Our group previously investigated the levels of anti-Gal and anti-nonGal IgM and IgG in a cohort of 75 healthy humans of various backgrounds, and found some significant differences related to factors such as age, gender, ABO blood group, diet, vaccination history, and geographic location during childhood. We have now expanded our cohort (n = 84) to investigate the levels of anti-Neu5Gc and anti-nonGal/nonNeu5Gc antibodies in healthy humans. Anti-nonGal and anti-nonGal/nonNeu5Gc human IgM and IgG binding to pRBCs and pAECs from GTKO/CD46 and GTKO/CD46/Neu5GcKO pigs were measured by flow cytometry. Anti-Gal and anti-Neu5Gc IgM and IgG levels were measured by ELISA. In summary, (i) the great majority (almost 100%) of humans had anti-Neu5Gc IgM and IgG antibodies that bound to pAECs and approximately 50% had anti-Neu5Gc antibodies that bound to pRBCs, (ii) there was significantly less human antibody binding to pig cells that did not express either Gal or Neu5Gc compared with those that did not express Gal alone, (iii) the levels of both IgM and IgG binding to GTKO/CD46/Neu5GcKO pRBCs and pAECs were low, (iv) the level of anti-Neu5Gc IgG was higher in men than women, (v) the level did not change with age or diet, and there was some variability associated with (vi) previous vaccination history and (vii) the geographic region in which the individual spent his or her childhood. Our study confirms that human antibody binding to RBCs and AECs from GTKO/CD46/Neu5GcKO pigs is greatly reduced compared to binding to GTKO/CD46 cells. However, all humans appear to have a low level of antibody that binds to pAECs that is not directed to either Gal or Neu5Gc. Our findings require consideration in planning clinical trials of xenotransplantation.

Cisplatin is a first-line chemotherapy drug that is commonly used in the treatment of epithelial ovarian cancer (EOC). However, insensitivity to cisplatin markedly influences the outcomes of chemotherapy. MicroRNAs (miRNAs/miRs) have been demonstrated to modulate drug resistance in a number of types of cancer. The aim of the present study was to investigate the key miRNAs involved in modulating drug resistance in ovarian cancer cells. miR-200b and miR-200c were identified to be frequently deregulated in ovarian cancer. Upregulation of miR-200b and miR-200c promoted EOC cell death in the presence of cisplatin. Upregulation of miR-125b-5p significantly decreased tumor growth in combination with cisplatin in a mouse model. Significantly, miR-200b and miR-200c reversed cisplatin resistance by targeting DNA methyltransferases (DNMTs) (directly targeting DNMT3A/DNMT3B and indirectly targeting DNMT1 via specificity protein 1). These results indicate that miR-200b- and miR-200c-mediated regulation of DNMTs serves a crucial function in the cellular response to cisplatin. miR-200b- and miR-200c-mediated downregulation of DNMTs may improve chemotherapeutic efficacy by increasing the sensitivity of cancer cells and thus may have an impact on ovarian cancer therapy.

Sister chromatid cohesion plays a key role in ensuring precise chromosome segregation during mitosis, which is mediated by the multisubunit cohesin complex. However, the molecular regulation of cohesin subunits stability remains unclear. Here, we show that NudCL2 (NudC-like protein 2) is essential for the stability of cohesin subunits by regulating Hsp90 ATPase activity in mammalian cells. Depletion of NudCL2 induces mitotic defects and premature sister chromatid separation and destabilizes cohesin subunits that interact with NudCL2. Similar defects are also observed upon inhibition of Hsp90 ATPase activity. Interestingly, ectopic expression of Hsp90 efficiently rescues the protein instability and functional deficiency of cohesin induced by NudCL2 depletion, but not vice versa. Moreover, NudCL2 not only binds to Hsp90, but also significantly modulates Hsp90 ATPase activity and promotes the chaperone function of Hsp90. Taken together, these data suggest that NudCL2 is a previously undescribed Hsp90 cochaperone to modulate sister chromatid cohesion by stabilizing cohesin subunits, providing a hitherto unrecognized mechanism that is crucial for faithful chromosome segregation during mitosis.Electronic supplementary materialThe online version of this article (10.1007/s00018-018-2957-y) contains supplementary material, which is available to authorized users.

PurposeTo test if a RapidPlan DVH estimation model and its training plans can be improved interactively through a closed‐loop evolution process.Methods and materialsEighty‐one manual plans (P0) that were used to configure an initial rectal RapidPlan model (M0) were reoptimized using M0 (closed‐loop), yielding 81 P1 plans. The 75 improved P1 (P1+) and the remaining 6 P0 were used to configure model M1. The 81 training plans were reoptimized again using M1, producing 23 P2 plans that were superior to both their P0 and P1 forms (P2+). Hence, the knowledge base of model M2 composed of 6 P0, 52 P1+, and 23 P2+. Models were tested dosimetrically on 30 VMAT validation cases (Pv) that were not used for training, yielding Pv(M0), Pv(M1), and Pv(M2) respectively. The 30 Pv were also optimized by M2_new as trained by the library of M2 and 30 Pv(M0).ResultsBased on comparable target dose coverage, the first closed‐loop reoptimization significantly (P < 0.01) reduced the 81 training plans’ mean dose to femoral head, urinary bladder, and small bowel by 2.65 Gy/15.63%, 2.06 Gy/8.11%, and 1.47 Gy/6.31% respectively, which were further reduced significantly (P < 0.01) in the second closed‐loop reoptimization by 0.04 Gy/0.28%, 0.18 Gy/0.77%, 0.22 Gy/1.01% respectively. However, open‐loop VMAT validations displayed more complex and intertwined plan quality changes: mean dose to urinary bladder and small bowel decreased monotonically using M1 (by 0.34 Gy/1.47%, 0.25 Gy/1.13%) and M2 (by 0.36 Gy/1.56%, 0.30 Gy/1.36%) than using M0. However, mean dose to femoral head increased by 0.81 Gy/6.64% (M1) and 0.91 Gy/7.46% (M2) than using M0. The overfitting problem was relieved by applying model M2_new.ConclusionsThe RapidPlan model and its constituent plans can improve each other interactively through a closed‐loop evolution process. Incorporating new patients into the original training library can improve the RapidPlan model and the upcoming plans interactively.

Background: In spinal cord injury (SCI), systemic inflammation and the death of nerve cells in the spinal cord are life threatening. The connection between gut microbiota and signaling pathways has been a hot research topic in recent years. The Toll-like receptor 4/Myeloid differentiation factor 88 (TLR4/MyD88) signaling pathway is closely related to the inflammatory response. This study explored whether the gut microbiota imbalance could affect the TLR4/MyD88 signaling pathway to regulate SCI to provide a new basis for SCI research and treatment.Methods: An SCI model was constructed to study the influence on the injury of gut microbiota. 16S amplicon sequencing was used to identify the diversity and abundance of gut microbes. Fecal microbiota transplantation was performed in mice with SCI. ELISA was used to detect the serum levels of pro-inflammatory and anti-inflammatory factors in mice. Hematoxylin and eosin staining was used to observe SCI in mice. Immunofluorescence was used to detect the rates of loss glial fibrillary acidic protein (GFAP), neuronal nuclear protein (NeuN), and ionized calcium-binding adapter molecule 1 (IBA1) in the spinal cord as indicators of apoptosis. The expression of the TLR4/MyD88 signaling pathway was detected by qRT-PCR and western blotting.Results: Significant differences were observed in the gut microbiota of SCI mice and normal mice. The gut microbiota of SCI mice was imbalanced. The levels of pro-inflammatory cytokines tumor necrosis factor-α, interleukin (IL)-1β, and IL-6 in SCI mice were increased, as was the level of the toxic induced nitric oxide synthase. The levels of anti-inflammatory factors IL-4, transforming growth factor-β, and IL-10 were decreased, as was the level of arginase-1. The apoptosis rates of GFAP, NeuN, and IBA1 were increased. The TLR4/MyD88 signaling pathway was activated. In the SCI group, inflammation increased after fecal transplantation, apoptosis of GFAP, NeuN, and IBA1 increased, and SCI was more serious.Conclusion: The TLR4/MyD88 signaling pathway promotes the death of nerve cells by inducing inflammation. Gut microbiota dysregulation can lead to aggravated SCI by activating the TLR4/MyD88 signaling pathway.

The interactive adjustment of the optimization objectives during the treatment planning process has made it difficult to evaluate the impact of beam quality exclusively in radiotherapy. Without consensus in the published results, the arbitrary selection of photon energies increased the probability of suboptimal plans. This work aims to evaluate the dosimetric impact of various photon energies on the sparing of normal tissues by applying a preconfigured knowledge-based planning (RapidPlan) model to various clinically available photon energies for rectal cancer patients, based on model-generated optimization objectives, which provide a comparison basis with less human interference. A RapidPlan model based on 81 historical VMAT plans for pre-surgical rectal cancer patients using 10MV flattened beam (10X) was used to generate patient-specific objectives for the automated optimization of other 20 patients using 6X, 8X, 10X (reference), 6MV flattening-filter-free (6F) and 10F beams respectively on a TrueBeam accelerator. It was observed that flattened beams produced very comparable target dose coverage yet the conformity index using 6F and 10F were clinically unacceptable (>1.29). Therefore, dose to organs-at-risk (OARs) and normal tissues were only evaluated for flattened beams. RapidPlan-generated objectives for 6X and 8X beams can achieve comparable target dose coverage as that of 10X, yet the dose to normal tissues increased monotonically with decreased energies. Differences were statistically significant except femoral heads. From the radiological perspective of view, higher beam energy is still preferable for deep seated tumors, even if multiple field entries such as VMAT technique can accumulate enough dose to the target using lower energies, as reported in the literature. In conclusion, RapidPlan model configured for flattened beams cannot optimize un-flattened beams before adjusting the target objectives, yet works for flattened beams of other energies. For the investigated 10X, 8X and 6X photons, higher energies provide better normal tissue sparing.

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Objective. To establish an open framework for developing plan optimization models for knowledge-based planning (KBP). Approach. Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. Main results. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50–0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P < 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model. Significance. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.