Local Effects Research Articles

Does the Uterine Ozone Therapy Alter the Transcript Profile of Anti- and Proinflammatory Genes in Mares With Endometritis?

This study aimed to evaluate the localised effects of intrauterine ozone therapy on endometrial recovery in mares with endometritis. Our investigation assessed changes in gene expression profiles of anti-inflammatory (IL-1RA and IL-10), proinflammatory (IL-R1B3i and TNFα) and pleiotropic (IL-6) cytokines, along with detailed histological measurements of epithelial and endometrial thickness and the glandular area ratio. Twenty mares were assigned to a 2 × 2 factorial design based on endometritis diagnosis and treatment (control or 42 μg/mL ozone insufflation), resulting in four groups: NC (negative for endometritis/control), NO (negative/ozone), PC (positive/control) and PO (positive/ozone). Oestrus was induced with 2 mg of oestradiol benzoate on Days -1, 1 and 3, plus 1 mg on Day 5. Day 0 marked the initial uterine treatment, followed by insufflations on Days 1 and 2 with O3 (ozone) or O2 (control). Uterine biopsies were taken before treatment on Day 0 and Day 6 for histological analysis and gene expression assessment. Data were analysed using a statistical model that included endometritis status, treatment type, biopsy times (D0 and D6) and their interactions, analysed with Proc Glimmix. Regardless of treatment or endometritis status, significant biopsy effects (p < 0.01) indicated increased epithelial height and endometrial thickness in Day 6 samples. Analysis of IL-1 and TNFα revealed a significant interaction (p < 0.05) among endometritis, treatment and biopsy, with higher IL-1B3i expression on Day 6 in the PC group. The treatment effect (p < 0.04) showed a higher frequency (p < 0.01) of animals with positive modulation in the PC group (66.7%) versus the PO group (0.0%). An interaction effect (p = 0.08) between endometritis and treatment resulted from higher IL-1RA expression on Day 6 in the PC group compared to the PO group. Biopsy effect was significant for IL-10 (p < 0.01), indicating higher values in the second sample associated with tissue repair. In the short-term evaluation, ozone therapy did not influence endometrial morphology and may modulate cytokine expression, specifically the reduction in IL-1 and TNFα levels. Therefore, this therapy appears to be a safe and potentially effective treatment for modulating the inflammatory response in mares with endometritis.

Clinical Benefits of DaxibotulinumtoxinA for Injection: Beyond Glabellar Line Effacement?

Botulinum toxin type A (BoNTA) is standard of care for glabellar lines ameliorization. DaxibotulinumtoxinA for Injection (DAXI) is a new BoNTA with a unique formulation representing the latest advancement in BoNTA technology. There is an unmet need for patients to understand the full potential of BoNTA treatment and new technologies. To update clinical data supporting the use of DAXI for glabellar lines within the context of clinical experience. A narrative review of the literature and summary of clinical experience with DAXI. The DAXI clinical trial program reflects clinical experience post-FDA approval, with DAXI demonstrating rapid onset, high patient response rates, and extended treatment duration versus conventional BoNTAs. Clinical observations suggest that DAXI has limited diffusion from the injection site, enabling more localized control of muscle activity and greater improvements in wrinkle severity. DAXI enables practitioners to exert greater finesse in their injections and in predicting changes to eyebrow shape and position and achieve improvement in skin quality. Advances in BoNTA technology can provide patients with greater options for treatment outcomes. The potential for enhanced localized effects with DAXI may contribute to more precise and targeted effects on muscle activity and additional aesthetic benefits to patients.

Gravity dam displacement monitoring using in situ strain and deep learning

AbstractRecent studies in dam displacement monitoring primarily focus on single‐response monitoring or model updating using advanced techniques. Few studies involve the combination analysis of displacement with other synchronized responses utilizing their monitoring characteristics. In situ strain data provide a strength‐safety perspective for dam displacement monitoring. The challenge lies in that estimating displacement directly using limited discrete strain data may be misleading. This paper analyzes the relationship between displacement and global, and multipoint local strains from the perspective of the differences in load effects of gravity dams, and indicates that introducing appropriate state factors improves the estimation. A displacement estimation model driven by strain data and state factors is developed using stacked convolutional neural network, and the variable relationships within the model are interpretated via accumulated local effects. Incorporating specific strength criteria, a novel displacement monitoring indicator based on the tensile safety of the dam heel is proposed. A case study of a gravity dam showcases the effectiveness of the proposed approach in comparison with the solely strain‐based model and the traditional hydrostatic‐seasonal‐time factors‐based model.

Comprehensive Survey on Datasets, Models, and Future Directions in Plant Disease Prediction

In recent years, advancements in computer vision (CV) and machine learning (ML) have facilitated significant progress in the field of plant disease prediction and detection. The growing danger to worldwide food security because of plant diseases necessitates the development of accurate and efficient methods for early disease identification. This paper provides an extensive overview of the current landscape of plant disease prediction using plant images, focusing on datasets, models, and potential future directions. Initially, publicly available datasets that comprise annotated images of healthy and diseased plants, enabling researchers to develop and evaluate predictive models are analyzed. These datasets, encompassing a wide range of crops and diseases, serve as crucial resources for training and benchmarking various algorithms. Also, explore both traditional and modern approaches, including expert systems, ML, and deep learning (DL) algorithms. Model architectures, transfer learning strategies, and ensemble techniques are discussed in terms of their effectiveness in disease classification and localization. This paper also addresses the challenges faced in plant disease prediction, such as data scarcity, model robustness, and scalability. Provide a rendition of the present state of research and identify potential avenues for future exploration, this paper aims to contribute to the advancement of plant disease prediction methods, fostering more resilient and productive agricultural practices.

CH4 hydrate dissociation and CH4 leakage characteristics: Insights from laboratory investigation based on stratified environment reconstruction of natural gas hydrate reservoir

Submarine natural gas hydrates (NGHs) are one of the largest methane reservoirs on Earth, offering huge potential as an alternative energy source and serving as a crucial global carbon sink. However, the substantial risk of methane leakage during NGH development seriously threatens marine and global ecological and environmental safety, presenting a major challenge for commercial NGH exploitation. Focusing on the unknown leakage mechanisms, this study employed a new simulation device to construct a stratified environment and to investigate the characteristics of hydrate dissociation and methane leakage during depressurization production, under conditions of varied fracturing in overlying sediment. A movable module was used to dynamically isolate and connect the hydrate reservoir with the overlying layer. The results showed that the intrusion of overlying water decelerated the reservoir depressurization rate, leading to a mass of hydrate reformation. The invasion locations and flow paths of the overlying water were influenced by the fracture scale of the overlying sediment. Benefiting from the additional sensible heat and reservoir space occupation of the overlying water in the later production stages, the methane recovery ratio in the fracture-containing systems were not significantly affected. However, the leakage methane increased as fracture channels enlarged, reaching up to 9.90 % of the total methane content in the hydrate reservoir. The leakage mechanism primarily involved local overpressure, buoyancy effects, and diffusion. The research, for the first time, experimentally revealed the response relationship between methane leakage and hydrate dissociation, providing foundational data and theoretical support for the safe and efficient NGH development.

Synchronisation of thermal imaging and multi-channel EIS to interpret planar array PCB fuel cell performance

The planar design of printed circuit board (PCB) fuel cells offers the advantages of simple structure, rapid prototyping and easy manufacturing. However, uneven reactants and heat distribution in each PCB cell module often result in inconsistent overall performance. Current characterisation methods mainly focus on the study of the overall performance and lack the analysis of individual cells, which provide a limited understanding of localised electrochemical and thermal effects that might play a critical part in further optimising and diagnosing the cell performance of this category. We have developed a multi-channel impedance diagnostic technique for PCB fuel cells. Combining with thermal imaging, we could simultaneously diagnose individual open cathode cell modules by measuring the heat distribution and electrochemical impedance spectra (EIS) of 11 PCB cell modules. Hence, the correlation between heat distribution, internal resistance and performance of different sections of PCB fuel cells can be established. By comparing the fuel cell’s pristine and degraded, we demonstrated how this non-destructive technique could identify and locate cell modules with deteriorated performance, which would be beneficial to real-time diagnostics, quality control and optimisation. The multi-channel impedance measurement takes several seconds only through optimised multi-frequency perturbation and can be readily extended to stacks containing more cells by simply increasing the number of voltage sensors, which can be further adapted to other electrochemical devices.

Preparation and Evaluation of Medicated Oral Jelly

Developed in the 20th century, oral medicinal jellies are still produced commercially and are still well-liked by customers. These are chewable solid dose forms that dissolve in the mouth or throat to provide either localized or systemic effects. They are taken orally. As a pharmacological composition, oral medicated jelly has some benefits but also certain drawbacks. They can be applied to the buccal, labial, gingival, and sublingual channels of drug administration, among other routes. These jellies, which come in flavors including chocolate, strawberry, pineapple, and mango, are over-the-counter drugs. They comprise medications for a number of ailments, including sore throat, antistatic, erectile dysfunction, arthritis, and hypertension. The Japanese Ministry of Health, Labour, and Welfare authorized a once-weekly oral program in 2012 The world's first medication for osteoporosis in a jelly formulation was approved by the Japanese Ministry of Health, Labour and Welfare and is to be taken orally once a week. A process of heating and congealing is used in their formulation. Oral medicated jellies serve as a new dosage form with vast uses in pharmaceuticals, nutraceuticals, and over-the-counter drugs. This study offers formulation scientists insight into new uses for this drug delivery technology by focusing on several facets of oral medicated jelly formulation. Orodispersible dose formulations provide patients additional possibilities for medication administration. They are simple to use and don't need ingesting big, solid dose forms or consuming a lot of water. This research aims to develop and assess the mouth-dissolving film of lisinopril as an ACE inhibitor for the treatment of congestive heart failure and hypertension. When compared to traditional solid oral dose forms, these forms are thought to increase the bioavailability of medications.

Chemical Dermal Exposure Risk Assessment in the Water Treatment Plant of Fertilizer Industry

Introduction:In water treatment plants (WTP), chemicals play a crucial role. However, some of these chemicals are hazardous. This study aims to conduct a dermal risk assessment in the WTP of an ammonia and urea production facility. Methods: The study was performed in August 2023 and assessed dermal exposure risk for four hazardous chemicals: NaOCl (30%), HCl (60%), H2SO4 (98%), and NaOH (48%), utilizing the Tier 2 RISKOFDERM model. Intrinsic toxicity was evaluated using risk phrases and toxicity information. Potential dermal exposure rates (PERBODY and PERHANDS) were determined based on task group and exposure modifier, while actual dermal exposure rates (AERBODY and AERHANDS) were determined based on clothing type and activity time. Health risk was assessed using actual exposure scores and intrinsic toxicity levels, which were categorized into 10 different levels ranging from 1 to 10. Results: The risk phrases indicated that four chemicals possessed a high level of intrinsic toxicity in terms of local effect but no systemic effect. PERBODY and PERHANDS were high (NaOCl, HCl) and low (H2SO4, NaOH). The actual exposure scores were determined to be 1 (high) for NaOCl and HCI, 0.01 (low) for H2SO4, and 0.03 (medium) for NaOH. Health risk values were 8 for NaOCl and HCI, 5 for H2SO4, and 6 for NaOH. Conclusion: Health risks in NaOCl and HCl were assigned action priority (AP) 1, followed by NaOH at AP-2, and H2SO4 at AP-3. The study recommends the implementation of control measures encompassing engineering solutions, administration, and personal protective equipment.

Simultaneous measurement of the distributed longitudinal strain and velocity field for a cantilevered cylinder exposed to turbulent cross flow

The structural response of a cantilevered cylinder under free-stream conditions both with low and high turbulence intensity generated by turbulence-generating grids is analysed with concurrent measurements of the velocity field and the distributed strain. The thin-walled cylinder, with a diameter (D) of 50 mm, is mounted in a water flume as a cantilevered beam supported at one end, with 95% of its body submerged and exposed to cross flow yielding a Reynolds number of Re = 25000. We employ a novel combination of simultaneous particle image velocimetry and distributed strain measurements using Rayleigh backscattering fibre optic sensors. These sensors are embedded onto the surface of the cylinder to measure the experienced strain (ε\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varepsilon $$\\end{document}) of the structure along its spanwise direction, covering both the windward and leeward faces of the cylinder. The sensors fine spatial resolution allows us to discern the influence of the flow on the structural response of the cylinder in two distinct regions of the structure: upstream and downstream of the mean separation location. This differentiation allows us to isolate the local effects introduced by the free-stream conditions on the loading events over the body from the global force generated by the vortex shedding and other coherent motions present within the flow. Distinguishing between these direct and indirect effects helps determine which is more relevant for fatigue-life cycle analysis. The cross power spectral density between the fluctuating velocity field and the strain reveals that the load is dominated by the vortex shedding, and this relationship is intensified with the introduction of free-stream turbulence. It also helps to discern the different dynamics imposed by the two free-stream turbulence conditions.

Construction of bilayer cellulose-based aerogel with salt-resistant design for efficient solar desalination and wastewater purification

Solar-driven interfacial evaporation (SDIE) technology, which utilizes green and renewable solar energy to produce clean water, has shown great potential in alleviating global water scarcity. However, practical applications still face numerous challenges, including salt crystallization precipitation and accumulation, low energy utilization, and complex preparation processes. Hence, We designed a vertically ordered porous bilayer aerogel based on nanofibrillated cellulose (NFC)/polyethyleneimine (PEI) with excellent salt resistance, light absorption and local thermal effects to achieve efficient solar steam generation. Specifically, the photothermal conversion layer (PCL) at the top had excellent light absorption and photothermal conversion efficiency by introducing graphene oxide (GO) as a highly efficient photothermal material. The water transport layer (WTL) at the bottom ensured a stable water supply to the evaporation layer by virtue of the vertical water transfer path and inherent hydrophilicity, and effectively prevented formation of salts in the evaporation area. In addition, the designed aerogel had a low thermal conductivity, which achieved effective thermal insulation and further enhanced the localized heating effect. This superhydrophilic bilayer aerogel achieved a high evaporation rate of 1.9596 kg m−2 h−1 and an energy conversion efficiency of 92.28% under one solar irradiation. It is noteworthy that evaporation process exhibited excellent stability during 8 h of continuous evaporation in 20 wt% brine and no salt accumulation was observed on the evaporated surface. In addition, the bilayer aerogel demonstrated excellent long-term stability and self-cleaning. Meanwhile, its excellent anti-contamination and wastewater treatment capabilities give SDIE technology a stable and continuous operation in practical applications, thus demonstrating significant application potential.

Active site requirements for bio-alcohol dehydration: Effect of chemical structure and site proximity

Synthesis-structure-activity relations are reported, describing how interzeolite conversion (IZC) allows synthesis of ZSM-5 (MFI framework) with fixed physicochemical properties, except the variable local acid site (Al) arrangement, by variation of the synthesis time. Local confinement and acidity effects are probed by applying both H-ZSM-5 and Na-ZSM-5 samples in alcohol dehydration. Pyridine and divalent cobalt ion probing are used to quantify the amount of accessible acid sites and of Al in close proximity. Al in close proximity shows a strong influence on n-butanol dehydration turnover rates. The turnover rates are also strongly dependent on local confinement: in Na-form, ZSM-5 synthesized with more Al present as isolated species is a factor of 3–7 times more active than Na-ZSM-5 with fewer isolated Al. However if the zeolites are in proton form, ZSM-5 with more proximate sites show a higher activity compared to ZSM-5 with more isolated sites. Linear butene selectivity increases in Na-ZSM-5 compared to H-ZSM-5, caused by a suppressed dibutyl ether formation. The selectivity towards 1-butene is enhanced to a greater extent on proximate sites, likely due to a local/steric constraint at the active site. Decomposition of DBE over Na-ZSM-5 is more active compared to n-butanol dehydration, independent of acid site proximity. Also for 2-propanol dehydration, Na-ZSM-5 is less active than H-ZSM-5, yet the activity difference is attenuated compared to n-butanol dehydration. Essentially, due to the intrinsic higher reactivity of 2-propanol, the acid site requirement is less stringent. These findings highlight the importance of local confinement and Al proximity in acid-catalyzed conversion of oxygenated compounds.

Phase unwrapping of SAR interferogram from modified U-net via training data simulation and network structure optimization

Phase unwrapping is the process of retrieving the true phase values from observed wrapped phases by adding the correct multiples of 2π. This process is crucial in synthetic aperture radar (SAR) interferometry, and numerous studies have aimed to enhance its performance. This study explored phase unwrapping using a modified U-Net regression model by optimizing both the network structure and training data. For network structure optimization, the study first compared model performance based on the size ratio of the lowest feature maps, determined by the number of pooling layers, to the size of convolutional kernels. A multi-kernel U-Net structure was developed to ensure robustness against variations in phase noise and gradient, compared to a standard single-kernel U-Net. Regarding the training data, data augmentation was implemented to address imbalances and better represent the local noise characteristics found in actual SAR interferograms. The training data was simulated to include local noise effects based on coherence measurements from real SAR data, as well as simple noise used for benchmarking the unwrapping performance with different training datasets. The results indicated that when the convolutional kernel size is smaller than the feature map size at the lowest layer, increasing the number of pooling layers leads to improvements in unwrapping performance. Conversely, performance decreased when the feature map size at the lowest layers was smaller than the convolutional kernel size. Specifically, the single-kernel U-Net with six pooling layers and the multi-kernel U-Net with five pooling layers exhibited the best unwrapping performance. Considering both simulated and real synthetic aperture radar interferogram data, the mean absolute errors for the single- and multi-kernel U-Net trained with simple noise were approximately 0.235 and 0.254, respectively. In contrast, for models trained with locally variable noise simulation data, the MAEs dropped to about 0.033 and 0.032, showing an improvement by approximately eightfold over models trained with simple noise. For real synthetic aperture radar interferograms, the mean absolute errors were 0.542 (single-kernel U-Net trained using simple noise), 0.592 (multi-kernel U-Net trained using simple noise), 0.542 (single-kernel U-Net trained using local noise), and 0.445 (proposed), respectively, underscoring the significant impact of training data on unwrapping performance. The study also evaluated the performance of the statistical-cost, network-flow algorithm for phase unwrapping (SNAPHU), obtaining mean absolute errors of about 0.043 for simulation data and 0.861 for real SAR data. Consequently, the multi-kernel model trained with locally different noise simulation data demonstrated roughly twice the performance compared to the traditional phase unwrapping method.

RTMS mechanisms for posttraumatic stress disorder treatment in a mouse model

BackgroundPosttraumatic stress disorder (PTSD) is a psychiatric disease that may follow traumatic exposure. Current treatments fail in about 30% of patients. Although repeated transcranial magnetic stimulation (rTMS) applied to the prefrontal cortex has been shown to be effective in the treatment of PTSD, the mechanisms need further investigation. ObjectiveUsing a PTSD animal model, we verify the beneficial effect of rTMS, and explore the changes it induces on two putative PTSD mechanisms, GABA/glutamate neurotransmission and neuroinflammation. MethodsPTSD-like symptoms were elicited in twenty-six mice using a foot-shock conditioning procedure. Fourteen of the 26 were then treated using rTMS (12 were untreated). In the control group (n = 30), 18 were treated with rTMS and 12 were untreated. Animals were sacrificed after re-exposure. The infralimbic (IL) cortex, basolateral amygdala (BLA) and ventral CA1 (vCA1) were isolated using laser microdissection. mRNA was then investigated using PCR array analysis targeting GABA/glutamate and inflammatory pathways. ResultsThe rTMS treatment significantly decreased the contextual fear memory phenotype. These changes were associated with reduced mRNA expression related to inflammation in the IL cortex and the vCA1, and lowered mRNA-related glutamate neurotransmission and increased GABA neurotransmission in the BLA. ConclusionOur results suggest that our rTMS treatment was associated with local anti-inflammatory effects and limbic effects, which seemed to counteract PTSD effects. Several of these changes (both stress- and rTMS-induced) have implications for the drug sensitivity of limbic brain areas, and may help in the design of future therapeutic protocols.

Wilberforce-like Larmor Magnetic Moment and Spin Precession.

In a Wilberforce pendulum, two mechanical oscillators are coupled: one pertains to the longitudinal (tension) motion and the other to the rotational (twisting) motion. It is shown that the longitudinal magnetic moment of circular currents, and similarly the magnetic moment of a spin-chain, can exhibit a Wilberforce-like vibration. The longitudinal oscillation is related to the Langevin diamagnetism, while the twisting motion is superimposed on the magnetic moment and spin precession. The calculations show that the coupling term is nonlinear in this (longitudinal) vibrating and (magnetic moment) precession system. By increasing the strength of the coupling we arrive at a spectrum, where further vibrational modes can be associated with the rotation of the precession. This means that the extent of the change in coherence can be demonstrated. Since the coupling strength can be different due to local effects, this can be an important factor from the point of view of signal propagation and in preserving signal shapes. The amount specifying the dissipation is introduced to express the degree of deviation. A relationship exists between the parameter characteristic of the coupling strength and how its quantity influences decoherence and dissipation.

Synergistic enhancement of singlet oxygen generation in Au and oxygen vacancy co-modified Bi2MoO6 ultrathin nanosheets for efficient ciprofloxacin degradation

Solar-driven molecular oxygen activation (MOA) is crucial for generating reactive oxygen species (ROS) for pollutant degradation, while the low activation efficiency greatly weakens the degradation efficiency. Herein, oxygen vacancies (OVs) and Au nanoparticles are co-introduced into Bi2MoO6 (ABMOH) to enhance the photocatalytic activity of Bi2MoO6 (BMO), thereby promoting MOA efficiency. Density functional theory demonstrates that the introduction of OVs not only improves the molecular oxygen adsorption on BMO, and but also strengthens the O-O bond dissociation of molecular oxygen, which is beneficial to MOA. Meanwhile, the unique localized surface plasmon resonance effect of Au nanoparticles immensely increases the photo-absorption capacity. Crucially, both OVs and Au nanoparticles work as “electron traps” to capture photogenerated electrons, thereby accelerating charge transfer. Based on the advantage of OVs and Au nanoparticles, ABMOH displays excellent MOA efficiency, and the degradation rate constant of ciprofloxacin (CIPF) by ABMOH-4 is 3.62-fold higher than BMO. Free radical trapping experiment and electron spin resonance suggest that singlet oxygen (1O2) can be selectively formed in the ABMOH system for CIPF degradation, and superoxide radical (•O2–) conversion and energy transfer are two pathways for 1O2 formation. This investigation serves as a beacon for the strategic design of high-performance and stable photocatalysts for MOA activation, paving the way for advancements in environmental remediation.

Formulation and evaluation of salicylic acid hydrogel based on hydrotropic solubility enhancement technique

Background and objective: Salicylic acid (SA) has keratolytic activities and it is used topically to treat dandruff and seborrheic dermatitis. The hydrotropic phenomenon in pharmaceutical preparations is utilized to enhance the solubility of water-insoluble drug molecules that promoted to prepare the salicylic acid as a hair gel for local effect and it can extend its keratolytic action for a longer period compared to the salicylic acid solution. Methods: Preformulation study was performed to exclude any unwanted chemical interaction between SA and excipients using Fourier-transform infrared spectroscopy (FTIR). The solubility of SA was determined separately in sodium acetate and sodium citrate solutions at a concentration of 1, 3, and 5 %w/v, using distilled water as a solvent. An optimum gel formulation was developed and it was used to prepare the SA gel formulation. Characterizations were performed in terms of physical appearance, viscosity, pH, and spreadability, in-vitro studies were performed in physiological pH, and ex-vivo diffusion studies were performed utilizing rats’ skin. Results: FTIR did not show any chemical interaction between the drug and sodium citrate. The hydrotropic solution of sodium citrate with a concentration of 5% w/v increased the solubility of SA by 28 folds, while the sodium acetate solutions with a concentration of 5% w/v increased the solubility of SA by 19 folds. The optimum gel formula (F1) with a drug content of 97% showed a slow dissolution rate and minimum diffusion through the skin. Conclusion: The hydrotropic solubilization technique significantly influenced the solubilization of salicylic acid in the water and the highest solubility rate was achieved from 5% w/v sodium citrate solution. The formulated hydrogels using carbopol 971P as gelling agent decreased the diffusion rate of SA.

Prognostic Role of Clinicopathological Characteristics and Serum Markers in Metastatic Melanoma Patients Treated with BRAF and MEK Inhibitors.

A total of 199 patients with advanced melanoma treated with BRAF + MEK inhibitors were included in our single-center retrospective study. We analyzed the risk of progression and death using multivariate Cox proportional hazard models. The predictive effect of prognostic factors on progression-free survival (PFS) was evaluated in ROC analysis. We found that primary tumor localization, Clark level, pT category, baseline M stage and baseline serum S100B are independent and significant prognostic factors for PFS. The discriminative power of the combination of these factors was excellent for predicting 18 month PFS (AUC 0.822 [95% CI 0.727; 0.916], p < 0.001). Primary tumor localization on the extremities, Clark level V, baseline M1c stage or M1d stage, and elevated baseline serum S100B and LDH levels were independently and significantly associated with unfavorable overall survival (OS). Baseline M stage and serum S100B appear to be independent prognostic factors for both PFS and OS in melanoma patients treated with BRAF + MEK inhibitors. We newly identified significant and independent prognostic effects of primary tumor localization and Clark level on survival that warrant further investigation.

Driving a deficient cathodic environment using anode to control selectivity for CO2 electroreduction

The anode has not been extensively studied in electrochemical CO2 reduction reaction (CO2RR) systems because it is believed to have no significant effect on the catalytic selectivity and activity of the cathode. Herein, we report that the anode can indeed influence the catalytic activity of the CO2RR by regulating the transfer of water and ions in a membrane electrode assembly. Despite employing identical cathode conditions, we observed optimal ethylene production at different current densities for distinct anode substrates: carbon paper (CP) and Ti meshes (TM). TM shows optimal ethylene Faradaic efficiency (31.1 %) in the high current density region, while CP demonstrates optimal ethylene Faradaic efficiency (20 %) in the low current density region. Based on the results of in situ/operando analysis and transparent cell tests, CP creates an environment deficient in water and cations, thereby promoting local pH effects. Consequently, this leads to a higher valence state of Cu during the CO2RR, resulting in increased catalytic activity for ethylene production. However, in the high-current-density region, the catalytic activity of CP degrades due to the uneven distribution of the reaction. Our study contributes to a deeper understanding of the reaction environment for CO2RR and offers insights for optimizing the catalytic activity of CO2RR systems.

Conceptual Models for Exploring Sea-Surface Temperature Variability Vis-à Long-Range Weather Forecasting

This paper analyzes the ability of three conceptual stochastic models (one-box, two-box, and diffusion models) to reproduce essential features of sea surface temperature variability on intra-annual time scales. The variability of sea surface temperature, which is particularly influenced by feedback mechanisms in ocean surface–atmosphere coupling processes, is characterized by power spectral density, commonly used to analyze the response of dynamical systems to random forcing. The models are aimed at studying local effects of ocean–atmosphere interactions. Comparing observed and theoretical power spectra shows that in dynamically inactive ocean regions (e.g., north-eastern part of the Pacific Ocean), sea surface temperature variability can be described by linear stochastic models such as one-box and two-box models. In regions of the world ocean (e.g., north-western Pacific Ocean, subtropics of the North Atlantic, the Southern Ocean), in which the observed sea surface temperature spectra on the intra-annual time scales do not obey the ν−2 law (where ν is a regular frequency), the formation mechanisms of sea surface anomalies are mainly determined by ocean circulation rather than by local ocean–atmosphere interactions. The diffusion model can be used for simulating sea surface temperature anomalies in such areas of the global ocean. The models examined are not able to reproduce the variability of sea surface temperature over the entire frequency range for two primary reasons; first, because the object of study, the ocean surface mixed layer, changes during the year, and second, due to the difference in the physics of processes involved at different time scales.

The long-term effects of job training on labor market and skills outcomes in Chile

Job training programs can be an effective policy for improving productivity and labor market outcomes in low- and middle-income countries. We report medium- and long-term impacts of a job training program for vulnerable workers in Chile on labor market and skill outcomes using experimental and administrative data. We estimate intention-to-treat effects, accounting for potential non-compliance by training providers in the assignment process, as well as local average treatment effects due to noncompliance with the assigned treatment status. Overall, the program shows limited effectiveness. While we find some positive impacts on labor income, the program fails to improve most labor outcomes. A detailed investigation of heterogenous effects by course-type, training provider and course quality, and gender reveals that the positive income effects are more likely to be realized for males and participants in courses that were offered by high-quality providers. Evidence on mechanisms indicates that the program's limited impact on labor outcomes could, at least partly, be due to its limited effect on workers’ skills.