Recent advances in environmental antibiotic resistance genes detection and research focus: From genes to ecosystems.

Antibiotic resistance genes (ARGs) persistence and potential harm have become more widely recognized in the environment due to its fast-paced research. However, the bibliometric review on the detection, research hotspot, and development trend of environmental ARGs has not been widely conducted. It is essential to provide a comprehensive overview of the last 30 years of research on environmental ARGs to clarify the changes in the research landscape and ascertain future prospects. This study presents a visualized analysis of data from the Web of Science to enhance our understanding of ARGs. The findings indicate that solid-phase extraction provides a reliable method for extracting ARG. Technological advancements in commercial kits and microfluidics have facilitated the efficacy of ARGs extraction with significantly reducing processing times. PCR and its derivatives, DNA sequencing, and multi-omics technology are the prevalent methodologies for ARGs detection, enabling the expansion of ARG research from individual strains to more intricate microbial communities in the environment. Furthermore, due to the development of combination, hybridization and mass spectrometer technologies, considerable advancements have been achieved in terms of sensitivity and accuracy as well as lowering the cost of ARGs detection. Currently, high-frequency terms such as "Antibiotic Resistance, Antibiotics, and Metagenomics" are the center of attention for study in this area. Prominent topics include the investigation of anthropogenic impacts on environmental resistance, as well as the dynamics of migration, dissemination, and adaptation of environmental ARGs, etc. The research on environmental ARGs has made significant advancements in the fields of "Microbiology" and "Biotechnology Applied Microbiology". Over the past decade, there has been a notable increase in the fields of "Environmental Sciences Ecology" and "Engineering" with a similar growth trend observed in "Water Resources". These three domains are expected to continue driving extensive study within the realm of environmental ARGs.

Preconcentration and detection of SARS-CoV-2 in wastewater: A comprehensive review.

Severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) affected the health of human beings and the global economy. The patients with SARS-CoV-2 infection had viral RNA or live infectious viruses in feces. Thus, the possible transmission of SARS-CoV-2 through wastewater received great attentions. Moreover, SARS-CoV-2 in wastewater can serve as an early indicator of the infection within communities. We summarized the preconcentration and detection technology of SARS-CoV-2 in wastewater aiming at the complex matrices of wastewater and low virus concentration and compared their performance characteristics. We described the emerging tests that would be possible to realize the rapid detection of SARS-CoV-2 in fields and encourage academics to advance their technologies beyond conception. We concluded with a brief discussion on the outlook for integrating preconcentration and the detection of SARS-CoV-2 with emerging technologies.

Induced abortion after advent of fetal sex detection technology and child sex at birth.

BACKGROUND: National level Sex Ratio at Birth (SRB) is normal in Bangladesh despite its patriarchal social structures, strong son preference, and low fertility level, widely recognized as preconditions for Gender-Biased Sex Selection (GBSS). To better understand this anomaly, we examine the trend in SRB in a sub-district in Bangladesh and assess the impact of the introduction of fetal sex-detection technology and the history of induced abortion on child sex using longitudinal data. METHODS: We have used secondary data collected routinely by icddr, b's Matlab Health and Demographic Surveillance System (HDSS) between 1982 and 2018. All births occurring during this period (N = 206,390) were included in the analyses. We calculated the SRB and used multivariate logistic regression analyses to assess the likelihood of birth of a male child before and after the introduction of ultrasonogram in Matlab. RESULTS: Overall, SRB was within the natural limit (106) during 1982-2018 in Matlab. SRB among women with a history of induced abortion was 109.3 before the introduction of ultrasonography in 2001 and 113.5 - after 2001. Women's history of induced abortion prior to introduction of ultrasonogram (1982-2000) increased the likelihood of birth of a male child 1.06 times (AOR 1.06; 95% CI- 1.01-1.11). In the period after, however, this likelihood was 1.08 (AOR 1.08; 95% CI- 1.02-1.15). CONCLUSIONS: In a context with normal SRB, it was found to be skewed among women who had induced abortion. SRB was relatively more skewed among such women after the advent of ultrasonogram compared to a period without ultrasonogram. Moreover, induced abortion after introduction of fetal sex determination technology increased the likelihood of birth of a male child. These findings suggest the plausibility of GBSS in a sub-group. Further research is needed, particularly in regions with skewed SRB to examine whether GBSS is indeed a threat to Bangladesh.

Experimental study on comprehensive detection technology of shallow gas in deep soft soil layer.

This study focuses on the underground shallow gas detection project in the Lingkun Island area of the northern entrance tunnel of the Wenzhou City Light Rail S2 line. Based on geological exploration data of shallow gas, we chose the technique of controlled-release gas with static pressure as the experimental foundation, integrating various technologies such as multi-functional in-situ probing, electrical methods, and seismic waves, comprehensively researching shallow gas detection technology in the Lingkun Island area. We conducted field probing experiments to accurately obtain the physical and mechanical properties of gas-rich soil layers and further studied the possibility of determining gas-rich locations. By applying parallel electrical methods, we can accurately identify and distinguish areas of anomalous resistivity in shallow geological structures. Based on abnormal changes in acoustic impedance in strata, we used seismic wave methods, including seismic CT and seismic wave scattering technology, to accurately reveal the presence and depth of shallow gas, providing reliable basis for accurate determination of shallow gas. Finally, we summarized a comprehensive plan for underground shallow gas detection technology, covering on-site data collection, data processing, and image interpretation of results, which will provide valuable references for future shallow gas exploration in relevant areas.

Diagnostic accuracy of truenat MTB plus for the detection of pulmonary and extrapulmonary tuberculosis.

BACKGROUND: The diagnosis of Tuberculosis (TB) has been a challenge till the advent of rapid molecular diagnostic tests. The traditional diagnostic tests have its own limitations with regard to its performance or the turnaround time. Truenat MTB Plus assay, a battery-operated molecular assay developed in India has been introduced for its use in pulmonary TB (PTB). However, the diagnostic accuracy of the assay is not well studied in comparison with Mycobacterial culture, especially for extrapulmonary TB (EPTB). AIM: We aimed at evaluating the diagnostic accuracy of Truenat MTB Plus assay for both PTB and EPTB comparing with culture for adult population. METHODS: The specimens from presumptive PTB and EPTB patients were processed for Truenat MTB Plus assay, solid or liquid culture and AFB staining. The electronic data of all the specimen reports collected retrospectively were analysed for the sensitivity and specificity. RESULTS: Out of the 736 samples which had valid culture reports, 364 (49.4 %) were respiratory and 372 (50.6 %) were extrapulmonary specimens. The test positivity rate for smear microscopy, Truenat MTB Plus assay and culture was 3.7 % (27), 8.2 % (60), 7.1 % (52) respectively. Of the 60 Truenat MTB Plus positive patients with TB, 33 (55 %) were PTB and 27 (45 %) were EPTB. We estimated overall sensitivity and specificity of Truenat MTB Plus as 90 % (95 % CI: 73.4-97.8) and 98. 2 (95 % CI:96-99.3) respectively for the detection of PTB. The overall sensitivity and specificity for EPTB was 81.8 % (95 % CI: 59.7-94.8) and 97.4 % (95 % CI: 95.1-98.8) respectively. CONCLUSIONS: Truenat MTB Plus assay has comparable diagnostic accuracy with other molecular assays. The Truenat MTB Plus assay can be used for the diagnosis of PTB and EPTB, especially in resource limited settings.

Mapping the main harmful algal species in the East China Sea (Yangtze River estuary) and their possible response to the main ecological status and global climate change via a global vision.

The Yangtze River Estuary (YRE) is one of the areas in China most severely affected by harmful algal blooms (HABs). This study explored the distributive patterns of HABs in the YRE and how they are influenced by the El Niño-Southern Oscillation (ENSO) and other environmental factors. Quantitative real-time PCR (qPCR) was employed to detect and quantify the four predominant HAB species in the YRE, Karenia mikimotoi, Margalefidinium polykrikoides, Prorocentrum donghaiense, and Heterosigma akashiwo. Additionally, the study analyzed how turbidity, pH, salinity, and temperature influence these algae. Distribution of the four HAB species in the YRE area shows clear geographical variations: K. mikimotoi is predominantly found in the northwest and central sea areas, M. polykrikoides (East Asian Ribotype, EAR) is mainly distributed in the southeastern part, P. donghaiense is abundant in the northern regions, and H. akashiwo is especially prevalent at stations S26 and S27 in the northeastern part of the study area. HABs dominated by H. akashiwo and P. donghaiense were observed in the northeastern sea area of the YRE on July 22, 2020. Our study reveals that K. mikimotoi, M. polykrikoides (EAR), and P. donghaiense are mainly affected by turbidity, pH, and salinity, while temperature predominantly influences the blooms of H. akashiwo. Moreover, runoff in the YRE has a certain correlation with ENSO events, which may also impact the nutrient content of the region. The findings of this study illustrate the distributive patterns of the four HAB species under various ecological conditions in the YRE and emphasize the importance of establishing practical cases for future warning systems. To better understand how climate change affects HABs, exploring the link between ENSO and HABs is essential.

Complex heterozygous mutations in hereditary spherocytosis: A case report.

BACKGROUND: The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis (HS) in children. We also hope to promote the application of gene detection technology in children with HS, with the goals of identifying more related gene mutations, supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children, and providing important guidance for the diagnosis, treatment, and prevention of HS in children. CASE SUMMARY: A 1-year and 5-month-old patient presented jaundice during the neonatal period, mild anemia 8 months later, splenic enlargement at 1 year and 5 months, and brittle red blood cell permeability. Genetic testing was performed on the patient, their parents, and sister. Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1. Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother. Combined with the clinical symptoms of the children, it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause, providing important guidance for revealing the pathogenesis, diagnosis, treatment, and promotion of gene detection technology in children with HS. CONCLUSION: This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1, which provides a reference for exploring HS.

Improving real-time object detection in Internet-of-Things smart city traffic with YOLOv8-DSAF method.

With the rise of global smart city construction, target detection technology plays a crucial role in optimizing urban functions and improving the quality of life. However, existing target detection technologies still have shortcomings in terms of accuracy, real-time performance, and adaptability. To address this challenge, this study proposes an innovative target detection model. Our model adopts the structure of YOLOv8-DSAF, comprising three key modules: depthwise separable convolution (DSConv), dual-path attention gate module (DPAG), and feature enhancement module (FEM). Firstly, DSConv technology optimizes computational complexity, enabling real-time target detection within limited hardware resources. Secondly, the DPAG module introduces a dual-channel attention mechanism, allowing the model to selectively focus on crucial areas, thereby improving detection accuracy in high-dynamic traffic scenarios. Finally, the FEM module highlights crucial features to prevent their loss, further enhancing detection accuracy. Additionally, we propose an Internet of Things smart city framework consisting of four main layers: the application domain, the Internet of Things infrastructure layer, the edge layer, and the cloud layer. The proposed algorithm utilizes the Internet of Things infrastructure layer, edge layer, and cloud layer to collect and process data in real-time, achieving faster response times. Experimental results on the KITTI V and Cityscapes datasets indicate that our model outperforms the YOLOv8 model. This suggests that in complex urban traffic scenarios, our model exhibits superior performance with higher detection accuracy and adaptability. We believe that this innovative model will significantly propel the development of smart cities and advance target detection technology.

Detection technology and clinical applications of serum viral products of hepatitis B virus infection.

Viral hepatitis, caused by its etiology, hepatitis virus, is a public health problem globally. Among all infections caused by hepatitis-associated viruses, hepatitis B virus (HBV) infection remains the most serious medical concern. HBV infection particularly affects people in East Asia and Africa, the Mediterranean region, and Eastern Europe, with a prevalence rate of > 2%. Currently, approximately 1 billion people worldwide are infected with HBV, and nearly 30% of them experience chronic infection. Chronic HBV infection can lead to chronic hepatitis B (CHB), liver cirrhosis, and hepatocellular carcinoma (HCC), resulting in the related death of approximately 1 million people annually. Although preventative vaccines and antiviral therapies are currently available, there is no cure for this infection. Clinical testing is not only the gateway for diagnosis of HBV infection, but also crucial for judging the timing of medication, evaluating the effect of antiviral therapy, and predicting the risk of relapse after drug withdrawal in the whole follow-up management of hepatitis B infected persons. With advances in detection technology, it is now possible to measure various viral components in the blood to assess the clinical status of HBV infection. Serum viral products of HBV infection, such as HBV DNA, HBV RNA, hepatitis B surface antigen, hepatitis B e-antigen, and hepatitis B core-related antigen, are non-invasive indicators that are critical for the rapid diagnosis and management of related diseases. Improving the sensitivity of monitoring of these products is essential, and the development of corresponding detection technologies is pivotal in achieving this goal. This review aims to offer valuable insights into CHB infection and references for its effective treatment. We provide a comprehensive and systematic overview of classical and novel methods for detecting HBV serum viral products and discusses their clinical applications, along with the latest research progress in this field.

Classification of Fashion Models' Walking Styles Using Publicly Available Data, Pose Detection Technology, and Multivariate Analysis: From Past to Current Trendy Walking Styles.

Understanding past and current trends is crucial in the fashion industry to forecast future market demands. This study quantifies and reports the characteristics of the trendy walking styles of fashion models during real-world runway performances using three cutting-edge technologies: (a) publicly available video resources, (b) human pose detection technology, and (c) multivariate human-movement analysis techniques. The skeletal coordinates of the whole body during one gait cycle, extracted from publicly available video resources of 69 fashion models, underwent principal component analysis to reduce the dimensionality of the data. Then, hierarchical cluster analysis was used to classify the data. The results revealed that (1) the gaits of the fashion models analyzed in this study could be classified into five clusters, (2) there were significant differences in the median years in which the shows were held between the clusters, and (3) reconstructed stick-figure animations representing the walking styles of each cluster indicate that an exaggerated leg-crossing gait has become less common over recent years. Accordingly, we concluded that the level of leg crossing while walking is one of the major changes in trendy walking styles, from the past to the present, directed by the world's leading brands.

Research advances in detection of food adulteration and application of MALDI-TOF MS: A review.

Food adulteration and illegal supplementations have always been one of the major problems in the world. The threat of food adulteration to the health of consumers cannot be ignored. Food of questionable origin causes economic losses to consumers, but the potential health risks cannot be ignored. However, the traditional detection methods are time-consuming and complex. This review mainly discusses the types of adulteration and technologies used to detect adulteration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is also emphasized in the detection of adulteration and authenticity of origin analysis of various types of food (milk, meat, edible oil, etc.), and the future application direction and feasibility of this technology are analyzed. On this basis, MALDI-TOF MS was compared with other detection methods, highlighting the advantages of this technology in the detection of food adulteration. The future development prospect and direction of this technology are also emphasized.

Enhancing the understanding of SARS-CoV-2 protein with structure and detection methods: An integrative review.

As the rapid and accurate screening of infectious diseases can provide meaningful information for outbreak prevention and control, as well as owing to the existing limitations of the polymerase chain reaction (PCR), it is imperative to have new and validated detection techniques for SARS-CoV-2. Therefore, the rationale for outlining the techniques used to detect SARS-CoV-2 proteins and performing a comprehensive comparison to serve as a practical benchmark for future identification of similar viral proteins is clear. This review highlights the urgent need to strengthen pandemic preparedness by emphasizing the importance of integrated measures. These include improved tools for pathogen characterization, optimized societal precautions, the establishment of early warning systems, and the deployment of highly sensitive diagnostics for effective surveillance, triage, and resource management. Additionally, with an improved understanding of the virus' protein structure, considerable advances in targeted detection, treatment, and prevention strategies are expected to greatly improve our ability to respond to future outbreaks.

Current status and new experimental diagnostic methods of invasive fungal infections after hematopoietic stem cell transplantation.

Invasive fungal infections (IFIs) are common and life-threatening complications in post-hematopoietic stem cell transplantation (post-HSCT) recipients, Severe IFIs can lead to systemic infection and organ damage, which results in high mortality in HSCT recipients. With the development of the field of fungal infection diagnosis, more and more advanced non-culture diagnostic tools have been developed, such as glip biosensors, metagenomic next-generation sequencing, Magnetic Nanoparticles and Identified Using SERS via AgNPs+ , and artificial intelligence-assisted diagnosis. The advanced diagnostic approaches contribute to the success of HSCT and improve the overall survival of post-HSCT leukemia patients by supporting therapeutical decisions. This review provides an overview of the characteristics of two high-incidence IFIs in post-HSCT recipients and discusses some of the recently developed IFI detection technologies. Additionally, it explores the potential application of cationic conjugated polymer fluorescence resonance energy transfer (CCP-FRET) technology for IFI detection. The aim is to offer insights into selecting appropriate IFI detection methods and gaining an understanding of novel fungal diagnostic approaches in laboratory settings.

Circulating tumor DNA methylation: a promising clinical tool for cancer diagnosis and management.

Cancer continues to pose significant challenges to the medical community. Early detection, accurate molecular profiling, and adequate assessment of treatment response are critical factors in improving the quality of life and survival of cancer patients. Accumulating evidence shows that circulating tumor DNA (ctDNA) shed by tumors into the peripheral blood preserves the genetic and epigenetic information of primary tumors. Notably, DNA methylation, an essential and stable epigenetic modification, exhibits both cancer- and tissue-specific patterns. As a result, ctDNA methylation has emerged as a promising molecular marker for noninvasive testing in cancer clinics. In this review, we summarize the existing techniques for ctDNA methylation detection, describe the current research status of ctDNA methylation, and present the potential applications of ctDNA-based assays in the clinic. The insights presented in this article could serve as a roadmap for future research and clinical applications of ctDNA methylation.

[Antibody druggability screening process and evaluation strategy].

Since the approval of OKT3 as the first therapeutic monoclonal antibody in 1986, there has been rapid development in antibody technology and antibody drugs. Monoclonal antibodies, antibody fragments, bi (multi) specific antibodies, fusion proteins, nanobodies, and antibody-drug conjugates (ADCs) have been introduced and play a significant role in the treatment of oncology, hematology, immunology, respiratory, metabolic and other related diseases. The process of antibody drug discovery involves multiple rounds of biological function and druggability assessments to identify the best candidate sequences that are safe, effective, stable, and scalable. This lays the foundation for the efficiency and success of drug development and clinical studies. In the phase of antibody drug discovery, "druggability screening and evaluation" has received increasing attention. It involves drug discovery and design, screening and optimization of lead molecules as well as the validation of candidate molecules, with the aim of detecting potential physicochemical risk factors and evaluating controllability to ensure the quality stability of the subsequent drug development process. This paper classifies and defines the process of druggability screening and evaluation in the antibody discovery phase, covering monoclonal antibodies, bispecific antibodies, nanobodies, ADCs and other related technologies and drug forms. It also summarizes the quality attributes and high-throughput detection technology that should be emphasized in the druggability screening and evaluation. The systematic elaboration of the druggability development process and strategy provides a reference for the druggability screening and evaluation of emerging innovative drugs, significantly improving the efficiency and success rate of antibody drug development.

Development of a rapid visual detection technology for BmNPV based on CRISPR/Cas13a system.

Pathogenic microorganism of silkworm are important factors that threaten the high-quality development of sericulture. Among them, Bombyx mori nucleopolyhedrovirus (BmNPV) caused diseases often lead to frequent outbreaks and high mortality, resulting in huge losses to sericultural industry. Current molecular detection methods for BmNPV require expensive equipment and sikilled technical personnel. As a result, the most commonly detection method for silkworm egg production enterprises involves observing the presence of polyhedra under a microscope. However, this method has low accuracy and sensitivity. There is an urgent need to develop a new detection technology with high sensitivity, high specificity, and applicability for silkworm farms, silkworm egg production enterprises and quarantine departments. In this study, we successfully established the CRISPR/Cas13a BmNPV visualized detection technology by combining Recombinase Polymerase Amplification (RPA) technology and CRISPR/Cas13a system. This technology is based on microplate lateral, flow test strips and portable fluorescence detector. The detection sensitivity can reach up to 1 copies/µL for positive standard plasmid and 1 fg/µL for BmNPV genome in 30-45 min, demonstrating high sensitivity. By detecting silkworm tissues infected with different pathogens, we determined that CRISPR/Cas13a detection technology has good specificity. In summary, the newly established nucleic acid detection technology for BmNPV is characterized by high sensitivity, high specificity, low cost and convenience for visualization. It can be applied in field detection and silkworm egg quality monitory system.

Bioaerosols in the atmosphere: A comprehensive review on detection methods, concentration and influencing factors.

In the past few decades, especially since the outbreak of the coronavirus disease (COVID-19), the effects of atmospheric bioaerosols on human health, the environment, and climate have received great attention. To evaluate the impacts of bioaerosols quantitatively, it is crucial to determine the types of bioaerosols in the atmosphere and their spatial-temporal distribution. We provide a concise summary of the online and offline observation strategies employed by the global research community to sample and analyze atmospheric bioaerosols. In addition, the quantitative distribution of bioaerosols is described by considering the atmospheric bioaerosols concentrations at various time scales (daily and seasonal changes, for example), under various weather, and different underlying surfaces. Finally, a comprehensive summary of the reasons for the spatiotemporal distribution of bioaerosols is discussed, including differences in emission sources, the impact process of meteorological factors and environmental factors. This review of information on the latest research progress contributes to the emergence of further observation strategies that determine the quantitative dynamics of public health and ecological effects of bioaerosols.

Advances in Detection Techniques for the H5N1 Avian Influenza Virus.

Avian influenza is caused by avian influenza virus infection; the H5N1 avian influenza virus is a highly pathogenic subtype, affecting poultry and human health. Since the discovery of the highly pathogenic subtype of the H5N1 avian influenza virus, it has caused enormous losses to the poultry farming industry. It was recently found that the H5N1 avian influenza virus tends to spread among mammals. Therefore, early rapid detection methods are highly significant for effectively preventing the spread of H5N1. This paper discusses the detection technologies used in the detection of the H5N1 avian influenza virus, including serological detection technology, immunological detection technology, molecular biology detection technology, genetic detection technology, and biosensors. Comparisons of these detection technologies were analyzed, aiming to provide some recommendations for the detection of the H5N1 avian influenza virus.

Argonaute protein-based nucleic acid detection technology.

It is vital to diagnose pathogens quickly and effectively in the research and treatment of disease. Argonaute (Ago) proteins are recently discovered nucleases with nucleic acid shearing activity that exhibit specific recognition properties beyond CRISPR-Cas nucleases, which are highly researched but restricted PAM sequence recognition. Therefore, research on Ago protein-mediated nucleic acid detection technology has attracted significant attention from researchers in recent years. Using Ago proteins in developing nucleic acid detection platforms can enable efficient, convenient, and rapid nucleic acid detection and pathogen diagnosis, which is of great importance for human life and health and technological development. In this article, we introduce the structure and function of Argonaute proteins and discuss the latest advances in their use in nucleic acid detection.

Diverse applications and development of aptamer detection technology.

Aptamers have received extensive attention in recent years because of their advantages of high specificity, high sensitivity and low immunogenicity. Aptamers can perform almost all functions of antibodies through the combination of spatial structure and target, which are called "chemical antibodies". At present, aptamers have been widely used in cell imaging, new drug development, disease treatment, microbial detection and other fields. Due to the diversity of modifications, aptamers can be combined with different detection technologies to construct aptasensors. This review focuses on the diversity of aptamers in the field of detection and the development of aptamer-based detection technology and proposes new challenges for aptamers in this field.