Tumour progression and metastasis remain the leading causes of cancer-related death worldwide. Tumour angiogenesis is essential for tumour progression. The vasculature surrounding tumours is not only a transport channel for nutrients, oxygen, and metabolites, but also a pathway for metastasis. There is a close interaction between tumour cells and endothelial cells in the tumour microenvironment. Recent studies have shown that tumour-associated endothelial cells have different characteristics from normal vascular endothelial cells, play an important role in tumour progression and metastasis, and are expected to be a key target for cancer therapy. This article reviews the tissue and cellular origin of tumour-associated endothelial cells and analyses the characteristics of tumour-associated endothelial cells. Finally, it summarises the role of tumour-associated endothelial cells in tumour progression and metastasis and the prospects for their use in clinical anti-angiogenic therapy. Angiogenesis was introduced by British surgeon John Hunter over 200 years ago to describe the growth of blood vessels in reindeer antlers . In 1971Angiogenesis is essential for tumour progression. Without blood vessels, tumours remain a mass of cells less than 2 mm in diameter . The bloThe success or failure of the tumour metastatic cascade response is highly dependent on the interactions between components of the tumour and the local microenvironment through a variety of bioactive molecules such as growth factors, cytokines, chemokines, and microRNAs . A partiVEGF-A (referred to as VEGF) is the major angiogenesis-inducing molecule released by tumour cells . Excess TECs are found on the inner surface of tumour vessels and are previously considered to be genetically stable . In factTumor blood vessels are the major source of TECs. TECs can be isolated using the endothelial markers, but they possess some specific characteristics, including the absence of von Willebrand factor (vWF), which distinguishes them from normal vascular endothelial cells .TECs including tumour-derived vascular endothelial cells (TDVEC) and tumour-derived lymphatic endothelial cells (TDLEC) have been identified in tumours. TEVEC isolated from malignant gliomas express an enriched angiogenesis-related gene profile, whereas TDLEC express interferon-alpha and interferon-beta, which may be involved in inflammation and immune cell recruitment . CompariDelivery of extracellular vesicles or non-coding RNAs into the tumour microenvironment plays an essential role in tumour angiogenesis . After oTumour stem cells may be involved in angiogenesis to form tumour vasculature. Cells derived from tumour to endothelial transdifferentiation express typical endothelial marker CD31 and vWF and stem cell markers such as Nestin and CD133, and cells contributed to vasculogenic mimicry lack CD34 and CD31 expression .Glioblastoma endothelial cells have a similar expression profile to other tumour cells. Glioblastoma stem cells positive for the stem cell marker CD133 may have an endothelial-like phenotype and function . HoweverAlthough transdifferentiation of tumor stem cells to enodothelial cells have been suggested in vasculogenic mimicry, whether tumour stem cells are origin of TECs and the transformation mechanism remains unclear.+CD45– progenitors formed entire blood vessels in wounds, inflamed skin, and tumors   . Anotherrs could . It is p+ circulating TECs are found in the peripheral blood of breast cancer patients  refers to the death of normal adnexal cells that are left suspended for long periods and become ‘homeless’. Non-coding RNAs are closely related to anoikis resistance of cancer cells . TECs wiAngiogenesis of lung TEC is closely associated with glycolysis and oxidative stress . InhibitFollowing first-line chemotherapy, the proportion of ABCB1-postive TEC in urothelial carcinoma was increased, which conferred drug resistance to the tumor .TECs isolated from highly metastatic human melanoma cell xenografts express high levels of multidrug resistance protein 1 (MDR1) and are resistant to the anticancer drug paclitaxel . CD105+ TECs highly express stemness markers such as CD105 and CD146 . The steTumour-associated vasculature is characterised by irregular morphology and structure, dysfunction, and reduced flow and leakage in comparison to normal vessels. The stiffness of tumour-derived extracellular matrix is increased, leading to high interstitial pressure . IncreasThe major characteristics of TEC are summarized in Tumour blood vessels, with abnormal thin-wall, contribute to metastasis . The immTECs may also provide signals that actively promote metastasis. CXCR7 regulated CXCL12-mediated migratory cues, driving CXCR4+CXCR7+ metastasis and tissue invasion . Howeverin vitro vascular model of neuroblastoma, the invasive behaviour of neuroblastoma cells co-cultured with human umbilical vein endothelial cells was significantly increased (TECs can transform tumour cells into more tumourigenic, invasive and chemoresistant cells . In a bincreased . By inhincreased .In addition, TECs can accelerate lung metastasis of tumour cells with low metastatic potential by releasing the vascular secretory factor biglycan . TECs exAnti-angiogenic drugs are currently used in a combination therapeutic model with immunotherapy and radiotherapy, which demonstrated promising anti-tumor activity in various advanced solid tumors . Anti-anDespite the benefits, anti-angiogenic therapies face challenges. Complications and adverse events such as hypertension, hand-foot syndrome, proteinuria and thyroid dysfunction can occur due to the adverse effect of anti-angiogenic drugs on normal blood vessels, as well as the possibility of drug resistance, which often requires drug replacement .in vitro evidence and possible mechanisms by which anti-angiogenic therapy may promote metastasis.Long-term anti-angiogenic therapy induces tumour hypoxia and invasiveness . HypoxiaTECs are mainly derived from tumour vasculature . They maTECs are distinctly different from normal endothelial cells, characterized by genetic instability, genetic heterogeneity, anoikis resistance, abnormal metabolism, resistance to anticancer drugs and adaptation to an abnormal mechanical microenvironment . TECs plFurthermore, the complexity of the tumour microenvironment and its intricate details remain unclear, and there is a lack of uniform standards for the detection of TECs. A comprehensive description of the tumour microenvironment and a better understanding of the mechanism underlying how TECs form and function will facilitate the design of novel approaches for overcoming resistance and monitoring the efficacy of anti-angiogenic therapy.


Clostridioides difficile exhibits phenotypic resistance to multiple classes of antibiotics. Associated antibiotic resistance genes (ARGs) are commonly transferred via mobile genetic elements, which often carry distinct ARG groupings. Increases in vancomycin non-susceptible C. difficile have been reported and understanding associated trends in ARG co-carriage are critical for strain transmission dynamics. Here we aimed to determine C. difficile resistome patterns associated with vancomycin non-susceptibility (NS).C. difficile isolated from adult patients hospitalized with C. difficile infection in two health systems  in the Houston Area between 2016–18. Isolates were ribotyped by fluorescent PCR and susceptibility tested by agar dilution in accordance with CLSI standards. Vancomycin NS was defined by minimum inhibitory concentrations (MICs) > 2 mg/L. Genome assembly and analysis was completed through The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) web resources.Whole genome sequencing (WGS) was performed (Illumina NextSeq 500) on Overall, 36% (13/36) of the cohort was vancomycin NS. The most common ribotypes were F106 (n=13), F027 (n=10), and F014-020 (n=7). Median ARG abundance was 46 (IQR 45 – 49) and included genes encoding targeted and non-specific  resistance. Specific antibiotics/classes targeted by identified ARGs included aminoglycosides, daptomycin, diaminopyrimidines, fluoroquinolones, fosfomycin, glycopeptides, isoniazid, lincosamides, macrolides, nitroimidazoles, oxazolidinones, rifamycins, streptogramins, and sulfonamides. Median ARG abundance did not differ between vancomycin NS (46.5 genes) and susceptible (46 genes) isolates and no differences in ARG patterns were observed. ARG abundance and patterns were similar amongst ribotypes.C. difficile vancomycin non-susceptibility did not correlate with increased ARG abundance or any distinct ARG patterns. Future studies investigating interactions and implications of the C. difficile resistome on the microbiome and host are warranted.Anne J. Gonzales-Luna, PharmD, BCIDP, Cidara Therapeutics: Grant/Research Support|Ferring Pharmaceuticals: Personal Fees|Paratek Pharmaceuticals: Grant/Research Support|Seres Therapeutics: Grant/Research Support Kevin W. Garey, PharmD, MS, Acurx: Grant/Research Support|Ferring: Advisor/Consultant|Paratek: Grant/Research Support


The thin needle is viewed as a revolutionary object since it has a thinner thickness than a boundary layer. As a consequence, scientific and engineering applications for instance electrical equipment, hot wire anemometers and geothermal power generation are significantly impacted by the flow deformed by a thin moving needle. MHD Eyring–Powell fluid flow over a thin needle perceiving heat source, chemical reaction and nonlinear thermal radiation is the subject of the current investigation. In addition, the present study utilizes the Buongiorno model to examine the special effects of the fluid's Brownian and thermophoretic forces. The solution of the dimensionless form of ODEs is produced by applying exact renovations to the given problem, which is determined by the structure of PDEs. The bvp4c algorithm, based on the finite difference approach is utilized to numerically solve such modified ODEs. For validation, the results obtained indicate good agreement when compared to the literature. Finally, a detailed graphical analysis of key parameters is shown and explained while keeping in mind the physical significance of flow parameters. The results show that as magnetic and fluid parameter values improve, the velocity gradient falls. Increasing heat source and radiation parameters optimises heat transfer rate. The augmentation of the Lewis number and chemical reaction accelerates the rate of mass transfer on the surface. Brownian motion and thermophoresis provide enhanced thermal performance for the fluid temperature. Growing the thermophoresis parameter from 0.1 to 0.3 upsurges the Nusselt number by 5.47% and the Sherwood number by 12.26%. The interest in non-Newtonian fluid flows has greatly risen in the last few decades owing to its extensive usage in the chemical process, food industry, building engineering, petroleum production, commercial and power engineering applications. The flow of non-Newtonian liquids around a stretched surface or a circular cylinder has numerous uses. It has attracted a great deal of curiosity to research various non-Newtonian fluid patterns. The Powell–Eyring fluid is an attractive non-Newtonian fluid that, despite being relatively complex, has numerous advantages among researchers3. Malik et al.4 conducted on convection in an MHD Eyring–Powell nanofluid over a stretching surface. They demonstrated that raising the mixed convection and fluid parameters accelerated the fluid. Hayat et al.6 explored Powell–Eyring fluid flow along a moving surface under a convective condition and a free stream. Malik et al.7 conducted an analytical study of heat transmission of Eyring–Powell liquid over a stretching cylinder with Vogel's and Reynolds forms of changing viscosity. The radiation's impact on Eyring–Powell fluid across an unstable oriented stretched sheet with a heat source/sink was evaluated by Hayat et al.8. The unsteady Eyring–Powell flow in a conduit with a porous surface was examined by Zaman et al.9. Rosca and Pop10 looked at how an Eyring–Powell fluid flows and transfers heat across a shrinking surface. Relevant components of the Eyring–Powell fluid flow have been examined in several studies14.The estimation of flow and mass transport in non-Newtonian fluids has generated considerable attention and debate plays an essential role in the industry, chemical engineering and biological processes. Examples of these sorts of uses include clay coatings, polymer production, and cosmetics. Due to the wide variety of non-Newtonian fluids, there is no one constitutive relationship between shear rate and stress that can account for all of the key rheological behaviour of such flows. Harris15. Afterwards, Eldabe et al.16 provided the MHD-free convective heat and mass transfer of Eyring–Powell fluid via a porous medium. The significance of magnetic flux over a thin needle moving vertically was searched by Salleh et al.17. MHD Williamson nanofluid moving thin needle flow was hypothetically directed by Khan et al.18. View some other notable research on MHD in22.Magnetohydrodynamics (MHD) is the learning of the magnetism and behaviour of conducting liquids. It is sometimes known as hydro-magnetism or magnetohydrodynamics. Magnetic fluids include liquid metal, plasma, electrolytes and salt water. The basic theory underlying MHD is that a magnetic field creates an electric current, which generates Lorentz force, which influences the flowing liquid. The optimal pre-use factor is required for both controlling the cooling rate and achieving acceptable product quality23 established the existence of such a concept by providing experimental validation of nanofluids. Dhanai et al.24 utilised the shooting methodology to present a solution of MHD power-law nanofluids caused by a shrinking/stretching surface. The numerical analysis of the MHD micropolar fluid flow on a contracting surface was done by Lund et al.25. The mixed convection of nanofluid contained in a thin needle was analyzed by Soid et al.26. A thin needle-induced variable fluid characteristic MHD flow of ceramic nanofluid was explored by Nayak et al.27. Alsenafi et al.28 discussed the heat transfer analysis with Blood-33.Common liquids are often not used extensively in a range of scientific and technical sectors due to their poor heat conductivity. Due to their undeniable thermal impact and unique applications in industries, biological research, and engineering sciences such as nuclear power, paper production, insolation collectors, glass-fibre manufacture, geothermal energy pipe cooling systems and heat transmission of heating nozzles in aircraft equipment, nanoparticles are gaining a lot of attention in the twenty-first century. Nanoparticles are small metallic particles (1–100 nm) having enhanced thermo-physical properties. Nanoparticles are sensitive to many interrelationships that may aid in the formation of particular turbidity patterns or the delimitation of density as well as the generation of nanoparticles and buoyant forces. Recently it was determined that nanofluids have higher thermal conductivity ratings than regular fluids. Choi34. Ishak et al.35 accomplished the double solution on a narrow needle. Waini et al.36 looked at the radiative flow rate of a fluid flowing on a thin needle. Afridi et al.37 exploited heat dissipation to induce entropy for nanofluid flow upon this thin needle. Trimbitas et al.38 examined the transmission of heat by convection on a vertical needle theoretically. The reader can further study thermal flows with fluid flowing over a thin needle in Refs.45.Thin needle geometry elaborates the blurring surface generated by spinning a parabola about its axis. In such geometries, physical events take place near the disparaging cylindrical tube with quasi-stiffness. The practical value of this particular geometry in a variety of areas, like blood flow challenges, cancer treatment, metal spinning, and led to its acceptance. Many researchers have investigated heat transmission and flow through the use of a moving thin needle. The boundary layer (BL) flow across a narrow needle was invented by Lee46 used chemical reactive phenomena to describe the convective heat flow for nanofluid over the permeable surface. Mabood et al.47 used chemically reactive effects over a needle. Ramzan et al.48 examined the stimulus of chemical process upon flow system on fluid flow across a needle. The MHD flowing for nanoparticles upon a horizontal surface has only been described by Makind and Animasaun49. Khan et al.50 have drawn a connection between the outcomes of a chemical reaction and a Casson fluid moving across a surface. The reader can further study about heat and mass transfer using chemical processes in Refs.56.There are many applications and importance of chemical processes in engineering, geophysics, and industry. Several chemical reactions are carried out in a reactor during industrial chemical operations to renovate less expensive crude resources into higher-standard products. The design of chemical processing machinery, blood pumping, food processing, blood pumping, glass production and other industrial processes all depend heavily on homogeneous/heterogeneous chemical reactions. Due to its benefit, distinct researchers have conducted evaluations for the thermal and mass flux that take into account how chemical reactions influence the flow system. Matin and PopWhat is the Eyring–Powell fluid's behaviour in the occurrence of a magnetic field parameter, and which fluid is most significantly impacted by the magnetic parameter?What is the behaviour of the Eyring–Powell fluids in the bearing of chemical reaction, and which fluid is most severely impacted by a chemical reaction?How do the heat sink/source, Brownian motion, and thermophoresis and for which fluid have a dominant impact?How does the nonlinear thermal radiation affect the Eyring–Powell fluids?To the extent that we are aware, no authors have taken into account this study. Until now, no research has been directed to demonstrate the 2-dimensional flow of an MHD Eyring–Powell fluid over a thin-needle in the dignity of a chemical reaction. Brownian motion, heat sink/source, thermophoresis and nonlinear thermal radiation are introduced in the report. The interaction of mass, momentum and energy culminates in the entire formulation of a nonlinear mathematical problem. The built-in finite difference method was used to perform nonlinear analysis on the velocity, Sherwood numbers, surface drag force, temperature, local Nusselt and nanoparticle concentration profiles. The authors must respond to the following research queries by the study's conclusion:x is the axial coordinate. The heat and momentum BL are thicker than the thin needle, which is thinner yet. The magnetic strength K) and 3) are the corresponding amounts at the needle's surface, whereas Consider the laminar, 2D, steady, MHD, and chemically reactive flow of Eyring–Powell nanofluid over the moving thin-needle in the availability of heat sink/source, thermophoresis, Brownian motion, and nonlinear thermal radiation. As presented in Fig. 42.The BL equations for continuity, thermal energy, momentum, and concentration can be stated in cylindrical coordinates under the aforementioned assumptionsIn Eqs. –4) the  the 4) t42;Now presenting the similarity transformationsFurthermore, assume The rate of heat transmission and surface drag force are acknowledged asExploiting (6), we getThe bvp4c technique is used to show the numerical solution of the altered Eqs.  to 9) w w9) withLet's take 42.In the present scenario, we choose an appropriate finite The exploration's focus on determining the manipulate of Brownian motion, nonlinear radiation and thermophoresis on the heat and mass transport properties of Eyring–Powell fluid flow via a thin-needle including chemical process. To get the desired results, the MATLAB-built bvp4c approach is used. For choose various values of the parameters such as 51, Ishak et al.35, Nadeem et al.42, and Song et al.29 see Table The findings for the code validation are remarkably comparable to the earlier research by HamidM on M reduces fluid velocity while an increase in fluid temperature. The drag force caused by the produced Lorentz force, which slows down the haphazard motion of fluid particles, is felt by the immersed nanoparticles as the magnetic flux strength steadily increases. Fluid velocity on a needled surface is slowed down by the resistance nanoparticles encounter. The heat released into the system and the thermal boundary profiles exhibit corresponding expansion when the slower fluid increases friction between the fluid layers. Figure H and Pr on the H and Pr heighten, so does the heat flow while the temperature and thermal BL thickness drop. The heat-generating mechanism boosts the fluid temperature in the BL zone of the needle by transmitting a substantial amount of heat energy from the needle to the liquid. The influence is more pronounced with lower Pr because its heat transmission rate is falling as the BL thickness, because the Pr is inversely related to thermal diffusivity.Figure Nb and Nt on Nb and Nt, raising the fluid temperature. The promptly moving molecules or atoms in the base fluid strongly influence the arbitrary moving of nanoparticles spread in it, known as Brownian motion. It occurs when molecules of liquids or gases and nanoparticles interact. Physically, a rise in the Nb is accompanied by a noticeable movement of nanoparticles, which raises their kinetic energy and causes them to produce more heat. In addition, this raises the liquid's temperature and the thickness of the thermal BL. This is because particles close to a hot surface produce a force called thermophoresis, which raises the liquid's temperature in the BL area. Thermo-phoresis is a process that pulls tiny particles from a hot surface to a cool one. This concept is supported by the fact that an elevation in Nt produces a stronger thermophoretic force, promoting further nanoparticle migrating from a heated surface to a cold ambient liquid, boosting the heat flux and escalating the thermal BL thickness. Figure Nt and Nb on Nt and Nb have a reverse influence on Nb drops it. The randomized mobility and the collision of the macroscopic particles in the fluid raise are realistically related to greater values of Nb. Also, Brownian motion is seen to be weaker for larger nanoparticles compared to smaller nanoparticles which reduce the fluid's concentration. As solid nanoparticles are thought to be spherical and evenly dispersed in ordinary fluid, the Nb in the Buongiorno pattern rises and falls to its size.Figure Le and Kr increase, the fluid concentration decrease. Rising Le values imply lower molecular movements, which declines the fluid concentration. A fluid with a higher Le has a lower Brownian diffusion, causing particles to diffuse deeper into the fluid. Therefore, greater values of the Le result in a lower concentration penetration depth. An interaction among two or more molecules that results in the formation of a new compound is known as a chemical reaction. Here, we take into account the constructive kind of chemical reaction, where fluid particles encounter a chemical reaction and merge for higher values of Kr. Also, as Kr increases, the chemical molecule's diffusivity declines and less diffusion appears. As a consequence, a rise in the Kr causes the reactant concentration to drop.Figure Table M is improved, the occurrence of a Lorentz force declines velocity while enhancing heat transfer, which also enables the Nusselt number of the fluid.When M lowers the surface drag force.The Nb is increased, the variance in nanoparticle concentration weakens, whereas Nt enhances the concentration.As the The Eyring–Powell fluid parameters display the opposite behaviour.The fluid behaves thermally better because of the thermophoresis and Brownian motion mechanisms. The consequences are also significant in the heating and cooling processes.Nr and temperature ratio values provide an optimum temperature gradient, which generates the highest heat transfer rate and causes the thermal profile to ascend.Larger As the chemical reaction and Lewis number are enhanced, the mass transfer rate is minimized.Increased Le, alpha and Kr increase the shoowerd number while demonstrating the opposite tendency.The The effects of varied thermal conductivity and variable viscosity can be added to the aforementioned investigation in the future. In addition, hybrid nanofluid may be used in place of the standard nanofluid in the current work.The current work used a binary chemical reaction to investigate a steady 2D MHD Eyring–Powell nanofluid flow over a thin needle that is moving horizontally. The system also includes a heat source/sink, the Begnano model, and nonlinear radiation. The similarity transformation and the bvp4c technique were operated to explain this system of equations, which resulted in the translation of the controlling PDEs into a pair of ODEs. Graphs have been used to discuss and show how different physical parameters affect the flow and thermal profiles. The following results of the study are highlighted:


The COVID-19 pandemic highlighted the potential pathogenicity of betacoronaviruses. This elucidates the need to further investigate human coronaviruses (HCoV), which includes both alpha and betacoronaviruses, to better understand their seasonality and severity among children.The New Vaccine Surveillance Network (NVSN) enrolled children at 7 pediatric medical centers in the United States seen at the emergency department (ED) or hospitalized with acute respiratory infection (ARI), during 12/1/2016–9/28/2020. Respiratory specimens were collected and tested using real-time reverse transcription polymerase-chain reaction assays. The frequency of seasonal HCoV  detections was measured and symptoms were reported by parent interview. Descriptive statistics were performed to compare HCoV-positive inpatients to those seen in the ED. SARS-CoV-2 infections were excluded.Of 34,455 children enrolled, 925 (2.7%) were positive for HCoV, of which 398 (43%) were inpatients and (57%) were ED patients (Table). 346 detections (37.4%) were HCoV-OC43, 298 (32.3%) HCoV-NL63, 186 (20.2%) HCoV-HKU1, and 107 (11.6%) HCoV-229E. More than one coronavirus was detected in 12 children (1.3%). HCoV were primarily detected between October and April of each season; 1 to 2 types dominated each year but not consecutively . Among HCoV-positive children, 527 (57.0%) received their highest level of care in the ED while 398 (43.0%) were hospitalized. HCoV-229E was the most common HCoV detected among inpatients (57.0%), followed by HCoV-HKU1-(45.2%); HCoV-OC43- (40.8%); and HCoV-NL63 (38.9%). Among those positive for a HCoV age, race, and insurance status were significantly associated with hospitalization.HCoV followed a winter-season circulation pattern, but with variation in the predominant type across years. HCoV-OC43 accounted for the largest number of HCoV infections whereas HCoV-229E had the highest proportion hospitalized. Further surveillance is required to evaluate the impact of the emergent circulation of SARS-CoV-2 on seasonal HCoVs.Natasha B. Halasa, MD, MPH, Merck: Grant/Research Support|Quidell: Grant/Research Support|Quidell: donation of kits|Sanofi: Grant/Research Support|Sanofi: vaccine support Rangaraj Selvarangan, BVSc, PhD, D(ABMM), FIDSA, FAAM, Abbott: Honoraria|Altona Diagnostics: Grant/Research Support|Baebies Inc: Advisor/Consultant|BioMerieux: Advisor/Consultant|BioMerieux: Grant/Research Support|Bio-Rad: Grant/Research Support|Cepheid: Grant/Research Support|GSK: Advisor/Consultant|Hologic: Grant/Research Support|Lab Simply: Advisor/Consultant|Luminex: Grant/Research Support Geoffrey A. Weinberg, MD, Merck & Co: Honoraria Janet A. Englund, MD, Ark Biopharma: Advisor/Consultant|AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Meissa Vaccines: Advisor/Consultant|Merck: Grant/Research Support|Moderna: Advisor/Consultant|Moderna: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant Pedro A. Piedra, MD, Ark Bioscience: Advisor/Consultant|Ark Bioscience: Grant/Research Support|GSK: Grant/Research Support|Icosavax: Advisor/Consultant|Icosavax: Grant/Research Support|Mapp Biologics: Grant/Research Support|Meissa Vaccines: Grant/Research Support|Moderna: Advisor/Consultant|Novavax: Advisor/Consultant|Novavax: Grant/Research Support|Sanofi-Pasteur: Grant/Research Support|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Takeda: Advisor/Consultant Mary A. Staat, MD, MPH, CDC: Grant/Research Support|Cepheid: Grant/Research Support|Merck: Grant/Research Support|NIH: Grant/Research Support|Pfizer: Grant/Research Support|Up-To-Date: Honoraria John V. Williams, MD, Merck: Grant/Research Support|Quidel: Board Member Marian G. Michaels, MD, MPH, Merck: Grant/Research Support|Viracor: Grant/Research Support


Although compounding has a long-standing tradition in clinical practice, insurers and pharmacy benefit managers have instituted policies to decrease claims for compounded medications, citing questions about their safety, efficacy, high costs, and lack of FDA approval. There are no reliable published data on the extent of compounding by community pharmacists nor on the fraction of patients who use compounded medications. Prior research suggests that compounded medications represent a relatively small proportion of prescription medications, but those surveys were limited by small sample sizes, subjective data collection methods, and low response rates.To determine the number of claims for compounded medications on a per user per year (PUPY) basis and the average ingredient cost of these claims among commercially insured patients in the United States for 2012 and 2013.This study used prescription claims data from a nationally representative sample of commercially insured members whose pharmacy benefits were managed by a large pharmacy benefit management company. A retrospective claims analysis was conducted from January 1, 2012, through December 31, 2013. Annualized prevalence, cost, and utilization estimates were drawn from the data. All prescription claims were adjusted to 30-day equivalents. Data-mining techniques (association rule mining) were employed in order to identify the most commonly combined ingredients in compounded medications.The prevalence of compound users was 1.1%  of eligible members in 2012 and 1.4%  in 2013, an increase of 27.3%. Approximately 66% of compound users were female, and the average age of a compound user was approximately 42 years throughout the study period. The geographic distribution of compound user prevalence was consistent across the United States. Compound users’ prescription claims increased 36.6% from 2012 to 2013, from approximately 7.1 million to approximately 9.7 million prescriptions. The number of claims for compounded medications increased by 34.2% during the same period, from 486,886 to 653,360. PUPY utilization remained unchanged at 2 prescriptions from 2012 to 2013. The most commonly compounded drugs were similar for all adult age groups and represented therapies typically indicated for chronic pain or hormone replacement therapy. The average ingredient cost for compounded medications increased by 130.3% from 2012 to 2013, from $308.49 to $710.36. The average ingredient cost for these users’ non-compounded prescriptions increased only 7.7%, from $148.75 to $160.20. For comparison, the average ingredient cost for all prescription users’ claims was $81.50 in 2012 and increased by 3.8% to $84.57 in 2013.Compound users represented 1.4% of eligible members in 2013. The average ingredient cost for compound users’ compounded prescriptions ($710.36) was greater than for noncompounded prescriptions ($160.20). The 1-year increase in average compounded prescription costs (130.3%) was also greater than for noncompounded prescriptions (7.7%). Although prevalence of compound users and the PUPY utilization for compounded prescriptions increased only slightly between 2012 and 2013, the mean and median cost of compounded medications increased dramatically during this time. Text mining revealed that drug combinations characteristic of topical pain formulations were among the most frequently compounded medications for adults. What is already known about this subjectScrutiny of compounded medications by insurers and regulatory agencies has recently increased. There are no published objective data on the number of compounded medications dispensed by community pharmacists nor on the costs associated with these prescriptions.Prior studies on the extent of compounding were based on surveys with small numbers of responses and respondents’ self-reported data.What this study addsThis is the first published study to profile trends in use and cost of compounded medications using an objective, nationally representative dataset.This study applies association data-mining procedures to discern the most often compounded drugs and the conditional likelihood to observe the occurrence of particular drug combinations.1 Pharmacy compounding allows for “the preparation, mixing, assembling, altering, packaging, and labeling of a drug, drug-delivery device, or device in accordance with a licensed practitioner’s prescription, medication order, or initiative based on the practitioner/patient/pharmacist/compounder relationship in the course of professional practice.”2Community pharmacists have traditionally compounded medications to provide patients with alternative doses or combinations of drugs, allergen-free formulations, or dosage forms that are not commercially available.5 A heightened focus has been placed on the practice of compounding by citizens, regulators, and insurers since the 2013 tragedy of contaminated steroid injections from the New England Compounding Center, which caused serious infections and other injuries to at least 751 patients and resulted in at least 64 patient deaths.8 The use of compounded oral, topical, and transdermal medications dispensed by community pharmacies is also increasingly being scrutinized.9 Proponents of compounding have argued that compounded medications represent invaluable personalized therapies for patients who are not treated adequately with traditional FDA-approved drug products.11Although compounding has a long-standing tradition in clinical practice, insurers and pharmacy benefit managers have recently instituted policies to decrease claims for compounded medications, citing questions about their safety, efficacy, high costs, and lack of U.S. Food and Drug Administration (FDA) approval.15 However, those studies were limited by small sample sizes, subjective data collection methods, and low response rates. As such, there are no reliable published data on the extent of compounding by community pharmacists nor on the fraction of patients who use compounded medications.Amid this debate, 2 important questions remain unanswered: How many patients use compounded medications per year, and how much do the medications cost? Survey research suggests that compounded medications represent a relatively small portion of prescription medications, ranging from 2.3% to 12.2%.17 With limited information about the usage patterns of compounded medications, prescription claim databases offer the advantages of objective data, sample sizes that are representative of a large proportion of the U.S. population, and detailed information on compounded medications.Considering that 61.8% of the U.S. population has private health insurance coverage and the Affordable Care Act requires prescription drug coverage as 1 of the 10 essential benefits that health plans must provide, prescription claims data can be leveraged to examine prevalence, cost, and use trends among compounded medications.The objective of this study was to determine the number of claims for compounded medications on a per user per year (PUPY) basis and the average ingredient cost of these claims among commercially insured patients in the United States for 2012 and 2013. An additional goal was to examine which drugs were most often compounded together.This study used prescription claims data from a nationally representative sample of commercially insured members whose pharmacy benefits were managed by a large pharmacy benefit management company. The health plan sponsors for these benefits included private- and public-sector employer groups, managed care organizations, third-party administrators, and unions. Inclusion was limited to members who were eligible for pharmacy benefits at any time between January 1, 2012, and December 31, 2013.A retrospective claims analysis was conducted from January 1, 2012, through December 31, 2013. Annualized prevalence, cost, and use estimates were drawn from the data. All prescription claims were adjusted to 30-day equivalents by dividing the days supply by 30.4. This normalization is based on an average month, calculated as 365 days per year ÷ 12 months per year = 30.4 days per month.Under provisions of the Health Insurance Portability and Accountability Act of 1996, all data specific to individual patients were removed from internal analytical datasets to maintain the privacy of protected health information. The study was declared exempt by both Southern Illinois University Edwardsville and St. Louis College of Pharmacy institutional review boards, as only de-identified administrative pharmacy claims data were used.The primary outcome measures were number and percentage of compound users by age bands, prevalence of users, PUPY utilization, and cost associated with compounded medication. Members were defined as persons eligible for prescription benefits at any time between January 1, 2012, and December 31, 2013. Prescription medication users were defined as members who had at least 1 claim for a prescription medication between January 1, 2012, and December 31, 2013. Compound users were defined as those prescription medication users who had at least 1 claim for a compounded medication during the same period. Compounded medications were identified at the point of service by the medication provider and submitted to the pharmacy benefit manager. Age categories were birth-9 years, 10-19 years, 20-29 years, 30-39 years, 40-49 years, 50-59 years, 60-69 years, and 70 years or older. The prevalence of compound users was calculated as the number of patients with at least 1 compound prescription in a calendar year divided by the number of members eligible for pharmacy benefits for that year, expressed as a percentage. Utilization measures were based on prescription claim counts. PUPY utilization for compounded medications was calculated as the number of 30-day adjusted compounded prescriptions divided by the number of compound medication users per year. Average cost per prescription was calculated by dividing the total ingredient cost of compounded medication claims by the number of 30-day adjusted compounded medication prescriptions per year. Ingredient cost was calculated according to the average wholesale price, without administrative or dispensing fees.Descriptive and bivariate statistics were generated for the prevalence of use, cost, and utilization measures for 2012 and 2013. Prevalence of compound users was analyzed by age groups and sex as well as by geography. Most often-used drugs were also analyzed by age group to detect similarities/differences in the type of compounded drugs used by patients in different age bands and sexes.23 However, to our knowledge, this is the first study to apply association rule mining to analyze compounded medications.In order to identify the most commonly combined ingredients in compounded medications, the data-mining technique of association rule was employed. Data mining is increasingly being used in health care research to examine myriad issues, including hospital infection control, screening of adverse drug reactions, prediction of heart disease, exposure to air pollution and respiratory illness, and diagnosis of medical conditions, and in clinical observations.A priori algorithms for association rule mining were used in this study to identify drugs that were most often compounded together. An a priori algorithm uses an iterative approach where n item sets are used to explore n + 1 item sets. In this study, item sets refer to unique drugs or different combinations of drugs. This approach efficiently ascertains frequent sets in data.To address the possibility of many frequently occurring combinations of drugs, minimum levels of support (frequency) and confidence  were used. Support refers to how many times a particular item/item set appears in the data, and confidence refers to the conditional probability of item y appearing when item/item set x is observed. In this study, we used a minimum support of 10% to determine how often a particular drug or a combination of drugs appeared in compound medication claims. In addition, a minimum confidence threshold of 50% was used to determine the drug combinations that occurred when a particular drug (with at least 10% support) was observed in compound medication claims.Claims from retail pharmacies constituted more than 99% of total claims for compounded medications. The remaining claims originated from hospitals, mail-order pharmacies, or other nonretail pharmacies.The demographics of the study population are summarized in Compound users represented 1.1% of members  in 2012 and 1.4% of members  in 2013. Compound users increased by 78,216 from 2012 to 2013, while members increased by 431,407. The prevalence of compound users thus increased by 27.3%, while the number of members increased by 1.9%. The prevalence of prescription medication users increased by only 1% during this time.The distribution of compound users by age and sex is shown in Figure 1. The distributions were similar for 2012  and 2013The prevalence of compound users by state of residence for 2013 is shown in Compound users’ prescription cost and utilization data are summarized in Ingredient cost statistics for compound users’ prescription claims are shown in The 10 drugs most frequently included in compounded prescriptions in 2013 are shown in A text-mining procedure was applied to 2013 data to reveal drug combinations that were frequently compounded together. Claims for compounded medications containing gabapentin  tended to also contain baclofen (67.7%), cyclobenzaprine (64.1%), and ketamine (52.2%). Cyclobenzaprine (72.9%), gabapentin (61.4%), and baclofen (60.6%) were frequently presented in claims with flurbiprofen. Neither progesterone nor fluticasone was associated with other drugs in the same claim at or above the 50% confidence level.The most frequently compounded drugs for children and adolescents (< 20 years of age) were more diverse than those for adults . The mos27 Custom Lipo-Max cream ; Lipoderm (PCCA); and Pracasil Plus (PCCA) are proprietary nonmedicated bases for topical drug products. Custom Lipo-Max appeared in the lists for all groups aged at least 10 years, and Lipoderm appeared in the lists for all groups aged at least 20 years. There were several differences between the lists of most expensive ingredients for 2012 (data not shown) and 2013 for patients older than 10 years. Gabapentin, ketoprofen, ketamine, cyclobenzaprine, and baclofen appeared on some of the lists for 2012, but with lower frequency than in 2013. Similarly, the nonmedicated topical bases appeared less frequently in 2012 than in 2013.The ingredients that contributed the greatest cumulative costs to compounded medication claims in 2013 are shown in The highest expense ingredients for patients younger than 10 years in both 2012 (data not shown) and 2013 primarily represented active drugs for treatment of a diverse array of medical conditions . The inactive ingredients were Pracasil Plus (2013), sodium bicarbonate (2013), and PCCA-Plus oral syrup vehicle (2012 and 2013).The current study has established that compound users represented a small but increasing proportion of eligible members for the study period of 2012-2013. The rate of increase in prevalence of compound users (27.3%) and the number of claims for compounded medications (34.2%) were several times greater than the rate of increase in eligible members (1.9%). Utilization was consistent at approximately 2 compounded prescriptions PUPY. There was a concurrent increase of 130.3% in the mean ingredient cost for compounded medications. The total ingredient costs for compounded medications increased from $134 million in 2012 to $457 million in 2013. These findings are significant for managed care providers as they reconcile providing access to medications for members while containing costs for clients. The increases in use and costs of compounded medications may indicate a nascent trend that managed care providers should understand and plan for.28 The coverage change incorporated inclusion of all ingredients in the compound medication for reimbursement as opposed to just the most expensive ingredient. Although the new standard went into effect January 1, 2012, pharmacy benefit managers had until April 1, 2012, to adopt and implement the standard. The pharmacy benefit manager providing data for this study adopted the standard starting January 1, 2012, but some claims that were inconsistent with D.0 were accepted until April 1, 2012. Implementation of the D.0 standard beginning in the second quarter of 2012 may have, in part, contributed to lower the ingredient costs for compounded medications in 2012.Compounded prescriptions represented a similar percentage of users’ total prescription claims in both years of the study . However, as a percentage of users’ total prescription cost, compounded medications increased by 76.2% from 2012 to 2013. The National Council for Prescription Drug Programs implemented the revised standard D.0, effective January 1, 2012.The decrease in median cost for compound users’ noncompounded prescriptions was surprising. Further investigation indicated that the primary cause was an increase in the generic fill rate for noncompounded prescriptions among these patients from 2012 to 2013 (data not shown).There appear to be no other data in the peer-reviewed literature with which to compare the results of this analysis. Prior research on compounding by community pharmacists relied on pharmacists’ self-reports of their prescription-dispensing volumes. The current data, on the other hand, represent a nationwide population and all of the claims submitted by eligible members for compounded medications for the 2 years studied. There are no comparable published data on compounded prescription costs.The prevalence of compound users was consistent across the United States, as most states exhibited rates similar to the national average. Only 4 states had a prevalence of compound users greater than 2% in 2013. Future research focused on states with high proportions of compound users may identify factors that predict compounded medication use and that contribute to the increasing number and costs of compounded prescriptions.29Given the variety of drug therapy problems that compounding can address, diversity in the most frequently compounded drugs by age and sex was expected. Claims for patients younger than 10 years represented several therapeutic indications. However, the most frequently compounded drugs and most expensive ingredients were very similar across all adult age and sex groups. For example, 20-29-year-old women and 60-69-year-old men had 9 of the 10 most frequently compounded drugs in common. The only drugs that were different between these groups were the hormone replacement products progesterone (women) and testosterone (men). The fact that pain management and hormone replacement were well represented in the most frequently compounded drugs is not surprising, as pharmacists have previously reported these as significant niche areas for pharmacy compounding, and two thirds of compound users were women.30 Pharmacists may develop drug formulations based on their own research and experience, or they may obtain standardized formulations from medical and pharmacy journals, compounding suppliers, or professional colleagues. Standardization is generally beneficial, in that pharmacists who employ well-characterized formulations are more likely to compound medications of high quality, safety, and purity.31 The high degree of association of several drugs in the same prescriptions suggests that a few standardized topical pain formulations were widely adopted.Prior research indicated that pharmacists were frequently called upon by physicians to recommend specific compounded formulations appropriate to their patients’ medical needs.the International Journal of Pharmaceutical Compounding (IJPC), for example, includes articles on professional and scientific issues related to compounding and specific example formulations for compounded medications. The formulations published in IJPC typically include quality control and stability information. The compounding supplier PCCA claims a “database of more than 8,000 proprietary formulations that have been pre-tested” and employs pharmacists to provide compounding-related technical support to their 3,600 member pharmacists in the United States.32 Thus it is plausible that the homogeneity in most frequently prescribed drugs was due, at least in part, to a few standardized topical pain formulations having been widely recommended by compounding pharmacists throughout the United States.The sources of the formulations have not been rigorously investigated. However, there are several references that pharmacists may use to support their compounding practice. Every issue of 40 The data suggest instead that most compounded medications were used for acute conditions. If so, the cost versus benefit relationship of the compounded medications would warrant further study, as there are numerous treatment modalities for acute pain syndromes, including manufactured drug products of several pharmacologic classes. It is also possible that the compounded medications were prescribed for chronic conditions, but the users discontinued them after a short duration of use for some reason, such as unsatisfactory therapeutic response or loss of insurance coverage. These data argue for research into patient satisfaction and adherence to therapy with compounded medications to elucidate the determinants of compounded medication use.The average utilization of 2 compounded prescriptions PUPY was unexpectedly low, considering that the most frequently compounded drugs were typically recommended for medical issues with longer expected durations of therapy, such as chronic pain and hormone replacement.3 While the full list is confidential, a subset of 25 noncovered ingredients was released to pharmacies. With the exceptions of lidocaine, testosterone, estradiol, estriol, progesterone, and triamcinolone acetonide, all of the 10 most frequently compounded drugs and 10 most expensive ingredients for adult age groups (≥ 20 years old) for 2013 appear on the excluded ingredient list (disclosed with permission). It is not clear if these exceptions will continue to be reimbursed. It is impossible to predict whether patients will continue to pay out of pocket for nonreimbursed compounded medications. However, the reimbursement of compounded medications for commercially insured patients is expected to decrease in 2014 due to the effects of the extensive ingredient exclusion lists.Health plans and pharmacy benefit managers have responded to the increase in the prevalence of compound users and costs of compounded medications by excluding ingredients used in compounding from reimbursement. Express Scripts announced in June 2014 that 1,000 ingredients used in compounding would no longer qualify for reimbursement beginning July 1, 2014.41 However, insured patients who purchased compounded medications from a nonparticipating pharmacy could submit a claim for reimbursement of the prescription, and those self-submitted claims were included in the database.There were several limitations, many of which were derived from the exclusive use of pharmacy claims data. The study population consisted only of commercially insured patients. Workers compensation claims, Medicare claims, and noninsured prescriptions were not represented in the study. The study population was members who were eligible at any time throughout the 2-year study period, so claims from chronic compound users who were not continuously eligible may have decreased the PUPY utilization value. An unknown fraction of pharmacies do not accept pharmacy benefit cards for compounded medications.The study results are generalizable to retail pharmacy claims, as they constituted more than 99% of the compounded medication claims. Claims from hospitals, mail-order pharmacies, or other nonretail pharmacies constituted less than 1% of the compounded medication claims.Finally, the data did not include medical claims or diagnosis codes associated with conditions for which compounded medications were being prescribed. Inferences regarding the therapeutic indications for compounded medications were based on the drugs’ therapeutic classifications and users’ age and sex.This is the first published study to profile trends in use of compounded medications using a diverse, nationwide pharmacy dataset. Compound users represented 1.4% of eligible members in 2013. The average ingredient cost for compound users’ compounded prescriptions ($710.36) was greater than for noncompounded prescriptions ($160.20). The 1-year increase in average compounded prescription costs (130.3%) was also greater than for noncompounded prescriptions (7.7%). Although prevalence of compound users and the PUPY utilization of compounded prescriptions increased only slightly between 2012 and 2013, the mean and median cost of compounded medications increased dramatically during this time. Text mining revealed that drug combinations characteristic of topical pain formulations were among the most frequently compounded medications for adults.


Their characterization comprises ultraviolet-visible spectroscopy, Fourier-transform infrared spectra, differential scanning calorimetry, scanning electron microscopy with energy-dispersive spectroscopy, and transmission electron microscopy assays. Moreover, the structural stability of the hydrogels was investigated through sequential swelling–deswelling cycles. The nanomaterials showed good mechanical properties in terms of their structural stability and revealed prominent antibacterial properties due to the reduced-size particles that promote their use as new advanced antimicrobial agents, an advantage compared to conventional particles in aqueous suspension that lose stability and effectiveness. Finally, theoretical analyses provided insights into the possible interactions, charge transfer, and stabilization process of nanoclusters mediated by the high-electron-density groups belonging to CS and HPMC, revealing their unique structural properties in the preparation of nano-scaled materials.In this work, we report a two-step methodology for the synthesis of small silver nanoparticles embedded into hydrogels based on chitosan (CS) and hydroxypropyl methylcellulose (HPMC) biopolymers. This method uses  Metal nanoparticles (NPs) are size- and shape-dependent atom clusters 1–100 nm) that stand out for their large specific surface area to volume ratio –100 nm t,3. In thAmong natural polymers, chitosan (CS) and hydroxypropyl methylcellulose (HPMC) are two polysaccharide-type macromolecules that have received significant attention in recent times, due to their biodegradability, biocompatibility, low cost, and interesting structural properties in the preparation of metallic particles ,11. In pFurthermore, biopolymeric materials such as CS and HPMC deserve special attention in the preparation of organic hydrogels a three-dimensional and crosslinked network of polymers needed for antimicrobial applications . During The novelty of the current work Is the fabrication of functional hydrogel–AgNPs materials using biopolymers (CS and HPMC) in environmentally friendly conditions without any organic solvents in order to set a simple protocol to reproduce. These hybrid composites were characterized with experimental techniques and then evaluated for their promising antibacterial applications, against both Gram-negative and Gram-positive bacteria. Additionally, a theoretical approach consisting of polymer–metal complexes was considered to gain insights into the interaction and stabilization mechanisms of selected nanocluster models, resulting in one of a few studies that complement experimental findings with computational analyses.3), N,N’-methylenebisacrylamide (MBA), tetramethylethylenediamine (TMEDA), ammonium persulfate (APS), and d-glucose were purchased from Sigma-Aldrich . Acrylamide (AAm) was obtained from Fischer Scientific . All chemicals were used without further purification. The water used in all experiments was purified using a Millipore Milli-Q system. Luria-Bertani broth (LB) and select agar were acquired from Invitrogen .Chitosan , hydroxypropyl methylcellulose , silver nitrate (AgNOw/v and 3% w/v). Later, CS and HPMC hydrogels were prepared in a 50 mL beaker by mixing 1 mL Milli-Q water and 1 mL of the polymer solution; then, the mixture was slowly stirred at ambient temperature before adding and dissolving the monomer . Next, the temperature was increased to 50 °C, and subsequently 1 mL of crosslinker MBA, 1 mL of activator TMEDA, and 1 mL of initiator APS were added. The free-radical polymerization (FRP) was carried out for 30 min until gelation was observed. Finally, hydrogel species were immersed in Milli-Q water to remove all the unreacted materials from the surface and inside the polymer matrix. The water was changed repeatedly every 6 h for 2 days. All gels were dried at ambient temperature for 2–3 days. The composition of the prepared hydrogels is depicted in Initially, stock solutions of CS were prepared in falcon tubes by dissolving different amounts of CS (2 mg/mL and 6.92 mg/mL) in 1% acetic acid solution (40 mL). Similarly, in the case of HPMC polymer, stock solutions were dissolved in 40 mL of Milli-Q water (0.5% 3 solution (52 mM) at room temperature. During this stage, silver ions are exchanged from the solution to inside the hydrogel network. Beakers were covered with aluminum foil to avoid silver salt decomposition by light. Afterward, the precursor solution was removed, and the gels were wiped off with tissue paper. The hydrogels were transferred to a beaker containing 25 mL of 1% d-glucose for 12 h at 60 °C. In this step, Ag+ ions are reduced into metallic silver (Ag) and are also stabilized by the internal structure of hydrogels [Firstly, 100 mg of dry gels were transferred to a 50 mL beaker and equilibrated overnight by adding 25 mL of AgNOydrogels ,16. FinaUV-vis measurements of the silver nanocomposites were carried out on a SpectraMax M2 Microplate Reader , operated in a range of 300–700 nm at a resolution of 1 nm. SoftMax Pro 7.0.3 was used for data acquisition and analysis. All graphs were plotted using Gnuplot 5.2 software .−1, on a Thermo Nicolet iS5  equipped with an iD7 ATR accessory , accumulating 300 scans per sample.Fourier transform infrared (FTIR) spectroscopy was used to record the spectra of pure CS and HPMC hydrogels and their silver nanocomposite counterparts. The samples were completely dried at 60 °C in an electric oven for 6 h before analysis and then were explored in a wavenumber range of 4000–500 cmTd) of the samples was established from the curve of heat flow vs. temperature using a Q2000 DSC . Heating scans were recorded between 5–200 °C at a scan rate of 10 °C/min under N2 flow (20 mL/min).Differential scanning calorimetry (DSC) was performed to evaluate the thermal stability of the CS and HPMC matrices. The denaturation temperature  . Samples were firstly frozen at −50 °C and coated with a 5.0 nm-thick carbon film using a low vacuum coater Leica EM-ACE200  and imaged with a secondary emission detector in a JSM-7500F FESEM  operated at 20 kV. Additional energy-dispersive spectroscopy (EDS) (Oxford X-ray INCA-EDS) analysis was also performed to study the elemental composition of the nanostructures. ImageJ 1.52   was usedTransmission electron microscope (TEM) images were collected to obtain insights about the size and morphology of the AgNPs embedded in CS and HPMC hydrogels. The samples were prepared by placing a drop of NPs resuspended from the composite hydrogels on a carbon-coated copper grid and subsequently drying in air, before transferring them to a JEM-2100F FETEM  microscope, operated at an accelerated voltage of 120 kV.Sg/g), according to a previously reported method [The water-absorbing capacity of the prepared hydrogels was evaluated through swelling ratio (d method . GravimeStaphylococcus aureus (ATCC 25923), as well as Gram-negative Pseudomonas aeruginosa (PAO1) and Escherichia coli (DH5α). Each strain was spread (100 µL) on the solid surface of the medium, containing around 106 CFU/mL. Afterward, swollen hydrogels (20 mg/1 mL) were cut into circular pieces (6.0 mm in diameter) before to being placed into the inoculated Petri dish and then incubated for 24 h at 37 °C. Hydrogels without AgNPs served as controls (pure CS and HPMC gels). At the end, the inhibition zones were measured and photographed.The antimicrobial properties of the silver nanocomposite hydrogels were qualitatively assessed through the agar diffusion test, using the standard method reported elsewhere ,32. Nutrn , taking as starting conformations those reported by Bonačić [In the first stage, the initial geometries of selected silver nanoclusters, Ag Bonačić , as well Bonačić  and then Bonačić . Full ge Bonačić ,37 witho Bonačić  was defi Bonačić  for Ag aFor the potential interactions between the silver nanoclusters and the polymers (CS and HPMC), in the next step, each optimized Ag cluster model was placed at 4 Å of each polymer, then all complexes were re-optimized at the 6-311G//LANL2DZ level. The GaussView 5 program was also used to explore the electronic structure in all optimizations.complexationE), as specified in Equation (2).n–CS and Agn–HPMC complexes, Agn free cluster, and free CS and HPMC polymer models, respectively. Thus, a negative value of Hence, the analysis of these interactions was focused on the complexation energies  analysis  was carrBoth chitosan (CS) and hydroxypropyl methylcellulose (HPMC) hydrogels were synthesized via the conventional FRP technique, i.e., the polymerization of base polymers in the presence of monomer AAm, cross-linker MBA, along with the initiator pair TMEDA/APS see . Pure CS3) and subsequent stabilization of AgNPs into the hydrogel network. In general, the chemical reduction of Ag+ ions leads to the formation of zerovalent silver (Ag0), followed by its agglomeration into metallic clusters, and at the end, silver particles are formed [d-glucose, a cost-effective and environmentally friendly reducing agent that can be easily integrated with natural polymers, to stabilize and protect the metal NPs [The preparation of silver nanocomposite hydrogels (CS/AgNPs and HPMC/AgNPs) initially involves the synthesis of pure hydrogels . In addition, the stretching of N–H bonds characteristic of the amide group is visible at 3186 cm−1. The absorption band that appeared at 1121 cm−1 is attributed to the C–O–C bending of the D-glucopyranose ring, whereas a very weak peak at 940 cm−1 was assigned to its β-configuration, confirming the presence of HPMC in the hydrogels [FTIR-ATR analysis is shown in ydrogels a, the stslinking . Amide Iydrogels . Followi−1. In particular, for CS/AgNPs hydrogels  and Gram-positive bacteria (S. aureus and E. coli) using the qualitative agar diffusion assay. Representative photographs are illustrated in The antibacterial activity of the prepared silver nanocomposites was evaluated against both Gram-negative , and the molecular models of both CS and HPMC polymers  analysis reveals negative values in all cases, indicating that the complex formation by CS and HPMC is energetically favored, showing minimum energy  analysis, it is simple to determine that an electron transfer from the polymer to the metal cluster occurred in all complexes, which is associated with the stabilization process. The net charge of the silver cluster in complexation with CS follows an increasing behavior, reaching the most negative value in the Ag8–CS complex (∆q = −0.483 a.u.), which agrees with its higher stability. Referring to HPMC complexes, the charge values also manifest an ascending trend, where the most negative value is consequently reached in the Ag8 cluster (−0.359 a.u.). However, in all silver nanoclusters, the charges are lower in the Agn–CS complexes as a sign of a higher amount of transferred electron density compared to Agn–HPMC complexes , and EA as the negative of LUMO energy (LUMOEA ≈ –E). The predicted IP and EA are summarized in n = 4–8 atoms. As the silver nanoclusters have higher IP and EA values than when forming complexes with CS or HPMC, the reactivity increases in these Agn-CS/HPMC systems, suggesting that the formation of metal aggregates is favored.Moreover, it is well established that electronic properties like ionization potential (IP) and electron affinity (EA) govern the reactivity of molecular systems. These properties can be estimated through the frontier molecular orbitals energies; according to Koopmans’ theorem ,74, IP c8, in complexation with CS and HPMC. As can be seen, both frontier orbitals are mainly localized on the silver clusters, suggesting a significant covalent character. The orbital mixing is also reflected in the other studied complexes: Ag2–, Ag4–, and Ag6–CS/HPMC.Finally, chemical bonding in metal complexes is determined by electrostatic and covalent interactions between the components. The covalent contribution is translated during the mixing of molecular orbitals, whereas the electrostatic effect is related to the atomic charges ,75. TherIn summary, we have synthesized and characterized hybrid composite hydrogels based on metallic silver nanoparticles and CS and HPMC biopolymers (CS/AgNPs and HPMC/AgNPs) through a simple and flexible two-step methodology. The swelling–deswelling cycles indicate that the developed nanocomposites have good mechanical properties in terms of their structural stability. Moreover, from the cryo-SEM studies, the nanostructures reveal a well-distributed cavity size, where the inclusion of AgNPs improved their thermal stability. The AgNPs deposited into hydrogels are small and spherical in shape, finding that both CS and HPMC polymers have a stabilizing effect, owing to their functional groups (hydroxyl or amino). Through TEM analysis, it was found that the diameters of the NPs were about 9 ± 3.4 nm and 12 ± 5.3 nm for CS-6.92/AgNPs and HPMC-3/AgNPs composites, respectively. The antibacterial assays showed significant inhibition zones against bacteria attributed to the reduced-size AgNPs, demonstrating the great potential of these silver nanocomposites for advanced antimicrobial applications. Despite the achieved results, additional evaluation of the prepared nanomaterials is needed, for instance, to perform cytotoxicity tests or quantitative antibacterial assays. Nevertheless, this method could be extended to other natural polymers and target metals  in the fabrication of metal composite hydrogels pursuing biomedical or pharmaceutical applications. Finally, theoretical calculations contributed to describe the covalent nature of the interactions between silver nanoclusters and CS and HPMC models, demonstrating that CS has a higher stabilizing effect over the studied complexes.


The primary endpoint was morbidity as assessed by the Clavien–Dindo (CD) score and the comprehensive complication index (CCI). Logistic regression models identified factors most predictive of postoperative morbidity. No association was found between postoperative morbidity and fluid management in the overall study population (p = 0.89). However, the normal fluid management group had shorter postoperative hospital stays (p = <0.001), shorter ICU stays (p = 0.035), and lower in-hospital mortality (p = 0.02). Elevated lactate levels (p < 0.001), duration (p < 0.001), and extent of surgery (p < 0.001) were the most predictive factors for postoperative morbidity. In the subgroup of major/extreme liver resection, very low total (p = 0.028) and normalized fluid balance (p = 0.025) (NFB) were associated with morbidity. Moreover, fluid management was not associated with morbidity in patients with normal lactate levels (<2.5 mmol/L). In conclusion, fluid management in liver surgery is multifaceted and must be applied judiciously as a therapeutic measure. While a restrictive strategy appears attractive, hypovolemia should be avoided.As optimal intraoperative fluid management in liver surgery has not been established, we retrospectively analyzed our fluid strategy in a high-volume liver surgery center in 666 liver resections. Intraoperative fluid management was divided into very restrictive (<10 m kg Liver surgery has become a safe treatment for primary and secondary liver tumors due to refinements in parenchymal transection and improved perioperative management. Compared to intestinal surgery, liver surgery is generally associated with higher blood loss, different metabolic stress responses, and organ-specific complications. In addition, liver surgery has higher morbidity and mortality rates compared to other surgical patient populations  ,2. InfloMore than 20 years ago, a low central venous pressure (CVP) strategy was identified as a strategy to reduce blood loss during liver surgery , since aThe enhanced recovery after surgery (ERAS) society also recommends balanced fluid management with the goal of euvolemia in liver surgery . AccordiHowever, optimal perioperative fluid management in patients undergoing major abdominal and, in particular, liver surgery is still under debate. Parameters to guide intraoperative fluid management have not yet been defined. Excessive fluid administration may compromise oxygenation  due to hThe aim of this study was to define solid parameters for optimal fluid management during general anesthesia for patients undergoing liver resection. Therefore, we compare the outcomes of patients with regard to intraoperative fluid management at a high-volume liver surgery center where general anesthesia is based on a low-fluid/low-CVP strategy.The data from patients who underwent liver resection at the Department of General, Visceral, and Transplantation Surgery of the University Medical Centre Mainz between December 2014 and September 2018 were analyzed. The primary data source was the hospital’s digital clinical database. The electronic health records were searched for operating codes 5-501 and 5-502 for liver procedures. Data were collected primarily to evaluate the influence of intraoperative fluid management on postoperative outcome in patients undergoing liver resection. Other risk factors for postoperative adverse events related to anaesthesiological management were also considered.The ethics committee of the Medical Association of the State of Rhineland–Palatine (Germany) approved this retrospective study (registration number: 2020-14894-retrospective) and waived the requirement for informed consent.Patients aged at least 18 years who underwent liver resection were eligible for analysis. We excluded liver transplantations and emergency procedures, as well as resections as part of other primary surgical procedures, due to special hemodynamic preconditions. We also excluded liver resections with an operative time of less than 70 min, incomplete documentation of intraoperative fluid administration, estimated blood loss, or diuresis . Only thThis is a retrospective analysis. The anesthesia team continuously documented intraoperative anesthesiological parameters .® ISO  is used as the standard crystalloid fluid according to ERAS recommendations [® 6% , Voluven® 6% , or gelatine solutions such as Gelafundin® ISO 40 mg mL−1 infusion solution  are administered. Intraoperative monitoring parameters, such as heart rate registration, invasive and non-invasive blood pressure measurements, SpO2 (% hemoglobin saturation), 5-channel echocardiogram, CVP, diuresis, estimated blood loss, and temperature (°Celsius), are used according to clinical standards. A pringle maneuver is applied on demand using an intermittent clamping strategy. Tissue dissection is usually performed mechanically using scissors or a crush-clamp technique. Hilar structures and hepatic veins are transected using vascular clamps and closed with prolene sutures. Postoperatively, patients are routinely monitored overnight in the recovery room. Depending on comorbidities, the extent of surgery, and the intraoperative course, patients may be transferred to the intermediate care unit (IMC) or intensive care unit (ICU). Patients are transferred to the regular ward the following day if there is no evidence of bleeding and hemodynamic support is not required. Pain management is based on intravenous analgesics such as metamizole and piritramid. Epidural anesthesia is not used for liver surgery.Patients scheduled for liver resection do not receive specific preoperative measures at our center. General anesthesia is routinely induced with propofol- and sufentanil-based injection anesthesia and maintained with balanced sevoflurane inhalation anesthesia. In general, fluid restriction with euvolemia and a low-CVP strategy are anticipated, and a decrease in arterial blood pressure of >20% is avoided. There was no standard operating procedure for fluid management in patients undergoing liver resection. Therefore, the intraoperative management decisions are made by the attending anesthesiologists, with potential patient-to-patient variability in the anesthesiological management based on provider preference. In general, balanced acetate and malate-buffered Sterofundinndations . For colLiver resections involving ≤3 segments were considered minor, whereas those involving four or more segments were considered major. Major resections with additional procedures such as portal vein or bile duct resection/reconstruction were categorized as extreme liver surgery.Total intraoperative total fluid balance (TFB) was calculated using the following formula:The total fluid balance was normalized for anesthesia time and patient weight (NFB).−1 h−1) or a normal fluid management group (≥10 mL kg−1 h−1) for study group characterization.Based on this intraoperative fluid management, patients were assigned to either a very restrictive fluid management group  was also documented. However, administration of erythrocytes, fresh frozen plasma (FFP), and platelets was not considered, as the volume is not standardized and can vary by 25–30%.The number of intraoperatively administered red blood cell units  ≤ 65 mmHg was established, and the influence on postoperative morbidity was investigated according to the same protocol.Postoperative morbidity based on the Clavien–Dindo (CD) classification is prospectively graded and documented in the surgical unit . In addiFor the analysis, the highest complication was considered for each patient, and the comprehensive complication index (CCI) was calculated, as a patient may have had several complications .−1 h−1 were categorized as having received very restrictive fluid management, whereas those with ≥10 mL kg−1 h−1 were categorized as having received normal fluid management. Logistic regression was used to predict a CD sum score of >0 vs. =0 from intraoperative fluid balance as a continuous risk factor, adjusting for sex, age, extent as well as duration of surgery, crystalloid infusion, last hemoglobin-level (<10 vs. ≥10 g/dL), highest intraoperative lactate level (<1.5 vs. ≥1.5 mmol∙L−1), norepinephrine, red blood cell transfusion, estimated blood loss, time of relative hypotension (<100 vs. ≥100 min), and ASA physical status (I/II vs. III/IV). Linear regression modelling was used to examine intraoperative fluid management as a continuous risk factor for postoperative complications graded by the CCI, adjusting for the same set of covariates. The association of postoperative length of stay with intraoperative fluid management was analyzed using Cox regression, adjusting for the same set of covariates. For patients admitted to the ICU, the association between ICU length of stay and intraoperative fluid management was examined using Cox regression with the same set of covariates. For these analyses, all IMC and ICU days per patient were summed, whereas overnight observation in the recovery room was not considered an ICU stay. Logistic regression for in-hospital mortality used continuous intraoperative fluid balance as a risk factor, adjusting for age, extent, duration of surgery, and crystalloid infusion rates. Here, the number of possible covariates was limited by the number of observed deaths. Linear regression for the log of norepinephrine normalized to patient weight and duration of anesthesia was used to examine the association of pharmacological vasoactive support with intraoperative fluid management, controlling for age. Hypotheses regarding intraoperative fluid management as a risk factor for postoperative complications were predefined. Additional exploratory analyses were performed to examine other risk factors for postoperative surgical adverse events. Finally, subgroup analyses were performed using logistic regression models for major and extreme liver resections and for the subgroup of normal lactate levels at the end of surgery for the same endpoints.The data were collected and independently checked for data entry errors by four authors. Data were analyzed using the statistical software R , version 4.2.2., and presented as mean ± SD or median for continuous variables and as frequencies and percentages for categorical variables. The primary endpoint was postoperative morbidity during hospitalization as assessed by the CD-classification (0 vs. 1–5) in any organ system. Secondary outcomes included morbidity assessed by the CCI, postoperative hospital and ICU length of stay, and in-hospital mortality. The postoperative hospital length of stay was measured from the date of surgery to hospital discharge. For the purpose of simple group comparison, patients with intraoperative NFB < 10 mL kgWe identified 820 patients scheduled for liver resection during the study period, of whom 666 met the eligibility criteria for this analysis .−1 h−1) and 275 patients to the normal (≥10 mL kg−1 h−1) groups. Patient demographics and characteristics are summarized in Of these, 391 patients were assigned to the very restrictive (<10 mL kgMost resections involved less than four segments (minor), and one third of the resections were major/extreme resections (35.5%).The duration of surgery, postoperative hospital length of stay a, and ICp = 0.001) than younger patients. In addition, higher blood loss was associated with higher norepinephrine doses (p < 0.001).In general, older patients required higher doses of norepinephrine . Intraoperative NFB showed only an insignificant (p = 0.86) association with pharmacological vasoactive support.The mean intraoperative NFB was 9.77 ± 5.24 mL kg−1 h−1) compared to patients in the very restrictive group (11.9 ± 3.56 mL kg−1 h−1)  .p = 0.09).Patients in the normal group received 4500 mL  of crystalloids, in contrast to 4000 mL  in the very restrictive group. The total crystalloid infusion rate gradually increased with the extent of surgery, with minor liver resections receiving 2723 mL (−600–8700 mL), major resections receiving 3203 mL (100–8100 mL), and extreme resections receiving the highest with 3884 mL , and 393/666 (59.9%) of patients required an ICU stay during the post-operative period for a median of 1 day (range 1–45 days).p < 0.001) and duration of liver surgery (p < 0.001) were associated with a longer hospital length of stay. While higher total (p = 0.004) and NFB  were associated with a longer hospital length of stay (The extent ( of stay .p = 0.008), a shorter duration of surgery (p < 0.002), and a lower NFB  had a post-operative complication, the majority of which were grade III (21.5%). The median CCI was 20.9.p < 0.001) and duration of surgery (p < 0.001) were associated with morbidity: the median CCI gradually increased with the extent of surgery, as minor liver resections had a mean CCI of 18.5 (0–100), whereas major and extreme resections had median CCIs of 23.6 (0–100) and 40.3 (0–100), respectively , estimated blood loss (p < 0.001), and intraoperative vasoactive support with norepinephrine (p = 0.02) were associated with higher morbidity. We found no association of morbidity with the last intraoperative hemoglobin level (p = 0.022), the time of relative hypotension (p = 0.29), or intraoperative NFB (p = 0.89) (Increased intraoperative lactate levels ( = 0.89) .p < 0.001). Interestingly, a very low NFB was also associated with a higher mortality rate (p = 0.023) compared to the total population in the study  patients died. As expected, major/extreme liver resections were associated with a higher mortality rate (p = 0.10).Additionally, after applying a MAP ≤65 mmHg as the cut-off for hypotension in the regression analysis, we did not find a significant association with postoperative complications as measured by the CD score (p = 0.026). Again, NFB and CCI were not significantly associated (p = 0.23).In this analysis, we found a significant association between NFB and CD score (p = 0.023) and length of hospital stay (p = 0.0057). However, the length of the ICU stay was no longer significantly associated with NFB.Moreover, NFB was again significantly associated with perioperative mortality  was 33.5 (0–100), with a mortality rate of 9.3%.p = 0.002), duration of surgery (p < 0.002), as well as very low total (p = 0.028), NFB (p = 0.025), and crystalloid fluid supplementation (p = <0.0001), were associated with a higher CCI. In this subgroup of patients, the highest lactate level (p = 0.007), the dose of norepinephrine (p = 0.004), the amount of blood loss (p = 0.003), and red blood cell transfusions (p < 0.001) were also associated with the CCI.In major/extreme liver resections, patient age (p = 0.01) and the use of crystalloids (p = 0.02) were associated with a longer hospital length of stay.For the other parameters, the duration of surgery (p < 0.0001) was an independent factor associated with a longer ICU length of stay in this subgroup analysis.In contrast to the overall cohort, only the duration of surgery (p = 0.01).Regarding mortality, only the use of crystalloids was significantly associated with mortality (−1).We found an association between a very low TFB and a longer postoperative hospital length of stay, a longer ICU LOS, and a higher postoperative mortality rate. To analyze whether our general fluid management may have been too restrictive, and hypovolemia is often associated with elevated lactate levels, we excluded patients with elevated lactate levels and focused on patients with normal serum lactate levels .p = 0.01) in this subgroup. In addition, duration of surgery remained a significant factor for morbidity (p < 0.001), length of hospital stay (p < 0.001), and ICU (p < 0.001) stay.Neither morbidity nor ICU length of stay were associated with NFB or crystalloid balance in this subgroup. We only found a longer hospital length of stay following liberal fluid management  and the normal  fluid management regimen as assessed by CD-classification . UnfortuPostoperative surgical complications have a major impact on patients’ disability-free survival, increase costs, and are a major burden on the healthcare system ,24,25. TAs expected, the extent and duration of surgery were independent risk factors for postoperative adverse events. Although we excluded procedures lasting less than 70 min, the effect of “frontloading” cannot be precluded: shorter procedures are associated with higher relative fluid doses as they are given during the induction period. This assumption is supported by higher crystalloid infusion rates in shorter procedures. In addition to intraoperative parameters, comorbidities and postoperative management may influence surgical morbidity. Due to the study design, we cannot completely exclude the effect of such parameters on our results.With a CCI of 20.9 and a mortality rate of 4.5%, our results are well comparable with other large series on the outcome of liver surgery  and supeFurthermore, the exclusion of high-risk patients by subgroup analysis suggests that optimization of perioperative management further improves outcomes. In our center, we have generally adopted a restrictive fluid policy, using mainly crystalloids for fluid replacement as recommended by the ERAS society . In addiMoreover, these data should support a less dogmatic fluid management strategy in liver surgery. The aim of intraoperative fluid management is to support the surgical strategy of minimizing blood loss by reducing CVP, as this is a well-established outcome parameter in liver surgery . AccordiThe complex relationship between fluid administration and morbidity has been described as a U-shape, with the lowest morbidity in normovolemia and increased morbidity in hypo- and hypervolemia ,17. Our A wide range and variability in fluid management among patients undergoing liver resection have been shown to be multifaceted and influenced by factors at the patient, surgical, and provider levels . ConsideTherefore, a more sophisticated strategy is required, and several parameters have been proposed to optimize intraoperative fluid management. However, the ideal parameters for optimal fluid management have not yet been identified. Moreover, calculated fluid balances between centers and publications are difficult to compare since different parameters have been included. In addition, some authors report total fluid administration or a total fluid balance, while others normalize for body weight and/or duration of anesthesia. Consequently, the crude parameters are difficult to compare. We provide a range of parameters that all demonstrate the same associations with our endpoints. Still, intraoperative fluid loss due to perspiration and blood, platelet, or fresh frozen plasma resuscitation has not been included in our fluid management due to the wide variation in volume included and the study design.Serum lactate is a surrogate parameter for impaired tissue perfusion and a widely used outcome indicator in critically ill patients. Our data are consistent with the findings of Wiggans et al. .−1 h−1 to define fluid management groups was based on heuristics and should be regarded as exploratory. Future studies will need to assess whether end-point-specific thresholds or possibly non-linear dose–response models for continuous fluid management better reflect the underlying mechanisms.The current trend in abdominal surgery is shifting towards goal-directed fluid management . In liveDue to the association between elevated lactate levels and outcomes, we are now using this parameter more intensively to control fluid management. Each center should decide on its own individual strategy to avoid peripheral hypoperfusion due to hypovolemia. Blood transfusions should also be used with caution in major liver resections, given the association with morbidity in our series.Our study has several limitations. First, our study is retrospective, which limits our ability to control for confounding variables such as patient lifestyle factors and treatment compliance. These factors may have influenced the results we observed.Second, our study was conducted at a single center, which may limit the generalizability of our findings.Thirdly, we relied on electronic medical records to collect data on patient outcomes and intraoperative anesthetic management, so missing or incomplete information cannot be completely ruled out.Finally, despite the large sample size of 666 patients, no power calculation was performed prior to the study, which may limit the statistical power of our findings.In this retrospective study, the influence of intraoperative fluid management on postoperative morbidity in 666 patients undergoing liver surgery was assessed using the CD-score and CCI. Low NFB was associated with longer hospital and ICU lengths of stay and higher mortality. In the major extreme procedure subgroup, low NFB was associated with increased postoperative morbidity. In patients with normal lactate levels, there was no association between fluid management and morbidity.Our results suggest that fluid management in liver surgery requires a more sophisticated approach to optimal fluid administration. Our study provides important insights into the relationship between fluid management and postoperative outcome in liver surgery and adds to the scarce literature in this area. Due to the apparent impact of intraoperative fluid management, further research in this area is required. Large-scale, standardized, preferably prospective, randomized controlled trials in patients undergoing liver surgery are needed to define the ideal parameter for fluid assessment and optimal intraoperative fluid management. Future standards should be based on the size of the procedure.


Metabolomics may also be used in the quest for habitual diet-induced metabolic signals in amniotic fluid. Finally, analysis of amniotic fluid can provide information on exposure to exogenous substances by detecting the exact levels of metabolites carried to the fetus and associated metabolic effects.Fetal and perinatal periods are critical phases for long-term development. Early diagnosis of maternal complications is challenging due to the great complexity of these conditions. In recent years, amniotic fluid has risen in a prominent position in the latest efforts to describe and characterize prenatal development. Amniotic fluid may provide real-time information on fetal development and metabolism throughout pregnancy as substances from the placenta, fetal skin, lungs, gastric fluid, and urine are transferred between the mother and the fetus. Applying metabolomics to monitor fetal well-being, in such a context, could help in the understanding, diagnosis, and treatment of these conditions and is a promising area of research. This review shines a spotlight on recent amniotic fluid metabolomics studies and their methods as an interesting tool for the assessment of many conditions and the identification of biomarkers. Platforms in use, such as proton nuclear magnetic resonance ( In recent years, "omics" technologies have become popular and changed the scientific approach due to their role in describing diseases and biological systems through the mostly non-invasive analysis of large volumes of data ,2. Among1H-NMR) spectroscopy, gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS) [Thorough metabolite analysis in biological fluids and different tissues can provide a comprehensive functional phenotype that incorporates clinical features and genetic and non-genetic factors , allowinThe end phenotype is determined by environmental influences such as dietary and lifestyle, age, and intake of drugs or presence of disease . MetabolFetal and perinatal periods are critical phases of neonatal development. The stimuli and conditions to which the fetus is exposed are important factors for neonatal development . Early dThe scope of this narrative review was to synthesize available data on recent amniotic fluid metabolomics studies as an evolving tool for the assessment of many conditions and the identification of diagnostic and predictive biomarkers.Amniotic fluid in metabolomics-based studiesAmniotic fluid has risen in a prominent position among metabolomics substrates in the latest efforts to describe and characterize prenatal development, being one of the more useful biological fluids utilized, as it reflects the metabolic profile of the fetus . The amnPregnancy progression1H-NMR) [The metabolic pathways characteristic of amniotic fluid in normal pregnancies were summarized by Orczyk-Pawilowicz et al. via proton nuclear magnetic resonance spectroscopy (1H-NMR)  in the f1H-NMR) . In part1H-NMR) . There w1H-NMR) . Since r1H-NMR) . Therefo1H-NMR) .Preterm deliveryOne out of 10 deliveries is preterm and can be associated with varying degrees of severity and highly variable outcomes . The exaPrematurity and bronchopulmonary dysplasiaPrevious untargeted metabolomics data on 32 preterm infants aimed to predict preterm delivery, especially in relation to infectious/inflammatory intra-amniotic tracts . UntargeGestational diabetes mellitusGDM has adverse effects on fetal, neonatal, and infant metabolic outcomes by affecting glucose metabolism and insulin balance. GDM impairs the fetal-uterine balance and predisposes to glucose intolerance, obesity, and type 2 diabetes ,41. TherFetal malformations and chromosomal diseasesA few metabolomic studies have addressed fetal malformations or chromosomal diseases, although metabolomics could aid in their understanding and early detection . In part1H-NMR analysis [Additionally, Ceccarelli et al. studied the impact of fetal myelomeningocele on metabolic pathways in amniotic fluid in a sheep model using analysis . The recanalysis . They deanalysis . Nearly analysis . Even ifanalysis . Furtheranalysis .ChorioamnionitisChorioamnionitis, an infection of the chorion and amnion, occurs when pathogenic microorganisms progress from the vagina into the uterus and infect the amniotic fluid, membranes, placenta, umbilical cord, and uterus -54. It mNeurodevelopmentInflammation can impair fetal development, particularly with regard to neurodevelopment . Rat modNutritionMoreover, metabolomics offers unique opportunities in attempting to probe the potential effect of maternal nutritional status on amniotic fluid composition ,60. It sOver the past decades, there is sufficient evidence from animal and human research highlighting the critical role of maternal nutrition on amniotic fluid composition and consequently on the intrauterine milieu. In this direction, several approaches have been employed, while, in recent years, there is a shift toward adopting metabolomic approaches instead of conventional analytical protocols Figure .1H-NMR spectroscopy to explore the potential association between maternal BMI before pregnancy, gestational age (GA), and human amniotic fluid composition [1H-NMR approach discriminated between the two BMI classes as well. The complementary application of the two methods indicated a compositional tendency in the metabolic profile of AF influenced by GA and maternal BMI before pregnancy [Athanasiadis et al. used a reversed-phase HPLC protocol based on precolumn derivatization of amino acids and position . Data enregnancy .1H-NMR for the identification of the metabolites related to habitual maternal diet expressed as protein intake. Seventy-eight pregnant women, at 18-24 weeks of gestation, were categorized based on protein intake  into deciles, quartiles, and tertiles. Amniotic fluid samples of women belonging to the lowest quantiles were characterized by elevated levels of choline and lactate, while those retrieved from women in the upper quantiles presented increased concentrations of glucose and amino acids  [In 2015, Fotiou et al.,  to confialanine) . Additioalanine) .NMR-based metabolomics was also used to unravel the potential effect of maternal habitual dietary patterns on amniotic fluid profile ,63. In aExposome effects on the fetusEnvironmental factors can be hostile to pregnancy, and they may affect the well-being of the fetus in a variety of ways. Maternal smoking as well as second-hand smoking, during pregnancy, can lead to FGR, prematurity, stillbirth, and sudden infant death syndrome . FischerIn addition, metabolomics can be used to detect traces of drug substances that have passed from mother to fetus; Burrai et al., in amniotic fluid samples from 194 pregnant women, assessed with LC-MS/MS and identified 13 different phenethylamine derivatives, a psychoactive group of controlled substances that include amphetamine, methamphetamine, and MDMA .Twins’ complicationsMonochorionic twin pregnancies are not without complications, including the twin-twin transfusion syndrome (TTTS) that can lead to cardiac overload and dysfunction in the twin recipient (70%), with a mortality rate of 90% if left untreated . Fetal cAmniotic fluid metabolomics1H NMR and mass spectrometry in biological fluids. 1H NMR has lower sensitivity and resolution when compared to LC-MS, GC-MS, and HPLC, which have a large metabolite repertoire, but 1H NMR quantitative nature has advantages that still make it attractive to biological matrices’ metabolomics [The above-reviewed studies shine a spotlight on metabolomics as an evolving tool for the assessment of many conditions and as possible future biomarkers for improved therapeutic strategies. Different platforms are in use, such as bolomics . A combibolomics .Studies carried out in recent years have provided interesting data on normal  and compWith regard to metabolic profile changes with nutrition, specific metabolic variations were seen in the amniotic fluid metabolism of mothers with GDM, which could underlie the different outcomes evident in the two sexes -50. MetaFinally, as a future target, metabolomics could prove useful in optimizing individualized treatment and nutritional guidance, assess drug-related efficacy or toxicity, identify phenotype changes associated with disease onset/progression and improve early diagnosis and prognosis. They could improve the accuracy of efficacy, paving the way for better clinical trials. Currently, a clear and well-defined association between each metabolite and its relative clinical importance is not available, although an atlas addressing the involvement of metabolites in many pediatric and neonatal diseases and conditions would be of value.