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Next-generation sequencing protocol of hematopoietic stem cells (HSCs). Step-by-step overview and troubleshooting guide
Populations of very small embryonic-like stem cells (VSELs) (CD34+lin-CD45- and CD133+lin-CD45-), circulating in the peripheral blood of adults in small numbers, have been identified in several human tissues and together with the populations of hematopoietic stem cells (HSCs) (CD34+lin-CD45+) and CD133+lin-CD45+constitute a pool of cells with self-renewal and pluripotent stem cell characteristics. Using advanced cell staining and sorting strategies, we isolated populations of VSELs and HSCs for bulk RNA-Seq analysis to compare the transcriptomic profiles of both cell populations. Libraries were prepared from an extremely small number of cells; however, their good quality was preserved, and they met the criteria for sequencing. We present here a step-by-step NGS protocol for sequencing VSELs and HSC with a description of troubleshooting during library preparation and sequencing.
Effect of proprioceptive neuromuscular facilitation on patients with chronic ankle instability: A systematic review and meta-analysis
Objective This study conducts a rigorous meta-analysis of existing literature to rigorously examine the efficacy of Proprioceptive Neuromuscular Facilitation (PNF) in ameliorating functional deficits associated with Chronic Ankle Instability (CAI). Methods Literature searches were conducted in multiple databases including China National Knowledge Infrastructure (CNKI), VIP, Wanfang, China Biology Medicine disc (CBM), PubMed, EBSCO (Medline, CINAHL, SPORTDiscus, and Rehabilitation & Sports Medicine Source), Embase, ScienceDirect, ProQuest, Cochrane Library, and Web of Science for randomized controlled trials assessing the effects of Proprioceptive Neuromuscular Facilitation interventions on patients with Chronic Ankle Instability. The publication timeframe spanned from the inception of each database until April 10, 2024. Meta-analysis was performed using STATA 12 software on the included studies. Results ① A total of 12 randomized controlled trials were included, encompassing 405 patients with Chronic Ankle Instability, demonstrating a generally high methodological quality of the literature.② Meta-analysis results indicate that compared to the control group, Proprioceptive Neuromuscular Facilitation (PNF) significantly enhanced the balance ability of patients with Chronic Ankle Instability as measured by the Y Balance Test (YBT) (Weighted Mean Difference (WMD) = 3.61, 95% CI [2.65, 4.56], z = 7.42, P<0.001) and the Star Excursion Balance Test (SEBT) (WMD = 5.50, 95% CI [3.80, 7.19], z = 6.36, P<0.001), with improvement in all eight directions of SEBT balance ability surpassing that of the control group (P<0.05); muscle strength around the ankle (SMD) = 0.19, 95% CI [0.03, 0.36], z = 2.26, P = 0.024), with both Plantar flexion and Dorsal flexion muscle strength improvements exceeding those of the control group (P<0.05); Visual Analog Scale (VAS) (WMD = -1.39, 95% CI [-1.72, -1.06], z = 8.23, P<0.001); Ankle instability questionnaire (WMD = 2.91, 95% CI [1.92, 3.89], z = 5.78, P<0.001).③Descriptive analysis results showed that the differences in Inversion Joint Position Sense and Dorsiflexion range of motion between the PNF and control groups were not statistically significant (P>0.05), however, the effects of PNF training persisted for a certain period even after cessation of treatment. Conclusion Proprioceptive Neuromuscular Facilitation (PNF) can significantly improve balance, muscle strength, and pain in patients with Chronic Ankle Instability (CAI). While PNF has shown improvements in joint position sense and dorsiflexion range of motion for CAI patients, with effects that remain for a period thereafter, these improvements were not significantly different when compared to the control group. Further research is required to substantiate these specific effects.
Developing and validating a cross-cultural competence scale for Japanese nurses
In recent years, Japan has experienced a significant increase in the number of foreign students and workers entering the country. This has resulted in a vast number of international patients in medical facilities. This shift emphasizes the immediate need for Japanese nurses who are both clinically proficient and culturally attuned. In response, our research developed and validated the Cross-cultural Competence Scale for Japanese Nurses (CCCSJN) to better equip nurses for diverse patient care. We conducted a cross-sectional study in Japan’s general hospitals using anonymous questionnaires with nurses and midwives. The scale, developed from data from 394 nurses, underwent both qualitative and quantitative evaluations to define its construct. We analyzed the data using exploratory factor analysis, criterion-related validity, internal consistency, and test-retest reliability, confirming the scale’s reliability and validity. The exploratory analysis revealed five factors: “cross-cultural understanding,” “cross-cultural communication ability,” “motivation for cross-cultural nursing,” “cooperation with multiple professions,” and “respect for foreign patients.” These factors explained 50.92% of the total variance. Cronbach’s α for the CCCSJN was 0.94, and the test-retest reliability correlation was 0.77. The construct validity, criterion-related validity, internal consistency, and test-retest reliability of the CCCSJN were verified. The CCCSJN can be used to assess the cross-cultural competencies of Japanese nurses and identify what skills need to be mastered, leading to improved cross-cultural competence and care.
Gluteus medius muscle activation patterns during gait with Cerebral Palsy (CP): A hierarchical clustering analysis
Duchenne gait, characterized by an ipsilateral trunk lean towards the affected stance limb, compensates for weak hip abductor muscles, notably the gluteus medius (GM). This study aims to investigate how electromyographic (EMG) cluster analysis of GM contributes to a better understanding of Duchenne gait in patients with cerebral palsy (CP). We analyzed retrospective gait data from 845 patients with CP and 65 typically developed individuals. EMG activity of GM in envelope format were collected and examined with gait kinematics and kinetics parameters in frontal plane and hip abductor strength, and hip abduction passive range of motion. Six key EMG envelope features during ten gait phases were extracted and normalized. A hybrid K-means-PSO clustering algorithm was employed, followed by hierarchical clustering. The identified clusters were characterized by having a low (cluster_1), medium (cluster_2), and high (cluster_3) activity of GM during loading response. The patients in cluster_1 also exhibited pathological gait characteristics, including increased trunk lateral lean and weak hip abductor, which are associated with Duchenne gait. The patients in this cluster were subclustered according to their response to the intervention: SUB_1 with a significant improvement in trunk obliquity, pelvic obliquity, and hip abduction after intervention, and SUB_2 without such improvement. Comparing pre-treatment EMG and clinical exam of the sub_clusters, SUB_1 had significantly higher activity of GM during 50–87% of the gait cycle with a greater passive range of hip abduction compared to SUB_2. This study established a relationship between EMG of GM and frontal plane gait abnormalities in patients with CP, highlighting potential improvement in Duchenne gait with prolonged GM activity during swing after the intervention.
Chronic disease risk factors among hospital employees: A cross-sectional study in Türkiye
Introduction Chronic diseases have become a significant public health problem with the prolongation of human life. There are four main behavioral risk factors for mortality. This study evaluated the significant risk factors for chronic diseases in university hospital employees. Materials and methods The cross-sectional study population consisted of hospital employees working at Gazi University Hospital for at least one year. The sample size was calculated to be 285, with a 100% response rate. The study’s independent variables were age, gender, educational status, working department, and presence of chronic diseases. Dependent variables were smoking, alcohol use, physical inactivity, and body mass index (BMI) categories. Data on participants’ characteristics, habits, and behaviors were obtained from the hospital system or with open-ended questions. Their body weight and height were measured. The International Physical Activity Questionnaire (IPAQ) was used to assess physical inactivity. Results The smoking prevalence of hospital employees was 41.8%. Regular alcohol use was 19.3%. Based on the BMI values obtained, 37.9% of the participants were pre-obese, and 18.2% were obese. According to the results of the IPAQ, 13.7% were inactive. The prevalence of smoking was 50.4%, alcohol consume 11.6%, physical inactivity 50.4%, and overweight 65.3% among those who graduated from high school or lower. In contrast, the prevalences were 35.4%, 25.0%, 69.5%, and 49.4%, respectively, among those who graduated from university or higher. A one-unit increase in age of participants without chronic disease increased BMI by 1.06 times (p<0.05). When individuals with a high school education or lower are taken as the reference group, it was found that physical inactivity is 1.78 times higher among those with a university degree or higher (p<0.05). Conclusion The effect of education level on health habits and behaviors should be considered in terms of the target group and content of preventive health programs and awareness-raising studies.
Correction: Diet Modification and Metformin Have a Beneficial Effect in a Fly Model of Obesity and Mucormycosis
Ultra-compact quintuple-band terahertz metamaterial biosensor for enhanced blood cancer diagnostics
Cancer and its diverse variations pose one of the most significant threats to human health and well-being. One of the most aggressive forms is blood cancer, originating from bone marrow cells and disrupting the production of normal blood cells. The incidence of blood cancer is steadily increasing, driven by both genetic and environmental factors. Therefore, early detection is crucial as it enhances treatment outcomes and improves success rates. However, accurate diagnosis is challenging due to the inherent similarities between normal and cancerous cells. Although various techniques are available for blood cancer identification, high-frequency imaging techniques have recently shown promise, particularly for real-time monitoring. Notably, terahertz (THz) frequencies offer unique advantages for biomedical applications. This research proposes an innovative terahertz metamaterial-based biosensor for high-efficacy blood cancer detection. The proposed structure is ultra-compact and operates across five bands within the range of 0.6 to 1.2 THz. It is constructed using a polyethylene terephthalate (PET) dielectric layer and two aluminum (Al) layers, with the top layer serving as a base for the THz-range resonator. Careful design, architectural arrangement, and optimization of the geometry parameters allow for achieving nearly perfect absorption rates (>95%) across all operating bands. The properties of the proposed sensor are extensively evaluated through full-wave electromagnetic (EM) analysis, which includes assessing the refractive index and the distribution of the electric field at individual working frequencies. The suitability for blood cancer diagnosis has been validated by integrating the sensor into a microwave imaging (MWI) system and conducting comprehensive simulation studies. These studies underscore the device’s capability to detect abnormalities, particularly in distinguishing between healthy and cancerous cells. Benchmarking against state-of-the-art biosensors in recent literature indicates that the proposed sensor is highly competitive in terms of major performance indicators while maintaining a compact size.
Digital technology innovation, supply chain resilience and enterprise performance-The case of listed automotive parts manufacturing companies
Digital technology innovation (DTI) is the core driving force for the development of the digital economy. This paper brings digital technology innovation and the supply chain of auto parts manufacturing under the same framework. This paper uses Stata 18 to empirically analyze the panel data of 130 A-share auto parts listed companies in Shanghai and Shenzhen from 2010 to 2022. The digital technology innovation indicator is divided into three levels: substantial digital technology innovation (SDTI), non-substantial digital technology innovation (NDTI), overall digital technology innovation (ODTI). To explore its impact mechanism on enterprise performance. The empirical results show that: (1) Digital technological innovation (DTI) has a positive and significant impact on enterprise performance, and supply chain resilience plays a mediating role in the relationship between digital technology innovation and enterprise performance, and R&D investment (RDI) positively moderates the role of supply chain resilience in promoting enterprise performance. (2) Heterogeneity analysis showed that the impact of supply chain resilience on enterprise performance was more significant in small and medium-sized enterprises. There are significant differences between different groups of business ownership. In economically underdeveloped regions, the effect of digital technology innovation on enterprise performance is more significant. This paper complements the perspective of supply chain to study the relationship between digital technology innovation and enterprise performance, expands the existing research, and its heterogeneity analysis provides new insights for understanding China’s auto parts manufacturing industry. This provides a basis for strengthening digital technology innovation and promoting the sustainable development of the auto parts industry.
Cross-layer latency analysis for 5G NR in V2X communications
The 5G network was developed to push the capabilities of wireless networks to previously unseen performance limits, e.g., transmission rates of several gigabits per second, latency of less than a millisecond, and millions of devices connected at the same time. To meet these requirements, it is necessary to access new spectrum (the so-called millimeter waves) and use techniques such as Massive MIMO (Multiple-Input Multiple-Output) and beamforming. This required the design of a new radio interface, known as 5G NR, that includes improvements to its physical components and new protocols. The performance of the 5G network will depend heavily on the behavior of these new protocols under certain configuration parameters, traffic conditions, device density, and network architecture. This paper introduces an analytical model for the performance evaluation of 5G NR. The developed model describes the behavior of the different layer 1 and 2 protocols involved in 5G radio communication. Using the model, it is possible to evaluate the performance of 5G NR in terms of throughput and latency, two key performance metrics used to describe QoS (Quality of Service) thresholds of different applications. The protocol layer approach gives the model sufficient granularity to identify critical behaviors that significantly impact performance. This can help focus efforts on improving these key points or propose improvements/modifications to the operation of network protocols or devices. The use of this model for performance evaluation is exemplified by studying a Remote Driving scenario operated over 5G. This scenario has very stringent delay requirements, which, according to the model’s results, can be satisfied if the network conditions are adequate. This model and its results can be used as a starting point for performance evaluations of application involving end-to-end (E2E) communications.
Neurokinin-3 Receptor Antagonism for Refractory Hot Flashes in Men
Fabrication of glipizide loaded polymeric microparticles; in-vitro and in-vivo evaluation
Controlled-release microparticles offer a promising avenue for enhancing patient compliance and minimizing dosage frequency. In this study, we aimed to design controlled-release microparticles of Glipizide utilizing Eudragit S100 and Methocel K 100 M polymers as controlling agents. The microparticles were fabricated through a simple solvent evaporation method, employing various drug-to-polymer ratios to formulate different controlled-release batches labeled as F1 to F5. Evaluation of the microparticles encompassed a range of parameters including flow properties, particle size, morphology, percentage yield, entrapment efficiencies, percent drug loading, and dissolution studies. Additionally, various kinetic models were employed to elucidate the drug release mechanism. Furthermore, difference and similarity factors were utilized to compare the dissolution profiles of the tested formulations with a reference formulation. The compressibility index and angle of repose indicated favorable flow properties of the prepared microparticles, with values falling within the range of 8 to 10 and 25 to 29, respectively. The particle size distribution of the microparticles ranged from 95.3 to 126 μm. Encouragingly, the microparticles exhibited high percent yield (ranging from 66 to 77%), entrapment efficiency (80 to 96%), and percent drug loading (46 to 54%). All formulated batches demonstrated controlled drug release profiles extending up to 12 hours, with glipizide release following an anomalous non-Fickian diffusion pattern. However, the drug release profiles of the reference formulation and various polymeric microparticles did not meet the acceptable limits of difference and similarity factors. In-vivo studies revealed sustained hypoglycemic effects over a 12-hour period, indicating the efficacy of the controlled-release microparticles. Overall, our findings suggest the successful utilization of polymeric materials in designing controlled-release microparticles, thereby reducing dosage frequency and potentially improving patient compliance.
Human Infection with a Novel Tickborne Orthonairovirus Species in China
Study on the influence of TiO2 nanoparticles on the breakdown voltage of transformer oil under severe cold conditions
The modified nanoparticles can significantly improve the insulation characteristics of transformer oil. Currently, there is a lack of research on the actual motion state of particles in nanofluid to further understand the micro-mechanism of nanoparticles improving the insulation characteristics of transformer oil. In this study, the nanofluid containing 0.01g/L of TiO2 with a particle size of 20nm is prepared using the thermal oscillation method. Breakdown voltage tests are carried out. The experimental test results show that adding nanoparticles can significantly reduce the breakdown probability of transformer oil. The more the water content, the less the enhancement effect of the nanofluid on breakdown voltage. The higher the temperature, the stronger the enhancement effect of the nanofluid on breakdown voltage. Finally, the polarization process of nanoparticles and the trajectory of charged particles in the transformer oil under different electric fields are simulated using COMSOL to further analyze the influence mechanism of nanoparticles on the insulation characteristics of transformer oil. The simulation results show that under the action of the electric field, nanoparticles polarize and generate charge shallow traps to adsorb electrons, reducing the high-speed free charges in the oil, and indirectly increasing the breakdown voltage.
Argyria
VARX Granger analysis: Models for neuroscience, physiology, sociology and econometrics
Complex systems, such as in brains, markets, and societies, exhibit internal dynamics influenced by external factors. Disentangling delayed external effects from internal dynamics within these systems is often difficult. We propose using a Vector Autoregressive model with eXogenous input (VARX) to capture delayed interactions between internal and external variables. Whereas this model aligns with Granger’s statistical formalism for testing “causal relations”, the connection between the two is not widely understood. Here, we bridge this gap by providing fundamental equations, user-friendly code, and demonstrations using simulated and real-world data from neuroscience, physiology, sociology, and economics. Our examples illustrate how the model avoids spurious correlation by factoring out external influences from internal dynamics, leading to more parsimonious explanations of these systems. For instance, in neural recordings we find that prolonged response of the brain can be explained as a short exogenous effect, followed by prolonged internal recurrent activity. In recordings of human physiology, we find that the model recovers established effects such as eye movements affecting pupil size and a bidirectional interaction of respiration and heart rate. We also provide methods for enhancing model efficiency, such as L2 regularization for limited data and basis functions to cope with extended delays. Additionally, we analyze model performance under various scenarios where model assumptions are violated. MATLAB, Python, and R code are provided for easy adoption: https://github.com/lcparra/varx.
Led Astray
Time-domain signatures of distinct correlated insulators in a moiré superlattice
Multifaceted confidence in exploratory choice
Our choices are typically accompanied by a feeling of confidence—an internal estimate that they are correct. Correctness, however, depends on our goals. For example, exploration-exploitation problems entail a tension between short- and long-term goals: finding out about the value of one option could mean foregoing another option that is apparently more rewarding. Here, we hypothesised that after making an exploratory choice that involves sacrificing an immediate gain, subjects will be confident that they chose a better option for long-term rewards, but not confident that it was a better option for immediate reward. We asked 250 subjects across 2 experiments to perform a varying-horizon two-arm bandits task, in which we asked them to rate their confidence that their choice would lead to more immediate, or more total reward. Confirming previous studies, we found a significant increase in exploration with increasing trial horizon, but, contrary to our predictions, we found no difference between confidence in immediate or total reward. This dissociation is further evidence for a separation in the mechanisms involved in choices and confidence judgements.