238 research outputs found

    Comparative study on the gut microbiotas of four economically important Asian carp species

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    Gut microbiota of four economically important Asian carp species (silver carp, Hypophthalmichthys molitrix; bighead carp, Hypophthalmichthys nobilis; grass carp, Ctenopharyngodon idella; common carp, Cyprinus carpio) were compared using 16S rRNA gene pyrosequencing. Analysis of more than 590,000 quality-filtered sequences obtained from the foregut, midgut and hindgut of these four carp species revealed high microbial diversity among the samples. The foregut samples of grass carp exhibited more than 1,600 operational taxonomy units (OTUs) and the highest alpha-diversity index, followed by the silver carp foregut and midgut. Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria were the predominant phyla regardless of fish species or gut type. Pairwise (weighted) UniFrac distance-based permutational multivariate analysis of variance with fish species as a factor produced significant association (P &lt; 0.01). The gut microbiotas of all four carp species harbored saccharolytic or proteolytic microbes, likely in response to the differences in their feeding habits. In addition, extensive variations were also observed even within the same fish species. Our results indicate that the gut microbiotas of Asian carp depend on the exact species, even when the different species were cohabiting in the same environment. This study provides some new insights into developing commercial fish feeds and improving existing aquaculture strategies.</p

    Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota

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    The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.</p

    Feature Extraction of Oscillating Flow with Vapor Condensation of Moist Air in a Sonic Nozzle

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    The sonic nozzle is commonly used in flow measurement. However, the non-equilibrium condensation phenomenon of moist air in the nozzle has a negative effect on the measuring accuracy. To investigate this complex phenomenon, the experiments on the oscillating condensation flow of moist air were conducted by an adjustable humidification apparatus with different relative humidity (0-100%), temperature (30-50° C) and carrier gas pressure (1-6 bar), where the micro size pressure measuring system was designed by Bergh-Tijdeman (B-T) Model. The accurate mathematical model of nonequilibrium condensation was also built and validated by the experimental data of time-averaged pressure distribution. Then, the frequency and intensity of pressure fluctuation of oscillating flow at a wide range of operation condition were obtained combining experimental data and physical simulation model. Importantly, a new semi-empirical relation of dimensionless frequency deduced from dimensionless analysis was identified accurately by experimental data. Finally, the signal nonstationarity was also observed by using the continuous wavelet transform (CWT). The instantaneous frequency saltation and the energy attenuation of pressure signals were observed in the condensation flow

    Integrating UMLS Knowledge into Large Language Models for Medical Question Answering

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    Large language models (LLMs) have demonstrated powerful text generation capabilities, bringing unprecedented innovation to the healthcare field. While LLMs hold immense promise for applications in healthcare, applying them to real clinical scenarios presents significant challenges, as these models may generate content that deviates from established medical facts and even exhibit potential biases. In our research, we develop an augmented LLM framework based on the Unified Medical Language System (UMLS), aiming to better serve the healthcare community. We employ LLaMa2-13b-chat and ChatGPT-3.5 as our benchmark models, and conduct automatic evaluations using the ROUGE Score and BERTScore on 104 questions from the LiveQA test set. Additionally, we establish criteria for physician-evaluation based on four dimensions: Factuality, Completeness, Readability and Relevancy. ChatGPT-3.5 is used for physician evaluation with 20 questions on the LiveQA test set. Multiple resident physicians conducted blind reviews to evaluate the generated content, and the results indicate that this framework effectively enhances the factuality, completeness, and relevance of generated content. Our research demonstrates the effectiveness of using UMLS-augmented LLMs and highlights the potential application value of LLMs in in medical question-answering.Comment: 12 pages, 3 figure

    Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

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    Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22−20 μm) and micro-eukaryotes (20−200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance

    Low-level prenatal lead exposure and infant sensory function

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    Abstract Background Lead is a pervasive neurotoxicant that has been associated with poorer cognitive, behavioral, and motor outcomes in children. The effects of lead on sensory function have not been well characterized. The aim of this study was to assess the effects of prenatal lead exposure on infant sensory function, as measured by auditory brainstem response (ABR) and grating visual acuity (VA). Methods Lead was measured in maternal blood in mid- and late-pregnancy (mean gestational age = 15.5 and 39.0 weeks, respectively) and umbilical cord blood in a cohort of full-term infants in rural northeastern China. ABR latencies (peaks I, III, V) were measured in newborns during unsedated sleep (n = 315). The ABR central-to-peripheral (C-P) ratio was calculated as the ratio between the III-V and I-III interpeak intervals. VA was measured in 6-week-olds using Teller Acuity Cards (n = 1019) and assigned as the narrowest grid the infant fixated on. Multivariate linear regression was used to evaluate relationships between tertiles of mid-pregnancy, late-pregnancy, or cord lead and newborn ABR or 6-week VA. Results Higher late-pregnancy lead levels were associated with higher ABR C-P ratios and lower VA. In covariate-adjusted analyses, mean C-P ratios were 4.6 and 3.2 % higher in infants whose mothers had lead > 3.8 μg/dL and lead = 2–3.8 μg/dL, respectively, than for infants whose mothers had lead  3.8 μg/dL and lead = 2–3.8 μg/dL, respectively, compared to lead < 2 μg/dL (p-trend =0.009). Conclusion Auditory and visual systems maturation appears delayed in infants with higher prenatal lead exposure during late-pregnancy, even at relatively low levels. Both systems start myelinating in late gestation and mature rapidly in infancy. Higher ABR C-P ratio and lower grating VA scores suggest effects of low-level lead exposure on sensory system myelination.http://deepblue.lib.umich.edu/bitstream/2027.42/136085/1/12940_2016_Article_148.pd

    Association of SLC11A1 Polymorphisms With Tuberculosis Susceptibility in the Chinese Han Population

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    Tuberculosis (TB) is an important health issue in the world. Although the relation of SLC11A1 polymorphisms with TB risk has been extensively studied, it has not been reported in the northwest Chinese Han population. Therefore, this study aimed to investigate the relationships between five polymorphisms in or near the SLC11A1 gene and susceptibility to TB. The Agena MassARRAY platform was conducted for genotyping from 510 TB patients and 508 healthy controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were analyzed through logistic regression adjustment age and gender to assess the relationships between polymorphisms and TB risk. Our results identified that rs7608307 was related to increased TB risk in males (CT vs. CC: OR = 1.69, 95%CI: 1.12–2.56, p = 0.013; CT-TT vs. CC: OR = 1.61, 95%CI: 1.08–2.41, p = 0.020) and age ≤41 group (CT vs. CC: OR = 1.66, 95%CI: 1.04–2.65, p = 0.035), respectively. The SNP rs13062 was associated with the TB risk both in males (p = 0.012) and age &gt;41 group (p = 0.021). In addition, we observed that the CC genotype of rs4674301 was correlated with increased TB risk in females (p = 0.043). Our results demonstrated the relationships between polymorphisms (rs7608307, rs4674301, and rs13062) in or near the SLC11A1 gene and age- and sex-specific TB risk in the northwest Chinese Han population

    Nearly a decade-long repeatable seasonal diversity patterns of bacterioplankton communities in the eutrophic Lake Donghu (Wuhan, China).

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    Uncovering which environmental factors govern community diversity patterns and how ecological processes drive community turnover are key questions related to understand the community assembly. However, the ecological mechanisms regulating long-term variations of bacterioplankton communities in lake ecosystems remain poorly understood. Here we present nearly a decade-long study of bacterioplankton communities from the eutrophic Lake Donghu (Wuhan, China) using 16S rRNA gene amplicon sequencing with MiSeq platform. We found strong repeatable seasonal diversity patterns in terms of both common (detected in more than 50% samples) and dominant (relative abundance &gt;1%) bacterial taxa turnover. Moreover, community composition tracked the seasonal temperature gradient, indicating that temperature is a key environmental factor controlling observed diversity patterns. Total phosphorus also contributed significantly to the seasonal shifts in bacterioplankton composition. However, any spatial pattern of bacterioplankton communities across the main lake areas within season was overwhelmed by their temporal variabilities. Phylogenetic analysis further indicated that 75%-82% of community turnover was governed by homogeneous selection due to consistent environmental conditions within seasons, suggesting that the microbial communities in Lake Donghu are mainly controlled by niche-based processes. Therefore, dominant niches available within seasons might be occupied by similar combinations of bacterial taxa with modest dispersal rates throughout different lake areas
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