Volume Growth Research Articles

High-density sampling reveals volume growth in human tumours

In growing cell populations such as tumours, mutations can serve as markers that allow tracking the past evolution from current samples. The genomic analyses of bulk samples and samples from multiple regions have shed light on the evolutionary forces acting on tumours. However, little is known empirically on the spatio-temporal dynamics of tumour evolution. Here, we leverage published data from resected hepatocellular carcinomas, each with several hundred samples taken in two and three dimensions. Using spatial metrics of evolution, we find that tumour cells grow predominantly uniformly within the tumour volume instead of at the surface. We determine how mutations and cells are dispersed throughout the tumour and how cell death contributes to the overall tumour growth. Our methods shed light on the early evolution of tumours in vivo and can be applied to high-resolution data in the emerging field of spatial biology.

Empirical study of the impact of E-CNY on low-carbon economy from AI trust concerns

The low-carbon economy is the major objective of China’s economy, and its goal is to achieve sustainable economic development. The study enriches the literature on the relationship between digital Chinese yuan (E-CNY), low-carbon economy, AI trust concerns, and security intrusion. The rapid growth of Artificial Intelligence (AI) offered more ways to achieve a low-carbon economy. The digital Chinese yuan (E-CNY), based on the AI technique, has shown its nature and valid low-carbon characteristics in pilot cities of China, it will assume important responsibilities and become the key link. However, trust concerns about AI techniques result in a limitation of the scope and extent of E-CNY usage. The study conducts in-depth research from the perspective of AI trust concerns, explores the influence of E-CNY on the low-carbon economy, and discusses the moderating and mediating mechanisms of AI trust concerns in this process. The empirical data results showed that E-CNY positively affects China’s low-carbon economy, and AI trust concerns moderate the positive impact. When consumers with higher AI trust concerns use E-CNY, their feeling of security intrusion is also higher. It affects the growth of trading volume and scope of E-CNY usage. Still, it reduces the utility of China’s low-carbon economy. This study provides valuable management inspiration for China’s low-carbon economy.

Finite generation of fundamental groups for manifolds with nonnegative Ricci curvature whose universal cover is almost 𝑘-polar at infinity

Abstract In this article, we prove that the fundamental group π 1 ⁢ ( M ) \pi_{1}(M) of a complete open manifold 𝑀 with nonnegative Ricci curvature is finitely generated, under the condition that the Riemannian universal cover M ̃ \tilde{M} satisfies an “almost 𝑘-polar at infinity” condition. Additionally, such π 1 ⁢ ( M ) \pi_{1}(M) is virtually abelian. Furthermore, we demonstrate that the base point of any tangent cone at infinity of such a manifold is nearly a pole. In the case where M ̃ \tilde{M} exhibits almost maximal Euclidean volume growth, we prove that 𝑀 deformation retracts to a closed submanifold 𝐹 which is diffeomorphic to a flat manifold, provided 𝑀 is not simply connected.

Artificial intelligence technologies in medicine: development dynamics in the Russian Federation and abroad

The rapid development of information technology in healthcare, the growth of data volumes and the complexity of diagnostic and treatment methods have led to the fact that artificial intelligence has begun to be used more and more often in this industry.The article examines the current state of artificial intelligence development in two leading healthcare countries: the Russian Federation and the United States of America. The choice of comparison objects is due to the openness of official sources of information on the state of the industry, as well as the high actual level of development of digitalization of medicine in these countries. The comparison was carried out on five points: prevalence, legal regulation, development directions, responsibility for development and the possibility of integration with the existing digital healthcare circuit.

TransmiR v3.0: an updated transcription factor-microRNA regulation database.

microRNAs (miRNAs) are active in various biological processes by mediating gene expression, and the full investigation of miRNA transcription is crucial for understanding the mechanisms underlying miRNA deregulation in pathological conditions. Here an updated TransmiR v3.0 database is presented with more comprehensive miRNA transcription regulation information, which contains 5095 transcription factor (TF) -miRNA regulations curated from 2285 papers and >6 million TF-miRNA regulations derived from ChIP-seq data. Currently, TransmiR v3.0 covers 3260 TFs, 4253 miRNAs and 514433 TF-miRNA regulation pairs across 29 organisms. Additionally, motif scanning of TF loci on promoter sequences of miRNAs from multiple species is employed to predict TF-miRNA regulations, generating 284527 predicted TF-miRNA regulations. Besides the significant growth of data volume, we also improve the annotations for TFs and miRNAs by introducing the TF family, TFBS motif, and expression profiles for several species. Moreover, the functionality of the TransmiR v3.0 online database is enhanced, including allowing batch search for flexible queries and offering more extensive disease-specific, as well as newly sex-specific TF-miRNA regulation networks in the 'Network' module. TransmiR v3.0 provides a useful resource for studying miRNA biogenesis regulation and can be freely accessed at http://www.cuilab.cn/transmir.

CSIG-04. ANTI-TUMOR RESPONSE OF ONCOMAGNETIC MONOTHERAPY IN GLIOBLASTOMA

Abstract BACKGROUND Glioblastoma (GBM) is the most lethal primary malignant brain tumor with a median survival of 15–20 months. Concurrent temozolomide (TMZ) chemotherapy and radiation (XRT) remain the current standard of care (SOC) treatment for newly diagnosed GBM. The addition of tumor treating fields (TTFs) improves median survival for newly diagnosed GBM from 16 to 20.9 months. This modest improvement underscores the urgent need to identify a new treatment modality as a safe and effective therapy. PURPOSE The noninvasive Oncomagnetic device developed in our laboratory selectively kills glioblastoma (GBM) in vitro. We studied the cellular and molecular effects of Oncomagnetic monotherapy (OMT) on GBM cell lines and investigated immune response in a syngeneic mouse model. RESULTS OMT significantly reduces cell proliferation and cell survival in vitro. OMT induces persistent ROS primarily by increasing superoxide level in cancer cells and reduces mitochondrial-membrane potential in GBM cells. It also induces DNA damage and arrests cells in G1-phase of the cell cycle. Whole-body Oncomagnetic stimulation caused a substantial retardation of tumor growth and reduction of the contrast-enhanced tumor volume in 9.4T MRI scans. OMT showed significant increase in overall survival in treated mice. We also observed upregulated immune response indicated by RNA sequencing data obtained from OMT-treated GBM cells as well as in treated GBM mouse tumor sections by imaging mass cytometry analysis. The tSNE analysis of various immune clusters suggests significant increase in immune response by activating CD4+, CD8+, murine-macrophages and M1-macrophages located at tumor site in the treated group. CONCLUSION The obtained data indicate significant anti-tumor response by inhibiting cancer signaling pathways and an increased immune response. Our findings suggest unique mechanism of action for OMT stimulation and provide a strong rationale for standalone OMT for GBM.

Regional Framework Towards Establishing Treatment, Storage, and Disposal (TSD) Facilities for PV Waste Management in the Philippines: A Case Study of Laguna Province

Abstract. The accelerated adoption of photovoltaic (PV) systems for renewable power generation in the Philippines will yield a tremendous amount of PV waste. However, the country lacks a comprehensive framework for understanding PV module waste volume growth and optimally siting Treatment, Storage, and Disposal (TSD) facilities for PV waste management based on minimum siting factor. The study aims to develop a regional framework that utilizes a geographic information system (GIS)-based approach to find the potential sites and optimal locations of TSD facilities in Laguna, Philippines, based on the estimated PV module waste growth of solar energy systems with service contracts and minimum siting criteria under Department of Environment and Natural Resources (DENR) Administrative Order 2013-22. By 2060, the projected amount of PV module waste in Laguna province will be around 162,230 metric tons based on the waste projection results. The suitable sites cover around 19,720.5 hectares or 11.21% of the total land area of Laguna, which were determined by various siting factors that encompass social, economic, and environmental factors and obtained using binary suitability analysis and vector overlay analysis. The optimal locations of the two TSD facilities were identified using strategic positioning based on hotspot analysis, clustering algorithm, and proximity analysis. Consequently, the distance and GHG emissions of the two optimal locations were calculated. Indeed, the approach will serve as a guide for policymakers and other stakeholders in understanding PV module waste growth and strategically and optimally position TSD facilities on suitable sites for efficient and effective PV waste management.

Dampak Penggunaan Quick Response Code Indonesia Standard Bagi Kinerja UMKM Nasabah KUR PT. Pegadaian Cabang Wonosobo

This study aims to analyze the impact of using the Quick Response Code Indonesia Standard on the Performance of MSMEs that are customers of the KUR at PT. Pegadaian Wonosobo Branch. Utilizing a quantitative approach, this research collected data through survey using non-probability sampling techniques to obtain a representative sample of the population of MSME in Wonosobo and Banjarnegara Regency who use QRIS. The QRIS variable indicators include ease of use, understanding, satisfaction, and security, while the MSME performance indicators encompass profitability, number of customers, sales volume, and asset growth. Data analysis was conducted using SmartPLS 4 software to test the hypotheses and research model. The results indicate that the use of Quick Response Code Indonesia Standard has a positive and significant impact on improving MSME performance, with a coefficient value of 0.839, a t-statistic of 19.085 and p-value of 0.000. these findings suggest that the implementation of QRIS facilitates more efficient and secure transaction processes and contributes to increase profitability, customer number, sales and assets of MSMEs that are KUR customers.

The benefit of automated sac volume measurements in postoperative endovascular aortic repair surveillance

Abdominal aortic aneurysm (AAA) shrinkage is considered a marker for success following endovascular aortic repair (EVAR). Although maximum diameter is widely used to assess sac behavior, research indicates that changes in AAA morphology do not always affect the maximum diameter. The aim of this study is to investigate if automated AAA sac volume measurements after EVAR can add more nuanced information on sac behavior compared with maximum diameter evaluation alone. A retrospective review of all patients treated for AAA with a standard or fenestrated EVAR at two tertiary referral centers was performed. Patients with a pre- and postoperative computed tomography angiography (CTA) ≥ two years after treatment were included. Data were collected using medical charts, radiologic institutional databases, and a deep learning based method called Augmented Reality for Vascular Aneurysm (ARVA). Volume and diameter assessments were automatically performed on CTAs using ARVA. Preoperative sac volumes and diameters were compared with those obtained at least two years after repair. Information on endoleaks (ELs) was collected. Continuous data were tested using t-test, and categorical data were tested using chi-square or Fishers test, depending on sample size. A total of 89 patients (standard EVAR n=46; fenestrated EVAR n=43) were included in this study. Of the 89 patients, 41 (46%) had sac diameter shrinkage, 38 (43%) had stable sac diameters, and 10 (11%) had diameter sac growth during follow-up. The distribution of sac volume behavior was different amongst these patients: 51 (57%) had volume shrinkage, only 9 (10%) had stable volumes, and 29 (33%) had volume growth. Significantly more patients had sac growth, and fewer had sac stability, when assessed with volume compared with diameter, p=.003 and p<.001, respectively. The increase in patients with volume-assessed sac shrinkage (57% vs 46%) was not statistically significant. Of the 18 (20%) patients with stable sac diameters and simultaneous volume growth, 13 (72%) had ELs (T2ELs: n=9, T1ELs, n=2, T3EL: n=1, and EL of undefined origin: n=1). This study found that volume-assessed sac behavior identifies more sac shrinkage or growth, and less sac stability than diameter does. If confirmed by larger studies, sac volume assessment should be performed routinely after endovascular repair.

Factors Affecting Export Demand for Malaysian Palm-Based Finished Products

The encouraging growth in volume and exports of palm-based finished products (PBFP) was directly related to an increase in their demand. It is thus important to investigate the factors influencing such demand. Our study attempts to elucidate this for the Malaysian PBFP in 10 major foreign markets, namely, Turkey, China, Iraq, Iran, Singapore, Romania, Australia, Pakistan, Russia, and Saudi Arabia. This study constitutes a panel data analysis for the 10 countries using data from 2007 to 2021 using the fully modified ordinary least squares (FMOLS) method. Pedroni and Westerlund cointegration test indicates the presence of a long-term relationship between the variables under study. The empirical results show that gross domestic product (GDP) has a long-term positive influence on the demand for PBFP, with every 1% increase in GDP will increase the demand for palm oil by 0.9%. In addition, population size (POP) also shows a positive sign and is statistically significant at the 1% level, indicating that a 1% increase in POP will lead to a 0.3% increase in PBFP demand. Substitute oil price also has a long-run positive influence where for every 1% increase in the price of both commodities will increase the demand for PBFP by 0.1%. Meanwhile the price of PBFP has a long-term positive influence on its demand. Thus, information regarding the factors influencing the demand for PBFP from our findings may help industry player and policymakers in formulating strategies to improve the markets, and academicians may also benefit from sharing the knowledge gained from the study.

Genomic selection in forest trees comes to life: unraveling its potential in an advanced four-generation Eucalyptus grandis population.

Genomic Selection (GS) in tree breeding optimizes genetic gains by leveraging genomic data to enable early selection of seedlings without phenotypic data reducing breeding cycle and increasing selection intensity. Traditional assessments of the potential of GS in forest trees have typically focused on model performance using cross-validation within the same generation but evaluating effectively realized predictive ability (RPA) across generations is crucial. This study estimated RPAs for volume growth (VOL), wood density (WD), and pulp yield (PY) across four generations breeding of Eucalyptus grandis. The training set spanned three generations, including 34,461 trees with three-year growth data, 6,014 trees with wood quality trait data, and 1,918 trees with 12,695 SNPs (single nucleotide polymorphisms) data. Employing single-step genomic BLUP, we compared the genomic predictions of breeding values (GEBVs) for 1,153 fourth-generation full-sib seedlings in the greenhouse with their later-collected phenotypic estimated breeding values (EBVs) at age three years. RPAs were estimated using three GS targets (individual trees, trees within families, and families), two selection criteria (single- and multiple-trait), and training populations of either all 1,918 genotyped trees or the 67 direct ancestors of the selection candidates. RPAs were higher for wood quality traits (0.33 to 0.59) compared to VOL (0.14 to 0.19) and improved for wood traits (0.42 to 0.75) but not for VOL when trained only with direct ancestors, highlighting the challenges in accurately predicting growth traits. GS was more effective at excluding bottom-ranked candidates than selecting top-ranked ones. The between-family GS approach outperformed individual-tree selection for VOL (0.11 to 0.16) and PY (0.72 to 0.75), but not for WD (0.43 vs. 0.42). Furthermore, higher levels of relatedness and lower genotype by environment (G × E) interaction between training and testing populations enhanced RPAs for VOL (0.39). In summary, despite limited effectiveness in ranking top VOL individuals, GS effectively identified low-performing individuals and families. These multi-generational findings underscore GS's potential in tree breeding, stressing the importance of considering relatedness and G × E interaction for optimal performance.

Patient-specific prostate tumour growth simulation: a first step towards the digital twin.

Prostate cancer (PCa) is a major world-wide health concern. Current diagnostic methods involve Prostate-Specific Antigen (PSA) blood tests, biopsies, and Magnetic Resonance Imaging (MRI) to assess cancer aggressiveness and guide treatment decisions. MRI aligns with in silico medicine, as patient-specific image biomarkers can be obtained, contributing towards the development of digital twins for clinical practice. This work presents a novel framework to create a personalized PCa model by integrating clinical MRI data, such as the prostate and tumour geometry, the initial distribution of cells and the vasculature, so a full representation of the whole prostate is obtained. On top of the personalized model construction, our approach simulates and predicts temporal tumour growth in the prostate through the Finite Element Method, coupling the dynamics of tumour growth and the transport of oxygen, and incorporating cellular processes such as proliferation, differentiation, and apoptosis. In addition, our approach includes the simulation of the PSA dynamics, which allows to evaluate tumour growth through the PSA patient's levels. To obtain the model parameters, a multi-objective optimization process is performed to adjust the best parameters for two patients simultaneously. This framework is validated by means of data from four patients with several MRI follow-ups. The diagnosis MRI allows the model creation and initialization, while subsequent MRI-based data provide additional information to validate computational predictions. The model predicts prostate and tumour volumes growth, along with serum PSA levels. This work represents a preliminary step towards the creation of digital twins for PCa patients, providing personalized insights into tumour growth.

Preoperative Tumor Growth Rate Does Not Predict Overall or Progression-free Survival in Patients With Glioblastoma.

Presurgical tumor volume progression in glioblastoma (GBM) may be a predictor of survival. This study aims to evaluate the potential impact of preoperative tumor growth and other clinical as well as laboratory parameters on overall survival (OS) of GBM patients. We retrospectively analyzed 98 adult patients with GBM who received two magnetic resonance imaging (MRI) scans between 2013 and 2023, before primary surgery and concurrent Stupp chemoradiotherapy. Tumor growth rates were calculated to classify GBM into slower and faster growing categories. Statistical analyses, including Kaplan-Meier and multivariable Cox regression survival analyses, were performed to evaluate the impact of various clinical and treatment-related factors on OS and progression-free survival (PFS). Slower growing tumors had a significantly longer doubling time than faster growing lesions. Univariable analysis showed no significant differences in OS (p=0.12) or PFS (p=0.4) when analyzed according to tumor growth. When stratified by O6-methylguanin-DNA-methyltransferase (MGMT) status, there were still no differences in OS (p=0.14), but in PFS (p=0.009). In the multivariable Cox regression analysis, radiation dose (p=0.02) and the number of adjuvant cycles of temozolomide (TMZ) (p=0.002) were significantly associated with OS. MGMT status (p=0.02) and the number of adjuvant TMZ cycles (p<0.001) were significantly associated with prolonged PFS. Specific volume growth rate (SVGR), patient age, baseline tumor volume, Karnofsky performance status, extent of resection, and total radiation dose were not significantly associated with PFS. SVGR was not significantly associated with OS or PFS. In contrast, MGMT status, radiation dose, and number of adjuvant TMZ cycles were identified as predictors of treatment outcomes. These factors can guide physicians when designing personalized treatment concepts for patients with GBM.

Longitudinal trends in testicular volume z scores from puberty to adulthood, sperm quality, and paternity outcomes after childhood cancer.

Childhood cancer therapy may cause subfertility. This study correlated cancer therapy exposures with testicular volumes from puberty to adulthood, spermatogenesis, and paternity outcomes in adulthood. The study population comprised 255 male childhood cancer survivors (CCS) (survival ≥5 years, diagnosed in 1964-2000 at the Helsinki Children's Hospital) whose testicular volume was measured at ages 12 years (n=38), 14 years (n=57), 16 years (n=63), 18 years (n=105), and in adulthood (n=43; median age, 27 years). Testicular volumes were converted to age-specific z scores. In addition, 92 CCS provided semen sample in adulthood (median age, 25.2 years); and paternity was evaluated through national register data (mean age at assessment, 37.6 years; n=252). Compared with age-specific reference values, CCS generally exhibited low testicular volume z scores at ages 12-18 years. Testicular volume z scores in CCS treated exclusively with chemotherapy returned to the reference range in adulthood. In contrast, patients exposed to testicular radiation ≥1 gray (Gy) (median dose, 12 Gy) showed no late recovery in testicular size. Testicular radiation ≥1 Gy and a cyclophosphamide equivalent dose ≥12 g/m2 were identified as risk factors for azoospermia in adulthood. Patients exposed to testicular radiation ≥1 Gy and a cyclophosphamide equivalent dose ≥4 g/m2 had lower paternity rates. Testicular volume growth after prolonged follow-up suggests a potential late recovery of spermatogenesis in CCS treated exclusively with chemotherapy. However, alkylating agents increased the risk of having prolonged azoospermia and nonpaternity. High-dose testicular radiation causes long-term depletion of spermatogonia and was the strongest risk factor for azoospermia and nonpaternity.

Branch-and-Price for the Capacitated Autonomous Vehicle Assisted Delivery Problem

In recent years, the exponential growth of package volumes has posed significant challenges for logistics networks, particularly in the realm of last-mile delivery. To mitigate costs while upholding service and delivery commitments, companies are increasingly investigating autonomous assisted delivery as a viable solution. In this paper, we study the Capacitated Autonomous Vehicle Assisted Delivery Problem, where an autonomous vehicle works in conjunction with a delivery person. The autonomous vehicle drops off the delivery person at designated locations, and the delivery person completes the deliveries (with a capacity constraint) on foot to the final addresses. Once the deliveries are completed, the vehicle picks up the delivery person and travels to the next reloading point. The goal is to decide on a route to serve all customers while minimizing the route completion time. We introduce an integer programming formulation with exponentially many variables and develop a branch-and-price approach. For generating promising columns, we present a tailored pulse algorithm to solve the pricing problem. Furthermore, by leveraging the structural properties of optimal solutions, we carefully design algorithmic enhancements, valid inequalities, and preprocessing steps to improve computational tractability. By conducting computational experiments based on instances derived from real-world data, we demonstrate the positive impact of these components. More importantly, we provide optimal certificates for 426 out of the 450 instances documented in the literature. Among the 100 instances in which driving could be slower than walking, we report solutions for the 40 largest instances for the first time. History: Accepted by David Alderson, Area Editor for Network Optimization. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0177 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0177 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Porphyromonas gingivalis Promotes Oral Squamous Cell Carcinoma Progression by Modulating Autophagy.

Porphyromonas gingivalis (P. gingivalis) is a keystone periodontal pathogen associated with various gastro-intestinal tract cancers. However, whether P. gingivalis can promote oral squamous cell carcinoma (OSCC) and the underlying mechanism associated with such promotion remain unclear. In this study, OSCC xenograft models were used to evaluate the effects of P. gingivalis on tumor progression. The functional studies were done on several OSCC cell lines invitro. P. gingivalis-specific 16S rRNA fluorescent insitu hybridization (FISH) was used to test its prevalence in clinical samples. We found that P. gingivalis increased tumor volume and tumor growth in OSCC nude models. Functional studies demonstrated that P. gingivalis inhibited the apoptosis of OSCC cells by promoting cellular autophagy. P. gingivalis was more prevalent in FISH samples from patients with OSCC than from patients with leukoplakia or healthy subjects (70% vs. 47.2% vs. 33.3%, p = 0.045 and p < 0.001, respectively). These data suggest that P. gingivalis plays an accelerating role in OSCC progression and contributes to OSCC by enhancing the autophagy pathway to reduce carcinoma apoptosis.

Rigidities of isoperimetric inequality under nonnegative Ricci curvature

The sharp isoperimetric inequality for non-compact Riemannian manifolds with nonnegative Ricci curvature and Euclidean volume growth has been obtained in increasing generality with different approaches in a number of contributions culminated by Balogh and Kristály (2023) also covering metric-measure spaces satisfying the nonnegative Ricci curvature condition in the synthetic sense of Lott, Sturm and Villani. In sharp contrast with the compact case of positive Ricci curvature, for a large class of spaces including weighted Riemannian manifolds, no complete characterization of the equality cases is present in the literature. The scope of this paper is to settle this problem by proving, in the same generality as Balogh and Kristály (2023), that the equality in the isoperimetric inequality can be attained only by metric balls. Whenever this happens the space is forced, in a measure theoretic sense, to be a cone. Our result applies to different frameworks yielding as corollaries new rigidity results: it extends the rigidity results of Brendle (2023) for weighted Riemannian manifolds and the rigidity results of Antonelli et al. (2023) for general \mathsf{RCD} spaces. It also applies to the Euclidean setting by proving that optimizers in the anisotropic and weighted isoperimetric inequality for Euclidean cones are necessarily the Wulff shapes.

Scientific mapping of green organizational culture: Main schools of thought and topical trends

AbstractThe green transition is increasingly viewed as a path to prosperity, or even survival, for organizations. In several countries, greening is vigorously pursued across various organizational activities, including organizational culture, which has garnered significant scholarly attention. However, there appears to be no comprehensive literature review on green organizational culture (GOC) indexed by reputable databases like Scopus. This paper aims to provide a bibliometric overview of GOC. A total of 558 documents from Scopus, spanning 1996–2023, were analyzed using bibliometric methods. The study examines the research performance on GOC, including volume growth trajectory, document types, contributing countries, international collaboration, research groups, influential authors, and prominent sources in GOC research. Notably, it identifies five main schools of thought and two topical trends in GOC literature. This may be the first effort to review GOC literature using Scopus data, highlighting performance and mapping the scientific landscape of this field.

A node deployment and resource optimization method for CPDS based on cloud‐fog‐edge collaboration

AbstractWith the development of the Internet of Things (IoT) in power distribution and the advancement of energy information integration technologies, the explosive growth in network data volume caused by massive terminal devices connecting to the power distribution network has become a significant challenge. Multi‐terminal collaborative computing is a key approach to addressing issues such as high latency and high energy consumption. In this article, fog computing is introduced into the computing network of the power distribution system, and a cloud‐fog‐edge collaborative computing architecture for intelligent power distribution networks is proposed. Within this framework, an improved weighted K‐means method based on information entropy theory is presented for node partitioning. Subsequently, an improved multi‐objective particle swarm optimization algorithm (MWM‐MOPSO) is employed to solve the task resource allocation problem. Finally, the effectiveness of the proposed architecture and allocation strategy is validated through simulations on the OPNET and PureEdgeSim platforms. The results demonstrate that, compared to traditional cloud‐edge service architectures, the proposed architecture and task offloading scheme achieve better performance in terms of processing latency and energy consumption.

Effectiveness of tolvaptan on renal replacement therapy in patients with autosomal dominant polycystic kidney disease: a retrospective cohort study from the TriNetX global collaborative network

Background and hypothesis Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a major genetic contributor to end-stage kidney disease (ESKD). Current evidence on tolvaptan primarily focuses on slowing estimated glomerular filtration rate (eGFR) decline and kidney volume growth. However, direct confirmation of its effectiveness in reducing the need for hemodialysis in ESKD remains limited. Methods We included ADPKD patients aged ≥18 years using TriNetx data from Sep 2, 2018, to Sep 3, 2023. Propensity score matching (PSM) ensured baseline comparability (standardized mean difference (SMD) <0.1). Hazard ratios (HRs) with 95% confidence intervals (CIs) evaluated outcomes, and subgroup analyses were performed. Results After 1:1 PSM, both groups comprised 673 patients. The average age was 45, with generally good health (3–5% diabetes, 2-3% ischemic heart disease). Baseline eGFR averaged ∼55 ml/min/1.732m2. Post-matching, all SMDs were <0.1, indicating successful matching. Tolvaptan users exhibited lower eGFR (51.45 ± 30.09 vs. 57.37 ± 33.65, p < 0.001) and higher risk of stage 4-CKD (HR: 2.436, 95% CI:1.649, 3.599) compared to non-users. However, tolvaptan users showed significantly reduced chances of initiating hemodialysis (HR:0.362, 95%CI:0.176, 0.745), experiencing urinary tract infections (HR:0.581, 95%CI:0.354, 0.956), and all-cause mortality (HR:0.355, 95% CI:0.180, 0.700). Kaplan-Meier curves for hemodialysis initiation indicated higher survival rates among tolvaptan users across age and number of medication refill subgroups. Conclusions This real-world study, employing precise matching, reveals tolvaptan’s role in reducing hemodialysis initiation risk in ADPKD, despite initial hemodynamic-induced lower eGFR.