MASLD-Related HCC: A Comprehensive Review of the Trends, Pathophysiology, Tumor Microenvironment, Surveillance, and Treatment Options.

Hepatocellular carcinoma (HCC) represents a significant burden on global healthcare systems due to its considerable incidence and mortality rates. Recent trends indicate an increase in the worldwide incidence of metabolic dysfunction-associated steatotic liver disease (MASLD) and a shift in the etiology of HCC, with MASLD replacing the hepatitis B virus as the primary contributor to new cases of HCC. MASLD-related HCC exhibits distinct characteristics compared to viral HCC, including unique immune cell profiles resulting in an overall more immunosuppressive or exhausted tumor microenvironment. Furthermore, MASLD-related HCC is frequently identified in older age groups and among individuals with cardiometabolic comorbidities. Additionally, a greater percentage of MASLD-related HCC cases occur in noncirrhotic patients compared to those with viral etiologies, hindering early detection. However, the current clinical practice guidelines lack specific recommendations for the screening of HCC in MASLD patients. The evolving landscape of HCC management offers a spectrum of therapeutic options, ranging from surgical interventions and locoregional therapies to systemic treatments, for patients across various stages of the disease. Despite ongoing debates, the current evidence does not support differences in optimal treatment modalities based on etiology. In this study, we aimed to provide a comprehensive overview of the current literature on the trends, characteristics, clinical implications, and treatment modalities for MASLD-related HCC.

Metagenomic 16S rRNA analysis and predictive functional profiling revealed intrinsic organohalides respiration and bioremediation potential in mangrove sediment.

BACKGROUND: Mangrove sediment microbes are increasingly attracting scientific attention due to their demonstrated capacity for diverse bioremediation activities, encompassing a wide range of environmental contaminants. MATERIALS AND METHODS: The microbial communities of five Avicennia marina mangrove sediment samples collected from Al Rayyis White Head, Red Sea (KSA), were characterized using Illumina amplicon sequencing of the 16S rRNA genes. RESULTS: Our study investigated the microbial composition and potential for organohalide bioremediation in five mangrove sediments from the Red Sea. While Proteobacteria dominated four microbiomes, Bacteroidetes dominated the fifth. Given the environmental concerns surrounding organohalides, their bioremediation is crucial. Encouragingly, we identified phylogenetically diverse organohalide-respiring bacteria (OHRB) across all samples, including Dehalogenimonas, Dehalococcoides, Anaeromyxobacter, Desulfuromonas, Geobacter, Desulfomonile, Desulfovibrio, Shewanella and Desulfitobacterium. These bacteria are known for their ability to dechlorinate organohalides through reductive dehalogenation. PICRUSt analysis further supported this potential, predicting the presence of functional biomarkers for organohalide respiration (OHR), including reductive dehalogenases targeting tetrachloroethene (PCE) and 3-chloro-4-hydroxyphenylacetate in most sediments. Enrichment cultures studies confirmed this prediction, demonstrating PCE dechlorination by the resident microbial community. PICRUSt also revealed a dominance of anaerobic metabolic processes, suggesting the microbiome's adaptation to the oxygen-limited environment of the sediments. CONCLUSION: This study provided insights into the bacterial community composition of five mangrove sediments from the Red Sea. Notably, diverse OHRB were detected across all samples, which possess the metabolic potential for organohalide bioremediation through reductive dehalogenation pathways. Furthermore, PICRUSt analysis predicted the presence of functional biomarkers for OHR in most sediments, suggesting potential intrinsic OHR activity by the enclosed microbial community.

Profiling of syngeneic mouse HCC tumor models as a framework to understand anti-PD-1 sensitive tumor microenvironments.

BACKGROUND AND AIMS: The treatment of hepatocellular carcinoma (HCC) has been transformed by the use of immune checkpoint inhibitors. However, most patients with HCC do not benefit from treatment with immunotherapy. There is an urgent need to understand the mechanisms that underlie response or resistance to immunotherapy for patients with HCC. The use of syngeneic mouse models that closely recapitulate the heterogeneity of human HCC will provide opportunities to examine the complex interactions between cancer cells and nonmalignant cells in the tumor microenvironment. APPROACH AND RESULTS: We leverage a multifaceted approach that includes imaging mass cytometry and suspension cytometry by time of flight to profile the tumor microenvironments of the Hep53.4, Hepa 1-6, RIL-175, and TIBx (derivative of TIB-75) syngeneic mouse HCC models. The immune tumor microenvironments vary across these four models, and various immunosuppressive pathways exist at baseline in orthotopic liver tumors derived from these models. For instance, TIBx, which is resistant to anti-programmed cell death protein 1 therapy, contains a high proportion of "M2-like" tumor-associated macrophages with the potential to diminish antitumor immunity. Investigation of The Cancer Genome Atlas reveals that the baseline immunologic profiles of Hep53.4, RIL-175, and TIBx are broadly representative of human HCCs; however, Hepa 1-6 does not recapitulate the immune tumor microenvironment of the vast majority of human HCCs. CONCLUSIONS: There is a wide diversity in the immune tumor microenvironments in preclinical models and in human HCC, highlighting the need to use multiple syngeneic HCC models to improve the understanding of how to treat HCC through immune modulation.

Salivary microbial shifting in hypertensive patients with chronic periodontitis after scaling and root surface debridement.

OBJECTIVES: This study aimed to evaluate the impact of scaling and root surface debridement (SRP) on salivary bacterial counts and systolic and diastolic blood pressure in hypertensive patients with chronic periodontitis, with a focus on clinical significance. METHODS: An observational trial included 24 chronic periodontitis patients, eleven of them were hypertensive patients. Non-surgical periodontal treatment was administered to all patients, with clinical parameters including gingival index (GI), plaque index (PI), and probing pocket depth (PPD) recorded. Saliva samples were collected before and after SRP to quantify total bacterial counts and specific bacterial counts. RESULTS: Two months following SRP, PI and PPD in every subject under study demonstrated good responses. In hypertension patients, the salivary bacterial count was significantly higher following SRP (P = 0.0221). The incidence of Porphyromonas gingivalis in hypertension patients significantly decreased after treatment (P = 0.0386). Despite this, there was no discernible decrease in blood pressure following treatment. CONCLUSIONS: SRP alone was ineffective in reducing overall bacterial counts, but P. gingivalis levels responded favorably. Regular periodontal assessment is crucial for hypertensive individuals to mitigate cardiovascular risk. CLINICAL SIGNIFICANCE: Periodontal therapy in hypertensive patients may improve oral health but might not significantly impact blood pressure. Regular periodontal evaluation is essential for managing cardiovascular risk in hypertension.

Synthesis biological evaluation and molecular docking of isatin hybrids as anti-cancer and anti-microbial agents.

Isatin, known as 1H-indole-2,3-dione, was originally recognised as a synthetic molecule until its discovery in the fruits of the cannonball tree, Couroupita guianensis. It is naturally occurring in plants of the genus Isatis and serves as a metabolic derivative of adrenaline in humans. Isatin possesses significant pharmacological importance, and its synthetic versatility has prompted extensive interest in its derivative compounds due to their diverse biological and pharmacological properties. These derivatives represent a valuable class of heterocyclic compounds with potential applications as precursors for synthesizing numerous valuable drugs. In the pursuit of advancing our research on isatin hybrids, we investigate the utilisation of readily available hydrazonoindolin-2-one and isatin as starting materials for the synthesis of a wide range of analogues. Characterisation of the synthesized compounds was carried out through various analytical techniques. Furthermore, the obtained compounds were subjected to extensive testing to evaluate their anticancer and antimicrobial activities. Specifically, their efficacy against key proteins, namely Staphylococcus aureus protein (PDB ID: 1JIJ), Escherichia coli protein (PDB ID: 1T9U), Pseudomonas aeruginosa protein (PDB ID: 2UV0), and Acinetobacter baumannii protein (PDB ID: 4HKG), was examined through molecular docking calculations. Several molecules, such as 3, 4, 6, 16, and 19, displayed remarkable activity against the renal cancer cell line UO-31. Additionally, the results of antimicrobial activity testing revealed that compound 16 exhibited significant cytotoxicity against Candida albicans and Cryptococcus neoformans. Subsequently, ADME/T calculations were performed to gain insights into the potential effects and reactions of these molecules within human metabolism. This comprehensive study provides valuable insights into the potential pharmacological applications of isatin derivatives and underscores their significance in drug development.

Synthesis and Molecular Docking of some new Thiazolidinone and Thiadiazole Derivatives as Anticancer Agents.

New sets of functionalized thiazolidinone and thiadiazole derivatives were synthesized, and their cytotoxicity was evaluated on HepG2, MCF-7, HTC-116, and WI38 cells. The synthetic approach is based on the preparation of 4-(4-acetamidophenyl)thiosemicarbazide (4) and their thiosemicarbazones 5 a-e, which are converted to the corresponding thiazoldin-4-one compounds 6 a-e upon cyclization with ethyl bromoacetate. The thiadiazole compounds 9 and 12 were obtained by reacting 4-(4-acetamidophenyl)thiosemicarbazide with isothiocyanates and/or ethyl 2-cyano-3,3-bis(methylthio)acrylate, respectively. The thiazolidinone compounds 6 c and 6 e exhibited strong cytotoxicity against breast cancer cells, with an IC50 (6.70±0.5 µM) and IC50 (7.51±0.8 µM), respectively, very close to that of doxorubicin (IC50: 4.17±0.2 µM). In addition, the anti-cancer properties of the tested thiazolidinone and thiadiazole scaffolds were further explored by the molecular docking program (MOE)-(PDB Code-1DLS). Compounds 5 d, 5 e, 6 d, 6 e, and 7 have the best binding affinity, ranging from -8.5386 kcal.mol-1 to -8.2830 kcal.mol-1.

Synthesis of Some Novel Thiophene Analogues as Potential Anticancer Agents.

The aim of this study involves the synthesis novel thiophene analogues that can be used as anticancer medications through a strategic multicomponent reaction connecting ethyl 4-chloroacetoacetate (1), phenyl isothiocyanate, and a series of active methylene reagents, including ethyl acetoacetate (2), malononitrile, ethyl cyanoacetate, cyanoacetamide 6a-c, N-phenyl cyanoacetamide derivatives 13a-c, and acetoacetanilide derivatives 18. This reaction was facilitated by dry dimethylformamide with a catalytic quantity of K2CO3. The resultant thiophene derivatives were identified as 4, 8a-b, 9, 12a-d, 15a-c, and 20a-b. Further reaction of compound 4 with hydrazine hydrate yielded derivative 5, respectively. When compound 1 was refluxed with ethyl 3-mercapto-3-(phenylamino)-2-(p-substituted phenyldiazenyl)acrylate 10a-e in the presence of sodium ethoxide, it produced thiophene derivatives 12a-d. Comprehensive structural elucidation of these newly synthesized thiophene-analogues was accomplished via elemental and spectral analysis data. Furthermore, the study delves into the cytotoxicity of the newly synthesized thiophenes was evaluated using the HepG2, A2780, and A2780CP cell lines. The amino-thiophene derivative 15b exhibited an increased growth inhibition of A2780, and A2780CP with IC50 values 12±0.17, and 10±0.15 µM, respectively compared to Sorafenib with IC50 values 7.5±0.54 and 9.4±0.14. This research opens new avenues for developing thiophene-based anticancer agents.

Synthesis of Competitive and Noncompetitive Inhibitors of Alpha-Glucosidase and Anticancer Agents.

Imidazoles and phenylthiazoles are an important class of heterocycles that demonstrate a wide range of biological activities against various types of cancers, diabetes mellitus and pathogenic microorganisms. The heterocyclic structure having oxothiazolidine moiety is an important scaffold present in various drugs, with potential for enzyme inhibition. In an effort to discover new heterocyclic compounds, we synthesized 26 new 4,5-diphenyl-1H-imidazole, phenylthiazole, and oxothiazolidine heterocyclic analogues that demonstrated potent α-glucosidase inhibition and anticancer activities. Majority of the compounds noncompetitively inhibited α-glucosidase except for two that exhibited competitive inhibition of the enzyme. Docking results suggested that the noncompetitive inhibitors bind to an apparent allosteric site on the enzyme located in the vicinity of the active site. Additionally, the analogues also exhibited significant activity against various types of cancers including non-small lung cancer. Since tubulin protein plays an important role in the pathogenesis of non-small lung cancer, molecular docking with one of the target compounds provided important clues to its binding mode. The current work on imidazoles and phenylthiazole derivatives bears importance for designing of new antidiabetic and anticancer drugs.

Early pigment spot segmentation and classification from iris cellular image analysis with explainable deep learning and multiclass support vector machine.

Globally, retinal disorders impact thousands of individuals. Early diagnosis and treatment of these anomalies might halt their development and prevent many people from developing preventable blindness. Iris spot segmentation is critical due to acquiring iris cellular images that suffer from the off-angle iris, noise, and specular reflection. Most currently used iris segmentation techniques are based on edge data and noncellular images. The size of the pigment patches on the surface of the iris increases with eye syndrome. In addition, iris images taken in uncooperative settings frequently have negative noise, making it difficult to segment them precisely. The traditional diagnosis processes are costly and time consuming since they require highly qualified personnel and have strict environments. This paper presents an explainable deep learning model integrated with a multiclass support vector machine to analyze iris cellular images for early pigment spot segmentation and classification. Three benchmark datasets MILE, UPOL, and Eyes SUB were used in the experiments to test the proposed methodology. The experimental results are compared on standard metrics, demonstrating that the proposed model outperformed the methods reported in the literature regarding classification errors. Additionally, it is observed that the proposed parameters are highly effective in locating the micro pigment spots on the iris surfaces.

Changes in the level of cytokines in the saliva of hypertensive patients with chronic periodontitis after scaling and root planning.

INTRODUCTION: Cytokines have a key role in the pathogenesis of both hypertension and periodontitis. Salivary diagnosis is a promising field with numerous clinical applications. Since limited studies have been carried out on how salivary inflammatory cytokines can be determined and how well periodontal disease and hypertension might react to scaling and root planning (SRP). The goal of this study was to identify the pattern of changes in salivary inflammatory cytokines in chronic periodontitis subjects with hypertension after nonsurgical periodontal therapy. METHODS: It included observational trial recruited 94 chronic periodontitis patients, 44 of whom had hypertension. All subjects have undergone non- surgical periodontal treatment. The clinical periodontal parameters included gingival index (GI), plaque index (PI), and probing of pocket depth (PPD). Unstimulated saliva was collected to determine the inflammatory biomarkers (using a commercial Elisa kit) both before and after SRP RESULTS: In comparison to non-hypertensive participants, the periodontal PPD was significantly higher in hypertensive subjects. All clinical parameters in the first examination, except for PI, were significantly higher in hypertensive than in non-hypertensive subjects. Plaque Index, GI, and PPD parameters at first visit and after finishing treatment positively correlated with salivary IL-1ß, excluding pretreatment GI. The current results demonstrate the presence of a positive correlation between diastolic blood pressure and TNF (r = 0.330 and P = 0.029). All patients enrolled in this study showed a significant increase in the salivary levels of IL-4 after SRP. CONCLUSIONS: The current study offer important and valuable information concerning the practical application of pro-inflammatory and anti-inflammatory cytokines as useful biomarkers and indicators for determining the outcome of SRP and progression of chronic periodontitis in patients with hypertension.

Investigating the association between asthma and opioid use disorder with interactions of anxiety and depression among a national sample of the US population.

INTRODUCTION: Previous studies have not examined the association between asthma and opioid use disorder (OUD) in a comprehensive national sample of the U.S. population. This study aims to investigate such an association. METHODS: This is a matched retrospective cohort study, with a follow-up period of two years, utilizing longitudinal electronic medical records of a comprehensive national healthcare database in the U.S.-Cerner-Real World DataTM. Patients selected for analysis were ≥12 years old with a hospital encounter between January 2000 and June 2020. Adjusted risk ratios (aRRs) of incident OUD for those with asthma compared to those without asthma were calculated using a modified Poisson regressions with robust standard errors via the Huber-White sandwich estimator, and results were stratified by comorbid mental illnesses. RESULTS: Individuals with asthma had a greater risk of OUD compared to those without asthma (aRR = 2.12; 95% CI 2.03-2.23). When stratified by anxiety and depression status, individuals with asthma and no anxiety or depression had a greater risk of incident OUD compared to individuals with asthma and either anxiety, depression, or both. Additionally, individuals with asthma medication had 1.29 (95% CI: 1.24, 1.35) greater overall risk for incident OUD compared to those without medication. Independent of comorbid mental illnesses, individuals with asthma medication had greater risk for incident OUD compared to those without medication among individuals without severe/obstructive asthma. CONCLUSIONS: Individuals with asthma face a higher OUD risk compared to those without asthma. Comorbid mental illnesses modulate this risk. Caution is advised in opioid prescribing for asthma patients.

Regulation of iron metabolism is critical for the survival of Salmonella Typhimurium in pasteurized milk.

Salmonella is known to survive in raw/pasteurized milk and cause foodborne outbreaks. Lactoferrin, present in milk from all animal sources, is an iron-binding glycoprotein that limits the availability of iron to pathogenic bacteria. Despite the presence of lactoferrins, Salmonella can grow in milk obtained from different animal sources. However, the mechanism by which Salmonella overcomes iron scarcity induced by lactoferrin in milk is not evaluated yet. Salmonella employs the DNA binding transcriptional regulator Fur (ferric update regulator) to mediate iron uptake during survival in iron deplete conditions. To understand the importance of Fur in Salmonella milk growth, we profiled the growth of Salmonella Typhimurium Δfur (ST4/74Δfur) in both bovine and camel milk. ST4/74Δfur was highly inhibited in milk compared to wild-type ST4/74, confirming the importance of Fur mediated regulation of iron metabolism in Salmonella milk growth. We further studied the biology of ST4/74Δfur to understand the importance of iron metabolism in Salmonella milk survival. Using increasing concentrations of FeCl3, and the antibiotic streptonigrin we show that iron accumulates in the cytoplasm of ST4/74Δfur. We hypothesized that the accumulated iron could activate oxidative stress via Fenton's reaction leading to growth inhibition. However, the inhibition of ST4/74Δfur in milk was not due to Fenton's reaction, but due to the 'iron scarce' conditions of milk and microaerophilic incubation conditions which made the presence of the fur gene indispensable for Salmonella milk growth. Subsequently, survival studies of 14 other transcriptional mutants of ST4/74 in milk confirmed that RpoE-mediated response to extracytoplasmic stress is also important for the survival of Salmonella in milk. Though we have data only for fur and rpoE, many other Salmonella transcriptional factors could play important roles in the growth of Salmonella in milk, a theme for future research on Salmonella milk biology. Nevertheless, our data provide early insights into the biology of milk-associated Salmonella.

Outcomes of Arthroscopic Joint Preservation Techniques for Chondral Lesions in the Hip: An Updated Systematic Review.

PURPOSE: To systematically review outcomes of joint preservation procedures for chondral lesions of the hip through analysis of survival rates and patient-reported outcomes (PROs). METHODS: A literature search from 2018 to May 2023 was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in 3 databases: PubMed, Embase, and Google Scholar. Studies were included if they reported on outcomes of patients undergoing hip arthroscopy for the treatment of chondral lesions of the hip joint and if there were quantifiable postoperative outcome measures. Quality assessment was completed using the Methodological Index for Non-Randomized Studies criteria. RESULTS: Twenty-seven studies were included, with 20 noncomparative and 7 comparative studies. Microfracture (MFx) was the most common procedure, reported in 17 studies. Other procedures include autologous chondrocyte transplantation (ACT) (5 studies), autologous matrix-induced chondrogenesis (AMIC) (3 studies), and MFx in conjunction with CarGel (3 studies). Seven other novel procedures were reported in individual separate studies. Survival rates, defined by no revision surgery or conversion to total hip arthroscopy (THA) at latest follow-up, for MFx (14 studies), AMIC (3 studies), and MFx in conjunction with CarGel (3 studies) ranged from 59.1% to 100%, 92.9% to 100%, and 94.4% to 95.7%, respectively. Survival rates of ACT, biological reconstruction, debridement and abrasion, microfragmented autologous adipose tissue transplantation, and ChondroFiller gel were all reported once in separate studies with rates of 100%, 100%, 85.4%, 100%, and 92.3%, respectively. All studies included PROs, most reporting statistically significant improvements (P < .05) at the latest follow-up. CONCLUSIONS: Isolated MFx remained the most commonly performed technique, but with lower survival and higher conversion to THA rates than in studies before 2018. Novel techniques that were performed in conjunction with MFx or that avoided MFx altogether had higher overall survival rates despite being minimally performed. Most patients across all techniques demonstrated significant improvements in PROs. LEVEL OF EVIDENCE: Level IV, systematic review of Level III and IV studies.

Enhanced In Vivo Wound Healing Efficacy of a Novel Piperine-Containing Bioactive Hydrogel in Excision Wound Rat Model.

These days an extensive amount of the attention of researchers is focused towards exploring bioactive compounds of natural or herbal origin for therapeutic intervention in different ailments of significant importance. One such novel bioactive compound that has a variety of biological properties, including anti-inflammatory and antioxidant activities, is piperine. However, until today, piperine has not been explored for its potential to improve inflammation and enhance healing in acute and chronic wounds. Therefore, the present study aimed to investigate the wound healing potential of piperine hydrogel formulation after topical application. Hydrogels fit the need for a depot system at the wound bed, where they ensure a consistent supply of therapeutic agents enclosed in their cross-linked network matrices. In the present study, piperine-containing carbopol 934 hydrogels mixed with Aloe vera gels of different gel strengths were prepared and characterized for rheological behavior, spreadability, extrudability, and percent (%) content uniformity. Furthermore, the wound healing potential of the developed formulation system was explored utilizing the excision wound healing model. The results of an in vivo study and histopathological examination revealed early and intrinsic healing of wounds with the piperine-containing bioactive hydrogel system compared to the bioactive hydrogel system without piperine. Therefore, the study's findings establish that the piperine-containing bioactive hydrogel system is a promising therapeutic approach for wound healing application that should be diligently considered for clinical transferability.

The flavonoid luteolin reduces mutant huntingtin aggregation and cytotoxicity in huntingtin-mutated neuroblastoma cells.

Background: Huntington's disease is an inherited progressive neurodegenerative disorder caused by an expansion of the polyglutamine tract leading to malformation and aggregation of the mutant huntingtin protein in the cell cytoplasm and nucleus of affected brain regions. The development of neuroprotective agents from plants has received considerable research attention. Objective: Our study aims to investigate the neuroprotective effects of luteolin and the mechanisms that underline its potential mediated protection in the mutant htt neuroblastoma cells. Methods: The mutant htt neuroblastoma cells were transfected with 160Q, and the control wild-type neuroblastoma cells were transfected with 20Q htt for 24 h and later treated with luteolin. Cell viability was determined by MTT and PI staining in both groups, while western blotting was used to evaluate caspase 3 protein expression. Aggregation formation was assessed via immunofluorescence microscopy. Also, western blotting was utilized to measure the protein expression of mutant htt aggregated and soluble protein, Nrf2 and HO-1. The impact of Nrf2 on luteolin-treated neuroblastoma cells was assessed using small interfering RNAs. Results: Our study reports that luteolin can protect cultured cells from mutant huntingtin cytotoxicity, evidenced by increased viability and decreased apoptosis. Also, luteolin reduced the accumulation of soluble and insoluble mutant huntingtin aggregates in mutant htt neuroblastoma cells transfected with 160Q compared to the control wild-type. The mutant htt aggregate reduction mediated by luteolin appeared to be independent of the Nrf2 -HO-1 antioxidant pathway. Conclusion: Luteolin presents a new potential therapeutic and protective agent for the treatment and decreasing the cytotoxicity in neurodegenerative diseases such as Huntington's disease.

Glycogen storage disease type 1a is associated with disturbed vitamin A metabolism and elevated serum retinol levels.

Glycogen storage disease type 1a (GSD Ia) is an inborn error of metabolism caused by mutations in the G6PC gene, encoding the catalytic subunit of glucose-6-phosphatase. Early symptoms include severe fasting intolerance, failure to thrive and hepatomegaly, biochemically associated with nonketotic hypoglycemia, fasting hyperlactidemia, hyperuricemia and hyperlipidemia. Dietary management is the cornerstone of treatment aiming at maintaining euglycemia, prevention of secondary metabolic perturbations and long-term complications, including liver (hepatocellular adenomas and carcinomas), kidney and bone disease (hypovitaminosis D and osteoporosis). As impaired vitamin A homeostasis also associates with similar symptoms and is coordinated by the liver, we here analysed whether vitamin A metabolism is affected in GSD Ia patients and liver-specific G6pc-/- knock-out mice. Serum levels of retinol and retinol binding protein 4 (RBP4) were significantly increased in both GSD Ia patients and L-G6pc-/- mice. In contrast, hepatic retinol levels were significantly reduced in L-G6pc-/- mice, while hepatic retinyl palmitate (vitamin A storage form) and RBP4 levels were not altered. Transcript and protein analyses indicate an enhanced production of retinol and reduced conversion the retinoic acids (unchanged LRAT, Pnpla2/ATGL and Pnpla3 up, Cyp26a1 down) in L-G6pc-/- mice. Aberrant expression of genes involved in vitamin A metabolism was associated with reduced basal messenger RNA levels of markers of inflammation (Cd68, Tnfα, Nos2, Il-6) and fibrosis (Col1a1, Acta2, Tgfß, Timp1) in livers of L-G6pc-/- mice. In conclusion, GSD Ia is associated with elevated serum retinol and RBP4 levels, which may contribute to disease symptoms, including osteoporosis and hepatic steatosis.

Device-to-Device (D2D) Multi-Criteria Learning Algorithm Using Secured Sensors.

Wireless networks and the Internet of things (IoT) have proven rapid growth in the development and management of smart environments. These technologies are applied in numerous research fields, such as security surveillance, Internet of vehicles, medical systems, etc. The sensor technologies and IoT devices are cooperative and allow the collection of unpredictable factors from the observing field. However, the constraint resources of distributed battery-powered sensors decrease the energy efficiency of the IoT network and increase the delay in receiving the network data on users' devices. It is observed that many solutions are proposed to overcome the energy deficiency in smart applications; though, due to the mobility of the nodes, lots of communication incurs frequent data discontinuity, compromising the data trust. Therefore, this work introduces a D2D multi-criteria learning algorithm for IoT networks using secured sensors, which aims to improve the data exchange without imposing additional costs and data diverting for mobile sensors. Moreover, it reduces the compromising threats in the presence of anonymous devices and increases the trustworthiness of the IoT-enabled communication system with the support of machine learning. The proposed work was tested and analyzed using broad simulation-based experiments and demonstrated the significantly improved performance of the packet delivery ratio by 17%, packet disturbances by 31%, data delay by 22%, energy consumption by 24%, and computational complexity by 37% for realistic network configurations.

Secure Edge-Based Energy Management Protocol in Smart Grid Environments with Correlation Analysis.

For the monitoring and processing of network data, wireless systems are widely used in many industrial applications. With the assistance of wireless sensor networks (WSNs) and the Internet of Things (IoT), smart grids are being explored in many distributed communication systems. They collect data from the surrounding environment and transmit it with the support of a multi-hop system. However, there is still a significant research gap in energy management for IoT devices and smart sensors. Many solutions have been proposed by researchers to cope with efficient routing schemes in smart grid applications. But, reducing energy holes and offering intelligent decisions for forwarding data are remain major problems. Moreover, the management of network traffic on grid nodes while balancing the communication overhead on the routing paths is an also demanding challenge. In this research work, we propose a secure edge-based energy management protocol for a smart grid environment with the support of multi-route management. It strengthens the ability to predict the data forwarding process and improves the management of IoT devices by utilizing a technique of correlation analysis. Moreover, the proposed protocol increases the system's reliability and achieves security goals by employing lightweight authentication with sink coordination. To demonstrate the superiority of our proposed protocol over the chosen existing work, extensive experiments were performed on various network parameters.

Sustainable Data-Driven Secured Optimization Using Dynamic Programming for Green Internet of Things.

The development of smart applications has benefited greatly from the expansion of wireless technologies. A range of tasks are performed, and end devices are made capable of communicating with one another with the support of artificial intelligence technology. The Internet of Things (IoT) increases the efficiency of communication networks due to its low costs and simple management. However, it has been demonstrated that many systems still need an intelligent strategy for green computing. Establishing reliable connectivity in Green-IoT (G-IoT) networks is another key research challenge. With the integration of edge computing, this study provides a Sustainable Data-driven Secured optimization model (SDS-GIoT) that uses dynamic programming to provide enhanced learning capabilities. First, the proposed approach examines multi-variable functions and delivers graph-based link predictions to locate the optimal nodes for edge networks. Moreover, it identifies a sub-path in multistage to continue data transfer if a route is unavailable due to certain communication circumstances. Second, while applying security, edge computing provides offloading services that lower the amount of processing power needed for low-constraint nodes. Finally, the SDS-GIoT model is verified with various experiments, and the performance results demonstrate its significance for a sustainable environment against existing solutions.

Machine Learning and Internet of Things Enabled Monitoring of Post-Surgery Patients: A Pilot Study.

Artificial Intelligence (AI) and Internet of Things (IoT) offer immense potential to transform conventional healthcare systems. The IoT and AI enabled smart systems can play a key role in driving the future of smart healthcare. Remote monitoring of critical and non-critical patients is one such field which can leverage the benefits of IoT and machine learning techniques. While some work has been done in developing paradigms to establish effective and reliable communications, there is still great potential to utilize optimized IoT network and machine learning technique to improve the overall performance of the communication systems, thus enabling fool-proof systems. This study develops a novel IoT framework to offer ultra-reliable low latency communications to monitor post-surgery patients. The work considers both critical and non-critical patients and is balanced between these to offer optimal performance for the desired outcomes. In addition, machine learning based regression analysis of patients' sensory data is performed to obtain highly accurate predictions of the patients' sensory data (patients' vitals), which enables highly accurate virtual observers to predict the data in case of communication failures. The performance analysis of the proposed IoT based vital signs monitoring system for the post-surgery patients offers reduced delay and packet loss in comparison to IEEE low latency deterministic networks. The gradient boosting regression analysis also gives a highly accurate prediction for slow as well as rapidly varying sensors for vital sign monitoring.