Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan.

Metabolism is deeply intertwined with aging. Effects of metabolic interventions on aging have been explained with intracellular metabolism, growth control, and signaling. Studying chronological aging in yeast, we reveal a so far overlooked metabolic property that influences aging via the exchange of metabolites. We observed that metabolites exported by young cells are re-imported by chronologically aging cells, resulting in cross-generational metabolic interactions. Then, we used self-establishing metabolically cooperating communities (SeMeCo) as a tool to increase metabolite exchange and observed significant lifespan extensions. The longevity of the SeMeCo was attributable to metabolic reconfigurations in methionine consumer cells. These obtained a more glycolytic metabolism and increased the export of protective metabolites that in turn extended the lifespan of cells that supplied them with methionine. Our results establish metabolite exchange interactions as a determinant of cellular aging and show that metabolically cooperating cells can shape the metabolic environment to extend their lifespan.

Functional Metabolomics Describes the Yeast Biosynthetic Regulome.

Genome-metabolism interactions enable cell growth. To probe the extent of these interactions and delineate their functional contributions, we quantified the Saccharomyces amino acid metabolome and its response to systematic gene deletion. Over one-third of coding genes, in particular those important for chromatin dynamics, translation, and transport, contribute to biosynthetic metabolism. Specific amino acid signatures characterize genes of similar function. This enabled us to exploit functional metabolomics to connect metabolic regulators to their effectors, as exemplified by TORC1, whose inhibition in exponentially growing cells is shown to match an interruption in endomembrane transport. Providing orthogonal information compared to physical and genetic interaction networks, metabolomic signatures cluster more than half of the so far uncharacterized yeast genes and provide functional annotation for them. A major part of coding genes is therefore participating in gene-metabolism interactions that expose the metabolism regulatory network and enable access to an underexplored space in gene function.

Maintaining Iron Homeostasis Is the Key Role of Lysosomal Acidity for Cell Proliferation.

The lysosome is an acidic multi-functional organelle with roles in macromolecular digestion, nutrient sensing, and signaling. However, why cells require acidic lysosomes to proliferate and which nutrients become limiting under lysosomal dysfunction are unclear. To address this, we performed CRISPR-Cas9-based genetic screens and identified cholesterol biosynthesis and iron uptake as essential metabolic pathways when lysosomal pH is altered. While cholesterol synthesis is only necessary, iron is both necessary and sufficient for cell proliferation under lysosomal dysfunction. Remarkably, iron supplementation restores cell proliferation under both pharmacologic and genetic-mediated lysosomal dysfunction. The rescue was independent of metabolic or signaling changes classically associated with increased lysosomal pH, uncoupling lysosomal function from cell proliferation. Finally, our experiments revealed that lysosomal dysfunction dramatically alters mitochondrial metabolism and hypoxia inducible factor (HIF) signaling due to iron depletion. Altogether, these findings identify iron homeostasis as the key function of lysosomal acidity for cell proliferation.

Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.

Environmental perturbations are encountered by microorganisms regularly and will require metabolic adaptations to ensure an organism can survive in the newly presenting conditions. In order to study the mechanisms of metabolic adaptation in such conditions, various experimental and computational approaches have been used. Genome-scale metabolic models (GEMs) are one of the most powerful approaches to study metabolism, providing a platform to study the systems level adaptations of an organism to different environments which could otherwise be infeasible experimentally. In this review, we are describing the application of GEMs in understanding how microbes reprogram their metabolic system as a result of environmental variation. In particular, we provide the details of metabolic model reconstruction approaches, various algorithms and tools for model simulation, consequences of genetic perturbations, integration of '-omics' datasets for creating context-specific models and their application in studying metabolic adaptation due to the change in environmental conditions.

Recent application of artificial intelligence on histopathologic image-based prediction of gene mutation in solid cancers.

PURPOSE: Evaluation of genetic mutations in cancers is important because distinct mutational profiles help determine individualized drug therapy. However, molecular analyses are not routinely performed in all cancers because they are expensive, time-consuming and not universally available. Artificial intelligence (AI) has shown the potential to determine a wide range of genetic mutations on histologic image analysis. Here, we assessed the status of mutation prediction AI models on histologic images by a systematic review. METHODS: A literature search using the MEDLINE, Embase and Cochrane databases was conducted in August 2021. The articles were shortlisted by titles and abstracts. After a full-text review, publication trends, study characteristic analysis and comparison of performance metrics were performed. RESULTS: Twenty-four studies were found mostly from developed countries, and their number is increasing. The major targets were gastrointestinal, genitourinary, gynecological, lung and head and neck cancers. Most studies used the Cancer Genome Atlas, with a few using an in-house dataset. The area under the curve of some of the cancer driver gene mutations in particular organs was satisfactory, such as 0.92 of BRAF in thyroid cancers and 0.79 of EGFR in lung cancers, whereas the average of all gene mutations was 0.64, which is still suboptimal. CONCLUSION: AI has the potential to predict gene mutations on histologic images with appropriate caution. Further validation with larger datasets is still required before AI models can be used in clinical practice to predict gene mutations.

Lysine harvesting is an antioxidant strategy and triggers underground polyamine metabolism.

Both single and multicellular organisms depend on anti-stress mechanisms that enable them to deal with sudden changes in the environment, including exposure to heat and oxidants. Central to the stress response are dynamic changes in metabolism, such as the transition from the glycolysis to the pentose phosphate pathway-a conserved first-line response to oxidative insults1,2. Here we report a second metabolic adaptation that protects microbial cells in stress situations. The role of the yeast polyamine transporter Tpo1p3-5 in maintaining oxidant resistance is unknown6. However, a proteomic time-course experiment suggests a link to lysine metabolism. We reveal a connection between polyamine and lysine metabolism during stress situations, in the form of a promiscuous enzymatic reaction in which the first enzyme of the polyamine pathway, Spe1p, decarboxylates lysine and forms an alternative polyamine, cadaverine. The reaction proceeds in the presence of extracellular lysine, which is taken up by cells to reach concentrations up to one hundred times higher than those required for growth. Such extensive harvest is not observed for the other amino acids, is dependent on the polyamine pathway and triggers a reprogramming of redox metabolism. As a result, NADPH-which would otherwise be required for lysine biosynthesis-is channelled into glutathione metabolism, leading to a large increase in glutathione concentrations, lower levels of reactive oxygen species and increased oxidant tolerance. Our results show that nutrient uptake occurs not only to enable cell growth, but when the nutrient availability is favourable it also enables cells to reconfigure their metabolism to preventatively mount stress protection.

Results of a nationally representative seroprevalence survey of chikungunya virus in Bangladesh.

There is an increasing global burden from chikungunya virus (CHIKV). Bangladesh reported a major epidemic in 2017, however, it was unclear if there had been prior widespread transmission. We conducted a nationally representative seroprevalence survey in 70 randomly selected communities immediately prior to the epidemic. We found 69/2,938 (2.4%) of sampled individuals were seropositive to CHIKV. Being seropositive to dengue virus (aOR 3.13 [95% CIs: 1.86-5.27]), male sex (aOR 0.59 [95% CIs: 0.36-0.99]), and community presence of Aedes aegypti mosquitoes (aOR: 1.80, 95% CI: 1.05-3.07) were significantly associated with CHIKV seropositivity. Using a spatial prediction model, we estimated that across the country, 4.99 (95% CI: 4.89 - 5.08) million people had been previously infected. These findings highlight high population susceptibility prior to the major outbreak and that previous outbreaks must have been spatially isolated.

Primaquine radical cure in patients with Plasmodium falciparum malaria in areas co-endemic for P falciparum and Plasmodium vivax (PRIMA): a multicentre, open-label, superiority randomised controlled trial.

BACKGROUND: In areas co-endemic for Plasmodium vivax and Plasmodium falciparum there is an increased risk of P vivax parasitaemia following P falciparum malaria. Radical cure is currently only recommended for patients presenting with P vivax malaria. Expanding the indication for radical cure to patients presenting with P falciparum malaria could reduce their risk of subsequent P vivax parasitaemia. METHODS: We did a multicentre, open-label, superiority randomised controlled trial in five health clinics in Bangladesh, Indonesia, and Ethiopia. In Bangladesh and Indonesia, patients were excluded if they were younger than 1 year, whereas in Ethiopia patients were excluded if they were younger than 18 years. Patients with uncomplicated P falciparum monoinfection who had fever or a history of fever in the 48 h preceding clinic visit were eligible for enrolment and were required to have a glucose-6-dehydrogenase (G6PD) activity of 70% or greater. Patients received blood schizontocidal treatment (artemether-lumefantrine in Ethiopia and Bangladesh and dihydroartemisinin-piperaquine in Indonesia) and were randomly assigned (1:1) to receive either high-dose short-course oral primaquine (intervention arm; total dose 7 mg/kg over 7 days) or standard care (standard care arm; single dose oral primaquine of 0·25 mg/kg). Random assignment was done by an independent statistician in blocks of eight by use of sealed envelopes. All randomly assigned and eligible patients were included in the primary and safety analyses. The per-protocol analysis excluded those who did not complete treatment or had substantial protocol violations. The primary endpoint was the incidence risk of P vivax parasitaemia on day 63. This trial is registered at ClinicalTrials.gov, NCT03916003. FINDINGS: Between Aug 18, 2019, and March 14, 2022, a total of 500 patients were enrolled and randomly assigned, and 495 eligible patients were included in the intention-to-treat analysis (246 intervention and 249 control). The incidence risk of P vivax parasitaemia at day 63 was 11·0% (95% CI 7·5-15·9) in the standard care arm compared with 2·5% (1·0-5·9) in the intervention arm (hazard ratio 0·20, 95% CI 0·08-0·51; p=0·0009). The effect size differed with blood schizontocidal treatment and site. Routine symptom reporting on day 2 and day 7 were similar between groups. In the first 42 days, there were a total of four primaquine-related adverse events reported in the standard care arm and 26 in the intervention arm; 132 (92%) of all 143 adverse events were mild. There were two serious adverse events in the intervention arm, which were considered unrelated to the study drug. None of the patients developed severe anaemia (defined as haemoglobin <5 g/dL). INTERPRETATION: In patients with a G6PD activity of 70% or greater, high-dose short-course primaquine was safe and relatively well tolerated and reduced the risk of subsequent P vivax parasitaemia within 63 days by five fold. Universal radical cure therefore potentially offers substantial clinical, public health, and operational benefits, but these benefits will vary with endemic setting. FUNDING: Australian Academy of Science Regional Collaborations Program, Bill & Melinda Gates Foundation, and National Health and Medical Research Council.

The role of Aquaporins in tumorigenesis: implications for therapeutic development.

Aquaporins (AQPs) are ubiquitous channel proteins that play a critical role in the homeostasis of the cellular environment by allowing the transit of water, chemicals, and ions. They can be found in many different types of cells and organs, including the lungs, eyes, brain, glands, and blood vessels. By controlling the osmotic water flux in processes like cell growth, energy metabolism, migration, adhesion, and proliferation, AQPs are capable of exerting their regulatory influence over a wide range of cellular processes. Tumour cells of varying sources express AQPs significantly, especially in malignant tumours with a high propensity for metastasis. New insights into the roles of AQPs in cell migration and proliferation reinforce the notion that AQPs are crucial players in tumour biology. AQPs have recently been shown to be a powerful tool in the fight against pathogenic antibodies and metastatic cell migration, despite the fact that the molecular processes of aquaporins in pathology are not entirely established. In this review, we shall discuss the several ways in which AQPs are expressed in the body, the unique roles they play in tumorigenesis, and the novel therapeutic approaches that could be adopted to treat carcinoma.

Alocasia macrorrhiza rhizome lectin inhibits growth of pathogenic bacteria and human lung cancer cell in vitro and Ehrlich ascites carcinoma cell in vivo in mice.

Cancer and antibiotic resistance represent significant global challenges, affecting public health and healthcare systems worldwide. Lectin, a carbohydrate-binding protein, displays various biological properties, including antimicrobial and anticancer activities. This study focused on anticancer and antibacterial properties of Alocasia macrorrhiza lectin (AML). AML, with a molecular weight of 11.0 ± 1.0 kDa was purified using Ion-exchange chromatography, and the homotetrameric form was detected by gel-filtration chromatography. It agglutinates mouse erythrocytes, that was inhibited by 4-Nitrophenyl-α-d-mannopyranoside. Maximum hemagglutination activity was observed below 60 °C and within a pH range from 8 to 11. Additionally, it exhibited moderate toxicity against brine shrimp nauplii with LD50 values of 321 µg/ml and showed antibacterial activity against Escherichia coli and Shigella dysenteriae. In vitro experiments demonstrated that AML suppressed the proliferation of mice Ehrlich ascites carcinoma (EAC) cells by 35 % and human lung cancer (A549) cells by 40 % at 512 µg/ml concentration. In vivo experiments involved intraperitoneal injection of AML in EAC-bearing mice for five consecutive days at doses of 2.5 and 5.0 mg/kg/day, and the results indicated that AML inhibited EAC cell growth by 37 % and 54 %, respectively. Finally, it can be concluded that AML can be used for further anticancer and antibacterial studies.

Domino Reaction Protocol to Synthesize Benzothiophene-Derived Chemical Entities as Potential Therapeutic Agents.

An efficient synthesis of 3-amino-2-formyl-functionalized benzothiophenes by a domino reaction protocol and their use to synthesize a library of novel scaffolds have been reported. Reactions of ketones and 1,3-diones with these amino aldehyde derivatives formed a series of benzothieno[3,2-b]pyridine and 3,4-dihydro-2H-benzothiopheno[3,2-b]quinolin-1-one, respectively. A plausible mechanism for the formation of fused pyridine derivatives by the Friedlander reaction has been elucidated by density functional theory (DFT) calculations. Furthermore, hydrazones were obtained by reacting the aldehyde functional group of benzothiophenes with different hydrazine derivatives. Preliminary screening of these compounds against several bacterial strains and cancer cell lines led to the discovery of several hit molecules. Hydrazone and benzothieno[3,2-b]pyridine derivatives are potent cytotoxic and antibacterial agents, respectively. One of the potent compounds effected ∼97% growth inhibition of the LOX IMVI cell line at 10 µM concentration.

Studying the Symphonizing Effect of NLO Properties in Hydrated and Non-hydrated Donor Acceptor Complexes Formed Via Charge Transfer.

The present work intended to report the synthesis of newly designed donor-acceptor complexes of the pyrimidine-based system namely TAPHIA 1 and TAPHIA 2, which are symphonized to give the NLO properties. The methodologies adopted for both complexes were different and hence influenced their geometrical properties. The synthesized complexes were characterized using different techniques including SCXRD, FTIR, UV, PXRD, and TGA to confirm their formation. The SCXRD analysis revealed that TAPHIA 1 was crystallized in the Pca21 space group in an orthorhombic system while TAPHIA 2 was crystallized in the P21/c space group in a monoclinic system. The third-order NLO properties of both complexes were explored using the Z-Scan technique by employing a continuous wave (CW) diode laser of 520 nm. The third-order NLO parameters including nonlinear refractive index (n2), nonlinear absorption coefficient (ß) and nonlinear optical susceptibility (χ (3)) were calculated at different powers; 40, 50 and 60 mW at fixed solution concentration (10 mM) for both the complexes. Moreover, the experimental properties including NLO, FTIR, and UV were well corroborated with theoretical results obtained at the B3LYP-D3/6-31++G(d,p) level of theory. The analysis of the theoretical and experimental properties of both complexes suggests that TAPHIA 2 is a better applicant to be employed in optical devices than TAPHIA 1 due to the enhanced ability of internal charge transfer.

Anti- COVID-19 drug discovery by flavonoid derivatives: an extensive computational drug design approach.

The present study deals with the in-silico analyses of several flavonoid derivatives to explore COVID-19 through pharmacophore modelling, molecular docking, molecular dynamics, drug-likeness, and ADME properties. The initial literature study revealed that many flavonoids, including luteolin, quercetin, kaempferol, and baicalin may be useful against SARS ß-coronaviruses, prompting the selection of their potential derivatives to investigate their abilities as inhibitors of COVID-19. The findings were streamlined using in silico molecular docking, which revealed promising energy-binding interactions between all flavonoid derivatives and the targeted protein. Notably, compounds 8, 9, 13, and 15 demonstrated higher potency against the coronavirus Mpro protein (PDB ID 6M2N). Compound 8 has a -7.2 Kcal/mol affinity for the protein and binds to it by hydrogen bonding with Gln192 and π-sulfur bonding with Met-165. Compound 9 exhibited a significant interaction with the main protease, demonstrating an affinity of -7.9 kcal/mol. Gln-192, Glu-189, Pro-168, and His-41 were the principle amino acid residues involved in this interaction. The docking score for compound 13 is -7.5 Kcal/mol, and it binds to the protease enzyme by making interactions with Leu-41, π-sigma, and Gln-189. These interactions include hydrogen bonding and π-sulfur. The major protease and compound 15 were found to bind with a favourable affinity of -6.8 Kcal/mol. This finding was further validated through molecular dynamic simulation for 1ns, analysing parameters such as RMSD, RMSF, and RoG profiles. The RoG values for all four of the compounds varied significantly (35.2-36.4). The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADME and drug-likeness properties, fulfilling all the necessary criteria. The findings of the study may support further efforts for the discovery and development of safe drugs to treat COVID-19.

Exploring the mechanism of action of spirooxindoles as a class of CDK2 inhibitors: a structure-based computational approach.

Cyclin-dependent kinase 2 (CDK2) regulates cell cycle checkpoints in the synthesis and mitosis phases and plays a pivotal role in cancerous cell proliferation. The activation of CDK2, influenced by various protein signaling pathways, initiates the phosphorylation process. Due to its crucial role in carcinogenesis, CDK2 is a druggable hotspot target to suppress cancer cell proliferation. In this context, several studies have identified spirooxindoles as an effective class of CDK2 inhibitors. In the present study, three spirooxindoles (SOI1, SOI2, and SOI3) were studied to understand their inhibitory mechanism against CDK2 through a structure-based approach. Molecular docking and molecular dynamics (MD) simulations were performed to explore their interactions with CDK2 at the molecular level. The calculated binding free energy for the spirooxindole-based CDK2 inhibitors aligned well with experimental results regarding CDK2 inhibition. Energy decomposition (ED) analysis identified key binding residues, including I10, G11, T14, R36, F82, K89, L134, P155, T158, Y159, and T160, in the CDK2 active site and T-loop phosphorylation. Molecular mechanics (MM) energy was identified as the primary contributor to stabilizing inhibitor binding in the CDK2 protein structure. Furthermore, the analysis of binding affinity revealed that the inhibitor SOI1 binds more strongly to CDK2 compared to the other inhibitors under investigation. It demonstrated a robust interaction with the crucial residue T160 in the T-loop phosphorylation site, responsible for kinase activation. These insights into the inhibitory mechanism are anticipated to contribute to the development of potential CDK2 inhibitors using the spirooxindole scaffold.

Environmental impact assessment via life cycle analysis on ultrafiltration membrane fabricated from polyethylene terephthalate waste to treat microalgal cultivation wastewater for reusability.

The current study had conducted the life cycle analysis (LCA) to assess the environmental impact of microalgal wastewater treatment via an integrated membrane bioreactor. The functional unit selected for this analysis was 1 kg of treated microalgal wastewater with contaminants eliminated by ultrafiltration membrane fabricated from recycled polyethylene terephthalate waste. Meanwhile, the applied system boundary in this study was distinguished based on two scenarios, namely, cradle-to-gate encompassed wastewater treatment only and cradle-to-cradle which included the reutilization of treated wastewater to cultivate microalgae again. The environmental impacts and hotspots associated with the different stages of the wastewater treatment process had clearly elucidated that membrane treatment had ensued the highest impact, followed by microalgal harvesting, and finally cultivation. Among the environmental impact categories, water-related impact was found to be prominent in the following series: freshwater ecotoxicity, freshwater eutrophication and marine ecotoxicity. Notably, the key performance indicator of all environmental impact, i.e., the global warming potential was found to be very much lower at 2.94 × 10-4 kg CO2 eq as opposed to other literatures reported on the LCA of wastewater treatments using membranes. Overall, this study had proffered insights into the environmental impact of microalgal wastewater treatment and its stimulus for sustainable wastewater management. The findings of this study can be instrumental in making informed decision for optimizing microalgal wastewater treatment and reutilization assisted by membrane technology with an ultimate goal of enhancing sustainability.

Taming the cytokine storm: small molecule inhibitors targeting IL-6/IL-6α receptor.

Given the increasing effectiveness of immune-based therapies, management of their associated toxicities is of utmost importance. Cytokine release syndrome (CRS), characterized by elevated levels of cytokine, poses a significant challenge following the administration of antibodies and CAR-T cell therapies. CRS also contributes to multiple organ dysfunction in severe viral infections, notably in COVID-19. Given the pivotal role of IL-6 cytokine in initiating CRS, it has been considered a most potential therapeutic target to mitigate hyperactivated immune responses. While monoclonal antibodies of IL-6 show promise in mitigating cytokine storm, concerns about immunotoxicity persist, and small molecule IL-6 antagonists remain unavailable. The present study employed sophisticated computational techniques to identify potential hit compounds as IL-6 inhibitors, with the aim of inhibiting IL-6/IL-6R protein-protein interactions. Through ligand-based pharmacophore mapping and shape similarity in combination with docking-based screening, we identified nine hit compounds with diverse chemical scaffolds as potential binders of IL-6. Further, the MD simulation of 300 ns of five virtual hits in a complex with IL-6 was employed to study the dynamic behavior. To provide a more precise prediction, binding free energy was also estimated. The identified compounds persistently interacted with the residues lining the binding site of the IL-6 protein. These compounds displayed low binding energy during MMPBSA calculations, substantiating their strong association with IL-6. This study suggests promising scaffolds as potential inhibitors of IL-6/IL-6R protein-protein interactions and provides direction for lead optimization.

A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition.

Effectiveness of Bedaquiline Use beyond Six Months in Patients with Multidrug-Resistant Tuberculosis.

Rationale: Current recommendations for the treatment of rifampicin- and multidrug-resistant tuberculosis include bedaquiline (BDQ) used for 6 months or longer. Evidence is needed to inform the optimal duration of BDQ. Objectives: We emulated a target trial to estimate the effect of three BDQ duration treatment strategies (6, 7-11, and ⩾12 mo) on the probability of successful treatment among patients receiving a longer individualized regimen for multidrug-resistant tuberculosis. Methods: To estimate the probability of successful treatment, we implemented a three-step approach comprising cloning, censoring, and inverse probability weighting. Measurements and Main Results: The 1,468 eligible individuals received a median of 4 (interquartile range, 4-5) likely effective drugs. In 87.1% and 77.7% of participants, this included linezolid and clofazimine, respectively. The adjusted probability of successful treatment was 0.85 (95% confidence interval [CI], 0.81-0.88) for 6 months of BDQ, 0.77 (95% CI, 0.73-0.81) for 7-11 months, and 0.86 (95% CI, 0.83-0.88) for ⩾12 months. Compared with 6 months of BDQ, the ratio of treatment success was 0.91 (95% CI, 0.85-0.96) for 7-11 months and 1.01 (95% CI, 0.96-1.06) for ⩾12 months. Naive analyses that did not account for bias revealed a higher probability of successful treatment with ⩾12 months (ratio, 1.09 [95% CI, 1.05-1.14]). Conclusions: BDQ use beyond 6 months did not increase the probability of successful treatment among patients receiving longer regimens that commonly included new and repurposed drugs. When not properly accounted for, immortal person-time bias can influence estimates of the effects of treatment duration. Future analyses should explore the effect of treatment duration of BDQ and other drugs in subgroups with advanced disease and/or receiving less potent regimens.

Unveiling the Influence of the Curve of Spee on Bite Force and Chewing Ability: A Comparative Study.

Aim: To investigate the impact of the curve of Spee (CS) accentuation on bite force, chewing ability, and additionally, other factors that influence chewing ability and bite force such as restorations, caries, gender, habits, and TMJ problems. Materials and Methods: 231 participants (118 male and 113 female, mean age = ±27.96 years) were recruited for this cross-section study. Participants completed a data collection sheet in which age, gender, Angle's classification of malocclusion, overjet, overbite, TMJ problems, habits, restorations, and caries experience were recorded. Two examiners made a lower impression, chewing ability test and measured the bite force for each participant. Measurement of the CS was obtained digitally from the poured dental cast, and the categorization was as follows: flat (<1 mm), normal (1-2 mm), or deep (>2 mm). Results: The mean maximum bite force (MBF) was 468.722 N for participants with flat CS, 389.822 N for normal CS, 647.08 N for deep CS, and 384.667 N for reverse CS. The average MBF was higher for participants with deep CS (p < 0.05). MBF force was higher in males. However, BMI was not significantly related to MBF values. Participants with normal and flat CS have comparable chewing capacity (p > 0.05). Also, a significant difference in bite force and chewing ability was found between the three categories of CS (p < 0.05). Conclusion: Bite force variations across various CS types were linked to gender and habits. Chewing ability showed no differences concerning gender, habits, TMJ problems, caries, or restorations, emphasizing CS's significant impact on bite force while showcasing the unchanged nature of chewing ability amidst diverse factors.

Tranilast treatment prevents chronic radiation-induced colitis in rats by inhibiting mast cells infiltration.

INTRODUCTION: Mast cells are the principal cells leading to acute and chronic colitis due to irradiation, radiation-induced colitis (RIC). Herein, we investigated whether pre-treatment with tranilast, mast cell inhibitor, could alleviate chronic RIC. METHODS: A total of 23 Sprague Dawley (SD) rats were randomly divided into three groups: control group (n=5, C), irradiation group (n=9, RG), and tranilast pre-treated irradiation group (n=9, TG). The rats in RG and TG were irradiated in the pelvic area (1.5cm from anus) with a single dose of 20 Gray under general anesthesia. Tranilast (100 mg/kg) was intraperitonially injected to mice of the TG for 10 days starting from the day of pelvic irradiation. Ten weeks after irradiation, the rats were euthanized. Rectal tissue samples were evaluated histologically for the total inflammation score (TIS) and mast cell count. Expression of MUC2, MUC5AC and matrix metalloproteinase 9 (MMP9) were also assessed immunohistochemically. RESULTS: Both TIS and some components of TIS, epithelial atypia, vascular sclerosis and colitis cystica profunda (CCP) were significantly higher in RG than in TG (P=0.02, 0.038, 0.025, 0.01, respectively). The number of infiltrating mast cells was significantly higher in the RG than in TG (20, 3-54 and 6, 3-25, respectively, P=0.034). Quantitatively, the number of MMP9-positive cells was significantly higher in the RG (23.67±19.00) than in the TG (10.25±8.45) (P<0.05). TIS and MMP9 exhibited strong associations (correlation coefficient r=0.56, P<0.05) Immunohistochemically, mucin-lake of CCP showed no staining for MUC5AX but positivity for MUC2. CONCLUSION: Tranilast pretreatment in RIC shows an anti-inflammatory effect on the RIC in association with the reduction of mast cell infiltration and MMP9 expression.