The primary paper for this week is Kristensen C, Kjeldsen T, Wiberg FC, Schäffer L, Hach M, Havelund S, Bass J, Steiner DF and Andersen AS (1997) Alanine Scanning Mutagenesis of Insulin JBC 272 12978–83. This is the paper you should read (large request, I know, give it the old college try) and write a no more than two hundred fifty word summary of before class. More details on what you'll find in a paper, generally, below.

The abstract is a synopsis of the paper in a very short form. It is likely to describe the model system used, what was done in that system and what was learned from the work. Being in such a short form, it is the bare minimum, nothing extra. There are no data here, just the highlights. As a result, abstracts give the flavor of the paper, raising your hunger to read the whole paper .

The introduction, just like a high school writing assignment, is designed to begin wide and bring the reader down to the particular question addressed in this paper. The introduction is likely to begin with some basics, the sort of thing that everyone will agree on. It usually begins there after narrowing the world down to a particular example which is going to serve as the model system in which to answer the major question of the paper. With a model system described, the introduction often moves to the particular problem of interest for the paper, and how they plan to attack that problem in this system (some detail about what they plan to do in the lab). The very end of the introduction usually provides clear statement of what the authors feel they have accomplished in this paper.

The methods section describes exactly what was done to produce the results in this paper. The rule is that the methods are described in enough detail that anyone familiar with working in the lab should be able to reproduce the experiments. That's really good if you'd like to do something similar, all the hard work of developing the methods to do something is freely shared. The downside for early readers of biochemistry is that a paper which has been rapidly progressing is now going to slowly wade through many, many details. And just like walking through deep water, there is some resistance in reading the methods section, particularly if you've never done similar experiments yourself. Typically I will only glance at the methods in the first pass through the paper. I am more interested in the next section, the results. The catch is, however, that when I want to fully understand the evidence in the results, I often return to the methods to make sure I know what they've done and how they did it. The methods section is usually divided into details about each experiment seperately so that it can be used more as a reference work than prose to be read line by line, start to finish.

The most valuable information is in the results section. The results section contains the data generated from all of the experiments described in the methods section. The results section also completes the core of the paper. The results, with the methods producing them, are the objective reality reported in the paper. The results, if supported with the correct methods, are the level on which you must agree with the authors. That is, the data are true. Certainly, there are some who enhance or fabricate data (see More than 10,000 research papers were retracted in 2023 — a new record for more on the paper fraud story), but by and large you can and should believe the data in scientific papers. While you might want to (and it is good that you do) argue with points of the discussion (the final section), if the methods support the data, you should believe them.

So, what's in the results. Foremost are the figures and tables. These visual tools will present the densest data by far. The prose may contain some results which are not in a figure or table, but for the most part the words are there to support what is presented graphically. The text is there to put the figures and tables into context and to wed them to the experiments that were done to generate them. I would start with figures and tables, using the prose to get a full feeling of what I am looking at in a panel. But do remember that what is in the text of this section is fully descriptive. It'll tell you what you see and how it was generated, but there is little interpretation in this section. The interpretation is written in the....

The discussion section is where the authors will revisit their data and begin to explain, not only what they mean, but also how they fit into a larger picture of how the things described in the introduction work. Remember that this section, as interpretation of data, is open for debate. You may suggest that a particular experiment does not show what the authors claim or you may suggest that evidence from another paper contradicts the conclusions of the author, all good. The data are objective reality, the conclusions are the interpreation of others. In first reading a paper, you may want to read the conclusions with little skepticism. The authors will typically have more knowledge and understanding and will be able to relate their work to a much larger body of work that, for a single paper, would be unfamiliar to you. Take the discussion with the results get a fuller picture of the work.

You want to be sure to identify the question they are trying to answer (it's usually near the end of the introduction and repeated in the discussion), the method(s) being used (abstract and methods), the model system (abstract and methods) and the data which answers their question (abstract and results).

The length requirement is two hundred fifty words, maximum. You may work in whichever file format you like. I'll take the burden of being able to read it. My assumption is that you'll use something like a word processor with a page metaphor. In that case, two hundred fifty words is a bit less than one page if the font size is 12 point, double spaced with about 1 inch margins. If you're a single spacer, it's a line or two less than one half page.

The short answer is exactly the same thing. Why do it all again? Well, you've (or you should have) learned a little bit more about not only this paper but papers in the general. It should be a bit easier to find the key elements, interpret the data and understand this small bit of the physical world. By coming back to a paper after some exposure, you'll gain confidence in your abilities. And with that confidence the next paper, even though it will be in a very different area, should be a little bit easier to read.