Pioneering heat transfer enhancements in latent thermal energy storage: Passive and active strategies unveiled.

Intermittent renewable energy sources such as solar and wind necessitate energy storage methods like employing phase change materials (PCMs) for latent heat thermal energy storage (LHTES). However, the low thermal conductivity of PCMs limits their thermal response rate. This paper reviews recent progress in active heat transfer augmentation methods for improving LHTES system performance, encompassing mechanical aids, vibrations, jet impingement, injection, and external fields. It compiles findings concerning the optimization of PCM charging and discharging processes. Proposals for future research directions are provided, highlighting the significance of extra energy input for storage. The study highlights how changing the mushy zone constant from 103 to 108 affects a PCM's melt fraction and heat storage. The article also overviews studies using fins and coils to enhance heat transfer in PCM-based LHTES systems. It discusses how geometric and material constraints influence the melting and solidification processes and the heat transfer surface orientation within the storage tank. Various PCMs with different melting temperatures are examined. A broad range of test cases was examined to determine how geometry and orientation-dependent convection affect the phase-changing process. This overview of heat transfer principles offers guidelines for system designers to optimize the geometry of heat transfer fluid (HTF) flow paths and the confinement of PCM to enhance heat transfer efficiency and overall system performance. The results also indicate research gaps for certain PCM melting temperature ranges. Few experimental studies exist for melting temperatures above 60 °C; most focus only on melting rather than solidification. More standardized studies using non-dimensional parameters for coil geometries are advocated.

Secondary rhinoplasty for unilateral cleft lip nasal deformity using the complex of autologous costal cartilage and fascia grafts.

BACKGROUND: Secondary unilateral cleft lip nasal deformity is a prevalent condition in the world, and surgical repair remains a formidable challenge. The objective of the study is to investigate functionally and aesthetically outcomes of a new technique using a complex of autologous costal cartilage and fascia grafts to repair the secondary unilateral cleft lip nasal deformity. METHODS: First, the autologous costal cartilage and fascia were harvested from a total of 34 patients with secondary unilateral cleft lip nasal deformity, who were undergoing treatments at the First Affiliated Hospital of Xi'an Jiaotong University from April 2020 to June 2023. Then, the cartilage was sub-divided into 6 pieces and placed on the depressed alar base, nasal columella, lower lateral cartilage, and nasal tip. At the same time, the fascia was trimmed to cover the nasal tip cap graft and augment the dorsum of the nose. Patient outcomes were assessed through subjective evaluation and objective anthropometric measurements. In addition, associated complications were also examined. RESULTS: All were primary healing incisions, and no patients were encountered with any clinical complications. We found that the overall mean score of the Independent Rhinoplasty Outcome Score (IROS) was very good during the subjective assessment. Also, the objective measurements indicated an excellent nasal symmetry. Furthermore, both functionally and aesthetically satisfactory outcomes were obtained in all the patients during long-time follow-up. CONCLUSIONS: Secondary rhinoplasty using the complex of autologous costal cartilage and fascia grafts is a safe and effective approach for unilateral cleft lip nasal deformity repair.

Advancing thermal management in electronics: a review of innovative heat sink designs and optimization techniques.

The ongoing trend towards miniaturizing electronic devices and increasing their power densities has created substantial challenges in managing the heat they produce. Traditional heat sink designs often fall short of meeting modern electronics' rigorous thermal management needs. As a result, researchers and engineers are turning to innovative heat sink designs and optimization methods to improve thermal performance. This review article offers an overview of the latest advancements in designing and optimising advanced heat sinks for electronic cooling. It explores various techniques to enhance heat transfer, including advanced surface geometries and microchannels. Additionally, the review covers computational fluid dynamics (CFD) modelling and experimental validation methods used to refine heat sink designs. Further insight into fouling and its prevention has been discussed. The insights provided in this article are intended to serve as a valuable resource for thermal engineers, and researchers focused on managing the heat in high-power electronic systems.

REMP: A unique dataset of rare and endangered medicinal plants in Bangladesh for sustainable healing and biodiversity conservation.

In Bangladesh, there are significant number of medicinal plants, but currently no comprehensive record of these valuable species is publicly available. Alarmingly, some of these plants are in a precarious state of endangerment. Therefore, we are creating a unique dataset of Bangladesh's rare, endangered, and threatened medicinal plants to support conservation efforts. It will help us to track and conserve endangered plant species, ensuring a more organized approach to research and preservation efforts. We conducted on-site visits to the National Botanical Garden and The Government Unani and Ayurvedic Medical College, capturing photographs of these plants in optimal sunlight conditions at various times of the day. This involved fieldwork, detailed image annotations, dataset organization, diversity augmentation, and contribution to the preservation of our natural heritage. We have collected a total of 16 types of rare and endangered medicinal plant leaf photos to create our unique dataset consisting of a total of 3494 images. This dataset will help researchers in biodiversity conservation through building efficient machine learning models and applying advanced machine learning techniques to identify rare and endangered medicinal plants.

Review on Nanofluids: Preparation, Properties, Stability, and Thermal Performance Augmentation in Heat Transfer Applications.

Nanoparticles play a crucial role in enhancing the thermal and rheological properties of nanofluids, making them a valuable option for increasing the efficiency of heat exchangers. This research explores how nanoparticle characteristics, such as concentration, size, and shape, impact the properties of nanofluids. Nanofluids' thermophysical properties and flow characteristics are essential in determining heat transfer efficiency and pressure loss. Nanoparticles with high thermal conductivity, such as metallic oxides like MgO, TiO2, and ZnO, can significantly improve the heat transfer efficiency by around 30% compared to the base fluid. The stability of nanofluids plays a crucial role in their usability. Various methods, such as adding surfactants, using ultrasonic mixing, and controlling pH, have been employed to enhance the stability of nanofluids. The desired thermophysical properties can be achieved by utilizing nanofluids to enhance the system's heat transfer efficiency. Modifying the size and shape of nanoparticles also considerably improves thermal conductivity, affecting nanofluid viscosity and density. Equations for determining heat transfer rate and pressure drop in a double-pipe heat exchanger are discussed in this review, emphasizing the significance of nanofluid thermal conductivity in influencing heat transfer efficiency and nanofluid viscosity in impacting pressure loss. This Review identifies a trend indicating that increasing nanoparticle volume concentration can enhance heat transfer efficiency to a certain extent. However, surpassing the optimal concentration can reduce Brownian motions due to higher viscosity and density. This Review offers a viable solution for enhancing the thermal performance of heat transfer equipment and serves as a fundamental resource for applying nanofluids in heat transfer applications.

Efficient Synthesis of Mannopyranoside-based Fatty Acyl Esters: Effects of Acyl Groups on Antimicrobial Potential.

BACKGROUND: The approval of Sucrose Fatty Acid Esters (SFAEs) as food additives/ preservatives with antimicrobial potential has triggered enormous interest in discovering new biological applications. Accordingly, many researchers reported that SFAEs consist of various sugar moieties, and hydrophobic side chains are highly active against certain fungal species. OBJECTIVE: This study aimed to conduct aregioselective synthesis of SAFE and check the effect of chain length and site of acylation (i.e., C-6 vs. C-2, C-3, C-4, and long-chain vs. short-chain) on antimicrobial potency. METHODS: A direct acylation method maintaining several conditions was used for esterification. In vitro tests, molecular docking, and in silico studies were conducted using standard procedures. RESULTS: In vitro tests revealed that the fatty acid chain length in mannopyranoside esters significantly affects the antifungal activity, where C12 chains are more potent against Aspergillus species. In terms of acylation site, mannopyranoside esters with a C8 chain substituted at the C-6 position are more active in antifungal inhibition. Molecular docking also revealed that these mannopyranoside esters had comparatively better stable binding energy and hence better inhibition, with the fungal enzymes lanosterol 14-alpha-demethylase (3LD6), urate oxidase (1R51), and glucoamylase (1KUL) than the standard antifungal drug fluconazole. Additionally, the thermodynamic, orbital, drug-likeness, and safety profiles of these mannopyranoside esters were calculated and discussed, along with the Structure-Activity Relationships (SAR). CONCLUSION: This study thus highlights the importance of the acylation site and lipid-like fatty acid chain length that govern the antimicrobial activity of mannopyranoside-based SFAE.

Nature exposure and mental health during the COVID-19 pandemic: A Navigation Guide systematic review with meta-analysis.

Prior reviews have highlighted that nature exposure was a valuable coping strategy enhancing mental health during the COVID-19 pandemic. However, no existing reviews have determined the quality of evidence and risk of bias of the empirical studies supporting this claim. To address this gap, we employed a Navigation Guide systematic review and meta-analysis approach to investigate associations between nature exposure and mental health during the pandemic. Searches in PubMed, Web of Science, Scopus, CINAHL, and PsycInfo retrieved relevant articles published between January 1, 2020, and March 4, 2024. We used the Navigation Guide methodology to assess the risk of bias and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessments to evaluate the overall quality of evidence. Our search retrieved 113 studies that met the inclusion criteria and reported diverse types of exposure, including nature availability, nature visit frequency, green space accessibility, and green space type, alongside associations with 12 mental health outcomes. Meta-analyses found access to gardens was associated with lower odds of depression [(Pooled odds ratio [OR] = 0.71, 95%CI = 0.61, 0.82), I2 = 0%, n = 3] and anxiety [(Pooled OR = 0.73, 95%CI = 0.63, 0.84), I2 = 0%, n = 3]. Increased time in green spaces was associated with lower level of stress [(Pooled Corr = -0.11, 95%CI = -0.17, -0.05), I2 = 0%, n = 2]. Higher frequency of visits to nature was associated with improved mental well-being [(Pooled standardized beta = 0.10, 95%CI = 0.07, 0.14), I2 = 0%, n = 2] and general mental health [(Pooled standardized beta = 0.11, 95%CI = 0.03-0.38), I2 = 82%, n = 2]. However, the number of pooled studies was small and the overall quality of evidence was "very low" for all outcomes, and high levels of bias were observed (26% of studies had high, 71% probably high). Nonetheless, given the trends in the results, nature-based solutions emphasizing exposure to gardens and green spaces near the home may have promoted psychological resilience during this public health crisis.

Deep Learning Insights into the Dynamic Effects of Photodynamic Therapy on Cancer Cells.

Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer cells, while logistic growth modelling predicts cellular behavior post-PDT. Rigorous model validation ensures the accuracy of the findings. Cellpose demonstrates significant morphological changes after PDT, affecting cellular proliferation and survival. The reliability of the findings is confirmed by model validation. This deep learning tool enhances our understanding of cancer cell dynamics after PDT. Advanced analytical techniques, such as morphological analysis and growth modeling, provide insights into the effects of PDT on hepatocellular carcinoma (HCC) cells, which could potentially improve cancer treatment efficacy. In summary, the research examines the role of deep learning in optimizing PDT parameters to personalize oncology treatment and improve efficacy.

Combination of epigallocatechin 3 gallate and curcumin improves D-galactose and normal-aging associated memory impairment in mice.

Previously, we observed curcumin improves aging-associated memory impairment in D-galactose (D-gal) and normal-aged (NA) mice. Evidence showed that multiple agents can be used in managing aging-induced memory dysfunction, drawn by the contribution of several pathways. Curcumin and Epigallocatechin 3 gallate (EGCG) combination substantially reduced the oxidative stress that commonly mediates aging. This study examined the combined effect of EGCG and curcumin on memory improvement in two recognized models, D-gal and normal-aged (NA) mice. The co-administration of EGCG and curcumin significantly (p < 0.05) increased retention time detected by passive avoidance (PA) and freezing response determined in contextual fear conditioning (CFC) compared to the discrete administration of EGCG or curcumin. Biochemical studies revealed that the combination of EGCG and curcumin remarkably ameliorated the levels (p < 0.05) of glutathione, superoxide dismutase, catalase, advanced oxidation protein products, nitric oxide, and lipid peroxidation compared to the monotherapy of EGCG or curcumin in mice hippocampi. The behavioral and biochemical studies revealed that the combination of EGCG and curcumin showed better improvement in rescuing aging-associated memory disorders in mice. EGCG and curcumin combination could serve as a better choice in managing aging-related memory disorders.

A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images.

Computerized brain tumor classification from the reconstructed microwave brain (RMB) images is important for the examination and observation of the development of brain disease. In this paper, an eight-layered lightweight classifier model called microwave brain image network (MBINet) using a self-organized operational neural network (Self-ONN) is proposed to classify the reconstructed microwave brain (RMB) images into six classes. Initially, an experimental antenna sensor-based microwave brain imaging (SMBI) system was implemented, and RMB images were collected to create an image dataset. It consists of a total of 1320 images: 300 images for the non-tumor, 215 images for each single malignant and benign tumor, 200 images for each double benign tumor and double malignant tumor, and 190 images for the single benign and single malignant tumor classes. Then, image resizing and normalization techniques were used for image preprocessing. Thereafter, augmentation techniques were applied to the dataset to make 13,200 training images per fold for 5-fold cross-validation. The MBINet model was trained and achieved accuracy, precision, recall, F1-score, and specificity of 96.97%, 96.93%, 96.85%, 96.83%, and 97.95%, respectively, for six-class classification using original RMB images. The MBINet model was compared with four Self-ONNs, two vanilla CNNs, ResNet50, ResNet101, and DenseNet201 pre-trained models, and showed better classification outcomes (almost 98%). Therefore, the MBINet model can be used for reliably classifying the tumor(s) using RMB images in the SMBI system.

Reconfigurable high-order mode pass filter for mode-division multiplexing.

In mode division multiplexing (MDM) optical system, the mode filter has become an inseparable part to reduce modal crosstalk and transmit the desired modes unabatedly. As filtering out lower-order mode is difficult, here we propose a reconfigurable structure of a higher-order mode pass filter consisting of two tunable mode converters and a directional coupler (DC) in a three-mode planar waveguide platform. By switching the working states of the mode converters, the structure can also be used as a fundamental mode (TE0) pass filter and hence dynamic output signals can be achieved. For the second-order mode (TE2) transmission, the simulated excess loss is ∼0.61 dB at 1.550 µm and the extinction ratio remains ≥24 dB (power ratio of TE0 & TE2 Launch) and ≥25 dB (power ratio of TE1 & TE2 Launch) at the entire C-band (1.530-1.565 µm). The device has negligible polarization dependence and hence the TM polarization exhibits similar results.

Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland.

Accurate prediction of evapotranspiration (ET) in wetlands is critical for understanding the coupling effects of water, carbon, and energy cycles in terrestrial ecosystems. Multiple years of eddy covariance (EC) tower ET measurements at five representative wetland ecosystems in the subtropical Big Cypress National Preserve (BCNP), Florida (USA) provide a unique opportunity to assess the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) ET operational product MOD16A2 and upscale tower measured ET to generate local/regional wetland ET maps. We developed an object-based machine learning ensemble approach to evaluate and map wetland ET by linking tower measured ET with key predictors from MODIS products and meteorological variables. The results showed MOD16A2 had poor performance in characterizing ET patterns and was unsatisfactory for estimating ET over four wetland communities where Nash-Sutcliffe model Efficiency (NSE) was less than 0.5. In contrast, the site-specific machine learning ensemble model had a high predictive power with a NSE larger than 0.75 across all EC sites. We mapped the ET rate for two distinctive seasons and quantified the prediction diversity to identify regions easier or more challenging to estimate from model-based analyses. An integration of MODIS products and other datasets through the machine learning upscaling paradigm is a promising tool for local wetland ET mapping to guide regional water resource management.

Mechanism of arsenic enrichment and mobilization in groundwater from southeastern Bangladesh: Water quality and preliminary health risks assessment.

To understand the mechanistic pathway of arsenic (As) enrichment and mobilization in groundwater (southeastern Bangladesh) and to evaluate the water quality as well as associated health risks, a suite of systematically collected groundwater samples (depth: 17-61 m) were analyzed. Arsenic concentrations (µg L-1) in the groundwater samples were ranged from 6 to 581 with a mean value of 199 which is significantly higher than the recommended values. The assessment of water quality using entropy water quality index and irrigation water quality indices revealed that the groundwater in the studied region was not recommended for drinking and irrigation, respectively with few exceptions. Dominant water types in the studied area were Ca-Mg-HCO3, Na-HCO3, and Na-Cl types. Various forms of water-rock interactions, leaching of evaporates, and the confined nature of the aquifer mostly control the hydro-chemical parameters. Fe/Mn bound As are likely to be released in the aquifer through the dissolution of carbonate minerals of Fe/Mn while the higher degree of water-rock interaction and probable oxidation of organic materials helped to elevate As concentration. The probable longer residence time of groundwater guided by topographic slope and the neighboring clayey aquitard govern the As mobilization in the aquifer. Probabilistic health risk assessment revealed that groundwaters from the studied area can cause both non-carcinogenic and carcinogenic health risks.

Synthesis and characterization of Mg-Zn ferrite based flexible microwave composites and its application as SNG metamaterial.

In this article, we propose SNG (single negative) metamaterial fabricated on Mg-Zn ferrite-based flexible microwave composites. Firstly, the flexible composites are synthesized by the sol-gel method having four different molecular compositions of MgxZn(1-x)Fe2O4, which are denoted as Mg20, Mg40, Mg60, and Mg80. The structural, morphological, and microwave properties of the synthesized flexible composites are analyzed using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and conventional dielectric assessment kit (DAK) to justify their possible application as dielectric substrate at microwave frequency regime. Thus the average grain size is found from 20 to 24 nm, and the dielectric constants are 6.01, 5.10, 4.19, and 3.28, as well as loss tangents, are 0.002, 0.004, 0.006, and 0.008 for the prepared Mg-Zn ferrites, i.e., Mg20, Mg40, Mg60, and Mg80 respectively. Besides, the prepared low-cost Mg-Zn ferrite composites exhibit high flexibility and lightweight, which makes them a potential candidate as a metamaterial substrate. Furthermore, a single negative (SNG) metamaterial unit cell is fabricated on the prepared, flexible microwave composites, and their essential electromagnetic behaviors are observed. Very good effective medium ratios (EMR) vales are obtained from 14.65 to 18.47, which ensure the compactness of the fabricated prototypes with a physical dimension of 8 × 6.5 mm2. Also, the proposed materials have shown better performances comparing with conventional FR4 and RO4533 materials, and they have covered S-, C-, X-, Ku-, and K-band of microwave frequency region. Thus, the prepared, flexible SNG metamaterials on MgxZn(1-x)Fe2O4 composites are suitable for microwave and flexible technologies.

Targeting cancer cells with nanotherapeutics and nanodiagnostics: Current status and future perspectives.

Nanotechnology is reshaping health care strategies and is expected to exert a tremendous impact in the coming years offering better healthcare facilities. It has led to not only therapeutic drug delivery feasibility but also to diagnostics. Materials in the size of nano range (1-100 nm) used in the design, fabrication, regulation, and application of therapeutic drugs or devices are classified as medical nanotechnology and nanopharmacology. Delivery of more complex molecules to the specific site of action as well as gene therapy has pushed forward the nanoparticle-based drug delivery to its maximum. Areas that benefit from nano-based drug delivery systems are cancer, diabetes, infectious diseases, neurodegenerative diseases, blood disorders and orthopedic-related ailments. Moreover, development of nanotherapeutics with multi-functionalities has a considerable potential to fill the gaps that exist in the present therapeutic domain. In cancer treatment, nanomedicines have superiority over current therapeutic practices as they can effectively deliver the drug to the affected tissues, thus reducing drug toxicities. Along this line, polymeric conjugates of asparaginase and polymeric micelles of paclitaxel have recently been recommended for the treatment of various types of cancers. Nanotechnology-based therapeutics and diagnostics provide greater effectiveness with less or no toxicity concerns. Similarly, diagnostic imaging holds promising future applications with newer nano-level imaging elements. Advancements in nanotechnology have emerged to a newer direction which use nanorobotics for various applications in healthcare. Accordingly, this review comprehensively highlights the potentialities of various nanocarriers and nanomedicines for multifaceted applications in diagnostics and drug delivery, especially the potentialities of polymeric nanoparticle, nanoemulsion, solid-lipid nanoparticle, nanostructured lipid carrier, self-micellizing anticancer lipids, dendrimer, nanocapsule and nanosponge-based therapeutic approaches in the field of cancer. Furthermore, this article summarizes the most recent literature pertaining to the use of nano-technology in the field of medicine, particularly in treating cancer patients.

Acute toxicity of an organophosphate insecticide sumithion to striped catfish Pangasianodon hypophthalmus.

Sumithion is widely used for crop safety and eradication of tiger bugs (Cicindela spp.) from larval rearing aquaculture ponds. To satisfy the high demand of fries and fingerlings of widely cultured species striped catfish, spawns are produced in large scale in the hatcheries through hormone induced breeding, and subsequently these spawns are reared in nursery ponds and marketed to fingerlings vendors for stocking in grow-out ponds. Considering the importance of healthy fries and fingerlings the present experiment was conducted to evaluate the toxic effects of sumithion on striped catfish fingerlings. Fish were exposed for 96 h to six concentrations of sumithion (0, 3, 4, 5, 6 and 7 mg/l) each with three replications. The 96 h LC50 value was calculated using probit analysis. After 96 h of exposure fishes were sacrificed to measure hemato-biochemical (Hemoglobin, Hb; Red blood cell, RBC; White blood cell, WBC and blood glucose) parameters. In addition, formation of micronucleus (MN) was examined in the blood erythrocytes. The 96 h LC50 value of sumithion for striped catfish was 5.886 mg/l. The values of RBCs and Hb decreased significantly in different concentrations of the toxicant compared to control, while the values of WBC and blood glucose levels showed opposite scenario. Consequently, the frequencies of formation of MN increased significantly in different concentrations of the toxicant compared to the control. The results of the current study denoted that sumithion exerts toxicity to striped catfish. It is expected that the findings of the present research will help in the development of awareness of the concerned people about the toxic effect of sumithion as well as other insecticides and pesticides in the environment.

Effect of induction hydroxy and hydrogen along with algal biodiesel blend in a CI engine: a comparison of performance and emission characteristics.

Gaseous fuel as a combustion enhancer with a pilot fuel offers significant benefits in improving engine efficiency. Hydrogen and hydroxy are the two most common gaseous fuels that have been widely investigated in the CI engine but which one performs best is still inconvenient. In this study, hydrogen and hydroxy were injected with BD40 (v/v) separately in a common diesel engine to compare the performance and emission characteristics of these fuels. Engine performance parameters include brake thermal efficiency (BTE) and brake-specific energy consumption (BSEC), and exhaust emissions include hydrocarbon (HC), CO, CO2, NOx, and smoke opacity. The induction of both hydroxy and hydrogen with BD40 has a positive effect on engine performance and emissions except NOx when compared to neat diesel fuel and BD40. The BTE of hydroxy-rich BD40 increased by 7.2% while BSEC reduced by 7.6% as compared to BD40 with hydrogen. The CO, HC, and smoke opacity of hydroxy-operated engine was found to be better than hydrogen-inducted engine. The NOx emission increased with the induction of both gaseous fuels and hydroxy-enriched BD40 produced 12.5% more emission than hydrogen-operated BD40 engine. Thus, more concisely, hydroxy-operated biodiesel engine performed better than hydrogen engine in terms of BTE, BSEC, CO, HC, and smoke opacity.

Induction of hydrogen, hydroxy, and LPG with ethanol in a common SI engine: a comparison of performance and emission characteristics.

In this investigation, performance and emission characteristics for enhancing LPG, hydrogen, and hydroxy with E20 were evaluated for the understanding of which fuel combination performs better in a gasoline engine. In the upper sequence, hydroxy-hydrogen-LPG could perform best in terms of brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC). The induction of gaseous fuel improves CO, CO2, and HC emission but increases the NOx emission. More concisely, the enhancement of hydroxy with E20 shows the best engine performance for highest BTE while lowest BSFC as well as lowest exhaust emissions (CO, HC, except NOx).

Chronic Obstructive Pulmonary Disease and Lung Cancer: Underlying Pathophysiology and New Therapeutic Modalities.

Chronic obstructive pulmonary disease (COPD) and lung cancer are major lung diseases affecting millions worldwide. Both diseases have links to cigarette smoking and exert a considerable societal burden. People suffering from COPD are at higher risk of developing lung cancer than those without, and are more susceptible to poor outcomes after diagnosis and treatment. Lung cancer and COPD are closely associated, possibly sharing common traits such as an underlying genetic predisposition, epithelial and endothelial cell plasticity, dysfunctional inflammatory mechanisms including the deposition of excessive extracellular matrix, angiogenesis, susceptibility to DNA damage and cellular mutagenesis. In fact, COPD could be the driving factor for lung cancer, providing a conducive environment that propagates its evolution. In the early stages of smoking, body defences provide a combative immune/oxidative response and DNA repair mechanisms are likely to subdue these changes to a certain extent; however, in patients with COPD with lung cancer the consequences could be devastating, potentially contributing to slower postoperative recovery after lung resection and increased resistance to radiotherapy and chemotherapy. Vital to the development of new-targeted therapies is an in-depth understanding of various molecular mechanisms that are associated with both pathologies. In this comprehensive review, we provide a detailed overview of possible underlying factors that link COPD and lung cancer, and current therapeutic advances from both human and preclinical animal models that can effectively mitigate this unholy relationship.