ABSTRACT
The ketogenic diet (KD) has demonstrated potential for treating neurological conditions like epilepsy, Alzheimer's disease, and cognitive decline as well as for enhancing brain health. Individual reactions to KD, however, differ because of things like lifestyle, metabolism, and heredity. It is difficult to achieve the best results with a one-size-fits-all dietary strategy because of this diversity. A new answer is provided by artificial intelligence (AI), which makes it possible to provide individualized nutritional advice that take individual characteristics into consideration. AI-driven models can forecast a person's reaction to KD and customize macronutrient ratios, calorie intake, and micronutrient supplementation by combining data from genomes, metabolomics, and clinical profiles. This individualized strategy can boost mitochondrial function, lower inflammation, increase neuroprotective advantages, and enhance cognitive function. This study investigates the application of AI to create a customized ketogenic diet that maximizes brain function.
ABSTRACT
The increasing global demand for protein has prompted a search for sustainable and cost-effective alternatives to traditional animal and dairy sources. Single-cell protein (SCP) produced from microorganism’s offers a promising solution due to its high protein content and rapid growth rates. This study addresses the challenge of utilizing rice husk, an abundant yet underutilized agricultural waste in Nigeria, as a substrate for SCP production. Through optimization of the production of SCP using Bacillus sp. AT-b3 and Bacillus sp. CMF 12 as model organisms. Molecular identification through 16S rRNA sequencing confirmed Bacillus sp. AT-b3 and Bacillus sp. CMF 12 as the most potent isolates for SCP production. Optimization studies were conducted using the One-Factor-at-a-Time (OFAT) method to determine the ideal fermentation conditions. The results showed that the optimal temperature for SCP production was 40 °C, with Bacillus sp. AT-b3 demonstrating superior production efficiency. pH optimization revealed that neutral pH (pH 7) was ideal for maximizing SCP production, with Bacillus spp. AT-b3 outperforming Bacillus sp. CMF 12 at this pH. Substrate concentration studies indicated that 2.0% was optimal for SCP production, and incubation time optimization indicated 48 hours as the optimal period for maximum yield. Amino acid profiling of the SCP produced showed significant variations between the two isolates. Bacillus sp. CMF 12 was richer in essential amino acids like Arginine and Methionine, while Bacillus sp. AT-b3 had a higher Glycine content at (p<0.05). The findings of this study suggest that both strains have potential applications in nutritional supplements, with Bacillus sp. AT-b3 being particularly suited for industrial-scale SCP production. This study concludes that Bacillus sp. AT-b3 is an efficient SCP producer under optimal conditions of neutral pH, moderate temperature, and appropriate substrate concentration. Further research is recommended to explore pilot-scale production, alternative substrates, and comprehensive safety assessments.
ABSTRACT
RSM was performed for the optimization of processing conditions to develop ghewar, traditional sweetmeat of India. Three variables i.e. frying temperature (160-180 ?C), batter temperature (5-10 ?C) and frying time (4-6 minute) were taken to investigate the effect on ghewar responses viz., oil content, moisture content, texture and sensory attributes (OA). The optimum conditions were 160 ?C frying temperature, 5?C batter temperature and 4 minute frying time. Upon optimization, the ghewar yielded the following results: 45.33% oil content, 4.65% moisture, 15.2 N texture (hardness), 54.89 L value, 15.16 a value, 24.97 b value, 58.73 hue value, 29.21 chroma value, 48.07 total color difference, and 0.24 water activity. Storage study of optimized ghewar was also carried out and found shelf stable for 30 days in metallised foil pouches. Hardness values were found to progressively drop from 15.2-9.40 N during the storage period, whereas moisture content, FFA, and peroxide value were found to gradually increase from 3.70-5.12%, 0.33-0.54 %, and 4.8-7.6 meq/kg, respectively.
ABSTRACT
The modern logistics environment faces the complex challenge of transporting perishable commodities, necessitating precise solutions to ensure on-time delivery while maintaining product integrity. This study delves into the critical aspect of managing time-sensitive perishable goods within the supply chain. Existing methods often fall short in providing optimal solutions, leading to increased costs and reduced quality. To address this, the paper introduces a novel approach utilizing Genetic Algorithms for route planning and vehicle allocation under time constraints. While current literature acknowledges the importance of ef?cient perishable goods transportation, it lacks comprehensive techniques that fully integrate the time-sensitive aspect. Our research aims to ?ll this gap by leveraging the ?exibility of genetic algorithms, a powerful optimization tool, to enhance the timely delivery of perishable items. We propose a framework that adapts genetic algorithms to outperform traditional methods in route planning, reducing transportation costs, and minimizing spoilage risk. Our hypothesis suggests that this approach will signi?cantly improve supply chain management outcomes. Empirical assessments indicate positive results, with the Genetic Algorithm-based framework optimizing the timely delivery of perishable goods, preserving product quality, reducing costs, and increasing route ef?ciency. The adaptability of genetic algorithms to dynamic environments ensures real-time responsiveness to changing demands and constraints. The study's ?ndings have practical implications for supply chain managers and the logistics industry, offering a sustainable and ef?cient solution for time-sensitive transportation, reducing environmental impact, and improving resource utilization. This work not only advances academic knowledge in logistics optimization but also provides a valuable guide for industry stakeholders seeking innovative and sustainable solutions for the transportation of perishable goods.
ABSTRACT
Introduction: Delays in non-traumatic emergency abdominal surgeries can significantly impact patient outcomes. Identifying the factors contributing to these delays is crucial for improving surgical efficiency and patient care. This study aims to prospectively analyze the determinants of delays in non-traumatic emergency abdominal surgeries and their effects on clinical outcomes. Methods: A prospective observational study was conducted on patients requiring non-traumatic emergency abdominal surgery over a one-year period. Data were collected on demographic variables, clinical characteristics, and time intervals from hospital admission to surgery. Factors such as diagnostic procedures, availability of surgical staff, operating room logistics, and preoperative optimization were analyzed. Statistical analysis was performed to identify significant predictors of surgical delays. Results: Out of 217 patients, 40% experienced significant delays (>6 hours) from admission to surgery. Key factors contributing to delays included prolonged diagnostic workup (35%), limited operating room availability (25%), and preoperative medical optimization (20%). Delays were associated with increased postoperative complications (15% in delayed group vs. 8% in non-delayed group, p<0.05) and extended hospital stay (mean of 7 days in delayed group vs. 4 days in non-delayed group, p<0.05). Discussion: The study highlights that diagnostic delays and operating room logistics are major contributors to surgical postponements. Addressing these issues through streamlined diagnostic protocols and improved operating room management can potentially reduce delays. Enhanced preoperative planning and resource allocation are also essential to mitigate the impact of delays on patient outcomes. Conclusion:Delays in non-traumatic emergency abdominal surgeries are influenced by multiple factors, including diagnostic processes, operating room availability, and preoperative medical optimization. Reducing these delays through targeted interventions can improve patient outcomes and optimize surgical care.
ABSTRACT
The integration of Artificial Intelligence (AI) in Orthopaedics represents a significant advancement in healthcare, offering novel approaches to diagnosis, treatment, and patient care. This review explores the multifaceted intersections between Orthopaedics and AI, highlighting its transformative potential and key challenges. Orthopaedics traditionally relies on clinical expertise, imaging modalities, and surgical interventions. However, the emergence of AI, fuelled by machine learning algorithms and big data analytics, has revolutionized the field by enabling data-driven decision-making and personalized treatment strategies. AI enhances diagnostic precision by analyzing complex imaging data and patient records, facilitating early detection and accurate prognostication of musculoskeletal conditions. Moreover, AI-driven predictive analytics assist in treatment planning and optimization, allowing orthopaedic practitioners to tailor interventions to individual patient characteristics and preferences. Despite its promise, the integration of AI in Orthopaedics presents challenges that must be addressed for responsible deployment. Issues such as data quality, interpretability of AI models, ethical considerations, and algorithmic biases require careful attention to ensure equitable and effective use of AI-driven technologies. Looking ahead, future directions in AI integration include advanced imaging techniques, personalized medicine approaches, robotics, telemedicine, and data-driven research. Interdisciplinary collaboration and ongoing education are essential for navigating the evolving landscape of AI in Orthopaedics and maximizing its potential for improving patient outcomes. In conclusion, the integration of AI in Orthopaedics offers exciting opportunities to enhance diagnostic accuracy, treatment efficacy, and patient satisfaction. By embracing AI-driven technologies and addressing associated challenges, orthopaedic practitioners can deliver personalized, evidence-based care, ushering in a new era of precision medicine and innovation in musculoskeletal healthcare.
ABSTRACT
Raw starch degrading enzyme (RSDE) is a group of enzymes that can directly degrade starch granules at low temperatures without the gelatinization process resulting in reduced cost and energy consumption. This work aimed to optimize the enzyme production, purification, and characterization of RSDE from Laceyella sacchari P43. The highest enzyme production was found at 171.8 ± 6.53 U/mL when using the low-cost agricultural crop and by-products from the brewing industry, including broken rice powder and dried brewer’s yeast at 8.0 and 4.7 g/L, respectively. The optimized medium resulted in a 5.03-fold improvement in RSDE production and an 8.5-fold reduction in cost compared to the non-optimized medium. The optimum physical factors enhancing RSDE production were pH at 6.5 and 50°C. The fed-batch fermentation was carried out in a 3.0 L airlift fermenter, which showed the highest enzyme production at 201 ± 11.53 U/mL. The purified enzyme has a molecular weight of 50 kDa and 35.2 purification folds with optimum activity at pH 6.0 and 55°C. The enzyme stimulated the activity by Co2+, Mn2+, and Ca2+ and was strongly inhibited by N-Bromosuccinimide, which confirmed that it was ?-amylase. The crude enzyme could hydrolyze the low-grade broken rice powder, yielding 40.31 ± 2.21 g/L after incubating for 9 h. This study developed the enzyme production process using low-cost substrates and enzyme application for sugar syrup production, which could be applied for further industrial application.
ABSTRACT
Background: Preeclampsia poses significant challenges to maternal healthcare due to its potential complications. Timely and accurate diagnosis is crucial for maternal and fetal well-being. Traditional methods like the 24-hour urine collection for assessing proteinuria have limitations. The spot urinary protein/creatinine ratio offers a quicker alternative, but its clinical significance remains underexplored.Methods: This cross-sectional study, conducted from July 1, 2018, to June 30, 2019, aimed to compare the spot urinary protein/creatinine ratio with the conventional 24-hour urine protein collection method in pregnant women with preeclampsia. A total of 90 inpatients were included, meeting specific inclusion and exclusion criteria.Results: In our study, 6.66% of subjects exhibited abnormal fundus examination findings, lower than a similar study (13%). No subjects had papilloedema, and conservatively managed abnormalities were comparable between studies. The mean urine protein creatinine ratio in our study was 1.75±2.32.Conclusions: This study highlights the potential of the spot urinary protein/creatinine ratio as an efficient diagnostic tool for preeclampsia at Kamla Nehru State Hospital for Mother and Child. Swift identification of significant proteinuria can streamline patient care, benefiting maternal and fetal outcomes in resource-constrained healthcare settings.
ABSTRACT
This study aimed at producing functional soy bean yoghurt by optimizing the production conditions using response surface methodology. The quantity of ferment (LYOFAST Y439A) (50�0 g) and quantity of cinnamon (10-40 g) were optimized using central composite design. Responses (global acceptability and scavenging activity) obtained from experimental runs were fitted into second order polynomial regression model. Also, the multiple optimization technic was used to obtain the compromised optimum condition. The optimized yoghurt was evaluated for its pH and proximate composition using standard methods. The optimum conditions for the production of this yoghurt was as thus: 69.64 g for quantity of ferment and 10 g for quantity of cinnamon, 100 g soya beans, 100 g of sugar and 1 L of water soybeans. Soy bean yoghurt made from optimized conditions had a global acceptability of 6.8, scavenging activity of 34 %. Also, protein, fat, carbohydrate, calcium, sodium magnesium and energy value was respectively 17.1%, 2.91%, 17.93%, 144 mg/100 g, 159.91 mg/100g, 159.91 mg/100g, 63.18 mg/100g and 166.31 kcal/100g. Thus, acceptable yoghurt with functional properties can be obtained from soya beans and cinnamon.
ABSTRACT
This study was carried out to optimize foaming preparation conditions for Artemia biomass using the three-level Box–Behnken experimental design of Response Surface Methodology. Three independent variables, namely, water/ Artemia ratio (WAR) (2/1, 4/1 and 6/1), egg albumin (EA) (9.2, 12.2 and 15.2%), and xanthan gum (XG) concentration (0.1, 0.24 and 0.38%), together with three dependent variables characterizing the foam stability, including foam expansion volume (EV), foam density (FD), and drainage volume (DV) were optimized. Multiple regression analyses were applied to analyze the relationship between dependent variables (EV, FS, and DV) and three independent variables (WAR, EA, and XG) as indicators of foaming capacity and foam stability. In addition, simultaneous optimization of multiple responses has also been applied. The optimal combination of WAR was 4.6 (v/w), EA = 13.5%, and XG = 0.25% which gave the maximum foam expansion 293.4%, minimum FD 0.27 g/mL, and volume drainage of at least 0.7 mL. The validated values were found to be very close to the experimental values.
ABSTRACT
Objective: A definitive objective for supporting drug discharge is to expand the remedial movement of the medication while limiting its incidental effects. Microspheres have become a unique medicine delivery mechanism for several disorders in this area. The popular fluoroquinolone antibiotic, Ciprofloxacin, is used to treat a variety of bacterial illnesses. This research aims to create Ciprofloxacin microspheres with sustained drug delivery using natural gum polymers.Methods: To choose and assess the ideal formulation, a variety of formulations (F1–F8) were developed. This work was completed using an innovative technology, the Ionic Gelation method. Central Composite Design (CCD) used the quadratic forward regression approach to carry out the optimization. The evaluation tests include Particle size, Scanning Electron Microscopy (SEM), FTIR, Percentage yield, Drug content, Drug Entrapment effectiveness and in vitro dissolution studies.Results: It was discovered that the best formulation was F4. From optimization, the ANOVA was found to be significant. The uneven, spherical structure of microspheres with a rough outer surface is confirmed by SEM investigation. The absence of drug-polymer interaction is confirmed by the FTIR. The formulation F4 was deemed ideal due to its high drug entrapment efficiency, drug content and maximal drug release (89.25% in 12 h).Conclusion: Due to the least plasma half-life, this drug is designed as microspheres thus maximizing the therapeutic activity and minimizing the negative effects. In this regard, microspheres have emerged as novel drug-delivery systems for various diseases. It maintains effective dose concentration, eliminates night-time dosage and decreases side effects, thus optimizing drug therapy.
ABSTRACT
Objective To sort out and summarize the research hotspots and trends of Chinese medicine nursing technolo-gy at the present stage.Methods We searched the research literature on TCM nursing technology included in China Knowledge,Wanfang,and Wipu build-up to November 30,2023,and used CiteSpace 6.1.R6 software to perform co-occurrence analysis of research institutions and keyword clustering,timeline,and emergence analysis.Results A total of 5 771 documents were in-cluded,with a general upward trend in the number of publications,peaking at 692 publications in 2021.5 206 documents from 673 journals were included in the research literature,of which 19 journals had ≥50 publications(35.47％).2 087 research or-ganizations were involved,of which 27 had ≥20 publications(13.24％).Involving 9 484 authors,there were a total of 8 au-thors ≥5 in the cluster,indicating the existence of stable teamwork in the cluster.The keyword co-occurrence analysis yielded the research hotspots of TCM nursing technology as TCM nursing,training,nursing management,clinical efficacy,complica-tions,and quality of life.Conclusion Based on the econometrics and visualization analysis of the literature on TCM nursing technology,we explored the research hotspots and trends in this field,and provided two theoretical paths for medical institution managers to construct and optimize the management system of TCM nursing technology:to standardize the TCM nursing technology in hospitals and establish a clinical access management system;and based on the multidimensional management method,to inno-vate the training system of TCM nursing technology.
ABSTRACT
The effective management of internal staffs plays an indispensable role in in the hospitals apart from the medi-cal services.A high level of human resource management in the hospitals is demanded since the launch of the reform of the medi-cal and health system.This article takes a hospital in the N city as an example.The unsatisfactory phenomena can be noticed,such as low efficiency,the burden of long sick leave staffs,and the low efficiency of outsourcing services.This article suggests establishing a performance management system,scrutinizing the vacation approval process,determining position responsibilities,allocating internal and external manpower properly,promoting the activeness of functional departments,and improving incentive mechanisms,which can be beneficial to the human resource management in hospitals.
ABSTRACT
Objective To analyze the effects of target volume optimization on oral mucosal reaction and salivary gland function in oropharyngeal cancer patients receiving intensity-modulated radiotherapy(IMRT).Methods A total of 120 patients with oropharyngeal cancer admitted to Affiliated Hospital of Jiangsu University from April 2020 to August 2022 were selected and randomly grouped into control group(n=60,conventional IMRT)and treatment group(n=60,cervical region Ⅱ and the oral target region were optimized during IMRT).The therapeutic efficacy,parotid gland dose,incidence of acute oral mucosal reaction,dry mouth and oral pain at 3 months after IMRT were compared between two groups.The resting-state apparent diffusion coefficient(ADC)values of parotid and submandibular glands at different time points(before radiotherapy,the 4th week of radiotherapy,the end of radiotherapy and 3 months after radiotherapy)were recorded.Results The difference in the objective reaction rate between two groups was trivial[80.00％(48/60)vs 75.00％(45/60),P>0.05].The mean dose(Dmean)and V34 of the unaffected parotid gland and the Dmean and V30 of the oral cavity in treatment group were lower than those in control group(P<0.05).The incidences of acute oral mucosal reaction,dry mouth and oral pain at 3 months after radiotherapy in treatment group were 41.67％,50.00％,and 58.33％,lower than those in control group(75.00％,78.33％,and 85.00％)(P<0.05).The resting-state ADC values of parotid and submandibular glands at the 4th week of radiotherapy,the end of radiotherapy,and 3 months after radiotherapy in both two groups were higher than those before radiotherapy(P<0.05).At the 4th week of radiotherapy,the end of radiotherapy,and 3 months after radiotherapy,the resting-state ADC values of parotid and submandibular glands in treatment group were lower than those in control group(P<0.05).Conclusion Optimizing target volume during oropharyngeal IMRT can effectively prevent the occurrence of radiation-induced mucositis,alleviate oral mucosal reaction,oral pain and dry mouth,reduce parotid gland dose,and diminish the effects of IMRT on salivary gland function in patients.
ABSTRACT
Aiming at the obstacle avoidance in simulated prosthetic vision,an improved instance segmentation model SOLOv2-RS is proposed for providing a basis for implant recipients to accurately perceive the relevant instance objects of navigation tasks in low-resolution prosthetic vision.According to the visual attention mechanism,the distance from the center of the visual field and the target scale are adopted as the importance calculation criteria for each instance,and the obtained importance score is used as the basis for the hierarchical representation of the obstacles to be avoided.Meanwhile,edge information is used to cue the tactile paving,and it is morphologically inflated for avoiding the edge information loss caused by the limited phosphene.The prosthetic vision simulation results demonstrate that the hierarchical optimization processing strategy for simulated prosthetic vision can effectively achieve the optimal representation of tactile paving and obstacles,thus facilitating the implant recipients to accomplish outdoor obstacle avoidance tasks more efficiently,and providing ideas for the research on the image processing of visual prosthetic devices.
ABSTRACT
@#Objective To select and optimize the process parameters of SARS-CoV-2 F61 affinity chromatography by the screening and optimization experiment of Design of Experiment(DoE),in order to obtain the optimal process conditions.Methods Eight process parameters that may affect the experimental response results in affinity chromatography were selected and their level ranges were determined.DoE screening test was used to perform 8 factor 2 level screening tests on the selected process parameters.The response values were detected and the mathematical model was fitted by statistical software.Three key process parameters significantly affecting the key quality attributes were obtained by Pareto diagram analysis(P < 0.05).Then DoE response surface method(RSM)was selected to optimize the key process parameters.First,the full factorial experiment design was completed,the response results were detected to fit the mathematical model,and the bending term P value was analyzed to judge the range of significant factors in the optimal range(bending P < 0.05),then according to the sequential complement of the central composite face-centered design(CCF)experiment,through the detection of the response results to fit the response surface model,the range of optimal conditions was obtained,and the stability of the optimal parameters was finally verified by repeated experiments.Results In the screening experiment,it was found that the significant factors affecting F61 in the affinity chromatography stage were elution buffer pH,elution buffer salt concentration,leaching buffer salt concentration and equilibrium buffer salt concentration.The optimal conditions of key process parameters in affinity chromatography were obtained by CCF.When the pH of elution buffer was 3.2,the elution buffer salt concentration was 0.07 mol/L NaCl,and the leaching buffer salt concentration was 0.31 mol/L NaCl,the yield of F61 reached 95.25%,the residual amount of host cell protein(HCP)was 97.33 ppm,and the monomer purity of the sample was98.51% at the affinity chromatography stage.Conclusion Different types of DoE methods were used to screen and optimize the process parameters of F61 affinity chromatography stage,and the optimal process conditions were obtained,which lays a foundation for the esta-blishment of F61 purification process.
ABSTRACT
Objective To study the mechanical properties of titanium mesh and three-dimensional(3D)-printed metal vertebral body substitutes(VBS)to provide guidance for the selection and structural optimization of artificial vertebral implants in clinical practice.Methods The equivalent elastic modulus,equivalent yield strength,and structural failure mode of titanium mesh and 3D-printed porous,truss,and topologically optimized VBS were systematically investigated using compression tests.Results The elastic modulus of the titanium mesh(2 908.73±287.39 MPa)was only lower than that of the topologically optimized VBS.However,their structural strengths and stabilities were inadequate.The yield strength of the titanium mesh(46.61±4.85 MPa)was only higher than that of the porous VBS and it was the first to yield during compression.The porous VBS was insufficient for use as the vertebral implant owing to its poor mechanical strength(18.14±0.17 MPa-25.79±0.40 MPa).The truss VBS had good elastic modulus(2 477.86±55.19 MPa-2 620.08±194.36 MPa)and strength(77.61±0.50 MPa-88.42±1.07 MPa).However,the structural stability of the truss VBS was insufficient,and instability occurred easily during compression.The topologically optimized VBS had the highest elastic modulus(3 746.28±183.80 MPa)and yield strength(177.43±3.82 MPa)among all the tested VBS types,which could provide improved security and stability for artificial vertebral implant in vivo services.Conclusions Topology optimization results in a high strength and high stability VBS design.Moreover,it provides a large design space and great safety margin to provide increased possibilities for lightweight and new material design of future artificial vertebral implants.
ABSTRACT
Objective A finite element simulation analysis of a bracketless orthodontic appliance was carried out to determine the correction amount under different working conditions.A design scheme for the bracketless orthodontic appliance was also formulated to create an orthodontic appliance formed by the fused deposition process with a personalized orthodontic effect.Methods Combined with the computed tomography data of the patient,a tooth model was reversely reconstructed.The correction amount of the tooth under tilting,twisting,and translation working conditions was established using the finite element method.Materials with different elastic moduli were chosen to make three-dimensional(3D)shaped bracketless orthodonitc appliance,and the orthodontic force was measured.Results Different correction amounts could be designed according to different working conditions so that the orthodontic appliance had a personalized treatment effect.The orthodontic force of the bracketless orthodontic appliance increased with elastic modulus and thickness.Under the given working conditions,the orthodontic force was minimal(90 mN)when the orthodontic material was at the minimum(90 mN).The orthodontic force reached its maximum value when the orthodontic material was at the maximum(61.66 N).Conclusions According to the patient's tooth condition and the size of the orthodontic force required for each step of correction in the whole correction process,the design should consider bracketless orthodontics with different elastic moduli and thicknesses to treat deformed teeth to realize the effect of staged orthodontic correction.
ABSTRACT
Objective To analyze the atrioventricular synchronization rate after implantation of Micra AV leadless pacemaker,and the impact of postoperative programming optimization on atrioventricular synchronization rate.Methods A prospective cohort study was conducted to select patients with complete atrioventricular block who underwent Micra AV leadless pacemaker implantation at Beijing Anzhen Hospital from August 2022 to June 2023.Programming optimization were performed at 1 week,1 month,and 3 months postoperatively,and atrioventricular synchronization rate,electrical parameters,and echocardiography were recorded.Results A total of 68 patients with complete atrioventricular block implanted with Micra AV were selected,with an average age of(68.2±9.7)years,including 47 males(69.1％).All patients were successfully implanted with Micra AV,and there were no serious postoperative complications;The average threshold,sense,and impedance parameters were stable during 1 week,1 month,and 3 months after the procedure;There was no significant difference in the EF value of postoperative echocardiography(P=0.162);The average atrioventricular synchronization rates at 1 week,1 month,and 3 months postoperatively were(75.2％vs.83.8％vs.91.6％,P=0.001).Conclusions As an mechanical atrial sensing,Micra AV requires personalized adjustment of relevant parameters;Postoperative follow-up programming optimization plays an important role in the atrioventricular synchronization and comfort level in patients with complete atrioventricular block after implantation of Micra AV leadless pacemaker.
ABSTRACT
Objective To predict the potential suitable growth areas of Epimedium brevicornu Maxim.under current climate conditions in China;To provide basis for the sustainable utilization of Epimedium brevicornu Maxim.resources and production planning.Methods Based on 267 screened species distribution data of Epimedium brevicornu Maxim.and 8 environmental factors,the MaxEnt parameters were optimized by the R language kuenm package.The main environmental factors that affect the distribution of Epimedium brevicornu Maxim.was analyzed and its potential distribution range was predicted.Results The omission rate of the optimal model operation results was 0.044 8,AICc=6 409.884 5,AUC=0.986,indicating a high accuracy of the model.Based on the contribution rate of environmental factors and the knife cut method,it was indicated that the key environmental factors affecting the current distribution of Epimedium brevicornu Maxim.were mainly the average precipitation in July,the average highest temperature in February,the average precipitation in September,the coldest season precipitation,the coefficient of variation of precipitation,the standard deviation of seasonal temperature changes,and the warmest season precipitation.The simulation results showed that the total suitable area for Epimedium brevicornu Maxim.in China under current climate conditions was approximately 221.14×104 km2,concentrated in the central and central southern regions of China.The area of the high suitability zone was approximately 23.13×104 km2;the area of the suitable growth zone was approximately 73.78×104 km2;the area of low suitability zone was approximately 124.22×104 km2.Conclusion This study provides a basis and reference for the artificial cultivation planning and sustainable utilization of Epimedium brevicornu Maxim.resources.