Magnetic soft microfiberbots for robotic embolization.

Cerebral aneurysms and brain tumors are leading life-threatening diseases worldwide. By deliberately occluding the target lesion to reduce the blood supply, embolization has been widely used clinically to treat cerebral aneurysms and brain tumors. Conventional embolization is usually performed by threading a catheter through blood vessels to the target lesion, which is often limited by the poor steerability of the catheter in complex neurovascular networks, especially in submillimeter regions. Here, we propose magnetic soft microfiberbots with high steerability, reliable maneuverability, and multimodal shape reconfigurability to perform robotic embolization in submillimeter regions via a remote, untethered, and magnetically controllable manner. Magnetic soft microfiberbots were fabricated by thermal drawing magnetic soft composite into microfibers, followed by magnetizing and molding procedures to endow a helical magnetic polarity. By controlling magnetic fields, magnetic soft microfiberbots exhibit reversible elongated/aggregated shape morphing and helical propulsion in flow conditions, allowing for controllable navigation through complex vasculature and robotic embolization in submillimeter regions. We performed in vitro embolization of aneurysm and tumor in neurovascular phantoms and in vivo embolization of a rabbit femoral artery model under real-time fluoroscopy. These studies demonstrate the potential clinical value of our work, paving the way for a robotic embolization scheme in robotic settings.

Fiberbots: Robotic fibers for high-precision minimally invasive surgery.

Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber. The fiber robot was fabricated by highly scalable fiber drawing technology using common low-cost materials. This low-profile (below 2 millimeters in diameter) robotic fiber exhibits remarkable motion precision (below 50 micrometers) and repeatability. We developed control algorithms coupling the robot with endoscopic instruments, demonstrating high-resolution in situ molecular and morphological tissue mapping. We assess its practicality and safety during in vivo laparoscopic surgery on a porcine model. High-precision motion of the fiber robot delivered endoscopically facilitates the effective use of cellular-level intraoperative tissue identification and ablation technologies, potentially enabling precise removal of cancer in challenging surgical sites.

Chemical Constituents from Berchemia polyphylla var. Leioclada.

One previously undescribed naphthoquinone-benzisochromanquinone dimer berpolydiquinone A (1), along with two previously undescribed naphthoquinone-anthraquinone dimers berpolydiquinones B and C (2-3), and one previously undescribed dimeric naphthalene berpolydinaphthalene A (4), were isolated from the stems and leaves of Berchemia polyphylla var. leioclada. The chemical structures of these compounds were determined using high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS), spectroscopic data, the exciton chirality method (ECM), and quantum chemical calculation. Notably, compounds (1-2 and 5) are dimeric quinones that share the same naphthoquinone moiety, specifically identified as 2-methoxystypandron. Compound (4) is a derivative of dimeric naphthalene with a symmetrical structure, which is a new structure type isolated from B. polyphylla var. leioclada for the first time. These findings suggest that B. polyphylla var. leioclada serves as a significant reservoir of structurally diverse phenolic compounds. This study provides a scientific foundation for regarding B. polyphylla var. leioclada as a potential source of "Tiebaojin".

A composition of ursolic acid derivatives from Ludwigia hyssopifolia induces apoptosis in throat cancer cells via the Akt/mTOR and mitochondrial signaling pathways and by modulating endoplasmic reticulum stress.

ETHNOPHARMACOLOGICAL RELEVANCE: Ludwigia hyssopifolia (LH), an ethnopharmacological herb used in Guangxi Zhuang medicine, is known for its extensive therapeutic use in treating throat disorders. The anti-laryngeal-cancer benefits of the ethyl acetate and petroleum ether fractions of the ethanolic extracts of LH have been shown in our prior cell-based research. Nevertheless, the specific impacts and underlying processes by which LH combats throat cancer effects have not been fully understood. AIM OF THE STUDY: This study involved the extraction of a composition containing two derivatives of ursolic acid from LH (LH-CUAD). The present study aimed to assess the anti-throat-cancer effects of these derivatives and the underlying mechanisms through in vitro and in vivo experiments. MATERIALS AND METHODS: Solvent extraction, fractionation, chromatography, and semipreparative high-performance liquid chromatography were used for the extraction, purification, and analysis of LH-CUAD. The in vitro and in vivo anti-throat-cancer effects of LH-CUAD were investigated using the throat cancer cell lines Hep-2 and FaDu as well as Hep-2 tumor-bearing nude mice. RESULTS: LH-CUAD significantly inhibited the proliferation and migration of throat cancer cells without any prominent toxicity. The Hoechst 33258 staining, Annexin V-FITC/PI double-staining assays, and flow cytometry confirmed that LH-CUAD could induce throat cancer cell death from early to late apoptosis in vitro. LH-CUAD exhibited significant antitumor activity and low toxicity in a xenograft model, and induced throat cancer cells apoptosis in vivo. The apoptotic effects of LH-CUAD therapy were validated using Western blotting, which demonstrated the activation of a caspase cascade response triggered by an imbalance between the endoplasmic reticulum and mitochondria. In addition, it was observed that LH-CUAD exhibited inhibitory effects on Akt and mTOR phosphorylation, hence promoting apoptosis. CONCLUSIONS: LH-CUAD induces apoptosis in both in vivo and in vitro models of throat cancer. This effect is achieved by activating the mitochondrial pathway, inhibiting the Akt/mTOR pathway and initiating endoplasmic reticulum stress. The findings of this study suggest that LH-CUAD has the potential to offer a novel approach to the clinical management of throat cancer.

A deep unrolled neural network for real-time MRI-guided brain intervention.

Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI). Here, we proposed a deep unrolled neural network, dubbed as LSFP-Net, for real-time i-MRI reconstruction. By integrating LSFP-Net and a custom-designed, MR-compatible interventional device into a 3 T MRI scanner, a real-time MRI-guided brain intervention system is proposed. The performance of the system was evaluated using phantom and cadaver studies. 2D/3D real-time i-MRI was achieved with temporal resolutions of 80/732.8 ms, latencies of 0.4/3.66 s including data communication, processing and reconstruction time, and in-plane spatial resolution of 1 × 1 mm2. The results demonstrated that the proposed method enables real-time monitoring of the remote-controlled brain intervention, and showed the potential to be readily integrated into diagnostic scanners for image-guided neurosurgery.

Anthraquinone-benzisochromanquinone dimers from the stems and leaves of Berchemia polyphylla.

Three new anthraquinone-benzisochromanquinone dimers polyphylldiquinones A-C (1-3), along with three known analogs floribundiquinone A-B (4-5) and 7-dehydroxyventiloquinone H (6), were isolated from the stems and leaves of Berchemia polyphylla. The chemical structures and absolute configurations of these compounds were determined using HR-ESI-MS, spectroscopic data, and electronic circular dichroism. Notably, compounds (1-5) are dimeric quinones that share the same benzisochromanquinone moiety, specifically identified as 7-dehydroxyventiloquinone H (6), which was the first time to report as a natural product. Compounds 1-2 and compounds 4-5 are two pairs of atropisomers respectively.

Garbractin A, a Polycyclic Polyprenylated Acylphloroglucinol with a 4,11-dioxatricyclo[4.4.2.01,5]Dodecane Skeleton from Garcinia bracteata Fruits.

Garbractin A (1), a structurally complicated polycyclic polyprenylated acylphloroglucinol (PPAP) with an unprecedented 4,11-dioxatricyclo[4.4.2.01,5] dodecane skeleton, was isolated from the fruits of Garcinia bracteata, along with five new biosynthetic analogues named garcibracteatones A-E (2-6). Their structures containing absolute configurations were revealed using spectroscopic data, the residual dipolar coupling-enhanced NMR approach, and quantum chemical calculations. The antihyperglycemic effect of these PPAPs (1-6) was evaluated using insulin-resistant HepG2 cells (IR-HepG2 cells) induced through palmitic acid (PA). Compounds 1, 3, and 4 were found to significantly promote glucose consumption in the IR-HepG2 cells and, therefore, may hold potential as candidates for treating hyperglycemia.

Isolation and antihyperglycemic effects of garcibractinols A-H, intricate polycyclic polyprenylated acylphloroglucinols from the fruits of Garcinia bracteata.

Eight previously undescribed polycyclic polyprenylated acylphloroglucinols (PPAPs) were isolated from the fruits of Garcinia bracteata and named garcibractinols A-H. Garcibractinols A-F (compounds 1-6) were bicyclic polyprenylated acylphloroglucinols (BPAPs) sharing a rare bicyclo[4.3.1]decane core. On the other hand, garcibractinols G and H (compounds 7 and 8) shared an unprecedented BPAP skeleton bearing a 9-oxabicyclo[6.2.1]undecane core. The structures andabsolute configurations of compounds 1-8 were determined by spectroscopic analysis,single-crystal X-ray diffraction analysis, and quantum chemical calculation. The breakage of the C-3/C-4 linkage through the retro-Claisen reaction was a key step in the biosynthesis of compounds 7 and 8. The antihyperglycemic effects of the eight compounds were evaluated in insulin-resistant HepG2 cells. At a concentration of 10 µM, compounds 2 and 5-8 significantly increased the glucose consumption in the HepG2 cells. Furthermore, compound 7 was more effective than metformin (which was used as a positive control) in promoting glucose consumption in the cells. The findings of this study suggest that compounds 2 and 5-8 have anti-diabetic effects.

Correction: Polycyclic polyprenylated acylphloroglucinols from Garcinia xanthochymus fruits exhibit antitumor effects through inhibition of the STAT3 signaling pathway.

Correction for 'Polycyclic polyprenylated acylphloroglucinols from Garcinia xanthochymus fruits exhibit antitumor effects through inhibition of the STAT3 signaling pathway' by Jing Xu et al., Food Funct., 2020, 11, 10568-10579, https://doi.org/10.1039/D0FO02535F.

Impact of dialysis dependence on survival for multiple myeloma with renal impairment: a multicenter study in China.

Renal impairment (RI) is a very common complication of multiple myeloma (MM) with a negative impact on survival. Herein we retrospectively analyzed 334 MM patients with renal impairment at diagnosis from three hospitals in China. All 334 patients were divided into three groups, including dialysis dependence (n=43), dialysis independence (n=42), and without dialysis (n=249). Compared with dialysis independence and without dialysis groups, dialysis dependence group had the lowest overall hematologic response (48.8% vs. 97.6% vs. 77.1%, P<0.001) and overall renal response (0.0% vs. 97.6% vs. 72.7%, P<0.001), as well as the highest early mortality within 24 months (50.0% vs. 24.4% vs. 26.3%, P=0.006). Dialysis dependence group had similar progression-free survival (24 vs. 26 vs. 27 months, P=0.231) and significantly shorter overall survival (25 vs. 69 vs. 45 months, P=0.001). Dialysis dependence was independently associated with high mortality within 24 months and shorter overall survival. In conclusion, MM patients with dialysis dependence still tend to suffer a dismal disease course, including a high probability to suffer early mortality, worse hematological and renal response, as well as shorter survival. Dialysis independence could be very promising for survival improvement.

Contrastive Adversarial Learning for Endomicroscopy Imaging Super-Resolution.

Endomicroscopy is an emerging imaging modality for real-time optical biopsy. One limitation of existing endomicroscopy based on coherent fibre bundles is that the image resolution is intrinsically limited by the number of fibres that can be practically integrated within the small imaging probe. To improve the image resolution, Super-Resolution (SR) techniques combined with image priors can enhance the clinical utility of endomicroscopy whereas existing SR algorithms suffer from the lack of explicit guidance from ground truth high-resolution (HR) images. In this article, we propose an unsupervised SR pipeline to allow stable offline and kernel-generic learning. Our method takes advantage of both internal statistics and external cross-modality priors. To improve the joint learning process, we present a Sharpness-aware Contrastive Generative Adversarial Network (SCGAN) with two dedicated modules, a sharpness-aware generator and a contrastive-learning discriminator. In the generator, an auxiliary task of sharpness discrimination is formulated to facilitate internal learning by considering the rankings of training instances in various sharpness levels. In the discriminator, we design a contrastive-learning module to mitigate the ill-posed nature of SR tasks via constraints from both positive and negative images. Experiments on multiple datasets demonstrate that SCGAN reduces the performance gap between previous unsupervised approaches and the upper bounds defined in supervised settings by more than 50%, delivering a new state-of-the-art performance score for endomicroscopy super-resolution. Further application on a realistic Voronoi-based pCLE downsampling kernel proves that SCGAN attains PSNR of 35.851 dB, improving 5.23 dB compared with the traditional Delaunay interpolation.

Deep anatomy learning for lung airway and artery-vein modeling with contrast-enhanced CT synthesis.

PURPOSE: Endobronchial intervention requires detailed modeling of pulmonary anatomical substructure, such as lung airway and artery-vein maps, which are commonly extracted from non-contrast computed tomography (NCCT) independently using automatic segmentation approaches. We aim to make the first attempt to jointly train a CNN-based model for airway and artery-vein segmentation along with synthetic contrast-enhanced CT (CECT) generation. METHODS: A multi-task framework is proposed to simultaneously generate three segmentation maps and synthesize CECTs. We first design a collaborative learning model with tissue knowledge interaction for lung airway and artery-vein segmentation. Meanwhile, a conditional adversarial training strategy is applied to generate CECTs from NCCTs guided by artery maps. Additionally, CECT identity and reconstruction help to regularize the model for plausible NCCT to CECT translation. RESULTS: Extensive experiments were conducted to evaluate the performance of the proposed framework based on three datasets (90 NCCTs for the airway task, 55 NCCTs for the artery-vein task and 100 CECTs for the artery task). The results demonstrate the effective improvement of our proposed method compared to other methods and configurations that can achieve more accurate segmentation maps (Dice score coefficients for these three tasks are: 93.6%, 80.7% and 82.4%, respectively) and realistic CECTs simultaneously. The ablation study further verifies the effectiveness of the components of the designed model. CONCLUSION: This study demonstrates the model potential in multi-task learning that integrates anatomically relevant segmentation and performs NCCT to CECT translation. Such an interaction approach promotes mutually for both promising segmentation results and plausible synthesis.

Prognostic nomogram for multiple myeloma early relapse after autologous stem cell transplant in the novel agent era.

BACKGROUND: The present study intended to establish a predictive nomogram for early relapse (ER) (<12 months) after autologous stem cell transplantation (ASCT) in the novel drug era for multiple myeloma (MM). PATIENTS AND METHODS: The nomogram was designed and constructed to a retrospective clinical data of newly diagnosed MM patients received novel agent induction therapy and subsequent ASCT at three centers in China from July 2007 to December 2018. The retrospective study was conducted among 294 patients in the training cohort and 126 in the validation cohort. The nomogram's predictive accuracy was evaluated by the concordance index, calibration curve and decision clinical curve. RESULTS: The study cohort included 420 newly diagnosed MM patients, and 100 (23.8%) were identified as having ER, including 74 in the training cohort and 26 in the validation cohort. According to the result of multivariate regression in the training cohort, the prognostic variables included in the nomogram were high-risk cytogenetics, LDH > UNL, and response less than very good partial response (VGPR) after ASCT. The calibration curve showed good fitness between the nomogram predictions and the actual observations and the nomogram was further validated by a clinical decision curve. The nomogram's C-index achieved 0.75 (95% CI, 0.70-0.80), which was higher than that of the Revised International Staging System (R-ISS) (0.62), ISS (0.59), and Durie-Salmon (DS) staging system (0.52). The discrimination ability of the nomogram in the validation cohort was superior to that of the other staging systems (C-index: 0.73 vs. R-ISS (0.54), ISS (0.55), and DS staging system (0.53)). DCA showed the prediction nomogram adds much more clinical utility. Different scores of the nomogram draw a distinction of OS. CONCLUSION: The present nomogram could serve as a feasible and accurate prediction of ER in novel drug induction transplantation-eligible MM patients, which could help modify the post-ASCT strategy for patients at high risk of ER.

Characteristics and Risk Factors of Ultra-High-Risk Patients with Newly Diagnosed Multiple Myeloma.

OBJECTIVE: To investigate the clinical characteristics and risk factors of ultra-high-risk (UHR) patients with newly diagnosed multiple myeloma (MM). METHODS: We screened UHR patients with a survival of less than 24 months and we selected patients with a concurrent survival of more than 24 months as a control group. We retrospectively analyzed the clinical characteristics of UHR patients with newly diagnosed MM and screened related risk factors. RESULTS: In total we analyzed 477 patients, which included 121 (25.4%) UHR patients and 356 (74.6%) control patients. Median overall survival (OS) and progression-free survival (PFS) of UHR patients was 10.5 months (7.5-13.5 months) and 6.3 months (5.4-7.2 months), respectively. Univariate logistic regression analysis showed that age > 65 years, hemoglobin (HGB) < 100 g/L, lactate dehydrogenase (LDH) > 250 U/L, serum creatinine (SCr) > 2 mg/dL, corrected serum calcium (CsCa) > 2.75 mmol/L, B-type natriuretic peptide (BNP) or N-terminal prohormone BNP (NT-proBNP) > 2 upper limit of normal (ULN), high-risk cytogenetics, Barthel index score, and International Staging System (ISS) stage III were associated with UHR MM. In a multivariate analysis, age > 65 years, LDH > 250 U/L, CsCa > 2.75 mmol/L, BNP or NT-proBNP > 2 ULN, high-risk cytogenetics, and Barthel index score were independent risk factors for UHR MM. Moreover, UHR patients had a worse response rate than control patients. CONCLUSION: Our study highlighted the characteristics of UHR MM patients and suggested that the combination of organ insufficiency and highly malignant myeloma cells resulted in poor outcomes of patients with UHR MM.

In-Vivo Validation of a Novel Robotic Platform for Endovascular Intervention.

OBJECTIVE: In-vivo validation on animal setting of a pneumatically propelled robot for endovascular intervention, to determine safety and clinical advantage of robotic cannulations compared to manual operation. METHODS: Robotic assistance and image-guided intervention are increasingly used for improving endovascular procedures with enhanced navigation dexterity and accuracy. However, most platforms developed in the past decade still present inherent limitations in terms of altered clinical workflow, counterintuitive human-robot interaction, and a lack of versatility. We have created a versatile, highly integrated platform for robot-assisted endovascular intervention aimed at addressing such limitations, and here we demonstrate its clinical usability through in-vivo animal trials. A detailed in-vivo study on four porcine models conducted with our robotic platform is reported, involving cannulation and balloon angioplasty of five target arteries. RESULTS: The trials showed a 100% success rate, and post-mortem histopathological assessment demonstrated a reduction in the incidence and severity of vessel trauma with robotic navigation versus manual manipulation. CONCLUSION: In-vivo experiments demonstrated that the applicability of our robotic system within the context of this study was well tolerated, with good feasibility, and low risk profile. Comparable results were observed with robotics and manual cannulation, with clinical outcome potentially in favor of robotics. SIGNIFICANCE: This study showed that the proposed robotic platform can potentially improve the execution of endovascular procedures, paving the way for clinical translation.

Prognostic value of t(4;14) translocation in newly diagnosed multiple myeloma patients in novel agent era.

OBJECTIVE: To evaluate the prognostic value of t(4; 14) translocation for newly diagnosed multiple myeloma (MM) patients in the novel agent era. METHODS: We retrospectively analyzed 606 newly diagnosed MM patients treated with novel agents. The propensity score matching technique was used to reduce the bias between groups. RESULTS: Among 606 patients, t(4; 14) was observed in 108 (17.8%) patients, among which 79 (73.1%) were accompanied by 1q21 gain and/or del 17p. Median overall survival (OS) (56.2 vs. 87.3 months) and progression-free survival (PFS) (25.7 vs. 37.6 months) were significantly shorter in patients with t(4;14) compared with patients without cytogenetic abnormalities. Univariate Cox proportional hazards regression analysis showed that the t(4;14) was not associated with shorter OS (p = 0.666) and PFS (p = 0.164). The multivariable analysis also showed t(4;14) was not a poor prognostic factor for OS and PFS of patients with newly diagnosed MM (p > 0.05). After balancing the distribution of factors between patients with and without t(4;14) by the propensity score matching technique, patients with t(4;14) had similar OS (57.6 vs. 56.5 months, p = 0.964) and PFS (26.5 vs. 28.1 months, p = 0.740) with the patients without t(4;14). CONCLUSIONS: These results demonstrated that t(4; 14) alone may be not a poor prognostic factor patients with newly diagnosed MM in the novel agent era.

Low Barthel index score is a poor prognostic factor for newly diagnosed multiple myeloma patients.

The basic activities of daily life may affect the prognosis of multiple myeloma (MM) patients and the Barthel index (BI) is currently the most widely used tool to evaluate basic activities of daily life, but few studies have evaluated its prognostic value in MM. We retrospectively enrolled patients with newly diagnosed MM and analyzed the association between the BI and the survival of newly diagnosed MM patients. We totally analyzed 538 patients and found that median overall survival (OS) and progression-free survival (PFS) were significantly shorter in the low BI (≤ 85) group compared with the high BI (> 85) group. Univariate Cox proportional hazards regression analysis showed that the low BI was associated with shorter OS and PFS. It was also confirmed that the low BI was poor prognostic factor for OS and PFS in multivariable analyses. In the propensity score matching analysis, patients with low BI also had shorter OS and PFS. Our study suggested that the low BI was a poor prognostic factor for patients with newly diagnosed MM.

Trustworthy learning with (un)sure annotation for lung nodule diagnosis with CT.

Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two generalizability issues in clinical practice. First, benign-malignant discrimination is often assessed by human observers without pathologic diagnoses at the nodule level. We termed these data as "unsure-annotation data". Second, a classifier does not necessarily acquire reliable nodule features for stable learning and robust prediction with patch-level labels during learning. In this study, we construct a sure-annotation dataset with pathologically-confirmed labels and propose a collaborative learning framework to facilitate sure nodule classification by integrating unsure-annotation data knowledge through nodule segmentation and malignancy score regression. A loss function is designed to learn reliable features by introducing interpretability constraints regulated with nodule segmentation maps. Furthermore, based on model inference results that reflect the understanding from both machine and experts, we explore a new nodule analysis method for similar historical nodule retrieval and interpretable diagnosis. Detailed experimental results demonstrate that our approach is beneficial for achieving improved performance coupled with trustworthy model reasoning for lung cancer prediction with limited data. Extensive cross-evaluation results further illustrate the effect of unsure-annotation data for deep-learning based methods in lung nodule classification.

Janus Micro/Nanorobots in Biomedical Applications.

Janus particles possess two or more distinct domains that are anisotropic in composition or surface features. They integrate different or even incompatible properties within a single particle, making them possible to perform diverse functions and multiple tasks simultaneously. Advances in micro/nanorobots demonstrate that they can effectively convert diverse energy sources into movement and reach target locations with precision. Integration of Janus structure with micro/nanobots is emerging as a promising tool for biomedical applications. In this review, the fabrication and energy sources of Janus micro/nanorobots are briefly introduced. After that, the recent progress of Janus micro/nanorobots for biomedicine, with a special focus on their applications for cargo delivery, bioimaging, biosensing, surgery, and therapy are presented and discussed. The application of Janus micro/nanorobots in biomedicine still faces serious challenges from fabrication, engines, biocompatibility, and biodegradation for their widespread in clinical situations. Nevertheless, a few emerging materials and approaches offer potential solutions to these problems.