Cancer has become one of the common causes of mortality around the globe due to mutations in the genome which allows rapid growth of cells uncontrollably without repairing DNA errors. Cancers could arise due alterations in DNA repair mechanisms (errors in mismatch repair genes), activation of oncogenes and inactivation of tumor suppressor genes. Each cancer type is different and each individual has a unique genetic change which leads them to cancer. Studying genetic and epigenetic alterations in the genome leads to understanding the underlying features. CAR T therapy over other immunotherapies such as monoclonal antibodies, immune checkpoint inhibitors, cancer vaccines and adoptive cell therapies has been widely used to treat cancer in recent days and gene editing has now become one of the promising treatments for many genetic diseases. This tool allows scientists to change the genome by adding, removing or altering genetic material of an organism. Due to advance in genetics and novel molecular techniques such as CRISPR, TALEN these genes can be edited in such a way that their original function could be replaced which in turn improved the treatment possibilities and can be used against malignancies and even cure cancer in future along with CAR T cell therapy due to the specific recognition and attacking of tumor. Genetic disorders are not easy to cure like other diseases. Gene therapy has become the novel tool to treat and cure genetic diseases by improving the body’s ability to fight against diseases either by replacing the disease causing gene with a healthy gene, inactivating disease causing gene, or by introducing modified gene which could function normally. Gene therapy could be done using prokaryotic vectors, plasmid vectors, or other human gene editing tools. This review discusses the ability of gene therapy with immunotherapy specially with CAR T cells to treat hematological malignancies. With the promise of CRISPR as an effective editing tool and CAR T therapy as the latest effective immunotherapy technology, this combination can be used as a weapon to cure many malignancies .E. coli type II acquired immune system, non-repeating, palindromic sequences by  Cilta-cel for hemophagocytic lymohohistiocytosis/macrophage activation syndrome and CRS , 2022) upon use.The therapeutic efficacy of CAR T cell therapy is dependent upon several factors involving intrinsic and extrinsic T cell related mechanisms, limitations with CAR T cell manufacturing and poor CAR T cell expansion and persistence upon infusion. Combating cancer in a hostile, immunosuppressive tumor microenvironment and the associated toxicities of CAR T cell therapy are few of the major hurdles faced. Autologous CAR T therapy has been highly successful in treating hematopoietic malignancies. On the contrary, the therapeutic efficacy against solid tumors has shown to be less than modest due to the attributes of solid tumors. They are disorganized, cancerous cellular structures surrounded by stromal cells of the TME and vasculature that nourishes them and are connected to an immune filtrate consisting of both innate and adaptive immune cells. Unlike B cell malignancies, solid tumors either lack tumor specific antigens or are composed of tumor associated antigens and antigens expressed in healthy cells. This heterogeneous expression makes inefficient trafficking and homing of CAR T cells to tumor site and on target, off tumor toxicity all the more challenging . TherefoEnhancing CAR T cell effector function and its persistence while mitigating T cell exhaustion caused due to chronic antigen stimulation and an immunosuppressive tumor microenvironment subsequently resulting in CAR T cell dysfunction, is a challenge. T cell dysfunction defined by the diminished proliferative capacity and antitumor activity, causes disease relapse within a few years in a majority of patients receiving CAR T cell therapy , 93. ThePD1 is a key inhibitory receptor significantly expressed on exhausted CD8 T cells, mediating immune escape in tumor cells by limiting the capabilities of TCR and CD28, upon interactions with its ligands PD-L1 or PD-L2 on T cells . In geneSystemic administration of checkpoint blockade has reportedly generated immune related adverse events in patients and therefore to circumvent this issue, Rafiq et al.  engineerAlso, with respect to solid tumors, Hu et al.  reportedTo minimize immunogenicity in allogeneic CAR T cell therapy, Liu et al.  knocked Another immunosuppressive component is the Fas receptor alternatively known as CD95 and APO-1, is a cell surface protein of the tumor necrosis factor (TNF) receptor family. Interactions between Fas and Fas ligand (FasL) trigger apoptosis in exhausted T cells via a mechanism known as activation induced cell death (AICD). Up-regulation of Fas receptors has been reported in CD8 T cells exposed to prolonged antigen stimulation . CRISPR Less research has been carried out in CAR T therapy with respect to CTLA-4, a cell surface receptor dampening T cell activation and generation of effector T cells. Anti-CTLA4 checkpoint blockade immunotherapy is used in the clinical management of malignant melanomas with the aim of suppressing T cell inhibitory activity. Lin et al.  attempteLymphocyte activation gene-3 (LAG-3), another hallmark of T cell exhaustion is generally expressed in activated CD4 and CD8 T cells, regulatory T cells, B cells and natural killer (NK) cells, and upregulated upon persistent antigen stimulation caused in cancer and chronic infections. Recently, LAG-3 is under clinical investigation as a candidate in immunotherapy against cancer . CRISPR Ciralo et al.  generate2 generating DAG and inositol triphosphate. DAG results in the downregulation of downstream signaling pathways including the RasGRP1/Ras/ERK and PKCθ/IKK/NF-κB pathways. On the other hand, PA is known to interact with mammalian targets of rapamycin (mTOR), SHP-1, RasGAP, Sos, PI5Kα, and p47(phox) [In addition to the immune checkpoint molecules, other T cell inhibitory molecules such as diacylglycerol kinase (DGK) are emerging as potential candidates in cancer immunotherapy. However, there is limited research with respect to CAR T cell therapy. DGK is an enzyme that acts as a critical regulator of diacylglycerol (DAG) and phosphatidic acid (PA) levels by phosphorylating DAG to PA, which is part of the phosphatidylinositol (PI) cycle and are two key lipids acting as second messengers in immune cell signaling in T cells . DGK act47(phox) .DGK attenuates DAG levels, restricting the function of the TCR signaling cascade and ultimately serving as a braking mechanism in the immune synapse , 112. DKAlthough transforming growth factor-β (TGF-β) is a tumor suppressor in pre-malignant cells, inhibiting cancer cell proliferation and inducing apoptosis, and over the course of tumor progression, TGF-β transforms to a multipotent cytokine responsible for creating an immunosuppressive tumor microenvironment via the and reprogramming cellular metabolism and the modulation of the proliferation and differentiation of immune cells and the matrix composition –116. TGFTGF-β secreted by CD4(+) T cells has been reported to mediate tumor immune escape and immunosuppression, while promoting the differentiation of CD4(+) T cells to FOXP3 dependent regulatory T cells leading to the execution of immune tolerance –119. MorAs a result, there is ongoing research on targeting TGF-β and TGF-β receptors to enhance antitumor efficacy of CAR T cell therapy against solid tumors , 88, 89.2AR acts as a critical regulator of CD8+ T cells in the TME [Adenosine is another potent immunosuppressive agent found in the tumor milieu known to interact with four types of receptors: A1R, A2AR, A2BR, and A3R, out of which A2AR and A2BR contribute to immunosuppressive effects through adenosine . More sp the TME . Adenosi the TME . In vitr the TME .CRISPR gene editing technology has also been utilized to knockdown A2AR in CAR T cells. Li et al.  knocked Protein Tyrosine Phosphatase N2 (PTPN2) hinders cytokine signaling which is a critical regulator of T cell function, homeostasis and differentiation by attenuating signal transducer and activator of transcription 5–1 (STAT-1), STAT-3 and STAT-5 . ConsistPAK4 is serine/threonin protein kinase enzyme which has been reported to be a critical regulator of mesenchymal related transcriptional activation in tumor ECs and thus reduces T cell adhesion due to consequent improved vessel permeability. CRISPR mediated PAK4 knockdown results in inhibited cell proliferation, migration and invasion and reduced monolayer permeability in human glioblastoma (GBM) derived tumor endothelial cells (EC) and leads to a normalization of the tumor vasculature and enhanced T cell infiltration. PAK4 deficiency improved CAR T immunotherapy in mouse GBM models .Disialoganglioside GD2 antigen, demonstrating restricted expression on normal tissues and increased expression levels in human cancers such as glioma, neuroblastoma and melanoma, has become an attractive and valuable target in CAR T cell therapy against solid tumors. Prapa et al.  reportedIKZF3 is a lymphocyte maturation driving transcription factor predominantly expressed in certain hematological malignancies and solid tumors, and its overexpression reportedly promotes metastasis in vivo . CRISPR The NR4A family of nuclear receptor transcription factors are associated with diminished T cell activity, in addition to being linked to the expression of inhibitory receptors such as PD-1 and TIM-3. Studies have found that the triple knockout of NR4A1, NR4A2 and NR4A3 transcription factors promoted tumor regression and survival of tumor murine models . FurtherThere are two types of toxicities associated with CART therapy that dampen their therapeutic efficacy. The most frequent toxicity is cytokine release syndrome (CRS) which is a systemic inflammatory response occurring due to the interplay between target tumor cells and the antigen expressing CART cells upon its infusion and migration to the tumor site . Upon anCRISPR gene editing platform can be utilized to tackle these obstacles in CART therapy. Sterner et al.  generateYi et al.  conducteNevertheless, the study done by Yi et al.  has to bAnother approach to control and reverse toxicity effects in the presence of autonomous uncontrolled T cell growth, is the use of inducible caspase 9, a suicide gene which effectively eliminates engineered CART cells when needed. Hoyos et al.  incorporPrior to application of CRISPR edited cells in a clinical setting, there are safety concerns that need to be addressed first. Cas9 activity, sgRNA design, delivery method and target site selection are several factors which determine the therapeutic efficacy and safety of the CRISPR gene editing platform. Among these, a main concern is the off target toxicity effect caused by unintended genetic cleavage and mutations at genomic sites related to the targeted sites, resulting in chromosomal rearrangements such as deletions and translocations, which potentially could be oncogenic depending on the genetic sequence affected . FurtherCancer has become one of the most difficult diseases to treat worldwide with a high fatality rate. Finding cures and treatment options are very important these days. In this review we discussed the upcoming treatment possibility for cancer, which is CAR T cell therapy with the help of CRISPR/Cas 9 system. CRISPR is a gene editing tool which uses recombinant T cells to treat cancer by interfering with immune cells. Different aspects of these cells can be targeted in cancer therapy such as knocking out endogenous genes, inhibitory receptors, and integration of specific genes. Among other gene editing tools, CRISPR shows immense possibilities to edit T cells either by adding, removing or altering genes to change its genome for good. Due to the fact that these cells target and attack only tumor cells major interference of chemo and radiotherapy which is healthy cell attacking can be avoided. With the usage of healthy donor cells can cause GVHD, which is one such obstacle of CAR T cells which could be overcome with the use of CRISPR. There are several FDA approved CAR T cell therapies which use gene editing tools such as CRISPR for the production process and these findings prove the fact that CRISPR can be used as a promising treatment option to treat blood cancer.Major safety concerns associated with CRISPR include off target toxicity, chromosomal breakage, limited efficiency of gRNA and concerns of delivery strategies. Furthermore, concerns regarding limited therapeutic efficacy of CAR T cell therapy include issues arising with the immunosuppressive tumor microenvironment, intricacy and expense associated with manufacturing autologous CAR T cell products and associated toxicity conditions (cytokine release syndrome and associated neurotoxicity). There are ongoing clinical trials of CRISPR modified CAR T cells as well as for solid tumors. Strategies such as whole exome and whole genome sequencing can be used to look out for any unwanted gene editing effects caused by CRISPR modified CAR T cell products.


Human Norwalk viruses (HuNoVs), the most common etiological agents of acute gastroenteritis, are genetically diverse RNA viruses that frequently cause mass food poisoning internationally. Although nucleic acid detection methods, such as reverse transcription–quantitative polymerase chain reaction (RT-qPCR), are the gold standard for the diagnosis of norovirus infection, alternative methods are needed for the specific and sensitive viral protein detection for rapid diagnosis and surveillance. In this study, we developed a robust and high-throughput targeted proteomic assay workflow to directly detect the VP1 major capsid protein of HuNoVs. A parallel reaction monitoring (PRM) assay using a high-resolution mass spectrometer was used to detect representative peptides derived from VP1 in six different HuNoV genotypes. An optimized protocol using synthesized heavy isotope-labeled peptides as internal standards was also used to simultaneously genotype and quantify the VP1 protein in human stool specimens. This method is expected to become a new tool for studying the molecular epidemiology of HuNoV and to shed new light on targeted proteomics in clinical practice. A. A4]. Am6 viral particles per gram of feces, and it requires a skilled operator and sophisticated setup for continuous implementation. Reverse transcription–quantitative polymerase chain reaction (RT-qPCR) is currently the most common technique for genotyping HuNoV in stool specimens, water, and food  lysine and  arginine  (H) were resuspended in 0.1% formic acid and 2% acetonitrile (ACN). All MS analyses were carried out using a Q-Exactive HF mass spectrometer (Thermo Fisher Scientific) coupled with an UltiMate 3000 high-performance liquid chromatography (HPLC) system (Thermo Fisher Scientific). MS data were acquired using either DDA or PRM.Desalted peptides (L) and the heavy isotope-labeled peptides synthesized with C-terminal [To identify peptides, DDA-MS data were analyzed using the SEQUEST HT search algorithm in Proteome Discoverer  against in silico translations from the VP1 nucleotide sequence database, allowing for methionine oxidation as a variable modification and cysteine carbamidomethylation as a fixed modification. Other parameters used for the search were as follows: Trypsin digestion with two missed cleavages permitted, 300–6000 Da, 6 minimum length of peptide, 40 maximum length of peptide, peptide mass tolerance for MS data ± 10 ppm, and fragment mass tolerance ± 0.05 Da. We used a 1% stringent false discovery rate as a cutoff value for peptide identification. The Skyline software   was usedm/z (the mass-to-charge ratio), no cleavage misses, and double- or triple-charged precursor ions. In addition, peptides with C-terminal ragged ends , peptides with proline at P2 (xxxxPK/R) or P3 (xxxxPxK/R), peptides with methionine, and peptides with N-terminal glutamine were excluded from the candidate target peptides for quantitative analysis by the PRM assay  from GII.3 as an example calibration curve. For VFGVASQR (2+), the LLOD was less than 0.1 fmol, the LLOQ was determined to be ~3 fmol, and linearity was excellent. Calibration curves for the other peptides are shown in To determine the lower limit of detection (LLOD) and the lower limit of quantification (LLOQ) in the PRM assay, reverse calibration curves were created by spiking heavy isotope-labeled peptides onto peptides derived from HeLa cell lysate and seven genotypes of recombinant HuNoV VP1 proteins. The linearity range of the calibration curve was defined as the range in which the coefficient of variation (CV) of the concentration of the recombinant VP1 protein (light peptide) was within 25% . Figure Human stool specimens are noninvasive and readily accessible samples rich in viruses in patients with infectious diseases. Therefore, to evaluate the quality of the PRM assays for detecting VP1 proteins, we performed targeted proteome analysis using stool specimens from patients with acute gastroenteritis infected with HuNoV. In this study, to reduce the host/microbial proteins ratio, we used PBS suspended matter from stool specimens for MS analysis A. As a rThe development of rapid and accurate detection techniques will help prevent the spread of viruses and initiate optimal therapy. Innovations in nucleic acid analysis technology, such as RT-qPCR, and the development of methods based on immunological applications, such as ELISA, have profoundly changed viral diagnosis ,11,12,20For most MS-based analyses, the typical dynamic range of detection is four to six orders of magnitude from high to low concentrations . TherefoThis study has limitations in showing that our PRM assay can be used as a routine diagnostic test for NoVs in acute gastroenteritis. One of these limitations is a lack of validation using multiple clinical samples of virus–positive and healthy individuals. Further studies with larger patient sample numbers as compared with healthy control subjects are needed to assess the quality of the PRM assays for detecting virus proteins. Further optimization of protein preparation methods from stool specimens is also needed to improve the detection sensitivity and reduce the processing time. In addition, this diagnostic method requires a highly sensitive and well-maintained mass spectrometer that can handle extremely low amounts of viral protein expression.In this study, we constructed a HuNoV detection system utilizing a PRM assay in conjunction with a high-resolution mass spectrometer. The PRM assay could identify genotypic HuNoV because it could detect unique target peptides for VP1 in some genotypes. Further technological developments are required before this technique can be used to comprehensively diagnose multiple viral infections and improve therapeutic algorithms for acute gastroenteritis.


Glaucoma is the leading cause of irreversible blindness and is a major health and economic burden. Current treatments do not address the neurodegenerative component of glaucoma. In animal models of glaucoma, the capacity to maintain retinal nicotinamide adenine dinucleotide (NAD) pools declines early during disease pathogenesis. Treatment with nicotinamide, an NAD precursor through the NAD salvage pathway, robustly protects against neurodegeneration in a number of glaucoma models and improves vision in existing glaucoma patients. However, it remains unknown in humans what retinal cell types are able to process nicotinamide to NAD and how these are affected in glaucoma. To address this, we utilized publicly available RNA-sequencing data  and antibody labelling in highly preserved enucleated human eyes to identify expression of NAD synthesizing enzyme machinery. This identifies that the neural retina favors expression of the NAD salvage pathway, and that retinal ganglion cells are particularly enriched for these enzymes. NMNAT2, a key terminal enzyme in the salvage pathway, is predominantly expressed in retinal ganglion cell relevant layers of the retina and declines in glaucoma. These findings suggest that human retinal ganglion cells can directly utilize nicotinamide and could maintain a capacity to do so in glaucoma, showing promise for ongoing clinical trials.The online version contains supplementary material available at 10.1186/s40478-023-01513-0. Age is the major risk factor for neurodegenerative disease. There is a pressing need to elucidate the underlying molecular mechanisms that drive retinal susceptibility to age. Metabolic decline may be a critical, and treatable, pathogenic component of aging and neurodegenerative disease. Neurons are highly bioenergetic and are intrinsically susceptible to mitochondrial dysfunction and metabolic failure . During e.g. Tenon’s fibroblasts . Data are expressed as normalized transcripts per million (nTPM) where normalization uses trimmed mean of M values to allow for between-sample comparisons. The human retina NucSeq dataset  was acce dataset  was avai dataset . MetadatStudent’s t-test. Unless otherwise stated, * = P < 0.05, ** = P < 0.01. For box plots, the center hinge represents the median with upper and lower hinges representing the first and third quartiles; whiskers represent 1.5 times the interquartile range.Statistical analyses of antibody labelling were performed in R using an unpaired NAMPT, NMNAT1, NMNAT2, NMNAT3) were expressed in whole retina from all individuals as was NMRK1, but not NMRK2 ). NAMPT and NMNAT3 were highly variable between individuals. The Preiss-Handler pathway transcript NAPRT was lowly expressed and only detected in 21 individuals (< 20%) but NADSYN1 was well expressed  Project through The Human Protein Atlas project portal, allowing for an assessment of transcripts in human retina across a sample of 105 individuals. NAD-salvage pathway transcripts  as a substrate over nicotinamide riboside (NR) in retinal neurons  revealed NAMPT and NMNAT1 expression to be normally distributed, whereas NMNAT2 had a greater variance, perhaps indicating RGC-subtype specific variation in NMNAT2. NMNAT3 expression was greatest in rods and cones, followed by RGCs  from 4 individual postmortem normal retina  and single nucleus RNA-sequencing dataset (NucSeq) from 4 individual postmortem normal retina . These allowed for identification of expression in retinal neurons , bipolar cells (BPs), amacrine cells (ACs), retinal ganglion cells (RGCs)), and non-neuronal retinal cells  in the NucSeq; Fig. Seq Fig. A. In conons Fig. A indicat1-3 Fig. A. NMRK1 sfection . AlthougNAMPT and NMNAT3  demonstrating that non-neuronal cells in the retina may have a greater flexibility in NAD production by utilizing more substrates and pathways  we identified that NMRK1 and NADSYN1 average expression and percentage of expressing cells is far greater in the anterior chamber of the eye  eyes from this archive . Importan = 11 control eyes; Fig. n = 10 control eyes) and NMNAT2 (n = 8 control eyes) labelling demonstrated contrasted localization with NMNAT1 located only in nuclei . While NMNAT1 labelling was highly uniform along the optic nerve  and NMNAT2  as is common for in vivo OCT imaging studies. NAMPT labelling in the central retina was significantly reduced in the GCC in glaucomatous samples relative to controls and was not significantly altered in the INL or outer retina  [Vision loss from glaucoma is a significant health and economic burden. However, the only current strategies to manage glaucoma target a risk factor; elevated intraocular pressure, and do not address the neurodegenerative components of the disease. Development of neuroprotective therapies and a clear understanding of their potential mechanisms of action is of crucial importance. NAD production is an ideal target for neuroprotection in glaucoma and other age-related ophthalmic diseases. In mammals, NAD is produced through 3 primary pathways: de novo from tryptophan, the Preiss-Handler pathway from niacin, and the NAD salvage pathway from nicotinamide  . The maiprotein) . As suchNMNAT2 expression is decreased in brains with Alzheimer's disease and has a highly variable expression in aged postmortem human brains [Nmnat2 in rodent RGCs in both an age- and disease-dependent manner [NMNAT2 expression levels may be a potential risk factor in human glaucoma. We expand this knowledge by demonstrating that RGCs are the predominant NMNAT2 gene expressing neurons of the retina , and that NMNAT2 protein is greatest in the RGC relevant layers of the retina and localizes to RGC axons in the optic nerve. NMNAT2 expression was variable in the retina and optic nerve head, which could potentially contribute to the variability of glaucoma progression. NMNAT2 has a rapid turnover time in vivo [As a neuron-specific, cytosolically expressed protein, NMNAT2 is emerging as an extremely important NAD producing enzyme in axons, protecting from axon degeneration. n brains . We havet manner , 21 and  in vivo . Importai.e. expression below cut-off in the majority of cells). Co-labelling with specific cell markers would be needed to identify whether this variability reflects inter- or intra- cell type variability. It is worth noting that the expression-cut offs in the single cell/nucleus sequencing have a high threshold for detection; in the NucSeq, on average only 2266 genes per nucleus were detected . The true percentage of cells expressing these genes is likely much higher.There was visible variability in the labeling intensity of NMNAT1 between nuclei in the retinal nuclear layers. The single cell/nuclear sequencing data reflects this, with low percentage expression across cell types , however protein labelling appears greater in the round nuclei of the GCL and INL than in non-uniform nuclei in the IPL  or in small capillary vascular walls. Conversely, there was intense labelling surrounding nuclei in the glial framework of the optic nerve head and the vasculature of the central retinal vessels  [Non-neuronal cells in the retina and eye had greater expression of Preiss-Handler pathway genes than neuronal cells, suggesting a lower reliance on the NAD-salvage pathway. Non neuronal cells also had greater expression of AD ratio , 24. NAM ligand) . The NAM ligand) . NAMPT w ligand) . That NAe.g. spontaneous knockdown of Nmnat2 triggers Wallerian degeneration in mouse neurons [NMNAT1 cause Leber’s congenital amaurosis [e.g. the high expression of NMNAT1 in photoreceptors in the outer retina).Supplementation of high dose nicotinamide has demonstrated robust neuroprotection in glaucoma across multiple animal species and models , 6 and h neurons  and redumaurosis   had high average expression in a high percentage of cells for NMRK1, and to a lesser extent NADSYN1. This is greater in comparison to retinal cells, suggesting that while the retina favors the NAD-salvage pathway, the anterior chamber favors the Preiss-Handler pathway and nicotinamide riboside as an alternative substrate to the NAD-salvage pathway.


Weight loss is recommended for improving glycemic control and reducing cardiovascular risk factors in persons with diabetes. However, both diabetes and weight loss have been associated with detrimental skeletal health. This review aims to summarize recent study findings on the effects of lifestyle interventions for weight loss on skeletal health among persons with type 2 diabetes (T2D).A few large-scale observational studies have demonstrated an increased fragility fracture risk associated with weight loss among persons with T2D. Randomized control trials in persons with T2D also have shown that intentional lifestyle interventions for weight loss are associated with a greater decrease in bone mineral density (BMD) and an increase in the risk of fracture. The biological mechanisms underlying the compromised bone health during lifestyle interventions for weight loss are complex and not yet conclusive. However, there is evidence to suggest that bone loss and increased fracture risk during intentional weight loss may be mitigated by some intervention approaches, such as high protein intake, calcium supplementation, and resistance and balance training.There is still a lack of studies investigating the effects of different interventions for weight loss on skeletal health among persons with T2D. However, certain types of diet and physical activity intervention combined with bone monitoring and fracture risk prediction may help achieve weight loss goals and maintain skeletal health among persons with T2D during intentional weight loss. Diabetes mellitus, especially type 2 diabetes (T2D), has emerged as a leading public health concern worldwide because of its escalating prevalence and considerable impact on human life and health expenditures , 2. DiabAlthough there are well-established beneficial effects of weight loss on improving cardiovascular risk factors in persons with T2D, weight loss has been associated with bone loss and potentially increased risk of fracture. It is also well-known that persons with T2D have an increased incidence of fracture despite having increased bone mineral density (BMD) . TherefoThe importance of weight management in T2D is well recognized. Both observational , 12 and Persons with diabetes have shown an increased risk for bone fragility fracture compared with persons without diabetes. A large-scale meta-analysis including over 17 million participants from 49 studies concluded that both T1D and T2D were associated with a higher risk of hip and non-vertebral fractures. In T2D, insulin use and longer diabetes duration are associated with a greater risk of hip fractures . The mecUnlike persons with T1D who typically have decreased BMD, persons with T2D usually have normal or elevated BMD as measured by dual-energy x-ray absorptiometry (DXA). So poor bone quality, such as deteriorated bone microarchitecture, has been suggested to contribute to skeletal fragility in T2D. Three major techniques  have been used to evaluate bone microstructure in T2D . TBS is Another possible mechanism contributing to bone fragility in T2D is the accumulation of advanced glycation end-products (AGEs) resulting from prolonged hyperglycemia. AGEs accumulation leads to the generation of undesired crosslinks in bone, which affects mineralization, material properties, and microstructure, thereby impairing biomechanical properties and reducing bone strength •. PersonThe increased risk for fracture is also related to the increased risk of falls in diabetes. Persons with T2D suffer a greater risk of falls , 29. TheAlthough it has been established that weight loss has multiple physiological and metabolic benefits, there is a substantial body of evidence that weight loss can lead to bone loss and an increased risk for fracture. Large-scale longitudinal cohort studies also observed an increased risk of fracture among individuals with intentional or unintentional weight loss –38. ClinBoth diabetes and weight loss have negative impacts on bone health. However, weight loss is still recommended for diabetes patients who are overweight or obese for glycemic control and the prevention of comorbidities. There is still a lack of research exclusively conducted in persons with T2D to examine the effect of weight loss on bone health and fracture risk. Two recent observational studies reported weight loss was associated with increased fracture risk in persons with T2D , 43. KomAlthough these observational studies may provide further evidence of weight loss-related bone loss in persons with T2D, it was unclear if the weight loss experienced by the study subjects was intentional or unintentional. Look AHEAD is still the largest randomized clinical trial of long-term intentional weight loss through ILI among overweight/obese persons with T2D. Look AHEAD has observed a greater short-term and long-term decrease in BMD among the subjects of the ILI group compared with those of the DSE group. In a substudy of Look AHEAD which included 642 subjects of ILI and 632 of DSE from 5 of 16 clinical centers, BMD was measured using DXA at years 1, 4, 8, and 12–16 years after randomization. At 1-year follow-up, BMD was significantly decreased at the total hip and femoral neck in ILI but not for the lumbar spine and whole body . At 4-yeThe biological mechanisms underlying bone loss and increased risk of fracture during intentional weight loss by lifestyle intervention among persons with T2D are complex and largely unknown Fig. . As we dIt seems clear that weight loss can induce bone loss and subsequently increase the risk of fracture. Also, weight loss is still the recommended first-line treatment for T2D to improve glycemic control and possibly prevent cardiovascular disease and other comorbidities. Therefore, it may be necessary to monitor bone health and evaluate fracture risk before and during weight loss. Different intervention methods for weight loss may have different effects on bone . It is iIt has been considered that the use of the Fracture Risk Assessment Tool (FRAX) underestimates fracture probability in individuals with T2D , 54. ManEnergy restriction combined with low fat or low carbohydrate intake is commonly used for weight loss , 62. RecThere is evidence to suggest that bone loss with intentional weight loss may be mitigated by calcium supplementation . HoweverN=20) has recently observed significant weight loss but no bone loss at 12 weeks of a self-selected daily 8-h eating window of ad libitum intake [Besides what to eat, when to eat may influence weight as well. Time-restricted eating (TRE) has been shown effective for weight loss –74. A smm intake . TRE mayTwo recent meta-analyses of randomized controlled trials concluded that exercise attenuates bone loss during weight loss induced by calorie restriction , 77. BotPreventing falls should be also considered for reducing the risk of fractures in persons with T2D who may have poor balance control and increased falls risk because of peripheral neuropathy. Balance training has improved balance and motor coordination and decreased the risk of falling in persons with T2D . TherefoThere is still an ongoing effort to investigate novel methods to mitigate bone loss during intentional weight loss. For example, the Incorporating Nutrition, Vests, Education, and Strength (INVEST) study is investigating the effect of a novel weight replacement method (via weighted vest use) on bone during weight loss interventions •. The meBoth T2D and weight loss have a deleterious impact on bone health. There are still very limited studies to investigate the approach to mitigate bone loss during weight loss interventions, especially for persons with T2D. Potential solutions may include optimization of diet and physical activity which minimize adverse bone effects during weight loss. The available evidence seems to support the potential application of calorie restriction combined with increased protein intake, resistance exercise, and balance training in weight loss interventions. Calcium plus vitamin D supplementation may also be beneficial. Also, novel biomarkers are required to improve the fracture risk prediction during weight loss to carry out timely treatment for the prevention of osteoporosis and fracture. In conclusion, future research is still warranted to investigate the approaches for maintaining and even improving bone health during weight loss and maximizing the health benefit from weight loss in persons with T2D.


The hypothalamus regulates innate social behaviors, including mating and aggression. These behaviors can be evoked by optogenetic stimulation of specific neuronal subpopulations within MPOA and VMHvl, respectively. Here we perform dynamical systems modeling of population neuronal activity in these nuclei during social behaviors. In VMHvl, unsupervised analysis identified a dominant dimension of neural activity with a large time constant (>50s), generating an approximate line attractor in neural state space. Progression of the neural trajectory along this attractor was correlated with an escalation of agonistic behavior, suggesting that it may encode a scalable state of aggressiveness. Consistent with this, individual differences in the magnitude of the attractor time constant were strongly correlated with differences in aggressiveness. In contrast, line attractors were not observed in MPOA during mating; instead, neurons with fast dynamics were tuned to specific actions. Thus, different hypothalamic nuclei employ distinct neural population codes to represent similar social behaviors. Different hypothalamic regions utilize distinct neural dynamics to encode mating and aggressive behaviors.  Classical brain stimulation and lesion experiments have implicated different hypothalamic regions (“nuclei”) in diverse innate behaviors (reviewed in9). More recently, optogenetic stimulation has identified genetically marked neuronal subpopulations that can evoke such behaviors13,(reviewed in17). Genetic ablation or reversible silencing has demonstrated that these subpopulations are essential for natural occurrences of these behaviors18.A fundamental problem in neuroscience is to understand how the brain controls innate behaviors. Many such behaviors are governed by the hypothalamus, a deep subcortical brain region present in all vertebrates21. Recordings of bulk calcium signals22 have confirmed that these neuronal subpopulations are active during the natural behaviors they can artificially evoke25. However, this averaging method obscures individual cell activity patterns.An important open question is how the activity of these neural subpopulations during naturally occurring behavior reflects their “causative” function. Relatively few single unit recordings have been performed in hypothalamic nuclei because of their inaccessibility27. Application of this approach to the hypothalamus has identified cells exhibiting stimulus-locked activity during natural behavior30. For example, imaging of estrogen receptor type 1 (Esr1)-expressing neurons in the medial preoptic area (MPOA), whose optogenetic activation can elicit mounting behavior in male mice32, has revealed cells that respond specifically during spontaneous mounting of females  neurons triggers attack behavior37, identifying these neurons as the likely cellular substrate of electrical brain-stimulated aggression38. Conversely, genetic ablation of VMHvl neurons expressing the progesterone receptor  or optogenetic silencing of VMHvlEsr1 neurons blocks natural aggression18,12The case of aggression, however, presents a paradox seemingly at odds with this view. On the one hand, optogenetic stimulation of Esr1Esr1 neurons during natural fighting revealed surprisingly few cells that exhibited time-locked, attack-specific activity29. Instead most such neurons exhibited “mixed selectivity,” responding during different phases of an aggressive interaction. Different subsets of Esr1+ neurons responded to male vs. female conspecifics, suggesting an encoding of conspecific sex39. Nevertheless, decoders trained on VMHvlEsr1 neural imaging data could accurately distinguish episodes of attack from sniffing29.On the other hand, miniscope imaging of VMHvlEsr1 neurons yield seemingly inconsistent views: these neurons causally control aggressive behavior, yet very few of them are specifically “tuned” to attack. There are two possible explanations for this paradox. First, the small fraction of VMHvlEsr1 neurons that are more active during attack may be the ones responsible for the specific causative influence of this population. Alternatively, the majority of VMHvlEsr1 neurons, despite their mixed behavioral selectivity, may control attack through some type of population code.Thus observational vs. perturbational studies of VMHvl42 (reviewed in43) has revealed signals in the dynamics of population activity that can robustly predict motor actions45. We have therefore carried out similar modeling of VMHvlEsr1 neural activity dynamics during naturalistic social behaviors, using legacy data from previous studies39. Our results reveal line attractor dynamics in VMHvl that correlate with escalating levels of aggressive behavior, suggesting they may represent or encode an aggressive internal state. Strikingly, line attractor dynamics are absent in MPOA activity during both mating and aggression. This analysis therefore reveals fundamental differences in the neural coding of social behaviors by different hypothalamic nuclei.In other systems where there is no clear correlation between single-unit spiking patterns and behavior, modeling neural populations as a dynamical systemEsr1 or VMHvlEsr1 neurons revealed distinct patterns of neuronal activation during social interactions31 , from two different studies39 in which recordings were made throughout male-male or male-female encounters . Specifically, we fit a recurrent switching linear dynamical system (rSLDS) model48, which approximates a complex non-linear dynamical system as a composite of more easily interpretable linear dynamical systems, or “states”  , defining a low-dimensional “state-space” in which the time-evolving population neural activity vector can be analyzed ➀. Populais (PCA) .48 and an additional metric that we call the “forward simulation error”  time constants persists and decays slowly. Strikingly, one of the rSLDS dimensions had an estimated time constant of over 100 seconds that was significantly higher than that of all other dimensions . In contrast a support vector machine (SVM) decoder trained to distinguish attack from sniffing periods explained much less variance , and increased further to a stable plateau value as the animal attacked , perhaps due to the gradual ramping of activity along this dimension. Remarkably, none of the other seven fit dimensions could be used to distinguish aggressive behaviors from sniffing with above chance accuracy . Because of its slow ramping and stable plateau, activity in the integration dimension did not decay during such IBIs and therefore could not distinguish behavioral bouts from adjacent IBIs  vs 2. HoEsr1 neural population activity that closely tracks and scales with an animal’s escalating level of aggressiveness and is reflected in the activity of approximately 20% of individual VMHvlEsr1 neurons. Different aggressive actions are observed as activity along this dimension reaches different thresholds, suggesting an aggression-intensity code in VMHvlEsr1 activity. The level of activity along the integration dimension could not be fully predicted from pose features such as the acceleration, facing angle, or velocity of the resident, or from the distance between mice . We confirmed that the rSLDS integration dimension makes the largest contribution to this PC ), but was otherwise low.We examined next how the integration dimension of the fit model influences the overall topology of neural state-space during social behavior . PCA ind this PC . Activitright, 58 (50-t340).). To quantitatively delimit this attractor, we calculated the points in the flow field where vector length is at a minimum , and is otherwise close to zero. We find that all mice with VMHvl recordings possess a line attractor score greater than zero, indicating the presence of a line attractor . We observed a trough-like structure in the 3D dynamics landscape in each imaged animal  of the landscape ; the x-yFigure 3Bd animal , along wd animal . Consist seconds –J.Although the animals’ behavior appears to occur while the system is in the line attractor, it could be that other rSLDS dimensions also show a change in their activity during behavior. To test this possibility, we computed each behavior’s “dynamic velocity”, by calculating the average vector length across all eight rSLDS dimensions at all time points in which a given behavior occurred. . Time po42  also exhibited an integration dimension with a longer time constant . This relationship held for imaging data from different studies39 using different versions of GCaMP .Since rSLDS was able to uncover evidence for integration in VMHvl, we next examined whether the same analysis would uncover population dynamics important for mating in MPOA, by fitting models to MPOA+ mounting bouts, while PC2 peaked during intromission  that is closely aligned to the onset and offset of attack behavior  nature of aggression has ethological relevance as a means of establishing dominance while minimizing the risk of injury64. Unexpectedly, in comparing data across multiple animals we discovered a strong positive correlation between each mouse’s level of aggressiveness and the magnitude of the time constant of its integration dimension. This result reveals a neural correlate of individual differences in aggressiveness within VMHvl.In other neural systems, line attractors often encode a continuous, low-dimensional variable59. Indeed, there is evidence that glutamatergic neurons in VMHdm that encode persistent defensive behaviors exhibit local connectivity65. However, slow dynamics can also be achieved using neuromodulatory signaling, and there is indirect evidence for peptidergic transmission in VMHvl66The different neural codes for social behavior we have uncovered in VMHvl and MPOA may reflect their distinct neurochemical and cytoarchitectonic features. VMH neurons are primarily glutamatergic. Recurrent connectivity among excitatory neurons is often invoked as a mechanism to achieve persistent activity39, giving rise to the rotational dynamics observed in neural data. The existence of such circuits in MPOA can be investigated using slice physiology or in vivo imaging once genetic access to the appropriate cell types is achieved.By contrast, MPOA neurons are 85% GABAergic; to our knowledge there is no way to achieve similar graded and persistent signals within a population of inhibitory neurons. However, GABAergic neurons could provide a substrate for reciprocal inhibitory connections between action-specific subpopulations. Such connectivity could produce winner-take-all dynamics or feed-forward dis-inhibitory circuits that control transitions between sequential action phases of mating, e.g., from sniffing to mountingWhy should MPOA and VMHvl utilize such different strategies for the coding of closely related social behaviors? It is tempting to attribute this difference in population dynamics to distinct features of reproductive vs aggressive behavior. For example, aggressive encounters can dynamically escalate or de-escalate to avoid serious injury or death to the combatants, whereas male mating must proceed to completion (ejaculation) to be reproductively beneficial. These differences are well-suited to control by ramping and rotational neuronal dynamics, respectively. In this view, the different properties and coding strategies of VMHvl and MPOA may have evolved to be optimally adaptive for fighting and mating, respectively.Esr1 neurons that is female-tuned and active during mating29. This suggests that line attractor-like dynamics are a general property of behavioral coding by VMHvl, not an aggression-specific feature. Conversely, MPOA contains specific Esr1+ neurons highly tuned to attack which do not exhibit line attractor dynamics . These data suggest that MPOA and VMHvl more likely encode different features of a given social behavior, such as action selection vs. motive state intensity, respectively. If so, then by extension the hypothalamus may contain GABAergic populations that control actionselection during aggression. Indeed, the anterior hypothalamic nucleus (AHN), which has a similar neurochemical and cytoarchitectonic structure as MPOA, can promote defensive attack68; it will be interesting to see whether rotational dynamics are observed in this structure. By the same token, PMv which controls aggression and is also primarily glutamatergic70, may utilize population coding like VMHvl.However, our analysis also revealed approximate line attractor dynamics in a subset of VMHvl46. It is unexpected to find such neural dynamics in the hypothalamus, which is widely viewed as controlling innate behaviors via action-specific cell types (as observed in MPOA33). What function(s) might such attractor dynamics serve, in the context of innate behaviors? Two explanations are possible, which are not mutually exclusive.Line attractors have been identified in cortical and hippocampal regions involved in cognitive functions, such as decision-making, spatial mapping and sensory discriminationAs mentioned earlier, progression along the line attractor may encode the intensity of an internal motive state of aggressiveness. This is supported by our finding that the integration dimension that contributes to this attractor can distinguish periods of nonsocial interaction during high- vs. low-intensity phases of aggressive escalation . In thisEsr1 neural activity is intruder sex29. Whether VMHvl encodes intruder sex per se, or an internal motive state tightly correlated with intruder sex, has been difficult to distinguish because males only attack other males and not females. In female mice, however, lactating mothers attack intruders of both sexes. Recently, we identified a subset of VMHvlEsr1 neurons in females that express the GPCR gene Npy2r, called ß cells, which are both necessary for maternal aggression and sufficient to promote attack in non-aggressive virgins 37. Bulk calcium measurements revealed that ß cells are strongly active during maternal aggression towards both male and female intruders. However, these cells display low activity in individual females that are non-aggressive 37. Thus in females the encoding of aggressive state by VMHvlEsr1 neurons can be decoupled from the encoding of intruder sex. These data reinforce the idea that in males, the VMHvlEsr1 line attractor  encodes aggressiveness, rather than simply intruder sex.Previous studies have indicated that the greatest source of variance in VMHvlDrosophila71 and predator escape in mice 72. These two hypotheses are not incompatible: the attractor could encode both the intensity of an internal state, and (indirectly) the selection of actions at different state intensities.An alternative function for the line attractor is that it may serve as an integrator that accumulates “evidence” used to make behavioral decisions, such as the decision to switch from sniff to dominance mount, or from dominance mount to attack. Such a function would require that different behaviors be triggered at different threshold values of the integrator. This type of ramp-to-threshold mechanism has been suggested to control sequential actions during male courtship behavior in Esr1 neurons show increased selective tuning for male vs. female intruders as a function of social experience 29, and exhibit a form of long-term potentiation that underlies the increase in aggressiveness that occurs when mice win a series of fights 73. It will be interesting to determine whether changes in flow field dynamics or attractor properties are associated with these forms of experience-dependent plasticity. Finally, we note that differences in line attractor properties were observed among mice which exhibited different and characteristic levels of aggressiveness  recurrent dynamics and feedback, as well as whether the attractor is truly “autonomous” and not input-driven. The biological line attractor in VMHvl is a ‘leaky’ approximation of a mathematically defined line attractor, exhibiting slow decay over time scales similar to line attractors discovered in other neural systems59. Further knowledge of the underlying neural mechanisms is required to understand the extent to which the region of stability identified here approximates a true line attractor.Our discovery of line attractor dynamics in VMHvl derives from quantitative analysis of a dynamical system model fit to neural data. While this analysis has revealed several conditions required for line attractor dynamics, such as persistence in the absence of input and robustness to behavioral perturbation, a definitive test requires experimental perturbation of neural activitywuwei@caltech.edu).Requests for resources and reagents should be addressed to lead contact, David J. Anderson  and the Institute Biosafety Committee (IBC) at the California Institute of Technology . All experiments utilized heterozygous Esr1cre/+ knock-in mice on a C457BL6/N background (B6N.129S6(Cg)-Esr1tm1.1(cre)AndIJ, JAX strain #017911). Expression of GCaMP6s  or GCaMP7f  was achieved by stereotaxic injection of a Cre-dependent GCaMP-expressing adeno-associated viruses (AAVs). Briefly, for data obtained from Karigo et al., 2021, mice expressing GCaMP6s selectively in Esr1 neurons in either the medial preoptic area (MPOA) or the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl), were allowed to interact with BALB/c male and female intruders in a standard resident intruder assay . Male or female intruders were introduced into the home cage in a random order, with a 5–10 min interval between intruder session. Each session typically lasted 10–20 minutes. Behavior videos of interacting animals were annotated using a custom MATLAB-based interface. A total of 7 behaviors including sniffing, dominance-mount, attack, mount, intromission, interact  were annotated with male and female intruders. A head-mounted micro-endoscope  was used to acquire Ca2+ imaging data at 15Hz from either MPOAEsr1 neurons  or VMHvlEsr1 neurons  for neural data analysis described in sections below.We analyzed data from three sets of previous experiments Esr1 neurons in VMHvl, were allowed to interact with BALB/c male intruders in a standard resident intruder assay. In addition to the behaviors annotated for above, male intruders were also “dangled”, where the ano-genital region of the dangled intruder is held next to the resident mouse. A head-mounted micro-endoscope was used to acquire Ca2+ imaging data at 30Hz from VMHvlEsr1 neurons (386 neurons from 3 mice) for neural data analysis described in sections below.For data obtained from Yang et al., 2022, Esr1-Cre mice in which GCaMP7f was expressed selectively in Esr1 neurons in VMHvl were allowed to interact with BALB/c male intruders in a standard resident intruder assay. A head-mounted micro-endoscope was used to acquire Ca2+ imaging data at 30Hz from VMHvlEsr1 neurons (358 neurons from 3 mice) for neural data analysis described in sections below. rSLDS models were fit to data from n=14 mice to extract the time constant of the integration dimension used for correlation with individual differences in aggressiveness in For data obtained from Remedios et al, 2017, Esr1-Cre mice in which GCaMP6s was expressed selectively in Esr1 or MPOAEsr1 by creating behavior tuning rasters  and area of ellipse fit to the resident mouse’s pose.As external input to the dynamical model (see next section), we selected two features of animal pose estimates produced by the Mouse Action Recognition System , a set of continuous latent factors (x) that captures the low-dimensional nature of neural activity, and the activity of recorded neurons (y). The model also allows for external inputs (u) which consists of extracted pose features including the distance between animals and the facing angle between the resident and intruder mouse.We model neural activity using a recurrent switching linear dynamical systems (rSLDS) according to previous methodsR, W and r parameterizes a map from the previous discrete state, continuous state and external inputs using a softmax link function to a distribution over the next discrete states.The model is formulated as follows: At each time zt determines the linear dynamical system used to generate the continuous latent factors at any time t:t) to each dimension of the latent space and d is the dimensionality of the latent space and m is the dimensionality of the external inputs. Thus, the discrete state specifies a set of linear dynamical system parameters and specify which dynamics to use when updating the continuous latent factors.The discrete state 77.Lastly, we can recover the activity of recorded neurons by modelling activity as a linear noisy Gaussian observation evidence lower bound (ELBO) which is equivalent to the Kullback-Leibler divergence between the approximate and true posterior, Model performance is reported as the t, we predict the trajectory of the population activity vector over an ensuing small time interval Δt using the model, then compute the mean squared error (MSE) between that trajectory and the observed data at time t+ Δt ” model evaluation metric calculated as follows: given observed neural activity in state space at time me t+ Δt . This MSformance . This mehttps://github.com/lindermanlab/ssm)Code used to fit rSLDS on neural data is available in the SSM package: (https://github.com/DJALab/VMHvl_MPOA_dynamics)Code to generate flow fields and energy landscapes from fit dynamical systems is available in  from the activity of the integration dimension on individual frames of a behavior (sampled at 15Hz) as described previously . We first created ‘trials’ from bouts of social behavior by merging all bouts that were separated by less than five seconds. We then trained a linear support vector machine (SVM) to identify a decoding threshold that maximally separates the values of our normalized “integration dimension” signal on frames during which behavior A occurred from values on frames during which behavior B occurred, for the pair-wise behavioral comparison. ‘Shuffled’ decoder data was generated by setting the decoding threshold on the same “trial”, but with the behavior annotations randomly assigned to each behavior bout. We repeated shuffling 20 times for each intruder and each imaged mouse. We report performances of actual and shuffled 1D-threshold “decoders” as the average F1 score of the fit decoder, on data from all other “trials” for each mouse. For significance testing, the mean accuracy of the decoder trained on shuffled data was computed across mice, with shuffling repeated 1000 times for each mouse. Significance is determined by bootstrapping; we considered observed F1 scores significant if they fell above the 97.5th percentile of the distribution of chance F1 scores as done previously 57 as follows. Consider a neural signal that displays a slow ramp in activity, which can be used to decode attack from sniffing As a stringent test for spurious correlations due to the slow decay seen in the integration, we performed a variation of session permutation Since the latent states are invariant to linear transformations, it is possible to apply a suitable transformation to obtain an equivalent model using rSLDS. We use PCA for this transformation as it allows us to describe our high dimensional rSLDS latent space in a concise manner with few dimensions while capturing the overall dynamics. To perform this the following steps are applied:tGiven latent factors: W such that Wx is the identityCompute a whitening transformation Compute the transformed linear dynamical system Compute the singular value decomposition (SVD) of the new emission matrix Compute the final transformed latent states  In this final transformation, since the singular values are ordered, the first two components of z. We then averaged this value across states, giving a definition of Tb is the set of all timepoints during which behavior b occurred, We devised a metric termed the “dynamic velocity” to quantify the average intrinsically generated rate of change of the fit dynamical system during a given behavior of interest. We first calculated the average norm of We also converted the flow-fields obtained from rSLDS into a 3D landscape for visualization by calculating the dynamic velocity at each point in neural state space and using it as the height of a 3D landscape.Data were processed and analyzed using Python, MATLAB, and GraphPad (GraphPad PRISM 9). All data were analyzed using two-tailed non-parametric tests. Mann-Whitney test were used for binary paired samples. Friedman test was used for non-binary paired samples. Kolmogorov-Smirnov test was used for non-paired samples. Multiple comparisons were corrected with Dunn’s multiple comparisons correction. Not significant (NS), P > 0.01; *P < 0.01; **P < 0.005; ***P < 0.001; ****P < 0.0001.1Supplementary Figure 1: Unsupervised discovery of aggression-enriched states in VMHvlRelated to Figure 21: rSLDS states in VMHvl mouse 1. I2: comparison of rSLDS states with behaviors. I3: behavioral composition of rSLDS states. State 3 possesses the highest amount of attack behavior across mice . I4: probability of attack aligned to the onset of state 3 (n = 6 mice). I5: timescale of behavior bouts and discovered states epochs. I6: state transition diagram from empirical transition probabilities. J: Same as F2, F3, F5 but for VMHvl mouse 2. K: Same as F2, F3, F5 but for VMHvl mouse 3.A: types of neural states identified by rSLDS. B1, B2: behaviors; Q0, Q1: periods of quiescence between behavior bouts; S0,S1,S2: rSLDS states. Case 1: rSLDS states cannot distinguish behavior vs internal states. Case 2: rSLDS reflects internal state-encoding due to persistence during behavioral quiescence. B: optimization of number of rSLDS states in example VMHvl mouse 1. Model performance is measured as ELBO see . C: same2Supplementary Figure 2: Characterization of aggression-integration dimensionRelated to Figure 22, n = 6 mice). B: fraction of overall variance explained by integration dimension (purple) compared to variance explained by decoder dimension trained to distinguish attack from sniff bouts . C: decoding behaviors from non-integration dimensions . D: absolute rSLDS weight on integration dimension of VMHvl mouse 1 (cell number on x-axis), sorted by choice probability values for male vs female intruder encounter. E-G: paradigm to account for spurious correlations: decoding threshold obtained using integration dimension of mouse 1  is used on integration dimension from mouse 2 (F). Spurious correlations lead to low F1 scores (F) while true correlations retain high F1 scores (G). H: decoding behaviors using paradigm described above  I: normalized activity of neurons times rSLDS weight for cells with significant weights for integration dimension of VMHvl mouse 1. J: example cells from I. K: integration dimension in VMHvl mouse 2. L: same as I for VMHvl mouse 2. M,N: Same as K,L for VMHvl mouse 3.A: variance explained by a generalized linear model trained to predict integration dimension from pose-features including distance between mice, facing angle, speed, acceleration, and velocity of resident mouse . C: low dimensional dynamics and flow field from model with no behavioral inputs included with line attractor highlighted. D: time constants from the fit dynamical system (n = 6 mice). E: line attractor score for VMHvl models without input. F: tracking features used in rSLDS shown alongside discovered states and integration dimension in VMHvl mouse 1. G: performance of decoder used to separate attack frames from sniff-alone frames using the distance between mice and facing angle of the resident. H: scatter plot of distance between mice and facing angle of resident. I: model performance (1-FSE) for different types of external inputs (n = 6 mice); current inputs = distance between animals, facing angle of resident. (***p<0.001).4Supplementary Figure 4: Properties of line attractor dynamics in VMHvl.Related to Figure 3A,B: absolute PCA weights of PC1(A) and PC2(B) on dimensions of dynamical system sorted by decreasing time constant in VMHvl mouse 1. C: behavior triggered average of top two principal components aligned to introduction of first intruder or first attack onset (n = 6 mice). D,E: low dimensional dynamics and flow field showing line attractor dynamics for VMHvl mouse 2 and mouse 3 with line attractor highlighted. F: schematic showing how perturbations orthogonal to a line attractor do not alter the position of the system. G: integration dimension in VMHvl mouse 1 . I3: timescale of behavioral bouts and states epochs. J1–3: same as I1–3 for MPOA mouse 3, selected mating bouts highlighted. K: rotational trajectories for 3 mating episodes in MPOA mouse 1. L: same as K, for mating bouts highlighted in highlighted in I1 for MPOA mouse 2. M: same as K, for mating bouts highlighted in highlighted in J1 for MPOA mouse 3.A: rSLDS states in MPOA mouse 1. B: comparison of rSLDS states with behavior in MPOA mouse 1 for period from t = 600s to t = 700s. C: behavioral composition of rSLDS states. D: probability of intromission and USV+ mounting aligned to the onset of state 2 and state 3 . E: timescale of behavioral bouts and states epochs. F: Reproduced from 6Supplementary Figure 6: Dynamical analysis of VMHvl activity in mating behavior and MPOA activity in aggression.Related to Figure 6A: rSLDS states in VMHvl mouse 1 during interactions with female intruders. B: comparison of rSLDS states with behaviors. C: behavioral composition of rSLDS states. State 3 possesses the highest amount of mating behavior across mice (see panel H). D: timescale of behavior bouts and state epochs. E: state transition diagram from empirical transition probabilities. F-H: Same as B-D for VMHvl mouse 2. This mouse did not achieve intromission. I: decoding behaviors from integration dimension (**p<0.005). ). J: empirical cumulative distribution of value of integration dimension  for various behaviors. K: dynamics velocity landscape showing a progression of mating behavior along the trough for VMHvl mouse 1. L: normalized activity times rSLDS weight for cells contributing significantly to integration dimension of VMHvl mouse 1. M: absolute rSLDS weight on integration dimension of VMHvl mouse 1 during mating behavior  and aggression  sorted by choice probability values for male vs female intruder encounter. N: top: state and behavior raster for MPOA mouse 1 during aggressive behavior. State 3 is aligned closely to the onset of attack bouts, bottom: behavioral composition of discovered states. O: behavior triggered average of principal component 1 in VMHvl (red line) and MPO (blue line) . P: comparison of dynamic velocity for similar behavior between VMHvl and MPOA (reproduced from 7Supplementary Video 1: neural trajectories and flow fields of VMHvl mouse 1 alongside behaviorRelated to Figure 3Video indicates the movement of neural trajectories in a low dimensional neural state space with inferred flow fields from dynamical systems overlayed. Behavior of the resident and intruder is shown on the left.8Supplementary Video 2: neural trajectories and dynamics landscapes of VMHvl mouse 1Related to Figure 3Video indicates the movement of neural trajectories in a low dimensional neural state space with inferred dynamics landscape from dynamical systems overlayed.


Here we have employed a branch-polymer stabilised nanoemulsion strategy to create highly robust oil droplets  containing different dissolved antiretroviral drugs used in the daily fight against HIV/AIDS. Although very limited difference in permeation through a Caco-2 gut epithelium model was seen for efavirenz, the permeation of the protease inhibitor lopinavir was considerably higher (approximately 10-fold) when applied to an epithelium monolayer in emulsion form than the control within an aqueous DMSO vehicle. The presented nanoemulsion approach may allow drug-specific permeation improvements for various drug substances.The delivery of drugs to the bloodstream  Branched copolymers offer very efficient nanoemulsion stabilisers with benefits for oral drug delivery. Several groups have reported exciting results of long-acting drug delivery from nano-enabled depot injections and prophylactic interventions to prevent disease.4–6 Importantly, oral delivery of therapies is the most patient-acceptable administration route, especially over long periods where the patient must self-administer; daily injection is therefore not relevant in these cases7 although long-acting parenterals/injectables are being increasingly sought to simplify dosing for chronic conditions.8The continued growth of fundamental nanomedicine studies, and progression to clinical products, has allowed the improvement of a range of therapies, and the development of new treatment options, across a range of healthcare needs. These span psychiatric conditions9 HIV presents a major global public health threat. The UNAIDS 2016 global update estimates that (in 2015): 36.7 million people worldwide were living with HIV (range 34.0–39.8 million); there were up to 2.4 million new infections and up to 1.3 million AIDS-related deaths.10 The success of ARV therapies is observed as a considerable decline in mortality and morbidity11 and, subsequently, this leads to a growing demand for access to therapy and subsequent growth in the ongoing cost of global treatment. The combined UNAIDS 90 : 90 : 90 target12 of collectively establishing the HIV status for 90% of those infected, providing ARV therapy to 90% of people diagnosed with HIV, and achieving viral suppression for 90% of those receiving ARV therapy by 2020 will require novel solutions for drug delivery that optimises current manufacturing capacity. HIV requires lifelong daily dosing, often with large doses of drug combinations, leading to considerable risk of poor adherence to therapies and the potential for the emergence of drug resistance.13 For example, efavirenz (EFV) is a non-nucleoside reverse transcriptase inhibitor used in combination with tenofovir and emtricitabine as a once daily fixed-dose tablet (marketed as Atripla®) with a 600 mg/300 mg/200 mg drug ratio respectively.14 Low oral bioavailability contributes to the high doses and strategies that improve drug permeation from the gut to the blood may significantly reduce the administered dose and impact the per-patient cost of therapy. HIV patient groups were evaluated recently to establish their interest in novel depot injection options and a willingness to switch to nanomedicine alternatives was reported if relevant benefits can be shown.15One such chronic disease is human immunodeficiency virus (HIV) infection and its progression to acquired immune deficiency syndrome (AIDS). HIV replication is suppressed by the daily co-administration of antiretroviral (ARV) drugs from multiple classes which simultaneously inhibit a number of targets within the viral replication cycle.16 parenteral16 and oral administration. For drug administration via the gut, lipids have been reported to alter drug absorption through a combination of mechanisms including (a) enabling lymphatic uptake, (b) presenting poorly water-soluble drugs as pre-dissolved solutions, (c) stimulation of bile secretion that may facilitate absorption, and (d) inhibition of cellular mechanisms such as efflux transporters 17 or cytochrome P450 enzymes.18 Self-forming nanoemulsifying drug delivery systems (SNEDDS)19 have enhanced the bioavailability of a range of poorly-water soluble drug compounds, including very recent reports of a SNEDDS formulation of EFV.20 In addition, very recent reports have demonstrated solid self-nanoemulsifying oily formulation (S-SNEOF)21,22 approaches to enhance the delivery of the ARVs lopinavir (LPV) and darunavir, clinically well-established protease inhibitors. Self-emulsifying systems are isotropic mixtures that contain an oil phase, the drug compound and a combination of surfactants; they may also comprise a mixture of solvents, co-solvents, surfactant and drug. In these cases, determination of ternary or pseudo-ternary phase diagrams are important to identify mixtures that will spontaneously emulsify on contact with the gastrointestinal fluids. Co-surfactants (or co-solvents) may include 1-butanol, 1-propanol and ethanol and regions of the phase diagrams that offer potential for formulation may be limited. The use of a single emulsifier to generate nanoemulsions for oral drug delivery would greatly simplify the process of generating candidate nanomedicines and large scale manufacturing as the need to finely balance complex mixtures would be avoided.In recent years, the use of lipid-based nanoemulsions has been shown to offer benefits for drug delivery after topical,23,24 We hypothesised that analogous branched polymer-stabilised emulsions could be generated in the nanoscale to provide advantages for orally-dosed ARVs to enable HIV nanomedicine development. Here, we describe the controlled radical polymerisation synthesis of an amphiphilic branched copolymer able to stabilise nanoemulsions containing dissolved LPV or EFV; the tuning of nanoemulsion droplet sizes; and studies of cytotoxicity, drug permeation using a gut epithelium model and subsequent antiviral activity of the drug compounds showing their potential value as future candidate nanomedicines.Our own research has reported the use of branched amphiphilic polymers as extremely efficient emulsifiers. Branched pH-responsive copolymers were also shown to form large scale objects with remarkable stability and reversible hydrogen bonding between emulsion droplets.All experimental details, materials and methods are described in the ESI.†23,24 we showed that the dodecanethiol chain transfer agent-mediated conventional free radical copolymerisation of oligo(ethyleneglycol) methacrylate , methacrylic acid (MAA) and ethyleneglycol dimethacrylate  generates relatively low molecular weight conjoined polymer structures with multiple hydrophobic chain ends. The multiple dodecyl chain ends were able to strongly interact with the oil-phase of dodecane and to form highly stable emulsion droplets in water in the absence of additional surfactants or polymers. Linear polymer structures, synthesised in the absence of EGDMA, were poor stabilisers in comparison.In our previous reports of branched copolymer emulsifiers,n-butyl methacrylate and EGDMA yielded very high molecular weight materials, under atom transfer radical polymerisation (ATRP) conditions, and shaped nanoparticles could be directly synthesised through also incorporating multifunctional initiators.25,26 Here, we have combined these approaches to generate high molecular weight branched hydrophilic copolymers of OEGMA (approximately 300 g mol−1) and EGDMA using the hydrophobic ATRP initiator dodecyl 2-bromoisobutyrate  under copper catalysed conditions using a 92.5 : 7.5% v/v IPA/water solvent mixture  of 90 units, showed nearly identical kinetics, reaching approximately 100% monomer conversion between 7–8 hours at ambient temperature  chains with a number average degree of polymerisation , with a number average molecular weight (Mn) of 218 330 g mol−1 and weight average molecular weight (Mw) of 3 181 000 g mol−1  region with multiple hydrophobic dodecyl chain ends. From a number average perspective, therefore, the most abundant species within the polymer sample has approximately 8 conjoined highly hydrophilic polymer chains, each with a dodecyl hydrophobic chain end; from a weight average perspective, the polymer structures contributing at least half of the mass of the polymer sample have at least 85 nominal conjoined chains with their corresponding dodecyl chain ends. This is an important consideration as the polymer is used as an emulsion stabiliser as a weight% ratio with respect to the added oil and water phases.Despite the near identical polymerisation kinetics, the presence of EGDMA within the branched copolymerisation (0.95 : 1 brancher to initiator ratio) yielded an amphiphilic copolymer, poly or FDA/CDER Inactive Ingredients lists or were designated as Generally Recognised as Safe and Effective (GRASE).Selection of the oil-phase for the targeted nanoemulsions was made based on several criteria. As the targeted administration route is 27 soybean oil28 and peanut oil29  component of the nanoemulsion formation process as it is listed on the FDA/CDER list of Inactive Ingredients as being present in intramuscular, oral, topical and transdermal products; it is also a Class 3 solvent listed within the European Medicines Agency's International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use guidelines for residual solvents, establishing this solvent as having a low human toxicity potential and no requirement for a health-based exposure limit.ΦEA) within the combined oil phase was varied from 99 vol% through to 50 vol% for each non-volatile oil-phase, leading to varying emulsion droplet z-average diameters (Dz) ranging from 205 nm  to 1.04 μm , as measured by DLS  followed by homogenisation using a hand-held Ultra-Turrax T-25; the aqueous phase contained the amphiphilic branched polymer emulsifier at 5% (w/v). The volume fraction of ethyl acetate (d by DLS . Given tΦEA = 99 vol%) from 0.5% to 5% (w/v) led to a systematic decrease in the final nanoemulsion droplet size from 630 nm to 210 nm  sample to serial dilution was studied  but decreased to a near stable value up to 4096-fold dilution; Dz measured above a 512-fold dilution should be treated with some caution as the automatically set attenuator for the DLS was reaching very high values. The specific differences in the observed Dz values  210 nm  values for the blank and drug-loaded nanoemulsions were all measured to be neutral (ζ < −1 mV) as expected from a highly branched OEGMA containing copolymer.The impact of loading EFV or LPV into the castor oil on nanoemulsion formation was monitored and no appreciable change in the polydispersity of the sample or the was seen  with onl50) values of 0.98% w/v and 2.9% w/v against HepG2 and Caco-2 cells respectively indicating very low cytotoxicity against these cell types. When assessing the unloaded and drug-loaded nanoemulsions against Caco-2 cells, and comparing to aqueous/DMSO solutions of the drug compounds, the EFV drug control exhibited an CC50 value = 55 μM but all other tests showed no overt cytotoxicity over the concentration ranges tested, demonstrated by the non-convergence of sigmoidal dose response curves -2,5-diphenyltetrazolium bromide (MTT) assay which employs the reduction of MTT to formazan to establish changes in mitochondrial enzyme activity Fig. S5. The bras Fig. S6. Againsts Fig. S6.Papp) of the candidate drug-loaded nanoemulsions were determined using the Caco-2 cells after forming a confluent monolayer, with tight junctions between the cells (confirmed by TEER), on a porous transwell membrane; this is a widely-used model for oral absorption.34 Within this assay, the cells polarise to present microvilli on the gut  side of the cells,35 reproducing the morphology and function of the small intestine. The blood  side of the cells models the interface with the systemic circulation.The apparent permeability (Papp of the nanoemulsion containing EFV showed no significant difference in gut to blood permeation after 1 hour but a significantly higher Papp after 2 hours (p ≤ 0.05)   ≤ 0.05) .Papp (p ≤ 0.05) was seen after 2 hours of the experiment compared to the aq/DMSO drug solution control. This is a highly interesting result as LPV is very poorly-absorbed in vivo and is a known substrate for a range of drug transporters found within the intestine and modelled in Caco-2 cells;36 efflux transporters, such as P-gp,37 actively pump drugs back into the gut (often against a concentration gradient), negatively impacting bioavailability. The nanoemulsion appears to enable the passage of LPV through the epithelial barrier whilst effectively hiding the drug from, or inhibiting, a range of potential mechanisms acting on the free drug compound.The nanoemulsion conferred a considerable impact upon the behaviour of LPV, where almost an order of magnitude higher A → B Papp in the basolateral to apical (B → A) direction is also critical to understand as the balance of B → A/A → B permeation provides a more accurate determinant of predicted bioavailability. The EFV-loaded nanoemulsions exhibited significantly lower B → A permeation than the aq/DMSO drug solution for both 1 hour  direction, which models absorption from the gut to blood, but in vivo absorption necessitates assessment of antiviral activity of the ARV-containing droplets and this was undertaken using HIV-1 IIIB-infected MT4 cells. EFV and LPV intervene at different points within the replication cycle with EFV inhibiting reverse transcription of the viral RNA, and LPV inhibiting protease-mediated maturation of virions. Importantly, the experiment conducted here is in the presence of cells with ongoing viral replication, therefore at least for EFV the drug must enter the cell to show any inhibition of further replication. Activity against the virus was determined by using an MTT cell viability assay to assess the number of live cells as viral replication leads to cell death.The potential ability to enhance the oral permeability of the antiretroviral drugs LPV and EFV may lead to increased drug absorption and a subsequent decrease in oral dose required to treat HIV patients. Drug permeation through the gut model employed here provides no information about whether free drug or intact nanoemulsions have traversed the epithelium. The potential for nanoemulsions entering the systemic circulation after 50 value of 0.25 μM (50 = 0.46 μM (2 significant figures)  was very similar to the EFV-loaded nanoemulsion with an IC 0.25 μM ; both thfigures) . Unloade39–41Nanoemulsions offer the potential to dissolve poorly-water soluble drugs within oils that are typically used in food products and overcome the poor gut absorption that is often associated with such compounds. A successful oral drug delivery system based on nanoemulsions needs to exhibit a range of important factors including: (1) ready and reproducible emulsion formation; (2) stability on storage; (3) significant drug loading; (4) low toxicity; (5) retention of drug activity (in emulsion and released drug formats); and (6) facilitation of drug passage across natural barriers. Here we have demonstrated much of what would be required to justify significant additional research as the system that was designed and studied has accomplished not only the above criteria but an additional benefit is the resistance to dilution as this not only offers stability within the body after administration (if absorbed intact) but also the potential for ready dose adjustment for individual patients, especially in a paediatric setting where there is limited availability to appropriate dosage forms.in vivo, and whether the nanoemulsions traverse the gut model  as intact droplets. If this is the case, the possibility of generating circulating nanoemulsion droplets after oral administration provides further bespoke opportunities for future research. Mechanistically, the exact route that the drug has taken to traverse the epithelium is unclear. One possibility is that the surrounding branched polymer presents a considerable amount of bound water and a near-neutral ζ that the nanoemulsion does not invoke any direct efflux response by the cells and, by encapsulating the drugs within the oil phase, they may be effectively smuggled across the membrane. Other possibilities include localised high concentrations of drug being released from the oil-phase or paracellular diffusion (between cells) of the nanoemulsion droplets. The drug-specific nature of the benefits seen for LPV, over the EFV comparative nanoemulsions, does suggest that this may be the overcoming of drug-related constraints but this is yet to be confirmed.Several aspects of this candidate therapeutic option are yet unstudied, including whether such benefits can be achieved in vivo confirmation of the in vitro studies presented here.Further work is needed to confirm the biocompatibility and safety of this nanoemulsion system, to understand the mechanistic aspects of the observed benefits and to establish JJH, SE, AO and SR are co-inventors of patents related to emulsion and nanoemulsion drug delivery.RA-008-C8RA01944D-s001