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BACKGROUND: PPM1G, a member of the serine/threonine protease family, dephosphorylates various proteins and may be involved in cancer development. The role and mechanism of PPM1G in HCC still needs to be verified. OBJECTIVE: This study aims to explore the role of PPM1G in the occurrence, development and prognosis of HCC. METHODS: Using bioinformatics (UALCAN, cBioPortal, Linkedomics, STRING and GSEA) to analyze the expression of PPM1G mRNA in HCC, its clinical relevance and possible involved signaling pathways. The expression of PPM1G protein was determined by immunohistochemistry in 311 cases of HCC to evaluate the association between PPM1G and clinical features and prognosis. RESULTS: The expression of PPM1G was significantly upregulated in HCC (P< 0.001), correlated with the metastasis (P= 0.020), pathological grade of HCC (P= 0.032), microvascular invasion (P= 0.040), and HBV infection (P= 0.041). Cox multivariate regression showed high expression of PPM1G was an independent prognostic factor for HCC. Its role in HCC may relate to methylation and frequency mutation. Furthermore, the database showed PPM1G is involved in the signal pathway such as cell cycle, WNT pathway, and mTOR pathway in HCC. CONCLUSION: PPM1G showed an essential function involving in tumor-related pathways in HCC, providing a biological basis for targeted treatment of HCC clinically.

Background COVID-19 is erupting globally. Mass quarantine had been implemented all around China which could influence the psychological status of patients with memory disorders and their caregivers. Aim To investigate the psychological impact of mass quarantine on patients with memory disorders and their caregivers in China. Methods We completed a cross-sectional study in 787 patients and their caregivers registered from 2010 to 2019 in Memory Clinic, The First Affiliated Hospital of Chongqing Medical University, by telephone interviews. The performance in neuropsychiatric symptoms (NPSs), sleep, nutrition, chronic diseases of patients, and the burden of care, anxiety and depression of caregivers was assessed by six assessment scales (MNA-SF, PSQI, NPI, RSS, PHQ-9 and GAD-7). Results Only 68 (8.6%) patients worried about the outbreak of COVID-19. The prevalence of NPSs among all subjects was nearly 60.0%. Approximately 50.0% of the caregivers reported distress. More than 70.0% of patients remained stable in NPSs. However, anxiety, depression, aberrant motor disorder and delusion were exacerbated (22.9%, 18.6%, 17.1% and 16.8%, respectively). Appetite and eating disorder led alleviation rate by 25.8% while disappearing rate of agitation led by 5.8%. 7.5% of caregivers manifested depressive symptoms while 4.9% expressed anxiety symptoms, and 40.8% showed care burden. The coefficients of RSS and PHQ-9, RSS and GAD-7, RSS and NPI-D, PHQ-9 and GAD-7 were 0.7, 0.5, 0.5 and 0.6, respectively (p

Qian Li,1,2,* Dan-Lei Xiong,3,* Heng Wang,1 Wei-Li Jin,4 Ying-Yu Ma,5 Xiao-Ming Fan1,2 1Graduate Department, Bengbu Medical College, Bengbu, Anhui, 233000, People’s Republic of China; 2Department of Ultrasound, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, 310014, People’s Republic of China; 3School of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, 310018, People’s Republic of China; 4Department of Gastroenterology, Nanxun People’s Hospital (Zhejiang Provincial People’s Hospital Nanxun Branch), Huzhou, 313009, Zhejiang Province, People’s Republic of China; 5Key Laboratory of Gastroenterology of Zhejiang Province, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, 310014, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ying-Yu MaKey Laboratory of Gastroenterology of Zhejiang Province, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, 310014, People’s Republic of ChinaTel + 86-0571-85893781Email myy011525@163.comXiao-Ming FanGraduate Department, Bengbu Medical College, Bengbu, Anhui, 233000, People’s Republic of ChinaTel + 86-0571-85893291Email fan-xiaoming@163.comPurpose: SLC41A3 is a member of the solute carrier family 41 (SLC41) and is involved in many cellular processes as a magnesium ion transporter. Although it plays an important role in cancer formation and development, the correlation between the expression of SLC41A3 and the occurrence and prognosis of hepatocellular carcinoma (HCC) remains unclear. Therefore, this study was focused on the evaluation of the relationship between SLC41A3 and the development and prognosis of HCC.Patients and Methods: Firstly, we collected the mRNA expression of SLC41A3 in HCC through the platform of Oncomine. Then, the subgroups of HCC were performed by the UALCAN website and the prognosis of HCC was analyzed by Kaplan–Meier Plotter database. Subsequently, immunohistochemistry (IHC) method was used to detect SLC41A3 expression in 323 clinically confirmed HCC samples and 184 non-cancerous liver tissues. Finally, function enrichment analysis was done using the LinkInterpreter module in LinkedOmics, and gene set enrichment analysis (GSEA) was performed using TCGA data set.Results: The Oncomine database and immunohistochemical (IHC) showed higher SLC41A3 expression in HCC tissue compared to normal tissue. The expression of SLC41A3 was significantly correlated with tumor metastasis, Edmondson grade, microvascular invasion, and AFP level. Kaplan–Meier and Cox regression analyses verified that high SLC41A3 expression is a significant prognostic factor for reduced overall survival in HCC patients.Conclusion: Our results demonstrated that high expression of SLC41A3 was the predictor of poor prognosis in HCC patients, suggesting that this protein may be a potential target for HCC therapy.Keywords: HCC, solute carrier 41A3, immunohistochemistry, bioinformatics

As a clean energy with mature technology, hydropower has been widely applied in industry. The hydraulic turbine unit plays an important role in hydropower station. Since the fault of turbine unit will affect the normal operation of the whole hydropower station, this paper proposes a universal, fast and memory-efficient method trend for time-series prediction of hydraulic turbines. The proposed method adopts the expressive power of deep neural networks and the time characteristics of sequence-to-sequence structure (parallel convolution and recurrent neural network) to make time-series prediction. It also uses convolutional quantile loss and memory network to predict future extreme events. The experimental results show that the proposed method is fast, robust and accurate. It can reduce at least 34% in mean square error and 33% in convergence speed compared with the existing methods.

We propose an ultrasensitive and tunable mid-infrared sensor based on plasmon-induced transparency (PIT) in a monolayer black phosphorus metasurface. Results show that there are two PIT windows, each of which occurs when the long axis of the metasurface is placed along the MBP’s armchair and zigzag crystal directions, respectively. The corresponding sensors based on these PIT effects show high sensitivities of 7.62 THz/RIU and 7.36 THz/RIU. Both PIT frequencies can be tuned statically by varying the geometric parameters or dynamically by changing the electron doping of monolayer black phosphorus, making the sensors adaptable to tackle with a variety of scenarios. We expect that this work will advance the engineering of metasurfaces based on monolayer black phosphorus and promote their sensing applications.

The objective of this study was to investigate the expression of vesicular amine transporter 1 (VAT1) in hepatocellular carcinoma (HCC) and its prognostic value and to analyze the relationship between VAT1 expression and clinicopathological features of HCC. First, several public databases, including Ualcan, GEPIA, and Oncomine, were used to analyze the expression of VAT1 in HCC and normal liver tissue. Next, 330 HCC and 190 normal liver samples were stained by immunohistochemistry and scored. Finally, we evaluated the clinical significance of VAT1 as a prognostic factor according to the clinicopathological characteristics. We observed that the expression level of VAT1 in HCC samples was significantly higher than that in normal liver tissues, and the high expression of VAT1 protein in HCC was significantly correlated with patient age, tumor size, number of tumors, and vascular metastasis (P < 0.05). The average survival time of HCC patients with high expression of VAT1 was significantly lower than that of patients with low expression of VAT1. Further analysis demonstrated that VAT1 expression was significantly correlated with the length of overall survival in HCC patients. In conclusion, VAT1 may have an essential function in the progression of HCC, and the level of its expression may effectively predict the invasion and prognosis of HCC. Moreover, the combination of information contained in public databases and the results of the analysis of clinical samples can help us to understand better the mechanism of action of molecular oncogenes in HCC.

Due to the scarcity and high cost of precious metals, the hydrogen economy would ultimately rely on non-platinum-group-metal (non-PGM) catalysts. The non-PGM-catalyzed oxygen reduction reaction, wh...

We propose dynamically switchable multispectral plasmon-induced transparency (PIT) with high modulation depth in a three-dimensional metamaterial standing on a flexible substrate. The proposed metamaterial is composed of a pair of metal–insulator–metal (MIM) nano-cut-wires and a pair of insulator–metal–insulator (IMI) nano-cut-wires. Results show that two PIT windows can be achieved because of the near-field coupling between the dipole supported by the IMI nano-cut-wire and two quadrupoles supported by the MIM structures. These two PIT windows can be blue-shifted or even flipped over by stretching the substrate along one direction, or be switched off by stretching along the other direction. A classical coupled oscillator model is developed to quantitatively describe and explain these results. We expect this work will find promising applications in multispectral sensors, slow light devices and nonlinear optical devices.

Long noncoding RNAs (lncRNAs) have been proposed as diagnostic or prognostic biomarkers of head and neck squamous carcinoma (HNSCC). The current study aimed to develop a lncRNA-based prognostic nomogram for HNSCC. LncRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. After the reannotation of lncRNAs, the differential analysis identified 253 significantly differentially expressed lncRNAs in training set TCGA-HNSC (n = 300). The prognostic value of each lncRNA was first estimated in univariate Cox analysis, and 41 lncRNAs with P < 0.05 were selected as seed lncRNAs for Cox LASSO regression, which identified 11 lncRNAs. Multivariate Cox analysis was used to establish an 8-lncRNA signature with prognostic value. Patients in the high-signature score group exhibited a significantly worse overall survival (OS) than those in the low-signature score group, and the area under the receiver operating characteristic (ROC) curve for 3-year survival was 0.74. Multivariable Cox regression analysis among the clinical characteristics and signature scores suggested that the signature is an independent prognostic factor. The internal validation cohort, external validation cohort, and 102 HNSCC specimens quantified by qRT-PCR successfully validate the robustness of our nomogram.

Skull base vagal nerve schwannoma (VNS) is relatively uncommon and poses a challenge to surgeons. Although schwannomas are benign and slowly growing neoplasms arising from Schwann cells, they may cause significant dysfunction by causing the surrounding structures compression or infiltrating vital structures such as the skull base, the orbit, and the cranial nerves. These tumors are resistant to radiotherapy and chemotherapy. Complete surgical removal is the optimal treatment modality, with recurrence being rare. The authors report a case of a 58-year-old man with an extensive VNS involving the left jugular foramen and parapharyngeal space. The clinical presentation, surgical management, and outcomes of VNS are discussed.

Blood-based tumor mutational burden (bTMB) has been studied to identify patients with NSCLC who would benefit from anti-programmed cell death protein 1 (anti-PD-1) or anti-programmed death ligand 1 (anti-PD-L1) therapies. However, it failed to predict overall survival (OS) benefits, which warrants further exploration.Three independent cohorts of patients with NSCLC treated with immunotherapy were used in this study. A new bTMB algorithm was first developed in the two independent cohorts (POPLAR, N = 211, and OAK, N = 462) and further validated in the third National Cancer Center (NCC) cohort (N = 64).bTMB-H (bTMB ≥ cutoff point) was not associated with favorable OS after immunotherapy regardless of the cutoff points in either the POPLAR and OAK or the NCC cohorts (p0.05) owing to its correlation with the amount of circulating tumor DNA, which was associated with poor OS. In the POPLAR and OAK cohorts, with allele frequency (AF) adjustment, a high AF bTMB (HAF-bTMB, mutation counts with an AF5%) was strongly correlated with the amount of circulating tumor DNA (Pearson r = 0.65), whereas a low AF bTMB (LAF-bTMB, mutation counts with an AF ≤ 5%) was not (Pearson r = 0.09). LAF-bTMB-H was associated with favorable OS (hazard ratio [HR] = 0.70, 95% confidence interval [CI]: 0.52-0.95, p = 0.02), progression-free survival (PFS; HR = 0.62, 95% CI: 0.47-0.80, p0.001), and objective response rate (ORR) (p 0.001) after immunotherapy but not chemotherapy, with a cutoff point of 12 trained in the POPLAR cohort and validated in the OAK cohort. The LAF-bTMB algorithm was further validated in the NCC cohort in which LAF-bTMB-H was associated with OS (HR = 0.20, 95% CI: 0.05-0.84, p = 0.02), PFS (HR = 0.30, 95% CI: 0.13-0.70, p = 0.003), and ORR (p = 0.001).We developed and validated a new LAF-bTMB algorithm as a feasible predictor of OS, PFS, and ORR after anti-PD-(L)1 therapies in patients with NSCLC, which needs to be prospectively validated.

Sleep is indispensable for human health, with sleep disorders initiating a cascade of negative consequences. As our closest phylogenetic relatives, non-human primates (NHPs) are invaluable for comparative sleep studies and exhibit tremendous potential for improving our understanding of human sleep and related disorders. Previous work on measuring sleep in NHPs has mostly used electroencephalography or videography. In this study, simultaneous videography and actigraphy were applied to observe sleep patterns in 10 cynomolgus monkeys ( Macaca fascicularis) over seven nights (12 h per night). The durations of wake, transitional sleep, and relaxed sleep were scored by analysis of animal behaviors from videography and actigraphy data, using the same behavioral criteria for each state, with findings then compared. Here, results indicated that actigraphy constituted a reliable approach for scoring the state of sleep in monkeys and showed a significant correlation with that scored by videography. Epoch-by-epoch analysis further indicated that actigraphy was more suitable for scoring the state of relaxed sleep, correctly identifying 97.57% of relaxed sleep in comparison with video analysis. Only 34 epochs (0.13%) and 611 epochs (2.30%) were differently interpreted as wake and transitional sleep compared with videography analysis. The present study validated the behavioral criteria and actigraphy methodology for scoring sleep, which can be considered as a useful and a complementary technique to electroencephalography and/or videography analysis for sleep studies in NHPs.

Visible images provide abundant texture details and environmental information, while infrared images benefit from night-time visibility and suppression of highly dynamic regions; it is a meaningful task to fuse these two types of features from different sensors to generate an informative image. In this article, we propose an unsupervised end-to-end learning framework for infrared and visible image fusion. We first construct enough benchmark training datasets using the visible and infrared frames, which can address the limitation of the training dataset. Additionally, due to the lack of labeled datasets, our architecture is derived from a robust mixed loss function that consists of the modified structural similarity (M-SSIM) metric and the total variation (TV) by designing an unsupervised learning process that can adaptively fuse thermal radiation and texture details and suppress noise interference. In addition, our method is an end to end model, which avoids setting hand-crafted fusion rules and reducing computational cost. Furthermore, extensive experimental results demonstrate that the proposed architecture performs better than state-of-the-art methods in both subjective and objective evaluations.

AIM: To develop a novel three-dimensional (3D) electric ophthalmotrope to improve the ophthalmology teaching effectiveness and evaluate the teaching value. METHODS: A 3D electric ophthalmotrope was designed by simulating the movement of the ocular and the extraocular muscles according to Sherrington's law. The model with joint bearing was to ensure the flexibility and centripetal rotation of the simulated ball and stepper motor as the driving device. A programmable processor was used to control the motion amplitude of the stepper motor. The size of hole was set at the back of the simulated shell to limit the amount of eye movement. Afterwards, using a 5-point Likert scale, 7 experts evaluated the 3D electric ophthalmotrope's simulation ability and precision, compared with the traditional anatomical model. In addition, the teaching effectiveness of the 3D electric ophthalmotrope was evaluated at in-class quiz and final exam in a randomized controlled trial. RESULTS: The 3D electric ophthalmotrope could be operated easily to demonstrate the eye movements with motion of different ocular muscles. The experts agreed that the 3D electric ophthalmotrope was different from the traditional model and was easier for students to understand every extraocular muscles' movement in each evaluation index (P

Patients with Parkinson’s disease (PD) exhibit systemic deficits, including arthritis and osteoporosis-like symptoms. However, the questions, how the deficits in periphery organs or tissues occur in PD patients, and what are the relationship (s) of the periphery tissue deficits with the brain pathology (e.g., dopamine neuron loss), are at the beginning stage to be investigated. Notice that both PD and osteoporosis are the products of a complex interaction of genetic and environmental risk factors. Genetic mutations in numerous genes have been identified in patients either with recessive or autosomal dominant PD. Most of these PD risk genes are ubiquitously expressed; and many of them are involved in regulation of bone metabolism. Here, we review the functions of the PD risk genes in regulating bone remodeling and homeostasis. The knowledge gaps in our understanding of the bone-to-brain axis in PD development are also outlined.

Background The differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis (CP) is clinically challenging due to a lack of minimally invasive diagnosis methods. MicroRNAs (miRNAs) derived from small extracellular vesicles (EVs) in the blood have been reported as a promising diagnosis biomarker for various types of cancer. However, blood small EV miRNA signatures and their diagnostic value to differentiate between PDAC and CP remain to be determined. Methods In this study, 107 patients with PDAC or CP were recruited, and 90 patients were finally enrolled for a training cohort (n = 48) and test cohort (n = 42). Small RNA sequencing was used to assess the expression of blood small EV miRNAs in these patients. Results The linear model from the differentially expressed blood small EV miR‐95‐3p divided by miR‐26b‐5p showed an average sensitivity of 84.1% and an average specificity of 96.6% to identify PDAC from CP in the training cohort and the test cohort, respectively. When the model was combined with serum carbohydrate antigen 19‐9 (CA19‐9), the average sensitivity increased to 96.5%, and the average specificity remained at 96.4% of both cohorts, which demonstrated the best performance of all the published biomarkers for distinguishing between PDAC and CP. The causal analysis performed using the Bayesian network demonstrated that miR‐95‐3p was associated with a “consequence” of “cancer” and miR‐26b‐5p as a “cause” of “pancreatitis.” A subgroup analysis revealed that blood small EV miR‐335‐5p/miR‐340‐5p could predict metastases in both cohorts and was associated with an overall survival (p = 0.020). Conclusions This study indicated that blood small EV miR‐95‐3p/miR‐26b‐5p and its combination with serum levels of CA19‐9 could separate PDAC from CP, and miR‐335‐5p/miR‐340‐5p was identified to associate with PDAC metastasis and poor prognosis. These results suggested the potentiality of blood small EV miRNAs as differential diagnosis and metastases biomarkers of PDAC., The challenge of separating pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis (CP) is the lack of minimally invasive clinically diagnostic methods. Blood small EV miR‐95‐3p/miR‐26b‐5p and its combination with CA19‐9 serum levels were discovered and validated to separate PDAC from CP. These results suggested the potentiality of blood small EV miRNAs as differential diagnosis biomarkers of PDAC.

The authors have requested that this preprint be removed from Research Square.

Single-cell RNA-seq and ATAC-seq analyses have been widely applied to decipher cell-type and regulation complexities. However, experimental conditions often confound biological variations when comparing data from different samples. For integrative single-cell data analysis, we have developed SCALEX, a deep generative framework that maps cells into a generalized, batch-invariant cell-embedding space. We demonstrate that SCALEX accurately and efficiently integrates heterogenous single-cell data using multiple benchmarks. It outperforms competing methods, especially for datasets with partial overlaps, accurately aligning similar cell populations while r,etaining true biological differences. We demonstrate the advantages of SCALEX by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19, which were assembled from multiple data sources and can keep growing through the inclusion of new incoming data. Analyses based on these atlases revealed the complex cellular landscapes of human and mouse tissues and identified multiple peripheral immune subtypes associated with COVID-19 disease severity.

Computational tools for integrative analyses of diverse single-cell experiments are facing formidable new challenges including dramatic increases in data scale, sample heterogeneity, and the need to informatively cross-reference new data with foundational datasets. Here, we present SCALEX, a deep-learning method that integrates single-cell data by projecting cells into a batch-invariant, common cell-embedding space in a truly online manner (i.e., without retraining the model). SCALEX substantially outperforms online iNMF and other state-of-the-art non-online integration methods on benchmark single-cell datasets of diverse modalities, (e.g., scRNA-seq, scATAC-seq), especially for datasets with partial overlaps, accurately aligning similar cell populations while retaining true biological differences. We showcase SCALEX’s advantages by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19 patients, each assembled from diverse data sources and growing with every new data. The online data integration capacity and superior performance makes SCALEX particularly appropriate for large-scale single-cell applications to build-upon previously hard-won scientific insights.

We propose a plasmonic platform for achieving out-of-plane quadrupolar plasmonic surface lattice resonances (SLRs) with large quality factors. The proposed platform is composed of a horizontal metal–insulator–metal (MIM) grating embedded in a homogeneous dielectric environment. Numerical results based on rigorous coupled-wave analysis show that under oblique incidences, high-Q out-of-plane quadrupolar SLRs can be excited at wavelengths of 1242 nm over a wide range of insulator widths, and the quality factor can reach 1036. As a comparison, under the same conditions, only dipolar SLRs with much lower quality factors of ∼ 300 can be excited in a vertical MIM grating, which has the same period and a quarter-turned unit cell. We expect that the proposed high-Q quadrupolar SLR platform will find applications in light–matter interactions on the nanoscale.

Adopting semiconductor materials with light-trapping architectures as the surface-enhanced Raman spectroscopy (SERS)-active substrates has received increasing attention, in which the multiple reflection and scattering of electromagnetic waves can improve the enhancement factor. However, the fabrication of these semiconductor SERS-active substrates commonly requires complicated processes, and these methods normally result in non-uniform and isolated particles/flakes, which have fundamental difficulties in meeting the practical needs in high performance and reliable SERS substrates. Herein, we demonstrate that SnSe2 nanoplate arrays (NPAs) via self-assembled growth can serve as uniform, highly sensitive and reliable SERS substrates. The cavity formed by the SnSe2 NPAs can trap light efficiently (∼96%) and thus improve the enhancement factor. Benefiting from the synergistic effect of the charge-transfer process and enhanced light trapping, the resulting SERS substrates based on pure SnSe2 NPAs show an ultralow detection limit (1 × 10−12 M), a high enhancement factor (6.33 × 106) and excellent uniformity (relative standard deviations down to 7.7%), demonstrating one of the highest sensitivities amongst the reported semiconductor SERS substrates. Furthermore, the effects of different SnSe2 structural configurations (planar vs. cavity), the height and tilt angle of the SnSe2 NPAs on the performance of SERS detection are systematically investigated. It is discovered that the SERS performance is strongly dependent on both the light-trapping ability and the absorption loss. We believe that our results not only provide an effective strategy to obtain tunable, uniform and high performance SERS substrates, but also lead to further understanding of designing 3D light trapping architectures.

With the rapid development of surgical technology, the minimally invasive surgery has obtained a widespread application in colorectal carcinoma resection. In recent years, natural orifice specimen extraction surgery (NOSES) has been applied in colorectal surgery. NOSES not only obtains radical oncological resection but also minimizes the postoperative pain. Laparoscopic radical resection with transanal specimen eversion and extracorporeal resection (NOSES I) is well suitable for lower rectal carcinoma. The advantage of this method is that the specimen is transected after being averted transanally, which helps to evaluate the definite distance of distal resection margin and reduce the possibility of positive resection margin. Six different methods of NOSES I have been reported. The key procedure of this method is the introduction of anvil into the bowel lumen of the sigmoid colon. However, how to complete this step aseptically is still the focus. Based on the clinical experience of colorectal resection with da Vinci robotic surgery system, we developed a modified NOSES I as robotic radical resection for lower rectal carcinoma with transanal pullout of rectum eversion and extracorporeal resection technique. The procedures of operation are as follows

A growing number of studies have shown immunotherapy to be a promising treatment strategy for several types of cancer. Short tandem repeats (STRs) have been proven to be alternative markers for the evaluation of hypermutability in gastrointestinal (GI) cancers. However, the status of STRs and microsatellite instability (MSI) in other tumors have not yet been investigated. To further compare STR and MSI alterations in different tumors, a total of 407 paired DNAs were analyzed from the following eight tumor types: breast cancer (BC), hepatocellular cancer (HCC), pancreatic cancer (PC), colorectal cancer (CRC), gastric cancer (GC), lung cancer (LC), esophageal cancer (EC), and renal cell cancer (RCC). The STR alteration frequencies varied in different tumors as expected. Interestingly, none of the patients possessed MSI-low (MSI-L) or MSI-high (MSI-H), except for the GI patients. The highest STR alteration was detected in EC (77.78%), followed by CRC (69.77%), HCC (63.33%), GC (54.55%), LC (48.00%), RCC (40.91%), BC (36.11%), and PC (25.71%). The potential cutoff for hypermutability was predicted using the published objective response rate (ORR), and the cutoff of LC and HCC was the same as that of GI cancers (26.32%). The cutoffs of 31.58% and 10.53% should be selected for BC and RCC, respectively. In summary, we compared MSI and STR status in eight tumor types, and predicted the potential threshold for hypermutability of BC, HCC, CRC, GC, LC, EC, and RCC.

Background: COVID-19 has infected tens of millions of people worldwide since its pandemic. CPT is one of the promising treatment methods and is favored by more and more researchers. However, the clinical efficacy and safety of CPT in COVID-19 remains unclear. Methods: We performed a matched control study by PSM analysis (including 163 cases with CPT and 163 controls with the standard treatment) and meta-analysis (including 498 cases and 557 controls) estimate the clinical efficacy and security of CPT and COVID-19, which will help inform clinical management of COVID-19 infection. Results: We found that days of hospital stay in case with CPT groups were significantly higher than matched control group (P< 0.0001). A significant reduction in mortality (OR= 0.496, 95%CI= 0.342-0.719, P< 0.0001) was found in the CPT group compared with the standard treatment group, and a true positive result was also found in sequential analysis. In terms of adverse events, sequential analysis found a false positive, although meta-analysis found a significant increase in the incidence of adverse events in patients treated with CPT compared to the control group. No differences between the two groups in terms of length of stay, improvement of clinical symptoms, and discharge were found. Conclusions: This study is the first to systematically review and meta-analysis the efficacy and safety of CPT in patients with COVID-19 in the largest sample size. Our results showed that CPT could significantly reduce the mortality rate of COVID-19 patients, and there was no significant increase in the incidence of adverse events. These data provide evidence favoring the efficacy and safety of CPT as a therapeutic agent in COVID-19 patients and provide comprehensive reference for COVID-19 treatment. Funding Statement: This work was supported by Scientific Research Project of Jiangsu Commission of Health (H2019065), Key Foundation of Wuhan Huoshenshan Hospital (2020[18]), Key Research & Development Program of Jiangsu Province (BE2018713), Medical Innovation Project of Logistics Service (18JS005). Declaration of Interests: The authors declare no conflicts of interest with this work. Ethics Approval Statement: The authors were approved by the ethics committee of Huoshenshan hospital, and were conducted in accordance with the tenets of the Declaration of Helsinki and its amendments. All participants provided written informed consent for the collection of samples and their subsequent analysis.

Interferon-alpha (IFN-α) is a cytokine widely used in the treatment of brain cancers and virus infections with side effects including causing depression. Monoamine neurotransmitter systems have been found playing important roles in peripheral IFN-α-induced depression, but how peripheral IFN-α accesses the central nervous system and contributes to the development of depression is poorly known. This study aimed to develop a non-human primate model using long-term intracerebroventricular (i.c.v.) administration of IFN-α (5 days/week for 6 weeks), to observe the induced depressive-like behaviors and to explore the contributions of monoamine neurotransmitter systems in the development of depression. In monkeys receiving i.c.v. IFN-α administration, anhedonia was observed as decreases of sucrose consumption, along with depressive-like symptoms including increased huddling behavior, decreases of spontaneous and reactive locomotion in home cage, as well as reduced exploration and increased motionless in the open field. Chronic central IFN-α infusion significantly increased the cerebrospinal fluid (CSF) concentrations of noradrenaline (NA), and 3,4-dihydroxyphenylacetic acid (DOPAC), but not 5-hydroxyindoleacetic acid (5-HIAA) and homovanillic acid (HVA). These CSF monoamine metabolites showed associations with some specific depression-related behaviors. In conclusion, central IFN-α administration induced anhedonia and depression-related behaviors comparable to the results with peripheral administration, and the development of depression was associated with the dysfunction of monoamine neurotransmitters.

Objectives: Earlier researches suggested patients should be routinely screened for bacteria and fungi infection after COVID-19 being confirmed. Here, we enrolled 236 patients with COVID-19 to analyze the clinical characteristics, fungal strains, mortality, and laboratory data of different groups. Design: Single center retrospective study Patients: A total of 236 COVID-19 patients from Huoshenshan Hospital were included in this study, consisting of 14(6%) died cases, 222(94%) discharged cases . Results: The result revealed that 5 mortality in positive group were all related to aspergillus infection while candida infection rarely caused death. Aspergillus was most common in non-survivors while candida was most common in survivors. In terms of interleukin-6 (IL6), viral loads, nucleic acid clearance time, etc, fungal serologically positive group had a higher level than negative group. Conclusions: Non-survivors of Covid-19 with fungal infection were almost associated with aspergillus infection. Aspergillus infection, instead of candida infection might be fatal for critical ill patients with COVID-19. There is great significance to carry out routine screening for fungal infection especially for critical patients to enable early treatment to be implemented. Keywords: coronavirus disease 2019 (COVID-19); fungal infection; aspergillus; mortality

Predicting the flight trajectory of the target fighter as accurately as possible to capture the fleeting time to attack is crucial for close-range air combat, so the research has always been a focus in related fields. Without exception, it is as hard as other prediction problems due to the large degree of freedom of the solution space. All the previous methods only used the time correlation in a single trajectory data to predict and ignored the spatial correlation between the trajectory data of both sides. Therefore, not only the traditional machine learning methods but the current popular deep learning methods have less accurate predictions of trajectories, especially in the case of quick-changing, which greatly limits the practical application of this technology. In this paper, both the time and space correlation of flight trajectories are considered to express the tactical intentions in close-range air combat. Thus, the LSTM trajectory prediction method is proposed based on the combination of confrontational data and attention mechanism. Two or more flight trajectory data are used for learning and training of encoder network parameters, and then the target's trajectory is predicted by a corresponding decoder module. The method also takes the advantage of attention mechanism to strengthen the prediction accuracy. The experimental results show that the accuracy of target trajectory prediction is greatly improved, especially when the trajectory changes quickly, so it is very suitable for practical application.

Targeted therapy based on specific genetic alterations has been proven to be an effective treatment for various types of cancer. In the present study, we aimed to explore the efficacy of personalized targeted therapy guided by targeted deep sequencing for patients with advanced biliary tract cancer (BTC) after non-radical resection. Targeted deep sequencing was performed on 49 patients with BTC, to whom biologic agents were recommended. Among 32 patients with stage IV and R2 resection (a non-radical resection), 21 patients underwent conventional chemotherapy (mGEMOX), while the remaining 11 patients received a personalized targeted agent. The genomic landscape of the 49 patients with BTC was determined and the results showed that genetic alterations were enriched in the ERBB family and cell cycle pathway. After a median follow-up of 12 months, the 11 BTC patients with personalized targeted therapy showed a median progression-free survival (PFS) of 4.5 months (2.5–20.5 months), a median overall survival (OS) of 12.9 months (4.7–24.8 months) and a disease control rate (DCR) of 63.6%. In the other 21 BTC patients, who were undergoing conventional chemotherapy, the BTC patients had a median PFS of 1.5 months (0.5–11.6 months), a median OS of 4.1 months (1.3–18.4 months), and a DCR of 33.3%. In addition, 36.4% of the patients in the personalized targeted therapy group experienced grade >2 treatment-related toxicity vs. 19.0% of patients in the conventional chemotherapy group. This real-world study suggests that targeted deep sequencing contributes to the guidance of personalized targeted therapy based on individual actionable mutations, which may benefit advanced BTC patients undergoing non-radical resection.

Under the development of green energy saving technology, the development of energy saving technology in the application of air conditioning engineering is becoming more and more common. The introduction of energy saving technology not only reduces the energy consumption and environmental pollution in construction, but also improves the construction precision and reduces the contradiction between supply and demand. This paper expounds some problems existing in the construction and design of air conditioning engineering and analyzes the important influence of corresponding solutions and energy-saving technologies for air conditioning engineering.

Central precocious puberty (CPP) severely affects children’s physical and mental health and needs to be treated promptly and effectively. This article aimed to research the therapeutic effect of Shugan Xiehuo Formula (SXF) on CPP. A female CPP rat model was established and then treated with leuprolide and different doses of SXF. Sex organ volume and index were measured. Ovaries and uteri were visualized by hematoxylin-eosin staining. The concentrations of follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), and estradiol (E2) in peripheral blood were determined. The expression levels of gonadotropin-releasing hormone (GnRH), gonadotropin-releasing hormone receptor (GnRHR), estrogen receptor alpha (ERα), and G protein-coupled receptor 30 (GPR30) in the hypophysis were investigated by Real-Time Quantitative Reverse Transcription PCR and western blot. GnRH expression in the hypothalamus and GnRHR expression in the ovary were detected by immunohistochemistry. SXF reduced the volume of the bilateral ovaries, as well as the volumes of the uterus, hypothalamus, and hypophysis in the female CPP rats and diminished the index of the ovary, uterus, hypothalamus, and hypophysis in the female CPP rats ( P < 0.05 or P < 0.01 ). SXF treatment inhibited follicle maturation and uterine wall thickening in the female CPP rats. SXF decreased the concentrations of FSH, LH, PRL, and E2 in the peripheral blood in the female CPP rats ( P < 0.01 or P < 0.001 ). SXF suppressed the expressions of GnRH, GnRHR, ERα, and GPR30 in the hypophysis ( P < 0.05 ), the expression of GnRH in the hypothalamus ( P < 0.01 ), and the expression of GnRHR in the ovaries ( P < 0.001 ) of the female CPP rats. Overall, our study revealed that SXF had therapeutic effects on CPP in female rats. This is worthy of promoting clinically.

The convolutional neural network (CNN) decoder for general convolutional decoding is proposed. The parameters of CNN are determined by the initial state of each input block and the constraint relationship between adjacent bits is extracted by the convolutional layer as the constraint features. Then CNN decoder realizes decoding process through the extracted constraint feature instead of codewords directly. The result shows that, without changing the structure of decoder, the decoding performance of CNN decoder on different convolutional codes is equivalent to Viterbi soft decoding algorithm. Compared with Viterbi decoding, the larger constraint length or the lower SNR, the greater gain can be obtained in CNN decoder. Besides, we consider CNN trained by the two kinds of training sets in order to further investigate the potential and limitations of CNN decoder with respect to decoding performance, analysing the advantages and factors of these two kinds of training sets.

Objectives: Earlier researches suggested patients should be routinely screened for bacteria and fungi infection after COVID-19 being confirmed. Here, we enrolled 236 patients with COVID-19 to analyze the clinical characteristics, fungal strains, mortality, and laboratory data of different groups. Design: Single center retrospective study Patients: A total of 236 COVID-19 patients from Huoshenshan Hospital were included in this study, consisting of 14(6%) died cases, 222(94%) discharged cases. Results: The result revealed that 5 mortality in positive group were all related to aspergillus infection while candida infection rarely caused death. Aspergillus was most common in non-survivors while candida was most common in survivors. In terms of interleukin-6 (IL6), viral loads, nucleic acid clearance time, etc, fungal serologically positive group had a higher level than negative group. Conclusions: Non-survivors of Covid-19 with fungal infection were almost associated with aspergillus infection. Aspergillus infection, instead of candida infection might be fatal for critical ill patients with COVID-19. There is great significance to carry out routine screening for fungal infection especially for critical patients to enable early treatment to be implemented. Funding Statement: This study was financially supported by grants Key Foundation of Wuhan Huoshenshan Hospital (2020[18]), Key Research& Development Program of Jiangsu Province (BE2018713), Medical Innovation Project of Logistics Service (18JS005). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was approved by the Medical Ethical Committee of Wuhan Huoshenshan Hospital (No. HSSLL011). Written informed consent was obtained from each patient.

Autism spectrum disorder (ASD) comprises a heterogeneous range of neurodevelopmental conditions represented by symptoms including, communication and language deficits, repetitive, and restricted patterns of behavior and inadequate social interactions. Gamma-aminobutyric acid (GABA) is known to mediate I responses in the central nervous system by interacting with GABA signaling receptors. In this context, several recent investigations suggest that imbalances in the GABAergic neurotransmission system may be implicated in the development of ASD as well as several other neurodevelopmental disorders, including Fragile X syndrome (FXS) and Rett syndrome. This review initially expounds the functional role of the GABAergic system in the mature brain and during neurodevelopment. This will be followed by discussions concerning the impact of deficiencies in the system on ASD and the other above-mentioned neurodevelopment disorders. Finally, the connections between these deficiencies and behavioral features observed in the clinic will be considered.

Previous studies from the Cancer Cell Line Encyclopedia (CCLE) project have adopted commercial pan-cancer cell line models to identify drug sensitivity biomarkers. However, drug sensitivity biomarkers in esophageal squamous cell carcinoma (ESCC) have not been widely explored. Here, eight patient-derived cell lines (PDCs) are successfully established from 123 patients with ESCC. The mutation profiling of PDCs can partially recapture the tumor tissue actionable mutations from 161 patients with ESCC. Based on these mutations and relative pathways in eight PDCs, 46 targeted drugs are selected for screening. Interestingly, some drug and biomarker relationships are established that were not discovered in the CCLE project. For example, CDKN2A or CDKN2B loss is significantly associated with the sensitivity of CDK4/6 inhibitors. Furthermore, both PDC xenografts and patient-derived xenografts confirm CDKN2A/2B loss as a biomarker predictive of CDK4/6 inhibitor sensitivity. Collectively, patient-derived models could predict targeted drug sensitivity associated with actionable mutations in ESCC., Predicting the drug response of patients with cancer is crucial for implementing targeted therapy. Here, Su et al. make patient-derived cell lines and perform targeted sequencing and RNA-seq to identify CDKN2A/2B loss as a predictor of response to CDK4/6 inhibitors in esophageal squamous cell carcinoma.

Single-cell ATAC-seq (scATAC-seq) profiles the chromatin accessibility landscape at single cell level, thus revealing cell-to-cell variability in gene regulation. However, the high dimensionality and sparsity of scATAC-seq data often complicate the analysis. Here, we introduce a method for analyzing scATAC-seq data, called Single-Cell ATAC-seq analysis via Latent feature Extraction (SCALE). SCALE combines a deep generative framework and a probabilistic Gaussian Mixture Model to learn latent features that accurately characterize scATAC-seq data. We validate SCALE on datasets generated on different platforms with different protocols, and having different overall data qualities. SCALE substantially outperforms the other tools in all aspects of scATAC-seq data analysis, including visualization, clustering, and denoising and imputation. Importantly, SCALE also generates interpretable features that directly link to cell populations, and can potentially reveal batch effects in scATAC-seq experiments., Single-cell ATAC-seq data is challenging to analyse for reasons such as high dimensionality and sparsity. Here, the authors develop SCALE, a deep learning method that leverages latent feature extraction for various tasks of scATACseq data analysis.

In recent years, high-speed railways (HSRs) are being developed rapidly all over the world because of their convenience, safety, comfort, and other advantages. However, the reliability and security of HSR wireless communication systems have faced severe challenges, such as the Doppler effect, complicated wireless channel model, frequent handovers and so on. The International Union of Railways is pushing the evolution of the global system for mobile communications for railway (GSM-R) internationally. In this study, a high-speed based adaptive beamforming handover scheme is proposed to improve the handover performance for HSR wireless communication systems. When the high-speed train enters the overlapping region, the serving evolved NodeB (eNodeB) and target eNodeB are using beamforming with different gain factors to improve the received signal quality. In addition, this scheme can dynamically adjust the handover hysteresis margins of the reference signal receiving power (RSRP) and the reference signal receiving quality (RSRQ) based on the speed and position. Simulation results have demonstrated that the proposed handover scheme can improve the handover performance by increasing the handover trigger probability and success probability effectively.

In a cognitive radio network (CRN), connectivity is essential for the information exchange between secondary users (SUs). However, the unpredictable activities of primary users (PUs) may result in an unconnected network. Most of the existing works could only guarantee the CRN’s connectivity with one channel reclaimed by PU, without considering a more general case that PUs request multiple channels simultaneously, and thus, a network partition may occur more likely. In this paper, first, k-channel-connectivity is defined to derive a CRN that remains connected whenever any $k-1$ channels are occupied concurrently. Then, we propose both centralized and distributed topology control algorithms to ensure both the ${k}$ -channel-connected and conflict-free properties. Particularly, it is accomplished by ensuring that any $k-1$ independent sets (i.e., groups of SUs transmitting on the same channel) are not any vertex-cut set of the CRN. Next, the correctness of both the algorithms is verified via theoretical analysis; meanwhile, the analysis demonstrates that the proposed algorithms can achieve the target with a reasonable computation complexity, and in particular, the distributed one can work with limited local information. Finally, simulation results reveal that the proposed algorithms enable the reduction of not only the required channels but also the power consumption of the CRN.

Plasmonic nanostructures with large local field enhancement have been extensively investigated for sensing applications. However, the quality factor and thus the sensing figure of merit are limited due to relatively high ohmic loss. Here we propose a novel plasmonic sensor with ultrahigh figure of merit based on super-narrow Rayleigh anomaly (RA) in a mirror-backed dielectric metasurface. Simulation results show that the RA in such a metasurface can have a super-high quality factor of 16000 in the visible regime, which is an order of magnitude larger than the highest value of reported plasmonic nanostructures. We attribute this striking performance to the enhanced electric fields far away from the metal film. The super-high quality factor and the greatly enhanced field confined to the superstrate region make the mirror-backed dielectric metasurface an ideal platform for sensing. We show that the figure of merit of this RA-based metasurface sensor can be as high as 15930/RIU. Additionally, we reveal that RA-based plasmonic sensors share some typical characteristics, providing guidance for the structure design. We expect this work advance the development of high-performance plasmonic metasurface sensors., 12 pages, 6 figures, 1 table

The whole process of concrete slump experiment was simulated with Particle Flow Code 3 Dimensions (PFC3D) software based on discrete element simulation. The simulation results are in good agreement with the macroscopic results obtained from field experiments, indicating that the use of PFC software for concrete had the feasibility of slump experiment simulation. The software simulation results have a good observation on the speed and direction of the particles in the process of concrete slump.

Polyadenylation is responsible for regulating mRNA function and translation efficiency. The accurate polyadenylation signal (PAS) recognition is essential for understanding the genome annotation and function. Currently, computational methods mainly rely on human-designed features and do not extract complex discriminative patterns. In this work, we first adopt a shallow neural network to automatically learn biological embedding information with discriminative patterns from biological sequences alone. Next, we devise a hybrid deep learning framework termed PASNet to automatically extract underlying patterns by integrating gated convolutional highway networks with a self-attention mechanism and then identify PAS from genomic sequences. Specifically, we devise a gated convolutional highway unit by gated convolutional mechanisms, and the highway unit has significant paths to allow unimpeded information to pass between two adjacent layers. PASNet requires little prior knowledge and no laborious feature engineering. Besides, we evaluate PASNet on four different organism datasets through genome-wide experiments. Compared to published machine learning and deep learning predictors, results show that our framework achieves the improvement with the error rate decreasing by 4% and 1.02% respectively on average.

In this paper, using H ∞control theory, a robust speed controller with smith predictor is proposed to improve the speed control performance of the permanent magnet synchronous motor (PMSM) servo system with time delay. The robust speed controller is designed to improve the robustness of control system. Meanwhile, considering the time delay of the system, the speed controller combined with smith predictor is used to compensate the impact of system time delay. Firstly, based on theH ∞state space (time domain) method, a robust speed controller is established, which has simple structure and easy to be realized. Secondly, theH ∞robust standard design problem is transformed to an optimization solution of the linear matrix inequalities (LMIs). Thirdly, a smith predictor is stalled at the parallel position of the robust speed controller, which is of great help to improve the performance of the servo system with time delay. Finally, simulation results demonstrate that compared with traditional PI controller, the novel robust controller has better control performance and the robust controller with smith predictor is effective for the PMSM drive system with time delay.

To meet the increasing demand of high-data-rate services of high-speed railway (HSR) passengers, cloud radio access network (C-RAN) is proposed. This paper investigates the tradeoff between energy efficiency (EE) performance and capacity in C-RAN of HSR. Considering that the train location can be predicted, we propose a predictable path loss based time domain power allocation method (PPTPA) to improve EE performance of HSR communication system. First, we consider that the communication system of HSR only bears the passenger information services (PISs). The energy-efficient power allocation problem with delay constraint is studied. The formulated problem is nonconvex. To deal with it, an equivalent convex problem is reformulated. Based on PPTPA, we propose an iterative algorithm to improve the EE performance. Second, we consider that the PISs and the train control services (TCSs) are all bore. A capacity optimization problem with joint EE and services transmission delay constraints is formulated. Based on PPTPA, we propose a hybrid power allocation scheme to improve the capacity of the system. Finally, we analyze the effect of small-scale fading on EE performance. The effectiveness of the proposed power allocation algorithm is validated by HSR channel measurement trace based emulation results and extensive simulation results.

The precision of initial rotor position detection is critical for the start and running performance of permanent magnet synchronous motor (PMSM). This work describes a new open loop approach for identifying the initial position of a PMSM with an incremental encoder, even when a constant load torque is being applied. By giving a testing current with high frequency to the stator winding, the initial rotor position of a PMSM can be detected with reasonable accuracy. The rotor almost does not move during the process of identification. The FFT algorithms are used to remove the phase bias effects in identification. Our approach is quicker and simpler than the conventional approaches.

// Feiling Feng 1, * , Qingbao Cheng 1, * , Liang Yang 1, * , Dadong Zhang 2, 3 , Shunlong Ji 2 , Qiangzu Zhang 2 , Yihui Lin 2 , Fugen Li 2 , Lei Xiong 2 , Chen Liu 1 , Xiaoqing Jiang 1 1 Department of Biliary I, Third Affiliated Hospital of PLA Second Military Medical University, Shanghai, China 2 Division of Translational Medicine, 3D Medicines Corporation, Shanghai, China 3 Changhai Hospital, The Second Military Medical University, Shanghai, China * These authors have contributed equally to this work Correspondence to: Xiaoqing Jiang, email: xqjiang_dandaoyike@163.com Chen Liu, email: chliu_dandaoyike@163.com Lei Xiong, email: simon.t@3dmedcare.com Keywords: gallbladder sarcomatoid carcinoma (GSC), patient-derived cancer cell (PDC), whole exome sequencing (WES), PIK3CA amplification, drug sensitivity Received: September 08, 2016 Accepted: November 22, 2016 Published: December 24, 2016 ABSTRACT Purpose: Gallbladder sarcomatoid carcinoma is a rare cancer with no clinical standard treatment. With the rapid development of next generation sequencing, it has been able to provide reasonable treatment options for patients based on genetic variations. However, most cancer drugs are not approval for gallbladder sarcomatoid carcinoma indications. The correlation between drug response and a genetic variation needs to be further elucidated. Experimental Design: Three patient-derived cells-JXQ-3D-001, JXQ-3D-002, and JXQ-3D-003, were derived from biopsy samples of one gallbladder sarcomatoid carcinoma patient with progression and have been characterized. In order to study the relationship between drug sensitivity and gene alteration, genetic mutations of three patient-derived cells were discovered by whole exome sequencing, and drug screening has been performed based on the gene alterations and related signaling pathways that are associated with drug targets. Results: It has been found that there are differences in biological characteristics such as morphology, cell proliferation, cell migration and colony formation activity among these three patient-derived cells although they are derived from the same patient. Their sensitivities to the chemotherapy drugs-Fluorouracil, Doxorubicin, and Cisplatin are distinct. Moreover, none of common chemotherapy drugs could inhibit the proliferations of all three patient-derived cells. Comprehensive analysis of their whole exome sequencing demonstrated that tumor-associated genes TP53 , AKT2 , FGFR3 , FGF10 , SDHA , and PI3KCA were mutated or amplified. Part of these alterations are actionable. By screening a set of compounds that are associated with the genetic alteration, it has been found that GDC-0941 and PF-04691502 for PI3K-AKT-mTOR pathway inhibitors could dramatically decrease the proliferation of three patient-derived cells. Importantly, expression of phosphorylated AKT and phosphorylated S6 were markedly decreased after treatments with PI3K-AKT-mTOR pathway inhibitors GDC-0941 (0.5 μM) and PF-04691502 (0.1 μM) in all three patient-derived cells. These data suggested that inhibition of the PI3K-AKT-mTOR pathway that was activated by PIK3CA amplification in all three patient-derived cells could reduce the cell proliferation. Conclusions: A patient-derived cell model combined with whole exome sequencing is a powerful tool to elucidate relationship between drug sensitivities and genetic alternations. In these gallbladder sarcomatoid carcinoma patient-derived cells, it is found that PIK3CA amplification could be used as a biomarker to indicate PI3K-AKT-mTOR pathway activation. Block of the pathway may benefit the gallbladder sarcomatoid carcinoma patient with this alternation in hypothesis. The real efficacy needs to be confirmed in vivo or in a clinical trial.

Peripherally inserted central catheters (PICCs) can provide nutritional and medical support for very low birth weight or critically ill newborns. The aim of this study was to retrospectively analyze the use of PICCs in our clinic for critically ill newborns to evaluate the relationship between catheter related factors and the occurrence of complications. Retrospective analysis was conducted for all newborns consecutively admitted at the Neonatal Intensive Care Unit (NICU), Chongqing Health Center for Women and Children, who underwent PICC insertion between May 2011 and March 2018. Data collected included total puncture success rate, one puncture success rate, infection rate, complication rate, unplanned catheter withdrawal rate, device days, and catheter indwelling time. Five-hundred eighty-eight infants (304 males and 284 females) aged 3.4 ± 3.9 days, mean gestational age of 30.9 ± 2.7 weeks and a mean body mass of 1.38 ± 0.47 kg at insertion were included. Total puncture success rate was 99.65%, one puncture success rate was 77.77%. The mean catheter retention was 13.6 ± 6.7 days: more than 30 days in 15 (2.61%) cases, 20 to 30 days in 60 (10.43%) cases, 10 to 19 days in 372 (64.70%) cases, and 62 days in 1 case. Complications occurred in 63 (10.71%) cases: with PICC insertion within 24 hours after birth in 29 (15.43%), within 48 hours in 13 (6.63%), and after 48 hours in 21 (10.99%) cases. Catheter tip culture was positive in 3 cases and there was 1 case of catheter-related bloodstream infection. Nursing measures of the maintenance of body temperature and the evaluation of blood vessels were important conditions for improving the success rate of one puncture in critically ill neonates. PICC catheterization as early as 48 hours will not increase the difficulty of PICC puncture. Nor did it increase the incidence of PICC complications.

Tissue sampling of biliary tract carcinomas (BTCs) for molecular characterization is challenging. The aim of this study was to investigate the possibility of identifying individual actionable mutations derived from bile cell-free DNA (cfDNA) using targeted deep sequencing. Ten BTC patients, four with gallbladder carcinomas and six with cholangiocarcinomas, were enrolled in the present study. Using targeted deep sequencing with a panel of 150 tumor-related genes, paired bile cfDNA and tumor DNA were analyzed for mutational variants individually and then compared. The present study, to the best of our knowledge, is the first to reveal that bile cfDNA is predominantly comprised of long DNA fragments, which is not the case for plasma cfDNA. Herein, paired bile cfDNA and tumors from ten BTC patients were examined using targeted deep sequencing. When comparing bile cfDNA and tumor DNA for single nucleotide variation (SNV)/insertion and deletion (Indel), the results using targeted deep sequencing revealed high sensitivity (94.7%) and specificity (99.9%). Additionally, the sensitivity of detecting a copy number variation (CNV) was 75.0%, with a specificity of 98.9%. When comparing two bile extraction methods, including percutaneous transhepatic cholangial drainage and operation, no significant difference in SNV/Indel or CNV detection sensitivity was noted. Moreover, when examining the tumor stage and incidence site, AJCC stage II and the distal bile duct both had significantly decreased CNV detection sensitivities. The present study revealed that targeted deep sequencing can reliably detect mutational variants within bile cfDNA obtained from BTC patients. These preliminary results may shed light on bile cfDNA as a promising liquid biopsy for BTC patients.

Importance Tumor mutational burden (TMB), as measured by whole-exome sequencing (WES) or a cancer gene panel (CGP), is associated with immunotherapy responses. However, whether TMB estimated by circulating tumor DNA in blood (bTMB) is associated with clinical outcomes of immunotherapy remains to be explored. Objectives To explore the optimal gene panel size and algorithm to design a CGP for TMB estimation, evaluate the panel reliability, and further validate the feasibility of bTMB as a clinical actionable biomarker for immunotherapy. Design, Setting, and Participants In this cohort study, a CGP named NCC-GP150 was designed and virtually validated using The Cancer Genome Atlas database. The correlation between bTMB estimated by NCC-GP150 and tissue TMB (tTMB) measured by WES was evaluated in matched blood and tissue samples from 48 patients with advanced NSCLC. An independent cohort of 50 patients with advanced NSCLC was used to identify the utility of bTMB estimated by NCC-GP150 in distinguishing patients who would benefit from anti–programmed cell death 1 (anti–PD-1) and anti–programmed cell death ligand 1 (anti–PD-L1) therapy. The study was performed from July 19, 2016, to April 20, 2018. Main Outcomes and Measures Assessment of the Spearman correlation coefficient between bTMB estimated by NCC-GP150 and tTMB calculated by WES. Evaluation of the association of bTMB level with progression-free survival and response to anti–PD-1 and anti–PD-L1 therapy. Results This study used 2 independent cohorts of patients with NSCLC (cohort 1: 48 patients; mean [SD] age, 60 [13] years; 15 [31.2%] female; cohort 2: 50 patients; mean [SD] age, 58 [8] years; 15 [30.0%] female). A CGP, including 150 genes, demonstrated stable correlations with WES for TMB estimation (medianr2 = 0.91; interquartile range, 0.89-0.92), especially when synonymous mutations were included (medianr2 = 0.92; interquartile range, 0.91-0.93), whereas TMB estimated by the NCC-GP150 panel found higher correlations with TMB estimated by WES than most of the randomly sampled 150-gene panels. Blood TMB estimated by NCC-GP150 correlated well with the matched tTMB calculated by WES (Spearman correlation = 0.62). In the anti–PD-1 and anti–PD-L1 treatment cohort, a bTMB of 6 or higher was associated with superior progression-free survival (hazard ratio, 0.39; 95% CI, 0.18-0.84; log-rankP = .01) and objective response rates (bTMB ≥6: 39.3%; 95% CI, 23.9%-56.5%; bTMB Conclusions and Relevance The findings suggest that established NCC-GP150 with an optimized gene panel size and algorithm is feasible for bTMB estimation, which may serve as a potential biomarker of clinical benefit in patients with NSCLC treated with anti–PD-1 and anti–PD-L1 agents.