Genome-wide identification and expression analysis of the C2H2-zinc finger transcription factor gene family and screening of candidate genes involved in floral development in Coptis teeta Wall. (Ranunculaceae).

Background: C2H2-zinc finger transcription factors comprise one of the largest and most diverse gene superfamilies and are involved in the transcriptional regulation of flowering. Although a large number of C2H2 zinc-finger proteins (C2H2-ZFPs) have been well characterized in a number of model plant species, little is known about their expression and function in Coptis teeta. C. teeta displays two floral phenotypes (herkogamy phenotypes). It has been proposed that the C2H2-zinc finger transcription factor family may play a crucial role in the formation of floral development and herkogamy observed in C. teeta. As such, we performed a genome-wide analysis of the C2H2-ZFP gene family in C. teeta. Results: The complexity and diversity of C. teeta C2H2 zinc finger proteins were established by evaluation of their physicochemical properties, phylogenetic relationships, exon-intron structure, and conserved motifs. Chromosome localization showed that 95 members of the C2H2 zinc-finger genes were unevenly distributed across the nine chromosomes of C. teeta, and that these genes were replicated in tandem and segmentally and had undergone purifying selection. Analysis of cis-acting regulatory elements revealed a possible involvement of C2H2 zinc-finger proteins in the regulation of phytohormones. Transcriptome data was then used to compare the expression levels of these genes during the growth and development of the two floral phenotypes (F-type and M-type). These data demonstrate that in groups A and B, the expression levels of 23 genes were higher in F-type flowers, while 15 genes showed higher expressions in M-type flowers. qRT-PCR analysis further revealed that the relative expression was highly consistent with the transcriptome data. Conclusion: These data provide a solid basis for further in-depth studies of the C2H2 zinc finger transcription factor gene family in this species and provide preliminary information on which to base further research into the role of the C2H2 ZFPs gene family in floral development in C. teeta.

Assessing synchronous ovarian metastasis in gastric cancer patients using a clinical-radiomics nomogram based on baseline abdominal contrast-enhanced CT: a two-center study.

BACKGROUND: To build and validate a radiomics nomogram based on preoperative CT scans and clinical data for detecting synchronous ovarian metastasis (SOM) in female gastric cancer (GC) cases. METHODS: Pathologically confirmed GC cases in 2 cohorts were retrospectively enrolled. All cases had presurgical abdominal contrast-enhanced CT and pelvis contrast-enhanced MRI and pathological examinations for any suspicious ovarian lesions detected by MRI. Cohort 1 cases (n = 101) were included as the training set. Radiomics features were obtained to develop a radscore. A nomogram combining the radscore and clinical factors was built to detect SOM. The bootstrap method was carried out in cohort 1 as internal validation. External validation was carried out in cohort 2 (n = 46). Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and the confusion matrix were utilized to assess the performances of the radscore, nomogram and subjective evaluation model. RESULTS: The nomogram, which combined age and the radscore, displayed a higher AUC than the radscore and subjective evaluation (0.910 vs 0.827 vs 0.773) in the training cohort. In the external validation cohort, the nomogram also had a higher AUC than the radscore and subjective evaluation (0.850 vs 0.790 vs 0.675). DCA and the confusion matrix confirmed the nomogram was superior to the radscore in both cohorts. CONCLUSIONS: This pilot study showed that a nomogram model combining the radscore and clinical characteristics is useful in detecting SOM in female GC cases. It may be applied to improve clinical treatment and is superior to subjective evaluation or the radscore alone.

A Water-Soluble Hydrogen Sulfide Donor Suppresses the Growth of Hepatocellular Carcinoma via Inhibiting the AKT/GSK-3ß/ß-Catenin and TGF-ß/Smad2/3 Signaling Pathways.

Hepatocellular carcinoma (HCC) is a disease with high morbidity, high mortality, and low cure rate. Hyaluronic acid (HA) is widely adopted in tissue engineering and drug delivery. 5-(4-Hydroxyphenyl)-3H-1, 2-dithiol-3-thione (ADT-OH) is one of commonly used H2S donors. In our previous study, HA-ADT was designed and synthesized via coupling of HA and ADT-OH. In this study, compared with sodium hydrosulfide (NaHS, a fast H2S-releasing donor) and morpholin-4-ium (4-methoxyphenyl)-morpholin-4-ylsulfanylidenesulfido-λ5-phosphane (GYY4137, a slow H2S-releasing donor), HA-ADT showed stronger inhibitory effect on the proliferation, migration, invasion, and cell cycle of human HCC cells. HA-ADT promoted apoptosis by suppressing the expressions of phospho (p)-protein kinase B (PKB/AKT), p-glycogen synthase kinase-3ß (GSK-3ß), p-ß-catenin, and also inhibited autophagy via the downregulation of the protein levels of p-Smad2, p-Smad3, and transforming growth factor-ß (TGF-ß) in human HCC cells. Moreover, HA-ADT inhibited HCC xenograft tumor growth more effectively than both NaHS and GYY4137. Therefore, HA-ADT can suppress the growth of HCC cells by blocking the AKT/GSK-3ß/ß-catenin and TGF-ß/Smad2/3 signaling pathways. HA-ADT and its derivatives may be developed as promising antitumor drugs.

Prediction of myocardial ischemia in coronary heart disease patients using a CCTA-Based radiomic nomogram.

Objective: The present study aimed to predict myocardial ischemia in coronary heart disease (CHD) patients based on the radiologic features of coronary computed tomography angiography (CCTA) combined with clinical factors. Methods: The imaging and clinical data of 110 patients who underwent CCTA scan before DSA or FFR examination in Changzhou Second People's Hospital, Nanjing Medical University (90 patients), and The First Affiliated Hospital of Soochow University (20 patients) from March 2018 to January 2022 were retrospectively analyzed. According to the digital subtraction angiography (DSA) and fractional flow reserve (FFR) results, all patients were assigned to myocardial ischemia (n = 58) and normal myocardial blood supply (n = 52) groups. All patients were further categorized into training (n = 64) and internal validation (n = 26) sets at a ratio of 7:3, and the patients from second site were used as external validation. Clinical indicators of patients were collected, the left ventricular myocardium were segmented from CCTA images using CQK software, and the radiomics features were extracted using pyradiomics software. Independent prediction models and combined prediction models were established. The predictive performance of the model was assessed by calibration curve analysis, receiver operating characteristic (ROC) curve and decision curve analysis. Results: The combined model consisted of one important clinical factor and eight selected radiomic features. The area under the ROC curve (AUC) of radiomic model was 0.826 in training set, and 0.744 in the internal validation set. For the combined model, the AUCs were 0.873, 0.810, 0.800 in the training, internal validation, and external validation sets, respectively. The calibration curves demonstrated that the probability of myocardial ischemia predicted by the combined model was in good agreement with the observed values in both training and validation sets. The decision curve was within the threshold range of 0.1-1, and the clinical value of nomogram was higher than that of clinical model. Conclusion: The radiomic characteristics of CCTA combined with clinical factors have a good clinical value in predicting myocardial ischemia in CHD patients.

HA-ADT suppresses esophageal squamous cell carcinoma progression via apoptosis promotion and autophagy inhibition.

Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer-related deaths. We have previously connected a non-sulfated glycosaminoglycan, hyaluronic acid (HA), with a common hydrogen sulfide (H2S) donor, 5-(4-hydroxyphenyl)-3H-1,2-dithiol-3-thione (ADT-OH), to reconstruct a novel conjugate, HA-ADT. In this study, we determined the effect of HA-ADT on the growth of ESCC. Our data suggested that HA-ADT exerted more potent effects than sodium hydrosulfide (NaHS, a fast H2S-releasing donor) and morpholin-4-ium (4-methoxyphenyl)-morpholin-4-ylsulfanylidenesulfido-λ5-phosphane (GYY4137, a slow H2S-releasing donor) on inhibiting the viability, proliferation, migration, and invasion of human ESCC cells. HA-ADT increased apoptosis by suppressing the protein expressions of phospho (p)-Ser473-protein kinase B (PKB/AKT), p-Tyr199/Tyr458-phosphatidylinositol 3-kinase (PI3K), and p-Ser2448-mammalian target of rapamycin (mTOR), but suppressed autophagy through the inhibition of the protein levels of p-Ser552-ß-catenin, p-Ser9-glycogen synthase kinase-3ß (GSK-3ß), and Wnt3a in human ESCC cells. In addition, HA-ADT was more effective in terms of the growth inhibition of human ESCC xenograft tumor than NaHS and GYY4137. In conclusion, HA-ADT can suppress ESCC progression via apoptosis promotion and autophagy inhibition. HA-ADT might be efficacious for the treatment of cancer.

Exploring value of CT coronary imaging combined with machine-learning methods to predict myocardial ischemia.

PURPOSE: To establish a machine-learning (ML) model based on coronary computed tomography angiography (CTA) images for evaluating myocardial ischemia in patients diagnosed with coronary atherosclerosis. METHODS: This retrospective analysis includes CTA images acquired from 110 patients. Among them, 58 have myocardial ischemia and 52 have normal myocardial blood supply. The patients are divided into training and test datasets with a ratio 7 : 3. Deep learning model-based CQK software is used to automatically segment myocardium on CTA images and extract texture features. Then, seven ML models are constructed to classify between myocardial ischemia and normal myocardial blood supply cases. Predictive performance and stability of the classifiers are determined by receiver operating characteristic curve with cross validation. The optimal ML model is then validated using an independent test dataset. RESULTS: Accuracy and areas under ROC curves (AUC) obtained from the support vector machine with extreme gradient boosting linear method are 0.821 and 0.777, respectively, while accuracy and AUC achieved by the neural network (NN) method are 0.818 and 0.757, respectively. The naive Bayes model yields the highest sensitivity (0.942), and the random forest model yields the highest specificity (0.85). The k-nearest neighbors model yields the lowest accuracy (0.74). Additionally, NN model demonstrates the lowest relative standard deviations (0.16 for accuracy and 0.08 for AUC) indicating the high stability of this model, and its AUC applying to the independent test dataset is 0.72. CONCLUSION: The NN model demonstrates the best performance in predicting myocardial ischemia using radiomics features computed from CTA images, which suggests that this ML model has promising potential in guiding clinical decision-making.

Application of Unenhanced Computed Tomography Texture Analysis to Differentiate Pancreatic Adenosquamous Carcinoma from Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: The objective of this study was to investigate the application of unenhanced computed tomography (CT) texture analysis in differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC). METHODS: Preoperative CT images of 112 patients (31 with PASC, 81 with PDAC) were retrospectively reviewed. A total of 396 texture parameters were extracted from AnalysisKit software for further texture analysis. Texture features were selected for the differentiation of PASC and PDAC by the Mann-Whitney U test, univariate logistic regression analysis, and the minimum redundancy maximum relevance algorithm. Furthermore, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the texture feature-based model by the random forest (RF) method. Finally, the robustness and reproducibility of the predictive model were assessed by the 10-times leave-group-out cross-validation (LGOCV) method. RESULTS: In the present study, 10 texture features to differentiate PASC from PDAC were eventually retained for RF model construction after feature selection. The predictive model had a good classification performance in differentiating PASC from PDAC, with the following characteristics: sensitivity, 95.7%; specificity, 92.5%; accuracy, 94.3%; positive predictive value (PPV), 94.3%; negative predictive value (NPV), 94.3%; and area under the ROC curve (AUC), 0.98. Moreover, the predictive model was proved to be robust and reproducible using the 10-times LGOCV algorithm (sensitivity, 90.0%; specificity, 71.3%; accuracy, 76.8%; PPV, 59.0%; NPV, 95.2%; and AUC, 0.80). CONCLUSION: The unenhanced CT texture analysis has great potential for differentiating PASC from PDAC.

Enhanced computed tomography radiomics-based machine-learning methods for predicting the Fuhrman grades of renal clear cell carcinoma.

OBJECTIVE: To develop and test an optimal machine learning model based on the enhanced computed tomography (CT) to preoperatively predict pathological grade of clear cell renal cell carcinoma (ccRCC). METHODS: A retrospective analysis of 53 pathologically confirmed cases of ccRCC was performed and 25 consecutive ccRCC cases were selected as a prospective testing set. All patients underwent routine preoperative abdominal CT plain and enhanced scans. Renal tumor lesions were segmented on arterial phase images and 396 radiomics features were extracted. In the training set, seven discrimination classifiers for high- and low-grade ccRCCs were constructed based on seven different machine learning models, respectively, and their performance and stability for predicting ccRCC grades were evaluated through receiver operating characteristic (ROC) analysis and cross-validation. Prediction accuracy and area under ROC curve were used as evaluation indices. Finally, the diagnostic efficacy of the optimal model was verified in the testing set. RESULTS: The accuracies and AUC values achieved by support vector machine with radial basis function kernel (svmRadial), random forest and naïve Bayesian models were 0.860±0.158 and 0.919±0.118, 0.840±0.160 and 0.915±0.138, 0.839±0.147 and 0.921±0.133, respectively, which showed high predictive performance, whereas K-nearest neighborhood model yielded lower accuracy of 0.720±0.188 and lower AUC value of 0.810±0.150. Additionally, svmRadial had smallest relative standard deviation (RSD, 0.13 for AUC, 0.17 for accuracy), which indicates higher stability. CONCLUSION: svmRadial performs best in predicting pathological grades of ccRCC using radiomics features computed from the preoperative CT images, and thus may have high clinical potential in guiding preoperative decision.

MRI-Based Radiomics Nomogram for Selecting Ovarian Preservation Treatment in Patients With Early-Stage Endometrial Cancer.

BACKGROUND: Ovarian preservation treatment (OPT) was recommended in young women with early-stage endometrial cancer [superficial myometrial invasion (MI) and grades (G) 1/2-endometrioid adenocarcinoma (EEC)]. A radiomics nomogram was developed to assist radiologists in assessing the depth of MI and in selecting eligible patients for OPT. METHODS: From February 2014 to May 2021, 209 G 1/2-EEC patients younger than 45 years (mean 39 ± 4.3 years) were included. Of them, 104 retrospective patients were enrolled in the primary group, and 105 prospective patients were enrolled in the validation group. The radiomics features were extracted based on multi-parametric magnetic resonance imaging, and the least absolute shrinkage and selection operator algorithm was applied to reduce the dimensionality of the data and select the radiomics features that correlated with the depth of MI in G 1/2-EEC patients. A radiomics nomogram for evaluating the depth of MI was developed by combing the selected radiomics features with the cancer antigen 125 and tumor size. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the radiomics nomogram and of radiologists without and with the aid of the radiomics nomogram. The net reclassification index (NRI) and total integrated discrimination index (IDI) based on the total included patients to assess the clinical benefit of radiologists with the radiomics nomogram were calculated. RESULTS: In the primary group, for evaluating the depth of MI, the AUCs were 0.96 for the radiomics nomogram; 0.80 and 0.86 for radiologists 1 and 2 without the aid of the nomogram, respectively; and 0.98 and 0.98 for radiologists 1 and 2 with the aid of the nomogram, respectively. In the validation group, the AUCs were 0.88 for the radiomics nomogram; 0.82 and 0.83 for radiologists 1 and 2 without the aid of the nomogram, respectively; and 0.94 and 0.94 for radiologists 1 and 2 with the aid of the nomogram, respectively. The yielded NRI and IDI values were 0.29 and 0.43 for radiologist 1 and 0.23 and 0.37 for radiologist 2, respectively. CONCLUSIONS: The radiomics nomogram outperformed radiologists and could help radiologists in assessing the depth of MI and selecting eligible OPTs in G 1/2-EEC patients.

Dual Enzyme-Like Performances of PLGA Grafted Maghemite Nanocrystals and Their Synergistic Chemo/Chemodynamic Treatment for Human Lung Adenocarcinoma A549 Cells.

In recent years, the emergence of non-toxic but catalytically active inorganic nanoparticles has attracted great attention for cancer treatment, but the therapeutic effect has been affected by the limited reactive oxygen species in tumors. Therefore, the combination of chemotherapy and chemodynamic therapy is regarded as a promising therapeutic strategy. In this paper, we reported the preparation and bioactivity evaluation of poly(lactic acid-co-glycolic acid) (PLGA) grafted-γ-Fe2O3 nanoparticles with dual response of endogenous peroxidase and catalase like activities. Our hypothesis is that PLGAgrafted γ-Fe2O3 nanoparticles could be used as a drug delivery system for the anti-tumor drug doxorubicin to inhibit the growth of lung adenocarcinoma A549 cells; meanwhile, based on its mimic enzyme properties, this kind of nanoparticles could be combined with doxorubicin in the treatment of A549 cells. Our experimental results showed that the PLGAgrafted γ-Fe2O3 nanoparticles could simulate the activity of catalase and decompose hydrogen peroxide into H2O and oxygen in neutral tumor microenvironment, thus reducing the oxidative damage caused by hydrogenperoxide to lung adenocarcinoma A549 cells. In acidic microenvironment, PLGA grafted γ-Fe2O3 nanoparticles could simulate the activity of peroxidase and effectively catalyze the decomposition of hydrogen peroxide to generate highly toxic hydroxyl radicals, which could cause the death of A549 cells. Furthermore, the synergistic effect of peroxidase-like activity of PLGA-grafted γ-Fe2O3 nanoparticles and doxorubicin could accelerate the apoptosisand destruction of A549 cells, thus enhancing the antitumor effect of doxorubicin-loaded PLGA-grafted γ-Fe2O3 nanoparticles. Therefore, this study provides an effective nanoplatform based on dual inorganic biomimetic nanozymes for the treatment of lung cancer.

Prognostic value of CT radiomics in evaluating lymphovascular invasion in rectal cancer: Diagnostic performance based on different volumes of interest.

OBJECTIVES: This study aims to evaluate diagnostic performance of radiomic analysis using computed tomography (CT) to identify lymphovascular invasion (LVI) in patients diagnosed with rectal cancer and assess diagnostic performance of different lesion segmentations. METHODS: The study is applied to 169 pre-treatment CT images and the clinical features of patients with rectal cancer. Radiomic features are extracted from two different volumes of interest (VOIs) namely, gross tumor volume and peri-tumor tissue volume. The maximum relevance and the minimum redundancy, and the least absolute shrinkage selection operator based logistic regression analyses are performed to select the optimal feature subset on the training cohort. Then, Rad and Rad-clinical combined models for LVI prediction are built and compared. Finally, the models are externally validated. RESULTS: Eighty-three patients had positive LVI on pathology, while 86 had negative LVI. An optimal multi-mode radiology nomogram for LVI estimation is established. The area under the receiver operating characteristic curves of the Rad and Rad-clinical combined model in the peri-tumor VOI group are significantly higher than those in the tumor VOI group (Rad: peri-tumor vs. tumor: 0.85 vs. 0.68; Rad-clinical: peri-tumor vs. tumor: 0.90 vs 0.82) in the validation cohort. Decision curve analysis shows that the peri-tumor-based Rad-clinical combined model has the best performance in identifying LVI than other models. CONCLUSIONS: CT radiomics model based on peri-tumor volumes improves prediction performance of LVI in rectal cancer compared with the model based on tumor volumes.

Nanomedicine: A Promising Way to Manage Alzheimer's Disease.

Alzheimer's disease (AD) is a devastating disease of the aging population characterized by the progressive and slow brain decay due to the formation of extracellular plaques in the hippocampus. AD cells encompass tangles of twisted strands of aggregated microtubule binding proteins surrounded by plaques. Delivering corresponding drugs in the brain to deal with these clinical pathologies, we face a naturally built strong, protective barrier between circulating blood and brain cells called the blood-brain barrier (BBB). Nanomedicines provide state-of-the-art alternative approaches to overcome the challenges in drug transport across the BBB. The current review presents the advances in the roles of nanomedicines in both the diagnosis and treatment of AD. We intend to provide an overview of how nanotechnology has revolutionized the approaches used to manage AD and highlight the current key bottlenecks and future perspective in this field. Furthermore, the emerging nanomedicines for managing brain diseases like AD could promote the booming growth of research and their clinical availability.

The Application of Nanotechnology for the Diagnosis and Treatment of Brain Diseases and Disorders.

Brain is by far the most complex organ in the body. It is involved in the regulation of cognitive, behavioral, and emotional activities. The organ is also a target for many diseases and disorders ranging from injuries to cancers and neurodegenerative diseases. Brain diseases are the main causes of disability and one of the leading causes of deaths. Several drugs that have shown potential in improving brain structure and functioning in animal models face many challenges including the delivery, specificity, and toxicity. For many years, researchers have been facing challenge of developing drugs that can cross the physical (blood-brain barrier), electrical, and chemical barriers of the brain and target the desired region with few adverse events. In recent years, nanotechnology emerged as an important technique for modifying and manipulating different objects at the molecular level to obtain desired features. The technique has proven to be useful in diagnosis as well as treatments of brain diseases and disorders by facilitating the delivery of drugs and improving their efficacy. As the subject is still hot, and new research findings are emerging, it is clear that nanotechnology could upgrade health care systems by providing easy and highly efficient diagnostic and treatment methods. In this review, we will focus on the application of nanotechnology in the diagnosis and treatment of brain diseases and disorders by illuminating the potential of nanoparticles.

Better Reporting and Awareness Campaigns Needed for Breast Cancer in Pakistani Women.

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer deaths in women globally. In 2018, 2.1 million new cases were reported, with 627,000 deaths. Pakistan has the highest incidence rate of breast cancer among Asian countries: one in every nine women has a lifetime risk of being diagnosed with breast cancer. By reason of many misconceptions about the etiology of the disease and socioeconomic factors, Pakistani women have very low rates of early detection and diagnose breast cancer at advance stages with fewer chances of survival. The key to cure the breast cancer is early diagnosis. The aim of current review is to highlight the factors leading to the delays in early presentation of breast cancer in Pakistani women and to summarize possible recommendations for educating women about early diagnosis along with palliative care facilities for patients suffering from breast cancer. Furthermore, this study appeals to both the general public and government in the belief that better reporting and awareness campaigns may bring more women to clinics for early diagnosis.

MRI-based radiomics approach for differentiation of hypovascular non-functional pancreatic neuroendocrine tumors and solid pseudopapillary neoplasms of the pancreas.

BACKGROUND: This study aims to investigate the value of radiomics parameters derived from contrast enhanced (CE) MRI in differentiation of hypovascular non-functional pancreatic neuroendocrine tumors (hypo-NF-pNETs) and solid pseudopapillary neoplasms of the pancreas (SPNs). METHODS: Fifty-seven SPN patients and twenty-two hypo-NF-pNET patients were enrolled. Radiomics features were extracted from T1WI, arterial, portal and delayed phase of MR images. The enrolled patients were divided into training cohort and validation cohort with the 7:3 ratio. We built four radiomics signatures for the four phases respectively and ROC analysis were used to select the best phase to discriminate SPNs from hypo-NF-pNETs. The chosen radiomics signature and clinical independent risk factors were integrated to construct a clinic-radiomics nomogram. RESULTS: SPNs occurred in younger age groups than hypo-NF-pNETs (P < 0.0001) and showed a clear preponderance in females (P = 0.0185). Age was a significant independent factor for the differentiation of SPNs and hypo-NF-pNETs revealed by logistic regression analysis. With AUC values above 0.900 in both training and validation cohort (0.978 [95% CI, 0.942-1.000] in the training set, 0.907 [95% CI, 0.765-1.000] in the validation set), the radiomics signature of the arterial phase was picked to build a clinic-radiomics nomogram. The nomogram, composed by age and radiomics signature of the arterial phase, showed sufficient performance for discriminating SPNs and hypo-NF-pNETs with AUC values of 0.965 (95% CI, 0.923-1.000) and 0.920 (95% CI, 0.796-1.000) in the training and validation cohorts, respectively. Delong Test did not demonstrate statistical significance between the AUC of the clinic-radiomics nomogram and radiomics signature of arterial phase. CONCLUSION: CE-MRI-based radiomics approach demonstrated great potential in the differentiation of hypo-NF-pNETs and SPNs.

Impact of the factors shaping gut microbiota on obesity.

Obesity is considered as a risk factor for chronic health diseases such as heart diseases, cancer and diabetes 2. Reduced physical activities, lifestyle, poor nutritional diet and genetics are among the risk factors associated with the development of obesity. In recent years, several studies have explored the link between the gut microbiome and the progression of diseases including obesity, with the shift in microbiome abundance and composition being the main focus. The alteration of gut microbiome composition affects both nutrients metabolism and specific gene expressions, thereby disturbing body physiology. Specifically, the abundance of fibre-metabolizing microbes is associated with weight loss and that of protein and fat-metabolizing bacteria with weight gain. Various internal and external factors such as genetics, maternal obesity, mode of delivery, breastfeeding, nutrition, antibiotic use and the chemical compounds present in the environment are known to interfere with the richness of the gut microbiota (GM), thus influencing weight gain/loss and ultimately the development of obesity. However, the effectiveness of each factor in potentiating the shift in microbes' abundance to result in significant changes that can lead to obesity is not yet clear. In this review, we will highlight the factors involved in shaping GM, their influence on obesity and possible interventions. Understanding the influence of these factors on the diversity of the GM and how to improve their effectiveness on disease conditions could be keys in the treatment of metabolic diseases.

Role of hydrogen sulfide donors in cancer development and progression.

In recent years, a vast number of potential cancer therapeutic targets have emerged. However, developing efficient and effective drugs for the targets is of major concern. Hydrogen sulfide (H2S), one of the three known gasotransmitters, is involved in the regulation of various cellular activities such as autophagy, apoptosis, migration, and proliferation. Low production of H2S has been identified in numerous cancer types. Treating cancer cells with H2S donors is the common experimental technique used to improve H2S levels; however, the outcome depends on the concentration/dose, time, cell type, and sometimes the drug used. Both natural and synthesized donors are available for this purpose, although their effects vary independently ranging from strong cancer suppressors to promoters. Nonetheless, numerous signaling pathways have been reported to be altered following the treatments with H2S donors which suggest their potential in cancer treatment. This review will analyze the potential of H2S donors in cancer therapy by summarizing key cellular processes and mechanisms involved.

Multifaceted behavior of PEST sequence enriched nuclear proteins in cancer biology and role in gene therapy.

The amino acid sequence enriched with proline (P), glutamic acid (E), serine (S), and threonine (T) (PEST) is a signal-transducing agent providing unique features to its substrate nuclear proteins (PEST-NPs). The PEST motif is responsible for particular posttranslational modifications (PTMs). These PTMs impart distinct properties to PEST-NPs that are responsible for their activation/inhibition, intracellular localization, and stability/degradation. PEST-NPs participate in cancer metabolism, immunity, and protein transcription as oncogenes or as tumor suppressors. Gene-based therapeutics are getting the attention of researchers because of their cell specificity. PEST-NPs are good targets to explore as cancer therapeutics. Insights into PTMs of PEST-NPs demonstrate that these proteins not only interact with each other but also recruit other proteins to/from their active site to promote/inhibit tumors. Thus, the role of PEST-NPs in cancer biology is multivariate. It is hard to obtain therapeutic objectives with single gene therapy. An especially designed combination gene therapy might be a promising strategy in cancer treatment. This review highlights the multifaceted behavior of PEST-NPs in cancer biology. We have summarized a number of studies to address the influence of structure and PEST-mediated PTMs on activation, localization, stability, and protein-protein interactions of PEST-NPs. We also recommend researchers to adopt a pragmatic approach in gene-based cancer therapy.

Roles of Hydrogen Sulfide Donors in Common Kidney Diseases.

Hydrogen sulfide (H2S) plays a key role in the regulation of physiological processes in mammals. The decline in H2S level has been reported in numerous renal disorders. In animal models of renal disorders, treatment with H2S donors could restore H2S levels and improve renal functions. H2S donors suppress renal dysfunction by regulating autophagy, apoptosis, oxidative stress, and inflammation through multiple signaling pathways, such as TRL4/NLRP3, AMP-activated protein kinase/mammalian target of rapamycin, transforming growth factor-ß1/Smad3, extracellular signal-regulated protein kinases 1/2, mitogen-activated protein kinase, and nuclear factor kappa B. In this review, we summarize recent developments in the effects of H2S donors on the treatment of common renal diseases, including acute/chronic kidney disease, renal fibrosis, unilateral ureteral obstruction, glomerulosclerosis, diabetic nephropathy, hyperhomocysteinemia, drug-induced nephrotoxicity, metal-induced nephrotoxicity, and urolithiasis. Novel H2S donors can be designed and applied in the treatment of common renal diseases.

Heterogeneity of T3 stage esophageal squamous cell carcinoma in different parts based on enhanced CT radiomics.

Esophageal cancer is a common malignant tumor of the digestive system with a high incidence and a poor prognosis. At the present, CT-based radiomics is providing more and more valuable information. However, the heterogeneity of the study and the poor repeatability of the texture feature parameters have limited its wider clinical application. In the present study, we focused on comparing the differences in the texture features of T3 stage esophageal squamous cell carcinoma at different locations and normal esophageal wall, aiming to provide some pieces of useful information for future research on esophageal squamous cell carcinoma.Fifty seven cases with throat CT imaging, including esophageal cancer contrast enhanced CT and conventional CT of healthy control group. The texture characteristics in control group and tumor group among different parts were compared. Using Univariable analysis, we compared the difference and conducted receiver-operator curve analysis to evaluate the performance of tumor grade diagnosis model.53 radiomic features were significantly different in control group and so as 93 features for tumor group. The upper section was the mostly different from the other 2 sections. Run-length matrix (RLM) features in tumor group accounted for the highest proportion, only Surface Volume Ratio was different.There are differences in the texture features of the tube wall in different parts of the esophagus of healthy adults, and this difference is more obvious in pT3 stage esophageal squamous cell carcinoma. In the future radiomics study of esophageal squamous cell carcinoma, we need to pay attention to this to avoid affecting the accuracy of the results.