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Background Pneumonia during pregnancy has been proven to be associated with increased maternal and fetal morbidity and mortality. The management of severe pneumonia in gravid patients is even more challenging. Thus, we summarized the characteristics and pregnancy outcomes of these patients and explored the probable risk factors and predictive factors for pneumonia during pregnancy and the appropriate timing of delivery in severe pneumonia patients. Methods A retrospective cohort study was conducted with 12 patients who were diagnosed with severe pneumonia complicating pregnancy at Peking Union Medical College Hospital between January 2010 and June 2017. The clinical features, treatment strategies, and pregnancy outcomes were collected from medical records and telephone calls. Results All 12 patients were in their late second or third trimester. The patients had a higher prevalence of anemia (50%) and preeclampsia (25%) than ordinary pregnant women. Delayed diagnoses were not uncommon. Two mothers died in our series, resulting in a mortality rate of 17%. Two intrauterine deaths were observed. Elective delivery was not performed in any of the four patients in their second trimester. Six of the seven patients who presented after 28 weeks of gestation and had live fetuses underwent emergency deliveries. Preterm births (6/7) and cesarean sections (5/7) were the two leading adverse outcomes in newborns. Conclusions Anemia, advanced gestational age, and preeclampsia might be associated with the severity of pneumonia. Chest radiographs should be taken as soon as pneumonia is highly suspected to facilitate an early diagnosis. High incidences of adverse fetal outcomes were observed; thus, termination of the pregnancy is recommended for patients in their third trimester when respiratory function deteriorates progressively. However, it might be reasonable to continue pregnancy for those in their first or second trimester.

Nucleic-acid biosensors have emerged as useful tools for on-farm detection of foodborne pathogens on fresh produce. Such tools are specifically designed to be user-friendly so that a producer can operate them with minimal training and in a few simple steps. However, one challenge in the deployment of these biosensors is delivering precise sample volumes to the biosensor’s reaction sites. To address this challenge, we developed an innovative drop dispenser using advanced 3D printing technology, combined with a hydrophilic surface chemistry treatment. This dispenser enables the generation of precise sample drops, containing DNA or bacterial samples, in volumes as small as a few micro-liters (∼20 to ∼33 μL). The drop generator was tested over an extended period to assess its durability and usability over time. The results indicated that the drop dispensers have a shelf life of approximately one month. In addition, the device was rigorously validated for nucleic acid testing, specifically by using loop-mediated isothermal amplification (LAMP) for the detection of Escherichia coli O157, a prevalent foodborne pathogen. To simulate real-world conditions, we tested the drop dispensers by integrating them into an on-farm sample collection system, ensuring they deliver samples accurately and consistently for nucleic acid testing in the field. Our results demonstrated similar performance to commercial pipettors in LAMP assays, with a limit of detection of 7.8×10 6 cells/mL for whole-cell detection. This combination of precision, ease of use, and durability make our drop dispenser a promising tool for enhancing the effectiveness of nucleic acid biosensors in the field.

An oleyl alcohol-based extended surfactant, sodium oleyl polyethylene oxide-polypropylene oxide sulfate (OE3P3S), was synthesized and identified using FT-IR and 1H NMR. The adsorption and aggregation behaviors of OE3P3S and its mixture with cationic surfactant alkyltrimethylammoniumbromide (ATAB) were investigated under different molar ratios. The static surface tension analysis indicated that the critical micellization concentration (cmc) and the critical surface tension (γcmc) of OE3P3S were 0.72 mmol/L, and 36.16 mN/m, respectively. The cmc and γcmc values of the binary system were much lower than that of the individual component. And the cmc values of OE3P3S/ATAB = 6:4 mixtures decreased with an increase in the chain length of the cationic surfactant in the binary system. It was found from the dynamic surface tension that there was a slower diffusion rate in the binary system compared to the pure surfactant, and the adsorption processes for OE3P3S/ATAB = 6:4 were mixed diffusion-kinetic adsorption mechanisms. With a combination of DLS data and TEM measurements, formations of vesicles in OE3P3S/ATAB = 6:4 solutions appeared to occur at a concentration of 0.05 mmol/L. By studying the formation of liquid crystal structures in an emulsion prepared with OE3P3S as the surfactant, it was found that the oil-in-water emulsion is birefringent with a Maltese cross texture, and the rheological properties revealed its predominant viscoelastic behavior and shear thinning properties.

Microfluidic paper-based analytical devices (µPADs) are an attractive format for colorimetric nucleic acid amplification tests (NAATs) because they enable low-cost, portable diagnostics in resource-limited settings. However, researchers often optimize colorimetric assays in liquid reactions in tubes before translating them to µPADs. Since both formats require separate instruments for incubation and real-time sensing, direct comparison of reactions between the two formats is difficult. To address these cross-platform limitations, we developed ThermiQuant™ AquaStream, a portable benchtop device (15 × 20 × 16 cm, ~ 5 kg; cost: USD 327) that supports seamless colorimetric loop-mediated isothermal amplification (LAMP) reactions in both µPADs and tubes under a common workflow. The system enables real-time reaction tracking (every 30 seconds) through onboard image processing, precise isothermal control (±0.5 °C) using a repurposed consumer-grade sous-vide heater, and medium-throughput (24 tubes or 42 µPADs). Testing with synthetic SARS-CoV-2 orf7ab DNA fragments demonstrated a limit of detection corresponding to a 95% probability of detection (LOD95) of 110 copies per reaction in tube (22 copies/µL) and 39 copies per reaction in µPADs (5 copies/µL), estimated using probit regression. In both formats the limit of quantification (LOQ), defined as the lowest concentration yielding a coefficient of variation (CV) of quantification time (Tq) ≤ 10%, was 250 copies/reaction resulting in a strong linear (R 2 = 0.98 & R 2 = 0.96 respectively for tube and µPADs) standard calibration curves. ThermiQuant™ AquaStream provides an affordable and versatile benchtop platform capable of supporting both tube- and µPAD-based colorimetric LAMP assays, serving as a proof-of-concept research tool for assay development and molecular diagnostics in One Health settings such as clinics, farms, and field environments.

In the past few decades, the use of acupuncture analgesia in clinical practice has increased worldwide. This is due to its various benefits, including natural alleviation of pain without causing various adverse effects associated with non-steroidal anti-inflammatory drugs (NSAID) and opioids. The acupoint represents the initial site of acupuncture stimulation, where diverse types of nerve fibers located at the acupoint hold significant roles in the generation and transmission of acupuncture-related information. In this study, we analyzed the patterns and mechanisms of acupuncture analgesic mediated by acupoint afferent fibers, and found that acupuncture stimulates acupoints which rapidly and directly induces activation of high-density primary afferent fibers under the acupoints, including myelinated A fibers and unmyelinated C fibers. During acupuncture stimulation at the muscle layer, the analgesic effects can be induced by stimulation of A fiber threshold intensity. At the skin layer, the analgesic effects can only be produced by stimulation of C fiber threshold intensity. Electroacupuncture (EA) activates A fibers, while manual acupuncture (MA) activates both A and C fibers. Furthermore, acupuncture alters acupoint microenvironments, which positively modulates afferent fibers, enhancing the transmission of analgesic signals. In addition to local activation and conduction at acupoints, nerve fibers mediate the transmission of acupuncture information to pain centers. In the spinal cord, acupuncture activates neurons by inducing afferent fiber depolarization, modulating pain gating, inhibiting long-term potentiation (LTP) of the spinal dorsal horn and wide dynamic range (WDR) neuronal activities. At higher nerve centers, acupuncture inhibits neuronal activation in pain-related brain regions. In summary, acupuncture inhibits pain signal transmission at peripheral and central systems by activating different patterns of afferent fibers located on various layers of acupoints. This study provides ideas for enhancing the precise application and clinical translation of acupuncture.

Carotid ultrasound requires skilled operators due to small vessel dimensions and high anatomical variability, exacerbating sonographer shortages and diagnostic inconsistencies. Prior automation attempts, including rule-based approaches with manual heuristics and reinforcement learning trained in simulated environments, demonstrate limited generalizability and fail to complete real-world clinical workflows. Here, we present UltraBot, a fully learning-based autonomous carotid ultrasound robot, achieving human-expert-level performance through four innovations: (1) A unified imitation learning framework for acquiring anatomical knowledge and scanning operational skills; (2) A large-scale expert demonstration dataset (247,000 samples, 100 × scale-up), enabling embodied foundation models with strong generalization; (3) A comprehensive scanning protocol ensuring full anatomical coverage for biometric measurement and plaque screening; (4) The clinical-oriented validation showing over 90% success rates, expert-level accuracy, up to 5.5 × higher reproducibility across diverse unseen populations. Overall, we show that large-scale deep learning offers a promising pathway toward autonomous, high-precision ultrasonography in clinical practice. Ultrasound examination significantly relies on manual operation, which has significant downsides. The authors present UltraBot, a carotid ultrasound robot capable of automated scanning, measurement, and plaque screening, and build an embodied foundation model using deep learning for intelligent, high-precision ultrasound.

Estimating household water consumption can facilitate infrastructure management and municipal planning. The relatively low explanatory power of household water consumption, although it has been extensively explored based on various techniques and assumptions regarding influencing features, has the potential to be enhanced based on the water-energy nexus concept. This study attempts to explain household water consumption by establishing estimation models, incorporating energy-related features as inputs and providing strong evidence of the need to consider the water-energy nexus to explain water consumption. Traditional statistical (OLS) and machine learning techniques (random forest and XGBoost) are employed using a sample of 1320 households in Beijing, China. The results demonstrate that the inclusion of energy-related features increases the coefficient of determination ( R 2 ) by 34.0% on average. XGBoost performs the best among the three techniques. Energy-related features exhibit higher explanatory power and importance than water-related features. These findings provide a feasible modelling basis and can help better understand the household water-energy nexus.

China launched a universal campaign of monovalent-inactivated EV-A71 vaccine in 2016. However, the monovalent-inactivated vaccine is ineffective against HFMD with other etiologies. To date, little is known about the epidemiological patterns and the replacement of the predominant pathogens that induce HFMD after the universal vaccination campaign. Using HFMD surveillance and VP1 sequencing data in pre- and post-vaccination periods, time series analysis, and Wavelet approaches, we identified pathogen replacement, changes in the viral spectrum and epidemiological patterns of HFMD. A prolonged but lower peak of HFMD occurred in the spring, and a late, higher peak presented during fall in the post-vaccination period. The typical half-year transmission cycle disappeared, the one-year cycle did not change, and the CVA16 and CVA6 serotypes have the potential to replace EV-A71 as the predominant strains. The epidemic pattern of HFMD has shifted after the vaccination campaign. While the EV-A71 vaccine reduced transmission in the spring season, it had little impact on reducing cases in fall. Meanwhile, potential new predominant strains have emerged. Public health system should incorporate enhanced surveillance by including whole genome sequencing to ensure close monitoring of serotype replacement and to assess the need for multivalent vaccines across Southern China.

Background Intra-hospital transport of critically ill, mechanically ventilated patients is associated with significant physiological risks. Adaptive Minute Ventilation (AMV) is a closed-loop ventilation mode that automatically maintains target minute ventilation. While AMV has shown promise in intensive care unit settings, its performance during intrahospital transport has not yet been evaluated. This trial aims to assess the safety and efficacy of AMV compared with conventional ventilation strategies during patient transport. Methods This is a single-centre, open-label, randomized controlled non-inferiority trial conducted at Peking Union Medical College Hospital. Fifty adult patients receiving invasive mechanical ventilation and requiring transport will be randomly assigned (1:1) to either AMV or their pre-transport ventilation mode. The primary endpoint is the change in arterial carbon dioxide pressure (PaCO₂) from 30 min before to 10 min after transport. Secondary outcomes include changes in oxygenation index (PaO₂/FiO₂), peak airway pressure, dynamic compliance, and rapid shallow breathing index. Randomization will be performed using permuted block randomization. Both intention-to-treat and per-protocol analyses will be conducted. Missing data will be handled using multiple imputation. The study protocol has been reviewed and approved by the Ethics Committee of Peking Union Medical College Hospital (Approval No. I-25PJ0781). It was registered in the Chinese Clinical Trial Registry (ChiCTR2500109659) on 23 September 2025 as a retrospective registration. Discussion This trial will be the first randomized study to evaluate AMV during intrahospital transport of critically ill patients. The findings will address an important evidence gap in transport ventilation strategies, potentially informing clinical practice on whether AMV provides a safe and effective alternative to conventional modes. By employing a non-inferiority design and standardized transport protocols, the study seeks to generate robust and clinically relevant evidence despite its single-centre setting and relatively small sample size. Trial registration Approved by the Ethics Committee of Peking Union Medical College Hospital (Approval No. I-25PJ0781). Trial registration: ChiCTR, ChiCTR2500109659. Registered 23 September 2025, https://www.chictr.org.cn/hvshowproject.html?id=284847 .

Paper-based biosensors are microfluidic analytical devices used for the detection of biochemical substances. The unique properties of paper-based biosensors, including low cost, portability, disposability, and ease of use, make them an excellent tool for point-of-care testing. Among all analyte detection methods, nucleic acid-based pathogen detection offers versatility due to the ease of nucleic acid synthesis. In a point-of-care testing context, the combination of nucleic acid detection and a paper-based platform allows for accurate detection. This review offers an overview of contemporary paper-based biosensors for detecting nucleic acids from pathogens. The methods and limitations of implementing an integrated portable paper-based platform are discussed. The review concludes with potential directions for future research in the development of paper-based biosensors.