Loss of epigenetic information as a cause of mammalian aging.

All living things experience an increase in entropy, manifested as a loss of genetic and epigenetic information. In yeast, epigenetic information is lost over time due to the relocalization of chromatin-modifying proteins to DNA breaks, causing cells to lose their identity, a hallmark of yeast aging. Using a system called "ICE" (inducible changes to the epigenome), we find that the act of faithful DNA repair advances aging at physiological, cognitive, and molecular levels, including erosion of the epigenetic landscape, cellular exdifferentiation, senescence, and advancement of the DNA methylation clock, which can be reversed by OSK-mediated rejuvenation. These data are consistent with the information theory of aging, which states that a loss of epigenetic information is a reversible cause of aging.

LanCLs add glutathione to dehydroamino acids generated at phosphorylated sites in the proteome.

Enzyme-mediated damage repair or mitigation, while common for nucleic acids, is rare for proteins. Examples of protein damage are elimination of phosphorylated Ser/Thr to dehydroalanine/dehydrobutyrine (Dha/Dhb) in pathogenesis and aging. Bacterial LanC enzymes use Dha/Dhb to form carbon-sulfur linkages in antimicrobial peptides, but the functions of eukaryotic LanC-like (LanCL) counterparts are unknown. We show that LanCLs catalyze the addition of glutathione to Dha/Dhb in proteins, driving irreversible C-glutathionylation. Chemo-enzymatic methods were developed to site-selectively incorporate Dha/Dhb at phospho-regulated sites in kinases. In human MAPK-MEK1, such "elimination damage" generated aberrantly activated kinases, which were deactivated by LanCL-mediated C-glutathionylation. Surveys of endogenous proteins bearing damage from elimination (the eliminylome) also suggest it is a source of electrophilic reactivity. LanCLs thus remove these reactive electrophiles and their potentially dysregulatory effects from the proteome. As knockout of LanCL in mice can result in premature death, repair of this kind of protein damage appears important physiologically.

Global chemical effects of the microbiome include new bile-acid conjugations.

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease1-9. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units10), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches11-13 to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry14. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.

Role of MicroRNA-21 in Prostate Cancer Progression and Metastasis: Molecular Mechanisms to Therapeutic Targets.

The role of noncoding RNA has made remarkable progress in understanding progression, metastasis, and metastatic castration-resistant prostate cancer (mCRPC). A better understanding of the miRNAs has enhanced our knowledge of their targeting mainly at the therapy level in solid tumors, such as prostate cancer (PCa). microRNAs (miRNAs) belong to a class of endogenous RNA that deficit encoded proteins. Therefore, the role of miRNAs has been well-coined in the progression and development of PCa. miR-21 has a dual nature in its work both as a tumor suppressor and oncogenic role, but most of the recent studies showed that miR-21 is a tumor promoter and also is involved in castration-resistant prostate cancer (CRPC). Upregulation of miR-21 suppresses programmed cell death and inducing metastasis and castration resistant in PCa. miR-21 is involved in the different stages, such as proliferation, angiogenesis, migration, and invasion, and plays an important role in the progression, metastasis, and advanced stages of PCa. Recently, various studies directly linked the role of high levels of miR-21 with a poor therapeutic response in the patient of PCa. In the present review, we have explained the molecular mechanisms/pathways of miR-21 in PCa progression, metastasis, and castration resistant and summarized the role of miR-21 in diagnosis and therapeutic levels in PCa. In addition, we have spotlighted the recent therapeutic strategies for targeting different stages of PCa.

Intratumoral Heterogeneity, Chemoresistance and Lymph Node Landing Zone Prognosis in Testicular Tumors Based on Histopathological Characteristics.

BACKGROUND: Existing data on the histopathological correlation of testicular tumors with lymph node prognosis have been poorly explored. We aimed to investigate the relationship of the histopathological properties of testicular tumors with lymph nodes and their involvement with chemoresistance and heterogeneity of testicular tumors. METHODS: Patients with non-seminomatous germ cell tumor (NSGCT) were selected for histopathological correlation of testicular tumor with lymph nodes and its relationship with chemoresistance and heterogeneity. Histopathological and radiological parameters associated with the risk of chemoresistance and tumor progression were measured pre- and post-chemotherapy. Binomial logistic regression and Kaplan-Meier analysis were implemented to determine the predictors of progression and adverse overall patient survival. All categorical variables were analyzed using the Chi-square test, while Pearson's R coefficient determined the correlation. RESULTS: Male patients who were diagnosed with NSGCT from March 2017 to December 2018 at Guwahati Medical College, Guwahati, India, were included in this study. Lymph node groups were predominantly incriminated with the EYST or EYS groups and minimally linked with the pure E and YCS groups. Furthermore, the highest number of lymph node stations was associated with pre-chemotherapy. In salvage chemotherapy in the form of VIP, we found exciting outcomes, as approximately 41% of cases responded positively, especially in the EYS group. CONCLUSION: Our study classifies NSGCT according to the most favorable histopathological grouping and explores the tumoral response in different intrinsic and extrinsic variables. Our analysis can serve as a triumphant histopathological nomogram for a sublime management protocol to deal with the onerous histological pairing in NSGCT.

Design of C2-symmetric pseudopeptides for in vivo detection of Cu(II) through controlled supramolecular nano-assembly.

Pseudopeptides are emerging next-generation soft bioinspired materials for biological applications. Therefore, a new class of C2-symmetric L-valine-derived pseudopeptides has been designed and developed. The newly developed pseudopeptides exhibit intracellular Cu(II) ion detection in live-cell fluorescence studies on RAW264.7 cells. We find that the changes in the amino acid side chain in desired pseudopeptidic moieties lead to a drastic change in their selectivity towards different metal ions. The L-valine-derived pseudopeptides exhibit selectivity towards Cu(II) ions through turn-off fluorescence, and the L-phenylalanine-derived pseudopeptides exhibit selectivity towards Zn(II) ions through turn-on fluorescence. In addition, the L-valine-derived pseudopeptides show an increase in spherical-shaped structures upon incubation with Cu(II) ions during supramolecular nano-assembly formation. In contrast, the L-phenylalanine-derived pseudopeptides show a decrease in spherical-shaped structures upon adding Zn(II) ions. The judiciously designed L-valine-derived and L-phenylalanine-derived bioinspired pseudopeptides are promising for exploring similar effects in various peptidomimetics in advanced biological applications.

Improved time complexity for spintronic oscillator Ising machines compared to a popular classical optimization algorithm for the Max-Cut problem.

Solving certain combinatorial optimization problems like Max-Cut becomes challenging once the graph size and edge connectivity increase beyond a threshold, with brute-force algorithms which solve such problems exactly on conventional digital computers having the bottleneck of exponential time complexity. Hence currently, such problems are instead solved approximately using algorithms like Goemans-Williamson (GW) algorithm, run on conventional computers with polynomial time complexity. Phase binarized oscillators (PBOs), also often known as oscillator Ising machines (OIM), have been proposed as an alternative to solve such problems. In this paper, restricting ourselves to the combinatorial optimization problem Max-Cut solved on three kinds of graphs (Mobius Ladder, random cubic, Erdos Renyi) up to 100 nodes, we empirically show that computation time/ time to solution (TTS) for PBOs (captured through Kuramoto model) grows at a much lower rate (logarithmically: O(log(N)), with respect to graph size N) compared to GW algorithm, for which TTS increases as square of graph size (O(N2). However, Kuramoto model being a physics-agnostic mathematical model, this time complexity/ TTS trend for PBOs is a general trend and is device-physics agnostic. So for more specific results, we choose spintronic oscillators, known for their high operating frequency (in GHz), and model them through Slavin's model which captures the physics of their coupled magnetization oscillation dynamics. We thereby empirically show that TTS of spintronic oscillators also grows logarithmically with graph size (O(log(N)), while their accuracy is comparable to that of GW. So spintronic oscillators have improved time complexity over GW algorithm. For large graphs, they are expected to compute Max-Cut values much faster than GW algorithm, as well as other oscillators operating at lower frequencies, while maintaining the same level of accuracy. .

Adaptive activation Functions with Deep Kronecker Neural Network optimized with Bear Smell Search Algorithm for preventing MANET Cyber security attacks.

An Adaptive activation Functions with Deep Kronecker Neural Network optimized with Bear Smell Search Algorithm (BSSA) (ADKNN-BSSA-CSMANET) is proposed for preventing MANET Cyber security attacks. The mobile users are enrolled with Trusted Authority Using a Crypto Hash Signature (SHA-256). Every mobile user uploads their finger vein biometric, user ID, latitude and longitude for confirmation. The packet analyser checks if any attack patterns are identified. It is implemented using adaptive density-based spatial clustering (ADSC) that deems information from packet header. Geodesic filtering (GF) is used as a pre-processing method for eradicating the unsolicited content and filtering pertinent data. Group Teaching Algorithm (GTA)-based feature selection is utilized for ideal collection of features and Adaptive Activation Functions along Deep Kronecker Neural Network (ADKNN) is used to categorizing normal and attack packets (DoS, Probe, U2R, and R2L). Then BSSA is utilized for optimizing the weight parameters of ADKNN classifier for optimal classification. The proposed technique is executed in python and its efficiency is evaluated by several performances metrics, such as Accuracy, Attack Detection Rate, Detection Delay, Packet Delivery Ratio, Throughput, and Energy Consumption. The proposed technique provides 36.64%, 33.06%, and 33.98% lower Detection Delay on NSL-KDD dataset compared with the existing methods.

Management of grade II and III furcation defects with intramarrow penetration along with indigenously prepared DFDBA and amniotic membrane: a clinical and radiographic study.

Managing furcation defects constitutes a problem in successful periodontal therapy. Guided tissue regeneration (GTR) is the mainstay for the management of such defects but is expensive. This study makes use of indigenously prepared demineralized freeze-dried bone allograft (DFDBA) and amniotic membrane (AM) as a cost-effective alternative. The purpose of the study was to compare the clinical outcome of grade II and III furcation defects with and without using indigenous DFDBA and AM prepared at Central Tissue Bank, MAIDS. 18 systemically healthy patients with chronic periodontitis displaying either grade II or III furcation defects were treated with open flap debridement (OFD) + intramarrow penetration (IMP) (control group) and OFD + IMP + DFDBA + AM (test group). The clinical and radiographic parameters were recorded at 3 and 6 months postoperatively. All parameters were statistically analyzed. Both treatment modalities resulted in improvement in all clinical variables evaluated. Radiographic dimensions evaluating bone fill showed a statistically significant difference in the test group compared to the control group. Within the limitations of this study, data suggest GTR using indigenously prepared DFDBA and amniotic membrane to be an economical and viable option for treating furcation defects.

End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini.

Background: End-of-life care (EOLC) is a critical aspect of healthcare, yet accessing reliable information remains challenging, particularly in culturally diverse contexts like India. Objective: This study investigates the potential of artificial intelligence (AI) in addressing the informational gap by analyzing patient information leaflets (PILs) generated by AI chatbots on EOLC. Methodology: Using a comparative research design, PILs generated by ChatGPT and Google Gemini were evaluated for readability, sentiment, accuracy, completeness, and suitability. Readability was assessed using established metrics, sentiment analysis determined emotional tone, accuracy, and completeness were rated by subject experts, and suitability was evaluated using the Patient Education Materials Assessment Tool (PEMAT). Results: Google Gemini PILs exhibited superior readability and actionability compared to ChatGPT PILs. Both conveyed positive sentiments and high levels of accuracy and completeness, with Google Gemini PILs showing slightly lower accuracy scores. Conclusion: The findings highlight the promising role of AI in enhancing patient education in EOLC, with implications for improving care outcomes and promoting informed decision-making in diverse cultural settings. Ongoing refinement and innovation in AI-driven patient education strategies are needed to ensure compassionate and culturally sensitive EOLC. How to cite this article: Gondode PG, Khanna P, Sharma P, Duggal S, Garg N. End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini. Indian J Crit Care Med 2024;28(6):561-568.

Functional inhibition of c-Myc using novel inhibitors identified through "hot spot" targeting.

Protein-protein interactions drive various biological processes in healthy as well as disease states. The transcription factor c-Myc plays a crucial role in maintaining cellular homeostasis, and its deregulated expression is linked to various human cancers; therefore, it can be considered a viable target for cancer therapeutics. However, the structural heterogeneity of c-Myc due to its disordered nature poses a major challenge to drug discovery. In the present study, we used an in silico alanine scanning mutagenesis approach to identify "hot spot" residues within the c-Myc/Myc-associated factor X interface, which is highly disordered and has not yet been systematically analyzed for potential small molecule binding sites. We then used the information gained from this analysis to screen potential inhibitors using a conformation ensemble approach. The fluorescence-based biophysical experiments showed that the identified hit molecules displayed noncovalent interactions with these hot spot residues, and further cell-based experiments showed substantial in vitro potency against diverse c-Myc-expressing cancer/stem cells by deregulating c-Myc activity. These biophysical and computational studies demonstrated stable binding of the hit compounds with the disordered c-Myc protein. Collectively, our data indicated effective drug targeting of the disordered c-Myc protein via the determination of hot spot residues in the c-Myc/Myc-associated factor X heterodimer.

Discovery and Biosynthesis of Ureidopeptide Natural Products Macrocyclized via Indole N-acylation in Marine Microbulbifer spp. Bacteria.

Commensal bacteria associated with marine invertebrates are underappreciated sources of chemically novel natural products. Using mass spectrometry, we had previously detected the presence of peptidic natural products in obligate marine bacteria of the genus Microbulbifer cultured from marine sponges. In this report, the isolation and structural characterization of a panel of ureidohexapeptide natural products, termed the bulbiferamides, from Microbulbifer strains is reported wherein the tryptophan side chain indole participates in a macrocyclizing peptide bond formation. Genome sequencing identifies biosynthetic gene clusters encoding production of the bulbiferamides and implicates the involvement of a thioesterase in the indolic macrocycle formation. The structural diversity and widespread presence of bulbiferamides in commensal microbiomes of marine invertebrates point toward a possible ecological role for these natural products.

Whole-Cell MALDI-ToF MS Coupled with Untargeted Metabolomics Facilitates Investigations of Microbial Chemical Interactions.

The emergence of drug-resistant pathogens necessitates the development of new countermeasures. In this regard, the introduction of probiotics to directly attack or competitively exclude pathogens presents a useful strategy. Application of this approach requires an understanding of how a probiotic and its target pathogen interact. A key means of probiotic-pathogen interaction involves the production of small molecules called natural products (NPs). Here, we report the use of whole-cell matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) mass spectrometry to characterize NP production by candidate probiotics (mouse airway microbiome isolates) when co-cultured with the respiratory pathogen Burkholderia. We found that a Bacillus velezensis strain inhibits growth of and elicits NP production by Burkholderia thailandensis. Dereplication of known NPs detected in the metabolome of this B. velezensis strain suggests that a previously unannotated bioactive compound is involved. Thus, we present the use of whole-cell MALDI as a broadly applicable method for screening the NP composition of microbial co-cultures; this can be combined with other -omics methods to characterize probiotic-pathogen and other microbe-microbe interactions.

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

Intracellular Zn(II) induced turn-on fluorescence of an L-phenylalanine-derived pseudopeptide.

A C2 symmetric L-phenylalanine-derived pseudopeptide has been synthesized for selective and sensitive recognition of Zn(II) ions in aqueous-organic media. The pseudopeptidic probes exhibit intracellular Zn(II) ion-sensing capabilities as demonstrated via live-cell fluorescence studies on RAW264.7 cells. Hence, we present a bioinspired pseudopeptide for potential biological applications involving intracellular Zn(II) ion detection.

Pseudobulbiferamides: Plasmid-Encoded Ureidopeptide Natural Products with Biosynthetic Gene Clusters Shared Among Marine Bacteria of Different Genera.

Ureidopeptidic natural products possess a wide variety of favorable pharmacological properties. In addition, they have been shown to mediate core physiological functions in producer bacteria. Here, we report that similar ureidopeptidic natural products with conserved biosynthetic gene clusters are produced by different bacterial genera that coinhabit marine invertebrate microbiomes. We demonstrate that a Microbulbifer strain isolated from a marine sponge can produce two different classes of ureidopeptide natural products encoded by two different biosynthetic gene clusters that are positioned on the bacterial chromosome and on a plasmid. The plasmid encoded ureidopeptide natural products, which we term the pseudobulbiferamides (5-8), resemble the ureidopeptide natural products produced by Pseudovibrio, a different marine bacterial genus that is likewise present in marine sponge commensal microbiomes. Using imaging mass spectrometry, we find that the two classes of Microbulbifer-derived ureidopeptides occupy different physical spaces relative to the bacterial colony, perhaps implying different roles for these two compound classes in Microbulbifer physiology and environmental interactions.

Targeted drug delivery using beeswax-derived albendazole-loaded solid lipid nanoparticles in Haemonchus contortus, an albendazole-tolerant nematode.

Targeted delivery has not been achieved for anthelmintic treatment, resulting in the requirement of excess drug dose leading to side effects and therapeutic resistance. Gastrointestinal helminths take up lipid droplets from digestive fluid for energy production, egg development, and defense which inspired us to develop biocompatible and orally administrable albendazole-loaded solid lipid nanoparticles (SLN-A) that were derived from beeswax and showed drug loading efficiency of 83.3 ± 6.5 mg/g and sustained-release properties with 84.8 ± 2.5% of drug released at pH 6.4 within 24 h at 37 °C. Rhodamine B-loaded SLN showed time-dependent release and distribution of dye in-vitro in Haemonchus contortus. The sustained-release property was shown by the particles that caused enhancement of albendazole potency up to 50 folds. Therefore, this formulation has immense potential as an anthelminthic drug delivery vehicle that will be able to reduce the dose and drug-induced side effects by enhancing the bioavailability of the drug.

Limited Metabolomic Overlap between Commensal Bacteria and Marine Sponge Holobionts Revealed by Large Scale Culturing and Mass Spectrometry-Based Metabolomics: An Undergraduate Laboratory Pedagogical Effort at Georgia Tech.

Sponges are the richest source of bioactive organic small molecules, referred to as natural products, in the marine environment. It is well established that laboratory culturing-resistant symbiotic bacteria residing within the eukaryotic sponge host matrix often synthesize the natural products that are detected in the sponge tissue extracts. However, the contributions of the culturing-amenable commensal bacteria that are also associated with the sponge host to the overall metabolome of the sponge holobiont are not well defined. In this study, we cultured a large library of bacteria from three marine sponges commonly found in the Florida Keys. Metabolomes of isolated bacterial strains and that of the sponge holobiont were compared using mass spectrometry to reveal minimal metabolomic overlap between commensal bacteria and the sponge hosts. We also find that the phylogenetic overlap between cultured commensal bacteria and that of the sponge microbiome is minimal. Despite these observations, the commensal bacteria were found to be a rich resource for novel natural product discovery. Mass spectrometry-based metabolomics provided structural insights into these cryptic natural products. Pedagogic innovation in the form of laboratory curricula development is described which provided undergraduate students with hands-on instruction in microbiology and natural product discovery using metabolomic data mining strategies.

Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.

The lack of intuitive and active human-robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented. This system was used to acquire kinematic and physiological signals during reaching and placing tasks performed by five healthy subjects. The onset motion data of each motion trial were extracted to input into traditional regression models and deep learning models for training and testing. The models can predict the position of the hand in planar space, which is the reference position for low-level position controllers. The results show that using IMU sensor with the proposed prediction model is sufficient for motion intention detection, which can provide almost the same prediction performance compared with adding EMG or MMG. Additionally, recurrent neural network (RNN)-based models can predict target positions over a short onset time window for reaching motions and are suitable for predicting targets over a longer horizon for placing tasks. This study's detailed analysis can improve the usability of the assistive/rehabilitation robots.