These results demonstrate that there are numerous miRNAs in human follicular fluids, some of which play important roles in steroidogenesis and PCOS. This study substantially revises our understanding of the content of human follicular fluid and lays the foundation for the future investigation of the role of miRNAs in PCOS.

Bacterial vaginosis (BV) is the most common vaginal infection found inwomen in the world. Due to increasing drug-resistance of virulent pathogen such as Gardnerella vaginalis (G. vaginalis), more than half of BV patients suffer recurrence after antibotics treatment. Here, metastable iron sulfides (mFeS) act in a Gram-dependent manner to kill bacteria, with the ability to counteract resistant G. vaginalis for BV treatment. With screening of iron sulfide minerals, metastable Fe 3 S 4 shows suppressive effect on bacterial growth with an order: Gram-variable G. vaginalis >Gram-negative bacteria>> Gram-positive bacteria. Further studies on mechanism of action (MoA) discover that the polysulfide species released from Fe 3 S 4 selectively permeate bacteria with thin wall and subsequently interrupt energy metabolism by inhibiting glucokinase in glycolysis, and is further synergized by simultaneously released ferrous iron that induces bactericidal damage. Such multiple MoAs enable Fe 3 S 4 to counteract G. vaginalis strains with metronidazole-resistance and persisters in biofilm or intracellular vacuole, without developing new drug resistance and killing probiotic bacteria. The Fe 3 S 4 regimens successfully ameliorate BV with resistant G. vaginalis in mouse models and eliminate pathogens from patients suffering BV. Collectively, mFeS represent an antibacterial alternative with distinct MoA able to treat challenged BV and improve women health.

We provide the first report that LTL is strongly associated with PCOS. This study suggests a new role for LTL in the pathophysiology of PCOS and might have important implications for our understanding of the etiology of the disease.

Background Spinal cord injury (SCI) is an inflammatory condition, and excessive adenosine triphosphate (ATP) is released into the extracellular space, which can be catabolized into adenosine by CD73. Extracellular vesicles have been designed as nano drug carriers in many diseases. However, their impacts on delivery of CD73 after SCI are not yet known. We aimed to construct CD73 modified extracellular vesicles and explore the anti-inflammatory effects after SCI. Methods CD73 engineered extracellular vesicles (CD73+ hucMSC-EVs) were firstly established, which were derived from human umbilical cord mesenchymal stem cells (hucMSCs) transduced by lentiviral vectors to upregulate the expression of CD73. Effects of CD73+ hucMSC-EVs on hydrolyzing ATP into adenosine were detected. The polarization of M2/M1 was verified by immunofluorescence. Furthermore, A2aR and A2bR inhibitors and A2bR knockdown cells were used to investigate the activated adenosine receptor. Biomarkers of microglia and levels of cAMP/PKA were also detected. Repetitively in vivo study, morphology staining, flow cytometry, cytokine analysis, and ELISA assay, were also applied for verifications. Results CD73+ hucMSC-EVs reduced concentration of ATP and promoted the level of adenosine. In vitro experiments, CD73+ hucMSC-EVs increased macrophages/microglia M2:M1 polarization, activated adenosine 2b receptor (A2bR), and then promoted cAMP/PKA signaling pathway. In mice using model of thoracic spinal cord contusion injury, CD73+ hucMSC-EVs improved the functional recovery after SCI through decreasing the content of ATP in cerebrospinal fluid and improving the polarization from M1 to M2 phenotype. Thus, the cascaded pro-inflammatory cytokines were downregulated, such as TNF-α, IL-1β, and IL-6, while the anti-inflammatory cytokines were upregulated, such as IL-10 and IL-4. Conclusions CD73+ hucMSC-EVs ameliorated inflammation after spinal cord injury by reducing extracellular ATP, promoting A2bR/cAMP/PKA pathway and M2/M1 polarization. CD73+ hucMSC-EVs might be promising nano drugs for clinical application in SCI therapy. Graphical Abstract

Machine learning (ML), as an advanced domain of artificial intelligence (AI), is progressively changing our view of the world. By implementing its algorithms, our ability to detect previously undiscoverable patterns in data has the potential to revolutionize predictive analytics. Scoliosis, as a relatively specialized branch in the spine field, mainly covers the pediatric, adult and the elderly populations, and its diagnosis and treatment remain difficult. With recent efforts and interdisciplinary cooperation, ML has been widely applied to investigate issues related to scoliosis, and surprisingly augment a surgeon's ability in clinical practice related to scoliosis. Meanwhile, ML models penetrate in every stage of the clinical practice procedure of scoliosis. In this review, we first present a brief description of the application of ML in the clinical practice procedures regarding scoliosis, including screening, diagnosis and classification, surgical decision making, intraoperative manipulation, complication prediction, prognosis prediction and rehabilitation. Meanwhile, the ML models and specific applications adopted are presented. Additionally, current limitations and future directions are briefly discussed regarding its use in the field of scoliosis. We believe that the implementation of ML is a promising revolution to assist surgeons in all aspects of clinical practice related to scoliosis in the near future.