Unveiling Direct Electrochemical Oxidation of Methane at the Ceria/Gas Interface.

Solid oxide fuel cells (SOFCs) stand out in sustainable energy systems for their unique ability to efficiently utilize hydrocarbon fuels, particularly those from carbon-neutral sources. CeO2-δ (ceria) based oxides embedded in SOFCs are recognized for their critical role in managing hydrocarbon activation and carbon coking. However, even for the simplest hydrocarbon molecule, CH4, the mechanism of electrochemical oxidation at the ceria/gas interface is not well understood and the capability of ceria to electrochemically oxidize methane remains a topic of debate. This lack of clarity stems from the intricate design of standard metal/oxide composite electrodes and the complex nature of electrode reactions involving multiple chemical and electrochemical steps. This study presents a Sm-doped ceria thin-film model cell that selectively monitors CH4 direct-electro-oxidation on the ceria surface. Using impedance spectroscopy, operando X-ray photoelectron spectroscopy, and density functional theory, it is unveiled that ceria surfaces facilitate C─H bond cleavage and that H2O formation is key in determining the overall reaction rate at the electrode. These insights effectively address the longstanding debate regarding the direct utilization of CH4 in SOFCs. Moreover, these findings pave the way for an optimized electrode design strategy, essential for developing high-performance, environmentally sustainable fuel cells.

Chromatin remodeling-driven autophagy activation induces cisplatin resistance in oral squamous cell carcinoma.

It is still challenging to predict the efficacy of cisplatin-based therapy, particularly in relation to the activation of macroautophagy/autophagy in oral squamous cell carcinoma (OSCC). We studied the effect of selected chromatin remodeling genes on the cisplatin resistance and their interplay with autophagy in 3-dimensional tumor model and xenografts. We analyzed gene expression patterns in the cisplatin-sensitive UMSCC1, and a paired cisplatin-resistant UM-Cis cells. Many histone protein gene clusters involved in nucleosome assembly showed significant difference of expression. Gain- and loss-of-function analyses revealed an inverse correlation between cisplatin resistance and HIST1H3D expression, while a positive correlation was observed with HIST3H2A or HIST3H2B expression. In UM-Cis, HIST3H2A- and HIST3H2B-mediated chromatin remodeling upregulates autophagy status, which results in cisplatin resistance. Additionally, knockdown of HIST3H2A or HIST3H2B downregulated autophagy-activating genes via chromatin compaction of their promoter regions. MiTF, one of the key autophagy regulators upregulated in UM-Cis, negatively regulated transcription of HIST1H3D, suggesting an interplay between chromatin remodeling-dependent cisplatin resistance and autophagy. On comparing the staining intensity between cisplatin-sensitive and -insensitive tissues from OSCC patients, protein expression pattern of the selected histone protein genes were matched with the in vitro data. By examining the relationship between autophagy and chromatin remodeling genes, we identified a set of candidate genes with potential use as markers predicting chemoresistance in OSCC biopsy samples.

Baseline viral load and on-treatment hepatocellular carcinoma risk in chronic hepatitis B: A multinational cohort study.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) risk persists in chronic hepatitis B (CHB) patients despite antiviral therapy. The relationship between pre-treatment baseline hepatitis B virus (HBV) viral load and HCC risk during antiviral treatment remains uncertain. METHODS: This multinational cohort study aimed to investigate the association between baseline HBV viral load and on-treatment HCC risk in 20,826 noncirrhotic, hepatitis B e antigen (HBeAg)-positive and HBeAg-negative patients with baseline HBV DNA levels ≥2,000 IU/mL (3.30 log10 IU/mL) who initiated entecavir or tenofovir treatment. The primary outcome was on-treatment HCC incidence, stratified by baseline HBV viral load as a categorical variable. RESULTS: In total, 663 patients developed HCC over a median follow-up of 4.1 years, with an incidence rate of 0.81 per 100 person-years (95% confidence interval [CI], 0.75-0.87). Baseline HBV viral load was significantly associated with HCC risk in a non-linear parabolic pattern, independent of other factors. Patients with baseline viral load between 6.00 and 7.00 log10 IU/mL had the highest on-treatment HCC risk (adjusted hazard ratio, 4.28; 95% CI, 2.15-8.52; P < .0001) compared to those with baseline viral load ≥8.00 log10 IU/mL, who exhibited the lowest HCC risk. CONCLUSION: Baseline viral load showed a significant, non-linear, parabolic association with HCC risk during antiviral treatment in noncirrhotic CHB patients. Early initiation of antiviral treatment based on HBV viral load may help prevent irreversible HCC risk accumulation in CHB patients.

Triglyceride-Catabolizing Lactiplantibacillus plantarum GBCC_F0227 Shows an Anti-Obesity Effect in a High-Fat-Diet-Induced C57BL/6 Mouse Obesity Model.

Given the recognized involvement of the gut microbiome in the development of obesity, considerable efforts are being made to discover probiotics capable of preventing and managing obesity. In this study, we report the discovery of Lactiplantibacillus plantarum GBCC_F0227, isolated from fermented food, which exhibited superior triglyceride catabolism efficacy compared to L. plantarum WCSF1. Molecular analysis showed elevated expression levels of α/ß hydrolases with lipase activity (abH04, abH08_1, abH08_2, abH11_1, and abH11_2) in L. plantarum GBCC_F0227 compared to L. plantarum WCFS1, demonstrating its enhanced lipolytic activity. In a high-fat-diet (HFD)-induced mouse obesity model, the administration of L. plantarum GBCC_F0227 mitigated weight gain, reduced blood triglycerides, and diminished fat mass. Furthermore, L. plantarum GBCC_F0227 upregulated adiponectin gene expression in adipose tissue, indicative of favorable metabolic modulation, and showed robust growth and low cytotoxicity, underscoring its industrial viability. Therefore, our findings encourage the further investigation of L. plantarum GBCC_F0227's therapeutic applications for the prevention and treatment of obesity and associated metabolic diseases.

How does the consecutive use of intraoral scanners affect musculoskeletal health? A preliminary clinical study.

BACKGROUND: Minimizing muscle strain and reducing the risk of musculoskeletal disorders associated with intraoral scanner (IOS) usage require ergonomic awareness, device selection, and workplace adjustments in dental practice. This preliminary clinical study aimed to simulate intraoral scanning tasks using wired and wireless IOSs and assess muscle activation and fatigue for both types. MATERIALS AND METHODS: Fourteen participants performed intraoral scanning tasks using wired and wireless IOSs (i700; MEDIT), with weights of 280 g and 328 g, respectively. The same computer system and software conditions were maintained for both groups (N = 14 per IOS group). Electrodes were placed on arm, neck, and shoulder muscles, and maximal voluntary contraction (MVC) was measured. Surface electromyography (EMG) was performed during the simulation, and EMG values were normalized using MVC. The root mean square EMG (%MVC) and muscle fatigue (%) values were calculated. Statistical comparisons were performed using the Mann-Whitney U and Friedman tests, with the Bonferroni adjustment for multiple comparisons (α = 0.05). RESULTS: Arm (flexor digitorum superficialis) and neck muscles (left sternocleidomastoid and left splenius capitis) showed significantly higher EMG values with wireless IOS (P < 0.05). The neck (left sternocleidomastoid and right levator scapulae) and shoulder muscles (right trapezius descendens) demonstrated significantly higher muscle fatigue with wireless IOS (P < 0.05). CONCLUSIONS: The consecutive use of heavier wireless IOS may increase the risk of muscle activation and fatigue in certain muscles, which may have clinical implications for dentists in terms of ergonomics and musculoskeletal health.

Revitalizing Oxygen Reduction Reactivity of Composite Oxide Electrodes via Electrochemically Deposited PrOx Nanocatalysts.

Solid oxide fuel cells that operate at intermediate temperatures require efficient catalysts to enhance the inherently poor electrochemical activity of the composite electrodes. Here, a simple and practical electrochemical deposition method is presented for fabricating a PrOx overlayer on lanthanum strontium manganite-yttria-stabilized zirconia (LSM-YSZ) composite electrodes. The method requires less than four minutes for completion and can be carried out under at ambient temperature and pressure. Crucially, the treatment significantly improves the electrode's performance without requiring heat treatment or other supplementary processes. The PrOx-coated LSM-YSZ electrode exhibits an 89% decrease in polarization resistance at 650 °C (compared to an untreated electrode), maintaining a tenfold reduction after ≈400 h. Transmission line model analysis using impedance spectra confirms how PrOx coating improved the oxygen reduction reaction activity. Further, tests with anode-supported single cells reveal an outstanding peak power density compared to those of other LSM-YSZ-based cathodes (e.g., 418 mW cm-2 at 650 °C). Furthermore, it is demonstrated that multicomponent coating, such as (Pr,Ce)Ox, can also be obtained with this method. Overall, the observations offer a promising route for the development of high-performance solid oxide fuel cells.

Chronic hepatitis B baseline viral load and on-treatment liver cancer risk: A multinational cohort study of HBeAg-positive patients.

BACKGROUND AND AIMS: A single-nation study reported that pretreatment HBV viral load is associated with on-treatment risk of HCC in patients who are HBeAg-positive without cirrhosis and with chronic hepatitis B initiating antiviral treatment. We aimed to validate the association between baseline HBV viral load and on-treatment HCC risk in a larger, multinational cohort. APPROACH AND RESULTS: Using a multinational cohort from Korea, Hong Kong, and Taiwan involving 7545 adult patients with HBeAg-positive, without cirrhosis and with chronic hepatitis B who started entecavir or tenofovir treatment with baseline HBV viral load ≥5.00 log 10 IU/mL, HCC risk was estimated by baseline viral load. HBV viral load was analyzed as a categorical variable. During continuous antiviral treatment (median, 4.28 y), HCC developed in 200 patients (incidence rate, 0.61 per 100 person-years). Baseline HBV DNA level was independently associated with on-treatment HCC risk in a nonlinear pattern. HCC risk was lowest with the highest baseline viral load (≥8.00 log 10 IU/mL; incidence rate, 0.10 per 100 person-years), but increased sharply as baseline viral load decreased. The adjusted HCC risk was 8.05 times higher (95% CI, 3.34-19.35) with baseline viral load ≥6.00 and <7.00 log 10 IU/mL (incidence rate, 1.38 per 100 person-years) compared with high (≥8.00 log 10 IU/mL) baseline viral load ( p <0.001). CONCLUSIONS: In a multinational cohort of adult patients with HBeAg-positive without cirrhosis and with chronic hepatitis B, baseline HBV viral load was significantly associated with HCC risk despite antiviral treatment. Patients with the highest viral load who initiated treatment had the lowest long-term risk of HCC development.

sEMG-based Sarcopenia risk classification using empirical mode decomposition and machine learning algorithms.

Early detection of the risk of sarcopenia at younger ages is crucial for implementing preventive strategies, fostering healthy muscle development, and minimizing the negative impact of sarcopenia on health and aging. In this study, we propose a novel sarcopenia risk detection technique that combines surface electromyography (sEMG) signals and empirical mode decomposition (EMD) with machine learning algorithms. First, we recorded and preprocessed sEMG data from both healthy and at-risk individuals during various physical activities, including normal walking, fast walking, performing a standard squat, and performing a wide squat. Next, electromyography (EMG) features were extracted from a normalized EMG and its intrinsic mode functions (IMFs) were obtained through EMD. Subsequently, a minimum redundancy maximum relevance (mRMR) feature selection method was employed to identify the most influential subset of features. Finally, the performances of state-of-the-art machine learning (ML) classifiers were evaluated using a leave-one-subject-out cross-validation technique, and the effectiveness of the classifiers for sarcopenia risk classification was assessed through various performance metrics. The proposed method shows a high accuracy, with accuracy rates of 0.88 for normal walking, 0.89 for fast walking, 0.81 for a standard squat, and 0.80 for a wide squat, providing reliable identification of sarcopenia risk during physical activities. Beyond early sarcopenia risk detection, this sEMG-EMD-ML system offers practical values for assessing muscle function, muscle health monitoring, and managing muscle quality for an improved daily life and well-being.

The Differential Effects of Multisensory Attentional Cues on Task Performance in VR Depending on the Level of Cognitive Load and Cognitive Capacity.

As the utilization of VR is expanding across diverse fields, research on devising attentional cues that could optimize users' task performance in VR has become crucial. Since the cognitive load imposed by the context and the individual's cognitive capacity are representative factors that are known to determine task performance, we aimed to examine how the effects of multisensory attentional cues on task performance are modulated by the two factors. For this purpose, we designed a new experimental paradigm in which participants engaged in dual (N-back, visual search) tasks under different levels of cognitive load while an attentional cue (visual, tactile, or visuotactile) was presented to facilitate search performance. The results showed that multi-sensory attentional cues are generally more effective than uni-sensory cues in enhancing task performance, but the benefit of multi-sensory cues changes according to the level of cognitive load and the individual's cognitive capacity; the amount of benefit increases as the cognitive load is higher and the cognitive capacity is lower. The findings of this study provide practical implications for designing attentional cues to enhance VR task performance, considering both the complexity of the VR context and users' internal characteristics.

Difference of Microbial Community in the Stream Adjacent to the Mixed Antibiotic Effluent Source.

Released antibiotics from source to stream can influence bacterial communities and potentially alter the ecosystem. This research provides a comprehensive examination of the sources, distribution, and bacterial community dynamics associated with varied antibiotic release sources adjacent to the stream. The residual of antibiotics from different sources was determined, and the bacterial community structure was examined to reveal the differences in the bacteria community in the stream. The residual of antibiotics was quantified with liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the Illumina MiSeq platform was utilized to sequence bacterial 16S rRNA genes, providing comprehensive insights into the bacterial community structure in the sediment across five different sites. Results indicated that the presence and distribution of antibiotics were significantly influenced by released sources. In the case of the bacterial community, the Proteobacteria and Firmicutes were the most dominant phyla in the sediment, and especially, the Firmicutes showed higher abundance in sites mostly affected by livestock sources. Additionally, livestock gut bacteria such as Clostridium saudiense, Proteiniclasticum ruminis, and Turicibacter sanguinis were prevalent in antibiotic-contaminated sites adjacent to livestock facilities. Overall, this study provides critical insights into the effect of antibiotic contamination by verifying the relationship between the occurrence of antibiotic residuals and the alteration in the bacterial community in the stream.

Differential effect of cancer-associated fibroblast-derived extracellular vesicles on cisplatin resistance in oral squamous cell carcinoma via miR-876-3p.

Rationale: Platinum-based chemotherapy is commonly used for treating solid tumors, but drug resistance often limits its effectiveness. Cancer-associated fibroblast (CAF)-derived extracellular vesicle (EV), which carry various miRNAs, have been implicated in chemotherapy resistance. However, the molecular mechanism through which CAFs modulate cisplatin resistance in oral squamous cell carcinoma (OSCC) is not well understood. We employed two distinct primary CAF types with differential impacts on cancer progression: CAF-P, representing a more aggressive cancer-promoting category, and CAF-D, characterized by properties that moderately delay cancer progression. Consequently, we sought to investigate whether the two CAF types differentially affect cisplatin sensitivity and the underlying molecular mechanism. Methods: The secretion profile was examined by utilizing an antibody microarray with conditioned medium obtained from the co-culture of OSCC cells and two types of primary CAFs. The effect of CAF-dependent factors on cisplatin resistance was investigated by utilizing conditioned media (CM) and extracellular vesicle (EVs) derived from CAFs. The impacts of candidate genes were confirmed using gain- and loss-of-function analyses in spheroids and organoids, and a mouse xenograft. Lastly, we compared the expression pattern of the candidate genes in tissues from OSCC patients exhibiting different responses to cisplatin. Results: When OSCC cells were cultured with conditioned media (CM) from the two different CAF groups, cisplatin resistance increased only under CAF-P CM. OSCC cells specifically expressed insulin-like growth factor binding protein 3 (IGFBP3) after co-culture with CAF-D. Meanwhile, IGFBP3-knockdown OSCC cells acquired cisplatin resistance in CAF-D CM. IGFBP3 expression was promoted by GATA-binding protein 1 (GATA1), a transcription factor targeted by miR-876-3p, which was enriched only in CAF-P-derived EV. Treatment with CAF-P EV carrying miR-876-3p antagomir decreased cisplatin resistance compared to control miRNA-carrying CAF-P EV. On comparing the staining intensity between cisplatin-sensitive and -insensitive tissues from OSCC patients, there was a positive correlation between IGFBP3 and GATA1 expression and cisplatin sensitivity in OSCC tissues from patients. Conclusion: These results provide insights for overcoming cisplatin resistance, especially concerning EVs within the tumor microenvironment. Furthermore, it is anticipated that the expression levels of GATA1 and miR-876-3p, along with IGFBP3, could aid in the prediction of cisplatin resistance.

Multiregional analysis of combined hepatocellular-cholangiocarcinoma reveals histologic diversity and molecular clonality.

Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare type of liver tumour that exhibits both hepatocytic and biliary differentiation within the same tumour. The histology and genomic alterations of recurrent/metastatic cHCC-CC are poorly understood. We selected six patients with cHCC-CC whose recurrent or metastatic tumours were histologically confirmed. Four patients with classic cHCC-CCs and two with intermediate cell carcinomas (ICs) were included. The clinicopathological features were evaluated, and next-generation sequencing was performed in 17 multiregional and longitudinal tumour samples. The histology of recurrent/metastatic lesions of classic cHCC-CCs was variable: hepatocellular carcinoma (HCC) was observed in one (25.0%) patient, cHCC-CC in one (25.0%) patient, and cholangiocarcinoma (CC) in two (50.0%) patients. Among 13 samples from four classic cHCC-CC patients, the most frequent pathological variants were TP53 (46.2%), TERT promoter (38.5%), ARID1A mutations (23.1%), and MET amplification (30.8%). In the sequencing analysis of each HCC and CC component, three (75.0%) of the four classic cHCC-CCs shared pathogenic variants. A large proportion of mutations, both pathogenic and those of undetermined significance, were shared by each HCC and CC component. Regarding ICs, the ATM mutation was detected in one patient. In conclusion, the histology of recurrent/metastatic cHCC-CCs was heterogeneous. Genomic profiling of classic cHCC-CCs revealed similar genomic alterations to those of HCC. Considerable overlapping genomic alterations in each HCC and CC component were observed, suggesting a monoclonal origin. Genetic alterations in ICs were different from those in either HCC or CC, suggesting the distinct nature of this tumour.

Machine learning-based classification and risk factor analysis of frailty in Korean community-dwelling older adults.

Frailty is a dynamic reversible state, characterized by frequent transitions between frailty status over time. The timely and effective detection of frailty is important to prevent adverse health outcomes. This study aims to develop machine learning-based classification models for frailty assessment and to investigate its risk factors. A total of 1,482 subjects, 1,266 robust and 216 frail older adults, were analyzed. Sixteen frail risk factors were selected from a random forest-based feature selection method, then used for the inputs of five ML models: logistic regression, K-nearest neighbor, support vector machine, gaussian naïve bayes, and random forest. Data resampling, stratified 10-fold cross-validation, and grid search were applied to improve the classification performance. The logistic regression model using the selected features showed the best performance with an accuracy of 0.93 and an F1-score of 0.92. The results suggest that machine learning techniques are an effective method for classifying frailty status and exploring frailty-related factors.Clinical Relevance- Our approach can predict frailty using data collectable in clinical setting and can help prevent and improve by identifying variables that change frailty status.

Image-based Gait Spatiotemporal Parameters Estimation using a Single Camera and CNN-Transformer Hybrid Network.

Vision-based gait analysis can play an important role in the remote and continuous monitoring of the elderly's health conditions. However, most vision-based approaches compute gait spatiotemporal parameters using human pose information and provide average parameters. This study aimed to propose a straightforward method for stride-by-stride gait spatiotemporal parameters estimation. A total of 160 elderly individuals participated in this study. Data were gathered with a GAITRite system and a mobile camera simultaneously. Three deep learning networks were trained with a few RGB frames as input and a continuous 1D signal containing both spatial and temporal gait parameters as output. The trained networks estimated the stride lengths with correlations of 0.938 and more and detected gait events with F1-scores of 0.914 and more.Clinical relevance- The proposed method showed excellent agreements with the GAITRite system in analyzing spatiotemporal gait parameters. Our approach can be applied to monitor the elderly's health conditions based on their gait parameters for early diagnosis of diseases, proper treatment, and timely intervention.

Hepatic hemangioma: proportion and predictor of surgical treatment with emphasis on its growth rate.

BACKGROUND/AIMS: There are limited studies on the management of hepatic hemangiomas (HHs). We investigated the proportion and predictors of surgical resection and analyzed HH growth rates in addition to associated factors. METHODS: A retrospective case-control study of patients treated in 2 centers was conducted. Thirty-six patients who underwent surgical resection were assigned to the case group. Patients who did not undergo surgical treatment were randomly sigselected at a 1:10 ratio and assigned to the control group (n = 360). Baseline characteristics, clinical course and surgical outcomes were analyzed. RESULTS: The proportion of surgically treated HH patients was 0.3% (36 per 11,049). The longest diameter at diagnosis (mean ± standard deviation) was 7.7 ± 5.2 cm in the case group and 2.4 ± 1.8 cm in the control group (p < 0.001). In the multivariate analysis, the presence of more than 2 HHs (odds ratio [OR] 7.64, 95% confidence interval [CI] 1.40-41.72) and a growth rate of more than 4.8%/year (OR 30.73, 95% CI 4.86-194.51) were independently associated with surgical treatment. Symptom development during follow-up was related to HH size > 10 cm (OR 10.50, 95% CI 1.06-103.77, p = 0.04). The subgroup analysis showed substantial growth in 41.3% with an overall mean annual growth rate of 0.14 cm. CONCLUSION: Approximately one in 300 patients with an HH underwent surgical treatment. Multiple HHs and a growth rate of more than 4.8%/year were indications for surgical treatment. Nearly half of the HHs showed growing pattern in our study.

View-independent gait events detection using CNN-transformer hybrid network.

Accurate gait detection is crucial in utilizing the ample health information embedded in it. Vision-based approaches for gait detection have emerged as an alternative to the exacting sensor-based approaches, but their application has been rather limited due to complicated feature engineering processes and heavy reliance on lateral views. Thus, this study aimed to find a simple vision-based approach that is view-independent and accurate. A total of 22 participants performed six different actions representing standard and peculiar gaits, and the videos acquired from these actions were used as the input of the deep learning networks. Four networks, including a 2D convolutional neural network and an attention-based deep learning network, were trained with standard gaits, and their detection performance for both standard and peculiar gaits was assessed using measures including F1-scores. While all networks achieved remarkable detection performance, the CNN-Transformer network achieved the best performance for both standard and peculiar gaits. Little deviation by the speed of actions or view angles was found. The study is expected to contribute to the wider application of vision-based approaches in gait detection and gait-based health monitoring both at home and in clinical settings.

Effects of Reward Schedule and Avatar Visibility on Joint Agency During VR Collaboration.

Joint agency, a group-level sense of agency, has been studied as an essential social cognitive element while engaging in collaborative tasks. The joint agency has been actively investigated in diverse contexts (e.g., performance, reward schedules, and predictability), yet the studies were mostly conducted in traditional 2D computer environments. Since virtual reality (VR) is an emerging technology for remote collaboration, we aimed to probe the effects of traditional reward schedule factors along with novel VR features (i.e., avatar visibility) on joint agency during remote collaboration. In this study, we implemented an experiment based on a card-matching game to test the effects of the reward schedule (fair or equal) and the counterpart's avatar hand visibility (absent or present) on the sense of joint agency. The results showed that participants felt a higher sense of joint agency when the reward was distributed equally regardless of the individual performance and when the counterpart's avatar hand was present. Moreover, the effects of reward schedule and avatar hand visibility interacted, with a bigger amount of deficit for the absent avatar hand when the reward was distributed differentially according to performance. Interestingly, the sense of joint agency was strongly correlated to the level of collaborative performance, as well as to perceptions of other social cognitive factors, including cooperativeness, reward fairness, and social presence. These results contribute to the understanding of joint agency perceptions during VR collaboration and provide design guidelines for remote collaborative tasks and environments for users' optimal social experience and performance.

Molecular Insights into Abiotic Stresses in Mango.

Mango (Mangifera indica L.) is one of the most economically important fruit crops across the world, mainly in the tropics and subtropics of Asia, Africa, and Central and South America. Abiotic stresses are the prominent hindrance that can adversely affect the growth, development, and significant yield loss of mango trees. Understanding the molecular physiological mechanisms underlying abiotic stress responses in mango is highly intricate. Therefore, to gain insights into the molecular basis and to alleviate the abiotic stress responses to enhance the yield in the mere future, the use of high-throughput frontier approaches should be tied along with the baseline investigations. Taking these gaps into account, this comprehensive review mainly speculates to provide detailed mechanisms and impacts on physiological and biochemical alterations in mango under abiotic stress responses. In addition, the review emphasizes the promising omics approaches in unraveling the candidate genes and transcription factors (TFs) responsible for abiotic stresses. Furthermore, this review also summarizes the role of different types of biostimulants in improving the abiotic stress responses in mango. These studies can be undertaken to recognize the roadblocks and avenues for enhancing abiotic stress tolerance in mango cultivars. Potential investigations pointed out the implementation of powerful and essential tools to uncover novel insights and approaches to integrate the existing literature and advancements to decipher the abiotic stress mechanisms in mango. Furthermore, this review serves as a notable pioneer for researchers working on mango stress physiology using integrative approaches.

A 3-month survival model after Gamma Knife surgery in patients with brain metastasis from lung cancer with Karnofsky performance status ≤ 70.

Gamma Knife surgery (GKS) for brain metastasis (BM) has been generally advocated for patients with a Karnofsky performance status (KPS) scale of ≥ 70. However, some patients with a poor KPS scale of < 70 are recoverable after GKS and show durable survival. A purpose of this study is to devise a 3-month survival prediction model to screen patients with BM with a KPS of ≤ 70 in whom GKS is needed. A retrospective analysis of 67 patients with a KPS scale of 60-70 undergoing GKS for BM of non-small cell lung cancer (NSCLC) from 2016 to 2020 in our institute was performed. Univariate and multivariate logistic regression analyses were performed to investigate factors related to survival for more than 3 months after GKS. The probability (P) prediction model was designed by giving a weight corresponding to the odds ratio of the variables. The overall survival was 9.9 ± 12.7 months (range 0.2-53.2), with a 3-month survival rate of 59.7% (n = 40). In multivariate logistic regression analysis, extracranial disease (ECD) control (p = .033), focal neurological deficit (FND) (p = .014), and cumulative tumor volume (∑ TV) (p = .005) were associated with 3-month survival. The prediction model of 3-month survival (Harrell's C index = 0.767) was devised based on associated factors. In conclusion, GKS for BMs is recommended in selected patients, even if the KPS scale is ≤ 70.