This research investigated the use of electrospun nanofibers as reinforcing laminates in textiles to enhance their mechanical properties for use as smart and technical textile applications. Crimping plays a crucial role in textiles. Because of crimp, fabrics have extensibility, compressibility, and improved quality. Although crimping is inevitable for fabrics used in smart textiles, it is also a disadvantage as it could weaken the fibers and reduce their strength and efficiency. The study focused on preparing laminated textile composites by electrospinning a polyacrylonitrile (PAN) polymer onto textile fabric. The research examined the effect of electrospun nanofibers on the fabric by using a tensile testing machine and scanning electron microscopy. The results revealed that the prepared laminated textile was crimp-free because of the orientation of the nanofibers directly electrospun on the fabric, which exhibited perfect bonding between the laminates. Additionally, the nanofiber-reinforced composite fabrics demonstrated a 75.5% increase in the elastic moduli and a 20% increase in elongation at breaking. The study concluded that the use of electrospun nanofibers as laminates in textile composites could enhance the elastic properties, and prepared laminated composites will have the advantages of nanofibers, such as crimp-free elastic regions. Furthermore, the mechanical properties of the laminated textile composite were compared with those of the micromechanical models, providing a deeper understanding of the behavior of these laminated composites. In recent years, there has been an increase in the demand for textiles that can serve as human-adaptive smart (electronic) skins , especiaHowever, traditional fabrics have disadvantages when used for such applications. Due to the wavy (3D) structure of the fabric, the crimping effect experienced by these fabrics reduces their efficiency  . This reNanofibers have recently emerged as a promising material for medical applications , such asConsidering the benefits of both PAN nanofibers ,20,21,22Most research on nanofibers reinforced with textiles has focused on different properties of the prepared composites; only limited studies have observed the changes in the mechanical properties of the prepared composites. For example, the work most similar to this present study, which was conducted by Jalalah et al., prepared nanofiber/textile composites using PA6 nanofibers fabricated by a needleless electrospinning process, and the change in the behavior of the stress–strain curve of the composite in the elastic region was unnoticed. The reason why this change remained unnoticed could have been that the aggregated nanofibers were not oriented in a single direction . Xiaolu Other research groups have developed methods for preparing crimp-free fabric, but no methods have considered incorporating nanofibers in the fabrication of composites. Hahn et al. reviewed methods for the development of stitch-free and non-crimping textiles that did not include the advantage of nanofibers . BhudoliThe authors’ previous experience  with texTo summarize, this article presents a novel method for creating crimp-free textiles using direct electrospun nanofibers on the textiles and an examination of their mechanical properties. The results of this study could potentially pave the way for the development of new high-performance materials that are lightweight and strong. By investigating the properties of these materials, we hope to contribute to the advancement of textile technology and inspire further research in this field. 2) was ordered from AB Linas . Solvent-free fabric glue (Art. 639820) was purchased from Gutermann GmbH .In this research, to prepare laminated textile composites reinforced with electrospun PAN nanofibers, electrospun nanofibers were produced using polyacrylonitrile (PAN) powder and N,N–dimethylformamide. Polyacrylonitrile , N,N–dimethylformamide (DMF), and ACS reagent  were obtained from Sigma-Aldrich . The fabric  at +80 ± 3 °C  and a stirring speed of 800 rpm (The PAN solution was prepared by adding the PAN powder to the solvent (DMF) at 10%  800 rpm a,b. It w2) via the manual lay-up method. It was measured by weighing the mass of the glue before and after application to the fabric. To test the PAN nanofiber mat, separately, a 5 cm × 5 cm square of aluminum foil  was kept on the glue; therefore, nanofibers could be collected later, and any effect of the glue on nanofibers could be avoided.To prepare the laminated textile compound, the fabric was precisely cut to the same length as the periphery of the rotating drum (45 cm × 5 cm), with a longer dimension in the direction of the weft. This fabric was covered on a rotating drum collector . Fabric glue was applied to the fabric (~208 g/mThe PAN nanofibers were spun c at a roThe scanning electron microscopy (SEM) images were taken with a TM300 tabletop microscope (Hitachi) with a magnification of 1500 mm and a vacuum of 10-2 Torr, and a coating of 6 mA gold (Au) ions with a thickness of 150 Å, as mentioned in . The nanThe plain fabric and the PAN nanofiber-laminated composites were tested according to the ASTM D2261 standard (strip method), with a specimen size of 75 mm × 25 mm a. A MecmC is Young’s modulus of the nanofiber-laminated composite fabric; EFA and ENF are the experimental Young’s modulus for the fabric and PAN nanofiber mat, respectively; and VFA represents the volume fraction of the fabric. The value of EC predicts the linear relationship between the fabric and the nanofiber mat. The volume fraction of the reinforced nanofiber mat was calculated on the basis of the increase in the thickness of the nanofiber-laminated composite fabric; the thickness of the glue was considered to be 50 µm and not considered in the calculation, as it could be varied, depending on the loop.For statistical significance, the observed tensile Young’s modulus was averaged across at least five specimens. To understand the elastic properties of the prepared nanofiber-laminated composite fabrics , we calcC is the elastic modulus of the nanofiber-laminated composite fabrics; ENF and EFA are the experimental moduli of the PAN nanofiber mat and fabric, respectively, with the fiber orientation factor η0 = 3/8, assuming an in-plane isotropic orientation of the fibers in a random short-fiber polymer composite; and s is the fiber aspect ratio, where the average length of the fibers L can be used to calculate s = L/D, where D is the fibers’ diameter [The tensile modulus was predicted using the Cox–Krenchel micromechanical model. This model, which was based on the classical shear-lag theory, is among the most popular. This model makes the following assumptions: first, the fiber and matrix respond elastically; secondly, there are no axial loads on the fibers’ ends; and lastly, the fiber–matrix interface is ideal. The Cox–Krenchel model is characterized asdiameter .L and ET are the longitudinal and transverse modulus of the nanofiber-laminated textile composite, respectively, which were computed longitudinally and transversely in the direction of the fibers, assuming a unidirectional composite with cylindrical fibers.Similarly, the elastic modulus of the nanofiber-laminated composite fabric was calculated assuming a random in-plane fiber orientation using the Tsai–Pagano model shown in Equation (4) :(4)EC=38The Halpin–Tsai model is a mathematical model that predicts the elasticity of composite materials based on the geometry and orientation of the filler, as well as the elastic properties of the filler and matrix. The model is based on the self-consistent field process but is also considered to be empirical. The Halpin–Tsai model is given in Equation (7):In Equations (7) and (8), η is a function and ζ denotes an empirical parameter or a curve-fitting parameter which is used to calculate the value that matches the experimental data. In this study, the empirical parameter ζ = 1 was selected, as this is used for a single composite ,37.The nanofiber-laminated composite fabric produced by electrospinning nanofibers on a rotating drum collector covered with woven fabric exhibited precise lamination and distribution of the nanofibers on the material, as evidenced by their uniform thickness. There were no visible signs of voids or separation between the nanofiber mat and the fabric, which confirmed the good phase morphology. The nanofiber-reinforced fabric was generally flat and straightforward to cut into rectangular specimens for tensile testing.The initial thickness of the fabric was 301 ± 12 µm, which increased to 565 ± 13 µm after electrospinning of the fabric. The thickness of the tested PAN nanofibers was 147.8 ± 7 µm, which was less than the extra layer on the fabric after electrospinning, which could be explained by the fabric glue, which had a thickness of 50 ± 2 µm. The nanofibers collected on the interleaved aluminum foil lost some nanofibers as well.The tensile strength of the PAN nanofiber mat was 10.2 ± 2 MPa. There was no significant change in the tensile strength at breaking in the comparison between the fabric and the nanofiber-laminated composite fabric. For the fabric, the ultimate tensile strength was 18.9 ± 2 MPa; for the nanofiber-laminated composite, it was 17.2 ± 1 MPa. The Young’s modulus of the fabric was 72.9 MPa in the linear region  reflected the initial response of the material to the applied force. However, the nanofiber-reinforced fabric also exhibited a non-linear region due to the delamination and constant elongation of the PAN nanofibers under constant stress. This behavior led to the nanofiber-laminated composite fabric entering the plastic region, where breakage of the nanofibers occurs.Another region depicted in The observed increase in the percentage of elongation can be explained by the delamination of the nanofiber mat and the fabric. After delamination, some nanofibers may break not only from the center but also from both ends. This behavior is influenced by the woven structure of the fabric, and the nanofibers tend to break at the ends after the failure of the woven loop.p-values, it is concluded that at a significance level of 0.05, there is no significant difference between the experimental values and any of the predicted numerical values.The observed overestimation of the elastic moduli by the rule of mixtures (ROM) model can be attributed to the assumption of ROM that considers the average behavior of two independent materials irrespective of their geometry and orientation. In this study, the nanofibers were oriented between 0° and 30° b and werThe Tsai–Pagano micromechanical model provided a more precise prediction of the elastic modulus within the range of the experimental results. This model accounted for both the random in-plane fibers and the transverse elastic modulus. The Tsai–Pagano model provided a more accurate estimation of the elastic modulus of the nanofiber-laminated composite material by taking these factors into account. Similarly, the Halpin–Tsai model accurately predicted the elastic modulus within acceptable limits. This model takes both the orientation and the geometry of the composite material into account, and the predictions were well within the range of 5% of the experimental results. By incorporating these variables, the Tsai–Pagano and Halpin–Tsai models provide more accurate predictions than the ROM model, which was within the range of 5% of the experimental elastic modulus.SEM was used to examine the morphology of the fractured tensile cross-sections of both the woven fabric and the nanofiber-laminated composite fabric. The fractured surface of the woven fabric revealed only broken fibers, indicating a mechanism of brittle fracture with deformation occurring within the same plane. In contrast, the fractured surface of the nanofiber-laminated composite fabric revealed the fracturing of individual fibers at different levels and planes. This observation can be explained by several factors. First, it may be due to the fabric glue, which facilitated the direct adhesion of the nanofibers to the microfibers of the yarn, as well as the adhesion of the directly electrospun nanofibers to the microfiber b. As shoThe SEM analysis provided visual evidence of the nanofibers’ interaction with the microfibers within the yarn’s structure. The presence of connected nanofibers after fracturing indicated that these bonds between the nanofibers and the microfibers remained intact, thereby contributing to the enhanced elongation and mechanical properties of the composite material.After fracturing, the SEM images demonstrated that the nanofiber-laminated composite fabric and the woven fabric separated from one another. During elongation, the in-plane shear stress between the layers of the nanofiber-laminated composite fabric caused this separation. The shear stress was generated as the result of mismatched elastic regions between the layers. Due to this shear stress, the laminates separated from one another, resulting in delamination. Even after this separation, some nanofibers remained connected to the adhesive, indicating the strength of the adhesive bond between the nanofibers and the fabric.Moreover, during elongation, shear stress was observed not only between the layers but also within the nanofiber mat itself. The SEM images demonstrate that the nanofiber mat separated into distinct layers, indicating that the mat itself was an orthotropic material consisting of distinct layers. This separation of the nanofiber mat during elongation further confirmed the presence of shear stress within the microlayers of the nanofiber mat.It is evident from the images that one of the microlayers remained connected to the fabric glue while the second layer of nanofibers was delaminated. This result indicated that the electrospinning technique used to apply nanofibers directly on the fabric’s surface resulted in sufficient adhesion between the nanofibers and the fabric glue to transfer the load in the crimping region. Even after the delamination of the fabric and the nanofiber mat, the first direct electrospun microlayer of the nanofibers and the adhesive glue maintained a bond, as one microlayer remained attached .This adhesion between the nanofibers and fabric adhesive was essential for the overall structural integrity and mechanical performance of the nanofiber-laminated composite fabric. Adhesion permits the efficient transfer of the load between the nanofibers and the fabric, enabling them to function as a composite material. In addition, this adhesion contributes to the enhanced mechanical properties observed, such as increased elongation and enhanced elasticity, as discussed in the earlier sections.This study examined the use of electrospun nanofibers as reinforcing laminates for smart textiles. The study focused on cost-effective electrospinning polyacrylonitrile (PAN) nanofibers onto a woven fabric to create laminated composite fabrics. The results demonstrated precise lamination and distribution of the nanofibers on the fabric, with no visible voids or separation. As a result of the oriented nanofibers being electrospun directly onto the fabric, the nanofiber-laminated composite fabrics exhibited crimp-free behavior.The fabric specimen’s (75 mm × 25 mm) mean weight was 274 ± 10 mg, and this value was observed to increase to 571 ± 10 mg after the fabrication of the nanofiber-laminated composite fabric. The results of tensile testing revealed that nanofiber-laminated composite fabric had greater elastic moduli than those of the fabric alone. The nanofiber-reinforced composite fabric demonstrated a 75.5% increase in the elastic moduli and a 20% increase in elongation at breaking. The adhesion between the nanofibers and the fabric’s fibers improved the transfer of the load, resulting in increased elastic moduli.Among all the micromechanical models considered for estimating the elastic moduli of the nanofiber-laminated textile composite, the Tsai–Pagano and Halpin–Tsai models provided accurate predictions of the elastic modulus compared with the experimental results. On the contrary, both the rule of mixtures (ROM) model and the Cox–Krenchel model misestimated the elastic moduli. This discrepancy highlighted the significance of considering the orientation of nanofibers in laminated composites when predicting their mechanical behavior.The SEM examination of the fractured surface provided visual evidence of the interaction between the nanofibers and the fabric’s microfibers. Even after fracturing, the presence of connected nanofibers indicated the strength of the adhesive bond, which contributed to the improved mechanical properties. The SEM images also revealed shear stress within the nanofiber-laminated composite fabric and separation of the layers during elongation (this was observed after breaking), confirming the presence of shear stress within the microlayers of the nanofiber mat.


Pyogenic granuloma is a common reactive oral lesion primarily found in the gingiva and rarely in extraction sockets. While it can develop at any age, it is more prevalent in the third and fourth decades of life with a higher occurrence in females. Various factors contribute to its development and surgical removal is the gold standard treatment; however, there are various other methods available. This case report documents a rare event in which a female patient in her early 40s presented with an exophytic lesion affecting the extraction socket of her maxillary right lateral incisor. The lesion was effectively removed through surgical excision. Additionally, it explores the clinical features and pathogenesis of this lesion. The purpose of this case report is to shed light on the uncommon incidence of pyogenic granuloma following tooth extraction. This non-neoplastic vascular growth often presents as an erythematous, ulcerated lesion with a tendency to bleed, with either a sessile or pedunculated base. Our case is one of only five instances documented in the literature, underscoring the importance of knowledge and timely response in such unusual circumstances. We emphasize the significance of early detection and management for improved patient outcomes and a better understanding of this rare condition. One of the most frequent pedunculated or sessile lesions in the oral cavity is the pyogenic granuloma, an inflammatory hyperplasia of vascular origin. Secondary triggers like trauma, local irritation, and hormonal imbalance cause pyogenic granuloma . The lesA 40-year-old female patient reported to the Department of Oral and Maxillofacial Surgery with a chief complaint of swelling in the upper anterior region of the jaw, persisting for five months. The onset of the lesion was noted approximately five months ago, initially manifesting as a small growth that gradually increased in size up to a centimeter. Importantly, the lesion did not elicit pain, bleeding, or discharge. The patient's dental history revealed that she had deep occlusal caries for which she underwent an extraction of the maxillary right lateral incisor six months back and the maxillary central incisor three years ago. Furthermore, she had a medical history of undergoing a resection procedure for a uterine myoma 10 years back, and in the literature, there is no evidence of documentation of the association between pyogenic granuloma and uterine myoma. There was no history of systemic illness like diabetes or hypertension. Notably, there was no habit history of tobacco, alcohol consumption, or smoking.On examination, a projecting soft tissue growth above the socket of the maxillary right lateral incisor was discovered. The dimensions of the growth were measured as approximately 1 x 0.75 centimeters. The lesion was roughly oval with a raised and smooth surface, displaying partial erythematous coloring and well-defined margins. Upon palpation, the lesion was found soft, non-tender, and attached by a pedunculated base Figure .Considering the amalgamated clinical and radiographic findings and differential diagnosis, which included gingival fibroma and peripheral ossifying fibroma, a provisional diagnosis of pyogenic granuloma was established.The case was planned for surgical excision under local anesthesia. Prior to surgery, the patient underwent a general examination and systemic examination and had all necessary blood tests, which were all within normal parameters. Following all aseptic protocols, under local anesthesia , the lesion was marked 1 mm away from its margin. The surgical excision was done using blade number 15. The surgical excision was mostly focused on excising the lesion from its base and including removal of the periosteal layer of bone. After excising the complete lesion, the bleeding points were cauterized, and a thorough wash with normal saline was given. The surgical site was examined and evaluated, and hemostasis was achieved Figures , 4. PresThe histopathological examination of the excised soft tissue stained with hematoxylin and eosin showed a para-keratinized stratified squamous epithelium exhibiting an underlying granulation tissue. The underlying connective tissue exhibits characteristics such as extensive vascular clefts and concentrated clusters of fibroblasts and endothelial cells, which are indicative of pyogenic granuloma Figure . The finIn the oral cavity, pyogenic granuloma is considered a non-neoplastic growth, but it still demands significant attention in terms of diagnosis, prevention, management, and treatment. This is because pyogenic granuloma can manifest in atypical ways, sharing characteristics with different conditions, making its clinical diagnosis quite challenging. To ensure accurate identification and minimize the chances of misdiagnosis, it is crucial to perform biopsies on all suspected pyogenic granuloma cases. When considering a differential diagnosis, it is essential to include peripheral ossifying fibroma and gingival fibroma as potential conditions with some similar presentations, which need to be examined. To rule out pyogenic granuloma, it is necessary to first understand the characteristic features of pyogenic granuloma, which can be categorized based on its occurrence, clinical presentation, radiological features, and histological features. Pyogenic granuloma is typically observed in individuals aged between 30 and 50 years. The epidemiological trends for pyogenic granuloma are different in different studies. According to one review, there is a slight predominance of males during their second decade and female predominance during the third and fourth decades. One study suggests that the occurrence of pyogenic granuloma is more common in females than males irrelevant of their age group.The characteristic clinical appearance of a pyogenic granuloma entails a minute deep red to reddish-purple lesion that can manifest either as a sessile or pedunculated growth on the gingiva. The lesion surface may exhibit varying textures ranging from smooth to lobular, occasionally presenting wart-like attributes. Clinically, this condition presents with lesions that appear erythematous and have a tendency to bleed easily. These lesions can manifest as either sessile or pedunculated growths . While rDelving into the histological intricacies, Kuo Yuan et al. provided illuminating insights through their study. Employing immunochemistry on various target proteins, including vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), thrombospondin-1 (TSP-1), angiostatin, and estrogen receptor (ER), their investigation revealed a strikingly elevated proportion of VEGF-positive cells . On the As for the root cause of pyogenic granuloma's development, it remains an enigma. The condition's association spans a spectrum of clinical contexts, prompting a multifaceted exploration. Numerous authors advocate multifactorial etiopathogenesis, given that studies have unveiled divergent findings. Some investigations posit pyogenic granuloma's emergence as a physiological reaction to insults. In contrast, others counter that it arises in response to secondary stimuli like trauma, local irritation, bacterial infections, and similar triggers. The spectrum of contributing factors proposed by Kerr  includesAccording to the findings of Whitaker et al. , the couIn our treatment plan, we opted for surgical excision under local anesthesia. This approach has exhibited promising treatment outcomes with minimal examples of recurrence. Another pertinent case, documented by Sara Ghadimi et al., involved the utilization of a diode laser for lesion treatment . The litTo conclude, pyogenic granuloma is a common lesion found in both the skin and oral cavity, particularly affecting the gingiva. This case report delves into a specific instance of gingival pyogenic granuloma in a female patient, shedding light on various aspects, including causes, clinical features, histological characteristics, treatment options, and the potential for recurrence. Laser technology has gained prominence in dental surgery for its user-friendliness benefiting both the dentist and the patient. Laser procedures, like excising exophytic lesions, are among its applications. Laser energy heats, coagulates, denatures proteins, vaporizes, and carbonizes cells. While most laser wavelengths and equipment tend to be costly and bulky, making them less cost-effective for simple surgical excisions. On the other hand, conventional scalpel surgical excision of gingival lesions involves cutting down to the periosteum and thorough scaling of adjacent teeth to remove potential sources of ongoing irritation. Conservative surgical excision, often curative, remains the preferred choice for treating pyogenic granuloma. This case underscores the trajectory of diagnosis and treatment, highlighting the successful outcome achieved through meticulous excision with adequate margin and base and careful monitoring over six months during which no recurrence was observed. This comparison not only underscores the complexity of the condition but also highlights the effectiveness of the chosen approach in achieving a positive result.


Generally, PFAA concentrations decreased with increasing distanceto the coast and increasing depth. The C6–C9 PFCAs and C6 andC8 PFSAs dominated in surface waters, while longer-chain PFAAs (C10–C11PFCAs) peaked at intermediate depths (500–1500 m). This profilemay be explained by stronger sedimentation of longer-chain PFAAs,as they sorb more strongly to particulate organic matter.Perfluoroalkyl acids(PFAAs) are widely distributed in the oceanswhich are their largest global reservoir, but knowledge is limitedabout their vertical distribution and fate. This study measured theconcentrations of PFAAs  with6 to 11 carbons and perfluoroalkanesulfonic acids (PFSAs) with 6 and8 carbons) in the surface and deep ocean. Seawater depth profilesfrom the surface to a 5000 m depth at 28 sampling stations were collectedin the Atlantic Ocean from ∼50° N to ∼50°S. The results demonstrated PFAA input from the Mediterranean Seaand the English Channel. Elevated PFAA concentrations were observedat the eastern edge of the Northern Atlantic Subtropical Gyre, suggestingthat persistent contaminants may accumulate in ocean gyres. The medianΣPFAA surface concentration in the Northern Hemisphere ( Understanding the spatial distribution in globaloceans is key to projecting how environmental levels respond to changedemissions9 and to modeling ocean-to-atmospheretransport of PFAAs through sea spray aerosols (SSA).13 As there is currently no oceanic monitoring program for PFAAs, currentknowledge is built on data generated from research cruises.25 Although numerous such studies have been carried out, the spatialdistribution of data points in open oceans is insufficient for verifyinghigh spatially resolved ocean transport models9 or for accurate prediction of atmospheric emission of PFAAs viaSSA.12 A recent review of PFAAs in the global oceansrevealed that the coastal areas of western Europe, China, Korea, andJapan account for most of the available concentration data.26 Additionally, the scientific studies that makeup the body of data have been carried out by different research groupsover the course of an almost 20-year period, during which time analyticalmethods have improved significantly.27Comparisons of therelative amounts of perfluoroalkyl acids (PFAAs)in multiple environmental reservoirs29 Due to a lownumber of data points and/or low detection frequencies, these havegenerally not been able to provide a high-resolution spatial distributionof oceanic PFAAs.23 Moreover, due to contradictoryobservations, there is a debate as to whether PFAAs act as chemicaltracers for ocean circulation15 or sorbto particulate organic matter and sediment to deeper waters.32 This illustrates the need for a better understanding of the fateof PFAAs in the ocean. More extensive deep-water measurements areneeded for a range of PFAA homologues to elucidate the processes thatcontrol their vertical transport. Therefore, this study aimed to (1)extensively investigate the spatial distribution  of PFAAs  andperfluoroalkanesulfonic acids (PFSAs)) in the Atlantic oceanic watercolumn and, through thorough interpretation of the data, (2) clarifythe ongoing debate concerning their fate and behavior in the oceanicenvironment.In lieuof high spatial resolution surface seawater measurements,vertical profiles along a cruise transect can provide valuable informationon the oceanic circulation of PFAAs and thus help in interpolationbetween surface water data points. Previously, only a few such studieshave been carried out.Table S1 for exact depths). Unfiltered seawater was extractedon Oasis weak ion exchange (wax) cartridges, using a previously publishedsolid phase extraction method (SPE),33 withminor modifications (see the Supporting Information (SI)). The samples (5 L) were loaded onto SPE cartridges onboard using a multichannel peristaltic pump and then eluted laterin the laboratory at Stockholm University. Field blanks were preparedby circulating 5 mL of Milli-Q through an SPE cartridge during theextraction of the samples (see SI). Theanalysis was performed on a Dionex Ultimate 3000 liquid chromatographcoupled to a Q Exactive HF Orbitrap (Thermo Scientific). The CTD samples(n = 196) were analyzed for 12 PFAAs (C6–C12).Due to contamination from reagents, all data points were blank subtractedfor perfluorooctanoic acid (PFOA), while a separate batch of sampleswere blank subtracted for perfluorohexanoic acid (PFHxA). Additionally,a CTD cast  had to be removed fromthe data set due to this reagent contamination, resulting in 28 representativesampling stations instead of originally 29 (see SI). A full description of the materials and methods as wellas of the batches is provided in the SI.Seawater sampleswere collected on the 29th Atlantic MeridionalTransect (AMT29) cruise, from Southampton (UK) to Punta Arenas (Chile)in the time period from October to November 2019. Depth profile sampleswere obtained at 28 stations with a conductivity, temperature, anddepth (CTD) rosette containing 24 × 20 L Ocean Test Equipment(OTE) Niskin bottles 1. At eacn = 28), collected at 2 or 5 m (Table S1). Perfluorononanoic acid (PFNA) had the highest detectionfrequency in surface water (n = 28) with 89%, followedby perfluoroheptanoic acid (PFHpA) (86%) and PFOA (78%). PFHxA, perfluorohexanesulfonate(PFHxS), perfluorooctanesulfonate (PFOS), perfluorodecanoic acid (PFDA),and perfluoroundecanoic acid (PFUnDA) had detection frequencies of64%, 68%, 50%, 39%, and 21%, respectively. Perfluorobutanoic acid(PFBA), perfluoropentanoic acid (PFPeA), perfluorododecanoic acid(PFDoDA), and perfluorobutanesulfonic acid (PFBS) were omitted fromthe study due to poor recoveries.Of the 12 PFAAs targeted,eight were detected in surface samples(20 The highest ΣPFAA surface concentration (224pg L–1) was measured at 45° N  and 28 pg L–1 (n = 11) in the NH and SH, respectively (p < 0.05)(note that there were fewer sampling stations in the SH). Lower openocean levels are expected in the SH, since most of the global manufactureand industrial use of PFAAs has occurred in the US, Europe, Japan,and China.7 This is also observed in otherstudies where concentrations of PFAAs decreased to levels below detectionlimits for most cruises that followed transects from the Northernto the Southern Atlantic.19 These previous studies were mostly limited to coastal samples, andtherefore, it is difficult to compare them with open ocean data fromthe present study. This highlights the difficulty in interpolatingthe data currently available in the published literature to obtainestimates of seawater concentrations representative of larger openocean regions. Contrary to other studies, González-Gaya etal. (2014) reported a higher median ΣPFAS concentration in thesurface water in the SH (1440 pg L–1) compared tothe NH (516 pg L–1) of the Atlantic Ocean.20 Differences in concentrations can be due todifferent sampling locations and the size of the sample set.The detection frequency was higher for all substances in the NorthernHemisphere (NH) compared to the Southern Hemisphere (SH). The medianconcentrations of ΣPFAAs in surface water were 105 pg Lectively 2. The co9 this study does not confirm such a trend. Otherhomologues such as PFNA (73%) and PFHpA (64%) had higher detectionfrequencies in the SH . In additionto absolute concentrations, trends in homologue patterns can alsobe influenced by the choice of sampling location. As coastal areasare closer to emission sources, coastal waters may contain relativelyhigher concentrations of homologues that sorb to the particulate organicmatter present in the water column. This is a possible explanationfor the discrepancy between our results and previous studies reportingPFOS as the dominant compound on the surface of the SH.20 High concentrations of PFOS havepreviously been measured off the Brazilian coast33 and are suspected to be related to the widelyused pesticide Sulfluramid in South America, which degrades in theenvironment to form PFOS and other PFAS.In our study, PFOS was detected throughout theEnglish Channeland the North Atlantic southward to 10° N CTD027, 1. Howeve35 In particular, pulp mills, which are commonin Uruguay, could be a potential source of PFOS and other PFAS.36 In a previous study by Langberg et al. (2021),the potential role of a pulp mill in Norway in PFOS contaminationof a lake was highlighted.37 However, theRio de la Plata catchment area is highly populated and industrialized,making it difficult to pinpoint a specific source that could be responsiblefor the elevated concentrations of PFOS in these two CTD casts. Forexample, Sulfluramid could also be a source of PFOS in the Rio dela Plata, as it is imported from Brazil and used in Argentina andUruguay.38The source of PFOSin the South Atlantic Ocean observed in ourdata set between 30° S and 40° S .41 Subsequently, plasticparticles can sink from the surface to deep water.44 Previous studies have indicated that plastic debris canact as carriers of organic contaminants such as polychlorinated biphenyls(PCBs), dichlorodiphenyltrichloroethane (DDT), dichlorodiphenyldichloroethylene(DDE), nonylphenols (NPs), and polycyclic aromatic hydrocarbons (PAHs).46 Furthermore, studies have shown the sorption potential of PFOS andperfluorooctanesulfonamide (FOSA) in microplastics.48 Our finding could be the first indication that chemicals can potentiallyget trapped in this gyre via plastic debris.A subsurface sample (95m) at approximately 30° N CTD013, 1 showed n = 80) and deep waters  are presented and discussed. Apart from PFDoDA,all target compounds could be detected at depth (n = 104). The detection frequency of ΣPFAAs (one PFAA or morein a sample) for the intermediate depths was 48%, while for deep waterit was only 29%. Including all depths, the detection frequency washighest for PFHpA (34%), followed by PFUnDA (32%). The lowest detectionfrequency was observed for PFOA (17%). Compared to surface samples,the detection frequency for PFUnDA increased with depth, while forPFDA it dropped. However, generally with increasing depth, a decreasein concentration was observed for C6–C9 PFCAs as well as C6and C8 PFSAs, while for the longer-chain PFAAs (C10–C11 PFCAs)concentrations increased with increasing water depth.In the following section, the concentrationsfor the depth samples taken from intermediate depths  obtained fromthe CTD measurements, it appears that this elevated concentrationarea (CTD011–014) was Mediterranean Outflow Water (MOW). Thisindicates a major input of PFAAs from the Mediterranean Sea into theAtlantic Ocean. Previously, studies have concluded that the AtlanticOcean is a source of contamination to the Mediterranean Sea49 or that there is no significant flow of PFAAsbetween the water bodies.28 These conclusionswere based on comparisons of surface water measurements made in differentstudies in the Mediterranean Sea49 and the AtlanticOcean.20 However, sinceoutward transport of Mediterranean seawater into the Atlantic Oceanoccurs at intermediate depth (500–1500 m) as well as at thesurface,50 comparisons of surface watermeasurements alone are not suitable to determine the flux of PFAAsbetween the two water bodies.Between40° N and 30° N at 500–1500 m depth in the NH, concentrationswere elevated relative to surrounding areas. In combination with oceanographicdata . Generally, PFAA concentrations at all depths decreased towardthe equator. Exceptions from this trend were observed around 500 mat 25° N and 1500 m at 35° N (MOW) where concentrationsof PFHxA, PFOA, PFHxS, and PFOS were higher than in surface waters.PFHxA, PFHpA, PFOA, PFNA, and PFHxS showed similar distribution patterns.Concentrations of C6–C9 decreased with depth at latitudes from50° N to 40° N. From around 28° N toward the equator,concentrations at depths below 500 m were mainly below the MDL. WhilePFAAs with chain lengths between C6 and C9 were mostly concentratedon the surface (0–500 m), the distribution pattern of PFUnDAlooked different. PFUnDA had nondetects at the surface throughoutmost of the sampling stations. Higher concentrations of PFUnDA wereobserved from 50 °N to 20° N in intermediate waters (800–2000m). This could be explained by the higher organic carbon–waterpartition coefficient (KOC) of PFUnDAin relation to the other homologues.51 Thepropensity to sorb to particulate organic matter can allow PFUnDAto sediment out of surface waters. PFDA showed an irregular distributionpattern, having concentration hotspots and nondetects at a few samplingpoints in the surface, but also at 2000 m depth at around 30°N (CTD013). In the literature, the biogeochemical pump has been discussedas a mechanism for the surface removal of PFAA.22 The increase in concentration around 30° N . Our findings suggest that downwardparticle transport occurs for PFAAs with chain lengths that contain10 or more carbon atoms. As such, these are inappropriate chemicaltracers for ocean circulation. However, a complication is that PFCAsand PFSAs have multiple direct and indirect sources,7 making interpretation of contamination patterns in theocean challenging.Due to the low detection frequenciesat depth in the SH, our discussionon vertical profiles focuses on the NH between 50° N and theequator. In  CTD013, 1 might iIn conclusion, PFAA concentrations were higher in the NH comparedto the SH, and there was a general decrease in PFAA concentrationswith increasing distance to the coast and increasing depth. Homologueswith a higher adsorption affinity tended to sorb to particulate matterand sink down the water column. Furthermore, vertical profiles enabledthe Mediterranean to be identified as a likely source of PFAAs tothe Atlantic, along with the English Channel. Finally, PFAAs wereconsidered to be unsuitable ocean circulation tracers due to theircomplex origin of sources and partitioning behavior within the watercolumn, i.e., their interaction with sinking particulate organic matter.


A striking characteristic of the molecular techniques of genetics is that they are derived from natural occurring systems. RNA interference, for example, utilizes a mechanism that evolved in eukaryotes to destroy foreign nucleic acid. Other case studies I highlight are restriction enzymes, DNA sequencing, polymerase chain reaction, gene targeting, fluorescent proteins , induced pluripotent stem cells, and clustered regularly interspaced short palindromic repeats-CRISPR associated 9. The natural systems’ strategy for technique development means that biologists utilize the activity of a mechanism's effector (protein or RNA) and exploit biological specificity (protein or nucleic acid can cause precise reactions). I also argue that the developmental trajectory of novel molecular techniques, such as RNA interference, has 4 characteristic phases. The first phase is discovery of a biological phenomenon. The second phase is identification of the biological mechanism's trigger(s): the effector and biological specificity. The third phase is the application of the trigger(s) as a technique. The final phase is the maturation and refinement of the technique. Developing new molecular techniques from nature is crucial for future genetic research. Biologists can explain the complex phenomena underlying living processes by identifying the genetic mechanisms that produce such processes . In contA striking feature of the development of molecular techniques, which biologists themselves often highlight  activity and the use of biological specificity (protein or nucleic acid can cause precise reactions). The importance of an effector's activity and the use of biological specificity for molecular techniques are often implicitly recognized by geneticists. For example, many studies on RNAi highlight the technique's effector, which is the RNA-induced silencing complex (RISC) see , and thaLiving systems use effector molecules to generate a particular activity within a mechanism . I have A technique's effector is either endogenous or exogenous to the experimental system . EndogenLiving systems need biological specificity to achieve precise control over their molecular mechanisms . GeneticXanthomonas , a technique that uses 2 protein domains coupled together  (the specificity and effector components), application of the technique, and maturation of the technique. Each of the 8 highly successful molecular techniques shows the 4 phases of technique development see . I use RIn the first phase of technique development, biologists identify and describe an unusual phenomenon in a natural system. At this stage, the underlying mechanism is not well characterized, and the biological function of the mechanism is typically unknown. These studies can be identified by examining the studies that the later phases build upon.Petunia hybrida flower and introduced synthetic sense RNA into the plant in order to overexpress a gene in the pathway that controls formation of the flower pigment. Contrary to expectation, these flowers had reduced pigment, rather than more. Therefore, the sense RNA had reduced the mRNA of the endogenous gene. During the 1990s, multiple studies were conducted on how different organisms actively respond to the introduction of RNA Therefore, the study was a conclusive demonstration of how dsRNA can be used to control the RNAi mechanism.After dsRNA was identified as a trigger, biologists wondered how it could bind and sequence specifically cleave mRNA. They found that dsRNA is processed into small RNA fragments (antisense and sense) in multiple organisms and suggested that these were necessary for RNAi .Drosophila melanogaster cells as Argonaute, which is part of the RISC ; to manipulate an effector's activity in a noncellular experimental system ; or as a tracer, to follow a biological process see . At thisCaenorhabditis elegans” (C. elegans. C. elegans. In particular, it should now be possible functionally to analyse many interesting coding regions21 for which no specific function has been defined.… adds to the tools available for studying gene function in Interestingly, For example, the RNAi technique was first applied in the elegans” . The stuWhatever their target, the mechanisms underlying RNA interference probably exist for a biological purpose.C. elegans (It is important to note that when a molecular technique is developed for an organismal experimental context , it is t elegans . When a In the fourth phase of technique development, the technique has been established, and biologists improve and expand its performance. The scientific community invests considerable research activity into characterizing, both spatially and temporally, the mechanism in natural systems. Therefore, the technique generates further research on the biological mechanism that underlies it. The new knowledge acquired may improve access to the mechanism or allow the technique to be better controlled, enabling the technique to continue to be refined and standardized.C. elegans (Nicotiana tabaccum and Oryza sativa (D. melanogaster (Immediately following the seminal RNAi study of  elegans ; 2 specinogaster . In mammnogaster . To thisThe 4 phases I have identified are necessary features of technique development when derived from a natural system. I have shown that 8 highly successful molecular techniques have these 4 phases of development . AdditioThe development of new molecular techniques helps accelerate research in genetics and generates new scientific knowledge that would otherwise not exist. A new technique can also help uncover previously undetected biological phenomena, in turn leading to the development of yet another technique. For example, restriction enzymes were instrumental to the initial detection of the RNAi phenomena (Three scientific values  are impoI have highlighted 8 highly successful techniques of contemporary genetics that are derived from natural systems. The history of these techniques, I have shown, falls into 4 distinctive phases. It is an open question whether genetics will continue to progress through the development of molecular techniques derived from natural systems. Perhaps knowledge construction in biology requires a natural systems strategy. Alternatively, there is some evidence that geneticists working on synthetic biology have started to use rational design in organisms . FurtherGenetics has a historically accumulated set of molecular techniques to manipulate, intervene on, and trace molecular processes. Progress in genetics is greatly dependent on its powerful techniques—the cycle between discovery of biological phenomenon, mechanistic understanding, and application as a technique will continue.


This study identifies the topical areas of research that have attempted a psychological approach to soccer research over the last 33 years (1990–2022) and explored the growth and stagnation of the topic as well as research contributions to soccer development. Data were obtained from 1863 papers from the Web of Science database. The data were collected through keyword text mining and data preprocessing to determine the keywords needed for analysis. Based on the keywords, latent Dirichlet allocation-based topic modeling analysis was performed to analyze the topic distribution of papers and explore research trends by topic area. The topic modeling process included four topic area and fifty topics. The “Coaching Essentials in Football” topic area had the highest frequency, but it was not statistically identified as a trend. However, coaching, including training, is expected to continue to be an important research topic, as it is a key requirement for success in the highly competitive elite football world. Interest in the research field of “Psychological Skills for Performance Development” has waned in recent years. This may be due to the predominance of other subject areas rather than a lack of interest. Various high-tech interventions and problem-solving attempts are being made in this field, providing opportunities for qualitative and quantitative expansion. “Motivation, cognition, and emotion” is a largely underrated subject area in soccer psychology. This could be because survey-based psychological evaluation attempts have decreased as the importance of rapid field application has been emphasized in recent soccer-related studies. However, measuring psychological factors contributes to the study of football psychology through a new methodology and theoretical background. Recognizing the important role of psychological factors in player performance and mental management, as well as presenting new research directions and approaches that can be directly applied to the field, will advance soccer psychology research. It is common knowledge that soccer is the most popular participation and spectator sport in the world today . This meIn recent years, the role of psychology in various subfields related to soccer has become very important . Many efThe above-mentioned reviews have all made valuable contributions to the current understanding of the research conducted in the field of sport and exercise psychology; therefore, there must be a large quantitative and qualitative accumulation of psychological research that has been continuously explored for the development of soccer over the years. Klarin (2019) reported that a macro view must be taken from a position of reflection and introspection for the discipline’s long-standing tradition to become more rooted and more forward-looking .There are ways to explore the intellectual structure of research through, for example, literature review, content analysis, and meta-analysis, but a framework that integrates large disciplines such as psychology constitutes natural language processing . The devIn particular, the emergence of the concepts of artificial intelligence and big data has made it possible to derive new insights from vast and unstructured data through high-level analysis . NaturalCompared to other literature review methodologies, topic modeling is advantageous, owing to its ability to explore the published literature in a field in depth.  reportedThe purpose of this study is to identify research topics in the field of soccer that have attempted to take a psychological approach to the study of soccer, and to identify their growth and stagnation, as well as their contributions and prospects for soccer development. First, this study set the scope of the collection database as the Science Citation Index Expanded, Social Sciences Citation Index, and Art & Humanities Citation Index indexed in the Web of Science (WOS) database. The first soccer study with a psychological approach found in the database was in 1990. Therefore, a database of articles collected over a 33-year period from 1990 to 2022 was established and topic keywords, topics, and topic areas were extracted. Second, we identified macro-level research trends in psychological approaches to soccer research by identifying key keywords, topics, and topic areas through topic modeling analysis. In addition, it contributed to providing insights into how the identified research topics played a role in different aspects of soccer fields. Third, we identified active and stagnant research areas through statistical analysis of changes in the frequency and share of each topic area. Then, we analyzed various backgrounds for this phenomenon and predicted future responses, changes, and research directions.In this study, WOS was selected as the database to collect the articles. Cheng et al. 2018) reported that WOS is rich in data volume, including complete coverage of more than 10,000 journal citations, is well recognized in the academic community, and supports batch extraction of article information, which enables fast and accurate data processing . In addi reportedNatural language processing involves synthesizing a set of processes that intuitively derive meaning from unstructured words in text documents organized into sentences. Furthermore, the natural language processing process of academic research involves analyzing abstracts that summarize the key content of the study . TherefoMost natural language processing analysis methods, including topic modeling, are preceded by data preprocessing techniques to identify only the words that will be used in the analysis. Data preprocessing involves a series of refinement processes, such as deleting words from a large set of documents that may contaminate the analysis results and unifying words with similar meanings . The datMeanwhile, among the representative keywords that describe the research topic area, a potential problem is that the representativeness of the area is excessively high and only the keyword influences the overall result. In this study, keywords such as “soccer” and “football” appeared as keywords in all papers at the time of the initial search. Thus, even if they do not appear in individual clusters of the topic model to be analyzed, they are sufficiently recognizable as basic topic areas. As an indicator to determine the presence of such words, TF-IDF(Term Frequency-Inverse Document Frequency) is a formula that calculates the number of words that appear universally in all documents and words that appear frequently in specific documents  . TF-IDF Various types of algorithms can be used for topic modeling, depending on the calculation method used, including individual analysis techniques. In this study, we used the latent Dirichlet allocation (LDA) technique. LDA is generally adopted when the topic areas across documents have a strong tendency to be reduced to a single contact point; it is also used to derive topic modeling results for knowledge technology documents that contain specific domain knowledge such as papers, news, and patents ,24. The The coherence coefficient is a virtual proxy for the number of cases with the alpha, beta, and number of topics settings described above, and it adopts the number of cases with coherence values close to 1. In this study, the number of cases for alpha and beta values was set to 0.01~0.99 to consider the optimal number of topics and parameters for topic modeling results. The number of topics varied from seven to twenty, considering the total number of papers, and the consistency index was calculated for the number of all cases. As a result, the consistency index was very high (0.921) when the number of topics was fifty . Therefore, by comparing the topic composition according to the number of topics, we derived core topics that show a high density of keyword composition in any setting and variable topics that indicate changes depending on the setting, and suggested the meaning and implications of the subject area implied by each topic. This study analyzed the growth and decline of the topic area over time by analyzing the frequency and share of articles on psychological-related soccer research over a 33-year period (1990–2022). Topics were segregated based on discernible patterns of growth or decline over the specified time. A linear regression model was applied utilizing SPSS 23.0 , with the timeline serving as the independent variable and the frequency and proportion of each topic acting as the dependent variables.The results were subsequently interpreted using a systematic, two-step approach. First, after linear regression analysis, if the Durbin–Watson statistic was within the range of 1.5 to 2.5, it was considered a suitable regression model, and the regression coefficient and significance were checked ,28. TopiThe topic modeling results are shown in Topic 4 focused on the role of goalkeepers in soccer, including their behavior and strategies when faced with penalty kicks and shots on goal. Topic 5 was clustered around the coaching process  and considered the crucial role of coaches in developing youth programs and their support towards parents. Topic 6 was clustered with keywords related to psychological aspects of sports, such as anxiety, stress, burnout, and emotions, as well as strategies and support for coping with stressors and events. Topic 7 was clustered into keywords related to youth athlete development in elite sports academies, including talent and career assessment processes, transition, and support. Topic 8 was clustered with keywords related to the validity and reliability of measures and instruments used to assess soccer student-athlete behavior, including standards, norms, and attitudes. Topic 9 was clustered with keywords related to injuries in soccer—specifically regarding the risk of concussions and head impacts—and brain injury prevention and exposure review for adult, youth, and elite soccer players during the season. Topic 10 was clustered into keywords related to training load and physical demands, including fatigue, speed, acceleration, intensity, and recovery, which affect soccer players’ physical performance, including their sprinting, long-distance running, and jumping performance. Topic 11 was clustered with keywords related to soccer players’ goal orientations and behaviors, including perception and mastery, aggression, self-efficacy, and achievement in youth development. Topic 12 was clustered with keywords related to the pattern and intensity of physical activity, including perfectionism, energy, muscle, and threshold states in the soccer elite sport system. Topic 13 was considered to explore the different tactical formations used by soccer teams and how they affect gameplay. Topic 14 was clustered with keywords related to decision-making processes involving expert knowledge, information, and video analysis of technical functions, conditions, and reactions in soccer matches. A visualization of the keyword network for each topic is shown in Each of the 14 clustered topics followed a detailed micro-classification of the soccer psychology domain. In the book “Football Psychology: From Theory to Practice”, Konter et al. (2019) organized the psychology of soccer into four macro-content areas, which were further organized into micro-disciplines . FollowiFirst, the “Motivation, Cognition, and Emotion” section focuses on soccer players’ motivation and psychological factors such as mood, grit, and mental strength. The topic modeling resulted in the inclusion of Topics 6 and 11, which are related to this topic area. Second, the “Coaching Essentials in Football” section covers the definition of a coach, competencies, leadership, effective coaching methods , and psychological aspects of training and practice. The topic modeling resulted in the inclusion of Topics 1, 2, 3, 10, and 13, which are related to this topic area. Third, “Psychological Skills for Performance Development” covers various psychotechnical approaches to improving soccer performance, including the development of psychological skills for goalkeeper performance development. The topic modeling resulted in the inclusion of Topics 4, 12, and 14 which are related to this topic area. Fourth, the “Developing the young player in Football” section covers parental coaching, talent development, education and support on how to succeed, and prevention of negative psychological factors in developing young players into elite players. The topic modeling resulted in the inclusion of Topics 5, 7, 8, and 9, which are related to this topic area.We assessed the change in trends over time for each clustered topic area. The change in frequency of each topic area from 1990, when soccer psychology research was first identified, to 2022 is shown in The trend changes based on the frequency of each topic area shown in p = 0.006), which is a significant positive coefficient, indicating that this was a hot topic. The topic area “Essentials of Soccer Coaching” had a Durbin–Watson value of 0.908, which is not in the range of 1.5 to 2.5. Therefore, the trend was not statistically significant. The topic area “Psychological Skills for Performance Development” had a Durbin–Watson value of 1.981, which is close to 2, meaning the trend could be validated through the regression coefficient. The regression coefficient was −0.384, which is not statistically significant; thus, this topic area was categorized as cool. Finally, the topic area “Motivation, Cognition, and Emotion” had a Durbin–Watson value of 2.443, which is close to 2, meaning that the trend could be validated through the regression coefficient. The regression coefficient was −0.384 (p > 0.027), which indicates a significant positive coefficient; therefore, this topic was classified as cold.“Developing the young player in Football” is an area of research focusing on the importance of understanding the player development process in identifying and nurturing soccer talent. This topic area was organized into Topics 5, 7, 8, and 9. Topic 5 has explored how feedback from parents and coaches can influence youth development ,31. In aThe process of effectively identifying and developing players with the potential for future success is becoming increasingly important . The impThe trends in this thematic area are a sharp increase in the frequency of research and a steady share after a certain period. After a certain period, the first paper in this topic area in the research period 1990–2022 was found in 1992. Although the frequency of research in this topic area fluctuates from year to year, there has been a steep increase since 2017, and the frequency has been increasing until now. The trend for increased frequency was not statistically significant; however, it was the only one of all topic areas to show a significant increase in share. An explosion in share was not observed by us either, but it was maintained steady in the 1990s, when the overall frequency of soccer psychology research was significantly lower. This suggests that this topic area can be expected to remain active according to the share regression model. Since the 1990s, the importance of psychological approaches in the development of youth players has been raised in various sports, including soccer . Neverth“Coaching Essentials in Football” refers to research on coaching, which is an essential component of elite sports, including soccer. Research in this area explores the relationship between coaches and players and the effectiveness of different coaching styles and support structures. This topic area was organized into Topics 1, 2, 3, 10, and 13. Topic 1 addresses the importance of skill training for the motor tasks that soccer players need to perform. Relevant research has identified the most effective training methods and strategies for improving accuracy, speed, footwork, balance, and coordination ,62,63. TConsistent with the sport-wide notion that coaches’ efforts to improve their coaching skills are fundamental to all sports and should be taken seriously, soccer psychology is one of the most active areas of coaching research . The EssThe research area “Coaching Essentials in Soccer” ranks high on the list of research areas in bibliographic analyses of soccer psychology research ,82. DuriThe topic area “Psychological Skills for Performance Development” addressed psychological approaches to soccer performance development, including the intervention of coaching but focusing on psychological skills. This topic area was organized into Topics 4, 12, and 14. Topic 4 has translated into topics exploring the strategies goalkeepers use to effectively defend against penalty kicks ,88, how One of the proven facts in this area of research is the ambivalence about perfectionism in soccer players. This is evidenced across almost all sports, and soccer is no exception ,102. ThiFrequency measures and significance tests in the regression model show that the number of studies on this topic published each year is not decreasing. However, as the overall research area of soccer psychology has increased, the share of this topic area has decreased somewhat over time. For this reason, it appears to be a somewhat stagnant research area according to the share regression model. However, this is more related to the relative activation of other research areas rather than a decrease in interest in this topic area. Researchers such as Mills et al. (2012) suggested that athletes do not need to possess all of the skills recommended in the talent development literature to develop at an elite level . InsteadThe topic area “Motivation, Cognition, and Emotion” was organized into topics that examined and evaluated psychological traits that occur in different situations experienced by soccer players. This topic area was organized into Topics 6 and 11. Topic 6 aims to understand professional soccer players’ experiences with burnout, with a focus on potential causes, such as overtraining, personal stressors, or the pressures of professional sports. Moreover, matches were determined and investigations were conducted to observe how stress and anxiety levels might affect players’ performance ,110. ResGiven the different goal orientations of athletes, the research identified in this topic area provides insight into considering whether soccer players are more focused on mastery goals or performance goals ,117, whiThe first paper in the database collected for this study, from 1990, was found within this topic area. The frequency of studies increases and decreases every year, and even the share has been gradually decreasing since 2010. The regression model for the decrease in share was found to be statistically significant. Overall, we can cautiously diagnose that research in this topic area of soccer psychology has stagnated somewhat. This topic area is largely composed of studies that have used questionnaires to collect and evaluate data. However, most research in elite sports, including soccer, is increasingly focused on direct application to the field . For a lThis study aimed to identify the knowledge structure of and research trends in soccer research from 1990–2022. Topic modeling resulted in 14 topics. The topic area “Essential Coaching in Soccer” was the most frequent, but not statistically trending. However, coaching, including training, is expected to continue to be an important research topic as it is a key requirement for success in the highly competitive world of elite soccer. Interest in the research area of “psychological skills for performance development” has waned in recent years, possibly due to the dominance of other subjects rather than a lack of interest. There are a number of cutting-edge interventions and problem-solving attempts in this area, providing opportunities for qualitative and quantitative expansion. “Motivation, cognition, and emotion” is a vastly underappreciated topic area in soccer psychology. This may be due to the fact that recent soccer research has emphasized the importance of rapid on-field application, resulting in fewer attempts at survey-based psychological assessment. However, measuring psychological factors contributes to the study of soccer psychology through new methodologies and theoretical backgrounds. Recognizing the important role that psychological factors play in players’ performance and mental management and providing new research directions and approaches with direct field application will advance soccer psychology research. Based on the theoretical basis of previous studies, this study searched for articles in WOS alone, but it is necessary to conduct an approach to identify the knowledge structure of soccer-psychology research topics that exist in a wider range of indexes and databases. Therefore, insights from an integrative perspective of data collection and analysis of academic databases including WOS, Scopus, and SportDISCUS are proposed as a future research direction.


Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF.The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic  analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways  over-representation analyses.Among 232 subjects, two molecular subtypes were identified. Subtype 1  and Subtype 2  had similar distributions of age  and sex . Subtype 1 had more severe disease based on composite physiologic index (CPI) . After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival  and similar transplant-free survival  as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature , and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling.Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials.NCT01915511The online version contains supplementary material available at 10.1186/s12931-023-02435-0. Idiopathic pulmonary fibrosis (IPF) is characterized by abnormal accumulation of extracellular matrix (ECM) in the pulmonary interstitium. The natural history of IPF is characterized by progressive decline in lung function, often culminating in death from respiratory failure . SignifiIntegrative multi-omics analyses have identified molecular subtypes of several forms of cancer –21. WithThis study included 300 patients enrolled in the US-based, multi-center, observational Idiopathic Pulmonary Fibrosis Prospective Outcomes (IPF-PRO) Registry (NCT01915511), whose key inclusion criterion is IPF diagnosed or confirmed at the enrolling center in the past 6 months . EnrollmWhole blood and plasma collected at enrollment were stored centrally. The process used to quantify plasma proteins by aptamer-based methods, measure miRNA expression in plasma, sequence total RNA (referred to as toRNA) in whole blood, and to perform bioinformatics analyses, is described in Additional file To identify molecular subtypes of IPF, an integrative, two-step method, spectral clustering Similarity Network Fusion (scSNF) was used to cluster subjects based on data from all three molecule types. First, Similarity Network Fusion, a method that integrates similarity networks, was applied to fuse proteomics, miRNA and toRNA expression data for each subject . Second,Patient characteristics within each molecular subtype were summarized using means and standard deviations for continuous variables and numbers and percentages for categorical variables. Characteristics were compared between the subtypes using the Kruskal-Wallis test for continuous variables and the Chi-square test for categorical variables, with p < 0.05 considered statistically significant. To determine the relationship between the molecular subtypes and clinically meaningful outcomes, the occurrence of two composite outcomes was determined: (1) lung transplant or death; and (2) disease progression, defined as ≥ 10% absolute decline in forced vital capacity (FVC) % predicted, lung transplant, or death. FVC decline recorded at the first instance of a post-enrollment value ≥ 10% lower than the enrollment value. These events were selected because they can be objectively assessed and have similar importance in the natural history of IPF . TransplNext, to place the molecular subtypes identified in this study in the context of existing literature, the previously described 52-gene expression signature was applied to group the subjects as high-risk or low-risk (for death or transplant) , 10. CohThe molecular characteristics that distinguished the subtypes identified by scSNF were investigated in several ways. First, Normalized Mutual Information (NMI) measured agreement of distribution of the subjects to the subtypes when clusters were formed using only one data type  compared to using all three data types . Next, hTo investigate the biology underlying the molecular subtypes, linear regression models identified differentially expressed features within each molecule set  subjects while subtype 2 comprised 127 (54.7%) subjects. Subtype 1 had more severe disease at baseline, with lower diffusion capacity of the lung for carbon monoxide (DLco) % predicted , lower FVC % predicted , and higher CPI . There were no significant differences in age, sex, smoking status, medical history, GAP stage , diagnosDuring a median follow-up of 27.5 months (interquartile range 15.8–36.7 months), the composite of lung transplant or death occurred in 95 (40.9%) subjects . The composite of disease progression occurred in 143 (61.6%) subjects . In the unadjusted analysis, subjects in subtype 1 experienced a significantly shorter time to lung transplant or death   subjects and the low-risk group 147 (63.3%) subjects. The molecular subtypes were distinct from the 52-gene signature risk groups, with no agreement beyond chance , p = 0.49; Additional file Based on good agreement  on the distribution of subjects to a cluster using a single molecule type compared to the scSNF multi-omics data, proteins (NMI = 0.41) and miRNAs (NMI = 0.62) contributed substantially to the clustering, while toRNAs had little effect (NMI = 0.0003)  to predict the molecular subtypes. To further assess the classifier’s performance to identify clinically meaningful subtypes of IPF, Cox proportional hazard models estimated the risk to experience each composite endpoint in each iteration’s training and validation datasets. Although the classification of subjects to the molecular subtypes based on each iteration’s classifier did not achieve p < 0.05 in all iterations, the point estimates of HR were in the same direction, suggesting consistent classification of subjects based on clinically meaningful outcomes using the molecular data Fig. . FeatureLinear regression identified 232 proteins  signature , 10. A sAccurate identification of patients with IPF who are likely to experience short-term disease progression has been proposed as part of an enrichment strategy for clinical trial design . PreviouIntegrating high-throughput data from multiple platforms remains a challenge. In this study, we initially considered three methods based on two general approaches. iCluster + and iClusterBayes include a variable selection step  followed by distillation of input matrices to a smaller set of latent variables, allowing joint clustering of samples and identification of cluster-relevant features , 31, 32.The molecular subtypes that we identified based on integration of data from several constituents of the gene-to-protein expression pathway appear to reflect the pathobiology of IPF. Several of the proteins that were different in subtype 1 compared to 2 have been implicated in IPF pathogenesis. For example, activation of GSK-3 beta protein, which is reduced in molecular IPF subtype 1, is enhanced by TGF-beta, contributing to myofibroblast differentiation; GSK-3 beta signaling inhibition has been proposed as a treatment strategy for IPF . PKB betSeveral miRNAs that have been mechanistically linked with IPF were differentially expressed in molecular IPF subtype 1 compared to 2. We identified increased expression of mir-142-5p and reduced expression of mir-130a-3p in subtype 1. Altered expression of these miRNA in macrophages (in a similar direction as we observed) has been implicated in lung and liver fibrosis via reduced STAT6 signaling; mir-142-5p targets SOCS1 (a negative regulator of STAT6 phosphorylation), and mir-130a-3p targets the PPAR-g inhibitor . We founTo gain additional insight into biologic differences between the molecular subtypes, canonical pathways over-representation analysis (IPA) was conducted separately for up- and down-regulated molecules in subtype 1 compared to 2. The intersection of these datasets comprised a number of pathways known to be altered in IPF .Our study has several limitations. First, the aptamer-based proteomics platform we used contains a targeted list of biomarkers that is not comprehensive of all the proteins that may be found in the blood or potentially associated with pathobiology. Second, molecules measured in peripheral blood may not reflect the pathobiology of the target tissue , 19, 24.In summary, we used a well-characterized, prospective, real-world cohort of patients with IPF to identify novel endotypes of IPF by integrating peripheral blood transcriptomic  and proteomic information. If externally validated, the classifier of patients with IPF to molecular subtype 1 or 2 could serve as a biomarker for prognostic enrichment in clinical trials. Constituents of the classifier, or pathways enriched among progression-associated molecules, could be explored further as therapeutic targets.https://www.usscicomms.com/respiratory/Todd/IPF-PROmultiomics.A podcast discussing these data and other analyses of circulating biomarkers in the IPF-PRO Registry is available at: Below is the link to the electronic supplementary material.Additional file 1: Section S1. Process used to quantify proteins, toRNA, and miRNA and perform bioinformatics analyses.Additional file 2: Table S1. Number of toRNA, miRNA and proteomics features available for modeling after filtering and pre-processing.Additional file 3: Section S2. Process used to develop classifier for molecular subtypes. Figure S1. Methods for development of classifier for molecular subtypes.Additional file 4: Section S3. Differential expression analyses.Additional file 5:Figure S2. Average Silhouette scores of consensus clustering for 2 to 10 clusters. Section S4. Multi-omics clustering by different methods. Table S2. Cluster membership consensus between scSNF and iClusterPlus or iClusterBayes. Table S3. Sensitivity analysis based on different variance filters for RNA-seq data. Table S4. Comparison of molecular subtypes based on scSNF with high-risk and low-risk groups based on the 52-gene signature. Table S5. Agreement  in distribution of subjects to molecular subtypes using a single molecule type compared to distribution using the scSNF fused multi-omics dataset. Table S6. Differentially abundant proteins by molecular subtype. Table S7. Differentially expressed miRNAs by molecular subtype.Additional file 6: Table S8. Canonical pathways that were significantly enriched  for genes associated with down-regulated proteins.Additional file 7: Table S9. Canonical pathways that were significantly enriched  for the experimentally-validated target genes of the 591 up-regulated and 1313 down-regulated miRNAs.


Whilst considering commissioning articles for QRB Discovery as Editor-in-Chief, I would like to explain what I think could be interesting topics for new articles in addition to unexpected amazing discoveries.Recently, I submitted a somewhat philosophical paper with the title ‘The Mole and Albert Einstein’ to which I had been invited by the Swedish Physics Society. To prepare myself, I had been reading Einstein’s famous papers and PhD Thesis of 1905  and was struck by his quite narrow approach in his attempt to address and generalize so many different problems. I do not want to diminish the impression of his genius, but I suddenly saw Einstein as a somewhat bewildered young (25 years) man eager to make an impact. When in 2005 the Physics world celebrated the anniversary of Einstein’s miracle year, he was claimed to be a Chemist by Nature columnist Philip Ball because of his work and PhD Thesis on molecular diffusion inspired by Brownian motion and his goal to determine Avogadro’s number – but then why not call Einstein a Biophysicist?pV* = nRT, which looks like the ideal gas law, and which he assumes to be a thermodynamic macroscopic equation of state integrating corresponding microscopic equations in which the colliding solvent molecules just balance the osmotic pressure. His analysis (including some strange detours) leads to the famous statistical error function for diffusion. His explanation of the Brownian motion also results in the final acceptance by the science society of the atom and molecule concepts in the shape we know them today. The jumpy random motions that Robert Brown observed pollen grains to perform when suspended in water, Einstein explains, reflect the thermal motions of surrounding water molecules, an unequal number obviously colliding from opposite sides of the grain, telling something about the size of the numbers. The molecular dynamics and molecular-kinetic theory of heat are at the heart of Einstein’s thinking in 1905 and many years later his endeavor to develop a universal theory for the fundamental forces can be seen as just an expansion of this early work on liquids and intermolecular forces, based on Newtonian kinetic theory of matter.Following van’t Hoff, the first Nobel Laureate in Chemistry (1901), Einstein starts with the osmotic pressure and van’t Hoff’s formula fundamentals of molecular diffusion as a problem area worth prioritized attention. Or maybe not since MD today is still limited to rather short times?Where am I heading with this? Well, I might ask: would a modern approach by molecular dynamics computation exactly agree with Einstein’s description of Brownian dynamics? Or might there be some deviations that could suggest additional, yet undiscovered mechanisms, such as wave front-like attacks by many coherently coupled solvent molecules by which the momentum transfer between the small molecules and big pollen grains could occur? The biophysical impact of such a mechanism could be earth-shattering, changing the rules for thermal activations of various processes inside the cell, adding large fluctuation forces. Unfortunately (or fortunately?), my checks in recent literature all indicate excellent agreement between modern molecular dynamics simulations and Brownian motion according to the classical Langevin equation as characterized in terms of autocorrelation memory and fluctuating force functions. Nor do any reported disagreement with experiment suggest the existence of any additional effects, neither under thermodynamic equilibrium conditions nor at investigated nonequilibrium conditions (electrophoresis and sedimentation). From this, I conclude that I must probably dismiss With this example, I would like to open a discussion asking: can we identify problem areas or paradigmatic models in biophysics and molecular biology that would deserve special attention because they are particularly important and not fully understood? Of course, we may not predict discovery, but as Pasteur says we could help chance for making one by having a prepared mind.With inspiration from ‘Hilbert’s 23 Problems’, I would encourage all our readers, Editors, and Editorial Board Members to come up with suggestions for a list of such problems in contemporary biophysics-related sciences, whether theoretical, experimental, or intrinsic to the dissipative systems of living organisms. But like in my example above, before a certain problem be put forward, I would expect that effort has been made to search for evidence in the literature of any violations or conflicting data that can motivate further digging.I shall list examples here, starting with fundamentals of mechanisms in biology and then theoretical challenges and potential future method developments. I welcome your adding more points to the list or complementing/correcting the current ones. We might also eventually do a scoring of the numbers in order of falling priority and to repeat this exercise when we have a more comprehensive list. Several problems are tough – if solved each likely to yield a Nobel Prize!QRB Discovery!Origin-of-life biophysics. How can molecular model systems and simulations give insight into possible events, interactions, and structures that led up to what we may call ‘life’? All the way from the simplest elementary molecular reactions to complex molecular systems with function. How were lipids and membranes first made during the chemical origin of life? How does chirality determine interactions of molecules of life? Can chiral bias by parity violation of electroweak interactions be amplified by e.g. helical crystallization errors or spin-orbit coupling?Liquid–liquid phase transitions in cells and membrane-free organelles. Roles in regulating life processes? Enthalpy-entropy compensation – frequently observed in biomolecular systems – potentially an effect of microscopic phase transitions (0 = ΔH − TΔS)?Designer organisms and engineered enzymes. Organisms with a minimal genome might become a tool for systematic studies of fundamental biological mechanisms and functions, and for producing bionic devices. Likewise designer proteins, in particular membrane protein design, may be exploited for making new bionic devices, including design of enzymes and design of whole cells. In the outskirts of biophysics, artificial DNA constructs (PNA) and DNA origami provide new challenges with applications outside biology. Using DNA-editing devices (CRISPR technology), one may envisage ‘DNA computation’.Memory enigma. What is the molecular basis of learning and memory? Is long-term memory at all molecular? Maybe long-term memory is using the same reading machinery as inherited ‘basic instincts memory’ does? Perhaps in shape of proteins over-expressed and ‘preserved’ as amyloid aggregates (with >100 years lifetime)? On the other hand, short-term memory may be completely different and e.g. related to nonmolecular, macroscopic dendrite imprints recognizable when revisited upon new dendrite growth? Holistic/neural network aspects? Engram neuron cells?Enigma of protein folding. How is misfolding and irreversible energy traps avoided? Steered folding: can one learn from experimental (designed model molecules) and theoretical models how enthalpic and entropic effects funnel the folding? The entropy seems notoriously hard to determine, a problem in molecular computations – could one develop some generic solution besides brutal force based on long and repeated simulations? Folding of partially synthesized protein emerging from ribosome may kinetically violate Anfinsen total length folded protein  by some Darwinian short-cuts?Machine learning and AI. How help understand protein folding? Can AI help us develop molecular modeling programs without losing track of mechanisms and our physical understanding?Hydrophobicity and water. In biology, hydrophobic effects lie behind the self-assembly and structuring of nucleic acids, folding of proteins, and aggregation of lipids into cell membranes. Despite the great importance of hydrophobic interactions, theoretical approaches do not seem able of providing any unifying picture of energetics and activation barriers to explain dynamics and catalytic effects of hydrophobic agents on structural changes and transport processes (such as motion within or crossing of a lipid membrane). Are there hydrophobic mechanisms that are not yet understood in terms of current theory or are they problematic just because of lack of sufficient free-energy accuracy (ΔG noise)? See also liquid–liquid phase transitions.Incomplete description of water. How can we explain: Electrolyte ion-pair-specific bubble–bubble fusion interactions. The Hofmeister effect. Dissolved gas and microbubbles effects. ‘Nano-bubbles’, do they exist?Nonequilibrium biophysics. Are current near-equilibrium models and short-time simulation tools insufficient for handling real nonequilibrium life processes? The theorems of Jarzynski and Crooks on thermodynamics and fluctuating forces suggest potentially new approaches to understand mechanisms of biological motors. Can collective motions or funneled transfer of momentum, such as soliton-like waves along a DNA coil, lead to large-amplitude fluctuations and energic ‘hot spots’ with roles in context of activation? Could vacuum shear slip overcome viscous damping? Can we develop generic models (shortcuts) to help us estimate entropy effects in molecular dynamics computations?Molecular motors. Molecular mechanisms of muscle contraction, cell/cargo transport and locomotion, flagellar motion, DNA replication and repair. Virus DNA capsid packaging motors. Energy landscapes, use of ATP hydrolysis, and powering of conformational change/locomotion; FoF1-ATPsynthase chemical-mechanic energy conversion. Polymerization motors: tubulin/microtubule, GTP, directionality. One overarching principle? Catalytic steps? Ratchet models, thermal noise fluctuations, and reversibility?Ion channels and neuroscience. Selectivity filters, ligand- and voltage-gated mechanisms. Proton channels. Receptor-mediated endocytosis mechanism. Evolution, selectivity, structure, and function – toxins and disease.Mechanism of olfaction. What is its biophysical and molecular basis – from receptor to nerve signal? How may signal strength variations between different receptors and the corresponding spectrum of substance–signal strength combinatorially code for a highly resolved ‘smell fingerprint’? May this function principle be used technologically in chemical analysis or in molecular computers? What is the evolutionary relationship between olfactory receptors and internal neural signal receptors?Amyloids. How do amyloid fibers form and what triggers their formation? How do their aggregation and degradation occur in cells? What is cause and what is consequence in the macroscopic aggregate formation, and what is its mechanistic relation to disease? Can aggregation be steered, safely inhibited or else controlled in a useful way? How are macroscopic hydrophobic and dielectric effects involved? Relation to prions? When do amyloids turn out to have infectious properties (‘turning bad’)? Intercellular transport by endocytosis?Cellular interactions and dynamics.Coherent motion of molecular reactions and flow. Membrane flow and cell migration. Interphase chromatin dynamics. Mechano-sensing.Crowding. What are chemical (molecular interactions), steric , and statistical (osmotic) effects?Communication between cells. ‘Glycolipid crypticity’. Transfer of signal molecules and small RNAs, etc.Cell-membrane penetration mechanisms. Cell-penetrating peptides. Molecular partners annihilating polarity and lowering Born barrier. Endocytosis. Organelle-specific delivery to cancer cells for therapy.Quantum biology. While in light-harvesting organisms, excitonic states are trivially quantum entangled pairs of excited states, it has been claimed that quantum entanglement may also lie behind amplifications of extremely tiny radical interactions and explain e.g. birds’ ability to navigate in the nighttime in Earth’s magnetic field. Does such quantum biology really exist i.e. are there any specific processes explainable only as quantum phenomena?Electric and magnetic biology. What is the origin of macroscopic electric and magnetic effects exhibited by bacteria? ‘Electrets’ are immobilized electric charges at surfaces but neither creation nor dielectric stabilization of an electret is well understood? ‘Magnetosomes’ as artificial magnetizable cell models?High hydrostatic pressure biophysics. Organism adaptions and habitat changes in deep sea, lipid desaturase activation, metabolic adjustment. What can be learnt from high-pressure experiments about local structures and phase transitions in cells?Methodology and translational science-driven developmentStructure/morphology at multiple scales. Advances in technology e.g. visualization/imaging techniques, open new biophysical avenues.Atomic scale Supramolecular scale (cryo-EM)Subcellular/cellular (cryo-ET and other high-resolution techniques)Dynamics at multiple scales. Not sufficient with spatial/structural/morphological view only, but their time evolution is needed too. Both experimental and computational techniques/models/simulations that examine time-dependent changes in structures  are important. Dynamics is the bridge between structure and function.System biology. Challenge to bridge experiments and theory. Theories/models that can be experimentally tested or take advantage of new data to build/improve new/existing models. ‘Systems-level’ approaches that provide a better understanding of systems dynamics in its physiological environment. Quantitative systems pharmacology typical example.4D genome. Ability today to do structure-based studies at the level of chromosomes or the entire chromatin. With advances in Hi-C technology, we now have 3D connectivity information on gene loci, which may be used for generating 3D structures, and even their equilibrium fluctuations (modes of motions using linear theory). So, do not think of DNA as a string of letters with a code, but as a 4D entity.Data-driven studies, machine learning, artificial intelligence. Such studies are extremely powerful, and papers on this area should be given serious consideration, provided that the utility of the method is illustrated/documented by concrete biological examples. Approaches that combine machine learning/AI methods and physical sciences-based methods, or those that allow for physical interpretations of AI predictions, should be encouraged.Cryoelectron Microscopy. Future developments from specimen preparation, electron energy, electron optics, detector, and image processing? Discovery of discrepancies revealing perturbation effects in the crystal state? Development of liquid cell system to image proteins/viruses in solution. Determining protein structure inside cells (including use of correlated light and electron microscopies).Free-electron laser x-ray diffraction. Future developments? Is single protein molecule diffraction really possible?Single molecule studies. Advantage to ensemble averaging: a single molecule is always perfectly macroscopically oriented! Rate studies: a molecular conformational transition back and forth can provide both statistical (thermodynamic) and dynamic (kinetic rate constants) data in one experiment. Today’s tools include various forms of pulling-force spectroscopy and fluorescence correlation microscopy. Anticipated new tools in the future?Microfluidics. and related methods connecting different spatial and temporal resolution scales for example molecular models, biomimics, and tissue samples. Complement transport with chemical reaction stations using covalent surface immobilization into microscopic assembly lines.Density functional theory. According to a theorem by Kohn and Hohenberg, an electron density functional always exists that can electrostatically uniquely define a molecular ground state without need for consideration of Schrödinger wavefunctions. However, despite this existence proof, nobody has yet been able to produce such a density functional, and so-called DFT methods do not rest on true Density Functionals.We would especially welcome authors of exciting reports related to any of the problem fields to submit contributions to