DNA Microarray Detection of 18 Important Human Blood Protozoan Species

Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review

Background

The prevalence of infectious diseases remains one of the major challenges faced by the Chinese health sector. Policymakers have a tremendous interest in investigating the spatiotemporal epidemiology of infectious diseases. We aimed to review the small-scale (city level, county level, or below) spatiotemporal epidemiology of notifiable infectious diseases in China through a systematic review, thus summarizing the evidence to facilitate more effective prevention and control of the diseases.

Methods

We searched four English language databases (PubMed, EMBASE, Cochrane Library, and Web of Science) and three Chinese databases (CNKI, WanFang, and SinoMed), for studies published between January 1, 2004 (the year in which China’s Internet-based disease reporting system was established) and December 31, 2021. Eligible works were small-scale spatial or spatiotemporal studies focusing on at least one notifiable infectious disease, with the entire territory of mainland China as the study area. Two independent reviewers completed the review process based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Results

A total of 18,195 articles were identified, with 71 eligible for inclusion, focusing on 22 diseases. Thirty-one studies (43.66%) were analyzed using city-level data, 34 (47.89%) were analyzed using county-level data, and six (8.45%) used community or individual data. Approximately four-fifths (80.28%) of the studies visualized incidence using rate maps. Of these, 76.06% employed various spatial clustering methods to explore the spatial variations in the burden, with Moran’s I statistic being the most common. Of the studies, 40.85% explored risk factors, in which the geographically weighted regression model was the most commonly used method. Climate, socioeconomic factors, and population density were the three most considered factors.

Conclusions

Small-scale spatiotemporal epidemiology has been applied in studies on notifiable infectious diseases in China, involving spatiotemporal distribution and risk factors. Health authorities should improve prevention strategies and clarify the direction of future work in the field of infectious disease research in China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07669-9.

Analysis and comparison of machine learning methods for blood identification using single-cell laser tweezer Raman spectroscopy

Raman spectroscopy, a "fingerprint" spectrum of substances, can be used to characterize various biological and chemical samples. To allow for blood classification using single-cell Raman spectroscopy, several machine learning algorithms were implemented and compared. A single-cell laser optical tweezer Raman spectroscopy system was established to obtain the Raman spectra of red blood cells. The Boruta algorithm extracted the spectral feature frequency shift, reduced the spectral dimension, and determined the essential features that affect classification. Next, seven machine learning classification models are analyzed and compared based on the classification accuracy, precision, and recall indicators. The results show that support vector machines and artificial neural networks are the two most appropriate machine learning algorithms for single-cell Raman spectrum blood classification, and this finding provides essential guidance for future research studies.

Detection and molecular identification of blood parasites in rodents captured from urban areas of southern Sarawak, Malaysian Borneo

BACKGROUND

Rodent species are well known for their potential as hosts and reservoirs for various zoonotic diseases. Studies on blood parasite infection in small mammals focused on urban cities in Peninsular Malaysia and have been conducted over the years. In contrast, there are information gaps related to molecular detection of blood parasites in urban areas of Sarawak that are associated with veterinary importance and zoonotic spillover potential. Increasing prevalence and transmission of blood parasite diseases is the most crucial public health issue, particularly in developing urban areas of Sarawak. Therefore, molecular identification studies were performed to determine and identify the blood parasites infecting rodents.

METHODS

A total of 40 rodent blood samples were analysed for blood parasite infection and a combined approach using polymerase chain reaction-based technique, and traditional microscopic examination (blood smear test) was conducted. 18s rRNA (Plasmodium spp.) and cytochrome b (Hepatocystis spp.) gene marker were used to identify the blood parasites.

RESULTS

Note that 67.5% (n = 27) blood samples were tested negative for blood parasites, while 32.5% (n = 13) blood samples collected were infected with at least one protozoan parasite. Out of 13 samples, 69.2% (n = 9) were detected with Hepatocystis sp., while 15.4% (n = 2) were positive with Hepatozoon ophisauri. Two individuals had multiple infections from both species. No Plasmodium spp. have been detected throughout this study using universal primer (targeted Plasmodium spp.); however, different parasite species which were H. ophisauri were detected.

CONCLUSION

Although there is no evidence of human infection from H. ophisauri and Hepatocystis sp. detected from the study, the data show the host species are heavily infected, and the information is essential for future prevention of zoonotic outbreaks and surveillance programmes. Therefore, it is suggested that the surveillance programmes should be incorporated in targeted areas with a high risk of disease emergence.

Blood identification at the single-cell level based on a combination of laser tweezers Raman spectroscopy and machine learning

Laser tweezers Raman spectroscopy (LTRS) combines optical tweezers technology and Raman spectroscopy to obtain biomolecular compositional information from a single cell without invasion or destruction, so it can be used to "fingerprint" substances to characterize numerous types of biological cell samples. In the current study, LTRS was combined with two machine learning algorithms, principal component analysis (PCA)-linear discriminant analysis (LDA) and random forest, to achieve high-precision multi-species blood classification at the single-cell level. The accuracies of the two classification models were 96.60% and 96.84%, respectively. Meanwhile, compared with PCA-LDA and other classification algorithms, the random forest algorithm is proved to have significant advantages, which can directly explain the importance of spectral features at the molecular level.

The role of vascular endothelium and exosomes in human protozoan parasitic diseases

The vascular endothelium is a vital component in maintaining the structure and function of blood vessels. The endothelial cells (ECs) mediate vital regulatory functions such as the proliferation of cells, permeability of various tissue membranes, and exchange of gases, thrombolysis, blood flow, and homeostasis. The vascular endothelium also regulates inflammation and immune cell trafficking, and ECs serve as a replicative niche for many bacterial, viral, and protozoan infectious diseases. Endothelial dysfunction can lead to vasodilation and pro-inflammation, which are the hallmarks of many severe diseases. Exosomes are nanoscale membrane-bound vesicles that emerge from cells and serve as important extracellular components, which facilitate communication between cells and maintain homeostasis during normal and pathophysiological states. Exosomes are also involved in gene transfer, inflammation and antigen presentation, and mediation of the immune response during pathogenic states. Protozoa are a diverse group of unicellular organisms that cause many infectious diseases in humans. In this regard, it is becoming increasingly evident that many protozoan parasites (such as Plasmodium, Trypanosoma, Leishmania, and Toxoplasma) utilize exosomes for the transfer of their virulence factors and effector molecules into the host cells, which manipulate the host gene expression, immune responses, and other biological activities to establish and modulate infection. In this review, we discuss the role of the vascular endothelium and exosomes in and their contribution to pathogenesis in malaria, African sleeping sickness, Chagas disease, and leishmaniasis and toxoplasmosis with an emphasis on their actions on the innate and adaptive immune mechanisms of resistance.

DNA-based microarray studies in visceral leishmaniasis: identification of biomarkers for diagnostic, prognostic and drug target for treatment

Visceral leishmaniasis (VL) is one of the major infectious diseases affecting the poorest regions of the world. Current therapy is not very much satisfactory. The alarming rise of drug resistance and the unavailability of an effective vaccine against VL urges research towards identifying new targets or biomarkers for its effective treatment. New technology developments offer some fresh hope in its diagnosis, treatment, and control. DNA microarray approach is now broadly used in parasitology research to facilitate the thoughtful of mechanisms of disease and identification of drug targets and biomarkers for diagnostic and therapeutic development. An electronic search on "VL" and "Microarray" was conducted in Medline and Scopus and papers published in the English mentioning use of DNA microarray on VL were selected and read to write this paper review. Functional analysis and interpretation of microarray results remain very challenging due to the inherent nature of experimental workflows, access, cost, and complexity of data obtained. We have explained and emphasized the use of curate knowledge of microarray in the case of VL for the identification of therapeutic target and biomarker and their selection/implementation in clinical use.

Establishment and application of the National Parasitic Resource Center (NPRC) in China

The National Parasitic Resource Center (NPRC) was created in 2004. It is a first-level platform under the Basic Condition Platform Center of the Ministry of Science and Technology of China. The resource centre involves 21 depository institutions in 15 regions of the country, including human parasite and vector depository, animal parasite depository, plant nematode characteristic specimen library, medical insect characteristic specimen library, trematode model specimen library, parasite-vector/snail model specimen library, etc. After nearly 15 years of operation, the resource centre has been built into a physical library with a database of 11 phyla, 23 classes, 1115 species and 117,814 pieces of parasitic germplasm resources, and three live collection bases of parasitic germplasm resources. A variety of new parasite-related immunological and molecular biological detection and identification technologies produced by the resource centre are widely used in the fields of public health responses, risk assessments on food safety, and animal or plant quarantine. The NPRC is the largest and top level resource centre on parasitology in China, and it is a leading technology platform for collecting and identifying parasitic resources.

Genotyping of KRAS Mutational Status by the In-Check Lab-on-Chip Platform

The KRAS oncogene is involved in the pathogenesis of several types of cancer, particularly colorectal cancer (CRC). The most frequent mutations in this gene are associated with poor survival, increased tumor aggressiveness and resistance to therapy with anti-epidermal growth factor receptor (EGFR) antibodies. For this reason, KRAS mutation testing has become increasingly common in clinical practice for personalized cancer treatments of CRC patients. Detection methods for KRAS mutations are currently expensive, laborious, time-consuming and often lack of diagnostic sensitivity and specificity. In this study, we describe the development of a Lab-on-Chip assay for genotyping of KRAS mutational status. This assay, based on the In-Check platform, integrates microfluidic handling, a multiplex polymerase chain reaction (PCR) and a low-density microarray. This integrated sample-to-result system enables the detection of KRAS point mutations, including those occurring in codons 12 and 13 of exon 2, 59 and 61 of exon 3, 117 and 146 of exon 4. Thanks to its miniaturization, automation, rapid analysis, minimal risk of sample contamination, increased accuracy and reproducibility of results, this Lab-on-Chip platform may offer immediate opportunities to simplify KRAS genotyping into clinical routine.