Effect of 5:2 Regimens: Energy-Restricted Diet or Low-Volume High-Intensity Interval Training Combined With Resistance Exercise on Glycemic Control and Cardiometabolic Health in Adults With Overweight/Obesity and Type 2 Diabetes-A Three-Arm Randomized Controlled Trial.

OBJECTIVE: We aimed to examine the effects of a 5:2 regimens diet (2 days per week of energy restriction by formula diet) or an exercise (2 days per week of high-intensity interval training and resistance training) intervention compared with routine lifestyle education (control) on glycemic control and cardiometabolic health among adults with overweight/obesity and type 2 diabetes. RESEARCH DESIGN AND METHODS: This two-center, open-label, three-arm, parallel-group, randomized controlled trial recruited 326 participants with overweight/obesity and type 2 diabetes and randomized them into 12 weeks of diet intervention (n = 109), exercise intervention (n = 108), or lifestyle education (control) (n = 109). The primary outcome was the change of glycemic control measured as glycated hemoglobin (HbA1c) between the diet or exercise intervention groups and the control group after the 12-week intervention. RESULTS: The diet intervention significantly reduced HbA1c level (%) after the 12-week intervention (-0.72, 95% CI -0.95 to -0.48) compared with the control group (-0.37, 95% CI -0.60 to -0.15) (diet vs. control -0.34, 95% CI -0.58 to -0.11, P = 0.007). The reduction in HbA1c level in the exercise intervention group (-0.46, 95% CI -0.70 to -0.23) did not significantly differ from the control group (exercise vs. control -0.09, 95% CI -0.32 to 0.15, P = 0.47). The exercise intervention group was superior in maintaining lean body mass. Both diet and exercise interventions induced improvements in adiposity and hepatic steatosis. CONCLUSIONS: These findings suggest that the medically supervised 5:2 energy-restricted diet could provide an alternative strategy for improving glycemic control and that the exercise regimen could improve body composition, although it inadequately improved glycemic control.

Demographic bias in misdiagnosis by computational pathology models.

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

Detunable wireless resonator arrays for TMJ MRI: A comparative study.

Temporomandibular Joint Magnetic Resonance Imaging (TMJ MRI) is crucial for diagnosing temporomandibular disorders (TMDs). This study advances the use of inductively coupled wireless coils to enhance imaging quality in TMJ MRI. After investigating multiple wireless resonator configurations, including a 1-loop design with a loop diameter of 9 cm, a 2-loop design with each loop having a diameter of 7 cm, and a 3-loop design with each loop having a diameter of 5 cm, our findings indicate that the 3-loop configuration achieves the optimal signal-to-noise ratio (SNR), surpassing other wireless arrays. Bilateral deployment of wireless coils further amplifies SNR, enabling superior visualization of TMJ structures, particularly with the 3-loop design. This cost-effective and comfortable solution, featuring a detunable design, eliminates the need for system parameter adjustments. The study indicates broad adaptability across MRI platforms, enhancing TMJ imaging for routine clinical diagnostics of TMDs.

Relationship between the natural cessation time of umbilical cord pulsation in full-term newborns delivered vaginally and maternal-neonatal outcomes: a prospective cohort study.

BACKGROUND: To analyze the impact of the time of natural cessation of the umbilical cord on maternal and infant outcomes in order to explore the time of clamping that would be beneficial to maternal and infant outcomes. METHODS: The study was a cohort study and pregnant women who met the inclusion and exclusion criteria at the Obstetrics and Gynecology Department of Qilu Hospital of Shandong University from September 2020 to September 2021. Analysis using Kruskal-Wallis rank sum test, Pearson's Chi-squared test, generalized linear mixed model (GLMM) and repeated measures ANOVA. If the difference between groups was statistically significant, the Bonferroni test was then performed. A two-sided test of P < 0.05 was considered statistically significant. RESULTS: A total of 345 pregnants were included in this study. The subjects were divided into the ≤60 seconds group (n = 134), the 61-89 seconds group (n = 106) and the ≥90 seconds group (n = 105) according to the time of natural arrest of the umbilical cord. There was no statistically significant difference in the amount of postpartum hemorrhage and the need for iron, medication, or supplements in the postpartum period between the different cord spontaneous arrest time groups for mothers (P > 0.05). The weight of the newborns in the three groups was (3316.27 ± 356.70) g, (3387.26 ± 379.20) g, and (3455.52 ± 363.78) g, respectively, and the number of days of cord detachment was 12.00 (8.00, 15.75) days, 10.00 (7.00, 15.00) days and 9.00 (7.00, 13.00) days, respectively, as the time of natural cessation of the cord increased. The neonatal lymphocyte ratio, erythrocyte pressure, and hemoglobin reached a maximum in the 61-89 s group at (7.41 ± 2.16) %, (61.77 ± 8.17) % and (194.52 ± 25.84) g/L, respectively. Lower incidence of neonatal hyperbilirubinemia in the 61-89 s group compared to the ≥90s group 0 vs 4.8 (P < 0.05). CONCLUSIONS: In full-term singleton vaginal births, maternal and infant outcomes are better when waiting for 61-89 s after birth for the cord to stop pulsating naturally, suggesting that we can wait up to 90s for the cord to stop pulsating naturally, and if the cord does not stop pulsating after 90s, artificial weaning may be more beneficial to maternal and infant outcomes.

Identification of immune-associated biomarker for predicting lung adenocarcinoma: bioinformatics analysis and experiment verification of PTK6.

BACKGROUND: Abnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear. OBJECTIVE: The aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance. METHODS: The prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses. RESULTS: PTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-ß signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed. CONCLUSION: PTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1.

Bibliometric and visualized analysis of type 2 diabetic osteoporosis from 2013 to 2022.

Type 2 diabetic osteoporosis (T2DOP) has received increasing attention from researchers. In this study, a total of 453 publications related to T2DOP from 2013 to 2022 were analyzed using bibliometric and visual analysis to identify the research trends and research hotspots in the field of T2DOP. PURPOSE: The objective of this study was to conduct a comprehensive bibliometric analysis of T2DOP-related publications from 2013 to 2022 to determine global research trends in T2DOP in terms of number of publications, countries/regions, institutions, authors, journals, funding agencies, and keywords. METHODS: All data were collected from the Web of Science Core Collection (WoSCC). All original research publications regarding T2DOP from 2013 to 2022 were retrieved. VOSviewer and Microsoft Office Excel were used to conduct the bibliometric and visual analysis. RESULTS: From 2013 to 2022, 515 relevant publications were published, with a peak in 2022 in the annual number of publications. The countries leading the research were USA and China. Sugimoto was the most influential authors. Capital Medical University and Nanjing Medical University were the most prolific institutions. Osteoporosis International was the most productive journal concerning T2DOP research. National Natural Science Foundation of China was the primary funding source for this research area. "Bone-mineral density", "fracture risk", and "postmenopausal women" were the most high-frequency keywords over the past 10 years. CONCLUSION: This was the first bibliometric study of diabetes mellitus and osteoporosis to exclusively examine type 2 diabetes mellitus. Our findings would provide guidance to understand the research frontiers and hot directions in the near future.

Synthesis, Characterization, and Properties of Heat-Resistant Energetic Materials Based on C-C Bridged Dinitropyrazole Energetic Materials.

Polycyclic energetic materials make up a distinctive class of conjugated structures that consist of two or more rings. In this work, 1,3-bis(3,5-dinitro-1H-pyrazol-4-yl)-4,6-dinitrobenzene (BDPD) was synthesized and investigated in detail as a polycyclic heat-resistant energetic molecule that can be deprotonated by bases to obtain its anionic (3-5) salts. All compounds were thoroughly characterized by 1H and 13C NMR, infrared spectroscopy, high-resolution mass spectrometry, and elemental analysis. The structural features of BDPD and its salts were investigated by single-crystal X-ray diffraction and analyzed by different kinds of computing software, like Multiwfn, Gaussian 09W, and so on. In addition, their thermal decomposition temperatures were evaluated by differential scanning calorimetry to be 319.8-329.0 °C, revealing that they possessed high thermal stabilities. The results of impact sensitivity and friction sensitivity analysis confirm that these energetic compounds were insensitive. The detonation properties of neutral compound BDPD and all its nonmetallic salts were calculated by the EXPLO5 v6.05.04 program. The results revealed that their detonation performances were higher than those of the widely used heat-resistant explosive 2,2',4,4',6,6'-hexanitrostilbene (HNS). Combining the above results, it is reasonable to suggest that these compounds have the potential to be heat-resistant energetic materials.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

Architecture of integrated solid-state zinc-ion battery based on sodium alginate gelation.

How to construct a new electrode/electrolyte interface structure in solid-state batteries (SSBs), enhance interface stability, and improve the cycling performance of SSBs is a great challenge for the development of SSBs. Here, an all-in-one "interface-free" structure was developed. This interfacial structure constructs a full-interface hydrogen bonding network through the abundant hydrogen bond donors and acceptors in the cathode and electrolyte to enhance the interfacial stability and avoid interfacial failure during charging and discharging, and generates cathode-electrolyte interface (CEI) in-situ to effectively regulate zinc ion transport. Square cells assembled in this structure are stabilized for 100 cycles at a current density of 0.1 mA cm-2. This integrated electrode provides a new idea for the long stable cycle of SSBs.

Focusing on mitochondria in the brain: from biology to therapeutics.

Mitochondria have multiple functions such as supplying energy, regulating the redox status, and producing proteins encoded by an independent genome. They are closely related to the physiology and pathology of many organs and tissues, among which the brain is particularly prominent. The brain demands 20% of the resting metabolic rate and holds highly active mitochondrial activities. Considerable research shows that mitochondria are closely related to brain function, while mitochondrial defects induce or exacerbate pathology in the brain. In this review, we provide comprehensive research advances of mitochondrial biology involved in brain functions, as well as the mitochondria-dependent cellular events in brain physiology and pathology. Furthermore, various perspectives are explored to better identify the mitochondrial roles in neurological diseases and the neurophenotypes of mitochondrial diseases. Finally, mitochondrial therapies are discussed. Mitochondrial-targeting therapeutics are showing great potentials in the treatment of brain diseases.

Self-healing hydrogel based on poly (vinyl alcohol)-poly (lysine)-gum arabic accelerates diabetic wound healing under photothermal sterilization.

Diabetic wounds are a significant clinical challenge. Developing effective antibacterial dressings is crucial for preventing wound ulcers caused by bacterial infections. In this study, a self-healing antibacterial hydrogel (polyvinyl alcohol (PVA)-polylysine-gum arabic, PLG hydrogels) with near-infrared photothermal response was prepared by linking PVA and a novel polysaccharide-amino acid compound (PG) through borate bonding combined with freeze-thaw cycling. Subsequently, the hydrogel was modified by incorporating inorganic nanoparticles (modified graphene oxide (GM)). The experimental results showed that the PLGM3 hydrogels (PLG@GM hydrogels, 3.0 wt%) could effectively kill bacteria and promote diabetic wound tissue healing under 808-nm near-infrared laser irradiation. Therefore, this hydrogel system provides a new idea for developing novel dressings for treating diabetic wounds.

Towards a more practical analysis of Newton's rings using deep learning.

As a typical form of optical fringes with a quadratic phase, Newton's ring patterns play an important role in spherical measurements and optical interferometry. A variety of methods have been used to analyze Newton's ring patterns. However, it is still rather challenging to fulfill the analysis. We present a deep-learning-based method to estimate the parameters of Newton's ring patterns and fulfill the analysis accordingly. The experimental results indicate the excellent accuracy, noise robustness, and demodulation efficiency of our method. It provides another applicable approach to analyzing Newton's ring patterns and brings insights into fringe analysis and interferometry-based measurements.

The role of short-chain fatty acids in central nervous system diseases: A bibliometric and visualized analysis with future directions.

Background: Short-chain fatty acids (SCFAs) are thought to play a key role in the microbe-gut-brain axis and involve in the pathogenesis of a variety of neurological diseases. This study aimed to identify research hotspots and evolution trends in SCFAs in central nervous diseases (CNS) and examine current research trends. Methods: The bibliometric analysis was performed using CiteSpace, and the results were visualized via network maps. Results: From 2002 to 2022, 480 publications in the database met the criteria. On the country level, China produced the highest number of publications, while the United States had the highest centrality. On the institutional level, University College Cork contributed to the most publications, and John F. Cryan from this university was the key researcher with considerable academic influence. The article, the role of short-chain fatty acids in microbiota-gut-brain, written by Boushra Dalile et al., in 2019 was the most cited article. Furthermore, the journal Nutrients had the maximum number of publications, while Plos One was the most cited journal. "Gut microbiome", "SCFAs", and "central nervous system" were the three most frequent keywords. Among them, SCFAs had the highest centrality. "Animal model" was the keyword with the highest burst strength, with the latest burst keywords being "social behavior", "pathogenesis", and "insulin sensitive". In addition, the research topics on SCFAs in CNS diseases from 2002 to 2022 mainly focused on following aspects: SCFAs plays a key role in microbe-gut-brain crosstalk; The classification and definition of SCFAs in the field of CNS; Several CNS diseases that are closely related to SCFAs research; Mechanism and translational studies of SCFAs in the CNS diseases. And the hotspots over the past 5 years have gradually increased the attention to the therapeutic potential of SCFAs in the CNS diseases. Conclusion: The research of SCFAs in CNS diseases is attracting growing attention. However, there is a lack of cooperation between countries and institutions, and additional measures are required to promote cooperation. The current evidence for an association between SCFAs and CNS diseases is preliminary and more work is needed to pinpoint the precise mechanism. Moreover, large-scale clinical trials are needed in the future to define the therapeutic potential of SCFAs in CNS diseases.

Natural polymorphisms in ZMET2 encoding a DNA methyltransferase modulate the number of husk layers in maize.

DNA methylation affects agronomic traits and the environmental adaptability of crops, but the natural polymorphisms in DNA methylation-related genes and their contributions to phenotypic variation in maize (Zea mays) remain elusive. Here, we show that a polymorphic 10-bp Indel (insertion/deletion) variant in the 3' untranslated region (3'UTR) of Zea methyltransferase2 (ZMET2) alters its transcript level and accounts for variation in the number of maize husk layers. ZMET2 encodes a chromomethylase and is required for maintaining genome-wide DNA methylation in the CHG sequence context. Disruption of ZMET2 increased the number of husk layers and resulted in thousands of differentially methylated regions, a proportion of which were also distinguishable in natural ZMET2 alleles. Population genetic analyses indicated that ZMET2 was a target of selection and might play a role in the spread of maize from tropical to temperate regions. Our results provide important insights into the natural variation of ZMET2 that confers both global and locus-specific effects on DNA methylation, which contribute to phenotypic diversity in maize.

What are optimum cycles for immediate primary closure of large cutaneous defects?

BACKGROUND: In the reconstruction of large complex cutaneous wounds, a myriad of mechanical devices has been designed to facilitate primary wound closure. However, there is a dearth of studies elucidating how best to achieve optimum use and efficiency of skin stretching (SS) when using the device for immediate primary closure of defects. METHODS: Skin defect wounds (7 × 7 cm) were prepared on the back of three Bama miniature pigs. A total of 15 cycles of SS (cycle loading) were subsequently performed on the skin edges of the wound by EASApprox® SS system. Then, the changes in equidistant points were recorded after each cycle. After the SS test, all wounds were sutured under low tension. RESULTS: Skin elongation was observed at all equidistant points on the back wounds of three Bama miniature pigs. Up to an additional 1.10 to 3.75 cm of tissue was garnered. The maximum skin elongation was typically achieved within eight cycles of stretching and relaxation. Beyond this range, additional stretching cycles did not result in further skin extension. CONCLUSION: There may be a close link between mobilization range and the times of acute cyclic stretching (cycle loading) during the process of primary wound closure. However, larger studies are required to further evaluate the accuracy and effectiveness.

Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

Workplace psychosocial factors, work organization, and physical exertion as risk factors for low back pain among U.S. workers: Data from the 2015 National Health Interview Survey.

OBJECTIVE: To evaluate the association between workplace psychosocial, organization, and physical risk factors with low back pain (LBP) among U.S. workers. METHODS: 2015 National Health Interview Survey data was analyzed to calculate prevalences and prevalence ratios for LBP across levels of workplace psychosocial and organizational risk factors among 17,464 U.S. adult workers who worked ≥20 hours/week. Results were also stratified by workplace physical exertion. RESULTS: The adjusted prevalences of LBP were significantly elevated for workers reporting high job demand, low job control, work-family imbalance, bullying, job insecurity, working alternate shifts, and physical exertion. Job control and nonstandard shifts were significantly associated with LBP only among those who reported low/no physical exertion. CONCLUSIONS: LBP prevalence was associated with select workplace psychosocial and organization risk factors. Stratification by physical exertion modified multiple associations.

Thermodynamic Origin-Based In Situ Electrochemical Construction of Reversible p-n Heterojunctions for Optimal Stability in Potassium Ion Storage.

Heterojunctions in electrode materials offer diverse improvements during the cycling process of energy storage devices, such as volume change buffering, accelerated ion/electron transfer, and better electrode structure integrity, however, obtaining optimal heterostructures with nanoscale domains remains challenging within constrained materials. A novel in situ electrochemical method is introduced to develop a reversible CuSe/PSe p-n heterojunction (CPS-h) from Cu3 PSe4 as starting material, targeting maximum stability in potassium ion storage. The CPS-h formation is thermodynamically favorable, characterized by its superior reversibility, minimized diffusion barriers, and enhanced conversion post K+ interaction. Within CPS-h, the synergy of the intrinsic electric field and P-Se bonds enhance electrode stability, effectively countering the Se shuttling phenomenon. The specific orientation between CuSe and PSe leads to a 35° lattice mismatch generates large space at the interface, promoting efficient K ion migration. The Mott-Schottky analysis validates the consistent reversibility of CPS-h, underlining its electrochemical reliability. Notably, CPS-h demonstrates a negligible 0.005% capacity reduction over 10,000 half-cell cycles and remains stable through 2,000 and 4,000 cycles in full cells and hybrid capacitors, respectively. This study emphasizes the pivotal role of electrochemical dynamics in formulating highly stable p-n heterojunctions, representing a significant advancement in potassium-ion battery (PIB) electrode engineering.