~/

CUTICON abstract submission guidelines word limit structured abstract dermatology 2026

~/attachments/34f5422c-0bcf-4d41-9876-8b0f54a021d3

python3 -c "from docx import Document; import sys; paths=sys.argv[1:]; for path in paths: print('\\n'+'='*28+' '+path.split('/')[-1]+' '+'='*28) d=Document(path) for i,p in enumerate(d.paragraphs): t=p.text.strip() if t: print(f'P{i} [{p.style.name}]: {t}') for ti,t in enumerate(d.tables): print(f'\\n[TABLE {ti}]') for row in t.rows: print(' | '.join(c.text.replace('\\n',' / ').strip() for c in row.cells)) " "/tmp/workspace/attachments/34f5422c-0bcf-4d41-9876-8b0f54a021d3/abstract- paper ppt.docx" "/tmp/workspace/attachments/34f5422c-0bcf-4d41-9876-8b0f54a021d3/dr itee thesis pdf.docx" > "/tmp/workspace/attachments/extracted_thesis_and_sample.txt" && wc -l "/tmp/workspace/attachments/extracted_thesis_and_sample.txt"

"METHODOLOGY" in ~/attachments

"Inclusion" in ~/attachments

"Tofacitinib" in ~/attachments

"Tacrolimus" in ~/attachments

"Sample" in ~/attachments

python3 -c "from docx import Document; p='/tmp/workspace/attachments/34f5422c-0bcf-4d41-9876-8b0f54a021d3/dr itee thesis pdf.docx'; d=Document(p); for i,x in enumerate(d.paragraphs): t=x.text.strip() if t and 120<=i<=260: print(f'P{i}: {t}')"

vitiligo AND topical tofacitinib

https://cuticontn2026.com/abstract

mkdir -p "/tmp/workspace/cuticon-abstract/output" "/tmp/workspace/cuticon-abstract/src" && python3 - <<'PY' from docx import Document from docx.shared import Pt from docx.enum.text import WD_ALIGN_PARAGRAPH from docx.enum.section import WD_SECTION from docx.oxml import OxmlElement from docx.oxml.ns import qn out='/tmp/workspace/cuticon-abstract/output/CUTICON_blinded_abstract_vitiligo.docx' title='Comparative efficacy of topical tacrolimus 0.1% and topical tofacitinib 2% in non-segmental vitiligo: a randomized pilot study' sections=[ ('Background', 'Vitiligo is an autoimmune pigmentary disorder that can cause substantial psychosocial morbidity. Topical tacrolimus is a commonly used steroid-sparing treatment, whereas topical tofacitinib, a Janus kinase inhibitor, may suppress interferon-gamma mediated melanocyte destruction. Direct comparative evidence remains limited.'), ('Aim', 'To compare the efficacy and safety of topical tacrolimus 0.1% and topical tofacitinib 2% in patients with stable non-segmental vitiligo.'), ('Methods', 'This prospective, randomized, open-label, parallel-arm pilot study will include 20 patients aged over 5 years with stable non-segmental vitiligo involving 10% or less body surface area. Participants will be randomized in a 1:1 ratio to receive tacrolimus 0.1% ointment or tofacitinib 2% ointment, applied twice daily for 16 weeks (10 patients per group). Patients with segmental vitiligo, pregnancy or lactation, drug allergy, or recent systemic immunosuppression or narrowband ultraviolet-B therapy will be excluded. Clinical assessments at baseline and weeks 4, 8, 12 and 16 will include standardized photographs, percentage repigmentation, onset of visible repigmentation, Vitiligo Noticeability Scale score, treatment discomfort, adherence and adverse events.'), ('Results', 'The study is designed to compare repigmentation and tolerability between the two treatment groups. Results will be reported after completion of follow-up; no efficacy outcomes are presented in this protocol abstract.'), ('Conclusion', 'This pilot study will provide preliminary head-to-head evidence on whether topical tofacitinib 2% offers efficacy or tolerability advantages over topical tacrolimus 0.1% in stable non-segmental vitiligo.')] text=' '.join(x for _,x in sections) import re count=len(re.findall(r"\b[\w%.-]+\b", text)) doc=Document() sec=doc.sections[0] sec.top_margin=Pt(54); sec.bottom_margin=Pt(54); sec.left_margin=Pt(72); sec.right_margin=Pt(72) style=doc.styles['Normal']; style.font.name='Times New Roman'; style._element.rPr.rFonts.set(qn('w:eastAsia'), 'Times New Roman'); style.font.size=Pt(12) style.paragraph_format.line_spacing=2 style.paragraph_format.space_after=Pt(0) p=doc.add_paragraph() p.alignment=WD_ALIGN_PARAGRAPH.CENTER p.paragraph_format.line_spacing=2 r=p.add_run(title); r.bold=True; r.font.name='Times New Roman'; r.font.size=Pt(12) for h,body in sections: p=doc.add_paragraph() p.paragraph_format.line_spacing=2 p.paragraph_format.space_after=Pt(0) r=p.add_run(h+': '); r.bold=True p.add_run(body) p=doc.add_paragraph() p.paragraph_format.line_spacing=2 r=p.add_run('Conflict of interest: '); r.bold=True p.add_run('None declared.') p=doc.add_paragraph() p.paragraph_format.line_spacing=2 r=p.add_run('Abstract word count: '); r.bold=True p.add_run(f'{count} words (title and conflict-of-interest statement excluded).') # prevent names/institution in abstract and add footer footer=sec.footer.paragraphs[0] footer.alignment=WD_ALIGN_PARAGRAPH.CENTER fr=footer.add_run('Blinded abstract for submission') fr.font.name='Times New Roman'; fr.font.size=Pt(9) doc.save(out) print(out) print('WORDCOUNT',count) PY python3 -c "from docx import Document; p='/tmp/workspace/cuticon-abstract/output/CUTICON_blinded_abstract_vitiligo.docx'; d=Document(p); print('\\n'.join(x.text for x in d.paragraphs))"