Multivariate analysis of craniodental morphology in mouse-eared bats (Chiroptera, Vespertilionidae, Myotis) from Vietnam.

This study conducted biostatistical multivariate analyses on 23 craniodental morphological measurements from 209 specimens to study interspecific variations amongst 15 bat species of the genus Myotis in Vietnam. Univariate and multivariate analyses demonstrated that the studied species can be divided into four groups as follows: extra-large-sized species (M.chinensis), large-sized species (M.pilosus, M.indochinensis and M.annectans), medium-sized species (M.altarium, M.hasseltii, M.montivagus, M.horsfieldii, M.ater, M.laniger and M.muricola) and small-sized species (M.annamiticus, M.aff.siligorensis, M.rosseti and M.alticraniatus). Our data revealed that the main craniodental features contributing to the variations in distinguishing Myotis species are the width of the anterior palatal, least height of the coronoid process, length of the upper and lower canine-premolar, zygomatic width and width across the upper canines and lower premolar-molar length. Based on patterns of morphological differences, we conducted comparisons between morphometrically closely resembling species pairs and further discussed additional characteristics that are expected to support the taxonomy and systematics of Vietnamese Myotis bats.

Associations of COVID-19-related fear with kidney disease quality of life and its subscales among hemodialysis patients as modified by health literacy: a multi-hospital survey.

Background: Receiving hemodialysis treatment makes end-stage renal disease (ESRD) patients highly vulnerable amidst the COVID-19 pandemic. Hence, their kidney disease quality of life (KDQOL) is affected. We aimed to examine the association between fear of COVID-19 (FCoV-19) and KDQOL, and the effect modification of Health literacy (HL) on this association. Material and Methods: A survey was conducted at 8 hospitals from July 2020 to March 2021 on 972 patients. Data collection includes socio-demographic factors, clinical parameters, HL, digital healthy diet literacy (DDL), hemodialysis diet knowledge (HDK), FCoV-19, suspected COVID-19 symptoms (S-COVID-19-S), and KDQOL. Results: Higher HL scores B = 0.13 (95% CI = 0.06-0.21, p = 0.001) and HDK scores B = 0.58 (95% CI = 0.31-0.85, p = 0.001) were associated with higher KDQOL scores. Whereas, S-COVID-19-S B = -6.12 (95% CI = -7.66 to - 4.58, p = 0.001) and FCoV-19 B = -0.91 (95% CI = -1.03 to - 0.80, p = 0.001) were associated with lower KDQOL scores. Notably, higher HL scores significantly attenuate the negative impact of FCoV-19 on overall KDQOL and the kidney disease component summary. Conclusions: In hemodialysis patients, FCoV-19 and S-COVID-19-S were associated with a lower KDQOL. Health literacy significantly mitigates the negative impact of FCoV-19 on KDQOL. Strategic public health interventions to improve HL are suggested to protect patient's KDQOL during the pandemic.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Insight into chromium adsorption from contaminated soil using Mg/Al LDH-zeolite.

The study investigated the effectiveness of Mg/Al LDH-zeolite (MALZ) in immobilizing exchangeable Cr (e-Cr) within the soil. The research systematically evaluated various variables affecting the immobilization of e-Cr in contaminated soil (CS), including soil pH levels (ranging from 5.0 to 9.0), different weight ratios of MALZ (1 %, 3 %, and 5 %), durations of differing incubation periods (15, 30 and 45 days), and different SM content levels (30 %, 50 %, and 70 %). The initial concentration of Cr in the CS was maintained at 50 mg/kg. The investigation findings revealed that the optimal conditions for immobilizing the e-Cr were a soil pH of 5.0, an MALZ weight ratio of 3 %, an incubation period of 30 days, and an SM level of 70 %. Under these ideal conditions, the percentage of e-Cr within the CS decreased significantly, from 87.49 % (45.64 mg/kg) in the control treatment (CT) to just 19.82 % (10.08 mg/kg) when incubated with MALZ. The primary mechanisms responsible for immobilizing the e-Cr onto MALZ included pore filling, reduction processes, co-precipitation, organic interactions and electrostatic attractions leading to the formation of carbonate-bound complexes such as Cr(VI)-carbonate, Cr(III)-carbonate, and organic complexes. Surface functional groups on MALZ, housing iron and aluminium oxyhydroxides and silicon and oxygen elements, expedited these procedures. This study provided a valuable understanding of the mitigation of soils contaminated with chromium and contributed to understanding the relations between MALZ and the e-Cr in the soil. The discoveries carry substantial consequences for the advancement of efficient remediation technologies.

Methanotrophs mediated biogas valorization: Sustainable route to polyhydroxybutyrate production.

This study explores the ability of methanotrophs to convert biogas into biopolymers, addressing H2S as a limitation in the utilization of biogas as a carbon source for bioconversion. Transcriptomic analysis was conducted to understand the growth and changes in the expression patterns of Type I and II methanotrophs under varying H2S concentrations. Results suggested that Type II methanotrophs can possess a native H2S utilization pathway. Both Type I and II methanotrophs were evaluated for their growth and polyhydroxybutyrate (PHB) production from biogas. Methylocystis sp. MJC1 and Methylocystis sp. OK1 exhibited a maximum biomass production of 4.0 and 4.5 gDCW/L, respectively, in fed-batch culture, aligning with the transcriptome data. Furthermore, Methylocystis sp. MJC1 produced 2.9 g PHB/L from biogas through gas fermentation. These findings underscore biogas-based biotechnology as an innovative solution for environmental and industrial challenges with further optimization and productivity enhancement research expected to broaden the potential in this field.

Discovery of a small-molecule inhibitor that traps Polθ on DNA and synergizes with PARP inhibitors.

The DNA damage response (DDR) protein DNA Polymerase θ (Polθ) is synthetic lethal with homologous recombination (HR) factors and is therefore a promising drug target in BRCA1/2 mutant cancers. We discover an allosteric Polθ inhibitor (Polθi) class with 4-6 nM IC50 that selectively kills HR-deficient cells and acts synergistically with PARP inhibitors (PARPi) in multiple genetic backgrounds. X-ray crystallography and biochemistry reveal that Polθi selectively inhibits Polθ polymerase (Polθ-pol) in the closed conformation on B-form DNA/DNA via an induced fit mechanism. In contrast, Polθi fails to inhibit Polθ-pol catalytic activity on A-form DNA/RNA in which the enzyme binds in the open configuration. Remarkably, Polθi binding to the Polθ-pol:DNA/DNA closed complex traps the polymerase on DNA for more than forty minutes which elucidates the inhibitory mechanism of action. These data reveal a unique small-molecule DNA polymerase:DNA trapping mechanism that induces synthetic lethality in HR-deficient cells and potentiates the activity of PARPi.

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications.

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

A missense mutation in the Hspa8 gene encoding heat shock cognate protein 70 causes neuroaxonal dystrophy in rats.

Neuroaxonal dystrophy (NAD) is a neurodegenerative disease characterized by spheroid (swollen axon) formation in the nervous system. In the present study, we focused on a newly established autosomal recessive mutant strain of F344-kk/kk rats with hind limb gait abnormalities and ataxia from a young age. Histopathologically, a number of axonal spheroids were observed throughout the central nervous system, including the spinal cord (mainly in the dorsal cord), brain stem, and cerebellum in F344-kk/kk rats. Transmission electron microscopic observation of the spinal cord revealed accumulation of electron-dense bodies, degenerated abnormal mitochondria, as well as membranous or tubular structures in the axonal spheroids. Based on these neuropathological findings, F344-kk/kk rats were diagnosed with NAD. By a positional cloning approach, we identified a missense mutation (V95E) in the Hspa8 (heat shock protein family A (Hsp70) member 8) gene located on chromosome 8 of the F344-kk/kk rat genome. Furthermore, we developed the Hspa8 knock-in (KI) rats with the V95E mutation using the CRISPR-Cas system. Homozygous Hspa8-KI rats exhibited ataxia and axonal spheroids similar to those of F344-kk/kk rats. The V95E mutant HSC70 protein exhibited the significant but modest decrease in the maximum hydrolysis rate of ATPase when stimulated by co-chaperons DnaJB4 and BAG1 in vitro, which suggests the functional deficit in the V95E HSC70. Together, our findings provide the first evidence that the genetic alteration of the Hspa8 gene caused NAD in mammals.

Antimicrobial Resistance Patterns of Staphylococcus Aureus Isolated at a General Hospital in Vietnam Between 2014 and 2021.

Purpose: Staphylococcus aureus is a commensal bacteria species that can cause various illnesses, from mild skin infections to severe diseases, such as bacteremia. The distribution and antimicrobial resistance (AMR) pattern of S. aureus varies by population, time, geographic location, and hospital wards. In this study, we elucidated the epidemiology and AMR patterns of S. aureus isolated from a general hospital in Vietnam. Methods: This was a cross-sectional study. Data on all S. aureus infections from 2014 to 2021 were collected from the Microbiology department of Military Hospital 103, Vietnam. Only the first isolation from each kind of specimen from a particular patient was analyzed using the Cochran-Armitage and chi-square tests. Results: A total of 1130 individuals were diagnosed as S. aureus infection. Among them, 1087 strains were tested for AMR features. Most patients with S. aureus infection were in the age group of 41-65 years (39.82%). S. aureus isolates were predominant in the surgery wards, and pus specimens were the most common source of isolates (50.62%). S. aureus was most resistant to azithromycin (82.28%), erythromycin (82.82%), and clindamycin (82.32%) and least resistant to teicoplanin (0.0%), tigecycline (0.16%), quinupristin-dalfopristin (0.43%), linezolid (0.62%), and vancomycin (2.92%). Methicillin-resistant S. aureus (MRSA) and multidrug-resistant (MDR) S. aureus were prevalent, accounting for 73.02% and 60.90% of the total strains respectively, and the strains isolated from the intensive care unit (ICU) had the highest percentage of multidrug resistance (77.78%) among the wards. Conclusion: These findings highlight the urgent need for continuous AMR surveillance and updated treatment guidelines, particularly considering high resistance in MRSA, MDR strains, and ICU isolates. Future research focusing on specific resistant populations and potential intervention strategies is crucial to combat this rising threat.

Engineered methane biocatalysis: strategies to assimilate methane for chemical production.

Methane (CH4), one of the greenhouse gases, is considered a promising feedstock for the biological production of fuels and chemicals. Although recent studies have demonstrated the capability of methanotrophs to convert CH4 into various bioproducts by metabolic engineering, the productivity has not reached commercial levels. As such, there is a growing interest in synthetic methanotrophic systems as an alternative. This review summarizes the strategies for enhancing native CH4 assimilation and discusses the challenges for the construction of synthetic methanotrophy into nonmethanotrophic industrial strains. Additionally, we suggest a mixed heterotrophic approach that integrates CH4 assimilation with glucose and xylose metabolism to improve productivity. The synthetic methanotrophic system presented in this review could pave the way for sustainable and efficient biomanufacturing using CH4.

Enhancing/Improving Forming Limit Curve and Fracture Height Predictions in the Single-Point Incremental Forming of Al1050 Sheet Material.

Single-point incremental forming (SPIF) has emerged as a cost-effective and rapid manufacturing method, especially suitable for small-batch production due to its minimal reliance on molds, swift production, and affordability. Nonetheless, SPIF's effectiveness is closely tied to the specific characteristics of the employed sheet materials and the intricacies of the desired shapes. Immediate experimentation with SPIF often leads to numerous product defects. Therefore, the pre-emptive use of numerical simulations to predict these defects is of paramount importance. In this study, we focus on the critical role of the forming limit curve (FLC) in SPIF simulations, specifically in anticipating product fractures. To facilitate this, we first construct the forming limit curve for Al1050 sheet material, leveraging the modified maximum force criterion (MMFC). This criterion, well-established in the field, derives FLCs based on the theory of hardening laws in sheet metal yield curves. In conjunction with the MMFC, we introduce a graphical approach that simplifies the prediction of forming limit curves at fracture (FLCF). Within the context of the SPIF method, FLCF is established through both uniaxial tensile deformation (U.T) and simultaneous uniform tensile deformation in bi-axial tensile (B.T). Subsequently, the FLCF predictions are applied in simulations and experiments focused on forming truncated cone parts. Notably, a substantial deviation in fracture height, amounting to 15.97%, is observed between simulated and experimental samples. To enhance FLCF prediction accuracy in SPIF, we propose a novel method based on simulations of truncated cone parts with variable tool radii. A FLCF is then constructed by determining major/minor strains in simulated samples. To ascertain the validity of this enhanced FLCF model, our study includes simulations and tests of truncated cone samples with varying wall angles, revealing a substantial alignment in fracture height between corresponding samples. This research contributes to the advancement of SPIF by enhancing our ability to predict and mitigate product defects, ultimately expanding the applicability of SPIF in diverse industrial contexts.

Room temperature roll-to-roll additive manufacturing of polydimethylsiloxane-based centrifugal microfluidic device for on-site isolation of ribonucleic acid from whole blood.

Polymer-based lab-on-a-disc (LoaD) devices for isolating ribonucleic acid (RNA) from whole blood samples have gained considerable attention for accurate biomedical analysis and point-of-care diagnostics. However, the mass production of these devices remains challenging in manufacturing cost and sustainability, primarily due to the utilization of a laser cutter or router computer numerical control (CNC) machine for engraving and cutting plastics in the conventional prototyping process. Herein, we reported the first energy-efficient room-temperature printing-imprinting integrated roll-to-roll manufacturing platform for mass production of a polydimethylsiloxane (PDMS)-based LoaD to on-site isolate ribonucleic acid (RNA) from undiluted blood samples. We significantly reduced energy consumption and eliminated thermal expansion variations between the mold, substrate, and resists by accelerating the PDMS curing time to less than 10 min at room temperature without using heat or ultraviolet radiation. The additive manufacturing technology was applied to fabricate a multi-depth flexible polymer mold that integrated macro (2 mm) and micro-sized (500 µm) features, which overcomes the economic and environmental challenges of conventional molding techniques. Our integrated R2R platform was enabled to print adhesion-promoting films at the first printing unit and continuously in-line imprint with a high replication accuracy (99%) for high-volume manufacturing of a new centrifugal microfluidic chip with an enhancement of mixing performance by integrating an efficient mixing chamber and serpentine micromixer. This research paved the way for scalable green manufacturing of large-volume polymer-based microfluidic devices, often required in real-world sample-driven analytical systems for clinical bioanalysis.

A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance.

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user's comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user's movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.

Assessment of aflatoxin B1 contamination in rice and maize

Introduction: Aflatoxins B1 are among the most common poisonous mycotoxins produced by certain fungi that harm animals and crops. Mycotoxins can cause a variety of adverse health effects and pose a serious health threat to humans. The Maximum Residue Limits of aflatoxin B1 in processed cereals and ingredients are 2 parts per billion (ppb) and 5 ppb, respectively. Objectives: To evaluate the status of aflatoxin B1 contamination in rice, corn and staple food produced in Ha Giang province compared with the maximum permitted levels. Methods: A total of 210 rice and maize samples were analyzed to quantify the level of aflatoxin B1. Analysis of mycotoxins was conducted by High Performance Liquid Chromatography using a fluorescence detector. Results: It was found that rice, rice products, maize, and maize products had a mean aflatoxin B1 content of 1.79 ppb, 2.55 ppb, 2.19 ppb, and 6.35 ppb, respectively. The results also showed that 71.9% of samples were contaminated with mycotoxins, and 14.28% of samples exceeded the maximum allowable limit. Conclusion: The concentration of aflatoxin B1 in 14.28% of the samples are over permissible limits by nationwide regulations.

Introducción: La aflatoxina B1 se encuentra entre las micotoxinas más comunes y venenosas producidas por ciertos hongos que dañan a los animales y los cultivos. Las micotoxinas pueden causar una variedad de efectos adversos para la salud y representar una grave amenaza para la salud de los seres humanos. Los límites máximos de residuos de aflatoxina B1en cereales e ingredientes procesados son de 2 ppb y 5 ppb, respectivamente. Objetivos: Evaluar el estado de contaminación por aflatoxina B1 en arroz, maíz y alimentos básicos producidos en la provincia de Ha Giang, en comparación con los niveles máximos permitidos. Métodos: Se analizaron un total de 210 muestras de arroz y maíz para cuantificar el nivel de aflatoxina B1. El análisis de micotoxinas se realizó mediante cromatografía líquida de alta resolución, utilizando un detector de fluorescencia. Resultados: Se encontró que el arroz, los productos de arroz, el maíz y los productos de maíz tenían un contenido medio de aflatoxin B1, de 1,79 ppb, 2,55 ppb, 2,19 ppb y 6,35 ppb, respectivamente. Los resultados también mostraron que el 71,9 % de las muestras estaban contaminadas con micotoxinas y el 14,28 % de las muestras excedieron el límite máximo permitido. Conclusión: La concentración de aflatoxina B1 en el 14,28 % de las muestras está por encima de los límites permisibles por la norma nacional.

Predicting Antibiotic Resistance in ICUs Patients by Applying Machine Learning in Vietnam.

Introduction: Artificial Intelligence (AI) and machine learning (ML) are used extensively in HICs to detect and control antibiotic resistance (AMR) in laboratories and clinical institutions. ML is designed to predict outcome variables using an algorithm to enable "machines" to learn the "rules" from the data. ML is increasingly being applied in intensive care units to identify AMR and to assist empiric antibiotic therapy. This study aimed to evaluate the performance of ML models for predicting AMR bacteria and resistance to antibiotics in two Vietnamese hospitals. Patients and Methods: A cross-sectional study combined with retrospective was conducted from 1st January 2020 to 30th June 2022. Five models were developed to predict antibiotic resistance of bacterial infections of ICU patients. Two datasets were prepared to predict AMR bacteria and antibiotics with ML models. The performance of the prediction models was evaluated by various indicators (sensitivity, specificity, precision, accuracy, F1-score, PRC, AuROC, and NormMCC) to determine the optimal time point for data selection. Python version 3.8 was used for statistical analyses. Results: The accuracy, F1-score, AuROC, and normMMC of LightGBM, XGBoost, and Random Forest models were higher than those of other models in both datasets. In both datasets 1 and 2, accuracy, F1-score, AuROC and normMCC of the XGBoost model were the highest among five models (from 0.890 to 1.000). Only Random Forest models had specificity scores higher than 0.850. High scores of sensitivity, accuracy, precision, F1-score, and normMCC indicated that the models were making accurate predictions for datasets 1 and 2. Conclusion: XGBoost, LightGBM, and Random Forest were the best-performed machine learning models to predict antibiotic resistance of bacterial infections of ICUs patients using the patients' EMRs.

Mobile Efficient Diagnostics of Infectious Diseases via On-Chip RT-qPCR: MEDIC-PCR.

The COVID-19 outbreak has caused public and global health crises. However, the lack of on-site fast, reliable, sensitive, and low-cost reverse transcription polymerase chain reaction (RT-PCR) testing limits early detection, timely isolation, and epidemic prevention and control. Here, the authors report a rapid mobile efficient diagnostics of infectious diseases via on-chip -RT-quantitative PCR (RT-qPCR): MEDIC-PCR. First, the authors use a roll-to-roll printing process to accomplish low-cost carbon-black-based disposable PCR chips that enable rapid LED-induced photothermal PCR cycles. The MEDIC-PCR can perform RT (3 min), and PCR (9 min) steps. Further, the cohort of 89 COVID-19 and 103 non-COVID-19 patients testing is completed by the MEDIC-PCR to show excellent diagnostic accuracy of 97%, sensitivity of 94%, and specificity of 98%. This MEDIC-PCR can contribute to the preventive global health in the face of a future pandemic.

High-flow nasal cannula therapy in patients with COVID-19 in intensive care units in a country with limited resources: a single-center experience.

OBJECTIVE: This study was performed to determine the outcomes of patients with coronavirus disease 2019 (COVID-19) who developed hypoxemic respiratory failure necessitating high-flow nasal cannula (HFNC) therapy and to identify the predictors of HFNC therapy success. METHODS: This retrospective observational study involved all patients treated with HFNC therapy at a center for COVID-19 in Viet Nam from August to October 2021. RESULTS: The study recruited 302 patients. Of these 302 patients, 171 (56.6%) underwent successful HFNC therapy, and the all-cause mortality rate was 33.44%. Non-critical COVID-19 and a higher respiratory rate-oxygenation (ROX) index at 48 hours after initiating HFNC therapy were independently correlated with HFNC therapy success. The statistically significant predictors of HFNC therapy success were younger age, non-critical COVID-19, a higher platelet count when starting HFNC therapy, and a higher ROX index at 24, 36, and 48 hours after HFNC therapy initiation. CONCLUSIONS: HFNC therapy appears to be effective in patients with COVID-19 who develop respiratory failure requiring respiratory support. Non-critical COVID-19 and a higher ROX index measured 48 hours after HFNC therapy initiation might serve as predictive factors for the success of HFNC therapy.

Transparent Pneumatic Tactile Sensors for Soft Biomedical Robotics.

Palpation is a simple but effective method to distinguish tumors from healthy tissues. The development of miniaturized tactile sensors embedded on endoscopic or robotic devices is key to achieving precise palpation diagnosis and subsequent timely treatment. This paper reports on the fabrication and characterization of a novel tactile sensor with mechanical flexibility and optical transparency that can be easily mounted on soft surgical endoscopes and robotics. By utilizing the pneumatic sensing mechanism, the sensor offers a high sensitivity of 1.25 mbar and negligible hysteresis, enabling the detection of phantom tissues with different stiffnesses ranging from 0 to 2.5 MPa. Our configuration, combining pneumatic sensing and hydraulic actuating, also eliminates electrical wiring from the functional elements located at the robot end-effector, thereby enhancing the system safety. The optical transparency path in the sensors together with its mechanical sensing capability open interesting possibilities in the early detection of solid tumor as well as in the development of all-in-one soft surgical robots that can perform visual/mechanical feedback and optical therapy.

SPOTTED-LEAF7 targets the gene encoding ß-galactosidase9, which functions in rice growth and stress responses.

ß-Galactosidases (Bgals) remove terminal ß-D-galactosyl residues from the nonreducing ends of ß-D-galactosidases and oligosaccharides. Bgals are present in bacteria, fungi, animals, and plants and have various functions. Despite the many studies on the evolution of BGALs in plants, their functions remain obscure. Here, we identified rice (Oryza sativa) ß-galactosidase9 (OsBGAL9) as a direct target of the heat stress-induced transcription factor SPOTTED-LEAF7 (OsSPL7), as demonstrated by protoplast transactivation analysis and yeast 1-hybrid and electrophoretic mobility shift assays. Knockout plants for OsBGAL9 (Osbgal9) showed short stature and growth retardation. Histochemical ß-glucuronidase (GUS) analysis of transgenic lines harboring an OsBGAL9pro:GUS reporter construct revealed that OsBGAL9 is mainly expressed in internodes at the mature stage. OsBGAL9 expression was barely detectable in seedlings under normal conditions but increased in response to biotic and abiotic stresses. Ectopic expression of OsBGAL9 enhanced resistance to the rice pathogens Magnaporthe oryzae and Xanthomonas oryzae pv. oryzae, as well as tolerance to cold and heat stress, while Osbgal9 mutant plants showed the opposite phenotypes. OsBGAL9 localized to the cell wall, suggesting that OsBGAL9 and its plant putative orthologs likely evolved functions distinct from those of its closely related animal enzymes. Enzyme activity assays and analysis of the cell wall composition of OsBGAL9 overexpression and mutant plants indicated that OsBGAL9 has activity toward galactose residues of arabinogalactan proteins (AGPs). Our study clearly demonstrates a role for a member of the BGAL family in AGP processing during plant development and stress responses.