Combination Of Techniques Research Articles

Presacral Neuroendocrine Neoplasms: A Multi-site Review of Surgical Outcomes.

Presacral neuroendocrine neoplasms (PNENs) are rare tumors, with limited data on management and outcomes. A retrospective review of institutional medical records was conducted to identify all patients with PNENs between 2008 and 2022. Data collection included demographics, symptoms, imaging, surgical approaches, pathology, complications, and long-term outcomes. Twelve patients were identified; two-thirds were female, averaging 44.8years of age, and, for the most part, presenting with back pain, constipation, and abdominal discomfort. Preoperative imaging included computed tomography scans and magnetic resonance images, with somatostatin receptor imaging and biopsies being common. Half of the patients had metastatic disease on presentation. Surgical approach varied, with anterior, posterior, and combined techniques used, often involving muscle transection and coccygectomy. Short-term complications affected one-quarter of patients. Pathologically, PNENs were mainly well-differentiated grade 2 tumors with positive synaptophysin and chromogranin A. Associated anomalies were common, with tail-gut cysts prevalent. Mean tumor diameter was 6.3cm. Four patients received long-term adjuvant therapy. Disease progression necessitated additional interventions, including surgery and various chemotherapy regimens. Skeletal, liver, thyroid, lung, and pancreatic metastases occurred during follow-up, with no mortality reported. Kaplan-Meier analysis showed a 5-year local recurrence rate of 23.8%, disease progression rate of 14.3%, and de novo metastases rate of 30%. The study underscores the complex management of PNENs and emphasizes the need for multicenter research to better understand and manage these tumors. It provides valuable insights into surgical outcomes, recurrence rates, and overall survival, guiding future treatment strategies for PNEN patients.

A Theoretical Study of Oxygen Anion Diffusion through the A-Site Deficient SrTiO3 Lattice Structure: A Machine Learning Approach.

The performance of strontium titanate-based perovskite materials, widely employed as electrode materials for reversible solid oxide cells, is directly characterized by their efficiency and their ability to facilitate the diffusion of generated oxygen ions. A technique frequently employed for enhancing oxygen ion diffusivity involves artificially generating A-site vacancies in these structures. In this study, the molecular-level mechanism of oxygen ion diffusion for a range of A-site deficient structures is extensively investigated using combined molecular dynamics simulations and machine learning-based technique. The analysis of molecular simulation trajectories yields diffusion parameters for the bulk system. Additionally, clustering analysis of time-overlapped locations of oxygen ions provides a spatial distribution of oxygen ion dislocations. Concurrently, tracking the motion of individual oxygen ions elucidates the contribution of each ion to the overall ionic conductance. Overall, the systematic generation of A-site deficiency is found to significantly influence oxygen ion dislocations, thereby impacting the performance of these materials in terms of oxide ion conduction.

Feature engineering-based analysis of DaTSCAN-SPECT imaging-derived features in the detection of SWEDD and Parkinson's disease

Scans without evidence of dopamine deficit (SWEDD) refer to patients with a normal dopamine transporter scan who have been clinically considered to have Parkinson's disease (PD). To prevent misdiagnosis between SWEDD and PD, it is imperative to identify the manifestations of SWEDD in the early stages. In this experiment, imaging-based striatum binding ratio (SBR) features of four striatum regions are utilized and obtained from the Parkinson's Progression Marker Initiative (PPMI). After that, by implementing feature engineering, six combinational pairs are created by taking two SBR features at a time using a mathematical-based combination (nCr)technique. Then, by evaluating the maximum and minimum values of features of each pair, the six new features are obtained from each combinational pair based on arithmetic operations. Finally, a total of thirty-six new features have been derived by using these existing four SBR features. These derived 36 features are further applied to various supervised and ensemble classifiers of machine learning for three binary classifications (PD vs SWEDD, PD vs healthy, and healthy vs SWEDD). From the consequences, it has been observed that the Naive Bayes classifier performed well across all classification probabilities and among other classifiers. To differentiate SWEDD from PD, the classifier achieved 98.03 % accuracy, 98.85 % recall, 96.29 % precision, 92.96 % Jaccard_score, 96.29 % F1-score, & 99.34 % AUC. Moreover, the comparison has been made between with and without implementing the feature engineering technique for all three classification probabilities for better interpretation. Thus, it is reasonable to hypothesize that the suggested method, which is based on feature engineering, may not only improve performance but also help medical professionals diagnose diseases at early stages.

Nowcasting of advance estimates of personal consumption of Services in the U.S. National Economic Accounts: Individual vs forecasting combination approach

AbstractAs part of continuing effort to research statistical methods for producing timely and accurate early estimates of national accounts statistics, this paper evaluates the ability of individual nowcasting and forecast combination techniques to reduce revisions in the first or advance estimates of U.S. quarterly personal consumption of services at the most detailed component level. At such a level, designated indicators for advance estimates are those directly relevant to the detailed components. Using the same indicators that were used in routine compilations, we show in a real time setting that nowcasting methods are able to reduce revisions in the advance estimates in over 90 percent of the detailed components, and the upper bound of the reductions reached over 60 percent. We evaluate the performances of all methods by comparing their root mean squared revisions for each component. Our study suggests that nowcasting techniques are potentially a powerful tool to reduce revisions in the early estimates in the national account statistics at the most detailed level.

Early age structural build-up and pore stability in raw foam at ambient conditions: Implications for the final properties of glass-ceramic foam

Alkali activation followed by foaming techniques is an effective method for glass-ceramic foam development where early-age reactions in the alkali-activated precursors and the foaming reaction happen simultaneously. Therefore, this early reaction stage must be clearly understood to control the pore characteristic in the glass-ceramic foams. However, correlations between early-age structural build-up and foaming stability and their consequences on the final properties of the sintered glass-ceramic foams have not been investigated. This research aims to examine this relationship. 80–95 wt % of waste glass and 5–20 wt % of slag were used as alkali-activated precursors in this research. Using the alkali activation and combined foaming technique, the raw glass foam was developed and hardened at ambient conditions. The early-age reactivity and structural build-up of the binder and foamed suspension were studied through the rheological parameter and chemical structure analysis over the hardening period. During the hardening process, the percolation effect and development of reaction gels contribute to network formation and stability of the foamed suspension. As the hardening time increases, the matrix strengthens, and the pores stabilise through crosslinking of the gels. After hardening, the raw glass foams were sintered and their properties were evaluated and correlated with early-age structural build-up in fresh glass foam. This study demonstrates that the early-age interaction during matrix development and the foaming process controls the pore stability, connected pore volume, and strength of the final glass-ceramic foams. By understanding these parameters, the properties and pore stability in final glass-ceramic foams can be controlled effectively.

Connecting Poincaré Inequality with Sobolev Inequalities on Riemannian Manifolds

We connect the Poincaré inequality with the Sobolev inequality on Riemannian manifold in a family of integral inequalities $(1.5)$. For these continuum of inequalities, we obtain topological structure theorems of manifolds generalizing previous unification theorems in both intrinsic and extrinsic settings ([33]). Manifolds which admit any of these integral inequalities are nonparabolic, affect topology, geometry, analysis, and admit nonconstant bounded harmonic functions of finite energy. As a consequence, we have proven a Conjecture of Schoen-Yau ([27, p.74]) to be true in dimension two with hypotheses weaker than that used in [1] and [33]$($ which were weaker than the hypotheses set in the conjecture, $($ cf. Remark 1.5$)$. In the same philosophy and spirit as in ([31]), we prove that if $M$ is a complete $n$-manifold, satisfying $\operatorname{(i)}$ the volume growth condition $(1.1)$, $\operatorname{(ii)}$ Liouville Theorem for harmonic functions, and either $\operatorname{(v)}$ a generalized Poincaré- Sobolev inequality $(1.5)$, or $\operatorname{(vi)}$ a general integral inequality $(1.6)$, and Liouville Theorem for harmonic map $u : M \to K$ with $\operatorname{Sec}^K \le 0$, then $(1)$ $M$ has only one end and $(2)$ there is no nontrivial homomorphism from fundamental group $\pi_1(\partial D)$ into $\pi_1 (K)$ as stated in Theorem $1.5$. Some applications in geometry $(\S 3)$, geometric analysis $(\S 4)$, nonlinear partial differential systems $(\S 5)$, integral inequalities on complete noncompact manifolds $(\S 6)$ are made $($cf. e.g., Theorems $3.1$, $4.1$, $5.1$, and $6.1)$. Whereas we made the first study in ([29, 32]) on how the existence of an essential positive supersolution of a second order partial differential systems $Q(u)=0$ on a Riemannian manifold $M$, (by which we mean a $C^2$ function $v \ge 0$ on $M$ that is positive almost everywhere on $M$, and that satisfies $Q(v)=\operatorname{div}(A(x,v,\nabla v)\nabla v)+b(x,v,\nabla v)v\leq 0\quad (5.1)\, $) affects topology, geometry, analysis and variational problems on the manifold $M$. Whereas we generate the work in [35], under $p$-parabolic stable condition without assuming the $p$-th volume growth condition $\lim _{r \to \infty} r^{-p}\operatorname{Vol}(B_r) =0$. The techniques, concepts, and results employed in this paper can be combined with those of essential positive supersolutions of degenerate nonlinear partial differential systems $($cf. for example, Theorems 5.1 - 5.5, 6.1, etc.$)\, $ generalizing previous work in [32, 4.11], which in term recaptures the work of Schoen-Simon-Yau ([25, Theorem 2]). The combined techniques, concepts and method of [32] and [35] can also be used in other new manifolds we found by an extrinsic average variational method ([34]).

Meta-Substituted Asymmetric Azobenzenes: Insights into Structure-Property Relationship.

This article presents a comprehensive investigation into the functionalization of methoxyphenylazobenzene using electron-directing groups located at the meta position relative to the azo group. Spectroscopic analysis of meta-functionalized azobenzenes reveals that the incorporation of electron-withdrawing units significantly influences the absorption spectra of both E and Z isomers, while electron-donating functionalities lead to more subtle changes. The thermal relaxation process from Z to E result in almost twice as prolonged for electron-withdrawing functionalized azobenzenes compared to their electron-rich counterparts. Computational analysis contributes a theoretical understanding of the electronic structure and properties of meta-substituted azobenzenes. This combined approach, integrating experimental and computational techniques, yields significant insights into the structure-property relationship of meta-substituted asymmetrical phenolazobenzenes.

Clot composition and recanalization outcomes in mechanical thrombectomy

BackgroundMechanical thrombectomy (MT) has become standard for large vessel occlusions, but rates of complete recanalization are suboptimal. Previous reports correlated radiographic signs with clot composition and a better response to...

Combatting ransomware in ZephyrOS-activated industrial IoT environments

The rapid growth of the Industrial Internet of Things (IIoT) has opened up new avenues for cyber threats, with ransomware being a primary area of concern. In response to this, proposed study introduces an innovative approach that combines the strength of the Gradient Boosting Machine (GBM) and the precision of Lasso Regression to effectively identify ransomware threats in IIoT settings. Functioning on the Zephyr operating system, the GBM's ability to handle large-scale datasets and traverse complex data dimensions is complemented by Lasso Regression's skill in curbing overfitting and extracting critical features. This combined ML technique is specifically designed to address the diverse data challenges of IIoT, providing a solid line of defense. Comprehensive tests on updated ransomware tools and the established RanSAP & IoT-23 datasets validated our model's capabilities, achieving an impressive 92 percent detection rate while keeping false positives to a minimum. When compared to existing strategies, projected solution showcased superior performance, highlighting its pivotal role in bolstering IIoT security against ransomware attacks. These results shed light on the next steps for ensuring a safer IIoT landscape, emphasizing the need for advanced, flexible cybersecurity measures in our ever-evolving industrial ecosystem.

Accelerating the shooting and bouncing ray based electromagnetic scattering calculations via CPU and GPU Implementations: Application to PREDICS tool

In this paper, we present the parallel computation of physical electromagnetic (EM) solvers, namely physical optics (PO), shooting and bouncing rays (SBR), and the physical theory of diffraction (PTD), which are used for EM scattering/diffraction calculations. The accelerated solvers have been tested on CPU and GPU kernels for significantly faster calculation times. As an application, the developed implementation is employed to recently developed tool of PREDICS that uses combined techniques PO, SBR, and PTD for the calculation of EM scattering/diffraction and radar cross section (RCS) from electrically large, complex objects. First, the CPU parallelization of these three combined techniques on the PREDICS code is explained. The parallelization implementation is specially tailored for the nature of SBR technique such that the CPU iteration loop is accomplished over triangular facets of the CAD file by employing a read/write spin lock task dispatching technique. Next, a lock-free implementation of the PO, SBR, and PTD techniques on the GPU threads is presented. Thanks to availability of many GPU cores, the parallelization procedure is widened such that triangular facets, observation angles of elevation and azimuth are used for a much faster calculation set-up. Numerical examples for the EM/RCS calculation of simple canonical and electrically big, complex objects are shared to demonstrate the effectiveness, accuracy and the computational acceleration based on the multi-CPU and multi-GPU implementations. The key metric of the contribution of the study is the speed-up value of the implementations. The acceleration gained via multi-CPU realization yielded directly in parallel with the number of available CPU cores. On the other hand, the acceleration factor can reach to hundreds when multi-GPUs are used. In fact, the acceleration factor has reached to 4.7 for a machine with 4 Core 8 Thread CPU processor, and 141.3 for a 2560 CUDA GPU Core system.

An integrated approach combining randomized kernel PCA, Gaussian mixture modeling and ICA for fault detection in non-linear processes

Principal component analysis (PCA) and independent component analysis (ICA), as well as their kernel extensions, have been widely applied in the past for industrial fault detection with Gaussian or non-Gaussian process data with linear or non-linear characteristics. Kernel-based techniques lead to computational complexity due to the high dimensionality of the dataset in the feature space. In this work, a randomization approach is used to obtain a low-rank approximation of the high-dimensional kernel matrix. A hybrid machine learning technique is proposed that integrates randomized kernel PCA (RKPCA) with ICA and Gaussian mixture modeling (GMM). The proposed approach, ICA-RKPCA-GMM, addresses the Gaussian and non-Gaussian characteristics of non-linear process data. Another hybrid algorithm combining three basic techniques of ICA, PCA and GMM is also developed (ICA-PCA-GMM). The fault detection performances of the proposed techniques (ICA-RKPCA-GMM and ICA-PCA-GMM) are compared with PCA, ICA, KPCA and combined ICA-PCA techniques by applying the techniques to two benchmark systems. Monitoring performances were evaluated by determining the false alarm rate and fault detection rate for different types of process and sensor faults. The simulation results show that the proposed ICA-RKPCA-GMM approach yields better results than individual ICA, PCA and KPCA techniques, the combined ICA-PCA and the proposed ICA-PCA-GMM technique.

Layer-Weighted Attention and Ascending Feature Selection: An Approach for Seriousness Level Prediction Using the FDA Adverse Event Reporting System

In this study, we introduce a novel combination of layer-static-weighted attention and ascending feature selection techniques to predict the seriousness level of adverse drug events using the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). We utilized natural language processing (NLP) to analyze the terms in the active substance field, in addition to considering demographic and event information such as patient sex, healthcare provider qualification, and drug characterization. Our ascending feature selection method, which progressively incorporates additional features based on their importance, demonstrated continuous enhancements in prediction performance. Simultaneously, we employed a layer-static-weighted attention technique, which dynamically adjusts the model’s focus between natural language processing (NLP) and demographic features. This technique achieved its best performance at a balanced weight of 50%, yielding an average test accuracy of 74.56% and CV ROC score of 0.83 when 4000 features were included, indicating a compelling advantage to include a larger volume of meaningful features. By integrating these methodologies, we constructed a robust model capable of effectively predicting seriousness levels, offering significant potential for improving pharmacovigilance and enhancing drug safety monitoring. The results underscore the value of NLP and demographic data in predicting drug event seriousness and demonstrate the effectiveness of our combined techniques. We encourage further research to refine these methods and evaluate their application to other clinical datasets.

Rapid Detection and Elimination of Subsurface Mechanical Damage for Improving Laser-Induced Damage Performance of Fused Silica

The fabrication of SSD-free fused silica optics is a crucial objective for high-power laser applications. To treat the surface of polished fused silica, a combination of RIE/RIBE and deep-controlled etch (DCE) techniques are typically employed. Currently, it is important to consider and study the ideal etching depth and precision while using combined etching techniques to remove the identified SSD. Herein, we present a novel approach to identify the distribution of SSD in fused silica, which corresponds to a specific grinding/polishing process condition. Our method involves using a mobile RIBE to perform cone cutting and remove material from the polished fused silica surface. Afterward, we etch the optical element’s surface with HF to visualize the subsurface cracks and understand their relationship with the RIBE depth. Through a systematic investigation of the combined etching technique, we establish a correlation between the depth of RIBE and DCE and the performance of laser damage. The combined etching technique can be implemented as a dependable approach to treat the surface/subsurface defects in fused silica and has the potential to improve laser damage resistance significantly.

Treatment of tibial bone defects caused by infection: a retrospective comparative study of bone transport using a combined technique of unilateral external fixation over an intramedullary nail versus circular external fixation over an intramedullary nail

BackgroundThe purpose of the study was to assess and compare the clinical efficacy of bone transport with either circular or unilateral external fixators over an intramedullary nail in the treatment of tibial bone defects caused by infection.MethodsBetween May 2010 and January 2019, clinical and radiographic data were collected and analyzed for patients with bone defects caused by infection. Thirteen patients underwent bone transport using a unilateral external fixator over an intramedullary nail (Group A), while 12 patients were treated with a circular external fixator over an intramedullary nail (Group B). The bone and functional outcomes of both groups were assessed and compared using the Association for the Study and Application of the Method of the Ilizarov criteria, and postoperative complications were evaluated according to the Paley classification.ResultsA total of 25 patients were successfully treated with bone transport using external fixators over an intramedullary nail, with a mean follow-up time of 31.63 ± 5.88 months. There were no significant statistical differences in age, gender, previous surgery per patient, duration of infection, defect size, and follow-up time between Group A and Group B (P > 0.05). However, statistically significant differences were observed in operation time (187.13 ± 21.88 min vs. 255.76 ± 36.42 min, P = 0.002), intraoperative blood loss (39.26 ± 7.33 mL vs. 53.74 ± 10.69 mL, P < 0.001), external fixation time (2.02 ± 0.31 month vs. 2.57 ± 0.38 month, P = 0.045), external fixation index (0.27 ± 0.08 month/cm vs. 0.44 ± 0.09 month/cm, P = 0.042), and bone union time (8.37 ± 2.30 month vs. 9.07 ± 3.12, P = 0.032) between Group A and Group B. The excellent and good rate of bone and functional results were higher in Group A compared to Group B (76.9% vs. 75% and 84.6% vs. 58.3%). Statistically significant differences were observed in functional results (excellent/good/fair/poor, 5/6/2/0 vs. 2/5/4/1, P = 0.013) and complication per patient (0.38 vs. 1.16, P = 0.012) between Group A and Group B.ConclusionsBone transport using a combined technique of external fixators over an intramedullary nail proved to be an effective method in treating tibial bone defects caused by infection. In comparison to circular external fixators, bone transport utilizing a unilateral external fixator over an intramedullary nail resulted in less external fixation time, fewer complications, and better functional outcomes.

Integration of statistical and simulation analyses for ternary hybrid nanofluid over a moving surface with melting heat transfer

In industrial and engineering fields including lamination, melt-spinning, continuous casting, and fiber spinning, the flow caused by a continually moving surface is significant. Therefore, the problem of ternary hybrid nanofluid flow over a moving surface is studied. This study explores the stability and statistical analyses of the magnetohydrodynamics (MHD) forced flow of the ternary hybrid nanofluid with melting heat transfer phenomena. The impacts of viscous dissipation, Joule heating, and thermal radiation are also included in the flow. Different fluids including ternary hybrid nanofluid, hybrid nanofluids, and nanofluids with base fluid ethylene glycol (EG) are examined and compared, where magnetite (Fe3O4) and silica (SiO2) are taken as the magnetic nanomaterials while silver (Ag) is chosen as the nonmagnetic nanomaterial. The skin friction coefficient and the local Nusselt number are estimated through regression analysis. By employing similarity transformations, the governing partial differential equations are converted into non-linear ordinary differential equations. Then, the least square method is applied to solve the equations analytically. Dual solutions are established in a particular range of moving parameter λ. Due to this, a stability test is implemented to find the stable solution by using the bvp4c function in MATLAB software. It is found that the first solution is the stable one while the second is unstable. The use of ternary hybrid nanomaterials improves the heat transport rate. The increasing values of the Eckert number enlarge the heat passage. The fluid velocity and temperature profiles for nonmagnetic nanomaterials are higher than that of magnetic nanomaterials. The uniqueness and originality of this study stems from the fact that, to the best of the authors’ knowledge, it is the first to use this combination technique.

GIS-based intelligent planning approach of child-friendly pedestrian pathway to promote a child-friendly city.

Pedestrian safety, particularly for children, relies on well-designed pathways. Child-friendly pathways play a crucial role in safeguarding young pedestrians. Shared spaces accommodating both vehicles and walkers can bring benefits to pedestrians. However, active children playing near these pathways are prone to accidents. This research aims to develop an efficient method for planning child-friendly pedestrian pathways, taking into account community development and the specific needs of children. A mixed-methods approach was employed, utilizing the Datang community in Guangzhou, China, as a case study. This approach combined drawing techniques with GIS data analysis. Drawing methods were utilized to identify points of interest for children aged 2-6. The qualitative and quantitative fuzzy analytic hierarchy process assessed factors influencing pathway planning, assigning appropriate weights. The weighted superposition analysis method constructed a comprehensive cost grid, considering various community elements. To streamline the planning process, a GIS tool was developed based on the identified factors, resulting in a practical, child-friendly pedestrian pathway network. Results indicate that this method efficiently creates child-friendly pathways, ensuring optimal connectivity within the planned road network.

High-precision microcline 40Ar/39Ar dating by combined techniques

K-feldspar is one of the most common minerals applied for 40Ar/39Ar dating because of its high K content and ubiquitous presence. Excess 40Ar in K-feldspar resulting in unreliable ages has long been reported, however, its occurrence and trapping time are still inconclusive. Combined argon extraction techniques, including laser step heating, and step crushing, as well as succedent furnace incremental heating, have been applied to six microcline samples from two hydrothermal ore deposits in South China, to address these issues. Two microcline samples (09SZ37 & 39) measured by all the above three gas extraction techniques yield flat age spectra and concordant inverse isochron ages respectively. However, one sample (09NL10) produces a flat spectrum but with abnormally low radiogenic 40Ar, and the other three samples obtain uneven age spectra, by laser heating. All six samples measured by step crushing yield quite similar age spectra characterized with declining staircases for the first several steps, and followed with very flat plateaus of high-precision plateau ages for the subsequent later crushing steps. The declining sections with abnormally old ages indicate that excess 40Ar (and obvious atmospheric argon) was trapped in the microcracks and the secondary fluid inclusions. The data points corresponding to age plateaus well define inverse isochron ages which are in consistence with their plateau ages respectively. Furthermore, the crushed powders of all six samples by further furnace step heating also yield very flat age spectra, whose plateau ages are well concordant with those obtained by the foregoing step crushing experiments. The trapped excess 40Ar caused the total fusion ages of laser heating 0.7–17.8% older than their true ages. Mineral grains of ca. 0.10 mm may effectively remove excess 40Ar in microcracks and secondary fluid inclusions, proposed for direct 40Ar/39Ar step heating. Stepwise crushing, combined with furnace heating, is not only very useful to date fluid inclusions, but also robust to remove excess 40Ar and obtain more precise true ages for K-bearing minerals, e.g., K-feldspar, amphibole, tourmaline, and so on.

Technical feasibility and economic benefit of combined shallot seedlings techniques in Indonesia

Abstract One of the important factors in the success of True Seed of Shallot (TSS)-based shallot production is the right seeding technology. The study aimed to obtain appropriate nursery techniques for producing high-quality seedlings to increase shallot productivity. The experiment was conducted in Cirebon Regency, West Java, Indonesia, from May to October 2021, using a factorial randomized block design with three treatment factors and three replications. They consisted of shallot varieties (V) (Trisula, Bima, Lokananta, and Maserati); seedlings age (U) (45 and 60 days); and seedling population density (P) (5, 7.5, and 10 g m−2 of TSS). The results revealed that seedling performance was negatively correlated to the bulb yield and revenue cost ratio (R/C). The use of young seedlings enhanced bulb production and R/C ratio in all varieties but had varied effects on cluster alterations in Maserati, Bima, and Trisula varieties. Young Lokananta seedlings prepared in the nursery at a seed density of 7.5 g m−2 proved to be the best treatment to generate the highest bulb production (39.92 t ha−1) and the highest R/C (3.62). Farmers are expected to implement seedling preparation techniques using young seedlings and managing seed populations in diverse varieties to maximize bulb production and R/C.

Characterization of the neural circuitry of the auditory thalamic reticular nucleus and its potential role in salicylate-induced tinnitus.

Subjective tinnitus, the perception of sound without an external acoustic source, is often subsequent to noise-induced hearing loss or ototoxic medications. The condition is believed to result from neuroplastic alterations in the auditory centers, characterized by heightened spontaneous neural activities and increased synchrony due to an imbalance between excitation and inhibition. However, the role of the thalamic reticular nucleus (TRN), a structure composed exclusively of GABAergic neurons involved in thalamocortical oscillations, in the pathogenesis of tinnitus remains largely unexplored. We induced tinnitus in mice using sodium salicylate and assessed tinnitus-like behaviors using the Gap Pre-Pulse Inhibition of the Acoustic Startle (GPIAS) paradigm. We utilized combined viral tracing techniques to identify the neural circuitry involved and employed immunofluorescence and confocal imaging to determine cell types and activated neurons. Salicylate-treated mice exhibited tinnitus-like behaviors. Our tracing clearly delineated the inputs and outputs of the auditory-specific TRN. We discovered that chemogenetic activation of the auditory TRN significantly reduced the salicylate-evoked rise in c-Fos expression in the auditory cortex. This finding posits the TRN as a potential modulatory target for tinnitus treatment. Furthermore, the mapped sensory inputs to the auditory TRN suggest possibilities for employing optogenetic or sensory stimulations to manipulate thalamocortical activities. The precise mapping of the auditory TRN-mediated neural pathways offers a promising avenue for designing targeted interventions to alleviate tinnitus symptoms.

Early results of the combined grafting–cementation technique for the treatment of giant cell tumors with a large subchondral bone defect: a case series

Background Giant cell tumor (GCT) is a rare, locally aggressive bone tumor. It typically affects young adults close to the joints, mainly the knee joint. The high recurrence rate, along with erosion of the subchondral bone complicates the surgical plan. Current treatment standards involve extended curettage followed by space-filling by cement or graft. We present a detailed technique using a combined technique using both bone graft and cement for reconstructing GCT-related subchondral damage. Patients and methods Eighteen patients underwent surgery from January 2018 to December 2021. The surgery involved extended curettage using a high-speed burr, and lavage using hydrogen peroxide. Placement of the graft as a subchondral shelf helps to support the articular cartilage. Bone cement was applied to fill the cavity and support the graft; internal fixation was used in large-sized lesions. Results The mean follow-up is 34.5 months. Oncologically, local recurrence was reported in one case, with a distal radius location, and no distant metastasis was reported. Functionally, 86.6% had excellent/good Musculoskeletal Tumor Society score scores. Graft union had occurred in all cases; mean union time was 12 weeks. Rehabilitation included immediate passive range of motion exercises and partial weight bearing. The pain had improved significantly in all cases. Muscle power had been temporarily affected in five cases. One patient had a wound infection, managed with antibiotics. Conclusion Treatment of GCTs is challenging. The standard treatment involves curettage and gap filling. The presence of the cement close to the articular cartilage can lead to osteoarthritis due to different modulus of elasticity. We describe this combined technique to provide support, insulation, and stability, and minimize the stresses on the articular cartilage. The results of this technique are promising and yield good functional and oncological outcomes. Further research is needed to evaluate its long-term efficacy in preventing progressive osteoarthritis.