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Introduction mabiDay is an exciting new project that showcases the power of modern web development technologies in creating a responsive and user-friendly interface for interacting with the recently released Mabinogi API. This technical blog post will delve into the architecture and key features of mabiDay, highlighting how it utilizes Next.js 14, shadcn UI components, Vercel hosting, and Bun as a runtime to deliver a seamless user experience. Tech Stack Overview Next.js 14: The latest version of the React framework, providing server-side rendering, routing, and API routes. shadcn UI: A collection of re-usable components built with Radix UI and Tailwind CSS. Vercel: A cloud platform for static and serverless deployment, offering seamless integration with Next.js. Bun: A fast all-in-one JavaScript runtime, used here as an alternative to Node.js. Key Features 1. Responsive Design mabiDay employs a mobile-first approach, ensuring that the application is fully functional and aesthetically pleasing on both desktop and mobile devices. This is achieved through: Tailwind CSS for responsive layouts Custom components that adapt to different screen sizes (e.g., sidebar for desktop, dropdown menu for mobile) 2. Real-time API Integration The application fetches data from the Mabinogi API in real-time, allowing users to search for items and view detailed information. Key aspects include: Asynchronous data fetching using fetch API State management with React hooks (useState, useEffect) Dynamic query parameter generation for API requests 3. Advanced Search and Filtering Users can search for items using various criteria: Text-based search for item names Category filtering

In recent years, the debate around carbohydrates, insulin, and their role in obesity has taken center stage in the world of nutrition. One popular theory claims that high carbohydrate intake triggers insulin secretion, which leads to fat storage and weight gain—this is known as the Carbohydrate-Insulin Model of Obesity. But how valid is this claim? Today, we'll dive deep into the science behind this controversial topic and explore why the simplistic notion of "insulin makes you fat" may be misleading. The Insulin-Carbohydrate Connection: Myth or Fact? The Carbohydrate-Insulin Model suggests that insulin, a hormone released after consuming carbohydrates, drives fat storage. This theory is based on the fact that insulin is lipogenic (i.e., it encourages the storage of fat) and lowers blood sugar levels, potentially triggering hunger. However, despite some theoretical support, real-world evidence pokes holes in this idea. Theoretical Problems with the Carbohydrate-Insulin Model While insulin does play a role in fat storage, it doesn’t tell the whole story. Insulin’s role is anabolic—it builds up tissues by shuttling nutrients into cells, including muscle and fat. The catch? Insulin can’t lead to weight gain without a calorie surplus. In other words, unless you’re consuming more calories than you’re burning, it’s nearly impossible for insulin to create net body fat gains. Endogenous and exogenous insulin have distinct effects on hunger hormones. Endogenous insulin, produced naturally by the body, tends to help regulate hunger by promoting a feeling of fullness. In most cases, it doesn't lead to a noticeable increase in hunger levels. On the other hand, exogenous insulin, which is injected or administered externally, can cause a sharp drop in blood sugar, triggering a rebound effect that stimulates hunger. This distinction is crucial because many people mistakenly believe that all insulin spikes drive hunger, when in reality, it's primarily the exogenous form that creates this feedback loop. Another problem with the model is that it ignores dietary fats, which are often consumed alongside carbohydrates. Foods like pizza and ice cream are high in both fat and carbs, making them highly lipogenic—yet these are the foods most associated with weight gain, not simple carbohydrates like fruits or whole grains. Real-World Evidence: Carbs vs. Fats In controlled studies, researchers compared high-carbohydrate, low-fat diets to high-fat, low-carbohydrate diets. The results? As long as calorie intake is the same, both diets lead to similar weight loss or gain. This means that insulin spikes from carbohydrates don't result in more fat gain compared to fats themselves. So, what actually causes weight gain? Overeating, especially on highly palatable and calorie-dense foods, regardless of whether they are high in carbs or fats. Most lipogenic foods aren't even high glycemic index (GI) foods! Pizza, ice cream, and cookies are loaded with fat and have moderate or low GI, which means they don’t spike blood sugar as much as people assume. Also, certain foods known to be insulinergic, like yogurt, skim milk, etc., do cause a spike in insulin, but they are unique in that they don’t lead to a subsequent drop in blood sugar. This is because the body counteracts the insulin spike with glucagon secretion. Glucagon, a hormone that raises blood sugar, signals the liver to release stored glucose into the bloodstream. This balancing mechanism ensures that despite the insulin increase, blood sugar remains stable. As a result, these foods do not trigger the hunger rebound often associated with sharp drops in blood sugar, making them less likely to contribute to overeating. The Role of Palatability and Overeating Perhaps the biggest driver of obesity is food palatability. Junk foods, which are typically high in both fat and sugar, are designed to taste good, making it easy to overeat. Foods like cookies, pizza, and ice cream stimulate the brain’s reward system, causing us to eat more even when we’re not hungry. This overeating leads to excess calorie intake, which is the real culprit behind fat gain. The insulin-carbohydrate model doesn’t explain why people get fat on junk food, but the "palatability-reward hypothesis" does. According to this model, we gain weight because calorie-dense, highly palatable foods encourage overconsumption. Blaming insulin alone oversimplifies a much more complex issue. Conclusion: Insulin Is Not the Villain

Research Link: https://pubmed.ncbi.nlm.nih.gov/30597865/ Summary: In a short-term energy deficit, high protein intake does not provide additional satiety for resistance-trained individuals Key Findings: High protein intake did not provide additional satiety during a short-term energy deficit. There were no significant differences in satiety, hunger, or desire to eat between the two protein levels. Absolute ghrelin levels significantly decreased post-meal with the PROMOD diet. PYY levels increased after high-protein meals in both PROMOD and PROHIGH. The desire to eat was more suppressed after meals in the PROMOD diet. PROHIGH did not offer additional satiety benefits compared to PROMOD. High-protein diets do not increase satiety over the long term. Changes in ghrelin and PYY were more pronounced with the PROMOD diet. Once protein needs are met, extra intake does not significantly increase satiety. Fiber-rich carbohydrates may maintain satiety better than additional protein. Conclusion: 1.8g/kg of protein intake is sufficient to maintain satiety. High-protein diets offer no additional satiety benefits. Ghrelin and PYY responses were more favorable with the PROMOD diet. Excessively high protein intake is not effective. Fiber-rich carbohydrates are more beneficial for satiety.

Research link: https://pubmed.ncbi.nlm.nih.gov/34135111/ Summary: Fasting offers no additional benefits over calorie restriction in terms of weight loss, fat reduction, or autophagy. Key Points: Comparison of the effects of 24-hour fasting and calorie restriction on metabolism and body composition. The fasting group showed weight loss but less fat reduction. The calorie restriction group showed greater reductions in both weight and fat. The group that fasted without calorie restriction had minimal weight and fat loss. No significant difference in autophagy-related gene expression between groups. No noticeable difference in cardiovascular health or metabolic regulation markers. Continuous calorie restriction is more effective for fat loss than fasting. Fasting shows no additional metabolic or cardiovascular health advantages. Fasting is not superior to calorie restriction in inducing autophagy. Evidence suggests fasting is not a magical weight loss tool. Conclusion: Fasting leads to less fat loss compared to calorie restriction. No difference in autophagy induction between the two methods. Calorie restriction is more effective for weight loss. No major differences in cardiovascular and metabolic health markers between the two. There is insufficient evidence that fasting is superior to calorie restriction.

Weight loss fundamentally relies on maintaining a energy balance deficit, which means consuming fewer calories than your body needs. This guide provides an easy-to-follow plan, focusing on macronutrients and calorie control to support fat loss, founded on the energy-balance model of obesity. Step 1: Estimate Your Total Daily Energy Expenditure (TDEE) To manage weight effectively, understanding your Total Daily Energy Expenditure (TDEE) is essential. The equation for calculating changes in energy storage (ΔES) is as follows: ΔES = EI - [BMR + TEF + (EEex + NEAT)] ΔES = Change in body energy storage (calories) EI = Energy intake (calories consumed through food and drink) BMR = Basal Metabolic Rate (energy needed for basic bodily functions at rest) TEF = Thermic Effect of Food (energy used for digestion and metabolism) EEex = Energy expenditure from planned exercise NEAT = Non-Exercise Activity Thermogenesis (energy expended through daily movement and activities) Calculating each component precisely can be complex, so a practical approach is to use online TDEE calculators that estimate your calorie needs based on age, weight, height, and activity level. Note that each calculators will vary slightly, so make sure to use the same TDEE calculator every time. I personally use one from KetoGains. Step 2: Set Caloric Intake for Weight Loss Once you have your TDEE, aim to create a caloric deficit for fat loss. A common recommendation is reducing calorie intake by 10-20% from your TDEE. For example, if your TDEE is 2,500 kcal/day, aiming for 2,000-2,250 kcal/day could support fat loss while minimizing muscle loss. Modifying TDEE Based on Results If you're losing weight: Continue following your current plan. If you're consistently losing weight over time without significant energy loss or hunger issues, your TDEE estimate is likely accurate. Keep doing what you're doing and monitor your progress. If you're gaining weight: Don’t immediately make adjustments if you notice a short-term increase in weight. Weight fluctuations can happen due to factors like water retention or muscle gain. Continue tracking your weight and calorie intake for at least 2 weeks. If you're still gaining weight after this period, it may indicate that your calculated TDEE is higher than your actual metabolism. In this case, reduce your TDEE estimate slightly and adjust your calorie intake accordingly. For women before menopause: Weight tracking can be more complex due to hormonal fluctuations and water retention during the menstrual cycle. These changes can cause temporary increases or decreases in weight, making it harder to assess actual progress. To account for this, track your weight consistently and compare averages across menstrual cycles rather than focusing on short-term changes. This method provides a more accurate picture of weight loss over time and helps avoid unnecessary adjustments to your TDEE based on temporary water retention. Step 3: Macronutrient Breakdown for Fat Loss After determining your daily caloric target, you can plan your macronutrient intake to optimize fat loss. 1. Protein Intake Recommendation: Consume approximately 2.2g of protein per kg of body weight daily.

Yesterday's Efforts vs. Today's Goals Since I worked hard on eating yesterday, I thought I should work hard on exercising today. I focused on a lower-body routine with squats and Romanian deadlifts. After the workout, I could feel how much my muscles were stimulated—my entire body felt sore, so I treated myself to a session with the massage gun for the first time in a while. Post-Workout Incident As I was taking off my workout clothes, I heard a little "pop!" sound, and something dropped to the floor. Upon closer inspection, I realized it was my continuous glucose monitor (CGM) that had been attached to my left forearm. Yes, it had been dangling since yesterday afternoon, and it finally gave way. Still, it hung on well until the morning of day 15, so I think it did its job. Actually, my interest in tracking blood sugar has decreased, and there were a few inconveniences as well, so I was planning to remove the sensor this afternoon instead of tomorrow when it expires. But maybe it worked out for the better. No Glucose Tracking Today Since the CGM is off, there's no glucose data for today. I had an iced Americano in the morning before working out, and afterward, I had a protein shake. For lunch, I ate bulgogi, had a Zero Coke brownie as a snack, and for dinner, I ate 150g of rice with homemade chashu. By my standards, this isn't a meal that would cause a big blood sugar spike. I usually maintain this kind of diet. Since it feels like a shame to end here, let's review some past data. Glucose Tracking Recap Looking at the average blood sugar over the entire period, my fasting glucose stayed in the 80-90 range, and even after meals, my blood sugar didn't rise significantly, so the average came to 97. I'd say that's a pretty healthy number. Excluding days like yesterday when I had cheat meals, there wasn’t much variation in my blood sugar levels. Nothing particularly interesting to note. Personal Conclusions from This Experiment Here are my personal takeaways: I am sensitive to white rice. I can handle about 3/4 of a bowl per meal. My blood sugar doesn't spike much even when I consume liquid carbs after strength training.

https://pubmed.ncbi.nlm.nih.gov/37676198/ Summary Walking at least 2,600 steps a day benefits heart health and reduces mortality, with gains increasing up to 8,800 steps. Key points Walking 2,600 steps per day significantly reduces mortality. 2,800 steps lower the risk of cardiovascular disease. Mortality benefits increase up to 8,800 steps. Cardiovascular risk reduction peaks at 7,200 steps. Moderate or fast walking pace benefits mortality reduction more than slow pace. Step counts positively impact health regardless of gender. Hip-worn accelerometers provide more accurate health predictions than wrist-worn ones. Significant health improvements are observed starting at 2,600 steps compared to 2,000. Step count is a simple activity measure, but the direct causal link to health improvement isn't certain. Breaking up sedentary time by walking may be more important than a high step count. Conclusion Walking more than 2,600 steps daily reduces mortality and cardiovascular disease risk. Health benefits increase as step count rises, up to 8,800 steps. Hip-worn accelerometers provide the most accurate health risk predictions. Faster walking pace offers additional mortality reduction benefits. Consistent physical activity is more important than just aiming for a high step count.

Today, I decided to test all the foods I don’t usually eat but occasionally indulge in, all in one day. I faced an unexpected challenge as soon as I woke up. Normally, my blood sugar stays around 80–100 while I sleep, but for some reason, my sensor started warning that my blood sugar was low. Since my blood sugar couldn’t have dropped that much, please take today’s cheat day and blood sugar log with a grain of salt. I ate a vague portion of rice cakes. Someone ate more of the rice cakes I had saved for today, so I scraped together the leftovers and ended up with a half-hearted portion. Even though the sensor has been tending to report my blood sugar on the low side, it’s good at catching the peaks. I saw my blood sugar hit 200 for the first time—it was quite surprising. Maybe I ate too much? Luckily, I didn’t feel too bad or uncomfortable. My blood sugar was all over the place, rising and dropping like crazy. When I did a finger prick test to check, the discrepancy wasn’t too bad. Especially for high readings, the sensor seemed reliable. For a snack, I wanted to buy a baguette and spread some butter on it, but unfortunately, it wasn’t available yet. So I bought a coffee bun and a cheese bagel instead. Since I don’t react much to flour, my blood sugar didn’t spike much. For lunch, I went out and bought sushi. I ate 12 pieces of sushi, a roll, and some udon, then walked about 1,500 steps back home. On the way back, my blood sugar dipped once but peaked again at just 105—not as big a deal as I thought.

On weekends, I tend to skip exercising and sleep in. When I lazily woke up and checked my messages, I saw someone’s breakfast: low-carb bread with peanut butter spread on it. When I opened my fridge, I found a tortilla, so I toasted it, spread some peanut butter on it, and feeling like it was missing something, I grilled a sausage and enjoyed it. Can my blood sugar even rise... from a tortilla? For lunch, I had three and a half hamburger steaks simmered in oyster sauce, ketchup, and stevia. My blood sugar plummeted after that. When that happens, my blood sugar monitoring app sends push notifications every five minutes, nagging me that my blood sugar is low. It’s so annoying, I could scream! I’m not going to die, I get it, you stupid app! Of course, I felt totally fine. For a snack, I had an ice cream sandwich. As expected, my blood sugar rose just as much as I anticipated. Since I’ve eaten it before, it wasn’t surprising at all. For dinner, I made bulgogi in a hot pot and added 100g of high-protein noodles, which are made from wheat flour. It was noticeably different from when I used 50g. I realized once again how important portion size is. They say 100g is one serving, but for me, 50g seems like the right amount. Today’s post turned out to be rather ordinary. Nothing new, and honestly, not very exciting. I’ll be back tomorrow with an exciting cheat day story. Wishing you all a good night!

Today, I focused on a front-side routine targeting the quadriceps, chest, and shoulders. The main exercise was the barbell pause full squat, and it took much more of a mental toll than a physical one. As expected, technique-focused exercises are mentally exhausting. I dropped the back-off set at RPE 9. After the workout, I had a protein shake mixed with creatine and coffee. My blood sugar didn’t rise much during the workout; could it be related to that? My blood sugar went up by 11 after the protein shake. Then, I was hungry, so I had a snack of salami sticks and iced Americano. My blood sugar rose to 110 later because I ate dumplings. Yes, that’s right. Today's lunch was fried dumplings. I noticed them in the freezer, and I had my eye on them since last night. My blood sugar rose to 122 twice, and it didn’t drop to double digits and stabilize until three hours after eating. For dinner, I had Australian bulgogi from Costco, along with some wrap vegetables. For the sauce, I mixed store-bought gochujang with avocado mayonnaise and stevia. I was so hungry that I ate about 300g of just the bulgogi, but I still feel hungry. I’m not exactly hungry, though; my mouth just keeps craving something. I had a busy week with a lot of external plans, so it must have been a bit exhausting. I’ll take it easy and rest this weekend. Everyone, you’ve worked hard this week!

This morning, I didn’t even drink coffee and went straight into an intense backside bodybuilding-style workout. I pushed myself so hard with deadlifts that my heart rate went up to 181. Now that I’m writing this, I notice I’ve got some pretty bad bruises on my legs. I feel proud. After the workout, I went to Starbucks to try the matcha cream frappuccino recipe by the legendary Arnold Hong from the Korean bodybuilding scene. Normally, it’s quite pricey, but thanks to a gift card I received, it wasn’t too bad this time. I’m grateful for the treat. I believe this drink contains maltodextrin, but it surprisingly didn’t spike my blood sugar much. That doesn’t mean it’s safe to drink without concern, though. As far as I know, even Arnold Hong avoids it during his diet periods. Think carefully if you’ve worked out hard enough to justify drinking this! For a snack, I got some fried chicken skin from KFC. Crispy fried chicken skin is always delicious! But perhaps because it has a lot of flour, my blood sugar spiked quite a bit despite not using any sauce. Still, it stayed within double digits. At lunchtime, I had galbi (grilled short ribs) and sashimi along with about 100g of rice in Apgujeong. There was a variety of food on the table, making it a really enjoyable meal! The flavor of the galbi was especially amazing. My blood sugar rose a bit late, but it stayed at 108, and 2 hours and 15 minutes after eating, it was back within the normal range. For dinner, I had mapo tofu with beef sirloin and some rice (about 150g) at home. Since I hadn’t consumed enough protein after my tough morning workout, I was so hungry that I ate about twice my usual amount. And that’s how my day went! How was your day? I don’t have any external plans tomorrow, so I’ll probably have home-cooked meals. Have a great night, everyone!

This morning, like usual, I started my day with a workout. On an empty stomach, I focused on chest, shoulders, and triceps. I don't particularly enjoy chest exercises, so I don’t do them often. Plus, since my shoulder muscles are small, it seems like my blood sugar doesn't rise much after working them out. The workout intensity felt quite high (RPE 8). For breakfast, I kept it simple with a protein shake. My blood sugar went up a bit today, though only slightly. For a mid-morning snack, I had a salami stick and a protein bar, and I sipped on an iced Americano with three shots of espresso over a fairly long period. For lunch, I went to Euljiro with some keto friends and had dakdoritang (spicy chicken stew) and chicken salad. The food was quite sweet, and despite not eating rice, my blood sugar spiked significantly. I think it was because I had a lot of the broth. For dinner, I grilled some beef and prepared it three ways: with salt, teriyaki sauce, and stir-fried with gochujang (Korean chili paste). I enjoyed it with leafy greens and, just like yesterday, a half-serving of rice (150g). I think having half a serving of rice with a clean meal is fine. However, with a meal like today’s lunch, which wasn’t as clean and was quite sweet, I should probably avoid rice. I’m happy to have collected meaningful data today. Another day has passed without any issues! Here’s to making it through to day 15!

Summary Squatting with bands is neither effective for reducing knee valgus nor for developing glutes, and may even worsen the problem. Key Points Band use can actually increase knee valgus rather than reduce it. Evidence linking knee valgus to injury is theoretical. Knee valgus can occur in elite lifters and doesn’t necessarily indicate poor technique. Knee valgus might be a biomechanical response for efficient force transmission. Stronger bands can result in greater knee valgus. Using bands for glute development is ineffective. Squats already provide sufficient glute stimulation; bands may reduce this effect. For better glute development, separate hip abduction exercises are more effective. Bands may interfere with the development of other muscles. To avoid knee valgus, don’t forcefully pull knees inward with bands. Conclusion Knee valgus does not necessarily increase injury risk. Using bands is inefficient for reducing knee valgus. Bands are unlikely to significantly impact glute development. Squats alone provide adequate glute stimulation. Separate hip abduction exercises are more effective than using bands. Terms Knee Valgus: A condition where the knees cave inward during movements like squats, often due to muscle imbalances in the hips and legs.

Today at the gym, I worked on my back and biceps. As expected, my blood glucose went up a bit. I skipped cardio and went straight to showering, and interestingly, my glucose rose a little more during the shower. It seems like showers might have some effect on my blood glucose. After the workout, I craved a big breakfast, so I grilled 2 sausages, 2 eggs, 2 protein pancakes, and some mushrooms, along with an iced Americano. Surprisingly, my blood glucose didn’t rise at all—probably because it was already dropping, and the high-protein, high-fat meal didn’t affect it much. For lunch, I experimented with my rice portion. Normally, a full bowl of white rice spikes my blood glucose significantly, but today I had only half a bowl with sous vide beef and teriyaki mushrooms. My glucose only went up by 3 points, from 97 to 100. It seems like half a bowl doesn’t have a big impact on me, but I need to experiment more. For dinner, I had beef yukjeon, rose pasta (50g dry), and rose risotto (using half a bowl of rice). My glucose rose by 25 points during the first peak, likely due to this meal. Later, I had some fried chicken, which caused the second peak on the graph, but my glucose stabilized quickly. I still need to test how half a bowl of rice affects me. Finally, I went for a walk to get some ice cream but discovered a new place selling Korean fried chicken. I skipped the ice cream and instead bought half fried and half sweet & spicy chicken, eating about 10 pieces. It didn’t have a big impact on my blood glucose. I should freeze the leftover chicken to enjoy later.

I really pushed myself at the gym today, especially with my legs. Even though I've lost some weight and that affected my performance, I’m still happy with the effort I put in. After the workout, I had 60g of protein, 5g of creatine, and 12g of glucose, but it barely nudged my blood sugar—just from 93 to 94 at its highest. Later, I spent time with my younger sister since she doesn’t have many friends here in Korea. We had Gyukatsu for lunch. I ordered the double beef meal with a little white rice, so my blood sugar didn’t spike much. It did drop quite a bit afterward, but I didn’t really feel it. We also indulged in some buttered bread, a lemon tart, and iced Americano. The desserts were tangy and refreshing, not too sweet. Afterward, we visited an espresso bar where I had a Cafe Romano. It had sugar, and I also enjoyed the snack they served, which caused my blood sugar to peak twice at 100. For dinner, we went to Seoul Forest and had spicy pork with white rice. I finished the whole bowl, and the sweet side dishes caused my blood sugar to rise from 89 to 122. White rice really is the key player in spiking my blood sugar. My family from Australia is visiting Korea for a while, so we've been busy going around and just eating all sorts of things. I'm not thinking of it as a ruined diet; I'm just enjoying life. When I'm able to stick to a diet again, I'll just do my best then. I’m exhausted from the leg workout and all the walking today. Time to crash.

I skipped breakfast today since I slept in until 10 AM. For lunch, I went to D-Lifestyle Kitchen, which is known for its LCHF and Mediterranean meals. I mostly had pasta, rice, and bread, but my blood glucose didn’t spike much. The small rise towards the end was from a donut I had afterward (you can see this in the next photos). Later, we stopped by Knotted for dessert. I had a whole milk cream donut with an iced Americano. My blood glucose had a slow, slight increase, peaking at 90 from 78. It was surprising, and I started to think my Continuous Glucose Monitor (CGM) might not be working right. After walking around a bit, I felt hungry and had a decaf iced Americano along with a Quest protein bar. My blood glucose dropped significantly afterward, which I think might be an exaggerated result—more on that later. For dinner, I went out for Gomtang. I did a BGM test to sync with my CGM, and there was just a 6-point difference—not too bad. I was feeling off, shaky, and a bit irritable, likely because my blood glucose was low. Since the meat in the Gomtang was a bit lacking, I decided to have another protein bar. Overall, I’ve noticed that white rice really does a great job of raising my blood glucose.

Started the day with 4 eggs, a salami stick, and an iced americano, along with my usual probiotics, creatine, and supplements. I usually skip breakfast on weekends to sleep in, but had to get up early to run some errands. As expected, my blood glucose stayed steady. For lunch, I had a double patty fried-mozzarella burger, a fried drumstick, and a Coke Zero. Surprisingly, my blood glucose only went up by 29 points, which was less than I expected. I only walked 20 steps post-meal, too. Dinner was rice paper rolls with a variety of sides: mashed sweet potato, mashed potato, tteokbokki, beef fried rice, and silky tofu with black sesame seed dressing. My blood glucose peaked at 130, which was manageable, but it took about 2 hours to reach that peak and an additional 1.5 hours to return to normal—overall, a 3.5-hour process. I didn’t move around much after eating, which might have contributed.

Push days, especially chest exercises, are not my favorite, so I usually don't go all out. But today, I pushed myself hard, focusing mostly on shoulders. Interestingly, my blood glucose peaked at just 109. It was probably because my shoulder muscles are tiny. I had my protein shake: 30g of WPC, 5g of creatine, 4 saccharin nitrate granules, plus a sachet each of probiotics and instant coffee. Surprisingly, this brought my blood glucose down to my typical fasted levels instead of raising it. Subway is a regular spot for me. I go for the rotisserie chicken on wheat bread with American cheese, all the veggies except pickles and jalapeños, and olive oil with salt and pepper. The sandwich didn’t spike my blood glucose much, which was reassuring. I was a bit concerned about the bread, but it seems to agree with me. Curious about how much I could eat without pushing my blood glucose over 150, I tested it with some tonkatsu and tuna gimbap. Even after walking about 1900 steps post-meal, my blood glucose rose from 84 to a peak of 146. Thankfully the rise was slow, and it took around three hours to return to stable levels. Today was a bit of an experiment with two meals out, but it went pretty well. I’m impressed by how much walking can help keep a high-carb meal from spiking blood glucose too much.

Today started with a solid back and biceps workout. My blood glucose peaked at 119, which seemed pretty manageable. Fun fact: when I started hitting my biceps after finishing off my back workout routine, blood glucose started dropping! Afterward, I came home for breakfast—a protein shake with one scoop of WPC (not double the usual like yesterday), 5g of creatine, 10g of unsweetened cocoa powder, 4 saccharin nitrate granules, and a sachet of each probiotics and instant coffee. Interestingly, my blood glucose stayed below 100. Lunch was chicken wings with homemade sugar-free teriyaki sauce. Delicious! Even though the graph might look a bit alarming, my blood glucose only went from 87 to 105 at the peak—nothing major. For a snack, I had Nature Valley's peanut butter protein bar. I was quite curious about this one because I eat this stuff pretty regularly. My BG increased slightly from 99 to 109, and I suspect the second small rise might have been due to work stress. Dinner was a beef steak paired with pasta made from Sampyo's protein noodles. My blood glucose went from 97 to 124, which I'm really happy with. Oh, and I also had a salami stick after about an hour and half which may explain the little bump at the end.

Today started off just right! After my morning coffee, I headed to the gym for a solid leg day workout. I was curious to see how my blood glucose levels would react, especially since leg days involve working those big muscle groups. Surprisingly, the rise in blood glucose wasn’t as high as I expected, but it was super interesting to see how my body responded. Post-workout, I treated myself to a protein shake—double the usual amount since I thought lunch might be lacking in protein. Some people say that protein shakes cause a blood sugar spike, but in my case, there wasn’t much of a change. If your blood sugar spikes after drinking protein shakes, it might be a good idea to check the ingredients in your protein powder. I occasionally have flavored ones, but I mostly stick to 100% unflavored whey protein. For lunch, I went all out with some Yangpyeong haejang-guk, complete with rice and all the sides. The soup was spicy and loaded with garlic—just how I like it! Later, I decided to try out this ice cream sandwich. It’s made with maltitol as the main sweetener and has a wheat-based wafer, so I was bracing for a blood glucose spike. But guess what? It didn’t happen! That was a nice surprise. Post-leg day hunger hit hard! I ended up having quite the spread: bulgogi, eggs, konjac noodles with soy sauce, a salami stick, fish cake, zero-sugar grape juice, and even a tangerine ice block. I just couldn’t stop eating—I was so wiped out from the morning workout. Leg days always make me crave extra food, especially protein. I saw this coming, but it still catches me by surprise every time. Interestingly, my blood sugar didn’t rise as much as I expected, considering what I ate. I feel great and drousy. I'm gonna go pass out now.

For breakfast I had bulgogi (Costco) and scrambled eggs. I would've had protein shake as per usual, but the new shaker came in broken so I had to eat something else. I had a salami stick as a snack. It didn't raise my blood glucose at all. It has about 3g of carbohydrates. Interesting. I went out to test soondae gukbap without soondae. So basically just meat gukbap. I ate everything including rice and the sides, then went straight home to get some more work done. I came back for Round 2 of soondae gukbap. This time I had the full soondae gukbap with soondae in it. I ate everything like I did at lunch. But this time, I went for a 30 minute walk after the meal. Even though there were a bit more carbohydrates than lunch, it only peaked my blood sugar by 28 points. Walking post-meal seems to help tremendously.

26th of August, 2024, around 1 PM, I applied my Continuous Glucose Monitor (CGM). It felt like a slight pinch, and there was a little bit of blood, but it wasn't painful or uncomfortable. First off, I want to clarify that I do not have diabetes, nor do I have any illness—I'm just an ordinary person. Please keep in mind that this is a personal experiment, and I take no responsibility for any outcomes if you decide to try something similar on your own. This is purely for fun and curiosity. In the evening, I had sashimi rice bowl and two pieces of tempura. While this was a relatively good choice (other people had noodles), my blood glucose still went up by 54 which isn't that bad, to be honest.

SUMMARY: Insufficient sleep significantly hampers fat loss and accelerates muscle loss, undermining the effectiveness of dietary efforts to reduce adiposity. KEY FINDINGS: Reduced sleep leads to a 50% increase in muscle loss compared to adequate sleep. Participants with restricted sleep lost 2.4 kg fat-free mass but only 0.6 kg fat. Adequately rested participants lost 1.5 kg fat-free mass and 1.4 kg fat. Both groups consumed identical diets with a major energy deficit (90% of BMR). Total weight loss was similar across both groups (~3 kg). Sleep quality plays a critical role in nutrient partitioning during weight loss. The study lasted 2 weeks in a controlled sleep research laboratory. The super-sleeper group showed balanced fat and muscle loss. Sleep is more critical than dietary macronutrient distribution in fat loss. The fitness community underestimates the importance of sleep in weight management. CONCLUSION: Adequate sleep is crucial for effective fat loss and muscle preservation. Sleep deprivation undermines dietary efforts to reduce body fat. Prioritizing sleep can improve nutrient partitioning during weight loss. Both sleep and diet must be considered for successful body composition changes. The fitness industry needs to emphasize the role of sleep in achieving optimal results. KEYWORDS: sleep study, muscle loss, fat loss, dietary efforts, nutrient partitioning, sleep deprivation, body composition, controlled lab study, weight loss, fitness.

SUMMARY: Mitochondrial polyP depletion exacerbates neuronal senescence; dietary restriction activates AMPK but doesn't reverse senescence in affected neurons. KEY FINDINGS: Neuronal senescence significantly contributes to neurodegenerative disorders and aging. Dysregulated mitochondrial function plays a pivotal role in neuronal senescence. Dietary restriction shows promise in mitigating neuronal senescence through mitochondrial function preservation. Inorganic polyphosphate (polyP) is crucial for mitochondrial physiology and bioenergetics. Depletion of mitochondrial polyP correlates with increased senescence in neuron-like SH-SY5Y cells. Short-term starvation (STS) restores some mitochondrial functions in polyP-depleted cells but not senescence. Increased levels of AMPK are observed with STS in polyP-depleted cells. Mitochondrial function and energy metabolism are affected by polyP levels. Male C57BL/6 mice show increased polyP levels and AMPK activation after intermittent fasting. Findings suggest targeting mitochondrial polyP metabolism could help combat neuronal senescence. CONCLUSION: Mitochondrial polyP depletion triggers neuronal senescence. Dietary restriction benefits mitochondrial function but doesn't fully revert increased senescence. AMPK activation may serve as a protective mechanism in polyP-depleted neurons. Mitochondrial health is crucial for neuronal longevity and function. Further research on polyP could uncover therapeutic targets against neurodegeneration. KEYWORDS: neurons, mitochondrial function, dietary restriction, neurodegeneration, senescence, inorganic polyphosphate, AMPK, aging, fasting, energy metabolism

SUMMARY: Strength training effectively improves body composition and strength in obese women, with similar fat loss and cardiovascular benefits as cardio. KEY FINDINGS: Strength training significantly increased fat-free mass and decreased body fat percentage. Both strength and cardio training resulted in similar fat mass and waist circumference reduction. Cardiovascular health improved similarly in both the strength and cardio groups. Strength training led to greater increases in overall strength, especially in the bench press. Muscle mass growth from strength training enhances long-term fat loss and resting energy expenditure. Strength training potentially suppresses appetite more than cardio. No constrained energy expenditure was noted with strength training, unlike cardio. The combination of resistance and aerobic training was most effective for body composition improvements. Strength training interventions showed the highest effectiveness for cardiorespiratory fitness. Incorporating resistance training is crucial for comprehensive health improvements in obese women. CONCLUSION: Strength training enhances muscle mass and fat loss effectively. Combining resistance and aerobic exercises yields the best overall health outcomes. Strength training improves cardiovascular health comparably to cardio. Appetite suppression and energy expenditure benefits are notable in strength training. Resistance training is vital for achieving significant health improvements in obese women. T/L Note EXOFFIT refers to 'Exercise for Obese Females: Improving Fitness and Health'

In the fast-evolving world of artificial intelligence, ChatPlayground stands out as a unique platform, offering a diverse range of AI models and tools to enhance your productivity and creativity. Whether you're a developer, data scientist, student, or AI enthusiast, ChatPlayground is designed to cater to your needs. Let's dive into the features and benefits that make ChatPlayground the go-to destination for AI interactions. Introduction to ChatPlayground ChatPlayground is an innovative platform that brings multiple AI perspectives into one interface, enabling users to achieve better AI answers 73% more often. By offering a variety of AI models, ChatPlayground ensures you have access to the best possible responses for your queries. With over 6,550 users, including industry leaders, leveraging its capabilities, ChatPlayground is revolutionizing the way we interact with AI. Industry-Leading AI Models ChatPlayground provides access to several top-tier AI models. Users like Brandon C., CEO of GroupUltra, have found it invaluable for exploring and comparing different models. This feature allows users to understand the strengths and applications of each AI model, making it a powerful tool for businesses and individuals alike. Web Copilot: Your AI Companion Across the Web The Web Copilot feature is an AI companion that assists you in reading and writing on any webpage. It can explain, summarize, rewrite, and improve any text within your browser. With AI Vision, you can capture any content on the web and ask the AI to perform various tasks, making it an invaluable tool for content creators and researchers. Additional Features ChatPlayground offers a suite of additional features, including: AI Document Editor: Enhance your writing with AI-powered editing tools. AI Learning Companion: An educational tool that helps students and researchers in their studies. Social Media Integrations: Connect with AI tools across platforms like Twitter, YouTube, Instagram, TikTok, LinkedIn, and WhatsApp. Conclusion ChatPlayground is a comprehensive platform designed to harness the power of multiple AI models, providing users with the best possible tools to enhance their productivity and creativity. Whether you're a professional or an enthusiast, ChatPlayground offers something valuable for everyone. Subscribe to IxTJ Blog for more insightful content like this and stay ahead in the world of AI!

SUMMARY: BetterTerminal allows users to customize their MacOS terminal for enhanced productivity with easy configurations and command shortcuts. KEY FINDINGS: Custom configurations can significantly boost terminal productivity. Users can create command shortcuts to save time and effort. Terminal appearance can be personalized with colors and fonts. A visual editor simplifies the customization process without dotfile hassle. One-off configuration costs $3.99, while lifetime access is $6.99. Users receive a shell command to apply their configurations. Reverting to a previous configuration is straightforward with a simple command. The tool supports Bash and Zsh shells on MacOS only. Users can preview config files before applying them for safety. BetterTerminal is currently unavailable for Windows users. CONCLUSION: Customizing your terminal can enhance your workflow and efficiency. Easy-to-use tools are available for creating personalized terminal setups. Affordable pricing makes it accessible for individual users. Safety features allow users to preview configurations before applying. The tool is specifically designed for MacOS users. KEYWORDS: custom terminal, productivity, MacOS, command shortcuts, visual editor, terminal configurations, Bash, Zsh, user-friendly, personalization

SUMMARY: TimeAlign is a gamified time management app for Apple Watch and iOS, optimizing schedules to align daily actions with long-term goals. KEY FINDINGS: TimeAlign combines time-blocking with behavioral psychology for effective time management. The app features customizable reminders and activity tracking for better productivity. Users can sync their calendars to streamline scheduling and task management. Data insights help visualize time spent versus scheduled time for informed decisions. Gamified elements encourage habit formation and goal achievement. Privacy and user data security are prioritized, with encrypted data storage. The app is currently available for iOS and will integrate with major calendars. Apple Health integration is planned to enhance productivity and well-being. Users can manage tasks in one app, increasing focus and efficiency. Early access is available with promotional discounts for new users. CONCLUSION: TimeAlign helps users align their time with personal goals effectively. The app's integration with wearable technology enhances time management. Data-driven insights facilitate informed scheduling and productivity improvements. Gamification encourages consistent use and habit development. Privacy-focused design ensures user data remains secure and confidential.

SUMMARY: A meta-analysis investigates the relationship between dietary protein intake and chronic kidney disease risk, revealing uncertain associations. KEY FINDINGS: Dietary protein intake may influence the progression of chronic kidney disease (CKD). The exact relationship between protein intake and CKD incidence is unclear. Total protein intake is a focus of the meta-analysis. Distinctions are made between plant and animal protein sources. The study is the first meta-analysis on this topic. Correlations among different protein types and CKD risk are explored. Findings may guide dietary recommendations for CKD patients. Further research is needed to clarify these associations. Protein consumption patterns could impact kidney health. The analysis contributes to understanding dietary influences on CKD. CONCLUSION: Dietary protein type may affect chronic kidney disease risk. Uncertainty remains regarding protein intake and CKD incidence. The meta-analysis provides foundational insights for future studies. Distinguishing between plant and animal protein is crucial. Findings could inform dietary guidelines for kidney health.

iewSUMMARY: Wim Hof's Method offers potential benefits for physical and mental health, as explored in systematic reviews of related studies. KEY FINDINGS: WHM combines breathing techniques, cold exposure, and meditation for health benefits. Studies suggest improved immune response through the practice of WHM. Participants report reduced stress and anxiety levels after WHM training. Enhanced physical performance has been observed in athletes practicing WHM. WHM may aid in pain management and recovery from injuries. Increased focus and mental clarity are reported by WHM practitioners. Cold exposure in WHM is linked to improved cardiovascular health. WHM shows potential in managing symptoms of depression. Regular practice of WHM can boost overall well-being and resilience. Further research is needed to fully understand WHM's long-term effects. CONCLUSION: WHM can positively impact both physical and mental health. Practicing WHM may enhance immune function and reduce stress. Athletes can benefit from improved performance through WHM. WHM may serve as a complementary approach for pain management. Continued research is essential to validate WHM's health claims. KEYWORDS: Wim Hof, cold exposure, breathing techniques, mental health, physical health, immune response, stress reduction, meditation, performance enhancement, resilience

SUMMARY: Conventional obesity treatments often fail due to biological responses; a carbohydrate-insulin model suggests alternative dietary strategies for effective weight management. KEY FINDINGS: Conventional obesity treatment relies on calorie restriction and increased physical activity. Long-term weight loss success is rare with traditional methods. Calorie restriction triggers biological responses that hinder weight loss. The carbohydrate-insulin model suggests high carbs lead to fat storage. Increased insulin levels promote hunger and reduce metabolic rate. Energy partitioning shifts towards fat storage with high carbohydrate intake. Common obesity forms result from gradual weight gain through this mechanism. Low-fat diets may not address the root causes of obesity. Lowering insulin secretion could enhance weight management effectiveness. The article is part of a broader discussion on obesity causes. CONCLUSION: Traditional weight loss methods often fail due to biological counter-responses. A high-carbohydrate diet can lead to increased fat storage. Understanding insulin's role is crucial for effective weight management. Alternative dietary strategies may improve long-term obesity outcomes. Addressing underlying causes of obesity is essential for sustainable health. KEYWORDS: obesity, weight loss, insulin, carbohydrates, dietary strategies, metabolism, health, energy balance, chronic disease, nutrition

SUMMARY: Physical exercise shows limited effects on Alzheimer's biomarkers, but specific populations may benefit from targeted interventions. KEY FINDINGS: Exercise benefits on brain health are widely recognized but mechanisms are still debated. Study focused on exercise's impact on Alzheimer's disease biomarkers. Selected biomarkers included beta-amyloid, tau, neurofilament light chain, and glial fibrillary acidic protein. No strong evidence of significant exercise effects on biomarkers in the general population. Women with obesity, pre-diabetes, or depression showed favorable changes in beta-amyloid levels. Cerebrospinal fluid beta-amyloid improvements noted in Alzheimer's allele carriers. Current evidence suggests exercise does not alter Alzheimer's pathophysiology for most older adults. Specific populations may experience positive effects from exercise interventions. Future research should include larger samples and long-term follow-ups. Other factors like diet and sedentary behavior need consideration in future studies. CONCLUSION: Exercise has limited overall impact on Alzheimer's biomarkers in older adults. Targeted exercise interventions may benefit specific populations. Further research is essential for conclusive evidence. Consideration of lifestyle factors is crucial for understanding exercise effects. Continued exploration of exercise's role in cognitive health is needed. KEYWORDS: brain health, Alzheimer's disease, exercise intervention, biomarkers, cognitive conditions, beta-amyloid, neurofilament, cerebrospinal fluid, older adults, metabolic disorders

SUMMARY: Long-term anabolic-androgenic steroid users may experience significant cognitive deficits, particularly in visuospatial memory, correlated with total AAS dosage. KEY FINDINGS: Anabolic-androgenic steroids (AAS) enhance muscle mass but may cause cognitive deficits. Long-term AAS users showed impaired visuospatial memory compared to nonusers. Cognitive tests indicated no deficits in reaction time and verbal memory for AAS users. AAS use correlates significantly with poorer performance on Pattern Recognition Memory. Lifetime AAS dose negatively affects visuospatial memory performance in users. Study involved 31 male AAS users and 13 non-users, ages 29-55. No significant differences found between groups on sustained attention tests. Cognitive impairments raise concerns about long-term health risks of AAS usage. Prior studies indicated potential neurotoxicity in neuronal cells due to AAS exposure. Future research should focus on AAS impact on brain regions linked to memory. CONCLUSION: Long-term AAS exposure may be detrimental to cognitive function. Significant declines in visuospatial memory associated with higher AAS dosages. Preliminary findings suggest a potential public health concern. Further studies are needed to confirm these findings and explore underlying mechanisms. Reference

SUMMARY: Exercise enhances all cognitive functions, showing notable benefits across age groups, with strength and endurance training both effective. KEY FINDINGS: Meta-analysis reviewed 54 trials with 6277 participants on exercise and cognitive functions. Exercise improves global cognition, executive function, memory, attention, and processing. Benefits are strongest in older adults but evident in all age groups. Strength training has the highest effect size for brain functioning. Endurance training is also effective and superior in some cognitive areas. Cognitive improvements are present across diverse exercise types. Exercise impacts both physical and mental well-being. The meta-analysis includes a wide range of cognitive domains. Results are significant for healthy adults and children too. Regular exercise is essential for overall personal development. CONCLUSION: Exercise benefits all cognitive functions across different age groups. Strength training shows the greatest overall improvement in brain function. Endurance training excels in specific cognitive subdomains. Both physical and mental health are enhanced by regular exercise. Comprehensive cognitive improvements highlight exercise's broad efficacy. Reference

The "Blue Screen of Death" (BSOD) is a notorious error screen displayed by Windows operating systems when a fatal system error occurs. However, with the rise of online pranks and misinformation, fake BSODs have become a common sight. This article delves into the implications of encountering a fake Windows BSOD, its potential uses, and how to differentiate between a real and a fake error screen. The Nature of Fake BSODs What is a Fake BSOD? Fake BSODs are designed to mimic the appearance of a genuine Windows error screen. They often display messages such as "Your PC ran into a problem and needs to restart," along with a stop code like "CRITICAL_PROCESS_DIED." These screens can be used for various purposes, including pranks or as a form of malware to scare users. Common Uses of Fake BSODs Fake BSODs are often employed in pranks to elicit a reaction from unsuspecting users. They can also be used in educational contexts to teach users about system errors and troubleshooting. However, they can also be a vector for malicious software, tricking users into downloading harmful programs. How to Identify a Fake BSOD Identifying a fake BSOD can be straightforward if you know what to look for. Genuine BSODs typically provide specific error codes and troubleshooting steps, while fake ones may lack these details or provide misleading information. Additionally, a real BSOD will not allow you to click on links or edit text. Conclusion While fake BSODs can be amusing, they also serve as a reminder to stay vigilant against potential scams and malware. Understanding the nature of these screens can help users navigate their digital environments more safely. If you found this article insightful, consider subscribing to IxTJ Blog for more informative content like this. Stay informed and protect yourself from digital pranks and threats!