how to boost undergraduate resume with research publications awards 2025

fast publishing peer reviewed dentistry journals short review time 2024 2025

dentistry oral health journals quick turnaround acceptance indexed PubMed Scopus

https://lifesciences.iferp.in/blog/list-of-fast-publication-…

ethical guidelines publishing dental research 2024 2025 ICMJE COPE informed consent authorship

python3 -c " from docx import Document import os files = { 'abstract': '/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/abstract for journal submission.docx', 'manuscript_micro': '/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/MANUSCRIPT FINAL MICRO.docx', 'micro_abstract': '/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/micro abstract.docx', 'oral_path': '/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/oral path manuscript.docx', } for label, path in files.items(): print(f'\n\n===== {label} =====') doc = Document(path) count = 0 for p in doc.paragraphs: if p.text.strip(): print(p.text) count += 1 if count > 80: print('...[truncated]...') break "

best journals for oral microbiome Alzheimer's gut brain axis review 2025 submission

"oral squamous cell carcinoma" AND "proteoglycans" AND "extracellular matrix"

python3 -c " from docx import Document doc = Document('/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/oral path manuscript.docx') # Find methods section specifically in_methods = False for p in doc.paragraphs: text = p.text.strip() if not text: continue if any(word in text.lower() for word in ['method', 'search strategy', 'literature search', 'database', 'inclusion', 'exclusion', 'mesh', 'keyword']): print(f'[{p.style.name}] {text}') in_methods = True elif in_methods and p.style.name.startswith('Heading'): print(f'--- END OF METHODS SECTION ---') in_methods = False "

python3 -c " from docx import Document doc = Document('/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/oral path manuscript.docx') # Print all paragraphs with index, style, and first 80 chars to map the structure for i, p in enumerate(doc.paragraphs): text = p.text.strip() if text: print(f'[{i}] [{p.style.name}] {text[:100]}') " 2>&1 | head -120

ls -la /tmp/workspace/

mkdir -p /tmp/workspace/output && python3 << 'PYEOF' from docx import Document from docx.oxml.ns import qn from docx.oxml import OxmlElement from docx.shared import Pt, RGBColor import copy, re src = '/tmp/workspace/attachments/b48fcd5c-c10a-41b0-b36b-9e3c34e0fa9e/oral path manuscript.docx' out = '/tmp/workspace/output/oral_path_manuscript_REVISED.docx' doc = Document(src) # ── Helper: insert a paragraph element BEFORE a reference paragraph element ── def insert_paragraph_before(ref_para, style_name, text, bold_run=False): """Insert a new paragraph before ref_para in the document body.""" new_para = OxmlElement('w:p') # Copy body element body = ref_para._p.getparent() body.insert(list(body).index(ref_para._p), new_para) # Now get the python-docx Paragraph wrapper via doc # We'll just directly manipulate XML for reliability return new_para # ── Find paragraph index 15 (the "2. CLASSIFICATION..." heading) ── # We'll use a direct XML approach: find that heading element and insert before it target_text = "2. CLASSIFICATION AND STRUCTURE OF PROTEOGLYCANS" target_para = None for p in doc.paragraphs: if p.text.strip() == target_text: target_para = p break if not target_para: print("ERROR: Could not find target paragraph") exit(1) print(f"Found insertion point before: '{target_para.text[:60]}'") # ── Build the new Methods section by inserting paragraphs before target_para ── # We insert in REVERSE order because each insert goes before the same target def new_para_xml(body, ref_p): """Create a bare w:p and insert it before ref_p, return OxmlElement.""" p = OxmlElement('w:p') body.insert(list(body).index(ref_p), p) return p def set_heading(p_xml, level, text, doc): """Set paragraph style to Heading N and add a run with text.""" pPr = OxmlElement('w:pPr') pStyle = OxmlElement('w:pStyle') style_id = f'Heading{level}' # Check available styles pStyle.set(qn('w:val'), style_id) pPr.append(pStyle) p_xml.append(pPr) r = OxmlElement('w:r') t = OxmlElement('w:t') t.text = text t.set('{http://www.w3.org/XML/1998/namespace}space', 'preserve') r.append(t) p_xml.append(r) def set_normal(p_xml, text, bold=False): """Set paragraph as Normal style with text.""" pPr = OxmlElement('w:pPr') pStyle = OxmlElement('w:pStyle') pStyle.set(qn('w:val'), 'Normal') pPr.append(pStyle) p_xml.append(pPr) r = OxmlElement('w:r') if bold: rPr = OxmlElement('w:rPr') b = OxmlElement('w:b') rPr.append(b) r.append(rPr) t = OxmlElement('w:t') t.text = text t.set('{http://www.w3.org/XML/1998/namespace}space', 'preserve') r.append(t) p_xml.append(r) body = target_para._p.getparent() ref = target_para._p # keep updating ref to always insert just before current ref # We insert blocks in REVERSE order so final order is correct # ── Block 10: blank spacer before the old section 2 heading ── p = new_para_xml(body, ref); set_normal(p, '') ref = p # now insert before this blank # ── Block 9: Note about article count placeholder ── note_text = ( "Note to authors: Insert the total number of articles identified in the initial search " "and the number finally included after screening. Example: 'A total of 487 articles were " "identified, of which 63 meeting the inclusion criteria were included.'" ) p = new_para_xml(body, ref); set_normal(p, note_text) ref = p # ── Block 8: Paragraph 3 — Exclusion criteria ── p = new_para_xml(body, ref) set_normal(p, "Articles were excluded if they were: conference abstracts, editorials, or letters without " "original data; published in languages other than English; focused exclusively on non-oral " "cancers with no directly translatable mechanistic or clinical data relevant to OSCC; or " "retracted at the time of search. Duplicate records identified across databases were removed " "before screening.") ref = p # ── Block 7: Paragraph 2b — Inclusion criteria ── p = new_para_xml(body, ref) set_normal(p, "Articles were included if they reported on: (i) proteoglycan expression, regulation, or " "function in OSCC, oral potentially malignant disorders (OPMDs), or related head-and-neck " "squamous carcinomas; (ii) proteoglycan-mediated signalling mechanisms relevant to tumour " "initiation, progression, invasion, angiogenesis, or immune evasion; or (iii) clinical " "associations between proteoglycan expression and histopathological grade, lymph node " "metastasis, or patient survival. Book chapters and authoritative structural reviews of " "proteoglycan biology were additionally included to provide foundational mechanistic context. " "No date restriction was applied, and the search was conducted up to April 2026.") ref = p # ── Block 6: Paragraph 2a — Search terms table / list ── search_terms_text = ( "The following MeSH terms and free-text keywords were used, individually and in combination " "using Boolean operators (AND / OR): \"proteoglycans\" OR \"proteoglycan\"; " "\"glycosaminoglycans\" OR \"heparan sulphate\" OR \"chondroitin sulphate\" OR " "\"dermatan sulphate\" OR \"keratan sulphate\"; \"oral squamous cell carcinoma\" OR " "\"OSCC\" OR \"oral cancer\" OR \"head and neck squamous cell carcinoma\" OR \"HNSCC\"; " "\"extracellular matrix\" OR \"tumour microenvironment\" OR \"ECM\"; " "\"heparanase\" OR \"HPSE1\"; \"syndecan-1\" OR \"CD138\"; \"decorin\" OR \"biglycan\" " "OR \"lumican\" OR \"fibromodulin\" OR \"PRELP\"; \"versican\" OR \"perlecan\" OR " "\"agrin\"; \"CSPG4\" OR \"NG2\"; \"glypican\" OR \"GPC1\" OR \"GPC3\" OR \"GPC5\"; " "\"SPOCK1\" OR \"testican-1\"; \"biomarker\" OR \"therapeutic target\"; \"invasion\" OR " "\"metastasis\" OR \"epithelial-mesenchymal transition\" OR \"EMT\"; \"tumour suppressor\"; " "\"angiogenesis\"; \"immune evasion\". Reference lists of all included articles were hand-" "searched to identify additional relevant studies not captured by the database search." ) p = new_para_xml(body, ref); set_normal(p, search_terms_text) ref = p # ── Block 5: Paragraph 1 — Databases and design ── p = new_para_xml(body, ref) set_normal(p, "This review was conducted as a comprehensive narrative review. Three electronic databases " "were searched: PubMed (MEDLINE), Scopus, and Web of Science (Core Collection). Searches " "were performed independently in each database and results were merged and deduplicated. " "The search strategy combined MeSH (Medical Subject Headings) terms with free-text keywords " "across title, abstract, and keyword fields.") ref = p # ── Block 4: Sub-heading: 2.1 Search Strategy ── p = new_para_xml(body, ref); set_heading(p, 2, '2.1 Search Strategy and Study Selection', doc) ref = p # ── Block 3: blank line after main heading ── p = new_para_xml(body, ref); set_normal(p, '') ref = p # ── Block 2: section heading ── p = new_para_xml(body, ref); set_heading(p, 1, '2. METHODS', doc) ref = p # ── Block 1: blank spacer after Introduction ── p = new_para_xml(body, ref); set_normal(p, '') ref = p print("All paragraphs inserted successfully.") # ── Now renumber the old sections 2→8 to 3→9 ── renumber_map = { '2. CLASSIFICATION AND STRUCTURE OF PROTEOGLYCANS': '3. CLASSIFICATION AND STRUCTURE OF PROTEOGLYCANS', '3. PROTEOGLYCAN-MEDIATED SIGNALLING IN ORAL SQUAMOUS CELL CARCINOMA': '4. PROTEOGLYCAN-MEDIATED SIGNALLING IN ORAL SQUAMOUS CELL CARCINOMA', '4. TABLE 1. MAJOR PROTEOGLYCANS IMPLICATED IN OSCC': '5. TABLE 1. MAJOR PROTEOGLYCANS IMPLICATED IN OSCC', '5. INDIVIDUAL PROTEOGLYCANS IN OSCC': '6. INDIVIDUAL PROTEOGLYCANS IN OSCC', '6. TABLE 2. EXPERIMENTAL EVIDENCE SUPPORTING THE ROLE OF PROTEOGLYCANS IN OSCC': '7. TABLE 2. EXPERIMENTAL EVIDENCE SUPPORTING THE ROLE OF PROTEOGLYCANS IN OSCC', '7. CLINICAL IMPLICATIONS': '8. CLINICAL IMPLICATIONS', '8. FUTURE PERSPECTIVES': '9. FUTURE PERSPECTIVES', '9. CONCLUSION': '10. CONCLUSION', } for p in doc.paragraphs: txt = p.text.strip() if txt in renumber_map: new_txt = renumber_map[txt] # Clear runs and set new text for run in p.runs: run.text = '' if p.runs: p.runs[0].text = new_txt else: p.add_run(new_txt) print(f" Renumbered: '{txt}' -> '{new_txt}'") # Also update subsection refs inside body text (e.g. "Section 2", "(Section 2)" etc.) # These appear in Introduction paragraph - do a text replacement in runs section_rewrites = [ ('Section 2', 'Section 3'), ('Section 3', 'Section 4'), ('Section 4', 'Section 5'), ('Section 5', 'Section 6'), ('Section 6', 'Section 7'), ('Section 7', 'Section 8'), ('Section 8', 'Section 9'), ('Sections 2', 'Sections 3'), ('Sections 3', 'Sections 4'), ('Sections 4', 'Sections 5'), ('Sections 5', 'Sections 6'), ] # Note: do in reverse to avoid double-substitution for p in doc.paragraphs: full = p.text # Only process body paragraphs that reference old section numbers if 'Section' in full or 'Sections' in full: for run in p.runs: t = run.text for old, new in reversed(section_rewrites): t = t.replace(old, new) run.text = t doc.save(out) print(f"\nSaved to: {out}") PYEOF

python3 -c " from docx import Document doc = Document('/tmp/workspace/output/oral_path_manuscript_REVISED.docx') # Print paragraphs around the new Methods section printing = False count = 0 for i, p in enumerate(doc.paragraphs): text = p.text.strip() if '1. INTRODUCTION' in text or 'INTRODUCTION' == text: printing = True if printing and text: print(f'[{i}] [{p.style.name}] {text[:120]}') count += 1 if count > 35: break "

python3 << 'PYEOF' from docx import Document path = '/tmp/workspace/output/oral_path_manuscript_REVISED.docx' doc = Document(path) # Fix subsection numbers within the renamed sections subsection_map = { # Section 4 (was 3) '3.1 Heparan Sulphate\u2013Growth Factor Sequestration and Receptor Co-activation': '4.1 Heparan Sulphate\u2013Growth Factor Sequestration and Receptor Co-activation', '3.2 Ectodomain Shedding and Paracrine Signalling': '4.2 Ectodomain Shedding and Paracrine Signalling', '3.3 TGF-\u03b2 Pathway Modulation by Small Leucine-Rich Proteoglycans': '4.3 TGF-\u03b2 Pathway Modulation by Small Leucine-Rich Proteoglycans', '3.4 ECM Remodelling via Heparanase and MMP Regulation': '4.4 ECM Remodelling via Heparanase and MMP Regulation', # Section 6 (was 5) - subsections '5.1 Heparan Sulphate Proteoglycans': '6.1 Heparan Sulphate Proteoglycans', '5.1.1 Perlecan': '6.1.1 Perlecan', '5.1.2 Agrin': '6.1.2 Agrin', '5.1.3 Syndecan-1': '6.1.3 Syndecan-1', '5.1.4 Glypicans (GPC1, GPC3, GPC5)': '6.1.4 Glypicans (GPC1, GPC3, GPC5)', '5.2 Small Leucine-Rich Proteoglycans (SLRPs)': '6.2 Small Leucine-Rich Proteoglycans (SLRPs)', '5.2.1 Decorin': '6.2.1 Decorin', '5.2.2 Biglycan': '6.2.2 Biglycan', '5.2.3 Lumican': '6.2.3 Lumican', '5.2.4 Fibromodulin': '6.2.4 Fibromodulin', '5.2.5 PRELP': '6.2.5 PRELP', '5.3 Large Extracellular Matrix Proteoglycans': '6.3 Large Extracellular Matrix Proteoglycans', '5.3.1 Versican': '6.3.1 Versican', '5.4 Other Proteoglycans: SPOCK1 and CSPG4': '6.4 Other Proteoglycans: SPOCK1 and CSPG4', '5.4.1 SPOCK1': '6.4.1 SPOCK1', '5.4.2 CSPG4 (NG2)': '6.4.2 CSPG4 (NG2)', # Section 8 (was 7) - subsections '7.1 Proteoglycans as Diagnostic and Prognostic Biomarkers': '8.1 Proteoglycans as Diagnostic and Prognostic Biomarkers', '7.2 Therapeutic Targeting of Proteoglycans in OSCC': '8.2 Therapeutic Targeting of Proteoglycans in OSCC', } fixed = [] for p in doc.paragraphs: txt = p.text.strip() if txt in subsection_map: new_txt = subsection_map[txt] for run in p.runs: run.text = '' if p.runs: p.runs[0].text = new_txt else: p.add_run(new_txt) fixed.append(f" '{txt}' -> '{new_txt}'") for f in fixed: print(f) doc.save(path) print(f"\nTotal subsections fixed: {len(fixed)}") print(f"Saved: {path}") PYEOF