Research Advances in Stem Cell Therapy for Erectile Dysfunction.

Erectile dysfunction (ED) is a common clinical condition that mainly affects men aged over 40 years. Various causes contribute to the progression of ED, including pelvic nerve injury, diabetes, metabolic syndrome, age, Peyronie's disease, smoking, and psychological disorders. Current treatments for ED are limited to symptom relief and do not address the root cause. Stem cells, with their powerful ability to proliferate and differentiate, are a promising approach for the treatment of male ED and are gradually gaining widespread attention. Current uses for treating ED have been studied primarily in experimental animals, with most studies observing improvements in erectile quality as well as improvements in erectile tissue. However, research on stem cell therapy for human ED is still limited. This article summarizes the recent literature on basic stem cell research on ED, including cavernous nerve injury, aging, diabetes, and sclerosing penile disease, and describes mechanisms of action and therapeutic effects of various stem cell therapies in experimental animals. Stem cells are also believed to interact with host tissue in a paracrine manner, and improved function can be supported through both implantation and paracrine factors. To date, stem cells have shown some preliminary promising results in animal and human models of ED.

Insights into the genetic influences of the microbiota on the life span of a host.

Escherichia coli (E. coli) mutant strains have been reported to extend the life span of Caenorhabditis elegans (C. elegans). However, the specific mechanisms through which the genes and pathways affect aging are not yet clear. In this study, we fed Drosophila melanogaster (fruit fly) various E. coli single-gene knockout strains to screen mutant strains with an extended lifespan. The results showed that D. melanogaster fed with E. coli purE had the longest mean lifespan, which was verified by C. elegans. We conducted RNA-sequencing and analysis of C. elegans fed with E. coli purE (a single-gene knockout mutant) to further explore the underlying molecular mechanism. We used differential gene expression (DGE) analysis, enrichment analysis, and gene set enrichment analysis (GSEA) to screen vital genes and modules with significant changes in overall expression. Our results suggest that E. coli mutant strains may affect the host lifespan by regulating the protein synthesis rate (cfz-2) and ATP level (catp-4). To conclude, our study could provide new insights into the genetic influences of the microbiota on the life span of a host and a basis for developing anti-aging probiotics and drugs.

Gut microbial genetic variation modulates host lifespan, sleep, and motor performance.

Recent studies have shown that gut microorganisms can modulate host lifespan and activities, including sleep quality and motor performance. However, the role of gut microbial genetic variation in regulating host phenotypes remains unclear. In this study, we investigated the links between gut microbial genetic variation and host phenotypes using Saccharomyces cerevisiae and Drosophila melanogaster as research models. Our result suggested a novel role for peroxisome-related genes in yeast in regulating host lifespan and activities by modulating gut oxidative stress. Specifically, we found that deficiency in catalase A (CTA1) in yeast reduced both the sleep duration and lifespan of fruit flies significantly. Furthermore, our research also expanded our understanding of the relationship between sleep and longevity. Using a large sample size and excluding individual genetic background differences, we found that lifespan is associated with sleep duration, but not sleep fragmentation or motor performance. Overall, our study provides novel insights into the role of gut microbial genetic variation in regulating host phenotypes and offers potential new avenues for improving health and longevity.

Integrated single-cell and spatial transcriptomic profiling reveals higher intratumour heterogeneity and epithelial-fibroblast interactions in recurrent bladder cancer.

BACKGROUND: Recurrent bladder cancer is the most common type of urinary tract malignancy; nevertheless, the mechanistic basis for its recurrence is uncertain. Innovative technologies such as single-cell transcriptomics and spatial transcriptomics (ST) offer new avenues for studying recurrent tumour progression at the single-cell level while preserving spatial data. METHOD: This study integrated single-cell RNA (scRNA) sequencing and ST profiling to examine the tumour microenvironment (TME) of six bladder cancer tissues (three from primary tumours and three from recurrent tumours). FINDINGS: scRNA data-based ST deconvolution analysis revealed a much higher tumour heterogeneity along with TME in recurrent tumours than in primary tumours. High-resolution ST analysis further identified that while the overall natural killer/T cell and malignant cell count or the ratio of total cells was similar or even lower in the recurrent tumours, a higher interaction between epithelial and immune cells was detected. Moreover, the analysis of spatial communication reveals a marked increase in activity between cancer-associated fibroblasts (CAFs) and malignant cells, as well as other immune cells in recurrent tumours. INTERPRETATION: We observed an enhanced interplay between CAFs and malignant cells in bladder recurrent tumours. These findings were first observed at the spatial level.

Intestinal bacteria-a powerful weapon for fungal infections treatment.

The morbidity and mortality of invasive fungal infections are rising gradually. In recent years, fungi have quietly evolved stronger defense capabilities and increased resistance to antibiotics, posing huge challenges to maintaining physical health. Therefore, developing new drugs and strategies to combat these invasive fungi is crucial. There are a large number of microorganisms in the intestinal tract of mammals, collectively referred to as intestinal microbiota. At the same time, these native microorganisms co-evolve with their hosts in symbiotic relationship. Recent researches have shown that some probiotics and intestinal symbiotic bacteria can inhibit the invasion and colonization of fungi. In this paper, we review the mechanism of some intestinal bacteria affecting the growth and invasion of fungi by targeting the virulence factors, quorum sensing system, secreting active metabolites or regulating the host anti-fungal immune response, so as to provide new strategies for resisting invasive fungal infection.

Inhibitory effects of a maleimide compound on the virulence factors of Candida albicans.

Candidiasis caused by Candida albicans infection has long been a serious human health problem. The pathogenicity of C. albicans is mainly due to its virulence factors, which are novel targets of antifungal drugs for low risk of resistance development. In this study, we identified a maleimide compound [1-(4-methoxyphenyl)-1hydro-pyrrole-2,5-dione, MPD] that exerts effective anti-virulence activity. It could inhibit the process of adhesion, filamentation, and biofilm formation in C. albicans. In addition, it exhibited low cytotoxicity, hemolytic activity, and drug resistance development. Moreover, in Galleria mellonella-C. albicans (in vivo) infection model, the survival time of infected larvae was significantly prolonged under the treatment of MPD. Further, mechanism research revealed that MPD increased farnesol secretion by upregulating the expression of Dpp3. The increased farnesol inhibited the activity of Cdc35, which then decreased the intracellular cAMP content resulting in the inhibition of virulence factors via the Ras1-cAMP-Efg1 pathway. In all, this study evaluated the inhibitory effect of MPD on various virulence factors of C. albicans and identified the underlying mechanisms. This suggests a potential application of MPD to overcome fungal infections in clinics.

Molecular mechanisms of glycogen particle assembly in Escherichia coli.

It has been reported that glycogen in Escherichia coli has two structural states, that is, fragility and stability, which alters dynamically. However, molecular mechanisms behind the structural alterations are not fully understood. In this study, we focused on the potential roles of two important glycogen degradation enzymes, glycogen phosphorylase (glgP) and glycogen debranching enzyme (glgX), in glycogen structural alterations. The fine molecular structure of glycogen particles in Escherichia coli and three mutants (ΔglgP, ΔglgX and ΔglgP/ΔglgX) were examined, which showed that glycogen in E. coli ΔglgP and E. coli ΔglgP/ΔglgX were consistently fragile while being consistently stable in E. coli ΔglgX, indicating the dominant role of GP in glycogen structural stability control. In sum, our study concludes that glycogen phosphorylase is essential in glycogen structural stability, leading to molecular insights into structural assembly of glycogen particles in E. coli.

Rapid identification of methicillin-resistant Staphylococcus aureus by MALDI-TOF MS: A meta-analysis.

Invasive infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with high mortality and morbidity. The sooner the pathogen is determined, the better it is beneficial to patient. However, routine laboratory inspections are time-consuming and laborious. A thorough research was conducted in PubMed and Web of Science (until June 2021) to identify studies evaluating the accuracy of MRSA identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). STATA 15.0 software was used to analyze the pooled results of sensitivity, specificity, and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) were utilized to show the overall performance of MALDI-TOF MS. Fifteen studies involving 2471 isolates were included in this study after the final selection in this meta-analysis. Using the random effects model forest plot to summarize the overall statistics, the sensitivity of MALDI-TOF MS for identifying MRSA was 92% (95% CI: 81%-97%), and the specificity was 97% (95% CI: 89%-99%). In the SROC curve, the AUC reached 0.99 (95% CI: 97%-99%). Deeks' test showed no significant publication bias in this meta-analysis. Compared with clinical reference methods, MALDI-TOF MS identification of MRSA shows a higher degree of sensitivity and specificity.

Machine learning analysis of SERS fingerprinting for the rapid determination of Mycobacterium tuberculosis infection and drug resistance.

Over the past decades, conventional methods and molecular assays have been developed for the detection of tuberculosis (TB). However, these techniques suffer limitations in the identification of Mycobacterium tuberculosis (Mtb), such as long turnaround time and low detection sensitivity, etc., not even mentioning the difficulty in discriminating antibiotics-resistant Mtb strains that cause great challenges in TB treatment and prevention. Thus, techniques with easy implementation for rapid diagnosis of Mtb infection are in high demand for routine TB diagnosis. Due to the label-free, low-cost and non-invasive features, surface enhanced Raman spectroscopy (SERS) has been extensively investigated for its potential in bacterial pathogen identification. However, at current stage, few studies have recruited handheld Raman spectrometer to discriminate sputum samples with or without Mtb, separate pulmonary Mtb strains from extra-pulmonary Mtb strains, or profile Mtb strains with different antibiotic resistance characteristics. In this study, we recruited a set of supervised machine learning algorithms to dissect different SERS spectra generated via a handheld Raman spectrometer with a focus on deep learning algorithms, through which sputum samples with or without Mtb strains were successfully differentiated (5-fold cross-validation accuracy = 94.32%). Meanwhile, Mtb strains isolated from pulmonary and extra-pulmonary samples were effectively separated (5-fold cross-validation accuracy = 99.86%). Moreover, Mtb strains with different drug-resistant profiles were also competently distinguished (5-fold cross-validation accuracy = 99.59%). Taken together, we concluded that, with the assistance of deep learning algorithms, handheld Raman spectrometer has a high application potential for rapid point-of-care diagnosis of Mtb infections in future.

Mitochondrial DNA polymorphisms in COX1 affect the lifespan of Caenorhabditis elegans through nuclear gene dct-15.

Mutations in the mitochondrial DNA (mtDNA) are closely related to age and age-related complex diseases, but the exact regulatory mechanism of mtDNA natural variation or polymorphism and ageing remains unclear. Recently, nuclear genes that regulate mitochondrial functions and thereby influence ageing have been widely studied. In this study, the relationship between the retrograde communication from the mitochondria to the nucleus and its ultimate effect on ageing has been elucidated. This study found that the natural variations in COX1 of the mitochondria in the Caenorhabditis elegans population do not correlate with multiple phenotypes, except for a mild correlation with lifespan. After excluding the differences in the nuclear genome, the correlation between natural mitochondrial variation and lifespan increased significantly. Moreover, mtDNA variation downregulated the nuclear dct-15 gene expression, which consequently reduced the lifespan, development rate and motility of C. elegans. dct-15 mutations decreased mitochondria copy number but increased ATP content and mitochondrial ultrastructure. Thus, the results indicated that dct-15 interacted with the mitochondrial DNA polymorphisms in COX1 and is associated with ageing. Finally, bioinformatic analyses revealed that mtDNA variation regulated the structural constituent of the cuticle via dct-15 and suggested that the structural constituent of the cuticle could have an important role in the development and ageing processes. These results provide insights into the mtDNA mechanism that can alter the nuclear gene and thereby regulate ageing and ageing-related diseases.

Seminal plasma extracellular vesicles tRF-Val-AAC-010 can serve as a predictive factor of successful microdissection testicular sperm extraction in patients with non-obstructive azoospermia.

BACKGROUND: There is a lack of biomarkers for distinguishing non-obstructive azoospermia (NOA) patients with successful sperm retrieval (Sp+) from those with failed sperm retrieval (Sp-). This study aimed to determine the potential of extracellular vesicles tRNA-derived small RNA (tsRNA) as a novel non-invasive biomarker for successful sperm retrieval by microdissection testicular sperm extraction (mTESE). METHODS: The study included 18 patients with NOA with successful sperm retrieval (Sp+) and 23 patients with NOA with failed sperm retrieval (Sp-), 15 obstructive azoospermia (OA) patients, 5 idiopathic oligospermia (IO) patients, and 12 healthy people. Seminal plasma extracellular vesicles tsRNA levels were used in a two-stage case-control study (screened by tsRNA sequencing on Illumina NextSeq instrument and validated by qRT-PCR). The bioinformatic analysis was performed to determine the role of tsRNA in the pathogenesis of non-obstructive azoospermia. RESULTS: Two tsRNAs (tRF-Val-AAC-010: AUC = 0.96, specificity = 80%, sensitivity = 95%; tRF-Pro-AGG-003: AUC = 0.96, specificity = 87%, sensitivity = 95%) were found to have high predictive accuracy for distinguishing the origin of azoospermia. In addition, the extracellular vesicles tRF-Val-AAC-010 resulted in high predictive ability (AUC = 0.89, sensitivity = 72%, specificity = 91%, P < 0.0001) in predicting the presence of sperm in non-obstructive azoospermia undergoing mTESE. Finally, bioinformatic analysis revealed that tRF-Val-AAC-010 were involved in spermatogenesis. CONCLUSIONS: This study identified that the extracellular vesicles tRF-Val-AAC-010 and tRF-Pro-AGG-003 are biomarkers for the diagnosis of non-obstructive azoospermia, and that tRF-Val-AAC-010 as a potential non-invasive biomarker for predicting the presence of sperm in non-obstructive azoospermia testicular tissue.

Interactions Between Intestinal Microbiota and Neural Mitochondria: A New Perspective on Communicating Pathway From Gut to Brain.

Many studies shown that neurological diseases are associated with neural mitochondrial dysfunctions and microbiome composition alterations. Since mitochondria emerged from bacterial ancestors during endosymbiosis, mitochondria, and bacteria had analogous genomic characteristics, similar bioactive compounds and comparable energy metabolism pathways. Therefore, it is necessary to rationalize the interactions of intestinal microbiota with neural mitochondria. Recent studies have identified neural mitochondrial dysfunction as a critical pathogenic factor for the onset and progress of multiple neurological disorders, in which the non-negligible role of altered gut flora composition was increasingly noticed. Here, we proposed a new perspective of intestinal microbiota - neural mitochondria interaction as a communicating channel from gut to brain, which could help to extend the vision of gut-brain axis regulation and provide additional research directions on treatment and prevention of responsive neurological disorders.

Circulatory exosomal tRF-Glu-CTC-005 and tRF-Gly-GCC-002 serve as predictive factors of successful microdissection testicular sperm extraction in patients with nonobstructive azoospermia.

OBJECTIVE: To identify circulating plasma exosomal transfer RNA-derived fragments (tRFs) as the predictive factors of successful microdissection testicular sperm extraction (micro-TESE) in patients with nonobstructive azoospermia (NOA). DESIGN: Case and control prospective study. SETTING: Academic research laboratory. PATIENT(S): Twelve patients with NOA with successful sperm retrieval by micro-TESE, 18 patients with NOA with failed sperm retrieval by micro-TESE, and 12 normozoospermic fertile controls. INTERVENTION(S): Blood samples were collected from participants. MAIN OUTCOME MEASURE(S): The abundance of tRFs normalized as counts per million of the total aligned reads with the next-generation sequencing system; candidate tRF levels were validated through quantitative reverse transcription polymerase chain reaction; predictive accuracy was evaluated by the receiver operating characteristic area under the curve analysis. The nomogram was built for ranking. RESULT(S): The plasma circulating exosomal tRF-Gly-GCC-002 and tRF-Glu-CTC-005 manifested the most confident differential expression between patients with NOA with successful sperm retrieval by micro-TESE and patients with NOA with failed sperm retrieval by micro-TESE. The target gene prediction of these 2 tRFs followed by the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated the functional enrichment of neuroendocrine protein metabolism and striatum/subpallium development. The herpes simplex virus 1 infection pathway was also involved. The receiver operating characteristic area under the curve (AUC) analysis demonstrated a promising predictive accuracy: tRF-Gly-GCC-002, AUC of 0.921, and tRF-Glu-CTC-005, AUC of 0.954. A regression model was built and presented with the nomogram for further assessment. CONCLUSION(S): This study described the exosomal tRF-Gly-GCC-002 and tRF-Glu-CTC-005 expression values, indicated a promising predictive effect for accessibility of sperm retrieval through micro-TESE from patients with NOA, and highlighted tRF-Gly-GCC-002 and tRF-Glu-CTC-005 as useful biomarkers in patients with NOA seeking in vitro conception with their residual sperm.

Comparative Analysis of Machine Learning Algorithms on Surface Enhanced Raman Spectra of Clinical Staphylococcus Species.

Raman spectroscopy (RS) is a widely used analytical technique based on the detection of molecular vibrations in a defined system, which generates Raman spectra that contain unique and highly resolved fingerprints of the system. However, the low intensity of normal Raman scattering effect greatly hinders its application. Recently, the newly emerged surface enhanced Raman spectroscopy (SERS) technique overcomes the problem by mixing metal nanoparticles such as gold and silver with samples, which greatly enhances signal intensity of Raman effects by orders of magnitudes when compared with regular RS. In clinical and research laboratories, SERS provides a great potential for fast, sensitive, label-free, and non-destructive microbial detection and identification with the assistance of appropriate machine learning (ML) algorithms. However, choosing an appropriate algorithm for a specific group of bacterial species remains challenging, because with the large volumes of data generated during SERS analysis not all algorithms could achieve a relatively high accuracy. In this study, we compared three unsupervised machine learning methods and 10 supervised machine learning methods, respectively, on 2,752 SERS spectra from 117 Staphylococcus strains belonging to nine clinically important Staphylococcus species in order to test the capacity of different machine learning methods for bacterial rapid differentiation and accurate prediction. According to the results, density-based spatial clustering of applications with noise (DBSCAN) showed the best clustering capacity (Rand index 0.9733) while convolutional neural network (CNN) topped all other supervised machine learning methods as the best model for predicting Staphylococcus species via SERS spectra (ACC 98.21%, AUC 99.93%). Taken together, this study shows that machine learning methods are capable of distinguishing closely related Staphylococcus species and therefore have great application potentials for bacterial pathogen diagnosis in clinical settings.

Multi-biomarker is an early-stage predictor for progression of Coronavirus disease 2019 (COVID-19) infection.

Coronavirus disease 2019 (COVID-19) has spread widely in the communities in many countries. Although most of the mild patients could be cured by their body's ability to self-heal, many patients quickly progressed to severe disease and had to undergo treatment in the intensive care unit (ICU). Thus, it is very important to effectively predict which patients with mild disease are more likely to progress to severe disease. A total of 72 patients hospitalized with COVID-19 in Shandong Provincial Public Health Clinical Center and 1141 patients included in the published papers were enrolled in this study. We determined that the combination of interleukin-6 (IL-6), Neutrophil (NEUT), and Natural Killer (NK) cells had the highest prediction accuracy (with 75% sensitivity and 95% specificity) for progression of COVID-19 infection. A binomial regression equation that accounted for a multiple risk score for the combination of IL-6, NEUT, and NK was also established. The multiple risk score is a good indicator for early stratification of mild patients into risk categories, which is very important for adjusting the treatment plan and preventing death.

Discovery of an orally active antitumor agent that induces apoptosis and suppresses EMT through heat shock protein 90 inhibition.

Background Nowadays, lung cancer seriously affects human health in the world. Therefore, it is of great significance to develop effective anti-lung cancer drugs. Methods In this work, chalcone derivative HYQ97 was designed via a molecular hybridization strategy. It was synthesized by the cycloaddition in the presence of sodium ascorbate under mild conditions. Lung cancer cell lines were cultured to investigate its antitumor effects in vitro and in vivo. Results HYQ97 inhibited the proliferation of lung cancer cell lines. Specifically, its IC50 value against lung cancer A549 cells was 74.26 nM. It could inhibit heat shock protein 90 (Hsp90) and degrade its client proteins in a dose-dependent manner. Furthermore, HYQ97 suppressed the epithelial mesenchymal transition process and induced apoptosis of A549 cells. Importantly, HYQ97 also had significant inhibitory effects on tumor growth in vivo. Conclusions Chalcone derivative HYQ97 is a promising candidate for lung cancer treatment.

Investigation into archaeal extremophilic lifestyles through comparative proteogenomic analysis.

Archaea are a group of primary life forms on Earth and could thrive in many unique environments. Their successful colonization of extreme niches requires corresponding adaptations at proteogenomic level in order to maintain stable cellular structures and active physiological functions. Although some studies have already investigated the extremophilic lifestyles of archaeal species based on genomic features and protein structures, there is a lack of comparative proteogenomic analysis in a large scale. In this study, we explored 686 high-quality archaeal genomes (proteomes) sourced from the Pathosystems Resource Integration Center (PATRIC) database. General patterns of genomic features such as genome size, coding capacity (coding genes and non-coding regions), and G + C contents were re-confirmed. Protein domain distribution patterns were then identified across archaeal species. Domains with unknown functions (DUFs) and mini proteins were investigated in terms of their distributions due to their importance in archaeal physiological functions. In addition, physicochemical properties of protein sequences, such as stability, hydrophobicity, isoelectric point, aromaticity and amino acid compositions in corresponding archaeal groups were compared. Unique features associated with extremophilic lifestyles were observed, which suggested that evolutionary adaptations to different extreme environments had intrinsic impacts on archaeal protein features. Taken together, this systematic study facilitates a better understanding of the mechanisms behind the extremophilic lifestyles of archaeal species, which will further contribute to the evolutionary explorations of archaeal adaptations both experimentally and theoretically in the future studies.Communicated by Ramaswamy H. Sarma.

Comparative genome analysis of 12 Shigella sonnei strains: virulence, resistance, and their interactions.

Shigellosis is a highly infectious disease that is mainly transmitted via fecal-oral contact of the bacteria Shigella. Four species have been identified in Shigella genus, among which Shigella flexneri is used to be the most prevalent species globally and commonly isolated from developing countries. However, it is being replaced by Shigella sonnei that is currently the main causative agent for dysentery pandemic in many emerging industrialized countries such as Asia and the Middle East. For a better understanding of S. sonnei virulence and antibiotic resistance, we sequenced 12 clinical S. sonnei strains with varied antibiotic-resistance profiles collected from four cities in Jiangsu Province, China. Phylogenomic analysis clustered antibiotic-sensitive and resistant S. sonnei into two distinct groups while pan-genome analysis reveals the presence and absence of unique genes in each group. Screening of 31 classes of virulence factors found out that type 2 secretion system is doubled in resistant strains. Further principle component analysis based on the interactions between virulence and resistance indicated that abundant virulence factors are associated with higher levels of antibiotic resistance. The result present here is based on statistical analysis of a small sample size and serves basically as a guidance for further experimental and theoretical studies.

Kalopanaxsaponin A induces reactive oxygen species mediated mitochondrial dysfunction and cell membrane destruction in Candida albicans.

Candidiasis causes high morbidity and mortality among immunocompromised patients. Antifungal drug resistance and cytotoxicity highlight the need of effective antifungal therapeutics. In this study, we found that kalopanaxsaponin A (KPA), a triterpenoid saponin natural product, could inhibit the proliferation of various Candida species, and exerted a fungicidal effect against C. albicans. To further explore its antifungal action mode, spectrofluorophotometer, fluorescence microscopy and transmission electron microscopy were performed, showing that KPA treatment induced the accumulation of intracellular reactive oxygen species (ROS), resulting in mitochondrial dysfunction. Meanwhile, KPA treatment also broke down the membrane barrier of C. albicans causing the leakage of intracellular trehalose, the entrance of extracellular impermeable substance and the decrease of ergosterol content. Both ROS accumulation and membrane destruction contributed to the death of C. albicans cells. Our work preliminarily elucidated the potential mechanisms of KPA against C. albicans on a cellular level, and might provide a potential option for the treatment of clinical candidiasis.