Search Results (439)

Background/Objective: Intermittent fasting (IF) shows promise for metabolic and mental health benefits, but evidence in older adults remains limited. This study systematically evaluated the safety and effectiveness of IF in adults aged ≥60 years, comparing different protocols using network meta-analysis. Methods: Systematic review and network meta-analysis following Cochrane and PRISMA guidelines were conducted, producing a literature search until June 2025 across PubMed, Scopus, and ScienceDirect databases, with inclusion criteria comprising randomized controlled trials, clinical trials, and observational studies evaluating IF in adults ≥60 years. Network meta-analysis compared time-restricted eating (TRE), IF 5:2 method, Islamic Sunnah fasting (ISF), Healthy Living Diet and usual diet. The NMA was conducted exclusively using randomized controlled trials (RCTs; n = 7); pre–post trials and observational studies were included solely in the narrative systematic review component and did not contribute to any pooled NMA estimates. Observational data contributed exclusively to the narrative synthesis. Results: Thirty-one studies were included; seven RCTs were eligible for network meta-analysis. ISF and TRE 16:8 were most effective for weight (ISF: −2.36 kg; TRE 16:8: −1.92 kg) and BMI reduction (−0.81 and −1.01 kg/m²) without lean mass loss. Findings on cardiometabolic parameters, mental health, and cognitive function are based on the narrative synthesis of individual studies. Long-term structured IF was associated with improvements in standardized cognitive performance assessed via validated instruments. However, very restrictive eating windows (≤10 h) and prolonged fasting (>12.38 h) were associated with adverse outcomes, including lower cognitive scores and 58% increased cardiovascular mortality. Conclusions: TRE 16:8 and ISF showed the strongest comparative evidence for weight reduction in the RCT-based NMA, with acceptable short-term safety profiles in the included trials. In the narrative review, these protocols were associated with clinically meaningful improvements in body weight, metabolic markers, and blood pressure while generally preserving lean muscle mass in older adults. The cardiovascular mortality risk associated with very restrictive eating windows may emphasize the importance of moderate fasting approaches in this vulnerable population. Further long-term research is needed to confirm optimal protocols and identify at-risk subgroups. Full article

Introduction: Intermittent fasting (IF) is becoming increasingly popular as a method of weight management, but it is unknown whether it affects plasticiser intake with resultant changes in glycaemic control in diabetes and vitamin D (VitD) levels; therefore, this study was undertaken in a cohort of control and type-2 diabetic (T2D) subjects during Ramadan time-restricted feeding (TRF). Methods: In T2D subjects (n = 19) and controls (n = 31) undertaking TRF, 24 h urinary levels of phthalate metabolites, bisphenols and serum VitD were determined pre- and post-TRF by liquid chromatography–tandem mass spectrometry (LC-MS/MS). Anthropometric data and glycosylated haemoglobin (HbA1c) were measured. Results: T2D subjects were older (52 versus 36.73 years, p < 0.001), and had higher BMI (36.54 versus 27.67 kg/m², p < 0.001), body weight (101.77 versus 80.36 kg, p < 0.001), and HbA1c (8.38 versus 5.46%, p < 0.001) compared to controls, while VitD levels did not differ (60.43 versus 63.95 nmol/L, p > 0.05). Post-TRF, HbA1c was unchanged in T2D subjects and there was no difference in weight, BMI or VitD. Increased mono-iso-butyl phthalate (MiBP) in T2D subjects (10 versus 6.1 ng/mL, p = 0.001) and mono-n-butyl phthalate (MnBP) in T2D subjects (37 versus 13 ng/mL, p = 0.018) and controls (8.3 versus 5.4 ng/mL, p = 0.007) were observed post-TRF; however, significance was lost after adjusting for baseline differences in age, BMI, and HbA1c using a general linear model (GLM) repeated-measures ANOVA. Despite having no median differences in DEHP (di-2-ethylhexyl phthalate) metabolites pre- and post-TRF, analyses revealed a significant time × HbA1c interaction for [mono(2-ethyl-5-carboxypentyl) phthalate, MECPP: F(1,42) = 4.79, p = 0.03, mono(2-ethyl-5-hydroxyhexyl) phthalate, MEHHP: F(1,42) = 8.56, p = 0.006, mono(2-ethylhexyl) phthalate, MEHP: F(1,42) = 4.64, p = 0.03 and mono(2-ethyl-5-oxohexyl) phthalate, MEOHP: F(1,42) = 8.19, p = 0.007] and time × group interactions [MEHHP: F(1,42) = 14.27, p < 0.001, MEHP: F(1,42) = 6.35, p = 0.01 and MEOHP: F(1,42) = 10.30, p = 0.003]. Estimated marginal means (adjusted for age, BMI, HbA1c, and VitD) further confirmed higher concentrations of DEHP metabolites [MECPP, MEHHP, MEHP, and MEOHP] in T2D participants over time compared with controls. Additionally, monomethyl phthalate (MMP) trajectories were significantly influenced by the time × group interaction (F(1,42) = 4.28, p = 0.04), with post-TRF elevations observed in T2D subjects. Vitamin D status was observed to modify MCPP and MEP trajectories over time. Conclusion: Ramadan TRF is associated with changes in plasticiser metabolite levels, with estimated increased levels in T2D subjects versus healthy controls. Metabolite levels were influenced by HbA1c and vitamin D, though BMI was not observed to be a contributing factor. Full article

Background/Objectives: Lipedema is a chronic adipose tissue disorder characterized by disproportionate fat accumulation, pain, microvascular dysfunction, and low-grade inflammation. Although low-carbohydrate, high-fat (LCHF) dietary approaches are increasingly used in clinical practice, their longer-term associations with vascular, lymphatic, and immunometabolic pathways in lipedema remain insufficiently understood. This preliminary exploratory study evaluated clinical outcomes and circulating mediators during a 7-month LCHF dietary intervention. Methods: Twenty-four women with lipedema (median age: 39 years) underwent a 7-month individualized, calorie-restricted LCHF diet under medical supervision. Outcomes included body mass index (BMI), leg volume, and adipose tissue pain assessed using a visual analogue scale (VAS). Fasting serum samples collected at baseline and follow-up were analyzed for angiogenic, inflammatory, endothelial, and lipid mediators using Luminex assays and liquid chromatography–tandem mass spectrometry (LC-MS/MS). Results: The intervention was associated with significant reductions in BMI, leg volume, and adipose tissue pain (p < 0.001). These changes were accompanied by increased vascular endothelial growth factor A (VEGF-A), vascular endothelial growth factor D (VEGF-D), and angiopoietin-2 (Ang-2), together with decreased pro-inflammatory cytokines and endothelial adhesion molecules. Several endocannabinoid-related lipid mediators, including oleoyl ethanolamide (OEA), arachidonoyl ethanolamide (AEA), and palmitoyl ethanolamide (PEA), also decreased. Baseline OEA and AEA concentrations, as well as reductions in OEA over time, were associated with greater BMI reduction. Change in interleukin-8 (IL-8) showed a nominal association with leg volume reduction, while pain improvement was associated with decreases in P-selectin and VEGF-A and increases in interleukin-13 (IL-13). Conclusions: A 7-month calorie-restricted LCHF dietary intervention in women with lipedema was associated with clinical improvement and changes in circulating vascular, inflammatory, and lipid mediators. These findings reflect systemic changes accompanying the intervention; however, causal relationships and specific mechanisms cannot be established. Full article

Suppose that we have a statistical model with q unknown parameters w, and an estimate $\widehat{w}$, based on a sample of size n. A basic question is: what is the covariance of the estimate? The covariance is needed for the Central Limit Theorem (CLT). This gives a first approximation for the distribution of $\widehat{w}$. But what if $q_n=n$ increases with n? How fast can it increase and the CLT still hold? An answer has so far only been given for the sample mean. The same is true for the Edgeworth expansions. These are expansions in powers of $n^{-1/2}$ for the density and distribution of $\widehat{w}$. For fixed q, these expansions are important, as they show how small n can be for the CLT to apply. When it does, they can greatly improve the accuracy of the CLT. I give conditions that allow for the Edgeworth expansions to remain valid when $q_n=q$ increases with n. Earlier Edgeworth expansions when $q_n=q$ increases, have only been done for a sample mean, and only for a 2nd order Edgeworth expansion. In contrast, I consider a very large class of estimates, the class of non-lattice standard estimates. An estimate is said to be a standard estimate if its mean converges to its true value as n increases, and for $r\ge 1$, its rth order cumulants have magnitude $n^{1-r}$ and can be expanded in powers of $n^{-1}$. For this class of estimates, I show that the Edgeworth expansions hold if $q_n$ grows as a power of n less than $1/6.$ That is, I give these expansions in powers of $n^{-1/2}{q}_n^3$. This large class of estimates has a huge range of potential applications, as estimates of high dimension are common in nearly all areas of applied statistics. The most important type of standard estimate is when $\widehat{w}$ is a smooth function of a sample mean, of dimension p say. When either or both $q_n=q$ and $p_n=p$ increase with n, I give conditions on their growth for the Edgeworth expansions for $\widehat{w}$ to remain valid: the eighth power of p times the sixth power of q cannot grow as fast as n. This holds for fixed $q=q_n$ if $p_n$ grows less than a power of n less than $1/8$. This appears to be the first time when Edgeworth expansions have been given when not one, but two dimensions, are allowed to increase to ∞ with n. This gives two different pathways for allowing an increase in dimensionality. When $q=1$, I give 5th order Edgeworth-Cornish-Fisher expansions for the standardized distribution and its quantiles of any smooth function of a sample mean of dimension $p_n$, when $p_n$ is a power of n less than $1/2$. However for the special case when this function is linear, there is no restriction whatever on how fast $p_n$ can increase! If also the components of the sample mean are independent, then these expansions are in powers of ${\left(np\right)}^{-1/2}$. I also give a method that greatly reduces the number of terms needed for the 2nd and 3rd order terms in the Edgeworth expansions, that is, for the 1st and 2nd order corrections to the CLTs. I also extend these results to the case where $\widehat{w}\in R^q$ is a function of several independent sample means, each of dimension increasing with n, with total dimension p. Full article

This paper proposes a co-design methodology for the power and control stages of a bidirectional battery charger/discharger based on a boost converter topology. The approach ensures safe operation by limiting the battery current derivative, preventing abrupt transients that could degrade battery lifespan. The control strategy combines a cascade structure with an inner sliding mode current controller (for robustness and fast response) and an outer adaptive PI voltage loop (to regulate the DC-link voltage under varying load conditions). Additionally, the design constrains the switching frequency to reduce power losses. Experimental validation on a prototype converter demonstrates the effectiveness of the co-design framework, showing precise current/voltage regulation, adherence to switching frequency limits, and compliance with battery charging/discharging requirements. The results highlight the methodology’s potential to enhance efficiency and reliability in energy storage systems. The dynamic restrictions, overshoot lower than 5%, settling time shorter than 5 ms, and a battery current limitation less than 50 A/ms were always met with SMC and, in some cases, with the PI controller, but the results with SMC were always better: lower overshoot, shorter settling time, and greater restriction on the derivative of the battery current. In addition, the SMC system was 2.5–5.0% more efficient than the PI controller. Full article

Background: Circadian disruption exacerbates type 2 diabetes mellitus (T2DM). Time-restricted feeding (TRF) and exercise (EX) improve metabolic health, but their combinatory effect remains unclear. This study investigated whether combined TRF and EX additively ameliorates metabolism via circadian reprogramming in db/db mice. Methods: Eight-week-old male db/db mice were assigned to control (Con), diabetic model (DM), TRF (8 h feeding window), EX (treadmill, 60 min/day, 5 days/week), or combined TRF + EX groups for 8 weeks (n = 8/group). Body weight, glucose/insulin tolerance, and 24 h energy metabolism (CLAMS) were assessed. Mitochondrial function, oxidative stress, inflammation, and expression of mitophagy (Pink1, Park2, Bnip3, Fundc1) and thermogenic (Ucp1, Pgc1a, Prdm16, Cidea) genes were measured. Results: Compared with the con group, DM mice showed obesity, hyperglycemia and blunted circadian metabolic rhythm. The TRF and EX groups improved these defects. Specifically, combined TRF + EX reduced fasting blood glucose from 25.3 ± 3.1 mmol/L (DM) to 13.2 ± 1.8 mmol/L (p < 0.05), body weight from 49.8 ± 2.5 g to 39.5 ± 1.7 g (p < 0.05), and body fat percentage from 45.6 ± 3.2% to 32.1 ± 2.2% (p < 0.05). GTT area under the curve (AUC) decreased from 3711.0 ± 186.5 (DM) to 2118.0 ± 112.4 (p < 0.05), and ITT AUC decreased from 2617.5 ± 135.8 to 1260.0 ± 68.9 (p < 0.05). Notably, the combination of TRF + EX produced greater effects than either intervention alone: body weight, fasting blood glucose, and glucose/insulin tolerance were greatly improved (p < 0.05). In addition, compared with the DM group, the diurnal metabolic amplitude and phase were improved in the TRF or EX group; the combination group showed further improvements in these parameters. Furthermore, TRF and EX each resulted in significantly higher expression of key thermogenic genes (Ucp1, Pgc1a, Prdm16, Cidea) in white adipose tissue (WAT) and brown adipose tissue (BAT) (p < 0.05), and the TRF + EX group showed the highest expression levels. Combined intervention also restored skeletal muscle SOD activity (31.2 ± 2.9 U/mg prot vs. DM 20.1 ± 2.5 U/mg prot, p < 0.05) and reduced serum TNF-α (28.5 ± 4.5 pg/mL vs. DM 65.8 ± 8.5 pg/mL, p < 0.05) and IL-6 (21.6 ± 3.8 pg/mL vs. DM 50.3 ± 7.1 pg/mL, p < 0.05). Conclusions: TRF + EX additively restores metabolic homeostasis in diabetes by re-entraining circadian energy rhythms, improving mitochondrial quality, and activating adipose thermogenesis, supporting further investigation of integrated lifestyle timing as a potential therapeutic strategy. Full article

High-speed railway corridors operating under dense traffic conditions often face capacity limitations and operational conflicts caused by minimum headway constraints and heterogeneous train services. Differences in running times and stopping patterns between fast and slow trains may lead to overtaking conflicts and inefficient infrastructure utilization. This study investigates a multi-objective timetable optimization problem for high-speed railways under minimum headway constraints. A timetable optimization framework is established for high-speed railways under dense heterogeneous operations. The core mathematical formulation explicitly models timetable variables and basic temporal bounds, including sectional running-time limits, dwell-time bounds, and operating time-window constraints. Additional engineering feasibility requirements, such as minimum headway, station-capacity restrictions, and in-station overtaking feasibility, are enforced through the BS-FGS feasibility-scheduling procedure and the repair-based constraint-handling mechanism in the improved MOPSO stage. A hierarchical solution framework is proposed in which a Binary Search–Feasibility-Guided Greedy Scheduling (BS-FGS) method first evaluates the maximum feasible train number and generates an initial feasible timetable, followed by an improved Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to obtain Pareto-optimal solutions within the feasible region. A case study on the Shanghai–Hangzhou High-Speed Railway corridor shows that system utilization can reach approximately 0.93–0.94 when in-station overtaking is allowed. Robustness simulations further demonstrate that the optimized timetables maintain stable train intervals and exhibit strong disturbance resistance. These results indicate that the proposed framework provides effective support for capacity evaluation and timetable optimization in high-density high-speed railway operations. Full article

Purpose: The aims of this study were to evaluate the feasibility of time-restricted eating (TRE) in patients with Cushing’s disease (CD) and assess its effects on body weight and metabolic parameters. Methods: Twelve CD patients in remission with obesity were enrolled in a TRE program restricting food intake to 10:00–18:00. Anthropometric data, glycemic and lipid profiles, and circadian cortisol secretion were assessed at baseline and post-intervention. Serum cortisol levels were measured at multiple time points to evaluate diurnal patterns. Results: Nine patients completed the study. Over the 12-week period, participants showed a significant reduction in body weight, with median values decreasing from 93.8 kg [83.1–106.5] to 82.6 kg [76.9–100.3] (p = 0.011). Body mass index (BMI) also declined from 37.6 kg/m² [34.2–39.7] to 34.4 kg/m² [32.6–38.3] (p = 0.012). No statistically significant changes were observed in fasting glucose, HbA1c, or lipid parameters. Notably, 24 h urinary free cortisol levels significantly decreased (p = 0.01), and serum cortisol showed a downward trend at all measured time points, with the most pronounced reductions during mid-day and evening hours. No clinical or biochemical evidence of CD relapse was observed during the 12-month follow-up. Conclusions: Time-restricted eating is a feasible and well-tolerated dietary approach for patients with CD in remission, promoting weight loss and modest improvements in metabolic markers and cortisol rhythmicity. Full article

Millimeter-wave radar has gradually gained popularity as a sensor mode for Human Activity Recognition (HAR) in recent years because it preserves the privacy of individuals and is resistant to environmental conditions. Nevertheless, the fast inference of high-dimensional and sparse 4D radar data is still difficult to perform on low-resource edge devices. Current models, including 3D Convolutional Neural Networks and Transformer-based models, are frequently plagued by extensive parameter overhead or quadratic computational complexity, which restricts their applicability to edge applications. The present paper attempts to resolve these issues by introducing RadarSSM as a lightweight spatiotemporal hybrid network in the context of radar-based HAR. The explicit separation of spatial feature extraction and temporal dependency modeling helps RadarSSM decrease the overall complexity of computation significantly. Specifically, a spatial encoder based on depthwise separable 3D convolutions is designed to efficiently capture fine-grained geometric and motion features from voxelized radar data. For temporal modeling, a bidirectional State Space Model is introduced to capture long-range temporal dependencies with linear time complexity $O\left(T\right)$, thereby avoiding the quadratic cost associated with self-attention mechanisms. Extensive experiments conducted on public radar HAR datasets demonstrate that RadarSSM achieves accuracy competitive with state-of-the-art methods while substantially reducing parameter count and computational cost relative to representative convolutional baselines. These results validate the effectiveness of RadarSSM and highlight its suitability for efficient radar sensing on edge hardware. Full article

Microinjection is one of the most established and effective techniques for introducing foreign substances into cells. However, issues such as cumbersome procedures, low success rates, and poor repeatability in manual cell microinjection have seriously restricted its practical applications in biomedical research and engineering. Responding to such problems, this paper designs an automated microinjection system that combines deep learning visual positioning and adaptive neural network sliding-mode motion control. The machine vision solution based on the deep learning YOLOv8 target detection algorithm is utilized by the system to provide positional prerequisites for automated microinjection. Then, stable and fast puncture is completed by controlling the end effector (composed of a piezoelectric actuator and a displacement amplification mechanism). Since the piezoelectric actuator has strong nonlinearity, the motion control of the end effector adopts the control strategy combining sliding mode variable structure and adaptive neural networks to meet the requirements of precise displacement output of microinjection. At the same time, a host computer control system is developed to integrate hardware equipment, visual positioning algorithms and motion control algorithms to achieve corresponding automated microinjection tasks. Finally, the effectiveness of the designed automated microinjection system is successfully verified on zebrafish embryos. Full article

Photocatalytic degradation is a highly efficient, stable and promising technology for water treatment. Developing high-performance photocatalysts is crucial for removing aquatic contaminants. However, traditional zinc oxide (ZnO) photocatalysts are severely restricted by intrinsic drawbacks, such as a wide band gap, fast recombination of photogenerated carriers, and high photocorrosion tendency. Conventional powder catalysts also suffer from difficult recovery and serious secondary pollution. Therefore, developing simple strategies to fabricate high-performance, reusable, and stable ZnO-based photocatalysts is of great scientific and practical importance. In this work, silver-loaded nitrogen-doped ZnO nanoarrays (Ag_Y@N_X-ZnO NAs, where X and Y represent the urea and AgNO₃ concentrations, respectively) were synthesized on 304 stainless steel sheets (SSS) using a two-step hydrothermal method combined with photoreduction at room temperature. The samples were characterized by XRD, FESEM, XPS, and UV-Vis DRS, and the catalytic mechanism was studied through active species trapping and EPR. Nitrogen doping and Ag loading exhibited a strong synergistic effect, narrowing the band gap, enhancing visible-light absorption, and promoting the separation of photogenerated carriers. The optimal sample (Ag_1.5@N₄-ZnO NAs) degraded 93.2% of Rhodamine B (RhB) within 180 min, with a reaction rate constant 2.65 times higher than pure ZnO. The main active species were ·O₂⁻ and ·OH. This work provides a feasible route to fabricate recyclable and stable stainless steel-based ZnO nanoarray photocatalysts for efficient water purification. Full article

Magnesium phosphate cement (MPC) is a type of rapid-hardening inorganic cementitious material, which has important application value in rapid road repair, solidification of hazardous and radioactive waste, and other fields. However, it suffers from excessively fast setting and hardening and a short working time retention, which severely restrict its engineering application. Therefore, the development of high-efficiency set retarders is of great significance for optimizing MPC performance, enhancing its construction workability, and expanding its application scope. In this study, the effect of sodium polyacrylate (PAAS) on the setting and hardening of magnesium potassium phosphate cement (MKPC) was investigated by testing the setting time and fluidity at a low water-to-solid ratio (W/S = 0.18). Through pH and electrical conductivity measurements, combined with XRD, TG/DTG, and FTIR characterizations, we elucidated the retarding mechanism of PAAS on MKPC using a high water-to-solid ratio (W/S = 10). The results indicate that the setting time of MKPC is positively correlated with the PAAS dosage, whereas the fluidity and compressive strength exhibited a negative correlation with the PAAS dosage. Additionally, PAAS reduces the total heat release and the heat release rate of MKPC. The addition of PAAS increased the pH of the suspension, thereby reducing the solubility of MgO, but did not inhibit the dissolution of KH₂PO₄. The carboxylate groups in PAAS chemically reacted with Mg²⁺ on the surface of MgO to form magnesium carboxylate complexes (Mg-PAA), which remained as precipitates in the MKPC suspension system, thus reducing the amount of available Mg²⁺ participating in the hydration reaction. Furthermore, PAAS had no effect on the final precipitate composition at the end of hydration, which was composed of MgKPO₄·6H₂O and Mg₃(PO₄)₂·22H₂O in all cases. Full article

This paper aims to present a non-destructive, optimized variational mode decomposition (VMD)-based ground-penetrating radar (GPR) method developed for identifying void defects in reinforced concrete (RC) structures. This study also presents an enhanced framework for defect detection in RC by integrating advanced spectrum analysis with deep learning techniques. A GPR investigation was conducted on an RC bridge deck with known structural defects to generate a representative dataset reflecting both intact and void-defective conditions. In addition to conventional spectral techniques such as fast Fourier transform (FFT), spectrogram, and scalogram, an optimized variational mode decomposition (VMD) method was implemented. The VMD approach decomposes GPR signals into intrinsic mode functions, enabling refined feature extraction beyond traditional spectral methods and allowing clear differentiation between intact and defective signals. The limited availability and quality of GPR small datasets have restricted the application of a functional 1D-CNN which generally requires at least several hundred datasets. To address this challenge, a data augmentation strategy is adopted. FFT-based features were successfully utilized to train a one-dimensional convolutional neural network (1D-CNN) for automated defect identification. The results demonstrate that both the advanced spectrum-based approach and the hybrid framework combining spectral analysis with deep learning significantly improve defect detection performance. Overall, the proposed methodology provides an effective and intelligent solution to support timely, data-driven decision-making for maintenance and safety assurance of bridge infrastructure. Full article

Background: Fasting-based interventions are increasingly investigated as adjuncts to cancer treatment for the potential to reduce therapy-related toxicities, improve metabolic health, and enhance quality of life. However, clinical evidence regarding their efficacy, tolerability, and acceptability remains limited and fragmented. This scoping review aimed to systematically map the current evidence on fasting-based interventions in cancer patients and survivors. Methods: A literature search was conducted in PubMed, Scopus, Web of Science, and CINAHL up to 10 June 2025. Eligible interventional studies included cancer patients or survivors and evaluated fasting-based interventions, such as time-restricted eating, intermittent fasting, short-term fasting, or fasting-mimicking diets. Studies were categorized by fasting types and outcomes like fatigue, treatment toxicity, metabolic and hematologic parameters, weight, quality of life, adherence, acceptability, illness perception, and adverse events were assessed. Result: Twenty interventional studies of FMD, TRE, STF, IF, or fasting combined with altered dietary approaches conducted across 10 countries were included, comprising a total of 871 participants. Participant ages ranged from 28 to 75 years. Overall, 9 of 20 studies exclusively enrolled breast cancer patients or survivors, and chemotherapy was the most common treatment context in 11 studies. Five of six studies reported reductions in fatigue. Among the five studies assessing quality of life, one demonstrated improvement, three reported no change, and one yielded mixed results. Six of eight studies reported reductions in chemotherapy-related toxicity, and weight loss was observed in 10 of 12 studies. Reductions in IGF-1 and insulin levels were reported in six of seven and four of five studies, respectively. Hematologic changes were noted in six studies, and only one study assessed illness perceptions, reporting positive findings. Fasting-related adverse events, reported in nine studies, were generally mild and transient. High adherence and acceptability were observed across studies; however, findings were heterogeneous across intervention types and were largely derived from small or moderate-strength studies. A descriptive quality metric assessment indicated that most studies were of moderate methodological strength. More intensive fasting protocols, such as FMD and STF, appeared to demonstrate more consistent metabolic effects, whereas TRE showed higher adherence but more variable clinical outcomes. Conclusions: Fasting-based interventions have the potential to be feasible and well tolerated among cancer patients and survivors, with early evidence suggesting benefits in reducing fatigue, minimizing treatment-related toxicities, and favorable metabolic effects. Large, well-designed trials including diverse cancer populations are needed to confirm long-term outcomes and guide clinical integration. Full article

Background/Objectives: Biorelevant in vitro dissolution testing is used increasingly to predict complex mechanisms in the gastrointestinal (GI) tract that determine oral bioavailability. However, the limited use of non-compendial systems is driven by the lack of widely accepted, standardized validation frameworks. This ongoing gap continues to restrict their adoption relative to United States Pharmacopeia (USP) apparatus. While the physiological relevance and biopredictive capabilities of the tiny-TIM and TIM-1 in vitro GI models have been demonstrated in previous studies, their inter-laboratory reproducibility has not been systematically established. Therefore, this international ring study evaluates the reproducibility of in vitro simulations of GI transit and absorption of paracetamol in fasted- and fed-state conditions in tiny-TIM and TIM-1. Methods: Three laboratories used TIM-1 and five used tiny-TIM to simulate oral administration of a 500 mg paracetamol solution to a healthy adult. Paracetamol solution was selected as a well-characterized and widely available BCS I compound to minimize formulation and solubility effects and focus on system performance, enabling the generation of a generic validation dataset for the reproducibility of TIM experiments. Results: Paracetamol bioaccessibility profiles were repeatable and reproducible (all pairwise f₂ > 50). Maximum differences in total bioaccessible paracetamol were 0.9% (TIM-1) and 2.8% (tiny-TIM) within laboratories and 3.4 and 5.9% between laboratories. Inter-lab variability at individual time points remained <4.0% (fasted) and 5.2% (fed). Both TIM models produced biopredictive metrics, correctly predicting no food effect on total paracetamol bioaccessibility and capturing delayed t_max. Gastric and intestinal environments showed repeatable pH, temperature, and GI transit characteristics, with fluctuations across transit stages that mirrored reported in vivo patterns. Conclusions: These results demonstrate that TIM systems can reproducibly simulate gastrointestinal conditions across laboratories and generate consistent measurements of drug product performance, despite the complexity of the dynamic processes involved. While this evaluation involving a single BCS I drug solution should not be directly extrapolated to experiments with poorly soluble compounds or different formulations, it supports the use of TIM systems as robust in vitro models in drug product development. This study provides a standardized, inter-laboratory, baseline performance dataset to support regulatory submissions incorporating TIM data and enable more confident interpretation of TIM experiments. Full article