Uniform Method Research Articles

Microwave pretreatment effects on the aroma precursors, sensory characteristics and flavor profiles of fragrant rapeseed oil

Microwave technology offers a rapid and uniform heating method. This study investigated how microwave pretreatment affects the aroma precursors and flavor of fragrant rapeseed oils (FROs). Microwave pretreatment led to decreased levels of polyunsaturated fatty acids, sugars, protein-bound amino acids, and glucosinolates. Using gas chromatography–mass spectrometry, we identified 66 volatile compounds in the oil samples. Among these, based on odor activity values (OAV ≥ 1), we found 9 aldehydes, 1 ketone, 6 pyrazines, 1 isothiocyanate, and 7 nitriles as the key aroma-active compounds, contributing fatty-like, nutty-like, and pungent-like odors, respectively. The electronic nose results highlighted W5S and W1W as primary sensors for determining the flavor profiles of FROs. Notably, aroma-active pyrazines exhibited strong negative correlations with sucrose, cysteine, lysine, and isoleucine. This research provides essential insights for enhancing the aroma of FROs.

Обязательное страхование ответственности за причинение морального вреда

The article analyses the legal regulation of civil liability insurance for moral damage. The author aims to find out whether the current insurance legislation is necessary and sufficient to introduce compulsory insurance of such liability. It is proved that the insurance of civil liability for moral damage within the meaning of the current versions of paragraph 1 of Article 931 of the Civil Code and paragraph 6 of Article 4 of the Law on the Organisation of Insurance business is lawful. The lack of uniform criteria or methods for calculating the amount of compensation for moral damage makes it difficult to assess the insured interest and is the reason for the rarity of this type of insurance in our country. The author comes to the conclusion that the existing prohibition against the introduction of compulsory insurance of civil liability for moral damage is an unjustified excessive regulation. A proposal is formulated to include in the Concept of Development of the provisions of Part Two of the Russian Civil Code on the insurance contract a provision on amending paragraph 1 of Article 935 of the Code in terms of expanding the list of types of civil liability in respect of which the law may establish the obligation to insure the corresponding risk.

A comparative study of breast lesions using the IAC Yokohama System for reporting breast cytopathology against histopathological biopsy

Abstract Background: Breast lumps pose a significant health concern globally, contributing to both illness and death. The International Academy of Cytology (IAC) Yokohama system has established a uniform method for reporting breast cytology, categorizing it into five groups: inadequate, benign, atypical, suspicious, and malignant. Aims and Objectives: This study primarily aimed to evaluate breast lesions using the IAC Yokohama System and compare the results with those of corresponding histopathological biopsies. Additionally, the study aimed to analyze the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of breast fine-needle aspiration cytology (FNAC) and determine the risk of malignancy associated with each category. Materials and Methods: In this study, 92 cases were analyzed and categorized according to the IAC Yokohama System. Sensitivity, specificity, PPV, NPV, diagnostic accuracy, and risk of malignancy were determined based on histopathological diagnosis, which was considered the reference standard. Results: Among the 92 breast FNACs, the risk of malignancy for the categories insufficient, benign, atypical, suspicious, and malignant were 0%, 0%, 18.75%, 100%, and 100%, respectively. The highest sensitivity (100%) was achieved when considering atypical, suspicious, and malignant cases as positive results. The specificity was highest (100%) when only malignant or both malignant and suspicious cases were considered positive results. The highest diagnostic accuracy (95.65%) was observed when including malignant and suspicious cases as positive results. Conclusion: Implementing the IAC Yokohama System for reporting breast cytopathology through structured reporting will enhance the quality, clarity, and reproducibility of reports among pathologists and clinicians, which would result in enhanced patient care and management.

Adjustment Methods Applied to Precipitation Series with Different Starting Times of the Observation Day

The study of long precipitation series constitutes an important issue in climate research and risk assessment. However, long datasets are affected by inhomogeneities that can lead to biased results. A frequent but sometimes underestimated problem is the definition of the climatological day. The choice of different starting times may lead to inhomogeneity within the same station and misalignment with other stations. In this work, the problem of temporal misalignment between precipitation datasets characterized by different starting times of the observation day is analyzed. The most widely used adjustment methods (1 day and uniform shift) and two new methods based on reanalysis (NOAA and ERA5) are evaluated in terms of temporal alignment, precipitation statistics, and percentile distributions. As test series, the hourly precipitation series of Padua and nearby stations in the period of 1993–2022 are selected. The results show that the reanalysis-based methods, in particular ERA5, outperform the others in temporal alignment, regardless of the station. But, for the periods in which reanalysis data are not available, 1-day and uniform shift methods can be considered viable alternatives. On the other hand, the reanalysis-based methods are not always the best option in terms of precipitation statistics, as they increase the precipitation frequency and reduce the mean value over wet days, NOAA much more than ERA5. The use of the series of a station near the target one, which is mandatory in case of missing data, can sometimes give comparable or even better results than any adjustment method. For the Padua series, the analysis is repeated at monthly and seasonal resolutions. In the tested series, the adjustment methods do not provide good results in summer and autumn, the two seasons mainly affected by heavy rains in Padua. Finally, the percentile distribution indicates that any adjustment method underestimates the percentile values, except ERA5, and that only the nearby station most correlated with Padua gives results comparable to ERA5.

Bibliometric Analysis of the Relationship Between Breast Cancer and Exercise Based on Citespace

This study aims to conduct a bibliometric analysis of the literature on the relationship between breast cancer and exercise using Citespace software, in order to explore the research hotspots, trends, and deficiencies in this field. Relevant literature including keywords such as “breast cancer” and “exercise” was retrieved from the Web of Science database and analyzed using Citespace software for data processing and visualization. The main conclusions of this study are as follows: In co-occurrence analysis of keywords, researchers mainly focus on the prevention, rehabilitation, and treatment of breast cancer, as well as the effects of different types of exercise on breast cancer. Meanwhile, the cooccurrence patterns of keywords in studies related to exercise and breast cancer indicate an increasing attention to the relationship between breast cancer and exercise, making it gradually one of the hotspots in breast cancer research. The timeline of keywords and burst detection analysis show that researchers have increasingly focused on the relationship between breast cancer and exercise in recent years, with research intensity showing an increasing trend year by year. Furthermore, in recent years, researchers have begun to emphasize the role of exercise in breast cancer rehabilitation, rather than just prevention and treatment. Discipline analysis indicates that research in this field involves multiple disciplinary areas, including medicine, oncology, sports science, nutrition, etc. Additionally, an analysis of papers published by country reveals that the United States leads in research on the relationship between breast cancer and exercise, followed closely by the United Kingdom, China, Canada, Australia, and other countries. Conclusion: Literature on the relationship between breast cancer and exercise shows a trend of increasing quantity year by year. However, there are still some deficiencies in this field, such as lack of uniform research methods, overly limited research samples, and insufficient rigor in research results. Therefore, further strengthening research on the relationship between breast cancer and exercise is highly necessary.

Design, Manufacture, and Characterization of a Critical-Sized Gradient Porosity Dual-Material Tibial Defect Scaffold.

This study proposed a composite tibia defect scaffold with radial gradient porosity, utilizing finite element analysis to assess stress in the tibial region with significant critical-sized defects. Simulations for scaffolds with different porosities were conducted, designing an optimal tibia defect scaffold with radial gradient porosity for repairing and replacing critical bone defects. Radial gradient porosity scaffolds resulted in a more uniform stress distribution, reducing titanium alloy stiffness and alleviating stress shielding effects. The scaffold was manufactured using selective laser melting (SLM) technology with stress relief annealing to simplify porous structure fabrication. The study used New Zealand white rabbits' tibia defect sites as simulation parameters, reconstructing the 3D model and implanting the composite scaffold. Finite element analysis in ANSYS-Workbench simulated forces under high-activity conditions, analyzing stress distribution and strain. In the simulation, the titanium alloy scaffold bore a maximum stress of 122.8626 MPa, while the centrally encapsulated HAp material delivered 27.92 MPa. The design demonstrated superior structural strength, thereby reducing stress concentration. The scaffold was manufactured using SLM, and the uniform design method was used to determine a collection of optimum annealing parameters. Nanoindentation and compression tests were used to determine the influence of annealing on the elastic modulus, hardness, and strain energy of the scaffold.

Real-time evaluation of the blending uniformity of industrially produced gravelly soil based on Cond-YOLOv8-seg

Industrial production of gravelly soil has been applied at construction sites in earth-rock engineering, which adopts automatic blending and belt-conveyer systems for gravelly soil. The blending uniformity of gravelly soil has a significant impact on its mechanical and physical properties including shear resistance and impermeability. Real-time evaluation of blending uniformity is key to controlling the quality of gravelly soil. This study proposes a real-time evaluation method for the blending uniformity of gravelly soil transported by a belt conveyor. First, Cond-YOLOv8-seg is adapted to accurately segment gravel particles from gravelly soil images, employing a conditional convolution segmentation head and an improved Protonet embedded with a recurrent criss-cross attention (RCCA) module based on YOLOv8-seg. Then, the segmented masks are used to analyze the spatial uniformity (SU) and blending ratio consistency (BRC) of individual and continuous gravelly soil images, employing the proposed evaluation criterion for SU based on the theory of deformable four-sided static distances and BRC based on the area ratio of different-scale gravel particles in one image. Cond-YOLOv8-seg achieved an AP50 of 0.803 and FPS of 58.3. The effectiveness of the proposed evaluation criteria is validated quantitatively. The average uniformity evaluation time of a 2048 × 1536 image is determined to be 0.1151s, which is close to the real-time evaluation of gravelly soil transported by a belt conveyor.

Real-world Observational Multi-center Study: Retrospective Analysis of Diagnostic and Treatment Patterns for Stage III–IV Melanoma in Ukraine from 2018 to 2020

BACKGROUND: Despite open-access sources with information about cancer patients (National Cancer Registry of Ukraine), there are considerable gaps about actual diagnostic methods and specific treatment patterns or any details on how different regimens are applied for melanoma treatment in Ukraine. OBJECTIVES: This non-interventional, multicenter, retrospective medical chart review study aims to describe real-world therapeutic strategies and characterize the profile of patients with melanoma Stage III–IV in real-life clinical practice in Ukraine. METHODS: Anonymized data were collected from medical records of 747 patients in 9 oncology centers in Ukraine - four private and five public. The data variables were retrieved, captured in electronic case report forms, and analyzed with descriptive statistical methods. INCLUSION CRITERIA: Subjects were not enrolled unless they met all the following criteria: (1) Age >18 years at the time of being diagnosed with III–IV stage melanoma. (2) Morphologically (including cytology) confirmed diagnosis of III–IV stage melanoma. Sufficient available medical records for data abstraction to meet the objectives of the study, that is, the patient has been under the medical care of the participating site for the entirety of the patient observation period or the patient’s detailed historical data on their disease course, and clinical management are otherwise available at the participating site consent has been granted by the Institutional Review Board/Ethical Committee of the study site. EXCLUSION CRITERIA: Subjects were not enrolled if they met any of the following criteria: (1) The patient has received treatment with anticancer systemic therapy for reasons other than melanoma. (2) Primary cancer other than melanoma. (3) The patient is participating (or was participating) in any investigational program/clinical trial with interventions outside of routine clinical practice. All the statistical tests were two sided and performed at a 0.05 significance level. p-values were rounded to three decimal places. p < 0.001 were reported as <0.001 in tables. RESULTS: Most melanoma cases (95.05%) were diagnosed histologically, although information about the primary tumor’s characteristics and treatment are heterogeneous. Most individuals (51.05%) diagnosed with Stage III undergo surgical treatment without additional therapy. Chemotherapy constitutes the primary form of systemic therapy for Stages III and IV, accounting for 33.3% and 45.65%, respectively. CONCLUSION: It is crucial to tackle the problems associated with diagnosing and treating melanoma in Ukraine. This involves creating a unified registry for melanoma patients, establishing uniform methods for staging and re-staging, and standardizing medical records. Nevertheless, the most critical issue is the absence of access to modern therapy, which should be addressed at the state level.

Investigation of long-term stability of a transmission Raman calibration model using orthogonal projection methods

Transmission Raman Spectroscopy (TRS) was implemented as an ‘Extended’ Content Uniformity (ECU) method for un-coated tablets for a commercial pharmaceutical product. By sampling un-coated tablets throughout the duration of the tablet compression stage, it can be demonstrated that the material from the preceding blend step was of uniform composition, and therefore the blend and compression unit-operations were in a state of control. TRS was selected as a rapid, non-destructive measurement that can be automated through the use of a sample tray that can hold many tablets. In this work, the performance of a multivariate calibration model (PLS) deployed to two Transmission Raman Spectrometers co-located within the same QC laboratory was studied using data obtained over a 3-year period. The aim of the investigation was to assess the impact of various annual instrument maintenance events, and to evaluate several chemometric methods for reducing or eliminating the spectral effects that led to deterioration of a models performance. Linear orthogonal projection approaches such as Transfer by Orthogonal Projection (TOP), Dynamic Orthogonal Projection (DOP) and Unsupervised Dynamic Orthogonal Projection (uDOP) were applied, along with a more recent, non-linear method called Transfer Component Analysis-Orthogonal Projection (TCA-OP). This works shows that each method has merits, depending on the nature of the spectral/model correction required. In most cases, the model performance could be fully restored, or significantly improved. This work also highlights how these various methods can be useful tools to better understand the root-cause for a deterioration in model performance.

Optimization of Bear Oil Extraction Process and Hair Growth Activity.

According to ancient Chinese books, bear grease has the effects of strengthening muscles and bones, which is beneficial for weakness, but there is relatively little research on it. Thus, the extraction of it is beneficial for compensating for research in this area. In this study, a uniform experimental design method was used to optimize the extraction process of bear grease by enzymatic hydrolysis extraction, and the extraction rate can reach 81.89% under optimized extraction conditions. Furthermore, the components of bear grease obtained by this study were analyzed by GC-MS, and the results showed that ursolic oil was rich in unsaturated fatty acids (67.51%), which was higher than that of the traditional method (66.92%). The composition of bear grease extracted by the enzymatic method was also better than that extracted by the traditional method. In addition, bear grease obtained in this study had the obvious activity of promoting hair growth. The length, weight, and number of hair follicles in the depilation area of mice in the high-dose group were significantly different from those in the blank group (p < 0.01). This study optimized the extraction process of bear grease and conducted a preliminary analysis of its fatty acid composition, which is expected to provide some reference for the development of the medicinal value of bear grease.

Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Parameter uniform hybrid numerical method for time-dependent singularly perturbed parabolic differential equations with large delay

ABSTRACT In this study, to solve the singularly perturbed delay convection–diffusion–reaction problem, we proposed a hybrid numerical scheme that converges uniformly. Parabolic right boundary layer outcomes from the presence of the small perturbation parameter. To grip this layer behaviour, the problem is solved by Bakhvalov–Shishkin mesh for spatial domain discretization and uniform mesh for temporal domain discretization. A hybrid scheme consisting of a non-polynomial spline scheme for fine mesh and a midpoint upwind scheme for coarse mesh is used to discretize the spatial derivative, while an implicit Euler scheme is used to discretize the time derivative. To make computed solutions more accurate and increase rate of convergence of the scheme, we applied Richardson extrapolation technique. The stability and convergence of the scheme are established. The scheme has a second order of convergence in the discrete supreme norm and is parametric uniformly convergent. The scheme's application is demonstrated through two test problems.

An electron density clustering based adaptive segmentation method for protein Raman spectrum calculation

Raman spectroscopy is a powerful technique for protein detection, but the calculation of Raman spectrum is a longstanding challenging problem due to the large sizes and complex structures of protein molecules. Dividing proteins into fragments can greatly accelerate the calculation, but this usually introduces large errors originating from ignored interactions between fragments into obtained spectra. In this paper, we proposed a new adaptive segmentation method based on the strength of interactions and molecular shapes and structures, i.e., electron density clustering, to divide proteins. It can reduce errors of obtained Raman spectra by about 20% compared to the uniform segmentation method without a significant increase in computational cost. This method can facilitate the validation and analysis of detected Raman spectra of proteins and promote the application of Raman spectroscopy in biological detection.

Optimizing androgen receptor prioritization using high-throughput assay-based activity models.

Introduction: Computational models using data from high-throughput screening assays have promise for prioritizing and screening chemicals for testing under the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP). The purpose of this work was to demonstrate a data processing method for the determination of optimal minimal assay batteries from a larger comprehensive model, to provide a uniform method of evaluating the performance of future minimal assay batteries compared with the androgen receptor (AR) pathway model, and to incorporate chemical cluster analysis into this evaluation. Although several of the assays in the AR pathway model are no longer available through the original vendor, this approach could be used for future evaluations of minimal assay models for prioritization and screening. Methods: We compared two previously published models and found that an expanded 14-assay model had higher sensitivity for antagonists, whereas the original 11-assay model had slightly higher sensitivity for agonists. We then investigated subsets of assays in the original AR pathway model to optimize overall testing strategies that minimize cost while maintaining sensitivity across a broad chemical space. Results and Discussion: Evaluation of the critical assays across subset models derived from the 14-assay model identified three critical assays for predicting antagonism and two critical assays for predicting agonism. A minimum of nine assays is required for predicting agonism and antagonism with high sensitivity (95%). However, testing workflows guided by chemical structure-based clusters can reduce the average number of assays needed per chemical by basing the assays selected for testing on the likelihood of a chemical being an AR agonist, according to its structure. Our results show that a multi-stage testing workflow can provide 95% sensitivity while requiring only 48% of the resources required for running all assays from the original full models. The resources can be reduced further by incorporating in silico activity predictions. Conclusion: This work illustrates a data-driven approach that incorporates chemical clustering and simultaneous consideration of antagonism and agonism mechanisms to more efficiently screen chemicals. This case study provides a proof of concept for prioritization and screening strategies that can be utilized in future analyses to minimize the overall number of assays needed for predicting AR activity, which will maximize the number of chemicals that can be tested and allow data-driven prioritization of chemicals for further screening under the EDSP.

Resource sharing for collaborative edge learning: A privacy-aware incentive mechanism combined with demand prediction

Edge intelligence benefits from ubiquitous resource capabilities by numerous edge devices. However, interest concerns and privacy issues caused by the openness of the edge network make smart devices reluctant to participate in collaborative edge learning. This work proposes a privacy-aware incentive mechanism based on combinatorial double auction (PIMCDA) to facilitate idle resource sharing of diversified edge devices. First, we establish an auction model based on blockchain to form a trusted sharing market in a multi-resource binding manner. Then, we propose a two-stage auction solution combined with differential privacy: The privacy-aware winner selection stage matches the optimal winner candidate to the task that is the closest in probability to maximize the revenue of resource providers with the obfuscated location information. The probabilistic pricing decision stage is designed based on a uniform pricing method and exponential mechanism, which can ensure bid privacy from inference attacks. Furthermore, to ensure the effectiveness of PIMCDA for long-term participation, we design a supply and demand balance mechanism with a learning-based resource prediction method. Theoretical and simulation analysis demonstrate that the proposed mechanism achieves privacy-preserving in location and bid information while ensuring effective incentive properties. Our approach effectively motivates the sharing of multiple resources in edge computing.

MDU‐sampling: Multi‐domain uniform sampling method for large‐scale outdoor LiDAR point cloud registration

AbstractSampling is a crucial concern for outdoor light detection and ranging (LiDAR) point cloud registration due to the large amounts of point cloud. Numerous algorithms have been devised to tackle this issue by selecting key points. However, these approaches often necessitate extensive computations, giving rise to challenges related to computational time and complexity. This letter proposes a multi‐domain uniform sampling method (MDU‐sampling) for large‐scale outdoor LiDAR point cloud registration. The feature extraction based on deep learning aggregates information from the neighbourhood, so there is redundancy between adjacent features. The sampling method in this paper is carried out in the spatial and feature domains. First, uniform sampling is executed in the spatial domain, maintaining local point cloud uniformity. This is believed to preserve more potential point correspondences and is beneficial for subsequent neighbourhood information aggregation and feature sampling. Subsequently, a secondary sampling in the feature domain is performed to reduce redundancy among the features of neighbouring points. Notably, only points on the same ring in LiDAR data are considered as neighbouring points, eliminating the need for additional neighbouring point search and thereby speeding up processing rates. Experimental results demonstrate that the approach enhances accuracy and robustness compared with benchmarks.

Prediction of bridge structure deformation and strain based on dynamic testing and intelligent algorithms

The field load test is a direct and effective method for evaluating the performance of bridge structures. However, existing bridge field static load tests are costly and inefficient; moreover, they obstruct traffic and cause unavoidable damage to the bridge structure. As an alternative the the static load test, a random model update method based on bridge dynamic load tests and the Bayesian inference is proposed in this paper. The bridge static load test results were predicted with a high accuracy. To speed up the Bayesian method to infer the posterior probability density of the updated parameters, the Gaussian process was used in place of the finite element model, and the Bayesian inference used the Markov chain Monte Carlo method based on the delayed rejection adaptive Metropolis algorithm. First, the parameters to be modified for the bridge structure analysis model were determined based on the global sensitivity analysis method. Second, a uniform design sampling method was used to establish the Gaussian process optimization model to update the random model of the bridge structure. Finally, a reinforced concrete truss arch bridge was used to verify the correctness of the static load results of the bridge predicted by the random model update method based on dynamic load testing and Bayesian inference. The research results reveal that the prediction results of the bridge static load test based on the dynamic load test and Bayesian inference method agree with the actual test results.

Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation Optimization Method with Limited Coherence Time

The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method.

Short-Term (6 Months or Less) Pain in Cemented versus Cementless Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

BackgroundCementless total knee arthroplasty (TKA) has increased in popularity to potentially improve survivorship. Radiostereometric studies demonstrate increased component migration during the first 3 to 6 months in cementless constructs, generating concern for increased postoperative pain during early osseointegration. The purpose of this study was to evaluate short-term (≤ 6 months) pain and function in cemented versus cementless TKA. We hypothesized that cementless TKA patients report increased pain during the short-term (≤ 6 months) postoperative period. MethodsThe MEDLINE, EMBASE, CINAHL, and Cochrane Libraries were searched for studies evaluating short-term (≤ 6 months) outcomes of cemented versus cementless primary TKA. Studies involving hybrid fixation were excluded. A meta-analysis was performed using standardized mean difference for primary outcomes (early postoperative pain) and weighted mean difference (WMD) for secondary outcomes (early postoperative function). ResultsThere were eleven studies included. There was no significant difference in acute postoperative pain between cemented and cementless TKA within 6 months of index TKA (standardized mean difference 0.08 in favor of cemented TKA; P = .10). Early postoperative forgotten joint scores (WMD 0.81; P = .81) and knee injury and osteoarthritis outcome scores for joint replacement (WMD 0.80 in favor of cemented TKA; P = .14) were also similar between groups. ConclusionsThere is no difference in short-term (≤ 6 months) pain or early function between patients receiving cemented and cementless TKA. This suggests that surgeons may utilize cementless TKA without fear of increased pain due to micromotion within 6 months of index arthroplasty. However, additional studies with uniform assessment methods are needed to further inform differences in short-term pain and early functional outcomes between cemented and cementless TKA.

Naturopathic Interventions for Reduction of Perceived Pain in Patients Suffering from Arthritis: A Systematic Review and Meta-Analysis.

Arthritis affects millions of lives with its pervasive effects on physical health and quality of life. Addressing the complexities of managing symptoms such as swelling, inflammation, and pain requires prolonged treatment. Naturopathy is a treatment method that enhances the body's innate ability to restoreoptimal health through a holistic approach including natural products and lifestyle modifications. This systematic review addresses the intersection of naturopathy and arthritis treatment to provide current evidence about its potential benefits. Four databases (PubMed, AYUSH Research Portal, Web of Science, and Google Scholar) were searched with the keywords "Naturopathy" AND "Arthritis". Randomized, non-randomized, and cross-over studies in English were included. Studies reporting perceived pain using a visual analogue scale (VAS) were selected for meta-analysis. A total of 15 studies were included in the systematic review. The studies were from Denmark, Egypt, France, Hungary, Israel, Italy, Spain, and Turkey, and the study periods ranged from 1992 to 2017. They suggested that naturopathic treatment modalities like exercise, mud compress, sand bath, or hydrotherapy may be used in addition to conventional modes of treatment for added benefit. There was a diversity of naturopathic treatment modalities and outcome evaluation methods. Most studies used mud compress or mud baths with reported improvement of symptoms. The meta-analysis of 10 studies (11 sets of data) showed a significant improvement in pain measured by VAS. The studies included in the review have a high level of heterogenicity. There is a need for more studies and uniform assessment methods with standardization of interventions for robust evidence. More clinical trials from countries where naturopathy is approved treatment modalities are needed.