Heart rate patterns of captive Asian elephant (Elephas maximus) in their natural habitat at Wild Elephant Valley, Xishuangbanna of China

There are few studies on the changes of heart rate of the Asian elephant (Elephas maximus), one of the largest tropical terrestrial mammals, with its self-factors and external environment. By measuring the heart rate of 35 Asian elephants, ranging in age from 4 months to 52 years, using a non-invasive electrocardiogram sensor in their natural habitat at Wild Elephant Valley, Xishuangbanna of China, we found factors that significantly influenced the HR were season, phase of the day, age, body weight, and the interaction between some of the above factors. We also observed that Asian elephants had lower resting heart rate in the morning of hot season than the cold and mild season, and the differences were significant, but the heart rate increased to similar levels in the afternoon regardless of the season. HR also decreased with age in all seasons and phases of the day. However, there was no significant effect of sex. This study reveals the adaptability of Asian elephant to tropical environment, and provides a basic reference for heart rate of Asian elephant under various natural conditions.

Flexible Metasurfaces for Multifunctional Interfaces

Optical metasurfaces, capable of manipulating the properties of light with a thickness at the subwavelength scale, have been the subject of extensive investigation in recent decades. This research has been mainly driven by their potential to overcome the limitations of traditional, bulky optical devices. However, most existing optical metasurfaces are confined to planar and rigid designs, functions, and technologies, which greatly impede their evolution toward practical applications that often involve complex surfaces. The disconnect between two-dimensional (2D) planar structures and three-dimensional (3D) curved surfaces is becoming increasingly pronounced. In the past two decades, the emergence of flexible electronics has ushered in an emerging era for metasurfaces. This review delves into this cutting-edge field, with a focus on both flexible and conformal design and fabrication techniques. Initially, we reflect on the milestones and trajectories in modern research of optical metasurfaces, complemented by a brief overview of their theoretical underpinnings and primary classifications. We then showcase four advanced applications of optical metasurfaces, emphasizing their promising prospects and relevance in areas such as imaging, biosensing, cloaking, and multifunctionality. Subsequently, we explore three key trends in optical metasurfaces, including mechanically reconfigurable metasurfaces, digitally controlled metasurfaces, and conformal metasurfaces. Finally, we summarize our insights on the ongoing challenges and opportunities in this field.

Application of the cell-based RT-qPCR assay (C-QPA) for potency detection of the novel trivalent rotavirus vaccine in China

BACKGROUND

Because of the deficiencies of traditional methods in multivalent rotavirus vaccine potency detection, a cell-based quantitative RT-qPCR assay (C-QPA) was established and validated for specificity, precision, and accuracy.

METHODS

In order to further validate the robustness of this method in actual titer detection, the linear range and the practical application under different conditions were tested using monovalent and trivalent rotavirus samples and standards.

RESULTS

Results showed that the linear range was 2.0-6.5, 3.9-8.3, and 3.5-8.1 UI (unit of infectivity) for G2, G3, and G4, respectively. Besides, unknown sample with high titer exceeding the linear range can be calculated by dilution. The UIs of serotypes G2, G3, and G4 in monovalent and trivalent rotavirus samples showed a relative deviation ≤4.10%, and the monovalent samples of the same serotype with or without protective agents showed a relative deviation ≤4.28%; the coefficient of variation (CV) of at least 176 tests (548 individual runs) of 3 in vitro-transcribed RNA standards with certain concentrations was not higher than 6.50%; the results of the trivalent samples tested by more than 149 times in 5 years (467 individual runs) showed the CVs lower than 12.66%; 15 samples detected by one laboratory showed a CV lower than 9.83%, while other three samples tested by two independent laboratories showed a CV lower than 6.90%.

CONCLUSION

In summary, the C-QPA has good linearity, durability, repeatability, and reproducibility in practical application and has been proved by the authority to be widely used in the production, quality control and release of the recently licensed trivalent vaccine in China.

The efficacy of hydrogen/oxygen therapy favored the recovery of omicron SARS-CoV-2 variant infection: results of a multicenter, randomized, controlled trial

Clinical studies had found that hydrogen/oxygen mixed inhalation was beneficial to ameliorate the respiratory symptoms in the adjuvant treatment of patients with COVID-19. We aimed to explore the efficacy of hydrogen/oxygen therapy in favoring the recovery of Omicron SARS-CoV-2 variant infection. There were 64 patients who randomly assigned to receive hydrogen/oxygen inhalation (32 patients) and oxygen inhalation (32 patients). The average shedding duration of Omicron in hydrogen/oxygen group was shorter than oxygen group. The trend of cumulative negative conversion rate of Omicron increased gradually after the third day. The IL-6 levels in hydrogen/oxygen group decreased by 22.8% compared with the baseline. After hydrogen/oxygen mixed gas inhalation, the lymphocyte count increased to 61.1% of the baseline on the 3rd day in the hydrogen/oxygen group. More patients in the hydrogen/oxygen group had resolution of pulmonary lesions. Our study showed the beneficial trends of molecular hydrogen in treating patients with COVID-19, which may offer a prospective solution to adjuvant therapy for COVID-19 Patients.

AFTR: A Robustness Multi-Sensor Fusion Model for 3D Object Detection Based on Adaptive Fusion Transformer

Multi-modal sensors are the key to ensuring the robust and accurate operation of autonomous driving systems, where LiDAR and cameras are important on-board sensors. However, current fusion methods face challenges due to inconsistent multi-sensor data representations and the misalignment of dynamic scenes. Specifically, current fusion methods either explicitly correlate multi-sensor data features by calibrating parameters, ignoring the feature blurring problems caused by misalignment, or find correlated features between multi-sensor data through global attention, causing rapidly escalating computational costs. On this basis, we propose a transformer-based end-to-end multi-sensor fusion framework named the adaptive fusion transformer (AFTR). The proposed AFTR consists of the adaptive spatial cross-attention (ASCA) mechanism and the spatial temporal self-attention (STSA) mechanism. Specifically, ASCA adaptively associates and interacts with multi-sensor data features in 3D space through learnable local attention, alleviating the problem of the misalignment of geometric information and reducing computational costs, and STSA interacts with cross-temporal information using learnable offsets in deformable attention, mitigating displacements due to dynamic scenes. We show through numerous experiments that the AFTR obtains SOTA performance in the nuScenes 3D object detection task (74.9% NDS and 73.2% mAP) and demonstrates strong robustness to misalignment (only a 0.2% NDS drop with slight noise). At the same time, we demonstrate the effectiveness of the AFTR components through ablation studies. In summary, the proposed AFTR is an accurate, efficient, and robust multi-sensor data fusion framework.

A Large-Scale Sensor Layout Optimization Algorithm for Improving the Accuracy of Inverse Finite Element Method

The inverse finite element method (iFEM) based on fiber grating sensors has been demonstrated as a shape sensing method for health monitoring of large and complex engineering structures. However, the existing optimization algorithms cause the local optima and low computational efficiency for high-dimensional strain sensor layout optimization problems of complex antenna truss models. This paper proposes the improved adaptive large-scale cooperative coevolution (IALSCC) algorithm to obtain the strain sensors deployment on iFEM, and the method includes the initialization strategy, adaptive region partitioning strategy, and gbest selection and particle updating strategies, enhancing the reconstruction accuracy of iFEM for antenna truss structure and algorithm efficiency. The strain sensors optimization deployment on the antenna truss model for different postures is achieved, and the numerical results show that the optimization algorithm IALSCC proposed in this paper can well handle the high-dimensional sensor layout optimization problem.

Coarse and Fine Two-Stage Calibration Method for Enhancing the Accuracy of Inverse Finite Element Method

The inverse finite element method (iFEM) is a novel method for reconstructing the full-field displacement of structures by discrete measurement strain. In practical engineering applications, the accuracy of iFEM is reduced due to the positional offset of strain sensors during installation and errors in structural installation. Therefore, a coarse and fine two-stage calibration (CFTSC) method is proposed to enhance the accuracy of the reconstruction of structures. Firstly, the coarse calibration is based on a single-objective particle swarm optimization algorithm (SOPSO) to optimize the displacement-strain transformation matrix related to the sensor position. Secondly, as selecting different training data can affect the training effect of self-constructed fuzzy networks (SCFN), this paper proposes to screen the appropriate training data based on residual analysis. Finally, the experiments of the wing-integrated antenna structure verify the efficiency of the method on the reconstruction accuracy of the structural body displacement field.

Mutational landscape of SWI/SNF complex genes reveal correlation to predictive biomarkers for immunotherapy sensitivity in lung adenocarcinoma patients

BACKGROUND

The search for prognostic biomarkers indicating sensitivity to immunotherapy in lung adenocarcinoma patients has zeroed in on genes in the switch/sucrose non-fermentable (SWI/SNF) pathway. The mutational profiles of key genes are not clearly defined, however, and no comparisons have been conducted on whether mutations in the genes involved provide the same predictive value.

METHODS

In this study, analysis of clinical factors, tumor mutation burden (TMB), chromosomal instability, and co-alterations was conducted for 4344 lung adenocarcinoma samples. Independent online cohorts (N = 1661 and 576) were used to supplement the analysis with survival and RNA-seq data.

RESULTS

Mutational burden and chromosomal instability analysis showed that ARID family mutations (including ARID1A, ARID1B, or ARID2 mutations) and SMARC family mutations (including SMARCA4 or SMARCB1 mutations) display different profiles from wild-type (WT) samples (TMB: ARID versus WT: P < 2.2 × 10^-16, SMARC versus WT: P < 2.2 × 10^-16; CIN: ARID versus WT: P = 1.8 × 10^-5, SMARC versus WT: P = 0.027). Both mutant groups have a higher proportion of transversions than transitions, whereas the ratio is more equal for wild-type samples. Survival analysis shows that patients with ARID mutations were more sensitive to immunotherapy treatment than wild-type and SMARC-mutated patients (P < 0.001 and P = 0.013, respectively), and multivariate Cox analysis reveals that the presence of ARID mutations is likely the main cause.

CONCLUSIONS

The research presented in this study shows that mutations in the ARID gene family, including ARID1A, ARID1B, and ARID2, are primarily responsible for the sensitive response to immunotherapy treatment in patients with lung adenocarcinoma.

An Online Measurement and Calibration Method for a Radio Telescope Sub-Reflector Support Structure Using Fiber Bragg Grating

The position and altitude of a sub-reflector have an important influence on the pointing accuracy of a radio telescope. With the increase of the antenna aperture, the stiffness of the support structure for the sub-reflector decreases. This causes deformation of the support structure when environmental loads, such as gravity, temperature, and wind load, are applied to the sub-reflector, which will seriously influence antenna pointing accuracy. This paper proposes an online measurement and calibration method for assessing the deformation of the sub-reflector support structure based on the Fiber Bragg Grating (FBG) sensors. Firstly, a reconstruction model between the strain measurements and the deformation displacements of a sub-reflector support structure is established based on the inverse finite element method (iFEM). In addition, a temperature-compensating device with an FBG sensor is designed to eliminate the effects of temperature variations on strain measurements. Considering the lack of the trained original correction, a non-uniform rational B spline (NURBS) curve is built to extend the sample data set. Next, a self-structuring fuzzy network (SSFN) is designed for calibrating the reconstruction model, which can further improve the displacement reconstruction accuracy of the support structure. Finally, a full-day experiment was carried out using a sub-reflector support model to verify the effectiveness of the proposed method.

VV116 versus Nirmatrelvir-Ritonavir for Oral Treatment of Covid-19

BACKGROUND

Nirmatrelvir-ritonavir has been authorized for emergency use by many countries for the treatment of coronavirus disease 2019 (Covid-19). However, the supply falls short of the global demand, which creates a need for more options. VV116 is an oral antiviral agent with potent activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

METHODS

We conducted a phase 3, noninferiority, observer-blinded, randomized trial during the outbreak caused by the B.1.1.529 (omicron) variant of SARS-CoV-2. Symptomatic adults with mild-to-moderate Covid-19 with a high risk of progression were assigned to receive a 5-day course of either VV116 or nirmatrelvir-ritonavir. The primary end point was the time to sustained clinical recovery through day 28. Sustained clinical recovery was defined as the alleviation of all Covid-19-related target symptoms to a total score of 0 or 1 for the sum of each symptom (on a scale from 0 to 3, with higher scores indicating greater severity; total scores on the 11-item scale range from 0 to 33) for 2 consecutive days. A lower boundary of the two-sided 95% confidence interval for the hazard ratio of more than 0.8 was considered to indicate noninferiority (with a hazard ratio of >1 indicating a shorter time to sustained clinical recovery with VV116 than with nirmatrelvir-ritonavir).

RESULTS

A total of 822 participants underwent randomization, and 771 received VV116 (384 participants) or nirmatrelvir-ritonavir (387 participants). The noninferiority of VV116 to nirmatrelvir-ritonavir with respect to the time to sustained clinical recovery was established in the primary analysis (hazard ratio, 1.17; 95% confidence interval [CI], 1.01 to 1.35) and was maintained in the final analysis (median, 4 days with VV116 and 5 days with nirmatrelvir-ritonavir; hazard ratio, 1.17; 95% CI, 1.02 to 1.36). In the final analysis, the time to sustained symptom resolution (score of 0 for each of the 11 Covid-19-related target symptoms for 2 consecutive days) and to a first negative SARS-CoV-2 test did not differ substantially between the two groups. No participants in either group had died or had had progression to severe Covid-19 by day 28. The incidence of adverse events was lower in the VV116 group than in the nirmatrelvir-ritonavir group (67.4% vs. 77.3%).

CONCLUSIONS

Among adults with mild-to-moderate Covid-19 who were at risk for progression, VV116 was noninferior to nirmatrelvir-ritonavir with respect to the time to sustained clinical recovery, with fewer safety concerns. (Funded by Vigonvita Life Sciences and others; ClinicalTrials.gov number, NCT05341609; Chinese Clinical Trial Registry number, ChiCTR2200057856.).

Unmasking BACE1 in aging and age-related diseases

The beta-site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) has long been considered a conventional target for Alzheimer's disease (AD). Unfortunately, AD clinical trials of most BACE1 inhibitors were discontinued due to ineffective cognitive improvement or safety challenges. Recent studies investigating the involvement of BACE1 in metabolic, vascular, and immune functions have indicated a role in aging, diabetes, hypertension, and cancer. These novel BACE1 functions have helped to identify new 'druggable' targets for BACE1 against aging comorbidities. In this review, we discuss BACE1 regulation during aging, and then provide recent insights into its enzymatic and nonenzymatic involvement in aging and age-related diseases. Our study not only proposes the perspective of BACE1's actions in various systems, but also provides new directions for using BACE1 inhibitors and modulators to delay aging and to treat age-related diseases.

A fault detection method based on the self-organizing fuzzy Luenberger for the generalized linear discrete time system with disturbances

A novel for an integrated fault and states estimator was proposed for the generalized linear discrete-time system with disturbances. The proposed scheme was based on a Self-Organizing fuzzy Luenberger system to estimate the states and approximate the fault information simultaneously for the generalized linear discrete-time system. For this purpose, a generalized linear discrete-time system with disturbances was transformed into an equivalent standard state-space system with disturbances and faults. Then, the faults and disturbances of generalized linear discrete-time system can be separated with the coordinate transform, meanwhile the Self-Organizing fuzzy Luenberger estimator was designed to obtain the accurate fault information. Based on the obtained fault information, the fault detection experiments were performed, and the fault feature parameters required for fault isolation were determined. Finally, the proposed strategy was applied for a direct current motor to demonstrate the effectiveness of the proposed approach.

Adaptive synapse-based neuron model with heterogeneous multistability and riddled basins

Biological neurons can exhibit complex coexisting multiple firing patterns dependent on initial conditions. To this end, this paper presents a novel adaptive synapse-based neuron (ASN) model with sine activation function. The ASN model has time-varying equilibria with the variation of externally applied current and its equilibrium stability involves transitions between stable and unstable points through fold and Hopf bifurcations, resulting in complex distributions of attractive regions with heterogeneous multi-stability. Globally coexisting heterogeneous behaviors are studied by bifurcation diagram, phase portrait, dynamical distribution, and basin of attraction. The results show that the number of coexisting heterogeneous attractors can be up to 12, but for a simple neuron model, such a large number of coexisting heterogeneous attractors has not been reported in the relevant literature. Most interestingly, the ASN model also has riddled-like complex basins of attraction and four illustrative examples are depicted by the phase portraits with small changes of the initial conditions. Besides, the ASN model is implemented using a simple microcontroller platform, and various heterogeneous coexisting attractors are acquired experimentally to validate the numerical results.

The state of the art in beyond 5G distributed massive multiple-input multiple-output communication system solutions

Beyond fifth generation (5G) communication systems aim towards data rates in the tera bits per second range, with improved and flexible coverage options, introducing many new technological challenges in the fields of network architecture, signal pro- cessing, and radio frequency front-ends. One option is to move towards cell-free, or distributed massive Multiple-Input Multiple-Output (MIMO) network architectures and highly integrated front-end solutions. This paper presents an outlook on be- yond 5G distributed massive MIMO communication systems, the signal processing, characterisation and simulation challenges, and an overview of the state of the art in millimetre wave antennas and electronics.

DetectFormer: Category-Assisted Transformer for Traffic Scene Object Detection

Object detection plays a vital role in autonomous driving systems, and the accurate detection of surrounding objects can ensure the safe driving of vehicles. This paper proposes a category-assisted transformer object detector called DetectFormer for autonomous driving. The proposed object detector can achieve better accuracy compared with the baseline. Specifically, ClassDecoder is assisted by proposal categories and global information from the Global Extract Encoder (GEE) to improve the category sensitivity and detection performance. This fits the distribution of object categories in specific scene backgrounds and the connection between objects and the image context. Data augmentation is used to improve robustness and attention mechanism added in backbone network to extract channel-wise spatial features and direction information. The results obtained by benchmark experiment reveal that the proposed method can achieve higher real-time detection performance in traffic scenes compared with RetinaNet and FCOS. The proposed method achieved a detection performance of 97.6% and 91.4% in AP50 and AP75 on the BCTSDB dataset, respectively.

Structural and Functional Characterization of a Novel Scorpion Toxin that Inhibits NaV1.8 via Interactions With the DI Voltage Sensor and DII Pore Module

Voltage-gated sodium channel Na_V1.8 regulates transmission of pain signals to the brain. While Na_V1.8 has the potential to serve as a drug target, the molecular mechanisms that shape Na_V1.8 gating are not completely understood, particularly mechanisms that couple activation to inactivation. Interactions between toxin producing animals and their predators provide a novel approach for investigating Na_V structure-function relationships. Arizona bark scorpions produce Na⁺ channel toxins that initiate pain signaling. However, in predatory grasshopper mice, toxins inhibit Na_V1.8 currents and block pain signals. A screen of synthetic peptide toxins predicted from bark scorpion venom showed that peptide NaTx36 inhibited Na⁺ current recorded from a recombinant grasshopper mouse Na_V1.8 channel (OtNa_V1.8). Toxin NaTx36 hyperpolarized OtNa_V1.8 activation, steady-state fast inactivation, and slow inactivation. Mutagenesis revealed that the first gating charge in the domain I (DI) S4 voltage sensor and an acidic amino acid (E) in the DII SS2 – S6 pore loop are critical for the inhibitory effects of NaTx36. Computational modeling showed that a DI S1 – S2 asparagine (N) stabilizes the NaTx36 – OtNa_V1.8 complex while residues in the DI S3 – S4 linker and S4 voltage sensor form electrostatic interactions that allow a toxin glutamine (Q) to contact the first S4 gating charge. Surprisingly, the models predicted that NaTx36 contacts amino acids in the DII S5 – SS1 pore loop instead of the SS2 – S6 loop; the DII SS2 – S6 loop motif (QVSE) alters the conformation of the DII S5 – SS1 pore loop, enhancing allosteric interactions between toxin and the DII S5 – SS1 pore loop. Few toxins have been identified that modify Na_V1.8 gating. Moreover, few toxins have been described that modify sodium channel gating via the DI S4 voltage sensor. Thus, NaTx36 and OtNa_V1.8 provide tools for investigating the structure-activity relationship between channel activation and inactivation gating, and the connection to alternative pain phenotypes.

Endothelial BACE1 Impairs Cerebral Small Vessels via Tight Junctions and eNOS

BACKGROUND

Cerebral small vessel injury, including loss of endothelial tight junctions, endothelial dysfunction, and blood-brain barrier breakdown, is an early and typical pathology for Alzheimer disease, cerebral amyloid angiopathy, and hypertension-related cerebral small vessel disease. Whether there is a common mechanism contributing to these cerebrovascular alterations remains unclear. Studies have shown an elevation of BACE1 (β-site amyloid precursor protein cleaving enzyme 1) in cerebral vessels from cerebral amyloid angiopathy or Alzheimer disease patients, suggesting that vascular BACE1 may involve in cerebral small vessel injury.

METHODS

To understand the contribution of vascular BACE1 to cerebrovascular impairments, we combined cellular and molecular techniques, mass spectrometry, immunostaining approaches, and functional testing to elucidate the potential pathological mechanisms.

RESULTS

We observe a 3.71-fold increase in BACE1 expression in the cerebral microvessels from patients with hypertension. Importantly, we discover that an endothelial tight junction protein, occludin, is a completely new substrate for endothelial BACE1. BACE1 cleaves occludin with full-length occludin reductions and occludin fragment productions. An excessive cleavage by elevated BACE1 induces membranal accumulation of caveolin-1 and subsequent caveolin-1-mediated endocytosis, resulting in lysosomal degradation of other tight junction proteins. Meanwhile, membranal caveolin-1 increases the binding to eNOS (endothelial nitric oxide synthase), together with raised circulating Aβ (β-amyloid peptides) produced by elevated BACE1, leading to an attenuation of eNOS activity and resultant endothelial dysfunction. Furthermore, the initial endothelial damage provokes chronic reduction of cerebral blood flow, blood-brain barrier leakage, microbleeds, tau hyperphosphorylation, synaptic loss, and cognitive impairment in endothelial-specific BACE1 transgenic mice. Conversely, inhibition of aberrant BACE1 activity ameliorates tight junction loss, endothelial dysfunction, and memory deficits.

CONCLUSIONS

Our findings establish a novel and direct relationship between endothelial BACE1 and cerebral small vessel damage, indicating that abnormal elevation of endothelial BACE1 is a new mechanism for cerebral small vessel disease pathogenesis.

Real-world circulating tumor DNA analysis depicts resistance mechanism and clonal evolution in ALK inhibitor-treated lung adenocarcinoma patients

Background

Sequential treatment with different generations of anaplastic lymphoma kinase (ALK) inhibitors have been widely applied to ALK-positive lung cancer; however, resistance mutations inevitably developed. Further characterization of ALK resistance mutations may provide key guidance to subsequent therapies. Here we explored the emergence of secondary ALK mutations during sequential ALK tyrosine kinase inhibitor (TKI) treatment in a real-world study of Chinese lung adenocarcinoma (ADC) patients.

Methods

A clinical-genomic database was queried for lung ADC patients with at least one ALK inhibitor treatment and at least one plasma sample collected following ALK inhibitor treatment. Targeted genome profiling was performed with a 139-gene panel in baseline tumor tissue and serial plasma samples of patients.

Results

A total of 116 patients met inclusion criteria. ALK G1202R was more common in patients with echinoderm microtubule-associated protein-like 4 (EML4)-ALK v3 fusion, whereas ALK L1196M was more common in v1. TP53 mutant patients were significantly associated with harboring multiple ALK resistance mutations (P = 0.03) and v3+/TP53 mutant patients had the highest rate of multiple ALK resistance mutations. The sequential use of ALK TKI led to an increased incidence of concurrent ALK mutations along the lines of therapies. Alectinib had a lower rate (9%) harboring ALK resistance mutation as first-line ALK TKI compared with crizotinib (36%). ALK compound mutations identified included ALK D1203N/L1196M, ALK G1202R/L1196M, and ALK G1202R/F1174C, which may be lorlatinib resistant. Using paired pretreatment and post-treatment samples, we identified several ALK-independent resistance-related genetic alterations, including PTPRD and CNKN2A/B loss, MYC, MYCN and KRAS amplification, and EGFR^19del.

Conclusions

Sequential postprogression plasma profiling revealed that increased lines of ALK inhibitors can accelerate the accumulation of ALK resistance mutations and may lead to treatment-refractory compound ALK mutations. The selection for optimal first-line TKI is very important to achieve a more efficacious long-term strategy and prevent the emergence of on-target resistance, which may provide guidance for clinical decision making.

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ALK resistance mutations were differentially enriched in the setting of EML4-ALK v1/v3 and TP53 status.

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Serial liquid biopsies NGS depicted accumulation of multiple ALK secondary mutations during sequential ALK treatments.

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Several lorlatinib-resistant ALK compound mutations and ALK-independent resistance genetic alterations were identified.

Distribution of COPD Comorbidities and Creation of Acute Exacerbation Risk Score: Results from SCICP

Background

Chronic obstructive pulmonary disease (COPD) often coexists with multiple comorbidities which may have a significant impact on acute exacerbations of patients. At present, what kind of comorbidities affects acute exacerbations and how comorbidities lead to poor prognosis are still controversial. The purpose of our study is to determine the impact of comorbidities on COPD exacerbation and establish an acute exacerbation risk assessment system related to comorbidities.

Methods

A total of 742 COPD patients participated in the Shanghai COPD Investigation on Comorbidity Program (SCICP, ChiCTR2000030911). Finally, the baseline information of 415 participants and one-year follow-up data were involved in the analysis. We collected hemogram indices, pulmonary function tests and acute exacerbation of COPD with regular medical follow-up. Q-type cluster analysis was used to determine the clusters of participants. Receiver operating characteristic (ROC) analysis was constructed to assess the ability of indicators in predicting acute exacerbations.

Results

Almost 65% of the population we investigated had at least one comorbidity. The distribution and incidence of comorbidities differed between exacerbation group and non-exacerbation group. Three comorbidity clusters were identified: (1) respiratory, metabolic, immune and psychologic disease (non-severe cases); (2) cardiovascular and neoplastic disease (severe cases); (3) less comorbidity. Different sub-phenotypes of COPD patients showed significant distinction in health status. Anxiety (OR=5.936, P=0.001), angina (OR=10.155, P=0.025) and hypertension (OR=3.142, P=0.001) were found to be independent risk factors of exacerbation in a year. The novel risk score containing BODEx and four diseases showed great prognostic value of COPD exacerbation in developing sample.

Conclusion

Our study detailed the major interaction between comorbidities and exacerbation in COPD. Noteworthily, a novel risk score using comprehensive index – BODEx – and comorbidity parameters can identify patients at high risk of acute exacerbation.

Identification of candidate genes associated with slaughter traits in F2 chicken population using genome-wide association study

Slaughter traits are crucial economic traits of chickens. We performed a GWAS to discover critical loci and candidate genes for 21 slaughter traits in an F2 chicken population resulting from crossing Luxi gamecocks and recessive white feather broilers. We found some SNPs and genes which were significantly associated with keel length, head length, body slope length, bilateral leg weight without shin, bilateral foot weight, subcutaneous fat thickness, heart weight, muscular stomach weight and glandular stomach weight. This study provides references for further investigation of slaughter traits and molecular breeding in chicken.

Music-based interventions for pain relief in patients undergoing hemodialysis: A PRISMA-compliant systematic review and meta-analysis

BACKGROUND

Music therapy and music-based interventions have been used widely in numerous medical procedures to reduce the physical and psychological disorders. However, the effect of music therapy on pain relief in hemodialysis patients still remains unclear.

METHODS

Electronic databases were comprehensively searched through MEDLINE, Web of Science, EMBASE, Cochrane, and WANFANG. All studies met inclusion criteria were eligible for systematic review and meta-analysis. Clinical variables were extracted and pooled results were obtained using STATA software.

RESULTS

A total of 10 studies with 722 participants were included for systematic review. Overall, music therapy showed a significantly favorable effect on reducing pain for patients undergoing hemodialysis (SMD: -0.90, 95%CIs: -1.25 to -0.55, P < .001). No publication bias was observed.

CONCLUSIONS

Music-based interventions could significantly relieve pain for patients undergoing hemodialysis, which should be promoted as an effective and safe complementary method.

Increased β-site APP cleaving enzyme 1-mediated insulin receptor cleavage in type 2 diabetes mellitus with cognitive impairment

INTRODUCTION

Patients with type 2 diabetes mellitus (T2DM) are at a high risk of cognitive impairment, with insulin resistance playing a pivotal role. β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is considered a predictor of Alzheimer's disease. However, the potential roles of BACE1 in insulin resistance and the risk of cognitive impairment in T2DM remain unclear.

METHODS

We measured plasma BACE1 levels, BACE1 cleavage activities for Swedish mutant amyloid precursor protein (APPsw) and insulin receptor β subunit (INSR-β), and soluble INSR (sINSR) levels in a clinical cohort study.

RESULTS

T2DM patients with or without cognitive impairment exhibited elevated plasma BACE1 levels and BACE1 enzymatic activities for APPsw and INSR-β, and sINSR levels. Moreover, the glycemic status correlated with elevated BACE1 levels and BACE1-mediated INSR cleavage, which was associated with insulin resistance.

DISCUSSION

The elevated BACE1 levels in T2DM may contribute to increasing the cognitive impairment risk through both amyloidogenesis and insulin resistance.

BMI modifies the association between serum HDL cholesterol and stroke in a hypertensive population without atrial fibrillation

PURPOSE

Both high-density lipoprotein cholesterol (HDL-C) and body mass index (BMI) have an impact on the prevalence of stroke. However, it is unclear whether BMI can modify the relationship between HDL-C and stroke. Therefore, we aimed to assess the effect of the BMI on the association between HDL-C and stroke in a hypertensive population without atrial fibrillation (AF).

METHODS

We analyzed data of 10,925 hypertensive patients without AF from the Chinese Hypertension Registry Study. BMI was categorized as < 24 and ≥ 24 kg/m². Multivariate logistic regression and smooth curve fitting (penalized spline method) were used to analyze the association between HDL-C and stroke in different BMI groups. Subgroup analysis and interaction tests were used to explore the effect of other variables on this relationship.

RESULTS

The results showed a negative association between HDL-C and stroke in the BMI < 24 kg/m² group, but HDL-C was not associated with stroke in the BMI ≥ 24 kg/m² group. In the BMI < 24 kg/m² group, each 1 mmol/L increase in HDL-C was associated with a 50% decreased risk of stroke [odds ratio (OR) 0.50, 95% confidence interval (CI) 0.38-0.66]. No significant relationship between HDL-C and stroke was observed in the BMI ≥ 24 kg/m² group (OR 0.73, 95% CI 0.49-1.10). There was a significant interaction between BMI and HDL-C in regard to the prevalence of stroke in the hypertensive population without AF (P_Interaction = 0.027).

CONCLUSIONS

We found an inverse association between HDL-C and stroke only in the BMI < 24 kg/m² group. The finding suggested that BMI could modify the association between HDL-C and stroke in hypertensive populations without AF.

The Combination of Hemogram Indexes to Predict Exacerbation in Stable Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is characterized by pulmonary and systemic inflammatory processes, and exacerbation of COPD represents a critical moment in the progression of COPD. Several biomarkers of inflammation have been proposed to have a predictive function in acute exacerbation. However, their use is still limited in routine clinical practice. The purpose of our study is to explore the prognostic efficacy of novel inflammatory hemogram indexes in the exacerbation among stable COPD patients. Method: A total of 275 stable COPD patients from the Shanghai COPD Investigation Comorbidity Program were analyzed in our study. Blood examinations, especially ratio indexes like platelet-lymphocyte ratio (PLR), platelet × neutrophil/lymphocyte ratio [systemic immune-inflammation index (SII)], and monocyte × neutrophil/lymphocyte ratio [systemic inflammation response index (SIRI)], lung function test, CT scans, and questionnaires were performed at baseline and routine follow-ups. Clinical characteristics and information of exacerbations were collected every 6 months. The relationship between hemogram indexes and diverse degrees of exacerbation was assessed by logistic regression. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the ability of hemogram indexes to predict exacerbation of COPD. Furthermore, the discrimination and accuracy of combined indexes were measured by ROC and calibration curve. Result: There was a significant positive correlation between PLR levels and total exacerbation of COPD patients in a stable stage in a year. Also, the predictive ability of PLR exceeded any other ratio indexes, with an AUC of 0.66. SII and SIRI ranked second only to PLR, with an AUC of 0.64. When combining PLR with other indexes (sex, COPD year, and St. George's Respiratory Questionnaire scores), they were considered as the most suitable panel of index to predict total exacerbation. Based on the result of the ROC curve and calibration curve, the combination shows optimal discrimination and accuracy to predict exacerbation events in COPD patients. Conclusion: The hemogram indexes PLR, SII, and SIRI were associated with COPD exacerbation. Moreover, the prediction capacity of exacerbation was significantly elevated after combining inflammatory hemogram index PLR with other indexes, which will make it a promisingly simple and effective marker to predict exacerbation in patients with stable COPD.

Establishment of a cell-based quantitative reverse transcription-polymerase chain reaction (RT-qPCR) assay for detection of multivalent rotavirus vaccine

Because of deficiencies of traditional potency tests in rotavirus detection, a one-step TaqMan probe-based quantitative reverse transcription-polymerase chain reaction (RT-qPCR) assay combined with cell-based method was established to determine the infectious potency of the target virus in multivalent live rotavirus vaccines in vitro. Series dilutions of rotavirus samples were inoculated into Vero cells and cultured for 24 hours. The cells were lysed and the potency was detected by RT-qPCR. The reference standards with a known titer (lgCCID50 /mL) were assayed in parallel, and the potencies of each sample were determined using parallel line method. The specificity, precision and accuracy of the assay were evaluated, respectively. The results showed that messenger RNA produced during rotavirus replication was the primary template of RT-qPCR and the primers and probes were specific to each strain. The coefficient of variation of different wells and different working days did not exceed 6% and the results of the assay were proved to be concordant with those of cell culture infective dose 50% with a relative deviation less than 5%. This assay is a more rapid, cost-effective and high-throughput way for detecting multivalent rotavirus vaccine, and will be a valuable tool in the quality control and stability monitoring of live multivalent rotavirus vaccine.

An in-vitro study on a novel six-phage cocktail against multi-drug resistant-ESBL Shigella in aquatic environment

Shigella spp. are water-borne pathogens responsible for mild to severe cases bacilli dysentery all around the world known as Shigellosis. The progressively increasing of antibiotic resistance among Shigella calls for developing and establishing novel alternative therapeutic methods. The present study aimed to evaluate a novel phage cocktail of lytic phages against extended spectrum beta lactamase isolates of Shigella species in an aquatic environment. The phage cocktail containing six novel Shigella specific phages showed a broad host spectrum. The cocktail was very stable in aquatic environment. The cocktail resulted in about 99% decrease in the bacterial counts in the contaminated water by several species and strains of Shigella such as Shigella sonnei, Shigella flexneri and Shigella dysenteriae. Achieving such a high efficiency in this in-vitro study demonstrates a high potential for in-vivo and in-situ application of this phage cocktail as a bio-controlling agent against Shigella spp. contamination and infections.

Machine-Learning-Driven Synthesis of Carbon Dots with Enhanced Quantum Yields

Knowing the correlation of reaction parameters in the preparation process of carbon dots (CDs) is essential for optimizing the synthesis strategy, exploring exotic properties, and exploiting potential applications. However, the integrated screening experimental data on the synthesis of CDs are huge and noisy. Machine learning (ML) has recently been successfully used for the screening of high-performance materials. Here, we demonstrate how ML-based techniques can offer insight into the successful prediction, optimization, and acceleration of CDs' synthesis process. A regression ML model on hydrothermal-synthesized CDs is established capable of revealing the relationship between various synthesis parameters and experimental outcomes as well as enhancing the process-related properties such as the fluorescent quantum yield (QY). CDs exhibiting a strong green emission with QY up to 39.3% are obtained through the combined ML guidance and experimental verification. The mass of precursors and the volume of alkaline catalysts are identified as the most important features in the synthesis of high-QY CDs by the trained ML model. The CDs are applied as an ultrasensitive fluorescence probe for monitoring the Fe³⁺ ion because of their superior optical behaviors. The probe exhibits the linear response to the Fe³⁺ ion with a wide concentration range (0-150 μM), and its detection limit is 0.039 μM. Our findings demonstrate the great capability of ML to guide the synthesis of high-quality CDs, accelerating the development of intelligent material.

Select Septate Junction Proteins Direct ROS-Mediated Paracrine Regulation of Drosophila Cardiac Function

Septate junction (SJ) complex proteins act in unison to provide a paracellular barrier and maintain structural integrity. Here, we identify a non-barrier role of two individual SJ proteins, Coracle (Cora) and Kune-kune (Kune). Reactive oxygen species (ROS)-p38 MAPK signaling in non-myocytic pericardial cells (PCs) is important for maintaining normal cardiac physiology in Drosophila. However, the underlying mechanisms remain unknown. We find that in PCs, Cora and Kune are altered in abundance in response to manipulations of ROS-p38 signaling. Genetic analyses establish Cora and Kune as key effectors of ROS-p38 signaling in PCs on proper heart function. We further determine that Cora regulates normal Kune levels in PCs, which in turn modulates normal Kune levels in the cardiomyocytes essential for proper heart function. Our results thereby reveal select SJ proteins Cora and Kune as signaling mediators of the PC-derived ROS regulation of cardiac physiology.

Two-Step Calibration Method for Inverse Finite Element with Small Sample Features

When the inverse finite element method (inverse FEM) is used to reconstruct the deformation field of a multi-element structure with strain measurements, strain measurement errors can lower the reconstruction accuracy of the deformation field. Furthermore, the calibration ability of a self-structuring fuzzy network (SSFN) is weak when few strain samples are used to train the SSFN. To solve this problem, a novel two-step calibration method for improving the reconstruction accuracy of the inverse FEM method is proposed in this paper. Initially, the errors derived from measured displacements and reconstructed displacements are distributed to the degrees of freedom (DOFs) of nodes. Then, the DOFs of nodes are used as knots, in order to produce non-uniform rational B-spline (NURBS) curves, such that the sample size employed to train the SSFN can be enriched. Next, the SSFN model is used to determine the relationship between the measured strain and the DOFs of the end nodes. A loading deformation experiment using a three-element structure demonstrates that the proposed algorithm can significantly improve the accuracy of reconstruction displacement.

Sitagliptin inhibits EndMT in vitro and improves cardiac function of diabetic rats through the SDF-1α/PKA pathway

OBJECTIVE

The aim of this paper was to study sitagliptin in improving the endothelial-mesenchymal transition (EndMT) of human aortic endothelial cells (HAECs) and cardiac function of rats with diabetes mellitus (DM) and its possible pathway.

MATERIALS AND METHODS

Sprague Dawley (SD) rats were divided into control group, DM group and sitagliptin group. The myocardial contraction and relaxation functions of rats in each group were observed via echocardiography. The changes in cardiac structure and fiber were observed via hematoxylin-eosin (HE) staining, Masson staining and Sirius red staining. The immunohistochemical assay was performed to observe the expressions of α-smooth muscle actin (α-SMA) and VE-cadherin in HAECs; the expression of reactive oxygen species (ROS) in HAECs was detected using the fluorescence probe. Moreover, the expressions of transforming growth factor-β1 (TGF-β1), phosphorylated-protein kinase A (p-PKA), PKA and extracellular signal-regulated kinase (ERK) were observed via Western blotting.

RESULTS

Sitagliptin could improve the myocardial contraction and relaxation functions in diabetic rats and EndMT and ROS production in HAECs. In the DM group, the expression of Glucagon-like peptide-1 (GLP-1) was decreased, while the expression of stromal-derived factor-1α (SDF-1α) was decreased and the expressions of downstream PKA/ERK pathway and TGF-β1 were increased. The above changes could be reversed by sitagliptin.

CONCLUSIONS

Sitagliptin can reverse the EndMT in HAECs as well as the cardiac function in diabetic rats through the SDF-1α/PKA pathway.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study

Background

The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19.

Methods

We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19.

Findings

We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 10⁹ per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 10⁹ per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19.

Interpretation

The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease.

Funding

National Natural Science Foundation of China.

A New Neurovascular Panel Discriminates Between Patients with Type 2 Diabetes Mellitus with Cognitive Impairment and Cognitive Impairment Alone

BACKGROUND

Recent studies showed that type 2 diabetes mellitus (T2DM) may increase the risk of cognitive impairment, but there are few biomarkers to diagnostically discriminate T2DM-associated cognitive impairment and cognitive impairment alone. In this study, we assessed certain cytokines involved in inflammation and vascular diseases and identified special panel of cytokines that could differentiate between T2DM and cognitive impairment.

OBJECTIVE

To investigate associations and differences between T2DM and cognitive impairment by cytokines analysis.

METHODS

A total of 264 participants were recruited, their blood samples were collected, and plasma and serum were separated and stored at - 80°C until the assessment of amyloid-β (Aβ)42, Aβ40 and 8 kinds of cytokines by Luminex multiplex assays.

RESULTS

Plasma Aβ40 is higher whereas Aβ42/40 ratio is lower in cognitive impairment and T2DM-associated cognitive impairment compared to other groups. As compared to health control, YKL-40 level was upregulated in cognitive impairment, PRGN was downregulated in T2DM associated cognitive impairment, OPN was substantially decreased in T2DM, and IL-6 was elevated in cognitive impairment and T2DM-associated cognitive impairment. Interestingly, VEGF and S100B were induced in T2DM when compared with cognitive impairment, and NSE level in T2DM-associated cognitive impairment is significantly lower than in T2DM or cognitive impairment.

CONCLUSION

Aβ42, Aβ40, and Aβ42/40 ratio cannot distinguish T2DM-associated cognitive impairment from cognitive impairment. Certain cytokines (YKL-40, NSE, and VEGF) have good performance in distinguishing T2DM-associated cognitive impairment from simple cognitive impairment. Taken together, this may improve the accuracy of the diagnosis and establishment of individualized therapy.