This paper fabricated a high-performance chitin nanofibers (ChNFs)-integrated bulk acoustic wave (BAW) humidity sensor with an asymmetric electrode configuration. The ChNFs were successfully prepared from crab shells and used as moisture-sensitive materials to compare the performance of quartz crystal microbalance (QCM) humidity sensors with symmetric and asymmetric electrode structures. The QCM humidity sensor with a smaller electrode area exhibited high sensitivity of 58.84 Hz/%RH, competitive response/recovery time of 30/3.5 s, and low humidity hysteresis of 2.5% RH. However, it is necessary to choose a suitable electrode diameter to balance the stability and sensitivity because the impedance analysis result showed that the reduction of the electrode diameter leads to a sharp decrease in the Q value (stability). Next, the possible humidity-sensitive mechanism of the ChNFs-integrated asymmetric n-m electrode QCM humidity sensor was discussed in detail. Finally, the reasons for the highest sensitivity of the asymmetric n-m electrode QCM humidity sensors having a smaller electrode diameter were analyzed in detail in terms of both mass sensitivity and fringing field effect. This work not only demonstrates that the chitin nanofiber is an excellent potential material for moisture detection, but also provides a new perspective for designing high-performance QCM humidity sensors. The growing demand for precise humidity detection in many fields such as agricultural farming, medical monitoring, weather forecasting, and industrial manufacturing has contributed to the further development of humidity sensors ,2,3. AmoIn general, a QCM humidity sensor consists of a quartz crystal resonator (QCR) and a humidity-sensing material deposited on its surface, as the bare QCR lacks selectivity for the target detection . It is wAsymmetric electrode QCM sensors are also sensitive to the changes in electrical properties, such as conductivity and relative permittivity, because the upper surface within its partially electroded region is not shielded by the metal electrode, resulting in an enhanced fringing field effect ,15,16,17For QCM humidity sensors, the electrical parameters of the humidity-sensitive materials also change when adsorbing or desorbing water molecules, and this change affects the resonance state of the asymmetric electrode QCM humidity sensors, which in turn enhances their sensitivity. In 2021, Chen et al. proposed an asymmetric QCM humidity sensor with a ring electrode configuration . Using lChitin is a rich natural polymeric polysaccharide, which is the main structural component of crustacean shells. Chitin nanofibers treated by hydrolysis and ultrasonication have excellent properties such as low bulk density, large surface area, good chemical reactivity, low toxicity, biodegradability, biocompatibility, antioxidant activity, antibacterial properties, and excellent mechanical properties, which is well suited as moisture-sensitive materials ,22,23,24The experimental setup is schematically shown in The AT-cut, 6 MHz QCMs with different electrode structures were fabricated at Wuhan Hitrusty Electronics Co., Ltd. . The diameter of the quartz wafer was 8 mm. The symmetric and asymmetric electrode structures were formed by depositing circular electrodes of different diameters on both sides of the quartz wafer using a thermal evaporation method. The silver electrode on one side has a diameter of 5 mm, and for comparison purposes, the silver electrodes on the other side have diameters of 3, 3.5, and 5 mm, respectively, and were also labeled 3-5 QCM, 3.5-5 QCM, and 5-5 QCM, respectively. The equivalent circuit parameters of QCM with symmetric and asymmetric electrode structures were tested before depositing the ChNF films, as shown in 2SO4 solution (97.3% RH), KCl solution (84.3% RH), NaCl solution (75.3% RH), NaBr solution (57.6% RH), MgCl2 solution (32.8% RH), and LiCl solution (11.3% RH) at 25 The experimental equipment mainly consisted of humidity generation devices, a phase-locked oscillator , a vector network analyzer , and a personal computer (PC). The PLO and VNA were each linked to the PC for recording and evaluating the humidity sensing performance and resonance state of the ChNFs integrated QCM sensors. The fixed humidity levels were produced by saturated K−1 and 1557 cm−1 in the FTIR spectrum are two typical characteristic peaks of chitin, mainly attributed to the C=O stretching of amide I, and the combination of N-H bending vibrations with C-N and N-H vibrations in amide II, respectively [−1 and 3253 cm−1 are attributed to the O-H and N-H stretching vibrations, respectively, which are typical hydrophilic groups [The TEM image of the chitin nanofiber is displayed in ectively . Overallc groups ,25. Genec groups . Figure The Butterworth–Van Dyke (BVD) model illustrated in ceptance , as showAs shown in The dynamic responses of ChNF-3, ChNF-3.5, and ChNF-5 are in 2) of 0.9796, 0.9623, and 0.9812, respectively, like most published humidity sensors [The sensitivity for frequency-response humidity sensors is usually defined as the ratio of the frequency shift to the change in humidity levels. As shown in  sensors ,32,33,34The maximum frequency differences of ChNF-5, ChNF-3.5, and ChNF-3 are 29, 59, and 125 Hz, thus the humidity hysteresis of the sensors can be calculated as 2.0%, 2.1%, and 2.5 % RH at the humidity environment of 57.6% RH, respectively e. As sho2O molecules can be adsorbed on hydrophilic groups through hydrogen bonds. ChNF’s mass and viscosity will change as a result of the adsorption or desorption of H2O molecules, altering the Q value and operating frequency of the QCM. However, the electrical parameters of the ChNF film also change, thus affecting the fringing field distribution, and thereby changing the resonant state of the QCM.+ ions in the hydrophobic functional groups of ChNF combine with a tiny number of H2O molecules to create H3O+. As the humidity increases, ChNF adsorbs more water molecules, resulting in the formation of multilayer water molecules. At this stage, the sensitive film’s mass and viscosity start to rise even more, which lowers the resonance frequency and Q value of the QCM humidity sensors. Additionally, the electric field will cause the water molecules to become polarized, creating a significant amount of H3O+ ions [+, which also greatly enhances the ionic conduction of ChNF films.Monolayer water molecules are adsorbed via chemical bonding on the surface of ChNF at low relative humidity. Additionally, the frequency and Q value of QCM decrease insignificantly at this stage. The H3O+ ions . At the Since the asymmetric n-m electrode QCM humidity sensor has no metal electrode shading on the upper surface of the partially electroded area enhances its fringing field effect. As a result, frequency shifts associated with changes in the electrical characteristics of moisture-sensitive materials are created in addition to the frequency variations caused by mass and viscosity. Thus, the frequency variation of the asymmetric n-m electrode QCM humidity sensor contains three components, i.e., At first, for the asymmetric n-m electrode configuration, the partially electroded region is not shielded by the metal electrode because of the different electrode diameters at the top and bottom, which enhances its fringing field effect. The fringing field distributions of symmetric and asymmetric n-m electrode configurations were simulated using the finite element analysis method, and their potential and electric field distributions are given in For simplicity, 4 mm diameter, 500 nm-thick cylinders were placed in the center of QCMs to simulate the moisture-sensitive layer. In another aspect, the mass sensitivities of QCM determining equation ,56:(3)Sfectively . The u˜, P , and U (non-electroded region); h region .The mass sensitivity distributions of the 3-5 QCM, 3.5-5 QCM, and 5-5 QCM were calculated through the parameters of the AT-cut, 6 MHz QCM, as shown in Breath detection is beneficial in monitoring human signs and early medical diagnosis. In this paper, we investigate the potential application of the ChNF integrated QCM humidity sensor for respiratory detection. The sensor was placed 7 cm away from the nose and mouth for testing, and the results are shown in In summary, three QCM humidity sensors were fabricated by spraying chitin nanofibers on the surface of AT-cut, 6 MHz QCM transducers with different upper electrode diameters. The QCM humidity sensor having a smaller electrode area exhibited high sensitivity of 58.84 Hz/%RH, competitive response/recovery time of 30/3.5 s, and low humidity hysteresis of 2.5% RH. However, it is necessary to choose a suitable electrode diameter to balance the stability and sensitivity because the impedance analysis result showed that the reduction of the electrode diameter leads to a sharp decrease in the Q value of the QCM. Next, the possible humidity sensing mechanism of the ChNF-integrated asymmetric n-m electrode QCM humidity sensor was discussed. Since the asymmetric n-m electrode QCM humidity sensor has no metal electrode shading on the upper surface of the partially electroded area enhances its fringing field effect. The mass sensitivities of the 3-5 QCM, 3.5-5 QCM, and 5-5 QCM were calculated from the mass displacement amplitude, and it was found that the 3-5 QCM has the highest mass sensitivity. Therefore, frequency shifts associated with changes in the electrical characteristics of moisture-sensitive materials are created in addition to the frequency variations caused by mass and viscosity. Finally, we demonstrated the potential application of the ChNF integrated QCM humidity sensor through breath detection experiments. This work not only demonstrates that chitin nanofibers are an excellent potential material for moisture detection, but also provides a new perspective for designing high-performance QCM humidity sensors.


Current studies in extractive question answering (EQA) have modeled the single-span extraction setting, where a single answer span is a label to predict for a given question-passage pair. This setting is natural for general domain EQA as the majority of the questions in the general domain can be answered with a single span. Following general domain EQA models, current biomedical EQA (BioEQA) models utilize the single-span extraction setting with post-processing steps.In this article, we investigate the question distribution across the general and biomedical domains and discover biomedical questions are more likely to require list-type answers (multiple answers) than factoid-type answers (single answer). This necessitates the models capable of producing multiple answers for a question. Based on this preliminary study, we propose a sequence tagging approach for BioEQA, which is a multi-span extraction setting. Our approach directly tackles questions with a variable number of phrases as their answer and can learn to decide the number of answers for a question from training data. Our experimental results on the BioASQ 7b and 8b list-type questions outperformed the best-performing existing models without requiring post-processing steps.https://github.com/dmis-lab/SeqTagQA.Source codes and resources are freely available for download at Bioinformatics online. Extractive question answering (EQA) is the process of finding answers to questions from given passages. Biomedical Question Answering (BioQA) is a branch of QA where both the subject of the question and the passage has a biomedical context . EQA haslist questions  are more abundant in biomedical questions than in general domain questions.Despite recently increased interests in the field of BioQA, research on the characteristics of biomedical questions and corresponding passages is rare. As The single-span extraction setting, or ‘start-end span prediction’ setting, is common in existing general domain EQA and Biomedical EQA (BioEQA) models . We empirically verify that the sequence tagging approach is beneficial for answering list-type questions, as models are able to learn to tag multiple answers at once rather than being restricted to extract one answer span at a time. Furthermore, our setting is an end-to-end approach for list-type QA task that the model can learn to output the ideal number of answers for a given question, without using the rather complicated external processes of previous works. Adopting our sequence tagging strategy to BioEQA tasks showed that our model can achieve state-of-the-art (SOTA) performance for list-type questions. Average performance improvements over baseline model are 3.80% and 6.22% for BioASQ 7b and 8b List questions, respectively (F1 score).In this section, we briefly summarize previous works related to the questions in QA datasets and various modeling approaches for QA tasks.A number of general domain QA datasets are available as of today. SQuAD v1 and v2  are compIn comparison to the general domain, only a small number of QA datasets are currently publicly available for Biomedical NLP. The QA dataset of the BioASQ competition   is a series of datasets (https://www.nlm.nih.gov/databases/download/CQC.html). We select Iowa IC Questions as our source of questions as it is collected from the most diverse set of physicians among the CQC datasets. The Iowa IC Questions dataset contains 1,062 questions that were collected by observing 48 physicians for a half-day.datasets  that arePubMed queries We use the PubMed Query Log Dataset collected by naturally posed questions by PubMed users collected over one day.  dataset as a question dataset in the general domain setting.Corresponding passages or answers are not provided for both biomedical question datasets as they are not originally built for QA tasks. We use the n = 100; 50 for each biomedical question dataset) manually. For general domain questions, we counted questions using the given answers of the NQ dataset. We classify a set of randomly chosen biomedical questions (Our study shows that the proportion of factoid questions (i.e. questions which can be answered with a single phrase) is lower in biomedical questions than in questions in the general domain. In other words, the number of list-type questions among EQA questions, specifically factoid and list-type questions, is significantly higher in the biomedical context than in the general context. This finding verifies our hypothesis that biomedical questions have a tendency to require multiple answers.While annotating the types of questions, we observed that factoid questions often have alternative valid answer spans. In most cases, they are varied forms of the originally annotated answer, such as synonyms or abbreviations. The prevalence of synonyms and abbreviations for biomedical entities  are language representation models that are pre-trained on biomedical literature such as articles from PubMed and PubMed Central. They are the primary building blocks of multiple BioNLP tasks, such as NER, RE and QA tasks, and provide contextualized representations of the input sequences.In our experiments, BioBERT   and BiLSFollowing NER tasks, we used the BIO tag schema to denote answer spans, where B stands for the ‘beginning’ of an answer span, I for ‘inside’ and O for ‘outside’.broken sub-word tokens.When calculating loss and gradients, we exclude tags predicted at the positions of special tokens and question tokens: this means that the model will not be penalized for predicting wrong tags for these tokens. Tokens that we ignored predictions are as follow: [SEP], [CLS], tokens that compose questions and 4.2.3detokenize the output of the final layer to restore tokenized strings into their original forms, including reconstruction of sub-word tokens and proper removal of whitespace around punctuation marks. Other essential task-specific post-processing steps are taken to fit our output to the official evaluation scripts for the datasets. For example, answer candidates of list questions of BioASQ can be prepared by simple concatenation of predictions of the passages that belong to a question. For the approach where BiLSTM-CRF layer is used as the Sequence Tagging Layer, we choose answer candidates by using the Viterbi algorithm, and rank candidates based on the probability scores of the LSTM network.We apply minimal post-processing steps to the output of a tagged sequence. The output of the final layer (i.e. the sequence tagging layer) is a sequence of tokenized words and their corresponding tags. The main purpose of the post-processing step is to In this section, we first elaborate on our experimental settings. For the rest of the section, we report our experimental results and comparisons between the models with different settings.The BioASQ datasets are directly derived from the BioASQ Challenge which is an annual competition for biomedical semantic indexing and QA . Following A single sample contained in the BioASQ datasets contains the question and URL of relevant articles and snippets  as a sample for training and testing. A triplet contains only one item for a question and a passage element. The number of items for an answer element in a triplet is only one for single-span extraction configuration, while for a sequence-tagging configuration, an answer element can contain multiple items. Specifically, for a list-type question Q with a set of relevant passages i for a sequence-tagging configuration. For the training dataset, we excluded passages from which we could not find any matching answers. We defer details regarding pre-processing to the Statistics of list-type questions and data points for the BioASQ datasets are described in http://participants-area.bioasq.org/Tasks/b/eval_meas_2018; https://github.com/BioASQ/Evaluation-Measures). Each example of list-type questions is evaluated based on the precision, recall and F-1 measures. The scores are averaged over the list-type questions and reported as the final score for the system.The official evaluation metrics for BioASQ datasets differ according to the question type . We used a single NVIDIA Titan RTX (24GB) GPU for fine-tuning (single run) and the training process took less than 24 h for an experiment.We used In this section, we report the experimental results and verify that our approach to reformulate QA as sequence tagging improves the performance of existing QA models on list-type questions.5.4.1number of answers detection from question strings for such questions containing a number. On top of the previous model, Our baseline model from The original models of 5.4.2Our experimental results using the fully connected linear layer as Sequence Tagging Layers are displayed in 5.5Previous research papers have shown that the application of Recurrent Neural Networks (RNN), such as LSTM, and CRF layer can boost the accuracy of popular sequence tagging tasks, such as NER or part-of-speech tagging . The number of answers is most frequent in the first bin  for the baseline, but in our model and the testing dataset, the second bin  was the most frequent, providing circumstantial evidence that our model can learn the proper number of answers for a given question.number of answers detection, to handle list-type questions. For example, in order to answer the question ‘What 2 biological processes are regulated by STAMP2 in adipocytes?’, the model detects any number in the question, two (2), and outputs answers as many as the detected number. However, models with number of answers detection are susceptible to the proportion of questions with answers that have numbers. For the BioASQ 8b testing dataset, the proportion is nearly half than that of BioASQ 7b . Average performance improvements over baseline model (btac397_Supplementary_DataClick here for additional data file.


The difficulties in social interaction present in individuals with autism spectrum conditions may are related with the abnormal attentional processing of emotional information. Specifically, it has been hypothesized that the hypersensibility to threat shown by individuals with autism may explain an avoidance behaviour. However, this hypothesis is not supported by research and the underlying psychological mechanisms of social interaction in autism still unclear.The aim of the present study was to examine attentional processing biases by administering a computer-based attentional task in a sample of 27 children with autism spectrum conditions and 25 typically developed participants (age 11-15 years).The initial orienting of attention, the attention al engagement, and the attentional maintenance to different emotional scenes in competition  were measured by recording the eye movements during a 20 seconds free-viewingtask.The main findings were: i) children with autism spectrum conditions showed an initial orientating bias towards threatening stimuli; and ii) while typically developed children revealed an attentional engagement and attentional maintenance bias towards threatening stimuli, children with autism spectrum conditions did not.The findings of the present study are consistent with the affective information processing theories and shed light on the underlying mechanisms of social disturbances in autism spectrum conditions.


Hydrollbot, harnesses energy from evaporation for spontaneous and continuous fast self-rolling locomotion with a programmable trajectory in a constant-humidity environment. Moreover, the geometric parameters of the film were fine-tuned to maximize the rolling speed, and the optimised hydrollbot is capable of carrying a payload up to 100% of its own weight. The ability to self-propel fast under constant conditions with programmable trajectories will confer practical advantages to this robot in the applications for sensors, medical robots, actuation, etc.A range of soft robotic systems have recently been developed that use soft, flexible materials and respond to environmental stimulus. The greatest challenge in their design is the integration of the actuator, energy sources, and body of robots while achieving fast locomotion and well-defined programmable trajectories. This work presents such a design that operates under constant conditions without the need for an externally modulated stimulus. By using a humidity-sensitive agarose film and overcoming the isotropic and random bending of the film, the robot, which we call the  Many kinds of artificial materials have been developed to respond to light –7, heat Hydrollbot. Meanwhile, we experimentally optimize the geometric design and adjust humidity to achieve the maximum rolling speed with programmed trajectories.To address this challenge, we focus on humidity-responsive materials, which can convert the energy from ambient evaporation into mechanical energy and thus have attracted increasing attentions to be used in humidity-driven actuators. Such materials include polymer gels –37, elasAgarose film contains abundant hydroxyl groups and is therefore very sensitive to moisture. It can rapidly absorb water under high humidity and desorb water under low humidity. As a result, it undergoes deformation and can aid in motion in very small humidity gradients . MeanwhiL) of 18 mm , width (w) of 5 mm, and thickness (t) of 10 μm, the total weight of the robot is 6.8 mg  · lQ > (mBP g) · lP, which causes the robot to roll to the end Q , which the film length uncovered by the tapes. For t = 10 μm and RH ≈ 60%, when L ≤ 18 mm with Lt = 3 mm, we observed no reverse rolling. When L = 21 mm still with Lt = 3 mm, the probability of reverse rolling increased to 25% , the substrate humidity, and the material properties.L = 18 mm, Lt = 3 mm, and RH ≈ 60% and varied t from 10 to 30 μm. The cycle duration, T, and robot speed, v ( = L/T), were measured for continuous 4-8 cycles, which was decided by the robot length and substrate length. The duration of the rolling cycle increased with film thickness  by adjusting the water temperature between 23 and 61°C in the vessel. Note that the humidity could only be controlled within a range of ±2%. The effect of humidity on the rolling locomotion is shown in t, L, and/or Lt are changed, the humidity limits will change accordingly. For example, when t is 30 μm, L = 35 mm, and Lt = 7 mm, the ideal RH is in the range of 33% to 70% with 70% humidity offering the highest speed. All the experiment data for Figures Third, apart from the dimensional parameters of the Hydrollbot, humidity strongly influences the locomotion. To investigate the effect of humidity, we set Fourth, to find out the effect of material property on the locomotion speed, we built a simplified analytical model to estimate the locomotion speed of the robot using energy method based on experimental observation. It was assumed in the model that the robot absorbed energy from the humid environment at a constant rate, which was used to bend the robot and overcome its gravity. Then, by equating the humidity energy absorption of the robot to the summation of bending energy gain and gravitational potential energy variation, the locomotion cycle was derived Note . It shout = 10 μm, L = 18 mm, Lt = 3 mm, and RH = 70%, the maximum speed reaches 0.714 BL/s. The locomotion comparison between this optimized robot and the one with randomly selected parameters  is presented in The analytical results drawn as black lines in Figures Meanwhile, the loading-carrying capability of Hydrollbot has been demonstrated in Movie A unique feature of Hydrollbot is that its trajectory can be programmed simply by changing the robot geometry. Because the agarose film is isotropic, we can change the rolling direction by designing the shape of the film and the positions of the feet attached to its short sides; additionally, we can control the bending direction of the film by adjusting the relative positions of the PET strips. Four representative example geometries and their corresponding trajectories are shown in Figures Our humidity-responsive soft robot can roll on a humid surface without any additional energy input. Unlike existing robots of this kind, which require an environment with actively controlled variable humidity to move, the rolling locomotion of the Hydrollbot is powered by the inherent difference in humidity between two sides of the robot body when operating on a constant-humidity substrate. The optimized rolling speed is 0.714 BL/s, which is two magnitudes faster than current reported state-of-the-art humidity-responsive soft robots that move in constant environments. Another advantage of the Hydrollbot is that in addition to performing straight-line locomotion, it can be programmed to move in curved, zigzag, or other predefined trajectories by simply altering its geometry. We expect that these features will greatly advance the applications of humidity-driven soft robots in medical treatment, sensing, actuation, and so on. Future research will focus on the design of more advanced Hydrollbot structures that can autonomously perform complex locomotion paths. Moreover, incorporation of new materials may enable the Hydrollbot responsive to multiple stimuli and with more intelligent and reliable performance.Agarose films were prepared according to the following procedure . 6.0 g ot ≤ 20 μm), it is not necessary to attach the PET strips on the area with tapes, which is P1 and Pn marked as dash line on Firstly, agarose film was cut into rectangle by a laser cutter. The width of the rectangle was fixed to 5 mm to avoid sideway rolling, while the length was tuned to achieve optimized performance. Then, tapes with specific size were attached to the two ends of the film. As shown in t = 10 μm, the PET strips allocated on the area of tapes were not attached, which is demonstrated as dash line in To prepare robot with zigzag trajectory, the film was cut into parallelogram and only 3 PET strips were attached parallel to the two short sides. To prepare robot with polygonal trajectory, the film was cut into trapezoid and 3 PET strips equally divided the angle between the two oblique sides. To prepare robot with circular trajectory, the film shape was changed into sector and 4 PET strips equally divided the sector angle. The robot with flower-shaped trajectory was developed by changing the film formed by two arches with different centers and radii. 4 PET strips equally divided the angle between the two short sides. Because the film thickness φ15, GB/T1914-2007) above a vessel (1 liter) in an oil bath (Figure To evaluate the rolling properties of the robot, Hydrollbots of different sizes were placed on a filter paper (h Figure . The wat


In the brain, primary cilia are found on most, if not all, central neurons. The importance of neuronal cilia is underscored by the fact that human diseases caused by primary cilia dysfunction, which are known as ciliopathies, are associated with neuropathologies, including neuropsychiatric disorders and learning and memory deficits. Neuronal cilia are enriched for certain G protein-coupled receptors and their downstream effectors, suggesting they sense and respond to neuromodulators in the extracellular milieu. GPCR ciliary localization is disrupted in neurons from mouse models of the ciliopathy Bardet-Biedl syndrome, with GPCRs failing to localize to cilia, indicating the Bardet-Biedl syndrome proteins are required for trafficking of G protein-coupled receptors into neuronal cilia. Yet, dopamine receptor 1 accumulates in cilia in the absence of Bardet-Biedl syndrome proteins, suggesting Bardet-Biedl syndrome proteins are required for normal ciliary import and export. To further explore the roles of the Bardet-Biedl syndrome proteins in neuronal cilia, we examined localization of ciliary signaling proteins in a new constitutive Bbs1 knockout mouse model. Interestingly, we find that two additional ciliary G protein-coupled receptors (Gpr161 and Gpr19) abnormally accumulate in cilia on Bardet-Biedl syndrome neurons. In addition, we find that the GPCR signaling protein β-arrestin accumulates in a subset of cilia in the brain, suggesting the presence of additional unidentified ciliary G protein-coupled receptors. These results confirm the importance of the Bardet-Biedl syndrome proteins in establishing ciliary GPCR pathways and indicate that loss of Bbs1 leads to complex changes in the localization of signaling proteins in the brain. Primary cilia are signaling organelles that mediate specialized signal transduction pathways critical for normal development and cellular homeostasis . These pCiliopathies are associated with neuropathologies, such as hyperphagia-induced obesity, neuropsychiatric disorders, and learning and memory deficits . CertainGPCR localization to neuronal cilia is dynamic and regulated by environmental cues. For example, D1 ciliary localization is increased in response to an increase in cyclic AMP levels and decreased in response to agonist treatment . NPY2 anPrevious studies characterizing the impact of Bbs1 loss in mice utilized a model where the most common human BBS mutation (M390R) was knocked into the mouse gene . AlthougBbs1 mRNA is lost following recombination (Bbs1+/−) to generate wildtype (Bbs1+/+) and constitutive knockout (Bbs1−/−) animals. To test whether loss of Bbs1 impacts ciliary GPCR localization in the brain, we colabeled brain sections from adult Bbs1+/+ and Bbs1−/− mice with antibodies against Sstr3, Mchr1, or D1 and an antibody against AC3, which serves as a marker for neuronal cilia   . The len < 0.05) , indicat < 0.05) . NeverthBbs1+/+ and Bbs1−/− mice with antibodies against Gpr161 and AC3. In Bbs1+/+ sections Gpr161-positive cilia were barely detectable    . Similar < 0.01) . Interessections , which min vivo findings, we colabeled cultured Bbs1+/+ and Bbs1−/− hippocampal neurons with antibodies against Gpr161 and AC3. In Bbs1+/+ cultures, we rarely observed Gpr161-positive cilia. The proportion of Gpr161-positive cilia we observed was significantly lower than what has been previously published    . However 0.0001) , providi1 allele . Gpr161 1 allele .Bbs1+/+ and Bbs1−/− mice using our labeling procedures, we tested the impact of Bbs1 loss on Gpr19 ciliary localization by colabeling cultured Bbs1+/+ and Bbs1−/− hippocampal neurons with antibodies against Gpr19 and AC3. Similar to Gpr161, we rarely observed Gpr19-positive cilia in Bbs1+/+ cultures but observed abundant Gpr19-positive cilia in Bbs1−/− cultures (p = 0.1)    but a si 0.0001) . Thus, tBbs1+/+ and Bbs1−/− mice with antibodies against β-arrestin and AC3. We did not observe β-arrestin-positive cilia in Bbs1+/+ sections but observed abundant β-arrestin-positive cilia in Bbs1−/− sections  of cilia  allele has been previously described (Bbs1wt/null mice on a congenic background (C57BL/6J) were crossed with FVB/NJ mice from the Jackson Laboratory (#001800). Constitutive Bbs1null/null mice were generated by intercrossing Bbs1wt/null male and female mice on a mixed background. Fixed mouse brains were generated and processed as previously described . For each section, six to nine fields were imaged and the number of Sstr3-, Mchr1-, D1-, Gpr161-, arrestin-, and AC3-positive cilia was counted by an individual blind to the genotype. The results were expressed as the proportion of AC3-positive cilia that were positive for each GPCR or arrestin. To quantify relative ciliary AC3 levels, fluorescence intensity of ciliary AC3 in D1-positive and -negative cilia and Gpr161-positive and -negative cilia were measured in ImageJ. ROIs were drawn around individual cilia and the mean fluorescence intensity of the cilium compared to background was calculated. The fluorescence intensity of AC3 in D1-and Gpr161-positive cilia were averaged and compared to the average fluorescence intensity of AC3 in D1-and Gpr161-negative cilia, respectively. Quantification of ciliary lengths was measured in ImageJ by drawing lines calibrated to the scale bar along the length of AC3-positive cilia. Quantification of Gpr161-and Gpr19-positive cilia in cultured neurons was performed on three coverslips from three animals for each condition and genotype. For each coverslip at least six fields were imaged. The number of nuclei, Gpr161-or Gpr19-positive cilia, and AC3-positive cilia was counted by an individual blind to the genotype. The results were expressed as the proportion of AC3-positive cilia to nuclei and the proportion of Gpr161-or Gpr19-positive cilia to AC3-positive cilia. Data were analyzed using Prism nine software (GraphPad Software) and results were expressed as mean ± SEM. Statistical significance was tested using Student’s t-test.Quantification of cilia in brain slices was performed using coronal sections from 5–7-week-old


R between 0.896 and 0.998). Used together, these reverse descriptors are graphed in relation to their response to graphene. Based on this study’s findings, it is possible to predict the exchange correlation energy as well as the geometric structures of graphene sheets with very little computational cost.Over the past few years, the popularity of graphene as a potential 2D material has increased since graphene-based materials have applications in a variety of fields, including medicine, engineering, energy, and the environment. A large number of graphene sheets as well as an understanding of graphene’s structural hierarchy are critical to the development of graphene-based materials. For a variety of purposes, it is essential to understand the fundamental structural properties of graphene. Molecular descriptors were used in this study to investigate graphene sheets’ structural behaviour. Based on our findings, reverse degree-based molecular descriptors can significantly affect the exchange-correlation energy prediction. For the exchange-correlation energy of graphene sheets, a linear regression analysis was conducted using the reverse general inverse sum indeg descriptor,  Carbon is a widely studied and influential element across many scientific disciplines. Many allotropes of carbon exist, each with special properties, such as graphite, diamond, and amorphous carbon as well as fullerenes, carbon nanotubes (CNTs), and graphene ,3,4,5,6.A nanostructure is composed of distinct and measurable elements, known as nano-patterns. In contrast to random patterns, these patterns follow the order of chemical and physical laws. Physical and chemical laws determine how atoms and molecules form discrete and measurable geometric structures, ranging from repeating lattices to complex shapes. Rules from the chemical graph theory can be used to analyze and predict the properties of these well-defined structures . In the In this article, molecular graphs are represented by e degree  of a verTo derive a set of reverse degree-based topological descriptors, we first define the reverse general inverse sum indeg descriptor, denoted by Our main objective is to offer an alternate method, with high accuracy, for computing the exchange-correlation energies of graphene sheets. The DFT calculations of the exchange-correlation energies of graphene sheets have the advantage of being accurate, but they also have the disadvantage of being computationally expensive. Therefore, A wide range of molecular descriptors have been proposed in the current literature, but many of them show little evidence that they correlate with any of the physical or chemical properties of the chemical structure. This section highlights the inquiry that was undertaken to determine whether reverse general inverse sum indeg descriptors possess any predictive power and whether or not they should be used in any chemical applications. In order to achieve this, we selected ten graphene sheets from one cycle to ten cycles. The molecular structures of these graphene sheets are provided in C24 (ii)(iii)(iv)(v)(vi)(vii)(viii)(ix)(x)(xi)Case 2. When Applying the definition of the reverse general inverse sum indeg descriptor, Using Remark 2.(i)(ii)(iii)(iv)(v)(vi)(vii)(viii)(ix)(x)(xi)Case 3. Forthe reverse edge partition of the graphene containsedges, edges, andedges.Using the definition of the reverse general inverse sum indeg descriptor, Using Remark 3.(i)(ii)(iii)(iv)(v)(vi)(vii)(viii)(ix)(x)(xi)Case 4. Whenthe reverse edge partition of the graphene contained onlyedges, and by the definition of reverse general inverse sum indeg descriptor, Remark 4.(i)(ii)(iii)(iv)(v)(vi)In this case, we noted the following 11 reverse topological descriptors for the graphene as follows:l and k. As these values increase, the magnitude of all reverse descriptors also increases, and this can be visualized by the 3D graphical representation in In The regression models  derived The reverse sum−connectivity descriptor with The density functional theory (DFT) calculations of the electronic structure, such as the exchange-correlation energies of the graphene sheets, were precise; however, they were computationally expensive while the reverse topological descriptors models presented herein required minimal computations and provided high levels of accuracy.Analytical expressions of the reverse first and second Zagreb descriptor, reverse Randić descriptor, reverse sum−connectivity descriptor, reverse harmonic descriptor, reverse hyper Zagreb descriptor, reverse geometric−arithmetic descriptor, reverse inverse sum indeg descriptor, and reverse redefined first and third Zagreb descriptors have been obtained for graphene structures.Researchers who are trying to better understand the behaviour of graphene are likely to find the numerical values and graphical representations presented in this article helpful.In this paper, we presented a reverse general inverse sum inverse degree descriptor


Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neuromuscular disorder with no cure available and limited treatment options. ALS is a highly heterogeneous disease, whereby patients present with vastly different phenotypes. Despite this heterogeneity, over 97% of patients will exhibit pathological TAR-DNA binding protein-43 (TDP-43) cytoplasmic inclusions. TDP-43 is a ubiquitously expressed RNA binding protein with the capacity to bind over 6000 RNA and DNA targets—particularly those involved in RNA, mitochondrial, and lipid metabolism. Here, we review the unique structure and function of TDP-43 and its role in affecting the aforementioned metabolic processes in ALS. Considering evidence published specifically in TDP-43-relevant in vitro, in vivo, and ex vivo models we posit that TDP-43 acts in a positive feedback loop with mRNA transcription/translation, stress granules, cytoplasmic aggregates, and mitochondrial proteins causing a relentless cycle of disease-like pathology eventuating in neuronal toxicity. Given its undeniable presence in ALS pathology, TDP-43 presents as a promising target for mechanistic disease modelling and future therapeutic investigations. SOD1, C9orf72, NEK1, ATXN2, and/or TARDBP . I. IP497S WT, TDP-43G298S, TDP-43A315T, TDP-43Q311K, or TDP-43M337V in NSC34 or HEK293T cells leads to a significant reduction in overall ATP production and specifically, a reduction in complex I activity  via the mitochondrial localisation motifs  176]. U. U176]. Q331K mouse model has been shown to have significant downregulation of NEK1, which regulates cell death and mitochondrial membrane permeability via VDAC1 phosphorylation  capability of mitochondria are their innate ability to undergo fission and fusion with one another—known as mitochondrial dynamics. This unique capability allows mitochondria to maintain cellular networks, metabolise ATP, and ensure cells have enough healthy mitochondria ,201. MitA315T mice, abnormal retrograde movement of mitochondria is observed prior to the onset of disease . I. IA315T  defects , while i defects .With a wide range of disrupted mitochondrial functions caused by TDP-43, a further understanding of TDP-43-mitochondrial interactions is required to elucidate the extent and breadth of pathological consequences in ALS. This is of particular relevance given evidence of TDP-43 eliciting inflammation via mitochondria  and repo2 which are then utilised in OXPHOS. Despite β-oxidation producing more energy per mole compared to glycolysis, β-oxidation is limited by glucose oxidation through channel import inhibition [To meet the large energy demands of neurons in the central nervous system, glucose is utilised as the predominant energy substrate to produce ATP via mitochondrial OXPHOS . For simhibition , whereasG93A mouse model [Q331K and TDP-43M337V models, mutant TDP-43 directly increased the expression of UCP2, however no indication of its effect on glucose or fatty acid oxidation was described [In ALS, an overwhelming amount of evidence suggests that energy metabolism is perturbed leading to dysregulation of cellular ,216,217 se model ,225,226.se model . Interesescribed . Given tTARDBP-inducible KO mice [A315T [A315T mice [N390D mice [Tbc1d1, an essential gene required for facilitating glucose uptake in skeletal muscles and fat deposition has been observed in TARDBP mice [A315T exhibits increased body fat percentage, decreased lean mass percentage, but no difference in blood glucose, cholesterol, or triglycerides between compared to their control counterparts [Tbc1d1 mRNA in skeletal muscle, rather than an increase in caloric consumption [Q331K mice, no alterations in Tbc1d1 mRNA was observed, despite these mice losing over 40% of their hind limb muscle mass [TARDBP mutations may alter Tbc1d1 mRNA, subsequently altering body composition and systemic metabolism through a switch to fatty acid oxidation due to a loss of glucose uptake. Extensive studies are needed to determine whether TDP-43 contributes to metabolic dyshomeostasis in ALS, and whether this might be underpinned by TDP-43-mitochondrial interactions.Despite the plethora of TDP-43 mice available for modelling ALS, evidence to demonstrate links between TDP-43 and changes in cellular glucose/lipid or systemic metabolism is scarce. No studies to date have utilised TDP-43 derived mouse tissues for in vitro analysis of metabolomics or lipodomics. However, at the systemic level, perhaps the most readily available data pertains to weight loss, which is a common phenomenon in ALS that is often used as a proxy to inform of whole-body metabolic balance. In TDP-43 mice, the timing of the onset of weight loss varies greatly, ranging anywhere from seven days of age in  KO mice , to 35 d KO mice , to 90 de [A315T , to 420 15T mice , to 700 15T mice , and not90D mice . While t90D mice ,234, a l90D mice , and a l90D mice . In suppDBP mice ,235. Morterparts . The incsumption . By contcle mass . AlthougC9orf72 patient fibroblasts the levels of oxidative stress in lipids was increased 2-fold leading to autophagy [PGC-1α, which would drive a switch from glycolysis to β-oxidation [A4VSOD, Q343RC9orf72, TDP-43, and sALS lines [Many studies have investigated metabolism in ALS patient-derived cell, and in sALS patients. Patient-derived cell models could prove to be a useful tool to investigate ALS disease mechanisms given the ability to capture similar ALS-like cell death pathways and TDP-43 mislocalisation as a hallmark of disease progression ,238. Invutophagy . In otheutophagy . This chxidation . In a muxidation . In partLS lines . Taken tTARDBP mutations are extremely rare in ALS patients, TDP-43 aggregates and signalling could explain some of the observed alterations in systemic metabolism—as seen in in vitro studies as stated above. There are several potential mechanisms through which TDP-43 can act on metabolic pathways. It is proposed that post-translational modifications of lipid metabolism pathways can alter patient phenotypes [SREBP2 a mediator of cholesterol metabolism [CYP27A1, in patients with TDP-43 proteinopathy [HNRNPK [TARDBP mutations on systemic metabolism in patients. Thus, this an exciting area of research that remains to be explored.In ALS patients hypermetabolism, hyperlipidemia, decreased body mass index and lower glucose use in the brain are associated with survival ,251,252.enotypes , or meditabolism . TDP-43 tabolism ,255. Inttabolism . Perturbinopathy . Additio [HNRNPK , a known [HNRNPK . Further [HNRNPK . In cere [HNRNPK  with alt [HNRNPK  homocyst [HNRNPK , and cho [HNRNPK ; these s [HNRNPK . DespiteTARDBP mutations or TDP-43 overexpression remain unknown. With the unique ability of TDP-43 to bind and alter the expression of thousands of RNA and DNA targets, there is little argument in discounting potential effects-whether direct or indirect-in altering cellular metabolism. Based on the evidence available, it appears that oxidative stress is an early indicator of cellular dysfunction. It also appears that the combination of oxidative stress and aggregated TDP-43 exerts a negative impact on mitochondrial function and downstream cellular metabolism. In surveying the evidence to date, we posit that the combination of cellular stress and TDP-43 aggregates leads to a relentless feedback loop between oxidative stress, stress granule formation, TDP-43 cytoplasmic aggregation, downregulation of essential mitochondrial and metabolic proteins, altered mitochondrial function and dynamics, a switch to fatty acid β-oxidation, and altered cellular metabolism—which collectively compounds leading to motor neuron death (ALS is a multifaceted and complex neurodegenerative disorder. The heterogeneous nature of this disease presents an enormous challenge in understanding the mechanisms and identifying efficient therapeutic targets. Early theories of ALS mechanisms surrounding proteinopathies and oxidative stress have been largely explored, however only until recently have they been considered mutually inclusive. TDP-43 cytoplasmic inclusions are a hallmark of ALS, and they are likely a disease target which unites several plausible mechanisms of disease. Each domain of TDP-43 proves essential in its respective role, however little outside of the CTD and the subsequently generated C-terminal fragments have been explored. Some evidence has demonstrated that the alteration of either the NLS, NES, or RRM domains facilitate cytoplasmic aggregation and RNA metabolic defects. Unfortunately, the exact mechanisms on how these aggregates form in patients or models without on death .With a plethora of evidence suggesting several cellular and mitochondrial defects in ALS, it is highly unlikely that one therapeutic would be able to repair or attenuate facets leading to motor neuron toxicity. To better understand the effect of TDP-43 on aberrant RNA function, mitochondrial dysfunction, and cellular and systemic metabolism, more relevant TDP-43 human iPSC-derived motor neuron and/or organoid models might prove to be beneficial in facilitating translational research outcomes in ALS. Such translation would be strengthened by complementary studies in humans.


This study evaluated risk factors of sarcoidosis among Airborne Hazards and Open Burn Pit Registry (AHOBPR) participants using a retrospective age and sex-matched case–control design of AHOBPR participants deployed to Afghanistan or Southwest Asia with and without sarcoidosis diagnosed in the Veterans Health Administration (VHA). Logistic regression models tested for associations between sarcoidosis and self-reported cumulative deployment-related exposures. 661 Veterans (0.37%) were diagnosed with sarcoidosis in VHA. Logistic regression demonstrated lower odds of sarcoidosis in Hispanic participants  and those who served in the Navy . African American veterans  and former smokers  were at elevated risk. Of the exposure variables, convoy activities had the highest odds of being associated with sarcoidosis and was marginally statistically significant . Sarcoidosis was an uncommon diagnosis among AHOBPR participants and was associated with only one of eight assessed cumulative deployment-related exposures. Patients often present with respiratory symptoms such as cough, dyspnea, and chest pain accompanied by fatigue, malaise, fever, and weight loss2. Definitive diagnosis requires chest radiographic evidence accompanied by noncaseating granulomas on biopsy, with all other causes of granulomas ruled out3. Sarcoidosis affects people of all racial and ethnic groups and occurs at all ages, although it usually develops before the age of 50 years, with the incidence peaking at 20–39 years. It is more common among African Americans with an adjusted annual incidence roughly three times that among white Americans 4. Women are also more likely to have sarcoidosis across racial and ethnic groups5. Low income and other financial barriers to care are significantly associated with sarcoidosis severity at presentation even after adjusting for demographic characteristics of race, sex, and age6.Sarcoidosis is an uncommon condition with a prevalence of 60 per 100,000 in the United States8. More recent exploration has supported a role for the epigenome in sarcoidosis, modulating the transcription of genes, perhaps in response to environmental factors, and initiating or perpetuating disease9. A 2016 meta-analysis involving more than 6000 patients from various countries worldwide suggests a significant association between sarcoidosis and some infectious agents, based on the marked difference in the percentage of microbial DNA-positive samples in sarcoidosis patients versus controls, especially mycobacteria (odds ratio (OR) 6.8) and P. acnes (OR 18.80)10. Both organic and inorganic materials have been found to be associated with sarcoidosis, especially in occupational cohorts11. Culprit materials include silica and silicates, metals, dust from the World Trade Center destruction, and wood combustion products identified through epidemiologic investigation and case reports15.Several factors have been associated with sarcoidosis including environmental and occupational exposures, infection, genetics, and epigenetics. It appears likely that the interplay of these factors triggers and sustains sarcoidosis. For example, numerous studies have consistently linked human leukocyte antigen genes to sarcoidosis and genome wide association studies have identified a few disease-risk alleles16. A separate race-stratified analysis of 27 years of Navy personnel data found higher frequencies of sarcoidosis among aviation structural mechanics and food service personnel17. The authors suggest that a dust or moisture-related lung disease may have been erroneously classified as sarcoidosis, or, alternatively, that sarcoidosis may be associated with an unspecified occupational exposure17. Another analysis indicated that the incidence of sarcoidosis declined among naval enlisted men during 1965–1993, particularly among African-American men, and that the risk for sarcoidosis was statistically associated with the assignment of naval enlisted men to aircraft carriers18. Overall, the literature supports the possibility of a higher risk of sarcoidosis among military service members with a past elevated risk among certain naval occupational specialties but does not pinpoint a specific exposure trigger.Because of unusual or even unique military exposures, sarcoidosis may be more common among US military service members and veterans, and risk may vary by military branch, occupation, and cohort of service. For example, elevated rates of sarcoidosis rates were detected in the 1960s and 1970s (the Vietnam era) among Navy personnel along with a decline in the African American/White ratio of these rates from about 17:1 to 6:1. The same analysis detected a lower risk of sarcoidosis among men who worked only on “clean ships”. These findings suggest that environmental exposures may cause (or increase one’s susceptibility to) sarcoidosis-like disease in naval settingsThe US Department of Veterans Affairs (VA) and Department of Defense (DoD) Airborne Hazards and Open Burn Pit Registry (AHOBPR) is a voluntary online questionnaire available to veterans and active military service members who deployed to Southwest Asia or Djibouti after 1990 or Afghanistan after 2001. The questionnaire addresses several items related to exposures of potential relevance to sarcoidosis, including burn pit smoke and sandstorm exposure, construction activities, and refueling and engine maintenance activities. We utilize AHOBPR data to identify U.S. veteran participants deployed after 2001 with a sarcoidosis diagnosis in the Veterans Health Administration (VHA) and age matched controls to identify military exposure and other factors associated with sarcoidosis in this subpopulation of veterans.This analysis draws from data for 212,427 individuals who were deployed to Southwest Asia, Afghanistan, or Djibouti after October 7, 2001, and completed the online AHOBPR questionnaire as of August 15, 2020.The project was reviewed by the Institutional Review Board and the Research and Development Committee of the VA-New Jersey Health Care System. These boards granted a waiver of informed consent for this secondary analysis of data collected for clinical purposes. All analyses were conducted in accordance with relevant guidelines and regulations.19.The study population is AHOBPR participants who completed the online questionnaire between April 1, 2014, and August 15, 2020, who had records in the Veteran Health Administration. A case of sarcoidosis was defined as an AHOBPR participant with one or more International Classification of Diseases (ICD) version 9 or 10 codes  for sarcoidosis in VHA records between 2011–2020. Controls were defined as AHOBPR participants with one or more VHA encounters between 2011–2020 and no documented sarcoidosis ICD codes. Optimal matching on age, stratified by gender, was performed at a 1:4 ratio to obtain the controlsRespondents listed all deployments  separately and duration of each deployment was calculated from deployment start and end dates. These were summed for a cumulative deployment length in days. Exposure to burn pit smoke (“Were you near a burn pit during these dates”) was queried for all deployments after October 7, 2001. Participants reported average number of hours of burn pit smoke exposure per day for each deployment segment which was multiplied by the number of days for that deployment. These values were summed for cumulative hours of burn pit smoke exposure over all deployments (“Cumulative Burn Pit Smoke”) which was divided by 24 h/day and average month length (365.25/12) to produce cumulative months of burn pit smoke exposure.Other self-reported military exposures and activities included: heavy smoke from weapons, signal smoke, markers, or other combat items (“Heavy Smoke”); work in convoys or other vehicle operations (“Convoy”); perform refueling operations (“Refueling”); perform aircraft, generator, or other large engine maintenance (“Engine Maintenance”); perform construction duties (“Construction”); perform pesticide duties (“Pesticides”); and dust storms (“Dust Storms”). Participants reported these exposures as a duration of 0–31 days per month on average over all deployments. Cumulative total exposure was calculated from the average number of days per month (0–31 days) multiplied by the total number of months deployed (cumulative number of days deployed divided by 31 days/month). The group ’Unknown’ includes the responses of ‘I do not know’ and ‘Do not wish to answer’, as well as missing responses. In recognition that there could be differences between cases and controls with regard to the time since last deployment that might impact the effective ascertainment period, we compared time since last deployment to the end of the ascertainment period (“Time since last deployment”).2) was calculated from self-reported height and weight on the AHOBPR questionnaire. BMI was treated as a continuous variable in the regression model; missing and non-physiologic values were labelled “Other”.Age in years, a continuous variable, was calculated from date of birth relative to questionnaire completion date from DoD personnel service records migrated into the AHOBPR. Data on sex , race  and ethnicity  was obtained from DoD records and supplemented with VHA data, if missing. Branch of service  was determined based on the branch during the participant’s last deployment from DoD personnel records. Body mass index  tested for associations between sarcoidosis case status (yes vs. no) and exposure variables of interest (described above). We report odds ratios (ORs) and 95% confidence intervals (95% CI’s) for each variable included in the model. ORs for cumulative deployment-related exposures were reported in 6 month increments to ease interpretation and better match the experience of typical deployment durations.A descriptive statistical analysis was performed for all variables by stratifying cases and controls. Bivariate analyses, From 212,427 individuals who were deployed to Southwest Asia, Afghanistan or Djibouti after October 7, 2001, we identified 177,718 AHOBPR participants who completed the AHOBPR by August 15, 2020, and had one or more encounters documented in VHA records. From that denominator we identified 661 veterans (0.37%) with an ICD code for sarcoidosis between 2011–2020. They were matched by sex and age to 2641 control AHOBPR participants who used VHA during the same period and had no ICD codes for sarcoidosis.2 vs. 29.1 kg/m2 in controls). The time since last deployment demonstrated a difference between cases (mean 14.7 (standard deviation 7.3) years) and controls (mean 12.2 (SD 6.4) years; p < 0.001).Bivariate analyses results are reported in Table Bivariate analysis of cumulative exposures by sarcoidosis status indicated no statistically significant differences in mean duration of any exposure Table . Mean duFully adjusted logistic regression analysis Table  demonstrOnly cumulative convoy exposure was associated with sarcoidosis diagnosis in the multivariable logistic regression model Table . ParticiWe post hoc explored the possibility of statistically significant interactions between cumulative burn pit smoke exposure and two variables associated with sarcoidosis: race and smoking status. Neither interaction was statistically significant see .Among veterans who served in Iraq, Afghanistan, and/or Djibouti after 2001, who utilized VHA one or more times between 2011–2020, and completed the AHOBPR between 2014–2020, we identified 661 with a diagnosis of sarcoidosis documented in the VHA medical record. In a multivariable model of self-reported military exposures, race, ethnicity, military branch, body mass index, time since last deployment, and smoking status, we found that African American race, non-Hispanic ethnicity, and former smoking status were associated with increased risk of sarcoidosis diagnosis while those who reported military service in the Navy were less likely to have sarcoidosis (compared to Army service). We found only self-reported cumulative convoy activity exposure independently associated with sarcoidosis in the adjusted model.21. The relationship between smoking and sarcoidosis is more complex due to their temporal dependence—individuals suffering from symptoms due to undiagnosed condition or those newly diagnosed with a chronic respiratory disease may be more likely to stop smoking, for example. However, most studies have identified a higher risk of sarcoidosis in never or former smokers, which is partially reflected in our data23. Concordant identification of these risk factors in this investigation with regard to published literature supports the validity of the study design, and it suggests that null associations with other factors may reflect their true relationship in the study population, AHOBPR respondents who utilize the VHA. Extrapolation of these findings to the broader population of deployed veterans is not appropriate due to the voluntary nature of participation in the AHOBPR.Participants of African American race, non-Hispanic ethnicity, and higher body mass index were associated with greater odds of a sarcoidosis diagnosis. These characteristics have been consistently identified as risk factors for incident sarcoidosis in epidemiologic studiesThe AHOBPR questionnaire explicitly asks respondents to report exposure to a list of factors which may be plausibly associated with lung health: burn pit smoke; heavy artillery and machinery smoke; convoy activity and vehicle operations; refueling; engine maintenance; construction; pesticide application duties; and dust storms. Only the association between sarcoidosis and convoy activity during deployment was statistically significant , suggesting hypotheses that could be pursued in future research. The actual wording of the survey item was “In a typical month, how many days were you in convoy or other vehicle operations?” a fairly non-specific question suggesting the need for more detailed approaches to exposure assessment relevant to this domain, e.g., location in vehicle, specific role/activities, availability/use of vehicle climate control, external environmental conditions. While it is possible that a larger sample might detect a small association between sarcoidosis and other examined exposures, in general, case–control studies overestimate associations, suggesting that the observed lack of associations may be robust to larger samples.24. Of note, the association between Navy service and lower odds of sarcoidosis is consistent with a recent study of Military Health System data showing that the Navy accounted for the lowest proportion of sarcoidosis cases compared to the other service branches over 2004–201325. Thus, while sailors have historically been considered at elevated risk for sarcoidosis, analysis of more recent data suggest the observed elevation of risk among Naval personnel may have peaked during the Vietnam era (1960s–1970s)28. Analysis of larger groups of military personnel across branches will be necessary to better answer these questions and to elucidate exposure- or task-specific risks of sarcoidosis.Supporting this conclusion, Forbes and colleagues examined sarcoidosis incidence rates among active-duty Army personnel from 2005 to 2010 and reported no difference between those deployed to Southwest Asia compared to those who were never deployed, suggesting that in-theater exposures may not meaningfully increase the risk of developing sarcoidosis26 and the consistency of findings comparing self-reported, and clinician documented diagnoses27. However, registry-only approaches are limited by reliance on self-report and selection biases from voluntary participation which is consistent with recommendations from the National Academies of Sciences, Engineering and Medicine (NASEM)28. Our analysis demonstrates this approach using a case–control analysis nested within the cohort of AHOBPR participants. A strength of this study and the use of the AHOBPR data is the relatively large cohort of individuals with sarcoidosis (n = 661) with available medical record data and self-reported exposure information and well-matched controls.This report is the first published analysis of AHOBPR data linked to VHA medical record data to explore risk factors for a disease not self-reported on the AHOBPR questionnaire. Leveraging the AHOBPR to characterize potential associations between burn pit and military-related environmental exposures and adverse health outcomes can inform operational harm reduction efforts and the design and implementation of post-deployment surveillance and treatment programs. Earlier analyses of AHOBPR have demonstrated its potential for detecting associations within the population of participants28. First, the AHOBPR is a voluntary activity and captures only a fraction of all potentially eligible veterans. Our cases were identified from the cohort participants as of August 15, 2020, representing only 212,427 participants out of an estimated 3.5 million eligible (see the NASEM report for information about the entire AHOBPR cohort)28. As such, there are likely several biases inherent in the data; eligible service members and veterans with greater concern about their exposures, those who are less healthy, and those with fewer alternatives to care may be more likely to participate in the AHOBPR. Second, while participants are presented with deployment segments from DoD records, the information gathered from the AHOBPR is self-reported, including information about any missed deployment segments. For these reasons, we do not fully discount the possibility of a clinically significant relationship between certain types of military exposures and sarcoidosis. Because of the self-reported and retrospective nature of the AHOBPR questionnaire, it is plausible that substantial inaccuracies in classification of the intensity and types of exposure may have masked a true association. Future analyses to address this limitation must incorporate data sources beyond the AHOBPR, including objective exposure ascertainment. On the other hand, because sarcoidosis was not a listed condition, we relied on documentation in the VHA medical record to classify cases and controls; a relative strength of this analysis. This does raise a third limitation of the study, however; we only included AHOBPR participants who had utilized the VHA one or more times to ensure accurate disease classification. Therefore, our findings cannot be applied to veterans who do not use the VHA. It is also well-established that disease codes captured at the time of care are not always accurate, another limitation of our approach. Finally, race and ethnicity is unknown for some cases and controls, although the proportions are relatively low for VHA and DoD data29.There are several limitations of this report as enumerated in the NASEM review of the AHOBPRAlthough it is unlikely that the diagnosis of sarcoidosis occurred prior to deployment, we were unable to confirm the exact onset or initial diagnosis outside the VHA medical record due to the retrospective nature of our analysis. To address potential differential time for recognition of sarcoidosis, we examined the time from last deployment to the end of the case status ascertainment period. Due to the difference in mean time between cases (14.7 (SD 7.3) years) and controls (12.2 (SD 6.4) years) (p < 0.001), we included this variable as a covariate in the final model. We were unable to address the possibility of differential reliance on VHA services between cases and controls which might have increased or decreased the likelihood of documentation of a sarcoidosis diagnosis.Our findings of an association between race and ethnicity and sarcoidosis are consistent with published literature, suggestive of external validity. This corroboration of a well-established risk factor of sarcoidosis supports our conclusion that, in this cohort of AHOBPR participants who use the VHA, the examined military exposures are not prominently associated with sarcoidosis. These results suggest the need for more targeted explorations of specific exposures of concern using rigorous epidemiologic approaches and objective assessments of exposure. Advancing our understanding of the genetic contributions and gene by environment interactions relevant to sarcoidosis, including military exposures, may also be a fruitful direction for future research. The AHOBPR and linkable data available from the VHA and Department of Defense may provide unique opportunities for large scale investigations to test hypothesized associations among genetic, exposure and other individual factors and sarcoidosis.Supplementary Table 1.


The Ag-graphene composites and nickel powder were ball-milled and mixed in a mass ratio of 85:15. The Ag-graphene/Ni was tested as an electrical contact material after the pressing, initial firing, repressing, and refiring processes. Its fusion welding force and arc energy were measured. The results show a 12% improvement in electrical conductivity with a graphene doping content of approximately 0.3 wt% compared to undoped contacts, resulting in 33.8 IACS%. The average contact fusion welding force was 49.49 cN, with an average reduction in the fusion welding force of approximately 8.04%. The average arc ignition energy was approximately 176.77 mJ, with an average decrease of 13.06%. The trace addition of graphene can improve the overall performance of Ag/Ni contacts and can promote the application of graphene in electrical contact materials.Ag/Ni composite contact materials are widely used in low-voltage switches, appliances, instruments, and high-precision contacts due to their good electrical conductivity and processing properties. The addition of small amounts of additives can effectively improve the overall performance of Ag/Ni contact materials. Graphene has good applications in semiconductors, thermal materials, and metal matrix materials due to its good electrical and thermal conductivity and mechanical properties. In this paper, Ag-graphene composites with different added graphene contents were prepared by in situ synthesis of graphene oxide (GO) and AgNO Ag/Ni contact material is widely used in power relays, small circuit breakers, line protection switches, and high-precision contacts. Under some circumstances, it can take the position of a hazardous AgCdO contact material because of its benefits of superior processing flexibility, strong electrical and thermal conductivity, and low contact resistance.Under high-current conditions, Ag/Ni contact materials can melt and weld, reducing the service life of the contacts. Fusion welding of contact materials often leads to safety accidents and reduces the reliability of electrical appliances. With the expansion of applications, new requirements have been placed on the resistance to fusion welding and arc erosion of Ag/Ni-based contact materials . Many stGraphene is a two-dimensional honeycomb monolayer sheet material composed of carbon atoms hybridized in sp2, which has attracted much attention due to its physical properties such as electrical, thermal and mechanical properties ,5. GraphGraphene can also be used as an additive to strengthen metal matrices that are nickel-based, copper-based, and aluminum-based, and can improve the overall electrical conductivity or mechanical properties of composite materials ,16,17. T3 and GO solutions at room temperature with vitamin C as the reducing agent to control silver nanoparticle-decorated graphene oxide (AgNP-GO) composites in terms of size [Ag-graphene composites are generally synthesized in situ from graphene oxide (GO) and metal salt solutions. the substrate of GO contains a large number of hydroxyl, epoxide, carbonyl, and carboxyl groups , which a of size . Yang et of size . Hao et  of size . GraphenBoth metals, Ag and Ni, have a low solubility in the solid state and cannot combine into a single liquid phase at temperatures higher than the Ni melting point (1453 °C) . Therefo3 and GO suspensions, the resulting material was subjected to X-ray diffraction (XRD), and all GO and AgNO3 were found to be reduced. Nickel powder and Ag-graphene were combined in a ball mill for two hours. The samples’ electrical contact qualities were evaluated following the powder’s pressing, initial firing, repressing, and refiring. Measurements were made of its various characteristics, including fusion welding force, contact angle, and arc energy.We chose safe and green ascorbic acid (vitamin C) as the reducing agent to co-reduce the AgNO3 was obtained from Tianjin Damao and polyvinylpyrrolidone (PVP) from Sinopharm , and all chemicals were of analytical grade or above.Graphene oxide (GO) powder was prepared using the improved Hummers method from Nanjing XF Nano Company . It has a thickness of 0.8–1.2 nm and a flake diameter of 0.5–5 μm. AgNOThe X-ray diffractometer (XRD) was a Rigaku SmartLab model made in Japan, with a scan range setting of 6° to 90° and a scan speed of 5°/min.We chose the JF04D, an electrical contact material test system developed by the Kunming Institute of Precious Metals, to test the samples, with a protection voltage setting of ±40 V, a test voltage of 24 V DC, and a current of 15 A DC.3 in 80 mL and combined them with GO solution after adding 1 mg of polyvinylpyrrolidone (PVP) for dispersion. At room temperature, 500 mL of 0.3 mol/L ascorbic acid solution was slowly added to reduce Ag and GO together, resulting in a white precipitate.Three portions of GO powder, each weighing 5 mg, 10 mg, and 20 mg, were sonicated for 30 min in a 100 mL solution of deionized water. We weighed three portions of 0.2 mol/L AgNOThe resulting precipitated powder was washed several times with deionized water and ethanol, filtered, dried, weighed, and mixed with Ni powder to produce an Ag-graphene powder with a weight ratio to Ni powder of 85:15. A set of Ag/Ni powders without graphene was also prepared. The powders were mixed in a ball mill for 2 h and then pressurised at 800 MPa to produce a cylinder with a diameter of 10 mm. The experimental procedure is shown in We performed 50,000 electrical contact tests on the sample using the JF04D electrical contact material test system at a DC voltage of 24 V and a DC current of 15 A. Its welding force and arc energy were measured. We prepared two sets of samples by the same method under the same experimental conditions. Although the mean and variance of the parameters varied slightly, the trends were generally consistent with the results.The conductivity of the Ag-graphene/Ni composites was tested using a Sigma-Scope SMP10 metal conductivity tester. The Vickers hardness was obtained by pressing a diamond into the diamond shape of the sample surface and measuring the diagonal of its indentation. The results of the measurements are shown in The hardness and conductivity behaved differently depending on the amount of graphene added. The addition of small amounts of graphene improves the overall performance of the material, with the conductivity showing a tendency to increase and then decrease as the amount added increases. At a doping content of approximately 0.3 wt% (10 mg), the sample showed the best conductivity, with a result of 33.8 IACS%, a 12% increase in conductivity compared to the undoped sample. The conductivity of 33.8 %IACS is slightly higher than that of silver-nickel oxide at 28.7 %IACS, which was prepared using the same process by Tianfu G et al. . GraphenAs the graphene content increased, the hardness showed a gradual increase. At a doping content of 0.6 wt% (20 mg), the Ag-graphene/Ni material showed a maximum hardness of 118.48 Hv, an increase of 3.9% compared to the unaddressed Ag/Ni material. At a doping level of 0.3 wt% (10 mg), there is little change in hardness. The hardness is higher than the 102 Hv of AgNi15 prepared by h et al. . The upp3 were analyzed by XRD, as shown in The samples before and after the reaction of graphene with AgNOUsing a cylindrical material with a 10 mm diameter and 1 mm height pressed from nickel powder as a substrate, pure silver powder and Ag-graphene composite powder were selected to be placed on the substrate. In a tube furnace under a vacuum, the silver was heated above its melting point (942 °C); we heated it to 1050 °C and held it for 30 min to melt the pure silver powder and Ag-graphene composite powder onto the nickel block substrate. After the samples had cooled, a contact angle meter was used to compare the difference between the added and unadded graphene.The wetting angle is determined by the molecular interactions between the liquid and the solid. The smaller the contact angle, the greater the wettability. As the contact angle approaches 180 degrees, wettability decreases. Strong adhesion with weak cohesion produces very low contact angles and almost complete wetting. The electric contact material produces a certain melting precipitation effect under the high temperature of the electric arc. That is, at high temperatures Ni particles dissolve in the silver melt, and when the temperature drops and the arc is extinguished, Ni particles reprecipitate to exist in the Ag matrix. The repeated action of the arc, with Ni particles constantly dissolving and precipitating, will enhance the Ag and Ni bonding strength. When the contact angle is smaller, the adhesion between Ag and Ni increases at high temperatures, and Ag and Ni bond better, which is less likely to produce material spatter and reduce material loss. As shown in We used the electrical contact material test system, type JF04D, to test the samples. We set the protection voltage to ±40 V, the experimental current to 15 A DC, the voltage to 24 V DC, the distance between contacts to 2 mm and the contact pressure to 86 cN. We measured the arc energy and the welding force of the material. We set the number of experiments on the sample to 50,000.The lower the welding force, the better the resistance to fusion welding, and the less likely it is that the contacts will stick together when in contact under operating conditions. The welding force of the undoped graphene contact material (sample d) generally fluctuated considerably. This indicates that the undoped Ag/Ni contacts are relatively unstable. The contacts with a graphene doping of approximately 0.3 wt% (sample b) had the lowest welding force with an average value of approximately 49.49 cN. Compared to the non-graphene-doped contacts, the contacts with a doping content of 0.3 wt% (sample b) had an average reduction in welding force of approximately 8.04%.The lower variance of the welding force distribution indicates that the contacts are less prone to sudden changes in the working condition, the welding force curve is flatter, and the working condition is more stable. Of the four groups of samples, the contact with 0.15 wt% doping has the lowest variance and is more stable in operation, but has a higher welding force. The variance of the 0.3 wt% doped contacts was 18.7, slightly weaker than the 0.15 wt% doped contacts.The results show that at a graphene doping level of approximately 0.3 wt%, the melt resistance of the contact material is improved, the welding force is reduced by 8.04%, and the stability in the operating condition is improved. A small amount of graphene doping can effectively reduce the welding force of silver-nickel contacts and improve the lifetime of silver-nickel contacts during operation.During the opening and closing of the contacts, an arc or other discharge phenomenon is generated between the contacts. The high temperature of the arc can cause the material on the surface of the contact to melt and splash, causing damage to the contact surface and affecting the performance of the contact. The results of the change in combustion arc energy are shown in Among the four sets of results, the graphene-doped samples a, b, and c had significantly lower ignition arc energy than the non-graphene-doped sample d. The curve of the ignition arc energy of the non-graphene-doped contacts was flat and stable, but the ignition arc energy was higher. The lowest arc energy was obtained for the graphene doping of about 0.3 wt% (sample b) with an average value of about 176.77 mJ. The burning arc energy is lower than the 200 mJ of AgNi15 prepared by Chen-Li et al. . The ave(1)The addition of graphene resulted in an increase in conductivity, with a 12% increase in conductivity at 0.3%wt. The hardness of the samples also tended to increase with a higher content.(2)The addition of graphene can make the contact angle of the Ag/Ni contact smaller and enhance the wettability between silver and nickel. Under the action of a high-temperature arc, the Ag/Ni contacts will reduce the spattering effect.(3)The addition of graphene reduces the fusion welding force and reduces the occurrence of fusion welding in the contacts, which can improve the life of the contacts. A graphene addition of 0.3%wt reduces the melt welding force by 8.04%, which is the best result.(4)The lowest arc energy was achieved at a graphene doping level of approximately 0.3 wt%, with an average value of approximately 176.77 mJ. Compared to the contacts without graphene doping, the average arc energy decreased by 13.06%, reducing the arc burn on the contacts.In this paper, we used a chemical in situ method to prepare Ag-graphene composites using ascorbic acid as a non-toxic reducing agent. The Ag-graphene composites were then mixed with nickel powder to prepare a circular block material with a mass ratio of 85:15. After we performed the pressing, sintering, repressing, and resintering processes on the samples, we compared the performance of the contact material with the addition of different mass ratios of graphene. The results show that the trace addition of graphene can improve the overall performance of Ag/Ni contacts and can promote the application of graphene in electrical contact materials. The specific findings are as follows: