BACKGROUND: The parasitic protozoan Giardia duodenalis is an important cause of diarrheal disease in humans and animals that can be spread by fecal-oral transmission through water and the environment, posing a challenge to public health and animal husbandry. Little is known about its impact on large-scale sheep farms in China. In this study we investigated G. duodenalis infection of sheep and contamination of the environment in large-scale sheep farms in two regions of China, Henan and Ningxia.
METHODS: A total of 528 fecal samples, 402 environmental samples and 30 water samples were collected from seven large-scale sheep farms, and 88 fecal samples and 13 environmental samples were collected from 12 backyard farms. The presence of G. duodenalis was detected by targeting the β-giardin (bg) gene, and the assemblage and multilocus genotype of G. duodenalis were investigated by analyzing three genes: bg, glutamate dehydrogenase (gdh) and triphosphate isomerase (tpi).
RESULTS: The overall G. duodenalis detection rate was 7.8%, 1.4% and 23.3% in fecal, environmental and water samples, respectively. On the large-scale sheep farms tested, the infection rate of sheep in Henan (13.8%) was found to be significantly higher than that of sheep in Ningxia (4.2%) (P < 0.05). However, the difference between the rates of environmental pollution in Henan (1.9%) and Ningxia (1.0%) was not significant (P > 0.05). Investigations of sheep at different physiological stages revealed that late pregnancy ewes showed the lowest infection rate (1.7%) and that young lambs exhibited the highest (18.8%). Genetic analysis identified G. duodenalis belonging to two assemblages, A and E, with assemblage E being dominant. A total of 27 multilocus genotypes were identified for members of assemblage E.
CONCLUSIONS: The results suggest that G. duodenalis is prevalent on large-scale sheep farms in Henan and Ningxia, China, and that there is a risk of environmental contamination. This study is the first comprehensive examination of the presence of G. duodenalis on large-scale sheep farms in China. Challenges posed by G. duodenalis to sheep farms need to be addressed proactively to ensure public health safety.

Pressure sensors urgently need high-performance sensing materials in order to be developed further. Sensitivity and creep are regarded as two key indices for assessing a sensor\'s performance. For the design and optimization of sensing materials, an accurate estimation of the impact of several parameters on sensitivity and creep is essential. In this study, sensitivity and creep were predicted using the response surface methodology (RSM) and support vector regression (SVR), respectively. The input parameters were the concentrations of nickel (Ni) particles, multiwalled carbon nanotubes (MWCNTs), and multilayer graphene (MLG), as well as the magnetic field intensity (B). According to statistical measures, the SVR model exhibited a greater level of predictability and accuracy. The non-dominated sorting genetic-II algorithm (NSGA-II) was used to generate the Pareto-optimal fronts, and decision-making was used to determine the final optimal solution. With these conditions, the optimized results revealed an improved performance compared to the earlier study, with an average sensitivity of 0.059 kPa-1 in the pressure range of 0-16 kPa and a creep of 0.0325, which showed better sensitivity in a wider range compared to previous work. The theoretical sensitivity and creep were relatively similar to the actual values, with relative deviations of 0.317% and 0.307% after simulation and experimental verification. Future research for transducer performance optimization can make use of the provided methodology because it is representative.

In this investigation, p-Mg2Si/n-Si heterojunction photodetector (PD) is fabricated by magnetron sputtering and low vacuum annealing in the absence of argon or nitrogen atmosphere. Multilayer Graphene (MLG)/Mg2Si/Si heterojunction PD is first fabricated by transferring MLG to Mg2Si/Si heterojunction substrate using the suspended self-help transfer MLG method. After characterizing the phase composition, morphology and detection properties of Mg2Si/Si and MLG/Mg2Si/Si heterojunction PDs, the successful fabrication of the Mg2Si/Si and MLG/Mg2Si/Si heterojunction PDs are confirmed and some detection capabilities are realized. Compared with the Mg2Si/Si heterojunction PD, the light absorption and the ability to effectively separate and transfer photogenerated carriers of MLG/Mg2Si/Si heterojunction PD are improved. The responsivity, external quantum efficiency (EQE), noise equivalent power (NEP), detectivity (D*), on/off ratio and other detection properties are enhanced. The peak responsivity and EQE of the MLG/Mg2Si/Si heterojunction PD are 23.7 mA/W and 2.75%, respectively, which are better than the previous 1-10 mA/W and 2.3%. The results illustrate that the fabrication technology of introducing MLG to regulate the detection properties of the Mg2Si/Si heterojunction PD is feasible. In addition, this study reveals the potential of MLG to enhance the detection properties of optoelectronic devices, broadens the application prospect of the Mg2Si/Si-based heterojunction PDs and provides a direction for the regulation of optoelectronic devices.

Plant cell walls (PCWs) form the outer barrier of cells that give the plant strength and directly interact with the environment and other cells in the plant. PCWs are composed of several polysaccharides, of which cellulose forms the main fibrillar network. Enmeshed between these fibrils of cellulose are non-cellulosic polysaccharides (NCPs), pectins, and proteins. This study investigates the sequence, timing, patterning, and architecture of cell wall polysaccharide regeneration in suspension culture cells (SCC) of the grass species Lolium multiflorum (Lolium). Confocal, superresolution, and electron microscopies were used in combination with cytochemical labeling to investigate polysaccharide deposition in SCC after protoplasting. Cellulose was the first polysaccharide observed, followed shortly thereafter by (1,3;1,4)-β-glucan, which is also known as mixed-linkage glucan (MLG), arabinoxylan (AX), and callose. Cellulose formed fibrils with AX and produced a filamentous-like network, whereas MLG formed punctate patches. Using colocalization analysis, cellulose and AX were shown to interact during early stages of wall generation, but this interaction reduced over time as the wall matured. AX and MLG interactions increased slightly over time, but cellulose and MLG were not seen to interact. Callose initially formed patches that were randomly positioned on the protoplast surface. There was no consistency in size or location over time. The architecture observed via superresolution microscopy showed similarities to the biophysical maps produced using atomic force microscopy and can give insight into the role of polysaccharides in PCWs.

Giardia duodenalis (syn. Giardia lamblia, Giardia intestinalis) is an important zoonotic parasite that parasitizes the gastro-intestines of humans and animals, with diarrhea as the most common clinical symptom. The goat has been indicated as one of the most important reservoirs of G. duodenalis for humans. In the present study, we investigated the prevalence and genetic diversity of G. duodenalis in goats in Shaanxi province, northwestern China. A total of 1311 faecal specimens were examined, and the overall prevalence was 7.1% (93/1311). Although all the meat, cashmere and dairy goats were positive for infection, the highest prevalence was found in cashmere goats (10.2%), followed by dairy (9.4%) and meat goats (2.0%). Negative correlation between age and prevalence was also observed, and the highest prevalence was detected in 0-2-month goats. Genetic analysis showed the presence of three assemblages, including two zoonotic (A and B) and one animal-adapted assemblage E, with E as the prevalent assemblage found in all breeds of positive goats. The zoonotic assemblage A was found in Guanzhong dairy and Shanbei cashmere goats, but B was only detected in Boar goats. Additionally, mixed assemblages E and A were also identified in two cashmere goats. Multi-locus genotyping (MLST) using the gene loci of the triosephosphate isomerase (tpi), b-giardin (bg) and glutamate dehydrogenase (gdh) identified four novel multi-locus genotypes (MLGs), including two assemblage E MLGs and two assemblage A MLGs. These results suggested that Boar, Guanzhong dairy and Shanbei cashmere goats in Shaanxi province would be potential reservoirs for human infections in this area, and this study also provided basic data for controlling G. duodenalis infection in goats as well as other hosts.

BACKGROUND: Giardiasis, caused by Giardia duodenalis (syn. Giardia intestinalis, Giardia lamblia), is a significant zoonotic parasitic disease of animals and humans worldwide. Accurate genotyping of G. duodenalis is essential for efficient control and management of giardiasis. The objectives of the present study were to investigate the prevalence and assemblages of giardiasis in pigs in Shaanxi Province, northwestern China, and for the first time study multilocus genotypes (MLGs) in pigs using multilocus genotyping technology in this region.
RESULTS: Of 560 faecal samples collected from five farms in Shaanxi Province, 45 were positive for G. duodenalis and significant differences in prevalence were observed among different locations. Differences in prevalence were also detected in pigs of different age groups, with the highest prevalence in sows and the lowest in boars. Two assemblages, A and E, were identified, and a mixed infection of both A and E was identified in one faecal sample. Assemblage E was predominant and widely distributed in all investigated areas and age groups. Genetic viability was detected for both assemblages, and four different multi-locus genotypes (MLGs) within assemblage E were found, MLGE1-MLGE4.
CONCLUSIONS: Giardia duodenalis was detected in pigs from Shaanxi Province, northwestern China, and genetic diversity was observed in these infections. Both assemblages A and E were detected, and four distinct MLGs within assemblage E were identified. These findings provide new data for controlling G. duodenalis infection in pigs.