Anti-Staphylococcus aureus potential of compounds from Ganoderma sp.: A comprehensive molecular docking and simulation approaches.

In this study, a series of secondary metabolites from Ganoderma sp. were screened against Staphylococcus aureus protein targets, including as phosphotransacetylase, clumping factor A, and dihydrofolate reductase, using molecular docking simulations. The chemicals that showed the strongest binding energy with the targeted proteins were ganodermanontriol, lucidumol B, ganoderic acid J, ergosterol, ergosterol peroxide, 7-oxoganoderic acid Z, ganoderic acid AM1, ganosinoside A, ganoderic acid D, and 24R-ergosta-7,2E-diene-3ß,5α,6ß-triol. Interestingly, ganosinoside A showed the greatest affinity for the protein clumping factor A, a result validated by molecular dynamic simulation. Additionally, three natural Ganoderma sp. Strains as Ganoderma lingzhi VNKKK1903, Ganoderma lingzhi VNKK1905A2, and Amauroderma subresinosum VNKKK1904 were collected from Kon Ka Kinh National Park in central land of Vietnam and evaluated for their antibacterial activity against Staphylococcus aureus using an agar well diffusion technique. These results suggest that the fungal extracts and secondary metabolites may serve as valuable sources of antibiotics against Staphylococcus aureus. These findings provided an important scientific groundwork for further exploration of the antibacterial mechanisms of compounds derived from Ganoderma sp. in future research.

Overview of Dermatological Manifestations Associated with the COVID-19 Infection.

COVID-19 is an infectious disease caused by SARS-CoV-2 that is characterized by respiratory symptoms, fever, and chills.[1] While these systemic symptoms are widely known and well understood, there have also been reports of dermatological manifestations in patients with COVID-19. These manifestations include chilblain-like lesions, maculopapular lesions, urticarial lesions, necrosis, and other varicella-like exanthems.[2] The pathogenesis of these lesions are not well understood, but the procoagulant and pro-inflammatory state induced by COVID-19 infections may be contributing to varied cutaneous manifestations.[3] Drug interactions and concurrent hypersensitivity reactions have also been postulated.[4] This review aims to compile and analyze various retrospective studies and case reports to summarize the clinical presentation of dermatological lesions associated with COVID-19 infections and suggest further areas of research.

Computationally efficient demographic history inference from allele frequencies with supervised machine learning.

Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele frequency spectrum (AFS) and maximum composite likelihood optimization. However, dadi's optimization procedure can be computationally expensive. Here, we present donni (demography optimization via neural network inference), a new inference method based on dadi that is more efficient while maintaining comparable inference accuracy. For each dadi-supported demographic model, donni simulates the expected AFS for a range of model parameters then trains a set of Mean Variance Estimation neural networks using the simulated AFS. Trained networks can then be used to instantaneously infer the model parameters from future genomic data summarized by an AFS. We demonstrate that for many demographic models, donni can infer some parameters, such as population size changes, very well and other parameters, such as migration rates and times of demographic events, fairly well. Importantly, donni provides both parameter and confidence interval estimates from input AFS with accuracy comparable to parameters inferred by dadi's likelihood optimization while bypassing its long and computationally intensive evaluation process. donni's performance demonstrates that supervised machine learning algorithms may be a promising avenue for developing more sustainable and computationally efficient demographic history inference methods.

Evaluating the benefit of virtual surgical planning on bony union rates in head and neck reconstructive surgery.

OBJECTIVES: Virtual surgical planning (VSP) has gained acceptance because of its benefits in obtaining adequate resection, achieving cephalometric accuracy, and reducing operative time. The aim of this study is to compare the rate of union between VSP and free-hand surgery (FHS), identify predictors of non-union and evaluate the difference in operative time. METHODS: Post-operative CT were retrospectively reviewed for 123 patients who underwent maxillary or mandibular reconstruction between 2014 and 2021 using either VSP or FHS. Each apposition was graded as complete, partial or non-union. The rate of union, risk difference and inter-rater reliability were calculated. The difference in operative time was assessed. Predictors of non-union were identified using logistic regression. RESULTS: A total of 326 appositions were graded (VSP n = 150; FHS n = 176). The rates of complete and partial union were higher with VSP than FHS (74.7% vs. 65.3%; 18% vs. 15.9%, respectively, p = 0.01). Non-union was found at a higher rate with FHS than with VSP (18.7% vs. 7.3%). The non-union risk difference was 11.4. FHS, major complications and apposition at the native bone were predictors of non-union (OR 2.9, p = 0.02; OR 3.4, p = 0.01; OR 2.5, p = 0.05, respectively). The mean surgical time was shorter with VSP than with FHS (265.3 vs. 381.5 min, p < 0.001). The inter-rater agreement was high (k = 0.85; ICC = 0.86). CONCLUSION: VSP demonstrated significantly higher bony union rates and shorter operative time. FHS, development of major complications and apposition with native bone correlated with non-union.

CXCL9/10-engineered dendritic cells promote T cell activation and enhance immune checkpoint blockade for lung cancer.

Immune checkpoint blockade (ICB) with PD-1/PD-L1 inhibition has revolutionized the treatment of non-small cell lung cancer (NSCLC). Durable responses, however, are observed only in a subpopulation of patients. Defective antigen presentation and an immunosuppressive tumor microenvironment (TME) can lead to deficient T cell recruitment and ICB resistance. We evaluate intratumoral (IT) vaccination with CXCL9- and CXCL10-engineered dendritic cells (CXCL9/10-DC) as a strategy to overcome resistance. IT CXCL9/10-DC leads to enhanced T cell infiltration and activation in the TME and tumor inhibition in murine NSCLC models. The antitumor efficacy of IT CXCL9/10-DC is dependent on CD4+ and CD8+ T cells, as well as CXCR3-dependent T cell trafficking from the lymph node. IT CXCL9/10-DC, in combination with ICB, overcomes resistance and establishes systemic tumor-specific immunity in murine models. These studies provide a mechanistic understanding of CXCL9/10-DC-mediated host immune activation and support clinical translation of IT CXCL9/10-DC to augment ICB efficacy in NSCLC.

The eukaryotic-like characteristics of small GTPase, roadblock and TRAPPC3 proteins from Asgard archaea.

Membrane-enclosed organelles are defining features of eukaryotes in distinguishing these organisms from prokaryotes. Specification of distinct membranes is critical to assemble and maintain discrete compartments. Small GTPases and their regulators are the signaling molecules that drive membrane-modifying machineries to the desired location. These signaling molecules include Rab and Rag GTPases, roadblock and longin domain proteins, and TRAPPC3-like proteins. Here, we take a structural approach to assess the relatedness of these eukaryotic-like proteins in Asgard archaea, the closest known prokaryotic relatives to eukaryotes. We find that the Asgard archaea GTPase core domains closely resemble eukaryotic Rabs and Rags. Asgard archaea roadblock, longin and TRAPPC3 domain-containing proteins form dimers similar to those found in the eukaryotic TRAPP and Ragulator complexes. We conclude that the emergence of these protein architectures predated eukaryogenesis, however further adaptations occurred in proto-eukaryotes to allow these proteins to regulate distinct internal membranes.

Conamonin A and dihydrochalcones from the whole plants of Conamomum rubidum (Lamxay & N.S.Lý) Skornick. & A.D. Poulsen showing anti-inflammatory and cytotoxic activities.

A new compound, conamonin A (1), was isolated from the whole plants of Conamomum rubidum with eight known dihydrochalcones (2-9). Their structures were elucidated by a combination of spectroscopic methods as well as by comparison with previously reported data. The absolute configuration of 1 was assigned by TDDFT-ECD method. Compounds 1 and 8 showed inhibitory activity against LPS-induced NO production in the RAW 264.7 cells, with IC50 values of 58.29 ± 2.88 and 81.77 ± 5.99 µM, respectively. Compounds 3/4 and 5/6 exhibited inhibitory effects, with IC50 values of 28.76 ± 1.16 and 29.89 ± 1.79 µg/mL, respectively. Compounds 2, 7-9 exhibited significant cytotoxic activity against human lung carcinoma (the SK-LU-1 cell line) with IC50 values ranging from 9.87 to 17.99 µM. This study offers valuable insights into the chemical constituents and biological activities of Conamomum rubidum, highlighting its potential as a source for discovering new anti-inflammatory and cytotoxic agents.

RNA therapeutics for respiratory diseases.

It has become increasingly common to utilize RNA treatment to treat respiratory illnesses. Experimental research on both people and animals has advanced quickly since the turn of the twenty-first century in an effort to discover a treatment for respiratory ailments that could not be accomplished with earlier techniques, specifically in treating prevalent respiratory diseases such as lung cancer, chronic obstructive pulmonary disease (COPD), respiratory infections caused by viruses, and asthma. This chapter has provided a comprehensive overview of the scientific evidence in applying RNA therapy to treat respiratory diseases. The chapter describes the development of this therapy for respiratory diseases. At the same time, the types of RNA therapy for respiratory diseases have been highlighted. In addition, the mechanism of this therapy for respiratory diseases has also been covered. These insights are indispensable if this therapy is to be developed widely.

Disaster after disaster: the outbreak of infectious diseases in Pakistan in the wake of 2022 floods.

In June 2022, Pakistan witnessed catastrophic floods, affecting millions of people. The ensuing epidemics of cholera, cryptosporidiosis, rotavirus infections, generalized diarrhoea, typhoid and paratyphoid fevers, as well as the frequency of vector-borne diseases including malaria and dengue fever, are studied in this investigation. It also explores the latest outbreak of poliomyelitis and the frequency of respiratory diseases such COVID-19, diphtheria, and tuberculosis, as well as how floods have contributed to skin and eye problems. The report also describes the obstacles governments must overcome in order to manage these health emergencies and offers possible solutions for reducing the effects of ongoing and anticipated epidemics. This flood emphasizes the pressing need for international action and acts as an alarming indicator of the significant impact of climate change. It emphasizes how crucial it is to have effective flood response and preparation strategies in developing nations that are vulnerable to natural disasters.

Computationally efficient demographic history inference from allele frequencies with supervised machine learning.

Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele frequency spectrum (AFS) and maximum composite likelihood optimization. However, dadi's optimization procedure can be computationally expensive. Here, we developed donni (demography optimization via neural network inference), a new inference method based on dadi that is more efficient while maintaining comparable inference accuracy. For each dadi-supported demographic model, donni simulates the expected AFS for a range of model parameters then trains a set of Mean Variance Estimation neural networks using the simulated AFS. Trained networks can then be used to instantaneously infer the model parameters from future input data AFS. We demonstrated that for many demographic models, donni can infer some parameters, such as population size changes, very well and other parameters, such as migration rates and times of demographic events, fairly well. Importantly, donni provides both parameter and confidence interval estimates from input AFS with accuracy comparable to parameters inferred by dadi's likelihood optimization while bypassing its long and computationally intensive evaluation process. donni's performance demonstrates that supervised machine learning algorithms may be a promising avenue for developing more sustainable and computationally efficient demographic history inference methods.

Experience of Autologous Immunotherapy for Non-Small Cell Lung Cancer Using Zoledronate-Actived Gammadelta T Cells.

BACKGROUND: Several nations around the world have utilized autologous immune enhancement therapy in the treatment of cancer, with initial positive outcomes. This study describes our experience with autologous gamma delta T cell immunotherapy for the treatment of non-small cell lung cancer patients in Vietnam, a developing nation. METHODS: Five patients with non-small cell lung cancer at stages III - IV were enrolled in the study. Each patient received six infusions of autologous γδT cells, separated by two weeks. Before, during, at the end of treatment, and three and six months after treatment, a comprehensive evaluation of clinical, laboratory, quality of life, and adverse events related to the method was conducted. RESULTS: At the time of culture seeding, the total number of cells ranged from 2.9 to 18.2 x 106, with γδT cells ranging in number from 10.7 to 19.6 x 104. On day 14 of the culture, the number of γδT cells ranged from 3.1 to 8.3 x 108. Regarding the safety of therapy in a total of 30 infusions, two (fever), one (myalgia), and one (joint pain) were graded as 1 by CTCAE criteria. After the course, no toxicity was observed in the hematopoietic system, kidney function, or liver function. Evaluation of the patient's response in accordance with the RECIST 1.1 criteria: 20% of patients (one patient) had partial response disease, and 80% of patients (four patients) had stable disease at the end of treatment. During the follow-up period of the study, three patients were still alive, and the disease remained stable. The patient's quality of life improved after treatment in most functional measures (activity, cognitive, and social), but physical and emotional scores decreased slightly. Two patients' fatigue symptoms increased, but after six months of treatment, the average value dropped from 25.3 to 8.3. Dyspnea symptoms decreased gradually from 33.3 at the start of treatment to 8.3 six months later. CONCLUSIONS: The initial results we obtained regarding the efficacy and safety of autologous γδT cell immunotherapy for patients with non-small cell lung cancer are extremely encouraging and comparable to those of previous studies.

An in vitro experimental pipeline to characterize the epitope of a SARS-CoV-2 neutralizing antibody.

IMPORTANCE: The COVID-19 pandemic remains a significant public health concern for the global population; the development and characterization of therapeutics, especially ones that are broadly effective, will continue to be essential as severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) variants emerge. Neutralizing monoclonal antibodies remain an effective therapeutic strategy to prevent virus infection and spread so long as they recognize and interact with circulating variants. The epitope and binding specificity of a neutralizing anti-SARS-CoV-2 Spike receptor-binding domain antibody clone against many SARS-CoV-2 variants of concern were characterized by generating antibody-resistant virions coupled with cryo-EM structural analysis and VSV-spike neutralization studies. This workflow can serve to predict the efficacy of antibody therapeutics against emerging variants and inform the design of therapeutics and vaccines.

KTt-45, a T-type calcium channel blocker, acts as an anticancer agent by inducing apoptosis on HeLa cervical cancer cell line.

The abnormal expression in the T-type calcium channels is involved in various cancer types, thus inhibiting T-type calcium channels is one of approaches in cancer treatment. The fact that KTt-45 acted as a T-type calcium channel inhibitor as well as a pain-relief agent prompts us to address if KTt-45 plays any role against cancer cells. The results showed that KTt-45 caused cytotoxic effects towards HeLa cervical, Raji lymphoma, MCF-7 breast cancer, and A549 lung cancer cell lines with IC50 values less than 100 µM, in which highly selective toxicity was against HeLa cells (IC50 = 37.4 µM, SI > 3.2). Strikingly, the KTt-45 induced an accumulation of cytoplasmic vacuoles after 48 h treatment and mitochondrial-dependent apoptosis activation as evidenced by morphological features, chromatin condensation, nuclear fragmentation, and significant activation of caspase-9 as well as caspase-3. In conclusion, KTt-45 could inhibit cell growth and trigger mitochondrial-dependent apoptosis in HeLa cervical cancer cells. The results, taken together, strongly demonstrated that KTt-45 is a potential agent for further study on anticancer drug development which not only targets cancer cells but also helps to relieve neuropathic pain in cancer patients.

Antimalarial activities of benzothiazole analogs: A systematic review.

BACKGROUND: Benzothiazole derivatives have been reported to possess a wide range of biological activities, including antimalarial activity. This systematic review aims to summarize and evaluate the antimalarial activities of benzothiazole analogs. METHODS: We conducted an electronic search using nine databases in October 2017 and subsequently updated in September 2022. We included all original in vitro and in vivo studies that documented the antimalarial activities of compounds containing benzothiazole analogs with no restriction. The risk of bias of each included study was assessed by ToxRTool. RESULTS: Twenty-eight articles were included in our study, which are in vitro, in vivo, or both. Of these, 232 substances were identified to have potent antiplasmodial activity against various strains of the malaria parasite. Benzothiazole analogs show different antimalarial mechanisms, including inhibition of Plasmodium falciparum enzymes in in vitro studies and inhibition of blood parasites in in vivo studies. CONCLUSIONS: Benzothiazole derivatives are promising substances for treating malaria. The structure-activity relationship studies suggest that the substitution pattern of the benzothiazole scaffold plays a crucial role in determining the antimalarial activity of the analog.

Multicenter observational survey on psychosocial and behavioral impacts of COVID-19 in people living with HIV in Northern Vietnam.

Socially marginalized groups, including people living with HIV/AIDS (PLHIV), could be disproportionately affected by Coronavirus disease 2019 (COVID-19). Following an initial single-center survey conducted in 2020, we conducted a second survey of 11 antiretroviral therapy (ART) sites in Northern Vietnam between June 2021 and January 2022. We tested anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) nucleocapsid IgG antibodies and assessed prevention against COVID-19 and impacts of COVID-19 on access to ART, economic security, risky health behaviors, and mental health using self-reported questionnaires. In total, 7808 PLHIV on ART participated in the second survey. The overall prevalence of SARS-CoV-2 antibody was as low as 1.2%. There was no clear upward trend in COVID-19 infection among PLHIV compared with the rate of infection among the general population. HIV treatment was generally maintained and no increase in risky health behaviors was observed. The economic impacts were significant, with high unemployment rate, poorer economic security, and binge drinking strongly associated with depression. However, the prevalence of depression decreased by 11.2% compared with pre-COVID-19 levels. Social support, including for patients to continue HIV treatment and effective employment/financial assistance, may help to alleviate the negative socioeconomic impacts of COVID-19 and improve mental health among PLHIV.

Dietary nitrate, nitrite, and nitrosamine in association with diabetes: a systematic review and meta-analysis.

CONTEXT: Diabetes is a global health concern, and diet is a contributing factor to diabetes. Findings regarding the connection between nitrate, nitrite, and nitrosamine and diabetes risk are inconsistent. OBJECTIVE: The aim was to examine the effects of these dietary compounds on diabetes risk. DATA SOURCES: The data were sourced from PubMed, EMBASE, Scopus, and Web of Science until February 28, 2023. Studies that reported individual-level consumption of these compounds were included. Review articles or ecological studies were excluded. DATA EXTRACTION: The number of events and total observations were recorded. DATA ANALYSIS: The pooled odds ratio (OR) was calculated and displayed in a forest plot. Subgroup and sensitivity analyses were predefined. A dose-response meta-analysis was conducted to determine the exposure intervals that may increase the risk of disease. Six observational reports that met the inclusion criteria were included, involving 108 615 individuals. Participants in the highest quantile of nitrite intake had a greater risk of diabetes compared with those in the lowest quantile (OR, 1.61; 95% confidence interval [CI], 1.08-2.39; I2 = 74%, P = 0.02). Higher nitrosamine consumption tended to increase diabetes risk (OR, 1.52; 95% CI, 0.76-3.04; I2 = 76%; P = 0.24). The relationship was stronger for type 1 (OR, 1.79; 95% CI, 1.20-2.67; I2 = 58%; P < 0.01) than for type 2 diabetes (OR, 1.42; 95% CI, 0.86-2.37; I2 = 71%; P = 0.17). Additionally, nitrite consumption had a dose-dependent association with both phenotypes. No association was found between diabetes risk and high nitrate intake (OR, 1.01; 95% CI, 0.87-1.18; I2 = 28%; P = 0.87). CONCLUSION: Attention should be paid to the consumption of nitrite-containing foods. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42023394462 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=394462).

The Role of Immune Checkpoint Inhibitors in Metastatic Pancreatic Cancer: Current State and Outlook.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors, characterized by its aggressive tumor biology and poor prognosis. While immune checkpoint inhibitors (ICIs) play a major part in the treatment algorithm of various solid tumors, there is still no evidence of clinical benefit from ICI in patients with metastatic PDAC (mPDAC). This might be due to several reasons, such as the inherent low immunogenicity of pancreatic cancer, the dense stroma-rich tumor microenvironment that precludes an efficient migration of antitumoral effector T cells to the cancer cells, and the increased proportion of immunosuppressive immune cells, such as regulatory T cells (Tregs), cancer-associated fibroblasts (CAFs), and myeloid-derived suppressor cells (MDSCs), facilitating tumor growth and invasion. In this review, we provide an overview of the current state of ICIs in mPDAC, report on the biological rationale to implement ICIs into the treatment strategy of pancreatic cancer, and discuss preclinical studies and clinical trials in this field. Additionally, we shed light on the challenges of implementing ICIs into the treatment strategy of PDAC and discuss potential future directions.

Conarubins A-D: Four Monoterpene-Chalcone Conjugates from Conamomum rubidum and Their Anti-inflammatory and Cytotoxic Activities.

Four novel compounds, conarubins A-D (1-4), were isolated from the whole plants of Conamomum rubidum collected in Vietnam. Their structures were elucidated by extensive spectroscopic analyses and by quantum chemical calculations of NMR and ECD. Compounds 1 and 2 were the first examples of monoterpene-monoterpene-chalcone conjugates in nature, whereas compound 4 was an unprecedented monoterpene-substituted chalcone containing a 3,4,5-trioxygenated cyclohexa-2,5-diene-1-one ring. The anti-inflammatory and cytotoxic activities of all isolates were investigated.

Smart greenhouse construction and irrigation control system for optimal Brassica Juncea development.

This paper contributes to smart greenhouses and IoT (Internet of Things) research. Our pioneering achievement centers on successfully designing, constructing, and testing a 30m2 smart greenhouse, explicitly focusing on the cultivation and development of Brassica Juncea, a mustard variety commonly grown in Vietnam. The construction phase entailed the meticulous integration of diverse IoT technologies and systems, culminating in the creation of a finely tuned environment to meet the unique needs of Brassica Juncea cultivation. Notably, our research team has realized the physical infrastructure and developed and implemented a robust web interface. This interface empowers users to monitor and remotely control the smart greenhouse conveniently. It provides real-time visualization of critical parameters, including temperature, humidity, soil moisture, and light intensity, enabling precise monitoring and supporting informed decision-making in crop management. In addition to the web interface, we have meticulously designed and completed an Android mobile application, further enhancing accessibility and convenience. This mobile app allows users to monitor and control the smart greenhouse while on the move. It is imperative to underscore that this work marks a significant milestone as the first complete smart greenhouse IoT solution dedicated to developing Brassica Juncea. Our pioneering accomplishments not only advance the frontiers of innovative greenhouse and IoT research but also contribute substantially to the progress of intelligent agriculture.