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Depression recovery can be hard to measure − new research on deep brain stimulation shows how objective biomarkers could help make treatment more precise

Deep brain stimulation can help some people with treatment-resistant depression feel better, but it can be unclear whether a bout of low mood is a relapse…

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Deep brain stimulation can alleviate treatment-resistant depression for some patients. PM Images/Digital Vision via Getty Images

It can be challenging to create a treatment plan for depression. This is especially true for patients who aren’t responding to conventional treatments and are undergoing experimental therapies such as deep brain stimulation. For most medical conditions, doctors can directly measure the part of the body that is being treated, such as blood pressure for cardiovascular disease. These measurable changes serve as an objective biomarker of recovery that provides valuable information about how to care for these patients.

On the other hand, for depression and other psychiatric disorders, clinicians rely on subjective and nonspecific surveys that ask patients about their symptoms. When a patient tells their doctor they are experiencing negative emotions, is that because they are relapsing in their depression or because they had a bad day like everyone does sometimes? Are they anxious because their depression symptoms have lessened enough that they are experiencing new feelings, or do they have some other medical problem independent of their depression? Each reason may indicate a different course of action, such as altering a medication, addressing an issue in psychotherapy or increasing the intensity of brain stimulation treatment.

We are neuroengineers. In our study, newly published in Nature, we identified potential biomarkers for deep brain stimulation that could one day help guide clinicians and patients when making treatment decisions for those using this approach to alleviate treatment-resistant depression.

Deep brain stimulation involves surgically implanting electrodes in the brain.

Biomarker for depression

Clinical depression does not respond to available therapies in a significant number of patients. Researchers have been working to find alternative options for those with treatment-resistant depression, and many decades of experiments have identified specific brain networks with abnormal electrical activity in those with depression.

This notion of depression as abnormal brain activity rather than a chemical imbalance led to the development of deep brain stimulation as a depression treatment: a surgically implanted, pacemaker-like device that delivers electrical impulses to certain areas of the brain. Studies testing this technique have found that it can decrease depression severity over time in most patients.

Our research team wanted to find specific changes in brain activity that could serve as a biomarker that objectively measures how well deep brain stimulation is helping patients with depression. So we monitored the brain activity of 10 patients receiving deep brain stimulation for severe treatment-resistant depression over six months.

At the end of six months, 90% of the patients responded to the therapy – defined by a reduction of symptoms by at least a half – and 70% were in remission, meaning they no longer met the criteria for clinical depression.

To identify a potential biomarker, we developed an algorithm that looked for patterns in brain activity changes as patients recovered. The algorithm was based on data from six out of the original 10 patients who had usable data from the experiment. We found that there are coordinated changes in different frequencies present in the electrical activity within the area of the brain being stimulated. Using these patterns, the algorithm was able to predict whether someone was in a stable recovery with 90% accuracy each week.

Interestingly, we observed some parts of this pattern moved in the opposite direction later in stimulation therapy compared with the patterns at the start of therapy. This finding provides evidence that the long-term recovery is due to the brain adapting to the stimulation in a process called plasticity rather than as a direct effect of the stimulation itself.

Person lying in bed, light speckled over their face.
Depression is a debilitating disease. Guido Mieth/Moment via Getty Images

We also saw other potential biomarkers worth investigating further.

For example, abnormalities in brain imaging taken before implanting the electrodes in specific parts of the brain correlated with how sick each patient was. This could provide clues about what’s causing depression in some people, or help develop imaging methods to determine who might be a good candidate for deep brain stimulation.

For another example, we found that the facial expressions of patients changed as their brains changed over the course of their treatment. While physicians often report this anecdotally, quantifying these changes may provide a way to develop objective markers of recovery that incorporate a patient’s behavior with their brain signals.

Because the results of our study are based on a small sample of patients, it’s important to further investigate how broadly they can be applied to other patients and newer deep brain stimulation devices.

Improving decision-making for depression

Clinical depression is a debilitating condition that causes significant personal and societal suffering. It is one of the largest contributors to the overall disease burden of many countries. Despite the many approved treatments available, nearly 30% of the 8.9 million U.S. adults taking medications for clinical depression continue to have symptoms.

Deep brain stimulation is one of the alternative therapies for treatment-resistant depression that researchers are investigating. Studies have shown that deep brain stimulation can offer effective and long-term relief for some patients.

Although deep brain stimulation is an approved treatment for other conditions like Parkinson’s disease, it remains an experimental therapy for treatment-resistant depression. While the results from small experimental studies have been positive, they have not been successfully replicated in large-scale, randomized clinical trials necessary for approval from the U.S. Food and Drug Administration.

Finding an objective biomarker that measures recovery in depression has the potential to improve treatment decisions. For example, one patient in our study had a relapse after several months of remission. Were a biomarker available at the time, the clinical team would have had warning that the patient was relapsing weeks before standard symptom surveys showed that anything was wrong. Such a tool could help clinicians intervene before a relapse becomes an emergency.

Christopher Rozell serves on the scientific advisory board and owns shares in Motif Neurotech, Inc. and is a listed inventor on intellectual property related to this work. He receives funding from NIH, NSF and the James. S. McDonnell Foundation. Hs is affiliated with the Georgia Institute of Technology, serves on the board of directors at Neuromatch, Inc., and serves on the advisory council of the Institute of Neuroethics.

Sankaraleengam Alagapan receives funding from the National Institute of Health. He is affiliated with the Georgia Institute of Technology. He is a listed inventor on intellectual property related to this work.

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February Employment Situation

By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…

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By Paul Gomme and Peter Rupert

The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.

Temporary help services employment continues a steep decline after a sharp post-pandemic rise.

Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.

The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.

The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.

Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.

As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.

Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.

The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.

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Mortgage rates fall as labor market normalizes

Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.

The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250


Below is an explanation of how we got here with the labor market, which all started during COVID-19.

1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.

2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.

Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.  

2-US_Job_Quits_Rate-1-2

3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too

Total employment data

4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels. 




From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.

Here are the jobs that were created and lost in the previous month:

IMG_5092

In this jobs report, the unemployment rate for education levels looks like this:

  • Less than a high school diploma: 6.1%
  • High school graduate and no college: 4.2%
  • Some college or associate degree: 3.1%
  • Bachelor’s degree or higher: 2.2%
IMG_5093_320f22

Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.

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Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Last month we though that the January…

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Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Last month we though that the January jobs report was the "most ridiculous in recent history" but, boy, were we wrong because this morning the Biden department of goalseeked propaganda (aka BLS) published the February jobs report, and holy crap was that something else. Even Goebbels would blush. 

What happened? Let's take a closer look.

On the surface, it was (almost) another blockbuster jobs report, certainly one which nobody expected, or rather just one bank out of 76 expected. Starting at the top, the BLS reported that in February the US unexpectedly added 275K jobs, with just one research analyst (from Dai-Ichi Research) expecting a higher number.

Some context: after last month's record 4-sigma beat, today's print was "only" 3 sigma higher than estimates. Needless to say, two multiple sigma beats in a row used to only happen in the USSR... and now in the US, apparently.

Before we go any further, a quick note on what last month we said was "the most ridiculous jobs report in recent history": it appears the BLS read our comments and decided to stop beclowing itself. It did that by slashing last month's ridiculous print by over a third, and revising what was originally reported as a massive 353K beat to just 229K,  a 124K revision, which was the biggest one-month negative revision in two years!

Of course, that does not mean that this month's jobs print won't be revised lower: it will be, and not just that month but every other month until the November election because that's the only tool left in the Biden admin's box: pretend the economic and jobs are strong, then revise them sharply lower the next month, something we pointed out first last summer and which has not failed to disappoint once.

To be fair, not every aspect of the jobs report was stellar (after all, the BLS had to give it some vague credibility). Take the unemployment rate, after flatlining between 3.4% and 3.8% for two years - and thus denying expectations from Sahm's Rule that a recession may have already started - in February the unemployment rate unexpectedly jumped to 3.9%, the highest since February 2022 (with Black unemployment spiking by 0.3% to 5.6%, an indicator which the Biden admin will quickly slam as widespread economic racism or something).

And then there were average hourly earnings, which after surging 0.6% MoM in January (since revised to 0.5%) and spooking markets that wage growth is so hot, the Fed will have no choice but to delay cuts, in February the number tumbled to just 0.1%, the lowest in two years...

... for one simple reason: last month's average wage surge had nothing to do with actual wages, and everything to do with the BLS estimate of hours worked (which is the denominator in the average wage calculation) which last month tumbled to just 34.1 (we were led to believe) the lowest since the covid pandemic...

... but has since been revised higher while the February print rose even more, to 34.3, hence why the latest average wage data was once again a product not of wages going up, but of how long Americans worked in any weekly period, in this case higher from 34.1 to 34.3, an increase which has a major impact on the average calculation.

While the above data points were examples of some latent weakness in the latest report, perhaps meant to give it a sheen of veracity, it was everything else in the report that was a problem starting with the BLS's latest choice of seasonal adjustments (after last month's wholesale revision), which have gone from merely laughable to full clownshow, as the following comparison between the monthly change in BLS and ADP payrolls shows. The trend is clear: the Biden admin numbers are now clearly rising even as the impartial ADP (which directly logs employment numbers at the company level and is far more accurate), shows an accelerating slowdown.

But it's more than just the Biden admin hanging its "success" on seasonal adjustments: when one digs deeper inside the jobs report, all sorts of ugly things emerge... such as the growing unprecedented divergence between the Establishment (payrolls) survey and much more accurate Household (actual employment) survey. To wit, while in January the BLS claims 275K payrolls were added, the Household survey found that the number of actually employed workers dropped for the third straight month (and 4 in the past 5), this time by 184K (from 161.152K to 160.968K).

This means that while the Payrolls series hits new all time highs every month since December 2020 (when according to the BLS the US had its last month of payrolls losses), the level of Employment has not budged in the past year. Worse, as shown in the chart below, such a gaping divergence has opened between the two series in the past 4 years, that the number of Employed workers would need to soar by 9 million (!) to catch up to what Payrolls claims is the employment situation.

There's more: shifting from a quantitative to a qualitative assessment, reveals just how ugly the composition of "new jobs" has been. Consider this: the BLS reports that in February 2024, the US had 132.9 million full-time jobs and 27.9 million part-time jobs. Well, that's great... until you look back one year and find that in February 2023 the US had 133.2 million full-time jobs, or more than it does one year later! And yes, all the job growth since then has been in part-time jobs, which have increased by 921K since February 2023 (from 27.020 million to 27.941 million).

Here is a summary of the labor composition in the past year: all the new jobs have been part-time jobs!

But wait there's even more, because now that the primary season is over and we enter the heart of election season and political talking points will be thrown around left and right, especially in the context of the immigration crisis created intentionally by the Biden administration which is hoping to import millions of new Democratic voters (maybe the US can hold the presidential election in Honduras or Guatemala, after all it is their citizens that will be illegally casting the key votes in November), what we find is that in February, the number of native-born workers tumbled again, sliding by a massive 560K to just 129.807 million. Add to this the December data, and we get a near-record 2.4 million plunge in native-born workers in just the past 3 months (only the covid crash was worse)!

The offset? A record 1.2 million foreign-born (read immigrants, both legal and illegal but mostly illegal) workers added in February!

Said otherwise, not only has all job creation in the past 6 years has been exclusively for foreign-born workers...

Source: St Louis Fed FRED Native Born and Foreign Born

... but there has been zero job-creation for native born workers since June 2018!

This is a huge issue - especially at a time of an illegal alien flood at the southwest border...

... and is about to become a huge political scandal, because once the inevitable recession finally hits, there will be millions of furious unemployed Americans demanding a more accurate explanation for what happened - i.e., the illegal immigration floodgates that were opened by the Biden admin.

Which is also why Biden's handlers will do everything in their power to insure there is no official recession before November... and why after the election is over, all economic hell will finally break loose. Until then, however, expect the jobs numbers to get even more ridiculous.

Tyler Durden Fri, 03/08/2024 - 13:30

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