Objective To study the clinical features,diagnosis and treatment of neonatal very early onset inflammatory bowel disease(VEO-IBD) to improve the diagnosis and treatment of the disease.Method From Jan 2013 to Dec 2015,five infants with VEO-IBD admitted to Peking University First Hospital were reviewed and analyzed.Their clinical data included general condition,clinical symptoms,laboratory tests,autoimmune antibodies (ANCA,dsDNA,ANA and ENA),colonoscopy,pathological results and therapeutic response.Interleukin-10 receptor A (IL-10RA) gene was examined in all patients.All the patients were followed up for more than 1 year.Result Three of the five patients had a family history.Persistent diarrhea was the most common presenting symptom.One of them received surgery because of intestinal necrosis and developed typical symptoms of IBD half a year later.Bloody stool or positive fecal occult blood test were found in all infants.Fever,anemia,oral ulcer,perianal lesions and malnutrition were common concomitant symptoms.Most of the patients had elevated WBC,CRP and ESR,and 4 of them had positive autoimmune antibodies.Colonoscopy showed multiple ulcers affecting the colon.Intestinal biopsies revealed acute and chronic inflammation.4 of patients were found to have cryptitis and crypt abscesses.Gene sequencing revealed IL-10RAgene mutation in all five patients,including 1 case with homozygous mutation and 4 heterozygous mutations.4 patients received steroid and mesalazine therapy and only 1 patient's symptoms were controlled.However,the colonoscopy result was still abnormal in this patient.4 patients had poor response to further infliximab and (or) thalidomide therapy.1 of them received surgery because of intestinal obstruction at 2-year-old.Conclusion Neonatal VEO-IBD was associated with IL-10RA gene mutation.The patients had severe symptoms and poor response to conventional medications.The effects of biological agents and thalidomide were still not sure.

As a renewable energy sources to replace conventional fossil fuels, biodiesel fuels have been becoming increasingly requirements to global fuels market. Biodiesel derived from oil crops cannot realistically satisfy even more fraction of the raw material existing costs and soil competitive demand for its growth. Microalgae appear to be the advantage of costs that is capable of higher photosynthetic efficiency, larger biomass, faster growth compared to those of oil crops. Lipid content of many microalgae is usually 80% of its dry weight. Genetic microalgae with high-oil productivity by genetic manipulations are capable of making microalgal biodiesel economically competitive with petrodiesel through large-scale production of genetic microalgal biomass. As demonstrated here, the use of biodiesel fuels in home and abroad are currently introduced, and the cost advantage of microalgae as the raw material is analyzed; And moreover, the progress of microalgal genetic engineering in regulation of lipid metabolism and the problems in the construct of genetic microalgae strains as well as approaches for making microalgal biodiesel appear to be an important source of renewable fuel that has the potential to completely displace fossil diesel are discussed in this review.
Bioelectric Energy Sources ; trends ; Biotechnology ; methods ; Eukaryota ; chemistry ; genetics ; metabolism ; Fatty Acids ; analysis ; Gasoline ; Lipids ; analysis

Objective: To investigate the correlation between Ground Glass Opacity (GGO) component proportion and quantitative classification of lepidic growth pattern in pathological stage Ⅰpulmonary adenocarcinoma. Methods: Pathological and HRCT data of 183 stage Ⅰ invasive adenocarcinoma patients from January 2005 to December 2012 were retrospectively reviewed. The proportion of GGO was calculated from diameter and volume.The correlation between GGO component proportion and lepidic growth pattern in pathological were analyzed by Spearman correlation. Results: Among 183 patients, the proportion of GGO component calculated by maximum diameter method and three-dimensional computerized quantification was 0.43±0.35 and 0.20±0.18, respectively. The percentage of lepidic growth pattern component using semi-quantitative analysis of pathological sections was 0.29±0.25.The proportion of GGO by diameter and three-dimensional computerized quantification was significantly correlated with the percentage of lepidic growth pattern component (r=0.599, P< 0.001; r=0.620, P<0.001). Conclusions There was a positive correlation between the content of lepidic growth pattern and the content of GGO in the small adenocarcinoma. Three-dimensional computerized quantification was a better method in preoperational evaluation.

Background Air pollution is a major public health concern. Air Quality Health Index (AQHI) is a very important air quality risk communication tool. However, AQHI is usually constructed by single-pollutant model, which has obvious disadvantages. Objective To construct an AQHI based on the joint effects of multiple air pollutants (J-AQHI), and to provide a scientific tool for health risk warning and risk communication of air pollution. Methods Data on non-accidental deaths in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces from January 1, 2013 to December 31, 2018 were obtained from the corresponding provincial disease surveillance points systems (DSPS), including date of death, age, gender, and cause of death. Daily meteorological (temperature and relative humidity) and air pollution data (SO₂, NO₂, CO, PM_2.5, PM₁₀, and maximum 8 h O₃ concentrations) at the same period were respectively derived from China Meteorological Data Sharing Service System and National Urban Air Quality Real-time Publishing Platform. Lasso regression was first applied to select air pollutants, then a time-stratified case-crossover design was applied. Each case was matched to 3 or 4 control days which were selected on the same days of the week in the same calendar month. Then a distributed lag nonlinear model (DLNM) was used to estimate the exposure-response relationship between selected air pollutants and mortality, which was used to construct the AQHI. Finally, AQHI was classified into four levels according to the air pollutant guidance limit values from World Health Organization Global Air Quality Guidelines (AQG 2021), and the excess risks (ERs) were calculated to compare the AQHI based on single-pollutant model and the J-AQHI based on multi-pollutant model. Results PM_2.5, NO₂, SO₂, and O₃ were selected by Lasso regression to establish DLNM model. The ERs for an interquartile range (IQR) increase and 95% confidence intervals (CI) for PM_2.5, NO₂, SO₂ and O₃ were 0.71% (0.34%–1.09%), 2.46% (1.78%–3.15%), 1.25% (0.9%–1.6%), and 0.27% (−0.11%–0.65%) respectively. The distribution of J-AQHI was right-skewed, and it was divided into four levels, with ranges of 0-1 for low risk, 2-3 for moderate risk, 4-5 for high health risk, and ≥6 for severe risk, and the corresponding proportions were 11.25%, 64.61%, 19.33%, and 4.81%, respectively. The ER (95%CI) of mortality risk increased by 3.61% (2.93–4.29) for each IQR increase of the multi-pollutant based J-AQHI , while it was 3.39% (2.68–4.11) for the single-pollutant based AQHI . Conclusion The J-AQHI generated by multi-pollutant model demonstrates the actual exposure health risk of air pollution in the population and provides new ideas for further improvement of AQHI calculation methods.