Key molecules regulating the blood meals of Rhipicephalus sanguineus (Acari: Ixodidae) revealed by transcriptomics.

Rhipicephalus sanguineus, a repulsive obligate blood feeder, is a three-host tick inflicting tremendous damage. Blood-sucking initiates tick-pathogen-host interactions along with alterations in the expression levels of numerous bioactive ingredients. Key molecules regulating blood meals were identified using the transcriptomic approach. A total number of 744 transcripts showed statistically significantly differential expression including 309 significantly upregulated transcripts and 435 significantly downregulated transcripts in semiengorged female ticks compared to unfed ticks, all collected in 2021. The top 10 differentially upregulated transcripts with explicit functional annotations included turripeptide OL55-like protein, valine tRNA ligase-like protein and ice-structuring glycoprotein-like protein. The top 10 differentially down-regulated transcripts were uncharacterized proteins. Gene Ontology (GO) enrichment analysis revealed four associated terms in the cellular component category and 16 in the molecular function category among the top 20 terms. Differentially expressed genes (DEGs) were enriched in GO terms ID 0000323 (lytic vacuole) and ID 0005773 (vacuole). The top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways included metabolism, cellular processes, organismal systems and human diseases. The DEGs were enriched in the KEGG term ID: ko-04142 (lysosome pathway) associated with intracellular digestion in the tick midgut epithelium. Molecular markers annotated via comparative transcriptomic profiling were expected to be candidate markers for the purpose of tick control.

Classification of colorectal cancer consensus molecular subtypes using attention-based multi-instance learning network on whole-slide images.

Colorectal cancer (CRC) is the third most common and second most lethal cancer globally. It is highly heterogeneous with different clinical-pathological characteristics, prognostic status, and therapy responses. Thus, the precise diagnosis of CRC subtypes is of great significance for improving the prognosis and survival of CRC patients. Nowadays, the most commonly used molecular-level CRC classification system is the Consensus Molecular Subtypes (CMSs). In this study, we applied a weakly supervised deep learning method, named attention-based multi-instance learning (MIL), on formalin-fixed paraffin-embedded (FFPE) whole-slide images (WSIs) to distinguish CMS1 subtype from CMS2, CMS3, and CMS4 subtypes, as well as distinguish CMS4 from CMS1, CMS2, and CMS3 subtypes. The advantage of MIL is training a bag of the tiled instance with bag-level labels only. Our experiment was performed on 1218 WSIs obtained from The Cancer Genome Atlas (TCGA). We constructed three convolutional neural network-based structures for model training and evaluated the ability of the max-pooling operator and mean-pooling operator on aggregating bag-level scores. The results showed that the 3-layer model achieved the best performance in both comparison groups. When compared CMS1 with CMS234, max-pooling reached the ACC of 83.86 % and the mean-pooling operator reached the AUC of 0.731. While comparing CMS4 with CMS123, mean-pooling reached the ACC of 74.26 % and max-pooling reached the AUC of 0.609. Our results implied that WSIs could be utilized to classify CMSs, and manual pixel-level annotation is not a necessity for computational pathology imaging analysis.

Assessment of risk, landscape epidemiology and management strategies to combat alveolar echinococcosis in the rural communities of Hunza, Pakistan.

Background: Human alveolar echinococcosis (AE) is a neglected zoonotic disease. Prevalence of AE in humans is reported in Pakistan as a result of poor economic and sanitary conditions, close proximity to wildlife and limited knowledge of AE. Studies on the prevalence and transmission of AE have been limited, especially for rural Pakistan. The study objectives were to identify knowledge, attitudes and practices relating to AE, to determine awareness of the disease, and to identify knowledge about possible risk factors of infections involving the landscape epidemiological attributes of rural villages in Hunza, one of the districts of Gilgit-Baltistan, a region of Pakistan that borders China. Methods: A community-based cross-sectional study was conducted among the general population of Hunza to establish the level of awareness, knowledge, attitudes, practices, landscape epidemiology, and disease management and control relating to AE in rural areas of Hunza. Data were collected by questionnaire. Results: A total of 387 questionnaires was received. Statistical analysis showed that the population's knowledge about the disease was poor. The attitudes and practices of the participants indicated that their risk of infection was low. Knowledge of landscape epidemiology of the disease was poor but knowledge about AE disease management was good. The attitudes of residents toward disease treatment and control strategies were positive, although the overall knowledge of participants about prevention of infection was poor. Conclusion: Knowledge of AE is poor among the residents of Hunza, Pakistan. Our study demands continued and strengthened awareness of the changes to lifestyle and practices associated with AE, not only in the study locality but throughout other areas of Pakistan.

Asymptomatic malaria infection at the China-Vietnam border: Knowledge and implications for the cross-border migrant population during the COVID-19 pandemic.

BACKGROUND: Eliminating malaria along the China-Vietnam border remains one of the greatest challenges in China, especially during the coronavirus disease 2019 (COVID-19) pandemic, which has disrupted the continuity of malaria control and elimination programs. Understanding the factors associated with asymptomatic malaria infection will inform control interventions aimed at elimination of the disease among migrants from Vietnam working in China, who constitute an at-risk population. METHODS: From March 2018 to September 2019, 108 migrants from Vietnam working in Ningming County, Guangxi, were enrolled in this study. Each person was interviewed using a structured questionnaire. Blood samples were collected and sent for PCR detection and sequencing. The obtained sequences were analyzed using the BLAST program and DNAMAN software. RESULTS: The proportion of participants with malaria knowledge was low, with 19.4% (21/108) reporting knowledge about transmission, 23.2% (25/108) reporting knowledge about clinical symptoms, 7.4% (8/108) reporting awareness of the risk of death and 14.8% (16/108) reporting awareness of prevention methods. No significant difference in the malaria knowledge rate was found among occupational groups, except in the migrant worker group, whose knowledge rate was higher than those in the other occupational groups (χ2 = 32.452, p < 0.001). Although most of the participants (80.6%, 87/108) owned mosquito nets, only approximately half of the participants (49.1%, 53/108) reported using bed nets. The parasitological analysis revealed that 5.6% (6/108) of all the participants were positive for malaria, including 5 participants with Plasmodium falciparum and 1 participant with Plasmodium vivax malaria. There were no statistically significant differences in the positivity rates among the different age, sex, family-size, nationality, occupational, and behavior groups. The positivity rates in individuals who did not use mosquito nets, did not use mosquito coils, and did not install mosquito nets were 4.8% (1/21), 6.8% (3/44), and 3.6% (2/55), respectively. CONCLUSION: Health education focused on high-risk populations, such as migrant workers and forest goers, should be strengthened. Verbal communication and information transmission via the internet, radio, and mobile phone platforms may be required during the COVID-19 pandemic. Further risk assessments and proactive case detection should also be performed in Ningming County and other border counties in Guangxi to detect active and asymptomatic infections in a timely manner and prevent re-establishment of the disease in these communities.