#Independent predictors

[juniperpublishers-endocrinology]

Evaluation of Pre-Transplant Risk Factors as Independent Predictors on the New Onset of Diabetes after Renal Transplants (NODAT)-Juniper Publishers

JUNIPER PUBLISHERS-OPEN ACCESS JOURNAL OF ENDOCRINOLOGY AND THYROID RESEARCH

Abstract

Background: One of the most potential complications in renal allograft recipients is post- operative impaired glucose tolerance leading to frank de novo Diabetes Mellitus known as New Onset Diabetes after Transplant (NODAT). It is multifactorial and is pathogenically similar to Type 2 Diabetes Mellitus. Having a variable incidence, it is usually associated with an increased risk of infection, cardiovascular morbidity, and graft dysfunction which can eventually cause mortality or loss of the allograft.

Methods: In this study we aimed at comparing pre-operative risk factors namely age, sex, gender, insulin resistance (estimated by HOMA-IR), ß cell function (estimated by HOMA-ß), pre-operative fasting plasma glucose, post-operative fasting plasma glucose, tacrolimus level, induction ATG and hepatitis C virus status as an implicating factor for those who developed NODAT in post-operative period versus those who maintained an euglycemic status throughout the study period (non-NODAT). The study was carried out at the renal transplant unit of NHRTIICS, Kolkata between Jan 2013 to Feb 2014.

Results: Among the 54 subjects included in the analysis, NODAT subjects (n=18) have significantly higher pre-operative insulin resistance levels (measured by HOMA-IR) than non-NODAT (n=36) subjects, p=0.021. Simultaneously, the beta cell function were significantly lower in the subjects in patients who developed NODAT compared to the non-NODAT subjects, p=0.007. Both the pre-operative and post-operative fasting plasma glucose were significantly higher in the patients who developed NODAT, p=0.032 and p<0.001 respectively. Tacrolimus levels were significantly higher in the NODAT patients, however, no significant difference was found with regards to induction ATG received (p=0.96) and hepatitis C virus status (p=0.62).

Conclusion: The incidence of NODAT is quite high in our renal transplant patients. Risk of development of post-transplant diabetes was more closely related to traditional risk factors namely age, pre-operative fasting plasma glucose, post-operative plasma glucose, pre-operative insulin resistance and immunosuppressive therapy.

Keywords: NODAT; Pre-operative risk factors; Independent predictors   

Introduction

Renal transplantation (KT) is the treatment of choice for end-stage renal disease (ESRD); nevertheless, aftermath complications are a major source of concern, one of which is development of post-transplant Diabetes Mellitus, a frequent complication that represents one of the leading causes of morbidity and mortality. Diabetes occurs in a substantial number of subjects following renal transplantation. Post-transplant diabetes mellitus (PTDM) refers to newly diagnosed diabetes in post-transplant setting, irrespective of timing or whether it was present but undetected prior to transplantation or not. However, the term PTDM should be utilized for clinically stable patients who have developed persistent post-transplantation hyperglycemia. On the other hand, new onset diabetes mellitus after transplant (NODAT) refers to the development of diabetes post-transplant in previously non-diabetic patients [1].

New onset Diabetes after transplant (NODAT) is associated with increased mortality and morbidity, and, in particular, higher rates of cardiovascular disease and infection, which are theleading causes of death in renal transplant recipients. Many of the same risk factors that predispose non-transplant subjects to diabetes mellitus have been identified as risk factors for its development after transplantation. Such common risk factors include age, obesity, African-American race and Hispanic ethnicity, family history, and impaired glucose tolerance. Risk models for NODAT have been developed and validated using pre-transplant variables alone. In addition, some risk factors are unique to the transplant population. These include specific agents used for immunosuppression, human leukocyte antigen (HLA) mismatch, donor sex, and type of underlying renal disease [2]. Impaired glucose tolerance prior to transplant and hyperglycemia in the immediate perioperative period may identify subjects at higher risk for the development of NODAT [3,4].   

Materials and Methods

This was a single centered retrospective real world observational study of 54 subjects who underwent renal transplantation over a period of one year in a tertiary care center in eastern India. NODAT was defined according to American Diabetes Association definition with fasting glucose level equal or greater than 126mg/dl on two separate blood tastings; and/or two hours OGTT values equal or greater than 200mg/dl; and/or glycosylated hemoglobin (HbA1C) equal or greater than 6.5. The Inclusion criteria were comprised of adult subjects with end stage renal disease who underwent live donor kidney transplantation, absence of diabetes prior to kidney transplantation, defined according to American Diabetes Association guideline (not on oral hypoglycemic agents or insulin with fasting glucose <126mg/dL) and received immunosuppressive medications that include Tacrolimus. Subjects who were capable of understanding the study and given informed written consent for study participation were only included. Subjects with a diagnosis of diabetes mellitus prior to kidney transplantation based on ADA criteria for diagnosis of diabetes mellitus or those receiving anti-diabetic medications or those who were not capable of providing consent were excluded from the study.

Statistical methods

Descriptive statistical analysis has been carried out in the present study. Results on continuous measurements are presented on Mean±SD and results on categorical measurements are presented in Number (%). Significance is assessed at a level of 5%.   

Results

Among the 54 subjects included in the analysis, mean age of the subjects were 46±10.33 years and 32.14±13.67 years in NODAT (n=18) and Non-NODAT (n=36) cohort respectively. There was a statistically significant difference between two groups with respect to age. The study has a slight male preponderance with only 13 (24.07%) were females and the rest 41 (75.93) were males. However, there was no significant between the two cohorts with respect to BMI (Table 1). In our study, NODATsubjects have significantly higher pre-operative insulin resistance levels (measured by HOMA-IR) than non-NODAT subjects, p=0.021 (Table 1). Simultaneously, the beta cell function were significantly lower in the subjects in patients who developed NODAT compared to the non-NODAT subjects, p=0.007 (Table 1). Both the pre-operative and post-operative fasting plasma glucose were significantly higher in the patients who developed NODAT, p=0.032 and p<0.001 respectively (Table 1). Tacrolimus levels were significantly higher in the NODAT patients, however, no significant difference was found with regards to induction ATG received (0.96) and hepatitis C virus status (0.62) (Table 1).   

Discussion

According to International Consensus Guidelines on NODAT, 2003 recommendations, American Diabetes Association (ADA) criteria for type 2 diabetes published in 2003 should be used for diagnosis. The guidelines recommends fasting plasma glucose (FPG) ≥126mg/dL, 2-hour post-glucose ≥200mg/dL and random plasma glucose =200mg/dL), on three or more occasions [5]. Risk of diabetes increase to nine folds in solid organ transplant recipients than their age matched controls. The incidence rates are even higher in the first six months after transplantation [6].

New onset diabetes mellitus after transplantation (NODAT) is a well-known complication reported to occur in 2% to 53% of renal transplant subjects [7]. Such a wide variation may be because of lack of a universal agreement on the definition of NODAT, the duration of follow-up, and the presence of modifiable and non-modifiable risks factors [8]. From Indian studies, the incidences of NODAT were 19.12% by Prakash J et al. [9] while Sharma A et al. [10] and Bora GS et al. [11] found incidence ofNODAT was 16.75% and 54.5%, respectively. So there is wide variation among incidence. In our study the incidence of NODAT is 33.33%. Out of 18, 15 (83.33%) were male and 3 (16.67%) were female, which is asserting with the existing results. In one of the recent Indian studies by Prakash J et al. [9], mean age of NODAT was 40.4 and in non-NODAT was 31.13 [9]. Similar finding was found in our study, mean age of the subjects was 46±10.33 years and 32.14±13.67 years in NODAT (n=18) and Non-NODAT (n=36) cohort respectively. There was a statistically significant difference between two groups with respect to age.

Obesity independently correlates with the development of NODAT [12,13]. An analysis of 15,309 patients using the Organ Procurement and Transplant Network/United Network for Organ Sharing (OPTN/UNOS) database found that the risk of NODAT increased 1.4-fold for those with a BMI of 25 to 30 and nearly doubled if the BMI was >30 [14]. Our study results didn���t find any significant difference in BMI between the NODAT (19.33±3.08) and non-NODAT cohort (19.99±3.45). The primary reason for not getting any significant difference is that all of the included patients had a low BMI, primarily attributable to the poor socio-economic status of our country.

According to International Consensus Guidelines on NODAT, 2003, the guidelines also recommends to preferred FPG test for diagnosing NODAT [7]. The subjects with diabetes and NODAT cohort showed increased fasting blood glucose levels, whereas normal cohort subjects were well within the normal limits [15,16]. Our study results were also providing evidence in the same line where the subjects who developed NODAThad significantly higher level of pre-operative fasting plasma glucose and post-operative fasting plasma glucose.

Consequently, high incidences of de novo hyperglycemia immediately after transplantation have been reported. This may be associated with the exposure of pancreatic β-cells to several stress factors, collectively the surgical procedure, weight gain due to physical inactivity immediately after surgery (insulin sensitivity), high doses of corticosteroids and initiation of calcineurin- inhibitor (CNIs) [17]. The underlying mechanism of development of NODAT can be classified into insulin resistance and defect in insulin secretion [7]. Preoperative impaired glucose tolerance generally identifies transplant candidates who are at higher risk for the development of NODAT. This was supported by one study in which impaired glucose tolerance was identified in 18 percent of non-diabetic patients prior to transplantation. Among 31 patients who developed NODAT after transplantation, 16 (52 percent) had impaired glucose tolerance pre-transplant [3]. In multivariate analysis, pre-transplant impaired glucose tolerance was associated with the development of NODAT (RR 2.4, 95% CI 1.1-5.3) [18,19]. Thus corroborating with the previous findings, the present study demonstrates that pre-operative insulin resistance (as measured by HOMA-IR) is significantly higher in the NODAT than non-NODAT cohort.

NODAT is consistent with type 2 diabetes and responds to the usual anti-diabetes agents. However, severe hyperglycemia during the early post-transplant period may necessitate the use of insulin. Also, high-dose glucocorticoid therapy for induction of immunosuppression (or treatment of acute rejection) may require the use of insulin therapy for glycemic control. After hospital discharge, close monitoring of blood glucose during the first month and every three months for the first year is recommended [17]. In the present study, tacrolimus levels were also significantly higher in the NODAT cohort as compared to the non-NODAT cohort. Thus from the above discussion, in the present study, tacrolimus levels, pre-operative insulin resistance levels and beta cell function were all significantly implicated in the development of NODAT.   

Conclusion

The incidence of NODAT is quite high in our renal transplant patients. Risk of development of post-transplant diabetes was more closely related to traditional risk factors namely age, pre-operative fasting plasma glucose, post-operative plasma glucose, pre-operative insulin resistance and immunosuppressive therapy.   

Limitations

The study has many limitations and the results should be interpreted in view of the limitations. As with any observational study, this study lacks the vigilance of a controlled environment and adverse events are under reported. Larger and more comprehensive trials are required to establish and further validate our findings.

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[justanothersyscourse]

Hi! On anon for my safety, but I saw the ISSTD tweeted smth on the etiology of DID and I wanted to know your thoughts on it? Mostly for processing’s sake as well, as I can struggle with understanding studies now and then

The link to the paper! http://ow.ly/r40x30mZF79

The paper is Revisiting the etiological aspects of dissociative identity disorder: a biopsychosocial perspective. A very good one that I recommend to anyone interested in the causation of DID! I don't think I can do it justice if I tried to summarize the entire thing, so I'll just write down some bullet points of things I found interesting:

What is DID?: 

DID is a complex, posttraumatic, developmental disorder that is caused by trauma in childhood (usually very early childhood).

What causes DID?:

DID arises when a child’s ability to develop an ordinary sense of self in relation to others is impeded by unintegrated trauma.

Emotional neglect by parents and/or siblings is the strongest predictor of DID (and any other dissociative disorder).

More covert trauma such as dysfunctional communication in families or subtle emotional neglect can lead to milder presentations DID.

DID VS PTSD:

Switching between alters is considered to be a more elaborated version of PTSD intrusions & avoidance.

People with PTSD & DID generally experience the same amount of feeling shame, betrayal, self-blame, anger and fear.

People with DID tend to experience more feelings of alienation, loneliness, and disconnection than people with PTSD.

DID VS normal experiences:

The human mind is naturally made up of multiple interconnected “modes” that make up their whole self.

Trauma & dissociation causes modes to become decoupled and start existing in smaller, isolated pockets.

In DID, the modes have become so disconnected that individual modes start functioning as if they, independently from each other, are the whole self.

In a non-DID brain, new modes are always being created and old modes are always being updated.

In DID, this process is impaired. New modes are created in a disjointed way, and old modes don't get updated correctly if at all.

[thelifeofchuckmovie]

“The Life of Chuck” is closing a distribution deal with Neon after winning Toronto Film Festival’s prestigious people’s choice award.

TIFF’s audience prize has historically been a reliable predictors of eventual Oscar success. It’s unclear if that’ll be the case this year, though “The Life of Chuck” has received largely positive reviews. The film will likely be released in summer of 2025 and will receive an awards push in the fall. Terms of the deal, which has not been finalized, weren’t immediately available. A spokesperson for Neon declined to comment.

Adapted from Stephen King’s 2020 novella, “The Life of Chuck” stars Tom Hiddleston and was directed by Mike Flanagan. Billed as a “life-affirming” story about an ordinary man named Charles Krantz, the film is split into three distinct chapters that unfurl in reverse chronological order and set against the backdrop of a world that appears to be slowly crumbling. Mark Hamill, Chiwetel Ejiofor, Karen Gillan, and Jacob Tremblay co-star in “The Life of Chuck,” which has been compared to King adaptations like “Shawshank Redemption” and “Stand By Me” rather than “It” or “Pet Sematary.”

In the film, the titular Chuck has an extended dance sequence. So Hiddleston, who plays the inhibited accountant whose life is shrouded in mystery, endured a six-week crash course to learn everything from jazz, swing, polka, samba and cha-cha to quickstep and moonwalk.

“I had to do all of these technical dances, none of which I have any training in,” Hiddleston told Variety at TIFF. “There are some that came more easily than others. I found I love dancing jazz and swing. Bossa nova is a technical thing that took my hips a minute to get my head around. Polka is like a 100-meter sprint. It feels like a gallop.”

WME Independent repped “The Life of Chuck.”

Elsewhere on the festival circuit, Neon landed rights to Sean Baker’s “Anora,” which won the Palme d’Or at Cannes, as well as Mohammad Rasoulof’s “The Seed of the Sacred Fig.” The studio’s recent titles include the breakout horror hit “Longlegs,” which has grossed $100 million globally to date; “Cuckoo,” a mysterious thriller starring Hunter Schafer and Dan Stevens; and “Immaculate,” a twisted religious tale led by Sydney Sweeney.

[gatheringbones]

[“One author of the Clinical Psychology Review article was Shira Maguen, a researcher who began to think about the moral burdens of warfare while counseling veterans at a PTSD clinic in Boston.

Like most Veterans Affairs psychologists, Maguen had been trained to focus on the aftershocks of fear-based trauma—IED blasts that ripped through soldiers’ Humvees, skirmishes that killed members of their unit. The link between PTSD and such “life-threat” events was firmly established. Yet in many of the cases she observed, the source of distress seemed to lie elsewhere: not in attacks by the enemy that veterans had survived, but in acts they had observed or carried out that crossed their own ethical lines.

Soldiers were not, of course, the only people who risked committing such transgressions. All of the counselors I interviewed at the Dade Correctional Institution struggled with inner conflicts related to horrifying things they’d witnessed but failed to prevent. What kind of person was she? Lovita Richardson wondered after seeing a prisoner bound to a chair get bludgeoned and not intervening to help him. “Why didn’t I do more?” Harriet Krzykowski asked herself after learning about the “shower treatment.” Many of the prison guards I’d interviewed had alluded to incidents where they’d done things they knew they shouldn’t, as when Bill Curtis slammed a man to the ground, nearly fracturing his skull. Moral injuries were an occupational hazard for anyone whose job involved “perpetrating, failing to prevent, or bearing witness to acts that transgress deeply held moral beliefs.” For most dirty workers, that is.

Among the veterans she counseled, Maguen grew particularly interested in the emotional toll of killing, which was sanctioned in the military but not when defenseless civilians were involved. “I was hearing about experiences where people killed and they thought they were making the right decision,” she told me, “and then they found out there was a family in the car.” To find out how heavy the burden of killing was, Maguen began combing through the databases in which veterans of conflicts dating back to the Vietnam War were asked if they had killed someone while in uniform. In some cases, veterans were also asked whom they killed—combatants, prisoners of war, civilians. Maguen wanted to see if there might be a relationship between taking another life and debilitating consequences like alcohol abuse, relationship problems, outbursts of violence, PTSD. The results were striking: even when controlling for different experiences in combat, she found, killing was a “significant, independent predictor of multiple mental health symptoms” and of social dysfunction.

Later, when she started directing a mental health clinic at a VA hospital in San Francisco, Maguen convened groups where veterans came together and talked about the killing they had done. In the VA no less than in the military, this was a taboo subject, so much so that clinicians often referred to it euphemistically, if at all. To ease the tension, a scene from a documentary was shown at the beginning of each session in which a veteran said, “Out there, it’s either kill or be killed. Nothing can really prepare you for war.” Afterward, Maguen would ask the veterans in the room a series of questions about how killing had impacted their lives. Some reacted angrily. Others fell silent. But many seized the opportunity to talk about experiences they later told Maguen they had never spoken about with anyone, not even their spouses and family members, for fear of being judged.

The veterans in Maguen’s groups didn’t talk a lot about fear and hyperarousal, emotions linked to PTSD. Mostly, they expressed self-condemnation and guilt. “You feel ashamed of what you did,” one said. Others described feeling unworthy of forgiveness and love. The passage of time did little to diminish the depth of these feelings, Maguen found. Geographic distance didn’t lessen them much either. Maguen recounted the story of a pilot who was haunted by the bombs he had dropped on victims far below. What troubled him was, in fact, precisely his distance from them—that instead of squaring off against the enemy in a fair fight, he had killed in a way that lacked valor. Obviously not all pilots felt this way. But the story underscored the significance of something Maguen had come to regard as more important than proximity or distance in shaping moral injury—namely, how veterans made sense of what they had done. “How you conceptualize what you did and what happened makes such a big difference,” she said. “It makes all the difference.”

Unlike PTSD, moral injury was not a medical diagnosis. It was an attempt to capture what could happen to a person’s identity and soul in the crucible of war, which is why it struck a chord among veterans who did not feel their wounds could be reduced to a medical disorder. “PTSD as a diagnosis has a tendency to depoliticize a veteran’s disquietude and turn it into a mental disorder,” observed Tyler Boudreau, a marine officer who served in Iraq and came back haunted by doubts about the war’s morality. “What’s most useful about the term ‘moral injury’ is that it takes the problem out of the hands of the mental health profession and the military and attempts to place it where it belongs—in society, in the community, and in the family—precisely where moral questions should be posed and wrangled with. It transforms ‘patients’ back into citizens and ‘diagnoses’ into dialogue.”]

eyal press, from dirty work: essential labor and the hidden toll of inequality in america, 2021

[231025]

Hi dear I wanted to ask something I dont want to disrespect anyone it just alot of readers says that bts v is cheating type like he will cheat hus spouse will he do that us he that type of person to cheat? Thank you for yur time and effort 🎀✨️

"Hi I wanted to request a readig alot of predictors said taehyung might cheat on his spouse or there is a tendency for it can you do reading on will he cheat on his future spouse or he is dearly committed to them thank you"

is he the type to cheat on his partner? - generally, i would say no. he is the type to refuse all kind of offers indifferently. he might sometimes fantasize about it but in the end it's not worth pursuing to him. he himself has bitter experiences with being cheated on. he is not really the type to make a move on someone. if he cheats it's already a sign that the relationship is dying over - it's just not the necessary communication happening and they're just delaying the break up. it just causes stress, tension and conflict he hates it - this is weird but i think that ppl (exes) in the past accused him of cheating without even listening to him and because he was so irritated (hurt) he just lied and said yes as he felt like 'them accusing him is already a sign that they don't trust and love him, why should he even explain himself", i also kinda got the vibe that he is or was the type that would cheat out of spite/grudge (if his s/o cheated or betrayed him first) but it would never be emotionally only physically or mentally (?). idk the energy just turned rly messy lol some unresolved feeling here... someone did him dirty damn...

will he cheat on his fs? - ok sit tight girlies. there will be some type of cheating happening, some betrayal of trust, okay. it might not be the typical sleeping with another woman thing but something else... and it's kinda happening… on accident? HOLD UP i know this is the lousiest excuse but let me explain: imagine the following situation... the relationship is experiencing a down moment. work is not going well and they don’t have much time together. his fs - the independent queen that she is - puts all the work into improving things, she sets boundaries, puts her cold competent mask on and proceeds forward. whereas taehyung struggles with his work (or life), he is not able to just ignore it and stay composed like his fs - he needs emotional support. his fs is a workaholic and starts neglecting the emotional side of the relationship. kth feels a little left behind, finds his fs a bit cruel in those moments. HOWEVER, said boy doesn't communicate about his emotional issue. his fs is not aware - she is oblivious and totally focused on other issues. the lack of attention bothers taehyung and he misses how things were before, he feels unstable, victim mindset, indecisiveness, he loses his grip, decides he wants to do something to get the attention back, he doesn't really plan it well - short term focus - rushes into something risky, he wants to win this at all cost, him being too prideful and cowardly falls into old patterns and ends up being unfaithful - doing sth that betrays his fs' trust - and even he himself is surprised by the outcome (that he ended up being unfaithful)! she is not aware of it. it bothers him a lot, he feels remorseful and full of regrets, he end up confessing the truth to her. it turns into an intense argument, his fs is shook, she reacts harsh and cold and in turn he overreacts and gets angry, hasty and reckless -> they end up putting a pause on their relationship and separating for a while. at some point, they decided to have a real deep conversation (as they miss each other too much) and talk about all their issues and its roots and how everything turned out this way. lotss of emotions, tears and break-downs and revealing inner feelings ... they end up deepening their relationship... uhmm and also get a new pet? another child? idk the family grows lmao. it ends in peace, they reconcile, it’ll end their problems, both behave more in moderation, communication is better than before and they’re healing. the end xD

you know how taehyung's aries moon (fire) squares all his capricorn placements - once his feelings overwhelm him, he sometimes acts childishly reckless on impulse. i think his fs has probably a less emotionally expressive moon sign like ex. aquarius, capricorn, gemini or virgo (someone used to repressing their emotions). they deal with stress and emotional issues differently and this will be one of the things they both have to learn to deal with !!

[covid-safer-hotties]

Reference saved in our archive

Smaller study, but malnourished people have worse outcomes from acute covid infections. We're not gonna eat our way out of the pandemic, but making sure you eat some greens and blueberries from time to time can literally save your life.

Background: Identifying nutritional risk in COVID-19 patients poses a challenge due to the unique qualities of every nutritional screening instrument. The objective was to assess the efficacy of six nutritional scores, including the Nutritional Risk Screening 2002 (NRS-2002) score, the NUTRIC (nutrition risk in the critically ill) score, the modified NUTRIC score, the prognostic nutritional index (PNI), controlling nutritional status (CONUT) score, TCB index (TCBI), predicting prognosis of COVID-19 patients.

Methods: Clinical data were collected from COVID-19 patients admitted to the First Affiliated Hospital of Wenzhou Medical University between December 2022 and February 2023. Participants in this research were divided into two groups: all patients and those specifically from the intensive care unit (ICU). Each group was further stratified into two groups: survivors and non-survivors.

Result: 506 COVID-19 patients and 190 COVID-19 patients in intensive care unit (ICU) were evaluated. In all COVID-19 patients, we found that NRS-2002 (p < 0.001) and TCBI (p = 0.002) were statistically significant independent predictors in multivariate analyses, while APACHE II score (p = 0,048) and the mNUTRIC score (p = 0.025) were statistically significant independent predictors in multivariate analyses in ICU patients. The NRS-2002 demonstrated a higher AUC value (0.687) than other nutritional scores in all patients, with an optimum cut-off value of 3, translating into a corresponding sensitivity of 66.2% and specificity of 68.7%. With an optimum cut-off value of 4, the mNUTRIC score demonstrated a higher AUC value (0.884) in ICU patients, resulting in a sensitivity of 88.4% and a specificity of 76.9%. By using the discrimination and clinical application (DCA) curve, NRS-2002 demonstrated the greatest net benefit in all patients, while NUTRIC score and mNUTRIC score offered the more significant overall advantage than other nutritional scores in ICU patients. Kaplan–Meier analyses showed lower survival rates in patients in low nutritional risk.

Conclusion: Malnutrition was common in COVID-19 patients. The mNUTRIC score and NRS-2002 were, respectively, more effctive scoring systems of prognosis in all COVID-19 patients and severe or critical COVID-19 patients of the intensive care unit (ICU).

[datasciencewithmohsin]

Simple Linear Regression in Data Science and machine learning

Simple linear regression is one of the most important techniques in data science and machine learning. It is the foundation of many statistical and machine learning models. Even though it is simple, its concepts are widely applicable in predicting outcomes and understanding relationships between variables.

This article will help you learn about:

1. What is simple linear regression and why it matters.

2. The step-by-step intuition behind it.

3. The math of finding slope() and intercept().

4. Simple linear regression coding using Python.

5. A practical real-world implementation.

If you are new to data science or machine learning, don’t worry! We will keep things simple so that you can follow along without any problems.

What is simple linear regression?

Simple linear regression is a method to model the relationship between two variables:

1. Independent variable (X): The input, also called the predictor or feature.

2. Dependent Variable (Y): The output or target value we want to predict.

The main purpose of simple linear regression is to find a straight line (called the regression line) that best fits the data. This line minimizes the error between the actual and predicted values.

The mathematical equation for the line is:

Y = mX + b

: The predicted values.

: The slope of the line (how steep it is).

: The intercept (the value of when).

Why use simple linear regression?

click here to read more https://datacienceatoz.blogspot.com/2025/01/simple-linear-regression-in-data.html

[contentment-of-cats]

The close of the year

It's grey and cloudy, and will rain later. My titanium in the right arm is an accurate predictor. I remember I once could not imagine breaking my 'good' arm, but after the fall and surgery I had to reimagine the world around me from wiping my butt onwards.

From October of that year and through my surgeries and recovery, I was not only surviving cancer but learning to navigate a changed world, but navigating as a person profoundly changed in physical ability, but with a changed soul. I did not become left-handed, or even ambidextrous, but my left arm and hand learned. Learned imperfectly, but well enough to do the job. Even two years after, I still work left-handed or left armed from habit on certain things.

A friend tells me they can't wrap their head around that I did this and cancer without a caretaker at my side. That I flew this one solo, that I essentially danced as every character in Swan Lake. And to me this was normal, my lifelong normal from the time Gran went away. I went from a beloved child to a feral teen, the way that a beloved pet is thrown out after the owner dies or goes into 'the home.' I felt that way about my gran's absence, the hole left in me when she was not longer there. My mother's attitude was a snarky and smug 'you're so smart, you figure it out' only to shred me when I, age 13, could not figure it out.

I fumbled and faceplanted my way into and through adulthood, loved not wisely but too well, and managed. I have to wonder would have become of me, what I would have become if I had not learned this imperfect independence, this gritted teeth and bowed into the wind survival. Could I have made it? What could have become of me if someone did not figure it out for me, but with me? On the other hand, given the agony I saw other caregivers go through at the cancer center, given what I have gone through as I lost pieces of my heart with friends' passing, how could I ask anyone to assume the agony?

*waves hands and turns on the mental stove vent*

Beanie is recovering from her surgery very well and will have her stitches taken out tomorrow. Gone will be the hated onesie! I'm giving her loads of food and she sleeps a lot - so did I in the back when as I recovered. I am her caregiver now. Veterinary oncology in December and metronomic chemo - per oral and at home.

I've been looking at new sofas as the one currently under my butt is 21 - enough to drink here in the US. It's an excellent quality frame, and has held up well, but at this point it costs more to refurbish than to buy new. I want something softer and deeper. More loungy and less company.

Distance from any given event, gives perspective. The ongoing journey lets me look back, sorting years and experiences, doing a kind of mental housecleaning. Most everyone's dead anyway, and that in itself is freeing. I am not glad of their deaths insomuch as they are no longer suffering with the maladies that brought them to the doors, but I am free of the relentless effort of being the black sheep. It sounds fucking horrible, though.

[religion-is-a-mental-illness]

https://www.adl.org/resources/report/antisemitic-attitudes-america-2024

By: Center for Antisemitism Research

Published: Feb 29, 2024

Executive Summary

In the months since the October 7th, 2023, terrorist attack in Israel, the global Jewish community has witnessed an increase in antisemitic activity, unprecedented in recent years. For many in and around Jewish communities, this period has felt inherently different, a sentiment that has raised several critical questions about the current scope, nature, and implications of antisemitism.

To explore this, the ADL Center for Antisemitism Research has collected data since October 7th related to the scale and structure of the phenomenon of antisemitism in the United States and compared results to past findings.

This study of 4,143 Americans, fielded between January 5th and January 18th, 2024, (with a margin of error of approximately 1.5%) found the following trends:

Anti-Jewish trope beliefs continue to increase, and younger Americans are showing higher rates.

From 2022 to 2024, the average number of anti-Jewish tropes endorsed by Americans increased from 4.18 to 4.31 out of 14. Using the original 11 statements comprising the ADL Index, agreement with 6 or more anti-Jewish tropes increased from 20% of the U.S. population in 2022 to just under 24% in 2024.

In a reversal of past trends, younger Americans are more likely to endorse anti-Jewish tropes, with millennials agreeing with the greatest number of anti-Jewish tropes on average, at 5.4. They’re followed by Gen Z at 5, Gen X at 4.2, and Baby Boomers at 3.1.

In addition to individual attitudes, more than 42% of Americans either have friends/family who dislike Jews (23.2%) or find it socially acceptable for a close family member to support Hamas (27.2%).

Conspiratorial thinking and social dominance orientation are key predictors of anti-Jewish belief.

Belief in conspiracy theories continues to be one of the main correlates of antisemitic attitudes, with an overall average correlation of .378 with anti-Jewish trope belief. Respondents who fall in the upper quartile of conspiracy theory belief endorsed over twice as many anti-Jewish tropes, on average, as those with the least conspiracy theory belief.

Anti-Jewish belief also correlates heavily with social dominance orientation – the belief that there should be higher status groups and that they should suppress lower status groups. For example, respondents who at least somewhat agreed with the statement that some groups of people are inferior to other groups were 3.6 times more likely to fall in the top quartile of anti-Jewish trope belief compared to those who did not.

There was also a strong relationship with the belief that the problems in the world “come down to the oppressor vs the oppressed.” Those who at least somewhat agreed with this belief were 2.6 times more likely to fall in the top quartile of anti-Jewish trope belief compared to those who disagreed with the statement.

A significant percentage of Americans hold anti-Israel positions, but also support a Jewish state’s right to exist.

Significant percentages of Americans hold certain anti-Israel positions, such as 20.1% who expressed support for removing Israeli products from a local grocery store and 30.4% who said supporters of Israel control the media. Younger Americans take these positions at significantly higher rates.

However, support for an independent Jewish state remains high, with 88.8% saying Jews have the right to an independent country. This is true even among those who take other anti-Israel positions. For example, 83.8% of people who believe that Israelis intend to cause as much suffering to Palestinians as possible believe that there should be a Jewish state.

October 7th and the ensuing Israel-Hamas war has not resulted in major changes in the percentage of Americans who hold anti-Israel positions.

However, in just about every anti-Israel position assessed, increased polarization appears evident. The proportion of respondents strongly agreeing or strongly disagreeing with Israel-related policies grew from the summer of 2023 to the present, whereas the proportion of those who somewhat agreed or somewhat disagreed shrank.

Individuals who held negative attitudes toward Israel-related policies, Israeli people, and Israel-oriented conspiracy theories were significantly more likely to believe anti-Jewish tropes.

Respondents not comfortable buying products from Israel were 3.4 times more likely to be among the top quartile of believers in anti-Jewish tropes.

Respondents who do not think Jews have the right to an independent country were 3.7 times more likely to be among the top quartile of believers in anti-Jewish tropes.

Respondents who believe Israelis intend to cause as much suffering to Palestinians as possible were 4.6 times more likely to be among the most antisemitic Americans.

Respondents who believe Israeli operatives are secretly manipulating US national policy through AIPAC or other influence tools were 7.5 times more likely to be among the top quartile of believers in anti-Jewish tropes.

Views of Hamas are also deeply concerning, with more than half of Gen Z expressing some degree of comfort being friends with a Hamas supporter.

[ Continued... ]

[crystalsenergy]

Solar Return Charts - what do they mean?

A reader asked me: "I really want to know more about Solar Returns charts. Are they predictors? Are they outlines? How can I read my own chart? How can I use it for my next year?"

Thanks for you question! 🧡🦋

Solar Return charts can be seen as prediction charts, but without determinism, in the sense of "this will definitely happen, there's no escaping it." It's a type of chart with very strong tendencies for the next year, which is why it's so valid to look at it to understand your personal year.

*SR = Solar Return

How to use it: Well, not everything in the Solar Return chart necessarily needs to be deeply explored, as not everything will manifest in our personal year (or if it does, it may represent subtle points that we won't notice).

So, here are some tips on what to focus on:

-> The Ascendant of the SR chart, which will represent your primary approach for that year. The Ascendant represents your behaviors for the year, how you will deal with the year, your temperament, and your energy to initiate things.

Example: Aries rising in SR chart means a great desire to achieve - unless other points directly conflict with this -, energy to act, to lead, the temperament becomes more impatient, the year seems more hectic, because from the inside this is how you are manifesting yourself . from the negative side, means stress, anxiety, immediacy, impatience, intensity; on the positive side, energy to act, assertiveness, willingness to get out of place, focus on achieving and having independence.

-> See which areas of your life (natal chart) will be most affected by the Solar Return. Do this by comparing SR chart with your natal chart.

What aspects exist between them?

Which natal houses will be impacted by the planets in the Solar Return chart. Is there a stellium? The matters related to this/these house(s) will be very strong in your year, and the way in which this will happen will be defined based on the planets/points involved.

How to read it: I have some posts here about reading Solar Return charts, a kind of "do it yourself" when it comes to interpreting your chart.

If you have more questions, feel free to ask! I'm answering as best as I can <3

[rjzimmerman]

Excerpt from this story from Inside Climate News:

This year is likely to bring two seemingly incongruous milestones. Sales of electric vehicles will hit an all-time high, and so will global oil consumption. It is as if the transition away from fossil fuels is moving faster than ever while barely gaining ground.

In fact, experts say, adoption of electric vehicles, or EVs, is accelerating more quickly than many people expected, despite some recent setbacks. Government subsidies and mandates in China, the United States and Europe have begun noticeably shifting sales of new cars, trucks and buses. Last year, nearly one in five new cars sold in the world was electric, according to the International Energy Agency, or IEA.

Yet oil demand has continued to climb nonetheless and now sits around 100 million barrels per day, underscoring how difficult it will be to shift the world’s engines away from fossil fuels fast enough to avoid more extreme climate warming.

“Under current policies, EVs are not an existential threat to global oil demand, not even close,” said Daniel Raimi, a fellow at Resources for the Future, an environment and energy research institute. “If we’re going to achieve our long-term climate goals we need additional public policies and technological innovation to get us where we need to go.”

Oil demand has grown faster than expected over the last couple of years, according to the IEA, and is now slightly higher than it was before the COVID-19 pandemic hit. And while the agency expects demand will peak before the end of the decade, oil consumption could remain strong for decades without new subsidies or mandates for electric vehicles.

The IEA’s “Stated Policies Scenario,” which aims to model what would happen under national policies that have already been adopted, foresees oil consumption declining only 3 percent by 2050.

But many experts say the IEA’s modeling fails to capture how quickly the world is changing. The Stated Policies Scenario, for example, is already out of date: It did not include the emissions rules for cars and trucks adopted by the Biden administration in March. Those rules are expected to speed adoption of electric and plug-in hybrid vehicles, which made up about 9 percent of new car sales last year, according to Wards Intelligence. EVs and plug-in hybrids are now expected to cut gasoline and diesel consumption by the equivalent of 2.7 million barrels per day by 2050, or about 14 percent of U.S. oil consumption, according to the Environmental Protection Agency.

China, the global leader in electric vehicle sales, hit its 2025 target three years early. Last year, 37 percent of new cars sold in that country were electric, according to Raymond James, a financial firm. 

This year, that figure could climb to 45 percent of new car sales in China, according to the IEA.

A report last year by RMI, an energy research institute, said these accelerating adoption rates are a better predictor of the future. Falling battery costs, increased policy support and shifting consumer attitudes could mean that electric vehicles will account for more than 60 percent of new vehicle sales globally by 2030, the report argued.

This more rapid adoption would mean that oil demand could start falling faster than current policies would suggest. The IEA has developed a separate modeling scenario based on countries’ broader climate and net-zero targets, independent of whether they are backed yet by specific policies, and determined that oil consumption would fall by nearly 8 percent by 2030 if nations were to meet these goals. By 2050, oil demand would be cut nearly in half.

That shift is not a foregone conclusion. Some oil companies have remained bullish on demand for their core product, and continue to resist policies that would speed adoption of electric vehicles.

[gayofthefae]

It's the fact that all the GA I've seen is pulling for Mike to end up with El only because it's what they think Mike wants but they live for her independence eras and their favorite line of hers is "I dump your ass" and they love her friendship with Max and they feel sad for Will and hopes he gets a happy ending

LITERALLY ALL THEY HAVE TO DO IS GO "Mike doesn't want that either so we don't need to revolve it around him" and they'll be like oh sick enjoy Byler gang I am too

They think Mike wants El Will wants Mike and El is indifferent but really Will wants Mike El wants independence and what Mike wants isn't actually canon so the predictors are only based on the other two.

Either, way nobody really thinks Will and El are fighting over Mike. It's actually very much giving Mike the power of choice which is nice that you don't see in a lot of love triangles (*cough* he is a man *cough*), they're just assuming his choice.

[ensafomer]

a Basic Linear Regression Model

What is linear regression?

Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.

This form of analysis estimates the coefficients of the linear equation, involving one or more independent variables that best predict the value of the dependent variable. Linear regression fits a straight line or surface that minimizes the discrepancies between predicted and actual output values. There are simple linear regression calculators that use a “least squares” method to discover the best-fit line for a set of paired data. You then estimate the value of X (dependent variable)

n statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable.[1][2][3][4][5] That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variable. The adjective simple refers to the fact that the outcome variable is related to a single predictor.

It is common to make the additional stipulation that the ordinary least squares (OLS) method should be used: the accuracy of each predicted value is measured by its squared residual (vertical distance between the point of the data set and the fitted line), and the goal is to make the sum of these squared deviations as small as possible. In this case, the slope of the fitted line is equal to the correlation between y and x corrected by the ratio of standard deviations of these variables. The intercept of the fitted line is such that the line passes through the center of mass (x, y) of the data points.

Formulation and computation

[edit]

This relationship between the true (but unobserved) underlying parameters α and β and the data points is called a linear regression model.

Here we have introduced

x¯ and y¯ as the average of the xi and yi, respectively

Δxi and Δyi as the deviations in xi and yi with respect to their respective means.

Expanded formulas

[edit]

Interpretation

[edit]

Relationship with the sample covariance matrix

[edit]

where

rxy is the sample correlation coefficient between x and y

sx and sy are the uncorrected sample standard deviations of x and y

sx2 and sx,y are the sample variance and sample covariance, respectively

Interpretation about the slope

[edit]

Interpretation about the intercept

Interpretation about the correlation

[edit]

Numerical properties

[edit]

The regression line goes through the center of mass point, (x¯,y¯), if the model includes an intercept term (i.e., not forced through the origin).

The sum of the residuals is zero if the model includes an intercept term:∑i=1nε^i=0.

The residuals and x values are uncorrelated (whether or not there is an intercept term in the model), meaning:∑i=1nxiε^i=0

The relationship between ρxy (the correlation coefficient for the population) and the population variances of y (σy2) and the error term of ϵ (σϵ2) is:[10]: 401 σϵ2=(1−ρxy2)σy2For extreme values of ρxy this is self evident. Since when ρxy=0 then σϵ2=σy2. And when ρxy=1 then σϵ2=0.

Statistical properties

[edit]

Description of the statistical properties of estimators from the simple linear regression estimates requires the use of a statistical model. The following is based on assuming the validity of a model under which the estimates are optimal. It is also possible to evaluate the properties under other assumptions, such as inhomogeneity, but this is discussed elsewhere.[clarification needed]

Unbiasedness

[edit]

Variance of the mean response

[edit]

where m is the number of data points.

Variance of the predicted response

[edit]

Further information: Prediction interval

Confidence intervals

[edit]

The standard method of constructing confidence intervals for linear regression coefficients relies on the normality assumption, which is justified if either:

the errors in the regression are normally distributed (the so-called classic regression assumption), or

the number of observations n is sufficiently large, in which case the estimator is approximately normally distributed.

The latter case is justified by the central limit theorem.

Normality assumption

[edit]

Asymptotic assumption

[edit]

The alternative second assumption states that when the number of points in the dataset is "large enough", the law of large numbers and the central limit theorem become applicable, and then the distribution of the estimators is approximately normal. Under this assumption all formulas derived in the previous section remain valid, with the only exception that the quantile t*n−2 of Student's t distribution is replaced with the quantile q* of the standard normal distribution. Occasionally the fraction ⁠1/n−2⁠ is replaced with ⁠1/n⁠. When n is large such a change does not alter the results appreciably.

Numerical example

[edit]

See also: Ordinary least squares § Example, and Linear least squares § Example

Alternatives

[edit]Calculating the parameters of a linear model by minimizing the squared error.

In SLR, there is an underlying assumption that only the dependent variable contains measurement error; if the explanatory variable is also measured with error, then simple regression is not appropriate for estimating the underlying relationship because it will be biased due to regression dilution.

Other estimation methods that can be used in place of ordinary least squares include least absolute deviations (minimizing the sum of absolute values of residuals) and the Theil–Sen estimator (which chooses a line whose slope is the median of the slopes determined by pairs of sample points).

Deming regression (total least squares) also finds a line that fits a set of two-dimensional sample points, but (unlike ordinary least squares, least absolute deviations, and median slope regression) it is not really an instance of simple linear regression, because it does not separate the coordinates into one dependent and one independent variable and could potentially return a vertical line as its fit. can lead to a model that attempts to fit the outliers more than the data.

Line fitting

[edit]

This section is an excerpt from Line fitting.[edit]

Line fitting is the process of constructing a straight line that has the best fit to a series of data points.

Several methods exist, considering:

Vertical distance: Simple linear regression

Resistance to outliers: Robust simple linear regression

Perpendicular distance: Orthogonal regression (this is not scale-invariant i.e. changing the measurement units leads to a different line.)

Weighted geometric distance: Deming regression

Scale invariant approach: Major axis regression This allows for measurement error in both variables, and gives an equivalent equation if the measurement units are altered.

Simple linear regression without the intercept term (single regressor)

[edit]

[thecatchat]

Alex - 8-10 years old

@inky-kaleidascope-dimensions

I realized I don't know what 8 year Olds or 10 year Olds are like so I researched. I think 8 years old is a good starting off point for Alex.

Yah, because if each lens is roughly a year in length, and she's 8 in Azure. Teal - 9 years old. Celadon - 10 years old. Sun - 11 years old. Clementine - 12 years old. Crimson - 13 years. Obsidian - 14 years old.

Here's my notes on 8 and 10 year Olds. Got from parents.com

8 year old milestones

- Increased vocabulary, budding learner, independent reading (reading a chapter book under the covers with a flashlight), abstract thought (allow kids to work with larger numbers and conceptualize symbols), understanding how time and money works.

- balance better and move more intentionally, may enjoy roller skating, skateboarding, biking, or dancing,

- can tie their shoes, handwriting becomes smaller and neater, can open lunch items like ziploc bags.

- empathy, desire to be part of a group, increased independence and desire for privacy, ask for sleep overs but may not emotionally be able to stay the whole night.

10 year old milestone

- some start looking and acting more mature, some remain more childlike, start thinking and sounding "almost grown up", able to argue view points and opinions, effective conversationalist at dinner table,

- fifth grade, expanding research skills, may enjoy active play and team sports, art, music, reading, or getting out in nature, enjoy using electronics.

- developing greater independence, having an increased attention span, learning good judgment, showing interest in pop culture,

- growth spurts, growing pains and injuries, more complex feelings and better control over them, may struggle with keeping emotions in check,

- peer pressure can play a big role, poor peer acceptance at 10 is a strong predictor of problematic adolescence, common age to begin to show romantic interest in other kids and explore gender identity,

- admires and imitates older youth, accepts parent/family beliefs, begins to question authority, enjoys creating secret codes, games, and passwords, prefers to work in groups

- place more emphasis on physical appearance and want to conform with peers, body images issues can develop,

[anthrofreshtodeath]

Oooh. For the prompts 22. Playful arguments please!

Let's do it! I'm being romantic about summer and baseball rn so here we go.

___

Children splashed in the Talucci pool with alternating shrieks and giggles, the displacement of water creating cool air where the July sun had been only oppressive when everyone had first arrived. Jane hadn’t been around that many Italians since her cousin Rita’s wedding three years prior, and she was drunk on familiarity, on culture comforts.

And also, honestly, on beer. 

And when Jane was drunk on beer, in the summer, surrounded by Italians, she liked to argue. Good naturedly, of course, and with anyone that would give her the time of day. Tommy was up flirting with the roommate that Marisa Talucci brought over, two med school girls he had zero chance with, so it wouldn’t be him, and Frankie sat right next to Jane, but he was also drunk and when drunk he liked to laugh. So he was a no go.

That didn’t matter, however, because this Independence Day, while cousin Danny and his kid stuffed their faces at the table next to her, Jane had the perfect interlocutor right across. She pointed the rim of her half-drained bottle in that direction. “I think you’re nuts,” she said, continuing the banter she’d started a few minutes before.

Maura, who had indulged Jane because she too may have had one too many beers and one too few glasses of water, gasped. She folded her arms over her bikini top and leaned in, tossing one of the peanuts in the bowl near the center of the table at Jane’s face. It landed, and Jane’s reflexes were too delayed to stop it. Frankie bellowed out a laugh. “How could you possibly counter? OPS combines two of the most basic offensive metrics in one to provide one of the strongest predictors of production! Only the top one half of one percent of the league has a superior OPS. Every single one of those players are perennial all-stars!” Maura shouted, though the din of family fun and sizzling barbecue tempered the sharpness of it.

“I dunno Janie, I think she’s got you. Remember when Mookie led the AL in OPS? MVP caliber year,” Cousin Danny said around a mouthful of hot dog. 

“Who asked you?” Jane whipped around, motioning for him to zip it. But when she turned her sights back on Maura, she grinned wickedly. She wore her navy road alternate jersey, the one she didn’t mind getting dirty, unbuttoned over her own bikini top, simple black to Maura’s deep, rich red. She leaned back when Maura leaned in, and probably on purpose: it showed off all the musculature she worked so hard for, the musculature that often set Maura off-kilter. “Anyway, here’s what I’m saying: you have a stat that has been around since the beginning of time that basically tells you the same damn thing.”

“Oh?” asked Maura, dripping with superiority. She held back a scoff only because she wanted another sip.

Jane sucked her teeth at the daintiness of that sip. At the pink pout cradling the lip of the bottle.

“Yeah - total bases,” she said as if Maura should have thought of it before. “The more total bases the better. Ya don’t need equations or averages or any of that. Ya just need to know how many knocks a guy got and how many bases each knock counted for. I guarantee ya that tells ya as much as a guy’s slug.”

Maura paused, blinked, clearly unsure if she saw Jane’s point or if the alcohol was seeing it for her. “Well, I…”

At that moment, a particularly large twelve year old kid cannonballed into the deep end just a few feet away, and the water on everyone’s feet at the table gave Jane a wet idea. “Wanna bet? Let’s go inside. I know Carla’s got the family computer in Marisa’s old room. We can do a whole spreadsheet right. Fuckin’. Now.” 

Maura dropped her mouth open at the audacity, and then at the implication. They’d be alone. In a bedroom. Collecting data sets. Arguing. “I do want to bet. Lead the way.”

Frankie only rolled his eyes when they shot up from the table and burst through the sliding glass door to the house. Another beer it was, then.

[compneuropapers]

Interesting Papers for Week 25, 2024

Silencing CA1 pyramidal cells output reveals the role of feedback inhibition in hippocampal oscillations. Adaikkan, C., Joseph, J., Foustoukos, G., Wang, J., Polygalov, D., Boehringer, R., … McHugh, T. J. (2024). Nature Communications, 15, 2190.

A multi-demand operating system underlying diverse cognitive tasks. Cai, W., Taghia, J., & Menon, V. (2024). Nature Communications, 15, 2185.

A view-based decision mechanism for rewards in the primate amygdala. Grabenhorst, F., Ponce-Alvarez, A., Battaglia-Mayer, A., Deco, G., & Schultz, W. (2023). Neuron, 111(23), 3871-3884.e14.

Local and global predictors of synapse elimination during motor learning. Hedrick, N. G., Wright, W. J., & Komiyama, T. (2024). Science Advances, 10(11).

Laminar evoked responses in mouse somatosensory cortex suggest a special role for deep layers in cortical complexity. Hönigsperger, C., Storm, J. F., & Arena, A. (2024). European Journal of Neuroscience, 59(5), 752–770.

Synaptic wiring motifs in posterior parietal cortex support decision-making. Kuan, A. T., Bondanelli, G., Driscoll, L. N., Han, J., Kim, M., Hildebrand, D. G. C., … Lee, W.-C. A. (2024). Nature, 627(8003), 367–373.

Organization of reward and movement signals in the basal ganglia and cerebellum. Larry, N., Zur, G., & Joshua, M. (2024). Nature Communications, 15, 2119.

Autokinesis Reveals a Threshold for Perception of Visual Motion. Liu, Y., Tian, J., Martin-Gomez, A., Arshad, Q., Armand, M., & Kheradmand, A. (2024). Neuroscience, 543, 101–107.

Temporally organized representations of reward and risk in the human brain. Man, V., Cockburn, J., Flouty, O., Gander, P. E., Sawada, M., Kovach, C. K., … O’Doherty, J. P. (2024). Nature Communications, 15, 2162.

Neural timescales reflect behavioral demands in freely moving rhesus macaques. Manea, A. M. G., Maisson, D. J.-N., Voloh, B., Zilverstand, A., Hayden, B., & Zimmermann, J. (2024). Nature Communications, 15, 2151.

Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex. Moon, H.-J., Albert, L., De Falco, E., Tasu, C., Gauthier, B., Park, H.-D., & Blanke, O. (2024). Proceedings of the National Academy of Sciences, 121(12), e2315758121.

Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex. Muhle-Karbe, P. S., Sheahan, H., Pezzulo, G., Spiers, H. J., Chien, S., Schuck, N. W., & Summerfield, C. (2023). Neuron, 111(23), 3885-3899.e6.

A persistent prefrontal reference frame across time and task rules. Muysers, H., Chen, H.-L., Hahn, J., Folschweiller, S., Sigurdsson, T., Sauer, J.-F., & Bartos, M. (2024). Nature Communications, 15, 2115.

Interactions between circuit architecture and plasticity in a closed-loop cerebellar system. Payne, H. L., Raymond, J. L., & Goldman, M. S. (2024). eLife, 13, e84770.

Functionally refined encoding of threat memory by distinct populations of basal forebrain cholinergic projection neurons. Rajebhosale, P., Ananth, M. R., Kim, R., Crouse, R., Jiang, L., López-Hernández, G., … Talmage, D. A. (2024). eLife, 13, e86581.

Functional architecture of dopamine neurons driving fear extinction learning. Salinas-Hernández, X. I., Zafiri, D., Sigurdsson, T., & Duvarci, S. (2023). Neuron, 111(23), 3854-3870.e5.

Neural attentional filters and behavioural outcome follow independent individual trajectories over the adult lifespan. Tune, S., & Obleser, J. (2024). eLife, 12, e92079.3.

Coordinated head direction representations in mouse anterodorsal thalamic nucleus and retrosplenial cortex. van der Goes, M.-S. H., Voigts, J., Newman, J. P., Toloza, E. H., Brown, N. J., Murugan, P., & Harnett, M. T. (2024). eLife, 13, e82952.

Specific rules for time and space of multisensory plasticity in the superior colliculus. Wang, L., Xin, H., Buren, Q., Zhang, Y., Han, Y., Ouyang, B., … Dong, C. (2024). Brain Research, 1828, 148774.

Structural constraints on the emergence of oscillations in multi-population neural networks. Zang, J., Liu, S., Helson, P., & Kumar, A. (2024). eLife, 12, e88777.3.