Classification of ledger accounts for creameries

In presenting this Classification of Ledger Accounts for Creameries it is the aim of the Bureau of Markets to emphasize the importance of the use of a definite and logical classification of accounts for keeping the financial records of any business and to describe in detail a classification which can be used advantageously by creameries. The use of such a classification is not only a great aid to the bookkeeper in the performance of routine duties, but its consistent use also insures a uniform method of presenting the financial information from year to year regardless of changes in the personnel. The use of these uniform methods by an industry as a whole makes possible the exchange of data regarding business operations, which is of untold value as a guide to efficient operation

Classification of income, profit and loss, and general balance sheet accounts for steam roads

This Classification of Income, Profit and Loss, and General Balance Sheet Accounts supersedes the Form of Income and Profit and Loss Statement for Steam Roads, First Issue, effective July 1, 1912, and the Form of General Balance Sheet Statement, First Revised Issue, effective June 15, 1910. It also supersedes conflicting instructions in Accounting Bulletin No. 8. The general and special instructions contain a comprehensive statement of the principles underlying the classification, indicating generally the application of the accounting rules. The attention of accounting officers is called to the importance of requiring all employees who are assigned to accounting work in connection with income, profit and loss, and general balance-sheet accounts to familiarize themselves thoroughly with these instructions

Chitohexaose Activates Macrophages by Alternate Pathway through TLR4 and Blocks Endotoxemia

Sepsis is a consequence of systemic bacterial infections leading to hyper activation of immune cells by bacterial products resulting in enhanced release of mediators of inflammation. Endotoxin (LPS) is a major component of the outer membrane of Gram negative bacteria and a critical factor in pathogenesis of sepsis. Development of antagonists that inhibit the storm of inflammatory molecules by blocking Toll like receptors (TLR) has been the main stay of research efforts. We report here that a filarial glycoprotein binds to murine macrophages and human monocytes through TLR4 and activates them through alternate pathway and in the process inhibits LPS mediated classical activation which leads to inflammation associated with endotoxemia. The active component of the nematode glycoprotein mediating alternate activation of macrophages was found to be a carbohydrate residue, Chitohexaose. Murine macrophages and human monocytes up regulated Arginase-1 and released high levels of IL-10 when incubated with chitohexaose. Macrophages of C3H/HeJ mice (non-responsive to LPS) failed to get activated by chitohexaose suggesting that a functional TLR4 is critical for alternate activation of macrophages also. Chitohexaose inhibited LPS induced production of inflammatory molecules TNF-α, IL-1β and IL-6 by macropahges in vitro and in vivo in mice. Intraperitoneal injection of chitohexaose completely protected mice against endotoxemia when challenged with a lethal dose of LPS. Furthermore, Chitohexaose was found to reverse LPS induced endotoxemia in mice even 6/24/48 hrs after its onset. Monocytes of subjects with active filarial infection displayed characteristic alternate activation markers and were refractory to LPS mediated inflammatory activation suggesting an interesting possibility of subjects with filarial infections being less prone to develop of endotoxemia. These observations that innate activation of alternate pathway of macrophages by chtx through TLR4 has offered novel opportunities to cell biologists to study two mutually exclusive activation pathways of macrophages being mediated through a single receptor

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Taxonomy based on science is necessary for global conservation

Peer reviewe

Angular analysis of the decay B-0 -> K*(0)mu(+)mu(-) from pp collisions at root s=8 TeV

Peer reviewe

Measurement of the WZ production cross section in pp collisions at root s=7 and 8 TeV and search for anomalous triple gauge couplings at root s=8 TeV

Peer reviewe