dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion To our knowledge, the present study is the largest cohort to report outcomes of kidney transplantation in patients with renal AA amyloidosis. Our main findings are high overall and graft survival rates and a low amyloidosis recurrence rate, suggesting that patients with AA amyloidosis can benefit from kidney transplantation with favorable outcomes. As a mean of comparison in the absence of a control group for our cohort, data for 34,776 patients from the French transplantation database (Agence de la Biom edecine, rapport Rein 2018  25  ) between 2007 and 2017 demonstrate a patient survival rate of 88. 4% at 5 years (95% CI, 88. 0-89. 0) and an all-cause graft survival rate of 78. 6% (95% CI, 78. 1-79. 1). During almost the same time period, in our cohort, the patient survival rate was slightly lower but comparable (85.
Acknowledgments: We thank  Emilie Savoye  ( Agence de la Biom edecine ) for the statistical expertise. Data Sharing: A subset of deidentified data may be available upon request to the corresponding author. Peer Review: Received September 30, 2022. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/ Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form July 24, 2023.
16. 7%), fibrofolliculomas/trichodiscomas (6. 1%), unspecified (8. 3%), not biopsied (6. 8%), skin tumors/ lesions (4. 2%), acrochordons (2. 7%), nevi or epidermal cysts (2. 3%), lipomas (2. 3%), perifollicular fibromas (2. 3%), dermatofibromas (1. 5%), trichodiscomas (1. 2%), angiofibromas (0. 3%), milia (0. 3%), mucinosis (0. 3%), sarcomas (0. 3%), and syringomas (0. 3%) (Supplementary Table  III , available via Mendeley at https://data. mendeley. com/datasets/ x4dmfnynjj/1). FLCN mutations were identified in 96% of SOC patients who underwent genetic testing, of which 12% were novel mutations (Supplementary Table IV, available via Mendeley at https://data. mendeley. com/datasets/x4dmfnynjj/1). The diagnosis of BHDS is based on a combination of genetic, clinical, and skin histopathological criteria (Supplementary Table I, available via Mendeley at https://data.
mendeley. com/datasets/ x4dmfnynjj/1). The cutaneous manifestations in SOC are highly variable and the rule of [5 fibrofolliculomas or trichodiscomas does not always apply, especially in Asians. In SOC, these lesions may mimic dermatosis papulosa nigra, acrochordons, milia, or comedones. 2, 5  As a result, these lesions may be frequently misdiagnosed or underdiagnosed in routine clinical practice. Multiple benign follicular papules should prompt the dermatologist to inquire about a personal or family history regarding pneumothorax, lung cysts, and renal malignancy. Our findings suggest that cutaneous manifestations may precede systemic involvement in SOC patients (Supplementary Table  II , available via Mendeley at https://data. mendeley. com/ datasets/x4dmfnynjj/1). Thus, it is important that dermatologists recognize BHDS as a potential cause of cutaneous lesions for early diagnosis of BHDS and prompt screening given the significant morbidity and mortality associated with this syndrome.
https://doi. org/10. 1016/j. jaad. 2023. 09. 081   Phase 2 open-label, multicenter, single-arm study of cemiplimab in patients with locally advanced basal cell carcinoma after hedgehog inhibitor therapy: Extended follow-up To the Editor: An unmet need exists among patients with advanced basal cell carcinoma (aBCC). Surgery and hedgehog signaling pathway inhibitors (HHIs) are proven treatments, but with challenges (eg, resistance, recurrence, or intolerance). 1, 2  Cemiplimab, an anti-programmed cell death-1 inhibitor, is approved for patients with aBCC resistant or intolerant to HHIs. 3, 4  In the phase 2 primary analysis (NCT03132636), cemiplimab demonstrated significant clinical benefit in patients with locally advanced basal cell carcinoma (laBCC) post-HHI treatment. 5  Here, we present the extended follow-up data.
The study design and primary analysis results were previously reported. 5  Briefly, patients received cemiplimab 350 mg intravenously every 3 weeks for up to 93 weeks, with tumor assessments at the end of each treatment cycle. The primary endpoint was objective response rate (ORR); data cutoff was May 20, 2021, when all patients were off-treatment. Eighty-four patients were included. The median (range) duration of follow-up and duration of exposure was 15. 9 months (0. 5-39. 7) and 47. 2 weeks (2. 1-97. 9) respectively; patients received a median of 15 doses (range: 1-31). ORR per independent central review (ICR) was 32. 1% (95% confidence interval [CI]: 22. 4-43. 2), improved from 31% (95% CI: 21-42) in the primary analysis (Table  I ). 5   I ). In responders, ongoing response at 12 months was 83.
Drs Yoo, Inocencio, Chen, Seebach, Lowy, and Fury are employees and shareholders of Regeneron Pharmaceuticals, Inc. Mr Okoye is also an employee and shareholder of Regeneron Pharmaceuticals, Inc. Dr Bassukas reports non-financial support from Leo Pharma and Novartis, and institutional grants from Leo Pharma. Dr Loquai reports personal fees from Roche, Sun Pharma, Bristol Myers Squibb, Merck Sharp & Dohme, Merck, Novartis, Pierre Fabre, Kyowa Kirin, Almirall Hermal, and BioNTech. Dr De Giorgi reports no conflict of interest. Dr Eroglu reports advisory board fees from Regeneron Pharmaceuticals, Inc, Novartis, Pfizer, Genentech, Eisai, OncoSec, and Natera; and research grants from Novartis, Pfizer, and Boehringer Ingelheim. Dr Gutzmer reports documentation fees to their institution from Regeneron Pharmaceuticals, Inc; personal fees and non-financial support from Amgen, Bristol Myers Squibb, Roche Pharma, Merck Serono, Pierre Fabre, Sanofi, and Regeneron Pharmaceuticals, Inc; grants, personal fees, and non-financial support from Novartis; grants and personal fees from Pfizer; grants from Johnson & Johnson; and personal fees from Merck Sharp & Dohme, Almirall Hermal, Sun Pharma, 4SC, and Immunocore.
547. 385, build 37, NM_020127. 2; ENST00000368849), of the TUFT1 gene in the two affected children, whereas the father was a heterozygous carrier for this variant. Sanger sequencing validation confirmed these findings and, in addition, showed the mother to be a heterozygous carrier as well (Figure  2b ). Splice site analysis programs (Alamut, version 2. 7. 2, SOPHiA Genetics, Lausanne, Switzerland) predicted skipping of exon 9 to be the most likely outcome, and given the 100% evolutionary conserved sequence   S5. (f) Effect of NMDi on relative TUFT1 mRNA expression levels in control and patient fibroblasts. After NMDi treatment, expression levels of mutated TUFT1 transcripts in the patient increased 3,700 times fold compared with TUFT1 transcript levels in controls with 26 times and 48 times fold increase; average Ct values:  and II1 þ NMDi ¼ 23.
9. Error bar ¼ SEM, data were analyzed by paired t-test; ***P < 0,0005. hom. denotes homogenous; het. denotes heterogenous. UTR, untranslated region; NMDi, nonsense-mediated mRNA decay inhibition. C1 ¼ 29. 8, C1 þ NMDi ¼ 24. 2, C2 ¼ 27. 9, C2 þ NMDi ¼ 23. 2, II1 ¼ 36. 2, of the À2A splice acceptor site, this nucleotide change was expected to destroy the splice acceptor site of intron 8  (Zhang, 1998). This variant was not present in the gnomAD database (version 2. 1. 1)  (Lek et al. , 2016)  or any other public population variant frequency database. None of the known genes involved in skin fragility and cardiocutaneous syndromes, as mentioned in Supplementary Table  S3 , were located in any of the identified homozygous regions nor revealed any variants indicative to be disease causing. RT-PCR was performed on lymphocyte mRNA from the patients and both parents and revealed alternative splicing leading to a frameshift and premature termination codon (Figure  2c  and d and Supplementary Figure  S1a ).
, 2016). In addition, a publicly available Gene Expression Omnibus dataset showed five genes in a human epidermal injury model, which show the same trendline of expression (upregulation of downregulation) as our KO Tuft1 murine model (Supplementary Figure  S5e ). TUFT1 localizes in the heart at the intercalated discs, but no significant cardiac abnormalities were present in Tuft1-KO mice The hearts of KO mice at age 12 months were not morphometrically different from those of WT (Supplementary Figure  S6a ). In WT heart tissue, TUFT1 specifically localized at the intercalated discs, similar to the desmosomal proteins DSP and DSC2 (Supplementary Figure  S6b ), and was absent in KO. No significant differences between WT and KO mice were found on magnetic resonance imaging analysis, showing normal end-systolic/-diastolic volumes, ejection fraction, stroke volume, and systolic/diastolic myomass of the left and right ventricles (Supplementary Figure  S6c  and d ).
Whole-exome sequencing Genomic DNA from whole blood was fragmented into 200e400 bp fragments using Covaris Adaptive Focused Acoustics shearing according to the manufacturer's instructions (Covaris, Woburn, MA). Illumina TruSeq DNA library preparation (Illumina, San Diego, CA) was performed on a Caliper SciClone NGS workstation (Caliper Life Sciences, Hopkinton, MA), followed by exome capture using a NimbleGen SeqCap EZ V2 kit (Roche Nimblegen, Madison, WI). This capture targets 44 Mb of exonic regions covering 30,246 coding genes, 329,028 exons, and 710 microRNAs. Paired-end sequencing (2 Â 100 bp) was performed at six samples per lane using Illumina TruSeq V3 chemistry on a HiSeq2000 (Illumina), with a total amount of at least 4 Gb per sample. Data processing and variant calling were done according to an optimized version of the Genome Analysis Tool Kit (Broad Institute, Cambridge, MA)  (McKenna et al.
, 2010). Variant annotation on final VCF (Variant Call Format) files was performed by an in-house developed pipeline, adapted, and extended from the Annovar tool  (Wang et al. , 2010) , including functional annotation, database frequencies, pathogenicity risk scores, and conservation predictions as well as gene coupled phenotypes. The exomes of the two affected children and their father were sequenced with a mean coverage for the separate samples of 54Â (II2), 61Â (II1), and 90Â (I1). Variants were filtered on the basis of recessive mode of inheritance, impact on protein function, and frequency <0. 0001 in public databases. One variant, in the TUFT1 gene, located on chromosome 1 remained in the total of homozygous areas indicated in Supplementary Table  S2.
Variant pathogenicity prediction Pathogenicity of exome-sequence variants and its impact on protein function were predicted by programs integrated into the Annovar tool  (Wang et al. , 2010). Splice-site variant prediction analysis was performed with Alamut variant interpretation Software, version 2. 7. 2 (SOPHiA GENETICS, Lausanne, Switzerland) and consisted of SpliceSiteFinderlike, MaxEntScan, NNSPLICE, and GeneSplicer.
Immunofluorescence and light microscopy Both human and mouse skin biopsies were snap frozen, sliced into 4 mm sections on a microtome, and immunofluorescent stained as previously described  (Jonkman et al. , 1992). Cultured human or mouse keratinocytes were grown in their specific media containing 1. 2 mM calcium for 2 days. For immunofluorescence staining, cells were fixed with 2% formaldehyde in PBS for 10 minutes, air dried, and frozen. Permeabilization was performed with 0. 5% Triton X-100 in PBS for 5 minutes at room temperature. Nonspecific staining was blocked by incubation with 1% ovalbumin for 20 minutes, followed by primary antibody incubation for 60 minutes at 37 C and 30 minutes with a secondary antibody. Cells were mounted with SlowFade DAPI (Thermo Fisher Scientific). Imaging was conducted with the Leica DFC350FX camera (Leica, Wetzlar, Germany) mounted on a LEICA DMRA microscope supported by LAS-software (Leica).
Proteins were separated in 5 or 10% SDS-PAGE gels and transferred to polyvinylidene fluoride membranes. The membranes were incubated overnight at 4 C with primary antibody, followed by secondary antibody (horse radish peroxidaseelabeled) incubation for 1 hour at room temperature. The images were acquired using ImageQuant LAS software. On the basis of normality, statistics were performed using unpaired t-test/ ManneWhitney test. Antibodies used are listed in Supplementary Table  S5.
Direct stochastic optical reconstruction microscopy Human primary keratinocytes were grown on 24 mm ø 1. 5 H cover glasses (Paul Marienfeld, Lauda-Ko ¨nigshofen, Germany) for 7 days with high calcium and immunostained as described earlier. TUFT1 was labeled in combination with desmoglein 3 or the rod domain of desmoplakin I followed by Alexa 647econjugated goat anti-rabbit IgG and Atto 488econjugated goat anti-mouse Fab-fragments. Imaging was performed on a Zeiss Elyra microscope (Zeiss, Jena, Germany) using a 100Â 1. 46 numerical aperture plan-apo lens as described previously  (Slotman et al. , 2020). In short, imaging was performed in low-oxygen buffer using high laser-power fluorophores forced into a dark state. Subsequently, a movie was made under similar conditions where each fluorophore that exited the dark state and thus emitted photons was detected and localized by Gaussian fitting using the Zeiss Zen software (Zeiss, Jena, Germany).
RNA sequencing Total RNA was isolated from snap-frozen whole skin, as described earlier for RT-PCR. The QuantSeq 3' mRNA kit (Lexogen, Vienna, Austria) was used to prepare cDNA sequence libraries. Libraries were sequenced at 2 Â 150 bp on a NextSeq 500 sequencer (Illumina). Raw sequence reads were aligned to the mm39 mouse reference genome using STAR (version 2. 7. 9a)  (Dobin et al. , 2013)  using basic twopass mode. Duplicate reads were marked using the Genome Analysis Toolkit (version 4. 2. 4. 0)  (McKenna et al. , 2010). Reads were counted per exon in the GENCODE, version M30, mouse gene annotation using featureCounts (subread version 2. 0. 3)  (Liao et al. , 2014). Count file was subset per tissue type and analyzed using edgeR (version 3. 36. 0), filtering on expression in at least three samples and transcript count of at least one count per million reads.
HaCaT transfection with fluorescent constructs Immortalized human keratinocytes (HaCaT) were 80e90% confluent at the time of transfection and cotransfected with desmoglein 2emCherry/keratin 14emApple, and TUFT1eC-GFP in a ratio of 6:2 Lipofectamine2000:DNA. Cells were fixated with 2% formaldehyde and mounted with SlowFade. Imaging was conducted with the Leica DFC350FX camera mounted on a LEICA DMRA microscope supported by LAS software.
Statistics All data are represented as means AE SEM. For all data, a ShapiroeWilk normality test was performed. If data were normally distributed, a t-test was performed, and if the data were not normally distributed, a ManneWhitney test was performed. A P < 0. 05 was considered statistically significant. For qPCR, the dCt values were used for statistical analysis, and 2 -DDCT was used for graphical representation. For western blotting, relative expression (protein/housekeeping protein) was used for statistical analysis, and the fold change was used for graphical representations. Statistics were performed using GraphPad Prism (GraphPad Software, San Diego, CA). Supplementary Table  S1.
ACKNOWLEDGMENTS MCB is the guarantor for this work. The authors thank the family and especially the children for their continuous cooperation, endless patience, perseverance, and trust. The authors acknowledge the late  A. P. Oranje  for his many years of dedicated supervision of the family. The authors thank  Joke Polak  and  Nicole van Koetsveld  for fibroblast cell culture;  Lida Prins-Bakker  and  Lies-Anne Severijnen  for experimental and technical support; the late  Michael Davidson  and  Michelle Baird  from the  United States  for cloning fluorescent constructs; and  Suzanne Pasmans ,  Senada Koljenovi  c,  Max Kros , and  Alice Brooks  for fruitful discussions. The authors thank  Inge Bruins  for her experimental contributions during her thesis. The authors thank  Stichting Vlinderkind  for the financial support to perform the studies.
Filtering curves based on goodness of fit FCS measurements can be subject to artefacts that distort FCS curves, for instance when bright clusters of fluorescent molecules enter the observation area. These curves need to be discarded from analysis to avoid biasing diffusion coefficient estimation. In point FCS, this is often done via manual inspection facilitated by dedicated softwares  (52). This approach is however impractical in imaging FCS due to the high parallelisation of FCS curves acquisition resulting in the generation of a high number of FCS curves (typically we acquire 350-500 FCS curves per hour in bacteria, considering only one pixel binning value). The issue of sample-induced artefact in FCS is well acknowledged and solutions to this issue were previously developed. It was notably proposed to compare each curve within a dataset to the averaged curve and to exclude outliers  (53).
This solution is however computationally intensive and might fail if signal levels vary within a dataset, for instance due of cell-to-cell heterogeneity. Another approach consists in rejecting curves with irregular residuals. One method for doing this consists in calculating the χ² goodness of fit (  30 ), but it does not handle well noisy curves  (53). It also requires knowledge of the standard deviation of the FCS curve, which is not always available. The Fourier transform was previously used to detect unevenly distributed residuals, relying however on fine-tuning three empirical parameters and making assumptions on the transit times observed  (33). As an alternative to these methods, we introduce here a simple error metric based on fitting residuals that quantifies fitting bias. Considering the mean square error (MSE): MSE= 1 n ∑ i n (r i ) 2 r i =( y i -ŷ i )/ ŷ 0 3 Where y i is the empirical FCS curve at lag time I, ŷ i is the corresponding fit value and r i the residual.
On the other hand, if the residual r i is positive but the residuals i-1 and i+1 are negative, there is no fitting bias (residuals are oscillating around the mean) and n adj,i =0. To evaluate the capability of MSE nl to evaluate fitting bias, we performed 2 TIR-FCS acquisitions on a flat sample of DOPC SLBs, at either high (740 µW) or low (185 µW) excitation power. The resulting dataset had heterogeneous signal levels representing the expected heterogeneity in biological samples. This dataset being acquired on the same SLB however we expected to find a comparable number of artefactual curves with either excitation intensities. Comparing MSE and MSE nl for every FCS curve in the dataset (Figure  1A ), we could observe that excitation intensity was a good predictor of MSE but not of MSE nl. Curves acquired at higher excitation intensity had in average a lower MSE but similar MSE nl , showing a lower dependence of MSE nl with signal levels.
Its reliability across datasets with different signal levels might prove useful in future high-throughput FCS studies, whether camerabased or not  (59). Using TIR-FCS instead of conventional confocal FCS offered several advantages, some of them already listed: high-throughput measurements, excellent axial selectivity allowing FCS measurements in single membranes and extraction of spatial information. Besides, using an unpolarised evanescent field with TIRF excitation allows excitation of fluorescent molecules irrespective of their dipole orientation. This is a major advantage when working with membrane markers that intercalate within a membrane and keep a fixed orientation, which can be orthogonal to the polarisation plane of e. g confocal excitation and therefore lead to poor excitation quality and inhomogeneous excitation of observation area.
, 1997). A multitude of additional parcellations can be found in the extensive literature on nonhuman primates (e. g. ,  Blatt & Rosene, 1998; Insausti et al. , 1987; Suzuki & Amaral, 2003). In addition to the improvement of histological methods, histological datasets have grown. In combination with the rise of in vivo neuroimaging techniques, this development has provided crucial insights into interindividual differences in neuroanatomy. For example, it has become apparent that the MTL cortex exhibits great interindividual variation in micro-as well as macrostructure  (Augustinack, van der Kouwe, et al. , 2013; Ding & Van Hoesen, 2010; Insausti et al. , 1998; Ono et al. , 1990). In particular, the rhinal and collateral sulci vary in depth and ramification. Variance in collateral sulcus depth and continuity have been linked to differing gross anatomical locations of MTL cortex subregions  (Ding & Van Hoesen, 2010; Insausti et al.
The difficulty of annotating transitional zones may increase when borders between structures do not run strictly parallel or perpendicular to the provided sections. Even when using a consistent plane of sectioning (i. e. , orthogonal to anterior commissure-posterior commissure (AC-PC) line) the irregular surface of the MTLalongside the obliquity of sulci and other gross anatomical landmarkscan add complexity and ambiguity to the interpretation of boundaries. In such cases, it is possible that sections of one subregion are interrupted by portions of other types of cortices (e. g. , appearance of olfactory cortex surrounded by ERC). In the present dataset, slices were cut perpendicular to the long axis of the hippocampus to aid the translation to thick-sliced in vivo MRI. For most neuroanatomists this is different from the common coronal sections cut perpendicular to the AC-PC line direction, which may have decreased certainty in border placement as well.
Strengths and limitations A major strength of the present study is the integration of input from four leading expert neuroanatomists in the field, forming a first-of-its-kind annotated dataset of MTL cortex subregions in three histological specimens representing varying demographic backgrounds and anatomical variability. Yet, the limitations of the study must be considered. First, no quantitative investigation of the differences in annotations was performed. Due to the manifold factors that influence the annotations of the neuroanatomists, we believe that it is not warranted to assess the differences in annotations quantitatively. Even more, focusing on quantitative measures of inter-rater agreement may lead to false conclusions and obscure the fine-grained picture that we are describing in this study.
Instead, we show that considering the complexity of this work is of utmost importance when investigating the fine-grained neuroanatomy of the MTL cortex. Second, the generalizability of our results is limited as the presented information is based on a small sample of three specimens. It has been reported that the location of MTL cortex subregions varies with collateral sulcus depth and ramification  (Ding & Van Hoesen, 2010; Insausti et al. , 1998). Although we included samples with different collateral sulcus depths and ramifications to account for this to some extent, a sample size of three specimens is clearly insufficient to fully characterize the role of anatomical variants in MTL subregion delineations. Unfortunately, because of the time and effort required (~9 hours per specimen) to generate a dataset comprising the entirety of macroscopic MTL cortex phenotypes it was not possible to perform the current comparison between neuroanatomical schools in a larger sample.
Acknowledgements We would like to acknowledge the donors and their family members for making this work possible. Special thanks go to the  Marcus Wallenberg foundation  for international scientific collaboration (2020. 0004) and the  Wenner-Gren foundation  ( ESh2020-002 ) for their generous support. This work was supported by  NIH  grants  R01-AG070592 ,  P01AG066597  and  P30AG072979.