacilli, such as xylanases and glycosyl hydrolases, phosphate transferases, hydrolases and isomerases ,124,125.a et al. . The preanescens . An increference . Encouraeference . The poseference .The above data show that algae polysaccharides have great potential for use as prebiotics in IBD and can realize health effects, including regulation of the composition and functions of microbiota, lowering the pH in the colon lumen and preventing intestinal colonization by pathogens, and reducing the production of reactive oxygen species providing energy sources for colonocytes and activating free fatty acid receptors. However, further studies of the prebiotic properties of oligo- and polysaccharides from algae are needed to obtain more complete information about their intestinal benefits, including in IBD.The problem of developing new technologies for the delivery of drugs with desired properties to therapeutic targets remains relevant at present . The delRecent preclinical studies have shown that nanoparticle-based drug delivery systems using algal polysaccharides can be promising tools with potentially effective results in the treatment of IBD . CarrageAlginate-chitosan nanoparticles cross-linked by zinc ions and intended for the joint delivery of zinc and 5-aminosalicylic acid showed an excellent therapeutic effect in reducing inflammation in rats with induced colitis .Wu et al.  investigLee et al.  also useUlva lactuca, possessing low toxicity and high anti-inflammatory activity. The complex had low toxicity and high anti-inflammatory activity. Supplementation with ULP-SeNPs resulted in a significant protective effect on DSS-induced acute colitis in mice including mitigation of body weight loss, and colonic inflammatory damage. ULP-SeNPs ameliorated macrophage infiltration as evidenced by decreased CD68 levels in colon tissue sections. The plasma levels of TNFα and IL-6, COX-2, and iNOS in these animals decreased compared to control animals not receiving the complex. Mechanistically, ULP-SeNPs inhibited the activation of macrophages by suppressing the nuclear translocation of NF-κB, which drives the transcription of these pro-inflammatory cytokines.Zhu et al.  construcWang et al.  used sodEnhanced degradation of chitosan particles by enterobacteria of the colon is also a useful strategy for targeting drug release to the distal intestine. Crcarevska et al.  orally aChang et al.  used ampThese studies show the potential of IBD treatment strategies using polysaccharide-based seaweed drug delivery systems. Nevertheless, for the successful application of this strategy in the treatment of IBD, further comprehensive studies of the patterns of accumulation of substances in the intestinal tissues are necessary.Inflammatory bowel disease is a serious health concern among western societies worldwide. Current therapeutic strategies that use anti-inflammatory drugs, immunosuppressants, and biological treatments are often ineffective and have adverse health effects. In this context, the use of natural products has attracted widespread attention. Seaweed is a valuable source of structurally diverse bioactive compounds. The cell walls of algae are rich in polysaccharides with a wide range of biological activity. The presented materials indicate that seaweed extracts and polysaccharides are effective candidates for the development of drugs, biological food additives, and functional nutrition products for the treatment and prevention of IBD. The high therapeutic effectiveness of the extracts is due to the harmonious combination and interaction of a wide range of biologically active substances  in their composition, which helps to enhance the pharmacological properties of each incoming ingredient and corresponds to the multivalence of the disease pathogenesis. The pleiotropic effect of sulfated polysaccharides of brown algae, due to their structural features, provides their ability to exert an effect on therapeutic IBD targets, including proinflammatory cytokines, adhesion molecules, nuclear factor NF-kB, and reactive oxygen and nitrogen forms. The prebiotic properties of oligo- and polysaccharides from seaweed are also an attractive alternative for both prophylactic and therapeutic intervention in IBD. Finally, algal polysaccharides have great potential in the development of drug delivery systems since the physicochemical properties of these carbohydrates provide the possibility of interaction with other compounds, whether drugs, proteins or other polymers.However, currently, the majority of studies regarding the effectiveness of algal polysaccharides in IBD have been carried out in experiments on animals or ex vivo using material from patients suffering from these diseases. This circumstance is associated with difficulties in obtaining standardized drugs, which could be the basis for the creation of dosage forms. Undoubtedly, the use of algal polysaccharides in medicine will expand every year due to the further development of science and the expansion of the possibilities of obtaining standardized preparations based on these compounds. The lack of theoretical knowledge about the influence of specific structural parameters of algal polysaccharides on their biological properties is also a limiting factor. In this regard, the molecular architecture of polysaccharides and the role of structural elements in the manifestation of their biological properties are still the subject of active study and are a logical step towards the creation of drugs based on them.We hope that further study of the relationship between the effect of polysaccharides from different types of algae, with different structure and molecular weights on immune and epithelial cells, intestinal microorganisms will contribute to a deeper understanding of their mechanisms and will help in the development of drugs, dietary supplements, functional foods for the treatment of patients with IBD.