Search Results (267)

(1) Research Highlights: This study provides the first integrated assessment of Scots pine (Pinus sylvestris L.) growing in the urban forests of Karaganda, Kazakhstan, a city consistently ranked among the most air-polluted cities globally. We examined the adaptive phyto-chemical response of needles to extreme technogenic stress and evaluated their dual potential as biological filters and renewable sources of bioactive compounds. (2) Background and Objectives: Urban forests are critical for mitigating air pollution; however, the biochemical responses of trees in heavily industrialized environments remain poorly understood. Karaganda faces severe atmospheric pollution from mining, metallurgy, and energy sectors, with particulate matter (PM) levels exceeding permissible limits by up to 20-fold. This study aimed to evaluate the state of Pinus sylvestris, a key component of local protective plantations, by studying heavy metal accumulation, anatomical localization of secondary metabolites, and the phytochemical profile and biological activity of needle extracts obtained using different extraction techniques. (3) Materials and Methods: Needles were collected from 15 trees across three sites in Karaganda’s industrial green zones. Heavy metal content (Pb, Cd, As, and Hg) was determined using atomic absorption spectroscopy and voltammetry. Anatomical–histochemical analysis localizes major metabolite classes. Liquid extracts were prepared using four methods, percolation (PER), vortex-assisted (VAE), microwave-assisted (MAE), and ultrasound-assisted (UAE) extraction, and analyzed by GC-MS. Antimicrobial activity was tested against S. aureus, B. subtilis, E. coli, and C. albicans using the disk diffusion method. The antioxidant capacity (water- and fat-soluble) was measured amperometrically. Statistical analysis was performed using one-way ANOVA with Tukey’s HSD test (p < 0.05). Results: Despite extreme ambient pollution, heavy metal concentrations remained below pharmacopoeial limits (Pb < 0.1, Cd < 0.05, As < 0.01, Hg < 0.001 mg/kg), indicating effective biofiltration without toxic accumulation. Histochemistry confirmed the active synthesis of protective phenolics, flavonoids, and essential oils in the mesophyll, epidermis, and schizogenic cavities. GC-MS identified 72 compounds in the PER extract, 70 (the VAE), 72 in (MAE), and 46 in (UAE). The PER extract exhibited the highest relative abundance of bioactive terpenoids: α-cadinol (5.24%), α-muurolene (4.32%), and caryo-phyllene (2.20%). UAE extracts exhibited elevated 5-hydroxymethylfurfural (6.90%), indicating degradation. Antimicrobial testing revealed that PER produced the largest inhibition zone against S. aureus (15.0 ± 1.0 mm), significantly exceeding that of the other methods (p < 0.001). PER extract also demonstrated the highest water-soluble antioxidant capacity (3600 ± 0.40 mg quercetin equiv./dm³) and substantial fat-soluble activity (1633 ± 0.23 mg gallic acid equiv./dm³). (4) Conclusions: Pinus sylvestris in Karaganda exhibits remarkable adaptive resilience, maintaining safe heavy metal levels while accumulating a rich repertoire of stress-induced secondary metabolites. Classical percolation optimally preserves this native phytocomplex, yielding extracts with superior antimicrobial and antioxidant properties. These findings support a dual-use model wherein urban pine plantations simultaneously serve as living biofilters and renewable sources of standardized bioactive extracts, a concept with direct implications for circular bioeconomy strategies in industrial regions worldwide. This supports the strategic importance of coniferous plantations for bioremediation and sustainable resource use in industrial regions. Full article

A high-sensitivity and high-stability on-chip temperature sensor based on a silicon-on-insulator (SOI) platform is proposed and experimentally demonstrated in this work. The device employs a ring-assisted asymmetric Mach–Zehnder interferometer (RAMZI), enhancing both temperature sensitivity and measurement stability. Broadband, wavelength-insensitive components, including multimode interference couplers and adiabatic 3 dB splitters, reduce the influence of laser wavelength fluctuations and mitigate interference errors caused by environmental perturbations. The sensor achieves a temperature sensitivity of 108.74 pm/K, corresponding to an approximately 40% improvement over a conventional AMZI with the same footprint. Moreover, a wavelength drift of only 18 pm over 45 min demonstrates excellent stability and robustness. This work provides an effective solution for highly sensitive and stable on-chip temperature sensing in photonic integrated systems. Full article

Novel porous geopolymer (IGP&SS), possessing mesoporous structure and a compressive strength of 9.40 MPa, was synthesized through alkali activation of double solid wastes such as iron tailings and steel slag. To overcome the high activation energy barrier of oxidants for refractory pollutant treatment, the IGP&SS was designed to efficiently activate peroxymonosulfate (PMS) under visible-light irradiation, generating reactive radicals for the rapid degradation of methylene blue (MB). The system achieved nearly complete removal within 30 min. To enhance MB removal, the effects of key factors including IGP&SS dosage, PMS dosage, initial MB concentration, temperature, and pH on the degradation process were systematically investigated. Quenching experiments revealed that several reactive oxygen species contributed to MB degradation, with the order of contribution being •OH > ¹O₂ > SO₄•⁻ > •O₂⁻. Mechanistic studies indicated that the efficient MB degradation was primarily attributed to the flexible Fe(II)/Fe(III) redox cycling in IGP&SS, which accelerated PMS activation and radical generation. X-ray photoelectron spectroscopy (XPS) analysis of the post-reaction catalyst confirmed its structural robustness, revealing a characteristic binding energy shift in the O 1s peak to 530.8 eV and a quantitative redistribution of iron species (Fe(III) content increasing from 40.4% to 57.0%). Given its outstanding performance, demonstrated stability, and eco-friendly preparation, IGP&SS holds great promise for PMS-based advanced oxidation processes in dye wastewater treatment, offering a sustainable approach for high-value utilization of iron tailings and steel slag while alleviating resource scarcity. Full article

Cold forging backward extrusion is mainly employed in the manufacturing of axisymmetric cup-like components used extensively in automotive and aerospace assemblies due to the process-induced strength that has a pivotal role in such applications. Although cold forging backward extrusion yields mechanically robust components, it demands high forces, subjecting tooling to immense stress, thereby restricting process capacity. The process encounters hindrances in gaining widespread industrial acceptance due to frequent failures of die elements, necessitating proper die design and control of major influencing factors for process viability and cost-effectiveness. The punches in backward extrusion are often susceptible to failures when processing steel billets. The punch service life is significantly affected by geometrical attributes, the type of steel undergoing deformation, and tool manufacturing aspects. Hence, the present study evaluates punch performance in cold forging backward extrusion using optimized geometrical attributes, manufactured through a design of an experimental approach comprising an L9 orthogonal array. The manufacturing factors considered are punch material, hardness, and advanced surface coating. Punches were designed for two industrial components using powder metallurgy (PM) steels—S600, S290, and S590, heat treated to 60–66 HRC, and coated via physical vapor deposition with TiN, AlTiN, and TiAlCN. Punch performance was analyzed against existing industry practices, and the strategy demonstrated improved productivity. Punch performance was determined based on the number of forgings produced before wear- and fatigue-induced failures. Significant improvements in punch performance were witnessed in both high-speed steel (HSS) and PM punches with optimized geometries. Fractographic investigations were carried out on fractured punches and analyzed, focusing on the coating’s effect on the thermal aspects of the punches. The proposed study will assist the cold-forging industry in determining appropriate variables to minimize forming responses, thereby enhancing tool life. The research also benefits industries by enhancing process robustness and improving process efficiency with respect to cost and time. Full article

Urban cyclists experience elevated traffic-related air pollutant (TRAP) exposures due to proximity to emissions and increased breathing rates during exercise. Conventional assessments rely on concentration summaries, which may misrepresent actual inhaled doses and misclassify individuals in health studies. Street-level concentrations exhibit high temporal variability, producing non-normal distributions that challenge conventional averaging approaches. This study compares concentration- and dose-based methods to characterize cyclist exposure during urban commuting. Fifty-seven healthy adults completed cycling trips on two 9-km routes (high- and low-traffic) using conventional or electrically assisted bicycles. Real-time monitoring measured black carbon, ultrafine particles, PM_2.5, and PM₁₀. Heart rate-derived breathing rates enabled individualized inhaled dose calculations using three temporal integration methods. Mean concentrations correlated strongly with time-integrated concentrations (r = 0.988–0.998). Simplified dose calculations closely approximated full temporal integration (r > 0.999), with median dose ratios of 0.99–1.01. However, correlations between mean concentrations and inhaled doses were weaker (r = 0.72–0.78). Between 29% and 50% of participants changed exposure quartiles when comparing concentration- and dose-based classifications, with the highest reclassification for ultrafine particles (46–50%). These findings demonstrate that physiological variability substantially influences exposure classification during active commuting, supporting the integration of inhaled dose metrics in cyclist exposure assessment and epidemiological studies. Full article

This study addresses the need for detecting human papillomavirus type 16 DNA (HPV-16), a high-risk factor for cervical cancer, by developing a highly sensitive fluorescence sensing method based on tungsten disulfide (WS₂) nanosheets and exonuclease III (EXO III)-assisted cyclic amplification. The method is constructed by combining the highly efficient fluorescence quenching capability of tungsten disulfide (WS₂) nanosheets with a fluorescein (FAM)-labeled complementary DNA (cDNA) probe. When the target HPV-16 is present, it specifically hybridizes with the cDNA to form a double-stranded structure. This double-stranded structure can be cleaved by EXO III. The cleaved cDNA is not adsorbed by WS₂ nanosheets, generating a significant fluorescence signal. The released HPV-16 can then participate in the reaction again, achieving multiple rounds of fluorescence signal amplification. Under optimal conditions, the detection limit of the method is 0.35 pM. The method was successfully applied to the detection of HPV-16 in spiked serum samples, demonstrating the advantages of operational simplicity, high sensitivity, and good specificity. It provides a promising rapid detection method for clinical application research related to human papillomavirus. Full article

Over recent years, the intensity of forest fires has escalated, with wildfire-emitted pollutants exerting substantial impacts on the environment, ecosystems, and human well-being. This study developed a robust predictive framework to quantify wildfire-induced PM_2.5 emission factors (EFs) using seven shrub species—Corylus mandshurica, Eleutherococcus senticosus, Philadelphus schrenkii, Sorbaria sorbifolia, Syringa reticulata, Spiraea salicifolia, and Lonicera maackii. These species represent ecological cornerstones of Northeast Asian forests and hold global relevance as widely introduced or invasive taxa in North America and Europe. The novelty of this research lies in the integration of traditional statistical inference with machine learning to resolve the complex coupling between fuel traits and emissions. We conducted 1134 laboratory-controlled burns in the Liangshui National Nature Reserve, evaluating two continuous and three categorical variables. Initial screening via Analysis of Variance (ANOVA) and stepwise linear regression (Step-AIC) identified the primary drivers of emissions and revealed that interspecific differences among the seven shrubs did not significantly affect the EF (p = 0.0635). To ensure statistical rigor, a log-transformation was applied to the EF data to correct for right-skewness and heteroscedasticity inherent in raw observations. Linear Mixed-effects Models (LMMs) and Gradient Boosting Machines (GBMs) were subsequently employed to quantify factor effects and capture potential nonlinearities. The LMM results consistently identified burning type and plant part as the dominant determinants: smoldering combustion and leaf components exerted strong positive effects on PM_2.5 emissions compared to flaming and branch components. Fuel load was positively correlated with emissions, while moisture content showed a significant negative effect. Notably, the model identified a significant negative quadratic effect for moisture content, indicating a non-linear inhibitory trend as moisture increases. While interspecific differences among the seven shrubs did not significantly affect EFs suggesting that physical fuel traits exert a more consistent influence than species-specific genetic backgrounds, complex interactions were captured. These include a negative synergistic effect between leaves and smoldering, and a positive interaction between moisture content and leaves that significantly amplified emissions. This research bridges the gap between physical fuel traits and chemical smoke production, providing a high-resolution tool for refining global biomass burning emission inventories and assisting international forest management in similar temperate biomes. Full article

The widespread application of Rhodamine B (RhB) poses a serious threat to the aquatic environment. ZnFe₂O₄, as a catalyst material, can effectively activate persulfate (PMS) and respond to visible light, thus effectively degrading RhB with the joint assistance of sunlight and PMS. This study recovered Fe₂O₃ from high-iron coal gangue through an activating–acid leaching–extracting–back-extracting process and synthesized ZnFe₂O₄ catalysts (CG-ZFO) using coal gangue back-extraction liquid as the Fe source by a hydrothermal method and cetyltrimethylammonium bromide (CTAB)-assisted hydrothermal method. The characterization results of X-ray diffraction (XRD), scanning electron microscopy (SEM), and diffuse reflectance spectroscopy (DRS) showed that the CG-ZFO has a pure crystal phase, and the addition of CTAB can effectively improve the photoelectric performance of the catalyst. The synthesized CG-ZFO can produce a significant synergistic effect with simulated sunlight (SS) and PMS, and the constructed SS/CG-ZFO/PMS system had a good degradation effect on RhB. Based on the conclusions of free radical-quenching experiments, electron paramagnetic resonance (EPR) spectroscopy, and X-ray photoelectron spectroscopy (XPS), the main active species in the SS/CG-ZFO/PMS system was identified as ₁O², and the degradation mechanism of RhB was elucidated. CG-ZFO prepared from coal gangue holds promising potential for application in the remediation of organic dye wastewater, and this study also provides a new approach for the resource regeneration of high-iron coal gangue. Full article

The realization of desirable vertical phase separation, enabled by sequential processing that allows for the separate deposition and targeted regulation of donor and acceptor components to construct a well-defined donor–acceptor (D-A) interface, serves as a pivotal factor governing the performance of layer-by-layer organic photovoltaics (LOPVs). This study explores the utility of 4-trifluoromethyl benzoic anhydride (4-TBA), a multifunctional benzene-based solid additive, in the PM6/L8-BO LOPV system, focusing on its role in regulating the vertical phase separation of donor-PM6 and acceptor-L8-BO components to form a well-structured D-A interface. To this end, 4-TBA is doped into the donor-PM6 layer, acceptor-L8-BO layer, or both layers, and its effects on device performance are systematically characterized. The results show that simultaneous doping of 0.05 wt% 4-TBA in both PM6 and L8-BO layers yields the optimal performance, with the power conversion efficiency reaching 18.49% compared to the pristine device with a PCE of 17.05%, and this is accompanied by a significant increase in short-circuit current density from 24.71 mA/cm² to 26.65 mA/cm². Additionally, the optimal devices exhibit better stability, as unencapsulated devices retain 76% of their initial PCE after 175 h under ambient conditions compared to 73% for the devices without 4-TBA doping. Essentially, solid additive 4-TBA modulates molecular packing via its interaction between the donor and acceptor molecules and enhances molecular aggregation and hydrophobicity, thereby suppressing bimolecular and trap-assisted recombination, reducing trap density of states, and forming favorable interpenetrating networks. This work validates 4-TBA, which contains benzene rings and other functional groups, as a versatile additive suitable for the LOPV system and offers a generalizable strategy for optimizing LOPV performance by leveraging multifunctional solid additives. Full article

Background/Objectives: Overweight and obesity is a continuing health concern for preadolescent youth. We assessed associations between sleep timing and sleep duration and body mass index/body composition in Latine youth. Methods: Participants were 119 Latine youth (mean age 11.53 year; 58.8% girls) and their mothers living in the rural Midwestern U.S. Youth reported their average bedtime and waking time. Heights and weights for children and mothers were measured by trained research assistants and were used to calculate BMI scores (in mothers), as well as BMI percentiles and overweight status (in youth). Mothers completed surveys for demographic variables. Results: Youth who went to bed before 9:30 PM (mean bedtime) obtained more sleep than those with later bedtimes (9.73 h vs. 8.63 h, respectively, t(117) = 7.88, p < 0.001). Each extra hour of sleep duration was associated with a decreased risk of being overweight (OR = 0.53 for weeknight sleep, OR = 0.67 for weekend night sleep), and each hour later to bed was related to increased risk for being overweight (OR = 2.35 on weeknights, and OR = 1.66 on weekend nights). To replicate previous work, we broke the youth up into four sleep timing groups: early-to-bed and early-to-rise (EE), early-to-bed and late-to-rise (EL), late-to-bed and early-to-rise (LE), and late-to-bed and late-to-rise (LL). Youth with LL sleep patterns on weeknights were much more likely to be overweight compared to youth with EE patterns (OR = 4.94). On weekend nights, compared to EE weekend youth, LE and LL weekend youth were more likely to be overweight (OR = 3.45 and OR = 3.32, respectively). Wake times were not significantly related to overweight risk. Conclusions: Sleep timing patterns, especially sleep duration and earlier bedtimes, may be important to address in future research on obesity interventions. Findings suggest that earlier bedtimes may play an important and complimentary role in health, in addition to sleep duration alone, and this study highlights the need for more research in underserved, minoritized populations. Full article

To enhance the sensitivity of graphene-DNA sensors for Hg²⁺ detection, a novel graphene nanoribbon-DNA sensor was fabricated using a template-assisted approach. Silicon nanowires served as templates to decorate the graphene device, followed by plasma etching to delineate graphene nanoribbons. After template removal, the resulting sensors based on silicon nanowire templates were successfully constructed. DNA sequences containing four guanine bases were conjugated with graphene sensors prepared using the templates. The carboxyl groups on the edges of the graphene nanoribbons were activated with EDC/NHS chemistry to facilitate covalent bonding with amino-modified DNA. The kinetic response and Hg²⁺ detection capability of the fabricated sensors were characterized using a semiconductor parameter analyzer. Results indicated that the silicon nanowire-templated graphene nanoribbon sensor exhibited high sensitivity, with a detection limit of 3.62 pM. This innovative approach further improved the sensitivity of graphene-DNA sensors for Hg²⁺ detection. Full article

Growing efforts to reduce air pollution have accelerated the development of advanced flue gas treatment technologies for coal-fired power plants. This study presents the design, development, and industrial-scale implementation of a microwave-assisted non-thermal plasma reactor, powered by a 75 kW, 915 MHz magnetron, for simultaneous sulfur dioxide (SO₂) removal and fly ash agglomeration. The reactor was installed on the outlet line of the selective catalytic reduction (SCR) system of a 22 MW_e pulverized-coal-fired boiler and evaluated under real flue gas conditions. The flue gas stream, extracted by an induced-draft fan, was supplied to the reactor through two configurations—radial and axial injection—to investigate the influence of gas flow rate and microwave power on SO₂ abatement performance. Under radial injection, the system achieved a maximum SO₂ removal efficiency of 99.0% at 5194 Nm³/h and 75 kW, corresponding to a specific energy consumption of 14.4 Wh/Nm³. Axial injection resulted in a removal efficiency of 97.5% at 4100 Nm³/h. Beyond SO₂ mitigation, exposure of flue gas to the microwave-assisted plasma environment significantly enhanced particle agglomeration, as confirmed by means of SEM imaging and particle size distribution analyses. Notably, the proportion of fine particles smaller than 2.5 µm (PM_2.5) decreased from 70.25% to 18.63% after plasma treatment, indicating improved capture potential in the downstream electrostatic precipitator (ESP). Overall, microwave-assisted plasma provides efficient SO₂ removal and enhanced particulate capture, offering a compact and potentially waste-free alternative to conventional systems. Full article

Nitrate contamination of water resources poses significant ecological and public health risks. This study developed a cobalt-immobilized microplastic catalyst (Co–MP) capable of activating peroxymonosulfate (PMS) and facilitating formic-acid-assisted catalytic denitrification of nitrate. Characterization via Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Energy-Dispersive X-ray Spectroscopy (EDX), and X-ray diffractometry (XRD) confirmed successful Co deposition, with the surface cobalt content reaching 5.2%. The system’s performance was optimized using Response Surface Methodology (RSM), identifying catalyst dosage and Co(II) concentration as the most significant factors. Under the optimized conditions (pH 5.5, reaction time 120 min, catalyst dosage 1.5 g L⁻¹, and Co(II) concentration 60 mg L⁻¹), the system achieved a nitrate removal efficiency of 90.6%, in excellent agreement with the model prediction (90.93%), along with an 86.7% reduction in total nitrogen, confirming stepwise denitrification to gaseous nitrogen species (N₂). The Co(II)/Co(III) redox cycle, sustained by PMS-assisted regeneration and driven by formic acid as the electron donor, ensured stable performance with minimal cobalt leaching (0.05 mg L⁻¹). This coupled oxidative–reductive system offers a sustainable dual-remediation strategy that simultaneously achieves selective nitrate conversion and valorizes microplastic waste for catalytic environmental applications. Full article

Background: Interstitial lung diseases (ILDs) often progress quickly and are associated with a poor prognosis. New noninvasive biomarkers to assist in the classification and prognostication of ILD are needed. Exhaled nitric oxide (FeNO), Cavity nitric oxide (CaNO), and carbon monoxide (eCO) are biomarkers of airway inflammation, widely used in respiratory inflammatory diseases such as asthma and chronic obstructive pulmonary disease (COPD). However, their value in ILD remains unclear. Objective: To evaluate the potential diagnostic and prognostic value of FeNO, CaNO, and eCO in ILD, and explore their integration into clinical practice. Methods: A total of 237 patients were recruited for the study, including 14 with idiopathic pulmonary fibrosis (IPF), 46 with interstitial pneumonia with autoimmune features (IPAF), 19 with mixed connective tissue disease–associated ILD (MCTD-ILD), 65 with polymyositis/dermatomyositis-associated ILD (PM/DM-ILD), 17 with rheumatoid arthritis-associated ILD (RA-ILD), 7 with systemic lupus erythematosus-associated ILD (SLE-ILD), 19 with Sjögren’s syndrome-associated ILD (SS-ILD), and 50 with systemic sclerosis-associated ILD (SSc-ILD). Multiple-flow FeNO and eCO analyses were performed in this population. The associations of these biomarkers with pulmonary function, acute exacerbations, and radiologic fibrosis classification were evaluated. Results: Patients with IPF exhibited significantly higher levels of FeNO at 50 mL/s (FeNO50) compared to those with connective tissue disease-associated ILD (CTD-ILD) and IPAF. Both CaNO and eCO were negatively correlated with pulmonary function parameters, particularly forced vital capacity (FVC) and diffusing capacity of the lung for carbon monoxide (DLCO). Receiver operating characteristic (ROC) curve analysis indicated that CaNO is a reliable biomarker for acute exacerbation, with an area under the ROC curve (AUC) of 0.8887, and a cutoff value of 6.35. Additionally, CaNO > 6.35 was associated with a relative risk (RR) of 12.87 for acute exacerbation (AE) compared to CaNO ≤ 6.35. Moreover, both CaNO and eCO levels were significantly higher in the fibrotic ILD group compared to the non-fibrotic group, with ROC analysis indicating AUCs of 0.7173 for CaNO and 0.6875 for eCO. Conclusions: FeNO, CaNO, and eCO can provide strong support for the early diagnosis and monitoring of ILD, especially with CaNO playing a crucial role in predicting acute exacerbations. Integrating these biomarkers into clinical practice can help doctors more accurately assess the progression of ILD and develop personalized treatment plans, ultimately improving the prognosis of ILD patients. Future research is needed to validate the effectiveness of these biomarkers in clinical management, facilitating their integration as standard tools for clinical monitoring. Full article

Objectives: Female fertility is increasingly threatened by environmental pollutants such as fine particulate matter (PM_2.5 and NO₂), endocrine-disrupting chemicals (BPA, phthalates, PFAS, and PCBs), and microplastics. These exposures are associated with impaired ovarian reserve, reduced implantation rates, and lower assisted reproductive technology (ART) success. Given the rising prevalence of obesity and weight-loss interventions, particularly bariatric surgery, understanding the combined influence of metabolic and environmental factors on reproductive outcomes is of critical importance. This review aimed to synthesize recent evidence on how these exposures interact to affect female fertility. Methods: A narrative review was conducted of studies published between 2019 and 2025 using PubMed, Google Scholar, Web of Science, and Wiley Online Library. The PubMed Boolean search string was “female fertility”, “ovarian function”, “IVF” and “pollution”, “endocrine disruptors”, “air pollutants”, and “microplastics”. Searches were limited to English language publications, with the last search performed on 30 March 2025. Human, animal, and in vitro data were screened separately. Human evidence was prioritized, and confounding factors (age, BMI, and smoking) were considered during interpretation. Results: Environmental pollutants were consistently associated with diminished ovarian reserve, poor oocyte quality, and reduced live birth rates in ART. PFAS exposure correlated with lower fecundability, while PM_2.5 and NO₂ were linked to decreased AMH and AFC levels. Mechanistic animal and in vitro studies support these findings through pathways involving oxidative stress, endocrine disruption, and epigenetic alterations. Rapid metabolic changes, particularly post-bariatric surgery, may transiently increase circulating lipophilic toxicants and reduce antioxidant defenses, amplifying reproductive vulnerability. Conclusions: Environmental exposures, especially PM_2.5, NO₂, PFAS, and microplastics, adversely influence ovarian and embryonic competence. Rapid metabolic transitions may further modulate this susceptibility through pollutant mobilization and micronutrient imbalances. Future interdisciplinary prospective studies integrating exposure monitoring, metabolic profiling, and reproductive endpoints are essential to guide clinical recommendations and precision fertility counseling. Full article