How School Burnout Affects Depression Symptoms Among Chinese Adolescents: Evidence from Individual and Peer Clique Level.

The impact of peer clique school burnout norms on adolescents' emotional adaptation is becoming increasingly prominent, but its underlying mechanisms remain unclear, especially in China where academic achievement is highly valued. The present study examined how clique burnout norms impact the relationship between school burnout, negative cognitive bias, and depressive symptoms. A total of 904 Chinese adolescents (57% boys; Mage = 12.73, SD = 0.43) participated in a two-wave longitudinal study (initiated in 2015, with approximately a 2-year interval). The results of multilevel models indicated that only in low clique burnout norms, adolescents with high school burnout at T1 would exhibit more negative cognitive bias and suffer from more depressive symptoms at T2, whereas the moderating effect was only observed in all-boys cliques. These findings reflect that a decrease in the overall level of burnout within a peer clique does not necessarily benefit every student, and the adaptation issues of students experiencing burnout still require attention even in a relatively healthy context.

Machine Learning Accelerates Precise Excited-State Potential Energy Surface Calculations on a Quantum Computer.

Electronically excited-state problems represent a crucial research field in quantum chemistry, closely related to numerous practical applications in photophysics and photochemistry. The emerging of quantum computing provides a promising computational paradigm to solve the Schrödinger equation for predicting potential energy surfaces (PESs). Here, we present a deep neural network model to predict parameters of the quantum circuits within the framework of variational quantum deflation and subspace search variational quantum eigensolver, which are two popular excited-state algorithms to implement on a quantum computer. The new machine learning-assisted algorithm is employed to study the excited-state PESs of small molecules, achieving highly accurate predictions. We then apply this algorithm to study the excited-state properties of the ArF system, which is essential to a gas laser. Through this study, we believe that with future advancements in hardware capabilities, quantum computing could be harnessed to solve excited-state problems for a broad range of systems.

Module-combinatorial design and screening of multifunctional polymers based on polyaspartic acid for DNA delivery.

It is crucial to develop non-viral gene vectors that can efficiently and safely transfect plasmid DNA into cells. Low transfection efficiency and high cytotoxicity of cationic polymers hinder their application as gene carriers. Modification of cationic polymers has emerged as an attractive strategy for efficient and safe nucleic acids delivery. In this study, a simple and rapid method is developed to synthesize a series of multifunctional polymers by utilizing biodegradable polyaspartic acid as the backbone and modifying it with three modules. This one-component polymer possesses capabilities for nucleic acid condensation, cellular uptake, and endosomal escape. Polymers containing imidazole, triazole, or pyridine group exhibited promising transfection activity. Substituted with dodecylamine or 2-hexyldecan-1-amine enhance cellular uptake and subsequent transfection. Furthermore, the influence of ionizable amine side chains on gene delivery is investigated. Two optimal polymers, combined with the avian encephalomyelitis virus (AEV) plasmid vaccine, induced robust specific antibody responses and cellular immune responses in mice and chickens. Through module-combination design and screening of polyaspartamide polymers, this study presents a paradigm for the development of gene delivery vectors.

From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning.

Data scarcity is one of the critical bottlenecks to utilizing machine learning in material discovery. Transfer learning can use existing big data to assist property prediction on small data sets, but the premise is that there must be a strong correlation between large and small data sets. To extend its applicability in scenarios with different properties and materials, here we develop a hybrid framework combining adversarial transfer learning and expert knowledge, which enables the direct prediction of carrier mobility of two-dimensional (2D) materials using the knowledge learned from bulk effective mass. Specifically, adversarial training ensures that only common knowledge between bulk and 2D materials is extracted while expert knowledge is incorporated to further improve the prediction accuracy and generalizability. Successfully, 2D carrier mobilities are predicted with the accuracy over 90% from only crystal structure, and 21 2D semiconductors with carrier mobilities far exceeding silicon and suitable bandgap are successfully screened out. This work enables transfer learning in simultaneous cross-property and cross-material scenarios, providing an effective tool to predict intricate material properties with limited data.

Heterogeneous solvent-metal-free aerobic oxidation of alcohol under ambient conditions catalyzed by TEMPO-functionalized porous poly(ionic liquid)s.

Heterogeneous solvent-metal-free aerobic oxidation of alcohols under ambient conditions is interesting but remains a significant challenge. Herein, a series of porous TEMPO-functionalized poly(ionic liquid)s (TEMPO-PILs) featuring a pure polycationic framework were successfully developed through the free radical polymerization of the ionic liquid 3-(2-chloroacetic acid-2,2,6,6-tetramethyl-1-oxo-4-piperidyl)-1-vinylimidazolium chloride and bis-vinylimidazolium bromide salt. Characterizations revealed that the obtained TEMPO-PILs possessed a high TEMPO density, abundant bromide ions, and a tunable porous structure, which enabled them to serve as solvent-free heterogeneous organocatalysts for the metal-free aerobic oxidation of benzyl alcohol under ambient conditions, exhibiting high catalytic activity and stable recyclability. A high yield of 99% coupled with a turnover frequency (TOF) of 13.3 h-1 was obtainable, which is higher than most of the reported TEMPO-based heterogeneous catalysts, even superior to homogeneous TEMPO-functionalized ionic liquids. Furthermore, a broad range of alcohols were effectively converted into their corresponding ketones and aldehydes. A possible reaction mechanism is proposed for understanding the catalytic oxidation behavior, indicative of the synergistic effect of TEMPO moieties and bromide ions.

How does the biochar-supported sulfidized nanoscale zero-valent iron affect the soil environment and microorganisms while remediating cadmium contaminated paddy soil?

In previous studies, iron-based nanomaterials, especially biochar (BC)-supported sulfidized nanoscale zero-valent iron (S-nZVI/BC), have been widely used for the remediation of soil contaminants. However, its potential risks to the soil ecological environment are still unknown. This study aims to explore the effects of 3% added S-nZVI/BC on soil environment and microorganisms during the remediation of Cd contaminated yellow-brown soil of paddy field. The results showed that after 49 d of incubation, S-nZVI/BC significantly reduced physiologically based extraction test (PBET) extractable Cd concentration (P < 0.05), and increased the immobilization efficiency of Cd by 16.51% and 17.43% compared with S-nZVI and nZVI/BC alone, respectively. Meanwhile, the application of S-nZVI/BC significantly increased soil urease and sucrase activities by 0.153 and 0.446 times, respectively (P < 0.05), improving the soil environmental quality and promoting the soil nitrogen cycle and carbon cycle. The results from the analysis of the 16S rRNA genes indicated that S-nZVI/BC treatment had a minimal effect on the bacterial community and did not appreciably alter the species of the original dominant bacterial phylum. Importantly, compared to other iron-based nanomaterials, incorporating S-nZVI/BC significantly increased the soil organic carbon (OC) content and decreased the excessive release of iron (P < 0.05). This study also found a significant negative correlation between OC content and Fe(II) content (P < 0.05). It might originate from the reducing effect of Fe-reducing bacteria, which consumed OC to promote the reduction of Fe(III). Accompanying this process, the redistribution of Cd and Fe mineral phases in the soil as well as the generation of secondary Fe(II) minerals facilitated Cd immobilization. Overall, S-nZVI/BC could effectively reduce the bioavailability of Cd, increase soil nutrients and enzyme activities, with less toxic impacts on the soil microorganisms.

Evidence-based practice attitudes, knowledge and skills of nursing students and nurses, a systematic review and meta-analysis.

AIM/OBJECTIVE: This study aims to carry out a meta-analysis of attitudes, knowledge, and skills level of nursing students and nurses in EBP, providing a reference for optimizing EBP education strategies. BACKGROUND: At present, no meta-analysis has been performed to quantitatively synthesize the attitudes, knowledge and skill levels of nursing students and nurses toward EBP. This makes it difficult to precisely identify the true level of EBP among nurses, implying that there is no evidence to support the adoption of EBP teaching strategies approaches. DESIGN: A total of 9 Chinese and English databases including CNKI, Wan fang, VIP, CBM, PubMed, Embase, Web of Science, Cochrane Library and CINAHL were used to search cross-sectional quantitative articles on EBP attitudes, knowledge and skills level of nurses and nursing students. The search time limit was from the inception of the database to September 2023. METHODS: Two researchers independently screened the literature and extracted the data. The Agency for Healthcare Research and Quality (AHRQ) was used to assess the quality of the included studies. Stata15.0 software was used for statistical analysis to summarize the scores of EBP attitude, knowledge and skills level of nursing students and nurses included in the study. RESULTS: A total of 25 cross-sectional studies from 13 countries were included, involving 11363 nursing students and nurses. The meta-analysis results revealed that nursing students and nurses lacked evidence-based practical knowledge and skills, with pooled mean scores of 3.06 (95 % CI: 2.72, 3.39), 2.91 (95 % CI: 2.60, 3.22), 4.31 (95 % CI: 4.08, 4.54) and 4.45 (95 % CI: 4.20, 4.70). In contrast, nursing students and nurses revealed a positive attitude towards EBP, with pooled mean scores of 3.57 (95 % CI: 3.28, 3.86) and 5.11 (95 % CI: 4.80, 5.42). Subgroup analysis revealed that senior nursing students and nurses with master's degree or above had higher attitudes, knowledge and skills. CONCLUSIONS: In summary, nursing students and nurses have a positive attitude towards EBP. However, they seem to lack the necessary knowledge and skills. Therefore, nursing educators should consider this as an opportunity to strengthen the teaching of their evidence-based practical knowledge and skills. This will lay a reference for developing nursing discipline.

A Radical Activation Strategy for Versatile and Stereoselective N-Glycosylation.

Previous N-glycosylation approaches have predominately involved acidic conditions, facing challenges of low stereoselectivity and limited scope. Herein, we introduce a radical activation strategy that enables versatile and stereoselective N-glycosylation using readily accessible glycosyl sulfinate as a donor under basic conditions and exhibits exceptional tolerance towards various N-aglycones containing alkyl, aryl, heteroaryl and nucleobase functionalities. Preliminary mechanistic studies indicate a pivotal role of iodide, which orchestrates the formation of a glycosyl radical from the glycosyl sulfinate and subsequent generation of the key intermediate, a configurationally well-defined glycosyl iodide, which is subsequently attacked by an N-aglycone in a stereospecific SN2 manner to give the desired N-glycosides. An alternative route involving the coupling of a glycosyl radical and a nitrogen-centered radical is also proposed, affording the exclusive 1,2-trans product. This novel approach promises to broaden the synthetic landscape of N-glycosides, offering a powerful tool for the construction of complex glycosidic structures under mild conditions.

Microbiota and metabolite alterations in pancreatic head and body/tail cancer patients.

Pancreatic head cancer (PHC) and pancreatic body/tail cancer (PBTC) have distinct clinical and biological behaviors. The microbial and metabolic differences in PHC and PBTC have not been studied. The pancreatic microbiota and metabolome of 15 PHC and 8 PBTC tissues and their matched nontumor tissues were characterized using 16S rRNA amplicon sequencing and untargeted metabolomics. At the genus level, Bradyrhizobium was increased while Corynebacterium and Ruminococcus were decreased in the PHC tissues (Head T) compared with the matched nontumor tissues (Head N) significantly. Shuttleworthia, Bacillus, and Bifidobacterium were significantly decreased in the PBTC tissues (Body/Tail T) compared with the matched nontumor tissues (Body/Tail N). Significantly, Ileibacterium was increased whereas Pseudoxanthomonas was decreased in Head T and Body/Tail T, and Lactobacillus was increased in Head T but decreased in Body/Tail T. A total of 102 discriminative metabolites were identified between Head T and Head N, which were scattered through linoleic acid metabolism and purine metabolism pathways. However, there were only four discriminative metabolites between Body/Tail T and Body/Tail N, which were related to glycerophospholipid metabolism and autophagy pathways. The differential metabolites in PHC and PBTC were commonly enriched in alpha-linolenic acid metabolism and choline metabolism in cancer pathways. Eubacterium decreased in Head T was positively correlated with decreased linoleic acid while negatively correlated with increased arachidyl carnitine and stearoylcarnitine. Bacillus decreased in Body/Tail T was negatively correlated with increased L-carnitine. These microbiota and metabolites deserve further investigations to reveal their roles in the pathogenesis of PHC and PBTC, providing clues for future treatments.

Development of Multifunctional Catalysts for the Direct Hydrogenation of Carbon Dioxide to Higher Alcohols.

The direct hydrogenation of greenhouse gas CO2 to higher alcohols (C2+OH) provides a new route for the production of high-value chemicals. Due to the difficulty of C-C coupling, the formation of higher alcohols is more difficult compared to that of other compounds. In this review, we summarize recent advances in the development of multifunctional catalysts, including noble metal catalysts, Co-based catalysts, Cu-based catalysts, Fe-based catalysts, and tandem catalysts for the direct hydrogenation of CO2 to higher alcohols. Possible reaction mechanisms are discussed based on the structure-activity relationship of the catalysts. The reaction-coupling strategy holds great potential to regulate the reaction network. The effects of the reaction conditions on CO2 hydrogenation are also analyzed. Finally, we discuss the challenges and potential opportunities for the further development of direct CO2 hydrogenation to higher alcohols.

Association between systemic immunity-inflammation index and psoriasis among outpatient US adults.

Background: Psoriasis is a chronic dermatological condition characterized by a complex pathogenesis that impacts approximately 3% of adults in the United States and brings enormous social burdens. For many diseases, the systemic immune-inflammatory index (SII), defined as neutrophils × platelets/lymphocytes, has been recognized as a prognostic indicator. Therefore, we conducted a cross-sectional study to assess the association between SII and psoriasis among outpatient US adults. Methods: In this cross-sectional study, we used data on the US adults 20 to 59 years of age from the National Health and Nutrition Examination Survey (NHANES) spanning 2003-2006 and 2009-2014. Sample-weighted logistic regression and stratified analysis of subgroups were used. Results: Among the 16,831 adults, there were 8,801 women and 8,030 men, with a psoriasis prevalence rate of 3.0%. A fully adjusted model revealed a positive association between a SII higher than 479.15 × 109/L and a high risk of psoriasis. According to subgroup analysis and interaction testing (p for interaction > 0.05), age, sex, alcohol drinking status, marital status, and body mass index (BMI) were not significantly correlated with this positive association. Conclusion: Our findings suggested that SII higher than 479.15 × 109/L was positively associated with a high risk of psoriasis among outpatient US adults. To the best of our knowledge, this is the first cross-sectional study using NHANES data focused on the risk of higher SII on psoriasis among outpatient US adults. The outcomes of this cross-sectional serve to supplement previous research, indicating a need for larger-scale prospective cohorts for further validation.

TORSEL, a 4EBP1-based mTORC1 live-cell sensor, reveals nutrient-sensing targeting by histone deacetylase inhibitors.

BACKGROUND: Mammalian or mechanistic target of rapamycin complex 1 (mTORC1) is an effective therapeutic target for diseases such as cancer, diabetes, aging, and neurodegeneration. However, an efficient tool for monitoring mTORC1 inhibition in living cells or tissues is lacking. RESULTS: We developed a genetically encoded mTORC1 sensor called TORSEL. This sensor changes its fluorescence pattern from diffuse to punctate when 4EBP1 dephosphorylation occurs and interacts with eIF4E. TORSEL can specifically sense the physiological, pharmacological, and genetic inhibition of mTORC1 signaling in living cells and tissues. Importantly, TORSEL is a valuable tool for imaging-based visual screening of mTORC1 inhibitors. Using TORSEL, we identified histone deacetylase inhibitors that selectively block nutrient-sensing signaling to inhibit mTORC1. CONCLUSIONS: TORSEL is a unique living cell sensor that efficiently detects the inhibition of mTORC1 activity, and histone deacetylase inhibitors such as panobinostat target mTORC1 signaling through amino acid sensing.

Fast Pure Shift NMR Spectroscopy Using Attention-Assisted Deep Neural Network.

Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi-dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention-assisted deep neural network. This deep learning protocol allows one to regain high-resolution signals and suppress undersampling artifacts, as well as furnish high-fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention-assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI-assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

Navigating new horizons: Prospects of NET-targeted radiopharmaceuticals in precision medicine.

In the evolving landscape of precision medicine, NET-targeted radiopharmaceuticals are emerging as pivotal tools for the diagnosis and treatment of a range of conditions, from heart failure and neurodegenerative disorders to neuroendocrine cancers. This review evaluates the advancements offered by 18F-labeled PET tracers and 211At alpha-particle therapy, juxtaposed with current 123I-MIBG SPECT and 131I-MIBG therapies. The enhanced spatial resolution and capability for quantitative analysis render 18F-labeled PET tracers potential candidates for improved detection and management of diseases. Alpha-particle therapy with 211At may offer increased specificity and tumoricidal efficacy, pointing towards a shift in therapeutic protocols. While preliminary data is promising, these innovative approaches require thorough validation against current modalities. Ongoing clinical trials are pivotal to confirm the expected clinical benefits and to address safety concerns. This review underscores the need for rigorous research to verify the clinical utility of NET-targeted radiopharmaceuticals, which may redefine precision medicine paradigms and significantly impact patient care.

Amplification editing enables efficient and precise duplication of DNA from short sequence to megabase and chromosomal scale.

Duplication is a foundation of molecular evolution and a driver of genomic and complex diseases. Here, we develop a genome editing tool named Amplification Editing (AE) that enables programmable DNA duplication with precision at chromosomal scale. AE can duplicate human genomes ranging from 20 bp to 100 Mb, a size comparable to human chromosomes. AE exhibits activity across various cell types, encompassing diploid, haploid, and primary cells. AE exhibited up to 73.0% efficiency for 1 Mb and 3.4% for 100 Mb duplications, respectively. Whole-genome sequencing and deep sequencing of the junctions of edited sequences confirm the precision of duplication. AE can create chromosomal microduplications within disease-relevant regions in embryonic stem cells, indicating its potential for generating cellular and animal models. AE is a precise and efficient tool for chromosomal engineering and DNA duplication, broadening the landscape of precision genome editing from an individual genetic locus to the chromosomal scale.

An NIR Type I Photosensitizer Based on a Cyclometalated Ir(III)-Rhodamine Complex for a Photodynamic Antibacterial Effect toward Both Gram-Positive and Gram-Negative Bacteria.

Type I photosensitizers offer an advantage in photodynamic therapy (PDT) due to their diminished reliance on oxygen levels, thus circumventing the challenge of hypoxia commonly encountered in PDT. In this study, we present the synthesis and comprehensive characterization of a novel type I photosensitizer derived from a cyclometalated Ir(III)-rhodamine complex. Remarkably, the complex exhibits a shift in absorption and fluorescence, transitioning from "off" to "on" states in aprotic and protic solvents, respectively, contrary to initial expectations. Upon exposure to light, the complex demonstrates the effective generation of O2- and ·OH radicals via the type I mechanism. Additionally, it exhibits notable photodynamic antibacterial activity against both Gram-positive and Gram-negative bacteria, demonstrated through in vitro and in vivo experiments. This research offers valuable insights for the development of novel type I photosensitizers.

Comprehensive molecular characterization of long-term glioblastoma survivors.

Fewer than 5 % glioblastoma (GBM) patients survive over five years and are termed long-term survivors (LTS), yet their molecular background is unclear. The present cohort included 72 isocitrate dehydrogenase (IDH)-wildtype GBM patients, consisting of 35 LTS and 37 short-term survivors (STS), and we employed whole exome sequencing, RNA-seq and DNA methylation array to delineate this largest LTS cohort to date. Although LTS and STS demonstrated analogous clinical characters and classical GBM biomarkers, CASC5 (P = 0.002) and SPEN (P = 0.013) mutations were enriched in LTS, whereas gene-to-gene fusions were concentrated in STS (P = 0.007). Importantly, LTS exhibited higher tumor mutation burden (P < 0.001) and copy number (CN) increase (P = 0.013), but lower mutant-allele tumor heterogeneity score (P < 0.001) and CN decrease (P = 0.026). Additionally, LTS demonstrated hypermethylated genome (P < 0.001) relative to STS. Differentially expressed and methylated genes both enriched in olfactory transduction. Further, analysis of the tumor microenvironment revealed higher infiltration of M1 macrophages (P = 0.043), B cells (P = 0.016), class-switched memory B cells (P = 0.002), central memory CD4+ T cells (P = 0.031) and CD4+ Th1 cells (P = 0.005) in LTS. We also separately analyzed a subset of patients who were methylation class-defined GBM, contributing 70.8 % of the entire cohort, and obtained similar results relative to prior analyses. Finally, we demonstrated that LTS and STS could be distinguished using a subset of molecular features. Taken together, the present study delineated unique molecular attributes of LTS GBM.

In situ phytoextraction of Mn and NH4+-N from aqueous electrolytic manganese residue solution by Pistia stratiotes: Effects of Fe/Co presence and rhizospheric microbe synergistic involvement.

The electrolytic manganese industry produces a large amount of electrolytic manganese residue (EMR). Soluble Mn, NH4+-N, and other pollutants may be released from the open-air stacked EMR and transported to the environment along with rainfall or surface runoff. Aqueous EMR solution (AES) generally contains various elements required for plant growth, and phytoremediation can be applied to remove these pollutants from AES. Since the contents of Fe and Co vary greatly in AES depending on the ore sources as well as the pre-treatment processes, the presence of bioavailable Fe and Co at different levels may affect plant growth, the rhizosphere microbes, and pollutant removal. The present study investigated the in-situ removal of Mn(II) and NH4+-N from AES solution using free floating aquatic plant Pistia stratiotes, focusing especially on the effects of Fe/Co presence and rhizospheric microbe synergistic involvement on contaminant removal. The results showed that 69.08% of Mn and 94.99% of NH4+-N were removed by P. stratiotes in 24 d. Both the presence of Fe(II) and Co(II) facilitated the Mn(II) immobilization and increased Mn(II) removal by 19-31% due to the enhanced peroxidase activity and the increased Mn accumulating in roots The complete removal of Mn from AES was found in the presence of Fe(II) at 2 mg L-1 or Co(II) at 0.5 mg L-1 and more than 51% accumulated Mn in the roots was stored in the vacuole and cytoplasm. BioMnOx was found on the surface of the roots, revealing that rhizofiltration, rhizospheric plaque/biofilm formation, and Mn biogeochemical cycle exert synergic effects on Mn(II) immobilization. The findings of the present study demonstrate the feasibility of using P. stratiotes in the treatment of aqueous EMR solutions and the presence of an appropriate amount of bio-available Fe and Co can promote the removal of Mn(II) and NH4+-N.

Effect of dental chew on reducing dental plaque, dental calculus and halitosis in beagle dogs.

Periodontosis is the most common clinical disease in adult dogs, which is mainly caused by plaque accumulation and seriously endangers the oral health of dogs and even cause kidney, myocardial, and liver problems in severe cases. The aim of this study was to determine the clinical efficacy of dental chew (Cature Brushing Treats product) with mechanical and chemical properties in beagles. The dogs in the experimental group were fed with a dental chew twice a day after meals; The control group had no treatment. Dental plaque was evaluated on the 14th day and 29th day, respectively. The concentration of volatile sulfur compounds (VSC) in the breath and dental calculus were also evaluated on the 29th day. The results showed that there was no significant difference in the indexes of dental plaque on the 14th day. While they had significantly reduced accumulation of plaque (37.63%), calculus (37.61%), and VSC concentration (81.08%) compared to when receiving no chew on the 29th day.

Optical biomarker analysis for renal cell carcinoma obtained from preoperative and postoperative patients using ATR-FTIR spectroscopy.

Renal cell carcinoma (RCC) is the most common malignant tumor in the urinary system, accounting for 80 % to 90 % for all renal malignancies. Traditional diagnostic methods like magnetic resonance imaging (MRI) and computed tomography (CT) lack the sensitivity and specificity as they lack specific biomarkers. These limitations impede effective monitoring of tumor recurrence. This study aims to employ Attenuated Total Reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy, an optical technology sensitive to molecular groups, to analyze the potential optical biomarkers in urine and plasma samples from RCC patients pre- and post-surgery. The results reveal distinctive spectral information from both plasma and urine samples. Post-surgery urine spectra exhibit complexity compared to plasma, showing reduced content at 1072 cm-1, 1347 cm-1 and 1654 cm-1 bands, while increased content at 1112 cm-1, 1143 cm-1, 1447 cm-1, 3334 cm-1 and 3420 cm-1 bands. Utilizing machine learning models such as eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), and artificial neural network (ANN), the study evaluated plasma and urine samples pre- and post-surgery. Remarkably, the XGBoost method excelled in distinguishing between tumor conditions and recovery, achieving an impressive AUC value of 0.99. These results underscore the potential of ATR-FTIR technology in identifying RCC optical biomarkers, with XGBoost showing promise as a valuable screening tool for RCC recurrence diagnosis.