Though current remote sensing technologies, especially synthetic aperture radars (SARs), exhibit huge potential for soil moisture content (SMC) retrievals, such technologies also present several performance disadvantages. This study explored the merits of proposing a novel data fusion methodology (partly decision level and partly feature level) for SMC estimation. Initially, individual estimations were derived from three distinct methods the inversion of an Empirically Adapted Integral Equation Model (EA-IEM) applied to SAR data, the Perpendicular Drought Index (PDI), and the Temperature Vegetation Dryness Index (TVDI) determined from Landsat-8 data. Subsequently, three feature level fusions were performed to produce three different novel salient feature combinations where said features were extracted from each of the previously mentioned methods to be the input of an artificial neural network (ANN). The latter underwent a modification of its performance function, more specifically from absolute error to root mean square error (RMSE). Eventually, all SMC estimations, including the feature level fusion estimation, were fused at the decision level through a novel weight-based estimation. The performance of the proposed system was analysed and validated by measurements collected from three study areas, an agricultural field in Blackwell farms, Guildford, United Kingdom, and two different agricultural fields in Sidi Rached, Tipasa, Algeria. Those measurements contained SMC levels and surface roughness profiles. The proposed SMC estimation system yielded stronger correlations and lower RMSE values than any of the considered SMC estimation methods in the order of 0.38%, 1.4%, and 1.09% for the Blackwell farms, Sidi Rached 1, and Sidi Rached 2 datasets, respectively.The Aspergillus Metabolome Database is a free online resource to perform metabolite annotation in mass spectrometry studies devoted to the genus Aspergillus. The database was created by retrieving and curating information on 2811 compounds present in 601 different species and subspecies of the genus Aspergillus. A total of 1514 scientific journals where these metabolites are mentioned were added as meta-information linked to their respective compounds in the database. A web service to query the database based on m/z (mass/charge ratio) searches was added to CEU Mass Mediator; these queries can be performed over the Aspergillus database only, or they can also include a user-selectable set of other general metabolomic databases. This functionality is offered via web applications and via RESTful services. Furthermore, the complete content of the database has been made available in .csv files and as a MySQL database to facilitate its integration into third-party tools. To the best of our knowledge, this is the first database and the first service specifically devoted to Aspergillus metabolite annotation based on m/z searches.Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. https://www.selleckchem.com/products/PLX-4032.html Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the "bitter" and "sweet" aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.Transimpedance amplifiers (TIA) are widely used for front-end signal conditioning in many optical distance measuring applications in which high accuracy is often required. Small effects due to the real characteristics of the components and the parasitic elements in the circuit board may cause the error to rise to unacceptable levels. In this work we study these effects on the TIA delay time error and deduce analytic expressions, taking into account the trade-off between the uncertainties caused by the delay time instability and by the signal-to-noise ratio. A specific continuous-wave phase-shift case study is shown to illustrate the analysis, and further compared with real measurements. General strategies and conclusions, useful for designers of this kind of system, are extracted too. The study and results show that the delay time thermal stability is a key determinant factor in the measured distance accuracy and, without an adequate design, moderate temperature variations of the TIA can cause extremely high measurement errors.Multi-vehicle (MV) crashes, which can lead to great damages to society, have always been a serious issue for traffic safety. A further understanding of crash severity can help transportation engineers identify the critical reasons and find effective countermeasures to improve transportation safety. However, studies involving methods of machine learning to predict the possibility of injury-severity of MV crashes are rarely seen. Besides that, previous studies have rarely taken temporal stability into consideration in MV crashes. To bridge these knowledge gaps, two kinds of models random parameters logit model (RPL), with heterogeneities in the means and variances, and Random Forest (RF) were employed in this research to identify the critical contributing factors and to predict the possibility of MV injury-severity. Three-year (2016-2018) MV data from Washington, United States, extracted from the Highway Safety Information System (HSIS), were applied for crash injury-severity analysis. In addition, a series of likelihood ratio tests were conducted for temporal stability between different years.

ronments.Since Marine sponge Dysidea avara is regarded as a source of anti-inflammatory compounds, we decided to evaluate its potential anti-psoriatic activity in a psoriasis Imiquimod-induced in the mouse model. Psoriatic mice were treated with three different methanolic extracts of Dysidea avara compared with betamethasone-treated mice in in- vivo studies. Clinical skin severity was assessed with the psoriasis area index (PASI), whilst ELISA detected the expression of TNF-α, IL-17A, and IL-22. Dysidea avara activity was studied by employing GC-MS (to distinguish compounds), HPTLC (for skin permeation and accumulation), and SEA DOCK to predict single compound potential anti-inflammatory activity. After 7 days of treatment, mice treated with Dysidea avara displayed a dose-dependent, statistically significant improvement compared to controls (p less then 0.001). In line with the clinical results, ELISA revealed a statistically significant decrease in IL-22, IL-17A, and TNF-α after treatment; the same SEA DOCK analysis suggests a possible anti-psoriatic activity of the extracts.Inter-hospital patient transfers (direct transfers) between healthcare facilities have been shown to contribute to the spread of pathogens in a healthcare network. However, the impact of indirect transfers (patients re-admitted from the community to the same or different hospital) is not well studied. This work aims to study the contribution of indirect transfers to the spread of pathogens in a healthcare network. To address this aim, a hybrid network-deterministic model to simulate the spread of multiresistant pathogens in a healthcare system was developed for the region of Lower Saxony (Germany). The model accounts for both, direct and indirect transfers of patients. https://www.selleckchem.com/products/c381.html Intra-hospital pathogen transmission is governed by a SIS model expressed by a system of ordinary differential equations. Our results show that the proposed model reproduces the basic properties of healthcare-associated pathogen spread. They also show the importance of indirect transfers restricting the pathogen spread to direct transfers only leads to 4.2% system wide prevalence. However, adding indirect transfers leads to an increase in the overall prevalence by a factor of 4 (18%). In addition, we demonstrated that the final prevalence in the individual healthcare facilities depends on average length of stay in a way described by a non-linear concave function. Moreover, we demonstrate that the network parameters of the model may be derived from administrative admission/discharge records. In particular, they are sufficient to obtain inter-hospital transfer probabilities, and to express the patients' transfers as a Markov process. Using the proposed model, we show that indirect transfers of patients are equally or even more important as direct transfers for the spread of pathogens in a healthcare network.The huge amount of data acquired by high-throughput sequencing requires data reduction for effective analysis. Here we give a clustering algorithm for genome-wide open chromatin data using a new data reduction method. This method regards the genome as a string of 1s and 0s based on a set of peaks and calculates the Hamming distances between the strings. This algorithm with the systematically optimized set of peaks enables us to quantitatively evaluate differences between samples of hematopoietic cells and classify cell types, potentially leading to a better understanding of leukemia pathogenesis.
Published information on snakebite is rare in Bhutan although remarkably higher number of snakebites and associated deaths are reported from other South Asian countries.

Structured questionnaire was used to collect knowledge of health workers in snakebite management and health seeking behavior of snakebite victims as observed by health workers. Study was conducted in purposively sampled 10 Dzongkhags (district level administrative units) with higher incidence of snakebites.

Heath workers scored 27-91% (with an average of 63%, SD = 14) for 52 questions related to snake identification and snakebite management. Among 118 health workers interviewed, 23% had adequate knowledge on snakes and snakebite management while 77% had inadequate knowledge. Among 32 Doctors, 63% of them scored above or equal to 75%. Health workers from Sarpang scored higher (76%, SD = 11) than those from other Dzongkhags. Snakebite victim's visit to local (traditional) healers prior to seeking medical help from hospital was observed byand traditional beliefs on local treatment practices. Empowering health workers with adequate knowledge on snakebite management and making locals aware in pre-hospital care of snakebites are needed to improve the pre- and in-hospital management of snakebite in Bhutan.How do we scale biological science to the demand of next generation biology and medicine to keep track of the facts, predictions, and hypotheses? These days, enormous amounts of DNA sequence and other omics data are generated. Since these data contain the blueprint for life, it is imperative that we interpret it accurately. The abundance of DNA is only one part of the challenge. Artificial Intelligence (AI) and network methods routinely build on large screens, single cell technologies, proteomics, and other modalities to infer or predict biological functions and phenotypes associated with proteins, pathways, and organisms. As a first step, how do we systematically trace the provenance of knowledge from experimental ground truth to gene function predictions and annotations? Here, we review the main challenges in tracking the evolution of biological knowledge and propose several specific solutions to provenance and computational tracing of evidence in functional linkage networks.Mycobacterium tuberculosis complex (MTBC) comprises closely related species responsible for human and animal tuberculosis (TB). Efficient species determination is useful for epidemiological purposes, especially for the elucidation of the zoonotic contribution. In Algeria, data on MTBC genotypes are largely unknown. In this study, we aimed to investigate the occurrence and diversity of MTBC genotypes causing human and bovine TB in Northern Algeria. During a two-year sampling period (2017-2019) in two regions of Northern Algeria, we observed an overall prevalence of 6.5% of tuberculosis (TB) among slaughtered cattle, which is higher than previous Algerian data yet comparable to neighboring countries. A total of 296 Mycobacterium tuberculosis complex (MTBC) isolates were genotyped by spoligotyping 181 from tissues with TB-like lesions collected from 181 cattle carcasses and 115 from TB patients. In human isolates, we identified 107 M. tuberculosis, seven M. bovis and one "M. pinnipedii-like", while for bovine samples, 174 isolates were identified as M.

[Rose-scented geranium fat through Algeria (Pelargonium graveolens L'Hérit.): Evaluation of de-oxidizing, anti-inflammatory and also anticancer components versus distinct metastatic cancer malignancy mobile lines].

For most of the >2000 CFTR gene variants reported, neither the associated disease liability nor the underlying basic defect are known, and yet these are essential for disease prognosis and CFTR-based therapeutics. Here we aimed to characterize two ultra-rare mutations - 1717-2A>G (c.1585-2A>G) and S955P (p.Ser955Pro) - as case studies for personalized medicine.

Patient-derived rectal biopsies and intestinal organoids from two individuals with each of these mutations and F508del (p.Phe508del) in the other allele were used to assess CFTR function, response to modulators and RNA splicing pattern. In parallel, we used cellular models to further characterize S955P independently of F508del and to assess its response to CFTR modulators.

Results in both rectal biopsies and intestinal organoids from both patients evidence residual CFTR function. Further characterization shows that 1717-2A>G leads to alternative splicing generating <1% normal CFTR mRNA and that S955P affects CFTR gating. Finally, studies in organoids predict that both patients are responders to VX-770 alone and even more to VX-770 combined with VX-809 or VX-661, although to different levels.

This study demonstrates the high potential of personalized medicine through theranostics to extend the label of approved drugs to patients with rare mutations.
This study demonstrates the high potential of personalized medicine through theranostics to extend the label of approved drugs to patients with rare mutations.Acute Pancreatitis (AP) is a multifactorial disease. It was characterized by severe inflammation and acinar cell destruction. Thus, the present study was initiated to evaluate the role the of Cinnamic acid nanoparticles (CA-NPs) as a modulator for the redox signaling pathway involved in the development of pancreatitis. AP in rats was induced by L-arginine and exposure to gamma radiation. The pancreatic injury was evaluated using biochemical and histological parameters. Upon the oral administration of CA-NPs, both the severity of acute pancreatitis and the serum levels of amylase and lipase were decreased. Furthermore, the malondialdehyde (MDA) levels of the pancreatic tissue were significantly reduced and the depletion of glutathione was considerably restored. The injury and apoptosis of pancreatic tissues were markedly improved by the reduction of the caspase-3 levels. Additionally, the alleviation of pancreatic oxidative damage by CA-NPs was accompanied by a down-regulation of the NLRP3, NF-κB, and ASK1/MAPK signaling pathways. Collectively, the current findings showed that CA-NPs could protect the pancreatic acinar cell from injury not only by its antioxidant, anti-inflammatory effect but also by modulation of the redox-sensitive signal transduction pathways contributed to acute pancreatitis severity. https://www.selleckchem.com/products/sp2509.html'>https://www.selleckchem.com/products/sp2509.html Accordingly, cinnamic acid nanoparticles have therapeutic potential for the management of acute pancreatitis.
Recent trials have indicated positive effects of bumetanide in autism spectrum disorder (ASD). We tested efficacy of bumetanide on core symptom domains using a single center, parallel-group, participant-randomized, double-blind, placebo-controlled phase-2 superiority trial in a tertiary hospital in the Netherlands.

Unmedicated children aged 7 to 15 years with ASD and IQ ≥55 were block-randomized 11 to oral-solution bumetanide versus placebo, titrated to a maximum of 1.0 mg twice daily for 91 days (D91), followed by a 28-day wash-out period. The primary outcome was difference in Social Responsiveness Scale-2 (SRS-2) total score at D91, analyzed by modified intention-to-treat with linear mixed models.

A total of 92 participants (mean age 10.5 [SD 2.4] years) enrolled between June 2016 and December 2018. In all, 47 children were allocated to bumetanide and 45 to placebo. Two participants dropped out per treatment arm. After 91 days, bumetanide was not superior to placebo on the primary outcome, the SRS-2 (utism Medication and Biomarker Study (BAMBI); https//www.clinicaltrialsregister.eu/; 2014-001560-35.
Traumatic brain injury (TBI) is a global problem and is the greatest contributor to death and disability among all trauma-related injuries worldwide. Road traffic accidents are an important cause of TBI. https://www.selleckchem.com/products/sp2509.html'>https://www.selleckchem.com/products/sp2509.html The purpose of this paper is to present the first data on TBI in Angola.

This was a retrospective study of the clinical and radiologic profile of patients admitted to the intensive care unit of a tertiary hospital in Luanda, Angola, from January 2018 to December 2018. The medical records of patients with moderate and severe TBI admitted to the intensive care unit were reviewed. The inclusion criteria were adult patients who suffered from TBI. The exclusion criteria were incomplete medical records, pediatric age, and mild TBI.

We included 29 patients (6 female) with a mean age of 31 years. Of them, 31% visited the hospital without an ambulance (using private or commercial vehicles), 58.6% suffered from severe TBI, and the mortality rate in our sample was 34.5%. Road accident was the most frequent cause of trauma.

This first report of TBI in Angola reveals major problems with TBI management, road accident prevention, prehospital management, and loss of lives of young patients.
This first report of TBI in Angola reveals major problems with TBI management, road accident prevention, prehospital management, and loss of lives of young patients.
New York City is the epicenter of the novel coronavirus disease 2019 (COVID-19) pandemic in the United States. Traumatic brain injury accounts for a significant proportion of admissions to our trauma center. We sought to characterize the effect of the pandemic on neurotraumas, given the cancellation of nonessential activities during the crisis.

Retrospective and prospective reviews were performed from November 2019 to April 2020. General demographics, clinical status, mechanism of trauma, diagnosis, and treatment instituted were recorded. We dichotomized the data between pre-COVID-19 (before 1 March) and COVID-19 periods and compared the differences between the 2 groups. We present the timeline of events since the beginning of the crisis in relation to the number of neurotraumas.

A total of 150 patients composed our cohort with a mean age of 66.2 years (standard deviation ±18.9), and 66% were male. More males sustained neurotrauma in the COVID-19 period compared with the pre-COVID-19 (60.4% vs. 77.6%, P= 0.

India was one of the countries to institute strict measures for Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control in the early phase. Since, then, the epidemic growth trajectory was slow before registering an explosion of cases due to local cluster transmissions.

We estimated the growth rate and doubling time of SARS-CoV-2 for India and high burden states using crowdsourced time series data. Further, we also estimated the Basic Reproductive Number (R0) and Time-dependent Reproductive number (Rt) using serial intervals from the data. We compared the R0 estimated from five different methods and R0 from SB was further used in the analysis. We modified standard Susceptible-Infectious-Recovered (SIR) models to SIR/Death (SIRD) model to accommodate deaths using R0 with the sequential Bayesian method for simulation in SIRD models.

On average, 2.8 individuals were infected by an index case. The mean serial interval was 3.9 days. The R0 estimated from different methods ranged from 1.43 to 1.85transmission. However, the estimated Basic Reproductive Number (R0) is relatively lower than those observed in high burden regions (range 1.43-1.85). Our simulation using susceptible-infectious-recovered/death model shows that peak of SARS-CoV-2 in India is farther than currently projected and is likely to affect around 12.5% of population.

The lower estimated R0 is indicative of the effectiveness of early social distancing measures and lockdown. Premature relaxation of the current control measures may result in large numbers of cases in India.
The lower estimated R0 is indicative of the effectiveness of early social distancing measures and lockdown. Premature relaxation of the current control measures may result in large numbers of cases in India.
In most settings, Female Sex Workers (FSW) bear a disproportionate burden of Human Immunodeficiency Virus (HIV) disease worldwide. Representative data to inform the development of behavioral and biomedical interventions for FSW in Namibia have not been published.

Our objectives were to measure HIV prevalence, identify risk factors for infection, and describe uptake of prevention, testing, and treatment among FSW in Namibia.

We conducted cross-sectional surveys using Respondent-driven Sampling (RDS) in the Namibian cities of Katima Mulilo, Oshikango, Swakopmund/Walvis Bay, and Windhoek. Participating FSW completed behavioral questionnaires and rapid HIV testing.

City-specific ranges of key indicators were HIV prevalence (31.0-52.3%), reached by prevention programs in the past 12 months (46.9-73.6%), condom use at last sex with commercial (82.1-91.1%) and non-commercial (87.0-94.2%) partners, and tested for HIV within past 12 months or already aware of HIV-positive serostatus (56.9-82.1%). https://www.selleckchem.com/products/gdc-0084.html Factors assocssion, including treatment as prevention and pre-exposure prophylaxis.
We sought to determine the knowledge of, perception, attitudes, and behaviors toward influenza virus and immunization, and the determinants of vaccination among students, patients, and Healthcare Workers (HCWs) at the American University of Beirut and its affiliated Medical Center.

We conducted a cross-sectional study between October 2016 and January 2017 utilizing a self-administered questionnaire that was provided to 247 randomly selected adult participants. Data collected included socio-demographic characteristics, prior vaccination against influenza, knowledge, perception, attitudes, and behaviors toward influenza and influenza immunization. A multivariable regression model was used to evaluate for independent associations between the different variables and regular or yearly vaccination as a primary outcome.

The overall survey response rate was 77%. A substantial proportion of respondents (47.4%) had never received the influenza vaccine. Only 10.2% of students, 19.1% of patients, and 35.6% of HCWs rated in the design of future campaigns.
Adherence rates with regular or yearly vaccination against influenza remain low across all study groups. We were able to identify predictors as well as barriers to vaccination. Future awareness and vaccination campaigns should specifically aim at correcting misconceptions about vaccination, particularly among HCWs, along with addressing the barriers to vaccination. Predictors of vaccination should be integrated in the design of future campaigns.
The purpose of this study was to assess the prevalence of
infection in Algerian patients with peptic disorders and evaluate the impact of different epidemiological factors (age, sex, sampling site, presence or absence of
, and type of pathology related to this bacterium).

We undertook a retrospective and descriptive study on a series of 735 symptomatic patients identified in the laboratory of pathological anatomy at Hassani Abdelkader University Hospital Center of Sidi Bel Abbes, Algeria, over a period of 16 years from January 2002 to December 2017. All patients had benefited from a high gastroscopic fibroscopy and the diagnosis was made by histological examination (hematoxylin-eosin staining). The epidemiological factors, as well as the main gastric diseases related to this bacterium, were studied.

The prevalence of
infection was 66.12%. The infection was more important in the age group 60-69 years (71.43%). The prevalence of
infection was statistically higher in women than in men (69.3% vs. 60.7%,
< 0.01).The antral region was most colonized by
(71.73%). In addition, the infection was associated mainly with atrophic gastritis (69.65%).

In this context, the identification of epidemiological data would be of great value in guiding strategies to control the spread of this bacterium.
In this context, the identification of epidemiological data would be of great value in guiding strategies to control the spread of this bacterium.
Corona Virus Disease 2019 (COVID-19) pandemic is a global health emergency. Health Care Workers (HCWs) with sound knowledge and practices can help curb the pandemic. This study aimed to assess the knowledge, attitude and practices of HCWs about COVID-19 and compare physicians and non-physicians in Saudi Arabia.

An online survey was conducted among HCWs in Saudi Arabia in March and April 2020. Data were collected using a structured questionnaire having four sections including; socio-demographic and professional profile, knowledge, attitude and practices regarding COVID-19. Questionnaire link was sent through social media. Descriptive analysis was used for assessment of knowledge, attitude and practice and Chi-square test was used for comparing physicians and non-physicians. Data were analyzed using SPSS version 21.0.

A total of 398 HCWs completed the questionnaire. Only 45% of the participants had correct knowledge about the agent while about 97% knew that close contact with infected person is the most important risk factor.

LD. The new terminology excluded participants with lower mortality risk and included participants with higher risk. Drug development for MAFLD should consider ethnic differences.Background and Aims Both non-alcoholic fatty liver disease (NAFLD) and depression have a high global prevalence which is projected to increase further. While studies exploring the association have been done, there are conflicting data. This study aims to assess the prevalence and association between depression and NAFLD. https://www.selleckchem.com/products/abt-199.html Methods Medline and Embase were searched from inception to March 3, 2020. Meta-analysis of proportions using the generalized linear mix model was conducted to analyze the pooled prevalence of depression in NAFLD patients. Risk factors for depression in NAFLD patients were evaluated in conventional pairwise meta-analysis. Results Ten studies involving 2,041,752 NAFLD patients were included. Pooled prevalence of depression was 18.21% (CI 11.12-28.38%) in patients with NAFLD and 40.68% (CI 25.11-58.37%) in patients with non-alcoholic steatohepatitis (NASH). NAFLD resulted in significantly higher risk of development of depression (OR 1.29, CI 1.02-1.64, p = 0.03). NASH patients had a significantly higher risk of depression compared with NAFLD patients (RR 2.83, CI 2.41-3.32, p less then 0.001). Diabetes, body mass index (BMI), female sex, smoking, and history of pulmonary disease were significant risk factors for depression in NAFLD patients. Conclusion This study demonstrated a high prevalence of depression in NAFLD patients and a significant association between both conditions. Furthermore, patients with NASH had a significantly higher risk of depression compared with those with NAFLD. Diabetes, BMI, history of lung disease or smoking, and female gender were significant risk factors. Further studies investigating the pathophysiological mechanism underlying depression and NAFLD are needed.Endemic malaria, which claimed 229 million new cases and 409,000 deaths in 2019 mainly in Africa, was eradicated from Europe by the mid-20th century. Historical descriptions of intermittent tertian and quartan fever reported in texts of Hippocrates in Greece and Celsus in Italy suggest malaria. A few paleomicrobiology investigations have confirmed the presence of malarial parasite Plasmodium falciparum in 1st, 2nd, and 5th century infected individuals in diverse regions of Italy, and Plasmodium sp. later in Bavaria. The causative Plasmodium pathogens, discovered in the 19th century in Algeria, were controversially used as therapeutic agents in the European pharmacopeia more than two centuries after effective quinine-based treatments had been introduced in Europe. How Europe managed to eradicate malaria and what the history of malaria was in Europe are of medical interest, and this review traces research pathways for a renewed understanding of malaria eradication in Europe through combined historical and paleomicrobiological investigations.Several advances in recent decades in digital imaging, artificial intelligence, and multiplex modalities have improved our ability to automatically analyze and interpret imaging data. Imaging technologies such as optical coherence tomography, optical projection tomography, and quantitative phase microscopy allow analysis of tissues and cells in 3-dimensions and with subcellular granularity. Improvements in computer vision and machine learning have made algorithms more successful in automatically identifying important features to diagnose disease. Many new automated multiplex modalities such as antibody barcoding with cleavable DNA (ABCD), single cell analysis for tumor phenotyping (SCANT), fast analytical screening technique fine needle aspiration (FAST-FNA), and portable fluorescence-based image cytometry analyzer (CytoPAN) are under investigation. These have shown great promise in their ability to automatically analyze several biomarkers concurrently with high sensitivity, even in paucicellular samples, lending themselves well as tools in FNA. Not yet widely adopted for clinical use, many have successfully been applied to human samples. Once clinically validated, some of these technologies are poised to change the routine practice of cytopathology.One of the most common extraintestinal manifestations of inflammatory bowel disease is iron deficiency anemia. It is often an untreated condition that significantly impairs patients' quality of life and elevates mortality and morbidity. Although it is often accompanied by mild symptoms (e.g., fatigue, lethargy), it can provoke severe health conditions, such as dyspnea, palpitation, angina, and mental disorders, and increases hospitalization and mortality rate as well. As anemia develops through several pathomechanisms, such as occult bleeding, chronic inflammation, and medicines (e.g., methotrexate), treating anemia effectively requires to manage the underlying pathological changes as well. Based on international publications and data, it is a frequent condition and more frequent in pediatrics. According to Goodhand et al., iron deficiency is present in more than 60% of children, whereas only 14% of them received oral iron therapy. Compared to adult patients, 22% have iron deficiency, and 48% of them received? We demand that more studies should be conducted regarding these issues.Legionella pneumophila can cause pneumonia, leading to severe acute respiratory distress syndrome (ARDS). Because of its harsh growth requirements, limited detection methods, and non-specific clinical manifestations, diagnosing Legionella pneumonia remains still challenging. Metagenomic next-generation sequencing (mNGS) technology has increased the rate of detection of Legionella. This study describes a patient who rapidly progressed to severe ARDS during the early stage of infection and was treated with extracorporeal membrane oxygenation (ECMO). Although his bronchoalveolar lavage fluid (BALF) was negative for infection and his serum was negative for anti-Legionella antibody, mNGS of his BALF and blood showed only the presence of Legionella pneumophila (blood mNGS reads 229, BALF reads 656). After antibiotic treatment and weaning from ECMO, however, he developed a secondary Aspergillus and Klebsiella pneumoniae infection as shown by mNGS. Mechanical ventilation and antibiotic treatment were effective. A search of PubMed showed few reports of secondary Aspergillus infections after Legionella infection.