Description: Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers.

Description: Nature Genetics 45, 1431 (2013). doi:10.1038/ng.2811 Authors: Mingzhou Li, Shilin Tian, Long Jin, Guangyu Zhou, Ying Li, Yuan Zhang, Tao Wang, Carol K L Yeung, Lei Chen, Jideng Ma, Jinbo Zhang, Anan Jiang, Ji Li, Chaowei Zhou, Jie Zhang, Yingkai Liu, Xiaoqing Sun, Hongwei Zhao, Zexiong Niu, Pinger Lou, Lingjin Xian, Xiaoyong Shen, Shaoqing Liu, Shunhua Zhang, Mingwang Zhang, Li Zhu, Surong Shuai, Lin Bai, Guoqing Tang, Haifeng Liu, Yanzhi Jiang, Miaomiao Mai, Jian Xiao, Xun Wang, Qi Zhou, Zhiquan Wang, Paul Stothard, Ming Xue, Xiaolian Gao, Zonggang Luo, Yiren Gu, Hongmei Zhu, Xiaoxiang Hu, Yaofeng Zhao, Graham S Plastow, Jinyong Wang, Zhi Jiang, Kui Li, Ning Li, Xuewei Li & Ruiqiang Li

Description: We explore the predictability of tropical Atlantic sea surface temperature (SST) and the potential influence of climate model bias on SST predictions over the tropical Atlantic. Two statistical methods are used to examine the skill in forecasting tropical Atlantic SST anomalies (SSTAs): linear inverse modeling (LIM) and analogue forecast (AF). The statistical models are trained either with observations or with data from two control integrations of the Kiel Climate Model (KCM), which only differ with respect to the resolution of its atmospheric component. Observed SSTAs suggest that Tropical Atlantic climatic changes are potentially predictable at lead times of up to 6 months over large parts of the Tropical Atlantic. The SSTAs from the KCM version employing a high-resolution atmosphere model (KCM-HRES) is potentially predictable at a level comparable to that derived from the observations, whereas the SSTAs from the KCM version employing a low-resolution atmosphere model (KCM-LRES) is considerably less potentially predictable. We show that the enhanced potential predictability in the former KCM version can be very likely related to the improved representation of ENSO-like dynamics and its seasonality. We used the statistical models in true forecast mode, i.e. the prediction schemes were trained from data independent of the forecast period. Using observed SSTAs to train the LIM yields significant skill in forecasting observed SSTAs at lead times of up to 4 months across all calendar months, which is mostly restricted to the northern and equatorial western Tropical Atlantic. Similar patterns, but with lower skill, are found when the models’ SSTAs are used, in which LIM trained with the KCM-HRES generally yields higher skills than that from the KCM-LRES. Applying AF yields significant skills in predicting observed SSTAs over the same regions, but the forecast skills are considerably smaller. When the SSTAs together with either sea level pressure (SLP) anomalies or dynamic sea level (DSL) anomalies from the KCM are used to construct the statistical models, the prediction of observed equatorial Atlantic SSTAs can be improved, with significant skill enhancement at lead times of up to 4 months in limited regions. An optimal initial SSTA pattern is found, which results in the largest transient anomaly growth over the entire domain. Independent of external forces, this amplification is developed internally; meaning that the seasonal forecast might be more sensitive to initial conditions than currently thought.

Description: Phage genomic information and the nature of host-phage interactions are important for phage applications. In this study, Pseudomonas aeruginosa phage K5 is characterized as a linear double-stranded genomic DNA molecule of 93,754 bp with identical 1182-bp direct terminal repeats. Comparative genomic analysis reveals that phage K5 is highly homologous to the “PaP1-like” phages. Thirteen mutants resistant to phage K5 are screened in a transposon mutant library. The disrupted genetic loci are identified as gene Y880_RS05480 encoding a putative O-antigen polymerase Wzy and gene wapH encoding a glycosyltransferase. The mutants are confirmed by the complementation experiment. The production of biofilm and the profile of lipopolysaccharide (LPS) are further analyzed in the Y880_RS05480 mutant. Our data indicate that LPS is the receptor of phage K5.

Description: Background: The excessive accumulation of body fat is a major risk factor to develop a variety of metabolic diseases. To investigate the systematic association between the differences in gene expression profiling and adipose deposition, we used pig as a model, and measured the gene expression profiling of six variant adipose tissues in male and females from three pig breeds which display distinct fat level. Results: We identified various differential expressed genes among breeds, tissues and between sexes, and further used a clustering method to identify sets of functionally co-expression genes linked to different obesity-related phenotypes. Our results reveal that the subcutaneous adipose tissues mainly modulate metabolic indicators, nonetheless, the visceral adipose tissues as well as the intermuscular adipose tissue were mainly associated with the impaired inflammatory and immune response. Conclusions: The present study provided the evidence of gene expression profiling that the subcutaneous adipose tissues are mainly affected the metabolism process, whereas the visceral and intermuscular adipose tissues should been term as the metabolic risk factors of obesity.

Description: [1]  The North China Craton (NCC) formed in the Paleoproterozoic and suffered cratonic destruction in the Mesozoic. It consists of the Western NCC (WNCC), the Trans-North China Orogen (TNCO) and the Eastern NCC (ENCC). We investigated the upper mantle structures in the southern NCC by using receiver functions analysis. Polarization analysis was applied to increase the quality of receiver functions. The seismic images show significant stratified structures in the upper mantle in the south of the NCC. In the south of the WNCC, the lithosphere is ~280 km thick and contains a low-velocity zone at ~110–220 km depth. This low-velocity zone is interpreted as an intracratonic partial melting zone. In the south of the TNCO and ENCC, there is a low-velocity zone at ~60–200 km depth, which results from the partial melting during the Mesozoic cratonic destruction. Its upper boundary is interpreted as new Lithosphere-Asthenosphere Boundary at ~60–100 km depth. Below this low-velocity zone, there are the remains of Archean lithosphere (RAL). Blocks of RAL stagnate in the asthenosphere and reach depths over 300 km. A high-velocity slab extends from the uppermost mantle of the WNCC into the RAL with a dip-angle of ~20°. This slab is interpreted as the Paleoproterozoic slab, which indicates an eastward subduction between the WNCC and the ENCC. The WNCC is stable. The lithosphere in the south of the TNCO and ENCC suffered the Mesozoic cratonic destruction, while the destruction is relatively weaker than that in the north of the ENCC.

Description: Background: Skeletal muscle is one of the most important economic traits in agricultural animals, especially in pigs. In the modern pig industry, lean type pigs have undergone strong artificial selection for muscle growth, which has led to remarkable phenotypic variations compared with fatty type pigs, making these different breeds an ideal model for comparative studies. Results: Here, we present comprehensive gene expression profiling for the white (longissimus dorsi muscle) and the red (psoas major muscle) skeletal muscles among male and female fatty Rongchang, feral Tibetan and lean Landrace pigs, using a microarray approach. We identified differentially expressed genes that may be associated the phenotypic differences of porcine muscles among the breeds, between the sexes and the anatomical locations. We also used a clustering method to identify sets of functionally coexpressed genes that are linked to different muscle phenotypes. We showed that, compared with the white muscles, which primarily modulate metabolic processes, the red muscles show a tendency to be a risk factor for inflammation and immune-related disorders. Conclusions: This analysis presents breed-, sex- and anatomical location-specific gene expression profiles and further identified genes that may be associated with the phenotypic differences in porcine muscles among breeds, between the sexes and the anatomical locations.

Description: Background:Adult mammalian hearts have a limited ability to generate new cardiomyocytes. Proliferation of existing adult cardiomyocytes (ACMs) is a potential source of new cardiomyocytes. Understanding the fundamental biology of ACM proliferation could be of great clinical significance for treating myocardial infarction (MI). We aim to understand the process and regulation of ACM proliferation and its role in new cardiomyocyte formation of post-MI mouse hearts.Methods:β-Actin-green fluorescent protein transgenic mice and fate-mapping Myh6-MerCreMer-tdTomato/lacZ mice were used to trace the fate of ACMs. In a coculture system with neonatal rat ventricular myocytes, ACM proliferation was documented with clear evidence of cytokinesis observed with time-lapse imaging. Cardiomyocyte proliferation in the adult mouse post-MI heart was detected by cell cycle markers and 5-ethynyl-2-deoxyuridine incorporation analysis. Echocardiography was used to measure cardiac function, and histology was performed to determine infarction size.Results:In vitro, mononucleated and bi/multinucleated ACMs were able to proliferate at a similar rate (7.0%) in the coculture. Dedifferentiation proceeded ACM proliferation, which was followed by redifferentiation. Redifferentiation was essential to endow the daughter cells with cardiomyocyte contractile function. Intercellular propagation of Ca2+ from contracting neonatal rat ventricular myocytes into ACM daughter cells was required to activate the Ca2+-dependent calcineurin-nuclear factor of activated T-cell signaling pathway to induce ACM redifferentiation. The properties of neonatal rat ventricular myocyte Ca2+ transients influenced the rate of ACM redifferentiation. Hypoxia impaired the function of gap junctions by dephosphorylating its component protein connexin 43, the major mediator of intercellular Ca2+ propagation between cardiomyocytes, thereby impairing ACM redifferentiation. In vivo, ACM proliferation was found primarily in the MI border zone. An ischemia-resistant connexin 43 mutant enhanced the redifferentiation of ACM-derived new cardiomyocytes after MI and improved cardiac function.Conclusions:Mature ACMs can reenter the cell cycle and form new cardiomyocytes through a 3-step process: dedifferentiation, proliferation, and redifferentiation. Intercellular Ca2+ signal from neighboring functioning cardiomyocytes through gap junctions induces the redifferentiation process. This novel mechanism contributes to new cardiomyocyte formation in post-MI hearts in mammals.

Description: Cheese is a typical handcrafted fermented food in Kazak minority from the Uighur Autonomy Region in China and Central Asia. Among the microbial community that is responsible for Kazak cheese fermentation, yeasts play important role in flavor formation during ripening. To develop ripening cultures, we isolated 123 yeasts from 25 cheese products in Kazak, and identified 87 isolates by the D1/D2 domain of the large subunit rRNA gene sequence. Pichia kudriavzevii was the dominant yeast in Kazak cheese, followed by Kluyveromyces marxianus and Kluyveromyces lactis . Of these, the ability to exhibit enzyme of dominant isolates and contribution to the typical flavor of cheeses was assessed. Enzyme producing yeast strains were inoculated in Hazak cheese-like medium and volatile compounds were identified by head space solid phase micro extraction coupled to gas chromatography and mass spectroscopy. Pichia   kudriavzevii N-X displayed the strongest extracellular proteolytic and activity on skim milk agar and produced a range of aroma compounds (ethanol, ethyl acetate, 3-methylbutanol, and acetic acid) for Kazak cheese flavor, could be explored as ripening cultures in commercial production of Kazak cheeses. Diversity of native yeasts in Kazak artisanal cheese was explored. Protease, lipase, and β-galactosidase activities of selected yeast strains were assessed. Impact of different enzyme producing yeast strains on volatile compounds was shown. Kluyveromyces lactis (isolate N-X) and Kluyveromyces marxianus (24-5) could be applied to manufacture of Kazak cheeses.