PLAGL1 overexpression induces cytoplasmic DNA accumulation that triggers cGAS/STING activation.

Pancreatic ß-cell damage mediated by apoptosis is believed to be a main trigger of type 1 diabetes mellitus (T1DM), which is proposed as an organ-specific autoimmune disease mediated by T cells. Nonetheless, the fundamental origins of T1DM remain uncertain. Here, we illustrate that an increase in PLAGL1 expression induces ß-cell apoptosis, as evidenced by mitochondrial membrane impairment and nucleolar degradation. The gene expression levels from cDNA samples were determined using qRT-PCR method. Western blot and Co-immunoprecipitation were applied for protein expression and interactions, respectively. Flow cytometry and TUNEL assay were used to detect pancreatic ß cell apoptosis. Female NOD/LtJ mice with recent-onset T1DM has been used in in vivo studies. Glucose-stimulated insulin secretion (GSIS) and glucose tolerance test (GTT) method is used for islet function assessment. Haematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) were performed to evalute histological improvement of islet beta. Subsequent cytoplasmic DNA accumulation triggers DNA senser, the cyclic guanosine monophosphate-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. STING activation further stimulates downstream IRF3 and NF-kB pathways, thus boost type-I interferon signalling and NF-kB mediated inflammation. These findings elucidate a molecular mechanism linking PLAGL1 induced cell apoptosis to type-I interferon signalling and suggest a potential benefit for targeting cGAS/STING in T1DM treatment.

Construction and implementation of a laparoscopic skill training course based on a smartphone application and virtual reality.

BACKGROUND: To develop a laparoscopic training course that combines a smartphone application (APP) and virtual reality (VR), and initially evaluate the feasibility and effectiveness of its implementation. METHODS: The Exploring Laparoscopy (Ex-Lap) app was developed to meet training demands. The course was designed by integrating the app with a VR simulator (LapSim®) and animal organ perfusion simulators. From January 2021 to December 2023, 91 participants were enrolled in the study and then divided into 5 separate batches to undergo the first stage of the course. The performance of the participants was evaluated by rating scale, the overall Training and Assessment of Basic Laparoscopic Techniques (TABLT) scores, and pass rates. Statistical analyses were conducted using SPSS 26.0, employing Kruskal-Wallis tests, Chi-squared analysis, and Fisher's exact test, depending on the data type. RESULTS: The Staged Training and Assessment of Laparoscopic Skills (STALS) course was developed, consisting of three stages. The overall pass rates for the first stage across the five batches ranged from 85 to 100%, with no significant difference (P = 0.387). No significant differences were found in the scale scores or TABLT scores for the training tasks among students from different batches (all P > 0.05). CONCLUSIONS: The STALS course is applicable in residency training, demonstrating satisfactory teaching effectiveness and replicability.

Prediction model establishment and validation for enteral nutrition aspiration during hospitalization in patients with acute pancreatitis.

BACKGROUND: Acute pancreatitis (AP) is a disease caused by abnormal activation of pancreatic enzymes and can lead to self-digestion of pancreatic tissues and dysfunction of other organs. Enteral nutrition plays a vital role in the treatment of AP because it can meet the nutritional needs of patients, promote the recovery of intestinal function, and maintain the barrier and immune functions of the intestine. However, the risk of aspiration during enteral nutrition is high; once aspiration occurs, it may cause serious complications, such as aspiration pneumonia, and suffocation, posing a threat to the patient's life. This study aims to establish and validate a prediction model for enteral nutrition aspiration during hospitalization in patients with AP. AIM: To establish and validate a predictive model for enteral nutrition aspiration during hospitalization in patients with AP. METHODS: A retrospective review was conducted on 200 patients with AP admitted to Chengdu Shangjin Nanfu Hospital, West China Hospital of Sichuan University from January 2020 to February 2024. Clinical data were collected from the electronic medical record system. Patients were randomly divided into a validation group (n = 40) and a modeling group (n = 160) in a 1:4 ratio, matched with 200 patients from the same time period. The modeling group was further categorized into an aspiration group (n = 25) and a non-aspiration group (n = 175) based on the occurrence of enteral nutrition aspiration during hospitalization. Univariate and multivariate logistic regression analyses were performed to identify factors influencing enteral nutrition aspiration in patients with AP during hospitalization. A prediction model for enteral nutrition aspiration during hospitalization was constructed, and calibration curves were used for validation. Receiver operating characteristic curve analysis was conducted to evaluate the predictive value of the model. RESULTS: There was no statistically significant difference in general data between the validation and modeling groups (P > 0.05). The comparison of age, gender, body mass index, smoking history, hypertension history, and diabetes history showed no statistically significant difference between the two groups (P > 0.05). However, patient position, consciousness status, nutritional risk, Acute Physiology and Chronic Health Evaluation (APACHE-II) score, and length of nasogastric tube placement showed statistically significant differences (P < 0.05) between the two groups. Multivariate logistic regression analysis showed that patient position, consciousness status, nutritional risk, APACHE-II score, and length of nasogastric tube placement were independent factors influencing enteral nutrition aspiration in patients with AP during hospitalization (P < 0.05). These factors were incorporated into the prediction model, which showed good consistency between the predicted and actual risks, as indicated by calibration curves with slopes close to 1 in the training and validation sets. Receiver operating characteristic analysis revealed an area under the curve (AUC) of 0.926 (95%CI: 0.8889-0.9675) in the training set. The optimal cutoff value is 0.73, with a sensitivity of 88.4 and specificity of 85.2. In the validation set, the AUC of the model for predicting enteral nutrition aspiration in patients with AP patients during hospitalization was 0.902, with a standard error of 0.040 (95%CI: 0.8284-0.9858), and the best cutoff value was 0.73, with a sensitivity of 91.9 and specificity of 81.8. CONCLUSION: A prediction model for enteral nutrition aspiration during hospitalization in patients with AP was established and demonstrated high predictive value. Further clinical application of the model is warranted.

Establishment of predictive models and determinants of preoperative gastric retention in endoscopic retrograde cholangiopancreatography.

BACKGROUND: Study on influencing factors of gastric retention before endoscopic retrograde cholangiopancreatography (ERCP) background: With the wide application of ERCP, the risk of preoperative gastric retention affects the smooth progress of the operation. The study found that female, biliary and pancreatic malignant tumor, digestive tract obstruction and other factors are closely related to gastric retention, so the establishment of predictive model is very important to reduce the risk of operation. AIM: To analyze the factors influencing preoperative gastric retention in ERCP and establish a predictive model. METHODS: A retrospective analysis was conducted on 190 patients admitted to our hospital for ERCP preparation between January 2020 and February 2024. Patient baseline clinical data were collected using an electronic medical record system. Patients were randomly matched in a 1:4 ratio with data from 190 patients during the same period to establish a validation group (n = 38) and a modeling group (n = 152). Patients in the modeling group were divided into the gastric retention group (n = 52) and non-gastric retention group (n = 100) based on whether gastric retention occurred preoperatively. General data of patients in the validation group and modeling group were compared. Univariate and multivariate logistic regression analyses were performed to identify factors influencing preoperative gastric retention in ERCP patients. A predictive model for preoperative gastric retention in ERCP patients was constructed, and calibration curves were used for validation. The receiver operating characteristic (ROC) curve was analyzed to evaluate the predictive value of the model. RESULTS: We found no statistically significant difference in general data between the validation group and modeling group (P > 0.05). The comparison of age, body mass index, hypertension, and diabetes between the two groups showed no statistically significant difference (P > 0.05). However, we noted statistically significant differences in gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction between the two groups (P < 0.05). Multivariate logistic regression analysis showed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were independent factors influencing preoperative gastric retention in ERCP patients (P < 0.05). The results of logistic regression analysis revealed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were included in the predictive model for preoperative gastric retention in ERCP patients. The calibration curves in the training set and validation set showed a slope close to 1, indicating good consistency between the predicted risk and actual risk. The ROC analysis results showed that the area under the curve (AUC) of the predictive model for preoperative gastric retention in ERCP patients in the training set was 0.901 with a standard error of 0.023 (95%CI: 0.8264-0.9567), and the optimal cutoff value was 0.71, with a sensitivity of 87.5 and specificity of 84.2. In the validation set, the AUC of the predictive model was 0.842 with a standard error of 0.013 (95%CI: 0.8061-0.9216), and the optimal cutoff value was 0.56, with a sensitivity of 56.2 and specificity of 100.0. CONCLUSION: Gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction are factors influencing preoperative gastric retention in ERCP patients. A predictive model established based on these factors has high predictive value.

Nonequilibrium Dynamic Phase Diagram for Transmembrane Transport of Active Particles.

In recent years, there has been considerable push toward the biomedical applications with active particles, which have great potential to revolutionize disease diagnostics and therapy. The direct penetration of active particles through the cell membrane leads to more efficient intracellular delivery than previously considered endocytosis processes but may cause membrane disruption. Understanding fundamental behaviors of cell membranes in response to such extreme impacts by active particles is crucial to develop active particle-based biomedical technologies and manage health and safety issues in this emerging field. Unfortunately, the physical principles underlying the nonequilibrium behaviors from endocytosis to direct penetration remain elusive, and experiments are challenging. Here, we present a computed dynamic phase diagram for transmembrane transport of active particles and identify four characteristic dynamic phases in endocytosis and direct penetration according to the particle activity and membrane tension. The boundaries dividing these phases are analytically obtained with theoretical models, elucidating the nonequilibrium physics and criteria for the transition between different phases. Furthermore, we numerically and experimentally show three distinct dynamic regimes related to the interplay between necking and wrapping during the endocytosis process of active particles, which strikingly contrast the regimes for passive particles. Overall, these findings could be useful for sharpening the understanding of basic principles underlying biological issues related to the safe and efficient biomedical applications of such emerging matters.

Designing antibacterial materials through simulation and theory.

Antibacterial materials have a wide range of potential applications in bio-antimicrobial, environmental antimicrobial, and food antimicrobial fields due to their intrinsic antimicrobial properties, which can circumvent the development of drug resistance in bacteria. Understanding the intricate mechanisms and intrinsic nature of diverse antibacterial materials is significant for the formulation of guidelines for the design of materials with rapid and efficacious antimicrobial action and a high degree of biomedical material safety. Herein, this review highlights the recent advances in investigating antimicrobial mechanisms of different antibacterial materials with a particular focus on tailored computer simulations and theoretical analysis. From the view of structure and function, we summarize the characteristics and mechanisms of different antibacterial materials, introduce the latest advances of new antibacterial materials, and discuss the design concept and development direction of new materials. In addition, we underscore the significance of employing simulation and theoretical methodologies to elucidate the intrinsic antimicrobial mechanisms, which is crucial for a comprehensive comprehension of the control strategies, safer biomedical applications, and the management of health and environmental concerns associated with antibacterial materials. This review could potentially stimulate further endeavors in fundamental research and facilitate the extensive utilization of computational and theoretical approaches in the design of novel functional nanomaterials.

Establishment and validation of a predictive model for peripherally inserted central catheter-related thrombosis in patients with liver cancer.

BACKGROUND: Peripherally inserted central catheters (PICCs) are commonly used in hospitalized patients with liver cancer for the administration of chemotherapy, nutrition, and other medications. However, PICC-related thrombosis is a serious complication that can lead to morbidity and mortality in this patient population. Several risk factors have been identified for the development of PICC-related thrombosis, including cancer type, stage, comorbidities, and catheter characteristics. Understanding these risk factors and developing a predictive model can help healthcare providers identify high-risk patients and implement preventive measures to reduce the incidence of thrombosis. AIM: To analyze the influencing factors of PICC-related thrombosis in hospitalized patients with liver cancer, construct a predictive model, and validate it. METHODS: Clinical data of hospitalized patients with liver cancer admitted from January 2020 to December 2023 were collected. Thirty-five cases of PICC-related thrombosis in hospitalized patients with liver cancer were collected, and 220 patients who underwent PICC placement during the same period but did not develop PICC-related thrombosis were randomly selected as controls. A total of 255 samples were collected and used as the training set, and 77 cases were collected as the validation set in a 7:3 ratio. General patient information, case data, catheterization data, coagulation indicators, and Autar Thrombosis Risk Assessment Scale scores were analyzed. Univariate and multivariate unconditional logistic regression analyses were performed on relevant factors, and the value of combined indicators in predicting PICC-related thrombosis in hospitalized patients with liver cancer was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Univariate analysis showed statistically significant differences (P < 0.05) in age, sex, Karnofsky performance status score (KPS), bedridden time, activities of daily living impairment, parenteral nutrition, catheter duration, distant metastasis, and bone marrow suppression between the thrombosis group and the non-thrombosis group. Other aspects had no statistically significant differences (P > 0.05). Multivariate regression analysis showed that age ≥ 60 years, KPS score ≤ 50 points, parenteral nutrition, stage III to IV, distant metastasis, bone marrow suppression, and activities of daily living impairment were independent risk factors for PICC-related thrombosis in hospitalized patients with liver cancer (P < 0.05). Catheter duration of 1-6 months and catheter duration > 6 months were protective factors for PICC-related thrombosis (P < 0.05). The predictive model for PICC-related thrombosis was obtained as follows: P predictive probability = [exp (Logit P)]/[1 + exp (Logit P)], where Logit P = age × 1.907 + KPS score × 2.045 + parenteral nutrition × 9.467 + catheter duration × 0.506 + tumor-node-metastasis (TNM) staging × 2.844 + distant metastasis × 2.065 + bone marrow suppression × 2.082 + activities of daily living impairment × 13.926. ROC curve analysis showed an area under the curve (AUC) of 0.827 (95%CI: 0.724-0.929, P < 0.001), with a corresponding optimal cut-off value of 0.612, sensitivity of 0.755, and specificity of 0.857. Calibration curve analysis showed good consistency between the predicted occurrence of PICC-related thrombosis and actual occurrence (P > 0.05). ROC analysis showed AUCs of 0.888 and 0.729 for the training and validation sets, respectively. CONCLUSION: Age, KPS score, parenteral nutrition, TNM staging, distant metastasis, bone marrow suppression, and activities of daily living impairment are independent risk factors for PICC-related thrombosis in hospitalized patients with liver cancer, while catheter duration is a protective factor for the disease. The predictive model has an AUC of 0.827, indicating high predictive accuracy and clinical value.

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures.

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mixtures and predicting mixture toxicity are crucial for effective mixture risk assessment. We tested the toxicities of 75 binary mixtures of antibiotics and fungicides against Auxenochlorella pyrenoidosa. Both regression and classification models for these mixtures were developed using machine learning models: random forest (RF), k-nearest neighbors (KNN), and kernel k-nearest neighbors (KKNN). The KKNN model emerged as the best regression model with high values of determination coefficient (R2 = 0.977), explained variance in prediction leave-one-out (Q2LOO = 0.894), and explained variance in external prediction (Q2F1 = 0.929, Q2F2 = 0.929, and Q2F3 = 0.923). The RF model, the leading classifier, exhibited high accuracy (accuracy = 1 for the training set and 0.905 for the test set) in distinguishing the synergistic and antagonistic mixtures. These results provide crucial value for the risk assessment of mixtures.

Efficient recovery of gold from solution with a thiocyanate-modified Zr-MOF: adsorption properties and DFT calculations.

The design and development of new large-capacity and selective materials for extracting rare precious metals via electronic waste is practically essential. In this paper, a new efficient UiO-66-NCS has been obtained as a consequence of the modification of the classical Zr-MOF (UiO-66-NH2), and its ability to recover gold has been investigated. These batch results adequately illustrated that UiO-66-NCS exhibited good adsorption capacity (675.5 mg g-1) and exceptional selectivity. In addition, UiO-66-NCS achieved faster adsorption equilibrium times of about 120 min. Adsorption kinetics and isotherms demonstrated that the pseudo-second-order adsorption scheme and a Langmuir-type procedure were shown by the adsorption of Au(III) on UiO-66-NCS. Characterized by pH effect experiments, TEM, XRD, and XPS, the adsorption of UiO-66-NCS with Au(III) relies on coordination, which further results in reduction, and the generated Au(0) is uniformly dispersed in the MOF. The adsorbent has considerable advantages for cyclic regeneration. Finally, DFT fitting results showed that the adsorption binding energy of UiO-66-NCS with [AuCl4]- was -8.63 kcal mol-1 for the adsorption process. UiO-66-NCS is likely to be an ideal substance for gold recovery.

Cold atom microwave clock based on intracavity cooling in China space station.

Atomic clocks with higher frequency stability and accuracy than traditional space-borne atomic clocks are the cornerstone of long-term autonomous operation of space-time-frequency systems. We proposed a space cold atoms clock based on an intracavity cooling scheme, which captures cold atoms at the center of a microwave cavity and then executes in situ interactions between the cold atoms and microwaves. As a result of the microgravity environment in space, the cold atoms can interact with the microwaves for a longer time, which aids in realizing a high-precision atomic clock in space. This paper presents the overall design, operational characteristics, and reliability test results of the space atomic clock based on the intracavity cooling scheme designed for the operation onboard the China space station. In addition, the engineering prototype performance of the space cold atoms microwave clock is also presented. The ground test results for the clock show a fractional frequency stability of 1.1 × 10-12 τ-1/2 reaching 2.5 × 10-15 at 200,000 s, providing solid technical and data support for its future operation in orbit.

X-Ray Multibeam Ptychography at up to 20 keV: Nano-Lithography Enhances X-Ray Nano-Imaging.

Hard X-rays are needed for non-destructive nano-imaging of solid matter. Synchrotron radiation facilities (SRF) provide the highest-quality images with single-digit nm resolution using advanced techniques such as X-ray ptychography. However, the resolution or field of view is ultimately constrained by the available coherent flux. To address this, the beam's incoherent fraction can be exploited using multiple parallel beams in an X-ray multibeam ptychography (MBP) approach. This expands the domain of X-ray ptychography to larger samples or more rapid measurements. Both qualities favor the study of complex composite or functional samples, such as catalysts, energy materials, or electronic devices. The challenge of performing ptychography at high energy and with many parallel beams must be overcome to extract the full advantages for extended samples while minimizing beam attenuation. Here, that challenge is overcome by creating a lens array using cutting-edge laser printing technology and applying it to perform scanning with MBP with up to 12 beams and at photon energies of 13 and 20 keV. This exceeds the measurement limits of conventional hard X-ray ptychography without compromising image quality for various samples: Siemens star test pattern, Ni/Al2O3 catalyst, microchip, and gold nano-crystal clusters.

Pushing the Limits of Capacitively Coupled Contactless Conductivity Detection for Capillary Electrophoresis.

Capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) has proven to be an efficient technique for the separation and detection of charged inorganic, organic, and biochemical analytes. It offers several advantages, including cost-effectiveness, nanoliter injection volume, short analysis time, good separation efficiency, suitability for miniaturization, and portability. However, the routine determination of common inorganic cations (NH4+, K+, Na+, Ca2+, Mg2+, and Li+) and inorganic anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-) in water quality monitoring typically exhibits limits of detection of about 0.3-1 µM without preconcentration. This sensitivity often proves insufficient for the applications of CE-C4D in trace analysis situations. Here, we explore methods to push the detection limits of CE-C4D through a comprehensive consideration of signal and noise sources. In particular, we (i) studied the model of C4D and its guiding roles in C4D and CE-C4D, (ii) optimized the bandwidth and noise performance of the current-to-voltage (I-V) converter, and (iii) reduced the noise level due to the strong background signal of the background electrolyte by adaptive differential detection. We characterized the system with Li+; the 3-fold signal-to-noise (S/N) detection limit for Li+ was determined at 20 nM, with a linear range spanning from 60 nM to 1.6 mM. Moreover, the optimized CE-C4D method was applied to the analysis of common mixed inorganic cations (K+, Na+, Ca2+, Mg2+, and Li+), anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-), toxic halides (BrO3-) and heavy metal ions (Pb2+, Cd2+, Cr3+, Co2+, Ni2+, Zn2+, and Cu2+) at trace concentrations of 200 nM. All electropherograms showed good S/N ratios, thus proving its applicability and accuracy. Our results have shown that the developed CE-C4D method is feasible for trace ion analysis in water quality control.

Annexin 1 Reduces Dermatitis-Induced Itch and Cholestatic Itch through Inhibiting Neuroinflammation and Iron Overload in the Spinal Dorsal Horn of Mice.

The unclear pathogenesis of chronic itch originating from several systemic disorders poses challenges to clinical intervention. Recent studies recapitulate the spinal neurocircuits associated with neuroinflammation and synaptic plasticity responsible for pruriceptive sensations. The resolution of nociception and inflammation by Annexin 1 (ANXA1) has been identified. Given that pain and itch share many neural mechanisms, we employed two mice models of chronic itch to study the underlying targets and therapeutic potential of ANXA1, comprising allergic contact dermatitis-induced itch and cholestatic itch. Herein, we report that spinal expression of ANXA1 is down-regulated in mice with dermatitis-induced itch and cholestatic itch. Repetitive injections of ANXA1-derived peptide Ac2-26 (intrathecal, 10 µg) reduce itch-like scratching behaviors following dermatitis and cholestasis. Single exposure to Ac2-26 (intrathecal, 10 µg) alleviates the established itch phenotypes. Moreover, systemic delivery of Ac2-26 (intravenous, 100 µg) is effective against chronic dermatitis-induced itch and cholestatic itch. Strikingly, Ac2-26 therapy inhibits transferrin receptor 1 over-expression, iron accumulation, cytokine IL-17 release and the production of its receptor IL-17R, as well as astrocyte activation in the dorsal horn of spinal cord in mouse with dermatitis and cholestasis. Pharmacological intervention with iron chelator deferoxamine impairs chronic itch behaviors and spinal iron accumulation after dermatitis and cholestasis. Also, spinal IL-17/IL-17R neutralization attenuates chronic itch. Taken together, this current research indicates that ANXA1 protects against the beginning and maintenance of long-term dermatitis-induced itch and cholestatic itch, which may occur via the spinal suppression of IL-17-mediated neuroinflammation, astrocyte activation and iron overload.

Correction: A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D).

Correction for 'A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D)' by Lin Li et al., Analyst, 2024, https://doi.org/10.1039/d4an00354c.

Symptom networks analysis among people with Meniere's disease: Application for nursing care.

Objectives: This study aimed to explore and visualize the relationships among multiple symptoms in patients with Meniere's disease (MD) and aid clinical nurses in the design of accurate, individualized interventions. Methods: This study included 790 patients with MD at the Eye and ENT Hospital of Fudan University from October 2014 to December 2021. A self-designed symptom checklist was used to assess 15 MD-related symptoms and construct contemporaneous networks with all 15 symptoms in R software. Qgraph package and Fruchterman-Reingold layout were used for network visualization. Bootstrapping methods were performed to assess network accuracy and stability, and three centrality indices were adopted to describe relationships among symptoms. Results: Symptom networks showed good accuracy and stability. "Anxiety and nervousness"(98.2%), "aural fullness"(84.4%) and "tinnitus"(82.7%) were the common symptom in MD patients, while "tinnitus", "aural fullness" and "decline in word recognition", were more serious. MD patients with longer disease duration had higher prevalence and severity for all symptoms (P < 0.05). Symptom networks showed good accuracy and stability. "Decline in word recognition," "fatigue," and "anxiety and nervousness" were at the center of the symptom networks, which had the largest strength values and closeness. "Decline in word recognition," "headache," and "spatial discrimination and poor orientation" were the symptoms with the highest betweenness with the strongest bridging effect. The ≥1-year disease group exhibited higher centralities for "drop attack" and "anxiety and nervousness," and a lower centrality for "headache" compared with the <1-year disease group. Conclusions: The symptom networks of MD patients with varying disease durations were revealed. Clinicians and nurses must provide precision interventions tailored to modifying symptom severity and centrality. Nursing interventions should focus on word recognition issues and associated discomfort in MD patients with multiple symptoms.

Need to Revise Classification of Physical Activity Intensity in Older Adults? The Use of Estimated METs, Measured METs, and V̇O2 Reserve.

BACKGROUND: Multiples of resting metabolic rate (RMR) are often used to classify physical activity intensity, a concept known as the metabolic equivalent of task (MET). However, the METs metrics may misclassify physical activity intensity in older adults because of age-related changes in RMR and maximal aerobic capacity (V˙O2max). This study aimed to (i) compare classifications of activity intensity by estimated (METsestimated) and measured (METsmeasured) METs and (ii) compare physical activity classified by absolute (METsmeasured) versus relative intensity (%V˙O2Reserve) in older adults. METHODS: Ninety-eight adults aged 75-90 years participated in the study. RMR and V˙O2 during sitting, standing, daily activities, and 6-minute walking test were measured. V˙O2Reserve was defined as the difference between V˙O2max and RMR. Moderate and vigorous intensity was classified as 3 and 6 METs and 40% and 60% of V˙O2Reserve, respectively. Paired t tests and a confusion matrix were used to investigate aims 1 and 2, respectively. RESULTS: METsmeasured was 24% lower than the standard 1 MET of 3.5 mL O2·min-1·kg-1. METsestimated underestimated the intensity during daily and walking activities when compared to METsmeasured. Nevertheless, when comparing METsmeasured to percentages of V˙O2Reserve, a mismatch was shown for moderate intensity in 47%-67% of the participants during daily activities and 21% of the participants during self-selected gait speed. CONCLUSIONS: Applying METsestimated for older adults leads to potential underestimation of physical activity intensity, suggesting that current classification metrics should be revised for older adults. V˙O2Reserve is a candidate metric for establishing precise physical activity intensity cut points for older adults. Clinical Trials Registration Number: NCT04821713.

Genomes of multicellular algal sisters to land plants illuminate signaling network evolution.

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum. We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.

Comparative Efficacy of Micro-Needle-Knife Therapy and Acupuncture in Acute Ankle Sprains: A Randomized Controlled Trial.

BACKGROUND Micro-needle knife (MNK) therapy releases the superficial fascia to alleviate pain and improve joint function in patients with acute ankle sprains (AAS). We aimed to evaluate the efficacy and safety of MNK therapy vs that of acupuncture. MATERIAL AND METHODS This blinded assessor, randomized controlled trial allocated 80 patients with AAS to 2 parallel groups in a 1: 1 ratio. The experimental group received MNK therapy; the control group underwent conventional acupuncture treatment at specified acupoints. Clinical efficacy differences between the 2 groups before (time-point 1 [TP1]) and after treatment (TP2) were evaluated using the visual analogue scale (VAS) and Kofoed ankle score. Safety records and evaluations of adverse events were documented. One-month follow-up after treatment (TP3) was conducted to assess the intervention scheme's reliability. RESULTS VAS and Kofoed ankle scores significantly improved in both groups. No patients dropped due to adverse events. At TP1, there were no significant differences between the 2 groups in terms of VAS and Kofoed scores (P>0.05). However, at TP2, efficacy of MNK therapy in releasing the superficial fascia was significantly superior to that of acupuncture treatment (P<0.001). At TP3, no significant differences in scores existed between the groups (P>0.05). CONCLUSIONS This study demonstrates that 6 sessions of MNK therapy to release the superficial fascia safely and effectively alleviated pain and enhanced ankle joint function in patients with AAS, surpassing the efficacy of conventional acupuncture treatment. Future studies should increase the sample size and introduce additional control groups to further validate the superior clinical efficacy of this intervention.

A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D).

Capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) has the advantages of high throughput (simultaneous detection of multiple ions), high separation efficiency (higher than 105 theoretical plates) and rapid analysis capability (less than 5 min for common inorganic ions). A compact CE-C4D system is ideal for water quality control and on-site analysis. It is suitable not only for common cations (e.g. Na+, K+, Li+, NH4+, Ca2+, etc.) and anions (e.g. Cl-, SO42-, BrO3-, etc.) but also for some ions (e.g. lanthanide ions, Pb2+, Cd2+, etc.) that require complex derivatization procedures to be detected by ion chromatography (IC). However, an obvious limitation of the CE-C4D method is that its sensitivity (e.g. 0.3-1 µM for common inorganic ions) is often insufficient for trace analysis (e.g. 1 ppb or 20 nM level for common inorganic ions) without preconcentration. For this technology to become a powerful and routine analytical technique, the system should be made compact while maintaining trace analysis sensitivity. In this study, we developed an all-in-one version of the CE-C4D instrument with custom-made modular components to make it a convenient, compact and high-performance system. The system was designed using direct digital synthesis (DDS) technology to generate programmable sinusoidal waveforms with any frequency for excitation, a kilovolt high-voltage power supply for capillary electrophoresis separation, and an "effective" differential C4D cell with a low-noise circuitry for high-sensitivity detection. We characterized the system with different concentrations of Cs+, and even a low concentration of 20 nM was detectable without preconcentration. Moreover, the optimized CE-C4D setup was applied to analyse mixed ions at a trace concentration of 200 nM with excellent signal-to-noise ratios. In typical applications, the limits of detection based on the 3σ criterion (without baseline filtering) were 9, 10, 24, 5, and 12 nM for K+, Cs+, Li+, Ca2+, and Mg2+, respectively, and about 7, 6, 6 and 6 nM for Br-, ClO4-, BrO3- and SO42-, respectively. Finally, the setup was also applied for the analysis of all 14 lanthanide ions and rare-earth minerals, and it showed an improvement in sensitivity by more than 25 times.