@article{LiuFengGuetal.2019, author = {Liu, Junzhong and Feng, Lili and Gu, Xueting and Deng, Xian and Qiu, Qi and Li, Qun and Zhang, Yingying and Wang, Muyang and Deng, Yiwen and Wang, Ertao and He, Yuke and B{\"a}urle, Isabel and Li, Jianming and Cao, Xiaofeng and He, Zuhua}, title = {An H3K27me3 demethylase-HSFA2 regulatory loop orchestrates transgenerational thermomemory in Arabidopsis}, series = {Cell research}, volume = {29}, journal = {Cell research}, number = {5}, publisher = {Nature Publ. Group}, address = {London}, issn = {1001-0602}, doi = {10.1038/s41422-019-0145-8}, pages = {379 -- 390}, year = {2019}, abstract = {Global warming has profound effects on plant growth and fitness. Plants have evolved sophisticated epigenetic machinery to respond quickly to heat, and exhibit transgenerational memory of the heat-induced release of post-transcriptional gene silencing (PTGS). However, how thermomemory is transmitted to progeny and the physiological relevance are elusive. Here we show that heat-induced HEAT SHOCK TRANSCRIPTION FACTOR A2 (HSFA2) directly activates the H3K27me3 demethylase RELATIVE OF EARLY FLOWERING 6 (REF6), which in turn derepresses HSFA2. REF6 and HSFA2 establish a heritable feedback loop, and activate an E3 ubiquitin ligase, SUPPRESSOR OF GENE SILENCING 3 (SGS3)-INTERACTING PROTEIN 1 (SGIP1). SGIP1-mediated SGS3 degradation leads to inhibited biosynthesis of trans-acting siRNA (tasiRNA). The REF6-HSFA2 loop and reduced tasiRNA converge to release HEAT-INDUCED TAS1 TARGET 5 (HTT5), which drives early flowering but attenuates immunity. Thus, heat induces transmitted phenotypes via a coordinated epigenetic network involving histone demethylases, transcription factors, and tasiRNAs, ensuring reproductive success and transgenerational stress adaptation.}, language = {en} } @misc{YangDarkoHuangetal.2017, author = {Yang, Xiaoping and Darko, Kwame Oteng and Huang, Yanjun and He, Caimei and Yang, Huansheng and He, Shanping and Li, Jianzhong and Li, Jian and Hocher, Berthold and Yin, Yulong}, title = {Resistant starch regulates gut microbiota}, series = {Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry and pharmacology}, volume = {42}, journal = {Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry and pharmacology}, number = {1}, publisher = {Karger}, address = {Basel}, issn = {1015-8987}, doi = {10.1159/000477386}, pages = {306 -- 318}, year = {2017}, abstract = {Starch is one of the most popular nutritional sources for both human and animals. Due to the variation of its nutritional traits and biochemical specificities, starch has been classified into rapidly digestible, slowly digestible and resistant starch. Resistant starch has its own unique chemical structure, and various forms of resistant starch are commercially available. It has been found being a multiple-functional regulator for treating metabolic dysfunction. Different functions of resistant starch such as modulation of the gut microbiota, gut peptides, circulating growth factors, circulating inflammatory mediators have been characterized by animal studies and clinical trials. In this mini-review, recent remarkable progress in resistant starch on gut microbiota, particularly the effect of structure, biochemistry and cell signaling on nutrition has been summarized, with highlights on its regulatory effect on gut microbiota.}, language = {en} } @article{HeWangHeetal.2022, author = {He, Yushuang and Wang, Feipeng and He, Li and Wang, Qiang and Li, Jian and Qian, Yihua and Gerhard, Reimund and Plath, Ronald}, title = {An insight Into the role of Nano-Alumina on DC Flashover-Resistance and surface charge variation of Epoxy Nanocomposites}, series = {IEEE transactions on dielectrics and electrical insulation}, volume = {29}, journal = {IEEE transactions on dielectrics and electrical insulation}, number = {3}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Piscataway}, issn = {1070-9878}, doi = {10.1109/TDEI.2022.3173510}, pages = {1022 -- 1029}, year = {2022}, abstract = {The addition of nano-Al2O3 has been shown to enhance the breakdown voltage of epoxy resin, but its flashover results appeared with disputation. This work concentrates on the surface charge variation and dc flashover performance of epoxy resin with nano-Al2O3 doping. The dispersion of nano-Al2O3 in epoxy is characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The dc flashover voltages of samples under either positive or negative polarity are measured with a finger-electrode system, and the surface charge variations before and after flashovers were identified from the surface potential mapping. The results evidence that nano-Al2O3 would lead to a 16.9\% voltage drop for the negative flashovers and a 6.8\% drop for positive cases. It is found that one-time flashover clears most of the accumulated surface charges, regardless of positive or negative. As a result, the ground electrode is neighbored by an equipotential zone enclosed with low-density heterocharges. The equipotential zone tends to be broadened after 20 flashovers. The nano-Al2O3 is noticed as beneficial to downsize the equipotential zone due to its capability on charge migration, which is reasonable to maintain flashover voltage at a high level after multiple flashovers. Hence, nano-Al2O3 plays a significant role in improving epoxy with high resistance to multiple flashovers.}, language = {en} } @article{WuttkeLiLietal.2019, author = {Wuttke, Matthias and Li, Yong and Li, Man and Sieber, Karsten B. and Feitosa, Mary F. and Gorski, Mathias and Tin, Adrienne and Wang, Lihua and Chu, Audrey Y. and Hoppmann, Anselm and Kirsten, Holger and Giri, Ayush and Chai, Jin-Fang and Sveinbjornsson, Gardar and Tayo, Bamidele O. and Nutile, Teresa and Fuchsberger, Christian and Marten, Jonathan and Cocca, Massimiliano and Ghasemi, Sahar and Xu, Yizhe and Horn, Katrin and Noce, Damia and Van der Most, Peter J. and Sedaghat, Sanaz and Yu, Zhi and Akiyama, Masato and Afaq, Saima and Ahluwalia, Tarunveer Singh and Almgren, Peter and Amin, Najaf and Arnlov, Johan and Bakker, Stephan J. L. and Bansal, Nisha and Baptista, Daniela and Bergmann, Sven and Biggs, Mary L. and Biino, Ginevra and Boehnke, Michael and Boerwinkle, Eric and Boissel, Mathilde and B{\"o}ttinger, Erwin and Boutin, Thibaud S. and Brenner, Hermann and Brumat, Marco and Burkhardt, Ralph and Butterworth, Adam S. and Campana, Eric and Campbell, Archie and Campbell, Harry and Canouil, Mickael and Carroll, Robert J. and Catamo, Eulalia and Chambers, John C. and Chee, Miao-Ling and Chee, Miao-Li and Chen, Xu and Cheng, Ching-Yu and Cheng, Yurong and Christensen, Kaare and Cifkova, Renata and Ciullo, Marina and Concas, Maria Pina and Cook, James P. and Coresh, Josef and Corre, Tanguy and Sala, Cinzia Felicita and Cusi, Daniele and Danesh, John and Daw, E. Warwick and De Borst, Martin H. and De Grandi, Alessandro and De Mutsert, Renee and De Vries, Aiko P. J. and Degenhardt, Frauke and Delgado, Graciela and Demirkan, Ayse and Di Angelantonio, Emanuele and Dittrich, Katalin and Divers, Jasmin and Dorajoo, Rajkumar and Eckardt, Kai-Uwe and Ehret, Georg and Elliott, Paul and Endlich, Karlhans and Evans, Michele K. and Felix, Janine F. and Foo, Valencia Hui Xian and Franco, Oscar H. and Franke, Andre and Freedman, Barry I. and Freitag-Wolf, Sandra and Friedlander, Yechiel and Froguel, Philippe and Gansevoort, Ron T. and Gao, He and Gasparini, Paolo and Gaziano, J. Michael and Giedraitis, Vilmantas and Gieger, Christian and Girotto, Giorgia and Giulianini, Franco and Gogele, Martin and Gordon, Scott D. and Gudbjartsson, Daniel F. and Gudnason, Vilmundur and Haller, Toomas and Hamet, Pavel and Harris, Tamara B. and Hartman, Catharina A. and Hayward, Caroline and Hellwege, Jacklyn N. and Heng, Chew-Kiat and Hicks, Andrew A. and Hofer, Edith and Huang, Wei and Hutri-Kahonen, Nina and Hwang, Shih-Jen and Ikram, M. Arfan and Indridason, Olafur S. and Ingelsson, Erik and Ising, Marcus and Jaddoe, Vincent W. V. and Jakobsdottir, Johanna and Jonas, Jost B. and Joshi, Peter K. and Josyula, Navya Shilpa and Jung, Bettina and Kahonen, Mika and Kamatani, Yoichiro and Kammerer, Candace M. and Kanai, Masahiro and Kastarinen, Mika and Kerr, Shona M. and Khor, Chiea-Chuen and Kiess, Wieland and Kleber, Marcus E. and Koenig, Wolfgang and Kooner, Jaspal S. and Korner, Antje and Kovacs, Peter and Kraja, Aldi T. and Krajcoviechova, Alena and Kramer, Holly and Kramer, Bernhard K. and Kronenberg, Florian and Kubo, Michiaki and Kuhnel, Brigitte and Kuokkanen, Mikko and Kuusisto, Johanna and La Bianca, Martina and Laakso, Markku and Lange, Leslie A. and Langefeld, Carl D. and Lee, Jeannette Jen-Mai and Lehne, Benjamin and Lehtimaki, Terho and Lieb, Wolfgang and Lim, Su-Chi and Lind, Lars and Lindgren, Cecilia M. and Liu, Jun and Liu, Jianjun and Loeffler, Markus and Loos, Ruth J. F. and Lucae, Susanne and Lukas, Mary Ann and Lyytikainen, Leo-Pekka and Magi, Reedik and Magnusson, Patrik K. E. and Mahajan, Anubha and Martin, Nicholas G. and Martins, Jade and Marz, Winfried and Mascalzoni, Deborah and Matsuda, Koichi and Meisinger, Christa and Meitinger, Thomas and Melander, Olle and Metspalu, Andres and Mikaelsdottir, Evgenia K. and Milaneschi, Yuri and Miliku, Kozeta and Mishra, Pashupati P. and Program, V. A. Million Veteran and Mohlke, Karen L. and Mononen, Nina and Montgomery, Grant W. and Mook-Kanamori, Dennis O. and Mychaleckyj, Josyf C. and Nadkarni, Girish N. and Nalls, Mike A. and Nauck, Matthias and Nikus, Kjell and Ning, Boting and Nolte, Ilja M. and Noordam, Raymond and Olafsson, Isleifur and Oldehinkel, Albertine J. and Orho-Melander, Marju and Ouwehand, Willem H. and Padmanabhan, Sandosh and Palmer, Nicholette D. and Palsson, Runolfur and Penninx, Brenda W. J. H. and Perls, Thomas and Perola, Markus and Pirastu, Mario and Pirastu, Nicola and Pistis, Giorgio and Podgornaia, Anna I. and Polasek, Ozren and Ponte, Belen and Porteous, David J. and Poulain, Tanja and Pramstaller, Peter P. and Preuss, Michael H. and Prins, Bram P. and Province, Michael A. and Rabelink, Ton J. and Raffield, Laura M. and Raitakari, Olli T. and Reilly, Dermot F. and Rettig, Rainer and Rheinberger, Myriam and Rice, Kenneth M. and Ridker, Paul M. and Rivadeneira, Fernando and Rizzi, Federica and Roberts, David J. and Robino, Antonietta and Rossing, Peter and Rudan, Igor and Rueedi, Rico and Ruggiero, Daniela and Ryan, Kathleen A. and Saba, Yasaman and Sabanayagam, Charumathi and Salomaa, Veikko and Salvi, Erika and Saum, Kai-Uwe and Schmidt, Helena and Schmidt, Reinhold and Ben Schottker, and Schulz, Christina-Alexandra and Schupf, Nicole and Shaffer, Christian M. and Shi, Yuan and Smith, Albert V. and Smith, Blair H. and Soranzo, Nicole and Spracklen, Cassandra N. and Strauch, Konstantin and Stringham, Heather M. and Stumvoll, Michael and Svensson, Per O. and Szymczak, Silke and Tai, E-Shyong and Tajuddin, Salman M. and Tan, Nicholas Y. Q. and Taylor, Kent D. and Teren, Andrej and Tham, Yih-Chung and Thiery, Joachim and Thio, Chris H. L. and Thomsen, Hauke and Thorleifsson, Gudmar and Toniolo, Daniela and Tonjes, Anke and Tremblay, Johanne and Tzoulaki, Ioanna and Uitterlinden, Andre G. and Vaccargiu, Simona and Van Dam, Rob M. and Van der Harst, Pim and Van Duijn, Cornelia M. and Edward, Digna R. Velez and Verweij, Niek and Vogelezang, Suzanne and Volker, Uwe and Vollenweider, Peter and Waeber, Gerard and Waldenberger, Melanie and Wallentin, Lars and Wang, Ya Xing and Wang, Chaolong and Waterworth, Dawn M. and Bin Wei, Wen and White, Harvey and Whitfield, John B. and Wild, Sarah H. and Wilson, James F. and Wojczynski, Mary K. and Wong, Charlene and Wong, Tien-Yin and Xu, Liang and Yang, Qiong and Yasuda, Masayuki and Yerges-Armstrong, Laura M. and Zhang, Weihua and Zonderman, Alan B. and Rotter, Jerome I. and Bochud, Murielle and Psaty, Bruce M. and Vitart, Veronique and Wilson, James G. and Dehghan, Abbas and Parsa, Afshin and Chasman, Daniel I. and Ho, Kevin and Morris, Andrew P. and Devuyst, Olivier and Akilesh, Shreeram and Pendergrass, Sarah A. and Sim, Xueling and Boger, Carsten A. and Okada, Yukinori and Edwards, Todd L. and Snieder, Harold and Stefansson, Kari and Hung, Adriana M. and Heid, Iris M. and Scholz, Markus and Teumer, Alexander and Kottgen, Anna and Pattaro, Cristian}, title = {A catalog of genetic loci associated with kidney function from analyses of a million individuals}, series = {Nature genetics}, volume = {51}, journal = {Nature genetics}, number = {6}, publisher = {Nature Publ. Group}, address = {New York}, organization = {Lifelines COHort Study}, issn = {1061-4036}, doi = {10.1038/s41588-019-0407-x}, pages = {957 -- +}, year = {2019}, abstract = {Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.}, language = {en} } @article{ChanChaudharySahaetal.2021, author = {Chan, Lili and Chaudhary, Kumardeep and Saha, Aparna and Chauhan, Kinsuk and Vaid, Akhil and Zhao, Shan and Paranjpe, Ishan and Somani, Sulaiman and Richter, Felix and Miotto, Riccardo and Lala, Anuradha and Kia, Arash and Timsina, Prem and Li, Li and Freeman, Robert and Chen, Rong and Narula, Jagat and Just, Allan C. and Horowitz, Carol and Fayad, Zahi and Cordon-Cardo, Carlos and Schadt, Eric and Levin, Matthew A. and Reich, David L. and Fuster, Valentin and Murphy, Barbara and He, John C. and Charney, Alexander W. and B{\"o}ttinger, Erwin and Glicksberg, Benjamin and Coca, Steven G. and Nadkarni, Girish N.}, title = {AKI in hospitalized patients with COVID-19}, series = {Journal of the American Society of Nephrology : JASN}, volume = {32}, journal = {Journal of the American Society of Nephrology : JASN}, number = {1}, publisher = {American Society of Nephrology}, address = {Washington}, organization = {Mt Sinai COVID Informatics Ct}, issn = {1046-6673}, doi = {10.1681/ASN.2020050615}, pages = {151 -- 160}, year = {2021}, abstract = {Background: Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associatedwith worse outcomes. However, AKI among hospitalized patients with COVID19 in the United States is not well described. Methods: This retrospective, observational study involved a review of data from electronic health records of patients aged >= 18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. Results: Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46\%) patients; 347 (19\%) of the patientswith AKI required dialysis. The proportionswith stages 1, 2, or 3 AKIwere 39\%, 19\%, and 42\%, respectively. A total of 976 (24\%) patients were admitted to intensive care, and 745 (76\%) experienced AKI. Of the 435 patients with AKI and urine studies, 84\% had proteinuria, 81\% had hematuria, and 60\% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50\% among patients with AKI versus 8\% among those without AKI (aOR, 9.2; 95\% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35\% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36\%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. Conclusions: AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30\% survived with recovery of kidney function by the time of discharge.}, language = {en} } @article{HeHuangLietal.2018, author = {He, Yongli and Huang, Jianping and Li, Dongdong and Xie, Yongkun and Zhang, Guolong and Qi, Yulei and Wang, Shanshan and Totz, Sonja Juliana}, title = {Comparison of the effect of land-sea thermal contrast on interdecadal variations in winter and summer blockings}, series = {Climate dynamics : observational, theoretical and computational research on the climate system}, volume = {51}, journal = {Climate dynamics : observational, theoretical and computational research on the climate system}, number = {4}, publisher = {Springer}, address = {New York}, issn = {0930-7575}, doi = {10.1007/s00382-017-3954-9}, pages = {1275 -- 1294}, year = {2018}, abstract = {The influence of winter and summer land-sea surface thermal contrast on blocking for 1948-2013 is investigated using observations and the coupled model intercomparison project outputs. The land-sea index (LSI) is defined to measure the changes of zonal asymmetric thermal forcing under global warming. The summer LSI shows a slower increasing trend than winter during this period. For the positive of summer LSI, the EP flux convergence induced by the land-sea thermal forcing in the high latitude becomes weaker than normal, which induces positive anomaly of zonal-mean westerly and double-jet structure. Based on the quasiresonance amplification mechanism, the narrow and reduced westerly tunnel between two jet centers provides a favor environment for more frequent blocking. Composite analysis demonstrates that summer blocking shows an increasing trend of event numbers and a decreasing trend of durations. The numbers of the short-lived blocking persisting for 5-9 days significantly increases and the numbers of the long-lived blocking persisting for longer than 10 days has a weak increase than that in negative phase of summer LSI. The increasing transient wave activities induced by summer LSI is responsible for the decreasing duration of blockings. The increasing blocking due to summer LSI can further strengthen the continent warming and increase the summer LSI, which forms a positive feedback. The opposite dynamical effect of LSI on summer and winter blocking are discussed and found that the LSI-blocking negative feedback partially reduces the influence of the above positive feedback and induce the weak summer warming rate.}, language = {en} } @article{HeLiuLuetal.2017, author = {He, Jing and Liu, Zhi-Wei and Lu, Yong-Ping and Li, Tao-Yuan and Liang, Xu-Jing and Arck, Petra and Huang, Si-Min and Hocher, Berthold and Chen, You-Peng}, title = {A systematic review and meta-analysis of influenza a virus infection during pregnancy associated with an increased risk for stillbirth and low birth weight}, series = {Kidney \& blood pressure research : official organ of the Gesellschaft f{\"u}r Nephrologie ; official organ of the Deutsche Liga zur Bek{\"a}mpfung des Hohen Blutdruckes e.V., Deutsche Hypertonie-Gesellschaft}, volume = {42}, journal = {Kidney \& blood pressure research : official organ of the Gesellschaft f{\"u}r Nephrologie ; official organ of the Deutsche Liga zur Bek{\"a}mpfung des Hohen Blutdruckes e.V., Deutsche Hypertonie-Gesellschaft}, number = {2}, publisher = {Karger}, address = {Basel}, issn = {1420-4096}, doi = {10.1159/000477221}, pages = {232 -- 243}, year = {2017}, abstract = {Background/Aims: Impaired pregnancy outcomes, such as low birth weight are associated with increased disease risk in later life, however little is known about the impact of common infectious diseases during pregnancy on birth weight. The study had two aims: a) to investigate risk factors of influenza virus infection during pregnancy, and b) to analyze the impact of influenza virus infection on pregnancy outcome, especially birth weight. Methods: Prospective and retrospective observational studies found in PubMed, MEDLINE, Embase, Google Scholar, and WangFang database were included in this meta analysis. Data of included studies was extracted and analyzed by the RevMan software. Results: Pregnant women with anemia (P=0.004, RR=1.46, 95\% CI: 1.13-1.88), obesity (P<0.00001, RR=1.35, 95\% CI: 1.25-1.46) and asthma (P<0.00001, RR=1.99, 95\% CI: 1.67-2.37) had higher rates of influenza virus infection. Regarding birth outcomes, influenza A virus infection did not affect the likelihood for cesarean section. Mothers with influenza had a higher rate of stillbirth (P=0.04, RR=2.36, 95\% CI: 1.05-5.31), and their offspring had low 5-minute APGR Scores (P=0.009, RR=1.39, 95\% CI: 1.08-1.79). Furthermore, the rate for birth weight < 2500g (P=0.04, RR=1.71, 95\% CI: 1.03-2.84) was increased. Conclusion: Results of this study showed that anemia, asthma and obesity during pregnancy are risk factors influenza A virus infection during pregnancy. Moreover, gestational influenza A infection impairs pregnancy outcomes and increases the risk for low birth weight, a known risk factor for later life disease susceptibility.}, language = {en} } @article{PattersonHeFolzetal.2020, author = {Patterson, Jenelle A. and He, Hai and Folz, Jacob S. and Li, Qiang and Wilson, Mark A. and Fiehn, Oliver and Bruner, Steven D. and Bar-Even, Arren and Hanson, Andrew D.}, title = {Thioproline formation as a driver of formaldehyde toxicity in Escherichia coli}, series = {Biochemical Journal}, volume = {477}, journal = {Biochemical Journal}, number = {9}, publisher = {Portland Press}, address = {London}, issn = {1470-8728}, doi = {10.1042/BCJ20200198}, pages = {1745 -- 1757}, year = {2020}, abstract = {Formaldehyde (HCHO) is a reactive carbonyl compound that formylates and cross-links proteins, DNA, and small molecules. It is of specific concern as a toxic intermediate in the design of engineered pathways involving methanol oxidation or formate reduction. The interest in engineering these pathways is not, however, matched by engineering-relevant information on precisely why HCHO is toxic or on what damage-control mechanisms cells deploy to manage HCHO toxicity. The only well-defined mechanism for managing HCHO toxicity is formaldehyde dehydrogenase-mediated oxidation to formate, which is counterproductive if HCHO is a desired pathway intermediate. We therefore sought alternative HCHO damage-control mechanisms via comparative genomic analysis. This analysis associated homologs of the Escherichia coli pepP gene with HCHO-related one-carbon metabolism. Furthermore, deleting pepP increased the sensitivity of E. coli to supplied HCHO but not other carbonyl compounds. PepP is a proline aminopeptidase that cleaves peptides of the general formula X-Pro-Y, yielding X + Pro-Y. HCHO is known to react spontaneously with cysteine to form the close proline analog thioproline (thiazolidine-4-carboxylate), which is incorporated into proteins and hence into proteolytic peptides. We therefore hypothesized that certain thioproline-containing peptides are toxic and that PepP cleaves these aberrant peptides. Supporting this hypothesis, PepP cleaved the model peptide Ala-thioproline-Ala as efficiently as Ala-Pro-Ala in vitro and in vivo, and deleting pepP increased sensitivity to supplied thioproline. Our data thus (i) provide biochemical genetic evidence that thioproline formation contributes substantially to HCHO toxicity and (ii) make PepP a candidate damage-control enzyme for engineered pathways having HCHO as an intermediate.}, language = {en} } @article{SunHuangMengetal.2012, author = {Sun, Sheng-Yun and Huang, Jin and Meng, Min-Jie and Lu, Jia-Hai and Hocher, Berthold and Liu, Kang-Li and Yang, Qin-He and Zhu, Xiao-Feng}, title = {Improvement of lipid profile and reduction of body weight by Shan He Jian Fei Granules in high fat diet-induced obese rats}, series = {Clinical laboratory : the peer reviewed journal for clinical laboratories and laboratories related to blood transfusion}, volume = {58}, journal = {Clinical laboratory : the peer reviewed journal for clinical laboratories and laboratories related to blood transfusion}, number = {1-2}, publisher = {Clin Lab Publ., Verl. Klinisches Labor}, address = {Heidelberg}, issn = {1433-6510}, pages = {81 -- 87}, year = {2012}, abstract = {Background: The goal was to study lipid profiles (TG, TC, LDL, HDL), effects on serum leptin, and fat tissue adiponectin, and resistin as well as body weight effects of Shan He Jian Fei Granules (SHJFG) in rats on a high fat diet. Methods: Rats were randomly divided into five groups: normal control group fed with normal fat diet, rats on high fat diet receiving low dosage, middle dosage, high dosage of Shan He Jian Fei Granules (SHJFG) as well as a high fat diet group receiving placebo. Rats were treated for 8 weeks. Body weight and naso-anal length of each rat were recorded and Lee's index was calculated. Serum TG, TC, LDL, HDL and leptin concentrations were analyzed. The gene expressions of adiponectin and resistin in adipose tissues were tested by RT-PCR. Results: Compared to the high-fat diet group, body weights, Lee's indexes, weight of fat tissues and serum TG, TC, LDL and leptin of SHJFG groups significantly decreased (p<0.05), whereas mRNA expressions of adiponectin and resistin of SHJFG groups significantly increased (p<0.05). Conclusions: SHJFG could significantly lower body weight and serum TG, TC, and LDL of obese rats. The effects of SHJFG in lowering leptin synthesis and raising mRNA expression of adiponectin and resistin in fat tissues may act as part of the mechanisms in lowering body weight of obese rats. Further studies are needed to demonstrate whether SHJFG may also reduce overall cardiovascular morbidity and mortality like other lipid lowering drugs.}, language = {en} } @article{LongdeMeloHeetal.2020, author = {Long, Xiang and de Melo, Gerard and He, Dongliang and Li, Fu and Chi, Zhizhen and Wen, Shilei and Gan, Chuang}, title = {Purely attention based local feature integration for video classification}, series = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {44}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, number = {4}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Los Alamitos}, issn = {0162-8828}, doi = {10.1109/TPAMI.2020.3029554}, pages = {2140 -- 2154}, year = {2020}, abstract = {Recently, substantial research effort has focused on how to apply CNNs or RNNs to better capture temporal patterns in videos, so as to improve the accuracy of video classification. In this paper, we investigate the potential of a purely attention based local feature integration. Accounting for the characteristics of such features in video classification, we first propose Basic Attention Clusters (BAC), which concatenates the output of multiple attention units applied in parallel, and introduce a shifting operation to capture more diverse signals. Experiments show that BAC can achieve excellent results on multiple datasets. However, BAC treats all feature channels as an indivisible whole, which is suboptimal for achieving a finer-grained local feature integration over the channel dimension. Additionally, it treats the entire local feature sequence as an unordered set, thus ignoring the sequential relationships. To improve over BAC, we further propose the channel pyramid attention schema by splitting features into sub-features at multiple scales for coarse-to-fine sub-feature interaction modeling, and propose the temporal pyramid attention schema by dividing the feature sequences into ordered sub-sequences of multiple lengths to account for the sequential order. Our final model pyramidxpyramid attention clusters (PPAC) combines both channel pyramid attention and temporal pyramid attention to focus on the most important sub-features, while also preserving the temporal information of the video. We demonstrate the effectiveness of PPAC on seven real-world video classification datasets. Our model achieves competitive results across all of these, showing that our proposed framework can consistently outperform the existing local feature integration methods across a range of different scenarios.}, language = {en} }