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Abstract Targeting mitochondrial metabolism represents a promising approach for cancer treatment. Here, we investigated the mitotoxic potential of the polybrominated diphenyl ether bromoxib, a natural compound isolated from the marine sponge Dysidea family. We could show that bromoxib comprised strong cytotoxicity in different leukemia and lymphoma cell lines (such as HL60, HPBALL, Jurkat, K562, KOPTK1, MOLT4, SUPB15 and Ramos), but also in solid tumor cell lines (such as glioblastoma cell lines SJ-GBM2 and TP365MG). Bromoxib activated the mitochondrial death pathway as evidenced by the rapid translocation of Bax to the mitochondria and the subsequent mitochondrial release of Smac. Accordingly, bromoxib-induced apoptosis was blocked in caspase 9 deficient Jurkat cells and Jurkat cells overexpressing the antiapoptotic protein Bcl-2. In addition, we could show that bromoxib functioned as an uncoupler of the electron transport chain with similar rapid kinetics as CCCP in terms of dissipation of the mitochondrial membrane potential (ΔΨm), processing of the dynamin-like GTPase OPA1 and subsequent fragmentation of mitochondria. Beyond that, bromoxib strongly abrogated ATP production via glycolysis as well as oxidative phosphorylation (OXPHOS) by targeting electron transport chain complexes II, III, and V (ATP-synthase) in Ramos lymphoma cells. Thus, bromoxib’s potential to act on both cytosolic glycolysis and mitochondrial respiration renders it a promising agent for the treatment of leukemia and lymphoma.

Abstract We investigate the use of various momentum methods in combination with an ensemble approximation of gradients, for accelerated optimization. Although momentum gradient descent methods are popular in machine learning, it is unclear how they perform when applied to time-consuming dynamic problems such as production optimization for petroleum reservoir management. Four different momentum methods are extensively tested on a reservoir test case in one deterministic and one robust setting. The numerical experiments show that momentum strategies yield, on average, a higher net present value with fewer simulations needed.

One of the initial problems faced by young interior designers is to make a creative pattern to draw potential consumers’ attention. Their belief in the creative pattern should fit consumers’ expectations. This study scrutinized the relationship between young interior designers and potential consumers about both expectation, designers’ capital, and designers’ strategy to cap-ture the pattern in the design market. To this end, young interior designers (n=100) and potential design consumers (n=100) were recruited as respon-dents. Multiple linear regression and ordinal logisic regression were applied. The data analysis result demonstrated young designers’ marketing patterns to draw potential consumers’ attention. A correlation was found between young designers and design consumers. The expectation, capital, and strategy of designers were found to be interrelated by 48.1%, while those of consumers were interrelated by 28.6%. The research variables, which are designer capital, designer strategy and the two respondent groups, were found to have an impact on the expectation by 94.5%. This study concludes that young designers have a marketing pattern to draw poten-tial consumers’ attention. It showed a relationship between designers’ and consumers’ expectations, designers’ capital or information received by consumers, and designers’ strategy. This study may serve as a refer-ence for young designers’ behaviors when entering the market design.

Abstract In the context of soft matter and cellular mechanics, microrheology - the use of micron-sized particles to probe the frequency-dependent viscoelastic response of materials – is widely used to shed light onto the mechanics and dynamics of molecular structures. Here we present the implementation of active microrheology in an Acoustic Force Spectroscopy setup (AFMR), which combines multiplexing with the possibility of probing a wide range of forces ( ~ pN to ~nN) and frequencies (0.01–100 Hz). To demonstrate the potential of this approach, we perform active microrheology on biological samples of increasing complexity and stiffness: collagen gels, red blood cells (RBCs), and human fibroblasts, spanning a viscoelastic modulus range of five orders of magnitude. We show that AFMR can successfully quantify viscoelastic properties by probing many beads with high single-particle precision and reproducibility. Finally, we demonstrate that AFMR to map local sample heterogeneities as well as detect cellular responses to drugs.

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard‐of‐care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in‐depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype‐first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population‐based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true‐positive and false‐positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype‐first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Background: The risk of atherosclerotic cardiovascular disease (ASCVD) in adults with congenital heart disease (ACHD) is comparable to that of the general population and is driven by traditional ASCVD risk factors. Objectives: The aim of the study was to estimate the prevalence of traditional ASCVD risk factors (hypertension, dyslipidemia, diabetes mellitus [DM], obesity, smoking, and physical inactivity) in ACHD and compare it with the general population. Methods: A systematic literature search was conducted up to May 15, 2024, to identify studies (with or without control group) reporting the prevalence of ASCVD risk factors in ACHD. Meta-analyses were conducted to synthesize the prevalence of risk factors and compare it with that of the general population, where applicable. Results: We identified 62 studies (30 controlled) encompassing 110,469 ACHD (mean age 39 years; 52% males, 88% with simple/moderate congenital heart disease complexity). Of these, 54% (45%-63%) reported lack of regular exercise, 33% (26%-40%) had hypertension, 18% (14%-22%) were obese, 17% (11%-25%) had dyslipidemia, 12% (9%-14%) were current smokers, and 7% (5%-9%) had DM. The prevalence of ASCVD risk factors was similar in ACHD and controls, with the exception of DM (higher prevalence in ACHD) and smoking (lower prevalence in ACHD). Significant heterogeneity was observed among the included studies, partially explained by differences in age, congenital heart disease complexity, and the presence of cyanosis. Conclusions: Except for DM and smoking, the prevalence of traditional ASCVD risk factors is similar in ACHD compared to the general population. Further research is needed to determine whether interventions applied in the general population are also effective in ACHD.

Summary: A quantitative description of nuclear mechanics is crucial for understanding its role in force sensing within eukaryotic cells. Recent studies indicate that the chromatin within the nucleus cannot be treated as a homogeneous material. To elucidate its material properties, we combine optical tweezers manipulation of isolated nuclei with multi-color fluorescence imaging of lamin and chromatin to map the response of nuclei to local deformations. Force spectroscopy reveals nuclear strain stiffening and an exponential force dependence, well described by a hierarchical chain model. Simultaneously, fluorescence data show a higher compliance of chromatin compared to the nuclear envelope at strains

BackgroundThe influence of atrial fibrillation (AF) and blood pressure (BP) on brain lesions and cognitive function is unclear. We aimed to investigate the association of BP with different types of brain lesions and cognitive decline in patients with AF.MethodsOverall, 1,213 AF patients underwent standardized brain magnetic resonance imaging at baseline and after 2 years, as well as yearly neurocognitive testing. BP was measured at baseline and categorized according to guidelines. New lesions were defined as new or enlarged brain lesions after 2 years. We defined cognitive decline using three different neurocognitive tests. Logistic and Cox regression analyses were performed to examine the associations of BP with new brain lesions and cognitive decline.ResultsThe mean age was 71 ± 8.4 years, 74% were male and mean BP was 135 ± 18/79 ± 12 mmHg. New ischemic lesions and white matter lesions were found in 5.4% and 18.4%, respectively. After multivariable adjustment, BP was not associated with the presence of new brain lesions after 2 years. There was no association between BP and cognitive decline over a median follow-up of 6 years when using the Montreal Cognitive Assessment or Digit Symbol Substitution Test. However, BP categories were inversely associated with cognitive decline using the Semantic Fluency Test, with the strongest association in patients with hypertension grade 1 [Hazard Ratio (95% Confidence Interval) 0.57(0.42 to 0.77)], compared to patients with optimal BP (p for linear trend: 0.025).ConclusionsIn a large cohort of AF patients, there was no association between BP and incidence of brain lesions after 2 years. Also, there was no consistent association between BP and cognitive decline over a follow-up of 6 years. Clinical Trial Registrationhttps://clinicaltrials.gov/study/NCT02105844, Identifier (NCT02105844).

Abstract Energetic stress compels cells to evolve adaptive mechanisms to adjust their metabolism. Inhibition of mTOR kinase complex 1 (mTORC1) is essential for cell survival during glucose starvation. How mTORC1 controls cell viability during glucose starvation is not well understood. Here we show that the mTORC1 effectors eukaryotic initiation factor 4E binding proteins 1/2 (4EBP1/2) confer protection to mammalian cells and budding yeast under glucose starvation. Mechanistically, 4EBP1/2 promote NADPH homeostasis by preventing NADPH-consuming fatty acid synthesis via translational repression of Acetyl-CoA Carboxylase 1 (ACC1), thereby mitigating oxidative stress. This has important relevance for cancer, as oncogene-transformed cells and glioma cells exploit the 4EBP1/2 regulation of ACC1 expression and redox balance to combat energetic stress, thereby supporting transformation and tumorigenicity in vitro and in vivo. Clinically, high EIF4EBP1 expression is associated with poor outcomes in several cancer types. Our data reveal that the mTORC1-4EBP1/2 axis provokes a metabolic switch essential for survival during glucose starvation which is exploited by transformed and tumor cells.

Summary: A key feature of neurons in the primary visual cortex (V1) of primates is their orientation selectivity. Recent studies using deep neural network models showed that the most exciting input (MEI) for mouse V1 neurons exhibit complex spatial structures that predict non-uniform orientation selectivity across the receptive field (RF), in contrast to the classical Gabor filter model. Using local patches of drifting gratings, we identified heterogeneous orientation tuning in mouse V1 that varied up to 90° across sub-regions of the RF. This heterogeneity correlated with deviations from optimal Gabor filters and was consistent across cortical layers and recording modalities (calcium vs. spikes). In contrast, model-synthesized MEIs for macaque V1 neurons were predominantly Gabor like, consistent with previous studies. These findings suggest that complex spatial feature selectivity emerges earlier in the visual pathway in mice than in primates. This may provide a faster, though less general, method of extracting task-relevant information.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating “avatars” (herein defined as an extension of “digital twins”) of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

A growing body of evidence has shown the influence that religion and spirituality have on individuals duelling with illness, especially at advanced stages of disease. It is often vital for such individuals to have their spiritual and religious beliefs respected and, potentially, integrated in a compassionate caregiving setting for healthcare systems. However, given the diversity in religions and spiritual practices, healthcare professionals ought to approach such cultural significance with cultural humility, i.e., approaching differences in beliefs without relying on stereotypes or assumptions. This process requires sufficient training and communication skills among healthcare providers, as well as a successful medico-pastoral partnership. The aim of this review is to provide insight into one specific religion, Eastern Orthodoxy, and discuss current evidence of the religion’s influence on healthcare and medicine. Within this review, we aim to provide a summary on religion and spirituality specific to the Eastern Orthodox identity and religious practices, along with providing clinical guidance on approaching people who identify with this faith in certain healthcare settings in a manner compatible with the principles of cultural humility. The review will discuss important key elements of religious belief and practice of Εastern Orthodoxy that may influence health and healthcare decisions by patients.

Purpose: This study evaluates a deep learning-based denoising algorithm to improve the trade-off between radiation dose, image noise, and motion artifacts in TIPSS procedures, aiming for shorter acquisition times and reduced radiation with maintained diagnostic quality. Methods: In this retrospective study, TIPSS patients were divided based on CBCT acquisition times of 6 s and 3 s. Traditional weighted filtered back projection (Original) and an AI denoising algorithm (AID) were used for image reconstructions. Objective assessments of image quality included contrast, noise levels, and contrast-to-noise ratios (CNRs) through place-consistent region-of-interest (ROI) measurements across various critical areas pertinent to the TIPSS procedure. Subjective assessments were conducted by two blinded radiologists who evaluated the overall image quality, sharpness, contrast, and motion artifacts for each dataset combination. Statistical significance was determined using a mixed-effects model (p ≤ 0.05). Results: From an initial cohort of 60 TIPSS patients, 44 were selected and paired. The mean dose-area product (DAP) for the 6 s acquisitions was 5138.50 ± 1325.57 µGy·m2, significantly higher than the 2514.06 ± 691.59 µGym2 obtained for the 3 s series. CNR was highest in the 6 s-AID series (p < 0.05). Both denoised and original series showed consistent contrast for 6 s and 3 s acquisitions, with no significant noise differences between the 6 s Original and 3 s AID images (p > 0.9). Subjective assessments indicated superior quality in 6 s-AID images, with no significant overall quality difference between the 6 s-Original and 3 s-AID series (p > 0.9). Conclusions: The AI denoising algorithm enhances CBCT image quality in TIPSS procedures, allowing for shorter scans that reduce radiation exposure and minimize motion artifacts.

Responses to natural stimuli in area V4-a mid-level area of the visual ventral stream-are well predicted by features from convolutional neural networks (CNNs) trained on image classification. This result has been taken as evidence for the functional role of V4 in object classification. However, we currently do not know if and to what extent V4 plays a role in solving other computational objectives. Here, we investigated normative accounts of V4 (and V1 for comparison) by predicting macaque single-neuron responses to natural images from the representations extracted by 23 CNNs trained on different computer vision tasks including semantic, geometric, 2D, and 3D types of tasks. We found that V4 was best predicted by semantic classification features and exhibited high task selectivity, while the choice of task was less consequential to V1 performance. Consistent with traditional characterizations of V4 function that show its high-dimensional tuning to various 2D and 3D stimulus directions, we found that diverse non-semantic tasks explained aspects of V4 function that are not captured by individual semantic tasks. Nevertheless, jointly considering the features of a pair of semantic classification tasks was sufficient to yield one of our top V4 models, solidifying V4's main functional role in semantic processing and suggesting that V4's selectivity to 2D or 3D stimulus properties found by electrophysiologists can result from semantic functional goals.

The reaction of sodium 2,2-dicyanoethene-1,1-bis(thiolate) with bromine (2 equiv.) in CCl4 gave 3,5-dibromoisothiazole-3-carbonitrile and 5,5′-thiobis(3-bromoisothiazole-4-carbonitrile) in 7% and 18% yields, respectively. The latter novel compound was fully characterized.

Nowadays, one of the greatest challenges in data meshes revolves around detecting and creating data domains and data products for providing the ability to adapt easily and quickly to changing business needs. This requires a disciplined approach to identify, differentiate and prioritize distinct data sources according to their content and diversity. The current paper tackles this highly complicated issue and suggests a standardized approach that integrates the concept of data blueprints with data meshes. In essence, a novel standardization framework is proposed that creates data products using a metadata semantic enrichment mechanism, the latter also offering data domain readiness and alignment. The approach is demonstrated using real-world data produced by multiple sources in a poultry meat production factory. A set of functional attributes is used to qualitatively compare the proposed approach to existing data structures utilized in storage architectures, with quite promising results. Finally, experimentation with different scenarios varying in data product complexity and granularity suggests a successful performance.

Treatment of the most aggressive and deadliest form of skin cancer, the malignant melanoma, still has room for improvement. Its invasive nature and ability to rapidly metastasize and to develop resistance to standard treatment often result in a poor prognosis. While the highly effective standard chemotherapeutic agent doxorubicin (DOX) is widely used in a variety of cancers, systemic side effects still limit therapy. Especially, DOX-induced cardiotoxicity remains a big challenge. In contrast, the natural chalcone cardamonin (CD) has been shown to selectively kill tumor cells. Besides its anti-tumor activity, CD exhibits anti-oxidative, anti-inflammatory and anti-bacterial properties. In this study, we investigated the effect of the combinational treatment of DOX with CD on A375 melanoma cells compared to normal human dermal fibroblasts (NHDF) and rat cardiac myoblasts (H9C2 cells). DOX-induced cytotoxicity was unselective and affected all cell types, especially H9C2 cardiac myoblasts, demonstrating its cardiotoxic effect. In contrast, CD only decreased the cell viability of A375 melanoma cells, without harming normal (healthy) cells. The addition of CD selectively protected human dermal fibroblasts and rat cardiac myoblasts from DOX-induced cytotoxicity. While no apoptosis was induced by the combinational treatment in normal (healthy) cells, an apoptosis-mediated cytotoxicity was demonstrated in A375 melanoma cells. CD exhibited thiol reactivity as it was able to directly interact with N-acetylcysteine (NAC) in a cell-free assay and to induce heme oxygenase-1 (HO-1) in all cell types. And that took place in a reactive oxygen species (ROS)-independent manner. DOX decreased the mitochondrial membrane potential (Δψm) in all cell types, whereas CD selectively decreased mitochondrial respiration, affecting basal respiration, maximal respiration, spare respiratory capacity and ATP production in A375 melanoma cells, but not in healthy cardiac myoblasts. The DOX-induced cytotoxicity seen in melanoma cells was ROS-independent, whereas the cytotoxic effect of CD was associated with CD-induced ROS-formation and/or its thiol reactivity. This study highlights the beneficial properties of the addition of CD to DOX treatment, which might protect patients from DOX-induced cardiotoxicity. Future experiments with other tumor cell lines or a mouse model should substantiate this hypothesis.

3,5-Diphenyl-4H-1,2,6-thiadiazin-4-one treated with meta-chloroperoxybenzoic acid undergoes an oxidative ring contraction to give 2-benzoyl-4-phenyl-1,2,5-thiadiazol-3(2H)-one 1,1-dioxide in a 29% yield, the structure of which is supported by single-crystal X-ray diffraction analysis and the available spectroscopic data.

Summary: Adhesion G-protein-coupled receptors (aGPCRs) form a large family of cell surface molecules with versatile tasks in organ development. Many aGPCRs still await their functional and pharmacological deorphanization. Here, we characterized the orphan aGPCR CG11318/mayo of Drosophila melanogaster and found it expressed in specific regions of the gastrointestinal canal and anal plates, epithelial specializations that control ion homeostasis. Genetic removal of mayo results in tachycardia, which is caused by hyperkalemia of the larval hemolymph. The hyperkalemic effect can be mimicked by a raise in ambient potassium concentration, while normal potassium levels in mayoKO mutants can be restored by pharmacological inhibition of potassium channels. Intriguingly, hyperkalemia and tachycardia are caused non-cell autonomously through mayo-dependent control of enterocyte proliferation in the larval midgut, which is the primary function of this aGPCR. These findings characterize the ancestral aGPCR Mayo as a homeostatic regulator of gut development.

In Neurofibromatosis type 1 (NF1), peripheral nerve sheaths tumors are common, with cutaneous neurofibromas resulting in significant aesthetic, painful and functional problems requiring surgical removal. To date, determination of adequate surgical resection margins-complete tumor removal while attempting to preserve viable tissue-remains largely subjective. Thus, residual tumor extension beyond surgical margins or recurrence of the disease may frequently be observed. Here, we introduce Shifted-Excitation Raman Spectroscopy in combination with deep neural networks for the future perspective of objective, real-time diagnosis, and guided surgical ablation. The obtained results are validated through established histological methods. In this study, we evaluated the discrimination between cutaneous neurofibroma (n = 9) and adjacent physiological tissues (n = 25) in 34 surgical pathological specimens ex vivo at a total of 82 distinct measurement loci. Based on a convolutional neural network (U-Net), the mean raw Raman spectra (n = 8,200) were processed and refined, and afterwards the spectral peaks were assigned to their respective molecular origin. Principal component and linear discriminant analysis was used to discriminate cutaneous neurofibromas from physiological tissues with a sensitivity of 100%, specificity of 97.3%, and overall classification accuracy of 97.6%. The results enable the presented optical, non-invasive technique in combination with artificial intelligence as a promising candidate to ameliorate both, diagnosis and treatment of patients affected by cutaneous neurofibroma and NF1.

Stille coupling between 5,5′-dibromo-4,4′-diphenyl-2,2′-bithiazole and 9-(2-ethylhexyl)-3-(tributylstannyl)-9H-carbazole in the presence of Pd(Ph3P)2Cl2 in toluene, heated at reflux for 2 h, gave 5,5′-bis[9-(2-ethylhexyl)-9H-carbazol-3-yl]-4,4′-diphenyl-2,2′-bithiazole in 85% yield.

Liquid chromatography purification of multiple recombinant proteins, in parallel, could catalyze research and discovery if the processes are fast and approach the robustness of traditional, "one-protein-at-a-time" purification. Here, we report an automated, four channel chromatography platform that we have designed and validated for parallelized protein purification at milligram scales. The device can purify up to four proteins (each with its own single column), has inputs for up to eight buffers or solvents that can be directed to any of the four columns via a network of software-driven valves, and includes an automated fraction collector with ten positions for 1.5 or 5.0 mL collection tubes and four positions for 50 mL collection tubes for each column output. The control software can be accessed either via Python scripting, giving users full access to all steps of the purification process, or via a simple-to-navigate touch screen graphical user interface that does not require knowledge of the command line or any programming language. Using our instrument, we report milligram-scale, parallelized, single-column purification of a panel of mammalian cell expressed coronavirus (SARS-CoV-2, HCoV-229E, HCoV-OC43, HCoV-229E) trimeric Spike and monomeric Receptor Binding Domain (RBD) antigens, and monoclonal antibodies targeting SARS-CoV-2 Spike (S) and Influenza Hemagglutinin (HA). We include a detailed hardware build guide, and have made the controlling software open source, to allow others to build and customize their own protein purifier systems.

The increasing prevalence of atrial fibrillation (AF) in adults with congenital heart disease raises significant questions regarding its management. The unique underlying anatomic and physiological background further adds to the difficulty in eliminating the AF burden in these patients. Herein, we provide an overview of the current knowledge on the pathophysiology and risk factors for AF in adult congenital heart disease, with a special focus on the existing challenges in AF ablation. Emerging imaging modalities and ablation techniques might have a role to play. Evidence regarding the safety and efficacy of AF ablation in adult congenital heart disease is summarized, especially for patients with an atrial septal defect, Ebstein anomaly of the tricuspid valve, tetralogy of Fallot, and Fontan circulation. Finally, any remaining gaps in knowledge and potential areas of future research are highlighted.

Data meshes are an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of data meshes and data products in response to user requests, ensuring that stakeholders have access to specific portions of the data mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates the secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of data meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory.

Low back pain (LBP) is associated with the degeneration of human intervertebral discs (IVDs). Despite progress in the treatment of LBP through spinal fusion, some cases still end in non-fusion after the removal of the affected IVD tissue. In this study, we investigated the hypothesis that the remaining IVD cells secrete BMP inhibitors that are sufficient to inhibit osteogenesis in autologous osteoblasts (OBs) and bone marrow mesenchymal stem cells (MSCs). A conditioned medium (CM) from primary human IVD cells in 3D alginate culture was co-cultured with seven donor-matched OB and MSCs. After ten days, osteogenesis was quantified at the transcript level using qPCR to measure the expression of bone-related genes and BMP antagonists, and at the protein level by alkaline phosphatase (ALP) activity. Additionally, cells were evaluated histologically using alizarin red (ALZR) staining on Day 21. For judging ALP activity and osteogenesis, the Noggin expression in samples was investigated to uncover the potential causes. The results after culture with the CM showed significantly decreased ALP activity and the inhibition of the calcium deposit formation in alizarin red staining. Interestingly, no significant changes were found among most bone-related genes and BMP antagonists in OBs and MSCs. Noteworthy, Noggin was relatively expressed higher in human IVD cells than in autologous OBs or MSCs (relative to autologous OB, the average fold change was in 6.9, 10.0, and 6.3 in AFC, CEPC, and NPC, respectively; and relative to autologous MSC, the average fold change was 2.3, 3.4, and 3.2, in AFC, CEPC, and NPC, respectively). The upregulation of Noggin in residual human IVDs could potentially inhibit the osteogenesis of autologous OB and MSC, thus inhibiting the postoperative spinal fusion after discectomy surgery.

Detecting micron-sized particles is an essential task for the analysis of complex plasmas because a large part of the analysis is based on the initially detected positions of the particles. Accordingly, high accuracy in particle detection is desirable. Previous studies have shown that machine learning algorithms have made great progress and outperformed classical approaches. This work presents an approach for tracking micron-sized particles in a dense cloud of particles in a dusty plasma at Plasmakristall-Experiment 4 using a U-Net. The U-net is a convolutional network architecture for the fast and precise segmentation of images that was developed at the Computer Science Department of the University of Freiburg. The U-Net architecture, with its intricate design and skip connections, has been a powerhouse in achieving precise object delineation. However, as experiments are to be conducted in resource-constrained environments, such as parabolic flights, preferably with real-time applications, there is growing interest in exploring less complex U-net architectures that balance efficiency and effectiveness. We compare the full-size neural network, three optimized neural networks, the well-known StarDist and trackpy, in terms of accuracy in artificial data analysis. Finally, we determine which of the compact U-net architectures provides the best balance between efficiency and effectiveness. We also apply the full-size neural network and the the most effective compact network to the data of the PK-4 experiment. The experimental data were generated under laboratory conditions.