DNA barcode reference libraries are now continuously produced for the tree of life, which are essential pillars for the study of biological diversity. Yet, our knowledge about global diversity is largely limited in undersampled regions such as the largest warm desert, the Sahara-Sahel. This dataset provides a DNA barcode reference library for the reptiles of the Western Sahara-Sahel (WSS) and neighbouring countries across this region. It includes 760 barcodes from 133 reptile taxa, distributed in 23 families, and covering the intraspecific diversity of some species. A total of 84 species were collected in the WSS  over 18 overland field expeditions conducted since 2003. DNA barcodes resulted in a high success rate (95%) of species identification and barcoding gap analysis highlighted the effectiveness of the COI fragment as a barcode marker for the WSS reptiles. This dataset represents a comprehensive and reliable DNA reference library for the WSS, filling an important biodiversity gap across a remote and hard-to-sample region.  Yet, the knowledge available about overall global biodiversity is very limited3 because many species have not been formally described, and certain geographic regions are still undersampled, which results in underestimation of biodiversity loss4. The Sahara Desert, together with the neighbouring arid Sahel, is the largest warm desert in the world and both represent two major ecoregions of the African continent, covering about 11,230,000 km2 5. Molecular taxonomy studies developed over the last decade within the Sahara-Sahel highlighted the need of urgent research to identify the hidden vertebrate diversity present in this arid and remote region7.Global biodiversity is currently undergoing an unprecedented crisis5 , with representatives from several ecoregions , making it one of the richest vertebrate groups in this region. Recent molecular studies have detected cryptic diversity in several reptile groups17, suggesting that a significant amount of diversity remains undescribed. This is mainly due to the extensive information gaps regarding local species richness and individual species across this remote and hard-to-sample area6, and is particularly important in the local biodiversity hotspots occurring in the mountains scattered across this region, which has been identified as priority for the conservation of Sahara-Sahel biodiversity19.The West Sahara-Sahel (hereafter WSS) spreads across Mauritania and southern Morocco and represents a transition zone between the Palaearctic and Afro-tropic biogeographical realms5 Fig. , acting 20. For this purpose, DNA barcoding comes as a fast and cost-efficient method that uses a single, short, standardized, and highly variable genetic marker for species identification and discovery in groups where mitochondrial DNA (mtDNA) is species-specific21. The Consortium for the Barcode of Life  aims at retrieving a DNA barcode for every species on Earth and lead to the development of numerous barcoding initiatives, including the ColdCode that aims at barcoding all herpetofauna22. This initiative established the widespread use of cytochrome c oxidase 1 (COI) mitochondrial marker for barcoding studies, resulting in the discovery and assessments of herptile diversity across the globe23, including the amphibians of the WSS7. DNA barcoding can thus aid to bridge the knowledge gap in poorly studied areas by providing means to understand local species diversity24. Rapid assessments of biodiversity are extremely important in current conservation decision-making25.An overall genetic assessment of the reptile diversity occurring in the WSS will help to: i) identify potential cryptic diversity; ii) study evolutionary and landscape processes associated with biodiversity distribution; and iii) contribute to the conservation planning of regional reptile diversityThis work represents the first DNA barcoding study of the reptiles in the WSS, which aims to: 1) establish a COI reference barcode library for the WSS reptiles; 2) assess the effectiveness of the barcode library for specimen identification using distance-based methods; and 3) identify possible candidate cryptic reptile species.2) includes nine terrestrial ecoregions5 with scattered scarps-like mountains separating sandstone plateaus . GenBank sequences from WSS taxa, within (N = 3) or outside the study area , and closely related species were also retrieved to aid barcoding gap analysis, which rely on the difference between maximum intraspecific and minimum interspecific genetic distances.A total of 18 overland field expeditions to WSS were conducted between 2003 and 2020 to collect samples. Field missions were developed annually, from September to December except in 2009 and 2017 (March-May) and 2015 (August). Given the remoteness of the study area and the danger of travelling in some regions  were performed in sterile and isolated rooms under special conditions optimized for the manipulation of low-quality DNA.Total genomic DNA was extracted using the QIAGEN EasySpin Kit or the QIAGEN QIAmp® DNA MicroKit for the samples for which the amount of tissue was limited. For samples where we expected DNA of low quality , the QIAGEN DNeasy Blood &Tissue Kit was used following manufacturer’s instructions. DNA from museum samples was extracted following an optimized protocolhttp://www.boldsystems.org). A COI fragment was amplified using degenerate primers RepCOI-F  and RepCOI-R 34, except for samples of Acanthodactylus scutellatus, Pristurus adrarensis and Philochortus zolii, and some samples of Acanthodactylus longipes, Acanthodactylus taghitensis and Chalcides delislei where COI was amplified with the universal primers LCO1490  and HC02198 35. A touchdown PCR was performed with the following conditions: initial denaturation at 95 °C for 10 min, followed by an initial phase of 9 cycles of 40 s of denaturation at 95 °C, 30 s of annealing at 52 °C with a decrease in the annealing temperature by 0.5 °C per cycle until the 48 °C, and extension at 72 °C for 45 s, and then followed by a second phase with 31 cycles of 40 s of denaturation at 95 °C, 30 s of annealing at 48 °C, and elongation during 45 s at 72 °C, and a final extension cycle of 10 min at 72 °C. Adjustments of the temperature gradients were done for some species. Quality of PCR products were checked by visual examination in electrophoresis using 2% agarose gel. PCR products were outsourced for Sanger sequencing to Beckman Coulter Genomics . The sequence chromatograms were visually inspected, assembled, and edited using Geneious Pro v.4.8.5 (Biomatters Ltd.). Sequences were aligned using the MUSCLE version implemented in Geneious Pro v.4.8.5 (Biomatters Ltd.) under default settings36. All sequences were translated into amino acids to aid the alignment, and were checked for stop codons to detect the presence of nuclear DNA pseudogenes (NUMTs). Once the absence of NUMTs were confirmed, the sequences were trimmed to the same length.We used the cytochrome c oxidase 1 (COI) mitochondrial marker, which is the standard barcoding marker for animals  and in BOLD (Ref: REWSS).This reference library contains the following information: 1) Specimen ID; 2) Species ID; 3) Georeferenced data  associated to each specimen collected in the field; 4) sampling date); 5) DNA barcode of each specimen; 6) Institution storing vouchers or tissue/DNA for each specimen; and 7) Photographs of live specimens collected in the field. A specimen was considered as reference for subsequent analysis and interpretation of results when the same identification was obtained from both molecular and morphological assessments. It also contains notes on the taxonomic ID for those specimens in which molecular and morphological identifications disagreed. All data associated with this study is hosted at Figshare8). These included: 1) 419 samples from 63 species known to occur in the WSS, collected within the study area; 2) 285 samples of WSS taxa collected outside the study area or lacking spatial reference; and 3) 56 samples from 46 outgroups (i.e. sister/close neighbours of WSS taxa). Samples were selected for analyses in order to cover the described taxonomic diversity and known geographic distribution of each taxon within the WSS, and represent 83% of the total reptile species richness described in the region32 (Sample list8). A total of 472 specimens were identified morphologically to the species level based on external diagnostic characters, from which 376 specimens were sampled in the WSS (Sample list8). Specimens where identification to species was not possible (documentation too poor or species pairs too difficult to identify from photos) were not treated as reference samples.A total of 760 barcode sequences from 133 reptile taxa distributed in 23 families were analysed  without regarding the genetic identification nor the geographic origin of the sample. Then, after listing the disagreements in identifications, the sequences and the voucher specimens or pictures were revised a second time to search for possible mistakes in the original identifications. Obvious mistakes in identification or in curation (mixing of photos for example) were corrected, in all other cases the mismatch between genetic and morphological identification was recorded as such.37 to estimate the largest intraspecific distance and the smallest interspecific distance using the statistics maxInDist and nonConDist, respectively, which are implemented in the R package spider v.1.338. We found the presence of a barcoding gap in 92% of the samples, with a lack of barcoding gap in Chalcides delislei, Malpolon moilensis, Spalerosophis diadema and Tarentola mauritanica. We also identified a lack of barcoding gap in samples of Acanthodactylus longipes Agama agama, Dasypeltis scabra and Spalerosophis diadema . Intraspecific genetic distances ranged from 0% to 20.7% . A 2.1% minimum interspecific divergence was found between Crocodylus suchus and C. niloticus.To assess the robustness of our library and detect potential cryptic diversity in our dataset (excluding outgroups), we first evaluated the existence of a barcoding gap. A barcoding gap exists when the maximum intraspecific distance of each species is lower than its minimum distance to the nearest neighbour, and thus allows to evaluate the performance of the COI marker as a barcode, but also unveil cryptic diversity. A pairwise distance matrix was first calculated between sequences using the Kimura 2-parameter model (K2P)39) as implemented in spider. These two methods use a threshold based criterion that compares all specimens within the threshold of the query, and then assigns a diagnosis to each identification query: i) “correct match” ; ii) “incorrect match” (i.e. closest match is a different species of the query); iii) “ambiguous match” (i.e. both correct and incorrect species matches within the threshold), and (iv) “no identification” (i.e. no species is identified within the given threshold). We explored a range of threshold values (1%–7%) before choosing the threshold value that minimized the cumulative error . Preliminary analyses indicated 5% as the most suited threshold for specimen identification .We also tested for barcoding efficiency (i.e. assignment of barcodes to the species level) in our dataset (excluding outgroups) using two query identification analyses based on genetic distance thresholds. We used the BOLD and Meier’s best close match functions . Our results suggest potential cryptic diversity at least in the following taxa (showing > 10% of intraspecific divergence): Acanthodactylus boskianus, Acanthodactylus longipes, Acanthodactylus taghitensis, Agama boulengeri, Chalcides delislei, Chalcides ocellatus, Latastia longicaudata, Lytorhynchus diadema, Malpolon moilensis, Mesalina guttulata, Ptyodactylus oudrii, Spalerosophis diadema, Stenodactylus mauritanicus, Stenodactylus sthenodactylus, Tarentola chazaliae, Tarentola ephippiata, Tarentola mauritanica, Tarentola parvicarinata, Trachylepis perrotetii and Tropiocolotes tripolitanus.The lack of barcoding gap in a handful of species and the high levels of intraspecific diversity unveiled in a high number of taxa pinpoints the urgent need of further studies and taxonomic re-evaluation of some groups across the WSS, as it has been recently done for other reptiles . We confirmed that COI is a reliable tool for specimen identification in most species of reptiles in our dataset.The main issue with mtDNA barcoding as a tool for specimen identification is the possibility that mtDNA is not species-specific, due to either lack of complete lineage sorting or mtDNA gene flow (introgression) after speciation. Very few barcoding studies explicitly examine this issue by careful identification of specimens independently of genetic results. Here, we evaluated the diagnostic power of COI barcodes by comparing morphological and barcode identification in most specimens (labelled “reference” in Sample listStenodactylus sthenodactylus and S. mauritanicus) or species complexes (e.g. Acanthodactylus scutellatus complex), reliable morphological identification from photographs is not possible in all specimens and discordance are more likely to result from morphological misidentifications than mtDNA lineage sharing. Indeed, a recent study combining mtDNA and nuclear data found no instance of mtDNA lineage sharing between species in the A. scutellatus complex.In a few species pairs . In other cases, the discordances involve taxa where species-level systematics and species limits remain poorly understood and our results are difficult to interpret: Trapelus boehmei and the extralimital T. mutabilis or the Tarentola ephippiata complex .A few (probably) real discordances between morphological and molecular identification remain after discarding possible morphological misidentifications. In one case, such discordance suggests mitochondrial introgression events between sister taxa across contact zones: Agama agama would match samples of Agama picticauda in Genbank because of the confused nomenclatural situation in the Agama agama complex. We totally agree with the interpretations of a molecular study41 that considers the neotype designation for Agama agama42 as invalid, and accept their conclusion on the origin of the lectotype of A. agama. As a consequence, we regard Agama agama as the valid name for the widespread species of the complex in Western African and treat Agama picticauda as a junior synonym of Agama agama.Last, nomenclatural instability is another source of confusion when using barcodes for specimen identification. Our samples of


An amorphous drug–polymer salt (ADPS) can be remarkablystable against crystallization at high temperature and humidity  and provide fast release. Here, we report that processconditions strongly influence the degree of proton transfer  between a drug and a polymer and in turn the product’sstability and release. For lumefantrine (LMF) formulated with poly(acrylicacid) (PAA), we first show that the amorphous materials prepared byslurry conversion and antisolvent precipitation produce a single trendin which the degree of drug protonation increases with PAA concentrationfrom 0% for pure LMF to ∼100% above 70 wt % PAA, independentof PAA’s molecular weight . Thisprofile describes the equilibrium for salt formation and can be modeledas a chemical equilibrium in which the basic molecules compete forthe acidic groups on the polymer chain. Relative to this equilibrium,the literature methods of hot-melt extrusion (HME) and rotary evaporation(RE) reached much lower degrees of salt formation. For example, at40 wt % drug loading, HME reached 5% salt formation and RE 15%, bothwell below the equilibrium value of 85%. This is noteworthy giventhe common use of HME and RE in manufacturing amorphous formulations,indicating a need for careful control of process conditions to ensurethe full interaction between the drug and the polymer. This need arisesdue to the low mobility of macromolecules and the mutual hindranceof adjacent reaction sites. We find that a high degree of salt formationenhances drug stability and release. For example, at 50% drug loading,an HME-like formulation with 19% salt formation crystallized fasterand released only 20% of the drug relative to a slurry-prepared formulationwith 70% salt formation. Based on this work, we recommend slurry conversionas the method for preparing ADPS for its ability to enhance salt formationand continuously adjust drug loading. While this work focused on saltformation, the impact of process conditions on the molecular-levelinteractions between a drug and a polymer is likely a general issuefor amorphous solid dispersions, with consequences on product stabilityand drug release. A recent progress in this area is the formulation of amorphousdrug–polymer salts (ADPS).7 An ADPS isformed by the acid–base reaction between a small-molecule drugand an oppositely charged polyelectrolyte. Relative to an ASD of neutraldrug and polymer, an ADPS is more stable in a hot and humid environment,a need for many medicines for global health. This enhanced stabilityresults from the strong ionic interaction between a drug and a polymer,which reduces the driving force for crystallization, and from thedifficulty for the drug and the polymer to form a co-crystal. Theincrease of thermodynamic stability, at first glance, suggests reducedsolubility, but excellent dissolution performance has been observedin biorelevant media for lumefantrine (LMF) and clofazimine (CFZ)formulated with poly(acrylic acid) (PAA)  and 15% protonated by rotaryevaporation (RE). These values indicate very low degrees of salt formationand a significant effect of the process condition. This effect isperhaps not surprising given the large size and low mobility of polymers,making a drug–polymer salt slower to form than a salt of smallions. In this work, we confirm the critical role of the process conditionin forming a drug–polymer salt and demonstrate that nearlycomplete salt formation is possible under proper conditions.For an ADPS, the extent of acid–basereaction is a criticalquality attribute. For a basic drug like LMF or CFZ, this refers tothe fraction of the molecules that are protonated by an acidic polymer.Song et al. reported significant variation in the fraction of LMFmolecules that were protonated by acidic polymers depending on theprocess condition.10 spray drying11 (SD), and RE.13 Our recent work introduced a low-cost slurry conversion method forsynthesizing ADPS.6 In this method, a physicalmixture of the drug and the polymer is stirred in the presence ofa small amount of solvent, which is then removed. Compared to SD andRE, this method uses less solvent and does not require complete dissolutionof the reactants; compared to HME, it uses a lower temperature, thusapplicable to thermally labile polymers such as PAA. In this work,we apply the slurry method to prepare the amorphous salt of LMF andPAA and compare the product with those prepared by HME and RE.8 In addition, antisolvent precipitation is testedas another method of preparation.15Many methods have been used to prepare ASDs, including HME,16 Being a malaria medicine,LMF formulations should be stable under tropical conditions sincemany regions afflicted by malaria are hot and humid. This requirementcan potentially be met using the approach of amorphous drug–polymersalts. As a weak base, LMF can be protonated by an acidic polymerlike PAA.8 Hiew et al. investigated amorphousLMF formulated with several polymers.17 Their work did not include PAA and did not consider the impact ofthe process condition on LMF protonation, which are the focus of thisstudy.Lumefantrine(LMF), the model drug of this study, is a low-solubilityWHO Essential Medicine and first-line antimalarial. Jain et al. haveshown that the bioavailability of LMF can be improved through an ASDformulation.8 highlighting the importance of process conditions in completingthe proton transfer between the drug and the polymer. We find thata high degree of salt formation leads to improved stability and drugrelease.We report that the amorphous formulations of LMF andPAA preparedby slurry conversion and antisolvent precipitation form a single trendwhere the degree of drug protonation increases with PAA concentrationfrom zero for pure LMF to ∼100% above 70 wt % PAA. This profileholds regardless of the synthetic method and the PAA molecular weight and thus describes the equilibrium conditionfor salt formation. Remarkably, the slurry conversion method achievedmuch more complete salt formation than HME and RE,MW = 1.8, 450, 4000 kg/mol) was purchased fromSigma-Aldrich , lumefantrine (LMF) from Nanjing BilatchemIndustrial Co. , dichloromethane (ChromAR grade) fromThermo Fisher Scientific , and ethanol from Decon Laboratories. All materials were used as received.Poly(acrylic acid) , a reduced temperature of 25 °C was tested and wefound that the products prepared after 30 min of reaction at 25 °Cshowed similar degrees of protonation as those prepared at 75 °C.The products were ground in an agate mortar with a pestle to a fineuniform powder prior to further analysis. For PAA of higher MW (450 and 4000 kg/mol), a reaction with LMFwas performed using both the slurry method of Yao et al.1 and another method with more vigorous mixing.In the latter method, a physical mixture of LMF and PAA at a chosendrug loading  was combined with the solvent  at a 4:1 solvent/solid ratio. The resulting paste wasmilled in a ball mill . The containerof the mill was a 25 mL capacity steel jar with five 5 mm stainlesssteel balls. The mill operated at 20 Hz and the milling time was 30min. The milling was performed at room temperature, and the internaltemperature was measured immediately after milling with an IR thermometer.The increase of the internal temperature was less than 5 °C.The slurry synthesis of amorphousLMF-PAA has been described by Yao et al.To assess the effect of the degree ofsalt formation on formulation performance, amorphous LMF-PAA was preparedusing a melt-quench method to simulate HME. A physical mixture ofLMF and PAA 450 kg/mol was prepared at 50 wt % drug and heated to135°C while stirring with a stainless steel spatula to mimicHME. The heating time was ∼4 min. The melt was cooled to roomtemperature by contact with an aluminum block. The product was groundin an agate mortar with a pestle to a fine powder before further analysis.A solution of LMF in acetone(50 mg/mL) was added to an aqueous solution of PAA (3.5 mg/mL) underagitation via a magnetic stir bar, causing precipitation. The precipitantwas filtered using Whatman Grade 2 Qualitative Filter Paper and driedunder vacuum overnight at room temperature and ground in an agatemortar with a pestle to a fine powder before further analysis.X-ray diffraction patternswere collected using a Bruker D8 Advance X-ray diffractometer witha Cu Kα source operating at a tube load of 40 kV and 40 mA.A powder sample (∼10 mg) was spread and flattened on a Si (510)zero-background holder and scanned between 3 and 40° (2θ)at a step size of 0.02° and a scan rate of 1 s/step.18 For an amorphous LMF-PAA formulation, approximately5 mg of powder was pressed into a tablet using a stainless steel press.For a sample of pure LMF, approximately 1 mg of LMF powder was meltedon a glass coverslip and quenched to room temperature by contact withan Al block. The samples were stored in a sealed plastic tube filledwith Drierite before analysis. The high-resolution spectrum of theN atom was used to measure the fraction protonated of LMF. For eachsample, the N spectrum was recorded in duplicate in two separate regions.Curve fitting was performed using the program Origin following smartbaseline subtraction.The detailsof XPS measurement and data analysis have been described previously.6Solubility tests were performed in simulatedgastric fluid (SGF). The details of sample preparation, data collection,and analysis have been described previously.6 that theglass transition temperatures of these materials were significantlyelevated relative to those of the pure components (17 °C forLMF and 126 °C for PAA), consistent with salt formation; forexample, at 50 wt % drug loading, the Tg exceeded 130 °C. The pure drug, a free base, shows a singlepeak at 399 eV, corresponding to the unprotonated amine N. With increasingPAA concentration (decreasing drug loading), this peak decreases anda new peak emerges at 401.5 eV. The new peak corresponds to the protonatedamine group.19 Together, the spectra in AP and AN are the areas of the protonated and the neutralN peaks, respectively, obtained by curve fitting  prepared by slurry conversion. For each MW grade, the fraction protonated is plotted against drugloading. For PAA 1800 g/mol, the results correspond to the productsof the standard slurry synthesis.6 Forhigher-MW PAA grades, the results correspondeither to the products of the standard synthesis or to those preparedwith more vigorous mixing. As discussed below, for formulations ofhigh polymer content, enhanced mixing was needed to complete the protontransfer. The data in MWs. This indicates thatthe acid–base reaction between LMF and PAA had reached equilibrium.Had the degree of salt formation been limited by kinetics, the larger,less mobile polymer would be slower to react, resulting in less completesalt formation. The simplest explanation for the “master curve”in w0 = 88 wt % corresponds to one LMF molecule (MW = 528.9 g/mol) per PAA monomer (MW = 72.1 g/mol). The observed profile indicates that even whenPAA monomers are in excess, not every monomer can react with a drugmolecule.6 This occurred at higher PAA MW and higher PAA concentration. We illustratethis in MW grade, significantgelling occurred upon addition of the solvent, making stirring difficultand the reaction less reproducible. In As noted above, some formulations required more vigorousmixingto reach reaction equilibrium than utilized in the standard slurrysynthesis.9 In thismethod, each component was dissolved first (LMF in acetone and PAAin water) and the mixing of the two solutions induced precipitation.The precipitant was confirmed amorphous by XRD. As in the case ofslurry conversion, antisolvent precipitation was performed using PAAof different MWs at different drug/polymer ratios that corresponded to 25, 50, and75% drug loading. This “bottom-up” method, in principle,enables more complete mixing of the reactants than a “top-down”method like HME and slurry conversion. An issue with the precipitationmethod, however, is the unknown composition of the precipitant sincesome reactants may remain dissolved in the supernatant. In contrast,the composition of a slurry-prepared product is known from the initialamounts of the ingredients because no ingredient is lost in the one-potsynthesis. For this reason, the drug concentration in a precipitatedproduct must be determined and we did so by XPS from the N/O atomicratios as described previously  of Strotman and Schenck.eviously 2.18MWs since the data cluster together. Similarly,for the precipitated products, the PAA MW had no significant effect on the degree of protonation observedand we simply plot the results together without distinguishing thePAA MWs. w0 (one LMF molecule per PAA monomer).In Despite their narrower range of composition, theproducts of antisolventprecipitation join the same trend as those prepared by slurry conversion.This single trend supports the idea that both methods reached theequilibrium for the proton transfer between the drug and the polymer.Consistent with this view, an equilibrium reaction model yields afitting curve that accounts for the observed data (see below). Betweenthe two methods, slurry conversion provided continuous tunabilityof drug loading, whereas antisolvent precipitation yielded productsof only high drug loading. For this reason, slurry conversion is themore versatile of the two and the method of choice for the remainderof this work.8 In addition, a melt-quenchformulation from this work is included. For a fair comparison, allthese materials were prepared with PAA of the same MW (450 kg/mol). All the % protonated values in In To investigate salt formation by HME, we preparedan amorphousformulation of LMF and PAA under conditions that mimic HME. This formulationwas prepared at 50% drug loading using PAA 450 kg/mol; the ingredientswere melted together and stirred in the molten state. This formulationreached 19% protonation and if is its activity coefficient. Aneffective equilibrium coefficient can be definedK isa constant independent of the concentrations. But since the activitycoefficients if in general depend on concentrations,so does Keff. Keff at each drug loading from the % protonationvalue. We find that Keff increases exponentiallywith xa0, the total AA monomer mole fraction. While this increase can arise from theconcentration dependence of all three activity coefficients, we speculatethat the coefficient for the AA monomer fa makes the largest contribution. At a low polymer concentration,LMF molecules must compete for the reaction sites on the same polymerchain. This would be difficult, and an average AA monomer would havea low probability to react with LMF (low activity). At a high polymerconcentration, many acidic groups are available to react with LMF,leading to a high probability of reaction (high activity). To generatethe fitting curves in Keff as a parameter.In addition, we assume that Keff has anexponential dependence on xa0: Keff = K0 + α exp(β xa0), where K0, α,and β are fitting parameters. The good fits obtained supportthe conclusion that slurry conversion and antisolvent precipitationcan achieve the equilibrium of proton transfer between LMF and PAA.Here, wedescribe a model for the equilibrium protonation profile of LMF byPAA, which was used to generate the fitting curves in MW (450 kg/mol), but different degrees of saltformation. By slurry synthesis, we prepared a material with 70% protonation,and by melt quench, a material with 19% protonation. To investigate the effect of salt formation on formulation performance,we studied the stability and dissolution of two amorphous LMF-PAAformulations that had identical drug loading (50 wt %) and PAA 6 whereas the melt-quenchedmaterial crystallized significantly after 30 days. This is fully consistentwith our understanding of the effect of drug–polymer salt formationon stability. The salt formation between a drug and a polymer reducesthe crystallization driving force to a greater extent than the mixingof a neutral drug with a neutral polymer. This comparison indicatesthe positive effect of more complete salt formation on stability.6 and CFZ7 formulated with PAA.Others have studied amorphous LMF formulations with polymers,21 and for a series of polymers (excluding PAA), Hiew et al. notedthat RE-prepared formulations containing protonated LMF tend to bemore stable against crystallization but have worse dissolution performance.17 Their conclusion agrees with ours with respectto stability but not dissolution. To understand this, we note thatthe polymer of our formulation, PAA, was not in their study and couldbe an outlier for their trend. In addition, the dissolution mediumis SGF in this study, but a phosphate buffer in their study. Furtherwork is warranted to develop a unified understanding.That the salt formation between LMF and PAA cansimultaneouslyenhance stability and drug release might seem counterintuitive sincehigh stability often leads to low solubility. In previous work, thisdual enhancement has been observed for both LMFMWs (1.8–4000kg/mol) have similar ability to protonate LMF. We now show that ata lower MW, PAA could have a greater protonatingpower. MW at a fixed drug loading of 75%. At this drug loading,the polymer formulations show a similar degree of salt formation,∼50%. We use maleic acid (MW =116.07 g/mol) as a mimic for a dimer of AA. An amorphous salt of LMFand maleic acid was prepared using a solvent evaporation method22 and was found to contain LMF that was 85% protonated.This suggests a possible increase of protonating power below MW ∼1 kg/mol. One explanation for thiseffect is that LMF is a larger molecule than a PAA monomer and bindingto one monomer on a polymer chain blocks access to the adjacent monomers.For a free-moving dimer, however, this crowding effect is less severe.Despite this potential increase of protonating power at low MW, we do not advocate the use of a small-moleculecounterion for salt formation because we would lose the stabilizingbenefit of a polyelectrolyte. Yao et al. showed that amorphous particlesof LMF formulated with PAA 450 kg/mol at 50 wt % drug loading remainedfree-flowing after 540 days at 40 °C and 75% R.H.6 In contrast, the same formulation prepared with maleicacid became a viscous liquid after 1 day under the same condition.This is a consequence of a large increase in the glass transitiontemperature of LMF by PAA while the same stabilizing effect is notachieved with an AA dimer.The results in 7 Both formulations were prepared using the slurrymethod with PAA 450 kg/mol. Gui et al. determined the degree of saltformation in CFZ-PAA by visible absorption spectroscopy, taking advantageof the color change of CFZ upon protonation. At the same drug loading,CFZ is protonated to a greater extent than LMF. CFZ is almost fullyprotonated below 60 wt % drug loading, whereas LMF does so below 30wt % drug loading. This demonstrates the important role of the drugmolecule in the degree of salt formation that can be reached. It isunclear why CFZ is more easily protonated by PAA than LMF. The literaturepKa values for the two molecules are 8.5for LMF,8 and 8.4 . In the crystal structure of CFZ with citricacid, this site is observed to form a hydrogen bond with a carboxylicacid group without ionization, while the primary site is protonatedand forms a hydrogen-bonded ion pair with a carboxylate ion.25 Similar multisite interactions could occur inCFZ-PAA, possibly aiding salt formation. It is interesting to notethat in the crystals, the protonated LMF and CFZ each form a cyclichydrogen-bonded ion pair with a carboxylate ion. In the fumarate saltof LMF, the ammonium group and the adjacent OH group form a cyclichydrogen bond with both oxygen atoms of the carboxylate ion.26 In the carboxylate salts of CFZ, the imine Nand the adjacent NH group are both hydrogen-bonded with one of theO atoms of the carboxylate ion.26 It ispossible that similar hydrogen-bonded ion pairs occur in the amorphousphase of LMF-PAA and CFZ-PAA.8.4 (ref ) and 9.38.4  and the rulewould predict proton transfer. Experimentally, we find that protontransfer does occur in these two systems, but the degree of protontransfer depends strongly on drug loading  requiredmore vigorous agitation to complete salt formation, especially whenpolymer concentration was high. Although this work focused on a systemin which the drug and the polymer can ionize each other, the stateof mixing is likely a general issue in developing amorphous soliddispersions, with strong impact on product performance.This work has provideda vivid illustration of the extremely differentphysical states that an amorphous drug–polymer formulationcan have because of a change in manufacturing method and process condition.The amorphous nature of a formulation might give the impression thatthe ingredients are uniformly mixed. But for the system studied here,the drug and the polymer can be almost fully reacted to form a saltor barely reacted at all, depending on the method of preparation 6. This t


Obesity and overweight are major risk factors for several chronic diseases. There is limited systematic evaluation of risk equations that predict the likelihood of developing an obesity or overweight associated complication. Predicting future risk is essential for health economic modelling. Availability of future treatments rests upon a model’s ability to inform clinical and decision-making bodies. This systematic literature review aimed to identify studies reporting (1) equations that calculate the risk for individuals with obesity, or overweight with a weight-related complication (OWRC), of developing additional complications, namely T2D, cardiovascular (CV) disease (CVD), acute coronary syndrome, stroke, musculoskeletal disorders, knee replacement/arthroplasty, or obstructive sleep apnea; (2) absolute or proportional risk for individuals with severe obesity, obesity or OWRC developing T2D, a CV event or mortality from knee surgery, stroke, or an acute CV event.Databases (MEDLINE and Embase) were searched for English language reports of population-based cohort analyses or large-scale studies in Australia, Canada, Europe, the UK, and the USA between January 1, 2011, and March 29, 2021. Included reports were quality assessed using an adapted version of the Newcastle Ottawa Scale.2) and lacked external validation. The remaining included studies (31 studies) reported the absolute or proportional risk of mortality (29 studies), or the risk of developing T2D in a population with obesity and with prediabetes or normal glucose tolerance (NGT) (three studies), or a CV event in populations with severe obesity with NGT or T2D (three studies). Most reported proportional risk, predominantly a hazard ratio.Of the 60 included studies, the majority used European cohorts. Twenty-nine reported a risk prediction equation for developing an additional complication. The most common risk prediction equations were logistic regression models that did not differentiate between body mass index (BMI) groups (particularly above 40 kg/mMore work is needed to develop and validate these risk equations, specifically in non-European cohorts and that distinguish between BMI class II and III obesity. New data or adjustment of the current risk equations by calibration would allow for more accurate decision making at an individual and population level.The online version contains supplementary material available at 10.1186/s13098-022-00952-4. Obesity is a disease in its own right but also a major risk factor for several chronic diseases, including type 2 diabetes (T2D), cardiovascular (CV) disease (CVD), particularly heart disease and stroke, musculoskeletal disorders, fatty liver disease, hypertension, and some cancers . Obesity2). A BMI between 25 and 29.9 kg/m2 is classified as overweight and obesity as a BMI greater than or equal to 30 kg/m2, further subdivided into class I (30.0–34.9 kg/m2) and class II (35.0–39.9 kg/m2) [2 is referred to as class III obesity.Obesity and overweight are defined as abnormal or excessive fat accumulation causing a deterioration in health –5. Epide2 was 60% of total obesity-related costs [2 is predicted to rise to one in four adults in the USA, becoming the leading BMI category for certain populations, including women, non-Hispanic Black adults, and low-income adults [Furthermore, obesity imposes an increasing economic burden on society and exacerbates the costs of both obesity-related and unrelated comorbidities . This ised costs . By 2030e adults , 9. Diree adults .2, has been lowered for Asian and South Asian populations to BMI 27.5 kg/m2 or 25 kg/m2 [2 was included in this systematic literature review (SLR) population criteria when a weight-related complication was present.Overweight, a precursor to obesity, significantly increases the risk of developing many complications also related to obesity . The ove25 kg/m2 , 14. To 2 is associated with substantially elevated rates of total mortality due to obesity complications [Very few analyses of populations with class III obesity exist, although a BMI of 40–59 kg/mications . The heaications , 17. Conications , 19.Risk equations can be developed to predict the likelihood of a person with or without a pre-existing condition of developing an associated obesity complication. These equations can help decision making at the patient and health management level. Informative risk equation outcomes hinge on choosing relevant risk predictors. Risk predictors can be lifestyle based , socio-economic , phenotypic , endotypic , as well as health and disease related . Risk predictor usage varies between equations and BMI’s association with the aforementioned diseases make it an obvious risk predictor choice to determine health outcome risk.Greater understanding is required as to how risk equations can be used to reliably predict individual and population-based risk –22. For Weight related risk prediction equations that account for the statistical interaction between BMI levels and other risk predictors with the risk of outcome are of high value, without which risks associated with certain populations will not be accurately predicted in models. In the absence of sensitivity or validation for individuals with high BMI levels, a calibration  of risk equations using current risk estimates from the literature  may lend precision to estimates of health outcomes. We sought to identify reliable risk prediction usage that distinguishes between, and were robust for, all BMI levels.While some studies have sought to predict the risk of weight-related mortality or complication development using risk equations, there has been limited systematic evaluation of these equations. This SLR had two overarching aims, firstly to identify published risk equations for developing obesity and overweight with a weight-related complication (OWRC) associated complications. Second, to identify studies that calculated absolute or proportional risk of individuals with OWRC, obesity, or severe obesity developing specific disease outcomes . This insight will aid economic modelers in developing more accurate predictions of weight-related disease outcomes, which will in turn aid decision makers in evaluating measures that promise to improve health outcomes and reduce the social and economic burden in these populations.A systematic review was undertaken to identify all studies that provide information on the risk associated with people living with obesity or OWRC developing complications. This review was conducted according to the York Centre for Reviews and Dissemination guidelines for conducting reviews  and is rThe following electronic databases were searched as standard evidence sources: MEDLINE, MEDLINE In-Process and e-publications ahead-of-print (via PubMed), Embase (via Embase.com), the technology appraisal submissions to the National Institute for Clinical Excellence (NICE) using risk equations, and bibliographic reference lists from included studies.Searches were conducted on March 25, 2021. All peer-reviewed articles or errata published in the past 10 years (January 2011–March 2021) in Australia, Canada, Europe, the UK, and the USA were included. Only English language studies were included, full inclusion and exclusion criteria are reported in Additional file 2 or BMI ≥ 25 kg/m2 with the presence of at least one weight-related complication. There were no restrictions for interventions or comparators. Studies reported at least one of the following four outcomes: (1) the risk equation which calculated the risk of developing at least one additional complication: prediabetes, T2D, CVD, heart disease (including heart failure with preserved ejection fraction), acute coronary syndrome , stroke, musculoskeletal disorders, knee replacement/arthroplasty, obstructive sleep apnea in a population with obesity or OWRC; (2) absolute risk or proportional risk of developing T2D in a population with obesity and prediabetes or normal glucose tolerance (NGT); (3) absolute risk or proportional risk of having a CV event in a population with class III obesity and NGT or T2D; (4) absolute risk or proportional risk of mortality from knee surgery, stroke, or acute CV events in a population with obesity or OWRC. For outcomes 2–4: complications are T2D, hypertension, dyslipidemia, obstructive sleep apnea, or CVD; absolute risk refers to risk, rate, odds, and hazard outcomes; proportional risk refers to risk ratio, odds ratio, hazard ratio, relative risk, and risk reduction.Included studies reported on adults of ≥ 18 years with a BMI ≥ 30 kg/mStudy selection was conducted independently in duplicate. Disagreement between the reviewers was reviewed by a senior researcher (PGF), who made the final decision on inclusion or exclusion of the record. Quality appraisal and data extraction   , having confounding variables (50), having incorrect population criteria (15), not measuring BMI or not defining obesity, or investigating other diseases (21), and can be found in Additional file Of the 60 included studies, 29 reported risk equations, three reported risk of T2D, three reported the risk of a CV event, and 28 the risk of mortality. All were cohort studies or used data from cohort studies, most (49) were large (> 2000 participants) and 11 were small (< 2000 participants).Twenty-nine included studies reported an equation to calculate the risk of people with obesity or OWRC developing at least one additional complication. Of these, 12 reported equations calculating the risk of T2D , 29–39, The most common risk equations reported were logistic regression models , 52, 55,All equations in the included studies were developed and/or validated using cohort data. These data ranged in terms of cohort size . When individual background was taken into account, both deprivation (17% of studies) and education (14% of studies) were considered as well as income (3%) and family medical history (41%). Smoking was the major lifestyle risk predictor used in 83% of studies, followed by alcohol consumption (28%) and physical activity (28%). Predictors that could alleviate risk such as lifestyle intervention or pharmacotherapy were not included in any study and neither was the metabolic health of people with obesity.The rationale behind why risk factors were selected for the equations varied. The majority reported on their rationale. Tools such as the Framingham or QRISK2 include risk predictors that were used in six studies , 41, 44 2, normal weight 18.5–24.9 kg/m2, overweight 25.0–29.9 kg/m2, obesity class I 30.0–34.9 kg/m2, obesity class II 35.0–39.9 kg/m2, obesity class III ≥ 40 kg/m2) yet only 13 studies used these categories [2 [2 in the baseline characteristics of the cohort used to develop or validate the risk equation or in the outcomes.The use of BMI as a categorization of obesity levels was an inclusion criterion for this SLR, however, the range and granularity of how BMI was included into each equation differed. WHO defines weight according to six BMI ranges  and NGT or prediabetes [Three studies reported the risk of developing T2D in a population with obesity  [2 [Only one study split obesity into multiple categories, BMI 30–34.9 kg/mobesity) , the othsity) [2 . All stusity) [2 , 58.On the NOS quality assessment scale, two of the studies were of low quality 10 stars) , 57 and 0 stars ,Three studies reported the risk of experiencing a CV event in a population with class III obesity and NGT or T2D –61 and wAll studies reported that class III obesity increased the relative risk of a CV event, except in the case of metabolically healthy obesity  where there was no increased risk of MI .Two of the studies were of medium quality 11 stars) , 60 and 1 stars ,Three studies reported the risk of mortality from total knee arthroplasty –64, fourAlmost all studies measured relative risk. Most studies reported risk of mortality increased with higher BMI counts, however, not all studies agreed. Two studies reporting on mortality following total knee arthroplasty showed no association with weight , 64. TheThe NOS rating for the studies on mortality from total knee arthroplasty were all of high quality. Of studies detailing mortality from stroke two were assessed as low quality (10 stars) , 67, oneThis SLR represents the current state on available data for risk equations that can predict the incidence of complications in populations with OWRC and obesity. It further exposes the unmet need for obesity specific equations, the limited ability of these equations to estimate risk for higher BMI categories, and the inconsistency of results between different risk equations on the same populations with OWRC and obesity. There is a clear necessity for new data or adjustment of the current risk equations to allow for more robust health economic modelling that can inform accurate decision-making strategies for the management of people living with obesity and specifically class III obesity.It is important to validate risk equations in external cohorts to assess their usability in different populations and regions . OtherwiOnly six studies reported on external validation of the risk equations , 43, 44 2 and not broken down further. Therefore, it can be assumed that these risk equations may work well up to a certain BMI level before they lose sensitivity. Only 17% of the risk equations detailed the BMI of the cohort used to develop and/or validate the risk equation by obesity class beyond ≥ 30 kg/m2 [2. Even with the lack of risk equation specificity for class III obesity some still calculated the risk of developing a complication more granularly, beyond this point. No explanation or insight was identified for including higher BMI groups into these risk equations, or how, if at all, a presumably small sample within the highest BMI groups was dealt with accurately to create these equations. The representation of each population in the development and validation process lacked clarity. Therefore, the accuracy of the calibration for calculating class III obesity specific risk and the subsequent performance of the risk equation is contentious.A common theme in the literature is the lack of granularity among BMI classes of obesity used to develop or validate the published risk equations. People living with obesity were typically characterized as having a BMI of ≥ 30 kg/m30 kg/m2 , 52, 56.30 kg/m2 , 54, 55.Absolute or relative risks, as identified in this SLR, can be used in calibration of risk equations to improve accuracy in higher BMI populations, or in populations not well represented . Poorly calibrated risk equations can be misleading and potentially harmful in clinical decisions. The identified calibration targets can either be used to calibrate an existing model to better fit populations with obesity or overweight with more precision, or to confirm if new risk equations are robust. Such risk measures can be used as calibration targets in simulations to help optimize risk equation parameters, for example . This apAs for the identified studies reporting absolute or proportional risk for development of T2D, CV events, and mortality in specific populations with obesity or OWRC, those assessing outcome and complication development often failed to distinguish multiple obesity classes and lacked precision. The results of different studies on the same topic were not always in agreement, making it difficult to draw concrete and meaningful conclusions. For example, different studies reported higher, lower, and no association for stroke mortality risk in association with obesity and OWRC –68. AlsoThe choice of risk predictor usage and its weighting depend on the outcome and population of interest. There is not one catch all risk predictor for weight related complications. If we consider patients with T2D, BMI is a strong independent risk factor of heart failure in a stepwise fashion, but not for acute myocardial infarction . In addiWhile not perfect, risk equations have been used to inform both clinical and health technology assessment (HTA) decision making in obesity and overweight . The UK’The studies included in this SLR used risk equations adapted for the target population but not built specifically for them and BMI categories that were inconsistently reported and adhered to, providing limited potential for comparison or accurate risk assessment. The included studies calculating absolute or proportional risk of specific disease outcomes can be built upon to inform more robust risk equations and so, provide more reliable health economic models to aid decision makers.The accuracy of the risk equations when applied to other populations and between BMI classes, in particular class III obesity, remains questionable. The majority of risk equations lacked external validation and those that did only calculated the risk of developing T2D and CVD. The risk equations were largely limited to European cohorts and made little attempt to delineate between obesity classes, particularly with regard to higher BMI groups.This SLR also identified a number of studies reporting absolute risks of developing T2D, CVD or mortality from CVD, T2D, or total knee arthroplasty in populations with obesity and OWRC. Such absolute scores can be used as calibration targets when calibrating risk equations, to help with accuracy in populations with higher BMIs or in subgroups of populations with obesity or OWRC.This SLR has highlighted several gaps to be addressed in future work, with real-world implications. Further work is needed to externally validate equations calculating the risk of populations with obesity or OWRC developing a complication. This should also include validating these equations in diverse populations to ensure generalizability. It should additionally ensure cohorts with obesity are clearly broken down by class, especially focusing on class III obesity, again to ensure accuracy in this population. We identified externally validated risk equations used to predict T2D and CV risk but, particularly for other obesity associated complications, found limited data and further development for all outcomes is required. Other approaches could include utilizing or generating real-world evidence to fill some of the data gaps and recalibrating existing risk equations. This will help to inform robust evaluations of obesity and overweight treatments, HTA decision making, and beyond. More studies informing on the absolute or proportional risk of a wider range of risk factors, specifically for populations ranging from overweight through class I, II, and III obesity, would help to calibrate and improve both existing and new risk equations for these populations.Many of the points raised above can enhance future risk equations and study design. We have discussed in detail the importance of categorising BMI and recommend that future studies harmonise through using, for example, the relevant WHO BMI scales, and avoid grouping weight categories. In addition to identifying specific risk, it will allow individual data sets to be pooled and reanalysed. Additional guidelines could include new risk equations focusing on weight associated complications that are poorly predicted by the existing risk equations such as metabolic abnormalities and risk of developing T2D. Also, the identification of new risk predictors through methods such as genetic profiling and related to metabolic alterations would add value, while new data can support existing risk predictors and determine how they are best weighted for each equation.As scientists increasingly understand the value of data sharing and open-source codes, big data will further change the way we predict risk. As an example, all modern predictive models of financial market risks are based on data driven analysis exploiting machine learning. One of the main reasons this is not done in medicine yet is due to the data deficit needed for a multifactorial analysis. Only a few areas in the medical field, such as radiomics, have harnessed this power with data driven analysis for diagnosis and prognosis of several diseases. As more data is gathered, risk modelling for weight related outcomes will become more powerful to accurately predict outcomes for populations living with obesity, populations that are growing rapidly in many parts of the world.This SLR was limited to countries by geographical scope  and therefore may have excluded potentially useful risk equations developed in other regions. Results predominantly reflected European studies, while Canada and the USA are not well represented. Furthermore, because a direct comparison of the risk equations was not possible due to each being developed or calculated using different methods for different purposes, a judgment on how each risk score performs is the opinion of the user or decision-maker in a particular context. Finally, obesity may not be a single homogenous disease. Thus, if there are different obesity subtypes leading to the same BMI in different people then a single unifying risk equation may not be possible, but rather better diagnostic ability of these obesity subtypes may be required to refine future risk equations.Additional file 1: Table S1. Inclusion and exclusion criteria used in the systematic literature review. Table S2. Search strings used for the Embase search. Table S3. Search strings used for the PubMed search. Table S4. Data extraction categories. Table S5. The adapted Newcastle–Ottawa Scale. Table S6. Studies excluded following the full-text screening. Table S7. Included studies. Table S8. Quality assessment of the included studies using the adapted Newcastle Ottawa Scale.


Such changes included the development of more advanced surgical procedures, with the oldest known indication of an ‘operation’ formerly thought to have consisted of the skeletal remains of a European Neolithic farmer  whose left forearm had been surgically removed and then partially healed3. Dating to around 7,000 years ago, this accepted case of amputation would have required comprehensive knowledge of human anatomy and considerable technical skill, and has thus been viewed as the earliest evidence of a complex medical act3. Here, however, we report the discovery of skeletal remains of a young individual from Borneo who had the distal third of their left lower leg surgically amputated, probably as a child, at least 31,000 years ago. The individual survived the procedure and lived for another 6–9 years, before their remains were intentionally buried in Liang Tebo cave, which is located in East Kalimantan, Indonesian Borneo, in a limestone karst area that contains some of the world’s earliest dated rock art4. This unexpectedly early evidence of a successful limb amputation suggests that at least some modern human foraging groups in tropical Asia had developed sophisticated medical knowledge and skills long before the Neolithic farming transition.The prevailing view regarding the evolution of medicine is that the emergence of settled agricultural societies around 10,000 years ago (the Neolithic Revolution) gave rise to a host of health problems that had previously been unknown among non-sedentary foraging populations, stimulating the first major innovations in prehistoric medical practices Around 31,000 years ago, a young individual from Borneo had part of their left lower leg surgically amputated, probably as a child, and lived for another 6–9 years after amputation. The bottom of the ovate-shaped grave cut terminated in SU8 and did not continue into the underlying SU9  based on a range of morphological considerations (σ) taller than the mean for most female individuals , each accompanied by laser scanning and photography  age of 31,133 to 30,437 calibrated radiocarbon years before present  with a 95.4% probability (D-AMS38332), providing a stratigraphic minimum date for the inhumation of TB1 (Supplementary Table bp (D-AMS38337). Charcoal recovered from SU9, the stratum underlying the burial feature, provides a stratigraphic maximum date, with an estimate of 31,519 to 31,054 cal. bp (D-AMS38338). The SU9 sample was situated immediately underneath the burial cut, although within a completely distinct stratum that clearly underlies both the burial feature and the equally distinct sediments of SU8. Thus, associated radiocarbon dating of the charcoal samples indicates an age estimate for the TB1 burial feature of between 31,519 and 30,437 cal. bp, with a mean of 30,978 cal. bp. Bayesian chronology suggests that the boundary between SU7, which caps the burial, and the burial feature itself, is 30,853 ± 770 cal. bp; and the boundary between the burial and the underlying SU8 is 31,135 ± 864 cal. bp . The positive age–depth relationship of these samples (completely lacking inversion) supports an argument for minimal deposit reworking and diminishes the possibility of introduced charcoals entering lower units, including burial-fill sediments.Immediately above the sediment of the distinct grave cut in SU7, a charcoal sample returned an accelerator mass spectrometry (AMS) radiocarbon  and this analysis returned an age estimate of 25.4 ± 4.3 thousand years old (1σ), which is within the error of the 14C burial-context age. Both the uranium-series analysis in isolation and radiocarbon dating of the skeletal remains were unsuccessful owing to insufficient amounts of uranium and collagen in the sample, respectively. Incorporating the electron spin resonance age into the Bayesian model gives a modelled date of 31,201 to 30,714 years ago (2σ or 95.4% probability) for the burial  recovered within the grave . Furthermore, it has long been a commonly held view among western scholars that healthcare systems and medical procedures of historically known foraging societies are, and were, rudimentary. It is recognized that traditional healing practices typically involve extensive knowledge of plant-based medicinal remedies27. Surgical intervention and treatment of people with illness or injury, however, are thought to have been poorly developed among small-scale foraging communities, and were generally limited to procedures such as suturing lacerations, dentistry, cranial trepanation and various body modification practices such as tooth avulsion, scarification, and genital mutilation , each of which no doubt requiring considerable expertise. The prevailing assumption has been that more complex surgeries were beyond the abilities of foraging societies past and present. The surgical removal of body parts, specifically, is thought to have been confined mostly to phalangeal (finger segment) amputation for punishment or symbolic purposes 28. Concerning the history of amputation surgery per se, historical accounts vary from ancient Roman sources to advances in surgical procedures developed during the past few centuries1. Review of the latter27 provides details of modern clinical procedures of amputation, exemplifying the level of anatomical understanding, hygiene, surgical skill, and required apparatus for success . In western societies, successful surgical amputation only became a medical norm within the past 100 years1. Before modern clinical developments, including antibiotics, it was widely thought that most people undergoing amputation surgery would have died, either at the time of amputation from blood loss and shock or from subsequent infection—scenarios that leave no skeletal markers of advanced healing.The surgical amputation of TB1’s left lower leg some 31,000 years ago has important implications for our understanding of the evolution of human medico-socio-cultural practices. Evidence of surgery in the time before written records is scarce. Until now, the earliest primary evidence of advanced medical knowledge, including amputation, was restricted to Holocene cases29. Finally, during surgery, the surrounding tissue including veins, vessels and nerves, were exposed and negotiated in such a way that allowed this individual to not only survive but also continue living with altered mobility. Intensive post-operative nursing and care would have been vital, such as temperature regulation, regular feeding, bathing, and movement to prevent bed sores while the individual was immobile29. The wound would have been regularly cleaned, dressed, and disinfected, perhaps using locally available botanical resources with medicinal properties to prevent infection and provide anaesthetics for pain relief 31. Although it is not possible to determine whether infection occurred after the surgery, this individual evidently did not suffer from an infection severe enough to leave permanent skeletal markers and/or cause death. Furthermore, it is inferred that life without a lower limb ’ who amputated this individual’s lower left leg must have possessed detailed knowledge of limb anatomy and muscular and vascular systems to prevent fatal blood loss and infection. They must also have understood the necessity to remove the limb for survival34 on the eastern margins of Sunda. We infer that the comprehensive knowledge of human anatomy, physiology, and surgical procedures evident in TB1’s community is likely to have been developed by trial and error over a long period of time and transmitted inter generationally through oral traditions of learning. Notably, it remains unknown whether this ‘operation’ was a rare and isolated event in the Pleistocene history of this region, or if this particular foraging society had achieved an unusually high degree of proficiency in this area. Risk of death from trauma and disease has always been with us, and complex medical acts, such as limb amputation, could well have been more commonplace in the pre-agricultural past of our species than is broadly assumed at present. Our understanding of this aspect of H. sapiens prehistory, however, may be affected by poor preservation of pathological bone, as well as by preconceptions about the ‘primitive’ nature of earlier medico-socio-cultural practices, especially among non-sedentary foraging populations in tropical Asia. On the other hand, we cannot exclude the possibility that human colonization of the ancient rainforests of Borneo both prompted and facilitated early advances in medical technology that were unique to this region. For example, rapid rates of wound infection in the tropics may have stimulated the development of new pharmaceuticals  that harnessed the medicinal properties of Borneo’s rich plant biodiversity and endemic flora31.In summary, the discovery of this exceptionally old evidence of deliberate amputation demonstrates the advanced level of medical expertise developed by early modern human foragers in a Late Pleistocene tropical rainforest environmentk values of 20 and a dipole–dipole l value of 5. ERT data were acquired with 120 V, an on-time of 1.2 s and an off-time of 0.2 s. Data were output using ZZ RData Check software, inverted in Res2D using the robust scheme and displayed with a colour scale constructed using the Jenks Breaks feature with ArcGIS.The geophysical survey using ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) was conducted in the chambers of Liang Tebo  were sieved using a soft nylon 0.5-mm screen. Whether recovered in situ or from sieved residues, all artefacts can be precisely associated with both a stratigraphical unit and an excavation unit. Cultural materials recovered throughout include stone artefacts, ochre, shell, faunal remains and macrobotanical remains, with a total lack of ceramic and metal finds. Human remains and all other delicate artefacts were excavated using handheld softwood tools to prevent damage, with other sediments removed using a fine leaf trowel. First encountered at 0.87 m depth in the western squares, the TB1 burial feature had a strongly defined stratigraphical boundary with distinctive infill sediment: revealing the grave cuts into SU8. The latter unit was marked by a very different colour and texture—a weakly cemented white (10YR 8/1) calcitic silt , for a total of 4 and 5 steps, respectively. Sample D-AMS 038338 showed signs of breakdown in base and thus received a less-aggressive acid–base–acid base step, using 0.09 M KOH at room temperature for 12 min followed by a deionized water rinse and 0.05 M HCl rinse, and treatment with 0.09 M KOH at 65 °C for 12 min and a deionized water rinse and, finally, washed using three 0.05 M HCl rinses. Carbon δ13C stable isotope values are not available for these samples.Throughout the nine stratigraphical units  at the GARG facility of the Southern Cross University. The tooth was first cut in half using a rotating diamond saw with a blade of 300 µm, before being polished to 5-µm smoothness. The sample was then analysed for uranium-series isotopes and concentration in both dentine and enamel using a laser ablation NWR ESI 213 laser coupled with a MC–ICPMS Neptune XT (Thermo Fisher) to calculate the internal dose rate. An enamel fragment was then measured on a Freiberg MS5000 ESR X-band spectrometer and irradiated with the Freiberg X-ray irradiation chamber. ESR intensities were extracted from the merged spectra obtained on the angular variation measurements37  dating was done on a left mandibular molar The age estimates are coeval and the uncertainties are relatively small. As such, the identified boundary ages are not sensitive to removal of individual dates or to changes in, for example, the model calculation resolution. None of the changes we made to the model set-up produced appreciable differences in the age model results. The age of the burial layer was conservatively estimated as the boundary between the base of this layer and the base of SU7, incorporating all of the constraints described above and the resulting age estimates  and taphonomy . Skeletal and dental completeness and post-depositional processes, including colour change, root damage, animal scavenging marks, sun and water exposure, post-mortem breakage and surface erosion, were each assessed45. Different fusion timings of the various epiphyses enable a narrow age estimate of late teenage years to early adulthood. Epiphyses (growth plates) that do not fuse until early adulthood, such as the medial end of the clavicle, were assessed following previously published studies46. Dental eruption, wear and formation methods supplemented these age-estimation protocols51.The TB1 individual was morphologically an adult, therefore adult age-at-death estimation techniques were applied. Pubic symphysis and auricular surface degeneration stage methods were compared with standards53 because of the similar proportions to the contribution of maximum tibia lengths, with 10 mm adjustments to the maximum tibial lengths52. Estimates for comparative pre-Neolithic hunter-gatherers in southeast Asia have traditionally been estimated from modern Asian populations in the United States, even if they pre-date migration of groups with morphological affinity to modern East Asian populations to the region. Therefore, these stature estimates are provided for comparison to other pre-Neolithic modern humans.Regression equations were used to estimate the stature from the maximum length of the long bones. The right femur and tibia were considered the most valuable bones for stature estimation because of their relationships in contributing to stature and preservation. Australo-Melanesian populations rather than East or southeast Asian populations are likely to provide better estimates for pre-Neolithic individuals from southeast Asia. The ‘American Black’ stature estimate standards were used56. Bone lesion location, aspects affected, percentage of bone affected by lesion and bone type affected  were recorded to assess the spatial distribution of lesions. The level of healing, margin definition, presence of necrotic bone (sequestrum), presence of shape changes to the bone, focality , laterality, symmetricity and lesion size were recorded to reconstruct the progression and pattern of disease for differential diagnosis. Lesions were compared against clinical and palaeopathological literature to determine possible candidates for disease origin (aetiology of the disease). Trauma analysis  followed previously published protocols56 to describe the mechanism of injury, force, type and time of trauma, and the degree and complications to healing.A full skeletal assessment of abnormal bone changes was completed. Lesions  were recorded following revised standard protocolsFurther information on research design is available in the Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-022-05160-8.Supplementary InformationAdditional notes on the Liang Tebo skeleton’s preservation, age-at-death and sex (p.1), analysis of the amputation site and dental pathology (p.2) and other trauma (p.3). Additional notes on the US–ESR dating analyses (p.5–8). Supplementary Tables 1–4 (p.9–12) include the stature estimates, linear enamel hypoplasia details, radiocarbon chronology and the Bayesian model and code, respectively.Reporting Summary


Gastric carcinoma is the most common malignant tumour of the human digestive system worldwide. CD44 serves as a marker for several tumour stem cells, including gastric cancer. However, the prognostic value of CD44 and its correlation with immune infiltration in gastric cancer remain unclear.The relative expression level of CD44 RNA in gastric cancer was analysed in the TCGA and GEPIA2 databases and validated in the GEO database. Differences in CD44 between gastric cancer cell lines and normal cells were detected by real-time PCR, and the HPA database was used to analyse the differential expression of CD44 protein in gastric cancer and normal tissues. The effect of CD44 on the proliferation and migration of gastric cancer cells was detected by CCK8 and transwell assays. UALCAN was used to analyse the relationship between CD44 expression and clinical parameters, and the Kaplan‒Meier Plotter was used to evaluate the prognostic value, including overall survival (OS), progression-free survival (PFS) and post-progression survival (PPS). The CD44 gene and protein interaction network was constructed by using the Linked Omics, GeneMANIA, STRING and DisGeNET databases. GO and KEGG analyses and GSEA of CD44 were performed by using R language. The correlation between CD44 and immune infiltration was explored by using the TIMER, CIBERSORT and GEPIA databases.CD44 is highly expressed in gastric cancer compared with normal tissues. Inhibition of proliferation and migration of gastric cancer cells after CD44 knockdown was observed. The UALCAN database showed that CD44 was independent of sex in gastric cancer but correlated with cancer stage and lymph node metastasis. Kaplan‒Meier Plotter online analysis showed that OS, PFS and PPS were prolonged in the CD44 low-expression group. GO and KEGG analyses and GSEA results showed that CD44 was mainly located in the endoplasmic reticulum and the extracellular matrix containing collagen, which was mainly involved in protein digestion and absorption. TIMER, CIBERSORT and GEPIA showed that CD44 was associated with infiltrating immune cells and thereby affected survival prognosis.CD44 is highly expressed in gastric cancer and is an independent prognostic factor associated with immune invasion, which can be used as a candidate prognostic biomarker to determine the prognosis associated with gastric immune invasion. Helicobacter pylori infection, life stress and dietary habit changes, the incidence of gastric carcinoma tends to occur in younger people. It is still a major disease affecting human life and health. Currently, the treatment of gastric carcinoma is based on surgery and neoadjuvant therapy, postoperative chemotherapy and biological immunotherapy[Gastric carcinoma is the most common malignant tumour of the human digestive system worldwide. However, as research continues, the incidence and mortality of gastric carcinoma have decreased. Nevertheless, according to the International Agency for Research on Cancer, the incidence of gastric carcinoma was the fifth highest at 5.6%, and the mortality rate was the fourth highest at 7.7% in 2020 . Due to notherapy. TherefoCD44, located on human chromosome 11, is an adhesion molecule found on the surface of cells that acts as a receptor for hyaluronic acid, osteopontin, collagen and metalloproteinases . CD44 isAccording to the cancer stem cell (CSC) hypothesis and studies of other solid tumours, CSCs are highly tumorigenic and have multidirectional differentiation ability and chemoradiotherapy resistance . They arTumour stem cells are subpopulations of undifferentiated cancer cells within the tumour bulk, and their external interaction with the surrounding tumour microenvironment can drive tumour growth by interacting with resident and infiltrating nontumor cells . Recent Many previous studies have shown that immune infiltration-related factors are highly correlated with the prognosis of different tumours –27, and Therefore, we used The Cancer Genome Atlas (TCGA) database to analyse the relative expression level of CD44 RNA in gastric cancer and validated our findings in the Gene Expression Omnibus (GEO) database. The Human Protein Atlas (HPA) database was used to analyse the differential expression of CD44 protein in gastric cancer and normal tissues. The relationships between CD44 and various clinicopathologies were analysed using the UALCAN database, and the relationships between CD44 and prognosis were plotted using the Kaplan‒Meier Plotter database. We combined Linked Omics, GeneMANIA, the STRING database and bioinformatics related to TCGA, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and gene set enrichment analysis (GSEA) to analyse the relationship between CD44-related genes and signalling pathways. Finally, the relationship between CD44 and immune cell markers was analysed using the Tumour Immune Estimation Resource (TIMER) database, CIBERSORT and Gene Expression Profiling Interactive Analysis (GEPIA). The objective was to explore the prognostic value of CD44 in gastric cancer and the possible mechanism of immune invasion.http://gepia2.cancer-pku.cn/#index) is an updated version of GEPIA. It can be used to analyse the RNA expression sequencing data of 9736 tumour samples and 8587 normal samples in TCGA and GTEx. We used this database to analyse the expression of CD44 across cancers. After cross-analysis with the results obtained by using TIMER, the common types of differential cancer were obtained.GEPIA2 . The TCGA database, the largest database of cancer genetic information, currently includes 33 cancer types based on large-scale genome sequencing, and genomic, transcriptomic, epigenetic, proteomic and other omics data are available.The original RNA expression data of 407 gastric cancer cases were downloaded from the TCGA database (https://www.ncbi.nlm.nih.gov/geo/) includes gene expression test data submitted by research institutions around the world. We downloaded microarray datasets GSE29272  and GSE79973  as the research objects.The GEO database (https://www.proteinatlas.org) is based on proteomics, transcriptomics and systems biology. It provides information on the tissue and cellular distribution of 24,000 human proteins. The protein expression data and clinical information of normal and tumour tissues are also included.The HPA database  is a comprehensive, interactive Web resource. In the TCGA module, after the input of the target genes CD44 and STAD, the correlation between CD44 and clinicopathological parameters  was analysed online.The UALCAN database  comprises an evaluation of the impact of 54,675 genes on survival outcomes in 21 cancers. We analysed the prognostic value of CD44 in gastric cancer using the Kaplan‒Meier Plotter database, including overall survival (OS), progression-free survival (PFS) and post-progression survival (PPS).The Kaplan‒Meier Plotter database (http://www.linkedomics.org) is a database of multiple omics and clinical data for 32 cancer types. Data types include miRNA, mRNA data, methylation data, mutation sites, etc. We used this database to obtain heat maps of genes positively and negatively correlated with CD44 in gastric cancer.The Linked Omics database (http://genemania.org) enables the prediction of gene function. We used the database’s rich genomics and proteomics to construct a network of genes that interact with CD44 and explored genes with similar functions to CD44.The GeneMANIA database (https://string-db.org/) is a database that analyses protein interactions. The protein–protein interaction (PPI) network of CD44 was constructed by using this database.The STRING database (https://www.disgenet.org/) can be used to retrieve the relationship between genes and diseases and between variant genes and diseases. The database systematically integrates data sources from expert-curated repositories, GEAS catalogues, animal models, and scientific literature. By using this database, we obtained disease-related targets related to “malignant neoplasm of stomach”.DisGeNET , cell composition (CC), and molecular function (MF), has been developed to provide consistent functional descriptions of gene products in various databases. KEGG analysis provides insights into higher-level functions of genes at the molecular level. We performed functional enrichment analysis of CD44-related genes by using the cluster profile package in R software and visualized the results.GSEA uses predetermined gene sets and arranges them in descending order by differential expression levels for gene enrichment analysis. Because GSEA uses whole-genome expression profiles obtained by sequencing or chip analyses, there is no need to specify the threshold value of differential genes, so the results obtained are more reliable than those obtained by GO and KEGG analyses.https://cistrome.shinyapps.io/timer/) is a database related to tumour immunity. It includes immunity, exploration and evaluation. We first performed a holistic assessment of CD44 expression in multiple types of cancer. In addition, the correlation between CD44 and immune cell infiltration, such as B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages and dendritic cells, was analysed by using the “gene” module. In addition, the correlation module was used to analyse the relationship between CD44 and immune cell markers.The TIMER database (http://gepia.cancer-pku.cn/) integrates TCGA cancer data with CRTx normal tissue data. It analyses the association and correlation between two genes. We used this database to analyse the correlation between CD44 and immune checkpoint genes.The GEPIA database (Human gastric cancer cells (SGC7901 and MGC803) and human gastric mucosal epithelial cells (GES-1) were obtained from Prof. Jie-Min Qi of Chengde Medical University and cultured in an RPMI-1640 medium containing 10% foetal bovine serum (FBS). All cells were incubated in an incubator with 5% carbon dioxide at 37 °C.The cells were transfected with human CD44 siRNA duplex oligo ribonucleotides, with a 5′-CTCTGAGCATCGGATTTGA-3′ targeting sequence, and negative control duplexes  and Lipofectamine 3000 (Invitrogen) were used.For real-time quantitative PCR (qRT‒PCR), total RNA was extracted from cells with TRIzol reagent  according to the manufacturer’s instructions. cDNA was synthesized with ABScript II RT Master Mix . qRT‒PCR analysis was performed using 2 × Universal SYBR Green Fast qPCR Mix . Total RNA levels were normalized to those of GAPDH. The primer sequences were as follows:CD44, forward: 5′-ACCGACAGCACAGACAGAATC-3′;CD44, reverse: 5′-GTTTGCTCCACCTTCTTGACTC-3′GAPDH, forward: 5′-CACAAGCAGAGTGCTGAAGGTG-3′; andGAPDH, reverse: 5′-ACCACCCTGTTGCTGTAGCCAA-3′.− ΔΔCT method. The experiment was repeated at least three times.The results were calculated by the 23 cells/ml after they were transfected with siCD44, and the cells were evaluated at 0, 24, 48, 72 and 96 h. The culture medium was added to 10 μl CCK8 solution and cultured for 1.5 h, and the OD value was measured at 450 nm. The experiment was repeated at least three times.Gastric cancer cells were seeded into a 96-well plate at a density of 3 × 10Gastric cancer cells were seeded into a 6-well plate to form a confluent monolayer and scratched with a 200 μl pipette. The damaged monolayer was washed with phosphate-buffered saline (PBS) to remove cell debris. The cells were cultured in a serum-free medium, and digital images of the wound surface were taken with an inverted microscope after 0 h and 24 h. To evaluate the wound area, we imported the wound image into ImageJ software for calculation. The experiment was repeated at least three times.2FoldChange|> 1 was defined as the differentially Upregulated and downregulated genes. The R software package complot was used to analyse the correlation between genes and infiltrating immune cells. The Kaplan‒Meier plots and survival outcome results are displayed with HR and R values based on a log-rank test. Spearman correlation analysis of GEPIA genes was performed. All grouped data in the figures are the means ± SDs. For all tests in this study, a P value of < 0.05 was considered statistically significant.Statistical analyses were carried out using GraphPad Prism (Version 9.00). R language was used for the different analysis based on the sample data obtained from the TCGA and GEO databases. The volcano map of differential genes in TCGA gastric cancer samples was drawn by using the R software package ggscatter, and |logP = 0.0374 < 0.05) , Gene Expression Profiling Interactive Analysis (GEPIA2), The Cancer Genome Atlas (TCGA), GEO and Human Protein Atlas platform (HPA) to comprehensively analyse whether CD44 exhibits different expression levels of mRNA and protein in gastric cancer. First, an overall evaluation of CD44 expression in a variety of common tumours was made by using the TIMER and GEPIA2 online databases Fig. A–B. Afte05) Fig. C. To ver05) Fig. D, E. Thi05) Fig. F.Fig. 1ETo further verify the CD44 transcription profile, staining and expression data from tumour pathological sections obtained from HPA were used. CD44 expression in tumours was compared with that in normal tissues at the same site. Images of immunohistochemically stained tissue samples showed that CD44 was almost not expressed in normal tissues with a quantity of < 25% but that it was significantly overexpressed in tumour tissues with a quantity of 75%–25% Fig. G. In conTo determine the role of CD44 in the proliferation and migration of gastric cancer cells, we used siRNA to knock down CD44 in SGC7901 and MGC803 cells. To detect the effect of CD44 knockdown on the proliferation of gastric cancer cells, the results of the CCK8 assay showed that low CD44 expression inhibited the proliferation of SGC7901 and MGC803 cells compared with that in the control group Fig. A. Wound P < 0.0001). In terms of nodal metastasis status, compared with that in the normal control group, the expression of CD44 was significantly increased at the N0, N1, N2 and N3 stages. However, there was no difference in the expression of CD44 at the N0, N1, N2 and N3 stages , cell composition (CC) and molecular function (MF). The “count” on the horizontal axis represents the number of genes enriched in that item. The colour represents the corrected P value, and the redder the colour is, the stronger the difference. Analysis showed that CD44 was enriched in BP during digestion, absorption and transportation. These include digestion, organic hydroxy compound transport, amine transport and regulation, intestinal lipid absorption, etc. In CC, CD44 is predominantly located in the endoplasmic reticulum lumen, chylomicrons, and collagen-containing extracellular matrix. In MF, enrichment results suggest that CD44 is involved in the inhibition and regulation of various enzyme activities, such as serine-type endopeptidase inhibitor activity, endopeptidase inhibitor activity, and endopeptidase regulator activity  are a crucial cell type in this context as they are capable of directly destroying malignant cells, CD44 functions as a critical regulator of intra-tumoral movement by stabilizing cell polarity in migrating T cells . Long-liIn conclusion, CD44 is expected to become a new immunotherapeutic target for gastric cancer by further exploration of the specific mechanism of CD44 and various immune cells and how it affect the survival and prognosis of gastric cancer patients.This study systematically analysed the expression level of CD44 in gastric cancer, the clinical influencing factors of CD44 expression level, survival prognosis assessment, genes that interact with CD44, pathway enrichment, and the correlation between CD44 and the immune microenvironment through biogenic analysis. This study has further improved our understanding of the relationship between CD44 and gastric cancer. However, the specific mechanism of the interaction between CD44 and various immune cells, inflammatory factors and cytokines in the immune microenvironment needs further study. As a potential therapeutic prognostic marker of gastric cancer, CD44 has important research value and broad prospects.Our study further solidifies the key role of CD44 in gastric cancer and reveals its close relationship with prognosis and immune infiltration, suggesting that CD44 can be used as an exact target for the diagnosis and treatment of gastric cancer.


Factor V and VIII deficiency (F5F8D) is a rare coagulopathy; it’s an autosomal recessive condition. This case report is about of 15-year-old unmarried Saudi female, who presented with a complaint of pain in the lower abdomen. Complete blood count and coagulation profile revealed low hemoglobin and prolongation of activated partial thromboplastin time (aPTT), prothrombin time (PT), and international normalized ratio (INR). The deficiency of factor V and factor VIII was confirmed with factor test revealing reduced activities of factor V and VIII Combined deficiency of factors V and VIII should be considered in differential diagnoses of patients with prolonged INR, PT, and aPTT. Medical management is reserved for those who present with significant bleeding. The combined factor V and factor VIII deficiency (F5F8D) is an autosomal recessive constitutional hematological disorder that is relatively uncommon, the condition was first identified in 1954 by Oeri et al. .Bleeding time and platelet count appear normal while international normalized ratio (INR) and activated partial thromboplastin time (aPTT) are observably prolonged. Mixing studies show the correction of prothrombin time (PT) and aPTT. To reach a diagnosis, further factor testing should be performed. Advanced genetic analysis could be done to identify the exact gene mutation responsible for the case. The successful management to prevent bleeding from surgery includes the administration of 1-deamino-8-d-arginine vasopressin  prior to, during, and after surgery due to persistently elevated PT, aPTT, and INR. Moreover, vitamin K and tranexamic acid were given. Her postoperative course was unremarkable with no bleeding. She was referred to a higher care center to do factor assays to establish a diagnosis. So, she conducted the factors assay in King Faisal Specialist Hospital & Research Center in Riyadh, and the results Table  showed rCongenital combined factor V and factor VIII deficiency is a form of peculiar autosomal recessive bleeding disorder which is more common in places where kindred marriages are more common. Combined factor V and factor VIII deficiency is the most common kind of combined plasma coagulation factor deficits. Families impacted have been reported from all over the world, including the Middle East, North America, Europe, and the Far East. However, Middle Eastern heritage has the highest prevalence of this illness .The disorder results from gene mutations in either two genes LMAN1  or MCFD2 . The two genes produce the ERGIC-53/MCFD2 protein complex, which serves as a cargo receptor, allowing coagulation factors V and VIII to be transported to the Golgi apparatus, coming from the endoplasmic reticulum. LMAN1 mutations explain around 70% of cases and solely comprise null mutations. MCFD2 mutations occur in about 30% of instances and include both null and missense variants . UnfortuA screening correlogram and factor assay are used to diagnose this disease. Factor V and factor VIII levels should be between 60% and 150% in the normal range. However, in F5F8D levels usually range from 1% to 46%, but most patients have levels between 5% and 30%. The levels of factor V and factor VIII in our patients is 8% and 6%, respectively. Diagnosis is usually considered after the discovery of prolonged activated partial thromboplastin and prothrombin times ,3. We reThe simultaneous reduction in plasma levels of factor V and factor VIII causes mild-to-moderate manifestations. Symptoms of bleeding vary; however, they are often comparable to those of single factor V or VIII insufficiency. Epistaxis, menorrhagia, easy bruising, bleeding following trauma or surgery, and to a lesser extent, hemarthrosis and muscle hematomas are the most prevalent symptoms ,5. Gum bRegular prophylaxis is not necessary for combination F5F8D, and patients are typically not treated until therapy is required; nevertheless, prophylaxis should indeed be considered in situations of recurrent hemarthrosis or intramuscular hemorrhage. Replacement of the factors is the therapy. FFP as a therapy regimen that can give factor V and factor VIII concentrate, has been suggested by the Hemophilia Centre Doctors’ Organization in the United Kingdom. Particular factor concentrates, whether plasma-derived or recombinant, are superior in replacing factor VIII. Published investigations have shown that an FFP-containing regimen can effectively limit bleeding during tooth extractions, circumcision, and labor preparation. Desmopressin can still be utilized to treat minor bleeds under certain circumstances .The overall prognosis for mild instances of the illness is good. Patients with more severe varieties of the disease shall be properly treated in a highly specialized hospital .The combined deficiency of factor V and factor VIII is more prevalent in areas where consanguinity is common such as middle eastern countries and the Mediterranean region. The disorder should be suspected in any patient who presents with prolonged PT and aPTT and meets the epidemiologic features. Management in form of regular replacement with FFP and factors concentrate is reserved for recurrent severe bleeding.