High Complexity Research Articles

The Pilot Study on Detecting Perforation with Abdominal Ultrasound During Gastric Endoscopic Submucosal Dissection.

Objectives: The indications for endoscopic submucosal dissection (ESD) for gastric adenoma and gastric cancer have expanded, leading to an increase in the number of patients with high procedural complexity. Post-ESD perforations prolong hospital stays and increase costs. However, no studies have focused on detecting micro-perforations during ESD. This study aimed to identify signs of perforation using abdominal ultrasound during gastric ESD. Materials and methods: This pilot study analyzed 50 patients who underwent abdominal ultrasound (VScan Air™, GE Healthcare) during ESD at Samsung Medical Center (March 2023-July 2024). Perforation was assessed via ultrasound, and post-procedure X-rays were performed for three days to detect free air. Results: Among 50 patients (median age 60, 76.1% male), the median procedure time was 60 min. Lesions were most common in the antrum (30.4%) and lesser curvature (17.4%). Pathology revealed 32.6% well-differentiated and 10.9% moderately differentiated adenomas, with 15.2% showing high-grade dysplasia. Free air was detected in three patients after procedures involving the body wall of the stomach. Abdominal US showed indirect signs of perforation, including an abnormal peritoneal line, hyperechoic shadowing, and an absence of normal gas patterns, confirmed by X-ray. Conclusions: Abdominal US is a simple, useful tool for rapid detection of perforation during ESD, enabling timely intervention. Further multicenter studies are needed to confirm these findings.

The Convergence of Renewable Energy and Aquacultural Engineering for a Sustainable Food System

Renewable energy and aquacultural engineering combine to provide a disruptive approach to developing a sustainable and resilient food supply. This area of aquacultural engineering would automate feeding systems, oxygenation, recirculating aquaculture systems, and water quality monitoring by integrating renewable energy sources such as sun, wind, hydropower, and bioenergy. In order to improve the efficiency of freshwater and marine aquaculture systems, energy from renewable sources will reduce waste and maximize the usage of IoT and AI toward resource efficiency. For the agricultural sector, implementing renewable energy will diminish greenhouse gas emissions, reduce operations cost, and create energy independence for farms especially off-grid and remote ones. Diversification promotes eco-friendly practices such as IMTA and biofloc systems, increasing the organization's resilience to energy volatility and climate change. Although there are obstacles in the form of high upfront costs and integration complexity, renewable technology and hybrid systems do offer a viable solution. Through the preservation of ecological balance and the provision of a sustainable food supply for future generations, this combination of renewable energy and aquacultural innovation has the potential to completely transform aquaculture.

Characteristics and Treatment of Effluent from a Ceramic Fiber Products Manufacturing Factory

Abstract: Wastewater generated from Ceramic Fiber industry poses serious environmental pollution due to its high chemical load and complex composition. This study investigates the wastewater generated from the production of various ceramic fiber products, such as ceramic fiber paper, board, and vacuum formed shapes. As ceramic fiber products provide excellent thermal insulation and are helpful in energy savings, growth of this industry in future is obvious. Though ceramic fiber production uses water in a considerable amount, comprehensive wastewater treatment is a necessity to reduce environmental footprint of this industry. The primary objective of this study was to analyze and characterize wastewater parameters such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Dissolved Solids (TDS). In this study, the chemical treatment utilizes poly aluminum chloride as a coagulant and poly electrolyte as a flocculant. Chemical treatment yields BOD and COD removal by 70.12% and 73.9% respectively. Further, the aerobic biological treatment provides a reduction of BOD by 77.1% and COD by 63.21%. An advanced oxidation process, ozonation trial was also employed for the evaluation of further reduction of pollutants to bring them within regulatory limits. The ozonation trail yields BOD and COD reduction by 75.2% and 55.8% respectively.

Research on Defect Detection in Lightweight Photovoltaic Cells Using YOLOv8-FSD.

Given the high computational complexity and poor real-time performance of current photovoltaic cell surface defect detection methods, this study proposes a lightweight model, YOLOv8-FSD, based on YOLOv8. By introducing the FasterNet network to replace the original backbone network, computational complexity and memory access are reduced. A thin neck structure designed based on hybrid convolution technology is adopted to reduce model parameters and computational load further. A lightweight dynamic feature upsampling operator improves the feature map quality. Additionally, the regularized Gaussian distribution distance loss function is used to enhance the detection ability for small target defects. Experimental results show that the YOLOv8-FSD lightweight algorithm improves detection accuracy while significantly reducing the number of parameters and computational requirements compared to the original algorithm. This improvement provides an efficient, accurate, and lightweight solution for PV cell defect detection.

Advancing ex vivo functional whole-organ prostate gland model for regeneration and drug screening

Model organisms are vital for biomedical research and drug testing but face high costs, complexity, and ethical issues. While newer techniques like organoids and assembloids have shown improvements, they still remain inadequate in addressing all research needs. In this study, we present a new method for maintaining the prostate gland of the earthworm, Eudrilus eugeniae ex vivo and examine its potential for regeneration and drug screening. We successfully maintained the earthworm prostate gland in cell culture media for over 200 days, with observed beating behavior confirming its viability. Apoptotic staining and histological analysis show no significant changes, indicating that the prostate gland remains stable. However, significant overexpression of H3 and H2AX on the 10th and 50th days suggests stem cell proliferation and differentiation. Alkaline phosphatase expression analysis confirmed that the stem cell niche is localized to the anterior region. Remarkably, the posterior region of the prostate gland demonstrated significant regenerative capacity, with complete regeneration occurring within 45 days following amputation. Furthermore, treatment with valproic acid enhanced posterior regeneration, leading to full restoration within 12 days. This study confirms the feasibility of maintaining the prostate gland of earthworms in an ex vivo setting, providing a valuable model for studying regeneration and conducting drug screening.

Sustainable supply chain practices: Driving efficiency, reducing waste, and promoting circular economy models

As the world increasingly focuses on sustainability, supply chain management has become a vital lever for the realization of environmental, social, and economic goals. Also, linear supply chain models that are traditional in nature (such as extract, consume, and dispose) lead to serious environmental degradation along with an enormous amount of resource depletion. On the other hand, sustainable supply chain initiatives focus on waste reduction, resource efficiency, and circular economy approaches that prioritize reuse, recycling, and recovery. Integrating sustainability into these supply chain strategies can improve operational efficiency, drive costs down, and meet stakeholder expectations for business environmental stewardship. These strategies involve implementing green procurement practices, optimizing logistics to minimize their carbon footprints, and incorporating new technological solutions (like IoT and blockchain) to improve sustainability transparency and traceability. These practices allow organizations to trace materials throughout their lifecycle, support accountability, and promote closed-loop systems supporting circularity. In addition, the collaboration between stakeholders will determine sustainable initiatives; suppliers, manufacturers, and consumers to name a few. Implementing sustainable supply chain practices is not without its challenges, including high initial costs, technological barriers, and complex regulatory landscapes. Solving for these issues takes policy incentives, investment in innovation, and stakeholder engagement. The role of the key findings and challenges of sustainable strategies for supply chain practices in the development of a circular economy model. By examining case studies as well as emerging trends, it provides key takeaways for organizations striving to navigate the delicate balance between efficiency and sustainability, with the end goal of fostering a resilient and eco-conscious future for all.

Detecting DoS and SPOOFING Attacks with DNN-based IDS using CICIoT 2024 DataSheet

With the rapid expansion of IoT (Internet of Things) devices, ensuring network security has become a critical challenge. Distributed Denial of Service (DoS) and spoofing attacks are among the most common and damaging threats in IoT ecosystems. Traditional Intrusion Detection Systems (IDS) often face difficulties in detecting these attacks due to the high volume and complexity of IoT network traffic. This study introduces a novel Deep Neural Network (DNN)-based IDS designed to effectively detect DoS and spoofing attacks using the CICIoT 2024 dataset. The CICIoT 2024 dataset provides a comprehensive benchmark with realistic IoT network traffic patterns, including benign and malicious activities. The results highlight the potential of DDN-based IDS to enhance IoT network security, paving the way for more resilient and intelligent defense mechanisms against evolving cyber threats. The detection results are promising, significantly improving attack detection performance, reaching up to 100%.

P-1783. Differences in stewardship strategies across hospitals performing well and poorly on a risk-adjusted metric for post-discharge antibiotic use

Abstract Background Antibiotic overuse at hospital discharge is common, and it is unclear which antibiotic stewardship (AS) strategies are effective at improving post-discharge antibiotic-prescribing. In this study, we compared how hospitals’ AS processes differed based on their performance on a risk-adjusted metric for post-discharge antibiotic use.Figure 1.Risk-adjusted comparison of post-discharge antibiotic-prescribing frequency and duration across 124 VA hospitalsGroup 1 hospitals (n=40) had less frequent post-discharge antibiotic-prescribing and used shorter post-discharge antibiotic duration. Group 2 hospitals (n=26) had more frequent post-discharge antibiotic-prescribing and used shorter post-discharge antibiotic durations. Group 3 hospitals (n=34) had less frequent post-discharge antibiotic-prescribing and used longer post-discharge antibiotic durations. Group 4 hospitals (n=24) had more frequent post-discharge antibiotic-prescribing and used longer post-discharge antibiotic durations. Methods We performed a retrospective study of discharges to home from 124 acute-care VA hospitals. Discharges occurred 6 months before/after a mandatory hospital-level AS survey (11/10/20); patients who received ≥ 30 days of post-discharge antibiotics were excluded. We built a zero-inflated negative binomial mixed-model with two random intercepts for each hospital to predict post-discharge oral antibiotic exposure and duration. Key model covariates included patient comorbidities, discharge diagnoses of infection, and inpatient antibiotic duration. Using the predicted random intercepts, hospitals were categorized into 4 groups. Next, we used a multinomial logistic regression model to compare how often AS processes, as reported in the survey, were used at hospitals across these groups.Table 1.Characteristics of 124 VA hospitals, stratified by a hospital’s performance on a risk-adjusted metric for post-discharge antibiotic useAbbreviations: AS = antibiotic stewardship; FTEE = full time employee equivalents; IQR = interquartile range; LOT = length of therapy; PA = prior authorization; PAF = prospective audit-and-feedback; SD = standard deviation. (1) Facility complexity scores are created by the VA Healthcare Analysis and Information Group. Hospitals are scored according to their patient population, clinical services (e.g., intensive care unit and surgery services), education and research. A score of 1a and 1b is categorized as the highest complexity. Lower complexity facilitates are scored as 1c, 2, or 3. (2) This survey question was dichotomized to compare stewardship physicians and stewardship pharmacists who interact daily or several times a week versus teams that interact weekly, monthly or less frequently than monthly. (3) This variable ranges from 1-10 and captures whether certain antibiotics were managed by prior authorization (PA) or prospective audit-and-feedback (PAF). Each additional antibiotic managed with one of these strategies increased the PA or PAF score by 1, except as noted: vancomycin (intravenous), daptomycin, oral/IV linezolid (each formulation = 0.5 points), piperacillin-tazobactam, cefepime, ceftazidime, anti-pseudomonal carbapenems, ertapenem, ciprofloxacin + levofloxacin oral/IV (each 0.5), and moxifloxacin oral/IV (each 0.5). Results There were 399,234 discharges; 17.2% received post-discharge antibiotics (median duration 6). Hospital performance on the metric is shown in Figure 1, and Table 1 shows hospital characteristics, based on the group. Forty (32.3%) hospitals were in group 1, i.e., they prescribed antibiotics less frequently than expected at discharge and used shorter post-discharge duration. Twenty-four (19.4%) hospitals were in group 4, i.e., they prescribed antibiotics more often than expected at discharge and used longer post-discharge duration. Compared to group 1 hospitals, hospitals in group 4 were less likely to report interactions between their AS physician and AS pharmacist(s) every day or several times per week (0.17, 95% CI 0.05-0.64). No other AS processes significantly differed between the groups (Table 2).Table 2.Odds ratios for a hospital within each group reporting the use of specific antibiotic stewardship processes, based on a multinomial logistic regression modelAbbreviations: AS = antibiotic stewardship; FTEE = full time employee equivalents; LOT = length of therapy; OR = odds ratio; PA = prior authorization; PAF = prospective audit-and-feedback; Ref = reference group. (1) This survey question was dichotomized to compare stewardship physicians and stewardship pharmacists who interact daily or several times a week versus teams that interact weekly, monthly or less frequently than monthly. (2) The odds ratio reflects the effect on the odds of increasing the number of antibiotics managed with this strategy by a single unit (i.e., managing 10 antibiotics by PA versus managing only 9 by PA). Conclusion The findings of this mixed-methods study suggest that routine AS physician-pharmacist collaboration may be important to reducing antibiotic overuse at discharge. Future studies should more precisely measure AS processes to better understand how these are associated with differences in hospital performance at this transition of care. Disclosures Daniel J. Livorsi, MD, Merck: Grant/Research Support Michihiko Goto, MD MSCI, Merck: Grant/Research Support

Microneedle Array-Based Dermal Interstitial Fluid Biopsy for Cancer Diagnosis: Advances and Challenges.

Current early cancer diagnostic technologies, such as imaging, molecular tests, endoscopic techniques, and biopsies, face considerable challenges in low-and middle-income countries (LMICs) due to high costs, procedural complexity, and limited resource access. Microneedle-based liquid biopsy for skin interstitial fluid (ISF) offers a practical and minimally invasive alternative for cancer diagnosis in these settings. This review systematically examines ISF liquid biopsy methods for their effectiveness in capturing cancer biomarkers directly from the skin and assesses their potential to address diagnostic needs in low-resource environments. Recent innovations in microneedle design and ISF underscore their potential in enabling early, accessible cancer detection tailored to LMICs' needs. Additionally, integrating artificial intelligence (AI) for data interpretation is proposed as a way to enhance diagnostic accuracy and enable real-time point-of-care (POC)applications. Collectively, these advances illustrate a flexible, scalable model for accessible cancer diagnostics, with significant implications for improving early detection and healthcare quality in resource-limited environments.

Cost-Effective Synthesis of Carbazole-Based Nanoporous Organic Polymers for SO2 Capture.

Sulfur dioxide (SO2), a pervasive air pollutant, poses significant environmental and health risks, necessitating advanced materials for its efficient capture. Nanoporous organic polymers (NOPs) have emerged as promising candidates; however, their development is often hindered by high synthesis temperatures, complex precursors, and limited SO2 selectivity. Herein, we report a room-temperature, cost-effective synthesis of carbazole-based nanoporous organic polymers (CNOPs) using 1,3,5-trioxane and paraldehyde, offering a significant advancement over traditional Friedel-Crafts alkylation methods. The resulting CNOPs exhibit a high surface area of up to 842 m2·g-1 and feature ultramicroporous structures optimized for SO2 adsorption. At 298 K and 1 bar, the CNOPs demonstrated SO2 adsorption capacities of up to 9.39 mmol·g-1. Ideal adsorbed solution theory (IAST) calculations revealed outstanding selectivities of 105 for SO2/CO2 and 6139 for SO2/N2 mixtures, supported by breakthrough experiments demonstrating superior separation performance. This work not only provides a straightforward synthetic route for CNOPs but also offers valuable insights into the design and development of porous materials tailored for enhanced SO2 capture, addressing critical environmental and health challenges.

MUNet: a novel framework for accurate brain tumor segmentation combining UNet and mamba networks.

Brain tumors are one of the major health threats to humans, and their complex pathological features and anatomical structures make accurate segmentation and detection crucial. However, existing models based on Transformers and Convolutional Neural Networks (CNNs) still have limitations in medical image processing. While Transformers are proficient in capturing global features, they suffer from high computational complexity and require large amounts of data for training. On the other hand, CNNs perform well in extracting local features but have limited performance when handling global information. To address these issues, this paper proposes a novel network framework, MUNet, which combines the advantages of UNet and Mamba, specifically designed for brain tumor segmentation. MUNet introduces the SD-SSM module, which effectively captures both global and local features of the image through selective scanning and state-space modeling, significantly improving segmentation accuracy. Additionally, we design the SD-Conv structure, which reduces feature redundancy without increasing model parameters, further enhancing computational efficiency. Finally, we propose a new loss function that combines mIoU loss, Dice loss, and Boundary loss, which improves segmentation overlap, similarity, and boundary accuracy from multiple perspectives. Experimental results show that, on the BraTS2020 dataset, MUNet achieves DSC values of 0.835, 0.915, and 0.823 for enhancing tumor (ET), whole tumor (WT), and tumor core (TC), respectively, and Hausdorff95 scores of 2.421, 3.755, and 6.437. On the BraTS2018 dataset, MUNet achieves DSC values of 0.815, 0.901, and 0.815, with Hausdorff95 scores of 4.389, 6.243, and 6.152, all outperforming existing methods and achieving significant performance improvements. Furthermore, when validated on the independent LGG dataset, MUNet demonstrated excellent generalization ability, proving its effectiveness in various medical imaging scenarios. The code is available at https://github.com/Dalin1977331/MUNet.

SRF: SpectrumRecombineFormer for Hyperspectral Image Classification

Hyperspectral (HS) imaging is a valuable technique for accurately classifying materials because of the abundance of spectral information and high resolution it provides. However, the characteristics of Hyperspectral images (HSI), such as high-dimensional features and information redundancy, pose significant challenges to data processing. Traditional dimensionality reduction methods often have information loss, high computational complexity, and easy to ignore the strong correlation between HSI spectral bands when dealing with HSI data. Although other methods can achieve satisfactory classification performance, they do not consider the dimensionality reduction of HSI, and they focus on the model performance, which limits further improvement in classification performance. This paper proposes a transformer-based framework called “SpectrumRecombineFormer” (SRF), which is composed of two key modules, namely “Spatial Spectral ReCombination” (SSRC) and “Cross-layer Fusion” (CF). The SSRC is capable of utilizing both adjacent and non-adjacent spectrums to generate the spatial-sequential perceptive representations, which alleviates the effect of the strong correlation between HSI spectral bands. The CF can avoid the loss of information during the feed-forward procedure among layers. Extensive experiments on five existing datasets (widely-adopted Indian Pines, Houston2013, Pavia University, Salinas and KSC) demonstrate the capability of our proposed method to address the above mentioned challenges. Both quantitative and qualitative experimental ablation studies, including visualization results, reveal that the proposed SRF method can successfully and efficiently classify hyperspectral images and surpass the other state-of-the-art methods. For access to the source code, please visit https://github.com/kangpeilun/SRF-HSI-Classification-master .

P-1400. Feasibility, Acceptability and Impact of Self-Sample Collection for Extra-genital STI Testing: Experience from a High Complexity VA Facility

Abstract Background Routine screening of all exposed extra-genital sites for sexually transmitted infections (STIs), specifically Neisseria gonorrhoeae (GC) and Chlamydia trachomatis (CT), is recommended for individuals at high risk, including some men who have sex with men (MSM) and individuals receiving Pre-Exposure Prophylaxis (PrEP). However, there are a number of barriers to screening including privacy and provider availability. While self-collected extra-genital STI samples have the potential to mitigate some of these barriers, this approach has not yet achieved widespread use. This study evaluates the implementation of self-collection of extra-genital STI tests at the VA Northeast Ohio Healthcare System (VANEOHS), assesses acceptability and measures impact on testing rates. Methods The study included people with HIV (PWH) and patients on PrEP at the VANEOHS’s infectious diseases clinic and covered 10 Ohio counties. Patients chose between self- and provider-collection. We followed GC and CT rectal and pharyngeal testing frequency and test completion rates and characterized reasons for unsuccessful completion. We also compared extra-genital GC/CT testing rates before and after the availability of self-collection. Finally, we deployed an anonymous survey to assess acceptability of self-collection and ease of use. We used descriptive statistics to report completion rates, survey findings and changes in rates of testing over time. Results Of the 276 tests ordered for self-collection for 95 unique veterans, 82 pharyngeal and 60 rectal GC/CT rectal tests were successfully completed and interpreted in the first 8 months of the study (Table 1). The testing rate increased from 8 tests/month to 15 tests/month for pharyngeal GC/CT and from 6 tests/month to 10 tests/month for rectal GC/CT (Figure 1). Of the survey respondents who performed self-collection, 11 of 17 were satisfied or very satisfied with self-collection and most found it easy or very easy to swab their own rectum (9/12) and throat (13/14) (Table 2). Conclusion Self-sample collection for extra-genital testing is feasible in a large healthcare network. It is highly desired by patients and has the potential to improve access and improve STI screening rates. Disclosures All Authors: No reported disclosures

378. Visby Medical Women’s Sexual Health Test: An Over-the-Counter Molecular Diagnostics Solution to STI Testing *The Visby Medical Women’s Sexual Health test has not been cleared or approved by the FDA for in vitro diagnostic use

Abstract Background Visby Medical has developed a palm-sized, single-use, PCR platform that combines sample preparation, nucleic acid amplification and detection into an integrated device (Figure 1) that delivers results within 30 minutes. This platform was used to develop the Women’s Sexual Health Test for the detection of DNA from pathogens Chlamydia trachomatis, Neisseria gonorrhoeae and Trichomonas vaginalis. Testing instructions were designed for lay users. A smartphone application was developed to guide users through the testing process with videos, including digital interpretation of the results using the smartphone camera.Table 1:The data summary table below shows the aggregate results from testing conducted by lay users across all thirteen sites to assess the performance of the Visby test relative to the comparator tests.PPA=Positive Percent Agreement; NPA=Negative Percent Agreement.TP=true positive; FP=false positive; TN=true negative; FN=false negative. Methods Performance characteristics of an investigational use only (IUO) version of the test were evaluated using clinical and analytical studies. The clinical study was carried out at 13 geographically diverse sites. A total of 2203 female subjects (14+ years old) were included in the performance evaluation. Subjects followed the printed and/or the digital instructions to self-collect a vaginal swab, place it in the Visby collection media, conduct the test, and interpret the results. Three additional swabs were collected from each subject for comparator testing. The analytical studies included limit of detection (LoD), inclusivity, cross reactivity, interference and flex studies. Human factors usability studies were also conducted.Figure 1:Visby Medical Women’s Sexual Health Test Results The Visby Medical Women’s Sexual Health Test* had a sensitivity of at least 95.0% and a specificity of at least 98.0% (see Table 1) for each of the three target organisms. Human Factors usability studies substantiated that a lay user could successfully perform the testing, and the analytical studies demonstrated that the test is sensitive (LoD, inclusivity), specific (cross-reactivity), and robust (interference and flex testing). Conclusion The performance characteristics of the Visby Medical Women’s Sexual Health Test when used by lay users in an at-home setting was equivalent to the results from high complexity assays, conducted in centralized laboratories by trained laboratory professionals. This test could potentially be the first PCR test cleared for at-home use with the ability to offer highly accurate testing for sexually transmitted infections (STIs) and remove barriers to promptly and accurately treating STIs. Disclosures Jennifer Albrecht, PhD, Visby Medical, Inc: Employee Brittany Owings, n/a, Visby Medical: Employee Paul Dentinger, PhD, Visby Medical: Stocks/Bonds (Private Company) Gary Schoolnik, MD, Visby Medical: I am the Chief Medical Officer of Visby Medical|Visby Medical: Stocks/Bonds (Private Company) Beth Lingenfelter, n/a, Visby Medical: Employee

Chronic IL-1-Exposed LNCaP Cells Evolve High Basal p62-KEAP1 Complex Accumulation and NRF2/KEAP1-Dependent and -Independent Hypersensitive Nutrient Deprivation Response.

Chronic inflammation is a cancer hallmark and chronic exposure to interleukin-1 (IL-1) transforms castration-sensitive prostate cancer (PCa) cells into more fit castration-insensitive PCa cells. p62 is a scaffold protein that protects cells from nutrient deprivation via autophagy and from cytotoxic reactive oxygen via NFκB and NRF2 antioxidant signaling. Herein, we report that the LNCaP PCa cell line acquires high basal accumulation of the p62-KEAP1 complex when chronically exposed to IL-1. p62 promotes non-canonical NRF2 antioxidant signaling by binding and sequestering KEAP1 to the autophagosome for degradation. But despite high basal p62-KEAP1 accumulation, only two of several NRF2-induced genes analyzed, GCLC and HMOX1, showed high basal mRNA levels, suggesting that the high basal p62-KEAP1 accumulation does not result in overall high basal NRF2 activity. Nutrient starvation induces NRF2-dependent GCLC upregulation and HMOX1 repression, and we found that chronic IL-1-exposed LNCaP cells show hypersensitivity to serum starvation-induced GCLC and HMOX1 regulation. Thus, chronic IL-1 exposure affects cell response to nutrient stress. While HMOX1 expression remains NRF2/KEAP1-dependent in chronic IL-1-exposed LNCaP cells, GCLC expression is NRF2/KEAP1-independent. Furthermore, the high basal p62-KEAP1 complex accumulation is not required to regulate GCLC or HMOX1 expression, suggesting cells chronically exposed to IL-1 evolve a novel NRF2-independent role for the p62/KEAP1 axis.

Precision oncology: The role of minimally-invasive ablation therapy in the management of solid organ tumors.

Solid organ tumors present a significant healthcare challenge, both economically and logistically, due to their high incidence and treatment complexity. In 2023, out of the 1.9 million new cancer cases in the United States, over 73% were solid organ tumors. Ablative therapies offer minimally invasive solutions for malignant tissue destruction in situ, often with reduced cost and morbidity compared to surgical resection. This review examines the current Food and Drug Administration-approved locoregional ablative therapies (radiofrequency, microwave, cryogenic, high-intensity focused ultrasound, histotripsy) and their evolving role in cancer care. Data were collected through a comprehensive survey of the PubMed-indexed literature on tumor ablation techniques, their clinical indications, and outcomes. Over time, emerging clinical data will help establish these therapies as the standard of care in solid organ tumor treatment, supported by improved long-term outcomes and progression-free survival.

A novel arc detection and identification method in pantograph-catenary system based on deep learning

Arc detection is crucial for ensuring the safe operation of power systems, where timely and accurate detection of arcs can prevent potential hazards such as fires, equipment damage, or system failures. Traditional arc detection methods, while functional, often suffer from low detection accuracy and high computational complexity, especially in complex operational environments. This limitation is particularly problematic in real-time monitoring and the efficient operation of power systems. In order to solve these problems, this paper proposes a method of arc detection based on deep learning, called arc multi-scene detection (ArcMSD), which leverages deep learning techniques to address these challenges. The primary distinction of this method lies in its enhancement of the Inception V3 model. This paper has redesigned the original Inception module by incorporating a guided anchor mechanism, an attention mechanism, and upsampling techniques to optimize detection performance. The improved Inception V3 network uses an attention mechanism to allow the model to focus on arc features in complex backgrounds, which can also prevent the model from overfitting. It performs upsampling and fusion with low-level features in the model. The fused features have better arc discrimination capabilities than the original input features, which better improves the accuracy of the model. In order to adapt to arcs with large size differences and improve detection efficiency, the guided anchor is selected to adjust the anchor generation algorithm. In terms of dataset, continuous frame images are intercepted from the video of Integrated Supervision and Control System (ISCS), and image preprocessing operations are performed to improve the model’s detection accuracy of pantograph arcs. Experimental results show that the mean Average Precision (mAP) of the deep learning model proposed in this article is 95.4%, which is far better than other models, thus verify the method’s efficacy.

Evaluation of Multipeptide Sequences Identified in Silico for the Serological Detection of Antibodies against Vector-Borne Diseases.

The socioecological conditions of Mexican regions are conducive to the spread of vector-borne diseases. Although there are established treatment guidelines for dengue and rickettsiosis, diagnosis is complicated. The objective of this work was to identify epitopes of Rickettsia and dengue virus that could be used in serology screening against vector-borne diseases. For this, epitopes with high histocompatibility complex class II binding efficiency of OmpB protein of Rickettsia rickettsii and NS2B protein of dengue virus were identified in silico through a reverse vaccinology strategy. The selected epitopes were grouped into multipeptide sequences that were synthesized and immobilized in a nitrocellulose membrane to evaluate the reactivity sera from patients previously infected with dengue or Rickettsia. The evaluation of the sequences of the NS2B and OmpB proteins was performed with 60 sera previously diagnosed as positive or negative by the respective gold standard techniques. The dot blot technique was used for the antigenic evaluation of the peptides against these serum samples. Dot blot analysis correctly identified 85% of sera positive for rickettsiosis and 75% of sera positive for dengue. Experimental evidence from multipeptide sequences suggests their potential use in the development of diagnostic tests for dengue and rickettsiosis.

High-speed spectral imaging via multispectral pulse illumination and temporal-spectral decoupling.

Spectral imaging (SI) faces inherent trade-offs among spatial, temporal, and spectral resolutions due to limited bandwidth. Current high-speed SI systems, relying on fast modulation or specific cameras, compromise spatial resolution or suffer high complexity and cost. This work presents a low-cost, high-speed SI scheme achieving up to 240 frames per second (fps) and even μs-resolved multispectral observation. This work reveals the inherent temporal-spectral redundancy in SI videos and reports an active temporal-spectral coupling (TSC) and decoupling (TSD) strategy for high-speed SI. We established a prototype system using a snapshot SI camera and a multispectral LED array. The LEDs sequentially illuminate the scene channel by channel in one exposure for TSC acquisition. Each channel of the measurement corresponds one-to-one to an illumination moment. A transformer-based network is applied to decouple textural and spectral information from the measurement and re-couple them to reconstruct images across all channels and time instances. Experiments validated that the reported framework can successfully record μs-resolved multispectral videos.

Innovative Technologies in Supply Chain Management for Bangladesh’s Readymade Garments Sector – A Comprehensive Review

Ready-Made Garments (RMG) sector is crucial to Bangladesh's economy, significantly contributing to GDP, employment, and exports. However, supply chain management (SCM) inefficiencies, such as poor demand forecasting, inventory management, logistics, and quality control, pose persistent challenges. This study investigates the potential of integrating advanced technologies like AI, IoT, blockchain, Big Data Analytics, and automation to improve SCM in the Bangladeshi RMG sector. Through a review of literature, industry reports, and case studies, the study assesses the benefits and challenges of technology adoption in the sector. Advanced technologies can enhance visibility, efficiency, quality control, decision-making, and sustainability in SCM. However, challenges such as high costs, data privacy, technical complexity, and resistance to change require strategic planning to overcome. Adopting these technologies can significantly improve the RMG sector's efficiency and global competitiveness, requiring collaboration between policymakers and industry leaders. This study provides a concise analysis of technology integration in Bangladeshi RMG SCM, offering balanced insights to guide future research and industry practices.