Global taxonomic, functional, and phylogenetic diversity of bees in apple orchards

An essential prerequisite to safeguard pollinator species is characterisation of the multifaceted diversity of crop pollinators and identification of the drivers of pollinator community changes across biogeographical gradients. The extent to which intensive agriculture is associated with the homogenisation of biological communities at large spatial scales remains poorly understood. In this study, we investigated diversity drivers for 644 bee species/morphospecies in 177 commercial apple orchards across 33 countries and four global biogeographical biomes. Our findings reveal significant taxonomic dissimilarity among biogeographical zones. Interestingly, despite this dissimilarity, species from different zones share similar higher-level phylogenetic groups and similar ecological and behavioural traits (i.e. functional traits), likely due to habitat filtering caused by perennial monoculture systems managed intensively for crop production. Honey bee species dominated orchard communities, while other managed/manageable and wild species were collected in lower numbers. Moreover, the presence of herbaceous, uncultivated open areas and organic management practices were associated with increased wild bee diversity. Overall, our study sheds light on the importance of large-scale analyses contributing to the emerging fields of functional and phylogenetic diversity, which can be related to ecosystem function to promote biodiversity as a key asset in agroecosystems in the face of global change pressures.

Adipocyte-derived PGE2 is required for intermittent fasting-induced Treg proliferation and improvement of insulin sensitivity

The intermittent fasting (IF) diet has profound benefits for diabetes prevention. However, the precise mechanisms underlying IF's beneficial effects remain poorly defined. Here, we show that the expression levels of cyclooxygenase-2 (COX-2), an enzyme that produces prostaglandins, are suppressed in white adipose tissue (WAT) of obese humans. In addition, the expression of COX-2 in WAT is markedly upregulated by IF in obese mice. Adipocyte-specific depletion of COX-2 led to reduced fractions of CD4+Foxp3+ Tregs and a substantial decrease in the frequency of CD206+ macrophages, an increase in the abundance of γδT cells in WAT under normal chow diet conditions, and attenuation of IF-induced antiinflammatory and insulin-sensitizing effects, despite a similar antiobesity effect in obese mice. Mechanistically, adipocyte-derived prostaglandin E2 (PGE2) promoted Treg proliferation through the CaMKII pathway in vitro and rescued Treg populations in adipose tissue in COX-2-deficient mice. Ultimately, inactivation of Tregs by neutralizing anti-CD25 diminished IF-elicited antiinflammatory and insulin-sensitizing effects, and PGE2 restored the beneficial effects of IF in COX-2-KO mice. Collectively, our study reveals that adipocyte COX-2 is a key regulator of Treg proliferation and that adipocyte-derived PGE2 is essential for IF-elicited type 2 immune response and metabolic benefits.

Urine Proteome Profiling Predicts Lung Cancer from Control Cases and Other Tumors

Development of noninvasive, reliable biomarkers for lung cancer diagnosis has many clinical benefits knowing that most of lung cancer patients are diagnosed at the late stage. For this purpose, we conducted proteomic analyses of 231 human urine samples in healthy individuals (n = 33), benign pulmonary diseases (n = 40), lung cancer (n = 33), bladder cancer (n = 17), cervical cancer (n = 25), colorectal cancer (n = 22), esophageal cancer (n = 14), and gastric cancer (n = 47) patients collected from multiple medical centers. By random forest modeling, we nominated a list of urine proteins that could separate lung cancers from other cases. With a feature selection algorithm, we selected a panel of five urinary biomarkers (FTL: Ferritin light chain; MAPK1IP1L: Mitogen-Activated Protein Kinase 1 Interacting Protein 1 Like; FGB: Fibrinogen Beta Chain; RAB33B: RAB33B, Member RAS Oncogene Family; RAB15: RAB15, Member RAS Oncogene Family) and established a combinatorial model that can correctly classify the majority of lung cancer cases both in the training set (n = 46) and the test sets (n = 14–47 per set) with an AUC ranging from 0.8747 to 0.9853. A combination of five urinary biomarkers not only discriminates lung cancer patients from control groups but also differentiates lung cancer from other common tumors. The biomarker panel and the predictive model, when validated by more samples in a multi-center setting, may be used as an auxiliary diagnostic tool along with imaging technology for lung cancer detection.

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A case-control study of biomarker discovery for lung cancer diagnosis was conducted.

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Human urine profiles in control cases and cancers were characterized.

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A list of candidate biomarkers was nominated and evaluated.

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A panel of urinary biomarkers was established and tumor-specificity was evaluated.

Cancer diagnosis with a noninvasive method at the early stage of the disease is highly desirable. Here, we analyzed hundreds of human urine samples from healthy individuals, patients with benign pulmonary diseases, and 6 types of cancers by proteomics and developed a panel of five urinary proteins that can separate the lung cancer from benign pulmonary diseases as well as the other 5 cancers (bladder, cervical, colorectal, esophageal and gastric) with a good sensitivity and disease specificity. Further validation experiments with expanded sample numbers are required to investigate whether this method can be applied in a clinical setting for the diagnosis of lung cancer.

Proof-of-Concept Workflow for Establishing Reference Intervals of Human Urine Proteome for Monitoring Physiological and Pathological Changes

Urine as a true non-invasive sampling source holds great potential for biomarker discovery. While approximately 2000 proteins can be detected by mass spectrometry in urine from healthy people, the amount of these proteins vary considerably. A systematic evaluation of a large number of samples is needed to determine the range of the variations. Current biomarker studies often measure limited number of urine samples in the discovery phase, which makes it difficult to determine whether proteins differentially expressed between control and disease groups represent actual difference, or are just physiological variations among the individuals, leads to failures in the validation phase with the increased sample numbers. Here, we report a streamlined workflow with capacity of measuring 8 urine proteomes per day at the coverage of >1500 proteins. With this workflow, we evaluated variations in 497 urine proteomes from 167 healthy donors, establishing reference intervals (RIs) that covered urine protein variations. We demonstrated that RIs could be used to monitor physiological changes by detecting transient outlier proteins. Furthermore, we provided a RIs-based algorithm for biomarker discovery and validation to screen for diseases such as cancer. This study provided a proof-of-principle workflow for the use of urine proteome for health monitoring and disease screening.

Advances in tumor markers of ovarian cancer for early diagnosis

Ovarian cancer often occurs in perimenopausal women. The mortality of ovarian cancer is in the first place among gynecological cancers because of no obvious early symptoms and the lack of effective diagnostic approach. Gene chips, proteomics, immunohistochemistry and other methods have become hot topics for early diagnosis of ovarian cancer. However, due to the variety of pathology and not clear enough of mechanism and etiology, there is still no ideal tumor markers with both high specific and sensitivity, which can be applied into clinical early diagnosis for ovarian cancer. Therefore, a new systematic method with high sensitivity and specificity for early diagnosis of ovarian cancer and new tumor markers need to be identified. We should make an examination of ovarian cancer in the early period in the crowd for early diagnosis and early treatment to further improve life quality of patients. This paper reviewed the recent advancements of tumor markers for early diagnosis of ovarian cancer.

S100 protein in breast tumor

S100 protein is the largest subtribe in calcium binding protein family. According to recent researches, abnormal expression of S100 protein is often related to tumor, including breast tumor. Breast tumor is the most common malignant disease in female with high mortality mainly due to metastasis. Estimating early diagnostic and prognostic markers are helpful to conduct treatment for patients with breast cancer. Accumulating investigations focused on the role of S100 proteins in breast tumor development and metastasis. This paper summarizes the expression situation of S100 proteins in breast tumor as well as its effects on metastasis and prognosis of breast tumor.

First Report of Leaf Spot Disease on Dictamnus dasycarpus Caused by Phoma dictamnicola in China

Fraxinella, Dictamnus dasycarpus Turcz (Rutaceae), is a perennial herbal plant and mainly distributed in Eurasia and North America. It is often used to treat jaundice, cough, rheumatism, and other diseases and is extensively cultivated in the northeast and northwest of China (3). In June 2009, a severe foliar disease was observed on D. dasycarpus in medicinal plantations in Antu, China. The disease occurred on 100% of the plants and at least 25% of the surface was affected. In the early stages of disease development, symptoms were visible on the top and bottom of infected leaves as small brown spots. Subsequently, these spots became elliptical to irregularly shaped, with beige or grayish white centers and dark brown margins. Within the spots, numerous, dark brown or black, subglobose or ostiolate pycnidia measuring 152 to 367 μm in diameter were observed. Fungal isolates were obtained from the infected leaves on potato dextrose agar (PDA) medium, with conidia that were aseptate or one-septate and ellipsoidal or reniform, measuring approximately 4.7 to 12.6 × 2.1 to 4.5 μm. On the basis of these characteristics, the fungus was identified as a Phoma sp. Four well-sporulating isolates, designated as DdPh-1, DdPh-2, DdPh-3, and DdPh-4, were selected for further studies. The morphological and cultural characteristics of these four isolates were studied as described by Boerema et al. and the fungus was identified as Phoma dictamnicola Boerema et al. (1). The internal transcribed spacer (ITS) region of the nuclear rDNA was amplified and sequenced using primers ITS4/ITS5 (2). All four of the ITS sequences were identical (GenBank Accession No. FR681861) and were 99% identical to P. dictamnicola strains CBS507.91 (Accession No. GU237877) and KACC42445 (Accession No. EF600960). Pathogenicity tests were performed by spraying the leaves of healthy D. dasycarpus plants with a conidial suspension (1 × 10⁶ conidia/ml). Five plants were inoculated with each isolate (DdPh-1, DdPh-2, DdPh-3, and DdPh-4) and five plants were mock inoculated with sterile water. The plants were covered with plastic bags and kept in a greenhouse at 20 to 25° for 72 h. After 9 to 13 days, all inoculated plants showed characteristic symptoms as previously described, while the control plants remained healthy. The fungus was reisolated from the leaf spots of inoculated plants. Currently, the economic importance of this disease is limited, but it may become a more significant problem in production of D. dasycarpus with the cultivation area increasing. The fungus was found in the Netherlands and Korea, but to our knowledge, this is the first report of P. dictamnicola on D. dasycarpus in China. References: (1) G. H. Boerema et al. Phoma Identificatión Manual: Differentiation of Specific and Infra-Specific Taxa in Culture. CABI Publishing. Wallingford, U.K., 2004. (2) D. E. L. Cooke et al. Mycol. Res. 101:667, 1997. (3) S. S. Jiang et al. Biosci. Biotechnol. Biochem. 72:660, 2008.