Abstract: This study develops and validates a climate-based, user-centred and data-informed framework to improve lighting performance in educational buildings through the integrated use of daylight and smart LED control systems. The research was conducted in a university facility in Madrid, Spain, using a mixed-methods approach combining on-site illuminance measurements, climate-based lighting simulations (CBMS) with Dialux Evo 12.1, and structured surveys on user perception. The objective was to quantify the dynamic interaction between daylight availability, artificial lighting demand, and perceived visual comfort, while assessing the energy-saving potential of daylight-responsive control strategies. Results show that existing LED systems meet current illuminance standards while maintaining low lighting power density (LPD). Daylight and electric lighting act complementarily, with daylight reducing artificial lighting demand by up to 50% in optimally oriented classrooms, particularly during spring and summer. Smart dimming and adaptive control systems provide additional energy savings ranging from 27% to 46%, with estimated payback periods of approximately four years. Overall, the findings demonstrate that integrating daylight and adaptive LED systems is an effective and scalable strategy for reducing energy use while maintaining visual comfort in educational buildings under Mediterranean climatic conditions.

Abstract: The C-C motif chemokine receptor 1 (CCR1) plays key roles in guiding leukocyte movement during immune surveillance and inflammatory responses. Targeting CCR1 is a promising approach for treating autoimmune diseases and cancers. We previously developed anti-mouse CCR1 (mCCR1) monoclonal antibodies (clones C1Mab-2 and C1Mab-6) for use in flow cytometry and western blotting. However, the specific binding sites have not yet been identified. This study examined the binding epitope of C1Mab-2 and C1Mab-6. Analysis of mCCR1 mutants with altered extracellular domains showed that C1Mab-2 and C1Mab-6 bind to the N-terminal region of mCCR1. Additionally, PA-tag substitution experiments identified the epitope as comprising amino acids 1–13 of mCCR1. Further, alanine (or glycine) scanning within the N-terminal region (amino acids 2–13) was performed using flow cytometry and western blotting. The results demonstrated that Met1, Glu2, Asp5, and Phe6 are critical for recognition by C1Mab-2, while Met1, Glu2, Ile3, and Asp5 are essential for recognition by C1Mab-6. These findings enhance our under-standing of how mCCR1 interacts with C1Mabs.

Abstract: We conducted this single-center, retrospective study to assess a concordance rate between the microsatellite instability (MSI) analysis and the immunohistochemistry (IHC) in a cohort of Korean patients with hereditary non-polyposis colorectal carcinoma (HNPCRC). A total of 251 patients (n = 251) were included in the current study, who comprise 149 men (59.4%) and 102 women (40.6%) and whose mean age was 64.6 ± 11.5 years old. In our series, MSI-high (MSI-H) and microsatellite-stable (MSS) were identified in 17 (6.7%) and 234 patients (93.3%), respectively. Concordance analysis showed a strong agreement between MSI status and IHC expression of mismatch repair (MMR) proteins. Of the 17 patients with MSI-H, 16 (94.11%) had a loss of expression of ³ one MMR protein in the IHC findings, while one patient (5.9%) with MSI-H retained an intact expression of all four MMR proteins. Moreover, of the 234 patients with MSS, four (1.71%) had a loss of expression of ³ one MMR protein in the IHC findings. Of the 20 patients with a loss of expression of ³ one MMR protein in the IHC findings, 16 (80%) and four (20%) were found to have MSI-H and MSS, respectively. By contrast, 231 patients retained an intact expression of all four MMR proteins, with only one case (0.4%) being MSI-H and the remaining 98.3% (n = 230) MSS. There were distinct associations between the pattern of IHC expression of MMR proteins and microsatellite status. The most frequent abnormal expression patterns include mutL homolog 1 (MLH1) (-) postmeiotic segregation increased 2 (PMS2) (-) (n = 7), all of which were MSI-H, and mutS homologs 2 (MSH2) (-) mutS homologs 6 (MSH6) (-) (n = 7), with six patients with MSI-H and one with MSS. PMS2 (-) alone was observed in three patients, one and two of whom were MSI-H and MSS, respectively. MSH6 (-) alone was observed in one patient with MSS. Finally, there were two patients with PMS2 (-) and MSH6 (-), both classified as MSI-H. The current study indicates the high concordance between IHC and MSI testing in HNPCRC. But this deserves further large-scale, prospective studies.

Abstract: Ultrafast physical random bit generators (PRBGs) are essential components for modern applications in secure communication, quantum cryptography, and artificial intelligence. While optical chaos-based PRBGs offer high-speed capabilities, conventional systems often rely on discrete components that suffer from system complexity and environmental instability. This paper proposes and experimentally demonstrates a robust, integrated solution using a two-section mutual injection DFB laser. The device was fabricated using the reconstruction equivalent chirp (REC) technique, which provides precise control over grating phase variation while utilizing low-cost, high-volume fabrication methods.The laser sections, each measuring 450 m in length, were designed with a free-running wavelength difference of 0.3 nm to ensure a flat optical spectrum and enhanced chaotic dynamics. By optimizing the bias currents, we achieved a chaos RF bandwidth of 20.1 GHz. Notably, the resulting chaotic signal lacks time-delayed signatures, which simplifies the randomness extraction process. To generate random bits, the chaotic waveform was sampled by an 8-bit analog-to-digital converter at 100 Gb/s. Following post-processing through delay-subtracting and the extraction of the four least significant bits (4-LSBs), we realized a total physical random bit rate of 400 Gb/s. The randomness of the generated sequence was successfully verified using the NIST SP 800-22 statistical test suite. This approach offers a compact, energy-efficient, and high-performance integrated chaotic source suitable for secure communication and high-performance computation.

Abstract: Soil salinization is increasingly threatening global agricultural productivity and food security, currently affecting over 6% of the world’s land and one-third of irrigated areas. Tomato (Solanum lycopersicum L.), a major vegetable crop worldwide, exhibits moderate sensitivity to salinity, which limits both its yield and fruit quality. In recent years, epigenetic regulation has gained attention as a key mechanism enabling flexible and reversible control of gene expression without altering DNA sequences. This review synthesizes current knowledge on the epigenetic control of salt stress responses in tomato, focusing on three interconnected levels: DNA methylation dynamics, RNA-directed DNA methylation (RdDM), and histone modifications. We explore how DNA methyltransferases reshape the methylome under salinity, using examples such as PKE1 and SlGI to illustrate functional gene-body methylation. The RdDM pathway is discussed with emphasis on the unexpected role of SlAGO4A as a negative modulator of stress tolerance and the growing evidence for RdDM-mediated regulation of transcription factors. We also examine the balanced regulation of histone acetylation and deacetylation, highlighting the conserved role of GCN5 in maintaining cell wall integrity and the diverse functions of HDACs (SlHDA1, SlHDA3, SlHDA5) in stress adaptation. Additionally, insights from wild tomato species and grafting-induced epigenetic changes are presented, revealing new dimensions of stress memory. Collectively, these epigenetic mechanisms constitute a complex regulatory framework that integrates stress responses with growth and development, providing potential targets for epigenetic breeding of salt-tolerant tomatoes.

Abstract: Ochratoxin A (OTA) is a mycotoxin commonly associated with coffee production and represents a potential concern for occupational health due to fungal exposure in agricultural environments. This study aimed to assess occupational risk related to fungal exposure and OTA in small-scale coffee production systems in Quindío, Co-lombia. A cross-sectional descriptive study was conducted in ten farms. OTA concen-trations in green coffee were analysed using High-Performance Liquid Chromatog-raphy with Fluorescence Detection (HPLC-FLD), while environmental variables, in-cluding temperature and relative humidity, were measured, and structured surveys were applied to evaluate agricultural practices and hygienic conditions. All samples showed OTA concentrations below the detection limit (< 0.8 µg/kg). However, compli-ance with hygienic practices averaged 48.9%, indicating deficiencies in preventive measures. Although OTA contamination was not detected under the evaluated condi-tions, the results indicate potential occupational exposure to fungal bioaerosols during coffee production activities. These findings highlight the importance of integrating en-vironmental monitoring, Good Agricultural Practices (GAP), and occupational risk management strategies to reduce biological hazards and protect agricultural workers.

Abstract: Peptides are short chains of amino acids with a unique pharmacological niche between small-molecule drugs and large proteins. Their use in sports medicine is rapidly expanding, driven by patient demand for accelerated injury recovery and performance enhancement. While numerous peptide drugs have undergone a rigorous approval process that evaluates both safety and efficacy, a parallel "gray market" of unapproved compounds has emerged, operating largely outside regulatory oversight. Our objective is to present the pharmacological mechanisms, safety profiles, and regulatory status of prominent approved and unapproved peptides marketed direct to patients, including AOD-9604 (Anti-Obesity Drug 9604), BPC-157 (Body Protection Compound 157), CJC-1295, FS-344 (Follistatin-344), GHK-Cu (Glycyl-L-histidyl-L-lysine copper), ipamorelin, MOTS-C (Mitochondrial ORF of the 12S rRNA type-c), sermorelin, SS-31 (Elamipretide), tesamorelin (Egrifta), Tβ4 (thymosin beta-4), and TB-500 (thymosin beta-4 fragment). Many unapproved peptides demonstrate favorable tissue repair and metabolic outcomes in animal models, but rigorous human safety data is scarce, and there is potential for serious harm to patients. This narrative review focuses on the utilization of peptides in sports medicine, and alternative treatments that may be considered. We provide a framework to navigate patient discussions about peptides to better facilitate evidence-based practices for musculoskeletal healing and athletic performance. We also discuss the placebo effect as a mediator of peptide efficacy, and how social media amplifies this effect.

Abstract: This study evaluates the environmental performance of feed‑grade soy protein concentrate (SPC‑Feed) produced by Porta Hnos. S.A. in Córdoba, Argentina, through a cradle‑to‑gate plus end‑of‑life Life Cycle Assessment (LCA), with a specific focus on carbon footprint (CF). The assessment follows ISO 14040, 14044, and 14067 standards, using SimaPro^® with Ecoinvent 3.10 and Agri‑footprint 6.0 databases. Primary agricultural data were collected from soybean‑producing farms in Córdoba for the 2023/2024 season, while industrial process data correspond to the 2024 production year. System boundaries include soybean cultivation, soybean pressing, SPC extraction and drying, packaging, transportation to local and international markets, and packaging end‑of‑life. Results show CF values ranging from 0.608 to 0.851 kg CO₂‑eq per kg of SPC‑Feed, depending on market destination and packaging type. Agricultural production contributes ≈25% of total emissions, driven mainly by crop residues (54.7%), herbicide use, and fuel consumption. Industrial emissions are dominated by natural gas use in cogeneration and thermal processes, representing ≈43% of total CF. Downstream emissions are highly dependent on transport distances, especially for international markets. Comparative assessments indicate that SPC‑Feed produced in Argentina exhibits lower carbon intensity than similar products modeled for Brazil, USA, and Europe, primarily due to favorable agricultural conditions and the absence of land‑use‑change emissions. These findings support the environmental competitiveness of Argentine SPC‑Feed and highlight opportunities for further emission reductions through energy efficiency and logistics optimization.

Abstract:

Alice stays outside a black hole; Bob falls in. Alice never sees the interior. Bob crosses the horizon but can never signal back. Physics holds subjectively for both, yet their realities objectively contradict. This illustrating a conflict between quantum and classical mechanics. AMPS is a thought experiment about this. It asks one observer to distil a purifier of a late Hawking mode \( B \) from early radiation $R$, then compare it with the interior partner \( A \) inside a single causal patch. The hidden cost is not just computation but control. If the correct decoder depends on the black hole microstate, the observer must carry a physical selector for the decoder family. I model that selector as a finite control register bounded by the covariant entropy bound on the patch. A covering argument shows that any fixed, state-independent decoder works on at most \( 2^{\alpha_* S_{\mathrm{BH}}+c_\varepsilon} \) microstates, so the observer needs at least \( (1-\alpha_*)S_{\mathrm{BH}}-c_\varepsilon \) control bits---requiring a patch with area fraction \( \rho^2 \ge 1-\alpha_* - c_\varepsilon/S_{\mathrm{BH}} \). A time-sharing objection fails because single-observer verification requires co-instantiation, not mere sequential occurrence; serialisation creates no free room. The conclusion: a subhorizon observer generally cannot certify the AMPS contradiction. In quantum gravity, control information is physical, and single-observer certification is a capacity problem. If the contradiction can never be measured, is it real?

Abstract: This paper introduces the Morphological Participation Index (MPI), a substrate-agnostic framework for estimating whether a system’s morphology can plausibly support strongly integrated, coherence-sensitive, trace-rich, and temporally scaffolded dynamics. “Participation” refers to the degree to which morphology actively contributes to, constrains, and scaffolds the integrated, trace-bearing, and temporally organized dynamics available to a system. The immediate motivation comes from two adjoining lines of work: spectral approaches to resistance to decomposition, and recent proposals by Schneider and Bailey concerning prototime, quantum Darwinist stabilization, and the selective emergence of conscious basins [2,16–18]. MPI evaluates the structural conditions under which a system might sustain unified dynamics, stable internal traces, and organized temporal regimes, without presupposing a human, cortical, or even purely biological baseline. Formally, MPI represents morphology as a weighted constraint hypergraph [4,24], or as an explicit multilayer family of such hypergraphs [11], and returns a score bundle rather than a single undifferentiated scalar. The core bundle consists of six components: integration geometry, multiscale nesting, resonant-mode support, trace geometry, temporal scaffolding, and robustness. An optional contextual patchiness module is provided for domains in which a defensible predicate family is available. The integration component is anchored in a balanced-cut spectral formalism: it uses sweep cuts over the Fiedler vector of the normalized Laplacian rather than raw minimum-cut objectives or simple sign cuts, thereby avoiding familiar degeneracies and linking MPI directly to contemporary spectral proxies for resistance to informational decomposition [6,19,23]. The principal contribution of MPI is a structural profile: seam maps, multiscale partitions, trace-capacity maps, temporal breadth measures, and perturbation-stability diagnostics, in a form that remains useful across biological, artificial, collective, and other nonstandard architectures. More generally, the same diagnostics may be useful in AI alignment. Seam topology, trace geometry, and temporal scaffolding provide a way to screen for architectures that may be difficult to audit, prone to distributed lock-in, or vulnerable to hidden coordination through narrow bottlenecks or persistent externalized traces. MPI can also serve as a screening tool for artificial systems whose structural profile merits closer safety and oversight attention.

Abstract: The global leather industry generates significant volumes of tannery wastes, creating conducive niche for the proliferation of proteolytic microbes. The study investigated microbial valorization of tannery waste through production and physicochemical characterization of a highly stable alkaline protease. Over 100 bacterial strains were isolated from the aqueous waste of Awash Tannery. Among these, 22 isolates were exhibited visible distinct clear zones around the colonies. Out of 22 bacterial strains, YATW18 was identified as the most efficient producer of extracellular alkaline protease; with 92.65 U/mL Activity at 48h. Molecular identification based on 16S rRNA gene sequence identified the strain YATW18 as Alkalihalophilus pseudofirmus. Physicochemical characterization of alkaline protease showed optimum activity at 55℃ and pH 10. The enzyme reached its saturation level within 20 min of incubation time and then linear activity was observed until 45 min. The enzyme activity of alkaline protease demonstrated a notable tolerance to increasing salt concentrations. Most metal ions had minimal influence on protease activity across concentrations, with the relative activity close to 100%. Overall, this study showed microbial valorization of tannery waste and its huge potential to be used as a key source of efficient and stable alkaline protease.

Abstract: Rationale: Informal waste scavenging is a critical livelihood strategy in many Nigerian urban settings, yet it exposes workers to occupational hazards and psychosocial stress. Limited data exist on how socio-demographic factors and work duration influence perceived stress and psychosocial challenges among waste scavengers. Objectives: To examine the socio-demographic characteristics of waste scavengers, assess associations between duration of engagement and perceived stress, and identify primary psychosocial challenges related to scavenging in Ilorin and Oshogbo, Nigeria. Methods: A cross-sectional survey was conducted among 155 waste scavengers recruited from Ilorin and Oshogbo. Data on age, gender, education, marital status, duration of engagement, perceived stress levels, and primary psychosocial challenges were collected using structured questionnaires. Associations were assessed using Pearson chi-square tests, with consideration of expected cell counts. Descriptive statistics summarized socio-demographics and psychosocial profiles. Results: The workforce was predominantly young (18-27 years, 27.1%), male (52.3%), and had primary or secondary education (55.5%). Most scavengers had engaged in waste collection for less than three years (69.7%). Perceived stress varied with duration but was not statistically significant (χ²(12) = 14.680, p = 0.259), though higher proportions of extreme stress were observed among longer-duration workers. Feelings of shame or embarrassment (38.8%) and anxiety about safety (31.6%) were the most frequently reported psychosocial challenges, consistently observed across stress categories, with no statistically significant association (χ²(20) = 16.666, p = 0.675). Conclusion: Waste scavengers experience persistent psychosocial challenges regardless of duration, highlighting stigma and occupational hazards as key stressors. Recommendation: Implement psychosocial support programs, cooperative frameworks, and safety interventions to mitigate occupational stress and improve well-being. Thus, addressing psychosocial and occupational risks among informal waste workers is essential for reducing mental health burden and enhancing safety in urban waste management.

Abstract: Large language models (LLMs) represent a cutting-edge breakthrough in the deep learning models designed for processing human languages. This study created a local LLM that used Book Four of the Civil Code of Catalonia relating to Successions and the regulations of the Notary Profession of Spain for summarization and answering questions in a context of increased security. The model summarized and replied to specific questions in a reasonable manner but was not absent of information loss and contextual misinterpretation. In the field of legal sciences, this technology represents an opportunity. However, only precise information and secure legal reliability should be considered valid.

Abstract: Immune checkpoint modulation has emerged as a promising strategy in cancer therapy, including the treatment of aggressive tumors such as glioblastoma. Among these targets, programmed death-ligand 1 (PD-L1) plays a key role in tumor immune evasion and represents an attractive target for small-molecule inhibitor development. In this study, a virtual screening approach was applied to identify potential PD-L1 modulators within a library of nucleoside-related compounds and structurally similar molecules. A dataset of 400 compounds was evaluated using molecular docking to predict their binding affinity (free energy values and binding pose) toward PD-L1. The resulting complexes were analyzed to identify non-bond interactions within the hydrophobic pocket formed at the PD-L1 dimer interface. In addition to docking results, physicochemical descriptors associated with drug-likeness and blood brain barrier penetration were calculated, including lipophilicity, molecular weight, hydrogen bond donors and acceptors, and topological polar surface area. To integrate these parameters, a multiparameter optimization (MPO) score was implemented. The analysis revealed that several top-ranked compounds exhibited favorable docking scores and physicochemical properties compatible with drug-like behavior. Interestingly BMS-1, a known PD-L1 inhibitor was identified among the highest-scoring compounds, supporting the reliability of the MPO protocol. Furthermore, multiple candidates displaying nucleoside-like scaffolds combined with reduced polarity and moderate lipophilicity emerged as promising molecules according to the MPO ranking. Overall, the results suggest that nucleoside-derived scaffolds may represent a viable starting point for the development of small-molecule PD-L1 modulators with potential applicability in glioblastoma therapy.

Abstract: In this review, we explore the evolving role of endoscopic ultrasound (EUS) in diagnosing and managing pancretobiliary malignancies. For solid pancreatic lesions, techniques like fine-needle biopsy (FNB), contrast-enhanced EUS (CE-EUS), and macroscopic on-site evaluation (MOSE) improve sample quality and diagnostic accuracy. In cystic pancreatic lesions, fine-needle aspiration (FNA), molecular testing, and confocal laser endomicroscopy (nCLE) aid in distinguishing benign from malignant cysts. For cholangiocarcinoma, EUS guided sampling is more accurate than CT in assessing distal lesions and lymph node metastases, while combining EUS with magnetic resonance cholangiography (MRC) enhances diagnostic sensitivity. In gallbladder cancer, EUS surpasses CT and MRI in detecting lymphadenopathy and staging tumors. EUS-FNB (Fine needle biopsy) improves biopsy accuracy, especially for unresectable cases. These advancements highlight EUS as a critical tool for early cancer detection, staging, and tissue acquisition. Beyond diagnosis, EUS plays a pivotal therapeutic role in managing complications such as malignant biliary obstruction and gastric outlet obstruction, offering minimally invasive alternatives like EUS-guided biliary drainage and gastroenterostomy with high clinical success and improved patient outcomes.

Abstract: Background/Objectives: Maternal mortality is a serious public health problem and reflects social, ethnic, racial, and regional inequalities in access to and quality of obstetric care. Despite advances in the surveillance and investigation of maternal deaths in Brazil, late maternal deaths (occurring between 43 days and 1 year after birth) are still underestimated and underexplored. Therefore, the objective of this study was to analyze the distribution and factors associated with maternal deaths and late maternal deaths in Brazil between 2010 and 2023. Methods: This was a population-based, retrospective cohort study with a quantitative approach, using secondary data from the Mortality Information System. All maternal deaths (Chapter XV of ICD-10) and late deaths recorded during the period were included. Sociodemographic, clinical, and administrative variables were analyzed. Statistical tests of association (chi-square, test of proportions, and 95% CI) were used, with a significance level of 5%. Results: A total of 26,953 deaths were identified, of which 24,387 were maternal and 2,566 were late deaths. Most deaths occurred among single, mixed-race women with 8 to 11 years of schooling, and residing in the Southeast region. Late deaths were more frequent in the South and among women aged 40 to 49. The main causes were direct obstetric conditions. A statistically significant association was observed between the type of death and sociodemographic variables. Conclusions: The results highlight structural inequalities in maternal mortality in Brazil and reinforce the importance of expanding postpartum surveillance beyond 42 days, with a focus on equity and continuity of care.

Abstract: This study investigates the safety measures associated with blending hydrogen (H₂) with methane (CH₄) to reduce carbon emissions in the hard-to-abate industries, trans-portation sectors and domestic uses. The results highlighted significant safety risks due to hydrogen's lower ignition energy (IE) and broader flammability range, especially under high-pressure conditions. Using Aspen HYSYS chemical process simulation and the HSC Chemistry platform, the study quantified carbon emissions and combustion heat release of H₂-CH₄ mixtures at various H₂ contents, temperatures, and pressures. The results suggest that blending H₂ with CH₄ can be beneficial, provided H₂ content does not exceed safe thresholds and stays within a recommended Wobbe Index (WI) range of 45 - 55 MJ/m³. The WI increases with H₂ concentration exceeding 50 mole% due to density effects outweighing HHV reductions. Hydrogen's high buoyancy and diffusivity reduce localized accumulation in open areas but pose risks in confined spaces due to its wide flammability range. H₂-CH₄ blends with ≤ 20 mole% H₂ are safer than higher concentrations or pure H₂. For blends with > 20 mole% H₂, engineered safety features (ESF) like leak detection, alarms, ventilation, and spark-free environ-ments are essential. Managing concentrations to avoid the detonation range (pure H₂: 18 - 59 mole% & pure CH₄: 6.3 - 13.5 mole%) is critical. Adhering to H2 safety codes limiting H₂ to ≤ 20 mole% in pipelines is recommended. Conservatively, < 18 mole% H2 reduces detonation risk, and ≤ 10 mole% provides added safety margins. These find-ings can guide policymakers and industry stakeholders in developing safe, efficient hydrogen-enhanced energy systems, hence supporting carbon reduction goals.

Abstract: Automatic modulation classification (AMC) is a key component of spectrum awareness, cognitive radio, and signal intelligence, enabling receivers to identify modulation schemes from noisy in-phase and quadrature (IQ) observations. Traditional approaches rely on likelihood-based methods or handcrafted feature extraction, which often struggle under channel impairments and real-world variability. Recent advances in deep learning enable models to learn directly from multiple signal representations, including raw IQ samples, engineered features, and time–frequency or constellation-based encodings, improving adaptability across diverse signal conditions. This paper presents a structured review of deep learning approaches for AMC, including CNNs, RNN/LSTM models, and transformer-based architectures, with a focus on performance, robustness, and system-level trade-offs. We analyze how representation choices, dataset design, and evaluation protocols influence reported results, and highlight key challenges such as domain shift, low-SNR environments, and multi-signal interference. Finally, we outline future directions focused on improving generalization, integrating classical signal processing with learning-based methods, and enabling efficient deployment in real-world and resource-constrained systems.

Abstract: To maintain homeostatic conditions and optimal function during stressors, mitochondria initiate nuclear retrograde signaling. The mitochondrial Integrated Stress Response (ISR) and Unfolded Protein Response (UPR^mt) are critical quality control mechanisms activated during instances of mitochondrial perturbations. Restoration of mitochondrial homeostasis is orchestrated by three transcription factors, ATF4, CHOP, and ATF5, which upregulate protective genes to counteract stress. As the health and function of skeletal muscle is heavily dependent on a highly adaptive mitochondrial network, defining how mitochondrial health is maintained across various conditions is essential. Although several studies demonstrate the importance of these responses following instances of stress, the signaling mechanisms required to initiate such pathways remain poorly characterized in skeletal muscle. This review examines how the mitochondrial ISR/UPRmt and related transcription factors respond to organellar stress by emphasizing the molecular events that occur during exercise, aging and muscle disuse. Through consolidating the literature, this work aims to highlight the current understanding of mitochondrial stress response signaling within skeletal muscle and thus emphasize areas for future research and potential therapeutic strategies during divergent metabolic conditions.

Abstract: Ultrasonic cyberattacks represent an emerging threat vector capable of exfiltrating information even from high-security systems. Modern computing devices equipped with integrated speakers and microphones can generate ultrasonic emissions that may be exploited for covert communication. Previous studies have demonstrated that malicious software can utilize ultrasonic audio channels to establish communication links between otherwise isolated systems, enabling data leakage from air-gapped environments by relaying information through acoustic signals. Experimental results have shown that data can be transmitted at rates of up to 20 bits per second over distances of approximately 18 meters (60 feet), facilitating the covert transfer of sensitive information. Moreover, networks of compromised devices can be chained together to bridge air-gapped systems and transmit data to external receivers. The work presents a real-time system that detects and disrupts covert ultrasonic communication used for hidden data transmission. The authors demonstrate the threat by building an ultrasonic Morse-code channel capable of transmitting data up to 20 meters. To counter this, they develop a mitigation framework using external acoustic hardware that detects ultrasonic signals and jams them with high-power interference. The system effectively prevents data exfiltration, showing strong performance at distances of 5, 10, and 15 meters across different environments.