Immune signature and therapeutic approach of natural killer cell in chronic liver disease and hepatocellular carcinoma.

Natural killer (NK) cells are one of the key members of innate immunity that predominantly reside in the liver, potentiating immune responses against viral infections or malignant tumors. It has been reported that changes in cell numbers and function of NK cells are associated with the development and progression of chronic liver diseases (CLDs) including non-alcoholic fatty liver disease, alcoholic liver disease, and chronic viral hepatitis. Also, it is known that the crosstalk between NK cells and hepatic stellate cells plays an important role in liver fibrosis and cirrhosis. In particular, the impaired functions of NK cells observed in CLDs consequently contribute to occurrence and progression of hepatocellular carcinoma (HCC). Chronic infections by hepatitis B or C viruses counteract the anti-tumor immunity of the host by producing the sheddases. Soluble major histocompatibility complex class I polypeptide-related sequence A (sMICA), released from the cell surfaces by sheddases, disrupts the interaction and affects the function of NK cells. Recently, the MICA/B-NK stimulatory receptor NK group 2 member D (NKG2D) axis has been extensively studied in HCC. HCC patients with low membrane-bound MICA or high sMICA concentration have been associated with poor prognosis. Therefore, reversing the sMICA-mediated downregulation of NKG2D has been proposed as an attractive strategy to enhance both innate and adaptive immune responses against HCC. This review aims to summarize recent studies on NK cell immune signatures and its roles in CLD and hepatocellular carcinogenesis and discusses the therapeutic approaches of MICA/B-NKG2D-based or NK cell-based immunotherapy for HCC.

Mitochondrial dysfunction in adult midbrain dopamine neurons triggers an early immune response.

Dopamine (DA) neurons of the midbrain are at risk to become affected by mitochondrial damage over time and mitochondrial defects have been frequently reported in Parkinson's disease (PD) patients. However, the causal contribution of adult-onset mitochondrial dysfunction to PD remains uncertain. Here, we developed a mouse model lacking Mitofusin 2 (MFN2), a key regulator of mitochondrial network homeostasis, in adult midbrain DA neurons. The knockout mice develop severe and progressive DA neuron-specific mitochondrial dysfunction resulting in neurodegeneration and parkinsonism. To gain further insights into pathophysiological events, we performed transcriptomic analyses of isolated DA neurons and found that mitochondrial dysfunction triggers an early onset immune response, which precedes mitochondrial swelling, mtDNA depletion, respiratory chain deficiency and cell death. Our experiments show that the immune response is an early pathological event when mitochondrial dysfunction is induced in adult midbrain DA neurons and that neuronal death may be promoted non-cell autonomously by the cross-talk and activation of surrounding glial cells.

A nonsense TMEM43 variant leads to disruption of connexin-linked function and autosomal dominant auditory neuropathy spectrum disorder.

Genes that are primarily expressed in cochlear glia-like supporting cells (GLSs) have not been clearly associated with progressive deafness. Herein, we present a deafness locus mapped to chromosome 3p25.1 and an auditory neuropathy spectrum disorder (ANSD) gene, TMEM43, mainly expressed in GLSs. We identify p.(Arg372Ter) of TMEM43 by linkage analysis and exome sequencing in two large Asian families segregating ANSD, which is characterized by inability to discriminate speech despite preserved sensitivity to sound. The knock-in mouse with the p.(Arg372Ter) variant recapitulates a progressive hearing loss with histological abnormalities in GLSs. Mechanistically, TMEM43 interacts with the Connexin26 and Connexin30 gap junction channels, disrupting the passive conductance current in GLSs in a dominant-negative fashion when the p.(Arg372Ter) variant is introduced. Based on these mechanistic insights, cochlear implant was performed on three subjects, and speech discrimination was successfully restored. Our study highlights a pathological role of cochlear GLSs by identifying a deafness gene and its causal relationship with ANSD.

Realization of a 594 Wh kg-1 Lithium-Metal Battery Using a Lithium-Free V2 O5 Cathode with Enhanced Performances by Nanoarchitecturing.

To realize a high-energy lithium metal battery (LMB) using a high-capacity Li-free cathode, in this work, nanoplate-stacked V2 O5 with dominantly exposed (010) facets and a relatively short [010] length is proposed to be used as a cathode. The V2 O5 nanostructure can be fabricated via a modified hydrothermal method, including a Li+ crystallization inhibitor, followed by heat treatment. In particular, the enlargement of the favorable Li+ diffusion pathway in the [010] direction and the formation of a robust hierarchical nanoplate-stacked structure in the modified V2 O5 improves the electrochemical kinetics and stability; as a result, the nanoplate-stacked V2 O5 electrode exhibits a higher capacity and rate performance (258 mAh g-1 at 50 mA g-1 [0.17 C], 140 mAh g-1 at 1 A g-1 [3.4 C]) and cycling capability (79% capacity retention after 100 cycles at 0.5 C) compared to the previously reported V2 O5 nanobelt electrode. Notably, the LMB composed of Li//nanoplate-stacked V2 O5 full-cells shows high specific energy densities of 594.1 and 296.2 Wh kg-1 at 0.1 and 1.0 C, respectively, and a high Coulombic efficiency of 99.6% during 50 cycles.

Advancing diagnostic efficacy using a computer vision-assisted lateral flow assay for influenza and SARS-CoV-2 detection.

Lateral flow assays (LFAs) have emerged as indispensable tools for point-of-care testing during the pandemic era. However, the interpretation of results through unassisted visual inspection by untrained individuals poses inherent limitations. In our study, we propose a novel approach that combines computer vision (CV) and lightweight machine learning (ML) to overcome these limitations and significantly enhance the performance of LFAs. By incorporating CV-assisted analysis into the LFA assay, we achieved a remarkable three-fold improvement in analytical sensitivity for detecting Influenza A and for SARS-CoV-2 detection. The obtained R2 values reached approximately 0.95, respectively, demonstrating the effectiveness of our approach. Moreover, the integration of CV techniques with LFAs resulted in a substantial amplification of the colorimetric signal specifically for COVID-19 positive patient samples. Our proposed approach, which incorporates a simple machine learning algorithm, provides substantial enhancements in assay sensitivity, improving diagnostic efficacy and accessibility of point-of-care testing without requiring significant additional resources. Moreover, the simplicity of the machine learning algorithm enables its standalone use on a mobile phone, further enhancing its practicality for point-of-care testing.

Convergence of Phase-Averaged, Transitional Flow in an Abdominal Aortic Aneurysmal Model.

Abdominal aortic aneurysm can exhibit transitional flow characteristics in laminar flow regimes. To report transitional flow characteristics, we examined the convergence of phase-averaged solutions by executing blood flow simulations of a patient-specific abdominal aortic aneurysmal model for 257 cardiac cycles with periodic, pulsatile boundary conditions. The phase-averaged solutions were computed by averaging the solutions over various numbers of cardiac cycles and compared against the ones averaged over 124 cycles. The phase-averaged solutions reported small differences when they were averaged over a large number of cardiac cycles. The instantaneous solutions, however, failed to exhibit fluctuations reported in the phase-averaged solutions. To study transitional blood flows in the aneurysmal region, we need to report phase-averaged solutions as they exhibit nonperiodic, disturbed flow characteristics. Additionally, when reporting phase-averaged solutions, it is preferred to compute an average over a large number of cardiac cycles to be able to represent flow structures of the converged phase-averaged solutions.

Aerial part of Houttuynia cordata reverses memory impairment by regulating amyloid beta accumulation and neuroinflammation in Alzheimer's disease model.

Alzheimer's disease (AD) is the most common neurodegenerative disease characterized by amyloid-ß (Aß) deposition, accompanied by neuroinflammation and memory dysfunction. Houttuyniae Herba (aerial parts of Houttuynia cordata, also known as fish mint; HH), an herbal medicine traditionally used to treat fever, urinary disorders, and pus, is revealed to protect neurons from Aß toxicity and regulate cholinergic dysfunction in AD models. In this study, we aimed to investigate the effects of HH on excessive accumulation of Aß followed by neuroinflammation, synaptic degeneration, and memory impairment. Two-month-old 5xFAD transgenic mice were administered HH at 100 mg/kg for 4 months. We observed that HH treatment ameliorated memory impairment and reduced Aß deposits in the brains of the mice. HH directly inhibited Aß aggregation in vitro using the Thioflavin T assay and indirectly suppressed the amyloidogenic pathway by increasing alpha-secretase expression in the mice brain. In addition, HH exerted antineuroinflammatory effects by reducing of glial activation and p38 phosphorylation. Moreover, HH treatment increased the expression of synaptophysin, a presynaptic marker protein. Overall, HH alleviates memory impairment in AD by facilitating nonamyloidogenic pathway and inhibiting neuroinflammation. Therefore, we suggest that HH can be a promising herbal drug for patients with AD requiring multifaceted improvement.

Mechanisms by Which the Fun for Wellness Intervention May Promote Subjective Well-Being in Adults with Obesity: a Reanalysis Using Baseline Target Moderation.

Fun For Wellness (FFW) is a self-efficacy theory-based online behavioral intervention that aims to promote growth in physical activity and well-being. The FFW conceptual model for the promotion of subjective well-being posits that FFW exerts both a positive direct effect, and a positive indirect effect through well-being self-efficacy, on subjective well-being. Subjective well-being is defined in FFW as an individual's satisfaction with their status in seven key domains of their life. Well-being self-efficacy is defined in FFW as the degree to which an individual perceives that they have the capability to attain a positive status in seven key domains of their life. The objective of this study was to use baseline target moderation to assess variation in the impact of FFW on subjective well-being dimensions in adults with obesity. Data (N = 667) from the Well-Being and Physical Activity Study (ClinicalTrials.gov, identifier: NCT03194854) were reanalyzed. There was evidence that well-being self-efficacy at baseline moderated the direct effect of FFW on well-being self-efficacy at 30 days post-baseline for the occupational and psychological dimensions. Both of these findings suggest a "compensatory" effect. Similarly, there was evidence that well-being self-efficacy at baseline moderated the indirect effect of FFW on subjective well-being at 60 days post-baseline through well-being self-efficacy at 30 days post-baseline for the occupational and psychological dimensions. Both of these findings suggest a "compensatory" effect. Finally, there was evidence that well-being self-efficacy at baseline moderated the direct effect of FFW on subjective well-being at 60 days post-baseline for the community, occupational, and physical dimensions. Each of these three findings suggests some version of a "rich-get-richer" effect. In summary, results provide both supportive and unsupportive (i.e., interpersonal, economic, and overall dimensions) evidence regarding variation in the impact of the FFW intervention and should impact the design of future FFW trials.

A Systematic Review of eHealth Interventions to Promote Physical Activity in Adults with Obesity or Overweight.

Use of information and communication technology to improve health, known as eHealth, is an emerging concept in healthcare that may present opportunities to promote physical activity in adults with obesity. The purpose of this research was to systematically review eHealth intervention studies to promote physical activity in adults with obesity. Five electronic databases were used. Two authors screened articles, assessed risk of bias, and extracted data independently. A qualitative data synthesis for summarizing the findings was performed using harvest plots. In the search, 2276 articles were identified, and 18 studies met all inclusion criteria. Study quality ranged from poor to good. The included studies varied in intervention technology (e.g., web-based), physical activity assessment (e.g., device-based), and control group (e.g., wait-list). Behavioral change techniques used in the included studies were consistent with some techniques (e.g., self-monitoring) known as effective in face-to-face interventions, but more efficiently employed in eHealth using information and communication technology. Overall, this systematic review showed that a web-based or physical activity monitor-based eHealth intervention had the potential to effectively promote physical activity in adults with obesity. Some recommendations for future eHealth interventions to promote physical activity in adults with obesity were provided (e.g., use of theory, accelerometers).

Optimized Replication of ADC-Based Particle Counting Algorithm with Reconfigurable Multi-Variables in Pseudo-Supervised Digital Twining of Reference Dust Sensor Systems.

As the application fields for digital twins have expanded, various studies have been conducted with the objective of optimizing the costs. Among these studies, research on low-power and low-performance embedded devices has been implemented at a low cost by replicating the performance of existing devices. In this study, we attempt to obtain similar particle count results in a single-sensing device replicated from the particle count results in a multi-sensing device without knowledge of the particle count acquisition algorithm of the multi-sensing device. Through filtering, we suppressed the noise and baseline movements of the raw data of the device. In addition, in the process of determining the multi-threshold for obtaining the particle counts, the existing complex particle count determination algorithm was simplified to make it possible to utilize the look-up table. The proposed simplified particle count calculation algorithm reduced the optimal multi-threshold search time by 87% on average and the root mean square error by 58.5% compared to existing method. In addition, it was confirmed that the distribution of particle count from optimal multi-thresholds has a similar shape to that from multi-sensing devices.

miR-431 promotes differentiation and regeneration of old skeletal muscle by targeting Smad4.

The myogenic capacity of myoblasts decreases in skeletal muscle with age. In addition to environmental factors, intrinsic factors are important for maintaining the regenerative potential of muscle progenitor cells, but their identities are largely unknown. Here, comparative analysis of microRNA (miRNA) expression profiles in young and old myoblasts uncovered miR-431 as a novel miRNA showing markedly reduced abundance in aged myoblasts. Importantly, elevating miR-431 improved the myogenic capacity of old myoblasts, while inhibiting endogenous miR-431 lowered myogenesis. Bioinformatic and biochemical analyses revealed that miR-431 directly interacted with the 3' untranslated region (UTR) of Smad4 mRNA, which encodes one of the downstream effectors of TGF-ß signaling. In keeping with the low levels of miR-431 in old myoblasts, SMAD4 levels increased in this myoblast population. Interestingly, in an in vivo model of muscle regeneration following cardiotoxin injury, ectopic miR-431 injection greatly improved muscle regeneration and reduced SMAD4 levels. Consistent with the finding that the mouse miR-431 seed sequence in the Smad4 3' UTR is conserved in the human SMAD4 3' UTR, inhibition of miR-431 also repressed the myogenic capacity of human skeletal myoblasts. Taken together, our results suggest that the age-associated miR-431 plays a key role in maintaining the myogenic ability of skeletal muscle with age.

Alverine citrate promotes myogenic differentiation and ameliorates muscle atrophy.

Sarcopenia is the age-related loss of muscle mass and function and no pharmacological medication has been approved for its treatment. We established an atrogin-1/MAFbx promoter assay to find drug candidates that inhibit myotube atrophy. Alverine citrate (AC) was identified using high-throughput screening of an existing drug library. AC is an established medicine for stomach and intestinal spasms. AC treatment increased myotube diameter and inhibited atrophy signals induced by either C26-conditioned medium or dexamethasone in cultured C2C12 myoblasts. AC also enhanced myoblast fusion through the upregulation of fusion-related genes during C2C12 myoblast differentiation. Oral administration of AC improves muscle mass and physical performance in aged mice, as well as hindlimb-disused mice. Taken together, our data suggest that AC may be a novel therapeutic candidate for improving muscle weakness, including sarcopenia.

All-Gas-Phase Synthesis of Heterolayered Two-Dimensional Nanohybrids Decorated with Metallic Nanocatalysts for Water Splitting.

Herein, a sequential gas-phase process involving air jet milling followed by chemical vapor deposition (CVD), is demonstrated to be an efficient strategy for the fabrication of heterolayered 2D nanohybrids (2DNHs) decorated with nanocatalysts. Tens of grams of the nanohybrids, which is a substantial quantity at the laboratory scale, are produced in the absence of solvents and water, and without the need for an extra purification procedure. Air jet milling enables the development of binary/ternary heterolayered structures consisting of graphene, WSe2 , and/or MoS2 via the gas-phase co-exfoliation of their bulk counterparts. Based on the X-ray photoelectron and Raman spectroscopy data, the heterolayers of the 2DNHs exert chemical and electronic effects on each other, while diminishing the interactions between same-component layers. Moreover, the electrochemically active surface area increases by >190% and the charge transfer resistance decreases by >35%. CVD is performed to introduce Pt and Ru nanoparticles with diameters of a few nanometers as additional electrocatalysts into the 2DNHs. The nanocatalyst-decorated 2DNHs show excellent performance for the production of hydrogen and oxygen gases in water-splitting cells. Notably, the proposed all-gas-phase processes allow for the large-scale production of functional 2DNHs with minimal negative environmental impact, which is crucial for the commercialization of nanomaterials.

COVID-19 Sequelae and Their Implications on Social Services.

BACKGROUND: The impact of persistent coronavirus disease 2019 (COVID-19) symptoms on quality of life remains unclear. This study aimed to describe such persistent symptoms and their relationships with quality of life, including clinical frailty and subjective health status. METHODS: A prospective longitudinal 3-month follow-up survey monitored symptoms, health quality, support needs, frailty, and employment. RESULTS: A total of 82 patients with a mean age of 52 years (ranging from 23-84 years) were enrolled, including 48 (58.6%) men, and 34 (41.5%) women. The fully active status decreased from 87.8% before admission to 78.1% post discharge. Two patients (2.4%) were ambulatory and capable of all self-care but unable to carry out any work-related activities 12 weeks after discharge. Clinical frailty scale (CFS) levels 1, 2, 3 and 4 changed drastically between admission and 12 weeks later after discharge. Just after admission, the median EuroQol visual analogue scales (EQ-VAS) was 82.23 (± 14.38), and it decreased to 78.10 (± 16.02) 12 weeks after discharge; 62 (75.6%) of patients reported at least one symptom 12 weeks after discharge. The most frequent symptom was fatigue followed by smell disorder, anxiety, sleep disorder, headache, depressive mood, dyspnea, and taste disorder. CFS was definitively associated with fatigue. Decreased EQ-VAS was associated with fatigue and palpitation, cough, taste disorder, and chest pain. EQ-VAS was worse in women (28%) than in men. Compared with regular outpatient clinic visits before admission, 21 patients (25.6%) reported increased outpatient clinic visits, one (1.4%) reported readmission, and one (1.4%) reported emergency room visits. Six of the 54 (77.1%) patients who were employed before admission lost their jobs. And most vulnerable type was self-employed, because three self-employed job workers were not working at 12 weeks after discharge. CONCLUSION: COVID-19 sequelae should not be underestimated. We find a decrease in health quality and increase in psychological problems in discharged COVID-19 patients, and some patients experience unemployment. The number of patients suffering from COVID-19 sequelae would not be negligible considering there are more than one million COVID-19 infection cases in Korea. Hence, the government should start a systematic monitoring system for discharged patients and prepare timely medical and social interventions accordingly.

Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator.

Haze is the most frequently encountered weather condition on the road, and it accounts for a considerable number of car crashes occurring every year. Accordingly, image dehazing has garnered strong interest in recent decades. However, although various algorithms have been developed, a robust dehazing method that can operate reliably in different haze conditions is still in great demand. Therefore, this paper presents a method to adapt a dehazing system to various haze conditions. Under this approach, the proposed method discriminates haze conditions based on the haze density estimate. The discrimination result is then leveraged to form a piece-wise linear weight to modify the depth estimator. Consequently, the proposed method can effectively handle arbitrary input images regardless of their haze condition. This paper also presents a corresponding real-time hardware implementation to facilitate the integration into existing embedded systems. Finally, a comparative assessment against benchmark designs demonstrates the efficacy of the proposed dehazing method and its hardware counterpart.

Trichosanthis Semen and Zingiberis Rhizoma Mixture Ameliorates Lipopolysaccharide-Induced Memory Dysfunction by Inhibiting Neuroinflammation.

Neuroinflammation, a key pathological contributor to various neurodegenerative diseases, is mediated by microglial activation and subsequent secretion of inflammatory cytokines via the mitogen-activated protein kinase (MAPK) signaling pathway. Moreover, neuroinflammation leads to synaptic loss and memory impairment. This study investigated the inhibitory effects of PNP001, a mixture of Trichosanthis Semen and Zingiberis Rhizoma in a ratio of 3:1, on neuroinflammation and neurological deficits induced by lipopolysaccharide (LPS). For the in vitro study, PNP001 was administered in LPS-stimulated BV2 microglial cells, and reduced the pro-inflammatory mediators, such as nitric oxide, inducible nitric oxide synthase, and cyclooxygenase-2 by downregulating MAPK signaling. For the in vivo study, ICR mice were orally administered PNP001 for 18 consecutive days, and concurrently treated with LPS (1 mg/kg, i.p.) for 10 days, beginning on the 4th day of PNP001 administration. The remarkably decreased number of activated microglial cells and increased expression of pre- and post-synaptic proteins were observed more in the hippocampus of the PNP001 administered groups than in the LPS-treated group. Furthermore, daily PNP001 administration significantly attenuated long-term memory decline compared with the LPS-treated group. Our study demonstrated that PNP001 inhibits LPS-induced neuroinflammation and its associated memory dysfunction by alleviating microglial activation and synaptic loss.

Otological aspects of NLRP3-related autoinflammatory disorder focusing on the responsiveness to anakinra.

OBJECTIVES: Gradually progressive sensorineural hearing loss (SNHL) is a prevalent sensory defect. It is generally untreatable, making rehabilitation by hearing aid or cochlear implantation the only option. However, SNHL as one of the symptoms of the hereditary autoinflammatory systemic disease cryopyrin-associated periodic syndrome, or as the only symptom of the cochlea-specific form (DFNA34), was suggested to respond to IL-1 antagonist (anakinra) therapy, which ameliorates NLRP3 variants-induced over-secretion of IL-1ß. We analysed genotypic and phenotypic spectrum of cryopyrin-associated periodic syndrome or DFNA34, specifically focusing on the responsiveness of SNHL to anakinra. METHODS: Seventeen families diagnosed with either cryopyrin-associated periodic syndrome or DFNA34 were recruited. Genotyping and phenotyping including audiogram, MRI findings, and in vitro IL-1ß assay were performed. RESULTS: Our cohort had an etiologic homogeneity of 94.1% to NLRP3 variants and a high de novo occurrence (84.6%). We identified the second DNFA34 pedigree worldwide with a novel NLRP3 variant supported by in vitro analysis. Significant improvement of hearing status against the natural course, showing response to anakinra, was identified in three probands, one of whom used to have severe SNHL. Hearing threshold worse than 60 dB at the start of anakinra and cochlear enhancement on brain MRI seemed to be related with poor audiologic prognosis and responsiveness to anakinra therapy despite stabilized systemic symptoms and inflammatory markers. CONCLUSION: We propose a constellation of biomarkers comprising NLRP3 genotypes, hearing status at diagnosis, and cochlear radiological findings as prognostic factors of hearing status after anakinra treatment and possibly as sensitive parameters for treatment dosage adjustment.

Chest CT abnormalities in COVID-19: a systematic review.

Computed tomography (CT) of the chest is one of the main diagnositic tools for coronavirus disease 2019 (COVID-19) infection. To document the chest CT findings in patients with confirmed COVID-19 and their association with the clinical severity, we searched related literatures through PubMed, MEDLINE, Embase, Web of Science (inception to May 4, 2020) and reviewed reference lists of previous systematic reviews. A total of 31 case reports (3768 patients) on CT findings of COVID-19 were included. The most common comorbid conditions were hypertension (18.4%) and diabetes mellitus (8.3%). The most common symptom was fever (78.7%), followed by cough (60.2%). It took an average of 5.6 days from symptom onset to admission. The most common chest CT finding was vascular enlargement (84.8%), followed by ground-glass opacity (GGO) (60.1%), air-bronchogram (47.8%), and consolidation (41.4%). Most lung lesions were located in the lung periphery (72.2%) and involved bilateral lung (76%). Most patients showed normal range of laboratory findings such as white blood cell count (96.4%) and lymphocyte (87.2%). Compared to previous published meta-analyses, our study is the first to summarize the different radiologic characteristics of chest CT in a total of 3768 COVID-19 patients by compiling case series studies. A comprehensive diagnostic approach should be adopted for patients with known COVID-19, suspected cases, and for exposed individuals.

Automating a Dehazing System by Self-Calibrating on Haze Conditions.

Existing image dehazing algorithms typically rely on a two-stage procedure. The medium transmittance and lightness are estimated in the first stage, and the scene radiance is recovered in the second by applying the simplified Koschmieder model. However, this type of unconstrained dehazing is only applicable to hazy images, and leads to untoward artifacts in haze-free images. Moreover, no algorithm that can automatically detect the haze density and perform dehazing on an arbitrary image has been reported in the literature to date. Therefore, this paper presents an automated dehazing system capable of producing satisfactory results regardless of the presence of haze. In the proposed system, the input image simultaneously undergoes multiscale fusion-based dehazing and haze-density-estimating processes. A subsequent image blending step then judiciously combines the dehazed result with the original input based on the estimated haze density. Finally, tone remapping post-processes the blended result to satisfactorily restore the scene radiance quality. The self-calibration capability on haze conditions lies in using haze density estimate to jointly guide image blending and tone remapping processes. We performed extensive experiments to demonstrate the superiority of the proposed system over state-of-the-art benchmark methods.

Visibility Restoration: A Systematic Review and Meta-Analysis.

Image acquisition is a complex process that is affected by a wide variety of internal and environmental factors. Hence, visibility restoration is crucial for many high-level applications in photography and computer vision. This paper provides a systematic review and meta-analysis of visibility restoration algorithms with a focus on those that are pertinent to poor weather conditions. This paper starts with an introduction to optical image formation and then provides a comprehensive description of existing algorithms as well as a comparative evaluation. Subsequently, there is a thorough discussion on current difficulties that are worthy of a scientific effort. Moreover, this paper proposes a general framework for visibility restoration in hazy weather conditions while using haze-relevant features and maximum likelihood estimates. Finally, a discussion on the findings and future developments concludes this paper.