Author: claimsbot

1. A bone plate for bone fixation, comprising:
a plate body defining a plurality of openings for receiving fasteners that secure the plate body to bone, the plurality of openings including an oblong opening defining a long axis; and
a locking element configured to be disposed in threaded engagement with a fastener extending at least from the oblong opening, then through the locking element and into bone, the locking element being connected slidably to the plate body, in the absence of the fastener, for movement at least substantially parallel to the long axis.
2. The bone plate of claim 1, wherein the plate body includes an inner face defining a cavity that at least partially receives the locking element, and wherein the plate body supports the locking element in the cavity when the inner face is facing downward.
3. The bone plate of claim 1, wherein the locking element includes at least one hook portion, and wherein the locking element is connected to the plate body using the at least one hook portion.
4. The bone plate of claim 3, wherein the locking element includes a bent metal sheet.
5. The bone plate of claim 1, wherein the locking element defines a through-hole with an internal thread.
6. A system for bone fixation, comprising:
a plate body defining a plurality of openings for receiving fasteners that secure the plate body to bone; and
a locking element for receiving a fastener that locks to the locking element while extending through an opening of the plate body and into bone, the locking element being disposed inward of the opening and being connected movably to the plate body in the absence of the fastener.
7. The system of claim 6, wherein the opening is oblong and defines a long axis, and wherein the locking element is slidable at least substantially parallel to the long axis.
8. The system of claim 7, wherein the opening includes a sloped countersink surface.
9. The system of claim 6, the locking element being a first locking element, further comprising one or more additional locking elements that form a set of locking elements collectively with the first locking element, wherein the set of locking elements is connected to the plate body, and wherein each locking element is movable individually.
10. The system of claim 6, wherein the plate body defines a long axis and a length measured parallel to the long axis, and wherein the locking element is capable of sliding motion at least substantially parallel to the long axis, with a range of motion restricted to only a subset of the length.
11. The system of claim 6, wherein the plate body includes an inner face defining a cavity that at least partially receives the locking element, and wherein the plate body supports the locking element in the cavity when the inner face is facing downward.
12. The system of claim 6, wherein the locking element is hooked to the plate body.
13. The system of claim 12, wherein the locking element is formed of a bent sheet of metal.
14. The system of claim 6, wherein the locking element defines a through-hole with an internal thread.
15. The system of claim 6, wherein the plate body has an outer face, and wherein the locking element is configured such that at least a portion of the locking element moves closer to the outer face as the fastener is tightened fully against the plate body.
16. The system of claim 6, further comprising a bone screw for placement through the opening of the plate body, into threaded engagement with the locking element, and into bone.
17. A method of bone fixation, comprising:
connecting a plate body of a bone plate to a first portion of bone;
placing a fastener into a second portion of bone from an oblong opening of the plate body and through a locking element disposed between the oblong opening and the second portion of bone, such that the fastener connects the bone plate to the second portion of bone and is locked to the locking element; and
moving the fastener, the locking element, and the second portion of bone collectively relative to the plate body and the first portion of bone, to urge the first and second portions of bone toward one another while the fastener remains locked to the locking element.
18. The method of claim 17, the fastener being a bone screw having a head, the plate body including a sloped countersink surface extending generally along the oblong opening, wherein the step of moving includes a step of turning the bone screw such that the head of the fastener travels along the sloped countersink surface.
19. The method of claim 17, further comprising a step of selecting a bone plate including the plate body connected to the locking element in the absence of the fastener, wherein the steps of connecting, placing, and moving are performed with the bone plate after the step of selecting.
20. The method of claim 17, the first and second portions of bone being arranged longitudinally along a bone, wherein the step of moving includes a step of urging the first and second portions toward one another longitudinally in relation to the bone.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method for optimizing a prediction of resource usage of multiple applications running in a virtual environment, comprising:
providing a predetermined set of benchmarks;
executing the predetermined set of benchmarks in a native hardware system in which the application natively resides;
executing the predetermined set of benchmarks in the virtual environment;
collecting first traces of first resource utilization metrics in the native hardware system based on the execution of the predetermined set of benchmarks in the native hardware system;
collecting second traces of second resource utilization metrics in the virtual environment based on the execution of the predetermined set of benchmarks in the virtual environment;
generating a first prediction model that maps a first selected set of the first traces of a selected one of the first resource utilization metrics to the second traces of resource utilization metrics;
generating a second prediction model that maps a second selected set of the first traces of the selected first resource utilization metric to the second traces of resource utilization metrics;
collecting first application traces of resource utilization metrics in the native hardware system based on an execution of a first application in the native hardware system;
collecting second application traces of resource utilization metrics in the native hardware system based on an execution of a second application in the native hardware system;
aggregating the first application traces of the first application and the second application traces of the second application into combined application traces of resource utilization metrics; and
predicting a combined resource usage of the first and second applications running in the virtual environment by applying the first and second prediction models to the combined application traces of resource utilization metrics.
2. The method of claim 1, wherein applying the first and second prediction models comprises:
applying each of the first and second prediction models to the combined traces of resource utilization metrics based on an inputout rate of a selected one of the resource utilization metrics.
3. The method of claim 1, further comprising:
generating a third prediction model that maps the first and second selected sets of the first traces of the selected first metric to the second traces of resource utilization metrics; and
predicting a combined resource usage of the first and second applications running in the virtual environment by applying the third prediction model to each of the collected first and second traces of resource utilization metrics.
4. The method of claim 3, wherein predicting the combined resource usage by applying the third prediction model comprises:
applying the third prediction model to the collected first application traces of resource utilization metrics to estimate a first resource usage of the first application running in the virtual environment;
applying the third prediction model to the collected second application traces of resource utilization metrics to estimate a second resource usage of the second application running in the virtual environment; and
predicting the combined resource usage of the first and second applications by aggregating the first and second resource usage.
5. The method of claim 3, further comprising:
calculating a first error associated with the first prediction model;
calculating a second error associated with the second prediction model; and
calculating a third error associated with the third prediction model.
6. The method of claim 5, wherein the step of predicting the combined resource usage by applying a combination of the first and second prediction models is performed upon a first condition based on a comparison of the third error against a sum of the first and second errors.
7. The method of claim 6, wherein the step of predicting the combined resource usage by applying the third prediction model is performed upon a second different condition based on a comparison of the third error against the sum of the first and second errors.
8. The method of claim 1, wherein aggregating the first and second traces of resource utilization metrics of the first and second applications comprises:
aggregating each of the first traces of resource utilization metrics to each of the second traces of resource utilization metrics when the first and second traces are of the same resource utilization metric.
9. The method of claim 1, wherein:
generating the first prediction model comprises generating the first prediction model for each virtual machine guest domain and each driver domain in the virtual environment; and
generating the second prediction model comprises generating the second prediction model for each virtual machine guest domain and each driver domain in the virtual environment.
10. The method of claim 1, wherein:
generating the first prediction model comprises generating the first prediction model for each virtual machine guest domain and a hypervisor in the virtual environment; and
generating the second prediction model comprises generating the second prediction model for each virtual machine guest domain and the hypervisor in the virtual environment.
11. A system for optimizing a prediction of resource usage of multiple applications running in a virtual environment, comprising:
a first hardware platform implementing a native hardware system in which an application natively resides and executes, the native hardware system operating to execute a predetermined set of benchmarks that includes at least one of a network-intensive workload and a disk-intensive workload;
a second hardware platform implementing a virtual environment therein, the virtual environment operating to execute the predetermined set of benchmarks;
a third hardware platform operating to collect first resource usage traces from the first hardware platform that result from the execution of the predetermined set of benchmarks in the native hardware system and second resource usage traces from the second hardware platform that result from the execution of the predetermined set of benchmarks in the virtual environment;
wherein the third hardware platform further operating to generate at least one prediction model that predicts a resource usage of each of the multiple applications executing in the virtual environment based on the collected first and second resource usage traces; and
wherein the third hardware platform further operating to:
a) collect first application traces of resource utilization metrics in the native hardware system based on an execution of a first one of the multiple applications in the native hardware system;
b) collect second application traces of resource utilization metrics in the native hardware system based on an execution of a second one of the multiple applications in the native hardware system;
c) apply the at least one prediction model to the collected first application traces of the first application to calculate a first estimate resource usage in the virtual environment by the first application;
d) apply the at least one prediction model to the collected second application traces of the second application to calculate a second estimate resource usage in the virtual environment by the second application; and
e) predicting an overall resource usage in the virtual environment by the first and second applications by aggregating the first and second estimate resource usages.
12. The system of claim 11, wherein the third hardware platform further operating to:
generate a third prediction model that maps a first selected set of the first traces of a selected one of the first resource utilization metrics to the second traces of resource utilization metrics;
generate a fourth prediction model that maps a second different selected set of the first traces of the selected first resource utilization metric to the second traces of resource utilization metrics;
aggregate the first application traces of the first application and the second application traces of the second application into combined application traces of resource utilization metrics; and
predict an overall resource usage of the first and second applications running in the virtual environment by applying the first and second prediction models to different sets of the combined application traces of resource utilization metrics.
13. The system of claim 11, wherein the virtual environment includes a driver domain and a virtual machine (VM) guest domain, and the second resource usage traces comprises:
a percentage of processor utilization in the virtual environment that is attributed to a utilization of hardware processing resources in the second hardware platform by the driver domain; and
a percentage of processor utilization in the virtual environment that is attributed to a utilization of hardware processing resources in the second hardware platform by the VM guest domain.
14. The system of claim 11, wherein the virtual environment includes a hypervisor and a virtual machine (VM) guest domain, and the second resource usage traces comprises:
a percentage of processor utilization in the virtual environment that is attributed to a utilization of hardware processing resources in the second hardware platform by the hypervisor; and
a percentage of processor utilization in the virtual environment that is attributed to a utilization of hardware processing resources in the second hardware platform by the VM guest domain.
15. A computer readable medium on which is encoded programming code executed by a computerized system for:
providing a predetermined set of benchmarks;
executing the predetermined set of benchmarks in a native hardware system in which the application natively resides;
executing the predetermined set of benchmarks in the virtual environment;
collecting first traces of first resource utilization metrics in the native hardware system based on the execution of the predetermined set of benchmarks in the native hardware system;
collecting second traces of second resource utilization metrics in the virtual environment based on the execution of the predetermined set of benchmarks in the virtual environment;
generating a first prediction model that maps a first selected set of the first traces of a selected one of the first resource utilization metrics to the second traces of resource utilization metrics;
generating a second prediction model that maps a second selected set of the first traces of the selected first resource utilization metric to the second traces of resource utilization metrics;
collecting first application traces of resource utilization metrics in the native hardware system based on an execution of a first application in the native hardware system;
collecting second application traces of resource utilization metrics in the native hardware system based on an execution of a second application in the native hardware system;
aggregating the first application traces of the first application and the second application traces of the second application into combined application traces of resource utilization metrics; and
predicting a combined resource usage of the first and second applications running in the virtual environment by applying the first and second prediction models to the combined application traces of resource utilization metrics.

1. An isolated nucleic acid comprising a nucleotide sequence encoding a vascular endothelial cell growth factor-E (VEGF-E) polypeptide comprising amino acid residues 1 through 345 of FIG. 2 (SEQ ID NO:2).
2. The nucleic acid of claim 1 comprising the sequence of nucleotides 259 through 1293 of FIG. 1 (SEQ ID NO:1), or its complement.
3. An isolated nucleic acid comprising a nucleotide sequence which hybridizes under stringent conditions to the nucleotide sequence of claim 1.
4. A vector comprising the nucleic acid of claim 1.
5. A host cell comprising the nucleic acid of claim 1.
6. The host cell of claim 5, wherein said cell is a Chinese Hamster Ovary cell, an insect cell, an E. coli cell, or a yeast cell.
7. The host cell of claim 6 that is a baculovirus-infected insect cell.
8. A process for producing a vascular endothelial cell growth factor-E (VEGF-E) polypeptide comprising culturing the host cell of claim 5 under conditions suitable for expression of the VEGF-E polypeptide and recovering the VEGF-E polypeptide from the cell culture.
9. A polypeptide produced by the process of claim 8.
10. A VEGF-E polypeptide comprising amino acid residues 1 through 345 of FIG. 2 (SEQ ID NO:2).
11. A VEGF-E polypeptide selected from the group consisting of:
(a) a polypeptide comprising amino acid residues 1 through 345 of FIG. 2 (SEQ ID NO:2); and
(b) a polypeptide fragment of (a), wherein said fragment is biologically active.
12. A VEGF-E polypeptide encoded by the nucleotide sequence insert of ATCC deposit No. 209653.
13. A chimeric polypeptide comprising the polypeptide of claim 10 fused to a heterologous amino acid sequence.
14. The chimeric polypeptide of claim 13, wherein said heterologous amino acid sequence is an epitope tag sequence or a Fc region of an immunoglobulin.
15. A composition comprising the polypeptide of claim 10 in admixture with a carrier.
16. The composition of claim 15 comprising a therapeutically effective amount of the polypeptide, wherein the carrier is a pharmaceutically acceptable carrier.
17. A pharmaceutical product comprising:
(a) the composition of claim 15;
(b) a container containing said composition; and
(c) a label affixed to said container, or a package insert included in said pharmaceutical product, referring to the use of said VEGF-E polypeptide in the treatment of a cardiovascular or endothelial disorder.
18. A method for treating a cardiovascular or endothelial disorder in a mammal comprising administering to the mammal an effective amount of the composition of claim 15.
19. The method of claim 18 wherein the disorder is cardiac hypertrophy, trauma, or a bone-related disorder.
20. The method of claim 19 wherein said cardiac hypertrophy is characterized by the presence of an elevated level of PGF2.
21. The method of claim 19 wherein said cardiac hypertrophy has been induced by myocardial infarction.
22. The method of claim 21 wherein said VEGF-E polypeptide administration is initiated within 48 hours following myocardial infarction.
23. A method for diagnosing a disease or a susceptibility to a disease related to a mutation in a nucleic acid sequence encoding vascular endothelial cell growth factor-E (VEGF-E) comprising:
(a) isolating a nucleic acid sequence encoding VEGF-E from a sample derived from a host; and
(b) determining a mutation in the nucleic acid sequence encoding VEGF-E.
24. A method of diagnosing cardiovascular and endothelial disorders in a mammal comprising detecting the level of expression of a gene encoding a vascular endothelial cell growth factor-E (VEGF-E) polypeptide (a) in a test sample of tissue cells obtained from the mammal, and (b) in a control sample of known normal tissue cells of the same cell type, wherein a higher or lower expression level in the test sample indicates the presence of a cardiovascular or endothelial dysfunction in the mammal from which the test tissue cells were obtained.
25. A method for identifying an agonist to a vascular endothelial cell growth factor-E (VEGF-E) polypeptide comprising:
(a) contacting cells and a candidate compound under conditions that allow the polypeptide to stimulate proliferation of the cells; and
(b) measuring the extent to which cell proliferation is inhibited by the compound.
26. An agonist to a VEGF-E polypeptide identified by the method of claim 25.
27. A method for identifying a compound that inhibits the expression or activity of a vascular endothelial cell growth factor-E (VEGF-E) polypeptide, comprising:
(a) contacting a candidate compound with the polypeptide under conditions and for a time sufficient to allow the compound and polypeptide to interact; and
(b) measuring the extent to which the compound interacts with the polypeptide.
28. A compound identified by the method of claim 27.
29. An isolated antibody that binds a vascular endothelial cell growth factor-E (VEGF-E) polypeptide.
30. The antibody of claim 29 that is a monoclonal antibody.
31. A method for determining the presence of a vascular endothelial cell growth factor-E (VEGF-E) polypeptide comprising exposing a cell suspected of containing the VEGF-E polypeptide to the antibody of claim 29 and determining binding of said antibody to said cell.
32. A method of diagnosing cardiovascular, endothelial, or angiogenic disorders in a mammal comprising (a) contacting the antibody of claim 29 with a test sample of tissue cells obtained from the mammal, and (b) detecting the formation of a complex between the anti-VEGF-E antibody and the VEGF-E polypeptide in the test sample.
33. An article of manufacture, comprising:
a container;
a label on the container; and

a composition comprising the antibody of claim 29 contained within the container; wherein the label on the container indicates instructions for using the antibody in a therapeutic method or diagnostic method.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A cutting insert for a milling cutter, the cutting insert comprising two polygonal main surfaces that are opposite each other and a plurality of side faces that are formed continuously with the sides of the main surfaces, the main surfaces being rake faces, the side faces being flank faces, and ridge lines at positions where the main surfaces and the side faces cross each other being used as cutting edges,
wherein the plurality of side faces include two major side surfaces that are opposite each other and a plurality of minor side surfaces that are formed continuously with the major side surfaces, a mounting hole is provided at the two major side surfaces in a direction in which the mounting hole extends therethrough, and areas of the two major side surfaces are greater than those of the main surfaces, and
wherein the major side surfaces and the minor side surfaces are provided with flutes along entire regions of the cutting edges, and flute faces of the flutes at a side along the cutting edges are tilted in a direction in which depths gradually increase with increasing distance from the cutting edges.
2. The cutting insert for the milling cutter according to claim 1, wherein a tilt angle of the flute face of each flute at the side along the cutting edge is greater than or equal to 2 degrees, and a flute width of each flute is greater than or equal to 0.5 mm and less than or equal to 5 mm.
3. The cutting insert for the milling cutter according to claim 1, wherein a central portion of each main surface is provided with a flat land that is seated on a support seat of a cutter body, and, with positions of the flat lands being lower than positions of the cutting edges, the rake faces that are tilted are provided between the cutting edges and the flat lands.
4. The cutting insert for the milling cutter according to either claim 2, wherein a central portion of each main surface is provided with a flat land that is seated on a support seat of a cutter body, and, with positions of the flat lands being lower than positions of the cutting edges, the rake faces that are tilted are provided between the cutting edges and the flat lands.