Sustainable wastewater purification with crab shell-derived biochar: Advanced machine learning modeling & experimental analysis.

Detoxifying ecologically persistent dyes is vital for environmental and human well-being. Herein, crabshell waste is transformed into porous carbon (CB900) through pyrolysis, achieving a remarkable removal rate of 90.5% (CR-RR) and adsorption capacity (∼256.36 mg g-1, qCR). Employing XGBoost modeling, with a robust R2 âˆ¼0.996, proved its superiority over others in predicting CR adsorption. PSO-XGB optimization led to an optimal configuration: 0.051 g adsorbent, 460.56 mg L-1 CR concentration, pH 3.16, and a 94.01 min contact time, resulting in 68.39% CR-RR and 822.15 mg g-1 qCR, simultaneously; sensitivity analysis unveiled the pivotal role of pH and adsorbent dose. CB900 exhibited physical, spontaneous, endothermic following both Langmuir and Freundlich isotherms. Remarkably, CB900 effectively eliminated various contaminants, including chromium and sulfasalazine antibiotic. Pilot-scale CB900 production cost via pyrolysis was $8.5/kg, a fraction of commercial powdered activated carbon, underscoring its economic viability and potential as a sustainable solution for the elimination of toxic contaminants from aqueous environments.

Multiple design and modelling approaches for the optimisation of carbon felt electro-Fenton treatment of dye laden wastewater.

This study utilizes artificial intelligence and statistical modelling to optimize the operating parameters of a carbon-based electro-Fenton process for purifying model dye (RB19)-contaminated wastewater. Multilevel experimental Box-Behnken and uniform deisgns (BBD, UD) with four variables were analysed using polynomial regression analysis (PRA) and artificial neural networks (ANN), while the process optimisation was done using desirability function. For the given testing range but different design matrices and runs, both designs predicted a maximum RB19 removal (RB19-RR) of 90 ± 2.1% at lowest energy consumption (EC) of 0.44 ± 2.5 Wh, when voltage, Na2SO4, FeSO4, and time were maintained as follows: 4-5.3 V, 7-11 mM, 0.4-0.6 mM, and 35-40 min, respectively. All the design-model combinations portrayed the similar senitivity analyses, revealing that RB19 degradation and EC are primarily influenced by electrolysis time and voltage. The performance assessment demonstrated that all the design-model combinations also excellently predicted for unseen conditions as the maximum root mean squared error (RMSE) value for RB19-RR was 4.07, while it was 0.072 for EC, however, BBD-ANN performance proved to be slightly better than others. Having ∼57% less experimentation, UD based models managed to accurately predict the results for unseen conditions as the statistical errors were quite insignificant, even in some cases, RMSE found to be less for UD compared to BBD, elucidating the potential of uniform design as an alternative of conventional factorial designs. Nevertheless, the prediction accuracy is also dependent on modelling approach, as in some cases ANN failed to predict the response precisely specially when dealing with small data. Furthermore, techno-economic evaluation results spell out the efficacy of carbon felt based enhanced electro-Fenton process as promising environmental remediation technology and highlight its practical implication from view of operational cost.

Entropy-based grid approach for handling outliers: a case study to environmental monitoring data.

Grid-based approaches render an efficient framework for data clustering in the presence of incomplete, inexplicit, and uncertain data. This paper proposes an entropy-based grid approach (EGO) for outlier detection in clustered data. The given hard clusters obtained from a hard clustering algorithm, EGO uses entropy on the dataset as a whole or on an individual cluster to detect outliers. EGO works in two steps: explicit outlier detection and implicit outlier detection. Explicit outlier detection is concerned with those data points that are isolated in the grid cells. They are either far from the dense region or maybe a nearby isolated data point and therefore declared as an explicit outlier. Implicit outlier detection is associated with the detection of outliers that are perplexedly deviated from the normal pattern. The determination of such outliers is achieved using entropy change of the dataset or a specific cluster for each deviation. The elbow based on the trade-off between entropy and object geometries optimizes the outlier detection process. Experimental results on CHAMELEON datasets and other similar datasets suggested that the proposed approach(es) detect the outliers more precisely and extend the capability of outliers detection to an additional 4.5% to 8.6%. Moreover, the resultant clusters became more precise and compact when the entropy-based gridding approach is applied on top of hard clustering algorithms. The performance of the proposed algorithms is compared with well-known outlier detection algorithms, including DBSCAN, HDBSCAN, RE3WC, LOF, LoOP, ABOD, CBLOF and HBOS. Finally, a case study for detecting outliers in environmental data has been carried out using the proposed approach and results are generated on our synthetically prepared datasets. The performance shows that the proposed approach may be an industrial-oriented solution to outlier detection in environmental monitoring data.

Design and implementation of real-time object detection system based on single-shoot detector and OpenCV.

Computer vision (CV) and human-computer interaction (HCI) are essential in many technological fields. Researchers in CV are particularly interested in real-time object detection techniques, which have a wide range of applications, including inspection systems. In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector (SSD) algorithm and deep learning techniques with pre-trained models. The system can detect static and moving objects in real-time and recognize the object's class. The primary goals of this research were to investigate and develop a real-time object detection system that employs deep learning and neural systems for real-time object detection and recognition. In addition, we evaluated the free available, pre-trained models with the SSD algorithm on various types of datasets to determine which models have high accuracy and speed when detecting an object. Moreover, the system is required to be operational on reasonable equipment. We tried and evaluated several deep learning structures and techniques during the coding procedure and developed and proposed a highly accurate and efficient object detection system. This system utilizes freely available datasets such as MS Common Objects in Context (COCO), PASCAL VOC, and Kitti. We evaluated our system's accuracy using various metrics such as precision and recall. The proposed system achieved a high accuracy of 97% while detecting and recognizing real-time objects.

End-to-End Deep Convolutional Recurrent Models for Noise Robust Waveform Speech Enhancement.

Because of their simple design structure, end-to-end deep learning (E2E-DL) models have gained a lot of attention for speech enhancement. A number of DL models have achieved excellent results in eliminating the background noise and enhancing the quality as well as the intelligibility of noisy speech. Designing resource-efficient and compact models during real-time processing is still a key challenge. In order to enhance the accomplishment of E2E models, the sequential and local characteristics of speech signal should be efficiently taken into consideration while modeling. In this paper, we present resource-efficient and compact neural models for end-to-end noise-robust waveform-based speech enhancement. Combining the Convolutional Encode-Decoder (CED) and Recurrent Neural Networks (RNNs) in the Convolutional Recurrent Network (CRN) framework, we have aimed at different speech enhancement systems. Different noise types and speakers are used to train and test the proposed models. With LibriSpeech and the DEMAND dataset, the experiments show that the proposed models lead to improved quality and intelligibility with fewer trainable parameters, notably reduced model complexity, and inference time than existing recurrent and convolutional models. The quality and intelligibility are improved by 31.61% and 17.18% over the noisy speech. We further performed cross corpus analysis to demonstrate the generalization of the proposed E2E SE models across different speech datasets.

An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health.

E-health has grown into a billion-dollar industry in the last decade. Its device's high throughput makes it an obvious target for cyberattacks, and these environments desperately need protection. In this scientific study, we presented an artificial intelligence (AI)-driven software-defined networking (SDN)-enabled intrusion detection system (IDS) to address increasing cyber threats in the E-health and internet of medical things (IoMT) environments. AI's success in various fields, including big data and intrusion detection systems, has prompted us to develop a flexible and cost-effective approach to protect such critical environments from cyberattacks. We present a hybrid model consisting of long short-term memory (LSTM) and gated recurrent unit (GRU). The proposed model was thoroughly evaluated using the publicly available CICDDoS2019 dataset and conventional evaluation measures. Furthermore, for proper validation, the proposed framework is compared with relevant classifiers, such as cu-GRU+ DNN and cu-BLSTM. We have further compared the proposed model with existing literature to prove its efficacy. Lastly, 10-fold cross-validation is also used to verify that our results are unbiased. The proposed approach has bypassed the current literature with extraordinary performance ramifications such as 99.01% accuracy, 99.04% precision, 98.80 percent recall, and 99.12% F1-score.

Cuprous Oxide Nanoparticles: Synthesis, Characterization, and Their Application for Enhancing the Humidity-Sensing Properties of Poly(dioctylfluorene).

In this paper, we report on the synthesis-via the wet chemical precipitation route method-and thin film characteristics of inorganic semiconductor, cuprous oxide (Cu2O) nanoparticles, for their potential application in enhancing the humidity-sensing properties of semiconducting polymer poly(9,9-dioctylfluorene) (F8). For morphological analysis of the synthesized Cu2O nanoparticles, transmission electron microscope (TEM) and scanning electron microscope (SEM) micrographs are studied to investigate the texture, distribution, shape, and sizes of Cu2O crystallites. The TEM image of the Cu2O nanoparticles exhibits somewhat non-uniform distribution with almost uniform shape and size having an average particle size of ≈24 ± 2 nm. Fourier transformed infrared (FTIR) and X-ray diffraction (XRD) spectra are studied to validate the formation of Cu2O nanoparticles. Additionally, atomic force microscopy (AFM) is performed to analyze the surface morphology of polymer-inorganic (F8-Cu2O) nanocomposites thin film to see the grain sizes, mosaics, and average surface roughness. In order to study the enhancement in sensing properties of F8, a hybrid organic-inorganic (F8-Cu2O) surface-type humidity sensor Ag/F8-Cu2O/Ag is fabricated by employing F8 polymer as an active matrix layer and Cu2O nanoparticles as a dopant. The Ag/F8-Cu2O/Ag device is prepared by spin coating a 10:1 wt% solution of F8-Cu2O nanocomposite on pre-patterned silver (Ag) electrodes on glass. The inter-electrode gap (≈5 µm) between Ag is developed by photolithography. To study humidity sensing, the Ag/F8-Cu2O/Ag device is characterized by measuring its capacitance (C) as a function of relative humidity (%RH) at two different frequencies (120 Hz and 1 kHz). The device exhibits a broad humidity sensing range (27-86%RH) with shorter response time and recovery time, i.e., 9 s and 8 s, respectively. The present results show significant enhancement in the humidity-sensing properties as compared to our previously reported results of Ag/F8/Ag sensor wherein the humidity sensing range was 45-78%RH with 15 s and 7 s response and recovery times, respectively. The improvement in the humidity-sensing properties is attributed to the potential use of Cu2O nanoparticles, which change the hydrophobicity, surface to volume ratio of Cu2O nanoparticles, as well as modification in electron polarizability and polarity of the F8 matrix layer.

Multi-object optimization of Navy-blue anodic oxidation via response surface models assisted with statistical and machine learning techniques.

This study aims to model, analyze, and compare the electrochemical removal of Navy-blue dye (NB, %) and subsequent energy consumption (EC, Wh) using the integrated response surface modelling and optimization approaches. The Box-Behnken experimental design was exercised using current density, electrolyte concentration, pH and oxidation time as inputs, while NB removal and EC were recorded as responses for the implementation and analysis of multiple linear regression, support vector regression and artificial neural network models. The dual-response optimization using genetic algorithm generated multi-Pareto solutions for maximized NB removal at minimum energy cost, which were further ranked by employing the desirability function approach. The optimal parametric solution having total desirability of 0.804 is found when pH, current density, Na2SO4 concentration and electrolysis time were 6.4, 11.89 mA cm-2, 0.055 M and 21.5 min, respectively. At these conditions, NB degradation and EC were 83.23% and 3.64 Wh, respectively. Sensitivity analyses revealed the influential patterns of variables on simultaneous optimization of NB removal and EC to be current density followed by treatment time and finally supporting electrolyte concentration. Statistical metrics of modeling and validation confirmed the accuracy of artificial neural network model followed by support vector regression and multiple linear regression anlaysis. The results revealed that statistical and computational modeling is an effective approach for the optimization of process variables of an electrochemical degradation process.

Therapeutic effects of chitosan-embedded vitamin C, E nanoparticles against cisplatin-induced gametogenic and androgenic toxicity in adult male rats.

Cisplatin, an anticancer drug used in treating various types of cancers, can cause reproductive toxicities during chemotherapy. Keeping this in view, the present study was designed to investigate the possible protective effects of normal vitamin C and E and vitamin C and E nanoparticles (embedded in chitosan) against cisplatin-induced reproductive toxicities. Vitamins C, E, and their nanoparticles in this regard proved to be an effective therapy. The work aimed to treat cisplatin-induced reproductive toxicities through vitamin C and E and their nanoparticles. Cisplatin exposure caused significant reduction in the weight, testosterone level, and changed lipid profile. Similarly, cisplatin induced significant widespread testicular atrophy and testicular lesions as evidenced by the gaps in the epithelium and loss of differentiating germ cells. Vitamin C and E and their nanoparticles rescued the weight, testosterone level, and testicular disturbances, which is associated with improved histological view of testicular tissues. The current study highlights evidence that designing a medication of vitamin C and E nanoparticles is useful in mitigating cisplatin-induced reproductive toxicity in cancerous male patients underlying chemotherapy.

SIRT1 Expression and Regulation in the Primate Testis.

The epigenetic mechanisms controlling germ cell development and differentiation are still not well understood. Sirtuin-1 (SIRT1) is a nicotinamide adenosine dinucleotide (NAD)-dependent histone deacetylase and belongs to the sirtuin family of deacetylases. It catalyzes the removal of acetyl groups from a number of protein substrates. Some studies reported a role of SIRT1 in the central and peripheral regulation of reproduction in various non-primate species. However, testicular SIRT1 expression and its possible role in the testis have not been analyzed in primates. Here, we document expression of SIRT1 in testes of different primates and some non-primate species. SIRT1 is expressed mainly in the cells of seminiferous tubules, particularly in germ cells. The majority of SIRT1-positive germ cells were in the meiotic and postmeiotic phase of differentiation. However, SIRT1 expression was also observed in selected premeiotic germ cells, i.e., spermatogonia. SIRT1 co-localized in spermatogonia with irisin, an endocrine factor specifically expressed in primate spermatogonia. In marmoset testicular explant cultures, SIRT1 transcript levels are upregulated by the addition of irisin as compared to untreated controls explants. Rhesus macaques are seasonal breeders with high testicular activity in winter and low testicular activity in summer. Of note, SIRT1 mRNA and SIRT1 protein expression are changed between nonbreeding (low spermatogenesis) and breeding (high spermatogenesis) season. Our data suggest that SIRT1 is a relevant factor for the regulation of spermatogenesis in primates. Further mechanistic studies are required to better understand the role of SIRT1 during spermatogenesis.

RF9 Rescues Cortisol-Induced Repression of Testosterone Levels in Adult Male Macaques.

Cortisol inhibits hypothalamic-pituitary-gonadal (HPG) axis whereas RF9, a potent agonist of kisspeptin receptor (GPR54) activates HPG-axis during fasting-induced stress and under normal physiological conditions. However, the effect of RF9 on the cortisol-induced repressed HPG-axis is not studied yet. This study investigated whether exogenous cortisol-induced repression of the HPG-axis can be rescued by RF9. Six intact adult male rhesus monkeys (Macaca mulatta) habituated to chair-restraint were administered hydrocortisone sodium succinate at a rate of 20 mg/kg of body weight (BW) per day for 12 days. Single blood sample was taken by venipuncture from each animal on alternate days for hormones analyses. On experimental day 12, hydrocortisone treated monkeys received a single intravenous bolus of RF9 (n = 3) and vehicle (n = 3). The animals were bled for a period of 4 h at 60 min intervals from an indwelling cannula in the saphenous vein. RF9 was administered intravenously at the dose of 0.1 mg/kg BW immediately after taking 0 min sample. Plasma cortisol and testosterone concentrations were measured by using specific enzyme immunoassays. Hydrocortisone treatment increased plasma cortisol levels (P ≤ 0.0001) and decreased plasma testosterone (P ≤ 0.0127) levels. Interestingly, compared to vehicle, RF9 treatment significantly increased plasma testosterone levels at 120 min (P ≤ 0.0037), 180 min (P ≤ 0.0016), and 240 min (P ≤ 0.0001) intervals in the hydrocortisone treated monkeys. From these results, we concluded that RF9 administration relieves the suppressed HPG-axis in term of plasma testosterone levels in the cortisol treated monkeys.

Amino Anthraquinone: Synthesis, Characterization, and Its Application as an Active Material in Environmental Sensors.

This work reports synthesis, thin film characterizations, and study of an organic semiconductor 2-aminoanthraquinone (AAq) for humidity and temperature sensing applications. The morphological and phase studies of AAq thin films are carried out by scanning electron microscope (SEM), atomic force microscope (AFM), and X-ray diffraction (XRD) analysis. To study the sensing properties of AAq, a surface type Au/AAq/Au sensor is fabricated by thermally depositing a 60 nm layer of AAq at a pressure of ~10-5 mbar on a pre-patterned gold (Au) electrodes with inter-electrode gap of 45 µm. To measure sensing capability of the Au/AAq/Au device, the variations in its capacitance and resistance are studied as a function of humidity and temperature. The Au/AAq/Au device measures and exhibits a linear change in capacitance and resistance when relative humidity (%RH) and temperature are varied. The AAq is a hydrophobic material which makes it one of the best candidates to be used as an active material in humidity sensors; on the other hand, its high melting point (575 K) is another appealing property that enables it for its potential applications in temperature sensors.

Irisin is expressed by undifferentiated spermatogonia and modulates gene expression in organotypic primate testis cultures.

The molecular mechanisms regulating undifferentiated spermatogonial cell proliferation and differentiation are still not fully understood. Irisin is an exercise-induced hormone, which is a cleaved and secreted fragment of the fibronectin type III repeat containing 5 (FNDC5) transmembrane protein. Recent studies have demonstrated the role of irisin in cell proliferation and differentiation in various tissues. However, testicular irisin expression and its potential action have not been analyzed. Here, we demonstrate expression of irisin in undifferentiated spermatogonia of primates and in the tree shrew, a bridging species between primates and insectivores. Rhesus monkeys are seasonal breeders with annual phases of high and low testicular activity and germ cell proliferation. Interestingly, expression of both FNDC5 mRNA and irisin is altered between breeding (high spermatogenesis) and nonbreeding seasons (low spermatogenesis). Organotypic testis culture in the presence of irisin increased the expression levels of the Sertoli cell (GDNF) and spermatogonial transcripts Kruppel-like factor 4 (KLF4), Inhibitor of differentiation 4 (ID4), Cluster of differentiation 117 (cKIT), and SALL4, compared to untreated controls, while irisin suppressed its own FNDC5 mRNA. Our data suggest that irisin is a novel endocrine factor involved in the regulation of spermatogonial activities in the testes of primates.

In-silico Analyses of Disease Causing Mutations in SLURP1 Gene.

The SLURP1 (secreted LY6/urokinase type plasminogen activator receptor related protein-1) belongs to the gene family of urokinase, a type of plasminogen activator receptor (uPAR). Mutations in the SLURP1 have been reported to cause serious genetic problems of skin, Mal De Meleda, and malignancies. With the advancement of computational tools, it became possible to predict the potential impact of gene variants on the structure and function of protein. Therefore, in present study, we aimed to perform in-silico analyses of the disease causing SLURP1 mutations using online tools. In-total, 21 variants occurring in coding and non-coding regions of SLURP1 were found from public databases. In curated data, we have found 57.14% (12/21) missense, 23.81% (5/21) splice site, 9.52% (2/21) nonsense, 4.76% (1/21) deletion, and 4.76% (1/21) frameshift mutations. Moreover, heterogeneity in genotypes and phenotypes, along with 7 hotspot points in SLURP1 has been noted. In-silico analyses of the subjected variants have depicted a range of pathogenicity by combinatorial predictions of different tools from being lowly to highly pathogenic. Thus, the present study paves a platform to link computational analyses of mutations for important regulatory genes that can be undertaken for their phenotypes and their correlation with the disease status in case control studies.

DDB1 Regulates Sertoli Cell Proliferation and Testis Cord Remodeling by TGFß Pathway.

Testis cords are the embryonic precursors of the seminiferous tubules. Development of testis cords is a key event during embryonic testicular morphogenesis and is regulated by multiple signaling molecules produced by Sertoli cells. However, the exact nature and the cascade of molecular events underlying testis cord development remain to be uncovered. In the current study, we explored the role of DNA damage binding protein 1 (DDB1) in Sertoli cells during mouse testis cord development. The genetic ablation of Ddb1 specifically in Sertoli cells resulted in the compromised Sertoli cell proliferation and disruption of testis cord remodeling in neonatal mice. This testicular dysgenesis persisted through adulthood, resulting in smaller testis and low sperm production. Mechanistically, we observed that the DDB1 degradation can stabilize SET domain-containing lysine methyltransferase 8 (SET8), which subsequently decreases the phosphorylation of SMAD2, an essential intracellular component of transforming growth factor beta (TGFß) signaling. Taken together, our results suggest an essential role of Ddb1 in Sertoli cell proliferation and normal remodeling of testis cords via TGFß pathway. To our knowledge, this is the first upstream regulators of TGFß pathway in Sertoli cells, and therefore it furthers our understanding of testis cord development.

The testis-specifically expressed Dpep3 is not essential for male fertility in mice.

More than 2300 genes have been reported to be involved in spermatogenesis but the functional roles of most genes in male fertility remain to be elucidated. In this study, we explored the function of dipeptidase 3 (Dpep3), a gene predicted to be testis-specific, in male fertility of mice. We showed that Dpep3 is evolutionarily conserved in human and mouse along with other eutherians. Its mRNA was exclusively detected in testicular tissue and expressed in testes from 7 days postpartum. To further explore its role in male fertility, we generated Dpep3 knockout mice (Dpep3-/-) using the CRISPR/Cas9 technology and found that the male Dpep3-/- mice are fertile despite a significant reduction in sperm count. Histology of testis and progression of meiotic prophase I showed no obvious difference between wild-type and Dpep3-/- mice. All these findings indicate that Dpep3 is not essential for male fertility in mice. These findings will help other researchers to avoid research duplication, save their time and resources to focus on the genes that are indispensable for male fertility.

Whole Exome Sequencing Revealed a Novel Nonsense Variant in the GNRHR Gene Causing Normosmic Hypogonadotropic Hypogonadism in a Pakistani Family.

BACKGROUND: Congenital hypogonadotropic hypogonadism (CHH) is a heterogeneous disorder characterized by delayed or loss of puberty and infertility due to functional deficiency in the hypothalamic gonadotropin-releasing hormone (GnRH). CHH can be classified into 2 subtypes on the basis of olfaction: Kallmann syndrome and normosmic CHH (nCHH). The spectrum of genetic variants causing CHH is continually expanding. Here, we recruited a consanguineous Pakistani family having 2 male and 2 female infertile patients diagnosed with idiopathic nCHH. AIMS: The aim of this study was to investigate the genetic cause of nCHH in the family. METHODS: Clinical and physical analyses were performed for the patients. Genetic analysis was carried out using whole exome and Sanger sequencing. RESULTS: Clinical and physical investigations confirmed low levels of gonadotropins and failure of secondary sexual development in the patients. Genetic analysis identified a novel nonsense mutation (chr4: g.68619942G>A, c.112C>T, p.Arg38*) in the gonadotropin-releasing hormone receptor gene (GNRHR) recessively co-segregating with nCHH in this family. All the patients are homozygous and their parents are heterozygous carriers, while normal siblings are heterozygous carriers or wild-type for this mutation, indicating that the identified mutation is pathogenic for nCHH in the family. CONCLUSION: We report the first homozygous nonsense mutation in the GNRHR gene (chr4: g. 68619942G>A, c.112C>T, p. Arg38*) that is associated with familial nCHH. Hence, our study displayed a good correlation of the genotype and phenotype of nCHH patients.

Irisin in the primate hypothalamus and its effect on GnRH in vitro.

Irisin, encoded by the FNDC5 gene, is a recently discovered endocrine factor mainly secreted as a myokine and adipokine. However, irisin/FNDC5 expression has also been reported in different other organs including components of the reproductive axis. Yet, there is the scarcity of data on FNDC5/irisin expression, regulation and its reproductive effects, particularly in primates. Here, we report the expression of FNDC5/irisin, along with PGC1A (peroxisome proliferator-activated receptor gamma coactivator 1-alpha) and ERRA (estrogen-related receptor alpha), in components of the reproductive axis of marmoset monkeys. Hypothalamic FNDC5 and ERRA transcript levels are developmentally regulated in both male and female. We further uncovered sex-specific differences in FNDC5, ERRA and PGC1A expression in muscle and the reproductive axis. Moreover, irisin and ERRα co-localize in the marmoset hypothalamus. Additionally, in the arcuate nucleus of rhesus monkeys, the number of irisin+ cells was significantly increased in short-term fasted monkeys as compared to ad libitum-fed monkeys. More importantly, we observed putative interaction of irisin-immunoreactive fibers and few GnRH-immunoreactive cell bodies in the mediobasal hypothalamus of the rhesus monkeys. Functionally, we noted a stimulatory effect of irisin on GnRH synthesis and release in mouse hypothalamic neuronal GT1-7 cells. In summary, our findings show that FNDC5 and irisin are developmentally, metabolic-status dependently and sex-specifically expressed in the primate hypothalamic-pituitary-gonadal axis and exert a stimulatory effect on GnRH expression and release in mouse hypothalamic cells. Further studies are required to confirm the reproductive effects of irisin in vivo and to illuminate the mechanisms of its regulation.

Changes in the Responsiveness of the Hypothalamic-Pituitary-Gonadal Axis to Kisspeptin-10 Administration during Pubertal Transition in Boys.

In human, no studies are available regarding changes in kisspeptin1 receptor (KISS1R) sensitivity during pubertal transition. In this study, healthy boys were classified into 5 Tanner stages of puberty (n = 5/stage). Human kisspeptin-10 was administered to boys at each Tanner stage and to adult men (n = 5) as an IV bolus for comparison. Serial blood samples were collected for 30 min pre- and 120 min post-kisspeptin injection periods at 30 min interval for measuring plasma LH and testosterone levels. There was insignificant effect of kisspeptin on LH and testosterone levels in boys of Tanner stages I-III. At Tanner stage IV, the effect of kisspeptin on plasma LH was insignificant. However, a paired t-test on a log-transformed data showed a significant (P < 0.05) increase in mean peak post-kisspeptin testosterone level. In Tanner stage V, a significant (P < 0.05) increase was observed in mean post-kisspeptin peak LH level as compared to the mean basal LH value. Post-kisspeptin plasma testosterone levels were also significantly (P < 0.05) increased as compared to the pre-kisspeptin level in Tanner stage V. Our data suggest that sensitivity of KISS1R on GnRH neurons with reference to LH stimulation in boys develops during the later part of puberty reaching to adult level at Tanner stage V. This trial is registered with WHO International Clinical Trial Registration ID NCT03286517.

Metabolic Impact on the Hypothalamic Kisspeptin-Kiss1r Signaling Pathway.

A large body of data has established the hypothalamic kisspeptin (KP) and its receptor, KISS1R, as major players in the activation of the neuroendocrine reproductive axis at the time of puberty and maintenance of reproductive capacity in the adult. Due to its strategic location, this ligand-receptor pair acts as an integrator of cues from gonadal steroids as well as of circadian and seasonal variation-related information on the reproductive axis. Besides these cues, the activity of the hypothalamic KP signaling is very sensitive to the current metabolic status of the body. In conditions of energy imbalance, either positive or negative, a number of alterations in the hypothalamic KP signaling pathway have been documented in different mammalian models including nonhuman primates and human. Deficiency of metabolic fuels during fasting causes a marked reduction of Kiss1 gene transcript levels in the hypothalamus and, hence, decreases the output of KP-containing neurons. Food intake or exogenous supply of metabolic cues, such as leptin, reverses metabolic insufficiency-related changes in the hypothalamic KP signaling. Likewise, alterations in Kiss1 expression have also been reported in other situations of energy imbalance like diabetes and obesity. Information related to the body's current metabolic status reaches to KP neurons both directly as well as indirectly via a complex network of other neurons. In this review article, we have provided an updated summary of the available literature on the regulation of the hypothalamic KP-Kiss1r signaling by metabolic cues. In particular, the potential mechanisms of metabolic impact on the hypothalamic KP-Kiss1r signaling, in light of available evidence, are discussed.