Ultrasound assessment of diaphragmatic dysfunction in non-critically ill patients: relevant indicators and update.

Diaphragm dysfunction (DD) can be classified as mild, resulting in diaphragmatic weakness, or severe, resulting in diaphragmatic paralysis. Various factors such as prolonged mechanical ventilation, surgical trauma, and inflammation can cause diaphragmatic injury, leading to negative outcomes for patients, including extended bed rest and increased risk of pulmonary complications. Therefore, it is crucial to protect and monitor diaphragmatic function. Impaired diaphragmatic function directly impacts ventilation, as the diaphragm is the primary muscle involved in inhalation. Even unilateral DD can cause ventilation abnormalities, which in turn lead to impaired gas exchange, this makes weaning from mechanical ventilation challenging and contributes to a higher incidence of ventilator-induced diaphragm dysfunction and prolonged ICU stays. However, there is insufficient research on DD in non-ICU patients, and DD can occur in all phases of the perioperative period. Furthermore, the current literature lacks standardized ultrasound indicators and diagnostic criteria for assessing diaphragmatic dysfunction. As a result, the full potential of diaphragmatic ultrasound parameters in quickly and accurately assessing diaphragmatic function and guiding diagnostic and therapeutic decisions has not been realized.

[Risk Assessment of Antibiotics in Agricultural Environment].

Antibiotics are widely used in animal husbandry, planting, and aquaculture in agricultural industries. A large amount of the parent antibiotics used are released into the environment through discharge via feces and urine, posing potential risks to human health and ecosystems. It is thus very important to understand how antibiotics in the agricultural environment threaten the ecological environment and human health. Accordingly, risk assessment of antibiotics in the environment has become the research focus in recent years. The aim of this study was to review the risk assessment methods of antibiotics. The results showed that the ecological environment risk has mainly been assessed by the risk quotient (RQ). Predicted no-impact concentrations (PNECs) are an important indicator for ecological environment risk assessment, but a definite value is still controversial. The hazard quotient (HQ) is generally used to assess health risks. At present, it is necessary to clarify the selection of antibiotic exposure pathways and toxicological thresholds. However, neither of these two methods have currently considered either mixed pollution or the risk of antibiotic metabolites. Further analysis indicated that the ecological risks of antibiotics in the water environment and feces/manure/soil environment were widespread, which had an impact on both the soil and water environment. The types of antibiotics with high risk were different for various cultivated types. The factors including test species, testing conditions, calculation methods, and soil types all affected the detection of PNECs. Human health risk caused by dietary intake of antibiotics was minimal, but it cannot be ignored given the seafood consumption in coastal areas. Moreover, quinolones have both high ecological and human health risks in the agricultural environment. Based on the amount of antibiotics in agriculture and the residual concentration or toxicity of antibiotics in the related environment, this study proposed a priority-control list of antibiotics in the agricultural environment and summarized the main problems in the current antibiotic risk assessment. It will provide helpful support for the scientific optimization of antibiotic risk assessment and the effective control of antibiotics in agricultural environments.

A predictive model for patent ductus arteriosus seven days postpartum in preterm infants: an ultrasound-based assessment of ductus arteriosus intimal thickness within 24†h after birth.

Objectives: To develop a predictive model for patent ductus arteriosus (PDA) in preterm infants at seven days postpartum. The model employs ultrasound measurements of the ductus arteriosus (DA) intimal thickness (IT) obtained within 24 h after birth. Methods: One hundred and five preterm infants with gestational ages ranging from 27.0 to 36.7 weeks admitted within 24 h following birth were prospectively enrolled. Echocardiographic assessments were performed to measure DA IT within 24 h after birth, and DA status was evaluated through echocardiography on the seventh day postpartum. Potential predictors were considered, including traditional clinical risk factors, M-mode ultrasound parameters, lumen diameter of the DA (LD), and DA flow metrics. A final prediction model was formulated through bidirectional stepwise regression analysis and subsequently subjected to internal validation. The model's discriminative ability, calibration, and clinical applicability were also assessed. Results: The final predictive model included birth weight, application of mechanical ventilation, left ventricular end-diastolic diameter (LVEDd), LD, and the logarithm of IT (logIT). The receiver operating characteristic (ROC) curve for the model, predicated on logIT, exhibited excellent discriminative power with an area under the curve (AUC) of 0.985 (95% CI: 0.966-1.000), sensitivity of 1.000, and specificity of 0.909. Moreover, the model demonstrated robust calibration and goodness-of-fit (χ2 value = 0.560, p > 0.05), as well as strong reproducibility (accuracy: 0.935, Kappa: 0.773), as evidenced by 10-fold cross-validation. A decision curve analysis confirmed the model's broad clinical utility. Conclusions: Our study successfully establishes a predictive model for PDA in preterm infants at seven days postpartum, leveraging the measurement of DA IT. This model enables identifying, within the first 24 h of life, infants who are likely to benefit from timely DA closure, thereby informing treatment decisions.

Polycyclic aromatic hydrocarbons and their halogenated derivatives in soil from Yellow River Delta: Distribution, source apportionment, and risk assessment.

The distribution of polycyclic aromatic hydrocarbons (PAHs) and halogenated PAHs (HPAHs) in surface soils from the petroleum industrial area of the Yellow River Delta (YRD) in China were investigated. The total concentrations of 16 PAHs ranged from 19.6 to 1560 ng/g, while 22 HPAHs ranged from 2.44 to 14.9 ng/g. Moreover, a high degree of spatial distribution heterogeneity was observed for both PAHs and HPAHs, which is likely attributed to the distinct industrial activities in studied area. The combustion of biomass and petroleum were identified as primary sources of soil PAHs and HPAHs in the YRD. Furthermore, benzo[b]fluoranthene, benzo[k]fluoranthene, and benzo[g,h,i]perylene exhibited high ecological risks (with risk quotients of 1.47, 1.44, and 1.02, respectively) in specific sites within the YRD. Considering the high toxicity of HPAHs and their potential joint environmental effects with PAHs, continuous attention should be directed towards the environmental risks associated with both PAHs and HPAHs.

Digital health literacy and associated factors among internet users from China: a cross-sectional study.

BACKGROUND: As the internet develops and 5G technology becomes increasingly prominent, the internet has become a major source of health-related information. Increasingly, people use the internet to find health-related information, and digital health literacy is now a set of essential capabilities to improve their health in the digital era. However, little is known about the factors that influencing digital health literacy. This study aimed to assess digital health literacy scores and identify its influencing factors among internet users in China. Additionally, this study explored the participant's actual skills using an additional set of performance-based items from the Digital Health Literacy Instrument (DHLI). METHODS: An online cross-sectional study was conducted in August 2022. Participants aged ≥18 years were recruited to complete the survey. Data were collected using the Chinese revised version of the DHLI, the self-reported internet use questionnaire, and the sociodemographic questionnaire. We conducted multivariate linear regression analyses to explore the relationships among the sociodemographic variables, behavior of internet use, and the digital health literacy scores. RESULTS: In total, 702 participants completed the survey. The mean DHLI score was 2.69 ± 0.61. Multivariate linear regression analyses showed that the age groups 35-49 (ß = - 0.08, P = 0.033), 50-64 (ß = - 0.161, P < 0.001), and ≥ 65 (ß = - 0.138, P < 0.001) were negatively associated with DHL scores. However, education level, including bachelor's or associate degree (ß = 0.255, P = 0.002) and master's degree and above (ß = 0.256, P < 0.001), frequency of health-related Internet usage (ß = 0.192, P < 0.001), the number of digital devices used (ß = 0.129, P = 0.001), and OHISB (ß = 0.103, P = 0.006) showed a positive relationship with DHL scores. CONCLUSIONS: The study findings demonstrate that age, educational levels, number of technological devices used, and greater use of the web for health information were independently associated with DHL scores. Healthcare providers should consider providing training programs tailored to specific sociodemographic factors to improve the ability that find and use accurate information online to meet digital health services, which contributes to enhance their self-management and reduce health disparities.

[Characterization of Metal Elements in Atmospheric PM2.5 and Health Risk Assessment in Heze in Winter from 2017 to 2018].

Atmospheric PM2.5 samples were collected in Heze, Shandong Province, from a total of three sampling sites at Heze College, Huarun Pharmacy, and a wastewater treatment plant between October 15, 2017 and January 31, 2018, to determine the concentrations of 21 metal elements in PM2.5 using inductively coupled plasma mass spectrometry (ICP-MS). The degree of elemental enrichment was also discussed, the health risks and potential heavy metal ecological risks were assessed. The results showed that ρ (PM2.5) ranged from 26.7 to 284.1 µg·m-3 at the three sampling sites during the sampling period, and the concentration values did not differ significantly, all of which were at high pollution levels. The highest concentrations of K were found in the three sampling sites, accounting for 31.03%, 39.47%, and 38.43% of the total, respectively, mainly due to the high contribution of biomass burning in autumn and winter in Heze, a large agricultural city. The highest concentrations of Zn, 89.70, 84.21, and 67.68 ng·m-3, were found in the trace elements at the three sampling sites, respectively. The enrichment factor results showed that the enrichment factor values of Zn, Pb, Sn, Sb, Cd, and Se were higher than 100, among which the enrichment factors of Cd and Se were higher than 2 000 and 4 000, respectively, which were significantly influenced by anthropogenic activities and might have been related to industrial production, metal smelting, road sources, and coal combustion emissions. The health risk results showed that there was some potential non-carcinogenic risk (HQ>0.1 for children and adults) for As and a combined potential non-carcinogenic risk (HI>0.1) and some potential carcinogenic risk (CRT>1×10-6) for both children and adults at the three sampling sites. There was a more significant carcinogenic risk (CRT>1×10-4) for adults at the wastewater treatment plant, and the slightly higher carcinogenic risk for adults than that for children may have been related to the longer outdoor activity and higher PM2.5 exposure for adults. The elements with the highest potential ecological risk values were Cd, As, and Pb, with Cd exhibiting a very high potential ecological risk that should be taken seriously. All three sampling sites showed a very high combined potential ecological risk, with the intensity spatially expressed as Heze College>Huarun Pharmacy>wastewater treatment plant.

Construction of an instrument to enable the assessment of the risk of falls in older outpatients: A quantitative methodological study.

OBJECTIVES: To develop an instrument to facilitate the risk assessment of falls in older outpatients. DESIGN: A quantitative methodological study using the cross-sectional data. METHODS: This study enrolled 1988 older participants who underwent comprehensive geriatric assessment (CGA) in an outpatient clinic from May 2020 to November 2022. The history of any falls (≥1 falls in a year) and recurrent falls (≥2 falls in a year) were investigated. Potential risk factors of falls were selected by stepwise logistic regression, and a screening tool was constructed based on nomogram. The tool performance was compared with two reference tools (Fried Frailty Phenotype; CGA with 10 items, CGA-10) by using receiver operating curves, sensitivity (Sen), specificity (Spe), and area under the curve (AUC). RESULTS: Age, unintentional weight loss, depression measured by the Patient Health Questionnaire-2, muscle strength measured by the five times sit-to-stand test, and stand balance measured by semi- and full-tandem standing were the most important risk factors for falls. A fall risk screening tool was constructed with the six measurements (FRST-6). FRST-6 showed the best AUC (Sen, Spe) of 0.75 (Sen = 0.72, Spe = 0.69) for recurrent falls and 0.65 (Sen = 0.74, Spe = 0.48) for any falls. FRST-6 was comparable to CGA-10 and outperformed FFP in performance. CONCLUSIONS: Age, depression, weight loss, gait, and balance were important risk factors of falls. The FRST-6 tool based on these factors showed acceptable performance in risk stratification. IMPACT: Performing a multifactorial assessment in primary care clinics is urgent for falls prevention. The FRST-6 provides a simple and practical way for falls risk screening. With this tool, healthcare professionals can efficiently identify patients at risk of falling and make appropriate recommendations in resource-limited settings. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution was received, due to our study design.

A low-cost, low-input method establishment for m6A MeRIP-seq.

N6-methyladenosine (m6A) is a highly prevalent modification found in mammal mRNA molecules that plays a crucial role in the regulation of cellular function. m6A RNA immunoprecipitation sequencing (MeRIP-seq) has been frequently used in transcriptomics research to identify the location of m6A. MABE572 (Millipore) is the most widely utilized and efficient anti-m6A antibody for MeRIP-seq. However, due to the high dose and price of this antibody, which has also been taken off the market, we discovered that CST's anti-m6A antibody can be used instead of MABE572 to map the m6A transcriptome. In the present study, we performed different concentrations of the CST anti-m6A antibodies with the corresponding initiation RNA of HEK293T cells, 2.5 µg antibody with 1 µg total RNA, 1.25 µg antibody with 0.5 µg total RNA, and 1.25 µg antibody with 0.1 µg total RNA. By comparing the m6A peak calling, enriched motifs, alternative splicing events, and nuclear transcripts modified by m6A between the CST and Millipore libraries, it was found that the CST library presented similar data to Millipore, even at incredibly low doses. The volume and cost of antibodies are significantly reduced by this refined MeRIP-seq using CST antibody, making it convenient to map future large-scale sample m6A methylation.

[Meteorological Impact Assessment of PM2.5 and O3 Complex Pollution in Key Regions of China Based on Meteorological Conditions Index].

Meteorological conditions play a key role in the occurrence and evolution of atmospheric complex pollution. Considering the different pollution formation mechanisms of PM2.5 and O3, statistical calculation and in-depth learning methods were used to construct the PM2.5 and O3 meteorological condition indexes based on long-term pollution meteorological observation data. A research method was developed to study the meteorological characteristics and impact contribution of atmospheric complex pollution by using the meteorological condition index, and quantitative analysis of the distribution and variation of pollution excluding the influence of regional meteorological differences was also conducted. The results showed that in the summer of 2021, the pollution meteorological conditions in the key regions in central and eastern China were generally worse in the north and better in the south(index:"2+26" cities>the border area of Jiangsu, Anhui, Shandong, and Henan>the Yangtze River Delta) and the worst in June and the best in July. The "double high" pollution began to appear when the PM2.5 meteorological condition index>30 and O3 meteorological condition index>100; meanwhile, the unfavorable meteorological conditions for O3 also promoted the increase in PM2.5 concentration, resulting in the frequency of "double high" increases with the increase in O3 meteorological condition index. Compared with that during the same period last year, ρ(PM2.5) of each region decreased by 3.9 µg·m-3, 3.3 µg·m-3, and 1.4 µg·m-3 due to the contribution of the improvement in the pollution meteorological conditions, which is nearly 58.5% on average of the total decrease in PM2.5 concentration. However, the change in O3 pollution meteorological conditions was better in the north and worse in the south, and the overall deterioration in the Yangtze River Delta Region led to approximately 2.8 µg·m-3 growth for the O3 concentration. The PM2.5 and O3 concentrations after excluding the impact of meteorological differences showed different distribution characteristics from the air quality monitoring, in which the high concentrations of PM2.5 were distributed along the Bohai Sea, the inter-provincial border, and the south of the region, whereas the high concentrations of O3 were concentrated along the Taihang Mountains, around Mount Tai, and in parts of the Yangtze River Delta. The daily concentration variations in a single city during a specific pollution control period could be used as a basis for evaluating the effectiveness of local supervision and control, which will provide a reference for the dynamic supervision and daily scheduling of local control management.

[Pollution Characteristics and Ecological Risk Assessment of Typical Antibiotics in Environmental Media in China].

To investigate the environmental pollution status of antibiotics in China on a national scale, a large number of the latest pollution data of antibiotics in water, sediment, and soil were collected, and ecological risks of antibiotics were evaluated using the risk quotients (RQs). The results showed that water, sediments, and soils in different parts of China were contaminated with antibiotics to varying degrees; antibiotics pollution of water bodies was relatively severe in the south of China but moderate in the west. The ecological risk assessment revealed that erythromycin, roxithromycin, tetracycline, colistin, sulfamethoxazole, and norfloxacin were high-risk pollutants in water, accounting for 20.9% of the total antibiotics, and were mainly distributed in Shandong, Hubei, Zhejiang, Sichuan, Guangdong, Hainan, Jiangsu, and Jiangxi provinces. Furthermore, norfloxacin was identified as the primary high-risk pollutant in river sediments, such as those of the Yellow River, Haihe River, Liaohe River, and Pearl River, accounting for 11.11% of all antibiotics. In contrast, tetracycline, tylosin, colistin, and norfloxacin were the main high-risk pollutants in aquaculture sediments, accounting for 72.5% of the total. In soil, tetracycline and colistin contents comprised a high ratio of the total amount (up to 28.6%); these were mainly distributed in Liaoning, Sichuan, Tianjin, and Shandong provinces. Relevant authorities should focus on the above-mentioned high-risk regions. This study provides sufficient scientific basis and data support for preventing and controlling antibiotic pollution in China.

The Application of Cold-Induced Liquid-Liquid Extraction for the Determination of 4-Methylimidazole in Tea and Associated Risk Assessment for Chinese Tea Consumers.

4-Methylimidazole (4-MEI), as a Maillard reaction product, often occurs in heat-processed food. Due to its widespread occurrence and strong carcinogenicity in food and beverages, 4-MEI has received attention from regulatory organizations and consumers. Some studies have reported the occurrence and exposure of 4-MEI in food, but few studies have involved traditional tea beverages, which is related to the limited analytical methods currently being influenced by complex tea matrices. For this issue, this study presents a simple, reliable, and highly sensitive analytical method for the determination of 4-MEI in tea using liquid chromatography-high resolution mass spectrometry. By means of this method, a total of 570 tea samples from typical tea-producing regions in China were monitored for contamination of 4-MEI. The results showed that the average 4-MEI level (136 µg/kg) in oolong tea was significantly higher than that in other types of tea samples. Based on contamination levels and tea consumption data in China, the daily intake doses (0.04-1.16 µg/day) of 4-MEI among tea consumers were obtained. As a result, the health risk of Chinese tea consumers consuming 4-MEI alone through tea consumption is relatively low, but the overall intake level of 4-MEI in other foods cannot be ignored.

The impacts of driving variables on energy-related carbon emissions reduction in the building sector based on an extended LMDI model: a case study in China.

As China's main contributor to energy-related carbon emissions, the building sector in Jiangsu Province generates around 13.58% of the national carbon emissions. However, the influential variables of the energy structure in Jiangsu Province have been little investigated during the past decade. With the increasing emphasis on China's investment in technological innovation and adjustment of its industrial structure, research and development (R&D) has become an inevitable area for carbon emissions reduction. Nevertheless, its role in carbon emissions has rarely been examined. In this research, based on the logarithmic mean Divisia index (LMDI) model, the variables affecting the fluctuation of carbon dioxide emissions in the building sector (CEBS) in Jiangsu Province during 2011-2019 were restructured by introducing technological factors related to the construction industry, including energy structure, energy intensity, R&D efficiency, R&D intensity, investment intensity, economic output, and population engaged in the construction industry. From the results, it can be inferred that (1) energy structure, energy intensity, R&D efficiency, and investment intensity operate as inhibitors in increasing CEBS, and investment intensity exerts a more prominent impact on suppressing the growth of CEBS; (2) R&D intensity, economic output, and population engaged have a promotional effect on the fluctuations of CEBS, among which the first factor most actively promoted the increase in carbon emissions, although its role was negligible for economic output and the population; and (3) R&D efficiency, R&D intensity, and investment intensity are the three most critical variables for influencing the CEBS, but they are volatile. The numerical fluctuation caused by the three factors might be correlated to national and local policy interventions. Finally, policy recommendations are put forward for strengthening the management and minimizing the CEBS in Jiangsu Province.

Relative bioavailability of selenium in rice using a rat model and its application to human health risk assessment.

Deficiencies of selenium (Se), a necessary microelement for humans, can be remedied by appropriately supplying Se-enriched rice. However, overconsumption of Se-enriched rice poses a potential risk. To accurately assess Se human health risks associated with Se-enriched rice consumption, we developed a rat in vivo model to systematically explore the relative bioavailability of Se (Se-RBA) from Se-enriched rice from a wide geographic range. Se concentrations were in the range of 0.06 ± 0.05 to 0.15 ± 0.15 mg kg-1, averaging 0.12 ± 0.11 mg kg-1, in 196 rice samples from 21 Chinese provinces, and selenomethionine (SeMet) was the dominant Se fraction (58.0-96.5%). The Se-RBA of Se-enriched rice calculated from urine ranged from 34.86% to 102.29%, averaging 62.27% (n = 12), and was positively correlated with the proportion of SeMet in rice (p < 0.05, R2 = 0.51). Furthermore, the Se intake calculated based on the Se-RBA indicated that the Se intake of consumers of Se-enriched rice was far less than the tolerable upper intake level. Thus, the limits established by law assume overestimates of the actual nutritional value of the Se content in Se-enriched rice, and it is important to consider Se bioavailability. The current study offers suggestions for future research and provides methods to reduce the uncertainty in estimating the health risks associated with Se intake from rice.

Effects of provisioning on the activity budget and foraging strategies of black-and-white snub-nosed monkeys (Rhinopithecus bieti) in the Baima Snow Mountain Nature Reserve, Yunnan, China.

Provisioning can significantly affect the ranging patterns, foraging strategies, and time budget of wild primates. In this study, we document for the first time, the effects of provisioning on the activity budget and foraging effort in an Asian colobine. Over 3-years, we used an instantaneous scanning method at 10-min intervals to collect data on the activity budget of a semiprovisioned breeding band (SPB) of black-and-white snub-nosed monkeys (Rhinopithecus bieti) (42-70 individuals) at Xiangguqing (Tacheng), Yunnan, China. We then compared the effects of provisioning in our study band with published data on a sympatric wild nonprovisioned breeding band (NPB) of R. bieti (ca. 360 monkeys) at the same field site. The SPB spent 25.6% of their daytime feeding, 17.1% traveling, 46.9% resting, and 10.3% socializing. In comparison, the NPB devoted more time to feeding (34.9%) and socializing (14.1%), less time to resting (31.3%), and was characterized by a greater foraging effort (1.74 versus 0.96, foraging effort = (feeding + traveling)/resting; see Methods). There was no difference between bands in the proportion of their activity budget devoted to traveling (15.7% vs. 17.1%). In addition, the SPB exhibited a more consistent activity budget and foraging effort across all seasons of the year compared to the NPB. These findings suggest that the distribution, availability, and productivity of naturally occurring feeding sites is a major determinant of the behavioral strategies and activity budget of R. bieti. Finally, a comparison of our results with data on six nonprovisioned R. bieti bands indicates that caution must be raised in meta-analyses or intraspecific comparisons of primate behavioral ecology that contain data generated from both provisioned and nonprovisioned groups.

Phytochemical Cue for the Fitness Costs of Herbicide-Resistant Weeds.

Despite increasing knowledge of the fitness costs of viability and fecundity involved in the herbicide-resistant weeds, relatively little is known about the linkage between herbicide resistance costs and phytochemical cues in weed species and biotypes. This study demonstrated relative fitness and phytochemical responses in six herbicide-resistant weeds and their susceptible counterparts. There were significant differences in the parameters of viability (growth and photosynthesis), fecundity fitness (flowering and seed biomass) and a ubiquitous phytochemical (-)-loliolide levels between herbicide-resistant weeds and their susceptible counterparts. Fitness costs occurred in herbicide-resistant Digitaria sanguinalis and Leptochloa chinensis but they were not observed in herbicide-resistant Alopecurus japonicas, Eleusine indica, Ammannia arenaria, and Echinochloa crus-galli. Correlation analysis indicated that the morphological characteristics of resistant and susceptible weeds were negatively correlated with (-)-loliolide concentration, but positively correlated with lipid peroxidation malondialdehyde and total phenol contents. Principal component analysis showed that the lower the (-)-loliolide concentration, the stronger the adaptability in E. crus-galli and E. indica. Therefore, not all herbicide-resistant weeds have fitness costs, but the findings showed several examples of resistance leading to improved fitness even in the absence of herbicides. In particular, (-)-loliolide may act as a phytochemical cue to explain the fitness cost of herbicide-resistant weeds by regulating vitality and fecundity.

Validation of Luminex immunological and competitive Luminex immunological assays for clinical immunogenicity assessment of a 14-valent recombinant human papillomavirus vaccine.

A novel virus-like particle (VLP)-based multivalent recombinant human papillomavirus (HPV) vaccine was developed and evaluated in human, including 14 HPV-type specific VLP antigens (HPV6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, and 59). The pseudovirus-based neutralizing assay (PBNA) method is widely used for immunogenicity assessment of HPV vaccine in clinical trials. However, as many as 14 antigen-specific antibody levels need be determined, PBNA is, for many reasons, challenging and time-consuming. In this study, we developed a Luminex immunological assay (LIA) and a competitive Luminex immunological assay (cLIA). These methods increase the throughput, reproducibility and precision, as well as reduce the complexity. All assay parameters showed good characteristics in the validation of both methods, benefiting from highly purified and structurally correct VLPs, high specific antibodies, standard VLP-microspheres and PE-mAbs conjugating process, adequate assay development and stable system. Validation data support the use of both methods for immunogenicity assessment in clinical trials. LIA showed higher sensitivity than cLIA, and due to limited epitopes of mAb, cLIA detected lower antibody responses, and therefore, fewer antibodies. This work not only supports clinical trials of 14-valent HPV vaccines more efficiently and reliably, but also provides a set of validation strategies and usable standards for general vaccine immunogenicity testing.

IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions.

MOTIVATION: A single gene may yield several isoforms with different functions through alternative splicing. Continuous efforts are devoted to developing machine-learning methods to predict isoform functions. However, existing methods do not consider the relevance of each feature to specific functions and ignore the noise caused by the irrelevant features. In this case, we hypothesize that constructing a feature selection framework to extract the function-relevant features might help improve the model accuracy in isoform function prediction. RESULTS: In this article, we present a feature selection-based approach named IsoFrog to predict isoform functions. First, IsoFrog adopts a reversible jump Markov Chain Monte Carlo (RJMCMC)-based feature selection framework to assess the feature importance to gene functions. Second, a sequential feature selection procedure is applied to select a subset of function-relevant features. This strategy screens the relevant features for the specific function while eliminating irrelevant ones, improving the effectiveness of the input features. Then, the selected features are input into our proposed method modified domain-invariant partial least squares, which prioritizes the most likely positive isoform for each positive MIG and utilizes diPLS for isoform function prediction. Tested on three datasets, our method achieves superior performance over six state-of-the-art methods, and the RJMCMC-based feature selection framework outperforms three classic feature selection methods. We expect this proposed methodology will promote the identification of isoform functions and further inspire the development of new methods. AVAILABILITY AND IMPLEMENTATION: IsoFrog is freely available at https://github.com/genemine/IsoFrog.

Utilization of lipidic food waste as low-cost nutrients for enhancing the potentiality of biofuel production from engineered diatom under temperature variations.

The scarcity of natural fossil fuels presents a promising opportunity for the development of renewable microalgae-based biofuels. However, the current microalgae cultivation is unable to effectively address the high costs of the production of biofuels. To tackle this challenge, this study focused on recruiting engineered Phaeodactylum tricornutum (FabG-OE) to enhance biomass accumulation and lipid production by employing food waste hydrolysate under temperature variations. The biomass and lipid accumulations of FabG-OE were improved effectively in mixed culture medium and food waste hydrolysate at a volume ratio (v/v) of 80:20 at 30 °C. It was found that oxidative stress might contribute to the overexpression of lipogenic genes, thereby leading to lipogenesis at 30 °C. Upscaling cultivation of FabG-OE at 30 °C using a semi-continuous strategy and batch strategy was conducted to achieve 0.73 and 0.77 g/L/d of biomass containing 0.35 and 0.38 g/L/d of lipid, respectively. In summary, these findings provide valuable insights for advancing microalgae-based biofuel production.

The impact of insurance status on in-hospital mortality in patients with hyperglycaemic crisis: A propensity score matching analysis.

AIM: This study was designed to determine the associations between insurance status and clinical outcomes among patients with hyperglycaemic crisis. METHODS: Overall, 1668 patients with hyperglycaemic crisis were recruited from the Chongqing Medical University Medical Data Science Academy's big data platform. In-hospital mortality, length of stay and complications (i.e., hypoglycaemia, hypokalemia, pulmonary infection, multiple systemic organ failure, acute kidney injury and deep venous thrombosis) were assessed. Propensity score matching analysis was used to reduce the confounding bias, and univariate and multivariate logistic regression were used to estimate the effect of insurance status on mortality in patients with hyperglycaemic crisis. RESULTS: After matching one uninsured patient to two insured patients with a calliper of 0.02, the uninsured group suffered a higher burden of in-hospital mortality than the insured group (16.9% vs. 9.8%); the insured status (odds ratio = 0.216, 95% confidence interval = 0.079-0.587) was a potential protect factor for in-hospital mortality of patients with hyperglycaemic crisis in the multivariate logistic regression analysis. CONCLUSIONS: Insurance status is associated with the outcomes of hospitalisation for hyperglycaemic crisis; uninsured patients with hyperglycaemic crisis face a higher risk of mortality in China.

The VLPFC-Engaged Voluntary Emotion Regulation: Combined TMS-fMRI Evidence for the Neural Circuit of Cognitive Reappraisal.

A clear understanding of the neural circuit underlying emotion regulation (ER) is important for both basic and translational research. However, a lack of evidence based on combined neuroimaging and neuromodulation techniques calls into question (1) whether the change of prefrontal-subcortical activity intrinsically and causally contributes to the ER effect; and (2) whether the prefrontal control system directly modulates the subcortical affective system. Accordingly, we combined fMRI recordings with transcranial magnetic stimulation (TMS) to map the causal connections between the PFC and subcortical affective structures (amygdala and insula). A total of 117 human adult participants (57 males and 60 females) were included in the study. The results revealed that TMS-induced ventrolateral PFC (VLPFC) facilitation led to enhanced activity in the VLPFC and ventromedial PFC (VMPFC) as well as attenuated activity in the amygdala and insula during reappraisal but not during nonreappraisal (i.e., baseline). Moreover, the activated VLPFC intensified the prefrontal-subcortical couplings via the VMPFC during reappraisal only. This study provides combined TMS-fMRI evidence that downregulating negative emotion involves the prefrontal control system suppressing the subcortical affective system, with the VMPFC serving as a crucial hub within the VLPFC-subcortical network, suggesting an indirect pathway model of the ER circuit. Our findings outline potential protocols for improving ER ability by intensifying the VLPFC-VMPFC coupling in patients with mood and anxiety disorders.SIGNIFICANCE STATEMENT Using fMRI to examine the TMS effect, we uncovered that the opposite neural changes in prefrontal (enhanced) and subcortical (attenuated) regions are not a byproduct of emotion regulation (ER); instead, this prefrontal-subcortical activity per se causally contributes to the ER effect. Furthermore, using TMS to amplify the neural changes within the ER circuit, the "bridge" role of the VMPFC is highlighted under the reappraisal versus nonreappraisal contrast. This "perturb-and-measure" approach overcomes the correlational nature of fMRI data, helping us to identify brain regions that causally support reappraisal (the VLPFC and VMPFC) and those that are modulated by reappraisal (the amygdala and insula). The uncovered ER circuit is important for understanding the neural systems underlying reappraisal and valuable for translational research.