Enhanced detection limit in an exceptional surface-based fiber resonator by manipulating Fano interference.

An exceptional surface (ES) has advantages in improving sensing robustness and enhancing frequency splitting. Typically, the eigenvalue splitting must exceed the mode linewidth in order to be clearly visible in the spectrum, which limits the precision of the ES-based sensing structure. In this paper, a strategy for manipulating spectral line shape in an ES-based structure is experimentally realized. In addition, the limit of the minimum detectable displacement can be further reduced by monitoring the peak intensity of the Fano interference line shape. The demonstration of Fano interference in an ES-based system opens the way for a new class of ultrasensitive optical sensors.

Dissolved trace elements in the Ganges-Brahmaputra-Meghna River Basin: A new approach for estimating trace element flux inputs from rivers into the world's oceans.

Understanding the changes in the chemical compositions of dissolved trace elements from source to sink is important for determining their spatiotemporal variations and the contributions from each sub-catchment in the Ganges, Brahmaputra, and Meghna Rivers. To estimate weathering and matter transfer in these Rivers and the Ganges-Brahmaputra-Meghna (G-B-M) Estuary, we measured 15 dissolved trace element concentrations from surface and bottom water samples and exchangeable trace metals from suspended particulate matter (SPM). From December 2019 to January 2020, post-monsoon samples were collected from the upstream of the three rivers and the G-B-M Estuary. Dissolved trace elements in the Ganges and Meghna Rivers exhibited remarkable spatial variations, whereas those in the Brahmaputra River and the G-B-M Estuary were uniform. The dissolved trace elements, basic information (river length and drainage area), and physicochemical parameters (pH, dissolved oxygen, and conductivity) of the three rivers were inconsistent. The sample sites near urban areas and industrial centers had high concentrations of dissolved trace elements. In the G-B-M Estuary, iron and lead concentrations decreased along the salinity gradient, whereas selenium levels gradually increased, which may have been released by the SPM owing to its highly exchangeable trace metals. Compared with historical concentrations, trace elements that entered the G-B Estuary from the Ganges and Brahmaputra Rivers exhibited either decreased or increased metal fluxes due to additional terrigenous sources, suggesting that the inputs of trace element flux from the Ganges and Brahmaputra Rivers into the oceans may need to be re-evaluated. Furthermore, Fe and Pb concentrations and river fluxes in the Ganges and Changjiang have decreased in recent years. Hence, the fluxes of certain trace elements that enter the oceans from large rivers may require re-evaluation.

Ultrasonic-assisted extraction of a low molecular weight polysaccharide from Nostoc commune Vaucher and its structural characterization and immunomodulatory activity.

In the current study, a novel crude polysaccharide (cNCEP) was extracted from N. commune Vaucher utilizing ultrasonic-assisted extraction (UAE) with 60 % ethanol, employing response surface methodology. The optimal yield of cNCEP was determined to be 8.07 ± 0.08 mg/g, achieved through ultrasonic-assisted extraction under the conditions of a material-to-liquid ratio of 1:22, temperature of 56 °C, power of 570 W, and duration of 147 min. Subsequent purification of NCEP via Sephadex G75 resulted in a novel polysaccharide with a molecular weight of 20.466 kDa. NCEP exhibited significant scavenging activites against DPPH and hydroxyl radicals, as well as notable in vitro immunomodulatory properties. Furthermore, the mechanisms underlying the immunomodulatory effects of NCEP, involving enhancement of immunity, were investigated, revealing potential regulation of MAPK and TLR4-IRF7-NF-κB signaling pathways through RNA-Seq and Western blot analyses. These findings highlight the promising potential of NCEP as an organic immunomodulatory agent and functional food ingredient.

Inoculum Size and False-Positive Detection of NDM- and OXA-48-Type Carbapenemases Using Two Multiplex Lateral Flow Assays.

The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs.

A HUG taxonomy of humans with potential in human-robot hugs.

Humans can easily perform various types of hugs in human contact and affection experience. With the prevalence of robots in social applications, they would be expected to possess the capability of hugs as humans do. However, it is still not an easy task for robots, considering the complex force and spatial constraints of robot hugs. In this work, we propose the HUG taxonomy, which distinguishes between different hugging patterns based on human demonstrations and prior knowledge. In this taxonomy, hugs are arranged according to (1) hugging tightness, (2) hugging style, and (3) bilateral coordination, resulting in 16 different hug types. We then further study the hug type preference of humans in different scenarios and roles. Furthermore, we propose a rule-based classification system to validate the potential of this taxonomy in human-robot hugs based on a humanoid robot with an E-skin of contact sensation. The HUG taxonomy could provide human hugging behavior information in advance, facilitating the action control of humanoid robots. We believe the results of our work can benefit future studies on human-robot hugging interactions.

Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.

BACKGROUND: In-home rehabilitation systems are a promising, potential alternative to conventional therapy for stroke survivors. Unfortunately, physiological differences between participants and sensor displacement in wearable sensors pose a significant challenge to classifier performance, particularly for people with stroke who may encounter difficulties repeatedly performing trials. This makes it challenging to create reliable in-home rehabilitation systems that can accurately classify gestures. METHODS: Twenty individuals who suffered a stroke performed seven different gestures (mass flexion, mass extension, wrist volar flexion, wrist dorsiflexion, forearm pronation, forearm supination, and rest) related to activities of daily living. They performed these gestures while wearing EMG sensors on the forearm, as well as FMG sensors and an IMU on the wrist. We developed a model based on prototypical networks for one-shot transfer learning, K-Best feature selection, and increased window size to improve model accuracy. Our model was evaluated against conventional transfer learning with neural networks, as well as subject-dependent and subject-independent classifiers: neural networks, LGBM, LDA, and SVM. RESULTS: Our proposed model achieved 82.2% hand-gesture classification accuracy, which was better (P<0.05) than one-shot transfer learning with neural networks (63.17%), neural networks (59.72%), LGBM (65.09%), LDA (63.35%), and SVM (54.5%). In addition, our model performed similarly to subject-dependent classifiers, slightly lower than SVM (83.84%) but higher than neural networks (81.62%), LGBM (80.79%), and LDA (74.89%). Using K-Best features improved the accuracy in 3 of the 6 classifiers used for evaluation, while not affecting the accuracy in the other classifiers. Increasing the window size improved the accuracy of all the classifiers by an average of 4.28%. CONCLUSION: Our proposed model showed significant improvements in hand-gesture recognition accuracy in individuals who have had a stroke as compared with conventional transfer learning, neural networks and traditional machine learning approaches. In addition, K-Best feature selection and increased window size can further improve the accuracy. This approach could help to alleviate the impact of physiological differences and create a subject-independent model for stroke survivors that improves the classification accuracy of wearable sensors. TRIAL REGISTRATION NUMBER: The study was registered in Chinese Clinical Trial Registry with registration number CHiCTR1800017568 in 2018/08/04.

Genomic investigation of Lactococcus formosensis, Lactococcus garvieae, and Lactococcus petauri reveals differences in species distribution by human and animal sources.

Lactococcus garvieae is a fish pathogen that can cause diseases in humans and cows. Two genetically related species, Lactococcus formosensis and Lactococcus petauri, may be misidentified as L. garvieae. It is unclear if these species differ in host specificity and virulence genes. This study analyzed the genomes of 120 L. petauri, 53 L. formosensis, and 39 L. garvieae isolates from various sources. The genetic diversity and virulence gene content of these isolates were compared. The results showed that 77 isolates previously reported as L. garvieae were actually L. formosensis or L. petauri. The distribution of the three species varied across different collection sources, with L. petauri being predominant in human infections, human fecal sources, and rainbow trout, while L. formosensis was more common in bovine isolates. The genetic diversity of isolates within each species was high and similar. Using a genomic clustering method, L. petauri, L. formosensis, and L. garvieae were divided into 45, 22, and 13 clusters, respectively. Most rainbow trout and human isolates of L. petauri belonged to different clusters, while L. formosensis isolates from bovine and human sources were also segregated into separate clusters. In L. garvieae, most human isolates were grouped into three clusters that also included isolates from food or other sources. Non-metric multidimensional scaling ordination revealed the differential association of 15 virulence genes, including 14 adherence genes and a bile salt hydrolase gene, with bacterial species and certain collection sources. In conclusion, this work provides evidence of host specificity among the three species. IMPORTANCE: Lactococcus formosensis and Lactococcus petauri are two newly discovered bacteria, which are closely related to Lactococcus garvieae, a pathogen that affects farmed rainbow trout, as well as causes cow mastitis and human infections. It is unclear whether the three bacteria differ in their host preference and the presence of genes that contribute to the development of disease. This study shows that L. formosensis and L. petauri were commonly misidentified as L. garvieae. The three bacteria showed different distribution patterns across various sources. L. petauri was predominantly found in human infections and rainbow trout, while L. formosensis was more commonly detected in cow mastitis. Fifteen genes displayed a differential distribution among the three bacteria from certain sources, indicating a genetic basis for the observed host preference. This work indicates the importance of differentiating the three bacteria in diagnostic laboratories for surveillance and outbreak investigation purposes.

ProtoCode: Leveraging large language models (LLMs) for automated generation of machine-readable PCR protocols from scientific publications.

Protocol standardization and sharing are crucial for reproducibility in life sciences. In spite of numerous efforts for standardized protocol description, adherence to these standards in literature remains largely inconsistent. Curation of protocols are especially challenging due to the labor intensive process, requiring expert domain knowledge of each experimental procedure. Recent advancements in Large Language Models (LLMs) offer a promising solution to interpret and curate knowledge from complex scientific literature. In this work, we develop ProtoCode, a tool leveraging fine-tune LLMs to curate protocols into intermediate representation formats which can be interpretable by both human and machine interfaces. Our proof-of-concept, focused on polymerase chain reaction (PCR) protocols, retrieves information from PCR protocols at an accuracy ranging 69-100 % depending on the information content. In all tested protocols, we demonstrate that ProtoCode successfully converts literature-based protocols into correct operational files for multiple thermal cycler systems. In conclusion, ProtoCode can alleviate labor intensive curation and standardization of life science protocols to enhance research reproducibility by providing a reliable, automated means to process and standardize protocols. ProtoCode is freely available as a web server at https://curation.taxila.io/ProtoCode/.

Genome-wide identification of JAZ gene family in sugarcane and function analysis of ScJAZ1/2 in drought stress response and flowering regulation.

The JASMONATE ZIM DOMAIN (JAZ) proteins are a key inhibitors of the jasmonic acid (JA) signaling pathway that play an important role in the regulation of plant growth and development and environmental stress responses. However, there is no systematic identification and functional analysis of JAZ gene family members in sugarcane. In this study, a total of 49 SsJAZ genes were identified from the wild sugarcane species Saccharum spontaneum genome that were unevenly distributed on 13 chromosomes. Phylogenetic analysis showed that all SsJAZ members can be divided into six groups, and most of the SsJAZ genes contained photoreactive and ABA-responsive elements. RNA-seq analysis revealed that SsJAZ1-1/2/3/4 and SsJAZ7-1 were significantly upregulated under drought stress. The transcript level of ScJAZ1 which is the homologous gene of SsJAZ1 in modern sugarcane cultivars was upregulated by JA, PEG, and abscisic acid (ABA). Moreover, ScJAZ1 can interact with three other JAZ proteins to form heterodimers. The spatial and temporal expression analysis showed that SsJAZ2-1/2/3/4 were highly expressed in different tissues and growth stages and during the day-night rhythm between 10:00 and 18:00. Overexpression of ScJAZ2 in Arabidopsis accelerated flowering through activating the expression of AtSOC1, AtFT, and AtLFY. Moreover, the transcription level of ScJAZ2 was about 30-fold in the early-flowering sugarcane variety than that of the non-flowering variety, indicating ScJAZ2 positively regulated flowering. This first systematic analysis of the JAZ gene family and function analysis of ScJAZ1/2 in sugarcane provide key candidate genes and lay the foundation for sugarcane breeding.

Circadian rhythms of melatonin and its relationship with anhedonia in patients with mood disorders: a cross-sectional study.

BACKGROUND: Mood disorders are strongly associated with melatonin disturbances. However, it is unclear whether there is a difference in melatonin concentrations and melatonin circadian rhythm profiles between depression and bipolar disorder. In addition, the relationship between anhedonia, a common symptom of affective disorders, and its melatonin circadian rhythm remains under-investigated. METHODS: Thirty-four patients with depression disorder, 20 patients diagnosed with bipolar disorder and 21 healthy controls participated in this study. The Revised Physical Anhedonia Scale (RPAS) was performed to assess anhedonia. Saliva samples were collected from all subjects at fixed time points (a total of 14 points) in two consecutive days for measuring the melatonin concentrations to fit circadian rhythms of subjects. Melatonin circadian rhythms were compared between the three groups using ANOVA. Partial correlation analysis and linear regression analysis were used to explore the correlation between melatonin rhythm variables and anhedonia. RESULTS: We found that the peak phase of melatonin in the depression group was significantly advanced compared to the control group (P < 0.001) and the bipolar disorder group (P = 0.004). The peak phase of melatonin and RPAS showed a negative correlation (P = 0.003) in depression patients, which was also demonstrated in the multiple linear regression model (B=-2.47, P = 0.006). CONCLUSIONS: These results suggest that circadian rhythms of melatonin are differentiated in depression and bipolar disorder and correlate with anhedonia in depression. Future research needs to explore the neurobiological mechanisms linking anhedonia and melatonin circadian rhythms in depressed patients.

Synthetic IMU Datasets and Protocols Can Simplify Fall Detection Experiments and Optimize Sensor Configuration.

Falls represent a significant cause of injury among the elderly population. Extensive research has been devoted to the utilization of wearable IMU sensors in conjunction with machine learning techniques for fall detection. To address the challenge of acquiring costly training data, this paper presents a novel method that generates a substantial volume of synthetic IMU data with minimal actual fall experiments. First, unmarked 3D motion capture technology is employed to reconstruct human movements. Subsequently, utilizing the biomechanical simulation platform Opensim and forward kinematic methods, an ample amount of training data from various body segments can be custom generated. Synthetic IMU data was then used to train a machine learning model, achieving testing accuracies of 91.99% and 86.62% on two distinct datasets of actual fall-related IMU data. Building upon the simulation framework, this paper further optimized the single IMU attachment position and multiple IMU combinations on fall detection. The proposed method simplifies fall detection data acquisition experiments, provides novel venue for generating low cost synthetic data in scenario where acquiring data for machine learning is challenging and paves the way for customizing machine learning configurations.

First-principles prediction of ferroelectric Janus Si2XY (X/Y = S/Se/Te, X ≠ Y) monolayers with negative Poisson's ratios.

Nowadays, two-dimensional (2D) materials with Janus structures evoke much attention due to their unique mechanical and electronic properties. In this work, Janus Pma2-Si2XY (X/Y = S/Se/Te, X ≠ Y) ferroelectric monolayers are firstly proposed and systematically investigated by first-principles calculations. These monolayers exhibit remarkable mechanical properties, including small Young's modulus values, negative Poisson's ratios (NPRs) and large critical strains, reflecting their exceptional flexibility and stretchability. More strikingly, the novel structures of Si2STe and Si2SeTe also endow them with in-plane spontaneous polarization (Ps) and low energy barrier for phase transition, with Ps and energy barrier values being 1.632 × 10-10 C m-1 and 159 meV for Si2STe and 1.149 × 10-10 C m-1 and 196.6 meV for Si2SeTe. The ab initio molecular dynamics (AIMD) simulations reveal high Curie temperatures (Tc) for Si2STe and Si2SeTe, ranging between 1300 K and 1400 K. Additionally, Si2XY monolayers exhibit high anisotropic carrier mobility (∼103 cm2 V-1 s-1) and an extraordinary light absorption coefficient (∼105 cm-1). Our research not only broadens the family of 2D Janus ferroelectric materials, but also demonstrates their potential applications in nanomechanical, nanoelectronic and optoelectronic devices.

Janus monolayer PXC (X = As/Sb) for photocatalytic water splitting with a negative Poisson's ratio.

Two-dimensional (2D) Janus materials have attracted considerable attention in photocatalysis owing to their robust redox capability and efficient segregation. In this study, we propose a novel Janus monolayer structure, denoted as PXC (X = As/Sb), exhibiting favorable stability in terms of dynamics, thermal properties, and mechanical characteristics. The PXC monolayers demonstrate a relatively smaller Young's modulus (132.5/119.5 N m-1 for PAsC/PSbC) and large negative Poisson's ratios (-0.15/-0.101 for PAsC/PSbC). Moreover, the HSE06 + SOC functional results show that PAsC/PSbC are indirect semiconductors with a 2.33/1.43 eV band gap, exhibiting a suitable band alignment for photocatalytic water splitting. The calculated high carrier mobility (104 cm2 V-1 s-1), along with a significant discrepancy, determined by the deformation potential theory and the built-up field induced by the large intrinsic dipole, effectively suppresses the recombination of photogenerated carriers. Furthermore, PXC monolayers possess a strong absorption capacity in the visible and ultraviolet light region (105 cm-1). Therefore, our results indicate that PXC monolayers hold great potential for application in the field of photocatalytic water splitting.

Effectiveness and Safety of Chinese Herbal Injections Combined with SOX Chemotherapy Regimens for Advanced Gastric Cancer: a Bayesian Network Meta-Analysis.

Background: Randomized controlled trials (RCTs) have demonstrated that combining Chinese herbal injections (CHIs) with oxaliplatin plus tegafur (SOX) chemotherapy regimens improves clinical effectiveness and reduces adverse reactions in patients with advanced gastric cancer (AGC). These RCTs highlight the potential applications of CHIs and their impact on AGC patient prognosis. However, there is insufficient comparative evidence on the clinical effectiveness and safety of different CHIs when combined with SOX. Therefore, we performed a network meta-analysis to rank the clinical effectiveness and safety of different CHIs when combined with SOX chemotherapy regimens. This study aimed to provide evidence for selecting appropriate CHIs in the treatment of patients with AGC. Methods: We searched eight databases from their inception until March 2023. Surface Under the Cumulative Ranking Curve (SUCRA) probability values were used to rank the treatment measures, and the Confidence in Network Meta-Analysis (CINeMA) software assessed the grading of evidence. Results: A total of 51 RCTs involving 3,703 AGC patients were identified. Huachansu injections + SOX demonstrated the highest clinical effectiveness (SUCRA: 78.17%), significantly reducing the incidence of leukopenia (93.35%), thrombocytopenia (80.19%), and nausea and vomiting (95.15%). Shenfu injections + SOX improved Karnofsky's Performance Status (75.59%) and showed a significant reduction in peripheral neurotoxicity incidence (88.26%). Aidi injections + SOX were most effective in reducing the incidence of liver function damage (75.16%). According to CINeMA, most confidence rating results were classified as "low". Conclusion: The combination of CHIs and SOX shows promising effects in the treatment of AGC compared to SOX alone. Huachansu and Shenfu injections offer the greatest overall advantage among the CHIs, while Aidi injections are optimal for reducing the incidence of liver damage. However, further rigorous RCTs with larger sample sizes and additional pharmacological studies are necessary to reinforce these findings.

Preparation of Gold Nanoparticles via Anodic Stripping of Copper Underpotential Deposition in Bulk Gold Electrodeposition for High-Performance Electrochemical Sensing of Bisphenol A.

Bisphenol A is one of the most widely used industrial compounds. Over the years, it has raised severe concern as a potential hazard to the human endocrine system and the environment. Developing robust and easy-to-use sensors for bisphenol A is important in various areas, such as controlling and monitoring water purification and sewage water systems, food safety monitoring, etc. Here, we report an electrochemical method to fabricate a bisphenol A (BPA) sensor based on a modified Au nanoparticles/multiwalled carbon nanotubes composite electrocatalyst electrode (AuCu-UPD/MWCNTs/GCE). Firstly, the Au-Cu alloy was prepared via a convenient and controllable Cu underpotential/bulk Au co-electrodeposition on a multiwalled modified carbon nanotubes glassy carbon electrode (GCE). Then, the AuCu-UPD/MWCNTs/GCE was obtained via the electrochemical anodic stripping of Cu underpotential deposition (UPD). Our novel prepared sensor enables the high-electrocatalytic and high-performance sensing of BPA. Under optimal conditions, the modified electrode showed a two-segment linear response from 0.01 to 1 µM and 1 to 20 µM with a limit of detection (LOD) of 2.43 nM based on differential pulse voltammetry (DPV). Determination of BPA in real water samples using AuCu-UPD/MWCNTs/GCE yielded satisfactory results. The proposed electrochemical sensor is promising for the development of a simple, low-cost water quality monitoring system for the detection of BPA in ambient water samples.

First description study on molecular characterization of Hemiclepsis khankiana (Hirudinea: Glossiphoniidae) in China.

BACKGROUND: Leeches are an integral component of aquatic biocenosis and can be found in a wide range of ecosystems such as freshwater, saltwater, flowing, and still-water ecosystems. It especially plays an important role in the freshwater benthic community and is an important part of the food web. In this study, a leech species was found in the mantle cavity of wild freshwater mussels in Zigong City, Sichuan Province, China, and its identity was determined through morphological analysis and molecular biological analysis. RESULTS: The leech is Hemiclepsis khankiana, a new species of Hemiclepsis that has been discovered in Russia in recent years. Through morphological analysis, the current survey observed that the morphological characteristics of Hemiclepsis khankiana eyespots were significantly different from the first reported description. The first pair of eyespots on the leech were separated and clear, while it had been reduced to unclear shadows in the previous report. The phylogenetic tree based on the COI gene showed that the COI gene sequence obtained in this study was in the same evolutionary branch as Hemiclepsis khankiana (MN295420, MN295421). Genetically, it was most closely related to Hemiclepsis kasmiana (mean COI p-distance = 3.98%). CONCLUSIONS: The current study reported on the new distribution range of Hemiclepsis khankiana, which was initially discovered in China. This study indicates that the distribution range of the leech species has expanded, laying a foundation for further studies in China.

Genome-wide identification of GTE family proteins in sugarcane (Saccharum spontaneum) reveals that SsGTEL3a confers drought tolerance.

The bromodomain is a highly conserved protein domain that specifically binds to acetylated lysine residues in histones, thereby activating transcription of target genes. Although some progress in Global Transcription Factor Group E (GTE) has been achieved in numerous animals and a few plant species, no systematic analysis of GTE gene families has been reported yet in sugarcane. In our study, 37 GTE and GTE-Like (GTEL) genes were characterized in the Saccharum spontaneum. All SsGTE/SsGTEL members were heterogeneously located on all chromosomes of the sugarcane genome and divided into five groups. Transcriptome data showed that SsGTEL3a was expressed at significantly higher levels under drought stress in drought-resistant varieties than in drought-sensitive varieties. Moreover, the overexpression of SsGTEL3a significantly improved the drought tolerance in Arabidopsis through improving the scavenging ability of reactive oxygen species. Additionally, an interaction between ScFAR1 and SsGTEL3a was identified, with ScFAR1 showing a positive response to drought stress in bacterium. In summary, this systematic analysis of GTE gene family in sugarcane and functional research of SsGTEL3a broadened deeper insight into their evolutionary dynamics and functional properties and provided new candidate genes for drought-resistant molecular breeding of sugarcane.

Evaluation of Two Tests for the Rapid Detection of CTX-M Producers Directly in Urine Samples.

Infections caused by extended-spectrum ß-lactamase-producing Enterobacterales have increased rapidly and are mainly attributed to the production of CTX-M enzymes. This study evaluated the NG-Test® CTX-M MULTI lateral flow assay (CTX-M LFA) and the Rapid ESBL NP® test (ESBL NP test) for rapid detection of CTX-M-producing Enterobacterales directly in midstream urine (MSU) samples. Testing was performed on 277 clinical MSU samples in a hospital microbiology laboratory from November 2022 to January 2023; 60 of these samples (30 positive for ESBL producers and 30 positive for non-ESBL producers) were tested retrospectively after the identification and susceptibility results were obtained, and 217 samples were tested prospectively immediately after a Gram stain showing the presence of Gram-negative bacilli. The results were compared against phenotypic detection of ESBL and molecular testing as the reference methods. Overall, 67 of the 277 samples were culture-positive for ESBL-producing Enterobacterales. PCR for the blaCTX-M gene was positive for all ESBL-producing Enterobacterales isolates. All CTX-M LFA results were interpretable, while three of the ESBL NP test results were noninterpretable. The sensitivity of the CTX-M LFA (100%, 95% CI 94.6-100%) was higher than that of the ESBL NP test (86.6%, 95% CI 76.0-93.7%). Both tests had high specificities (CTX-M LFA, 99.1%, 95% CI 96.6-99.9% and ESBL NP test, 100%, 95% CI 98.2-100%). In conclusion, both the CTX-M LFA and the ESBL NP test can deliver rapid results that could improve antimicrobial stewardship for urinary tract infections.

Synthetic EMG Based on Adversarial Style Transfer Can Effectively Attack Biometric-Based Personal Identification Models.

Biometric-based personal identification models are generally considered to be accurate and secure because biological signals are too complex and person-specific to be fabricated, and EMG signals, in particular, have been used as biological identification tokens due to their high dimension and non-linearity. We investigate the possibility of effectively attacking EMG-based identification models with adversarial biological input via a novel EMG signal individual-style transformer based on a generative adversarial network and tiny leaked data segments. Since two same EMG segments do not exist in nature; the leaked data can't be used to attack the model directly or it will be easily detected. Therefore, it is necessary to extract the style with the leaked personal signals and generate the attack signals with different contents. With our proposed method and tiny leaked personal EMG fragments, numerous EMG signals with different content can be generated in that person's style. EMG hand gesture data from eighteen subjects and three well-recognized deep EMG classifiers were used to demonstrate the effectiveness of the proposed attack methods. The proposed methods achieved an average of 99.41% success rate on confusing identification models and an average of 91.51% success rate on manipulating identification models. These results demonstrate that EMG classifiers based on deep neural networks can be vulnerable to synthetic data attacks. The proof-of-concept results reveal that synthetic EMG biological signals must be considered in biological identification system design across a vast array of relevant biometric systems to ensure personal identification security for individuals and institutions.

[Simulator of Heart Rate and Respiratory Rate for Monitoring Accuracy of Intelligent Sleep Monitoring Devices].

OBJECTIVE: Invent a simulator which provides a simulation of heart rate and respiratory rate to the intelligent sleep monitoring devices based on precision pressure sensors. METHODS: The simulator was composed of control part and simulated silicone doll. The simulated silicone doll contains heartbeat simulator and breathing simulation airbag. Heartbeat and breathing combination pressure signal can be produced according to frequency set values. Frequencies of pressure signal of the simulator were compared with the monitoring results of intelligent sleep monitoring devices with known accuracy to verify the frequency accuracy of pressure signal of the simulator. Verified the repeatability and stability of the simulator with a stopwatch. RESULTS: The heart rate of the simulator was with in ±2 beats per minute of the monitoring results of intelligent sleep monitoring devices and the respiratory rate of the simulator was with in ±2 times per minute of the monitoring results. The repeatability and stability of the simulator was better than ±5% according to results with a stopwatch. CONCLUSIONS: It's practicable to use the simulator which provides a simulation of heart rate and respiratory rate to the accuracy test of the intelligent sleep monitoring devices based on precision pressure sensor.