SNHG4-mediated PTEN destabilization confers oxaliplatin resistance in colorectal cancer cells by inhibiting ferroptosis.

Oxaliplatin resistance poses a significant challenge in colorectal cancer (CRC) therapy, necessitating further investigation into the underlying molecular mechanisms. This study aimed to elucidate the regulatory role of SNHG4 in oxaliplatin resistance and ferroptosis in CRC. Our findings revealed that treatment with oxaliplatin led to downregulation of SNHG4 expression in CRC cells, while resistant CRC cells exhibited higher levels of SNHG4 compared to parental cells. Silencing SNHG4 attenuated oxaliplatin resistance and reduced the expression of resistance-related proteins MRD1 and MPR1. Furthermore, induction of ferroptosis effectively diminished oxaliplatin resistance in both parental and resistant CRC cells. Notably, ferroptosis induction resulted in decreased SNHG4 expression, whereas SNHG4 overexpression suppressed ferroptosis. Through FISH, RIP, and RNA pull-down assays, we identified the cytoplasmic localization of both SNHG4 and PTEN, establishing that SNHG4 directly targets PTEN, thereby reducing mRNA stability in CRC cells. Silencing PTEN abrogated the impact of SNHG4 on oxaliplatin resistance and ferroptosis in CRC cells. In vivo experiments further validated the influence of SNHG4 on oxaliplatin resistance and ferroptosis in CRC cells through PTEN regulation. In conclusion, SNHG4 promotes resistance to oxaliplatin in CRC cells by suppressing ferroptosis through instability of PTEN, thus serves as a target for patients with oxaliplatin-base chemoresistance.

Method and system design for spectral imaging based on dual micro-lens array field-of-view segmentation.

The function of a mask in the integral field imaging spectrometer (IFIS), which segments image and samples, leads to the drawback of low spectral energy transmittance. Here, we improve field-of-view segmentation method and propose a dual micro-lens array imaging spectrometer (DMAIS). DMAIS comprises a projection lens (PL), a segmentation collimation module (SCM), and a telecentric lens (TL). And SCM, based on a dual micro-lens array, is the core component of it. By employing a lens array focusing approach instead of aperture sampling, DMAIS effectively enhances energy transmittance and reduces spectral bending. The ZEMAX simulation results indicate that compared to IFIS, DMAIS demonstrates a 109.2% increase in energy transmittance and a 32.9% reduction in spectral bending.

SPINK4 promotes colorectal cancer cell proliferation and inhibits ferroptosis.

BACKGROUND: Little is known about the role of serine peptidase inhibitor Kazal type 4 (SPINK4) in colorectal cancer (CRC) and ferroptosis. Therefore, this study aimed to determine the effect of SPINK4 on CRC pathogenesis and ferroptosis. METHODS: SPINK4 expression was analyzed in public datasets and examined using immunohistochemistry. The biological function of SPINK4 in CRC cell lines and its effect on ferroptosis were tested. An immunofluorescence assay was performed to determine the location of SPINK4 in cells, and mouse models were established to determine the effects of SPINK4 in vivo. RESULTS: CRC datasets and clinical samples analysis revealed that SPINK4 mRNA and protein levels were significantly reduced in CRC tissues compared to control tissues (P < 0.05). Two CRC cell lines (HCT116 and LoVo) were selected, and the in vitro and in vivo experiments showed that overexpression of SPINK4 greatly promotes the proliferation and metastasis of CRC cells and tumor growth (P < 0.05). The immunofluorescence assay indicated that SPINK4 is mainly located in the nucleoplasm and nucleus of CRC cells. Furthermore, SPINK4 expression was reduced after cell ferroptosis induced by Erastin, and overexpression of SPINK4 greatly inhibited ferroptosis in CRC cells. The results of mouse model further demonstrated that SPINK4 overexpression inhibited CRC cell ferroptosis and facilitated tumor growth. CONCLUSIONS: SPINK4 was decreased in CRC tissues and promoted cell proliferation and metastasis; overexpression of SPINK4 inhibited CRC cell ferroptosis.

Retrospect and prospect of aerobic biodegradation of aniline: Overcome existing bottlenecks and follow future trends.

Aniline is a highly bio-toxic industrial product, even at low concentrations, whose related wastewater has been flowing out worldwide on a large scale along with human production. As a green technology, aerobic biological treatment has been widely applied in industrial wastewater and exhibited various characteristics in the field of aniline wastewater. Meanwhile, this technology has shown its potential of synchronous nitrogen removal, but it still consumes energy badly. In the face of resource scarcity, this review comprehensively discusses the existing research in aerobic biodegradation of aniline wastewater to find out the developmental dawn of aerobic biological treatment. Primarily, it put forward the evolution history details of aniline biodegradation from pure culture to mixed culture and then to simultaneous nitrogen removal. On this basis, it presented the existing challenges to further expand the application of aerobic biotechnology, including the confusions of aniline metabolic mechanism, the development of co-degradation of multiple pollutants and the lack of practical experience of bioreactor operation for aniline and nitrogen removal. Additionally, the prospects of the technological shift to meet the needs of an energy-conserving society was described according to existing experiences and feasibility. Including but not limiting to the development of multifunctional bacteria, the reduction of greenhouse gases and the combination of green technologies.

A novel peptide encoded by N6-methyladenosine modified circMAP3K4 prevents apoptosis in hepatocellular carcinoma.

BACKGROUND: Circular RNAs (circRNAs) regulate various biological activities and have been shown to play crucial roles in hepatocellular carcinoma (HCC) progression. However, only a few coding circRNAs have been identified in cancers, and their roles in HCC remain elusive. This study aimed to identify coding circRNAs and explore their function in HCC. METHODS: CircMAP3K4 was selected from the CIRCpedia database. We performed a series of experiments to determine the characteristics and coding capacity of circMAP3K4. We then used in vivo and in vitro assays to investigate the biological function and mechanism of circMAP3K4 and its protein product, circMAP3K4-455aa, in HCC. RESULTS: We found circMAP3K4 to be an upregulated circRNA with coding potential in HCC. IGF2BP1 recognized the circMAP3K4 N6-methyladenosine modification and promoted its translation into circMAP3K4-455aa. Functionally, circMAP3K4-455aa prevented cisplatin-induced apoptosis in HCC cells by interacting with AIF, thus protecting AIF from cleavage and decreasing its nuclear distribution. Moreover, circMAP3K4-455aa was degraded through the ubiquitin-proteasome E3 ligase MIB1 pathway. Clinically, a high level of circMAP3K4 is an independent prognostic factor for adverse overall survival and adverse disease-free survival of HCC patients. CONCLUSIONS: CircMAP3K4 is a highly expressed circRNA in HCC. Driven by m6A modification, circMAP3K4 encoded circMAP3K4-455aa, protected HCC cells from cisplatin exposure, and predicted worse prognosis of HCC patients. Targeting circMAP3K4-455aa may provide a new therapeutic strategy for HCC patients, especially for those with chemoresistance. CircMAP3K4 is a highly expressed circRNA in HCC. Driven by m6A modification, IGF2BP1 facilitates circMAP3K4 peptide translation, then the circMAP3K4 peptide inhibits AIF cleavage and nuclear distribution, preventing HCC cells from cell death under stress and promoting HCC progression.

Insights on Ferroptosis and Colorectal Cancer: Progress and Updates.

Patients with advanced-stage or treatment-resistant colorectal cancer (CRC) benefit less from traditional therapies; hence, new therapeutic strategies may help improve the treatment response and prognosis of these patients. Ferroptosis is an iron-dependent type of regulated cell death characterized by the accumulation of lipid reactive oxygen species (ROS), distinct from other types of regulated cell death. CRC cells, especially those with drug-resistant properties, are characterized by high iron levels and ROS. This indicates that the induction of ferroptosis in these cells may become a new therapeutic approach for CRC, particularly for eradicating CRC resistant to traditional therapies. Recent studies have demonstrated the mechanisms and pathways that trigger or inhibit ferroptosis in CRC, and many regulatory molecules and pathways have been identified. Here, we review the current research progress on the mechanism of ferroptosis, new molecules that mediate ferroptosis, including coding and non-coding RNA; novel inducers and inhibitors of ferroptosis, which are mainly small-molecule compounds; and newly designed nanoparticles that increase the sensitivity of cells to ferroptosis. Finally, the gene signatures and clusters that have predictive value on CRC are summarized.

Fabrication of lanthanum/chitosan co-modified bentonite and phosphorus removal mechanism from low-concentration landscape water.

It is essential to solve the problem of phosphorus pollution in urban landscape water and reduce the degree of eutrophication. In this paper, lanthanum-modified bentonite (La-B) was prepared by high-temperature calcination and liquid-phase precipitation. Then La-B was modified with chitosan to prepare a low-cost environment-friendly functional material: lanthanum/chitosan co-modified bentonite (La-BC). It can reach the adsorption equilibrium within 30 min, and the maximum adsorption capacity is 15.5 mg/g (initial phosphate concentration 50 mg/L); when the target concentration is 2 mg/L, the removal rate can reach 98.5%. La-BC has a stronger anti-interference ability to common coexisting anions SO42-, HCO3-, NO3- and Cl- in the urban landscape water body. La-BC has excellent performance in weakly acidic to neutral water, and its pH applicable range has been improved, making it possible to apply in practical water. The fitting results show that the adsorption behavior conforms to the pseudo-second-order kinetic model and the Freundlich model. After 5 regenerations, the removal efficiency remained around 80%. In the actual water test results, the phosphate concentration can be controlled below 0.1 mg/L and the removal rate is above 75%. Due to its low cost and reusability, it has great potential in the practical application of phosphate removal from landscape water.

Construction of a long noncoding RNA-based competing endogenous RNA network and prognostic signatures of left- and right-side colon cancer.

BACKGROUND: Cancers located on the right and left sides of the colon have distinct clinical and molecular characteristics. This study aimed to explore the regulatory mechanisms of location-specific long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) in colon cancer and identify potential prognostic biomarkers. METHOD: Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between right- and left-side colon cancers were identified by comparing RNA sequencing profiles. Functional enrichment analysis was performed for the DEGs, and a ceRNA network was constructed. Associations between DELs and patient survival were examined, and a DEL-based signature was constructed to examine the prognostic value of these differences. Clinical colon cancer tissues and Gene Expression Omnibus (GEO) datasets were used to validate the results. RESULTS: We identified 376 DELs, 35 DEMs, and 805 DEGs between right- and left-side colon cancers. The functional enrichment analysis revealed the functions and pathway involvement of DEGs. A ceRNA network was constructed based on 95 DEL-DEM-DEG interactions. Three DELs (LINC01555, AC015712, and FZD10-AS1) were associated with the overall survival of patients with colon cancer, and a prognostic signature was established based on these three DELs. High risk scores for this signature indicated poor survival, suggesting that the signature has prognostic value for colon cancer. Examination of clinical colon cancer tissues and GEO dataset analysis confirmed the results. CONCLUSION: The ceRNA regulatory network suggests roles for location-specific lncRNAs in colon cancer and allowed the development of an lncRNA-based prognostic signature, which could be used to assess prognosis and determine treatment strategies in patients with colon cancer.

The Carboxyl Terminus of Tegument Protein pUL21 Contributes to Pseudorabies Virus Neuroinvasion.

Following its entry into cells, pseudorabies virus (PRV) utilizes microtubules to deliver its nucleocapsid to the nucleus. Previous studies have shown that PRV VP1/2 is an effector of dynein-mediated capsid transport. However, the mechanism of PRV for recruiting microtubule motor proteins for successful neuroinvasion and neurovirulence is not well understood. Here, we provide evidence that PRV pUL21 is an inner tegument protein. We tested its interaction with the cytoplasmic light chains using a bimolecular fluorescence complementation (BiFC) assay and observed that PRV pUL21 interacts with Roadblock-1. This interaction was confirmed by coimmunoprecipitation (co-IP) assays. We also determined the efficiency of retrograde and anterograde axonal transport of PRV strains in explanted neurons using a microfluidic chamber system and investigated pUL21's contribution to PRV neuroinvasion in vivo Further data showed that the carboxyl terminus of pUL21 is essential for its interaction with Roadblock-1, and this domain contributes to PRV retrograde axonal transport in vitro and in vivo Our findings suggest that the carboxyl terminus of pUL21 contributes to PRV neuroinvasion.IMPORTANCE Herpesviruses are a group of DNA viruses that infect both humans and animals. Alphaherpesviruses are distinguished by their ability to establish latent infection in peripheral neurons. After entering neurons, the herpesvirus capsid interacts with cellular motor proteins and undergoes retrograde transport on axon microtubules. This elaborate process is vital to the herpesvirus lifecycle, but the underlying mechanism remains poorly understood. Here, we determined that pUL21 is an inner tegument protein of pseudorabies virus (PRV) and that it interacts with the cytoplasmic dynein light chain Roadblock-1. We also observed that pUL21 promotes retrograde transport of PRV in neuronal cells. Furthermore, our findings confirm that pUL21 contributes to PRV neuroinvasion in vivo Importantly, the carboxyl terminus of pUL21 is responsible for interaction with Roadblock-1, and this domain contributes to PRV neuroinvasion. This study offers fresh insights into alphaherpesvirus neuroinvasion and the interaction between virus and host during PRV infection.

The Prediction of the Gas Utilization Ratio based on TS Fuzzy Neural Network and Particle Swarm Optimization.

Gas utilization ratio (GUR) is an important indicator that is used to evaluate the energy consumption of blast furnaces (BFs). Currently, the existing methods cannot predict the GUR accurately. In this paper, we present a novel data-driven model for predicting the GUR. The proposed approach utilized both the TS fuzzy neural network (TS-FNN) and the particle swarm algorithm (PSO) to predict the GUR. The particle swarm algorithm (PSO) is applied to optimize the parameters of the TS-FNN in order to decrease the error caused by the inaccurate initial parameter. This paper also applied the box graph (Box-plot) method to eliminate the abnormal value of the raw data during the data preprocessing. This method can deal with the data which does not obey the normal distribution which is caused by the complex industrial environments. The prediction results demonstrate that the optimization model based on PSO and the TS-FNN approach achieves higher prediction accuracy compared with the TS-FNN model and SVM model and the proposed approach can accurately predict the GUR of the blast furnace, providing an effective way for the on-line blast furnace distribution control.

A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces.

Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF), depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS) to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.

Alumina Concentration Detection Based on the Kernel Extreme Learning Machine.

The concentration of alumina in the electrolyte is of great significance during the production of aluminum. The amount of the alumina concentration may lead to unbalanced material distribution and low production efficiency and affect the stability of the aluminum reduction cell and current efficiency. The existing methods cannot meet the needs for online measurement because industrial aluminum electrolysis has the characteristics of high temperature, strong magnetic field, coupled parameters, and high nonlinearity. Currently, there are no sensors or equipment that can detect the alumina concentration on line. Most companies acquire the alumina concentration from the electrolyte samples which are analyzed through an X-ray fluorescence spectrometer. To solve the problem, the paper proposes a soft sensing model based on a kernel extreme learning machine algorithm that takes the kernel function into the extreme learning machine. K-fold cross validation is used to estimate the generalization error. The proposed soft sensing algorithm can detect alumina concentration by the electrical signals such as voltages and currents of the anode rods. The predicted results show that the proposed approach can give more accurate estimations of alumina concentration with faster learning speed compared with the other methods such as the basic ELM, BP, and SVM.

A lexicon-based diachronic comparison of emotions and sentiments in literary translation: A case study of five Chinese versions of David Copperfield.

In the Chinese context, translations have served as a useful conduit for providing access to wider literature authored in other languages. A prominent question has been whether translators' linguistic choices are influenced by factors such as translators' social and cultural background and emotions towards the texts they are translating. When multiple translations of the same text over a span of time are produced, another layer of complexity is introduced, and research such as the present study, must examine how or whether variation in the expression of emotions within translations produced over a period of time is discernible. To this end, the present study made use of Lexicon-based Sentiment Analysis (LBSA), a common natural language processing (NLP) approach, to study people's attitudes, opinions or emotions towards a certain person or thing. LBSA has attracted much attention in the literary works or translated works for analyzing reader response and appraisal of the works themselves. The present study undertook a diachronic comparison of emotions and sentiments in five translations of David Copperfield based on the emotion lexicons. The corpus of the study comprised translations of five books and 3,084,599 tokens. We applied the computational method of emotion and sentiment analysis to the emotion words in the five translations. In addition, we used python and R package to analyze the positive and negative words in five versions. The study revealed that translators as social beings in the target world express unique reactions towards the same emotion in the original text as well as in literary translations. Yet, the modern vernacular Chinese versions also showcase a similarity in the expression of emotions thus demonstrating the decisive role of the overall flow of emotion in the original plays and in translation. The contribution of the study is significant as it is a pioneering investigation given that it undertakes a sentiment and emotion analysis of literary translations in Chinese.

A 640 nA IQ Output-Capacitor-Less Low Dropout (LDO) Regulator with Sub-Threshold Slew-Rate Enhancement for Narrow Band Internet of Things (NB-IoT) Applications.

An ultra-low quiescent current output-capacitor-less low dropout (OCL-LDO) regulator for power-sensitive applications is proposed in this paper. To improve the gain of the OCL-LDO feedback loop, the error amplifier employs a combination of a cross-coupled input stage for boosting the equivalent input transconductance and a negative resistance technique to improve the gain. Meanwhile, in order to address the issue of transient response of the ultra-low quiescent current OCL-LDO, a sub-threshold slew-rate enhancement circuit is proposed in this paper, which consists of a transient signal input stage and a slew-rate current increase branch. The proposed OCL-LDO is fabricated in a 0.18 µm CMOS process with an effective area of 0.049 mm2. According to the measurement results, the proposed OCL-LDO has a maximum load current of 100 mA and a minimum quiescent current of 640 nA at an input voltage of 1.2 V and an output voltage of 1 V. The overshoot and undershoot voltages are 197 mV and 201 mV, respectively, and the PSR of the OCL-LDO is -72.4 dB at 1 kHz when the load current is 100 µA. In addition, the OCL-LDO has a load regulation of 7.6 µV/mA and a line regulation of 0.87 mV/V.

First-line immune checkpoint inhibitors in low programmed death-ligand 1-expressing population.

Introduction: Inhibitors of programmed cell death 1 (PD1) and its ligand (PDL1) have exhibited favorable long-term survival in many types of advanced-stage cancer and current approvals have to date been granted in certain tumour types irrespective of PD-L1 status. Methods: We extracted the following information: study sample size, trial period, cancer types, intervention of treatment, type of PD-L1 antibody, immunohistochemistry (IHC) scoring method, number and percentage of PD-L1 < 1% population, and median follow- up time. PD-L1 expression was defined as percentage of number of PD-L1-stained tumor cells (TPS), area of tumor infiltrated by PD-L1-stained immune cells (IPS), number of PD-L1-stained cells (tumor cells, lymphocytes and macrophages; CPS). Different trials used distinct method to define low PD-L1 expression. The risk of bias of the included trials was assessed by using the Cochrane risk of bias tool for RCTs. Results: Here, a total of 34 trials were included to extract individual patient data (IPD) to evaluate the survival benefit of first line PD1/PDL1 inhibitors vs. standard-of-care (SOC) in patients with PDL1 < 1%. In term of anti-PD-1/PD-L1 monotherapy, OS (HR = 0.90, 0.81-1.01) and PFS (HR = 1.11, 0.97-1.27) between PD-1/PD-L1 inhibitor group and SOC group were comparable. In term of anti-PD-1/PD-L1 combination therapy, PD-1/PD-L1 inhibitor group exhibited longer OS (median 19.5 months vs. 16.3 months; HR = 0.83, 0.79-0.88, p < 0.001) and PFS than those of SOC group (median 8.11 months vs. 6.96 months; HR = 0.82, 0.77-0.87, p < 0.001).Subgroup analysis showed that survival benefit was mainly observed in non-small cell lung cancer (NSCLC) (HROS = 0.74; HRPFS = 0.69; p < 0.001), small-cell lung cancer (SCLC) (HROS = 0.58, p < 0.001; HRPFS = 0.55, p = 0.030), esophageal squamous cell carcinoma (ESCC) (HROS = 0.62, p = 0.005; HRPFS = 0.79, p < 0.001), melanoma (HROS = 0.53, p < 0.001) and nasopharyngeal carcinoma (NPC) (HRPFS = 0.35, p = 0.013). Conclusion: Anti-PD-1/PD-L1 combinational therapy rather than monotherapy exhibit survival benefit in the low PD-L1 population in the first-line setting, and the survival benefit was mainly observed in specific tumor types.

Analyzing the factors influencing speeding behavior based on quasi-induced exposure and random parameter logit model with heterogeneity in means.

INTRODUCTION: Speeding behavior is a major threat to road traffic safety, which can increase crash risks and result in severe injury outcomes. Although several studies have been conducted to analyze speeding crashes and relevant influential factors, the heterogeneity of variables has not been fully explored. Based on the traffic crash data extracted from the Crash Report Sampling System, the study aims to identify the factors that influence speeding driving with the consideration of variable heterogeneity. METHOD: Quasi-induced exposure technique is adopted to identify the disparities in the propensities of speeding for various driving cohorts. The random parameter logit model with heterogeneity in means is employed to examine the factors impacting speeding behavior. RESULTS: Results indicate that: (a) driving cohorts such as young drivers, male drivers, passenger cars, and pickups appear to have higher propensities of engaging in speeding driving; (b) the propensity of speeding is higher when the driver is drinking, distracted, changing lanes, negotiating a curve, driving in lighted condition, and on curved roads; and (c) the random parameter logit model with heterogeneity in means has better performance as opposed to that without heterogeneity in means. CONCLUSIONS: Speeding behavior can be influenced by various factors in terms of driver-vehicle characteristics, physical condition, driving actions, and environmental conditions. PRACTICAL APPLICATIONS: The findings could serve to develop effective countermeasures to reduce speeding behavior and improve traffic safety.

lncRNA SNHG4 inhibits ferroptosis by orchestrating miR-150-5p/c-Myb axis in colorectal cancer.

LncRNAs have shown to regulate ferroptosis in colorectal cancer (CRC), but the mechanism remains largely unknown. This study unveiled the mechanism of SNHG4 underlying ferroptosis in CRC. RNA-seq and RT-PCR assay confirmed SNHG4 was decreased after Erastin treatment in CRC cells. Overexpression of SNHG4 inhibited and silence promoted CRC cells ferroptosis. SNHG4 was positively correlated to c-Myb in CRC tissues and both located in cytoplasm of CRC cells. RIP and RNA pull-down assays verified the interaction between SNHG4 and c-Myb. Silence of c-Myb alleviated the suppressing effect on ferroptosis by SNHG4 in CRC cells. Dual-luciferase reporter assay revealed that SNHG4 sponging miR-150-5p in CRC cells. Overexpression of SNHG4 decreased the miR-150-5p and increased c-Myb expression. c-Myb was a direct target gene of miR-150-5p in CRC cells. Moreover, effect of CDO1 on ferroptosis was regulated transcriptionally by c-Myb, overexpression of c-Myb reduce CDO1 expression and enhance the GPX4 levels. The animal models confirmed that regulatory effect of SNHG4 on miR-150-5p and c-Myb after inducing ferroptosis. We concluded that SNHG4 inhibited Erastin-induce ferroptosis in CRC, this effect is via sponging miR-150-5p to regulate c-Myb expression, and activated CDO1/GPX4 axis. These findings provide insights into the regulatory mechanism of SNHG4 on ferroptosis.

[Study on syndrome quantification, differentiation and classification of traditional Chinese medicine with data envelopment analysis].

To raise the syndrome sequence quantification, differentiation and classification algorithm based on data envelopment analysis for solving the modeling issue of syndrome differentiation and classification of traditional Chinese medicine (TCM). This algorithm has three steps: first, in order to obtain basic units for explaining pathogenesis, and establish a syndrome collection on this basis mechanisms of syndrome differentiation and classification were analyzed and classified according to TCM theory, mechanisms of syndrome differentiation and classification were analyzed and classified according to TCM theory; second, regularity and syndromes of corresponding prescriptions were sought according to the incidence and development progress of syndromes, and mathematical tools of data envelopment analysis were used to calculate state data of syndromes in each stage and obtain quantitative syndrome sequence; finally, syndrome sequence was taken as the measurement standard to quantify candidate syndromes and diagnostic information, and the similarity was calculated to obtain the matching degree between diagnostic information and candidate syndromes, so as to complete the syndrome differentiation and classification calculation. According to the results of model-based reasoning, the algorithm could indicate the regularity implied in prescription materials, and grasp the dynamic process of syndromes in an all-round way, and its results were verified through calculation and analysis on clinical cases. At least, it provides an idea for quantitative modeling of TCM.

Distributed Neural-Network-Based Cooperation Control for Teleoperation of Multiple Mobile Manipulators Under Round-Robin Protocol.

This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data transmission from the multiple slaves to the master. The control task is to guarantee the task-space position synchronization between the master and the grasped object with the mobile bases in a fixed formation. A fully distributed control strategy including neural-network-based task-space synchronization controllers and neural-network-based null-space formation controllers is proposed, where the radial basis function (RBF) neural networks with adaptive estimation of approximation errors are used to compensate the dynamical uncertainties. The stability and the synchronization/formation features of the single-master-multiple-slaves (SMMS) teleoperation system are analyzed, and the relationship among the control parameters, the upper bound of the time delays, and the maximum allowable sampling interval is established. Experiments are implemented to validate the effectiveness of the proposed control algorithm.

STAG2 Regulates Homologous Recombination Repair and Sensitivity to ATM Inhibition.

Stromal antigen 2 (STAG2), a subunit of the cohesin complex, is recurrently mutated in various tumors. However, the role of STAG2 in DNA repair and its therapeutic implications are largely unknown. Here it is reported that knockout of STAG2 results in increased double-stranded breaks (DSBs) and chromosomal aberrations by reducing homologous recombination (HR) repair, and confers hypersensitivity to inhibitors of ataxia telangiectasia mutated (ATMi), Poly ADP Ribose Polymerase (PARPi), or the combination of both. Of note, the impaired HR by STAG2-deficiency is mainly attributed to the restored expression of KMT5A, which in turn methylates H4K20 (H4K20me0) to H4K20me1 and thereby decreases the recruitment of BRCA1-BARD1 to chromatin. Importantly, STAG2 expression correlates with poor prognosis of cancer patients. STAG2 is identified as an important regulator of HR and a potential therapeutic strategy for STAG2-mutant tumors is elucidated.